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In this research, the Coupled-Ocean-Atmosphere-Wave-Sediment Transport (COAWST) Model was utilized to study the summer climate over eastern China and its adjacent ocean from 2009 to 2018. The COAWST model, equipped with a convection-permitting resolution of approximately 4 km for both atmosphere and ocean model, effectively replicated the patterns of precipitation for both land and ocean, including sub-daily extreme precipitation, and the diurnal cycle. The COAWST model offers accurate simulations of the land-sea contrast in terms of the diurnal cycle of precipitation, showing the peaks of rainfall over land and sea in the afternoon and morning respectively. The model exhibited higher skill in extreme precipitation intensity over the ocean, while it was more skillful in wet frequency over the land. Overestimation of land precipitation may be due to the combined effects of higher wind speeds (~ 0.6 m/s higher over the ocean) from the atmospheric model and the elevated sea surface temperatures (about 0.8 °C warmer) from the ocean model, which may have influenced sea surface evaporation, increased latent heat release, and consequently increased precipitation. The significant topographical effects at the convective permitting resolution may have intensified land precipitation. [ABSTRACT FROM AUTHOR]

Mesoscale convective systems (MCSs) are complex meteorological phenomena that significantly influence precipitation and weather patterns globally. While extensive research on MCSs has been conducted in various parts of the world, South America, home to some of the most intense MCSs and storms, remains a relatively understudied region. This study addresses this knowledge gap by investigating observed MCSs and their representation in a 20-year 4 km grid spacing simulation using the Weather Research and Forecasting model across different subregions of South America. MCS characteristics, such as size, duration, and maximum precipitation, are found to be well-represented by the model, although there is a tendency to overestimate maximum precipitation. Additionally, this research explores the impact of the El Niño Southern Oscillation (ENSO) on MCS occurrence in South America. The Southeast South America tends to experience more MCS occurrences during El Niño events, while the North–South America exhibits the opposite pattern. However, the study also reveals nuanced deviations from expected correlations during specific ENSO events, highlighting the complex relationship between ENSO and MCS behavior. These findings contribute to advancing our comprehension of mesoscale convective processes in South America and set the stage for further investigations that will focus on climate change impacts on the region. [ABSTRACT FROM AUTHOR]

The Clausius–Clapeyron (CC) scaling, which indicates a roughly 7% increase in saturated water vapor per 1 °C increase in temperature, can serve as a strong constraint linking the intensity of precipitation extremes and local temperature. However, the relationship between precipitation extreme and local temperature (referred to as the PE-T relationship) does not always follow the CC scaling and is highly dependent on climate regimes. In this study, we investigated the impacts of different moisture processes and precipitation types on the PE-T relationship over eastern China during the summertime based on convection-permitting model simulations. Consistent with observations, the simulated intensity of precipitation extremes increases with temperature at a rate close to CC (double-CC) scaling below (above) 20 °C. When the temperature exceeds 25 °C, precipitation intensity starts to drop. Precipitation extremes are mainly contributed by the stratiform, MCS (i.e., mesoscale convective system) convective, and non-MCS convective precipitation at low (< 20 °C), medium (20–25 °C), and high (> 25 °C) temperatures, respectively, suggesting that the double-CC scaling occurs when convective types become dominant, while the negative scaling at high temperatures is attributed to the reduced horizontal scale of convection. Corresponding to the reduced intensity of precipitation at high temperatures, there are stronger divergence and subsidence in the low-level atmosphere, which is probably caused by the net cooling associated with the enhanced melting and evaporation of falling hydrometeors due to the lower relative humidity in the low-level atmosphere. Overall, our findings contribute to a deeper understanding of the temperature dependence of precipitation extremes in eastern China. [ABSTRACT FROM AUTHOR]

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

We present a new approach to identify severe hailstorms in a convection-permitting climate model, and build a climatology of severe hail potential in Europe using an ingredients-based approach based on a 20-year long hindcast simulation. Severe hail in Europe occurs mostly in southern regions (up to 40 times a year per 10,000 km2 around Northern Italy), and from May to August. It peaks from afternoon to evening hours on land, whilst sea areas are prone to hail at any time of the day. The Mediterranean Sea experiences severe hailstorms mostly in autumn: the central Mediterranean has the highest frequency among all regions studied, and may be considered as an unknown alley for hailstorms in Europe. Results derived from the high-resolution model are in very good agreement with existing hail climatologies constructed from observations, including the fine scale spatial variation. We conclude that our approach provides a reliable proxy for studying future changes in severe hail in convection-permitting simulations. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

