Arthropods play vital roles in the ecosystem (e.g., pollinators, decomposers, biological pest control), and thus can act as indicators of ecosystem integrity. The state of these ecosystems is sensitive to variations in climate conditions, especially on small islands. The Circum-Sicilian islands are a chain of small islands around Sicily in the central Mediterranean. With the use of Convection permitting simulations, many of these islands can finally be adequately resolved. The objective of the project PALEOSIM (PALEOclimate modelling of Small Islands in the Mediterranean and possible impacts on arthropod habitats) is to study climate impacts on the habitats of arthropods (mainly insects) in the Circum-Sicilian islands. To achieve this, RegCM5 is driven by CMIP6 and PMIP4 data for a 3 km region covering the west and central Mediterranean.

Climate indices from the simulations have been used to assess the ecological niche of select arthropod species and hence determine how these conditions have changed across different time scales. The data used to drive RegCM5 allows for the study of time slices across several scenarios, which include: the last glacial maximum, mid-Holocene, ~1000 CE, ~1850 CE, ~1995 CE (a historical baseline), and Global Warming Levels of 1.5, 2, and 3 °C. This analysis reveals how some species are especially sensitive to changes in climate conditions, and the significant threat of the current climate crisis.

How to cite: Ciarlo, J., Coppola, E., Micallef, A., and Mifsud, D.: Climate-induced variations in arthropod habitats of the Circum-Sicilian islands according to convection permitting simulations of the Mediterranean driven by CMIP6 and PMIP4 data, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-8279, https://doi.org/10.5194/egusphere-egu24-8279, 2024.

Derechos are severe convective storms known for producing widespread damaging winds. While less frequent than in the United States of America (USA), derechos also occur in Europe. The notable European event on 18 August 2022 exhibited gusts exceeding 200 km h^-1, spanning 1500 km in 12 hours. This study presents a first climatology of warm-season derechos in France, identifying thirty-eight (38) events between 2000 and 2022. Similar to Germany, derechos in France are associated with a southwesterly circulation and display comparable frequencies. While a suggestive trend of higher late-season frequency and a potential larger proportion of low-intensity events in France are observed, caution is warranted due to the lack of statistical significance arising from a relatively small sample size. The study also examines synoptic and environmental changes linked with analogues of the 500 hPa geopotential height patterns associated with past warm-season derechos, comparing analogues from a relatively distant past (1950–1980) with a recent period (1992–2022). For most events, a notable increase in convective available potential energy (CAPE) is observed, consistent with Mediterranean trends. However, there is no consistent change in 0–6 km vertical wind shear in the recent period. These environmental shifts align with higher near-surface temperatures, altered mid-level atmospheric flow patterns, and often, increased rainfall. The role of anthropogenic climate change in these changes remains uncertain, given potential influences of natural variability factors such as the El Niño Southern Oscillation (ENSO) or the Atlantic Multidecadal Oscillation (AMO).

How to cite: Fery, L. and Faranda, D.: Analyzing 23 years of warm-season derechos in France: a climatology and investigation of synoptic and environmental changes, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-11710, https://doi.org/10.5194/egusphere-egu24-11710, 2024.

In Europe, extreme weather events are expected to increase noticeably in frequency, duration, and intensity with the continued warming of the planet's climate. Land-atmosphere feedbacks have been shown to play an important role in the exacerbation of events such as heat waves and droughts. Due to the important role of convective events in local weather an improved understanding of the role that land-atmosphere feedback plays in the development of convection initiation is required.

The heated condensation framework (HCF) enables the quantification of land-atmosphere coupling strength and local convection events in dependence of the temperature and moisture profiles from the ground to the planetary boundary layer height. The HCF is applied to the hourly data from the Weather Research and Forecasting (WRF) model application of the University of Hohenheim (UHOH) within the decadal km-scale regional climate simulations within CORDEX-FPS convection.

The analysis reveals the Po-Valley area as a hotspot of land-atmosphere coupling-induced local convection initiation in central Europe. Further strong wet and dry soil anomalies impact the number of local convection initiation events throughout the studied domain.

How to cite: Breuninger, N. and Warrach-Sagi, K.: Land-atmosphere coupling induced local moist convection initiation in central Europe, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-672, https://doi.org/10.5194/egusphere-egu24-672, 2024.

Heatwaves have emerged as an increasingly recurrent extreme meteorological event, in the Mediterranean region and throughout Europe, during the summer. This is attributable to shifts in the distribution and magnitude of temperatures. In particular, the Comunitat Valenciana a region in Spain experienced the last summer its highest temperature, registering a 1.6ºC increase in the monthly average temperature compared to the reference period (1991-2020). On August 10, the historical record was exceeded by 3.4ºC, with temperatures exceeding 40ºC in more than 50% of the territory as reported by the Spanish Meteorological Agency (AEMET). During this climatic event, the Mortality Monitoring (MoMo) system reported a substantial spike in excess deaths, reaching 1,990 in August. This figure significantly exceeded the preceding month’s tally of 686 fatalities and the subsequent month’s count of 186 deaths. This concentration of mortality in the hottest month underscores the severity of the impact.

