This session highlights the opportunities and challenges of kilometer-scale climate modelling across both regional and global domains. We aim to showcase how high-resolution models enhance the representation of local processes, illuminate cross-scale interactions, and improve understanding of extremes. By bringing together the regional CPM community (e.g. CORDEX Flagship Pilot Studies) and the emerging global storm-resolving community (e.g. DYAMOND, nextGEMS, Destination Earth, EERIE), the session seeks to foster dialogue, synergy, and collaboration. Contributions using variable-resolution frameworks, which connect regional detail with the global Earth system context are also of interest.
We invite submissions that:
1. Apply regional or global CPMs to advance understanding of extremes and demonstrate added value over coarser models.
2. Bridge regional and global frameworks through nesting or variable resolution approaches.
3. Investigate cross-scale feedback between convection and large-scale circulation.
4. Assess climate change signals and scale-dependent extreme event responses.
5. Advance evaluation, model development, and understanding of biases in CPMs.
6. Address uncertainty and computational challenges, including ensembles and novel strategies for long-term simulations.
By uniting diverse initiatives, this session aims to push the frontiers of extreme events research and climate process understanding at unprecedented resolution, while building stronger links between regional and global modelling communities.
Orals: Tue, 5 May, 08:30–12:30 | Room 0.31/32
The capability to simulate, rather than model the Earth System, implies the use of solvers applied to equations that generalize to other situations. For instance, km-scale storm resolving models solve the same equations as used in LES of the marine boundary layer at much higher resolution, the dynamics of a buoyant thermal, or the interaction of flow with topographic features. By limiting the use of models (parameterization) to the non-fluid component, e.g., photons or droplets, rather than a part of the flow that is artificially severed from the rest, e.g., convection, scale separation can be better enforced, and the ensuant models can be put on a better theoretical footing. This approach results in more physical models grounded in assumptions that are countably small, often separable, and more directly comparable to observations. That creates new opportunities to test the ability of the models to represent constituent processes within the Earth system, and a new basis for developing physical understanding. This leads to new scientific opportunities which we highlight by reviewing the diversity of configurations being applied, the problems they are solving, and the benefits being derived from their compatibility with advanced observations — including those from an emerging and a promised new generation of active satellite remote sensing.
How to cite: Stevens, B., Fievét, R., Nowak, J., Ohno, T., and Segura, H.: Some implications of simulating the Earth System, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-14187, https://doi.org/10.5194/egusphere-egu26-14187, 2026.
The emergence of kilometer-scale atmospheric models represents more than just increased resolution: it offers three key advantages. First, by explicitly resolving deep convection, these models eliminate the convective parameterisation that previously masked deficiencies in other processes. This reduces the problem to a finite set of well-defined processes (microphysics, turbulence, radiation, surface interactions, and forcing data), each testable and improvable independently. Second, they enable direct comparison between models and observations by matching spatio-temporal sampling rates, avoiding artifacts from upscaling and time-averaging. This synergy allows direct assessment of the model's underlying physics against real-world observations. Finally, since regional and global models now share the same core physics, any insight gained from regional simulations directly translate to better global climate projections.
The ORCESTRA campaign over the tropical Atlantic (August-September 2024) provided such an opportunity for model development. We ran ICON in its Sapphire-configuration at 1.25 km resolution in parallel with field operations. Overlapping 48-hour simulations forced by IFS analyses generated high-frequency output matching observational sampling from space (EarthCARE satellite), the air (HALO plane and dropsonde) and the surface (METEOR ship and radiosondes). ICON captures large-scale circulation well, but with some important caveats: persistent atmospheric drying, insufficient upper-tropospheric ice clouds with weak humidity contrasts, undersized systems failing to organise into mesoscale clusters, and reduced surface wind variability. Critically, cloud radar measurements reveal an obvious microphysical flaw: rain falls twice as fast as observed. This excessive fall speed plausibly connects all biases through premature moisture depletion. Rapidly falling drops reach the surface before evaporating (weakening cold pools), before detraining moisture upward (reducing ice clouds), and before enabling mesoscale organisation.
