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The Guangdong‐Hong Kong‐Macao Greater Bay Area (GBA), a cluster of world‐class cities, is undergoing rapid urbanization. However, the heterogeneity of the urban thermal environment resulting from the diversity of urban forms is not yet fully understood. This paper assesses the heterogeneity of the urban heat island (UHI) effect in the GBA using the coupled Weather Research and Forecasting (WRF) model/multi‐layer urban canopy and building energy model (BEP/BEM), with high‐resolution local climate zone (LCZ) map as urban land use/land cover data. The average UHI intensity is found to peak at 1.8 ± 0.4°C in the evening, when the average UHI intensity of LCZ 2 can reach a maximum of 2.4 ± 0.58°C. Properly setting air‐conditioning temperatures can effectively prevent the enhancement of the UHI phenomenon at night by the anthropogenic heat (AH) released from air‐conditioning. The UHI‐induced local circulations and enhanced surface roughness inhibit the penetration of sea breezes inland, and surface wind speed decreases in all LCZs, with a maximum change of more than 0.8 m s−1. However, the increased thermal difference between land and sea leads to enhanced sea breezes offshore, especially in the Pearl River estuary. In addition, a series of sensitivity experiments have been conducted in this paper on initial and boundary conditions, building drag coefficients and urban fractions, which paves the way for further analyzing urban climate in GBA using WRF model and LCZs. Plain Language Summary: With the rapid urbanization of the world, the demand for functional buildings has increased. Along with the diversification of urban forms, the differences in the thermal environment within cities are becoming more and more significant. This study therefore provides an in‐depth study of the urban thermal environment in the Guangdong‐Hong Kong‐Macao Greater Bay Area (GBA) based on numerical simulation and local climate zones (LCZs). It was found that the urban heat island (UHI) intensity in different urban forms has obvious differences, and may vary by 1°C. However, the daily variation trends are similar, all showing a stronger UHI intensity at night than during the day, and reasonable setting of air‐conditioning temperature can effectively mitigate the UHI intensity at night. The UHI‐induced local circulations and enhanced surface roughness weaken the surface wind speed and inhibit the penetration of sea breeze inland, but enhance the sea breezes offshore, especially in the Pearl River estuary. This study provides references for urban planning and future sustainable development, especially for areas located along the coast that are undergoing rapid development. In addition, a series of sensitivity experiments on initial and boundary conditions, building drag coefficients and urban fractions provide useful suggestions for numerical model configuration in the GBA. Key Points: Tests of initial and boundary conditions, building drag coefficient and urban fractions provide recommendations for Weather Research and Forecasting configurationUrban heat island (UHI) varies between different local climate zones, but all peak in evening, and proper setting of air‐conditioning temperatures can mitigate UHI at nightUrbanization weakens surface wind speeds and inhibits the penetration of sea breezes inland, but strengthens the sea breezes offshore [ABSTRACT FROM AUTHOR]

The Western Pacific jet stream (WPJS) is an essential part of atmospheric circulation in winter, which significantly influences the weather and climate of the North Pacific and North America. In this paper, the characteristics and mechanism of WPJS subseasonal variation in winter are investigated. The upstream atmospheric disturbances in the East Asian polar‐front jet and subtropical jet merge over the Northwestern Pacific to form the subseasonal variability in WPJS, which has a significant period of 40–60 days. During the positive phase events of subseasonal WPJS, the convergence position of the upstream atmospheric disturbances shifts southwardly accompanied with the local enhancement and eastward extension of subseasonal WPJS. On the other hand, the subseasonal WPJS divides into the southern and northern westerly branches during the negative phase events. By the horizontal propagation of local Eliassen‐Palm fluxes in the upper atmosphere, the northward drift of the upstream atmospheric disturbances convergence dominates the delayed acceleration of the northern upper westerly branch. However, the intensification of atmospheric baroclinicity and upward baroclinic energy caused by the leading strong subtropical frontal zone determine the acceleration of the southern upper westerly branch. Plain Language Summary: As an important part of the atmospheric circulation in the Northern Hemisphere, the Western Pacific jet stream (WPJS) has significant impacts on the climate and weather of the North Pacific and North America. However, previous studies more focused on the interannual or synoptic variability of WPJS. The characteristics and mechanism of the subseasonal variability of WPJS have not been appropriately explained, which are very important for the persistent disastrous weather. In this paper, the subseasonal variability characteristics and mechanism of WPJS in winter are investigated by using the daily average reanalysis data from year 1979 to 2022. About 130 WPJS persistent positive and negative phase events are detected, each of which can sustain more than 20 days. Further results show that the subseasonal variability of WPJS is determined by the synergistic effects of upstream atmospheric disturbances and subtropical frontal zone (STFZ). With the southward (northward) convergence of the strong upstream atmospheric disturbances and weaker (stronger) STFZ, the lagging positive (negative) subseasonal phase events of WPJS is more likely to occur and persist. This study is beneficial to the weather and climate forecasts of North Pacific and North America. Key Points: About 130 subseasonal events of winter Western Pacific jet stream (WPJS) are detected from year 1979–2022, each of which persists more than 20 daysWPJS shows local enhancement and extension during the positive subseasonal phase, but meridional separation in the negative oneThe synergistic effects of the upstream atmospheric disturbances and oceanic subtropical front on the subseasonal WPJS are revealed [ABSTRACT FROM AUTHOR]

Providing skilful predictions of high‐impact weather up to 2 weeks ahead is on the agenda of international weather centers. Evaluating the capabilities of current numerical systems in predicting past events can bring extremely valuable contributions to the assessment of the information content available today with operational models. In the framework of the activities for the fiftieth anniversary of the extreme precipitation event that occurred in Italy in November 1966, this paper investigates its predictability using state‐of‐the‐art global and regional ensemble simulations. The first goal is to assess if and how many days in advance, this event can be predicted by current European Centre for Medium‐Range Weather Forecasts (ECMWF) global ensembles. A second goal is to evaluate the potential added value of running nested higher‐resolution and convection‐permitting ensembles. It is shown that ECMWF ensembles are able to provide valuable information up to 3 days before the event. Within this forecast range, convection‐permitting simulations can provide more accurate estimations of precipitation maxima. However, the results indicate also a strong underestimation of rainfall amounts with both global and regional models even at short forecast range. To partially explain this shortcoming, we discuss how the scarcity of observations available in 1966 for the analysis process limits the quality of the ensemble initial conditions and we adopt a method to obtain more reliable ensemble forecasts. The paper concludes with a comparison with previous similar works; results indicate a gain in predictability of up to 12 hr with respect to numerical revisitations performed to mark the fortieth anniversary of the event. Key Points: Current state‐of‐the‐art global ensembles are able to provide valuable information up to 3 days before the Arno River flooding event (Italy, November 1966)Convection‐permitting ensembles provide more accurate estimations of precipitation maximaAdvances in numerical modeling occurred in the last 10 years, determine a gain in predictability of up to 12 hr with respect to similar works [ABSTRACT FROM AUTHOR]

In this paper we coupled a crop growth model to the Weather Research and Forecasting model with its land surface model Noah‐MP and demonstrated the influence of the weather driven crop growth on land‐atmosphere (L‐A) feedback. An impact study was performed at the convection permitting scale of 3 km over Germany. While the leaf area index (LAI) in the control simulation was the same for all cropland grid cells, the inclusion of the crop growth model resulted in heterogeneous crop development with higher LAI and stronger seasonality. For the analyses of L‐A coupling, a two‐legged metric was applied based on soil moisture, latent heat flux and convective available potential energy. Weak atmospheric coupling is enhanced by the crop model, the terrestrial coupling determines the regions with the L‐A feedback. The inclusion of the crop model turns regions with no L‐A feedback on this path into regions with strong positive coupling. The number of non‐atmospherically controlled days between April and August is increased by 10–15 days in more than 50% of Germany. Our work shows that this impact results in a reduction of both cold bias and warm biases and thus improves the metrics of distributed added value of the monthly mean temperatures. The study confirms that the simulation of the weather driven annual phenological development of croplands for the regional climate simulations in mid‐latitudes is crucial due to the L‐A feedback processes and the currently observed and expected future change in phenological phases. Key Points: Coupling a crop growth model with the Weather and Research Forecasting model significantly improves the simulation of the leaf area indexLand‐atmosphere coupling strength is enhanced by weather dependent crop growth simulationThe distributed added value metric shows a reduction in temperature biases of up to 80% in croplands throughout the season in Germany [ABSTRACT FROM AUTHOR]

The retrieval of the asymmetry parameter from nephelometer measurements can be challenging due to the inability to detect the whole angular range. Here, we present a new method for retrieving the asymmetry parameter of ice crystals with relatively large size parameters (>50) from polar nephelometer measurements. We propose to fit the angular scattering measurement with a series of Legendre polynomials and the best fitted coefficients give the asymmetry parameter. The accuracy of the retrieval is analyzed by accessing the smoothness of the phase function, which is closely linked to the complexity of ice particle. It is found that the uncertainty of retrieval could be smaller than 0.01, provided the measured intensity profile is smooth enough. As an application, we report an case study on Arctic cirrus, which shows a mean value for the asymmetry parameter of 0.72. Plain Language Summary: The asymmetry parameter of ice crystals is a parameter that can largely determine cirrus cloud's interaction with solar radiation energy, and therefore its magnitude is important for climate and weather prediction models. In‐situ measurements using nephelometers is a direct way to measure partial angular scattering functions, and the accuracy of these measurements is of upmost importance. In this paper, we report a novel method for retrieving the asymmetry parameter from polar nephelometer measurements. Depending on the smoothness of the measured angular scattering function, the accuracy of the retrieval could be very high. We report a case study over the Arctic region, showing a low asymmetry parameter around 0.72. Key Points: A new algorithm is developed for retrieving the asymmetry parameter of large and complex ice crystals from polar nephelometer measurementsAccuracy of retrieval could be better than 0.01, provided sufficient smoothness of the phase functionA case study of Arctic cirrus measurement during the CIRRUS‐HL campaign is reported [ABSTRACT FROM AUTHOR]

A large portion of lakes on the Tibetan Plateau (TP) have experienced considerable expansion in the past decades. However, how the lake surface area expansion has influenced regional precipitation, especially its underlying mechanism, has not been investigated. By selecting the most dramatically expanded lake on the TP as a case study, this paper investigates the magnitude and extent of the precipitation response to lake expansion and its underlying mechanism using twin Weather Research and Forecasting (WRF) simulations with and without lake expansion. The results show that the precipitation response to the lake expansion exhibits pronounced spatial and seasonal variations and is generally more intense in the downwind direction than in the upwind direction. During the wet season (the South Asian summer monsoon, SASM), precipitation decreases in the downwind area by −25% ± 16% and −13% ± 15% in the 0–50 km and 50–100 km intervals (from the lake's center), respectively. Conversely, the precipitation increases in the downwind area during the dry season (before the freeze and after the SASM) by 27% ± 36% in the 0–50 km interval. The thermal and evaporative effects, which are generated by lake expansion and propagate in the downwind direction, are the key factors responsible for the precipitation changes. The cooling effect, which generally occurs in the daytime, stabilizes the atmosphere and triggers downward motion, consequently inhibiting precipitation. The warming effect has the opposite effect, and the additional water vapor strengthens this process. However, the effects vary with the seasons, causing seasonal variations in the precipitation response. Plain Language Summary: A large portion of lakes on the Tibetan Plateau have experienced considerable expansion in the past decades. This study aims to assess the regional precipitation response to the expansion of a large lake Seling Co on the Tibetan Plateau and its underlying mechanisms. The results show that the precipitation response to the lake expansion exhibits pronounced spatial and seasonal variations and is generally more intense in the downwind direction than in the upwind direction. The expanded lake tends to inhibit precipitation in the wet season and promote it in the dry season. These findings suggest more attention need to be paid to the areas located downwind of these expanded lakes and an urgent need to improve the understanding of the climate response to the imbalance of the Tibetan Plateau. Key Points: Precipitation response to the expansion of Seling Co on the Tibetan Plateau exhibits pronounced spatial and seasonal variationsThe precipitation response is generally more intense in the downwind directionThe thermal and evaporative effects of the expanded lake dominate the precipitation response [ABSTRACT FROM AUTHOR]

This study assesses the benefit of convective‐scale data assimilation (DA) for model initialization using well‐known functional relationships between lightning flash rate and vertical velocity. Based on the relationships, a lightning DA scheme to update model kinematic states was implemented in the Weather Research and Forecasting Data Assimilation (WRFDA) three‐dimensional variational (3DVar) system. This scheme combines total lightning observations with model‐based prescribed vertical velocity profiles to retrieve kinematic information through a DA scheme. With the availability of space‐borne lightning imagers in recent years, total lightning observations from the Lightning Mapping Imager (LMI) on board the FY‐4A geostationary satellite were assimilated in combination with radar DA. A detailed analysis of the impact of the lightning DA scheme on convective precipitation forecasting was conducted using a squall line case over Beijing on 13 July 2017. The assimilation of LMI data provides added benefits to the assimilation of radar radial winds by reducing wind errors and strengthening convergence along the squall line in the analysis. Although the microphysical states are identical due to the assimilation of reflectivity, the lightning DA scheme helps in promoting updraft developments at lightning observation locations, which improves the representation of mixed‐phase convection. The quantitative verification of short‐term convective forecasts indicated that the lightning DA adds value to the radar DA by improving the precipitation forecast skill. The lightning DA scheme was evaluated further for a heavy rainfall case in 2018 over the Beijing metropolitan area and revealed overall similar forecast improvements for composite reflectivity and accumulated rainfall. Plain Language Summary: Lightning flashes are closely related to the upward air motions in thunderstorms and hence are indicative of strong wind convergence. Currently, lightning imagers on board the geostationary satellites provide increased availability of lightning data over broad regions and can improve weather forecasting accuracy. This paper describes how the space‐borne lightning observations could be employed to update model kinematic states and improve convective precipitation forecasting. Key Points: A lightning data assimilation (DA) scheme to update model kinematic states was developed using a three‐dimensional variational (3DVar) systemThe event data from Lightning Mapping Imager (LMI) aboard the FY‐4A geostationary satellite were assimilated to reflect lightning horizontal dimensionThe new lightning DA scheme improves the convective analysis and storm forecasting in two severe convective cases [ABSTRACT FROM AUTHOR]