The analysis of heatwaves is crucial to provide scientific support for the necessary formulation of inform adequate public policies. Additionally, it enables the population to undertake necessary actions to mitigate the adverse effects of high temperatures.

In a context of increasing temperatures due to climate change, foreseeing its future evolution would provide valuable information for better preparedness. The present research analyses future heatwaves and trends in the city of Valencia, Spain. Future temperatures refer to five bias adjusted CMIP6 (Coupled Model Intercomparison Project Phase 6) climate change models across four different scenarios: historical (1979 to 2014), SSP126, SSP370 and SSP585 (2015-2100). Model suitability is evaluated comparing historical runs with reference data from W5E5-ERA5Land. Afterwards, an analysis of future heatwaves is conducted, using the operational definition of heatwave from Spain: periods of at least three consecutive days where maximum temperature exceeds a critical threshold set by each municipality, which in Valencia refers to the 90th percentile of maximum temperatures for the historical period.

For each detected heatwave the selected indicators are: the number, frequency, duration, intensity, amplitude, and risk level associated with these climatic events. Our analysis evaluates how the number of heatwaves vary, as well as to understand the behaviour of heatwaves in Valencia to determine how the risk might evolve in future contexts, and in a future generating a predictive model providing information on their spatial distribution, intensity, duration and severity.

Acknowledgements:

This study has received funding from the: “THE HUT project” (The Human-Tech Nexus – Building a Safe Haven to cope with Climate Extremes), under the European Union’s horizon research and innovation programme (GA No. 101073957).

How to cite: Fernandez-Garza, A., Gielen, E., Pulido-Velazquez, M., Macian-Sorribes, H., Rubio-Martin, A., and Avila-Velasquez, D.: Heatwave analysis over the city of Valencia (Spain) for past and future climate change models and scenarios, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-10599, https://doi.org/10.5194/egusphere-egu24-10599, 2024.

Increasing spatial resolution to kilometre scales allows the deactivation of deep convection parameterisation schemes. As a result of various global initiatives for the next generation of climate studies, continental convection-permitting model (CPM) simulations are now accessible. Nonstationary local extremes, like heatwaves and intense precipitation, are probabilistically linked to regional circulation through scaling relationships. However, these relationships have not been extensively explored in the new simulations available in the early 2020s. Hourly time series data were extracted from the UK Climate Science for Service Partnership (CSSP) and the US South America Affinity Group (SAAG) CPM simulations to compare extreme characteristics of precipitation and temperature for 39 stations in a region of São Paulo, Brazil. Compared to reanalysis and satellite data, which exhibit lower variance in hourly time series, these two sets of CPM simulations have precipitation that is more similar to station observations than the ERA5 data and the Integrated Multi-satellitE Retrievals for the Global Precipitation Measurement (IMERG) data.

The cross-correlation structures of the time series are investigated to quantify temporal dependence and reveal patterns between temperature and precipitation at an hourly timescale. Within a higher-dimensional probability space for joint risk, the cross-correlation structures between temperature and precipitation at different lags demonstrate the "memory" of these variables, indicating the influence of past values on future behaviour across multiple time points. Their forecasting power for these two variable based on each other is also explored to offer insights into the physical processes within the evolving simulated dynamic system.

Overall, the results underscore the added value of convection-permitting models in providing more realistic simulations of local dynamics of extremes. The identified cross-correlation structures from the CPMs are valuable for exploring opportunities to design AI engines based on weather generator algorithms that use stochastic differential equations. Using CPM simulations, these weather generators can be employed to develop AI approaches for rapid decision support tools aimed at stakeholders facing extreme weather events related to compound risks of temperature and precipitation.

How to cite: Chun, K. P., Octavianti, T., Tyralis, H., Papacharalampous, G., da Rocha, R. P., Toker, E., Ezber, Y., Danaila, L., Halladay, K., and Kahana, R.: Exploring Continental Convection-Permitting Model Simulations for South America: Cross-correlation Dynamics between precipitation and temperature time series at São Paulo, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-6792, https://doi.org/10.5194/egusphere-egu24-6792, 2024.

Given that cities concentrate more than half of the global population, it becomes crucial to assess the potential impacts of future climate change on cities. This study employs the Pseudo Global Warming (PGW) methodology to replicate recent heatwave (HW) episodes in the Metropolitan Area of Barcelona (AMB) under projected climate conditions until the year 2100. Initially, we identify all the HW events in the AMB over the past three decades (1991-2020) and simulate these HWs using the high-resolution Weather and Research Forecasting model (WRF) with the urban parameterizations BEP+BEM. 

Subsequently, the HWs observed in the last 30 years are replicated under mid-century (2041-2070) and end-century (2071-2100) climate conditions based on the SSP370 scenario. This scenario considers a future where greenhouse gas emissions and temperatures consistently rise, reflecting current climatic trends and geopolitical realities, including regional conflicts. Anticipated CO2 emissions are forecasted to nearly double from present levels by the year 2100.

