CL2.4

Compared to standard regional climate models (RCMs), convection-permitting models (CPMs) provide an improved representation of sub-daily precipitation statistics and extremes thanks mainly to the possibility to switch off the deep convection parameterisation, a known source of model error and uncertainties. The more realistic representation of local processes in CPMs leads to a greater confidence in their projections of future changes in short-duration precipitation extremes.

The quantification of uncertainties on future changes at this resolution has been barely touched. Using the first-ever ensemble of CPMs run within the UK Climate Projections project, Fosser et al. (2020) found that the climate change signal for extreme summer precipitation may converge in CPMs in contrast to RCMs, thanks to a more realistic representation of the local storm dynamics.

Here we use the first multi-model CPMs ensemble over the greater Alpine region, run under the auspices of the World Climate Research Programme’s (WCRP) Coordinated Regional Downscaling Experiment Flagship Pilot Study on Convective phenomena at high resolution over Europe and the Mediterranean (Coppola et al. 2020). Several statistics are used to determine the uncertainties in the climate change signal trying to disentangle model uncertainties from natural variability. We found that the contribution of model to the total uncertainties is substantially reduced in CPMs compared to the driving models in summer. This is likely linked to the removal of the uncertainties associated with the convective parameterisation and to a more realistic representation of convective and local dynamical processes in the CPMs.

Fosser G, Kendon EJ, Stephenson D, Tucker S (2020) Convection‐Permitting Models Offer Promise of More Certain Extreme Rainfall Projections. Geophys Res Lett 47:0–2. doi: 10.1029/2020GL088151

Coppola, E., Sobolowski, S., Pichelli, E. et al.A first-of-its-kind multi-model convection permitting ensemble for investigating convective phenomena over Europe and the Mediterranean. Clim Dyn55, 3–34 (2020). https://doi.org/10.1007/s00382-018-4521-8

How to cite: Fosser, G., Adinolfi, M., Ban, N., Belušić, D., Caillaud, C., Cardoso, R. M., Coppola, E., Demory, M.-E., De Vries, H., Dobler, A., Feldmann, H., Gaetani, M., Görgen, K., Kendon, E. J., Lenderink, G., Pichelli, E., Schär, C., Soares, P. M. M., Somot, S., and Tölle, M. H.: Convection-permitting climate models Offer More Certain Extreme Rainfall Projections, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-7679, https://doi.org/10.5194/egusphere-egu22-7679, 2022.

Sub-daily precipitation extremes can have a huge impact on society as they cause hazards such as flooding, erosion and landslides. For example, the July floods in Germany, Belgium and nearby countries, were one of the costliest events in Europe, with insured losses up to USD 13 billion. Climate change is expected to intensify precipitation extremes as atmospheric water content increases by 6-7% per degree of warming, underscoring the need to predict  future hydrological hazards. Regional Climate Models (RCMs) typically run at a spatial resolution of 12-25 km, but they insufficiently describe the small-scale features of observed sub-daily precipitation extremes. The past decade, convection-permitting RCMs were developed which run at high resolution (1-4 km), and explicitly resolve deep convection. Confidence in future projections requires that RCMs adequately simulate the statistical features of observed sub-daily extreme precipitation and  also represent the physical processes associated with convective events. We propose a diagnostic framework for simulated 1h-24h rainfall extremes that summarizes the overall RCM performance. This includes the following metrics: the seasonal/diurnal cycle, temperature and humidity dependency, temporal scaling, and spatiotemporal clustering. A substantial part of the work is devoted to the statistical modelling of the metrics with Extreme Value Theory (EVT). We illustrate the evaluation tool with convection-permitting RCM simulations over Belgium against high-frequency observations and assess the benefit of the convection-permitting RCMs with respect to coarser scales. Finally, we give some guidelines for bias correction of simulated precipitation extremes.

How to cite: Van de Vyver, H., Van Schaeybroeck, B., De Troch, R., De Cruz, L., Hamdi, R., Villanueva-Birriel, C., Marbaix, P., van Ypersele, J.-P., Wouters, H., Vanden Broucke, S., van Lipzig, N., Doutreloup, S., Wyard, C., Scholzen, C., Fettweis, X., Caluwaerts, S., and Termonia, P.: Evaluation and Bias Correction of Simulated Sub-daily Rainfall Extremes by Regional Climate Models, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-1669, https://doi.org/10.5194/egusphere-egu22-1669, 2022.

Despite continued progress and a growing literature assessing regional climate change worldwide, modeling and assessing climate characteristics in mountainous regions remain challenging. Yet the stakes are high in these regions. As significant changes affect glaciers and snowpack, having
cascading effects on regional hydrology, quantifying them as accurately as possible is necessary for societal actors to adapt and reduce the growing climate risks.

Convection permitting climate modelling is a promising avenue for climate change research and services, particularly in mountainous regions. Work is required to evaluate the results of high resolution simulations against relevant reference dataset and put them in a broader context against coarser resolution modeling frameworks.

Our research assesses the potentials and limitations of high resolution climate models to represent past and future changes in snow conditions in the European Alps.

Here, we present an insight from the convection permitting climate model (CPRCM) CNRM-AROME ran at 2.5 km horizontal resolution over a large pan-Alpine domain in the European Alps, using either the ERA-Interim or CNRM-CM5 output as boundary conditions.

Annual and seasonal characteristics of four variables (2m temperature, total precipitation, solid fraction of precipitation and snow depths) are compared over the French Alps with the local reanalysis S2M, and raw or adjusted, with the ADAMONT method, simulations of the regional
climate model CNRM-ALADIN driven either by the ERA-Interim reanalysis or the CNRM-CM5 global climate model.

The study generally highlights similar differences in past and future climate between the datasets, as well as obstacles to the use of some CNRM-AROME outputs as they stand. These consist of excessive accumulation of snow on the ground above 1800 m a.s.l., as well as lower temperature
values at same elevations than the S2M reanalysis and the ADAMONT-adjusted outputs.

Nevertheless, clear advantages of CNRM-AROME simulations compared to raw CNRM-ALADIN outputs appear, concerning the temperature fields, the better representation of precipitations, as well as the spatial variability closer to the reference data.

How to cite: Monteiro, D., Caillaud, C., Samacoĩts, R., Lafaysse, M., and Morin, S.: Potential and limitations of convection-permitting CNRM-AROME climate modelling in the French Alps, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-4886, https://doi.org/10.5194/egusphere-egu22-4886, 2022.

