The relationship between urban areas and higher temperatures, commonly referred to as the urban heat island effect, is well-established within the scientific community and holds critical relevance for policymakers, given that a significant portion of the global population resides in urban regions. However, much less is understood about how cities may influence precipitation patterns in their vicinity. For instance, temperature changes above urban areas could alter atmospheric stability and potentially trigger convective precipitation.
This study examines the impact of urbanization on the diurnal cycle of both precipitation and temperature using the high-resolution CORDEX FPS-CONV convective-permitting model simulation ensemble over the ALP-3 European domain. The ensemble provides kilometer-scale resolution, offering a robust tool to study the urban climate effect. Analyses of current and future climate scenarios reveal that large cities, such as Paris or Barcellona, can significantly influence the diurnal cycles of both temperature and precipitation and differences are highlighted between costal and continental cities in the Mediterranean region.
The ensemble members exhibit considerable variability in how urbanization affects precipitation, with discrepancies not only across ensemble members but also among different cities within the same model simulation. This variability underscores the challenges in precisely quantifying the impact of urbanization on precipitation patterns and highlights the need for more detailed future studies leveraging high-resolution kilometer-scale model ensembles to better understand the complex interplay between urbanization and local climate dynamics.
How to cite: Coppola, E., de Leeuw, J., Nogherotto, R., Zazulie, N., and Raffaele, F.: Impact of cities on the diurnal precipitation and temperature cycle in a changing climate, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-18394, https://doi.org/10.5194/egusphere-egu25-18394, 2025.
Similarly to weather forecasting techniques, climate projections also aim to achieve very high spatial and temporal resolutions, which are needed both as inputs to impact models and to perform reliable risk assessment studies. This is all the more true for the Mediterranean region and the Italian territory in particular, whose heterogeneous and complex morphology do affect the local climate (highly sensitive to global warming), making this area particularly vulnerable to hydrogeological risks, such as heavy rainfall, landslides and flooding with serious losses of both human lives and economic. We present the results of downscaling CMIP6 global climate projections to local scales for the Mediterranean and Italian regions, aiming to produce high-resolution climate information for assessing climate change signals, with a particular focus on small-scale phenomena and extreme events. We performed hindcast (i.e. ERA5-driven) and historical simulations (driven by the MPI-ESM1-2-HR model) to simulate the present (1980-2014) and future (2014-2100) climate under three different emission scenarios (SSP1-2.6, SSP2-4.5, SSP5-8.5). For each experiment, we used a double nesting approach to downscale global data first to a regional domain, covering the whole of Europe (EURO-CORDEX domain) with a spatial resolution of 15 km, and subsequently to a fine spatial scale domain centered over Italy and the north-western Mediterranean with a resolution of 5 km, (i.e. close to the convection permitting limit resolution). We explore the effects of pushing the resolution to km-scale while still falling within the so-called “gray zone” (5-10 km), where deep convection can still be insufficiently resolved and a parameterization of the deep convection is still needed to fully represent it. We present the analysis of the most relevant Essential Climate Variables (ECVs), and the statistics of extreme events for both the current climate and for end of the century scenarios. Results highlight that the gray-zone model in the configuration here implemented mimics the behavior of a convection permitting model and improves the representation of the mean precipitation field over the entire domain. This improvement is also detectable for heavy precipitation, represented through high percentile of daily precipitation (p95 – p99). We show the multi-scenario projection of the climate signal for both the simulations on the common domain.
This study was carried out within: RETURN Extended Partnership and received funding from the European Union Next-GenerationEU (National Recovery and Resilience Plan – NRRP, Mission 4, Component 2, Investment 1.3 – D.D. 1243 2/8/2022, PE0000005);
ICSC Italian Research Center on High-Performance Computing, Big Data and Quantum Computing and received funding from the European Union Next-GenerationEU (National Recovery and Resilience Plan – NRRP, Mission 4, Component 2, Investment 1.4 – D.D: 3138 16/12/2021, CN00000013)
How to cite: Struglia, M. V., Anav, A., Antonelli, M., Calmanti, S., Catalano, F., Dell'Aquila, A., Pichelli, E., and Pisacane, G.: Effects of increasing spatial resolution towards convection permitting scales in the Mediterranean area, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-6558, https://doi.org/10.5194/egusphere-egu25-6558, 2025.
Recent studies have highlighted the intensification of heavy precipitation events in a warming climate, particularly over orographically complex regions such as the Alps. This study builds on our previous work, which analyzed precipitation scaling rates in kilometer-scale convection-permitting climate models (CPMs) with respect to the Clausius–Clapeyron (CC) relation. Here, we first investigate whether hourly precipitation extremes consistently follow the expected CC scaling in the Alpine region or show deviations indicative of super-CC behavior. Second, we assess the regional variability of precipitation scaling by examining four subdomains in the Greater Alpine Region, each characterized by distinct topographical features and climatic regimes. Third, we explore whether and how present-day observations can be extrapolated into the future.
To address these questions, we use a ten-year, multi-model ensemble of kilometer-scale CPM simulations from the CORDEX-FPS over the Greater Alpine Region, with resolutions of approximately 2.2 to 4 km. This high resolution is crucial for accurately capturing convective processes and extreme events in mountainous terrain. We condition hourly precipitation on local daily temperature within a 25 km radius.
We find that the models in the ensemble show consistent scaling rates in the ERA-Interim–driven evaluation runs. Comparing historical simulation runs to future simulations reveals regional differences in the shift of precipitation scaling curves. Our findings provide insights into the physical drivers of precipitation scaling rates, and the results suggest that local scaling rates can be used to approximate future changes in heavy precipitation.
How to cite: Lehmann, L. S., Fischer, E., Schär, C., and Knutti, R.: Extreme Precipitation Scaling with Temperature in the Alpine region for historical and future CORDEX-FPS simulations, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-13820, https://doi.org/10.5194/egusphere-egu25-13820, 2025.
Increases in surface temperatures and changes in precipitation patterns due to climate change affect crop yields and require adaptation of agricultural systems. High-resolution climate data, especially precipitation, are critical for impact modelling in agriculture and difficult to obtain from general circulation models. Dynamical downscaling with regional climate models (RCM), such as the Weather and Research Forecasting (ARW/WRF) model, is widely used to generate such data. Despite their improvements, RCM rainfall simulations still contain biases that make it difficult, if not impossible, to use them directly in impact models. To address this, bias correction methods have been proposed to improve the performance of rainfall simulations, but they introduce additional sources of uncertainty (e.g. changes in the state of the climate regime) and remain controversial. These persistent problems in the RCM outputs are due to inherited biases in the forcing data, the limitations of the physical schemes and the downscaling protocol itself. The resolution and reliability of the ERA5 reanalyses lead us to compare one- and two-domain downscaling protocols to reproduce the local climate regime and variability over the main French agricultural production basins.
Both protocols share the Euro-Cordex geographical area as their first domain, while the second protocol adds another domain around France. The target grid cell resolution is 8 km. ERA5 reanalyses data forced the WRF parent domain every six hours along (1) the 1979-1985 period, (2) the yield-damaging summer drought of 2003, and (3) the low rainfall spring of 2011 for five agroclimatic zones in mainland France. Spectral nudging is applied only to the first domain, and subgrid-scale cloud-radiation interactions are activated. The study focuses on five agriculturally relevant variables: maximum and minimum temperatures (Tmax and Tmin), potential evapotranspiration (PET), and the annual amount and cycle of precipitation. These variables are critical for crop growth stages, irrigation management, and yield prediction.
The single-domain simulation, although computationally efficient (time, cost), overestimates summer precipitation, both in terms of amount and number of rainy days, and fails to capture drought events in croplands. In particular, this protocol produces more summer convective rain, associated with a higher summer cloud fraction than for the two-domain downscaling, particularly on low clouds. The two-domain downscaling performs better, accurately reproducing annual cycles, precipitation variability and the extreme 2003 drought, although it struggles with the less severe 2011 event. However, the two-domain downscaling amplifies positive biases in Tmax and PET, possibly due to overestimation of incoming shortwave radiation passing through reduced cloud cover and no nudging in the second domain. Bias correction for these variables may be necessary to avoid accelerated crop growth in impact models.
The performance of a direct downscaling of reanalyses to reproduce the local climate at less than 12 km (0.11°) over the Euro-CORDEX domain is questionable for territorial studies in Europe. Despite the limitations on Tmax and PET, the two-domain downscaling is a credible approach for agricultural studies and provides a reliable basis for analysing precipitation extremes and their impact on crops.
How to cite: Cournault, Q. and Castel, T.: Two domains vs single-domain ERA5 dynamical downscaling with WRF over Euro-Cordex improves precipitation hindcast: A 6-year case study over mainland France for agricultural studies, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-10200, https://doi.org/10.5194/egusphere-egu25-10200, 2025.
This work investigates the capacity of several regional climate models to describe the main characteristics of Cierzo, Levante and Poniente, the main regional winds over the Iberian Peninsula, using as the evaluation period 1995-2011, by comparing them against reanalysis. For this purpose, regional wind classification algorithms have been proposed, based on previous detailed studies made. Then three models (REMO, MPIOM-REMO and CNRM-RCSM4) have been selected based their capability to describe those winds for present conditions, to inspect their projections for future climate conditions, under the RCP 8.5 emissions scenario (2006-2099), using MPI-ESM-LR and CRNM-CM5 as the forcing global models for them. Changes are obtained comparing them with the historical period (1950-2005) simulation results. Several results are obtained related to the sensitivity of resolution and parameterizations employed by the models. Thus, spatial resolution seems to be a key aspect to detect these winds, especially in terrestrial flows such as Cierzo. The internal physics of each model also causes increased variability for spatial resolutions larger than 10 kilometres. A low subdaily temporal resolution introduces inaccuracies in the calculation of regional wind events. The effect of using atmosphere-ocean coupled simulations does not show robust results, as it depends on the analzyed flows. In general, models are able to simulate historical frequencies of Cierzo events (100-130 days), Levante and Poniente (150-160 days), which is similar to what has been seen with observations and previous studies. Temporal trends shows that Cierzo extension could decrease by 1.5% of the valley in a statistically significant way by the end of the century. The results also indicate a strong increase of 10-20 annual Levante events depending on the model. Poniente wind shows a weakening of its characteristics for all models, specifically a decrease in the number of annual Poniente events by 5-20 days.
