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This study investigates the regional characteristics and land/sea differences in precipitation and wind along the coast of China, utilizing the Weather Research and Forecasting (WRF) model for continuous 10-year (2009–2018) simulations at 4 km resolution. The results indicate that the WRF model, operating at convection-permitting resolution, can accurately simulate annual precipitation and rainfall frequency, but tends to underestimate the precipitation over the ocean while overestimate the frequency of drizzle rain. The study also reveals that, along the Chinese coastal region, the sub-daily scale precipitation events are most frequent in Eastern China (EC), and WRF tends to underestimate the frequency of events lasting longer than 3 h. The WRF simulations show relatively slight difference in maximum precipitation between land and sea areas. The smallest deviation from the observation of maximum hourly precipitation is over the sea, below 20%. Furthermore, observations show that the diurnal cycle of precipitation peaks at 16:00–17:00 local time over land, with most afternoon precipitation lasting approximately 1 to 6 h. The WRF model successfully captures the observed diurnal variation of precipitation over land and sea in different regions. However, the WRF simulations indicate shorter duration of afternoon precipitation, lasting less than 5 h and an earlier peak. In addition, WRF adequately reproduces the annual and seasonal mean windspeeds for each region, with a slight overestimation during summer. WRF also reasonably captures the frequency distribution of windspeed and wind direction and can identify the occurrence frequency of land-sea breeze in each sub-region. Overall, the study offers valuable insights into the regional characteristics of precipitation and wind along the coast of China and highlights the WRF model's effectiveness in accurately simulating these phenomena. Key points: Convection permitting model (CPM) performs well in simulating the climate characteristics and regional differences in the Chinese coastal areas. There are significant land-sea contrast in the amount, frequency and intensity of precipitation along the eastern coast in China. Water vapor flux convergence and vertical motion due to topographic effects in the model lead to overestimated precipitation over land. [ABSTRACT FROM AUTHOR]

The study assesses the predictability of rainfall patterns in India through 3-day precipitation forecasts from a regional climate model ensemble framework operating at convection-permitting (CP) scales. Initially, 149 experiments are conducted across four events representing different rainfall mechanisms. The performance of a larger set of 55 ensemble members within the multi-physics ensemble framework is evaluated using quantitative metrics such as composite scaled scores and cross-correlation analyses. This evaluation led to the development of an optimally designed smaller member ensemble framework, WRF-CP7, which reduces turnaround time while maintaining the spatial and temporal performance of simulated precipitation fields. The study further assesses the reliability of this framework over an extended period, utilizing insights from 5544 simulations (792 days × 7 ensemble members running for a 90-h lead time) conducted between September 2015 and December 2017. Comparisons between WRF-CP7 and a global climate model forecasts available at coarser resolution highlight the need of parameterization and ensemble framework at convection-permitting scale. WRF-CP7 demonstrates skill in capturing spatiotemporal variability of rainfall occurrences, evidenced by a higher spread–error correlation (0.9 vs. 0.6 in the global model) among ensemble members. The correlation remains consistent even at higher lead-times, in contrast to the reducing skill of the global model with increasing lead-time. WRF-CP7 also shows reduction in spatial and temporal errors within simulated diurnal precipitation patterns, notably during Indian Summer Monsoon, Pre-Monsoon Thunderstorm activities and North-East Monsoon. A notable 30% increase in predictability for moderate to heavy rain intensities is observed across all seasons, accompanied by a 10% decrease in false alarms compared to global model ensemble forecasts. The spatial skill of WRF-CP7 for moderate-heavy intensity events remains high (50–80%) even with a longer lead time of 72-h on an intra-seasonal timescale. With a substantial sample size, the results underscore the effectiveness of using the multi-physics ensemble framework at convective scales for operational forecasting and dynamic downscaling of climatology across the Indian subcontinent. [ABSTRACT FROM AUTHOR]

Realistic representation of rainfall characteristics on local scales by state-of-the-art climate models remains a key challenge, especially on sub-daily timescales. In this study, the convection-permitting Weather Research and Forecasting (WRF) model configured with 1.5 km grid spacing is used to simulate precipitation on sub-daily timescales over the Yangtze River Delta Region of China for continuous 10 years (2005–2014). The simulations are compared with rain gauge observations, reanalysis data, and the simulations of a lower resolution WRF with 9 km grid spacing that has a parameterization of convection. The results show that precipitation over the region can be well captured by using the convection-permitting model (CPM). Furthermore, the intensity, duration and coverage of these precipitation events can be more accurately described by the CPM. On the convection timescales of 1–4 h, especially for heavy rainfall events, the CPM is more accurate than the convection-parameterized model in capturing the short-duration events, which may be due to its better account of physical processes related to the convection on the convection-permitting scale. In addition, the extreme events which are more localized and with short-duration can be represented better by the CPM while the convection-parameterized model tends to produce widespread precipitation events covering more grid cells than observations Biases of the simulation by the 9-km mesh convection-parameterized mode appear to be related to the deficiencies in the representation of convections. [ABSTRACT FROM AUTHOR]

A set of six convection-permitting (CP) domain configurations were implemented to perform 72-hour long simulations of three extreme precipitation events over Southeastern South America (SESA). The goal of the study is to determine the most adequate configuration for reproducing not only the rainfall evolution and intensity, but also the synoptic triggering mechanisms that led to these extreme events, taking into account the trade-off between model performance and computational cost. This study assesses the impact of (1) the horizontal resolution in the CP domain, (2) the horizontal resolution of the driver domain, (3) the size of both CP and driver domains and (4) the nesting strategy (one-step versus two-step nesting). Each simulation was performed with the Weather Research and Forecasting model driven by the ERA-Interim reanalysis. For each event and domain configuration, a 6-member physics ensemble is built, making a total of 36 simulations for each event. No significant differences were found between the 4 km and 2.4 km CP ensembles. Increasing the horizontal resolution of the driver domain from 20 km to 12 km introduced only subtle differences. Increasing the size of the CP domain improved the model performance, probably because of better resolved topography and, hence, better resolved synoptic environment. The results in this study reveal that the one-step nesting CP ensemble at 4 km horizontal resolution covering an area of 29 ∘ x 21 ∘ (lon-lat) arises as the optimal domain configuration among these tested to simulate extreme precipitation events over SESA. [ABSTRACT FROM AUTHOR]

The Guangdong-Hong Kong-Macao Greater Bay Area (GBA) is the world's largest bay area in terms of land area and population, which has been increasingly suffering from weather and climate extremes under global warming. It is thus desired to produce reliable high-resolution climate information at a regional scale in order to enhance resilience to climate change over the GBA. For the first time, this study develops the multi-decadal nested-grid climate projections at a convection-permitting scale for the GBA, and assesses the abilities of the Weather Research and Forecasting (WRF) model with 36-, 12- and 4 km resolutions in representing precipitation, temperature and their extremes. Our findings indicate the added value of the convection-permitting WRF model for simulating the spring and summertime precipitation as well as extreme heavy rainfall events with daily amounts larger than 30 mm over the GBA. Increasing the spatial resolution of the WRF model does not necessarily lead to a significant improvement on temperature simulations. In addition, our findings reveal that the GBA is expected to have an increasing number of heavy and extreme heavy rainfall events by the end of the twenty-first century. Moreover, the GBA is projected to have a large temperature change across different seasons, and an enhanced warming will appear in autumn. The GBA is also expected to have more summer days with longer durations, thereby leading to an increasing risk of heatwaves and heat stress. [ABSTRACT FROM AUTHOR]

Dynamical downscaling with high-resolution regional climate models may offer the possibility of realistically reproducing precipitation and weather events in climate simulations. As resolutions fall to order kilometers, the use of explicit rather than parametrized convection may offer even greater fidelity. However, these increased resolutions both allow and require increasingly complex diagnostics for evaluating model fidelity. In this study we focus on precipitation evaluation and analyze five 2-month-long dynamically downscaled model runs over the continental United States that employ different convective and microphysics parameterizations, including one high-resolution convection-permitting simulation. All model runs use the Weather Research and Forecasting Model driven by National Center for Environmental Prediction reanalysis data. We show that employing a novel rainstorm identification and tracking algorithm that allocates essentially all rainfall to individual precipitation events (Chang et al. in J Clim 29(23):8355–8376, 2016) allows new insights into model biases. Results include that, at least in these runs, model wet bias is driven by excessive areal extent of individual precipitating events, and that the effect is time-dependent, producing excessive diurnal cycle amplitude. This amplified cycle is driven not by new production of events but by excessive daytime enlargement of long-lived precipitation events. We further show that in the domain average, precipitation biases appear best represented as additive offsets. Of all model configurations evaluated, convection-permitting simulations most consistently reduced biases in precipitation event characteristics. [ABSTRACT FROM AUTHOR]

