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This study assessed the sensitivity of West African climate to varying vegetation fractions. The assessment of a such relationship is critical in understanding the interactions between land surface and atmosphere. Two sets of convection-permitting simulations from the UK Met Office Unified Model at 12 km horizontal resolution covering the monsoon period May-September (MJJAS) were used, one with fixed vegetation fraction (MF-V) and the other with time-varying vegetation fraction (MV-V). Vegetation fractions are based on MODIS retrievals between May and September. We focused on three climatic zones over West Africa: Guinea Coast, Sudanian Sahel, and the Sahel while investigating heat fluxes, temperature, and evapotranspiration. Results reveal that latent heat fluxes are the most strongly affected by vegetation fraction over the Sahelian and Sudanian regions while sensible heat fluxes are more impacted over the Guinea Coast and Sudanian Sahel. Also, in MV-V simulation there is an increase in evapotranspiration mainly over the Sahel and some specific areas in Guinea Coast from June to September. Moreover, it is noticed that high near surface temperature is associated with a weak vegetation fraction, especially during May and June. Finally, varying vegetation seems to improve the simulation of surface energy fluxes and in turn impact on climate parameters. This suggests that climate modellers should prioritise the use of varying vegetation option to improve the representation of the West African climate system.

Recent studies using convection-permitting (CP) climate simulations have demonstrated a step-change in the representation of heavy rainfall and rainfall characteristics (frequency-intensity) compared to coarser resolution Global and Regional Climate models. The goal of this study is to better understand what explains the weaker frequency of precipitation in the CP ensemble by assessing the triggering process of precipitation in the different ensembles of regional climate simulations available over Europe. We focus on the statistical relationship between tropospheric temperature, humidity and precipitation to understand how the frequency of precipitation over Europe and the Mediterranean is impacted by model resolution and the representation of convection (parameterized vs. explicit). We employ a multi-model data-set with three different resolutions (0.44°, 0.11° and 0.0275°) produced in the context of the MED-CORDEX, EURO-CORDEX and the CORDEX Flagship Pilot Study "Convective Phenomena over Europe and the Mediterranean" (FPSCONV). The multi-variate approach is applied to all model ensembles, and to several surface stations where the integrated water vapor (IWV) is derived from Global Positioning System (GPS) measurements. The results show that all model ensembles capture the temperature dependence of the critical value of IWV (IWVcv), above which an increase in precipitation frequency occurs, but the differences between the models in terms of the value of IWVcv, and the probability of its being exceeded, can be large at higher temperatures. The lower frequency of precipitation in convection-permitting simulations is not only explained by higher temperatures but also by a higher IWVcv necessary to trigger precipitation at similar temperatures, and a lower probability to exceed this critical value. The spread between models in simulating IWVcv and the probability of exceeding IWVcv is reduced over land in the ensemble of models with explicit convection, especially at high temperatures, when the convective fraction of total precipitation becomes more important and the influence of the representation of entrainment in models thus becomes more important. Over lowlands, both model resolution and convection representation affect precipitation triggering while over mountainous areas, resolution has the highest impact due to orography-induced triggering processes. Over the sea, since lifting is produced by large-scale convergence, the probability to exceed IWVcv does not depend on temperature, and the model resolution does not have a clear impact on the results.

We present the first evaluation of the wind field from the CORDEX-FPS ensemble of kilometer-scale simulations, with focus on the Adriatic region. Kilometer-scale climate models, also known as convection-permitting models (CPMs), produce a good representation of small-scale topographic features and consequently a more detailed depiction of dynamical and thermal circulation. These enable a reliable view of climate characteristics of the wind field, especially in coastal regions and over complex terrain, such as the Adriatic. We investigate the (potential) added value introduced by CPMs compared to classical “cumulus-parametrized” regional climate models (RCMs), reanalysis and station observations. For this purpose, wind components at 10 meter level are used at 3-hourly frequency. All simulations cover a 10-year period, extending from 2000 to 2009. In terms of the standard statistical parameters such as correlation coefficient and temporal standard deviation, CPMs are very dependent on their parent RCM performance. However, the orographic forcing emphasizes the potential added value and CPMs contain some fine spatial scale variability (i.e. stronger extremes by 25% and accurate wind direction) that is absent in coarser RCMs and reanalysis. The potential added value is higher in the cold season compared to the warm season due to the proportion of severe wind events. CPMs reproduce well the typical wind regimes along the Adriatic coast, namely Bora and Sirocco. The benefit of using CPMs is especially pronounced in simulating Bora maximum wind speeds in northern Adriatic and Sirocco frequencies in southern Adriatic. Based on our overall analysis, we conclude that CPMs provide added value compared to coarser models, especially in the complex coastal terrain.

This paper presents results from high-resolution climate change simulations that permit convection and resolve mesoscale orography at 3-km grid spacing over Fenno-Scandinavia using the HARMONIE-Climate (HCLIM) model. Two global climate models (GCMs) have been dynamically down-scaled for the RCP4.5 and RCP8.5 emission scenarios and for both near and far future periods in the 21st century. The warmer and moister climate conditions simulated in the GCMs lead to changes in precipitation characteristics. Higher precipitation amounts are simulated in fall, winter and spring, while in summer, precipitation increases in northern Fenno-Scandinavia and decreases in the southern parts of the domain. Both daily and sub-daily intense precipitation over Fenno-Scandinavia become more frequent at the expense of low-intensity events, with most pronounced shifts in summer. In the Scandinavian mountains, pronounced changes occur in the snow climate with a shift in precipitation falling as snow to rain, reduced snow cover and less days with a significant snow depth. HCLIM at 3-km grid spacing exhibits systematically different change responses in several aspects, e.g. a smaller shift from snow to rain in the western part of the Scandinavian mountains and a more consistent decrease in the urban heat island effect by the end of the 21st century. Most importantly, the high-resolution HCLIM shows a significantly stronger increase in summer hourly precipitation extremes compared to HCLIM at the intermediate 12-km grid spacing. In addition, an analysis of the statistical significance of precipitation changes indicates that simulated time periods of at least a couple of decades is recommended to achieve statistically robust results, a matter of important concern when running such high-resolution climate model experiments. The results presented here emphasizes the importance of using “convection-permitting” models to produce reliable climate change information over the Fenno-Scandinavian region.

The CORDEX Flagship Pilot Study ELVIC (climate Extremes in the Lake VICtoria basin) was recently established to investigate how extreme weather events will evolve in this region of the world and to provide improved information for the climate impact community. Here we assess the added value of the convection-permitting scale simulations on the representation of moist convective systems over and around Lake Victoria. With this aim, 10-year present-day model simulations were carried out with five regional climate models at both PARameterized (PAR) scales (12-25km) and Convection-Permitting (CP) scales (2.5-4.5km), with COSMO-CLM, RegCM, AROME, WRF and UKMO. Most substantial systematic improvements were found in metrics related to deep convection. For example, the timing of the daily maximum in precipitation is systematically delayed in CP compared to PAR models, thereby improving the agreement with observations. The large overestimation in the total number of rainy events is alleviated in the CP models. Systematic improvements were found in the diurnal cycle in Top-Of-Atmosphere (TOA) radiation and in some metrics for precipitation intensity. No unanimous improvement nor deterioration was found in the representation of the spatial distribution of total rainfall and the seasonal cycle when going to the CP scale. Furthermore, some substantial biases in TOA upward radiative fluxes remain. Generally our analysis indicates that the representation of the convective systems is strongly improved in CP compared to PAR models, giving confidence that the models are valuable tools for studying how extreme precipitation events may evolve in the future in the Lake Victoria basin and its surroundings.

Climate change is expected to increase the frequency and intensity of rainfall extremes. Understanding future changes in rainfall is necessary for adaptation planning. Eastern Africa is vulnerable to rainfall extremes because of low adaptive capacity and high future population growth. Convection-permitting climate models have been found to better represent moderate (yearly) rainfall extremes than parameterized convection models, but there is limited analysis of rare extremes that occur less frequently than once per year. These events often have the largest socioeconomic impacts. We use extreme value theory and regional frequency analysis to quantify rare rainfall extremes over East Africa in a convection-permitting climate model (CP4A). We compare the results with its parameterized counterpart (P25), the Coordinated Regional Climate Downscaling Experiment for the African region (CORDEX-Africa) ensemble, and observations to understand how the convection parameterization impacts the results. We find that CP4A better matches observations than the parameterized models. With climate change, we find the parameterized convection models have unrealistically high changes in the shape parameter of the extreme value distribution, which controls the tail behavior (i.e., the most extreme events), leading to large increases in return levels of events with a return period of >20 years. This suggests that parameterized convection models may not be suitable for looking at relative changes in rare rainfall events with climate change and that convection-permitting models should be preferred for this type of work. With the more realistic CP4A, RCP8.5 end-of-century climate change leads to 1-in-100-yr events becoming 1-in-23-yr events, which will necessitate serious adaptation efforts to avoid devastating socioeconomic impacts. Significance Statement We use a new, high-resolution climate model to examine how rare extreme rainfall events in East Africa might change in the future with climate change and compare the results with those from standard-resolution climate models. We find that the standard-resolution models have unrealistically large increases in rainfall for events that occur less frequently than every 20 years. The high-resolution model is more realistic and is required to illustrate possible future changes in rare rainfall extremes. Extreme events will become more common with climate change, and in the more realistic model we show that a 1-in-100-yr event may become a 1-in-23-yr event by the end of the century if greenhouse gas emissions are not significantly reduced.