How to cite: Sanchez, E., Gutierrez, C., Lopez-Franca, N., Molina, M. O., Cabos, W., Sein, D., and Ortega, M.: Regional winds over the Iberian Peninsula: evaluation and future projections from an ensemble of regional climate models, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-7307, https://doi.org/10.5194/egusphere-egu25-7307, 2025.
The majority of CORDEX RCMs show an underestimation of historical warming compared to observations, as well as an underestimation of projected warming compared to global climate models. This is in part due to a lack of consideration of changing aerosol concentrations, with a particularly strong effect in Europe leading to a delayed warming. We have developed a new method to address this issue and present the results of the warming-adjusted data. The method adjusts the CORDEX RCM simulations by using a mapping based on large scale warming with only few parameters and minimal interventions, preserving time monotony. The impact of the method is strongest for high emission scenarios but can be demonstrated for all emission scenarios.
An application is shown for a central European region and within this framework we analyze adjusted climate projections. Compared to global climate model experiments, warming-adjusted RCM simulations better capture fine-scale details such as complex orography, yet – by design – feature the same overall temperature evolution across Western Europe. The presented method could also be useful for CORDEX projections for other regions and can provide information for upcoming assessment reports.
How to cite: Börsig, S., Schumacher, D. L., Hauser, M., and Seneviratne, S. I.: What do warming-adjusted CORDEX RCM projections tell us about climate change in central Europe?, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-15870, https://doi.org/10.5194/egusphere-egu25-15870, 2025.
Extreme events cause great financial loss and loss of life across Europe every year, and while the impacts of these events are increasing due to society’s increasing exposure, the hazardous events themselves are projected to change. Accurate projections of these changes are invaluable for the stakeholders responsible for preparing the European cities to withstand future extreme events. They are also of great value and interest to many industries which are heavily exposed to the impacts of extreme events, including insurance, construction, and energy. However, any adaptation requires information that is tailored to the needs and workflow of the decision makers.
In the EU-funded Impetus4Change (I4C) project, we worked with stakeholders to select hazard indicators that are directly applicable to their ongoing work in adapting to climate change in four major European cities. The cities, Barcelona, Paris, Prague and Bergen, were selected because they face different hazardous events and represent a wide range of climates across Europe. There are 19 indicators in total, which primarily focus on extreme temperatures and precipitation, but which also include indices on drought and fire weather. These indicators have now been calculated in 67 models from the 0.11° simulations of EURO-CORDEX, covering all of Europe for the period of 1980 to 2100. They have also been calculated in numerous available convection-permitting simulations over sub-domains of Europe, at the higher horizontal resolution of 3 km. These indices are analyzed for both their changes over the timeseries but also at Global Warming Levels of 1, 1.5, 2, 3, and 4 degrees. In this talk we will present the first analysis of selected indices for the European domain. The full dataset of these indices is planned to be made openly available through an online, user-friendly toolkit as part of the I4C project.
How to cite: Outten, S., Raffaele, F., Zazulie, N., Vandeskog, S. M., and Sobolowski, S.: Stakeholder relevant hazard indicators in regional climate models from the EU-Impetus4Change project, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-17903, https://doi.org/10.5194/egusphere-egu25-17903, 2025.
Cities play a fundamental role in climate at local to regional scales through modification of heat and moisture fluxes, as well as affecting local atmospheric chemistry and composition, alongside air-pollution dispersion. Vice versa, regional climate change impacts urban areas and is expected to increasingly affect cities and their citizens in the upcoming decades. Simultaneously, the share of the population living in urban areas is growing and is projected to reach about 70 % of the world population by 2050. This is especially critical in connection to extreme events, for instance, heat waves with extremely high temperatures exacerbated by the urban heat island effect, in particular during night-time, with significant consequences for human health. Thus, cities are becoming one of the most vulnerable environments under climate change.
Additionally, from the perspective of recent regional climate model development with increasing resolution down to the city scale within convection permitting RCMs, proper parameterization of urban processes plays an important role to understand local/regional climate change. The inclusion of the individual urban processes affecting energy balance and transport (i.e. heat, humidity, momentum fluxes, emissions) via special urban land-surface interaction parameterization of local processes becomes vital to simulate the urban effects properly. This will enable improved assessment of climate change impacts in cities and inform adaptation and/or mitigation options, as well as adequately prepare for climate-related risks (e.g. heat waves, smog conditions, etc.). Actually, IPCC is preparing the Special Report on Cities and Climate Change in 7th assessment cycle, where these aspects will be considered.
We introduced this topic to the CORDEX platform, within the framework of so-called flagship pilot studies on challenging issues and gaps in regional climate change knowledge. The main aims and progress of this activity will be presented, especially an analysis of Stage-0 experiments using case studies of heat wave and convection episode within ensemble simulations for City of Paris with convection permitting RCMs from different groups over the world. Further outlook with preliminary results will be presented as well for long term (10 years) climate simulation with these models, in common strategy to IMPETUS4CHANGE Horizon Europe Project.
How to cite: Halenka, T., Langendijk, G., and Hoffmann, P.: CORDEX Flagship Pilot Study URB-RCC: Urban Environments and Regional Climate Change – Where We Are and Where We Are Going, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-15667, https://doi.org/10.5194/egusphere-egu25-15667, 2025.
The intensification of the water cycle with climate change not only affects hydroclimatic extremes but also water resources, i.e., water availability, with implications for natural and managed systems, including agricultural, industrial and domestic water use. As part of the ongoing Coordinated Regional Downscaling Experiment European initiative (EURO-CORDEX) downscaling CMIP6 GCMs, we contribute with the fully coupled TSMP1 to the EURO-CORDEX regional climate model ensemble. TSMP1 consists of the atmospheric model COSMO, the Community Land Model, and the integrated hydrologic model ParFlow, connected through the OASIS3-MCT coupler. TSMP1 simulates the complete terrestrial water cycle from the groundwater (down to -60m) to the atmosphere. We show initial results from a transient climate run from 1950 to 2100, downscaling the MPI ESM1.2-HR CMIP6 GCM historical and SSP1-2.6 and SSP3-7.0 scenarios over the 12km pan-European CORDEX domain (EUR-12). Simulations are aligned with the CORDEX-CMIP6 simulation protocol and further extend the balanced GCM-RCM matrix. We investigate the future evolution of essential variables related to the terrestrial water cycle, such as the total water storage, groundwater recharge, and water table depth for 30-year mid- and end-of-the-century time slices over PRUDENCE regions. Past hydroclimatic extremes, decadal variability, and future trends are well reflected in the TSMP1 groundwater to top-of-atmosphere representation, which provides physically consistent 4D images of the coupled terrestrial water and energy cycles.
How to cite: Goergen, K., Poll, S., Zhang, Y., and Kollet, S.: Future evolution of European terrestrial water resources in the groundwater-to-atmosphere regional climate system model TSMP1, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-17892, https://doi.org/10.5194/egusphere-egu25-17892, 2025.
Regional Climate Models (RCMs) are dependent on boundary conditions provided by Global Climate Models (GCMs). A significant challenge in regional climate modelling is the "Garbage in – garbage out" problem. Specifically, if the input boundary conditions from a GCM are unrealistic, the RCM cannot rectify this and will consequently produce inaccurate results. While we can avoid using unrealistic GCMs, this issue is critical as all GCMs, even the best performing, exhibit biases. Here we explore whether bias correction of GCM boundary conditions can mitigate this problem and enhance RCM simulations.
In this presentation, we provide evidence that bias correction of boundary conditions leads to improved RCM simulations. We investigate the impact of various bias correction techniques including multivariate bias correction, the role of the relaxation zone in propagating these corrections to the interior of the domain, the importance of maintaining physical consistency within the boundary conditions, and the impact of sub-daily corrections. Our findings demonstrate that corrected boundary conditions enhance multiple aspects of the simulated climate, including the mean climate, extremes, compound events, and synoptic systems. It is worth noting that even with these enhancements, errors in the simulated climate remain, and continued improvements in global and regional climate models are required to produce the most useful and reliable climate projections.
How to cite: Evans, J., Kim, Y., and Sharma, A.: Enhancing Regional Climate Model Simulations through Bias Correction of Global Climate Model Boundary Conditions, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-13856, https://doi.org/10.5194/egusphere-egu25-13856, 2025.
The current phase of Arctic CORDEX, facilitated by the PolarRES project, provides an ensemble of five regional climate models downscaling two CMIP6 global climate simulations selected using a novel storyline approach. The simulations are provided by MAR (University of Liège), ICON (Alfred Wegener Institute), RACMO (University of Utrecht), HCLIM (Metrological Institute of Norway) and WRF (NORCE Norwegian Research Centre). The models provide a hindcast simulation driven by ERA5 data for the period 2001-2020 and scenario simulations for the period 1985-2100 driven by global CNRM-ESM2-1 and NorESM2-MM simulations.
We use the Global Summary of the Day (GSOD) land station data set to analyse the performance of the regional models for five different variables: daily minimum, mean and maximum temperature, daily mean wind speed and daily mean sea level pressure. We use percentiles of seasonal distributions as a measure of comparison, as well as direct comparison of daily time series between models and observations. For precipitation, we use the Global Historical Climate Network land station dataset to analyse model performance based on seasonal mean precipitation.