This research work focuses on the problem of climate simulation of rainfall over West Africa and particularly over coastal countries of the Gulf of Guinea by Regional Climate Models. The sensitivities of Weather Research and Forecasting (WRF) Model were tested for changes in horizontal resolution (convection permitting versus parameterized) on the replication of West African monsoon for the year 2014. Sensitivity test was also performed for response of rainfall to changes in microphysics (MP) and planetary boundary layer (PBL) schemes. Generally, the result shows that WRF is able to replicates rainfall distribution with an adequate representation of the dynamical features of West African monsoon system. The high-resolution (wrf-4km) shows dry bias along the coast of the Gulf of Guinea but generally outperforms wrf-24km run especially in replication of the extreme rainfall distribution. The dry bias along the coastal area is suggested to not to be only related to convection but mostly to microphysics and PBL parameterisation schemes. Differences were noticed between the dynamics of WRF and ERA-interim outputs despite the use of spectral nudging in the experiment which then suggest strong interactions between scales. These differences were observed to be restricted mainly to the low-layer monsoon flow in JJA. Both runs at 24 and 4 km hardly simulate the typical diurnal distribution of rainfall. The sensitivity of WRF to MP (only sophisticated MP were tested) and PBL reveals a stronger impact of PBL than MP on rainfall distribution and the most significant added value over the Guinean coast and surroundings area was provided by the configurations using non-local PBL scheme (as ACM2). The changes in MP and PBL schemes in general seem to have less effect on the explicit runs (wrf-4km) in the replication of the rainfall over the Gulf of Guinea and the surroundings seaboard. [ABSTRACT FROM AUTHOR]

Convection-permitting regional climate models have been shown to improve precipitation simulation in many aspects, such as the diurnal cycle, precipitation frequency, intensity and extremes in many studies over several geographical regions of the world, but their skill in reproducing the warm-season precipitation characteristics over the East Asia has not been robustly tested yet. Motivated by recent advances in computing power, model physics and high-resolution reanalysis, we use the convection-permitting weather research and forecasting (WRF) model configured with 3 km grid spacing to simulate the warm-season precipitation in eastern China for 10 seasons (2008–2017). The hourly 31-km-resolution ERA5 reanalysis data are used to provide initial and boundary conditions for the simulations. The objectives are (1) to evaluate the model skill in simulating warm-season precipitation climatology in the East Asian monsoon region, (2) to identify the promises and problems of the convection-permitting simulation, and (3) to investigate solutions for the model deficiencies. Results demonstrate that the 3-km-resolution WRF model reasonably reproduces the spatial characteristics of seasonal and sub-seasonal precipitation, the seasonal meridional migration associated with the summer monsoon activity, the diurnal variation phase and amplitude, and the propagating convection east of the Tibetan Plateau. The major deficiency is that the model overestimates precipitation amount, especially in the afternoon. Analysis and sensitivity experiments suggest that improved treatment of sub-grid cloud fraction and the aerosol effects may help to suppress the oft-reported high precipitation bias. These results provide useful guidance for improving the model skill at simulating warm-season precipitation in East Asia. [ABSTRACT FROM AUTHOR]

With a decadal long period (1998–2010) climate simulation using the Weather Research and Forecasting model at convection-permitting resolution (4 km) (WRF_CPM), the diurnal cycles of precipitation amount (PA), frequency (PF) and intensity (PI) and their related large-scale atmospheric circulations over eastern China are analyzed. The simulations are further compared against the CN05.1, CMORPH v1.0 and the ECMWF Re-Analysis Interim (ERAIN). Results show that WRF_CPM can reasonably represent the observed seasonal rainfall and the atmospheric circulations. As for the features at a sub-daily scale, WRF_CPM is superior at reproducing the diurnal amplitude of PF that is similar to PA in terms of the spatial distribution. Moreover, the diurnal peak timing of summer PF and PA over the three sub-regions, i.e., North China (NC), Yangtze-Huaihe River basin (YHR) and South China (SC), can be properly reproduced by WRF_CPM. The observed precipitation systems exhibit obvious eastward propagation from the Plateau to its downstream, which may be due to the solenoid circulations associated with the low-level anomalous wind and moisture convergence. However, they are almost overestimated by WRF_CPM and in turn causing overestimated precipitation along YHR. The early morning precipitation in WRF_CPM has a larger fraction than CMORPH, which is related to the overestimated nocturnal low-level jet. Whereas, due to the solar heating and the land-sea breezes, the late-afternoon precipitation peak is mainly located along the coasts of eastern China, which matches well with the vertical motion in WRF_CPM. [ABSTRACT FROM AUTHOR]

Understanding future changes in hydroclimatic variables plays a crucial role in improving resilience and adaptation to extreme weather events such as floods and droughts. In this study, we develop high-resolution climate projections over Texas by using the convection-permitting Weather Research and Forecasting (WRF) model with 4 km horizontal grid spacing, and then produce the Markov chain Monte Carlo (MCMC)-based hydrologic forecasts in the Guadalupe River basin which is the primary concern of the Texas Water Development Board and the Guadalupe-Blanco River Authority. The Parameter-elevation Regressions on Independent Slopes Model (PRISM) dataset is used to verify the WRF climate simulations. The Model Parameter Estimation Experiment (MOPEX) dataset is used to validate probabilistic hydrologic predictions. Projected changes in precipitation, potential evapotranspiration (PET) and streamflow at different temporal scales are examined by dynamically downscaling climate projections derived from 15 Coupled Model Intercomparison Project Phase 5 (CMIP5) general circulation models (GCMs). Our findings reveal that the Upper Coast Climate Division of Texas is projected to experience the most remarkable wetting caused by precipitation and PET changes, whereas the most significant drying is expected to occur for the North Central Texas Climate Division. The dry Guadalupe River basin is projected to become drier with a substantial increase in future drought risks, especially for the summer season. And the extreme precipitation events are projected to increase in frequency and intensity with a reduction in overall precipitation frequency, which may result in more frequent occurrences of flash floods and drought episodes in the Guadalupe River basin. [ABSTRACT FROM AUTHOR]

Based on the hourly gauge-satellite merged precipitation data with the spatial resolution of 0.1° × 0.1° during 2013 ~ 2018, we have evaluated the performance of the convection-permitting Weather Research and Forecasting model at Nanjing University (WRF_NJU) in forecasting the precipitation diurnal variation and the associated atmospheric circulation over the eastern Tibetan Plateau and its surrounding regions during summer. Results indicate that WRF_NJU model can well reproduce the diurnal cycle of the summer precipitation in terms of the diurnal peak time, duration and magnitude. In addition, the eastward propagation of rainfall systems with long duration along the eastern Tibetan Plateau (ETP) and its adjacent areas can also be properly captured. The WRF_NJU model can reasonably reproduce the relevant atmospheric circulation during summer as well. However, the model tends to underestimate the summer precipitation amount (PA) and precipitation frequency (PF) over most time of a day. Relatively larger biases in the occurring time and magnitude of PA and PF diurnal peaks can be noted over the ETP and Sichuan Basin. Further analysis suggests that the underestimation of PA over the ETP is attributed to the much lower moisture supply, weaker low-level southwesterly winds and less convective available potential energy (CAPE) in the WRF_NJU model than in ERA5. Over Sichuan Basin, the underestimated PA is related to the weaker upward motion, which is corresponding to the cold biases of surface air temperature in WRF_NJU. Findings of this study provide the basic model biases and may be helpful to further improve the model physical processes. [ABSTRACT FROM AUTHOR]