Aerosol‐cloud interactions remain a major source of uncertainty in our understanding and modeling of the Earth's hydrological cycle. Based upon a diagnostic and modeling analysis utilizing the latest field measurements from the Integrative Monsoon Frontal Rainfall Experiment (IMFRE) 2018, this paper reports the effects of aerosols on the cloud properties along the Mei‐yu front over the Middle Reaches of Yangtze River in China. Numerical experiments with the Weather Research and Forecasting (WRF) model suggest that increasing aerosol number concentration reduces surface precipitation by ~8.8% and delays the onset of rainfall by ~30 min. Furthermore, warm clouds are suppressed but the convective cores are slightly intensified. This corresponds to an overall aerosol effect of "localization and invigoration" of the Mei‐yu rainfall and thus an elevated probability of short‐term heavy rainfall. The signals of "convective invigoration" with a bulk scheme in this study are relatively weak compared to those simulated by bin microphysics. The increased aerosol concentration strengthens Mei‐yu front and changes local morphology of the front, consistent with earlier studies demonstrating positive effects of convective heating on the genesis and maintenance of Mei‐yu front via conditional instability of the second kind (CISK) and diabatic generation of potential vorticity. Also discussed are the uncertainties of bulk microphysics in simulating aerosol‐cloud interactions, which may shed light on the design of future field campaigns to further understand the impact of aerosol‐cloud interactions on weather and climate over China in boreal summer. Key Points: Increased aerosol concentration suppresses warm clouds and slightly strengthens convection,leading to an overall effect of "localization and invigoration" of the Mei‐yu rainfallEnhanced latent heating in polluted conditions intensifies updrafts of convective coresIncreased aerosol concentration strengthens the Mei‐yu front and changes the local morphology of the front [ABSTRACT FROM AUTHOR]

Recent increases in computing power mean that atmospheric models for numerical weather prediction are now able to operate at grid spacings of the order of a few hundred meters, comparable to the dominant turbulence length scales in the atmospheric boundary layer. As a result, models are starting to partially resolve the coherent overturning structures in the boundary layer. In this resolution regime, the so‐called boundary layer "gray zone," neither the techniques of high‐resolution atmospheric modeling (a few tens of meters resolution) nor those of traditional meteorological models (a few kilometers resolution) are appropriate because fundamental assumptions behind the parameterizations are violated. Nonetheless, model simulations in this regime may remain highly useful. In this paper, a newly formed gray zone boundary layer community lays the basis for parameterizing gray zone turbulence, identifies the challenges in high‐resolution atmospheric modeling and presents different gray zone boundary layer models. We discuss both the successful applications and the limitations of current parameterization approaches, and consider various issues in extending promising research approaches into use for numerical weather prediction. The ultimate goal of the research is the development of unified boundary layer parameterizations valid across all scales. Key Points: The grid resolution of atmospheric models has become fine enough that are able to partially resolve turbulent motions in the boundary layerThis resolution regime comprises the turbulence "gray zone" where the assumptions behind traditional parameterizations are no longer validWe review the current efforts by modelers to overcome the gray zone problem in order to provide useful simulations at high resolutions [ABSTRACT FROM AUTHOR]

Demands are growing rapidly in the operational prediction and applications communities for forecasts that fill the gap between daily weather forecasts and seasonal climate outlooks. Recent scientific advances have identified sources of predictability on this time range, and modeling advances are leading to better forecasts. However, much remains to be done to further improve their skill and to develop new climate service forecast products to help countries and sectorial decision makers better manage weather risks and extremes and to adapt to climate change. This paper reviews the history and describes the main challenges and opportunities for the modeling and forecast‐applications communities to improve subseasonal to seasonal (S2S) forecasts and products, along with current developments catalyzed by the World Weather Research Programme and World Climate Research Programme's joint Sub‐Seasonal to Seasonal Prediction Project. The case of tropical cyclones is highlighted as an illustrative example of the points discussed. Plain Language Summary: The forecast range between weather forecasts and seasonal outlooks was long thought to be a "predictability desert" with little forecast skill. However, many management decisions in agriculture and food security, water, disaster risk reduction, and health fall into this gap in prediction capabilities, so that developing forecast capabilities for this time range would be of considerable societal value. New research and better models have begun to close this gap through increased international collaboration between weather and climate forecasting centers, national research programs, and the academic and user communities. Better understanding of the coupled ocean‐atmosphere‐land‐cryosphere system has identified multiple sources of S2S predictability that are starting to be exploited to fill the prediction gap spurred by creation of new forecast databases. Key Points: Subseasonal to seasonal prediction is a new and rapidly developing area of forecasting capabilitiesCollaborative research on interactions between weather and climate has been accelerated by new multimodel databases of forecastsSubseasonal tropical cyclone forecasts have improved substantially with good prospects for developing useful early warning systems [ABSTRACT FROM AUTHOR]

Atmospheric microbursts are low‐level meteorological events that can produce significant damage on the surface and pose a major risk to aircraft flying close to the ground. Studies and ad hoc numerical models have been developed to understand the origin and dynamics of the microburst; nevertheless, there are few researches of the phenomenon using global and mesoscale models. This is mainly due to the limitations in resolution, as microbursts normally span for less than 4 km and 20 min. In this paper, the Weather Research and Forecasting model is used at resolutions of 400 m and 3 min to test if it can properly capture the variables and dynamics of high‐reflectivity microbursts. Several microphysics and planetary boundary layer parametrizations are tested to find the best model configuration for the simulation of this kind of episodes. General conditions are evaluated by using thermodynamic diagrams. Surface and vertical wind speed, reflectivity, precipitation, and other variables for each simulated event are compared with observations, and the model's sensitivity to the variables is assessed. The dynamics and evolution of the microburst is evaluated using different plots of a chosen event. The results show that the model is able to reproduce high‐reflectivity microbursts in accordance with observations, although there is a tendency to underestimate the intensity of variables, most markedly on the wind vertical velocity. Regarding the microphysics schemes, the Morrison parametrization performs better than the WRF single‐moment 6‐class scheme. No major differences are found between the Mellor‐Yamada‐Janjic and the Mellor‐Yamada‐Nakanishi‐Niino planetary boundary layer parametrizations. Key Points: The Weather Research and Forecasting numerical model is able to reproduce high‐reflectivity microburstsThe characteristic variables of the microburst are properly simulated, although some intensities are lower than observationsDifferences are observed between different microphysics and planetary boundary layer parametrizations [ABSTRACT FROM AUTHOR]

Stochastic schemes, designed to represent unresolved subgrid‐scale variability, are frequently used in short and medium‐range weather forecasts, where they are found to improve several aspects of the model. In recent years, the impact of stochastic physics has also been found to be beneficial for the model's long‐term climate. In this paper, we demonstrate for the first time that the inclusion of a stochastic physics scheme can notably affect a model's projection of global warming, as well as its historical climatological global temperature. Specifically, we find that when including the "stochastically perturbed parametrization tendencies" (SPPT) scheme in the fully coupled climate model EC‐Earth v3.1, the predicted level of global warming between 1850 and 2100 is reduced by 10% under an RCP8.5 forcing scenario. We link this reduction in climate sensitivity to a change in the cloud feedbacks with SPPT. In particular, the scheme appears to reduce the positive low cloud cover feedback and increase the negative cloud optical feedback. A key role is played by a robust, rapid increase in cloud liquid water with SPPT, which we speculate is due to the scheme's nonlinear interaction with condensation. Plain Language Summary: Accurate estimates of the extent of global warming by 2100 are crucial for determining effective climate policies. However, large uncertainties still remain, due in large part to uncertainties in the response of clouds to global warming. Model uncertainties arise largely from the need to crudely estimate the effects of processes too small to represent perfectly (given the limits of current computing power). "Stochastic schemes" aim to represent such errors, thereby, potentially, improving climate models. Indeed, many such improvements have been found over the last decade. In this paper, we show that the inclusion of such a scheme in one particular climate model has the effect of reducing the projected global warming by 10%. We link this to the scheme having changed the response of clouds to global warming. A potential consequence of this result is that carefully calibrated stochastic schemes could, by representing model errors, improve the accuracy of global warming projections. Key Points: The inclusion of a stochastic scheme reduces climate sensitivity in a general circulation modelThis reduction, of around 10%, is linked to changes in cloud cover and cloud optical depth feedbacksWell‐calibrated stochastic schemes may give more accurate global warming projections [ABSTRACT FROM AUTHOR]

This paper introduces a synthetic polarimetric radar simulator and retrieval package, POLArimetric Radar Retrieval and Instrument Simulator (POLARRIS), for evaluating cloud‐resolving models (CRMs). POLARRIS is composed of forward (POLARRIS‐f) and inverse (retrieval and diagnostic) components (iPOLARRIS) to generate not only polarimetric radar observables (Zh, Zdr, Kdp, ρhv) but also radar‐consistent geophysical parameters such as hydrometeor identification, vertical velocity, and rainfall rates retrieved from CRM data. To demonstrate its application and uncertainties, POLARRIS is applied to simulations of a mesoscale convective system over the Southern Great Plains on 23 May 2011, using the Weather Research and Forecasting model with both spectral bin microphysics (SBM) and the Goddard single‐moment bulk 4ICE microphysics. Statistical composites reveal a significant dependence of simulated polarimetric observables (Zdr, Kdp) on the assumptions of the particle axis ratio (oblateness) and orientation angle distributions. The simulated polarimetric variables differ considerably between the SBM and 4ICE microphysics in part due to the differences in their ice particle size distributions as revealed by comparisons with aircraft measurements. Regardless of these uncertainties, simulated hydrometeor identification distributions overestimate graupel and hail fractions, especially from the simulation with SBM. To minimize uncertainties in forward model, the particle shape and orientation angle distributions of frozen particles should be predicted in a microphysics scheme in addition to the size distributions and particle densities. Key Points: New polarimetric radar simulator was developed for CRM evaluationThere are uncertainties remained in the assumptions of axis ratio and canting angles of ice particlesHydrometeor identification allows robust evaluation for bulk and bin microphysics [ABSTRACT FROM AUTHOR]

Föhn winds are warm, strong, downslope winds on the leeside of mountains, which can last from several hours to a few days. The years 1995 and 2002 saw the dramatic breakup of huge parts of the Larsen Ice Shelf (LIS) on the east of the Antarctic Peninsula. It is widely accepted that hydrofracturing, the widening of crevasses due to the excess hydrostatic pressure exerted by meltwater which accumulates inside them, is the mechanism behind the breakup of the Larsen A and Larsen B ice shelves. On the LIS, in the lee of the mountain range that runs along the spine of the Antarctic Peninsula, Föhn winds are thought to provide the atmospheric conditions for significant warming over the ice shelf, leading to the initial firn densification, and subsequently providing the melt water for hydrofracturing. Measurements provide evidence that in some cases Föhn events reach an Automatic Weather Station on the LIS at over 100 km distance. In this paper, we examine the representation of Föhn events during 2011 as they were observed in measurements by an Automatic Weather Station and in simulations with the Weather Research and Forecasting Model as run for the Antarctic Mesoscale Prediction System (AMPS). We find that, while the model generally simulates meteorological parameters very well and shows good skill in capturing the occurrence, frequency, and duration of Föhn events, it underestimates the temperature increase and humidity decrease during the Föhn significantly and may thus underestimate the contribution of Föhn to driving surface melt on LIS. Key Points: We compare high-resolution model AMPS with observational data in AntarcticaAMPS and observations agree better outside Föhn than during FöhnAMPS underestimates temperature and overestimates RH during Föhn [ABSTRACT FROM AUTHOR]