We investigated positive temperature (warm) and negative precipitation (dry) biases in convection-permitting model (CPM) simulations for Europe (2.2 km grid spacing) that were considerably larger than in equivalent regional climate model (RCM) simulations (12 km grid spacing). We found that improvements in dry biases could be made by (1) using a more complex runoff scheme which takes into account topography and groundwater, (2) delaying the onset of water stress in vegetation to enhance transpiration, (3) changing the microphysics scheme to CASIM (Cloud AeroSol Interacting Microphysics) which also decreases heavy rainfall and increases light rainfall. Increasing soil moisture to the critical point can remove dry precipitation biases in southern Europe but not in northern areas, indicating that soil moisture limitation is a key contributor to precipitation biases in the south only. Instead, in the north, changing the cloud scheme of the model has more impact on precipitation biases. We found that the more intense and intermittent nature of rainfall in the CPM, which is more realistic leads to different canopy interception compared to the RCM. This can impact canopy evaporation, evapotranspiration and feed back on precipitation. Increasing rainfall storage in the canopy only leads to small improvements in warm biases, since it still fills rapidly with intense CPM rainfall, suggesting the need for an additional moisture store via improved groundwater modelling or surface pooling. Overall, this work highlights the challenge of correctly capturing land surface feedbacks in CPMs, which play an important role in future climate projections in some regions. [ABSTRACT FROM AUTHOR]

Meteorological processes over islands with complex orography could be better simulated by Convection Permitting Regional Climate Models (CP-RCMs) thanks to an improved representation of the orography, land–sea contrasts, the combination of coastal and orographic effects, and explicit deep convection. This paper evaluates the ability of the CP-RCM CNRM-AROME (2.5-km horizontal resolution) to simulate relevant meteorological characteristics of the Mediterranean island of Corsica for the 2000–2018 period. These hindcast simulations are compared to their driving Regional Climate Model (RCM) CNRM-ALADIN (12.5-km horizontal resolution and parameterised convection), weather stations for precipitation and wind and gridded precipitation datasets. The main benefits are found in the representation of (i) precipitation extremes resulting mainly from mesoscale convective systems affected by steep mountains during autumn and (ii) the formation of convection through thermally induced diurnal circulations and their interaction with the orography during summer. Simulations of hourly precipitation extremes, the diurnal cycle of precipitation, the distribution of precipitation intensities, the duration of precipitation events, and sea breezes are all improved in the 2.5-km simulations with respect to the RCM, confirming an added value. However, existing differences between model simulations and observations are difficult to explain as the main biases are related to the availability and quality of observations, particularly at high elevations. Overall, better results from the 2.5-km resolution, increase our confidence in CP-RCMs to investigate future climate projections for Corsica and islands with complex terrain. [ABSTRACT FROM AUTHOR]

We present the first evaluation of the wind field from the ensemble of kilometer-scale simulations from the CORDEX-Flagship Pilot Study on convection, 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 circulations. These enable a reliable view of climate characteristics of the wind field, especially in coastal regions and over complex terrain, such as the Adriatic region. 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 m 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 more 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. [ABSTRACT FROM AUTHOR]

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

Since a decade, convection-permitting regional climate models (CPRCM) have emerged showing promising results, especially in improving the simulation of precipitation extremes. In this article, the CPRCM CNRM-AROME developed at the Centre National de Recherches Météorologiques (CNRM) since a few years is described and evaluated using a 2.5-km 19-year long hindcast simulation over a large northwestern European domain using different observations through an added-value analysis in which a comparison with its driving 12-km RCM CNRM-ALADIN is performed. The evaluation is challenging due to the lack of high-quality observations at both high temporal and spatial resolutions. Thus, a high spatio-temporal observed gridded precipitation dataset was built from the collection of seven national datasets that helped the identification of added value in CNRM-AROME. The evaluation is based on a series of standard climatic features that include long-term means and mean annual cycles of precipitation and near-surface temperature where CNRM-AROME shows little improvements compared to CNRM-ALADIN. Additional indicators such as the summer diurnal cycle and indices of extreme precipitation show, on the contrary, a more realistic behaviour of the CNRM-AROME model. Moreover, the analysis of snow cover shows a clear added-value in the CNRM-AROME simulation, principally due to the improved description of the orography with the CPRCM high resolution. Additional analyses include the evaluation of incoming shortwave radiation, and cloud cover using satellite estimates. Overall, despite some systematic biases, the evaluation indicates that CNRM-AROME is a suitable CPRCM that is superior in many aspects to the RCM CNRM-ALADIN. [ABSTRACT FROM AUTHOR]