Soil moisture plays an important role in modulating regional climate from sub-seasonal to seasonal timescales. Particularly important, soil moisture deficits can amplify summer heatwaves (HWs) through soil moisture-temperature feedback which has critical impacts on society, economy and human health. In this study, we evaluate decade-long convection-permitting Weather Research and Forecast (WRF) model simulations over the contiguous US on simulating heatwaves and their relationship with antecedent soil moisture using a dense observational network. We showed that the WRF model is capable of capturing the spatial patten of temperature threshold to define HWs, though the simulation shows a warm bias in the Midwest and cold bias in western mountainous regions. Two HW indices, based on frequency (HWF) and magnitude (HWM), are evaluated. Significant anti-correlations between antecedent soil moisture and both HW indices have been found in most parts of the domain except the South Pacific Coast. A detailed study has been conducted for the Midwest and South Great Plains regions, where two heatwaves had occurred in the last decade. In both regions, the high quantile of the HWF distribution shows a strong dependence on antecedent soil moisture: drier soil leads to much larger increase on the upper quantile of HWF than it does on the lower quantile. Soil moisture effects on the higher end of HWM are not as strong as on the lower end: wetter antecedent soil corresponds to a larger decrease on the lower quantile of HWM. WRF captures the heterogeneous responses to dry soil on HWF distribution in both regions, but overestimates these HWM responses in the Midwest and underestimates them in the South Great Plains. Our results show confidence in WRF's ability to simulate HW characteristics and the impacts of antecedent soil moisture on HWs. These are also important implications for using high-resolution convection-permitting mode to study the coupling between land and atmosphere. [ABSTRACT FROM AUTHOR]

Climate models project increasing precipitation intensity but decreasing frequency as greenhouse gases increase. However, the exact mechanism for the frequency decrease remains unclear. Here we investigate this by analyzing hourly data from regional climate change simulations with 4 km grid spacing covering most of North America using the Weather Research and Forecasting model. The model was forced with present and future boundary conditions, with the latter being derived by adding the CMIP5 19-model ensemble mean changes to the ERA-interim reanalysis. The model reproduces well the observed seasonal and spatial variations in precipitation frequency and histograms, and the dry interval between rain events over the contiguous US. Results show that overall precipitation frequency indeed decreases during the warm season mainly due to fewer light-moderate precipitation (0.1 < P ≤ 2.0 mm/h) events, while heavy (2 < P ≤ 10 mm/h) to very heavy precipitation (P > 10 mm/h) events increase. Dry spells become longer and more frequent, together with a reduction in time-mean relative humidity (RH) in the lower troposphere during the warm season. The increased dry hours and decreased RH lead to a reduction in overall precipitation frequency and also for light-moderate precipitation events, while water vapor-induced increases in precipitation intensity and the positive latent heating feedback in intense storms may be responsible for the large increase in intense precipitation. The size of intense storms increases while their number decreases in the future climate, which helps explain the increase in local frequency of heavy precipitation. The results generally support a new hypothesis for future warm-season precipitation: each rainstorm removes ≥7% more moisture from the air per 1 K local warming, and surface evaporation and moisture advection take slightly longer than currently to replenish the depleted moisture before the next storm forms, leading to longer dry spells and a reduction in precipitation frequency, as well as decreases in time-mean RH and vertical motion. [ABSTRACT FROM AUTHOR]

The simulation of Saharan mid tropospheric clouds is investigated with the weather research and forecasting (WRF) regional atmospheric model at convection permitting (4 km) horizontal grid-spacing. We identify two potential problems in such simulations: one that affects cloud cover, and another that affects the mean and geographic patterns of both cloud and precipitation. Our simulations show that using a vertical grid typical of GCMs (38 levels) inhibits the formation of Saharan mid-level clouds. In particular, it underestimates the supercooled water content that often resides at the top of these clouds, in favour of ice which falls out of the cloud quickly. When the vertical resolution becomes high enough to allow layers of supercooled water and ice to exist separately, the simulation of the Saharan mid-level clouds improves significantly. Additional improvement is achieved by using realistic high resolution surface albedo, which also shows that low albedo areas favour the formation of mid-level clouds much more than high albedo ones. The simulation of precipitation on the northern edge of the Sahel is also improved with the use of realistic surface albedo. Overall, despite the disagreement of the simulated and the observed clouds, our results show that using increased resolution and realistic surface albedo seems to fully reproduce their observed radiative effect. [ABSTRACT FROM AUTHOR]

High-accuracy meteorological datasets are urgently required for understanding hydrological processes across the Third Pole (Qinghai-Tibetan Plateau, or TP), where meteorological stations are sparse. Low-resolution weather and climate simulations have significant errors in this region due to their inability to resolve meso-microscale processes associated with the complex terrain and convective clouds. This work presents a contribution to CORDEX Convection-Permitting Third Pole (CPTP) using dynamical downscaling of the latest global reanalysis data produced by the European Centre for Medium-Range Weather Forecasts (i.e., ERA5) at very high resolution (approximately 0.033°) based on the Weather Research and Forecasting (WRF) model. The results show that the kilometer-scale horizontal grid spacing simulation (WRF3) outperforms the ERA5 and the High Asia Refined regional reanalysis (HAR v2) in terms of smaller biases and root mean square errors, as well as higher spatial pattern correlation coefficients for 10-m wind speed and precipitation. Furthermore, WRF3 more realistically reproduces observed night-time precipitation peaks in the interior TP, while ERA5 and HAR v2 show erroneous afternoon precipitation peaks. Therefore, the added values achieved by resolving detailed physical processes when increasing grid spacing are considerable. This work demonstrates the potential for developing a reliable high resolution meteorological dataset required for research in this unique region. [ABSTRACT FROM AUTHOR]

Convection-permitting models (CPM) with at least 4 km horizontal grid spacing enable the cumulus parameterization to be switched off and thus simulate convective processes more realistically than coarse resolution models. This study investigates if a North American scale CPM can reproduce the observed warm season precipitation diurnal cycle on a climate scale. Potential changes in the precipitation diurnal cycle characteristics at the end of the twenty first century are also investigated using the pseudo global warming approach under a high-end anthropogenic emission scenario (RCP8.5). Simulations are performed with the Advanced Research Weather Research and Forecasting (ARW-WRF) model with 4-km horizontal grid spacing. Results from the WRF historical run (2001–2013) are evaluated against hourly precipitation from 2903 weather stations and a gridded hourly precipitation product in the U.S. The magnitude and timing of the diurnal cycle peak are realistically simulated in most of the U.S. and southern Canada. The model also captures the transition from afternoon precipitation peaks eastward of the Rocky Mountains to night peaks in the central U.S., which is related to propagating mesoscale convective systems. However, the historical climate simulation does not capture the observed early morning peaks in the central U.S. and overestimates the magnitude of the diurnal precipitation peak in the southeast region. In the simulation of the future climate, both the precipitation amount of the diurnal cycle and precipitation intensity increase throughout the domain, along with an increase in precipitation frequency in the northern region of the domain in May. These increases indicate a clear intensification of the hydrologic cycle during the warm season with potential impacts on future water resources, agriculture, and flooding. [ABSTRACT FROM AUTHOR]

Uncertainties in gridded and regional climate estimates of precipitation are large at high elevations, where observations are sparse and spatial variability is substantial. We explore these uncertainties for water year 2008 across California's Sierra Nevada in 10 datasets: 6 regional climate downscalings generated using the weather research and forecasting (WRF) model at convection-permitting resolution with differing lateral boundary conditions and microphysical parameterizations, and four gauge-based, interpolation-gridded precipitation datasets. Precipitation from these 10 datasets is evaluated against 95 snow pillows and a precipitation dataset inferred from stream gauges using a Bayesian inference method. During water year 2008, the gridded datasets tend to underestimate frozen precipitation on the windward slope of the Sierra Nevada, particularly in the vicinity of Yosemite National Park. The WRF simulations with single-moment microphysics tend to overestimate precipitation throughout much of the region, whereas the WRF simulations with double-moment microphysics tend to better agree with both the snow pillows and inferred precipitation estimates, although they somewhat overestimate the windward/leeside precipitation contrast in the northern Sierra Nevada. WRF simulations, in particular those with single-moment microphysics, better distinguish spatial patterns of wet-versus-dry pillows and watersheds over the water year than the gridded estimates. Our results suggest treating gauge-based datasets as 'truth' may give a misleading representation of model accuracy, since these gauge-based datasets often have issues of their own. [ABSTRACT FROM AUTHOR]