Convection permitting climate models (CPMs) are nowadays increasingly used in climate change assessment. These models have shown to have vastly improved convective rainfall statistics compared to parameterized regional climate models (RCMs). Here, we analyse hourly rainfall extremes within the framework of scaling, investigating the dependencies on temperature, dew point temperature as measure of absolute humidity, and dew point depression as a measure of relative humidity. We compared  7 RCM simulations and 5 CPM simulations to observations from The Netherlands (a moderate moist climate) and Southern France (a warm and dryer climate). Although present-day scaling is no simple predictor of climate change, reproducing observed dependencies on the various temperature and humidity measures provides evidence that these models are  trustworthy in a climate change setting. We find that RCMs display a large spread in outcomes, in particular in their  dependency on relative humidity and usually strongly biased towards too strong suppression of extremes in low relative humidity conditions.  CPMs have (unsurprisingly) much better overall rainfall statistics, show much less inter-model spread, and temperature and humidity dependencies more consistent with the observations. Yet, most CPMs have a climatology biased towards too low relative humidity, affecting also the rain statistics, and underestimate the frequency of rain, in particular for conditions with high relative humidity. Our results suggests that, while CPMs are clearly better in convective rain processes, improvement are needed in weakly surface forced convection as well as the overall climatology/water balance of the models. 

How to cite: Lenderink, G., de Vries, H., Brisson, E., Berthou, S., and Kendon, E.: Evaluation of hourly precipitation in convection permitting models using scaling: are they better than parameterized models?, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-11776, https://doi.org/10.5194/egusphere-egu22-11776, 2022.

In the last decade, records have been broken in Turkey's temperature and precipitation observations. In 2020, including the effect of increasing urbanization, the measured temperatures in Istanbul were about 3 °C higher than the 100-year monthly average. In addition, the frequency and intensity of excessive precipitation, especially in northern Turkey, show an increasing trend. Moreover, the change in precipitation patterns is also observed due to climate change. Therefore, to decide Turkey's strategies to combat climate change, it is necessary to determine how accurately the climate model results reflect these changes. For this reason, this study aims to determine the biases of the historical climate models compared with observations. Moreover, comparisons of these models with mild and dramatic scenarios in the CMIP5 and CMIP6 protocols are discussed. The climate models (INM-CM4 and INM-CM5; CNRM-CM5.2 and CNRM-CM6-1; and MRI-ESM1 and MRI-ESM2-0) that were not analyzed before were studied to construct an ensemble overall. Thus, it is aimed to create climate model ensembles for temperature and precipitation. Accuracies of the selected climate models are analyzed by comparing the results of the models with the observations in the 1965-2015 periods utilizing ten-year probability distribution fractions. In addition, simple Daily precipitation intensity index (ECASDII), precipitation days index (ECAPD), extremely wet days index (ECAR99P) analyzes for precipitation and very warm days index (ECATX90P), warm nights index (ECATN90P), and intra-temperature analysis for precipitation. -period extreme temperature range (ECAETR) indices were analyzed. Preliminary results show that climate models simulate temperature changes more accurately than precipitation changes for Turkey. In addition, CMIP6 results were more advantageous than CMIP5 results.

How to cite: Hazar, I., Aksu, A. N., Yogun, B., Dursun, B. C., and Tan, E.: Analysis of Historical Climate Scenarios of Turkey related to temperature and precipitation for comparing CMIP5 and CMIP6 protocols., EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-12357, https://doi.org/10.5194/egusphere-egu22-12357, 2022.

Heatwaves occur due to atmospheric blockages and high-pressure systems' long-term stasis in the relevant regions. They are extreme weather events that negatively affect life. For example, in Turkey, wildfires during summer 2021 succeeded in a significant heatwave event. Depending on climate change, it is expected that the intensity, duration, and frequency of heatwaves will increase. It is expected that the semi-arid zones, including Turkey, will be more affected by this change. Therefore, this study aims to analyze how well different climate models capture historical heatwave events and determine the differences depending on the CMIP5 and CMIP6 protocols. Scenarios corresponding to 4.5 W/m2 and 8.5 W/m2 radiative forcings are discussed for both protocols. The climate models (CMCC-CM and CMCC-CM2-HR4; MRI-ESM1 and MRI-ESM2-0; and HadGEM2-ES and HadGEM3-GC31-LL) which have not been studied for Turkey until now are selected to create a model ensemble for historical heatwave events. Historical heatwaves, which occurred between 1965 and 2015, were compared with the climate models, including the CMIP5 and CMIP6 protocols, using probability density functions for ten-year periods. In addition, warm spell days index (ECAHWFI), heatwave duration index (ECAHWDI), heating degree days (ECAHD) climate indices were also analyzed. Preliminary results show that the intensity, duration, and frequency of heatwaves have increased dramatically in Turkey since 2002, and the success of historical climate models in capturing these changes varies from model to model.

How to cite: Yogun, B., Dursun, B. C., Aksu, A. N., Hazar, I., and Tan, E.: Heatwave Climate Variability of Historical CMIP5 and CMIP6 Protocols for Turkey, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-12310, https://doi.org/10.5194/egusphere-egu22-12310, 2022.

Located in the semi-arid region, Turkey is much more vulnerable to the drought effects of climate change. It is expected that the severity, duration, and frequency of drought episodes will increase due to climate change. The observations reveal that the drought episodes in Turkey have increased dramatically over the last decade. For example, in 2020, the occupancy rates of dams in Istanbul dropped below 30%. Therefore, the accuracy of the projections of climate models is essential in developing adaptation strategies related to drought types. Therefore, the study aims to compare the bias of the runoff and moisture content of the climate projection models (NorESM1-M and NorESM2; FGOALS-g2 and FGOALS-g3; and GFDL-CM3 and GFDL-CM4) with the observations. In addition, the scenarios in the CMIP5 and CMIP6 protocols were compared by calculating the probability distribution functions of the flow data for ten-year periods. In addition, consecutive dry days index (ECACDD), warm spell duration index (ECAHWFI), water storage deficit index, and Palmer drought severity index are also analyzed. Preliminary conclusions indicate that climate models vary significantly in capturing historical events. For this reason, an ensemble of the models needs to be created for decision-making purposes.