Water vapor is a key driver for the evolution of weather system. To investigate the impact of assimilating Sentinel‐3 precipitable water vapor (PWV) on weather forecasting, Sentinel‐3 PWV retrievals over the South China with two different assimilation schemes are assimilated into the Weather Research and Forecasting (WRF) model. In the first assimilation scheme, only Sentinel‐3 clear‐sky PWV are assimilated, while Sentinel‐3 all‐sky PWV are assimilated for the second assimilation scheme. For both data assimilation schemes, we totally conduct 28 WRF data assimilation runs and forecasts for 28 selected days over two periods, that is, 14 days in March 2020 and 14 days in June 2020. The weather condition in June 2020 is much wetter than March 2020. Generally, assimilating Sentinel‐3 PWV improves the WRF forecasting performance, particularly for June 2020. Assimilation of all‐sky PWV outperforms assimilation of clear‐sky PWV. The comparison results with radiosonde profiles show that assimilating Sentinel‐3 PWV appreciably corrects the bias of WRF water vapor mixing ratio forecasting results for June 2020. The rainfall validation results show that both assimilation schemes show a positive impact in June 2020, but a neutral impact in March 2020. For June 2020, assimilating Sentinel‐3 all‐sky PWV improves rainfall forecast skill score by 2.4%, while the rainfall forecast score is improved by 1.0% after assimilating clear‐sky PWV. Additionally, assimilation of Sentinel‐3 PWV can modify the WRF moisture field, which further improves the rainfall spatial pattern. Plain Language Summary: Water vapor is a key parameter in weather forecasting models as it plays a crucial role in the formation and evolution of weather process. Incorporating accurate water vapor observations from satellite‐based platforms has been demonstrated to be an effective way to improve the performance of forecasting model. While most of previous studies paid their attention on assimilating water vapor radiance data at infrared or microwave bands, this study assimilates the near infrared (NIR) water vapor data. The NIR data obtained from the Ocean and Land Colour Instrument aboard Sentinel‐3A/3B satellites are assimilated into the Weather Research and Forecasting (WRF) model. The Sentinel‐3A/3B water vapor data assimilation experiments are conducted for two different periods with two different weather conditions, that is, dry period (March 2020) and wet period (June 2020). The experiment results showed that assimilation of Sentinel‐3A/3B water vapor data can improve the WRF water vapor forecasting accuracy and rainfall forecasting performance. The bias of forecast humidity profile has also been considerably corrected after assimilation. The improvements gained from Sentinel‐3A/3B water vapor data are larger for the wet period. Key Points: Assimilating Sentinel‐3 precipitable water vapor (PWV) considerably reduces the bias in Weather Research and Forecasting model's humidity forecasting field during wet periodAssimilating Sentinel‐3 PWV improves the probability of detection of 12‐hr accumulated rainfall by 2.4% during wet periodAssimilating all‐sky PWV can get a higher rainfall pattern correlation than no data assimilation and assimilating clear‐sky PWV [ABSTRACT FROM AUTHOR]

The Weather Research and Forecasting model was applied in a nested configuration from the convection‐permitting resolution of 2.5 km, via an intermediate resolution of 500 m down to the 100 m turbulence‐permitting scale to investigate the spatial and temporal evolution of the convective boundary layer and their interaction with the underlying land surface. This included detailed comparisons with observations collected during the Land‐Atmosphere Feedback Experiment, performed at the Central Facility in Oklahoma. The simulation was driven by the operational analysis of the European Center for Medium‐range Weather Forecasting for a cloud‐free case on 23 August 2017 for which the measurement operation was extended into the following night to include the evening decay of the daytime convective boundary layer. The mesoscale 2.5 km resolution was capable to represent the correct boundary layer height and its temporal evolution. Details of the morning and evening transitions between the nighttime and daytime boundary layer as well as its internal structure were only simulated by the 100 m turbulence‐permitting simulation. Although systematic differences between the simulation and lidar observations were found, the model captured the temporal and spatial structure and the statistics of turbulence rather well. Comparison with data from Eddy‐Covariance stations showed that the model was able to reproduce the evolution of many near‐surface meteorological fields. Systematically higher surface temperatures and related differences in the surface fluxes suggest weaknesses in the representation of land surface processes although the simulation was initialized with accurate and high‐resolution initial fields. Plain Language Summary: A nested configuration of the Weather Research and Forecast model was applied to simulate the evolution of the convective boundary layer for a cloud‐free case during the Land Atmosphere Feedback Experiment. The simulation was driven by the European Center for Medium‐range Weather Forecasting operational analysis and applied nests with 2,500, 500, and 100 m resolution. Detailed comparisons with observations revealed that the applied model configuration was capable to realistically simulate the spatial and temporal evolution of the convective boundary layer including the morning transition and the evening decay. Systematic differences were an overestimated boundary layer height, weaker turbulent variability or a too weak decrease of moisture above the boundary layer, indicating that some processes may not be captured properly by the selected configuration or model physics. Comparison of higher‐order moments of water vapor mixing ratio over a three‐hour time period with lidar data revealed that the model was capable to realistically resolve the turbulence statistics, but also here systematic differences to the observations were found. Finally, comparison of surface meteorological observations with data from Eddy‐Covariance stations revealed weaknesses in the simulation of land surface atmosphere interaction. Key Points: A nested Weather Research and Forecasting simulation from 2.5 km down to 100 m horizontal resolution was set up for a cloud‐free case study during the Land‐Atmosphere Feedback Experiment experimentThe turbulence‐permitting 100 m domain captured the spatial and temporal evolution of the convective boundary layer rather wellComparison with lidar data showed that the model was capable to represent the turbulence statistics although differences in detail occurred [ABSTRACT FROM AUTHOR]

The performance of 4‐km Weather Research and Forecasting model in predicting reflectivity structure in China over three summer months is investigated using three‐dimensional (3D) reflectivity observations. Three verification domains, namely Southern China (SC), Central and Eastern China , and North China, that correspond to the three major rainfall centers of mainland China are selected. Results show that the forecasts reproduce the distribution and diurnal variation of precipitation well, but significant differences exist in the vertical distributions of the predicted and observed reflectivities. In observations, the highest frequency (of reflectivity ≥35 dBZ) occurs between 3 and 6 km, whereas it is at the surface in the forecast. The forecasts tend to over‐predict reflectivity intensity at the lower levels, especially in SC. Further evaluation using object‐based verification methods show that the forecasts greatly underestimate the afternoon peak frequency of precipitation clouds with reflectivity >30 dBZ. The forecasts fail to reproduce the diurnal variation of 35 dBZ mean and maximum height of the objects, producing less variation than observations. Analyses show that the failure in properly reproducing small‐scale reflectivity objects (with diameter <100 km) is primarily responsible for the underestimation of the mean and maximum object heights. Evaluation using additional 3D information show that the forecasts tend to produce a greater proportion of faster‐moving small‐scale objects. This study reveals that the simulation of the 3D structure of precipitation clouds in terms of reflectivity remains a great challenge, especially for smaller convective cells. Plain Language Summary: The simulation of precipitation clouds is associated carries the largest uncertainty in numerical weather prediction and climate models. With continued advancement in observations and numerical models, forecasts of horizontal distribution, intensity, diurnal variation and propagation of precipitation have been greatly improved. However, faithful representation of three‐dimensional (3D) cloud structure remains a great challenge, with the lack of systematic evaluations being one of the key causes. In this study, 3D gridded radar reflectivity observations are used to evaluate the precipitation clouds structure (with reflectivity ≥30 dBZ) predicted at a convection‐permitting‐resolution (CPR) over three summer months of 2016 in China. The evaluation reveals differences between the simulated and observed reflectivity structures, including the reflectivity intensity profile, the 35 dBZ mean and maximum height, the fraction of fast‐moving objects. CPR models still have difficulties in simulating 3D reflectivity structures especially for relatively small‐scale objects (with diameter <100 km). Key Points: Reflectivity structure predicted by the 4‐km Weather Research and Forecasting model are evaluated using 3D radar observationsThe model overpredicts the intensity of reflectivity at lower levels and fails to reproduce the diurnal variation of object heightThe failure to correctly reproduce the structure of smaller reflectivity objects is primarily responsible for the deviations [ABSTRACT FROM AUTHOR]

An extreme heavy rainfall event in Henan Province (HnHRE) of central China in July 2021, which is jointly affected by the western Pacific subtropical high (WPSH) and Typhoon In‐Fa (2021), is comprehensively studied through five experiments conducted using the Weather Research and Forecasting Model (WRF). The patterns of the WPSH, In‐Fa, and precipitation are well reproduced in the control experiment. The magnitude of potential vorticity (PV) anomaly associated with the WPSH (In‐Fa) is increased and decreased by 50% in the initial condition based on the piecewise PV inversion method, namely, SH150 and SH050 (TC150 and TC050), respectively. The analysis shows that the 54‐hr rainfall accumulations in TC150 and TC050 are reduced by 39.5% and 31.8%, respectively, more than 28.8% in SH150 and 20.1% in SH050, indicating that Typhoon In‐Fa plays a more critical role in the rainfall amplification than the WPSH. This result also confirms that the HnHRE occurs within the quite favorable configuration of WPSH and In‐Fa circulations. The WPSH and In‐Fa majorly control the meridional and zonal moisture transports, respectively. The diagnosis of moist ageostrophic ω $\omega $ turns out that diabatic heating is closely related to the vertical motion during the HnHRE. Besides, the heavy rainfall region is also closely attributed to the distributions of equivalent potential temperature and divergence. Plain Language Summary: This study focuses on a typical heavy rainfall event (HRE) related to the western Pacific subtropical high (WPSH) and Typhoon In‐Fa (2021). The study aims to quantitatively analyze the effects of the WPSH and In‐Fa and their interactions, which play a vital role in the HRE. The distribution and amount of rainfall are reasonably reproduced in a numerical model. Moreover, the four sensitivity experiments are conducted to identify the influence of the WPSH and In‐fa on the HRE. The results confirm that the HRE occurs under the highly favorable WPSH and In‐Fa circulations and their cooperation. Typhoon In‐Fa plays a more critical role in rainfall amplification than the WPSH. This finding emphasizes that the interaction of the WPSH and typhoon has an important effect on the HRE. Key Points: Typhoon In‐Fa plays a more critical role in the rainfall amplification than the western Pacific subtropical highThe western Pacific subtropical high and Typhoon In‐Fa majorly control the meridional and zonal moisture transports, respectivelyDiabatic heating plays a primary role in vertical motion during this heavy rainfall event [ABSTRACT FROM AUTHOR]

In this study, we developed a regional coupled model for the western North Pacific (WNP) and East Asian region. The atmospheric/oceanic component of the coupled model was the Weather Research and Forecasting and the Regional Ocean Modeling System, coupled through the National Center for Atmospheric Research Coupler version 7 (CPL7). An evaluation is provided through the simulation of the climatology and interannual variability of the summer monsoon climate from 1982 to 2015. The coupled model is also compared with a solely atmospheric run, which is driven by the observed sea surface temperature (SST) as the surface boundary. The results show that the coupled model has good capability in modeling the climate in the WNP and East Asian domain, including the climatology of summer precipitation and circulation, the subseasonal (month‐to‐month) variation in the western Pacific subtropical high and associated precipitation, and the seasonal cycle of the East Asian rain belt. One merit of this model is its ability to simulate the northward and eastward shift from early to late summer. With respect to the interannual variability, the model captures the spatial pattern of the leading mode of summer precipitation, with a north–south dipole mode in the studied region. The model also reproduces the larger SST variability in the northern part of this region. The temporal correlation coefficient between the coupled simulation and observation was 0.70 for the precipitation and 0.53 for the SST leading mode. The coupled model also captures the precipitation–SST relationship, which results from reasonably considering the air–sea coupling processes in the coupled run. Plain Language Summary: Due to the resolution of global models is relatively coarse and cannot describe the regional features, especially in the monsoon regions, regional climate model is an essential solution for regional climate simulation and projection. Compared with atmospheric alone model which is driven by prescribed sea surface temperature, regional air‐sea coupled model can describe reasonably the air‐sea coupling processes and has better performance. In this study, an regional coupled model is developed based on the Community Earth System Model coupler version 7 framework. Based on our analysis, the regional coupled model reasonably reproduced most key characteristics in the East Asian monsoon region. In addition to being used in regional climate simulation and projection, it can also be conveniently coupled with global models through the coupler 7. Thus with this useful tool in future we can develop global‐regional two‐way coupling simulation system for climate predictions and projections. Key Points: A regional coupled model is developed for East Asia and western North Pacific region based on Community Earth System Model frameworkClimatology and interannual variability of the summer monsoon climate have been evaluatedThe model can well capture the climatological northward and eastward movements of the western Pacific subtropical high from June to August [ABSTRACT FROM AUTHOR]

Previous numerical studies have focused on the direct impact of microphysics schemes on multiscale atmospheric systems that produce rainfall. However, the indirect impact of microphysics schemes on the key large‐scale circulation around areas of extreme rainfall has not yet been examined systematically. We used the ARW‐WRF (Advanced Research WRF (Weather Research and Forecasting) Model) to simulate the extreme rainfall event in Henan province, China from 19 to 21 July 2021. Experiments were conducted to investigate the sensitivity of the simulation to the three popular double‐moment microphysics parameterizations: the Thompson, Morrison and WDM6 (WRF Double‐Moment 6‐Class Microphysics Schemes). We found significant sensitivity to the microphysics parameterization, with the maximum precipitation varying by up to 400 mm and the area‐averaged precipitation by 33 mm. The Thompson and Morrison microphysics schemes produced the largest amount of precipitation, whereas the WDM6 scheme produced the smallest amount of precipitation. The simulated southerly flow varied substantially between the different microphysics schemes. This is due to the ability of the microphysics schemes to produce latent heat, which enhances the southerly flow, leading to more intense precipitation. The higher the parameterized latent heat, the stronger and more obvious the southerly flow over southern Henan province, with the WDM6 scheme simulating a much weaker southerly flow and the Thompson scheme producing the strongest southerly flow. These results indicate that the indirect effects on the key circulation patterns can be just as sensitive to the formulation of the microphysics scheme as the direct effects on extreme rainfall. These results may help to improve the prediction of extreme rainfall events. Plain Language Summary: Complex microphysical processes have crucial impacts on the accurate prediction of the intensity and areal extent of extreme rainfall. However, previous studies have focused on rain amount related to the microphysical schemes caused by intrinsic microphysical processes or direct influencing systems—such as typhoons, squall lines and convective systems—and little attention has been paid to increase of rain amount related to the microphysical schemes caused by the surrounding key circulation of extreme rainfall. Through numerical simulations of the extreme rainfall event in Henan province, China from 19 to 21 July 2021 using three popular microphysics schemes, we show that indirect effect of microphysical schemes on the extreme rainfall can effectively regulate the southerly flow over southern China. The microphysics schemes influence the southerly flow through latent heating. A greater amount of latent heat can produce a stronger southerly flow, which favors the transport of water vapor and energy to the Henan region and produce more intense precipitation. Key Points: The simulated southerly flow and precipitation vary substantially between different microphysics schemesThe microphysics schemes influence the southerly flow through latent heatingThe Thompson and Morrison schemes produce more latent heat, and therefore a stronger southerly flow, than the WDM6 (WRF Double‐Moment 6‐Class Microphysics scheme) [ABSTRACT FROM AUTHOR]