Modelling the rare but high-impact Mediterranean Heavy Precipitation Events (HPEs) at climate scale remains a largely open scientific challenge. The issue is adressed here by running a 38-year-long continuous simulation of the CNRM-AROME Convection-Permitting Regional Climate Model (CP-RCM) at a 2.5 km horizontal resolution and over a large pan-Alpine domain. First, the simulation is evaluated through a basic Eulerian statistical approach via a comparison with selected high spatial and temporal resolution observational datasets. Northwestern Mediterranean fall extreme precipitation is correctly represented by CNRM-AROME at a daily scale and even better at an hourly scale, in terms of location, intensity, frequency and interannual variability, despite an underestimation of daily and hourly highest intensities above 200 mm/day and 40 mm/h, respectively. A comparison of the CP-RCM with its forcing convection-parameterised 12.5 km Regional Climate Model (RCM) demonstrates a clear added value for the CP-RCM, confirming previous studies. Secondly, an object-oriented Lagrangian approach is proposed with the implementation of a precipitating system detection and tracking algorithm, applied to the model and the reference COMEPHORE precipitation dataset for twenty fall seasons. Using French Mediterranean HPEs as objects, CNRM-AROME’s ability to represent the main characteristics of fall convective systems and tracks is highlighted in terms of number, intensity, area, duration, velocity and severity. Further, the model is able to simulate long-lasting and severe extreme fall events similar to observations. However, it fails to reproduce the precipitating systems and tracks with the highest intensities (maximum intensities above 40 mm/h) well, and the model’s tendency to overestimate the cell size increases with intensity.

Convection-permitting (CP) models promise much in response to the demand for increased localization of future climate information: greater resolution of influential land surface characteristics, improved representation of convective storms, and unprecedented resolution of user-relevant data. In practice, however, it is contended that the benefits of enhanced resolution cannot be fully realized due to the gap between models’ computational and effective resolution. Nevertheless, where surface forcing is strongly heterogeneous, one can argue that usable information may persist close to the grid scale. Here we analyze a 4.5-km resolution CP projection for Africa, asking whether and where fine-scale projection detail is robust at sub-25-km scales, focusing on geolocated rainfall features (rather than Lagrangian motion). Statistically significant detail for seasonal means and daily extremes is most frequent in regions of high topographic variability, most prominently in East Africa throughout the annual cycle, West Africa in the monsoon season, and to a lesser extent over Southern Africa. Lake coastal features have smaller but significant impacts on projection detail, whereas ocean coastlines and urban conurbations have little or no detectable impact. The amplitude of this sub-25-km projection detail can be similar to that of the local climatology in mountainous regions (or around a third near East Africa’s lake shores), so potentially beneficial for improved localization of future climate information. In flatter regions distant from coasts (the majority of Africa), spatial heterogeneity can be explained by chaotic weather variability. Here, the robustness of local climate projection information can be substantially enhanced by spatial aggregation to approximately 25-km scales, especially for daily extremes and equatorial regions. Significance Statement Recent substantial increases in the horizontal resolution of climate models bring the potential for both more reliable and more local future climate information. However, the best spatial scale on which to analyze such data for impacts assessments remains unclear. We examine a 4.5-km resolution climate projection for Africa, focusing on seasonal and daily rainfall. Spatially fixed fine-scale projection detail is found to be statistically robust at sub-25-km scales in the most mountainous regions and to a lesser extent along lake coastlines. Elsewhere, the model data may be better aggregated to at least 25-km scales to reduce sampling uncertainties. Such evolving guidance on the circumstances and extent of high-resolution data aggregation will help users gain greater benefit from climate model projections.

International audience; We here inter-compare four different tracking algorithms by applying them onto the precipitation fields of an ensemble of convection-permitting regional climate models (cpRCMs) and on high-resolution observational datasets of precipitation. The domain covers the Alps and the northern Mediterranean and thus we here analyse heavy precipitation events, that are renowned for causing hydrological hazards. In this way, this study is both, an inter-comparison of tracking algorithms as well as an evaluation study of cpRCMs in the Lagrangian frame of reference. The tracker inter-comparison is performed by comparison of two case studies as well as of climatologies of cpRCMs and observations. We find that that all of the trackers produce qualitatively equal results concerning characteristic track properties. This means that, despite of quantitative differences, equivalent scientific conclusions would be drawn. This result suggests that all trackers investigated are reliable analysis tools of atmospheric research. With respect to the model ensemble evaluation, we find an encouraging performance of cpRCMs in comparison to radar-based observations. In particular prominent hotspots of heavy precipitation events are well-reproduced by the models. In general most characteristic properties of precipitation events have positive biases. Assuming the under-catchment of precipitation in observations in a domain of such complex orography, this result is to be expected. Only the mean area of tracks is underestimated, while their duration is overestimated. Mean precipitation rate is estimated well, while maximum precipitation rate is overestimated. Furthermore, geometrical and rain volume are overestimated. We find that models overestimate the occurrence of precipitation events over all mountain chains, whereas over plain terrain in summer precipitation events are seen underestimated. This suggests that, despite the convection-permitting resolution, thermally driven thunderstorms are either not triggered or their dynamics still under-resolved. Eventually we find that biases in the spatio-temporal properties of precipitation events appear reduced when evaluating cpRCMs against Doppler radar-based and rain gauge-adjusted observational datasets of comparable spatial resolution, strengthening their role in evaluation studies.

Hail is a significant convective weather hazard, often causing considerable crop and property damage across the world. Although extremely damaging, hail still remains a challenging phenomenon to model and forecast given the gaps in understanding the processes involved in hail formation. Recently, a physically-based one- dimensional hail model called HAILCAST was developed. HAILCAST forecasts the maximum expected hail diameter at the ground using a vertical profile of the updraft, temperature, liquid and ice water content and can be embedded within a convection-permitting model (CPM). Furthermore, lightning activity is a characteristic phenomenon that often accompanies severe weather, and especially hailstorms, as well as a damaging phenomenon in itself. One of the ways to diagnose the areas prone to lighting activity is by using a Lightning Potential Index (LPI). LPI is a measure of the potential for charge generation and separation inside a thundercloud, which results in lightning flashes during convective thunderstorms. Therefore, LPI maps the area with the potential for electrical activity based on the model’s dynamical and microphysical fields. Here, eight hailstorms occurring over the Alpine- Adriatic region are analyzed using Weather Research and Forecasting (WRF) and Consortium for Small Scale Modeling in Climate Mode (COSMO) simulations with embedded HAILCAST and LPI at convection-permitting resolution (~2.2 km). In addition, a model intercomparison study is performed to investigate the ability of different modeling systems in reproducing such convective extremes and to further assess the uncertainties associated with simulations of such local-area phenomena. The results are verified by direct hail observations from Croatia (hailpad network), radar estimates of hail from Switzerland (probability of hail, maximum expected severe hail size) and lightning measurements from the LINET network using neighborhood and spatial verification methods. The analysis revealed that both HAILCAST and LPI are able to reproduce the observed hail and lightning activity. Namely, both models are able to reproduce the areas affected by hail and lightning as well as its intensity. Moreover, the fields produced by both models are remarkably similar, although, a slight tendency of WRF to produce smaller hail swaths with larger hailstone diameters and larger LPI values seems to be present. Overall, the analysis revealed promising results and indicates that both HAILCAST and LPI could be valuable tools for real-time forecasting and climatological assessment of hail and lightning occurrence in current and possibly changing climate.