How to cite: Dursun, B. C., Yogun, B., Hazar, İ., Aksu, A. N., and Tan, E.: Comparisons of historical CMIP5 and CMIP6 protocols for the drought indices of Turkey, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-12365, https://doi.org/10.5194/egusphere-egu22-12365, 2022.

The spatio-temporal heterogeneity in surface characteristics is considered to play a key role in terrestrial surface processes. Its characterization is essential for adaptation strategies. Here, we conducted regional climate simulations with COSMO-CLM (v5.0_clm16) with different land cover input data driven by ERA5 reanalysis over Germany at convection-permitting horizontal resolution of 3 km from 2000 to 2011. The difference between the land cover data of GLC2000, CCI_LC and ECOCLIMAP and the operational used GLOBCOVER2009 dataset on temperature and its extremes is investigated. The results reveal that the differences in turbulent fluxes and temperature are related to land cover classes. Even though the land cover class fractional differences are small among the land cover maps, some land cover types, such as croplands and urban areas, have greatly changed over the years. These distribution changes can be seen in the temperature differences. Simulations based on the CCI_LC retrieved in 2000 and 2015 revealed no accreditable difference in the climate variables as the land cover changes that occurred between these years are marginal, and thus, the influence is small over Germany. Increasing the land cover types as in ECOCLIMAP leads to higher temperature variability. The largest differences among the simulations occur in maximum temperature and from spring to autumn, which is the main vegetation period. The temperature differences seen among the simulations relate to changes in the leaf area index, plant coverage, roughness length, latent and sensible heat fluxes due to differences in land cover types. The vegetation fraction was the main parameter affecting the seasonal evolution of the latent heat fluxes based on linear regression analysis, followed by roughness length and leaf area index. If the same natural vegetation (e.g. forest) or pasture grid cells changed into urban types in another land cover map, daily maximum temperatures increased accordingly. Similarly, differences in climate extreme indices (e.g., SU or TR) are strongest for any land cover type change to urban areas. The uncertainties in regional temperature due to different land cover datasets were overall lower than the uncertainties associated with climate projections. Although the impact and their implications are different on different spatial and temporal scales as shown for urban area differences in the land cover maps. Thus, to realistically simulate land use/cover change effects on regional and local climate and draw conclusions for management strategies, numerical models would benefit from land surface characteristics, which are as accurate as possible in retrieval year, number of land cover classes, their distribution and fractions and have a high spatial resolution.

How to cite: Tölle, M. and Churiulin, E.: The role of different land cover input data on local climate and its extremes, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-6507, https://doi.org/10.5194/egusphere-egu22-6507, 2022.

Climatic changes will likely increase the frequency and intensity of extreme weather events (e.g. heat waves or droughts) in the future. Vegetation is one of the key factors, which has a significant impact on extreme temperatures, which is clearly evident in climate simulations at convection-permitting scale. The process of evapotranspiration is related to vegetation and controlled by stomatal resistance, which is playing a major role in regulating water loss and carbon uptake. However, the regional climate model of the Consortium for Small-scale Modelling (COSMO-CLM v5.16) uses a simplified stomatal resistance algorithm, which is not capable of modelling complex processes depending on temperature, water availability and day length. Here, we demonstrate the changes in the total evapotranspiration parameter caused by updates of the stomatal resistance algorithms based on the physically Bell-Berry approach coupled with the Farquhar photosynthesis model and “two-big leaf” approach. The latter is necessary for dividing the photosynthetic active radiation flux on two phases, which are sunlit and shaded. The algorithms from two different versions (v3.5 and v4.5) of the Community Land Model (CLM) were implemented. The stomatal resistance algorithm of CLM v3.5 depends on leaf photosynthesis, CO₂ partial and vapor pressure and minimum stomatal conductance. The algorithm of CLM v4.5 is additionally limited by the soil water stress function. In a third update, we also implemented in COSMO-CLM the water flux calculation algorithm based on CLM v4.5 for dry and wet leaf transpiration. Then single column simulations were conducted over three observational research domains with C₃ grass plants in Germany from 2001 to 2015 and analyzed for the exceptionally warm and dry summer 2013. Model results were compared with GLEAM data. Differences between simulations begin to appear with the leaf growth and reach the maximum values in summer months, especially in June 2013 when the standardized temperature anomaly was fixed. In June, the reference simulation reaches mean values of the total evapotranspiration equal to 2.7 mm month^-1, while the GLEAM datasets and experimental simulations show similar values in the range of 3.3 to 3.6 mm month ^-1. The simulations with the new algorithms have slightly greater correlation coefficient (0.879, 0.875 and 0.867) with GLEAM data than the reference simulation (0.856). Applied performance indices like Kling-Gupta Efficiency index (KGE > 0.77) and the distribution added value index (DAV > 0.007) confirm those results. Model results for the exceptional warm and dry summer 2013 showed that the new algorithms of stomatal resistance are much more sensitive to the changes in environmental conditions (e.q.: soil moisture deficit, warm temperatures), while the reference simulation demonstrates similar to usual summer values of stomatal resistance. We anticipate our results to be a starting point for more sophisticated developments in the COSMO-CLM model. The new stomatal resistance algorithms can be used for the modern algorithm for the leaf area index based on the biomass evolution.

How to cite: Churiulin, E., Tölle, M. H., Kopeikin, V., Übel, M., Helmert, J., and Bettems, J. M.: Evaluating changes in the total evapotranspiration parameter due to the updates in stomatal resistance algorithms of COSMO-CLM model on the example of the exceptionally warm summer of 2013, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-185, https://doi.org/10.5194/egusphere-egu22-185, 2022.

Urbanization alters land surface properties and the local surface energy balance and, therefore, land and near surface air temperature. Urban morphology and processes are represented in climate models using urban land-surface models with varying levels of complexity, which parameterise the effects of urban environments on surface fluxes without representing buildings explicitly.

This study focuses on the eastern Mediterranean and the Middle East (EMME) area over which the effect of urban parameterisation and resolution difference on simulated 2-meter air and land surface temperatures is investigated. Two high-resolution simulations at 16 km and 4 km are performed over the EMME domain using the Weather Research and Forecasting (WRF) model coupled with NoahMP land surface scheme for the period of 2000-2002. The bulk urban parameterisation scheme is implemented, which assigns fixed values for land properties such as surface albedo, roughness length etc., appropriate for the resolved urban areas. Focusing on several cities of the region of interest for the summer season (June-July-August, JJA), the effect of the model horizontal resolution and the grid-box land type on air (minimum and maximum) and land temperatures is examined. The temperature difference of the urban-characterised grid-boxes compared to their rural surroundings is also studied. Station (Integrated Surface Dataset - ISD) and satellite (MODIS-TERRA) observations together with reanalysis data (ERA5-LAND) are used for the evaluation of the simulation output.