This study investigates the relative impact of assimilating the ground‐based WSR‐88D radar (GBR) and the airborne Tail Doppler Radar (TDR) observations on the analysis and prediction of Hurricane Harvey (2017) during its landfalling stage. Results show that the assimilation of GBR (experiment "DAG") outperforms the assimilation of TDR (experiment "DAT") in multiple aspects. For example, "DAG" produces better predictions in Vmax, radial velocity, brightness temperature, and precipitation than "DAT." The advantages of "DAG" over "DAT" are likely from the better analyzed thermodynamical structures in addition to the better data availability. The average Minimum Sea Level Pressure (MSLP) prediction error is the only aspect of "DAG" that is inferior to "DAT." Diagnostics show that such an inferior performance of MSLP for "DAG" is associated with the systematic bias from the Hurricane Weather Research and Forecasting model. The combined assimilation of both observations (experiment "DAB") shows complementary effects and performs the best overall among all experiments. Plain Language Summary: The Ground‐based WSR‐88D Radar (GBR) and the airborne tail Doppler Radar (TDR) observations have been separately assimilated and evaluated in the analysis and prediction of landfalling hurricanes in the past. This study explores their relative and combined impacts. Using a newly developed, GSI‐based, hourly hybrid three‐dimensional ensemble‐Kalman‐Filter‐Variational data assimilation system for the Hurricane Weather Research and Forecasting, experiments are performed for the landfalling stage of Hurricane Harvey (2017). Results showed that the continuous availability allows GBR to produce better and more persistent improvements in the analysis and the subsequent forecasts than TDR. Investigations show that the improvements are not only in the wind fields but also in the precipitation and brightness temperature predictions. The combined assimilation shows complementary effects and further improves upon GBR alone. Key Points: Both ground‐based radar and airborne radar observations are critical to analyzing and predicting the landfalling of hurricane HarveyThe continuous ground‐based radar observations benefit the analysis and prediction of Harvey more than the intermittent airborne datasetsCombining both observations shows complementary effects and produces Harvey's overall best analysis and predictions [ABSTRACT FROM AUTHOR]

We introduce the latest version of the RegCM regional climate modeling system, RegCM5. Compared to the previous model version (RegCM4) the main new development is the inclusion of the non‐hydrostatic dynamical core from the weather prediction model MOLOCH, which is more accurate and much more computationally stable and efficient than the previous one. In particular, the new dynamical core is best designed for use at convection‐permitting resolutions of a few km. Several physics schemes and coupled model components have also been upgraded compared to the previous version of the model. A set of test simulations for present day climate conditions at parameterized convection and convection permitting resolutions over different European domains is presented for illustrative purposes. Overall, for these simulations RegCM5 exhibits a better performance than RegCM4 for the majority of statistics analyzed, especially at convection‐permitting resolutions. However, this performance depends on the physics schemes used, and further optimization work is under way to fully test the model in different climate settings and reduce current biases. RegCM5 is a freely available, computationally efficient, flexible, and portable Regional Earth System model designed for community use, so that prospective model users are welcome to access its code and use it for different applications. Plain Language Summary: We introduce the latest version of the RegCM regional climate modeling system, RegCM5, in which the main new development, in addition to some physics upgrades, is the inclusion of the non‐hydrostatic dynamical core from the weather prediction model MOLOCH. This makes the model more accurate and much more computationally efficient than the previous version, especially at convection‐permitting resolutions of a few km. A set of test simulations for present day climate conditions at parameterized convection and convection permitting resolutions over different European domains is presented for illustrative purposes. Overall, these simulations show that RegCM5 mostly exhibits a better performance than RegCM4 for most statistics analyzed, especially at convection‐permitting resolutions, although this performance depends on the physics schemes used. Further optimization work is under way to fully test the model in different climate settings and reduce current biases. RegCM5 is a freely available, computationally efficient, flexible, and portable Regional Earth System model designed for community use, so that prospective model users are welcome to access its code and use it for different applications. Key Points: The fifth version of the regional climate modeling system RegCM, has been developed and releasedIllustrative experiments show that the model overall performs better and is much more computationally efficient than the previous versionThe model is a community resource so that prospective users are encouraged to access it and use it [ABSTRACT FROM AUTHOR]

Temperatures near 0°C represent a critical threshold for many environmental processes and socio‐economic activities. This study examines surface air temperatures (T) near 0°C (−2°C ≤ T ≤ 2°C) across much of southern Canada over a 13 year period (October 2000–September 2013). It utilized hourly data from 39 weather stations and from 4‐km resolution Weather Research and Forecasting model simulations that were both a retrospective simulation as well as a pseudo‐global warming simulation applicable near the end of the 21st century. Average annual occurrences of near‐0°C conditions increase by a relatively small amount of 5.1% from 985 hr in the current climate to 1,035 hr within the future one. Near‐0°C occurrences with precipitation vary from <5% to approximately 50% of these values. Near‐0°C occurrences are sometimes higher than values of neighboring temperatures. These near‐0°C peaks in temperature distributions can occur in both the current and future climate, in only one, or in neither. Only 4.3% of southern Canada is not associated with a near‐0°C peak and 65.8% is associated with a near‐0°C peak in both climates. It is inferred that latent heat exchanges from the melting and freezing of, for example, precipitation and the snowpack contribute significantly to some of these findings. Plain Language Summary: Our changing climate is spurring the development of huge efforts to improve resiliency. For many regions of the world, these efforts must account for potential changes in near‐0°C conditions within which both melting and freezing can occur and the accompanying latent heat exchanges can push air temperature toward 0°C. This article focuses on the occurrence of near‐0°C surface temperatures across southern Canada through an examination of observational and model information including projections in a future warmer (average 6.1°C increase) climate near the end of the 21st century. Average annual occurrences of near‐0°C conditions increase by a relatively small amount of 5.1% in the future climate and highest values continue to be along the Pacific coast or within the Western Cordillera and lowest values continue to be within central and northern areas. Near‐0°C occurrences are often higher than those of neighboring temperatures in the present climate and some of these elevated occurrences persist into the future one despite dramatic warming. It is inferred that latent heat exchanges from the melting and freezing of precipitation and snowcover contribute to these findings. Key Points: Near‐0°C surface air temperatures were examined over southern Canada using retrospective and pseudo‐global warming simulationsOverall average occurrences increase slightly and their spatial patterns are largely maintained in the warmer climateNear‐0°C occurrences sometimes exceed those of neighboring temperatures and this feature often persists despite dramatic warming [ABSTRACT FROM AUTHOR]

The calculation of surface sensible heat (SH) and latent heat (LE) fluxes using the bulk transfer models for complex terrains, tall vegetation regions, and morning and evening transition periods remains a challenging problem in numerical weather and climate models. The maximum entropy production (MEP) model, a new method of calculating surface heat fluxes, is coupled with the Noah land surface model (LSM) in the Weather Research and Forecasting (WRF) model. Surface heat fluxes and meteorological variables including air temperature, relative humidity, soil temperature, and precipitation data at nine intensive observation stations and 453 routine meteorological operational observation stations in the Tibetan Plateau (TP) from 1 June to 31 August 2015 are used to evaluate the coupled model. The results show that the MEP method improves the nonclosure of the surface energy balance in the WRF (with an energy residual from 24.3 to 1.9 W m−2), reducing the overestimations of SH and LE and the underestimation of the surface ground heat flux over the complex terrain of TP (with the bias decreases of 50.6% and 117.1% for SH and LE in turn), especially during the daytime. The improved SH and LE reduce the cold and wet biases in the TP by 29.4% and 51.7%, respectively. The MEP model also reduces the overestimated soil temperature by 63%. Moreover, the overestimated daily precipitation is reduced by 3% over the TP. The successful application of the MEP method demonstrates its advantage over the bulk transfer method, providing a new approach for reducing the overestimation of surface heat fluxes and wet and cold biases in numerical forecast models in complex terrains. Plain Language Summary: In this study, the maximum entropy production (MEP) model, as a new promising method of calculating surface heat fluxes, is coupled to the Weather Research and Forecasting Noah land surface model to replace the original bulk transfer model. The coupled MEP model improves the predictions of surface sensible and latent heat fluxes, air temperature and humidity, precipitation, and soil temperature when compared to observations in the Tibetan Plateau (TP) and the adjacent areas. Overall, the coupled MEP model overcomes some drawbacks of modeling surface heat fluxes with bulk transfer models in numerical forecast models and improves the understanding of land‐atmosphere interactions in the TP and their impacts. Key Points: We use the maximum entropy production (MEP) method instead of the bulk transfer method to calculate surface heat fluxes in the Weather Research and Forecasting (WRF) Noah land surface modelThe MEP method improves the nonclosure of the surface energy budget in the WRF, reducing the overestimation of sensible heat and latent heat over the Tibetan Plateau (TP)The MEP method reduces the cold and wet biases around the TP, leading to an improved understanding of land‐atmosphere interactions [ABSTRACT FROM AUTHOR]

Convective clouds are important for both the vertical redistribution of tropospheric trace gases and the removal, via microphysical scavenging, of soluble trace gas precursors of ozone. We investigate wet scavenging of formaldehyde (CH2O), hydrogen peroxide (H2O2), and methyl hydrogen peroxide (CH3OOH) in quasi‐marine and land convective storms over Texas, USA observed on 18 September 2013 during the 2013 SEAC4RS campaign. Cloud‐resolving simulations using the Weather Research and Forecasting model with Chemistry (WRF‐Chem) were performed to understand the effect of entrainment, scavenging efficiency (SE), and ice physics processes on these trace gases with varying solubility. While marine and land convection can have distinctly different microphysical properties, we did not find significant differences in the SEs of CH2O, H2O2, or CH3OOH. The SEs of 44%–53% for CH2O and 85%–90% for H2O2 are consistent with our previous studies from SEAC4RS and the 2012 DC3 field experiment storms. Using WRF‐Chem simulations, the ice retention factor (rf) for CH2O was determined to be 0.5–0.9, which is higher than found in previous studies. We show that the CH2O rf is higher in airmass and multicell storms than in severe storms and hypothesize that ice shattering may affect CH2O rf values. The CH3OOH SEs (39%–73%) were higher than expected from Henry's Law equilibrium. While recent studies suggest that CH3OOH measurements have interference due to methane diol, we find that this interference cannot fully explain the higher‐than‐expected CH3OOH SEs determined here and during DC3, suggesting further research is needed to understand CH3OOH vertical redistribution. Plain Language Summary: Thunderstorms are important mechanisms for the transport and removal of trace gases in the atmosphere. This study investigates the transport and removal processes of tropospheric ozone trace gas precursors in marine and land convective storms over Texas, USA. Numerical simulations were performed to understand storm processes affecting atmospheric gases with different solubilities. While marine and land storms can have distinctly different storm structure and updraft winds, we did not find significant differences in the amount of gases removed by these storms. The results show that the efficiency of the storm in removing gas from the atmosphere is consistent with our previous findings for moderate to severe storms over the US. In addition, the analysis showed when cloud drops freeze onto ice and snow particles that formaldehyde had more retention in the frozen particle in moderate storms compared to severe storms suggesting that there are many processes affecting this key ozone precursor in deep convection. The more soluble hydrogen peroxide did not show the same ice retention behavior because it is removed by precipitation in the warmer, liquid‐only region of the storm. Key Points: Although marine and land convection have different microphysical properties, there are no relevant differences in the scavenging efficiencyWRF‐Chem simulations analysis shows ice retention factor for formaldehyde is higher than found in previous studiesMethyl hydrogen peroxide scavenging efficiencies are higher than expected from Henry's Law, even with potential measurement interference [ABSTRACT FROM AUTHOR]

In numerical weather prediction models, the typhoon track and intensity forecast performances are highly sensitive to physics parameterization schemes. To investigate the impact of physics parameterization schemes on the real‐time short‐term forecasts, we simulated six typhoons which directly/indirectly affected the South Korea region in recent years using the Weather Research and Forecasting (WRF) model. Three cumulus parameterization schemes (CPSs) of Kain‐Fritsch (KF), Betts‐Miller‐Janjić (BMJ), modified Tiedtke (TDK), and two cloud microphysics parameterization schemes (MPSs) of WRF‐single‐moment‐microphysics class 6 (WSM6), Predicted Particle Properties (P3) 1‐category were selected for the sensitivity experiment. The results showed that there was a significant difference in simulated typhoon track and intensity performances depending on the physics schemes. On average, the typhoon forecast performances were improved when applying the KF scheme for CPS and WSM6 scheme for MPS in our experimental setup. The BMJ‐applied runs showed the worst performances, which simulated westward shifted typhoon tracks compared to other runs. Overall, the typhoon track and intensity spreads tended to be more sensitive to CPSs and MPSs, respectively. We conducted additional sensitivity experiments using the BMJ scheme with modified reference and temperature profiles. The result showed that the overactivity of the BMJ scheme at low latitudes was reasonably reduced, leading to the improved simulation of typhoons and synoptic fields. Plain Language Summary: To improve the real‐time short‐term forecast performances for the recent typhoon cases that affected South Korea, sensitivity experiments for the various physics parameterization schemes, such as cumulus parameterization and cloud microphysics schemes, were conducted. Through additional experiments with one of the modified schemes and a comparison of detailed inner cloud processes, the reason for the different track and intensity forecast performances among the sensitivity experiments were revealed. Key Points: The effect of cumulus parameterization and cloud microphysics schemes on the real‐time forecast of typhoons around South Korea is studiedOne of the cumulus parameterization schemes was modified to decrease its activity at low latitudesEven short‐term typhoon forecasts could be largely affected by the forecast performances of convective processes at the tropics [ABSTRACT FROM AUTHOR]