Hail is a significant convective weather hazard, often causing considerable crop and property damage across the world. Although extremely damaging, hail still remains a challenging phenomenon to model and forecast given the gaps in understanding the processes involved in hail formation. Recently, a physically-based one- dimensional hail model called HAILCAST was developed. HAILCAST forecasts the maximum expected hail diameter at the ground using a vertical profile of the updraft, temperature, liquid and ice water content and can be embedded within a convection-permitting model (CPM). Furthermore, lightning activity is a characteristic phenomenon that often accompanies severe weather, and especially hailstorms, as well as a damaging phenomenon in itself. One of the ways to diagnose the areas prone to lighting activity is by using a Lightning Potential Index (LPI). LPI is a measure of the potential for charge generation and separation inside a thundercloud, which results in lightning flashes during convective thunderstorms. Therefore, LPI maps the area with the potential for electrical activity based on the model’s dynamical and microphysical fields. Here, eight hailstorms occurring over the Alpine- Adriatic region are analyzed using Weather Research and Forecasting (WRF) and Consortium for Small Scale Modeling in Climate Mode (COSMO) simulations with embedded HAILCAST and LPI at convection-permitting resolution (~2.2 km). In addition, a model intercomparison study is performed to investigate the ability of different modelling systems in reproducing such convective extremes and to further assess the uncertainties associated with simulations of such local-area phenomena. The results are verified by direct hail observations from Croatia (hailpad network), radar estimates of hail from Switzerland (probability of hail, maximum expected severe hail size) and lightning measurements from the LINET network. The analysis revealed that both HAILCAST and LPI are able to reproduce the observed hail and lightning activity. Namely, both models are able to capture the areas affected by hail and lightning as well as its intensity. Moreover, the fields produced by both models are remarkably similar, although, a slight tendency of WRF to produce smaller hail swaths with larger hailstone diameters and larger LPI values seems to be present. Overall, the analysis revealed promising results and indicates that both HAILCAST and LPI could be valuable tools for real-time forecasting and climatological assessment of hail and lightning occurrence in current and possibly changing climate.

Convection-permitting resolutions, which refer to kilometer-scale horizontal grid spacings, have become increasingly popular in regional numerical weather prediction and climate studies. However, this resolution range is in the gray zone for the simulation of convection, where conventional cumulus convection and subgrid-scale (SGS) turbulence parameterizations are inadequate for such grid spacings due to invalid assumptions and simplifications. Recent studies demonstrated that the magnitudes of SGS fluxes of momentum and scalars are comparable to those of resolved fluxes at convection-permitting resolutions and that horizontal SGS components are as important as the vertical SGS component. Thus, it appears necessary to adapt available schemes to model the SGS effects of convective motions for the gray zone. Here, we investigated the efficacy of separately parameterizing the vertical and horizontal SGS effects in improving the convection-permitting simulation of Typhoon Vicente (2012). To represent the vertical SGS turbulence effect, we evaluated the Grell-3, Tiedtke, and multiscale Kain–Fritsch (MSKF) schemes in the Weather Research and Forecasting (WRF) Model; the MSKF scheme is scale adaptive, whereas the other two are conventional cumulus schemes. For horizontal SGS turbulence, we evaluated the effects of the traditional Smagorinsky scheme and our newly developed reconstruction and nonlinear anisotropy (RNA) model, which models not only downgradient diffusion but also backscatter. We found that the simulation combining the MSKF and RNA schemes exhibits the best skill in predicting precipitation, especially rainfall extremes. The advantages are rooted in the MSKF scheme’s scale-awareness and parameterized cloud–radiation feedback and in the backscatter-enabling capability of the RNA model. Significance Statement Operational numerical weather prediction and some climate simulations have approached kilometer-scale horizontal resolutions, called convection-permitting resolutions. However, details of convective storms are not well represented at these resolutions, and small-scale fluid motions can potentially impact the overall simulation performance. In practice, the effects of such unresolved turbulent eddies were once neglected. We suggest representing these effects in the vertical and horizontal directions with an adaptive cumulus convection parameterization and an advanced turbulence model, respectively, which significantly improve the simulation of tropical cyclones. This framework allows us to adapt convection schemes developed by the mesoscale modeling community and turbulence schemes studied by large-eddy simulation groups for representing three-dimensional turbulence in the convection-permitting regime.

In this work, we characterized the occurrences and conditions before the initiations of mesoscale convective systems (MCSs) in the central United States, using 15 years of observations and convection-permitting climate model simulations. The variabilities of MCSs in summer were obtained using high-resolution (4 km) observation data [Stage-IV (stIV)] and ECMWF Re-Analysis v5 (ERA5)-forced Weather Research and Forecasting (WRF) Model simulations (E5RUN). MCSs were identified using the object tracking algorithm MODE-time domain (MTD). MTD-determined MCSs were divided into daytime short-lived MCSs (SLM12), daytime long-lived MCSs (LLM12), nighttime short-lived MCSs (SLM00), and nighttime long-lived MCSs (LLM00). E5RUN showed skill to simulate MCSs by obtaining similar statistics in occurrences, areal coverages, and propagation speeds compared to those of stIV. We calculated the 15 parameters using sounding data from E5RUN before an MCS was initiated (−1, −3, −6, and −9 h) at each location of an MCS. The parameters were tested to figure out the significance of predicting the longevities of MCSs. The key findings are 1) LLM12 showed favorable thermodynamic variables compared to that of SLM12 and 2) LLM00 showed significant conditions of vertically rotating winds and sheared environments that affect the longevity of MCSs. Moreover, storm-relative helicity of 0–3 km, precipitable water, and vertical wind shear of 0–6 km are the most significant parameters to determine the longevities of MCSs (both daytime and nighttime MCSs). Significance Statement The purpose of this study is to understand the features of mesoscale convective systems (MCSs) in observational data and convection-permitting climate model simulations. We tested long-term simulations using new forcing data (ERA5) to see the benefits and limitations. We designed a novel approach to obtain the distributions of meteorological parameters (instead of obtaining one value for one event of MCS) before initiations of MCSs to understand preconvective conditions (times from −9 to −1 h from initiation). We also divided MCSs into daytime/nighttime and short-/long-lived MCSs to help predict MCSs longevity considering the initiation times. Our results provide hints for the forecasters to predict MCS longevity based on preconvective conditions from parameters discussed in this work.

Gaining a deeper physical understanding of the high-impact weather events repeatedly occurring over the Croatian coast is highly needed to reduce the casualties and economic impacts due to these highly localized and hardly predictable phenomena. Recently obtained national hail climatology in Croatia revealed that parts of the Croatian coast are frequently struck by early morning hailstorms with the local maximum of the daily activity occurring approximately at 08:00 h local time (CET). While the afternoon maximums of hail activity could be attributed to the daily heating cycle over land, the mechanisms responsible for the occurrence of the early morning maximum of hail activity are still unknown. This high uncertainty regarding the mechanisms associated with early morning hail formation stem from the scarcity of high-resolution modeling studies and observations of such events further lowering their forecasting ability. Benefiting from the advantages associated with the convection-permitting high-resolution numerical modeling, this work aims to inspect the triggering mechanism and evolution of such hailstorms. Moreover, a special focus is on the role that synoptic, mesoscale, but also local conditions such as orography or the shape of the coastline, play in the formation of the convergence zone responsible for severe weather effects. Several cases of early morning hailstorms are selected for simulations using Weather Research and Forecasting (WRF) model alongside HAILCAST and Lightning Potential Index (LPI) parameterizations. HAILCAST is a one-dimensional hail growth model that forecasts the maximum hail diameter at the ground. Similarly, LPI highlights the areas with the potential for developing lightning activity. Using these recently developed tools alongside a highly valuable data set of hail observations from Croatian meteorological stations, Croatian hailpad network, and lightning observations from the LINET network, the ability of HAILCAST and LPI to reproduce the observed hail and lightning activity is assessed. By utilizing a process-oriented approach for analyzing such high impact events, a deeper understanding of the synoptic, mesoscale and local conditions that benefit the development of hailstorms is obtained. This directly benefits the forecasting ability of early morning hail over the Croatian coast, but also highlights the ability and potential improvements of the high-resolution modeling systems and specific tools to represent such highly localized severe weather phenomena.

Dynamic and thermodynamic factors involved in future changes in local-scale short-term extreme summertime precipitation on the mesoscale and hourly time scale in Japan were examined using convection-permitting regional climate model simulations under the representative concentration pathway 8.5 scenario. The change in the dynamic component primarily contributes to the total change in vertically integrated moisture flux convergence over the analysis domain that is located off Okinawa Island, whereas the thermodynamic component is dominant over the analysis domain that is located off Kyushu Island. Differences in the amount of the dynamic and thermodynamic components are noticeable in these two domains. These results are explained by the difference in the vertical profiles of the convergence term, and hence the convergence itself between the two specific domains. A mesoscale low pressure system on the seasonal rain front—termed the baiu front—is a key factor underlying the difference in the magnitudes and vertical profiles of convergence between the two specific domains. In the vicinity of the domain off Okinawa Island, a mesoscale low pressure system on the baiu front enhances low-level convergence in the future climate when compared with the present climate. This atmospheric state is attributable to the location of the baiu front itself, which is located relatively southward in the future climate and is affected by the domain off Okinawa Island. In the domain where the dynamic component is dominant such as the domain off Okinawa Island, the total moisture flux convergence follows a super–Clausius–Clapeyron scaling.