How to cite: Constantinidou, K., Hadjinicolaou, P., Tzyrkalli, A., Zittis, G., and Lelieveld, J.: How are air and land temperatures affected by the horizontal resolution and the bulk urban parametrisation in WRF model simulations over the eastern Mediterranean and the Middle East?, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-4610, https://doi.org/10.5194/egusphere-egu22-4610, 2022.

Detailed information about extreme precipitation is crucial due to the impacts on the human environment. Recently, high-resolution regional climate models (RCMs) are run at convection-permitting scales to investigate the regional precipitation extremes. The Black Sea region is one of the intriguing regions for modelling studies because of its distinctive topographical features where orographic forcing and strong air-sea interactions intensify destructive heavy precipitation. Recently, RCMs have been tested in order to find the most suitable configuration to represent precipitation over this region. Although the historical simulations are beneficial to test the model performance, model configurations may exhibit different spatiotemporal characteristics in simulating extreme precipitation due to the shift of the seasons in a possible warmer future. Recent studies focusing on the intensification of extreme precipitation events highlighted the model sensitivity to increasing sea surface temperature (SST) over the Black Sea. Therefore, future simulations focusing on different model configurations may provide valuable information to understand the response of RCMs in a changing climate. In this study, we downscaled the last generation CMIP6 MPI-ESM1.2-HR outputs by using the WRF model at 3 km horizontal resolution to test the model’s sensitivity for different microphysical and planetary boundary layer (PBL) parameterization options under the SSP5-8.5 future socioeconomic global change scenario. We selected cold and warm extreme precipitation cases and performed 3-days convection-permitting simulations over the complex topography of the Black Sea region. For the cold case, simple single-moment schemes produced less precipitation compared to more complex schemes, especially over the mountains, because of the insufficient representation of snowfall. For the warm case, the difference between the simulations is similar to the cold case but, the magnitude is lower. The change of the PBL scheme affects the vertical and horizontal distribution of microphysical properties and precipitation distribution near the coasts and the mountains.

How to cite: Kelebek, M. B. and Önol, B.: Sensitivity to Microphysics and PBL Schemes for Extreme Precipitation over the Black Sea Region in Future Climate: Warm and Cold Cases, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-408, https://doi.org/10.5194/egusphere-egu22-408, 2022.

Mesoscale Convective Systems (MCS) are common over Europe during the warm season (Morel and Senesi, 2002b) and are able to produce severe weather such as extreme precipitation leading to flash floods (Fiori et al., 2014). Studies analyzing the climatological characteristics of MCS over Europe are rare and were often based on only a few years of data or were focused on a limited area of Europe. In their recent research, Surowiecky and Taszarek (2020) showed that MCS over Poland can frequently adopt typical morphology of mid-latitude extreme-rain producing MCS (Schumacher and Johnson, 2005).
With the recent Integrated Multi-satellitE Retrievals for Global Precipitation Measurement (IMERG; Huffman et al., 2019) satellite precipitation climatology, we identify and track MCS for nearly 20 years over Europe. Our detection/tracking algorithm is inspired from the one proposed by Feng et al. (2021). Cell-tracking from precipitation data is not straightforward, especially for fast moving and small systems. Here, we make use of a spatio-temporal filter and track cells according to the overlapping of filtered precipitation patches between two consecutive time steps. We fit an ellipse to the precipitating patches for a quick scan of their morphology and orientation. The algorithm is able to distinguish between non-convective rain bands from convective rain patches, thus reducing potential identification errors.
We use this new European MCS climatology to evaluate their main characteristics in Europe and their potential evolution over the last 20 years. In particular, we examine their occurrence frequency in extreme rainfall events in this region and the environmental conditions leading to these extremes, with respect to other (non-MCS) convective systems. This work contributes to better understanding the role that convective organization plays in driving extreme rain in mid-latitudes from an observational perspective.

References

Feng Z, Leung LR, Liu N, Wang J, Houze RA, Li J, Hardin JC, Chen D, Guo J. 2021. A global high-resolution mesoscale convective system database using satellite-derived cloud tops, surface precipitation, and tracking. Geophys. Res. Atmos., 126, e2020JD034202, doi: 10.1029/2020JD034202. 

Fiori E, Comellas A, Molini L, Rebora N, Siccardi F, Gochis D, Tanelli S, Parodi A. 2014. Analysis and hindcast simulations of an extreme rainfall event in the Mediterranean area: the Genoa 2011 case. Atmos. Res., 138, pp. 13–29, doi: 10.1016/j.atmosres.2013.10.007.

Huffman GJ, Stocker EF, Bolvin DT, Nelkin EJ, Tan J. 2019. GPM IMERG final precipitation L3 half hourly 0.1 degree x 0.1 degree V06, Greenbelt, MD, Goddard Earth Sciences Data and Information Services Center. doi: 10.5067/GPM/IMERG/3B-HH/06.

Morel C, Senesi S. 2002b. A climatology of mesoscale convective systems over Europe using satellite infrared imagery. II: Characteristics of European mesoscale convective systems. Quart. J. Roy. Meteor. Soc., 128, 1973–1995, doi: 10.1256/003590002320603494.

Schumacher RS, Johnson RH. 2005. Organization and environmental properties of extreme-rain-producing mesoscale convective systems. Month. Weath. Rev., 133, 961–976, doi: 10.1175/MWR2899.1.

Surowiecki, A., & Taszarek, M. (2020). A 10-Year Radar-Based Climatology of Mesoscale Convective System Archetypes and Derechos in Poland, Month. Weath. Rev., 148(8), 3471–3488, doi: 10.1175/MWR-D-19-0412.1.

How to cite: Da Silva, N. and Haerter, J.: The role of mesoscale convective organization in the generation of extreme precipitation over Europe, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-5483, https://doi.org/10.5194/egusphere-egu22-5483, 2022.