During 14 to 17 December 2013, the Pearl River Delta (PRD) in South China received its largest wintertime 4-day precipitation of above 100 mm since 1998, due to strong cold air intrusion. Here we investigate the extent to which such extreme rainfall can be attributed to human activities, by carrying out Weather Research and Forecasting (WRF) model multi-physics integrations at a convection-permitting resolution. The factual WRF runs were conducted using the European Centre for Medium-Range Weather Forecasts (ECMWF) Reanalysis (ERA)-Interim as boundary and initial conditions, and the counterfactual runs by the same ERA-Interim forcing with human influences removed. The latter was deduced by subtracting the Coupled Model Intercomparison Project Phase 5 (CMIP5) historical-natural from the historical run outputs. Results show that the 4-day mean rainfall could increase by 11% for 1.2 K near-surface warming on average under human-induced thermodynamic forcing in relation to humidity changes, whereas it increases by 17% for 2 K warming under all forcing (i.e., including dynamic forcing associated with wind circulation changes), which is nearly the Clausius–Clapeyron rate. Moreover, the former and latter forcing can intensify the 95th percentile daily rainfall by ~ 13% and ~ 19%, respectively, suggesting that human-caused dynamic forcing can further exacerbate the thermodynamic-driven rainfall enhancement in this event. Indeed, there is stronger land-sea thermal contrast with anomalous low-level southerly winds and convergence in coastal South China under all forcing. The frontal system and ascending motion are therefore intensified, resulting in even stronger rain rates than under thermodynamic forcing. Moisture budget analysis reveals that the dynamic component accounts for most of the increase in 4-day mean rainfall while the thermodynamic contribution is negligible under all forcing. Our findings highlight the salient role of dynamic effects on intensifying PRD's extreme rainfall in wintertime. [ABSTRACT FROM AUTHOR]

The Weather Research and Forecast (WRF) model with its land surface model NOAH was set up and applied as regional climate model over Europe. It was forced with the latest ERA-interim reanalysis data from 1989 to 2008 and operated with 0.33° and 0.11° resolution. This study focuses on the verification of monthly and seasonal mean precipitation over Germany, where a high quality precipitation dataset of the German Weather Service is available. In particular, the precipitation is studied in the orographic terrain of southwestern Germany and the dry lowlands of northeastern Germany. In both regions precipitation data is very important for end users such as hydrologists and farmers. Both WRF simulations show a systematic positive precipitation bias not apparent in ERA-interim and an overestimation of wet day frequency. The downscaling experiment improved the annual cycle of the precipitation intensity, which is underestimated by ERA-interim. Normalized Taylor diagrams, i.e., those discarding the systematic bias by normalizing the quantities, demonstrate that downscaling with WRF provides a better spatial distribution than the ERA interim precipitation analyses in southwestern Germany and most of the whole of Germany but degrades the results for northeastern Germany. At the applied model resolution of 0.11°, WRF shows typical systematic errors of RCMs in orographic terrain such as the windward-lee effect. A convection permitting case study set up for summer 2007 improved the precipitation simulations with respect to the location of precipitation maxima in the mountainous regions and the spatial correlation of precipitation. This result indicates the high value of regional climate simulations on the convection-permitting scale. [ABSTRACT FROM AUTHOR]

The frequency and intensity of extreme hydrological events (droughts and floods) have been increasing over the past few decades, which has been posing a threat to water security and agriculture production. Thus, projecting the future evolution of hydrological extremes plays a crucial role in sustainable water management and agriculture development in a changing climate. In this study, we develop the high-resolution projections of multidimensional drought characteristics and flood risks using the convection-permitting Weather Research and Forecasting (WRF) model with the horizontal grid spacing of 4 km for the Blanco and Mission River basins over South Texas. Uncertainties in model parameters are addressed explicitly, thereby leading to probabilistic assessments of hydrological extremes. Our findings reveal that the probabilistic multivariate assessments of drought and flood risks can reduce the underestimation and the biased conclusions generated from the univariate assessment. Furthermore, our findings disclose that future droughts are expected to become more severe over South Texas even though the frequency of the occurrence of droughts is projected to decrease, especially for the long-term drought episodes. In addition, South Texas region is expected to experience more floods with an increasing river discharge. Moreover, the Blanco and Mission river basins will suffer from higher flood risks as flood return periods are expected to become longer under climate change. [ABSTRACT FROM AUTHOR]

Precipitation patterns are expected to change in the future climate, affecting humans through a number of factors. Global climate models (GCM) are our best tools for projecting large-scale changes in climate, but they cannot make reliable projections locally. To abate this problem, we have downscaled three GCMs with the Weather Research and Forecasting (WRF) model to 50 km horizontal resolution over South America, and 10 km resolution for central Chile, Peru and southern Brazil. Historical simulations for years 1996–2005 generally compare well to precipitation observations and reanalyses. Future simulations for central Chile show reductions in annual precipitation and increases in the number of dry days at the end-of-the-century for a high greenhouse gas emission scenario, regardless of resolution and GCM boundary conditions used. However, future projections for Peru and southern Brazil are more uncertain, and simulations show that increasing the model resolution can switch the sign of precipitation projections. Differences in future precipitation changes between global/regional and high resolution (10 km) are only mildly influenced by the orography resolution, but linked to the convection parameterization, reflected in very different changes in dry static energy flux divergence, vertical velocity and boundary layer height. Our findings imply that using results directly from GCMs, and even from coarse-resolution (50 km) regional models, may give incorrect conclusions about regional-scale precipitation projections. While climate modelling at convection-permitting scales is computationally costly, we show that coarse-resolution regional simulations using a scale-aware convection parameterization, instead of a more conventional scheme, better mirror fine-resolution precipitation projections. [ABSTRACT FROM AUTHOR]

Some 180 million people depend on the Indus River as a key water resource, fed largely by precipitation falling over the western Himalaya. However, the projected response of western Himalayan precipitation to climate change is currently not well constrained: CMIP5 GCMs project a reduced frequency and vorticity of synoptic-scale systems impacting the area, but such systems would exist in a considerably moister atmosphere. In this study, a convection-permitting (4 km horizontal resolution) setup of the Weather Research and Forecasting (WRF) model is used to examine 40 cases of these synoptic-scale systems, known as western disturbances (WDs), as they interact with the western Himalaya. In addition to a present-day control run, three experiments are performed by perturbing the boundary and initial conditions to reflect pre-industrial, RCP4.5 and RCP8.5 background climates respectively. It is found that in spite of the weakening intensity of WDs, net precipitation associated with them in future climate scenarios increases significantly; conversely there is no net change in precipitation between the pre-industrial and control experiments despite a significant conversion of snowfall in the pre-industrial experiment to rainfall in the control experiment, consistent with the changes seen in historical observations. This shift from snowfall to rainfall has profound consequences on water resource management in the Indus Valley, where irrigation is dependent on spring meltwater. Flux decomposition shows that the increase in future precipitation follows directly from the projected moistening of the tropical atmosphere (which increases the moisture flux incident on the western Himalaya by 28%) overpowering the weakened dynamics (which decreases it by 20%). Changes to extreme rainfall events are also examined: it is found that such events may increase significantly in frequency in both future scenarios examined. Two-hour maxima rainfall events that currently occur in 1-in-8 WDs are projected to increase tenfold in frequency in the RCP8.5 scenario; more prolonged (1-week maxima) events are projected to increase fiftyfold. [ABSTRACT FROM AUTHOR]

In this study, we use convection-permitting high resolution (3 km) simulations to quantify and analyse the water budget, precipitation efficiency and water sources of 100 intense Mediterranean cyclones. To this end, we calculate the water content, advection and microphysical processes of water vapour and rain water by implementing new diagnostics to the Weather Research and Forecasting (WRF) model. The 100 intense cyclones have been randomly selected from a 500 intense cyclones dataset, identified and tracked in an 11-year time period in part I of this study. Results are presented in a composite approach showing that most rainfall takes place to the north-east side of the cyclones, close to their centre. Rainfall location is concomitant to the area of horizontal moisture flux convergence and is quasi-equal to the amount of water vapour loss due to microphysical processes. Similar results were found regardless if cyclones produce high or low rainfall amounts. Vertical profiles of the water budget terms revealed deeper clouds for the cyclones producing high rainfall, consistent with higher values of vertical advection of both water vapour and rain water. Finally, cyclones were analysed with respect to their precipitation efficiency, i.e. the ratio between the rainwater produced in an atmospheric column and the consequent rainfall, and showed that cyclones tend to be more efficient when their rainfall production takes place over land. Therefore, there is a complex relation between water vapour advection, precipitation efficiency and rainfall which is discussed through the comparison of two tropical-like cyclones with two cyclones that produced low rainfall amounts. Finally, our analysis is complemented by applying a Lagrangian approach to all 100 cyclones in order to quantify the water vapour source regions that contribute to the cyclones' rainfall due to local surface evaporation. Results showed that these regions are located over both the Atlantic and the Mediterranean, however we show that cyclones producing high rainfall are related with higher water transport from both the subtropical Atlantic and the Mediterranean Sea. [ABSTRACT FROM AUTHOR]