Warm conveyor belts (WCBs) are important Lagrangian features in extratropical cyclones for the evolution of clouds, precipitation and flow dynamics. According to the classical concept, WCBs rise continuously from the boundary layer to the upper troposphere with ascent rates of less than 50 hPa/hr. Recent studies identified embedded convection in WCBs with ascent rates exceeding 50 hPa/hr, however, its significance and characteristics have not yet been analysed systematically. This study presents a detailed analysis of a frontal wave cyclone that occurred during the North Atlantic Waveguide and Downstream Impact Experiment (NAWDEX) and investigates the occurrence of convection with ascent rates exceeding 100-200 hPa/hr embedded in the WCB. A set of diagnostics, based on the combination of Meteosat products, ECMWF data, and a convection-permitting simulation, reveals consistently that convection occurs frequently in the warm sector of the investigated cyclone, in particular in the region of the WCB. These convective regions are characterized by increased surface precipitation, low values of convective available potential energy, and significant large-scale forcing for ascent, indicating that this type of convection embedded in WCBs differs from classical air mass convection with higher vertical velocities. This is qualitatively confirmed by airborne radar observations of the considered cyclone with reflectivities hardly exceeding 30 dBZ. In the investigated WCB, the ascent is not continuous, but characterized by intermittent periods of very strong or even convective ascent and occasionally by short periods of descent. Together, these results provide a refined view on the concept of WCBs and its embedded convection.

Floods are the primary natural hazard in the French Mediterranean area causing damages and fatalities every year. These floods are triggered by heavy precipitation events (HPEs) characterized by limited temporal and spatial extents. For a decade, a new generation of regional climate models at the kilometer scale have been developed, allowing an explicit representation of deep convection and improved simulations of local-scale phenomena such as HPEs. Convection-Permitting regional climate Models (CPMs) have been scarcely used in hydrological impact studies, and future projections of Mediterranean floods remain uncertain with Regional Climate Models (RCMs). In this paper, we use the CNRM-AROME CPM (2.5 km) and its driving CNRM-ALADIN RCM (12 km) at the hourly timescale to simulate floods over the Gardon d’Anduze catchment located in the French Mediterranean region. Climate simulations are bias-corrected with the CDF-t method. Two hydrological models, a lumped and conceptual model (GR5H), and a processed-based and distributed model (CREST), successively forced with historical and future climate simulations from the CPM and from the RCM, have been used. The CPM model confirms its ability to reproduce extreme hourly rainfall compared to the RCM. This added value is propagated on flood simulation with a better reproduction of flood peaks. Future projections are consistent between the hydrological models, but differ between the two forcing climate models. With the CNRM-ALADIN RCM, all floods are projected to increase, whereas a threshold effect is found for simulations driven by the CNRM-AROME CPM, where the magnitude of the largest floods is expected to increase while the moderate floods are expected to decrease. In addition, different flood event characteristics indicate that floods are expected to become flashier in a warmer climate, regardless of the model. This study is a first step for impact studies driven by CPMs over the Mediterranean.

In the autumn, the French Mediterranean area is frequently exposed to heavy precipitation events whose daily accumulation can exceed 300 mm. One of the key processes contributing to these precipitation amounts is deep convection, which can be explicitly resolved by state-of-the-art convection-permitting models to reproduce heavy rainfall events that are comparable to observations. This approach has been tested and performed at climate scale in several studies in recent decades for different areas. In this research, we investigate the added value of using an ensemble of three climate simulations at convection-permitting resolution (approx. 3 km) to replicate extreme precipitation events at both daily and shorter timescales over the south of France. These three convection-permitting simulations are performed with the Weather Research and Forecasting (WRF) Model. They are forced by three EURO-CORDEX simulations, which are also run with WRF at the resolution of 0.11∘ (approx. 12 km). We found that a convection-permitting approach provides a more realistic representation of extreme daily and 3-hourly rainfall in comparison with EURO-CORDEX simulations. Their similarity to observations allows use for climate change studies and its impacts.

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.

Tropical cyclogenesis can be influenced by convectively coupled equatorial waves; yet, existing datasets prevent a complete analysis of the multi-scale processes governing both tropical cyclones (TCs) and equatorial waves. This study introduces a convection-permitting aquaplanet simulation that can be used as a laboratory to study TCs, equatorial waves, and their interactions. The simulation was produced with the Model for Prediction Across Scales-Atmosphere (MPAS-A) using a variable resolution mesh with convection-permitting resolution (i.e., 3-km cell spacing) between 10oS–30oN. The underlying sea-surface temperature is given by a zonally symmetric profile with a peak at 10oN, which allows for the formation of TCs. A comparison between the simulation and satellite, reanalysis, and airborne dropsonde data is presented to determine the realism of the simulated phenomena. The simulation captures a realistic TC intensity distribution, including major hurricanes, but their lifetime maximum intensities may be limited by the stronger vertical wind shear in the simulation compared to the observed tropical Pacific region. The simulation also captures convectively coupled equatorial waves, including Kelvin waves and easterly waves. Despite the idealization of the aquaplanet setup, the simulated three-dimensional structure of both groups of waves is consistent with their observed structure as deduced from satellite and reanalysis data. Easterly waves, however, have peak rotation and meridional winds at a slightly higher altitude than in the reanalysis. Future studies may use this simulation to understand how convectively coupled equatorial waves influence the multi-scale processes leading to tropical cyclogenesis.

The aim of this study is to present an assessment of precipitation, simulated with the non-hydrostatic regional climate model RegCM4.7.1 at a regional and convection-permitting (CP) scale for a decade-long period, over Bulgaria domain. The simulations use a horizontal grid spacing of 3 km and are driven by the ERA-Interim reanalysis (0.75° x 0.75°) through an intermediate driving RegCM4 simulation at 15 km grid spacing using parameterized deep convection. The km-scale simulation is evaluated against E-OBS (0.1° x 0.1°) and CHIRPS (0.05° x 0.05°) datasets and is compared with the coarser-resolution driving simulation. We focus on different precipitation statistics such as seasonal mean daily precipitation, seasonal wet-day intensity, seasonal wet-day frequency, and seasonal heavy precipitation. The simulated period is 2000 - 2010. The simulations are carried out on the HPC Discoverer supercomputer, located in Sofia Tech Park in Sofia, Bulgaria. Acknowledgements This work is supported by the Bulgarian National Science Fund, KP-06-М57/3. We acknowledge Discoverer PetaSC and EuroHPC JU for awarding this project access to Discoverer supercomputer resources. Keywords: RegCM4.7.1; km-scale resolution; convection-permitting; extreme precipitation; intensity; frequency; regional climate modelling; Bulgaria

Data assimilation techniques can improve the simulation of regional precipitation and temperature over complex regions. Nowadays, regional climate simulations using convection-permitting scales are becoming available, but the number of those simulations including an additional data assimilation scheme is rather small because of their high computational costs. Hence, it is important to evaluate the effect of data assimilation schemes for such convection-permitting simulations, and to determine if data assimilation produces any improvement in the simulation of temperature or precipitation fields.To investigate this, we employ the Weather Research and Forecasting model (WRF; version 3.8.1) to dynamically downscale the state-of-the-art ERA5 reanalysis over Western Europe. A 3 km spatial resolution grid is employed, together with 51 vertical levels. The temporal resolution of the WRF outputs is one hour. Two model configurations are tested in two experiments spanning the period 2010-2020 after a one-year spin-up. In the first experiment (NoDA), after the initialization of the model, the boundary conditions drive the model. The second experiment (DA) is configured the same way as NoDA, but the additional 3DVAR data assimilation step (WRFDA) is run every six hours (00, 06, 12 and 18 UTC – analysis times). Observations obtained from the PREPBUFR dataset (NCEP ADP Global Upper Air and Surface Weather Observations) are employed, and only those included inside a 120 min window around analysis times were assimilated. For DA, monthly varying background error covariance matrices were created. In both cases, the model uses the Noah-MP land surface model, and high-resolution daily-varying SST fields from the NOAA OI SST v2 data set instead of the SST field from ERA5.The results of this study show that both experiments produce similar monthly precipitation patterns to those from observational data sets such as IMERG and CHIRPS, or the reanalysis ERA5. However, in general, and particularly during summer months, DA produces larger amounts of precipitation than NoDA. These amounts are in line with those from CHIRPS. In terms of temperature, DA show colder temperatures than NoDA in most of the months, which again are similar to those from observational data sets such as CRU or EOBS. The monthly temperature patterns of both experiments are similar to those from both observational data sets. These results highlight the fact that NoDA already is able to generate reliable precipitation and temperature fields compared to diverse gridded observational data sets, but the 3DVAR data assimilation can additionally improve the performance of the regional model when convection-permitting scales are employed.