Guided by these observations, we revised ICON's rain microphysics by 1) incorporating lognormal particle size distributions (Feingold & Levin, 1986), 2) evaluating fall velocities based on Van Boxel (1998) and, 3) consistently adjusting evaporation and accretion rates. Targeted reruns along EarthCARE overpasses show that this revision successfully re-aligns the Doppler velocities with observations and appreciably affect the model's representation of convective organisation. Overall, this work illustrates the synergy between kilometer-scale models and field measurements: by operating at observational scales and explicitly resolving convection, models can be physically interpreted and improved, with these refinements directly serving global climate projections.
How to cite: Fiévet, R., Daniel-Lacombe, M., Downey, P.-O., and Stevens, B.: Testing Kilometer-Scale Model Against Observations: Microphysical Insights from the ORCESTRA Campaign, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-19860, https://doi.org/10.5194/egusphere-egu26-19860, 2026.
Convection-permitting global climate simulations are seen as a promising route to reducing long-standing biases in conventional global climate models, and thereby may offer more reliable climate projections.
The Met Office and academic partners have developed a global-regional model hierarchy, comprising several global models that drive multiple nested limited-area models (LAMs), utilising a range of different resolutions and model physics configurations. This framework enables assessment of the upscale impacts of explicit convection and has been run for a year following the DYAMOND3 protocol.
A novel member of the hierarchy is a convection-permitting global model (grid length of ~5km), which uses a physics configuration employed in regional km-scale NWP and climate modelling at the Met Office. We demonstrate that through tuning of model cloud properties, a realistic top-of-atmosphere (TOA) energy balance is obtained, establishing a suitable configuration for climate change experiments. Initial results show realistic large-scale conditions and improved intensity of mesoscale phenomena relative to the other models in the hierarchy. Finally, we discuss plans for multi-year idealised climate change experiments (Cess-Potter +4K SST) with km-scale global models, aiming to begin to understand how cloud feedbacks differ from conventional global climate models.
How to cite: Scullion, C., Short, C., Jones, R., Lewis, H., Shchepanovska, D., and Sanchez, C.: Towards global km-scale climate simulations at the Met Office Hadley Centre, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-9494, https://doi.org/10.5194/egusphere-egu26-9494, 2026.
Accurately representing upscale interactions between convection and the large-scale flow remains a major challenge for global atmospheric models. While global kilometer-scale simulations that resolve deep convection can improve coupling with midlatitude circulation, the influence of vertical resolution remains far less explored. Here, we investigate how deep convection interacts with midlatitude circulation using a suite of Model for Prediction Across Scales (MPAS) experiments with systematically varied horizontal and vertical resolution.
We analyze four simulations initialized following the DYAMOND Phase 3 protocol and run for 40 days: (1) 3.75 km horizontal resolution, 127 vertical levels; (2) 15 km, 127 levels; (3) 15 km, 55 levels; and (4) 15 km, 55 levels with boundary-layer vertical refinement. The 127-level simulations have an average tropospheric grid-spacing of 190 m, compared to 310 m in the 55-level runs.
Simulations with 127 levels exhibit enhanced upscale kinetic energy transfer from deep convection, particularly in warm-conveyor-belt genesis regions about the tropopause. This drives quasi-stationary Rossby waves downstream, producing dry anomalies over Western Europe and Western North America. In contrast, 55-level simulations show weaker upscaling, favoring more zonal flow and wetter conditions. Horizontal refinement appears to only have a secondary effect. Preliminary diagnostics suggest that eddy viscosity treatment by the Planetary Boundary Layer scheme in MPAS is highly sensitive to vertical spacing, substantially influencing the mesoscale kinetic energy spectrum and, in turn, shaping the upscaling and midlatitude circulation response. Ongoing work looks to expand the ensemble of simulations.
The results highlight the critical role of vertical resolution when configuring kilometer-scale global models. Understanding how vertical resolution interacts with model physics may also be key in reducing contemporary biases in midlatitude Rossby wave and blocking frequency.