We present the first convection-permitting regional climate model (CPRCM) simulations at 4.5 km horizontal resolution for South America at near-continental scale, including full details of the experimental setup and results from the reanalysis-driven hindcast and climate model-driven present-day simulations. We use a range of satellite and ground-based observations to evaluate the CPRCM simulations covering the period 1998–2007 comparing the CPRCM output with lower resolution regional and global climate model configurations for key regions of Brazil. We find that using the convection-permitting model at high resolution leads to large improvements in the representation of precipitation, specifically in simulating its diurnal cycle, frequency, and sub-daily intensity distribution (i.e. the proportion of heavy and light precipitation). We tentatively conclude that there are also improvements in the spatial structure of precipitation. We see higher precipitation intensity and extremes over Amazonia in the CPRCMs compared with observations, though more sub-daily observational data from meteorological stations are required to conclusively determine whether the CPRCMs add value in this regard. For annual mean precipitation and mean, maximum and minimum near surface temperatures, it is not clear that the CPRCMs add value compared with coarser-resolution models with parameterised convection. We also find large changes in the contribution to evapotranspiration from canopy evaporation compared to soil evaporation and transpiration compared with the RCM. This is likely to be related to the shift in precipitation intensity distribution of the CPRCMs compared to the RCM and its impact on the hydrological requires further investigation. [ABSTRACT FROM AUTHOR]

The development of the Singapore regional climate model (SINGV-RCM) is documented in this study. The model's skill in predicting mean and extreme rainfall over the Maritime Continent at 8 km and 2 km grid resolution is assessed using observed rainfall. The model's sensitivity to vertical grid and convection parametrization is also evaluated. Results demonstrate the added value of downscaling to 8 and 2 km. The spatial and temporal characteristic of the diurnal rainfall is shown to be in good agreement with the observation. The model also demonstrates skill in capturing extreme rainfall. In general, the rainfall in the 8 km and 2 km simulations are quite similar, when regrided to a coarser resolution. Even then, the convection-permitting simulation at 2 km is found to add value over the 8 km simulation, particularly in capturing the higher rainfall thresholds. Mean biases over the ocean is found to be larger than that over the land, which suggests the need to further tune SINGV-RCM for long climate simulations. [ABSTRACT FROM AUTHOR]

Global climate models project a mean drying of the North American Monsoon (NAM) at grid spacings where convection is not explicitly resolved. We investigate the response of the NAM to climate warming at convection-permitting scales, utilizing output from a series of 13-year continental scale regional climate model runs performed at 4-km grid spacing. These include a control run forced by reanalysis and a pseudo global warming run that applies a mean perturbation to the boundaries derived from end-of-century changes projected by an ensemble of global climate models. NAM precipitation (June–September) shows averaged increases of 38.6% for portions of Arizona and western New Mexico. Over central Mexico, daily mean precipitation shows increases of 8.13%. Increases in rainfall amount are primarily associated with mean increases in precipitation intensity that overcome reductions in precipitation frequency. This increase in precipitation intensity is attributed to higher precipitable water concentrations, enhanced near-surface horizontal moisture fluxes off the Gulf of California, and stronger moisture flux convergence along the mountain peaks. Results from an offline semi-Lagrangian tracer model reveal that moisture contributions from the local land surface are significant in the control climate and produce proportionally less of the total precipitation in the warmed climate. Instead, contributions from nearby oceanic sources, notably the Gulf of California and Gulf of Mexico, increase. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

The convection-permitting regional climate model CNRM-AROME was applied on a spatial domain restricted to the northern half of France for analyzing its performances in simulating the urban climate of Paris region, and its potential added value compared to the regional climate model CNRM-ALADIN. In addition to its fine horizontal resolution (2.5 km compared to 12.5 km for CNRM-ALADIN), CNRM-AROME has the advantage of integrating the urban canopy model TEB into its land-surface modeling system. A hindcast simulation was performed for the past period 2000–2017, following an evaluation configuration for which CNRM-AROME was driven by CNRM-ALADIN, driven itself by the ERA-Interim reanalyses. Long-term gridded observations with kilometric resolution allowed a fine spatial scale evaluation of the atmospheric variables simulated by both models. They showed in particular a significant overestimation of spring precipitation, but an improvement of summer precipitation in CNRM-AROME compared to CNRM-ALADIN. Above all, thanks to its horizontal resolution and the use of a dedicated urban model, CNRM-AROME was shown to offer significant added value for the simulation of urban heat islands, for the mapping of heat-warming areas, and for representing the effects of the city on precipitation. It is a promising tool to diagnose climatic and impact indicators at the city scale, and their evolution in a changing climate. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