The contrast between recent and future HWs is examined not only in terms of temperature and relative humidity but also concerning the synoptic patterns responsible for generating HW conditions. The findings reveal a potential increase in geopotential height by up to 100 geopotential meters (gpm) by the end of the century, reaching values of up to 6050 gpm. Average maximum 2-m air temperatures are projected to rise by 2.5°C during the mid-century and 4.2°C by the end of the century. The most significant temperature anomalies (deviations from the mean temperature) are associated with persistent and stable synoptic patterns, which are projected to increase the most in frequency and intensity. The findings on relative humidity reveal a general decrease over the AMB, with a peak value of -16.2% in the west of the domain during the PGW-END.

How to cite: Ventura, S., Miró, J. R., Segura-Barrero, R., Chen, F., Martilli, A., Liu, C., Ikeda, K., and Villalba, G.: Determining the intensity of future heatwave episodes at urban scales: the case study of the Metropolitan Area of Barcelona, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-12016, https://doi.org/10.5194/egusphere-egu24-12016, 2024.

Extreme weather and climate events such as heat waves, droughts or heavy precipitation are already impacting urban areas worldwide, and such extremes are expected to become more frequent and/or severe with climate change. For vulnerability assessment and climate resilient urban planning, local decision-makers and stakeholders need high-resolution climate information that is tailored to their needs according to different geographical contexts (e.g. through the representation of mountainous areas, coastal lines or city characteristics). They also need information on the appropriate time scale, from specific events of a few days to decade-long statistics. Today, regional climate information often comes from global climate models that are downscaled to the local scale using statistical tools or regional climate models (RCMs) such as those used in the CORDEX initiative.

Longterm RCM simulations achieve horizontal resolutions of the order of ten kilometers and offer added value in certain respects compared with their global counterparts, but remain insufficient in certain specific geographical contexts such as the representation of cities, highly heterogeneous mountainous areas or along coastlines. The latest generation of RCMs, known as Convection Permitting Regional Climate Models (CPRCMs), now reach a spatial resolution of a few kilometers and can better represent heterogeneous land surfaces, with the potential offering a new quality of climate information better suited to local applications.

Here, we compare some evaluation simulations (e.g. driven by reanalysis) carried out as part of the EURO-CORDEX initiative (12,5 km RCM) and the CORDEX Flagship Pilot Study on Convection (3 km CPRCM) over the period 2000-2009. We analyze their ability to represent the urban climate of different European cities and the differences resulting from choices in urban parameterizations, land cover representation approaches (dominant coverage or fractional approaches) and land cover databases. We show that:

• For most European cities, RCM simulations have a too coarse resolution; for example, for all coastal cities, the points that should be considered urban are mainly covered by water.

• CPRCM simulations enable these areas to be better represented thanks to the increased resolution, but there are significant differences depending on how the different land covers are represented in a grid cell and how urban areas are simulated.

• Depending on the meteorological variables of interest, some of the simpler urban parameterizations (altered slab) give results that are relatively close to the more sophisticated ones (multi-layer urban canyon).

• While the increased complexity of CPRCM simulations enables urban climate to be better represented, it also increases the differences between simulations and makes it more difficult to quantify uncertainties and synthesize results into a general assessment (which is often needed by decision-makers) underlining the growing need to use ensembles of climate models for impact assessment.

How to cite: Le Roy, B. and Rechid, D.: Added values and uncertainties of convection permitting regional climate model simulations for urban impact studies over Europe, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-11048, https://doi.org/10.5194/egusphere-egu24-11048, 2024.

The past 10 years of research proved that regional convection-permitting models (RCPMs) more realistically represent sub-daily statistics and extremes compared to GCMs and RCMs thanks to the possibility to switch off the parameterisation of convection at this resolution. Now, thanks to recent computational advancements, GCMs are approaching convection-permitting resolution (GCPM), but little is known on their performance at climatological scale over Europe.

Here we compare two 5-year GCPM simulations performed with IFS and ICON, respectively at 9 and 5km, within the NextGEMs project against the multi-model RCPM ensemble at circa 3 km run under the CORDEX Flagship Pilot project on Convective Phenomena over Europe and the Mediterranean (FPS Convection). The analysis focuses on the representation of sub-daily precipitation characteristics between GCPMs in comparison with the RCPM ensemble and several regional observational datasets over the greater Alpine region. In additional, the impact of a higher resolution (5km instead of 25km) of the ocean model is investigated thanks to an additional GCPM run. The natural variability of the GCPMs is evaluated with a bootstrapping approach and put in relation with the total and model uncertainty of the RCPM ensemble.  

Having GCMs that realistically represent the large-scale dynamics as well as the local scale process would be a crucial step forward and provide further confidence on the climate projections and support the Destination Earth project of the European Community.