How to cite: Lojko, A. and Skamarock, W.: Why Vertical Resolution May Matter More Than Horizontal for Midlatitude Circulation Biases: The Critical Role of Convective Upscaling, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-567, https://doi.org/10.5194/egusphere-egu26-567, 2026.
The GRIST model is used for the first time in a regional downscaling experiment, based on the convection-permitting third-pole monsoon case. The simulations driven by external reanalysis data sets are assessed and compared with the global simulation through a rigorous global-regional integrated modeling approach. Additional regional simulations with boundary data taken from the global simulation reveal the critical role of cross-boundary flows in aligning regional model behaviors with global results. The study focuses on downscaling performance, global-regional comparisons, and the impact of lateral boundary flow. The downscaling simulations using different reanalysis data sets produce overall comparable large-scale circulation patterns and mean precipitation biases. Nudged lateral boundary conditions improve the circulation performance but result in mixed precipitation outcomes, including higher mean-state biases and artificial rainfall around the Tibetan Plateau area. Some intrinsic model biases (e.g., diurnal cycle and excessive light rainfall frequency) are consistent across global and regional simulations. Using explicit convection can address these limitations. Intense rainfall events and topographic precipitation errors show high sensitivity to lateral boundary flow variations, underscoring the complexity of interactions between regional dynamics and boundary flows. Systematic topographic precipitation biases persist but varying lateral boundary flows can regulate the magnitude. The results underscore the uncertainties associated with kilometer-scale downscaling simulations under strong lateral boundary flows particularly concerning small-scale intense and/or topographic rainfall events.
References:
1. Chen, T., Y. Zhang, Y. Wang, and W. Yuan, (2025), Impact of Lateral Boundary Flows on Regional Convection-Permitting Simulations Over the Tibetan Plateau: A Global-Regional Integrated Modeling Study. Journal of Geophysical Research: Atmospheres, 130(15), e2024JD042952.doi:https://doi.org/10.1029/2024JD042952.
2. Zhang, Y., Z. Liu, Y. Wang, and S. Chen, (2024), Establishing a limited-area model based on a global model: A consistency study. Quarterly Journal of the Royal Meteorological Society, 150(764), 4049–4065.doi:https://doi.org/10.1002/qj.4804.
How to cite: Zhang, Y., Chen, T., Wang, Y., and Yuan, W.: Impact of Lateral Boundary Flows on Regional Convection-Permitting Simulations Over the Tibetan Plateau: A Global-Regional Integrated Modeling Study, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-34, https://doi.org/10.5194/egusphere-egu26-34, 2026.
Accurately simulating mesoscale convective systems (MCSs) is essential for predicting global precipitation patterns and extreme weather events. Despite the ability of advanced models to reproduce MCS climate statistics, capturing extreme storm cases over complex terrain remains challenging. This study utilizes the Global–Regional Integrated Forecast System (GRIST) with variable resolution to simulate an eastward-propagating MCS event. The impact of three microphysics schemes, including two single-moment schemes (WSM6, Lin) and one double-moment scheme (Morrison), on the model sensitivity of MCS precipitation simulations is investigated. The results demonstrate that while all the schemes capture the spatial distribution and temporal variation of MCS precipitation, the Morrison scheme alleviates overestimated precipitation compared to the Lin and WSM6 schemes. The ascending motion gradually becomes weaker in the Morrison scheme during the MCS movement process. Compared to the runs with convection parameterization, the explicit-convection setup at 3.5-km resolution reduces disparities in atmospheric dynamics due to microphysics sensitivity in terms of vertical motions and horizontal kinetic energy at the high-wavenumber regimes. The explicit-convection setup more accurately captures the propagation of both main and secondary precipitation centers during the MCS development, diminishing the differences in both precipitation intensity and propagation features between the Morrison and two single-moment schemes. These findings underscore the importance of microphysics schemes for global nonhydrostatic modeling at the kilometer scale. The role of explicit convection for reducing model uncertainty is also outlined.