In the ERA5-driven hindcast simulations, averaged daily root mean square errors show high agreement with station data for both daily mean wind speed (below 2.5 m/s) and daily mean sea level pressure (below 4 hPa), with similar performance for all seasons and percentiles. Except for MAR, temperatures deviate less than 3 K, with the best performance in summer and autumn. The comparison of the percentiles between the ERA5-driven simulations and the averaged daily root mean square errors are in broad agreement.
The ERA5-driven simulations clearly outperform the GCM-driven simulations for all percentiles, seasons and variables in all models for temperature, wind speed and sea level pressure. However, the GCM-driven simulations also outperform the GCMs themselves, again for all percentiles, seasons and variables. Neither the bias patterns of the ERA5-driven simulations nor the bias patterns of the GCMs themselves translate directly into the bias patterns of the GCM-driven RCM simulations, highlighting the added value of the regional simulations. Comparing the pan-Arctic performance of the RCMs, we find that for temperature and mean sea level pressure, the 10th percentile is most often the worst fit compared to observations, with an improvement in performance towards the 90th percentile, independent of forcing, in autumn, winter and spring. For wind speed, however, performance is most often best at the 10th percentile and declines towards the 90th percentile.
For precipitation, the ERA5-driven simulations also tend to be closer to the observations than the GCM-driven simulations, but there are exceptions. For example, in autumn, the NorESM-driven WRF simulation outperforms the ERA5-driven simulation, and the CNRM-driven MAR simulation also outperforms the ERA5-driven MAR simulation.
How to cite: Matthes, H., Mooney, P., de Falco, C., Mottram, R., Landwehrs, J., Rinke, A., Fettweis, X., Lambin, C., Gilbert, E., van de Berg, W. J., van Dalum, C., and Landgren, O.: Performance of the Arctic CORDEX simulations over land analysed from comparison with in situ observations, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-12846, https://doi.org/10.5194/egusphere-egu25-12846, 2025.
Agriculture in East Africa is rain-fed and, thus, depends on the occurrence of precipitation. Given its location around the equator, the occurrence of precipitation in East Africa is characterized by marked seasonality with either one rainy season centred around local summer in the regions that are further away from the equator (except for the Horn of Africa) and two rainy seasons in the regions near the equator and at the Horn of Africa in boreal autumn and boreal spring.
In this study, the extent to which the simulations contributing to the CORDEX-CORE experiment Africa represent the seasonal variation of rainfall in East Africa realistically is investigated. These are simulations for recent decades with three different regional climate models, either forced with observed lateral meteorological boundary conditions or with data from global climate simulations with three different models. The CHIRPS data are considered as observational data of daily rainfall. The seasonal variation of rainfall is described by the characteristics of the mean annual cycle of daily rainfall, e.g., whether it is dominated by an annual or a semi-annual variation, as well as by the timing, i.e., the onset and cessations dates, and the length of the prominent rainy seasons.
The realistic representation of the seasonal variation of rainfall in East Africa in the regional climate simulations is crucial for the validity of future climate scenarios simulated by the respective models and, thus, the potential future impacts of climate change on agriculture in East Africa.
How to cite: May, W.: How well do the CORDEX-CORE simulations capture the seasonal variation of rainfall in East Africa?, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-4020, https://doi.org/10.5194/egusphere-egu25-4020, 2025.
Climate hazards triggered by extreme events have recently gained growing attention due to their potential socioeconomic and environmental risks (Luo et al., 2022). Heatwaves can be categorized into: those occurring only during the day, only at night, and those encompassing both day and night. Although prior studies have extensively explored the independent heatwaves, the compound day-night events and related atmospheric conditions remain underexplored, in particular over North Africa.
This study focuses on analyzing summer compound heatwaves (CHW) in North Africa as represented by ERA5 and the CORDEX-CORE ensemble of regional climate models (RCMs) data in the historical period (1979–2005). According to reanalysis data, CHWs predominantly occur over Morocco, except in the Atlas mountains, as well as in eastern Algeria and Egypt, with an annual average of approximately one event per year lasting 3 to 4 days. The CORDEX-CORE multimodel mean shows CHWs across most of the region, with the exception of the Atlas mountains. RCMs multimodel gives a relatively higher annual duration ranging from 4 to 7 days and a frequency, averaging 1.5 events per year.
Our composite diagnostic analyses of near-surface variables suggest that compound heatwaves are associated with increased solar radiation and clear sky during daytime, combined with an increase in the downward longwave radiation along with the specific humidity during the night. In fact, the increased water vapor during the night enhances the absorption of outgoing longwave radiation and increases the re-emission of longwave radiation back to the surface (Luo et al.,2022; Wu et al., 2023), contributing to nighttime surface warming. The composite of geopotential height at mid-troposphere (500 hPa) and upper-troposphere (200 hPa) show pronounced positive anomalies, associated with extreme daytime and nighttime temperatures during compound heatwaves especially on coastal areas.
The wider spatial distribution of events identified in the multimodel ensemble compared to the reanalysis can be attributed to the overestimation of downward solar radiation in the RCMs across the entire region, in contrast to ERA5 where positive solar radiation anomalies are more localized in coastal areas. A similar pattern is also observed in the specific humidity.
References:
Luo, M., Lau, N.-C. & Liu, Z. Different mechanisms for daytime, nighttime, and compound heatwaves in Southern China. Weather Clim. Extremes 36, 100449 (2022).
Wu, S., Luo, M., Zhao, R. et al. Local mechanisms for global daytime, nighttime, and compound heatwaves. npj Clim Atmos Sci 6, 36 (2023). https://doi.org/10.1038/s41612-023-00365-8
How to cite: Arjdal, K., Driouech, F., and balhane, S.: Exploring Summer Compound Heatwaves in North Africa: Insights from Reanalysis and RCMs, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-11692, https://doi.org/10.5194/egusphere-egu25-11692, 2025.
Islands, especially those with complex topography, are exceptionally vulnerable to climate change due to the dependency of their economies on climate-sensitive sectors like tourism and agriculture. These regions face significant challenges, including rising sea levels, tropical and extratropical cyclones, increasing temperatures, and shifting rainfall patterns. Despite these pressing threats, global climate models (GCMs) often lack the necessary resolution to capture the critical local processes that shape island climates. Similarly, conventional regional climate models (RCMs) frequently fall short in providing the robustness required to address the unique dynamics of these areas. This study seeks to explore two new km-scale regional climate simulations prepared through the European Climate Prediction project over the Madeira and Canary Islands, which are Portuguese and Spanish archipelagos located in the North Atlantic, off the African coast. The simulations are based on two models using different modelling approaches. One simulation was run by the Euro-Mediterranean Center on Climate Change (CMCC) Foundation with a horizontal grid spacing of around 3 km, based on a time slice approach. The RCM COSMO-CLM is used with a three-step nesting at 50, 25 and 3 km grid spacing based on a time-slice approach driven by a global climate model. The other simulation was run by the Swiss Federal Institute of Technology (ETH) in Zurich. The RCM COSMO-crCLIM is used with a two-step nesting at 12 and a grid spacing of around 1 km. This model was using the pseudo-global warming approach for the future-climate simulation, while the current-day simulations are driven by ERA-Interim reanalysis. Both models parameterize shallow convection, while the parameterization is switched off for deep convection.
The analyses focus on the representation of hourly precipitation and temperature indices for the current and future climate: frequency, intensity, mean, and extreme values for the former, and mean and daily maximum values for the latter.
Although the modelling approaches are different, several findings are highlighted: (1) the use of km-scale simulation is essential to properly represent temperature and precipitation mean and extremes over small islands that are characterized by complex topography; (2) the projected changes in temperature and precipitation mean and extremes are qualitatively similar in all seasons except autumn; (3) the differences in the autumn projections are shown to be due to the large-scale driving conditions, which are different for the three simulations. The differences when comparing the signals between the two experimental designs might be related to the configuration of the respective forcing models and parameterizations. This suggests a careful selection of the former and opens up possible extensions of the analysis to other important factors.
The results hope to set the cornerstone in filling an important gap for local climate services, highlighting the need for further coordinated kilometer-scale projections over regions of similar character, that are often neglected by large modelling initiatives. The presented work contributes to filling this gap for local policy makers, stakeholders and climate services.
How to cite: Adinolfi, M., Loprieno, L. L., Demory, M.-E., Zeman, C., and Schär, C.: Current and future climate conditions over Canary islands and Madeira: an overview of two different km-scale COSMO-CLM simulations, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-9326, https://doi.org/10.5194/egusphere-egu25-9326, 2025.
The increasing frequency and intensity of extremely high temperatures anticipated in the future are likely to introduce greater uncertainty and complexity in the development of renewable energy policies. Countries in East Asia, located in the mid-latitudes, are particularly vulnerable to extreme climatic conditions intensified by global warming. Consequently, it is essential to assess recent trends in PVpot (Photovoltaic power potential) and project future changes under scenarios of extremely high temperatures, as temperature plays a critical role in determining solar panel efficiency. This study evaluates the impact of the increasing frequency and intensity of extremely high temperatures driven by global warming on current PVpot, utilizing high-resolution regional climate models over the East Asian domain.
Over the past 44 years, the PVpot associated with extremely high temperature days across East Asia has been consistently higher than the summer mean across all regions. Recent changes in PVpot for extremely high temperature days have shown increases in Korea, central China, southern China, and Japan, whereas no significant changes have been observed in the PV hotspot areas. However, the recent rise in the mean temperature of extremely high temperature days has contributed to a reduction in the proportion of these days occurring during high PVpot conditions across East Asia.