The representation of upper tropospheric deep convective divergent outflow (UTDCDO) is compared between ICON-simulations with convection-permitting and convection parameterised set-ups (1 and 13 km resolution) for a convective event over Germany and the Alps on June 10th-11th 2019. Three hypotheses on those UTDCDO have been formulated using idealised Large Eddy Simulations and are now tested on ICON in a convection-permitting set-up: 1. Dimensionality affects the magnitude of UTDCDO in ICON; 2. Convective aggregation and organisation affects the magnitude of those convective outflows in ICON and 3. Convective momentum transport does not affect the magnitude of UTDCDO. A moving box is used to integrate mesoscale divergence, precipitation rate and convective momentum transport. Additionally, ellipse fitting is used to make estimates of convective organisation (dimensionality, area of convective precipitation, etc.).Variability in UTDCDO at a given net latent heating rate is reduced in ICON with parameterised deep convection, compared to the convection-permitting set-up. Hints, but no conclusive results are found on the effect of dimensionality on the magnitude of UT divergent deep convective outflows. An impact of convective organisation and aggregation on UTDCDO is significant in the dataset: as a consequence of outflow collisions, UTDCDO increases sub-linearly with net latent heating. We also found a statistical relation between normalised UTDCDO and normalised convective momentum transport.

In response to global warming, an intensification of extreme precipitation has been observed, and models project this trend to continue. Since the return values of extreme precipitation events are regularly used in practice in the form of heavy rainfall hazard products, a reliable update of these products is required. Moreover, for resilient planning a projection of future conditions is urged by practice stakeholders.A promising tool for projection are convection permitting climate simulations, which have been shown to better represent extreme precipitation events compared to coarser simulations and thus provide higher confidence in future extreme estimates. However, due to the large computation time of convection permitting simulations, evaluations are mostly based on single time slice experiments. Therefore, we explore the potential of an unique transient convection permitting (2.8 km) ensemble with COSMO-CLM regional simulations (1971-2100) over Germany, with four ensemble members driven by MPI-ESM-LR, EC-EARTH, CNRM-CM5, and HadGEM2-ES with the emission scenario RCP8.5. Extreme precipitation is derived over 30-year running time slices and the scales investigated span from hourly to 3-day event duration and return periods from 1 year to 100 years, representing the wide range of events considered for application.Within the historical period (1971-2005) we found adequate agreement between the simulations and the observation data set KOSTRA with increasing bias with longer event duration. Furthermore, the climate change signal, derived as a relative value with regard to the historical period of the simulation, was found to increase with return period and for shorter durations. Strongest relative changes lie within the range of Clausius-Clapeyron-scaling with global warming. Analysis of the uncertainty revealed a substantial residual standard deviation of the linear approximation of the change signal over global warming, highlighting the benefit of a transient ensemble that enables a more robust estimation of the change signal of extreme events. Moreover, the results indicate an increased variance of future extreme precipitation.

Convection-permitting (CP) climate simulations represent a major advance in capturing land surface effects on convection. From observational analyses in West Africa, we know that land surface conditions are a major driver of storm initiation as well as intensification during later stages of the storm life cycle. Dry soils of 10 km to several 100s of km scale can cause anomalous warming of the planetary boundary layer and affect horizontal circulations, regional moisture convergence as well as instability. However, to date it remains unclear whether, in a warming climate, larger and more intense storms may change the scale and frequency of surface patterns, feeding back on these identified processes. Here, we evaluate the ability of a pioneering convection-permitting (4.4km) pan-African climate simulation to capture the observed land effects on the pre-convective environment in West Africa and subsequent storm characteristics. This is compared to a CP climate projection representing a decade under a very high emission scenario around 2100 in order to reveal potential changes in process interactions and consequences for organised convection in the future.

The regional climate models are recently run at grid spacings of 4 km or less, so-called the convection-permitting scale, over different regions of the world. The previous studies highlighted the added value of the convection-permitting simulations, especially in representing the daily and sub-daily precipitation over complex topography. The Black Sea Basin, including the coastal areas of the Black Sea and a broad part of the Anatolian Peninsula, is one of the climate change hot-spots with its complex topographical features and where strong air-sea interactions occur. Previously, this region has become a subject of regional climate modelling studies at horizontal resolutions on the order of 10 km. In this study, we performed a decade-long convection-permitting climate simulation at 3 km horizontal resolution between 2061-2070 based on the SSP3-7.0 greenhouse gas emission scenario over the Black Sea Basin. To this end, we downscaled the last generation CMIP6 MPI-ESM1.2-HR outputs by using the WRF model. The results indicate that the daily 2m mean, minimum, and maximum air temperatures increase in the spring, summer, and autumn by about 3°C compared to the 2005-2014 reference period over the study area. Nevertheless, the increase in the cloud cover suppresses the warming in the winter. In terms of precipitation, the total precipitation amount decreases in spring and summer over the Black Sea Basin. On the other hand, the total precipitation amount increases significantly by about 3 mm/day in winter over the Eastern Black Sea region due to the positive change in evaporation of around 15%. The maximum daily precipitation amount reaches 350 mm over the northeast of Turkey and over the Caucasus. The intensification of the daily precipitation is most pronounced in the coastal subregions of the Black Sea Basin. Furthermore, the results highlight the intensification of sub-daily precipitation in these regions. In particular, the afternoon precipitation increases in autumn over the coastal regions of Turkey.

Heavy rainfall is the main driver of soil erosion by water which is a threat to soil and water resources across the globe. As a consequence of climate change, precipitation – and especially extreme precipitation – is increasing in a warmer world, leading to an increase in rainfall erosivity. However, conventional global climate models struggle to represent extreme rain events and cannot provide precipitation data at the high spatio-temporal resolution that is needed for an accurate estimation of future rainfall erosivity. Convection-permitting simulations (CPS) on the other hand, provide high-resolution precipitation data and a better representation of extreme rain events, but they are mostly limited to relatively small spatial extents and short time periods. Here we present for the first time rainfall erosivity and soil erosion scenarios in a large modelling domain such as Central Europe based on high-resolution CPS climate data generated with COSMO-CLM. We calculate rainfall erosivity for the past (1971–2000), present (2001–2019), near future (2031–2060) and far future (2071–2100) and apply the new data set in the soil erosion model WaTEM/SEDEM for the Elbe River basin. Our results showed that future increases in rainfall erosivity in Central Europe can be up to 84 % in the river basins of Central Europe. These increases are much higher than previously estimated based on regression with mean annual precipitation. In consequence, soil erosion and sediment delivery in the Elbe River basin are also increasing strongly. Locally, changes in erosion rates can be as high as 120 %. We conclude that despite remaining limitations, convection-permitting simulations have an enormous and to date unexploited potential for climate impact studies on soil erosion. Thus, the soil erosion modelling community should follow closely the recent and future advances in climate modelling to take advantage of new CPS for climate impact studies.

Upper-tropospheric deep convective outflows during an event on 10th–11th of June 2019 over Central Europe are analysed from simulation output of the operational numerical weather prediction model ICON. Both, a parameterised and an explicit representation of deep convective systems are studied. Near-linear response of deep convective outflow strength to net latent heating is found for parameterised convection, while coherent patterns in variability are found in convection-permitting simulations at 1 km horizontal grid spacing. Furthermore, three hypotheses on factors that may affect the magnitude of the convective outflow are tested in the convection-permitting configuration: organisation of convection through dimensionality of the systems, organisation of convection through aggregation and convective momentum transport. Convective organisation and aggregation induce a non-linear increase in the magnitude of deep convective outflows with increasing net latent heating, as shown by the confidence interval of the best fit between power transformed net latent heating and detected magnitude of outflows. However, mixed and weaker than expected signals are found in an attempt to detect the representation of dimensionality of the convection and its consequences for the divergent outflows with an ellipse fitting algorithm that describes the elongation of the intense (convective) precipitation systems. As opposed to expectations, convective momentum transport is identified to slightly increase the magnitude of divergent outflows in this case study.

Warm seasons of 2021 was quite exceptional if we consider the hail occurrence in the continental part of Croatia which attracted a lot of public attention due to the announced changes in the Law on the Hail Suppression System. One of the events that sparked a great debate in the public occurred on 25 June near the town of Požega due to hail size and damage, although this event was very well forecasted, and orange warning for thunderstorm was issued one day in advance. This work aims to explore the atmospheric conditions present during this hailstorm but also a forecasting potential of such events using the convection-permitting km-scale numerical models. On that day ahead of an advancing trough that stretched from Scandinavia to the western Mediterranean all necessary ingredients for severe deep moist convection were recognized. Convective initiation started first in Bosnia and Herzegovina ahead of the surface cold front. For damage in the vicinity of town Požega, most important were convective cells that were advected into the area of Slavonian Posavina. They experienced "explosive" development, and then moved in the southwestern and southern flow across western Slavonia. The estimated convective available potential energy of the air parcel raised from the ground to the level of free convection (SBCAPE) in the Zagreb area, based on radiosounding at 12 UTC was about 2700 J/kg and the deep layer wind shear was estimated at 20-25 m/s, which favored the formation of a supercell thunderstorm. Here, convection-permitting km-scale WRF model is utilized to inspect the ability of the WRF model to reproduce the atmospheric conditions leading to formation and evolution of an extremely damaging hailstorm. Additionally, the ability of HAILCAST and Lightning Potential Index (LPI) diagnostics to reproduce the main characteristics of observed hail and lightning is explored. HAILCAST is a one-dimensional hail growth model that forecasts the maximum hail diameter at the ground. Similarly, LPI highlights the areas with the potential for developing lightning activity. Moreover, the sensitivity experiments are performed to investigate the impact that convection parameterization has on the simulated timing and characteristics of convection. The results reveal that the WRF model, when run at the km-scale resolution (1.5 km) can reproduce the synoptic and mesoscale conditions present during an extremely damaging hailstorm occurring over Croatia. Moreover, HAILCAST and LPI diagnostics reproduce hail and lightning characteristics comparable to those observed.