How to cite: Fosser, G. and Bordoni, S.: Lessons learnt on convection-permitting models and their uncertainty at both global and regional scale , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-10431, https://doi.org/10.5194/egusphere-egu24-10431, 2024.

Convection permitting climate models (CPMs) display much improved present-day rainfall statistics at local scales as compared to common regional and global climate models. Yet, because CPMs are computationally very demanding, runs are short — typically covering 10 to 20 years  only  —  which makes it hard to distinguish the changes due to global warming from the noise due to internal variability. In addition, runs cover a limited set of changes at larger scales as only few global climate models have been downscaled so far. This challenges the representativeness of the results. Here, we discus these issues within the context of the production of the Dutch climate scenarios issued in fall 2023. We use spatial pooling of information to improve signal to noise. To produce scenarios for local rainfall extremes, we combined information from the CPMs with information from CMIP6 and one RCM (RACMO) using a simple scaling framework. From the CPMs we derived sensitivities of changes in rainfall intensity to surface dew point temperature change. By using spatial pooling and by taking out rain frequency change (using wet conditional statistics) a reasonable collapse of the data of 7 CPM simulations could be obtained, with typical dependencies between 1 and 2 times the Clausius Clapeyron relation. The change in rain frequency and the dew point temperature are derived from a  set of RACMO simulations using pseudo-global warming perturbations derived from CMIP6 combined with a simple perturbed physics method. With these RACMO simulations we covered a range in large-scale conditions compatible with CMIP6.  Subsequently, rain intensity change and frequency change are combined using a transformation of the observed rainfall distribution.  In this way, we could produce a set of climate scenarios for daily and hourly precipitation extremes covering a wide range in global change conditions. Besides these changing rainfall statistics, we also analyzed the spatial temporal characteristics of showers in order to investigate whether showers become larger in scale in the future climate.

How to cite: Lenderink, G., de Vries, H., and van Meijgaard, E.: Combining convection permitting modeling results with CMIP6 global climate model results to produce scenarios for local precipitation extremes, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-10660, https://doi.org/10.5194/egusphere-egu24-10660, 2024.

How to cite: Sun, W., Li, J., Yu, R., Li, N., and Zhang, Y.: Exploring changes of precipitation extremes under climate change through global variable-resolution modeling, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-3009, https://doi.org/10.5194/egusphere-egu24-3009, 2024.

Thunderstorm-related severe weather, in particular hail, causes extensive damage to life and infrastructure in the Alpine region. However, changes in hail impact due to a warmer climate are still not fully understood. In the scClim project, convection-permitting regional climate simulations over Europe using the model COSMO with a ~2.2 km horizontal resolution have been conducted for present-day climate conditions (2011-2021) and a climate scenario with a 3°C global warming using a pseudo-global-warming approach. ERA5 reanalyses were used as boundary conditions and a CMIP6 simulation (MPI-ESM1-2-HR) to infer the large-scale climate-change signal. The integrated online diagnostic HAILCAST is used to calculate maximum hail size. The simulations provide total precipitation and maximum hail size estimates every 5 minutes, which allows for hail cell tracking in the climate simulations and the analysis of hail events in a warmer climate. Validation of the present-day simulation against observations of temperature, precipitation and hail shows an overall good model performance. For hail in particular, radar-based, station-based and crowd-sourced observations have been used to assess the model performance in simulating hail on spatial, diurnal and seasonal scales. The validation outcome encourages further study of the climate signal of hail as simulated with the pseudo-global-warming approach. We will show projected changes in the spatial distribution and seasonal cycle of hail over Europe as well as changes in lifetime, storm area and location of hail cells due to a 3°C global warming.

How to cite: Thurnherr, I., Cui, R., Velasquez, P., Brennan, K., Wilhelm, L., Wernli, H., Steger, C. R., and Schär, C.: How does 3°C global warming affect hail over Europe?, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-11130, https://doi.org/10.5194/egusphere-egu24-11130, 2024.

Past studies have shown that in orographically complex terrain, observed extreme precipitation intensity is impacted by elevation in different ways at different durations. Convection-permitting climate models (CPMs) are receiving increasing attention thanks to the more realistic representation of extreme sub-daily precipitation compared to coarser climate models. Two almost still unexplored themes concern: i) CPMs' ability to represent the observed relationship between precipitation and topography and ii) how the model ensemble uncertainty depends on elevation. To address these questions, we evaluate sub-daily extreme precipitation from an ensemble of eight CPM members (reanalysis-driven simulations) on topographically diverse terrains. We use observed data from rain gauges as benchmark. The analysis is conducted over the Eastern Italian Alps, where a strong relationship between precipitation sub-daily extremes and topography is observed (Dallan et al., 2023). We apply a non-asymptotic statistical approach (Simplified Metastatistical Extreme Value, SMEV) to estimate extreme precipitation return levels and assess their intra-model and inter-model uncertainties using a bootstrapped samples method. It is shown that the ensemble mean describes in a realistic way the precipitation extremes, with fractional standard errors of the mean-over-the-ensemble return levels ranging between 0,16 (24 hrs duration, 2 yrs return time) to 0,41 (1 hr duration, 100 yrs return time). We found that, compared to rain gauges, CPMs systematically underestimate extreme return levels in lowlands, whereas overestimate them at higher altitudes. Nevertheless, the CPMs can capture the relationship between rain depth and elevation, which is particularly important for 1-3 hrs duration. While the intra-model uncertainty decreases systematically with elevation at all durations, a more complex behaviour is observed for both inter-model and total uncertainty. These findings help to characterize the impact of elevation on the ensemble of CPM simulations, which is particularly required for the applications of these simulations for adaptation to future flood risk.