How to cite: Zhou, Y., Yu, R., Zhang, Y., Li, J., and Chen, H.: Sensitivity of a Kilometer-Scale Variable-Resolution Global Nonhydrostatic Model to Microphysics Schemes in Simulating a Mesoscale Convective System, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-1569, https://doi.org/10.5194/egusphere-egu26-1569, 2026.
Variable-Resolution Community Earth System Model (VR-CESM) employs a global grid which is refined only over a limited area, thus substantially decreasing the computational demand while allowing global simulations with regional resolutions that are mostly unaffordable with uniform resolution GCMs. This technique can leverage today’s parallel computing platforms almost to their fullest extent by offering near-perfect scalability. The geographic location and complicated topography of Euro-Mediterranean leads to a regional climate governed by complex nonlinear interactions and cascade of feedbacks between multitude of scales, from global to local, and spatiotemporally highly varied climatic characteristics. Therefore, the region serves as a suitable testbed for the utilization of VR-CESM.
Here, VR-CESM is employed to investigate the climate of the Euro-Mediterranean region. Two variable-resolution grids with regionally refined resolutions of 0.25° and 0.125° over the study domain are used and historical climate is simulated for between 1998-2014 in an Atmospheric Model Intercomparison Project (AMIP) setup. The fidelity of VR-CESM simulations is evaluated considering the near-surface air temperature and precipitation fields in comparison to available observation-based data sets and those of a coarse resolution (quasi-uniform 1°) control simulation.
The improvements obtained are mainly related to a better representation of the complex topography of the region with higher resolution and consistent incorporation of the large scale circulation. Specifically, we report improvements in the representation of the topographically induced processes (e.g. orographic uplift), extreme events, vertical air motion and synoptic scale moisture transport. Overall, this work validates the benefits of VR-CESM for use in regions under the influence of many processes across global-to-regional scales coupled with a complex topography and that, as a modeling approach, VR-CESM is a useful (even superior for some scientific inquiries) alternative to investigate the Euro-Mediterranean’s climate.
How to cite: boza, B., Herrington, A., Ilicak, M., Danabasoglu, G., and Sensenomerlutfi@gmail.com, O. L.: Evaluating the Performance of the Variable-Resolution CESM (VR-CESM) in Simulating the Euro-Mediterranean's Climate, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-1174, https://doi.org/10.5194/egusphere-egu26-1174, 2026.
Northern Italy is an area located in the Northern-eastern part of the Mediterranean region widely recognized as a regional hot-spot for climate change and characterized by the occurrence, in particular in Autumn, of severe convective thunderstorms. These weather extremes, due to the presence in the area of several small and steep river catchments, often drive the occurrence of devastating flash-floods and flooding. The need for a better understanding of past and future changes in the frequency of these extremes has produced in the last years an increasing interest in using over the area high-resolution convection-permitting models (hereafter CPMs) that explicitly simulate the convection in the atmosphere instead of using parametrizations as it occurs at a coarser resolution. However, recent studies have stressed that the absence in the CPMs of an active and explicit coupling between atmosphere and ocean affects the simulation of convective events, partially explaining the observed biases between simulated and observed precipitation over the area.Here we combine a convection-permitting resolution (3 km) and an explicit coupling between atmosphere and ocean in a single modeling tool and assess its performance in simulating the precipitation regime over the Northern Italian during the ERA5 period. The modeling system, named RegCM-ES, is composed by: (i) the atmospheric module RegCM5 with an horizontal resolution of 3 km and 41 vertical levels, (ii) the ocean module MITgcm with an horizontal resolution of approximately 700 m and 59 vertical levels (non hydrostatic), and (iii) the river discharge module CHyM with an horizontal resolution of approximately 1 km. Moreover, RegCM5 has a prescribed time evolving aerosol concentration and is coupled with the CLMU urban model.The performances and the added value of the RegCM-ES with respect to the standalone atmospheric RegCM5 in simulating the precipitation regime and its extreme over the Northern Italy have been evaluated by comparing the numerical outputs of an hindcast experiment that adopt as initial and boundary conditions state-of-the-art atmospheric and ocean reanalysis, with some high-resolution observational and reanalysis datasets available for the area. The comparison, although still showing for both modelings tools significant wet/dry biases over the Alps/lowland areas of the Northern Italy, found an improvement in the representation of the precipitation regime and related extremes in particular in Autumn over the Eastern part of the domain that is the area where the coupling between ocean and atmosphere is effective. Moreover, an improvement in the simulation of the river discharge is found, spatially coherent with the improvements of the simulated precipitation. Overall, this comparison has offered valuable indications that RegCM-ES in convection-permitting configuration can be considered a suitable tool for studying the factors driving the extremes in the region, and is currently adopted to produce high resolution ocean and climate projections for the region.