Future projections indicate that the East Asia-averaged summer mean PVpot and PVpot for extremely high-temperature days will decline under all scenarios and future periods. These decreases are expected to intensify toward the late 21st century, with a more pronounced reduction under the high-carbon emissions scenario compared to the low-carbon emissions scenario. Notably, by the mid-and late 21st century, the PVpot for extremely high temperature days is projected to decline significantly in hotspot areas, particularly in northern China and southern Mongolia.
How to cite: Park, C. and Cha, D.-H.: Impact of extreme high temperature on future photovoltaic potential over East Asia, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-8019, https://doi.org/10.5194/egusphere-egu25-8019, 2025.
Coastal jets, characterized by wind maxima at low atmospheric levels, are a prominent feature of Eastern Boundary Upwelling Systems (EBUS) and play a crucial role in regional ocean dynamics and climate. These jets significantly affect environmental processes and human activities, particularly in marine ecosystems and fisheries. Despite their importance, the coastal jet in the Peruvian Upwelling System remains one of the least studied phenomena within EBUS.
This study employs high-resolution (7 km) regional climate simulations using the Weather Research and Forecasting (WRF) model to analyze the characteristics of coastal jets off the coast of Peru. We performed a retrospective simulation for the period 1994–2003, driven by NCEP2 reanalysis data, to characterize the baseline conditions of coastal jets in terms of their frequency of occurrence, intensity, vertical structure, and directional patterns. The identification of coastal jets was based on a detailed analysis of vertical wind and temperature profiles, focusing on wind speed maxima at low atmospheric levels and their association with upwelling events and coastal features. The vertical profiles of wind and temperature were examined at multiple altitudes (from 10 m to 1000 m a.s.l.) to determine the spatial distribution, intensity, and vertical extent of these jets.
In addition to the retrospective analysis, we conducted future climate projections for the period 2086–2095 under the RCP8.5 climate change scenario. The future simulations were forced with climate change signals derived from the CMIP5 ensemble, which includes the differences between monthly mean climatologies for the periods 2080–2100 and 1989–2009. These climate change forcings were added to the NCEP2 reanalysis data to simulate future atmospheric conditions. The future projections focus on the potential changes in the frequency, intensity, and altitude of coastal jets, as well as shifts in their seasonal patterns and directional tendencies.
Results indicate that coastal jets occur year-round, with variations in frequency and spatial distribution. In summer, jets are more frequent and concentrated near the coastline, with intensities between 8 and 10 m.s⁻¹ and altitudes ranging from 200 to 300 m a.s.l. In contrast, winter coastal jets are less frequent but cover larger areas, with intensities between 9 and 11 m.s⁻¹ and altitudes of 400–500 m a.s.l. The predominant direction of the jets is south-southeast, parallel to the coastline, throughout the year, except in winter when significant occurrences are also observed from the southeast.
Under the climate change scenario, the frequency of coastal jets is projected to increase, particularly along the northern and central coasts of Peru. A notable increase of up to 20% in frequency is expected during June, July, August, September, and October, especially north of the Paracas Peninsula (14°S). While the intensity of the jets remains largely unchanged, the vertical distribution of coastal jets is expected to shift, with a tendency towards lower altitudes in future projections.
How to cite: Chamorro, A., Colas, F., Echevin, V., and Tam, J.: High-resolution regional climate modeling of coastal jets and their future evolution in the Peruvian Upwelling System, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-14880, https://doi.org/10.5194/egusphere-egu25-14880, 2025.
In February 2023, the northern coast of São Paulo state (Brazil) experienced the highest 24-hour rainfall ever recorded at meteorological stations operated by the National Institute of Meteorology and the National Center for Monitoring and Early Warning of Natural Disasters (CEMADEN). The Barra da Una station (23.758°S, 45.764°W), for instance, recorded 633 mm of rainfall in 24 hours between 18 and 19 February 2023 (from 1200 to 1200 UTC). Rainfall estimates from the Salesópolis radar also indicated precipitation exceeding 450 mm/day along the coast between the municipalities of Bertioga and São Sebastião. On the other hand, satellite estimates, such as CHIRPS, were unable to capture this precipitation event. In this context, the objective of the study is to analyze the performance of the Regional Climate Model version 5 (RegCM5) in convection-permitting (CP) mode in simulating this extreme daily precipitation event on the northern coast of São Paulo state. A simulation with a horizontal resolution of 4 km, nested in the ERA5 reanalysis, was conducted with a domain over southeastern Brazil. This simulation started on February 17 at 00 UTC. The simulation results were compared with rainfall data measured at CEMADEN stations and precipitation estimates obtained from the Salesópolis radar. The comparisons indicated that RegCM5-CP underestimates precipitation along the coast and misplaces the maximum precipitation. For instance, radar data of accumulated precipitation from 0000 UTC on February 18 to 0000 UTC on February 20, 2023, show the maximum precipitation occurring at the sea-land interface, whereas RegCM5-CP shifts it to the mountainous region inland. Additionally, the model displays other cores with maximum precipitation, such as along the border with Minas Gerais state, which are not observed in the radar data. New experiments are being conducted to test different physical parameterizations to improve the representation of the studied event. The authors thank CNPq, FAPESP and FAPEMIG for the financial support.
How to cite: Reboita, M., Baldoni, T., Silva, P., Miguel, G., Chaves, R., da Rocha, R., and Silva, L.: Performance of the RegCM5-CP in simulating a rainfall extreme event on the northern coast of São Paulo state, Brazil, in 2023, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-5006, https://doi.org/10.5194/egusphere-egu25-5006, 2025.
Cantabria, a region in the north of Spain, known for offering the possibility of skiing and enjoying the beach in less than an hour, has experienced a remarkable growth in tourism in the last 15 years. Although the region only accounts for 1.80% of tourists in Spain, such an influx is remarkable in relation to its size (1.05% of the national territory) and population (approximately 1.23% of the country's population), and the arrival of tourists has a considerable impact on its local economy. Most visitors are nationals, attracted by a mild climate, green landscapes and numerous natural resources. For that reason, attendance displays a clear seasonality, also conditioned by the official holiday schedule, which concentrates most of the visitors in late summer and other key dates, such as Easter. This concentration at specific times of the year, in a context of climate change, poses challenges for the well-being of visitors and the management of tourism infrastructures.
The objective of this study is to analyze the changes in tourists' comfort under different global warming scenarios of up to 4°C through the calculation of a well-known bioclimatic index such as the Universal Thermal Climate Index (UTCI). For this purpose, projected daily climate data of temperature (maximum and minimum values), wind speed, solar radiation and relative humidity have been used through several simulations from Regional Climate Models (RCMs) driven by several General Circulation Models (GCMs). These simulations, belonging to the CORDEX initiative, represent the largest data set available for Europe at a spatial resolution of approximately 12.5 km. Due to the systematic biases in the models, a bias correction method has been applied using ERA5-Land as observational reference.
The results reveal significant changes in tourists’ comfort compared to the historical period, mainly associated with the increase in temperatures. Although variations in other climatic variables are also observed, these are less marked and/or have a lesser effect on comfort. Some specific examples are presented in key tourist locations in the region, related to both sun and beach tourism and winter tourism, among others. This study provides a basis for understanding how climate change will affect the comfort of tourists in the north of Spain, facilitating the development of adaptation strategies to mitigate negative impacts and the identification of emerging opportunities, to ensure the sustainability of the tourism sector in the region of Cantabria.
A.C. and J.B. acknowledge support from PID2023-149997OA-I00 funded by MICIU/AEI/10.13039/501100011033 and by ERDF/EU.
How to cite: Casanueva, A., Conde-Oria, F., Bedia, J., and Rasilla-Alvarez, D. F.: Projected changes of tourism comfort in northern Spain under climate change, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-18283, https://doi.org/10.5194/egusphere-egu25-18283, 2025.
Posters on site: Mon, 28 Apr, 10:45–12:30 | Hall X5
It is well known that the results of climate model simulations differ from observations, and accordingly such projections can lead to different future temperature characteristics for the same region of interest. While the relative changes described by different climate models are of similar magnitude, the absolute temperature characteristics (based on their relative performance compared to observations) can be so different. At different warming levels (WLs, where a given temperature threshold can be calculated from temperature projections relative to a reference period or observations) global climate models (GCMs) can provide valuable information on climate change at the global scale. The main uncertainty factor for different WLs is time relative to a reference period (e.g. 1976-2005). Moving from global to regional scales, from coarser (~150 km) to finer (~12 km) resolution, regional climate models (RCMs) are expected to provide more detailed information than GCMs. For example, RCMs can better capture precipitation extremes at finer resolutions than the driving GCMs, especially over regions with complex topography, illustrating the benefits of high-resolution modelling. Thus, the timing of reaching a given WL can be assessed at regional and local scales based on high-resolution RCM simulations and high-resolution observations available for the region of interest. The REtuning Climate Model Outputs (RECMO) method helps to reduce differences between different RCM simulations by reducing uncertainties arising from the different climates described by different climate models under different WLs. It should be noted that the reference is based on observations and not on the model outputs from which the WLs are determined. It can be argued that the RECMO method may be too selective depending on the performance of the climate models over the region (as RCMs with a relatively large cool bias may never reach that WL). Accordingly, the high-resolution raw and bias-corrected EURO-CORDEX and Med-CORDEX outputs are also used in the present work following the RECMO method for the Carpathian Region. Overall, the new concept helps to reduce differences between climate model simulations and leads to more reliable results with respect to possible future climatic temperature conditions for the region of interest. It should be emphasized that the concept is generally applicable to climate models over any region of the globe, the only limitation being the availability of data.
How to cite: Torma, C. Z.: Connecting climate model projections of temperature change with observations at regional and local scales – REtuning Climate Model Outputs (RECMO method): the Carpathian Region, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-1179, https://doi.org/10.5194/egusphere-egu25-1179, 2025.