10.1007/s00382-020-0539-w 21 Jacob D, Elizalde A, Haensler A, Hagemann S, Kumar P. Assessing the transferability of the regional climate model REMO to different coordinated regional climate downscaling experiment (CORDEX) regions. All these issue are currently under discussion within the CORDEX community, so that the CORDEX-CORE initiative can remain a central resource for the climate modeling and climate service communities. The CORDEX-CORE EXP-I dataset is indeed intended to be a community resource for the study of regional climate phenomena in a climate change context and for application to vulnerability-impacts-adaptation (VIA) assessment studies and climate service activities. The Coordinated Regional Downscaling Experiment (CORDEX, Giorgi et al. [15]; Jones et al. [24]) is the main reference program for the climate downscaling community. [Extracted from the article]

Cold-season windstorms represent an important, and potentially changing, geophysical hazard in the Northeastern United States. Here we employ an integrated research methodology including both a storyline approach, where three intense windstorms from the current climate are subjected to pseudo-global warming (PGW) experiments, and a long-term transient simulation using the Weather Research and Forecasting (WRF) model. An ensemble of WRF simulations is built for each windstorm using different planetary boundary layer and microphysical parameterizations. The fidelity assessment suggests all ensemble members capture the windstorm evolution in contemporary climate. The configuration with highest fidelity is used in the PGW experiments performed with perturbed temperature fields, constant relative humidity, and deiced Great Lakes. These perturbation simulations indicate some evidence for a reduction of sea level pressure and increases in wind speed over and downwind of the Great Lakes and over the Atlantic Ocean plus an increase in precipitation accumulation but a reduction in snow coverage. These changes are spatially inhomogeneous in terms of magnitude and sign but are consistent with changes in potential vorticity. Alberta Clippers and Colorado Lows dominate the cyclones responsible for historical windstorms and thus are sampled in the PGW simulations. However, the transient simulation suggests an increasing role for tropical cyclones that undergo transition to extratropical cyclones. This reinforces the value of combining information from both PGW perturbation experiments within a storyline context and transient simulations when seeking to quantify the future risk associated with cold-season windstorms under changing climate. [ABSTRACT FROM AUTHOR]

Realistic regional climate simulations are important in understanding the mechanisms of summer rainfall in the southeastern United States (SE US) and in making seasonal predictions. In this study, skills of SE US summer rainfall simulation at a 15-km resolution are evaluated using the weather research and forecasting (WRF) model driven by climate forecast system reanalysis data. Influences of parameterization schemes and model resolution on the rainfall are investigated. It is shown that the WRF simulations for SE US summer rainfall are most sensitive to cumulus schemes, moderately sensitive to planetary boundary layer schemes, and less sensitive to microphysics schemes. Among five WRF cumulus schemes analyzed in this study, the Zhang-McFarlane scheme outperforms the other four. Further analysis suggests that the superior performance of the Zhang-McFarlane scheme is attributable primarily to its capability of representing rainfall-triggering processes over the SE US, especially the positive relationship between convective available potential energy and rainfall. In addition, simulated rainfall using the Zhang-McFarlane scheme at the 15-km resolution is compared with that at a 3-km convection-permitting resolution without cumulus scheme to test whether the increased horizontal resolution can further improve the SE US rainfall simulation. Results indicate that the simulations at the 3-km resolution do not show obvious advantages over those at the 15-km resolution with the Zhang-McFarlane scheme. In conclusion, our study suggests that in order to obtain a satisfactory simulation of SE US summer rainfall, choosing a cumulus scheme that can realistically represent the convective rainfall triggering mechanism may be more effective than solely increasing model resolution. [ABSTRACT FROM AUTHOR]

The potential changes in the characteristics and damage potential of three of the most damaging tropical cyclone (TC) events (Haiyan 2013, Bopha 2012, Mangkhut 2018) in the Philippines have been simulated using the pseudo global warming (PGW) technique. Simulations were performed using the Weather Research and Forecasting model at 5 km resolution with cumulus parameterization (5 kmCU) and 3 km without cumulus parameterization (3 kmNoCU), with PGW deltas derived from a selection of the CMIP6 models. We found that re-forecasting the three TCs under future warming leads to more intense TCs, with changes in maximum wind of 4%, 3%, and 14% for the 5 kmCU runs, and 14%, 4%, and 12% for the 3 kmNoCU runs of Typhoon Haiyan, Bopha, and Mangkhut, respectively. The changes in track, translation speed, and size are relatively small. The TC cases have a higher impact potential in the future, as expressed by the cyclone damage potential index, ranging from ~ 1% to up to 37% under the SSP5-8.5 scenario. Based on the pre-industrial runs, climate change has had, so far, only a weak influence on TC intensity and not much influence on track, translation speed, and size. Simulations without convective parameterization show similar changes in the sign of the projected TC intensity response, but different signals of change in translation speed and size. [ABSTRACT FROM AUTHOR]

Tropical cyclones (TCs) simulated at gray-zone resolution (9 km) in the Advanced Research version of the Weather Research and Forecasting Model (WRF-ARW) are evaluated over the Western North Pacific (WNP) during 11-year (2008–2018) TC seasons (June–November). The effects of the cumulus parameterization (CPS) are tested with two sets of numerical experiments: one involving CPS (ICPS) and one without (NICPS). Through comparisons with the observation and reanalysis, it is shown that the ICPS experiment yields good skills in simulating TC frequency due to more realistic large-scale mean states, including stronger low-tropospheric circulation, wetter mid-tropospheric environment, and stronger ascending motion over the TC main development region (MDR). On the other hand, the NICPS experiment is found to better reproduce intense TCs (Saffir–Simpson hurricane categories 3, 4 and 5) in terms of intensity, accumulated cyclone energy (ACE), and inner-core size. NICPS can also reasonably capture TC inner-core structure with stronger radial inflow in the boundary layer, rising motion around the eyewall and outflow in the mid to upper troposphere. Nevertheless, NICPS significantly underestimates TC outer size due to rapidly decay of TC outer wind field, suggesting limited severe convective activities in the outer region. [ABSTRACT FROM AUTHOR]

The Tibetan Plateau (TP), also called the Third Pole, is considered to be "the world water tower". The northwestern TP (NWTP), which has an average elevation higher than 4800 m, is an arid region where the summer precipitation is largely overestimated by the ERA5 global reanalysis product. We hypothesize that this wet bias is mainly caused by unrealistic lower-level winds that trigger strong convection over the region; it can be reduced by using a high-resolution regional climate model with a large domain that allows realistically representing interactions between the Westerlies and Asian summer monsoons. Here, downscaling using the Weather Research and Forecasting (WRF) model driven by ERA5 was conducted with a large domain (8°‒50° N, 65°‒125° E) at 9 km for the period 1979‒2019 (WRF9km). Precipitation values from WRF9km and ERA5 were evaluated against satellite observations; compared with ERA5, WRF9km captured the climatological summer precipitation over the NWTP with a much-reduced wet bias. The ERA5 overestimation is mainly caused by excessive convective precipitation, likely linked to strong vertical motions over the NWTP induced by an overestimated lower-level southerly wind. [ABSTRACT FROM AUTHOR]

Cloud-radiation process has a strong impact on surface air temperature (SAT). Using the Weather Research and Forecasting (WRF) model, this study investigates the effects of cumulus and radiation parameterization on SAT simulation over Eastern China (EC) during the summer season from 2001 to 2020. Four experiments are performed at a 30 km resolution using the combination of two cumulus schemes (KF and KF-CUP) and two radiation schemes (CAM and RRTMG). The results indicate that the KF and RRTMG scheme can produce warmer SAT than KF-CUP and CAM, respectively. By decomposing the differences in SAT simulation, it is found that KF and RRTMG have greater surface downward shortwave radiation (DSR), and the DSR shows a significant positive correlation with SAT in most parts of EC. Further analysis reveals that low-level cloud (LC) can strongly reflect the DSR, and the LC fraction (LCF) of KF and RRTMG is less than that of KF-CUP and CAM, respectively. The reason for this phenomenon is that the sub-grid cumulus heating rate is higher in KF and RRTMG, resulting in their higher air temperature (T) and greater differences between T and dew point (Td), which is not conducive to the formation of large-scale stratiform cloud and the increase of LCF. As a result, KF and RRTMG have more DSR and higher SAT than KF-CUP and CAM, respectively. The same mechanism can also explain the differences in the sub-seasonal cycle simulations between the four experiments. By comparing the SAT error in each subregion, this study can also provide a reference for future dynamic downscaling over the EC region. [ABSTRACT FROM AUTHOR]