The Tibetan Plateau (TP) is often referred to as 'the Third Pole' and plays an essential role in the global climate. However, it remains challenging for most global and regional models to realistically simulate the characteristics of climate over the TP. In this study, two Weather Research and Forecasting model (WRF) experiments using spectral nudging with gray-zone (GZ9) and convection-permitting (CP3) resolution are conducted for summers from 2009 to 2018. The surface air temperature (T2m) and precipitation from the two simulations and the global reanalysis ERA5 are evaluated against in-situ observations. The results show that ERA5 has a general cold bias over southern TP, especially in maximum T2m (Tmax), and wet bias over whole TP. Both experiments can successfully capture the spatial pattern and daily variation of T2m and precipitation, though cold bias for temperature and dry bias for precipitation exist especially over the regions south of 35° N. Compared with ERA5, the added value of the two WRF experiments is mainly reflected in the reduced cold bias especially for Tmax with more improvement found in CP3 and the reduced wet bias. However, the ability of the convection-permitting WRF experiment in improving the simulation of precipitation seems limited when compared to the gray-zone WRF experiment, which may be related to the biases in physical parameterization and lack of representativeness of station observation. Further investigation into surface radiation budget reveals that the underestimation of net shortwave radiation contributes a lot to the cold bias of T2m over the southeastern TP in GZ9 which is improved in CP3. Compared with GZ9, CP3 shows that larger specific humidity at low-level (mid-high level) coexists with more precipitation (clouds) over the southern TP. This improvement is achieved by better depiction of topographic details, underlying surface and atmospheric processes, land–atmosphere interactions and so on, leading to stronger northward water vapor transport (WVT) in CP3, providing more water vapor for precipitation at surface and much wetter condition in the mid-high level. [ABSTRACT FROM AUTHOR]

This study presents a comprehensive assessment of a dynamical downscaling of ERA5 Reanalysis recently performed over Italy through the COSMO-CLM model at a convection-permitting scale (0.02°) over the period 1989–2020. Results are analysed against several independent observational datasets and reanalysis products. The capability of the downscaling to realistically represent the climatology for 2 m temperature and precipitation is analysed over the whole peninsula and subdomains. Hourly precipitation patterns, orography effects, and urban climate dynamics are also investigated, highlighting the weaknesses and strengths of the convection-permitting model. In particular, gains in performances are achieved in mountainous areas where the climate characteristics are correctly represented, as are the hourly precipitation characteristics. Losses in performances occur in coastal and flat areas of the Italian peninsula, where the convection-permitting model performance does not seem to be satisfactory, as opposed to complex orographic areas. The adopted urban parameterisation is demonstrated to simulate heat detection for two Italian cities: Rome and Milan. Finally, a subset of extreme climate indicators is evaluated, finding: (i) a region-dependent response, (ii) a notable performance of the convection-permitting model over mountainous areas and (iii) discrepancies in the South, Central and Insular subdomains. Climate indicators detect extreme events at a detailed scale, becoming an important tool for turning climate data into information. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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

Freezing precipitation has major consequences for ground and air transportation, the health of citizens, and power networks. Previous studies using coarse resolution climate models have shown a northward migration of freezing rain in the future. Increased model resolution can better define local topography leading to improved representation of conditions that are favorable for freezing rain. The goal of this study is to examine the climatology and characteristics of future freezing rain events using very-high resolution climate simulations. Historical and pseudo-global warming simulations with a 4-km horizontal grid length were used and compared with available observations. Simulations revealed a northerly shift of freezing rain occurrence, and an increase in the winter. Freezing rain was still shown to occur in the Saint-Lawrence River Valley in a warmer climate, primarily due to stronger wind channeling. Up to 50% of the future freezing rain events also occurred in present day climate within 12 h of each other. In northern Maine, they are typically shorter than 6 h in current climate and longer than 6 h in warmer conditions due to the onset of precipitation during low-pressure systems occurrences. The occurrence of freezing rain also locally increases slightly north of Québec City in a warmer climate because of freezing rain that is produced by warm rain processes. Overall, the study shows that high-resolution regional climate simulations are needed to study freezing rain events in warmer climate conditions, because high horizontal resolutions better define small-scale topographic features and local physical mechanisms that have an influence on these events. [ABSTRACT FROM AUTHOR]