Climate change is one of the biggest threads to humanity, and its effects are already detected. According to the IPCC, not only hot extremes, but droughts and precipitation-related extremes have also become more frequent. The lack of precipitation means severe problem to the ecosystems, agriculture and human health, however, intense rainfalls can also cause damages, e.g. flash floods, which are one of the most devastating natural disasters. Therefore, it is important to know, how the precipitation is likely to change in the future.
The main goal of our research is to investigate the projected changes of precipitation over Hungary for the near future (2021–2050) and the far future (2070–2099) with respect to the reference period of 1976–2005. In addition, the aim of our study is to investigate how the choice of the reference dataset and different calibration periods affects the changes. For this purpose, the results of different datasets are compared: raw and bias-corrected RCM projections. In total three bias-corrected RCM based datasets are included in the present study: RCM projections available from the EURO-CORDEX initiative (using MESAN as reference data), the FORESEE-HUN database and an additional bias-corrected database, newly created for this research (referred to as BC-HUCLIM in the following). The bias-correction was carried out by applying the internationally widely used percentile-based quantile mapping method on a monthly level using the most accurate, quality controlled HuClim dataset as a reference. Each database contains the simulations of 5 RCMs (CCLM, HIRHAM, RACMO, RCA, REMO) from the framework of EURO-CORDEX at a horizontal resolution of 0.11° (about 12.5 km). Two Representative Concentration Pathway (RCP) scenarios are used: RCP4.5 and RCP8.5, respectively.
Beside the assessment of the mean precipitation characteristics on different time scales, the following extreme precipitation-related climate indices are analyzed: wet days, very heavy precipitation days, frequency of at least 50 mm 5-day precipitation total, the highest daily precipitation sum and extremely wet days. According to our results, the mean annual precipitation is expected to increase by 10% on lowland areas and by 30% in mountainous areas on average under the RCP8.5 scenario by the end of the 21st century. In the Northern Mountains, the most pronounced changes are shown by BC-HUCLIM, and the raw and bias-corrected RCM simulations using MESAN project the smallest increase. Under the RCP4.5 scenario, the changes remain below 20% and negligible differences are found between the databases. The greatest increase in the annual number of very heavy precipitation days is expected by BC-HUCLIM for the far future in the south-western part of Hungary.
How to cite: Simon, C., Torma, C. Z., and Kis, A.: Projected changes of mean and extreme precipitation in Hungary: comparison of raw and bias-adjusted EURO-CORDEX simulations, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-6439, https://doi.org/10.5194/egusphere-egu25-6439, 2025.
In Ukraine, the consequences of climate change are exacerbated by the military aggression of the Russian Federation (RF) not only in the temporarily occupied territories but also for the entire country, since all resources are primarily directed at strengthening defense capabilities and confronting the enemy. Nevertheless, climate change has not stopped and rather intensified in recent years. At the same time, due to the massive and targeted shelling of RF, almost all generating capacities at thermal power plants in Ukraine have been destroyed, the largest hydroelectric power plants have also been damaged and destroyed, and nuclear plants often cannot operate at full capacity, especially in the summer due to the heatwaves, when temperature in water cooling reservoirs increases significantly and the efficiency of nuclear power plants decreases. On the other hand, due to the same heatwaves, the demand for electricity increases significantly due to the need for air conditioning, which requires redistribution and other planning of electricity generation in the system. That is why Ukraine needs to solve problems simultaneously and plan development strategically, taking into account changed climatic conditions. Moreover, renovation of the country's infrastructure, in particular the energy and communal sectors, needs thorough consideration of the climate changes that are inevitable in the future.
To analyze climate change to date, the E-Obs database of the European ECA&D project was used, and to estimate future changes in indicators, data from 34 regional climate models of the International Coordinated Scaling Experiment for Europe (Euro-CORDEX) were used, which were calculated under two scenarios RCP 4.5 and RCP 8.5 until 2100 with a high resolution of 0.1o.
We analyzed specialized indicators (Climatic Impact-Drivers – CIDs) for the energy sector as follows: heating period (in Ukraine with t<8oC) duration, start and end dates; number of days per year which require the air conditioning (t>22oC); mean temperatures of the heating and cooling periods and heating and cooling degree days (HDD and CDD); as well as the temperatures of the warmest and coldest 5-day periods to determine peak loads on the power system for 3 future periods (2021-2040, 2041-2060, and 2081-2100) vs 1991-2010.
In general by the end of the century, under the RCP 4.5 scenario in Ukraine, all analyzed CIDs may be the same as in the middle of the century under the RCP 8.5 scenario. As for degree days, their decrease in HDD does not compensate for the increase in CDD in the warm period for the high-concentration scenario. Moreover, the changes will occur in different regions differently with a significant decrease in the demand for thermal energy in winter in the north-eastern regions and a significant increase in costs during the air conditioning period in the southern and south-eastern regions with maximum values in the Autonomous Republic of Crimea.
The results obtained are the basis for the development of climate change adaptation strategies for almost all sectors of the economy and should become the basis for further assessment of risks and vulnerabilities of the energy and other economic sectors in Ukraine.
How to cite: Kryshtop, L., Krakovska, S., Shpytal, T., Savchuk, S., Chyhareva, A., and Palamarchuk, L.: Specialized climate indices for the energy sector in Ukraine based on the Euro-CORDEX projections, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-20339, https://doi.org/10.5194/egusphere-egu25-20339, 2025.
Within the Horizon 2020 project PolarRES, a new ensemble of regional climate simulations has been developed using the latest generation of regional climate models (RCMs) for the Arctic. These state-of-the-art RCMs downscale the ERA5 reanalysis over the period 2001-2020, covering the entire Arctic region at a grid spacings of approximately 12km. Furthermore, all simulations follow the Polar CORDEX protocol for the next generation of regional climate projections of the polar regions. This new ensemble of high-resolution climate simulations offers considerable opportunities to advance our understanding of the present-day climate of the Arctic. However, a first step to realising this potential is to evaluate the performance of the regional climate models, highlighting their strengths and limitations. This is also necessary for understanding and interpreting the future projections that will be generated by these RCMs using a novel storylines approach to downscale CMIP6 models.
The work presented here will focus on the simulations of the present-day climate driven by the ERA5 reanalysis. As part of the evaluation process, a clustering technique is applied to reanalysis data to identify regions with similar annual and seasonal characteristics of surface temperature and precipitation. This approach allows for a better understanding of the regional climates of the Arctic, provides a more physically consistent basis for model evaluation, and eases the investigation of model deficiencies in simulating regional scale forcings. This work will focus on the regionalisation of the Arctic for model evaluation and present preliminary results of the application of this regionalisation to the aforementioned Arctic climate simulations.
How to cite: Mooney, P., de Falco, C., Samantaray, A., van de Berg, W. J., Cassano, J., van Dalum, C., Fettweis, X., Gilbert, E., Lambin, C., Landgren, O., Landwehrs, J., Matthes, H., Mottram, R., Orr, A., and Rinke, A.: Performance of the PolarRES and Arctic CORDEX regional climate ensemble, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-12824, https://doi.org/10.5194/egusphere-egu25-12824, 2025.
In the evaluation of high-resolution climate model output, most research focuses on the variables and time-scales where added value is usually expected, e.g. short-term precipitation extremes. Simple temperature characteristics such as means of minimum and maximum temperatures are rarely evaluated, even though shortcomings in the representation of temperature might negatively influence multiple physical processes in the models.
In our research we analyse the representation of minimum and maximum temperatures in convection-resolving models in Austria. We make use of the ERA-Interim driven CORDEX-FPS Convection ensemble in the period 2000-2009, covering the greater Alpine region, and compare it against several available observation-based datasets - ERA5, EOBS, EMO-5 and SPARTACUS.
Using the Austrian climate dataset SPARTACUS as the main reference, we compute the seasonal means of maximum and minimum temperatures and identify season dependent biases. We find notable differences between the CORDEX-FPS simulations and SPARTACUS, however the observations exhibit a certain spread as well. While maximum temperatures are underestimated in winter and spring, minimum temperatures are overestimated in summer and autumn. Consequently, we find that the diurnal temperature range is underestimated throughout the year. We presume that these biases are caused by parameterizations of radiation and cloud-related properties.
Additionally, we investigate the elevation-temperature relationship in the model ensemble and the observations. We identify an elevation-dependent bias in the convection-resolving models for both minimum and maximum temperatures. The difference between the model ensemble and SPARTACUS becomes more negative with higher elevations. As a consequence, the near-surface temperature lapse rate is constantly overestimated in the model ensemble. We assume this might be caused by inadequate parameterizations as well, and potentially the representation of the annual snow cover.
We explore the correlations between the aforementioned properties and parameterized processes like radiation and cloud cover, in order to get a deeper understanding of the physical processes in the models.
How to cite: Kohlhauser, I., Medvedova, A., Maraun, D., and Ban, N.: Evaluation of Minimum and Maximum Temperatures in Convection-Resolving Climate Models (CORDEX-FPS Convection), EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-15839, https://doi.org/10.5194/egusphere-egu25-15839, 2025.
Small islands, particularly those with complex topography and fragile economies reliant on climate-sensitive sectors like tourism and agriculture, are highly vulnerable to climate change. Challenges such as rising sea levels, tropical and extratropical cyclones, increasing temperatures, and shifting rainfall patterns significantly affect these territories. However, current global climate models (GCMs) lack the resolution needed to capture critical local processes essential for these regions. The “FPS on Macaronesian Archipelagos. Convection Permitting projections focused on island processes (FPS-I-Mac)” is a Flagship Pilot Study (FPS) initiative focuses on Macaronesia, an Atlantic region comprising the Azores, Madeira, Cape Verde, and the Canary Islands archipelagos.