REFERENCES
Dallan, E., Marra, F., Fosser, G., Marani, M., Formetta, G., Schär, C., & Borga, M. (2023). ID56. How well does a convection-permitting regional climate model represent the reverse orographic effect of extreme hourly precipitation? Hydrology and Earth System Sciences, 27(5), 1133–1149. https://doi.org/10.5194/hess-27-1133-2023.

How to cite: Correa Sánchez, N., Dallan, E., Marra, F., Fosser, G., and Borga, M.: Evaluating sub-daily extreme precipitation from an ensemble of convection-permitting simulations: the role of topography., EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-11157, https://doi.org/10.5194/egusphere-egu24-11157, 2024.

Convection-permitting climate models (CPMs) have demonstrated enhanced capability in capturing extreme precipitation compared to convection-parameterization models. Despite this, a comprehensive understanding of their added values in daily or sub-daily extremes, especially at local scale, remains limited. In this study, we conduct a thorough comparison of daily and sub-daily extreme precipitation from HCLIM3 and HCLIM12 across Norway, divided into eight regions, using gridded and in-suit observations. Our main focus is to investigate the added values of HCLIM3 compared to HCLIM12 for precipitation extreme indices at daily and sub-daily time-steps on both local and regional scales. We find that the HCLIM3 better captures the maximum 1-day precipitation (Rx1d) at most of the regions except south-western region. Notably, the performance of HCLIM3 in capturing Rx1d shows a notable coastal-inland division, overestimating along the coastal areas and underestimating in the inland regions. In general, HCLIM3 better matches observations than HCLIM12 for daily and sub-daily precipitation extreme indices at regional scale in Norway. However, at the local scale, neither HCLIM3 nor HCLIM12 can capture the temporal evolution of Rx1h during 10 years, except one station near Oslo (eastern region), where only HCLIM3 fits the observations. In general, HCLIM3 performs better than HCLIM12 on Rx1d and Rx1h in Norway with the mean of bias distribution closer to zero, although it varies a bit among regions (for example, HCLIM3 performs worse in the south-western region). In addition, the seasonality of Rx1h can be also better captured by HCLIM3 at both regional and local scales, while HCLIM12 tends to underestimate hourly extremes. In a future warming climate, HCLIM3 with higher Clausius-Clapeyron (CC) scaling, exhibits a higher increase than HCLIM12 in the Rx1h and Rx1d over most regions of Norway except southern and south-west regions. Under global warming, short-duration extreme events with greater CC scaling have a higher increase rate than long-lasting events. This study highlights the importance of more realistic convection-permitting regional climate predictions and projections in providing reliable insights into the characteristics of precipitation extremes and their future changes across Norway's eight regions. Such information is crucial for effective adaptation management to mitigate severe hydro-meteorological hazards, especially for the local extremes.

How to cite: Xie, K., Li, L., Sobolowski, S., Chen, H., and Xu, C.-Y.: Convection-Permitting Climate Models: Present and Future Insights on daily and sub-daily Extreme Precipitation in Norway, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-16029, https://doi.org/10.5194/egusphere-egu24-16029, 2024.

In September 2023, Storm Daniel hit the central Mediterranean and became the deadliest storm in the recorded history of the region. The storm originated from a low-pressure system around 4^th September, which genesis can be attributed to an omega block centred in southern Europe. Then, it evolved into a Mediterranean tropical-like cyclone (medicane), impacting both the northern and the southern Mediterranean shores before dissipating around 12^th September.

The storm particularly impacted Greece and Libya and, although the casualties and other major consequences are closely linked to significant infrastructure failures in Libya, both countries registered record-breaking rainfall amounts. For example, Zagora (Greece) experienced 754 mm in just 18 hours and Al-Bayda (Libya) saw a record highest daily rainfall of 414 mm. These events require an extraordinary supply of water vapor to maintain such rainfall rates. In the complex interplay of factors contributing to the development and intensity of weather systems like Storm Daniel, the Sea Surface Temperature (SST) stands as a likely primary driver. High SSTs provide not only the necessary energy, but also the moisture required to fuel the cyclone.