The parameterization of deep convection is one of the primary sources of uncertainties in regional climate simulations. Due to computational constraints, long-term kilometer-scale simulations with explicit deep convection have been limited, especially over East Asia. We here conduct a pair of 10-years (2001–2010) reference simulations, one convection-parameterizing simulation at 12 km (0.11 ∘ ) resolution covering the CORDEX East Asia domain, and one 4.4-km (0.04 ∘ ) convection-permitting simulation over a subdomain. The two simulations are driven by the ERA5 reanalysis and the coarser-resolution simulation, respectively. The 4.4-km convection-permitting simulation noticeably improves the representation of the top-of-atmosphere outgoing longwave and shortwave radiation as well as precipitation intensity. In addition, sensitivity simulations are performed with perturbed sulfate and black carbon aerosols, considering the direct and semi-direct aerosol radiative effects. For the simulations with sulfate aerosol perturbations, the cloud radiative effect partly offsets the aerosol radiative effects. Decreasing sulfate aerosols leads to low-level warming, destabilizing the atmospheric stratification and thereby increasing mean precipitation and the frequency of wet days. Increasing sulfate aerosols leads to an approximately opposite response. For the simulations with black carbon aerosol perturbations, there is some near-surface warming for both increases and decreases in aerosol concentration. Also, there are significant changes in cloud cover, but changes in precipitation are comparatively weak. While for sulfate aerosol perturbations the response is approximately linear (in the sense that positive and negative perturbations yield approximately opposite effects), the response to black carbon aerosol perturbations is more complex and shows some nonlinearity, regardless of the treatment of deep convection in the simulations. We present a simple interpretation for this surprising result. [ABSTRACT FROM AUTHOR]

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

The 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. [ABSTRACT FROM AUTHOR]

In this study, we have assessed the added value on the spatio-temporal distribution of the precipitation of convection-permitting simulation (3 km) compared to the parent coarse-scale parameterized convection simulation (20 km) with the high-resolution observational datasets i.e., SPREAD (5 km) and IBERIA01 (10 km) over the Iberian Peninsula (IP) in all four seasons during 2000–2009. Both simulations are evaluation runs based on ERA-Interim reanalysis and performed with the RegIPSL regional earth system model in the frame of the European Climate Prediction system (EUCP) H2020 project and COordinated Regional climate Downscaling Experiment (CORDEX). We have not found significant improvement in the convection-permitting simulation compared to the parent coarse-scale simulation for the seasonal mean precipitation of the IP except the spatial variation over mountainous peaks. The kilometer-scale simulation significantly underestimates the observed seasonal mean precipitation over the western parts of the IP compared to the coarse-scale simulation, which may be attributed to a change of local dynamics in the kilometer-scale simulation with a weakening and southward shift of the moisture-laden westerly winds approaching from the Atlantic Ocean over the IP (i.e., a decline in atmospheric moisture transport from the Atlantic Ocean towards the IP). However, the added value of kilometer-scale simulation over the driving coarse-scale simulation is obtained for various indices; in the representation of the spatio-temporal distribution of the wet-day precipitation frequency and intensity, and the extreme/heavy precipitation events for each season at both resolutions i.e., downscaled and upscaled. It has also been noted that the spatio-temporal distribution of precipitation for all metrics used varies between the two observational datasets for all seasons. [ABSTRACT FROM AUTHOR]

This study describes the implementation and performances of a weather hindcast obtained by dynamically downscaling the ERA5 data across the period 1979–2019. The limited-area models used to perform the hindcast are BOLAM (with a grid spacing of 7 km over the Mediterranean domain) and MOLOCH (with a grid spacing of 2.5 km over Italy). BOLAM is used to provide initial and boundary conditions to the inner grid of the MOLOCH model, which is set in a convection-permitting configuration. The performances of such limited-area, high-resolution and long-term hindcast are evaluated comparing modelled precipitation data against two high-resolution gridded observational datasets. Any potential added-value of the BOLAM/MOLOCH hindcast is assessed with respect to ERA5-Land data, which are used as benchmark. Results demonstrate that the MOLOCH hindcast, compared to observations, provides a lower bias than ERA5-Land as regards both the mean annual rainfall (- 1.3% vs 8.7%) and the 90th percentile of summer daily precipitation, although a wet bias is found in southern Italy (bias ≃ 17.1%). Improvements are also gained in the simulation of the 90th percentile of hourly precipitations both in winter and, to a minor extent, in summer. The diurnal cycle of summer precipitations is found to be better reconstructed in the Alps than in the hilly areas of southern Italy. This study also presents the rainfall peaks obtained in the simulation of two well-known severe precipitation events that caused floods and damages in north-western Italy in 1994 and 2011. Finally, it is discussed how the demonstrated reliability of the BOLAM and MOLOCH models associated to the documented low computational cost, promote their use as a valuable tool for downscaling not only reanalyses but also climate projections. [ABSTRACT FROM AUTHOR]