The present study investigated future temperature and precipitation changes over Greece using the Weather Research and Forecasting (WRF) model. WRF was driven by EC-EARTH over Greece at very high resolution for the historical period (1980–2004), along with projected simulations, in the near future (2025–2049) and far future (2075–2099) under the Representative Concentration Pathways 4.5 (RCP4.5) and 8.5 (RCP8.5). Climatic variables were produced at 5-km grid spacing and 6-h interval. The historical simulation was evaluated against the available station observations. The analysis showed that the model underestimated the maximum temperatures and slightly overestimated the minimum temperatures. Also, the model simulated a small dry bias in precipitation with an excellent representation of the spatial patterns. The model projections for temperature under the two emission scenarios compared to the historical simulation revealed a robust magnitude of future warming with the most pronounced changes predominantly over the eastern areas of the country under the RCP8.5 in the far future. Projected precipitation changes were more evident in the far future with an overall decrease of the annual precipitation all over the eastern part of the country (with islands included) with the most dramatic reductions (above 40%) of seasonal precipitation observed under RCP8.5. Increases in the number of hot days were found everywhere with more pronounced changes over the plain areas under RCP8.5 in the far future. Significant increases of dry days were projected over the eastern part of the mainland and more intensely under RCP8.5 in the far future. [ABSTRACT FROM AUTHOR]

Colombia is highly vulnerable to climate change which may be intensified due to the climatic effects of regional deforestation. Here, we quantify the impact of historical (1900–2011) land cover changes (LCC) and of global warming during ENSO events (CC) on precipitation, temperature and surface energy balance components by running the Weather Research and Forecasting model WRF v3.9 at 10 km resolution. We find that historical anthropogenic CC causes a mean temperature increase of 0.77 ± 0.02 °C in Colombia, which is more pronounced in high altitudes. Precipitation is enhanced by 0.98 ± 0.30 mm/day (+ 9%), particularly over forested areas and reduced at the Pacific coast. LCC imply a reduction of precipitation particularly above the Andes (− 0.48 ± 0.10 mm/day) and Caribbean Coast (− 0.67 ± 0.12 mm/day), where LCC effects dampen CC effects by 24% and 72%, respectively. La Niña tends to intensify LCC and CC effects in the Andes but dampens them at the Coast, roughly by a factor of two compared to El Niño impacts in both regions. At the subregional level, LCC and CC can have impacts of similar magnitude on precipitation highlighting the need to precisely account for both drivers in hydroclimatic assessments. Contrary to almost all observations and similar simulations with climate models, WRF simulates a cooling bias after historical deforestation in Colombia, even with alternative WRF land surface models. We identify two main sources of biases in the default WRF parametrization to explain this inaccuracy: (1) surface shortwave radiation reflected after deforestation is overestimated; (2) associated evapotranspiration loss is underestimated. Improved model representation and validation of tropical vegetation properties are necessary to provide more robust and confident projections. [ABSTRACT FROM AUTHOR]

In this study we present a methodological framework to obtain statistically downscaled high resolution climate projections over the Attica region in Greece. The framework relies on the construction of a local daily gridded dataset for temperature variables (maximum, minimum and mean daily temperatures) and daily precipitation sums. To this aim, a mosaic of data that includes observations derived from ground stations and a high resolution simulation, performed by the Weather Research and Forecasting (WRF) model, for 1 year (1995) are blended using various gridding techniques to produce a 1 km 1 km high resolution daily gridded dataset for the period 1981–2000. The comparison of the gridded dataset against the observations reveals that the produced dataset maintains the observed long term statistical properties over the period 1981–2000 for both temperature and precipitation variables. Consequently, the produced dataset is used to statistically downscale Regional Climate Model simulations from the EURO-CORDEX initiative for the present (1981–2000) and the future climate (2081–2100) under the Representative Concentration Pathway (RCP) 8.5 climate scenario using two different bias adjustment techniques. The results indicate that the selection of the bias adjustment method is important and can affect the simulated climate change signals in a different way. Thus bias adjustment should be performed with caution and examined thoroughly before any such downscaled climate change projection dataset reach decision and policy makers in order to plan climate change related adaptation strategies. [ABSTRACT FROM AUTHOR]

Land–atmosphere energy and moisture exchange can strongly influence local and regional climates. However, high uncertainty exists in the representation of land–atmosphere interactions in numerical models. Parameterization of surface exchange processes is greatly affected by parameter Czil, which, however, is typically defined as a domain-wide constant value. In this study, we examine the sensitivity of regional climate simulations over China to different surface exchange strengths via three Czil schemes (default (without Czil), constant (Czil = 0.1), and dynamic canopy-height-dependent Czil-h schemes) within a 13-km-resolution Weather Research and Forecasting model coupled with the Noah land surface model with multiparameterization options (WRF/Noah-MP). Our results demonstrate that compared to the other two schemes, the Czil-h scheme substantially reduces land–atmosphere coupling strength overestimation, and comparison to Chinese terrestrial ecosystem flux research network (ChinaFLUX) observations reveals the capability of the Czil-h scheme to better match observed surface energy and water variations. The results of the application of the various Czil schemes in four typical climate zones in China demonstrate that the Czil-h simulations achieve the closest agreement with field observations. The Czil-h scheme can narrow the positive discrepancies in the simulated precipitation and surface fluxes and the negative biases of the land surface temperature in Northeast China, North China, eastern Northwest China, and Southwest China. In particular, the above remarkable improvements produced by the Czil-h scheme primarily occur in areas covered with short vegetation. Additionally, the precipitation simulated with the Czil-h scheme exhibits more intricate and uncertain changes compared with surface flux simulations due to the nonlocal impacts of the surface exchange strength resulting from atmospheric fluidity. Overall, our findings highlight the applicability of the dynamic Czil scheme as a better physical alternative to the current treatment of surface exchange processes in atmosphere coupling models. [ABSTRACT FROM AUTHOR]

This study presents the results of high-resolution dynamical downscaling of 5 km on maximum (TX) and minimum (TN) air temperature and precipitation, for Greece, with the Weather Research and Forecasting (WRF) model. The ERA-Interim (ERA-I) reanalysis dataset is used for initial and boundary conditions. The model results (WRF_5) are evaluated against available ground observations for the period 1980–2004 through the calculation of mean climatology, statistical metrics, and distributions of extreme events on daily, monthly and seasonal scales. WRF_5 model captures very well the geographical distribution of TX and TN of the study area, and illustrates finely the seasonal differences. Statistical results for TX (TN) indicate a cold (warm) bias of − 0.6 °C (1 °C) regarding WRF_5 and − 3 °C (0.5 °C) for ERA-I. The efficiency metrics for temperatures showed a highly improved performance of the model compared to reanalysis for all temporal scales investigated. The observed mean annual cycle and inter-annual variability of precipitation are also well represented by model simulation. Although WRF_5 overestimates rainfall during most of the year, the seasonal pattern of WRF_5 presented similar correlation coefficients for all stations with a range of 0.6–0.85, showing a good model ability to simulate the precipitation in Greece. The results reveal the capability of the configured WRF high resolution model to reproduce the main climatological variables of the study area, outperforming the coarse resolution ERA-Interim in a region that is dominated by highly variable topographic characteristics. This is deemed necessary for undertaking any further studies concerning future climate change impacts in various sectors. [ABSTRACT FROM AUTHOR]

A crucial step in the application of the Weather Research and Forecasting (WRF) model to regional climate research is the selection of the proper combinations of physical parameterizations. In this study, we examined the performance of various parametrization schemes in the WRF model in terms of precipitation and temperature over the Haihe river basin in northern China. The WRF experiments were integrated with 13-km horizontal resolution and driven by ERA-INTERIM reanalysis data over the period from 1st June to 31st August, 2016. Fifty-eight members of physics combinations derived from five types of physics options were assessed against the available observational temperature and precipitation data by utilizing the multivariable integrated evaluation (MVIE) method. Our results indicated that the best combination of physical schemes consisted of CAM5.1 microphysics, MRF PBL, BMJ cumulus, CAM Longwave/Shortwave radiation, and Noah Land Surface schemes. The optimal setup's differences with the observational data, temporally and spatially, were much smaller than other setups in terms of surface air temperature and precipitation, which proves that the optimal setup showed better performance than the other setups. Further analysis of the sensitivities of model outputs to different types of physics options suggests that the microphysics, planetary boundary layer (PBL), and cumulus schemes have a more significant impact on the model performances than the radiation scheme and Land Surface schemes. [ABSTRACT FROM AUTHOR]