Over the months preceding Storm Daniel, the Mediterranean SST has consistently reached anomalously high levels, which was potentially a key ingredient in shaping the storm characteristics. To quantify the influence of local SST on the storm intensity, we used five ensembles of convection-permitting simulations (2 km) with an atmospheric model, which each of the ensemble members were initialized at different times. The five ensembles vary on the atmospheric and SST boundary and initial conditions, which were generated using different approaches to create counterfactual scenarios, from a simple removal of the mean climatological difference to an innovative data-driven method, which removes the long-term climate change signal correlated to global warming from SST. Combining these different estimates of atmosphere and SST counterfactual scenarios, we could quantify the relative contribution of global warming through local high SSTs and remote factors to rainfall amounts by Storm Daniel. In addition, we used a back-tracking algorithm to determine the source of water vapor that precipitated over Greece and Libya to understand the differences between the two phases of the event and the role of local SSTs. Our results show that local SST was crucial on the Libyan phase of the storm, while the rainfall amounts registered in Greece were mainly driven by remote factors. Also, the comparison of the different ensembles showed that the effects of long-term trends in SST are important in Libya, but the dominant contribution comes from the anomalous high SSTs that the region has recently experienced, which cannot be directly explained by mean climatological changes. In fact, these exception conditions are responsible for most of the record-breaking rainfall amounts observed during the second phase of the storm.

How to cite: Argüeso, D., Marcos, M., and Amores, Á.: The influence of high Mediterranean Sea surface temperature on Storm Daniel intense rainfall, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-12651, https://doi.org/10.5194/egusphere-egu24-12651, 2024.

The detection of local climate change signals, in particular those related to extreme events, is challenging due to the large internal variability of the climate system. The BMBF-funded project ClimXtreme Module B-CoDEx focuses on improving the signal-to-noise ratio of climate change signals in extreme weather events using innovative data compression methods.

This study uses principal component analysis (PCA) for spatial extremes (Cooley and Thibaud, 2019) to analyse heatwaves and droughts over the northern hemisphere. An extremal pattern index (EPI) is introduced as an integrative measure of the intensity and spatial extent of an extreme heat anomaly. Its bivariate extension is used to account for simultaneous spatial extremes in two variables. EPI provides us with a compact description of heatwaves. We see, for example, that preceding precipitation deficits significantly influence the development of heatwaves, and that heat waves often coincide with instantaneous short-term droughts. 

To investigate extreme hourly precipitation, a scale-dependent decomposition using the dual-tree wavelet transform is proposed, as described e.g. in Buschow and Friederichs (2021). For this study, we rely on reanalysis data (COSMO-REA6, CERRA) over Germany. A comparison of the two datasets regarding their representation of large- and small-scale events shows significant differences, especially for the small-scale events. Furthermore, we apply established methods to perform a scale-dependent detection of extreme precipitation and to reveal trends that are hidden by variability on other scales. 

How to cite: Szemkus, S. and Friederichs, P.: Investigating heatwaves/droughts and convective precipitation extremes using compact descriptions of spatio-temporal fields, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-18175, https://doi.org/10.5194/egusphere-egu24-18175, 2024.

In the last 10 years, the very high resolution regional climate models have started to be used and recently the newly available regional climate model ensemble for the Great Alpine region, at the convection permitting (CP-RCM) resolution (> 3 km), has been released by the CORDEX Flagship Pilot Study on Convective phenomena at high resolution over Europe and the Mediterranean (FPSCONV). At such resolution, the improvement of the representation of local hydrological processes becomes relevant because the climate impact on the hydrological cycle at that scale is expected to be much better captured.  

To this aim, the CETEMPS hydrological model (CHyM) is used coupled off-line with the different CP-RCM ensemble members.  The model has been run in two different configurations, using either temperature and precipitation from the driving CP-RCM or directly the runoff. The hydrological simulation ensemble has been validated against local station data for the Po river and central Italian river basins, by using hydrological indicators, such as the Kling–Gupta efficiency (KGE). The climate change projections are compared with previous lower resolution simulation driven by convection parametrized regional climate models from the Euro-CORDEX ensemble.  

How to cite: Vargas-Heinz, L., Coppola, E., and García-Valdecasas Ojeda, M.: Impact of climate change on the hydrological cycle of the Great Alpine region by means of regional climate convection permitting high resolution simulations and hydrological model simulations. , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-10350, https://doi.org/10.5194/egusphere-egu24-10350, 2024.

Climate change can involve changes in mean conditions, and in their variability on short to long timescales. But which of the two  is more important for our future climate?  We present a study indicating that for the number of extreme precipitation days, changes in climate variability dominate over  changes in the mean state. This analysis is based on three large ensemble simulations across three CMIP6 models (MPI-ESM1-2-LR, CanESM5, and ACCESS-ESM1-5). Here, we decompose the total changes in daily summer precipitation and daily maximum temperature into mean and variability components (standard deviation and skewness of the daily probability density functions).  Our key findings are that:1) Changes in climate variability (i.e., day-to-day variability of precipitation and changes in the precipitation distribution) have a more pronounced impact on extreme precipitation events than changes in the mean state. 2) In contrast, changes in the mean temperature state play a more dominant role in determining overall changes in daily temperature. These insights  are valuable for understanding the mechanisms driving extreme weather events and  highlight the need to consider daily variability changes in climate change impact assessments.