How lightning and hail will change in the future with global warming is highly uncertain, mainly due to the small space and time scales of these phenomena, which requires high-resolution climate simulations for their accurate representation. Recently km-scale climate simulations have become available that are ‘convection-permitting’ and give the possibility of studying how convective storms may change. We use a pan-European convection-permitting (2.2km grid spacing) model to analyse future changes in deep moist convection, lightning, and hail across Europe under a high emissions-scenario. This includes a physically based lightning prediction scheme, that uses graupel and ice-fluxes that are explicitly represented within the model. It also provides convective-scale outputs, not previously available from conventional climate models, exploited here to study future changes using an ingredients-based approach inherited from severe storm forecasting. For hail, we derive a new severe hail potential metric that represents the likelihood of hail >2cm at the surface, accounting for hail growth and subsequent melting. Overall, we find an increasing frequency of deep moist convection across Europe mainly due to more instability with warming, but partially limited by greater convective inhibition. However, the increase in storms does not directly translate to an increase in lightning, mainly due to much higher melting level heights resulting in less cloud ice and hence less electrification. Weaker circulation and a northward shift of favourable weather regimes in the future simulation also affects the results, which vary regionally. While lightning increases in future over the mountains (due to enhanced Alpine Pumping) and in the north, lightning decreases over much of central Europe and over the sea. The potential for severe hail generally decreases in future, although storms locally produce higher amounts of graupel in the south. We also identify a new, warmer type of thunderstorms in the future, which may have important implications for changes to the frequency of the largest hailstones.

This study investigates the influences of urban land cover on the extreme rainfall event over the Zhengzhou city in central China on 20 July 2021 using the Weather Research and Forecasting model at a convection-permitting scale [1-km resolution in the innermost domain (d3)]. Two ensembles of simulation (CTRL, NURB), each consisting of 11 members with a multi-layer urban canopy model and various combinations of physics schemes, were conducted using different land cover scenarios: (i) the real urban land cover, (ii) all cities in d3 being replaced with natural land cover. The results suggest that CTRL reasonably reproduces the spatiotemporal evolution of rainstorms and the 24-h rainfall accumulation over the key region, although the maximum hourly rainfall is underestimated and displaced to the west or southwest by most members. The ensemble mean 24-h rainfall accumulation over the key region of heavy rainfall is reduced by 13%, and the maximum hourly rainfall simulated by each member is reduced by 15–70 mm in CTRL relative to NURB. The reduction in the simulated rainfall by urbanization is closely associated with numerous cities/towns to the south, southeast, and east of Zhengzhou. Their heating effects jointly lead to formation of anomalous upward motions in and above the planetary boundary layer (PBL), which exaggerates the PBL drying effect due to reduced evapotranspiration and also enhances the wind stilling effect due to increased surface friction in urban areas. As a result, the lateral inflows of moisture and high-θe (equivalent potential temperature) air from south and east to Zhengzhou are reduced.

This paper describes the first implementation of the Δx = 3.25 km version of the Energy Exascale Earth System Model (E3SM) global atmosphere model and its behavior in a 40‐day prescribed‐sea‐surface‐temperature simulation (January 20 through February 28, 2020). This simulation was performed as part of the DYnamics of the Atmospheric general circulation Modeled On Non‐hydrostatic Domains (DYAMOND) Phase 2 model intercomparison. Effective resolution is found to be ∼6× the horizontal dynamics grid resolution despite using a coarser grid for physical parameterizations. Despite this new model being in an immature and untuned state, moving to 3.25 km grid spacing solves several long‐standing problems with the E3SM model. In particular, Amazon precipitation is much more realistic, the frequency of light and heavy precipitation is improved, agreement between the simulated and observed diurnal cycle of tropical precipitation is excellent, and the vertical structure of tropical convection and coastal stratocumulus look good. In addition, the new model is able to capture the frequency and structure of important weather events (e.g., tropical cyclones, extratropical cyclones including atmospheric rivers, and cold air outbreaks). Interestingly, this model does not get rid of the erroneous southern branch of the intertropical convergence zone nor the tendency for strongest convection to occur over the Maritime Continent rather than the West Pacific, both of which are classic climate model biases. Several other problems with the simulation are identified, underscoring the fact that this model is a work in progress.

Terrestrial evapotranspiration (ET) over the Tibetan Plateau (TP) exerts considerable impacts on the local climate and the water cycle. However, the high-altitude, mountainous areas over the TP pose a challenge for field observations. To finely capture its ET characteristics, we employed dynamical downscaling modeling (DDM) with a 28 km resolution and convection-permitting modeling (CPM) with a 4 km resolution in a normal climatology year, 2014. The benchmark data were the surface energy balance–based global land ET dataset (EB). Other compared data included the Global Land-Surface Data Assimilation System (GLDAS) and two reanalysis datasets: ERA-Interim and ERA5. Results showed that EB exhibits a gradient from the southeastern to northwestern TP, which is in line with the precipitation pattern. GLDAS generally reproduces the annual mean magnitude and pattern but poorly represents the seasonal variations. DDM and CPM perform well in the monsoon season but underestimate ET in the non-monsoon season. The two reanalysis datasets greatly overestimate the ET in the monsoon season, but ERA-Interim performs well in the non-monsoon season. All five datasets underestimate the ET over tundra and snow/ice areas, both in the annual and seasonal means. ET deviations are dominated by precipitation deviations in the monsoon season and by surface net radiation deviations in the non-monsoon season.

The partitioning of rainfall at the land surface into interception, infiltration and surface runoff plays an important role in the water cycle as it controls the time scale at which water returns to the atmosphere. Rainfall intensity is of crucial importance to this partition. High resolution convection permitting models significantly improve simulated sub-daily rainfall intensity distributions, in particular those associated with convective rainfall in the tropics. Here we compare the land surface hydrological response in a pair of 10-year simulations over an African domain performed using the Met Office Unified Model: a typical configuration using parameterised convection operating at 25 km and the second a high resolution convection permitting simulation at 4.5 km with the parametrized convection switched off. Overall pan-African interception in the convection permitting scheme is 70% lower, whilst surface runoff is 43% higher than the parameterized convection model. These changes are driven by less frequent, but more intense rainfall with a 25% increase in rainfall above 20 mm h−1 in the 4.5 km model. The parameterised scheme has a ~ 50% canopy water contribution to evaporative fraction which is negligible in the convection permitting scheme. Conversely, the convection permitting scheme has higher throughfall and infiltration leading to higher soil moisture in the weeks following rain resulting in a 30–50% decrease in the daytime sensible heat flux. We examine how important the sub-grid rainfall parameterisation in the model is for the differences between the two configurations. We show how, switching a convective parameterisation off can substantially impact land surface behaviour.

This study presents a novel, high-resolution, dynamically downscaled dataset that will help inform regional and local stakeholders regarding potential impacts of climate change at the scales necessary to examine extreme mesoscale conditions. WRF-ARW version 4.1.2 was used in a convection-permitting configuration (horizontal grid spacing of 3.75 km; 51 vertical levels; data output interval of 15-min) as a regional climate model for a domain covering the contiguous US Initial and lateral boundary forcing for the regional climate model originates from a global climate model simulation by NCAR (Community Earth System Model) that participated in phase 5 of the Coupled Model Inter comparison Project. Herein, we use a version of these data that are regridded and bias corrected. Two 15-year downscaled simulation epochs were examined comprising of historical (HIST; 1990–2005) and potential future (FUTR; 2085–2100) climate using Representative Concentration Pathway (RCP) 8.5. HIST verification against independent observational data revealed that annual/seasonal/monthly temperature and precipitation (and their extremes) are replicated admirably in the downscaled HIST epoch, with the largest biases in temperature noted with daily maximum temperatures (too cold) and the largest biases in precipitation (too dry) across the southeast US during the boreal warm season. The simulations herein are improved compared to previous work, which is significant considering the differences in previous modeling approaches. Future projections of temperature under the RCP 8.5 scenario are consistent with previous works using various methods. Future precipitation projections suggest statistically significant decreases of precipitation across large segments of the southern Great Plains and Intermountain West, whereas significant increases were noted in the Tennessee/Ohio Valleys and across portions of the Pacific Northwest. Overall, these simulations serve as an additional datapoint/method to detect potential future changes in extreme meso-γ weather phenomena.