Northeast China cold vortex (NECV) is the major influencing weather system in northern China. Yet the impacts of complex terrain on the evolution of NECV remains poorly understood. This work studies the influence of subgrid orographic drag (SOD) on a heavy‐rain‐producing NECV occurred in July 2011 using the Weather Research and Forecasting model. A series of numerical experiments are conducted with different parameterizations of SOD including turbulent orographic form drag (TOFD), flow blocking drag (FBD), and mountain wave drag (MWD). Results show that the NECV intensity is overestimated in the absence of SOD parameterization, accompanied with too‐low geopotential height (GPH) and too‐strong horizontal winds. The parameterization of TOFD can significantly decelerate the 10‐m winds, whereas the FBD and MWD play a minor role. However, the influence of TOFD is overwhelmed by FBD and MWD in the troposphere, especially the latter. This implies that the breaking of mountain waves play a more important role in weakening the NECV than the low‐level flow blocking. The lower‐tropospheric MWD directly weakens the convergence and ascent motion of the NECV, producing an anti‐cyclonic circulation that uplifts the GPH under the constraint of quasi‐geostrophic vertical vorticity. This MWD‐induced circulation indirectly weakens the NECV in the mid‐upper troposphere by producing a warm advection that counters the low‐level cold advection to the southwest of the NECV. The findings provide useful insights into the impacts of complex terrain on the NECV and highlight the importance of topographic drag parameterization in the simulation and short‐range forecast of NECV. Plain Language Summary: Northeast China cold vortex (NECV) is a major influencing weather system in northern China which often promotes severe convective weather like heavy rainfall, hail, and tornado. Past studies have revealed the importance of atmospheric circulations (e.g., Rossby waves associated with Eurasian blocking), sea surface temperature anomalies over North Pacific, and large‐scale orography in East Asia on the evolution of NECV. However, the underlying terrain in East Asia is much complex. It is still unclear how the NECV is affected by complex terrain. This work studies a NECV case using the Weather Research and Forecasting model, focusing on the impacts of different topographic drags including turbulent orographic form drag (TOFD), mountain wave drag (MWD), and flow blocking drag (FBD) produced by complex terrain. The influence of TOFD is basically confined in the boundary layer whereas the FBD and MWD play a major role in the troposphere, especially the latter. The low‐level MWD directly weakens the NECV in the lower troposphere by inducing an anti‐cyclonic circulation. Consequently, the low‐level cold advection to the southwest of the NECV is suppressed which indirectly weakens the NECV in the mid‐upper troposphere. The findings highlight the importance of topographic drag parameterization in the simulation and short‐range forecast of NECV. Key Points: The impacts of different topographic drag on the Northeast China cold vortex are firstly studied using numerical sensitivity experimentsTurbulent orographic form drag dominates the impact on near‐surface winds, while mountain wave drag plays a major role in the troposphereLow‐level mountain wave drag directly and indirectly weakens the cold vortex in the lower and mid‐upper troposphere, respectively [ABSTRACT FROM AUTHOR]

Wave breaking under strong wind conditions in tropical cyclones (TCs) can generate sea spray droplets, which, during their suspension in air, release sensible heat due to the air‐sea temperature difference while absorb sensible heat from the environment when they evaporate and release latent heat to the environment. Since the spray mass flux is a function of surface drag coefficient (CD), the effect of spray on TC evolution should depends on CD parameterization, while this has not been addressed so far. This study examines the effects of sea spray on the simulated TC evolution with two different CD parameterizations (the Weather Research and Forecasting (WRF) default scheme and the Donelan scheme). Results show that during the primary intensification stage, the TC with spray effect becomes stronger than that without spray when the WRF CD scheme is used, but becomes weaker when the Donelan CD scheme is used. This occurs because CD is maximum outside the radius of maximum wind (RMW) with the Donelan scheme, which produces relatively large spray‐mediated latent heat flux outside the RMW, which is unfavorable for TC intensification. The difference is enlarged by a feedback between spray and TC intensification involving the inertial stability and surface friction‐induced radial inflow. However, in the mature stage, the simulated TCs with spray become stronger no matter which CD scheme is used. In addition, the spray effect on the TC inner‐core size evolution also weakly depends on the drag parameterization. When CD is relatively greater outside the RMW, the inclusion of the spray effect would lead to the inner‐core size increase. Plain Language Summary: Wave breaking under strong wind conditions, such as in tropical cyclones (TCs), can generate abundant sea‐spray droplets, which, during their suspension in air, release sensible heat due to the air‐sea temperature difference while absorb sensible heat from the environment when they evaporate and release latent heat to the environment. This will mediate the air‐sea enthalpy transfer and affect the TC intensification. As the spray mass flux is closely related with sea surface drag coefficient (CD), we investigated how the spray effects on TC intensity evolution depend on the CD scheme used in idealized numerical simulations. Two CD schemes were used to perform four numerical experiments. Results show that the sea spray effect on TC intensity evolution depends on the CD scheme used and the stages of the TC lifetime, largely due to the different wind speed dependence of CD and its effect on the radial distribution of the spray‐mediated latent flux. However, the finding demonstrates that caution should be given to surface drag parameterization when the sea spray effects on TC evolution are studied using numerical models. It is also suggested that efforts to measure spray properties under TC conditions should be conducted to validate/improve spray parameterization in the future. Key Points: The sea spray effect on tropical cyclone (TC) intensity evolution depends on the surface drag (CD) scheme used and the stages of the TC lifetimeDifferent wind speed dependence of CD can affect the radial distribution of the spray mass flux and thus spray‐mediated enthalpy fluxAlthough spray can speed up or slow down the intensification rate, it contributes positively to the mature‐stage TC intensity [ABSTRACT FROM AUTHOR]

The Weather Research and Forecasting (WRF) model was applied to simulate the current and future climates over eastern China at a convection‐permitting resolution (∼4 km). A continuous 10‐year (1998–2007) simulation was performed for the historical climate, and three pseudo‐global warming (PGW) experiments driven by climate perturbations during 2070–2099 were conducted under the RCP2.6, RCP4.5, and RCP8.5 scenarios. After validation against reanalysis and observational data, the historical simulation was found capable of reasonably reproducing the characteristics of mean precipitation, extreme hourly precipitation, and large‐scale circulation. The PGW experiments projected an increase in precipitation intensity over most regions, especially North China under the RCP8.5 scenario (up to 30%). However, the precipitation frequency was projected to decrease, especially over the Yangtze River Basin in summer. A wetting (drying) trend was observed over North China (South China) in summer (winter), due to the increase (decrease) in precipitation intensity (frequency). The intensity and frequency of extreme events were projected to increase over most areas of eastern China, and the increase was the most dramatic under the RCP8.5 scenario, indicating a greater flood risk under stronger global warming. The relationship between extreme precipitation and temperature (EP–T) displayed a hook‐shape structure in both the present and future climates. The extreme precipitation intensity increased with temperature at a super Clausius–Clapeyron (C–C) scaling rate (>7%/K) until reaching a peak at temperatures of around 25–29°C, and then decreased at higher temperatures. The decreases were mainly attributed to moisture limitation at high temperatures. In the future, the EP–T relationship is expected to change mostly following the C–C law, with greater precipitation peaks under scenarios with higher carbon emissions, indicating that warmer climates contribute to further enhancement of extreme precipitation. Plain Language Summary: The extreme precipitation–temperature (EP–T) scaling relation is a useful conceptual tool for understanding the changes in extreme precipitation in present and future climates. EP‐T relation is related to Clausius–Clapeyron (C–C) relationship which indicates that precipitation is expected to increase by 7% for each degree of temperature increasing. However, EP‐T relation can deviate from the C–C scaling according to studies based on observations and numerical models. The relation between hourly EP and T is essential for predicting instantaneous weather hazards over eastern China, but such relation was not well reproduced by previous studies using GCMs with coarser resolution. In this study, we investigated the current and future hourly EP–T relation over eastern China using high‐resolution (4 km) convection‐permitting RCM (CP‐RCM). Our analysis indicates that CP‐RCM can well reproduce the characteristics of extreme hourly precipitation and large‐scale circulation. Precipitation intensity will increase but precipitation frequency will decrease in the future over eastern China. The EP–T relation displays a hook‐shape structure in both the present and future climates mainly due to moisture limitation at higher temperatures. The warmer the future climates, the more intense the extreme precipitation. Key Points: Future changes in precipitation over eastern China were assessed using pseudo‐global warming simulations at a convective‐permitting resolutionHourly extreme precipitation was projected to be more frequent and intense over eastern China in the future, while light and moderate rain will likely decreaseHourly extreme precipitation and temperature over eastern China displayed a hook‐shape relationship, due to moisture limitation at high temperatures [ABSTRACT FROM AUTHOR]

Current lightning predictions are uncertain because they rely on empirical diagnostic relationships and often use coarse‐scale climate scenario simulations in which deep convection is parameterized. Previous studies demonstrated that simulations with convection‐permitting resolutions improve lightning predictions compared to coarser‐grid simulations using convection parameterizations for different geographical locations but not over the boreal zone. In this study, lightning simulations with the NASA Unified‐Weather Research and Forecasting model are evaluated over a domain including the Great Slave Lake in Canada, for six lightning seasons. The simulations are performed at convection‐parameterized (9 km) and convection‐permitting (3 km) resolution using the Goddard 4ICE and the Thompson microphysics schemes. Four lightning indices are evaluated against observations from the Canadian Lightning Detection Network, in terms of spatiotemporal frequency distribution, spatial pattern, daily climatology, and an event‐based overall skill assessment. The Thompson scheme is, regardless of the spatial resolution, superior to the Goddard 4ICE scheme in predicting daily climatology but worse in predicting the spatial patterns of lightning occurrence. Results indicate that lightning estimation benefits from modeling at convection‐permitting resolution, in particular for the ice‐based lightning indices. In contrast, the product of convective available potential energy and precipitation rate proved to be the most robust index that was largely invariant to varying spatial resolution. Finally, this study reveals issues of the models to reproduce the observed spatial pattern of lightning well, which might be related to an insufficient representation of land surface heterogeneity, including peatlands, in the study area. Plain Language Summary: Lightning is a phenomenon known by everyone. To predict when and where lightning will occur, numerical models are used. These models combine complex mathematical equations to make a model of the real world. By starting from a real‐life example, models could predict the future. In our everyday life, models are present everywhere. One of the most obvious examples is the weather forecast. This study uses such a model to try to predict lightning occurrence while starting from known past conditions. But since the small‐scale processes that lead to lightning are so difficult to model, different people came up with different methods to predict lightning. In this study, four of these methods are compared for the boreal zone where lightning could increase with global warming and mobilize carbon through wildfire ignition. Our results show that there is no single best method to predict lightning, but a finer model resolution does improve the accuracy of the models. Finally, this study shows that the model still cannot predict accurately where lightning will occur. This might be due to problems of the models to simulate the water and energy cycle over specific boreal land elements such as peatlands. Key Points: The NASA Unified‐Weather Research and Forecasting modeling framework is run at two resolutions to predict lightning over the boreal zoneLightning estimation benefits from modeling at convection‐permitting resolutionIce‐based lightning indices are more sensitive to model resolution than nonice‐based lightning indices [ABSTRACT FROM AUTHOR]

In June‐July 2020, the Middle and Lower Yangtze River Region (MLYR) encountered the most severe precipitation event over the past 60 years. The Indian Ocean Dipole (IOD) in the previous autumn of the unusual precipitation event was the main contributing factor. Nonetheless, not every strong IOD event could bring anomalously high precipitation in the MLYR. This study showed significantly enhanced influence of IOD on East Asia climate since 2000. The IOD's effect on MLYR summer precipitation has strengthened significantly with the correlation coefficient up to 0.55 during 2000–2020. The northward movement of East Asia–Pacific pattern associated with IOD since 2000 (as compared with before) was primarily responsible for the enhanced effect. Since 2000, the MLYR has been controlled by a deep baroclinic instability system with anomalous low pressure in the lower troposphere and anomalous high pressure (completely different from before). Furthermore, the western Pacific subtropical high shifted northward and westerly jets were significantly enhanced with eastward expansion. All of these patterns contributed to the water vapor convergence and precipitation generation in the MLYR, which was not the case in the past. The record‐breaking IOD in 2019 autumn and the enhanced IOD's climatic effect in 2000–2020 contribute to the extreme Meiyu in 2020 jointly. The significant change in the influence of IOD and the enhanced climate effect of IOD highlight exciting new avenues for improving climate predictions in the MLYR. Plain Language Summary: The excessive Meiyu rainfall over the Middle and Lower Yangtze River Region (MLYR) during summer 2020 was beyond expectations of meteorologists, because in the 2019/20 winter, the Niño3.4 index was marginal at only 0.5°C as compared to 2.4°C and 2.6°C in 1997/98 and 2015/16 winters, respectively. Researches pointed out that the severely positive Indian Ocean Dipole (IOD) in the previous season was the main contributing factor on 2020 extreme Meiyu event in the MLYR. Nonetheless, not every strong IOD event could bring anomalously high precipitation in the MLYR. Our study shows significantly enhanced influence of IOD on East Asia climate since 2000. The IOD's effect on MLYR summer precipitation has strengthened significantly with the correlation coefficient up to 0.55 during 2000–2020. The IOD‐induced circulation patterns, including East Asia–Pacific pattern, the western Pacific subtropical high, and westerly jets, shifted northward with stronger intensity since 2000 (as compared with before). These results help us to reconsider the influence of tropical Indian Ocean sea surface temperature when forecasting weather or the possible climate changes under global warming. Key Points: The impact of Indian Ocean Dipole (IOD) on the Yangtze precipitation has enhanced in recent decadesThe IOD‐induced East Asia–Pacific pattern moves northward since 2000The interdecadal change in IOD's climatic effect largely contributes to the extreme Meiyu in 2020 [ABSTRACT FROM AUTHOR]