Tropical cyclones (TCs) that make landfall over India's east coast are responsible for significant loss of life along affected coastlines. TCs forming over the Bay of Bengal (BoB) region in October, November, and December have, in the past, intensified significantly at the time of landfall. The effects of climate change on TCs of different strengths and their characteristics such as track, intensity, precipitation, and convective available potential energy over the BoB region have not been well studied. This study explores the effects of climate change on two TCs of very severe cyclonic storm (VSCS) category (TC Vardah and TC Madi), and two other TCs of extremely severe cyclonic storm (ESCS) category (TC Hudhud and TC Phailin) formed over BoB, both in the short term (2035) and long term (2075). The high-resolution Weather Research and Forecasting (WRF) model is used to simulate the TCs under current and future climate conditions. The simulated TC track and intensity in the current climate agree well with the observations. To explore the impacts of climate change on TCs, the mean climate change signal, computed from future projections of the Community Climate System Model (CCSM4) in different representative concentration pathway (RCP) scenarios, is added to current climate conditions by using the pseudo global warming method. Results show a climate change-related reduction in TC translation speed, deepening of TC core, increased maximum surface wind, and increased precipitation over land in future RCP (4.5, 6.0, and 8.5) scenarios. The TCs in future RCP scenarios are seen to be more intensified compared to current climate simulations. Results demonstrate that all VSCS and ESCS category TCs considered in this study are likely to further intensify to the next higher category level with respect to their current classification, particularly in the far future RCP 6.0 and in the far future RCP 8.5 scenarios. The cyclone damage potential index of TC Vardah, TC Hudhud, and TC Phailin is projected to increase in a future warming climate. [ABSTRACT FROM AUTHOR]

The precipitation recycling (PR) ratio is an important indicator that quantifies the land-atmosphere interaction strength in the Earth system's water cycle. To better understand how the heterogeneous land surface in the Tibetan Plateau (TP) contributes to precipitation, we used the water-vapor tracer (WVT) method coupled with the Weather Research and Forecasting (WRF) regional climate model. The goals were to quantify the PR ratio, in terms of annual mean, seasonal variability and diurnal cycle, and to address the relationships of the PR ratio with lake treatments and precipitation amount. Simulations showed that the PR ratio increases from 0.1 in winter to 0.4 in summer when averaged over the TP with the maxima centered at the headwaters of three major rivers (Yangtze, Yellow and Mekong). For the central TP, the highest PR ratio rose to over 0.8 in August, indicating that most of the precipitation was recycled via local evapotranspiration in summer. The larger daily mean and standard deviation of the PR ratio in summer suggested a stronger effect of land-atmosphere interactions on precipitation in summer than in winter. Despite the relatively small spatial extent of inland lakes, the treatment of lakes in WRF significantly impacted the calculation of the PR ratio over the TP, and correcting lake temperature substantially improved both precipitation and PR ratio simulations. There was no clear relationship between PR ratio and precipitation amount; however, a significant positive correlation between PR and convective precipitation was revealed. This study is beneficial for the understanding of land-atmosphere interaction over high mountain regions. [ABSTRACT FROM AUTHOR]

In this study, the Weather Research and Forecasting (WRF) model is used to produce short-term regional climate simulations with several configurations for the Carpathian Basin region. The goal is to evaluate the performance of the model and analyze its sensitivity to different physical and dynamical settings, and input data. Fifteen experiments were conducted with WRF at 10 km resolution for the year 2013. The simulations differ in terms of configuration options such as the parameterization schemes, the hydrostatic and non-hydrostatic dynamical cores, the initial and boundary conditions (ERA5 and ERA-Interim reanalyses), the number of vertical levels, and the length of the spin-up period. E-OBS dataset 2 m temperature, total precipitation, and global radiation are used for validation. Temperature underestimation reaches 4–7 °C for some experiments and can be reduced by certain physics scheme combinations. The cold bias in winter and spring is mainly caused by excessive snowfall and too persistent snow cover, as revealed by comparison with satellite-based observations and a test simulation without snow on the surface. Annual precipitation is overestimated by 0.6–3.8 mm day−1, with biases mainly accumulating in the period driven by large-scale weather processes. Downward shortwave radiation is underestimated all year except in the months dominated by locally forced phenomena (May to August) when a positive bias prevails. The incorporation of downward shortwave radiation to the validation variables increased the understanding of underlying problems with the parameterization schemes and highlighted false model error compensations. [ABSTRACT FROM AUTHOR]

Two long continuous regional climate simulations over China have been carried out using the Regional Climate Model version 4 (RegCM4) and Weather Research and Forecasting model (WRF). The Simulations are forced by NCEP Reanalysis II data with a horizontal grid spacing of 30 km during 1981–2010. It is demonstrated that the RegCM4 and WRF had pronounced temperature and precipitation downscaling ability, producing more regional details and smaller biases than the driving R2. Overall, WRF tended to better capture the temperature and precipitation pattern and magnitude, daily temperature frequency, the monsoon rain belt movement, and seasonal precipitation variations over most wet regions, while larger deficits than RegCM4 were shown over some dry regions. The extreme precipitation indices of the two RCMs were quite different, with strong regional and seasonal dependence. WRF was better at simulating the annual mean temperature and precipitation trends, with higher spatial pattern correlations. The optimal ensemble approach combining the advantages of RegCM4 and WRF showed improved simulation compared to the individual models. The optimal ensemble reduced the annual temperature biases from the two models by 15–30%, and increased the precipitation spatial pattern correlations by 0.08–0.13. Further works are needed to improve the performances of the ensemble approach by using more RCMs. [ABSTRACT FROM AUTHOR]

Low-level jets (LLJs) over the Great Plains are well-known for their importance in transporting moisture from the Gulf of Mexico and forming precipitation in the Central US. However, the impact of irrigation practice on LLJs is rarely studied. To understand the irrigation impact on the Great Plains LLJs, the Weather Research and Forecasting (WRF) model is employed with and without an irrigation scheme. The simulated wind fields are evaluated against the observed wind from the Midlatitude Continental Convective Clouds Experiment (MC3E) as well as the North America Regional Reanalysis dataset. The results show that adding irrigation improves the simulated wind, especially at altitudes below 800 hPa. Irrigation reduces the LLJ frequency over the Great Plains, mainly by reducing the intense LLJ frequency. The reduced LLJ frequency is caused by the irrigation-induced weakening of meridional wind. The favorable conditions for LLJs have been identified by examining the mechanism associated with LLJs: a ridge-like pattern with weak and calm synoptic-scale conditions in the mid-levels and a strong west–east temperature gradient at lower levels that promote meridional winds. Irrigation-induced cooling leads to a baroclinic pattern with high pressure at lower altitudes over the irrigation region and low pressure in the mid- and upper levels in the downstream region, resulting in a northerly component that hinders the formation of LLJs. Low-level surface cooling also decreases the west–east temperature gradient and hence weakens the thermal wind forcing. The irrigation-induced mid-level low and weaker west–east temperature gradient are responsible for the reduced meridional winds and the reduced LLJ frequencies. [ABSTRACT FROM AUTHOR]

Regional weather forecasting models like the Weather Research and Forecasting (WRF) model allow for nested domains to save computational effort and provide detailed results for mesoscale weather phenomena. The sudden resolution change by nesting may cause artefacts in the model results. On the contrary, the novel global Model for Prediction Across Scales (MPAS) runs on Voronoi meshes that allow for smooth resolution transition towards the desired high resolution in the region of interest. This minimises the resolution-related artefacts, while still saving computational effort. We evaluate the MPAS model over Europe focussing on three mesoscale weather events: a synoptic gale over the North Sea, a föhn effect in Switzerland, and a case of organised convection with hail over the Netherlands. We use four different MPAS meshes (60 km global refined to-3 km (60– 3 km), analogous 30–3 km, 15–3 km, global 3 km) and compare their results to routine observations and a WRF setup with a single domain of 3 km grid spacing. We also discuss the computational requirements for the different MPAS meshes and the operational WRF setup. In general, the MPAS 3 km and WRF model results correspond to the observations. However, a global model at 3 km resolution as a replacement for WRF is not feasible for operational use. More importantly, all variable-resolution meshes employed in this study show comparable skills in short-term forecasting within the high-resolution area at considerably lower computational costs. [ABSTRACT FROM AUTHOR]