Precipitation is an essential contributor to the water resources over the Tibetan Plateau (TP). However, realistically simulating precipitation over the TP is still a major challenge for most models. In order to better depict the precipitation spatial and temporal distributions over the TP, a 4-km-resolution convection-permitting modelling (CPM) and a 28-km-resolution dynamical downscaling modelling (DDM) were applied to a summer season (from 1st June to 31st August 2014). The simulations and four other gridded datasets (APHRODITE, GPM, ERA-Interim and ERA5) were evaluated against station observations, in terms of monthly and seasonal mean precipitation amount, frequency, intensity and diurnal cycle. We found that the six datasets show considerable differences in precipitation amount, and these differences are mainly caused by the frequency. DDM shows substantial advantages in depicting precipitation over the reanalyses, in which significant overestimation of precipitation and an overly early diurnal peak dominate. However, the excessive daytime convective precipitation and stronger nocturnal precipitation still exit in DDM, which are mainly related to its strong convective available potential energy (CAPE) and nocturnal water vapor transport, respectively. The inaccurate early peak in DDM (1600 local solar time) is found to be related to the stronger moist convective instability at most stations and areas over the TP. Compared to DDM, CPM reduces the overestimation of precipitation over the northern and eastern TP and better captures the observed diurnal cycle. Moreover, CPM adds the most value in depicting the diurnal cycle in June, with the late afternoon precipitation maximum. [ABSTRACT FROM AUTHOR]

Extra-tropical windstorms are one of the costliest natural hazards affecting Europe, and windstorms that develop a sting jet are extremely damaging. A sting jet is a mesoscale core of very high wind speeds that occurs in Shapiro–Keyser type cyclones, and high-resolution models are required to adequately model sting jets. Here, we develop a low-cost methodology to automatically detect sting jets, using the characteristic warm seclusion of Shapiro–Keyser cyclones and the slantwise descent of high wind speeds, within pan-European 2.2 km convection-permitting climate model (CPM) simulations. The representation of wind gusts is improved with respect to ERA-Interim reanalysis data compared to observations; this is linked to better representation of cold conveyor belts and sting jets in the CPM. Our analysis indicates that Shapiro–Keyser cyclones, and those that develop sting jets, are the most damaging windstorms in present and future climates. The frequency of extreme windstorms is projected to increase by 2100 and a large contribution comes from sting jet storms. Furthermore, extreme wind speeds and their future changes are underestimated in the global climate model (GCM) compared to the CPM. We conclude that the CPM adds value in the representation of extreme winds and surface wind gusts and can provide improved input for impact models compared to coarser resolution models. [ABSTRACT FROM AUTHOR]

Two regional climate simulation experiments (spectral nudging and re-initialization) at convection-permitting scale are conducted using the WRF model driven by the 4th generation Global Reanalysis data (ERA5) from European Centre for Medium-Range Weather Forecasts over the Tibetan Plateau (TP). The surface air temperature (T2m) and the precipitation in summer during 2016–2018 are evaluated against the in-situ station observations and the Global Satellite Mapping of Precipitation (GSMaP) dataset. The results show that both experiments as well as ERA5 can successfully capture the spatial distribution and the daily variation of T2m and precipitation, with reasonable cold bias for temperature and dry bias for precipitation when compared with the station observations. In addition, the diurnal cycle of precipitation is investigated, indicating that both experiments tend to simulate the afternoon precipitation peak in advance and postpone the night precipitation peak. The precipitation bias is reduced by using the spectral nudging technique, especially at night and early morning. Both WRF experiments outperform ERA5 in reproducing the diurnal cycle of precipitation amount. Possible causes for the differences between the two experiments are also analyzed. In the re-initialization experiment, the daytime net shortwave radiation contributes a lot to the cold biases of Tmax, and the stronger vertically integrated moisture flux convergence leads to more precipitation compared with the spectral nudging experiment over the central and southeastern TP. These results can provide valuable guidance for further fine-scale simulation studies over the TP. [ABSTRACT FROM AUTHOR]

Mesoscale convective systems (MCSs) are important warm-season precipitation systems in eastern China. However, our knowledge of their climatology and capability in their simulation is still insufficient. This paper examines their characteristics over the 2008–2017 warm seasons using convection-permitting climate simulations (CPCSs) with a 3-km grid spacing that explicitly resolves MCSs, as well as a high-resolution gauge-satellite merged precipitation product. An object-based tracking algorithm is applied to identify MCSs. Results indicate that the MCS genesis and occurrence are closely related to the progression of the East Asian monsoon and are modulated by the underlying topography. On average, about 243 MCSs are observed each season and contribute 19% and 47% to total and extreme warm-season precipitation. The climatological attributes and variabilities are reasonably reproduced in the CPCS. The major model deficiencies are excessive small MCS occurrence and overmuch MCS rainfall, consequently overestimating the precipitation contributions, whereas observational uncertainties may play a role too. Both the observed and simulated MCS precipitation feature a nocturnal or morning maximum and an eastward delayed diurnal peak east of the Tibetan Plateau, in contrast to the dominant afternoon peak of non-MCS precipitation. The favorable comparison with observations demonstrates the capability of CPCSs in simulating MCSs in the Asian monsoon climate, and its usefulness in projecting the future changes of MCSs under global warming. The finding that non-MCS precipitation is responsible for the high biased afternoon precipitation provides helpful guidance for further model improvement. [ABSTRACT FROM AUTHOR]