Dust aerosols pose non‐negligible impacts on regional and global climate, particularly over northwest China (NWC), where dust events frequently occur. Here, six dust events with different intensities occurred from 2014 to 2019 in NWC were simulated by the Weather Research and Forecasting model coupled to Chemistry (WRF‐Chem) to quantitatively evaluate the contributions of dust aerosols to radiation fluxes, surface energy, and meteorology, with specific consideration to the distinctions between daytime and nighttime. The results show that the contributions of dust aerosols to surface energy and meteorology were significantly affected by dust concentrations and dust layer heights and exhibited diurnal variation. In the case with high dust concentration and low dust layer height, dust aerosols increased the surface energy during the nighttime but decreased in the daytime, and the increase was much greater than the decrease. As a result, dust aerosols increase surface energy (0.06 W/m2 in the dust source region; 0.13 W/m2 in the dust affected region (DAR)) and surface temperature (0.0088°C in the DSR; 0.0781°C in the DAR) and decrease surface relative humidity (−0.053% in the DSR; −0.205% in the DAR) throughout the whole day. In contrast, dust causes opposite impacts on surface meteorology throughout the whole day due to the nighttime warming effect from the dust events with low dust concentration and high dust layer height is lesser than the daytime cooling effect. The study provides scientific insights for improving our understanding of dust aerosols‐regional meteorology interaction. Plain Language Summary: Dust aerosols pose non‐negligible impacts on regional and global climate, particularly over northwest China, where dust events frequently occur. However, the differences in the impacts of dust aerosols on surface energy and meteorological fields during daytime and nighttime are still not fully understood and warrant in‐depth investigations. Six dust events simulated by the WRF‐Chem model show that the contributions of dust aerosols to surface energy and meteorology are significantly affected by dust concentrations and dust layer heights and exhibit diurnal variation. The underlying mechanisms of the impacts of two kinds of typical dust events on surface energy and meteorology are revealed. The study provides scientific insights for improving our understanding of dust aerosols‐regional meteorology interaction. Key Points: The dust direct radiative forcing over different regions of northwest China exhibits significant differences during daytime and nighttimeThe underlying mechanisms of the impacts of two kinds of typical dust events on surface energy and meteorology are revealedThe dust concentration and dust layer height are the key factors resulting in opposite changes in surface atmospheric variables [ABSTRACT FROM AUTHOR]

Winter season Saharan dust aerosols are transported into West Africa and pose as a natural hazard with individual dust events significantly reducing air quality. We simulate four multi‐day dust events using the Weather, Research and Forecasting Chemistry (WRF‐CHEM) in Senegal during December 2016, December 2017, February 2019, and March 2019. We use Geospatial Informational System mapping to estimate PM10 concentrations for the 14 administrative districts within Senegal. Saharan dust events are evaluated using surface PM10 concentrations at Dakar, Senegal, Moderate Resolution Imaging Spectrometer Aerosol Optical Depth, Aerosol Robotic Network, and the WRF‐CHEM model to evaluate dust concentrations across Senegal. We show that a north to south pressure gradient associated with the southward movement of the Azores high into North Africa are responsible for dust generation and transport into Senegal during 2016 and 2017. Conversely, Saharan depressions moving across the Sahara Desert are responsible for the two high‐impact dust events in February and March of 2019. Based on our analysis, the most severe of the four dust events impacting Senegal occurred in December 2017, with hazardous PM10 concentrations simulated for 7 days affecting an estimated 86% of Senegal's population. Furthermore, the February 2019 dust event occurred during the presidential elections, potentially exposing many voters to poor air quality. A network of surface dust observations and dust forecasts are critical for protecting the Sahelian public from dangerous dust events. Together, they allow for preventative measures to minimize harmful PM10 concentration exposure, especially for children under 5, the elderly, and those with existing respiratory and cardiovascular diseases. Plain Language Summary: Across the Sahara Desert, mobile synoptic‐scale high and low‐pressure areas can produce pressure gradients driving strong winds and generating surface dust emissions transported into West Africa. Previous studies have shown that exposure to high levels of PM10 can have negative health implications, specifically for children under the age of 5. We analyze four significant North African dust events that impacted Senegal during the winter months of 2016, 2017, and 2019. For each storm, we evaluate the meteorological conditions responsible for the transport of dust and the observed surface and satellite aerosols and modeled PM10 concentrations. The simulated dust events are compared to station data in Dakar, Senegal, and suggest varying unhealthy air quality from each storm. The simulated spatial scale of unhealthy air quality ranges from the northern half of Senegal to the entire country in the case of the December 2017 dust event. The February 2019 dust event occurred during Senegal's presidential elections, potentially exposing many voters to poor air quality. Developing a network of surface measurements can help evaluate and improve dust forecasts in Sahelian countries for Saharan dust events. Key Points: The four high impact winter dust events affecting Senegal are driven by the Azores High and Saharan depressionsThe Weather Research and Forecasting simulation of the four events show multi‐day unhealthy air quality across SenegalImproving surface measurements of PM in Senegal could improve dust forecast and understanding health implications of dust events [ABSTRACT FROM AUTHOR]

An important assumption made in most variational, ensemble, and hybrid‐based data assimilation systems is that all minimized errors are Gaussian random variables. A theory developed at the Cooperative Institute for Research in the Atmosphere enables for the Gaussian assumption for the different types of errors to be relaxed to a lognormally distributed random variable. While this is a first step toward using more consistent distributions to model the errors involved in numerical weather/ocean prediction, we still need to be able to identify when we need to assign a lognormal distribution in a mixed Gaussian‐lognormal approach. In this paper, we present some machine learning techniques and experiments with the Lorenz 63 model. Using these machine learning techniques, we show detection of non‐Gaussian distributions can be done using two methods: a support vector machine and a neural network. This is done by training past data to classify (1) differences with the distribution statistics (means and modes) and (2) the skewness of the probability density function. Key Points: Machine learning can be used to detect non‐Gaussian behavior [ABSTRACT FROM AUTHOR]

Pyrocumulus (pyroCu) formation during convective fire‐atmosphere interaction is a driving factor causing extreme and unpredictable wildfires. Here, by investigating several cases of pyroCu occurrence, we have monitored fire‐induced changes in atmospheric boundary layer (ABL) vertical profiles of state variables (temperature, humidity, and wind). Particular emphasis is placed in relating them to observed versus modeled fire spread biases. To this end, during the 2021 fire season in the Iberian Peninsula, we conducted a pyroconvection monitoring campaign. We gathered data on hourly fire spread, plume surface, deepening and penetration stages, and in‐situ radiosoundings within wildfire plumes. European Centre for Medium‐Range Weather Forecasts ERA5 weather data completed the analysis as reference modeling information to characterize the meso and synoptic scales on the thermodynamic profiles. We propose a novel classification of pyroconvection‐type events based on (a) differences in ABL thermodynamic stability, (b) regions characterized by high turbulence in the sub or pyroCu‐layers, and (c) the reinforced entrainment of free‐tropospheric air on top of every convective plume. This classification defines four types: (a) convective plumes, (b) overshooting pyroCu, (c) resilient pyroCu, and (d) deep pyroCu/pyroCb. Those prototypes change ABL conditions (temperature, humidity, height) differently depending on the dry or moist convection enhancement that drives them. Using this distinct behavior, we find correlations between observed ABL thermodynamic changes after fire‐atmosphere interaction and fire spread biases. Our findings pave the way to quantify the pyroconvection effect on fire spread and facilitate safer and more physically sound decisions when analyzing extreme fires. Plain Language Summary: Extreme wildfires pose severe problems for responders and managers. Those fires are unpredictable, driven by fire‐induced convection phenomena such as pyrocumulus (pyroCu). Therefore, to anticipate fire spread in these uncertain scenarios, we need to understand pyroCu formation better. During the 2021 summer season in Iberian Peninsula, we monitored pyroCu events and launched sondes into the fire plumes. To investigate fire‐induced changes in atmosphere vertical profile variables (temperature, humidity, and wind), we compared these in‐situ sonde measures with modeled profiles from atmospheric model ERA5. Finally, we correlated the atmospheric vertical profile changes with fire spread biases. We identified different types of changes characterized by four distinctive types of pyroclouds. In all cases, changes resulted from air mass dryness from the upper layers of the atmosphere being transported down into the lower layers. The resulting modified atmospheric boundary layer created different than expected burning conditions and changed fire behavior to the extreme. We quantified those changes in fire rate of spread correlated with the updraft vertical velocity inside the fire plume. This research proposes a first quantitative correlation to predict extreme wildfire behavior driven by pyroCu. Key Points: Importance of turbulence near the atmospheric boundary layer (ABL) entrainment zone to determine the classification of pyroconvection typesPyrocloud layer entrainment into sub‐pyrocloud layer creates moist or dry convection regimes, defining the changes induced into ABLThe fire plume updraft vertical velocity is positively correlated to fire rate of spread bias during pyroconvection events [ABSTRACT FROM AUTHOR]

The west‐east terrain cross‐section along ∼150 km of the northern part of Israel has a coastal plain—mountain—valley structure; hereafter denoted iCMV. The boundary layer height (BLH) evolution mechanism across the iCMV has not yet been fully understood. We use Weather Research and Forecasting (WRF) simulations and ceilometer measurements to decipher the iCMV BLH evolution mechanism during the late summertime period of 5–14 September 2017, where the daily maximum BLH at the mountainous city of Jerusalem (JrM; 800 m above sea level) varies by ∼1,000 m. We first verify the BLH, simulated by five model configurations (with four different BL schemes). The RMSE for the three best configurations are around 160 and 200 m for the coastal and JrM areas, respectively. An analysis of the simulated daily BL evolution reveals a general mechanism. In the early morning, the upslope flows and synoptic forcing interact to induce a surface flow convergence (SFC) zone. During a westerly (easterly) synoptic flow, the SFC is induced east (west) of JrM. Assisted by the inland propagating sea breeze front, the SFC is advected eastwards during the afternoon, until it collapses at the valley bottom. The SFC zone is accompanied by a substantial positive vertical wind column and a locally elevated BLH. The more western the morning time SFC is, the more likely the elevated BLH will pass during midday through JrM, with a higher daily maximum BLH. The exact dependence of the BLH evolution and of the associated temperature and humidity variations upon the synoptic regime require further study. Key Points: Weather Research and Forecasting simulations are used to study the boundary layer height (BLH) evolution across the Israeli coast—mountain—valley (west‐east) terrainBefore midday, the synoptic, and upslope flows induce a stationary surface convergence zone of hyperelevated BLHThe initial location of the elevated BLH zone depends on the synoptic regime. It is later advected toward the valley by the sea breeze [ABSTRACT FROM AUTHOR]

Arctic cyclones are a fundamental component of Arctic climate, influencing atmospheric heat and moisture transport into the region and surface energy, moisture, and momentum fluxes. Arctic cyclones can also drive changes in sea ice and energize ocean waves. Here we investigate a record low sea level pressure (SLP) Arctic cyclone which formed in East Greenland and tracked NE over the Barents and Kara seas between 21 and 27 January 2022. At its peak intensity on 24 January, the cyclone reached an estimated depth of 932.2 mb at 79.5°N 20°E. North of 70°N, this is the lowest SLP in the ERA‐5 reanalysis over 1979 to present. The cyclone resulted in a record (over the period 1979–2022) weekly loss of regional sea ice area and surface wind speeds, and generated ocean waves exceeding 8 m that impinged on sea ice in the Barents sea, observed via satellite altimetry as large waves‐in‐sea ice up to 2 m in amplitude more than 100 km into the ice pack. Surface heat fluxes were strongly impacted by the cyclone, with record atmosphere‐to‐surface turbulent fluxes. However, the direct atmospheric thermodynamic impact on sea ice loss was modest, and the record sea ice changes were likely mainly driven by dynamical and/or ocean processes. While the storm was well predicted up to 8 days in advance, subsequent changes in sea ice cover were not, likely due to biases in the forecasts' sea ice initial conditions and missing physics in the forecast model such as wave‐sea ice interaction. Plain Language Summary: The strongest recorded storm in the Arctic took place in January 2022. This storm was characterized by record wind speeds, sea ice loss and turbulent fluxes, and anomalous but less extreme temperature anomalies. We learned that some of this storm's record‐breaking characteristics were predicted well by model forecasts. However, the effects of this storm on the Arctic sea ice cover were not well predicted. Forecasts underestimated the decrease in sea ice thickness and area from the storm. Satellite data showed large waves traveling into the icepack, which may have contributed to the sea‐ice loss. Such processes may be poorly represented in the model, which hinder its ability to accurately forecast sea‐ice conditions. Improving initial conditions and the representation of interactions between the atmosphere, sea ice, and ocean in models may help improve forecasts of weather and sea ice. Key Points: A record low sea level pressure cyclone was observed in the Arctic in January 2022This low resulted in a record weekly loss of sea ice cover and record surface wind speeds, despite non‐record warm conditionsWhile the storm was well predicted, the rapid decreases in sea ice thickness and area were not [ABSTRACT FROM AUTHOR]