How to cite: Nordling, K., Samset, B., and Fahrenbach, N.: Climate variability outweighs influence of climate mean on summer precipitation extremes, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-4916, https://doi.org/10.5194/egusphere-egu24-4916, 2024.

The frequency and severity of extreme weather events, including temperature and precipitation extremes, have been increasing globally due to human-induced climate change. The Black Sea Basin (BSB), with its complex topography and strong air-sea interactions, is particularly susceptible to climate change and serves as a hot-spot for studying regional climate extremes. To obtain reliable information in BSB, high-resolution convection-permitting simulations are necessary. In this research, we performed convection-permitting climate simulations for historical (2005–2014) and future (2061–2070) periods to investigate the changes in temperature and precipitation extremes and underlying mechanisms based on the SSP3-7.0 climate change scenario over the BSB. To achieve this, we downscaled the CMIP6-based MPI-ESM1.2-HR outputs to 3 km horizontal resolution using the WRF model. The future simulation demonstrates an increased exposure to warm extremes as indicated by the positive change of the TX90P index by about 18% and an increase of the heat wave duration index (HWDI) reaching 55 days per year over the BSB. These changes primarily occur over the highlands of Eastern Anatolia due to enhanced land-atmosphere interactions. In March, a change in low-level circulation leads to a sudden warming of approximately 6°C and an early onset of the melting season, resulting in a 20% reduction in snow cover over Eastern Anatolia. This shift increases extreme temperatures due to a substantial snow albedo feedback caused by a 10% reduction in surface albedo in this area. Furthermore, our analyzes highlight the intensification of daily and sub-daily precipitation along the coastal regions of the Black Sea. Particularly in winter and autumn, the ratio of daily extreme precipitation amounts to the seasonal total precipitation (R90PTOT index) reaches 45% in the future over the eastern Black Sea. Additionally, daily precipitation probabilities shift towards higher values for extreme precipitation amounts in the same area with maximum precipitations exceeding 280 mm/day. At the sub-daily scale, this region experiences an intensification in hourly precipitation throughout the day due to a 22% increase in low-level moisture flux resulting from 1°C warmer sea surface temperatures in winter. The increased extreme precipitation in the autumn is associated with the intensification of afternoon precipitation along the Black Sea coasts of Türkiye. This study emphasizes the importance of convection-permitting climate simulations in improving our understanding of climate extremes in the topographically complex BSB. It provides valuable insights for mitigation and adaptation efforts in this climate change hot-spot.

Acknowledgment: The numerical calculations reported in this paper were fully performed at TUBITAK ULAKBIM, High Performance and Grid Computing Center (TRUBA resources).

How to cite: Kelebek, M. B., Batibeniz, F., and Önol, B.: Highlighting future climate extremes in CMIP6-based convection-permitting simulations over the Black Sea Basin, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-733, https://doi.org/10.5194/egusphere-egu24-733, 2024.

When cold, dry air travels over a relatively warmer lake, lake-effect snow (LES) develops due to an increase in moisture flux from the lake to the atmosphere, which in turn promotes cloud formation and subsequent precipitation. A destructive LES storm struck the Buffalo region in New York, from November 17-20, 2022. Buffalo, located at the eastern end of Lake Erie and subject to winter winds that sweep across the lake, was inundated with nearly 7 feet of snow, prompting the declaration of federal emergencies by multiple counties. The LES storm highlighted the need for at-risk communities to enhance their preparedness for comparable future incidents. Using a cloud-resolving 4 km scale, we investigated how such an LES storm might manifest in a warmer future climate by employing the Pseudo-Global Warming (PGW) method and a two-way coupled lake-atmosphere regional climate modeling system. The modeling system comprises a two-way coupled Weather Research and Forecasting (WRF) model and a Finite Volume Community Ocean Model (FVCOM)-based three-dimensional lake model. Under the PGW methodology, the future atmospheric forcing necessary for our regional climate modeling system was derived from a reanalysis climate dataset by incorporating projected atmospheric changes from a variety of CMIP6 earth system models. Furthermore, we integrated the warming signals in the lakes by utilizing the projected lake conditions obtained from a regional climate modeling system that was previously established and also incorporated an FVCOM-based lake model. According to our findings, the total storm precipitation for such an event by the end of this century could increase by 14% under a high-emission scenario, with an increase in rainfall at the expense of snowfall. Under the present-day climate conditions, snowfall was the primary type of precipitation experienced during the event. However, in a warmer future climate, the distribution of precipitation might be nearly equal between snowfall and rainfall. By conducting two additional simulations in which either the lake or atmosphere is warmed individually using the projected future conditions, we found that the warmer lakes primarily contributed to the increase in storm precipitation through increased evaporation, while the warmer atmosphere primarily influenced the form of storm precipitation during such an LES storm in the future.