Lightning climate change projections show large uncertainties caused by limited empirical knowledge and strong assumptions inherent to coarse-grid climate modeling. This study addresses the latter issue by implementing and applying the lightning potential index parameterization (LPI) into a fine-grid convection-permitting regional climate model (CPM). This setup takes advantage of the explicit representation of deep convection in CPMs and allows for process-oriented LPI inputs such as vertical velocity within convective cells and coexistence of microphysical hydrometeor types, which are known to contribute to charge separation mechanisms. The LPI output is compared to output from a simpler flash rate parameterization, namely the CAPE × PREC parameterization, applied in a non-CPM on a coarser grid. The LPI's implementation into the regional climate model COSMO-CLM successfully reproduces the observed lightning climatology, including its latitudinal gradient, its daily and hourly probability distributions, and its diurnal and annual cycles. Besides, the simulated temperature dependence of lightning reflects the observed dependency. The LPI outperforms the CAPE × PREC parameterization in all applied diagnostics. Based on this satisfactory evaluation, we used the LPI to a climate change projection under the RCP8.5 scenario. For the domain under investigation centered over Germany, the LPI projects a decrease of 4.8 % in flash rate by the end of the century, in opposition to a projected increase of 17.4 % as projected using the CAPE × PREC parameterization. The future decrease of LPI occurs mostly during the summer afternoons and is related to (i) a change in convection occurrence and (ii) changes in the microphysical mixing. The two parameterizations differ because of different convection occurrences in the CPM and non-CPM and because of changes in the microphysical mixing, which is only represented in the LPI lightning parameterization. [ABSTRACT FROM AUTHOR]

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

Southeastern South America (SESA) stands out as a remarkable region of occurrence of deep convection. This is mainly due to the proximity of the Andes, which eventually determine their magnitude and intensity. In this work, we used a set of convection-permitting (4 km horizontal resolution) regional climate models to explore their ability to reproduce the synoptic forcings that trigger deep convection over La Plata basin. The study considered simulating three extreme convective precipitation events in two different timescales. On one hand, a short-term simulation initiated a few hours before the onset of each event, spanning 3–4 days. On the other hand, as regional climate modelling, a 6-month simulation that includes the three selected events. In contrast to parameterized convection, the convection-permitting resolutions not only intensified the events, but also modified the location of the maximum precipitation by modulating the low-level atmospheric circulation. Vertically integrated moisture flux convergence emerged as a noticeable footprint of deep moist convection, regardless of the model and timescale. The performance of the models in reproducing the observed precipitation was also quantitatively analyzed. The skill depends on the spatial scale. The results were case-dependent in the short-term simulations. However, an analysis over multiple events in the long-term simulations revealed that, in general, convection-permitting resolutions better capture the spatial distribution of the extreme precipitation in SESA. The study comprises the first multi-model ensemble of convection-permitting simulations over the region, a seed for a further analysis with a more complete ensemble to better understand the results presented here. [ABSTRACT FROM AUTHOR]

Numerical climate models have been upgraded by the improved description of terrestrial hydrological processes across different scales. The goal of this study is to explore the role of terrestrial hydrological processes on land–atmosphere interactions within the context of modeling uncertainties related to model physics parameterization. The models applied are the Weather Research and Forecasting (WRF) model and its coupled hydrological modeling system WRF-Hydro, which depicts the lateral terrestrial hydrological processes and further allows their feedback to the atmosphere. We conducted convection-permitting simulations (3 km) over the Heihe River Basin in Northwest China for the period 2008–2010, and particularly focused on its upper reach area of complex high mountains. In order to account for the modeling uncertainties associated with model physics parameterization, an ensemble of simulations is generated by varying the planetary boundary layer (PBL) schemes. We embedded the fully three-dimensional atmospheric water tagging method in both WRF and WRF-Hydro for quantifying the strength of land–atmosphere interactions. The impact of PBL parameterization on land–atmosphere interactions is evaluated through its direct effect on vertical mixing. Results suggest that enabled lateral terrestrial flow in WRF-Hydro distinctly increases soil moisture and evapotranspiration near the surface in the high mountains, thereby modifies the atmospheric condition regardless of the applied PBL scheme. The local precipitation recycling ratio in the study area increases from 1.52 to 1.9% due to the description of lateral terrestrial flow, and such positive feedback processes are irrespective of the modeling variability caused by PBL parameterizations. This study highlights the non-negligible contribution of lateral terrestrial flow to local precipitation recycling, indicating the potential of the fully coupled modeling in land–atmosphere interactions research. [ABSTRACT FROM AUTHOR]