Extreme precipitation and temperature events (EPTE) cause devastating impacts to ecosystems and society. The diversity of climates around the world does not allow a single definition of extreme events given the multiplicity of conditions in which each event develops. In regions of complex topography, interactions with vegetation have as a result numerous atmospheric circulation patterns and the existence of various phenomena at different spatial and temporal scales, which impedes homogeneity of distribution, frequency, and intensity of extreme events. It is known that El Niño Southern Oscillation (ENSO) influences the interannual variability of precipitation and temperature in different regions around the world. However, it is not clear how this phenomenon interacts with the frequency and intensity of EPTE in regions with complex topography gradient and a diversity of climates. Here we focus on the Colombian Andes mountain range in northern South America because it occupies a quarter of the territory, gathers most of the socio-economic development, and concentrates the majority of the country´s population. In this context, we use statistical analysis to characterize EPTE during La Niña, El Niño, and neutral years. In this work, we also compare the frequency and intensity of EPTE between La Niña and neutral years and El Niño and neutral years. Unlike other studies, we want to know if there is any pattern of increase or decrease of EPTE when an ENSO phase is active. We discuss the months in which there is an increase or decrease in EPTE according to the interannual variability of precipitation and temperature, as well as the months in which there is a significant relationship between the sea surface temperature of the Niño 3.4 region with precipitation and temperature. Our results show that the highest intensities of extreme precipitation events occur in the rainy seasons March-April-May and September-October-November. Also, the highest frequency of extreme precipitation events occurs between December and March for both the 95th and 99th percentile. The difference analysis showed that during El Niño and La Niña periods, extreme precipitation events are more intense than in neutral years. Additionally, the frequency of events is higher during El Niño, but their localization is variable in time and space. The behavior of temperature extremes is more marked since the most intense events occur during El Niño from February to September, and the highest frequency of extreme events occurs between April and September and varies throughout the year in the Andes region according to the active phase of ENSO. These results provide a basis for the design of adaptation and mitigation policies in the face natural variability and climate change, and for improving hydrometeorological forecasts.

How to cite: Acero, I. C. and Vieira, S. C.: Characterization of extreme precipitation and temperature events during El Niño Southern Oscillation in the Colombian Andes, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-9008, https://doi.org/10.5194/egusphere-egu22-9008, 2022.

India experienced more flood situations due to the increasing extreme rainfall events over the different Indian River Basins (IRBs) during the last few decades. An Extreme Value Theory (EVT) is used to examine trends of rainfall extremes over the IRBs using long-term observed high-resolution grid-based rainfall (1901-2019) of the India Meteorological Department. The analysis depicts that when generalized extreme value theory (GEV) is applied to annual maximum rainfall over IRBs, statistically significant uniform trends were not seen. The spatial variations in the annual maximum rainfall for the 10-, 30- and 100-year return levels show statistically significant increasing trends over the IRBs. The shifting trend of rainfall extremes from northeast towards the western river basins of IRBs in the last two decades and resulted in damage to life and property on the west coast. The decadal changes in average intensity of dry and wet condition at 12- months running time window reveals that the shifting and increasing pattern of the rainfall extremes events during the last decades of the 20th century (1981-2000) and current decades of the 21st century (2001-2019) over the western ghats and west-flowing river basin leads to several floods situations. This research highlights the significant increasing trend in extreme rainfall events over the IRBs, which may pose a grave risk to agriculture, human life, and predominantly on the vulnerable sections of the society.

How to cite: Chaubey, P. K. and Mall, R. K.: Western shifting of Extreme Rainfall Events over the different Indian River Basins in the last 119 years, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-188, https://doi.org/10.5194/egusphere-egu22-188, 2022.

The occurrence of extreme precipitation events is a matter of concern for any nation because a slight change to it can have a devastating effect on the socio-economic condition for the state. To assess the temporal and spatial variability of precipitation extremes, extreme rainfall data over India (except Island part) have analyzed using quantile perturbation method. The data used in the study is taken from the Climate Research Unit, University of East Anglia (UK). It is a gridded data of 0.5^o × 0.5^o resolution. The analysis showed that different part of the studied area had varying perturbations in the precipitation extremes. The study found a significant anomaly in precipitation extreme for all the periods but the 1910s, 1920s, 1930s, 1940s, 1990s, and 2000s decades had covered wide area as compared to the remaining periods with reference to the long period of 1901-2017. In the 1910s, the positive anomaly was found near most of North East India, while negative anomaly was found in central and north India. In 1930-1940s, the central part had a positive anomaly, and the north part had a negative anomaly. Negative perturbation is present in the most of east region (the Gangetic plain) in 1990-2000s. A positive anomaly found on the west side. But in the recent decade very few anomaly present in the whole region. To partially address the reason behind the perturbation correlation analysis has been done between extreme precipitation anomaly and Indian Ocean Dipole. The result shows most of the part of East, North East side of India are having moderately negative correlation while some of the South and North India are having moderately positive correlation. The sea surface temperature over the Indian Ocean might be the main driver for the decadal perturbations in precipitation extremes.

How to cite: Mandraha, S. and Ray, S.: Temporal and spatial variability of precipitation extremes across India, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-309, https://doi.org/10.5194/egusphere-egu22-309, 2022.

Heavy rainfall is among the most impactful natural events. Our understanding of such events has improved significantly in the last decades, but large uncertainties remain around their recent and future response to a changing climate. At global scales, the frequency and intensity of daily extreme precipitation has increased, the hydrological cycle is becoming faster. However, the response at regional scales and shorter timescales is much more complex. The study of sub-daily or even sub-hourly data has been explored to some extent only, mostly due to the limited availability of data. When using high-resolution models to explore rainfall changes, it is possible to examine much higher frequencies, yet most studies focus on daily rainfall changes.

Here, we demonstrate inherent limitations of daily data to study present and future precipitation extremes. Limitations that are not purely a matter of refining our sampling, but do have a physical background because outstanding rainfall rates rarely occur over the course of a day. Our results show that fundamental aspects of rainfall changes are not described with daily data, and the assessment of future changes in daily precipitation likely leads to misrepresentation of causes and impacts. We show that the short-lived and intermittent nature of most rainfall extremes need at least hourly data to be properly characterized, otherwise heavy rainfall is poorly detected. Analyzing higher frequencies also reveals aspects of extremes that cannot be addressed with daily data, such as changes in their intensity and duration. This is particularly relevant for risk and impact assessment studies because a significant part of changes in extremes occur at sub-daily scales. Such changes go unnoticed or, even worse, are misrepresented by daily rainfall amounts.