How to cite: Reale, M., Giuliani, G., Giordano, F., Garcia-Valdecasas Ojeda, M., Vargas-Heinz, L., Coppola, E., Querin, S., Solidoro, C., and Salon, S.: Convection-permitting coupled simulations over the Northern Italy with the Regional Earth System RegCM-ES , EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-12169, https://doi.org/10.5194/egusphere-egu26-12169, 2026.
At the UK Met Office, recent advances in km-scale climate modelling include the first continuous 100-year ensemble projections at 2.2km resolution over the UK ( ‘UKCP Local’), and 4.5km ensemble projections over Africa. In this talk I will highlight new understanding of changes in heavy rainfall, convective storm hazards and tropical cyclones, with implications for flooding and adaptation planning. This includes insights into the interplay between natural variability and climate change, and the factors leading to apparent rapid transitions in the occurrence of local rainfall extremes through time. Over Europe, new understanding includes changes in severe convective storms and hail, that contrast with previous studies based on environmental proxies from coarser resolution climate models. Over Africa, km-scale models are able to capture the most intense tropical cyclones, providing a key advance in our modelling capability. This is showing that we need to be prepared for Category 5 tropical cyclones making landfall over Africa and the potential for landfall at southerly latitudes, both of which are unprecedented in the historical record.
How to cite: Kendon, E., Dauster, E., Kahraman, A., Macholl, J., Short, C., and Tucker, S.: Exploiting km-scale climate projections to provide new insights into changing convective hazards in UK, Europe and Africa , EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-3880, https://doi.org/10.5194/egusphere-egu26-3880, 2026.
Convective wind gusts produced by downburst or cold pools can have devastating impacts on our infrastructure: buildings, powerlines, railways. Yet, how climate change affects convective wind gust is largely unexplored, with only very few publications. Despite this, changes in a number of thermodynamic processes point at potential increases in convective gusts. Heavier precipitation increases the liquid water loading of downdrafts, producing larger downward drag and greater potential of evaporation of rain and therefore stronger negative buoyancy. In addition, predicted decreases in boundary layer relative humidity increases boundary layer depth and evaporation of rain, and may also promote the occurrence of more organized convective systems. Here, we present results from a long convection-permitting model simulation showing a clear relationship between cold pool strength and maximum gust. In addition, we investigated a case of severe convection in our “Future Weather” system (repeating present-day weather events in warmer and colder climates using pseudo global warming). In these simulations we show a clear relation between the downward mass flux of air and the strength of the maximum wind gust.
How to cite: Lenderink, G. and de Vries, H.: Increases in convective wind gusts from enhanced thermodynamically driven processes in a warmer climate, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-19205, https://doi.org/10.5194/egusphere-egu26-19205, 2026.
Cloud responses to warming represent a substantial source of uncertainty in future climate projections, in part due to uncertain convective parameterizations in the global climate models (GCMs) used to estimate cloud feedbacks. A new generation of convection-permitting simulations at km-scale horizontal resolution offers new insight into clouds in a changing climate: Recent work has demonstrated a reduction in the thick ice clouds associated with convective cores relative to the optically thin anvil in idealized simulations. Here, we use multi-year simulations of the western Pacific in present-day and warmer climates to demonstrate fundamental differences in cloud-circulation interactions between convection-permitting models and GCMs. In particular, we find that strong descent in the mid-troposphere in our simulations is associated with both downdrafts in convective cores and radiatively-driven subsidence, in contrast to GCMs, which only represent the latter. We separate these influences on descending air using column relative humidity and demonstrate that the presence of downdrafts reduces the cooling effect of deep convective clouds. We show that our km-scale simulations exhibit the previously reported thinning of deep convective clouds with warming. Additionally, we show that this thinning is driven by a reduction in thick clouds associated with ascent, while that associated with descent – downdrafts – expands, and mean descent rates increase. We hypothesize that this increase in descent speeds is driven by increases in ascent, thus increasing the condensate loading and negative buoyancy in downdrafts, indicating a potential role for microphysical-dynamical pathways in cloud feedbacks largely absent in GCMs.