Each archipelago exhibits unique climatic characteristics, influenced by its topography and geographical location. For instance, the Azores are the rainiest, while the Canary Islands are more influenced by continental air masses. All four archipelagos experience distinct annual cycles, with heavier rainfall during autumn and winter. Unlike other regions, intense summer convective rain is uncommon.
This communication presents the main objectives and challenges of this FPS:
- Investigate multiscale climatic processes and their interactions to improve climate projections in Macaronesia.
- Assess the influence of sea surface temperature (SST) and aerosols in these oceanic regions.
- Compare high-resolution simulations with standard-resolution models to evaluate their added value in extreme event analysis.
- Create a shared database and produce ensembles of climate projections generated by different dynamical techniques (as models, empirical-statistical downscaling, hybrid techniques as emulators) tailored for Vulnerability, Impacts, and Adaptation (VIA) communities.
- Foster collaboration between scientific communities and end-users.
Expected Impact are, between others:
- Enhanced understanding and modeling of climate in islands with complex topographies.
- Reduction of uncertainties in 21st-century climate projections for the Macaronesian region.
- Provision of accurate data for key sectors such as agriculture, health, energy meteorology, and risk management.
- Strengthened synergies among stakeholders, promoting a fair ecological transition in these vulnerable regions.
The FPS aligns with CORDEX objectives by improving regional climate projections for small islands, which are underexplored in current studies. We will use different regional climate models (RCMs) at convection-permitting resolution, but also empirical-statistical downscaling (ESD), and hybrid strategies for high-resolution simulations, enabling detailed analysis of extreme events. Local and satellite observations associated with reanalysis products will validate these processes. By contributing to global discussions and integrating end-user needs from the outset, this initiative will support both local decision-making and broader climate research in the area during the next 5 years. The current team includes research groups from Portugal, Switzerland, Italy, and Spain, but it is open to new participants in different topics.
How to cite: Diaz, J. P., Rodríguez-Guisado, E., Iturbide, M., Fernandez, J., Adinolfi, M., Vasconcelos, H., Meirelles, M., Sánchez, E., Gaertner, M. A., Argüeso, D., and Soares, P. M. M.: New CORDEX Flagship Pilot Study on Island processes in the Macaronesian Archipelagos (FPS-I-Mac): Objectives and challenges, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-9361, https://doi.org/10.5194/egusphere-egu25-9361, 2025.
The EURO-CORDEX CMIP5-based model simulation ensemble is very large, with 8 GCMs being downscaled by 11 RCMs for three different RCP scenarios, resulting in a total of 136 simulated GCM-RCM-Scenario combinations at the time of this work. Still, the GCM-RCM-Scenario 3-dimensional combination matrix is not at all complete.
With a simple linear ANOVA-based technique some missing simulations can be emulated simply by taking appropriate combinations of linear terms calculated from the matrix of existing simulations. This means that approximate ensemble averages can be calculated, where all GCMs as well as all RCMs have the same weight in the averaging.
We aim at emulating values of various fields for combinations, which have not actually been performed, in order to get a more “democratic” picture
of ensemble means. We will show results for a number of standard variables: Seasonal means of temperature, precipitation, and wind strength as well as some extremes. Also, a complete sub-matrix has been systematically analysed with successive numbers of simulations being left out, in a bootstrap procedure, to estimate variability and errors of ensemble members as well as averages using the ANOVA technique as compared to the complete sub-matrix.
We will demonstrate use and necessary adaptations of this technique for filling the entire EURO-CORDEX matrix based on large sub-sets of all existing simulations.
How to cite: Christensen, O. B.: Estimating democratic averages across GCMs, RCMs, and scenarios in the CMIP5-based EURO-CORDEX simulation ensemble, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-4176, https://doi.org/10.5194/egusphere-egu25-4176, 2025.
Understanding the interaction between energy and water fluxes at the atmosphere-surface interface is essential for advancing knowledge of climate dynamics and variability. This study evaluates the surface water (including soil moisture) and energy flux components, alongside air temperature, in global and regional climate model (GCM and RCM) simulations applied in the NUKLEUS project (funded by the German Federal Ministry of Education and Research, BMBF). The analyses aim to enhance the understanding of the consistency of the process representation between RCMs and their driving global climate models.
In this study, biases are assessed for winter and summer between RCMs and their driving GCMs, using ERA5 as a reference to explore model behavior over both land and ocean. Historical and future climatologies under the SSP3-7.0 scenario are examined as well to explore climate change signal patterns. The work addresses two main research questions: (1) How consistent are biases between GCMs and RCMs? (2) Do GCMs and RCMs exhibit similar climate change signal patterns?
The study evaluates nine simulations: three GCMs from the CMIP6 framework (EC-Earth3-Veg, MIROC6, and MPI-ESM1-2-HR) and their corresponding downscaled simulations with two RCMs (COSMO-CLM6 and ICON-CLM, version 2.6.5). Analyses focus on the European domain at 12 km grid resolution, with detailed assessments of the Mediterranean and Mid-Europe regions, which represent different climate conditions.
Our results reveal partly low consistency in biases and climate change signal patterns across GCMs and RCMs, with significant variations both within and between models. These discrepancies are often seasonal- and variable-specific. Notably, the Mediterranean region exhibits stronger biases compared to Mid-Europe, particularly over oceanic areas. Contrary to expectations of bias propagation from GCMs to RCMs, the study identifies cases where biases are amplified or newly introduced in RCMs. This is particularly evident in MIROC6-driven simulations, where the RCMs react in a plausible way to strong biases of the sea surface temperature, inherited from the GCM.
In summary, this study provides a clearer understanding of biases in RCMs and their underlying causes. Furthermore, the study highlights the importance of assessing surface fluxes across different domains to fully capture the complexity of model performance and enhance the accuracy of future climate extreme projections.
How to cite: Cusinato, E., Braun, C., Feldmann, H., Geyer, B., Ludwig, P., Trachte, K., and Pinto, J. G.: From GCMs to RCMs: Consistency Assessment of Surface Water and Energy Fluxes, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-10693, https://doi.org/10.5194/egusphere-egu25-10693, 2025.
Tropical cyclone (TC) activity in the Caribbean Sea from May to October is related to the structure and dynamics of the Caribbean- Low-Level jet (CLLJ), which has great temporal variability and a maximum of 15 m/s during July, at 15°N, 75°W and 925 hPa. The vertical shear generated by this CLLJ has great seasonal and interannual variability and modulates the inhibition of tropical cyclones, whose vertical movement is essential for their development.
To estimate the potential changes associated with pseudo global warming (PGW) conditions of both TC and the CLLJ, as well as their relationship, analysis of regional numerical simulations was applied using both dynamical and statistical methods to identify local atmospheric structures and processes associated with TC and the CLLJ.
The application of this regional dynamical analysis to evaluate simulations for the Caribbean is analyzed, this under the hypothesis that in active (inactive) years associated to TC, the CLLJ is weak (intense), due to weak (strong) vertical shear in the core of the jet. The dynamical methodology in which this hypothesis will be explained is by correlating the convergence of momentum associated with perturbations and how these perturbations contribute to the acceleration of this low-level jet between of May and July and how this jet contributes to the intensification of cyclones between August and September.
To evaluate the interannual variability of TC on seasonal and interannual scales and their impacts on precipitation, numerical simulations were carried out (control simulations) using the RegCM model in the convection permitting mode with a resolution of 4.5 km and 41 vertical levels from 1 June - 31 October for the years: 1980, 1988, 1995, 1996, 1998, 2004, 2005, 2007, 2008, 2017, years with greater TC activity in the Caribbean Sea. To apply this analysis, two numerical experiments were evaluated, the first one is a control period driven by ERA5 data and the second one a pseudo global warming approach (PGW), based on 19 CMIP5 RCP8.5 models. This is an evaluation of how well a regional numerical model can reproduce the interaction of processes of different spatial and temporal scales in the tropics.
The results of the analysis indicate that the RegCM model adequately reproduces the structure of the CLLJ and its seasonal variability, as well as the TC activity through the kinetic energy associated with perturbations (PKE) between 3 and 9 days of period.
Under PGW conditions there is an increase in the CLLJ (compared to the control simulations) and a decrease in the PKE, this being associated with the increase in vertical shear in the region close to the core of the CLLJ.
The implications of the inverse relationship between TC and CLLJ are discussed in terms of impacts on precipitation in Central America and southern Mexico.
How to cite: Salinas, J. A., Coppola, E., Torres, J. A., Rafaelle, F., and Giuliani, G.: Potential changes applying the pseudo-global warming (PGW) approach in the relationship between tropical cyclones (TC) and the Caribbean Low-Level Jet (CLLJ)., EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-4536, https://doi.org/10.5194/egusphere-egu25-4536, 2025.