How to cite: Argüeso, D. and Di Luca, A.: On the need for sub-daily data to study changes in extreme rainfall., EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-10496, https://doi.org/10.5194/egusphere-egu22-10496, 2022.

The dynamical downscaling of global circulation models (GCMs) with regional climate models (RCMs) is a computationally expensive process, even more so running at the convection permitting scale (CP). The high-resolution product of these simulations is an important factor for consideration and is relevant to provide a  proper characterization of climate extremes, to address hazard assessment and manage associated risk. Moreover, an increasing number of studies shows improvements in regional climate model performances at CP scale if compared to their driving RCMs. The assessment of extreme events indicators, as defined by the joint CCl/WCRP/JCOMM Expert Team on Climate Change Detection and Indices (ETCCDI), is here proposed over the Iberian peninsula using CP simulations at around 3km of resolution for evaluation experiment as well as for future spans. The same indicators are also assessed for the available observations and for the driving RCM simulation at around 12km of resolution. Such approach allows, from one side to evaluate the results of CP simulation by comparison against observations and, on the other one, to quantify if there are any improvement by comparison against RCM simulation at a coarser resolution. Then, indicators are calculated in a near future 10 years-long period from both CP and RCM simulations, in order to highlight the differences in the climate projections. The selected indicators as consecutive dry days and maximum value of daily maximum temperature are strictly connected to high-impact events as droughts and temperature extremes. Their exploiting provide useful information about the expected changes in next decades due to the climate warming.

How to cite: Adinolfi, M., Raffa, M., and Mercogliano, P.: Climate indicators for high-impact weather events as droughts and temperature extremes over the Iberian Peninsula with convection permitting scale simulations, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-3791, https://doi.org/10.5194/egusphere-egu22-3791, 2022.

The latest generation of Convection Permitting Regional Climate Models (CPRCMs, <4 km resolution) provides a step change in our understanding of regional-to-local scale climate processes.

Recent studies highlight how km-scale modeling provides a more accurate representation of precipitation extremes compared to the driving convection-parameterized RCMs. Further, evidence suggests that changes in the soil moisture-precipitation feedback and regional precipitation recycling occur when moving to a km-scale. This generally translates into drier conditions in km-scale simulations, mainly during summer. Consequently, the different soil moisture content in explicit vs. parameterized simulations results in a different partitioning between heat fluxes, which in turn can modulate temperature extremes and heatwaves (HWs).

This study explores the representation of HWs and their future changes from an ensemble of twelve CPRCMs downscaled from CMIP5 GCM projections for historical and end-of-century periods over a greater alpine region. The two-step dynamical downscaling consists of downscaling GCMs to an intermediate 12–15 km resolution (convection-parameterized RCMs) and then using these fields to further downscaling to the kilometer scale.

Analyses are two-fold: (i) Exploring if the warmer/drier signal introduced by the km-scale points toward an improvement compared to the driving convection-parameterized simulations over the historical period. Here, distribution-based grid- and station-scale evaluation metrics are considered. (ii) Assessing if the km-scale signal is temporally stationary or if modulation of summer temperatures and HWs future changes can be expected. Key metrics are summer maximum temperature and relevant HW statistics (e.g., amplitude, persistence magnitude). HWs local-scale forcing, represented by the land-atmosphere coupling magnitude, is also analyzed.

Preliminary results show an added value from km-scale simulations. RCM cold biases are reduced and summer maximum temperature distribution is improved over a majority of reference stations. Concerning future changes both resolutions show a summer maximum temperature change signal ~ +6 °C characterized by a large spread among members (+4/+8 °C). Considering the ensemble mean, we do not observe strong modification of the climate change signal by the CPRCMs (±10%). However, this results from averaging change signal modifications from individual members that can be as much as up to ±25%, with no clear tendency toward an amplification/reduction of the driving RCM change signal.

Similar results are obtained considering only HW days. Driving the change signal alteration observed in some models is a difference between CPRCMs and RCMs in the partitioning of latent heat during HW days. In contrast to the CPRCMs, some RCMs produce positive future changes in latent heating during HW days, meaning there is sufficient soil moisture to allow latent heat to increase in response to an increased radiative forcing. 

To conclude, CPRCMs are warmer than RCMs during the historical period, resulting from improved and more realistic physics. This does not translate into an unambiguous modulation of the ensemble mean future change signal. However, those models that exhibit strong modulation could be driven by a different sign of HWs latent heat change signal. This aspect deserves further analysis since alterations of other relevant HW features, such as magnitude and persistence, have potentially large societal impacts.    

How to cite: Sangelantoni, L. and Sobolowski, S.: Exploring the effect of kilometer-scale climate modeling on the representation of historical and future heat waves. A multi-model ensemble perspective, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-4318, https://doi.org/10.5194/egusphere-egu22-4318, 2022.

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.

How to cite: Malečić, B., Cui, R., Jelić, D., Horvath, K., Telišman Prtenjak, M., Ban, N., Demory, M.-E., Mikuš Jurković, P., Strelec Mahović, N., and Schär, C.: Performance of HAILCAST and lightning potential index coupled with WRF and COSMO in convection-permitting simulations of hailstorms over the Alpine-Adriatic region, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-2499, https://doi.org/10.5194/egusphere-egu22-2499, 2022.

Precipitation is typically analysed from an Eulerian perspective, in which rainfall is considered at a fixed location. Lagrangean analysis of precipitation represents an alternative approach. Here, precipitation objects – for example, convective cells – are identified in a precipitation field and are then tracked through space and time, allowing object properties over the whole life of a convective cell to be collected. For the study of precipitation under climate change, this approach may offer additional insights into the mechanisms by which precipitation increases or decreases; for example, changes in cell lifetime or areal extent.

In this study, we analyse the climate-change response of convective cells’ properties by combining Lagrangean tracking with the pseudo global warming (PGW) modelling approach. A 14-day period of unusually high convective activity over central Europe is first simulated under observed conditions in an 18-member ensemble with the COSMO-CLM at convection-permitting resolution (2.8 km). The ensemble is then re-simulated under PGW conditions, created by modifying the initial and boundary conditions based on an RCP8.5 end-of-century scenario. All convective objects are then systematically tracked through space and time. Here we present the response to warming of the convective cell characteristics for the study period, and explore the variability of these changes across the full distribution of objects. Cell characteristics considered include cell area, intensity, volume, lifetime and distance travelled.