How to cite: Kayastha, M., Xue, P., Huang, C., Wang, J., Yang, Z., Pringle, W., Chakraborty, T., Qian, Y., and Hetland, R.: How Could Lake-Effect Snow Storms Evolve in a Warming Future Climate?, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-4436, https://doi.org/10.5194/egusphere-egu24-4436, 2024.

In recent decades reanalysis products have emerged as a pivotal resource for numerical model evaluations, significantly enhancing our understanding of Earth’s system. They have also been employed in various projects aimed at climate monitoring and assessment of climate change impacts. In this study, we present first results from ongoing work aimed at creating a first of its kind high resolution reanalysis ensemble for Austria. ECMWF's ERA5 ensemble is downscale to a 2.5 km resolution by employing three-dimensional variational assimilation (3DVAR) system available in AROME. Upon completion, this dataset will provide spatially, temporally, and physically consistent 3D and 2D atmospheric fields spanning from 2012 to 2022. The presented analysis focused on representation of three distinct extreme precipitation events simulated in a one and a half year long simulation (01-01-2021 to 30-06-2022). The reanalysis ensemble is compared with operational weather models and a high resolution (1 km x 1 km) gridded observational reanalysis. Based on statistical scores, all variations are ranked. In general, the results are on par with our operational models, however, some ensemble members exhibit slightly better performance compared to our operational models, which highlights the advantages of employing an ensemble system.

How to cite: Awan, N. K., Wittmann, C., Wastl, C., and Meier, F.: High resolution regional re-analysis ensemble for Austria, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-20433, https://doi.org/10.5194/egusphere-egu24-20433, 2024.

Islands of French Polynesia, located in the tropical Pacific Ocean, are small – Tahiti, the largest is about 50 km long – and can exhibit complex orography due to their volcanic origin. In order to simulate properly the atmospheric flow and convective motions over these islands, the non-hydrostatic model AROME is used at high-resolution (2.5 km) to produce a 20-year simulation of the climate over the Society Islands as well as part of the Tuamotu archipelago and Austral Islands. This simulation enables to evaluate AROME ability to simulate these island climates, particularly in terms of rainfall and wind.

AROME is significantly better than the quasi-hydrostatic regional climate model ALADIN with coarser resolution (20 km) at simulating the climate of French Polynesia, and provides a better description of this climate than the available gridded observation products.

By comparing model’s precipitation to observed precipitation at weather stations, results generally show a correct simulation of mean daily rainfall and diurnal cycles. There is however a dry bias for windward stations over Tahiti and a wet bias for leeward stations. These biases remain relatively weak and less pronounced than the biases of other gridded datasets such as IMERG and CMORPH satellite estimates.

The model also simulates winds that compare well to in situ observations and other gridded data. The typical island effect on low-level circulation is well simulated by AROME contrary to ERA5 and satellite data.

How to cite: Casnin, A., Bellon, G., Hopuare-Klouman, M., Caillaud, C., Laurent, V., and Martinoni-Lapierre, S.: High-resolution simulation of French Polynesia climate, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-11440, https://doi.org/10.5194/egusphere-egu24-11440, 2024.

This study employs the latest versions of global climate models (GCMs) from the Coupled Model Intercomparison Project Phase 6 (CMIP6) to evaluate climate extremes in Türkiye from 2015 to 2100 under two future scenarios, SSP2-4.5 and SSP5-8.5. Utilizing a number of high resolution CMIP6 models and different scenarios over the full projection period make this study unique over the region. To downscale coarse-resolution climate models to approximately 9 km (0.1° × 0.1°) spatial resolution, Quantile Delta Mapping (QDM) is employed. The downscaling process utilizes the European Centre for Medium-Range Weather Forecasts Reanalysis 5-Land (ERA5-Land) dataset as the reference data. Analysis of 12 extreme precipitation indices (EPIs) and 12 extreme temperature indices (ETIs) between 2015 and 2100 consistently indicates an increased frequency and intensity of extreme weather events in Türkiye under both future scenarios. The SSP5-8.5 scenario predicts a higher degree of water stress compared to SSP2-4.5, with a 20% reduction in total precipitation in the Aegean and Mediterranean regions of Türkiye. Despite an overall decrease in precipitation, the findings suggest an increase in the severity and frequency of extreme precipitation events. This implies that a greater proportion of total precipitation will be contributed by these extreme events. Anticipated trends include an increase in temperature extremes, encompassing both the lowest and highest daily maximum temperatures across all regions of Türkiye. This signifies a warming signal of up to 7.5 °C by the end of the current century. Cold extremes also exhibit a tendency towards warming, as evidenced by a significant decrease in the number of ice days across all areas. This trend may potentially result in less snow accumulation, which negatively affects various sectors.

How to cite: Gümüş, B., Oruç, S., Yücel, İ., and Yılmaz, M. T.: Assessing Future Climate Extremes in Türkiye: A High Resolution CMIP6-based Analysis, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-18290, https://doi.org/10.5194/egusphere-egu24-18290, 2024.