How to cite: Mackie, A., Byrne, M. P., Short, C. J., and Torri, G.: Increased frequency and intensification of convective downdrafts with warming in km-scale simulations , EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-3322, https://doi.org/10.5194/egusphere-egu26-3322, 2026.
Accurate urban-resolving climate data are essential for urban climate research and applications. However, General Circulation Models
(GCMs) often lack the resolution and urban representation needed to provide reliable fine-scale climate information over urban areas.
Convection-permitting modeling (CPM) has emerged as a promising solution to this challenge, despite its computational demands. Based on high-resolution regional climate model coupled with urban canopy model, kilometer-scale dynamic downscaling simulations (DDM and CPM) have been proved to be able to maintain the large-scale climate information from the driving fields, and at the same time kilometer-scale dynamic downscaling simulations generates more detailed information on regional or local scale. At the local scale, CPM well reproduced observed precipitation rates at daily and sub-daily time scales, diurnal precipitation variations and urban heat island intensity. Furthermore, we conducted CPM over urban areas under climate change scenarios and proposed kilometer-scale climate change dataset. These insights will greatly enhance future high-resolution regional climate simulations and climate change projections over urban areas in China.
How to cite: Pei, L., Miao, S., Zhao, L., and Chen, D.: Convection-permitting scale Urban Climate Simulation, Projection and adaptation in China, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-1626, https://doi.org/10.5194/egusphere-egu26-1626, 2026.
Short-duration heavy precipitation poses a persistent and significant risk to the densely populated Yangtze River Delta (YZR) region. This study employs the Weather Research and Forecasting (WRF) model at a convection-permitting scale (∼4 km) to simulate and project hourly precipitation over the YZR. We conducted a 10-year historical simulation (1998-2007) and three pseudo-global warming (PGW) experiments for the late 21st century (2070-2099) under RCP2.6, RCP4.5, and RCP8.5 scenarios. The convection-permitting regional climate model (CPM) demonstrates robust skill in reproducing key characteristics of observed hourly precipitation including its diurnal cycle, event duration, peak intensity, and extremes. Future projections indicate hourly precipitation intensity is projected to increase, alongside a rising frequency of heavy precipitation events. Notably, short-duration events are expected to become more intense and frequent, while small-coverage heavy precipitation events are also projected to increase, thereby heightening regional climate risks. These findings underscore the critical value of CPMs for high-resolution climate risk assessment and the development of targeted adaptation strategies in the YRD.
How to cite: Xiong, Y.: Convection-Permitting Simulations of Hourly Precipitation in the Yangtze River Delta Region: Evaluation and Future Projections, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-2475, https://doi.org/10.5194/egusphere-egu26-2475, 2026.
Severe convective storms capable of producing extreme surface impacts simultaneously (such as large hailstones, strong winds, and heavy rainfall) present a major challenge to numerical weather prediction and risk assessment. On 6 July 2023, the Ebro Valley (Aragon, Spain) was impacted by a series of two high-impact supercells. The first supercell exhibited an extraordinary multi-hazard nature, producing a 50-km swath of giant hail (≥ 10 cm), a tornado, and a downburst with estimated gusts exceeding 200 km/h. The second supercell triggered flash flooding in the city of Zaragoza (population > 700,000) and large hail (> 5 cm) to the south of the city.