Due to the ongoing climate change, there has been an observed increase in atmospheric and sea surface temperatures. This has led to a rise in the frequency of extreme weather events, including excessive precipitation and tornadoes. This study aims to examine the potential changes in extreme weather cases that will amplify their effects, specifically during November, in the Eastern Mediterranean, one of the two regions in Europe most affected by climate change. The analysis is planned to be carried out with the help of high-resolution simulations produced by the numerical weather model WRF-ARW using CMIP6 MPI-ESM1.2 projections. Initially, the months of November with a significant potential for extreme weather events were identified within the MPIESM1.2 global model projection using the SeveR index, a metric designed to estimate the likelihood of severe storm environments characterized by convective rainfall. A series of high-resolution simulations were produced for November in the years 2039, 2057, 2069, 2077, 2079, 2082, and 2097 identified as having high extreme weather potential based on SeveR index. To compare these simulations with the climatic conditions of the November months from 2004 to 2014, additional simulations were produced. A detailed analysis of the monthly total precipitation for November revealed that the highest estimated total precipitation amounts were 683.5 mm and 680.2 mm in Rize Çayeli in 2039 and 2097, respectively, and 959.1 mm and 614.6 mm in Muğla Köyceğiz in 2057 and 2079, respectively. Notably, the mountainous region west of Crete was predicted to accumulate 1,397.7 mm and 598.3 mm in 2077 and 2082, respectively. Additionally, 555.1 mm was predicted to accumulate over the sea off the coast of Antalya Kumluca in 2069. Conversely, an analysis of the reference years demonstrated that 2008 and 2014 were the wettest years. In 2008, the maximum monthly total precipitation was predicted to be 933.4 millimeters in Gazipaşa, Antalya. In 2014, 1224.8 millimeters of rainfall were forecasted in Arta, Greece. A detailed analysis of future daily maximum rainfall amounts reveals a prediction of 184.2 millimeters of rainfall over the sea south of Rhodes Island on November 19, 2097, and 237.3 millimeters over the sea in the northeast of Crete on November 24, 2077. Finally, on November 25, 2069, 144.4 millimeters of daily precipitation was predicted in the mountainous region in the western part of Crete. In addition to precipitation patterns, a comprehensive examination of wind speeds reveals that, according to the simulation for November 2077, a maximum wind speed of 59.3 m/s is predicted in the southwest of Crete.
How to cite: Doğan, O. H., Önol, B., Kahraman, A., and Kadıoğlu, M.: Projected Changes in Severe Storm Environments in the Eastern Mediterranean: A Convective Permitting Simulation Approach, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-12420, https://doi.org/10.5194/egusphere-egu25-12420, 2025.
This study examines the characteristics of convective and stratiform precipitation in three runs of the high-resolution (2.3 km) regional climate model ALADIN-CLIMATE/CZ, operated by the Czech Hydrometeorological Institute, over the Czech Republic for the period 1990–2014. The first run (reanalysis run) is driven by ERA5 boundary conditions and includes station data assimilation, the second run (evaluation run) is similarly forced by ERA5 but without station data assimilation, and the third run (historical run) is driven by the global climate model CNRM-ESM2-1. types. These model runs are compared againts station measurements and ERA5 reanalysis to evaluate the model’s skill in simulating both convective and stratiform events across the Czech Republic. Spatial distribution and trends of precipitation characteristics are also assessed.
Results show that the ALADIN-CLIMATE/CZ model overestimates both stratiform and convective precipitation in all months. In summer, convective precipitation is better captured by the modelthan stratiform precipitation. Among the three simulations, the reanalysis run,which includes data assimilation, exhibits the closest alignment with observations. By identifying and understanding the strengths and limitations of each model run, this research provides valuable insights into the reliability of high-resolution regional climate models and theirs applications for future climate assessments.
How to cite: Rulfova, Z. and Beranova, R.: Evaluation of Convective and Stratiform Precipitation in High-Resolution Regional Climate Model Runs over the Czech Republic, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-6393, https://doi.org/10.5194/egusphere-egu25-6393, 2025.
Operational weather forecasts in South Korea currently extend up to 10 days but often fall short of adequately addressing the needs of weather-dependent sectors, such as agriculture, for longer-term meteorological predictions. However, extending forecasts beyond this timeframe remains a significant challenge. While traditional physical models have long been the foundation of weather forecasting, recent advancements in machine learning (ML) models for weather prediction have demonstrated promising forecasting skills that are comparable to, or even surpass, those of physical models. In particular, FuXi-ENS, an ML model trained on ECMWF ERA5 reanalysis data, provides global 6-hourly ensemble forecasts at a 0.25° resolution and shows great potential for one-month forecasts. To evaluate the forecasting performance of FuXi-ENS in South Korea and overcome its coarse spatial resolution, dynamical downscaling of multiple ensemble members is conducted using a regional climate model specifically tailored for Korea. For benchmarking purposes, dynamical downscaling of NOAA CFSv2 is also performed using the same regional climate model. Forecasting skill is comprehensively evaluated from both quantitative and qualitative analyses. Based on this comparative assessment, this study aims to provide valuable insights for enhancing subseasonal-to-seasonal forecasts in South Korea, offering practical benefits for various sectors reliant on extended-range forecasts.
Keywords: extended-range forecasting, dynamical downscaling, ML-based global predictions
(Acknowledgments) This study was supported by the “Research Program for Agricultural Science & Technology Development (Project No. RS-2024-00399847)”, National Institute of Agricultural Sciences, Rural Development Administration, Republic of Korea.
How to cite: Ha, S., Zhong, X., Hur, J., and Im, E.-S.: Improving 1-month forecasts in South Korea through the dynamical downscaling of machine learning based global predictions, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-3181, https://doi.org/10.5194/egusphere-egu25-3181, 2025.
While the added value of Convection-Permitting Models (CPMs) in precipitation simulations compared to regional climate models with typical horizontal resolutions has been gradually recognized across various regions, systematic investigations of CPMs' ability to capture the major characteristics of extreme precipitation in South Korea remain limited. To address this gap, this study aims to develop a Weather Research and Forecasting (WRF)-based Convection-Permitting Model (CPM) with a 3 km horizontal resolution and to optimize its performance in reproducing historical extreme events by adjusting the domain size and turning spectral nudging on/off. For this purpose, we selected three record-breaking extreme rainfall cases in South Korea caused by quasi-stationary fronts. Using the peak date as the center, simulations are conducted for a total of 15 days, including a 7-day spin-up period both before and after the peak. We design three domains with expanding sizes, all centered over the Korean Peninsula with a uniform horizontal resolution of 3 km. Their differences in the lateral boundary conditions allow us to perform sensitivity tests to determine the optimal domain size and lateral boundaries for accurately reproducing heavy precipitation events. Their lateral boundary conditions derived from ECMWF-ERA5 reanalysis data at 6-hour intervals. In addition, we assess the effectiveness of spectral nudging by comparing the model performance with and without spectral nudging. A coefficient of 0.0003 s-1 is applied to winds above the planetary boundary layer, showing improvements in reproducing time-series, synoptic patterns, and vertical structures against observations. If the optimal configuration of the CPM contributes to reproducing extreme precipitation events over the Korean Peninsula, it will be helpful for understanding their physical mechanisms.
Acknowledgments
This study was supported by the Korea Meteorological Administration Research and Development Program under Grant RS-2024-00403386, Republic of Korea.
How to cite: Song, D., Im, E.-S., Kwon, D., Seo, G.-Y., and Min, S.-K.: Impacts of Spectral Nudging and Domain Size on Heavy Precipitation Simulations in Korea using a Convection-Permitting Model, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-7868, https://doi.org/10.5194/egusphere-egu25-7868, 2025.
Marine heatwaves (MHWs), prolonged periods of abnormally high ocean temperature, have more than doubled globally since the 1980s, with their frequency and intensity projected to increase further due to global warming, according to the Special Report on Ocean and Cryosphere in a Change Climate (SROCC). In particular, the Korean Peninsula has experienced noticeably more frequent and intense MHWs in recent years amidst ongoing climate change. To improve our understanding of these changes, this study quantitatively investigates the impact of human activities on the MHWs around the Korean Peninsula using Weather Research and Forecasting (WRF) and Regional Ocean Modeling System (ROMS) regional coupled models. To achieve this, we conduct control (CTL) and pseudo-NAT (NAT) experiments. The CTL experiment uses reanalysis data as the initial and boundary conditions of WRF and ROMS models. In contrast, the NAT experiment uses reanalysis data with anthropogenic influences removed. Anthropogenic influences are estimated as the difference between the Coupled Model Intercomparison Project Phase 6 (CMIP6) hist-nat simulation with natural forcing only and historical simulation with both natural and anthropogenic forcing over 1985–2014. Although the WRF and ROMS models tend to underestimate sea surface temperatures, they reasonably capture their spatial patterns, with higher temperatures in the order of Jeju Island, the South Sea, the West Sea, and the East Sea. Our findings reveal that anthropogenic forcing raised SSTs by approximately 0.3 to 0.6°C in the major waters of Korea. As a result, the frequency, intensity, duration, and spatial extent of MHWs have significantly increased in the major waters of Korea. These results highlight the critical role of human activities in driving recent changes in MHW characteristics around the Korean Peninsula and underscore the importance of mitigating anthropogenic climate change impacts.
How to cite: Kim, Y.-H., Cha, D.-H., Cho, W., and Kang, T.: Quantifying the contribution of human activities to marine heatwaves around the Korean Peninsula using the WRF-ROMS regional coupled model, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-7875, https://doi.org/10.5194/egusphere-egu25-7875, 2025.
The East Asian Summer Monsoon (EASM) presents a formidable challenge for regional climate modeling due to its intricate interactions between atmospheric dynamics, oceanic variability, and regional processes. This study explored how different Planetary Boundary Layer (PBL) and Cumulus Parameterization Schemes (CPS), alongside horizontal resolution, influence the simulation of EASM precipitation in 2022. Using the Weather Research and Forecasting (WRF) model, simulations were conducted over the CORDEX-East Asia domain at 12 km resolution with a nested 4 km domain, incorporating four distinct PBL-CPS combinations.
Comparisons with satellite and ground-based observations reveal that Multi-scale Kain-Fritsch (MSKF)-based schemes consistently outperform KIM Simplified Arakawa-Schubert (KSAS)-based schemes, offering more reliable representations of monsoon precipitation. High-resolution simulations more effectively capture localized terrain effects and convective processes. However, specific combinations, such as the Asymmetric Convective Model version 2 (ACM2)-KSAS, tend to overestimate convection in lower latitudes. Conversely, MSKF-based schemes exhibit reduced sensitivity to resolution changes and provide a more accurate representation of monsoon frontal progression. This highlights the critical role of parameterization choices in modulating large-scale monsoon dynamics and local-scale variability.