The early development of Super Typhoon Lekima (2019) under moderate vertical wind shear (VWS) is examined on the basis of a convection‐permitting simulation with the Weather Research and Forecast model. The tropical cyclone (TC) evolves from a tilted vortex to an upright vortex with a meso‐γ‐scale high‐vorticity core and finally to a vortex with a well‐defined eyewall preceding rapid intensification. The shift of the upper‐middle‐tropospheric vortex to the upshear‐left quadrant is critical to the establishment of an upright TC vortex with high vorticity concentrated in the center. As the upper‐middle‐tropospheric vortex reaches the upshear‐left quadrant, it drifts toward the TC center under the horizontal advective effect of VWS, leading to a reduction of TC vortex tilt. The low stability and high humidity below the upper‐middle‐tropospheric vortex together with the fast increase of upper‐middle‐tropospheric vorticity promote the convection around the TC center, which is important to the maintenance of the nearly upright TC vortex and the development of the high‐vorticity core in TC vortex. The evolution of the TC from an upright vortex with a high‐vorticity core to a vortex with a well‐defined eyewall is bound with the convection near the radius of maximum azimuthal‐mean tangential velocity. The convection enhances the boundary‐layer inflow and then the supergradient force above the radially inward side of the strong boundary‐layer inflow. In this way, the convergence within and above the boundary layer is strengthened, favoring the formation of a ring of deep convection and high vorticity. Such processes are similar to those leading up to secondary eyewall formation. Key Points: Lekima evolves from a tilted vortex to an upright vortex with a high‐vorticity core and then to a vortex with a distinct eyewall before rapid intensificationShift of the upper‐middle‐level vortex to the upshear‐left promotes the formation of an upright vortex with meso‐γ‐scale vorticity coreConvection near the RMW promotes the enhancement and inward penetration of boundary‐layer inflow, favoring the circular eyewall formation [ABSTRACT FROM AUTHOR]

An extreme rainfall case occurred on 20 July 2016 in northern China, producing over 600 mm of maximum 24 hr accumulated rainfall. The case is characterized by low‐echo centroid (LEC) based on radar observations. It is simulated by Weather Research and Forecasting model at 4 km grid spacing using the Morrison two‐moment microphysics scheme. Infrared brightness temperature (BT) simulated using a radiative transfer model together with simulated reflectivity are used to evaluate the simulated cloud structures. In general, the model predicts the rainfall amount, location, and propagation well. However, it fails to accurately predict the three‐dimensional cloud structures. The predicted convective cores (>35 dBZ) are higher than the freezing level, suggesting the presence of active cold‐cloud processes while the observed LEC suggests that warm‐cloud processes dominate. The simulation also produces too many upper level clouds and over‐predicts the fractions of overshooting clouds, resulting great over‐prediction of cloud top height (CTH). Additionally, the sensitivity of simulated BT to predicted cloud properties including CTH, cloud species and hydrometeor effective radii are examined to better understand the sources of error in simulated BT. Among those factors, CTH is found to be most critical to BT simulation. For every kilometer of CTH over‐prediction, there is about 6.431 K of negative BT bias owing to the lapse rate and the absorption and scattering effects of cloud particles. For most cloudy regions, cloud ice dominates the effect on simulated BT. Using diagnosed effective radii of simulated hydrometeors within the radiative transfer model results in small improvement to the BT simulation. Key Points: The 3D cloud structure of a severe low‐echo centroid (LEC) convection case is poorly simulated with three popular two‐moment microphysics schemesOver‐prediction of convective core heights and upper‐level cloud fraction suggest deficiencies in the microphysics schemes in simulating LECSimulated brightness temperature is most sensitive to cloud top height and vertical distribution of ice particles [ABSTRACT FROM AUTHOR]

Solar phenomena such as flares and solar energetic particles events are potential candidates to affect the global atmospheric electric circuit. One can study these effects using measurements of the atmospheric electric field in fair weather regions. In this paper, we investigate deviations of the atmospheric electric field daily curve during solar disturbances (solar flares and solar proton events) from mean values obtained in fair weather conditions. Using the superposed epoch analysis, in order to enhance the visualization of small effects, we study the atmospheric electric field data observed between January 2010 and December 2015 at the Complejo Astronómico El Leoncito, San Juan, Argentina. The results show no deviation of the atmospheric electric field after solar flares, and an increase of about 10 V/m after solar proton events. The last result suggests possible ionization effects above thunderstorm in disturbed weather regions, which alters the global atmospheric electric circuit. On the other hand, we analyze the variation of the atmospheric electric field during a ground level enhancement on 17 May 2012, which was capable to produce changes on the surface electric field. Key Points: Solar flare photons are unlikely to affect the global atmospheric electric circuit at low latitudesSolar proton events enhance the conductivity above thunderstorms resulting in an atmospheric electric field increase in fair weather regions at low latitudesGround level enhancement that occurred on 17 May 2012 was capable to produce an atmospheric electric field decrease in fair weather conditions at low‐latitude regions [ABSTRACT FROM AUTHOR]

Frontal boundaries have been shown to cause large changes in CO2 mole‐fractions, but clouds and the complex vertical structure of fronts make these gradients difficult to observe. It remains unclear how the column average CO2 dry air mole‐fraction (XCO2) changes spatially across fronts, and how well airborne lidar observations, data assimilation systems, and numerical models without assimilation capture XCO2 frontal contrasts (ΔXCO2, i.e., warm minus cold sector average of XCO2). We demonstrated the potential of airborne Multifunctional Fiber Laser Lidar (MFLL) measurements in heterogeneous weather conditions (i.e., frontal environment) to investigate the ΔXCO2 during four seasonal field campaigns of the Atmospheric Carbon and Transport‐America (ACT‐America) mission. Most frontal cases in summer (winter) reveal higher (lower) XCO2 in the warm (cold) sector than in the cold (warm) sector. During the transitional seasons (spring and fall), no clear signal in ΔXCO2 was observed. Intercomparison among the MFLL, assimilated fields from NASA's Global Modeling and Assimilation Office (GMAO), and simulations from the Weather Research and Forecasting‐—Chemistry (WRF‐Chem) showed that (a) all products had a similar sign of ΔXCO2 though with different levels of agreement in ΔXCO2 magnitudes among seasons; (b) ΔXCO2 in summer decreases with altitude; and (c) significant challenges remain in observing and simulating XCO2 frontal contrasts. A linear regression analyses between ΔXCO2 for MFLL versus GMAO, and MFLL versus WRF‐Chem for summer‐2016 cases yielded a correlation coefficient of 0.95 and 0.88, respectively. The reported ΔXCO2 variability among four seasons provide guidance to the spatial structures of XCO2 transport errors in models and satellite measurements of XCO2 in synoptically‐active weather systems. Key Points: First airborne observations of column average CO2 dry‐air mole‐fraction (XCO2) changes across fronts observed during ACT‐A are reportedXCO2 frontal structures compare reasonably well with Weather Research and Forecasting—Chemistry and an in situ data driven assimilation systemResults reveal that the differences across models and data were generally much smaller than the magnitude of XCO2 frontal contrasts [ABSTRACT FROM AUTHOR]

In mesoscale Weather Research and Forecasting (WRF) model, several urban‐modeling options exist, such as Single‐layer Urban Canopy Model, Building Effect Parameterization, and Building Energy Model. However, these models have limitations in terms of the choice of land surface models (LSMs) and planetary boundary layer (PBL) schemes, the associated computational expenses, and other constraints. Recently, Dy et al. (2019, https://doi.org/10.1029/2018JD029333) included the urban‐momentum drag effect for wind‐speed modeling by developing a new multilayer model based on a modified nonlocal Asymmetric Convective Model version‐2 (ACM2) PBL scheme. This urban‐based ACM2 (UACM) has demonstrated a significantly improved ability over the base‐ACM2 (BACM) to predict wind speed near the urban ground surface and shown an inflection point at roof level in the vertical profile of horizontal wind. In this study, urban thermal and moisture components are introduced into the Pleim‐Xiu (PX) LSM and coupled with UACM. The diurnal variation in street, walls, and roof‐surface temperatures is modeled using the two‐layer force‐restore algorithm. Simple radiation treatment is considered to account for shadowing on streets based on the solar zenith angle and building morphology. Heat and moisture flux evolution are considered explicitly on all urban surfaces. The advantages of this novel UACM are simple formulation, more efficient execution, and its requirement for only a few fundamental urban morphological parameters. The idealized and real urban data case WRF simulations are performed over the Pearl River Delta region in southern China to test the new UACM. The computationally efficient UACM is expected to perform faster for operational forecasting runs. Key Points: Urban thermal and moisture effects are included in the Pleim‐Xiu land surface model, and connected to the Urban Asymmetric Convective ModelAbility of new UACM is confirmed by performing idealized simulations to analyze model sensitivity to various urban morphological parametersImprovement in the urban wind, temperature, and moisture‐prediction is demonstrated with the new UACM by conducting real‐data case studies [ABSTRACT FROM AUTHOR]

The impacts of topography and urbanization on an extreme rainfall (ER) event in the Hangzhou Bay (HZB) region were investigated using the Weather Research and Forecasting model with one control simulation and three artificial scenarios of no‐HZB, no‐mountains on the south bank of HZB, and no‐urban. Thirty members with different combinations of physical parameterizations were considered for each scenario. The control test results were evaluated and they showed that the model well reproduced the ER that occurred in the HZB region, and the ensemble results were valuable and credible. The existence of HZB, mountains, and urbanization would increase the ensemble mean of accumulated precipitation by 52.07%, 37.11%, and 9.35%, and the probability of heavy rainfall by about 25%, 20%, and 15% in the main rain belt region, respectively. In addition, these factors also introduced more uncertainties in the same physical scheme combination. The impacts of these factors on the distribution, intensity, and mechanism were different. The comparison results showed that the existence of HZB played the most important role in this ER event by the remarkable influence of low‐level wind field and horizontal convergence, followed by the existence of mountains, which mainly affected the distribution of rainfall caused by the airflow climbing up the hill before the mountain. Although urbanization exerted positive effects on this ER event, the impact was relatively small and locally near the urban regions compared with the other two factors. Plain Language Summary: The impacts of topography and urbanization on an extreme rainfall (ER) event in the Hangzhou Bay (HZB) region were investigated by ensemble forecast method. The control test results were evaluated and showed that the model reproduced the ER that occurred in the HZB region reasonably well, and the ensemble results were valuable and credible. The microphysics parameterization scheme exhibited the highest levels of uncertainty in this ER event, followed by the planetary boundary layer, land surface, and urban physics schemes. The comparison results showed that the existence of HZB, mountains, and urban would increase the ensemble mean of accumulated precipitation and the probability of heavy rainfall, and these factors also introduced more uncertainties in the same physical scheme combination. The existence of HZB played the most important role in this ER event by the remarkable influence of low‐level wind field and horizontal convergence, followed by the existence of mountains, which mainly affected the distribution of rainfall caused by the airflow climbing up the hill before the mountain. Although urbanization exerted positive effects on this heavy rainfall, the impact was relatively small and locally near the urban regions compared with the two other factors. Key Points: The ensemble results were valuable and credible, and the microphysics and PBL schemes exhibited the highest two levels of uncertaintyThe existence of Hangzhou Bay played the most important role in this extreme rainfall event, followed by the existence of mountains and urbanThe existence of these factors would increase the rainfall amount and the probability of heavy rainfall, and introduced more uncertainties [ABSTRACT FROM AUTHOR]

The hydroclimatology and hydrometeorology of flooding over the Third Pole region is poorly understood, despite its societal and environmental significance. Here we examine extreme rainfall and flooding over the eastern Tibetan Plateau (TP) based on empirical analyses of long‐term, in‐situ rainfall and stream gaging observations as well as the ECMWF Reanalysis fields. We develop a flood catalog that consists of 168 extreme rainfall‐runoff floods over the eastern TP, and characterize the synoptic conditions for flood‐producing storms based on the principal component analysis. We show the transitional pattern form Asian summer monsoons to midlatitude systems as the most frequent synoptic conditions for flooding over the eastern TP. The interplay between complex terrains and moisture transport determines the contrasting flood characteristics (in terms of intensity and spatial pattern) under different synoptic environments. We carry out high‐resolution Weather Research and Forecasting modeling analysis for four flood‐producing storms over the eastern TP. We highlight the interaction of complex terrains and nocturnal low level jets as the key mesoscale ingredients in dictating a pronounced diurnal cycle of extreme rainfall over the southeastern portion of TP. Our results establish the link between large‐scale synoptic environment, mesoscale process, and regional flood hydrology over the eastern TP, and therefore contribute to improved flood risk management practices over the Third Pole region under a changing climate. Key Points: We examine meteorological floods over the eastern Tibetan Plateau based on long‐term, in‐situ stream gaging and rainfall observationsThe transitional pattern from Asian summer monsoons to midlatitude systems is the most frequent synoptic condition for floodingThe interplay between complex terrains and moisture transport dictates contrasting flood characteristics under different synoptic patterns [ABSTRACT FROM AUTHOR]