How to cite: Meredith, E. P., Rust, H. W., and Ulbrich, U.: Lagrangean analysis of convective cells under climate change, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-142, https://doi.org/10.5194/egusphere-egu22-142, 2022.

Due to associated hydrological risks, there is an urgent need to provide plausible quantified changes in future extreme rainfall rates. Convection-permitting (CP) climate simulations represent a major advance in capturing extreme rainfall and its sensitivities to atmospheric changes under global warming. However, they are computationally costly, limiting uncertainty evaluation in ensembles and covered time periods. This is in contrast to the Climate Model Intercomparison Project (CMIP) 5 and 6 ensembles, which cannot capture relevant convective processes, but provide a range of plausible projections for atmospheric drivers of rainfall change. Here, we quantify the sensitivity of extreme rainfall within West African storms to changes in atmospheric rainfall drivers, using both observations and a CP projection representing a decade under the Representative Concentration Pathway 8.5 around 2100. We illustrate how these physical relationships can then be used to reconstruct better-informed extreme rainfall changes from CMIP, including for time periods not covered by the CP model. We find reconstructed hourly extreme rainfall over the Sahel increases across all CMIP models, with a plausible range of 37-75% for 2070-2100 (mean 55%, and 18-30% for 2030-2060). This is considerably higher than the +0-60% (mean +30%) we obtain from a traditional extreme rainfall metric based on raw daily CMIP rainfall, suggesting such analyses can underestimate extreme rainfall intensification. We conclude that process-based rainfall scaling is a useful approach for creating time-evolving rainfall projections in line with CP model behaviour, reconstructing important information for medium-term decision making. This approach also better enables the communication of uncertainties in extreme rainfall projections that reflect our current state of knowledge on its response to global warming, away from the limitations of coarse-scale climate models alone.

How to cite: Klein, C., Parker, D. J., Jackson, L. S., Marsham, J. H., Taylor, C. M., Rowell, D. P., Guichard, F., Vischel, T., Famien, A. M., and Diedhiou, A.: Combining CMIP data with a convection-permitting model and observations to project extreme rainfall under climate change, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-5269, https://doi.org/10.5194/egusphere-egu22-5269, 2022.

In the warming climatic scenario, Indian Summer Monsoon (ISM) rainfall and its extremes, especially on the local scale, is expected to alter that profoundly impact the societal, environmental, and economic well-being of the million people residing in central India. Therefore, understanding ISM mean and extreme rainfall for the past, current, and reliable projection are crucial for effective adaptation strategies, remains a major scientific challenge. The Regional Earth System Model (ROM) driven by MPI-ESM-LR over the CORDEX-South Asia framework under the RCP8.5 scenario at a finer horizontal resolution of 0.22° was used to investigate the future of mean and extreme precipitation over central India. The ROM’s performance is demonstrated with respect to observed precipitation data from India Meteorological Department. ROM shows its skill in capturing the mean and extreme precipitation (PEs) during the ISM along with its intraseasonal variability.  Further, an effort is made to investigate the projected changes in precipitation extremes (PEs) during the mid-future (MF; 2040-2069) and far-future (FF; 2070-2099) concerning the historical period (1969-2000) under the RCP8.5 scenario. The results highlight, two-fold rise in the frequency of PEs is likely to be expected by the end of the century. In addition to this, the study also projects the intraseasonal variability, i.e., the active and break spells that crop up during the peak monsoon months (July and August). The active spells were found to be more persistent in the projected period. The changes in the different precipitation events are subjected to strong cyclonic circulation, reduced vertical wind shear, and enhanced moisture transport.

How to cite: Kumari, A. and Kumar, P.: Precipitation Extremes over central India - Past, Present, and Future: Regional Earth System Model Perspective, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-289, https://doi.org/10.5194/egusphere-egu22-289, 2022.

Profound changes have been observed in the precipitation pattern of Turkey due to climate change during the last decade. This variation in precipitation pattern affects the amount of snow cover and the temporal and spatial distribution of snow. In addition, significant variability was observed in the initial time of snowmelt that water resources, especially groundwater, might be adversely affected. On the other hand, this adverse effect in snow cover is also crucial for Turkey's winter sports tourism. For this reason, the study aims to analyze the historical simulation results of climate models (MIROC5 and MIROC6; CanESM2 and CanESM5; and GISS-E2-H and GISS-E2-1-H) based on CMIP5 and CMIP6 protocols depending on snow cover variables and compare the consistency of these models with observations. Probability distribution functions of surface snow area fraction and snowfall flux variables over ten-year periods were analyzed. In addition, the frost days index (ECAFD), Ice days index (ECAID), and very cold days (ECATX10P) index were also analyzed. As a preliminary result, it was found that the snow cover values of the CMIP6 protocol climate models were more consistent with the observations.

How to cite: Aksu, A. N., Hazar, I., Dursun, B. C., Yogun, B., and Tan, E.: Snow Cover Analysis of Turkey comparing to Historical Climate Scenarios of CMIP5 and CMIP6 protocols, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-12312, https://doi.org/10.5194/egusphere-egu22-12312, 2022.

The frequency and intensity of heavy and extreme precipitation events in Europe have increased since the 1950s. Earlier studies have found, using observational datasets, that frequency increases more than intensity and that both increase more with event rareness. Here we compare changes in intensity and frequency for different observational and model datasets. Both CMIP6 global models with ensembles and regionally downscaled model results are analyzed. The regional models (from CORDEX) are driven by both reanalysis and CMIP5 models. Data are analyzed over two 30-year periods from 1951 to 1980 and 1981 to 2010. Results show that the models do not manage to produce the same increase in frequency as observed, however results are more similar for intensity increase. There are large differences in the change in extreme precipitation in model ensembles. The probability density functions for each of the observational and model datasets show that there are differences in the pattern of the shift between the two time periods.

How to cite: Steensen, B., Myhre, G., Hodnebrog, Ø., and Altherskjær, K.: Differences in the increase of frequency and intensity of extreme precipitation between models and scales over Europe, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-5988, https://doi.org/10.5194/egusphere-egu22-5988, 2022.

Flash floods rank among the most dangerous and costliest hazards of the alpine and mediterranean region. The severe convective storms causing them are influenced by both, the presence of a large body of sea water and a complex orography. These storms are the main subject of the present study and in the following referred to as heavy precipitation events (HPEs).