The stochastically perturbed parameterizations scheme (SPP) is here implemented and tested in HarmonEPS—the convection-permitting limited area ensemble prediction system by the international research program High Resolution Limited Area Model (HIRLAM) group. SPP introduces stochastic perturbations to values of chosen closure parameters representing efficiencies or rates of change in parameterized atmospheric (sub)processes. The impact of SPP is compared to that of the stochastically perturbed parameterization tendencies scheme (SPPT). SPP in this first version in HarmonEPS perturbs 11 parameters, active in different atmospheric processes and under various weather conditions. The main motivation for this study is the lack of variability seen in cloud products in HarmonEPS, as reported by duty forecasters. SPP in this first version is able to increase variability in a range of weather variables, including the cloud products. However, for some weather variables the root-mean-squared error of the ensemble mean is increased and the mean bias is impacted, especially in winter. This indicates that (some) parameter perturbation distributions are not optimal in the current configuration, and a further sensitivity analysis is required. SPPT resulted in a smaller increase in variability in the ensemble, but the impact was almost completely masked out when combined with perturbations of the initial state, lateral boundaries, and surface properties. An in-depth investigation into this lack of impact from SPPT is here presented through examining, among other things, accumulated tendencies from the model physics. Significance Statement Small inaccuracies, simplifications, or errors in any part of a complex and nonlinear system like a weather model can amplify and in a short time become significant. We wanted to introduce a physically consistent way of representing these uncertainties in a model that is used in several European countries. To do this we introduce variations in a few parameters that are used in the model description, and that we know are uncertain. By doing this we were able to increase the variability of the cloud products as desired. We see this as a promising approach for capturing the possibilities of fog occurring or not in this model. Further refinements are needed before it can be used in operational weather forecasts.

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 significantly the model performance, mainly 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 21°x29° (lat-lon) arises as the optimal domain configuration to simulate extreme precipitation events over SESA.

The largest type of deep convection, mesoscale convective systems (MCSs), regulate changes in the hydrological cycle and large-scale tropical circulation. During the Indian summer monsoon (June-September), synoptic-scale systems move across the monsoon zone, causing MCSs to form frequently. MCSs cause widespread and heavy rain throughout the monsoon zone. Past MCS studies in India used either observations or simulation in a short period or with case studies approach. Studies on structure and evolution of MCSs highlighting the organization of convection over the monsoon zone are lacking.In this study, a 4-month, convection-permitting simulation is conducted over the Indian monsoon zone using the Weather Research Forecast (WRF) model with 4-km grid spacing and two microphysics parameterizations and is compared with observations to evaluate composite MCS characteristics and microphysics sensitivities. We first apply a cloud-tracking algorithm to two high-resolution observation data sets, NASA global merged infrared brightness temperature (IR Tb) and GPM IMERG surface precipitation to identify and track individual MCS events during monsoon. Ground-based S-band radar observations are used to examine the 3-D structures of storms embedded within the tracked MCSs and analyze evolution of convective, stratiform and anvil components of the MCSs. A similar cloud-tracking algorithm is then applied to WRF simulated data (radar reflectivity, IR Tb and precipitation) to identify and track MCS in model simulation. As a result, the observed and simulated MCSs are consistently identified and tracked, making it possible to compare WRF MCS population statistics with observed MCSs.Results show that the properties of MCS including composite evolution, and frequency distribution are reasonably captured by the two simulations with some noticeable differences. In general, the Thompson simulation produces better agreement with observations for convective area and precipitation amount, MCS propagation speed but exhibits underestimation of stratiform area. The composite evolution of simulated MCS cloud and precipitation structures showed a gradual increase from convective initiation to around the first half of the MCSs lifetime, which was consistent with observations. The MCS eccentricity reaches to minimum value at maximum horizontal extent, indicating a quasi-circular shape of MCS. We observed that PDF of MCS precipitation intensity largely agrees well with observations. The highest altitude reached by intense convective cores (30-dBZ echo-tops) is 8 km, but the model significantly underestimates it. The detailed comparison of multiple aspects of MCSs (e.g., initiation, size, intensity, lifetime, propagation) and embedded storms (e.g., convective-stratiform areas) and associated precipitation between the simulation and observations for one monsoon season will be discussed.

Sub-daily extreme precipitation can generate fast hydro-geomorphic hazards such as flash floods and debris flows, which cause fatalities and damages especially in mountainous regions. Reliable projections of extreme future precipitation is fundamental for risk management and adaptation strategies. Convection-permitting climate models (CPMs) esplicitely resolve large convective systems and represent local processes, especially sub-daily extreme precipitation, more realistically than coarser resolution models, thus leading to higher confidence in their projections. Given their high computation cost, however, the available CPM simulations cover relatively short time periods (10–20 years), too short for deriving precipitation frequency analyses with conventional extreme value methods based on annual maxima or threshold exceedances.In this work, we evaluate the potential of a non-asymptotic approach based on “ordinary” events, the so-called Simplified Metastatistical Extreme Value (SMEV), to provide information on the future change of short-duration precipitation extremes. We focus on a complex-orography region in the Eastern Italian Alps, where significant changes in sub-daily annual maxima have been already observed. The study is based on COSMO-crCLIM model simulations at 2.2 km resolution under the RCP8.5 scenario and uses three 10-year time periods: historical 1996-2005 (the control period), near-future 2041-2050 and far future 2090-2099. We estimate extreme precipitation for durations ranging from 1 h to 24 h and assess the projected changes with respect to the control period. Specifically, we analyze annual maxima, return levels up to 50 years, and the parameters of the statistical model. A bootstrap procedure is used to evaluate the uncertainty of the estimates, and a permutation test is applied to assess the statistical significance of the projected changes. We compare our results with a modified Generalized Extreme Value (GEV) approach, recently applied for the study of extremes in CPM future time periods.We found that annual maxima and higher return levels exhibit a general increase in the future especially for the far future and the shorter event durations. On average, the magnitude of the far future change decreases with the precipitation temporal scale. The changes show an interesting spatial organization that can be associated with the orography of the region: significant future increases are mostly located at high elevations, while lowlands and coastal zones show no clear pattern.This work shows that SMEV reduces the uncertainty in the estimates of higher return levels compared to GEV and can thus provide improved estimates of their future changes from short CPM runs. These findings advance our knowledge about the projected changes in extreme precipitation and their spatial distribution at the different time scales. They can thus help improving risk management and adaptation strategies.

The convection permitting (CP) version of Regional Climate Model (RegCM) has been applied to investigate extreme events in southeastern South America in the context of CORDEX collaborative network Flagship Pilot Studies. In this context, we developed a long-term RegCM simulation (from June 2018 to June 2021) at CP resolution (4 km of horizontal grid spacing). RegCM simulation was forced by ERA5 reanalysis and its domain extends from center to southeast (from ~ 15o to 35oS) of South America. In this assessment, simulated daily climatology was compared with both ERA5 reanalysis and with a great number of local stations. These comparisons will help us to understand if CP simulation aggregates relevant information to the ERA5 reanalysis in reproducing local aspects of the climate. Using the winds from stations, the ability of CP simulation in reproducing the local circulations, such as sea-breeze, is also investigated. We also discuss how well long-term CP simulation captures long dry and wet periods that were observed in southeastern South America.

Snow dynamics are affecting the climate system, water cycle, ecology, human society, and infrastructure. Furthermore, the representation of snow on the land surface within regional climate models is crucial for the mass and energy balance in the modelled climate. Simulated daily snow depths of two high-resolution regional climate models, the WRF at 1.5 km resolution and the COSMO-CLM (CCLM) at 3 km resolution both driven by ERA5 reanalysis data are evaluated with 83 station observations in southern Germany during 1987 – 2018. Furthermore, based on the atmospheric output of CCLM, the hydrometeorological snow model AMUNDSEN is run at the point scale of the climate stations. In addition, the ERA5-Land dataset (9 km) complements the comparison as state-of-the-art reanalysis land surface product driven by the same atmospheric conditions of ERA5. ERA5-Land shows considerable deviations of grid cell elevation and station elevation (mean absolute error: 93 m) and moderate biases in air temperature (-0.3 °C) and precipitation (+19.1 %). However, there is a strong positive bias in mean winter snow depth (+3.5 cm) and snow cover duration (+33.3 d). The WRF simulation features a cold bias of -1.2 °C and moderate bias in precipitation (-5.2 %) during winter. This results in a slight overestimation of snow depth (+0.4 cm) and snow cover duration (+6.6 d). The CCLM strongly underestimates snow depth (-2.5 cm) and snow cover duration (-19.8 d), albeit a very good reproduction of air temperature (+0.0°C) and precipitation (+9.7 %). AMUNDSEN reverses the underestimations of the CCLM to an overestimation of snow depth (+2.2 cm), however improving the reproduction of snow cover duration (+6.4 d). All models fail to skilfully predict white Christmas.Extremes of snow dynamics such as annual maximum snow depths, maximum daily snow accumulation and melting are not well reproduced by ERA5L and CCLM. WRF and AMUNDSEN can improve the representation of extremes but still with considerable limitations. In conclusion, the simulation of snow depths with WRF and AMUNDSEN can benefit from the finer resolution of the topography in the high-resolution climate models compared to ERA5-Land. However, even though driven by the same large-scale atmospheric conditions of ERA5, the four snow depth simulations vary by a huge margin. The high spatial resolution of convection-permitting climate models shows potential in reproducing the winter climate in southern Germany. However, the uncertainties within the snow modelling prevent a further straightforward use for impact research. Hence, careful evaluation is needed before any impact-related interpretation of the simulations, also in the context of climate change research.