Convection-permitting climate models have shown superior performance in simulating important aspects of the precipitation climate including extremes and also to give partly different climate change signals compared to coarser-scale models. Here, we present the first long-term (1998–2018) simulation with a regional convection-permitting climate model for Fenno-Scandinavia. We use the HARMONIE-Climate (HCLIM) model on two nested grids; one covering Europe at 12 km resolution (HCLIM12) using parameterized convection, and one covering Fenno-Scandinavia with 3 km resolution (HCLIM3) with explicit deep convection. HCLIM12 uses lateral boundaries from ERA-Interim reanalysis. Model results are evaluated against reanalysis and various observational data sets, some at high resolutions. HCLIM3 strongly improves the representation of precipitation compared to HCLIM12, most evident through reduced "drizzle" and increased occurrence of higher intensity events as well as improved timing and amplitude of the diurnal cycle. This is the case even though the model exhibits a cold bias in near-surface temperature, particularly for daily maximum temperatures in summer. Simulated winter precipitation is biased high, primarily over complex terrain. Considerable undercatchment in observations may partly explain the wet bias. Examining instead the relative occurrence of snowfall versus rain, which is sensitive to variance in topographic heights it is shown that HCLIM3 provides added value compared to HCLIM12 also for winter precipitation. These results, indicating clear benefits of convection-permitting models, are encouraging motivating further exploration of added value in this region, and provide a valuable basis for impact studies. [ABSTRACT FROM AUTHOR]

A recently launched project under the auspices of the World Climate Research Program's (WCRP) Coordinated Regional Downscaling Experiments Flagship Pilot Studies program (CORDEX-FPS) is presented. This initiative aims to build first-of-its-kind ensemble climate experiments of convection permitting models to investigate present and future convective processes and related extremes over Europe and the Mediterranean. In this manuscript the rationale, scientific aims and approaches are presented along with some preliminary results from the testing phase of the project. Three test cases were selected in order to obtain a first look at the ensemble performance. The test cases covered a summertime extreme precipitation event over Austria, a fall Foehn event over the Swiss Alps and an intensively documented fall event along the Mediterranean coast. The test cases were run in both "weather-like" (WL, initialized just before the event in question) and "climate" (CM, initialized 1 month before the event) modes. Ensembles of 18–21 members, representing six different modeling systems with different physics and modelling chain options, was generated for the test cases (27 modeling teams have committed to perform the longer climate simulations). Results indicate that, when run in WL mode, the ensemble captures all three events quite well with ensemble correlation skill scores of 0.67, 0.82 and 0.91. They suggest that the more the event is driven by large-scale conditions, the closer the agreement between the ensemble members. Even in climate mode the large-scale driven events over the Swiss Alps and the Mediterranean coasts are still captured (ensemble correlation skill scores of 0.90 and 0.62, respectively), but the inter-model spread increases as expected. In the case over Mediterranean the effects of local-scale interactions between flow and orography and land–ocean contrasts are readily apparent. However, there is a much larger, though not surprising, increase in the spread for the Austrian event, which was weakly forced by the large-scale flow. Though the ensemble correlation skill score is still quite high (0.80). The preliminary results illustrate both the promise and the challenges that convection permitting modeling faces and make a strong argument for an ensemble-based approach to investigating high impact convective processes. [ABSTRACT FROM AUTHOR]

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

In this study, the impact of different configurations of the Goddard radiation scheme on convection-permitting simulations (CPSs) of the West African monsoon (WAM) is investigated using the NASA-Unified WRF (NU-WRF). These CPSs had 3 km grid spacing to explicitly simulate the evolution of mesoscale convective systems (MCSs) and their interaction with radiative processes across the WAM domain and were able to reproduce realistic precipitation and energy budget fields when compared with satellite data, although low clouds were overestimated. Sensitivity experiments reveal that (1) lowering the radiation update frequency (i.e., longer radiation update time) increases precipitation and cloudiness over the WAM region by enhancing the monsoon circulation, (2) deactivation of precipitation radiative forcing suppresses cloudiness over the WAM region, and (3) aggregating radiation columns reduces low clouds over ocean and tropical West Africa. The changes in radiation configuration immediately modulate the radiative heating and low clouds over ocean. On the 2nd day of the simulations, patterns of latitudinal air temperature profiles were already similar to the patterns of monthly composites for all radiation sensitivity experiments. Low cloud maintenance within the WAM system is tightly connected with radiation processes; thus, proper coupling between microphysics and radiation processes must be established for each modeling framework. [ABSTRACT FROM AUTHOR]