We here study heavy precipitation events by using an ensemble of convection permitting regional climate models and applying a tracking algorithm, and focus on their charateristic properties. The domain covers the Alps and the central part of the Mediterranean, and we investigate and compare three 10-year periods under the rcp85 forcing scenario: historical [2000-2009], near-future [2040-2049] and far-future [2090-2099].

Our analysis reproduces a most important message: even though in the future the mediterranean climate is drying, precipitation associated with heavy precipitation events is increasing. Further, HPEs will be more frequent in the future. In particular, their occurrence frequency will increases in wintertime, whereas it will decrease in summertime.

We investigate the climate change signal of characteristic properties describing the propagation, the spatial and temporal scales and the intensity of HPEs: on average HPEs travel by 10% farther [8km], they last longer by 5% [20 min], their area increases by 16% and their total rain volume by 34%. Regarding metrics of intensity the changes of the highest percentiles are greatest: the 90th percentiles of a HPE's precipitation field increases by 5.6%, the 99th percentile by 9.4% and the maximum increases by 12.7%.

Eventually we unravel the characterics for specific regions and seasons: changes are more dramatical for HPEs that cross the coastline and in wintertime.

In summary, this study confirms important messages of climate research in an ensemble of state-of-the-art regional climate models, demonstrates the capabilities of convection-permitting spatial resolution and explores the possibilities that come with applying a tracking algorithm and by looking into precipitation extremes in the Lagrangion framework of reference.

How to cite: Müller, S. K., Pichelli, E., Coppola, E., Berthou, S., Brienen, S., Caillaud, C., Demory, M.-E., Dobler, A., Feldmann, H., Mercogliano, P., Tölle, M., and de Vries, H.: A Climate Change Study of Heavy Precipitation Events in the Mediterranean and Alps, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-5481, https://doi.org/10.5194/egusphere-egu22-5481, 2022.

Subdaily extreme precipitation may trigger fast hydro-geomorphic responses, such as flash floods and debris flows, which cause numerous fatalities and large damage. Compared to coarser resolution models, high-resolution models, called convection-permitting (CPMs), more realistically represent convective processes that are key for the correct representation of subdaily extremes, and thus provide higher confidence in the future extreme estimates. However, due to the high computational demands, the existing CPM simulations are only available for relatively short time periods (10–20 years at most), too short for deriving precipitation frequency analyses with conventional approaches. Recent extreme value analysis methods, based on all “ordinary” observations rather than on just yearly maxima or a few values over a high threshold, offer an opportunity for exploiting these short data records to reliably estimate return levels associated with long return periods. Here, we examine subdaily precipitation extremes from three 10-year time slices (historical 1996-2005, near-future 2041-2050, and far future 2090-2099 – under the RCP8.5 scenario) of COSMO-crCLIM model simulations at 2.2 km resolution. We focus on the Eastern Alpine transect characterised by a complex orography, where significant changes in subdaily annual maxima have been already observed. We find that, although the storms' frequency will decrease in the region, the mean annual maxima will increase continuously in the near and far future, especially at shorter durations. Investigation of extreme return levels shows a similar trend, with larger changes in the far future. A shift in the seasonality is also reported, with extremes moving from late summer-autumn (historical), to autumn (near future), and autumn-winter (far future).

How to cite: Roghani, B., Dallan, E., Fosser, G., Schär, C., Marani, M., Borga, M., and Marra, F.: Changes in future subdaily extreme precipitation at convection-permitting scale over an alpine transect, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-5924, https://doi.org/10.5194/egusphere-egu22-5924, 2022.

Recent research with “km-scale” or “convection-permitting” climate models (resolutions with grid-spacing generally < 4km) has described substantial improvements in the representation of precipitation when compared to conventional parameterized models. In particular, the distribution of precipitation is more faithfully reproduced and, in particular, precipitation extremes are more closely aligned with observations in terms of frequency, magnitude and duration. Future changes for many regions largely follow the mantra “the extremes become more extreme”. These results imply serious consequences arising from impacts commonly associated with extreme precipitation such as flash flooding, landslides, as well as  water resources availability. However, questions remain regarding the robustness of these responses as well as which types of precipitation contribute (and how) to the projected changes. Most of the existing literature at convection permitting scale consists of one or two model experiments and characteristics of precipitation are often defined based on arbitrary intensity thresholds. 

Here we employ the coordinated, multi-model ensemble of convection-permitting simulations generated within the WCRP CORDEX Flagship Pilot Study on Convection over Europe and the Mediterranean. While the domain covers the greater Alpine region we focus here on the Alps themselves given its exposure to a  wide variety of storm types and extremes and the importance of representing convection and its interactions with the complex topography for the local climate. This multi-model ensemble is now complete and the present paper investigates the changing characteristics of precipitation over the complex terrain of the Alps.

A physically-based algorithm is employed to categorize precipitation as either convective, stratiform or orographic. The algorithm was specifically designed for use with km-scale modeling and uses commonly available variables on only a few levels of the atmosphere. This algorithm has been shown previously to accurately categorize precipitation types over the Scandanavian mountains as well as the Alps. 

The results show strong decreases in annual convective and orographic precipitation over the greater Alpine region, while stratiform precipitation changes little if at all. Upon closer inspection, using the Analysis of precipitation across scales method (AsoP) and traditional IDF analyses, a more nuanced picture emerges. IDF plots show that the frequency of high intensity events increases, across all durations over all Alpine regions (NW, NE, S). Conversely, frequency decreases for more moderate events, most strongly in the summer season. The AsoP analysis shows that this occurs due to a shifting of the entire distribution of precipitation for all precipitation types. This shift to higher intensities comes at the expense of more moderate intensity events, which decrease. While all seasons show similar patterns of change the change is most pronounced in summer. Convective and orographic precipitation show similar patterns but the magnitude of the change is largest for convective precipitation. Thus, despite an overall drying over the Alps, the extremes indeed become more extreme and more frequent. This behavior is remarkably robust across the entire ensemble.

How to cite: Lorenz, T. and Sobolowski, S. and the CORDEX Flagship Pilot Study on Convection over Europe and the Mediterranean - ensemble on precipitation types: A robust shift towards higher intensity convective and orographic rainfall over the Alps in a warmer climate, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-7066, https://doi.org/10.5194/egusphere-egu22-7066, 2022.