Investigation of the variations of hydrological cycles during the Last Interglacial (130–115 ka; LIG) may deepen our understanding of climate change in a warmer‐than‐present world induced by Earth's orbit. Here we revealed an intensified atmospheric branch of the hydrological cycle over the Tibetan Plateau (TP) in summer during the LIG relative to the preindustrial period, using the mesoscale Weather Research and Forecasting model driven by the Community Earth System Model. Our results showed that precipitation over the TP increased by 5.65 × 107 kg s−1, with 63.2% of the increase contributed by advected moisture transports, and the remaining 36.8% caused by local moisture recycling processes. As for advected moisture transports, the inflow increased by 1.93 × 107 kg s−1 and the outflow decreased by 0.87 × 107 kg s−1, respectively. Variations of the moisture transport were more profound at the eastern and northern edges, which were linked with changes in Indian summer monsoon and westerly jets. Regarding local moisture recycling processes, evaporation enhanced by 2.85 × 107 kg s−1 over the TP, influenced by variations in surface air temperature, surface net radiation flux, surface relative humidity, and surface wind fields. Increased evaporation accompanied by enhanced moisture inflow resulted in an enriched precipitation recycling ratio of ∼1% over the TP during the LIG relative to the preindustrial in summer. Our results aid in understanding the atmospheric branch of the hydrological cycle over the TP in an orbit‐induced warmer world and shed light on the future evolution of the hydrological cycle over the TP at multi‐millennial and orbital timescale. Key Points: Dynamical downscaling simulations for the Last Interglacial from Weather Research and Forecasting driven by Community Earth System ModelIntensified atmospheric branch of the summer hydrological cycle over the Tibetan Plateau during the Last Interglacial (LIG)Intensified hydrological cycle was manifested in both external and internal cycles during the LIG [ABSTRACT FROM AUTHOR]

Hypothermia killed 21 participants of the 100 km cross‐country Ultramarathon Mountain race in Baiyin, Gansu Province in northwestern China on 22 May 2021, when a large‐scale cold front passed by the race site. The hypothermia was caused by low temperatures, high winds, and hail‐like precipitation, as reported by survivors. However, there is no meteorological station near the race site, leading to a lack of data on the exact weather conditions during the race. Considering the complex topography of the race site, the weather conditions must be re‐built using high‐resolution model simulations, so that the tragedy can be investigated. In this study, the weather conditions in this mountainous area were simulated using the Weather Research and Forecasting model with a 333 m horizontal grid size. The results show that interaction between the mountain wind and orographic precipitation led to a 6.7°C decrease in temperature and a 12 m s−1 increase in wind speed. Precipitation increased owing to orographic accent and convergence, and fell as graupel. High‐speed downslope winds were the result of large‐amplitude trapped lee waves. The combination of low temperatures, high winds, and spillover graupel on the lee resulted in the blizzard‐like weather during the race, thus the hypothermia amongst the runners. The apparent temperature was estimated to be as low as −10°C. Our study shows that mesoscale numerical models with a grid size of hundreds of meters should be used to improve weather forecasts in mountainous regions and prevent future tragedies for special events. Key Points: A small‐scale mountain played a key role in the weather conditions that caused 21 deaths of hypothermia during an ultramarathonThe spillover graupel and high downslope winds led to blizzard‐like weather on the lee and an apparent temperature of −10°CMesoscale numerical models of hundreds‐meter resolution may improve weather forecasts in mountainous regions to prevent future tragedies [ABSTRACT FROM AUTHOR]

Eastern China is perennially hit by mesoscale convective systems (MCSs), yet it remains an open question as to whether and how their general properties change throughout the annual cycle. By leveraging high‐resolution satellite observations and a hybrid tracking algorithm, we present a 20‐year (2001–2020) climatology of MCSs over eastern China during eight subseasonal‐to‐seasonal (S2S) monsoon stages. MCSs contribute up to 50% of the stage‐total precipitation and over 60% of the rainband‐zone precipitation during the Pre‐Meiyu and Meiyu episodes, and their contributions remain non‐trivial during the transition seasons. We discover two contrasting regimes of MCSs that alternate immediately upon the Pre‐Meiyu and the Fall onsets. The wintertime regime features fast‐propagating shallow systems initiated at night in a strongly sheared and dry environment. The summertime regime, instead, features an outbreak of MCSs in the south, where the systems often initiate in the afternoon and propagate 2–3 times slower than the cold‐season ones. Based on multivariate clustering analysis, the nighttime MCSs that dictate the winter stages often initiate over a deep nocturnal boundary layer with moist rear inflows upgliding above it. In contrast, the afternoon‐initiated MCSs under the summertime regime feature a pronounced convective available potential energy (CAPE) "tongue" and upslope flows in their southeast quadrant. The southwesterly moist ascending flows are likely to shallow the convective inhibition at the tip of the CAPE tongue and facilitate the intense updrafts of the MCSs. Findings here may offer insights into S2S weather prediction and facilitate agricultural and water management throughout the year. Plain Language Summary: Eastern China has been one of the worst‐hit regions globally by extreme precipitation and floods. Many of these hazards result from intense and well‐organized rainstorms, also known as mesoscale convective systems (MCSs), typically lasting for several hours with a horizontal scale of 100 km or larger. Despite numerous case studies on their evolution and dynamics, the annual cycle of the impacts and properties of MCSs is yet to be fully understood. Using high‐resolution satellite observations and a hybrid tracking algorithm, we present a 20‐year (2001–2020) climatology of MCSs in eight monsoon stages year‐round. We discover a dual regime wherein two distinct regimes of MCS characteristics are observed throughout the annual cycle. It turns out that MCSs can contribute up to 50% of the stage‐total precipitation and over 60% of the rainband‐zone precipitation during the pluvial episodes, and their contributions remain non‐trivial during the transition seasons. The prevailing environmental conditions at the initiation of MCSs are revealed and discussed. Findings from the present study help broaden our understanding of the annual cycle of MCSs and may offer insights into numerical weather simulations and prediction, water and agricultural management, and disaster risk reduction in eastern China. Key Points: An unprecedented monsoon‐annual‐cycle climatology of mesoscale convective systems (MCSs) in eastern ChinaDiscovery of two contrasting regimes of MCSs that alternate upon the Pre‐Meiyu and Fall onsetsMoist rear inflows, static instability, upslope flows, and cold pool‐shear interactions are recurring in convective initiation [ABSTRACT FROM AUTHOR]

Characterizing macrophysical properties of deep convective systems on a global scale is a precursor to understanding their influence on Earth's Energy Budget and Water Cycle. This study documents the properties of global convective objects (COs) in the early afternoon (1:30 p.m. local time; LT) and overnight (1:30 a.m. LT) measurements from the A‐Train satellite constellation. CloudSat measurements are used to identify convective cores and establish their intensity, while other A‐Train data sets define cloud structure, storm spatial extent, rainfall yield, and radiative effects of each CO. Global distributions of storm characteristics are consistent with previous studies in which the most intense convection is located over tropical land, particularly over the Amazon and Congo Basin, while the largest COs occur over the Maritime Continent. Despite their limited twice‐daily sampling, A‐Train measurements capture that early afternoon convection over tropical land is both more intense and produces heavier rainfall than nighttime land‐based convection, while the day‐night differences are minimal over the tropical ocean. High‐resolution estimates of updraft cores reveal that CO size increases as the number of distinct cores in a CO increases owing to an increase in nonconvective rain and anvil cloud area. Convective objects generally cool the environment, which is strongest over the Northern Hemisphere midlatitudes, but cooling weakens as the nonconvective cloud fraction increases such that 30% of COs actually exert a net warming effect. These results suggest that A‐Train measurements may capture bulk connections between deep convective cloud features, precipitation, and radiative effects despite a lack of complete diurnal sampling. Plain Language Summary: Storm clouds have a large impact on Earth's weather and climate. They produce a large fraction of global rainfall in short intense downpours and can both cool and warm the environment by reflecting sunlight and reducing emitted thermal radiation. Whether they cool or warm the atmosphere depends on cloud size and thickness as well as rainfall amount. These features impact the moisture and energy transfer within local and large‐scale environments, which influence weather patterns. Yet, it is difficult to represent the influences that storms have on a global scale in climate and weather forecasting models. This work provides a global perspective of early afternoon and late night storm signatures and their energy and rainfall contributions. Using global satellite observations, storms are the strongest and produce the heaviest rainfall over tropical land during early afternoon, but they are the largest over tropical ocean. Storms generally cool the Earth at this time of day, but cooling weakens as the amount of nonraining cloud within the storm grows. This work may help improve storm representation in numerical models by connecting properties, such as the cloud size, strength, and frequency, to rain rates and energy output to better assess features that have the largest impact on weather and climate. Key Points: The A‐Train observes several thousand convective objects (COs) to link cloud, rainfall, and radiative features despite limited diurnal samplingConvection is the most intense over land, but the largest systems with the strongest radiative effects occur over tropical oceanCOs generally cool the tropics at 1:30 p.m./a.m. local time but this effect weakens as the number of embedded cores increases [ABSTRACT FROM AUTHOR]

The impact of eddy diffusivities in the Mellor–Yamada–Nakanishi–Niino (MYNN) boundary layer parameterization on the fine‐scale turbulence and intensity of tropical cyclone (TC) simulations at gray‐zone resolution was investigated through comparison with large‐eddy simulation (LES) and observations. A series of idealized experiments were performed with varying vertical mixing lengths using the Advanced Research version of the Weather Research and Forecasting model. For enhanced eddy diffusivity cases, the storm intensity was sensitive to the eddy diffusivities and reducing the overestimation of the eddy diffusivities caused a significant increase in intensity. For the reduced eddy diffusivity cases, the TC intensity was marginally influenced by the eddy diffusivities. However, the reduction in eddy diffusivities effectively reproduced the fine‐scale turbulence. The stronger the resolved fine‐scale turbulence that could be established, the more frictional tendencies near the location of maximum wind were provided to the TC, the closer it was to the reference LES and observations. The resolved turbulence also had consequences in terms of preventing the wind gradient from increasing, which was one of the primary reasons for the discrepancies in the nonlinear intensity and fine‐scale features. The results of this study demonstrate that the modification of eddy diffusivities in the MYNN scheme can measure or guide improvements in the simulation of TC boundary layer fine‐scale features and intensity when operating at the gray‐zone resolution. Plain Language Summary: Eddy diffusivities—key parameters in planetary boundary layer parameterization—are not well understood owing to a lack of sufficient data on the tropical cyclone (TC) boundary layer (TCBL). Moreover, their effects on the TCBL may be further complicated at the turbulent gray‐zone resolution when turbulence starts to be resolved. Therefore, the role of eddy diffusivities in the simulation of TC fine‐scale features and intensity needs to be further investigated at the gray‐zone resolution. In this study, we focused on how boundary layer fine‐scale turbulence and TC intensity are influenced by eddy diffusivities in a widely used boundary layer scheme at resolutions down to 500 and 166 m. The results indicated that the eddy diffusivities were overestimated in the boundary layer scheme. The reduction of eddy diffusivities reproduced better fine‐scale features and TC intensity, and a closer vertical structure to a reference large‐eddy simulation and observations. In conclusion, artificial modification of eddy diffusivities can serve as a measure or as guidance toward improving the simulation of TC boundary layer fine‐scale features and intensity when operating at gray‐zone resolutions. Key Points: Direct modification of KM is applicable to improve a turbulent kinetic energy planetary boundary layer scheme, which can improve the tropical cyclone (TC) turbulence simulation at gray‐zone resolutionImproving the resolved turbulence provides considerable frictional tendency near the height of maximum wind and reduces the vertical gradientFor TC simulation at gray‐zone resolution, the resolved turbulence is one of the key reasons for the nonlinear effect of KM on TC intensity [ABSTRACT FROM AUTHOR]

The surface of the Great Lakes interacts with the atmosphere, influencing the weather and climate over the Great Lakes Region (GLR). However, most climate models were not designed with sufficient emphasis on lake–atmosphere interactions, which could potentially cause model biases over the GLR. To understand how lake surface temperature (LST) affects the regional summer climate over the GLR, we conducted twin experiments using the Weather Research and Forecasting model at a spatial resolution of 4 km using two different LST data sets as the bottom boundary condition over the Great Lakes. Our simulations include 10 ensemble members for the summer of 2018 and a single multiyear run for the summers of 2014–2020. Results show that variations in LST influence atmospheric temperature and moisture at a local scale—while affecting the convective environment and precipitation processes over a much larger spatial scale. In particular, an LST that is only 1°C–3°C warmer (depending on the lake) increases near‐surface air temperature by 1.93°C and 0.97°C over Lake Superior and Lake Erie, respectively, and increases evaporation over the lakes by 0.23 and 1.1 mm day−1. The warmer LST reduces mesoscale convective precipitation upstream of the GLR; however, it increases isolated deep convective precipitation and nonconvective precipitation downstream of GLR due to increased local instability and enhancement of moisture transport. Our analyses confirm the robustness of these impacts, which is at least 2 times larger than the model internal variability and is seen across all simulated summer seasons. Key Points: Small differences in lake surface temperature (LST) can change summer climate at both local and nonlocal scales over the Great Lakes Region (GLR)Warmer LSTs create an unstable environment and enhance isolated deep convection downwind of the GLRThe influences of the difference in LST are robust and significantly larger than the model's internal variability [ABSTRACT FROM AUTHOR]