This study applies a sub-km-scale pseudo-global warming storyline approach to this compound high-impact event to quantify how anthropogenic climate change will alter its physical drivers and destructive potential. We downscale global climate perspectives to the storm scale by comparing a factual simulation with a future scenario (SSP5-8.5). We perturb initial and boundary conditions using climate change deltas derived from each CMIP6 climate model. We focus on the physical understanding of cascading hazards: specifically, whether future warming enables a transition towards storms that sustain giant hail growth while simultaneously enhancing precipitation efficiency (flash flood risk) and downdraft intensity. Our results aim to demonstrate how event-based storylines can unravel the interactions between thermodynamic changes and storm dynamics, revealing if such unprecedented multi-hazard supercells will become the new reality for extremes in semi-arid regions, thereby amplifying their destructive potential.
How to cite: Calvo-Sancho, C., González-Alemán, J. J., Halifa-Marín, A., Martín, M. L., and Azorin-Molina, C.: Future intensification of severe multi-hazard supercells in a semi-arid environment of Southern Europe, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-18069, https://doi.org/10.5194/egusphere-egu26-18069, 2026.
Convective storms impact populations all over the world, bringing heavy rainfall, strong winds, lightning and sometimes hail. These hazards can lead to flooding, wildfires, damage to infrastructure and loss of life. Improved forecasting of storms hazards requires accurate prediction of the location and timing of convective initiation. Understanding factors that influence where convection kicks off is therefore crucial for reducing the impact of thunderstorms on the population.
Mesoscale soil moisture heterogeneity can trigger sea breeze like circulations that favour convective initiation over dry soil patches. Recent observational work over Sub-Saharan Africa has revealed that the sensitivity of convective initiation to soil moisture is enhanced by wind shear, with the most rapidly developing storms occurring when the mid-level wind direction opposes low-level soil moisture induced circulations.
The current work evaluates the representation of the observed interaction between soil moisture, wind shear and convective initiation in current kilometre-scale models, including DYAMOND-3 year-long global UM simulations. We further exploit RAL3 simulations to further our understanding of the observed mechanism and explore the impact of different wind shear configurations on convective updrafts and moisture inflow.
How to cite: Barton, E., Taylor, C., and Klein, C.: Sensitivity of convective initiations to soil moisture and directional shear in k-scale models, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-13550, https://doi.org/10.5194/egusphere-egu26-13550, 2026.
The evaluation of km-scale climate models is often centered on variables and time scales for which added value is expected, e.g. short-term wind and precipitation extremes. However, potential shortcomings of basic temperature characteristics might be overlooked, even though temperature is a key variable. Especially in regions with complex topography, parameterizations and model physics that were originally designed for larger-scale applications might be inadequate; although a better resolved orography might support an improved representation of temperature, it is not guaranteed.
In our research, we investigate the representation of temperature characteristics in complex terrain in km-scale regional climate models. For this purpose, we exploit the CORDEX-FPS ensemble on convective phenomena over the Alps at two resolutions: km-scale (2.2 - 4 km) and coarse-scale (12 - 15 km). We evaluate these ensembles against SPARTACUS, a high-resolution gridded observation-based dataset in Austria, during the period 2000-2009.
We find season-dependent biases in both the coarse-scale and km-scale model ensembles accompanied by a high ensemble spread. Hot and cold extremes are generally overestimated, with the km-scale models showing a higher overestimation than their driving coarse-scale models. Consequently, most km-scale models overestimate the frequency of hot days (daily maximum temperature >30°C) and frost days (daily minimum temperature <0°C). Additionally, both ensembles exhibit a strong and mostly negative elevation-dependent bias, which is most pronounced for daily minimum temperatures. The biases become more negative with increasing elevation for both ensembles and become as large as -5.0°C for the multi-model mean. The near-surface temperature lapse rate is therefore systematically overestimated for both daily minimum and maximum temperature and season-dependent. Our results highlight that adequately representing temperature characteristics remains challenging even at the km-scale.
How to cite: Kohlhauser, I., Medvedova, A., Ban, N., and Maraun, D.: Evaluating Daily Temperature Characteristics in the km-scale CORDEX-FPS Convection Ensemble in the Greater Alpine Region, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-9414, https://doi.org/10.5194/egusphere-egu26-9414, 2026.