These findings offer valuable insights into the interactions between parameterizations, resolution, and large-scale monsoon processes, contributing to the enhancement of regional climate model performance. Moreover, this study emphasizes the importance of carefully optimized modeling strategies to improve EASM precipitation forecasts, particularly in the context of climate change and its influence on extreme events.
How to cite: Park, J., Cha, D.-H., and Lee, D.-K.: Influence of PBL-CPS Combinations and Resolution on the Simulation of East Asian Summer Monsoon Precipitation in 2022 Using WRF, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-8015, https://doi.org/10.5194/egusphere-egu25-8015, 2025.
Extreme precipitation presents a significant environmental challenge that threatens the economic and social stability of Southeast Asian countries, highlighting the critical need for reliable model simulations for early warnings and impact mitigations. Recently, the fifth version of the regional climate model (RegCM5) has been released, featuring updates in multiple model components including the physical parameterizations, which is expected to advance the simulation capability for extreme precipitation events. However, optimizing the model parameterization remains challenging due to the vast array of parameters that require fine-tuning. Traditional approaches that use random-based sensitivity tests to identify optimal scheme combinations are constrained by computing power and often fail to explore the complete range of possible combinations needed for accurate regional climate representation. Moreover, parameters within each scheme exist on a continuous spectrum rather than as discrete options, exponentially increasing model optimization's complexity and computational demands.
To overcome these limitations, advanced optimization techniques have emerged to efficiently explore the complete range of possible combinations, without relying solely on random-based sensitivity tests. In this study, we employ a micro-genetic algorithm (micro-GA) for combinatorial optimization of key parameters within the cumulus convection schemes in RegCM5. The model, driven by ECMWF Reanalysis version 5 (ERA5), covers most of Southeast Asia at a 0.22-degree resolution. This study aims to:
(1) validate the capability and efficiency of the coupled RegCM5-micro-GA interface in improving the simulation of extreme precipitation events in Southeast Asia
(2) investigate the sensitivity of the RegCM5-micro-GA algorithm to different fitness functions and different physical parameters
(3) reveal the mechanism of model optimization by examining physical processes improved by the tuned cumulus convection parameters.
The findings will provide valuable insights to facilitate the wider use of RegCM5 and benefit the broad community in model optimization, fostering more accurate and timely predictions of extreme weather events.
[Acknowledgements]
This research was supported by project GRF16308722, which was funded by the Research Grants Council (RGC) of Hong Kong. This study was also supported by the “Research Program for Agricultural Science & Technology Development (Project No. RS-2024-00399847)”, National Institute of Agricultural Sciences, Rural Development Administration, Republic of Korea.
How to cite: Zhou, Z., Nguyen-Xuan, T., Im, E.-S., Yoon, J. W., and Park, S. K.: Combinatorial Optimization of Cumulus Convection Scheme Parameters in RegCM5 Using a Micro-Genetic Algorithm for Extreme Precipitation Event Simulations in Southeast Asia, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-4222, https://doi.org/10.5194/egusphere-egu25-4222, 2025.
Intensive irrigation in the North China Plain (NCP) has raised significant environmental concerns. Recent research highlights the bidirectional and regional-dependent feedback between irrigation and climate, prompting studies that utilize regional climate models to assess these impacts in mesoscale. However, inconsistencies in results persist across current modeling efforts, particularly regarding summer precipitation and extreme heat. These discrepancies may arise from diverse model choices and inherent limitations in existing regional climate models, such as the lack of dynamic vegetation simulations, neglect of double cropping rotation, omission of groundwater pumping, and inappropriate parameter selection for the NCP.
To address these challenges, we selected two widely used regional climate models: the Weather Research and Forecasting model version 4 with Noah-MP land surface model (WRF4 with Noah-MP) and the Regional Climate Model version 5 with Community Land Model (RegCM5 with CLM). We enhanced these two models to better simulate large-scale irrigation practices in the NCP by incorporating dynamic double-cropping vegetation, interactive irrigation, and groundwater pumping. Parameters were recalibrated using local data, and validation was conducted across hydrological, agricultural, and atmospheric sectors. The improved models allow for a comprehensive examination of the mutual feedback between irrigated crops and the atmosphere.
By comparing the outputs of these two enhanced models, we gain greater confidence in our conclusions regarding the irrigation impact on the NCP and its surrounding areas, particularly concerning the alterations to the hydrological cycle, groundwater depletion, and extreme weather events. Additionally, the differences in model results will elucidate the extent to which irrigation impacts are model-dependent and provide insights into the reasons for inconsistencies found in previous studies. Overall, our study enhances land representation and its coupling with regional climate models, offering valuable implications for future model development.
This study was supported by the Research Program for Agricultural Science & Technology Development (Project No. RS-2024-00399847) from the National Institute of Agricultural Sciences, Rural Development Administration, Republic of Korea.
How to cite: Fan, Y., Pokhrel, Y., Hur, J., and Im, E.-S.: Assessing the Irrigation Impact in North China Plain Using Regional Climate Models with Dynamic Vegetation and Groundwater Pumping, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-7692, https://doi.org/10.5194/egusphere-egu25-7692, 2025.
Climate change is having profound effects on forest ecosystems. Forests, as major carbon sinks, play a vital role in regulating the Earth’s climate. However, climate-induced disturbances threaten these ecosystems, creating feedback loops that exacerbate global warming. Monitoring vegetation dynamics and simulating future conditions are crucial for sustainable ecosystem management.
While global climate models or Earth System models (ESMs) are useful for large-scale assessments, they often fail to capture local phenomena. Regional Climate Models (RCMs), offer higher-resolution simulations but also face challenges in accurately representing biosphere-atmosphere interactions.
In this study, we explore the sensitivity of the Modèle Atmosphérique Régional (MAR) to vegetation changes to support the future coupling of MAR with the dynamic vegetation model CARAIB. We conducted multiple simulations by perturbing the MAR Leaf Area Index (LAI) input. The perturbations consist of varying scenarios of vegetation growth and decline and changes in dynamics by using MODIS satellite LAI observations varying weekly as input instead of fixed monthly climatology from MERRA2 reanalysis LAI data and applying Gaussian noise.
Our results show that the impact of LAI perturbations is non-linear, with distinct differences between increased and decreased vegetation. For instance, when vegetation was decreased by an average of 92%, evapotranspiration (ET) rates dropped by 83.4%. In contrast, a scenario with a 178.4% increase in LAI showed less drastic changes, with an increase of 29.8%. This behavior of the model suggests an asymmetric response to vegetation perturbations.
Further analysis highlighted how MAR simulates daily ET when used with an observed LAI instead of a climatology. The study reveals a moderate correlation between MAR ET and observation data (r²=0.37) overall with MAR performing slightly better during drought conditions (r²=0.38) than in moist periods (r²=0.36). The model tends to underestimate ET in drought conditions and often overestimates it during moist periods.
These findings provide valuable insights into the influence of vegetation dynamics on regional climate simulations. They emphasize the importance of accounting for vegetation-climate interactions in RCMs to improve local-scale predictions and understand feedback mechanisms under various climate scenarios.
How to cite: Dethinne, T., Ghilain, N., Lecart, B., Fettweis, X., and Jonard, F.: Sensitivity of the Regional Climate Model MAR to Vegetation Dynamics in Forested Areas, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-11286, https://doi.org/10.5194/egusphere-egu25-11286, 2025.
The accurate estimation of soil texture is crucial as it significantly impacts soil moisture and other hydrological variables. While the Weather Research and Forecasting Hydrological Extension (WRF-Hydro) model is a useful tool for investigating various aspects of hydrological processes and their interactions with the atmosphere, the default soil map provided by USGS and MODIS exhibits potential issues associated with coarse resolution and limited accuracy. To address this deficiency, this study conducts a series of sensitivity experiments that consider additional data sources or alternative soil mapping approaches within WRF-Hydro model framework. A comparative analysis is performed by focusing on hydrological variables such as soil moisture and runoff. The study will enhance our understanding of how changes in soil properties influence key hydrological processes and shed light on the impact of diverse soil conditions on the robustness of simulation results.
[Acknowledgment]
This work was supported by Korea Environment Industry & Technology Institute(KEITI) through Water Management Program for Drought, funded by Korea Ministry of Environment(MOE) (2480000175).
How to cite: Kang, S., Fabian, P. S., Im, E. S., and Kwon, H.-H.: The impact of soil texture on hydrological processes in South Korea based on WRF-Hydro simulations, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-14486, https://doi.org/10.5194/egusphere-egu25-14486, 2025.
Posters virtual: Thu, 1 May, 14:00–15:45 | vPoster spot 5
EGU25-8577 | Posters virtual | VPS6
A review of climate change impacts in the Canary IslandsThu, 01 May, 14:00–15:45 (CEST) | vP5.16
Environmental and socioeconomic factors increase small islands' exposure and vulnerability to climate change. This study reviews issues related to current and future climatic change and its impacts on the small island environments in the Canary Islands. Convection-permitting regionalized projections driven by data from three global climate models included in the Coupled Model Intercomparison Project (CMIP5) have been performed, covering the recent past (1980–2009) and future (2070–2099) periods, under two Representative Concentration Pathways, 4.5 and 8.5. The impact analysis includes water resources, energy, ecosystems and biodiversity, natural hazards, and health issues. We provide a succinct review of sectors that warrant particular attention, due to their weight in the gross domestic product, agriculture and tourism. The concluding section discusses adaptation and response strategies, and the portfolio of research that needs to be addressed.
How to cite: Carrillo, J., Barrancos, J., Tondreau, P. S., Pérez, J. C., González, A., Expósito, F. J., and Díaz, J. P.: A review of climate change impacts in the Canary Islands, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-8577, https://doi.org/10.5194/egusphere-egu25-8577, 2025.