New evaluation simulations with the ERA5 boundary conditions have been completed with the new model RegCM5 for all CORDEX-CORE domains at 25 km resolution. Model performances are satisfactory for all evaluation metrics for both the mean climate and extreme climate and for temperature, precipitation and cloud variables. For some of the domains the new model is able to remove some well know biases like the dry bias in the Amazon region in the CAM domain or the warm bias in the La Plata basin for the SAM domain. In other domains the RegCM5 performs consistently with the previous model version. One simulation at convection permitting resolution (CP) has been completed for the first time for the whole Euro-CORDEX domain thanks to the new semi implicit dynamical core implemented in the RegCM5 that allow the model to remain stable at such resolution even with time steps of 30 seconds at 3 km resolution. The evaluation of the CP simulation is comparable with the previous model evaluation over the ALPS domain with a tendency to improve both the dry and wet bias in summer and winter respectively. Over the whole Euro-CORDEX domain validation of the sub daily statistic for the precipitation frequency, intensity and diurnal cycle confirm the fitness for purposes of this new model version to run at such resolution for such extended region. A further CP configuration is also tested with two overlapping longitudinal stripe domains covering the Euro-CORDEX domain and the comparison is shown between the two CP simulations.

Quantifying design rainfall events at varying durations is crucial for assessing flood risk and mitigating losses and damages. Yet, in a changing climate, they are fundamental tool for a reliable design of water related infrastructures, such as flood retention reservoirs, spillways, and urban drainage systems. Usually, design rainfall is quantified where rain gauges are located, and regionalization methods are used to provide estimates in ungauged locations. During the last years, convection-permitting climate models (CPM) are receiving increasing attention because, thanks to their high spatial resolution (~3km) and ability of explicitly resolving atmospheric convection, they allow for better estimating precipitation spatial patterns and extreme rainfall at multiple durations compared to coarser models.In this work, we combine at-site rain gauge measurements with CPM simulations, within a non-asymptotic statistical framework for the analysis of extreme rainfall. We aim at quantifying the added value of the physics-based information provided by CPM simulations for the estimation of high quantiles of rainfall in ungauged locations. The performance of the new regionalization approach is compared with traditional interpolation methods (i.e. interpolation of distribution function parameters) using leave- one-out cross-validation as well as considering different rain gauge densities.Preliminary results show that the proposed methodology based on CPM simulation provides: i) similar performances compared to traditional gauge-based regionalization methods for high station density scenarios and ii) improved performances for low station density scenarios.

To improve sub-seasonal forecasts, different global initiatives generate continental convection-permitting simulations for resolution less than 10 kilometres for multiple decades. These simulations, however, are based on land use maps with only single urban type. In this study, we explore how the density and height information of the urban canopy based on Local Climate Zones (LCZs) affect the dynamics among temperatures, precipitation and land use types for the 2022 summer heatwave in the Southwest UK. Four numerical experiments at a 3 km grid are run by switching off the parameterization of deep-convection in the Weather Research and Forecasting (WRF) models. These experiments are based on (i) the no urban scenario, (ii) the default MODIS land use scheme, (iii) the building environment parameterization (BEP), and (iv) the building energy model (BEM).Results show that the cold advection over the UK led to downward motion according to a Q-vector analysis. The regional downward motion caused the formation of a heat dome. It is against the hypothesis that the 2022 summer heatwave was due to the hot circulation from Spain and equatorial Africa. Even though four land use schemes have similar simulated cold advection across the UK, our findings show that land use types affected water recycling due to local convection differently. These differences were related to the strength of rainstorms at the dissipating heatwave stage. Our results suggest that urban areas were more likely to have more persistent heatwaves since the intensity of rainstorms was affected by the lower local water recycling. This advanced understanding of the UK heatwave mechanism based on regional advection conditions and local convection processes will guide us on how to improve our sub-seasonal forecast in the urban area.

Urban areas will not be spared from the effect of climate change and will face more and more extreme weather events (e.g., heatwaves and floods). Such changes already cause severe environmental issues, economics damages, and many casualties, especially in cities where most activities and populations are concentrated. Evaluating the impacts of future extreme events on urban areas is a major challenge to prepare the adaptation.Urban areas are very complex systems that require specific modeling tools. The latest advances in regional climate modeling allow simulations to be performed over longer time periods with finer horizontal resolutions of up to few kilometers. The scientific community emphasizes the considerable improvements in using Convection-Permitting Models (CPM), especially for the representation of small-scale phenomena. Also, CPMs offer an interesting modeling framework for studying the interaction between regional climate and urban effects (especially urban heat island) and city-scale impacts through the explicit coupling of the atmospheric climate model with a dedicated urban surface model.In this study, the CNRM-AROME CPM, coupled with the Town Energy Balance (TEB) urban-canopy model, is used at 2.5-km horizontal resolution. Climate simulations were performed on an extended France domain (northwestern Europe) as part of the EUropean Climate Prediction system (EUCP) project over an historical period (1986-2005) and two future periods (mid-term, 2041-2050 and long-term, 2080-2099) using the RCP8.5 emission scenario. Here, scientific objectives are (1) to evaluate the urban heat island evolution for some metropolitan French cities, and (2) to quantify the evolution of specific meteorological hazards on cities and population. With this aim, we selected indicators related to heatwaves (based on Ouzeau et al. (2016) methodology) and heavy precipitation event, considered as some of the most relevant extreme meteorological events. These indicators were tested and evaluated on the evaluation simulation, and then analyzed in a changing climate to quantify the impacts on the cities. The multi-city approach makes it possible to investigate the variability that can exist between cities depending on their geographical and climatic contexts.

Understanding the impact of orography on the probability distribution of extreme precipitation at short (i.e., sub-daily) temporal scales, as well as on extreme-rainfall causative processes, is critical for managing risk from rainfall-triggered natural hazards in mountainous regions. High-resolution convection-permitting models (CPMs) are crucial for this type of analysis since they better represent convective processes key to short-duration extremes. Here, we assess the ability of multi-model CPM ensemble CORDEX-FPS to represent the upper tail of sub-daily precipitation in a complex-orography region in the Eastern Italian Alps. In this area, different orographic impacts on sub-daily precipitation upper tail were reported at different event durations, and significant temporal trends in precipitation intensity were reported during the last few decades, making it a challenging and interesting test case for CPM simulations. An ensemble of six CPMs with a horizontal grid spacing of ∼2.2 km, driven by ERA-Interim reanalysis, are analysed and evaluated against ∼180 rain gauges. Since CPM simulations are too short (10 years) for analysing extremes using conventional methods, we use a non-asymptotic statistical approach (Simplified Metastatistical Extreme Value, SMEV), which was proven to provide reliable results even using short time records. We explore how the model spread vary with elevation and the ability of the multi-model mean to reproduce the distribution parameters and the extreme quantiles up to 100-year return period at different elevations.

NOAA is collaborating with the US weather and climate science community to develop the next generation fully coupled earth system modeling capability for both research and operational forecast applications across different temporal and spatial scales. In this presentation we explore the possibility of running the UFS at convection-permitting resolution for global medium-range weather forecasting. A few sensitivity experiments were performed at a global uniform 3-km resolution with and without parameterized convection. Results were compared with the 13-km control experiments to investigate the impact of model resolution and convection parameterization on precipitation and cloud-radiation interaction. Aerosol indirect effect on clouds is also tested and evaluated within this framework to understand its sensitivity to model resolution and parameterized convection. Aerosol indirect effect occurs when aerosols act as cloud condensation nuclei and ice nuclei within clouds and consequently alter cloud radiative properties and cloud lifetime. Using the Thompson double-momentum microphysics scheme, the number concentrations of water friendly aerosol and ice friendly aerosol are either diagnosed from the MERRA2 aerosol climatology or predicted and advected with source and sink terms derived from the climatology. The relations between clouds, radiation and precipitation with and without the presence of aerosol indirect effects are analyzed for simulations made at both the control 13-km and experimental 3-km UFS model resolutions.