Three sub-regions of the Indian Ocean in which SSTs significantly influence the equatorial East African short rains on interannual timescales are identified, and the physical processes of this influence are studied using regional climate model simulations from the Weather Research and Forecasting model (WRF). Five 20-year ensemble integrations are generated to represent a control climate and to simulate the individual and combined effects of SSTAs in the influential regions. SSTAs in the western Indian Ocean exert a stronger influence on the equatorial East African short rains than central and eastern Indian Ocean SSTAs both in terms of the coverage of significantly-changed precipitation and the magnitude of the precipitation response. Positive western Indian Ocean SSTAs significantly increase the short rains over 95% of the equatorial East Africa domain (30°–40°E, 5°S–5°N), while only 30% of the region responds to central and eastern Indian Ocean SSTAs. Evidence of an influential Indian Ocean dipole mode does not emerge from the analysis. The mechanisms of this influence are diagnosed using atmospheric moisture budget and moist static energy analyses, with reference to Kelvin and Rossby wave generation as in the Gill model, but in the presence of complicated topography and nonzero background flows. Wind convergence anomalies in a moist environment primarily support precipitation anomalies in all cases, while changes in atmospheric instability are largely controlled by low-level moisture. Central and eastern Indian Ocean SSTAs change circulations and precipitation locally, but the remote influence on East Africa is weaker than that of the western Indian Ocean SSTAs. [ABSTRACT FROM AUTHOR]

The Tibetan Plateau (TP) is often referred to as the "water tower of Asia" or the "Third Pole". It remains a challenge for most global and regional models to realistically simulate precipitation, especially its diurnal cycles, over the TP. This study focuses on evaluating the summer (June–August) precipitation diurnal cycles over the TP simulated by the Weather Research and Forecasting (WRF) model. The horizontal resolution used in this study is 9 km, which is within the gray-zone grid spacing that a cumulus parameterization scheme (CU) may or may not be used. We conducted WRF simulations with different cumulus schemes (CU experiments) and a simulation without CU (No_CU experiment). The selected CUs include the Grell-3D Ensemble (Grell), New Simplified Arakawa-Schubert (NSAS), and Multiscale Kain-Fritsch (MSKF). These simulations are compared with both the in-situ observations and satellite products. Results show that the scale-aware MSKF outperforms the other CUs in simulating precipitation in terms of both the mean intensity and diurnal cycles. In addition, the peak time of precipitation intensity is better captured by all the CU experiments than by the No_CU experiment. However, all the CU experiments tend to overestimate the mean precipitation and simulate an earlier peak of precipitation frequency when compared to observations. The frequencies and initiation timings for short-duration (1–3 h) and long-duration (> 6 h) precipitation events are well captured by the No_CU experiment, while these features are poorly reproduced by the CU experiments. The results demonstrate simulation without a CU outperforms those with a CU at the gray-zone spatial resolution in regard to the precipitation diurnal cycles. [ABSTRACT FROM AUTHOR]

A regional climate model, WRF (Weather Research and Forecasting model), was set-up and fine-tuned to simulate the possible impacts of climate change to the Mackenzie River Basin (MRB) of Canada from May to October. The baseline (1979–2005) regional climate of the MRB simulated by WRF agrees well with gridded observed climate data, ANUSPLIN of Environment Canada. Next, WRF projected the regional climate change of MRB for 2041–2100 by dynamic downscaling RCP4.5 and RCP8.5 climate scenarios of three global climate models (GCMs), ACCESS1–3, CCSM4, and CanESM2. Based on RCP4.5 and RCP8.5 climate scenarios downscaled by WRF, air temperature of MRB is projected to increase by 2.5–3.8 °C and 4.5–6.9 °C in the 2050 s and 2080 s, respectively. In general, the air temperature of MRB is projected to increase marginally higher in colder regions of higher latitude and elevation. In contrast, the seasonal precipitation of MRB is only projected to increase marginally in the 2080 s under the RCP4.5 and RCP8.5 scenarios, respectively. The projected extreme precipitation indices show that future precipitation events would become more intensive and of longer durations. Under both RCP4.5 and RCP8.5 climate scenarios, the annual counts of days with total precipitation exceeding 10 mm of MRB (R10mm) are projected to increase by 18% in 2041–2100; the maximum 5-day precipitation (Rx5day) could increase by 9.4%. More studies should be conducted to gain a better understanding of the potential impacts of global warming to MRB and possible adaptive measures to mitigate these impacts. [ABSTRACT FROM AUTHOR]

In August 2018, the Indian state of Kerala received an extended period of very heavy rainfall as a result of a low-pressure system near the beginning of the month being followed several days later by a monsoon depression. The resulting floods killed over 400 people and displaced a million more. Here, a high resolution setup (4 km) of the Weather Research and Forecasting (WRF) model is used in conjunction with a hydrological model (WRF-Hydro, run at 125 m resolution) to explore the circumstances that caused the floods. In addition to a control experiment, two additional experiments are performed by perturbing the boundary conditions to simulate the event in pre-industrial and RCP8.5 background climates. Modelled rainfall closely matched observations over the study period, and it is found that this would this would have been about 18% heavier in the pre-industrial due to recent weakening of monsoon low-pressure systems, but would be 36% heavier in an RCP8.5 climate due to moistening of the tropical troposphere. Modelled river streamflow responds accordingly: it is shown the six major reservoirs that serve the state would have needed to have 34% more capacity to handle the heavy rainfall, and 43% had the deluge been amplified by an RCP8.5 climate. It is further shown that this future climate would have significantly extended the southern boundary of the flooding. Thus it is concluded that while climate change to date may well have mitigated the impacts of the flooding, future climate change would likely exacerbate them. [ABSTRACT FROM AUTHOR]

The ability of the Weather Research and Forecasting (WRF) model in simulating the seasonal and diurnal cycles of rainfall over the Coordinated Regional Climate Downscaling Experiment East Asia Phase II (CORDEX-EA-II) domain is validated against the Tropical Rainfall Measuring Mission (TRMM) datasets. A focus is placed on the role of convective parameterization (CP) schemes. A set of numerical experiments at a 25 km resolution for 1998–2009, using six different CPs, is performed to evaluate the physics-dependency of simulation results. All CPs simulate realistic summer mean precipitation and its northward propagation, with the best performance in the Simplified Arakawa-Schubert (SAS). The biases in the seasonal evolution of rainfall are related to the deficiency in simulated low-level winds and the northward propagation of the cyclonic vorticity. The simulated earlier peak time in other CPs is delayed by about 1–2 h by the Kain-Fritsch with a modified trigger function (KFMT), although this scheme shows a disadvantage in the magnitude. The performance of different CPs in simulating diurnal rainfall cycles is dependent on regions, and none of them performs better than the others for all the sub-regions. The initiation of simulated convection is weakly physics-dependent. However, the timing and magnitude of stratiform precipitation differ among the six experiments. A further analysis shows that the dry biases over the lower Yangtze River basin are a result of the weakened southwesterly water vapor transport, while the excessive afternoon rainfall in the Kain-Fritsch (KF) simulation is attributed to the largest positive perturbation in the lower level atmosphere, especially the enhanced vertical transport of humidity. [ABSTRACT FROM AUTHOR]

This study investigates the added value of very high resolution in long-term climate simulations over South Korea using the Weather Research and Forecasting (WRF) model. A one-way double-nested modeling system consisting of a mother domain (20-km resolution) and nested domain (5-km resolution) is customized for simulating the distinct climatological patterns in Korea, where the region-specific climate is largely influenced by the area's complex geographical features. The ERA-Interim reanalysis data are used for the initial and boundary conditions, and the simulation spans the period from December 1, 1985 to December 31, 2005 (20-year analysis period with 1-month spin-up). Simulations from both the mother and the nested domain show reasonable performance in capturing the general characteristics of summer temperature and precipitation in terms of temporally and spatially averaged quantities. However, the added value from the nested domain with its higher resolution is apparently found in the reproduction of the intensity and frequency of extreme events and in the physical realism related to the partitioning of convective and large-scale precipitation. The nested domain not only better resolves the sharp gradients of temperature variation over short distances but also substantially reduces the systematic cold bias seen in temperature extremes produced by the mother domain. Furthermore, the nested domain is better able to simulate the upper tail of precipitation distributions and thus of extreme events. The higher resolution also improves the simulation of partitioning between convective and large-scale precipitation, leading to a plausible relationship between extreme precipitation and temperature and showing good agreement with in situ observation. Given the different behaviors of convective and large-scale precipitation in response to temperature changes, their realistic partitioning in the model has important potential for enhancing the reliability of precipitation projection under global warming. [ABSTRACT FROM AUTHOR]