Severe convective storms pose significant challenges to societal resilience and represent a critical test for Subseasonal-to-Seasonal (S2S) forecasting at longer lead-times. This study investigates the predictability of the torrential 2015 May Texas-Oklahoma extreme rainfall event, during which record-breaking rainfall abruptly terminated a multi-year drought, only to be followed by a second wave of heavy rainfall by Tropical Storm Bill in June. We evaluated the performance of the MPAS-NoahMP S2S prediction system in capturing this extreme rainfall event. Three sets of global mesh are designed, a global 60-km uniform mesh, two regional refinement mesh centered in the US for 60-15km, and 60-4km going down to convection-permitting resolution.
At the 1-week lead time, ensemble forecasts demonstrate high fidelity, skillfully capturing the timing, magnitude, and spatial pattern of precipitation anomalies. At 2- and 3-week lead times, the model maintains a persistent signal of the May wet event, albeit with a damped magnitude and significantly larger ensemble spread, which itself is a useful indicator of potential high-impact weather. We further investigate the added values of regional refinement for this extreme rainfall event, in terms of extreme precipitation distribution, diurnal cycle, and land-atmosphere interactions priori to the rainfall.
This study discusses the applications of km-scale convection-permitting simulation in subseasonal forecasts (2-6 week) and the valuable findings translating probabilistic S2S forecasts into actionable intelligence for stakeholders, such as water managers, who must navigate these increasingly volatile weather regimes.
How to cite: He, C., Zhang, Z., Jaye, A., Berner, J., Barlage, M., Fowler, M., Richter, J., and Yang, Z.-L.: Subseasonal prediction at km-scale: the 2015 Texas-Oklahoma Extreme Rainfall-Flood event , EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-15861, https://doi.org/10.5194/egusphere-egu26-15861, 2026.
High-resolution climate simulations with convection-permitting models (CPMs) are essential for studying sub-daily precipitation extremes, but their computational cost severely limits the length, domain size, and ensemble size of continuous simulations. This poses a major challenge for obtaining robust extreme-value statistics at kilometre scale. Here we introduce a case-selective dynamical downscaling (CSDD) framework that enables the reconstruction of extreme precipitation statistics at convection-permitting resolution without requiring long, continuous CPM simulations.
The approach identifies time windows likely to contain extreme rainfall using precipitation from a coarser-resolution driving simulation, and dynamically downscales only these selected periods. Applied to a 30-year regional climate simulation, CSDD reproduces the statistical distribution of 1–6 hour precipitation extremes from a full continuous CPM simulation while requiring only about 10 % of the computational cost. Because individual cases are independent, simulations can be executed fully in parallel, allowing wall-time reductions of several orders of magnitude and facilitating ensemble-based uncertainty quantification.
Our results demonstrate that reliable kilometre-scale extreme precipitation statistics can be obtained without continuous CPM integrations, making CSDD a complementary strategy to traditional regional climate modelling. By alleviating key computational bottlenecks in long-term CPM applications, the framework enables efficient ensemble generation for extreme-precipitation research and opens new opportunities for extreme-event analysis at convection-permitting resolution.
How to cite: Dewettinck, W., Van de Vyver, H., Degrauwe, D., Termonia, P., and Caluwaerts, S.: Case-Selective Dynamical Downscaling for Efficient Extreme Precipitation Statistics at Convection-Permitting Scale, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-11762, https://doi.org/10.5194/egusphere-egu26-11762, 2026.
The Black Sea Basin (BSB) is one of the climate change hot-spots where intense atmosphere–sea interactions and complex topography shape temperature distribution, precipitation regimes, and extreme weather events. Accurate simulation of these regional climate patterns in high-resolution atmospheric models requires microphysical parameterization schemes that realistically represent hydrometeor evolution and temperature tendencies. In this study, we evaluate a suite of convection-permitting WRF simulations at 3 km resolution to identify the microphysics scheme that most reliably reproduces temperature, precipitation, hail occurrence, and snow cover across three meteorologically contrasting years over the BSB. Annual sensitivity simulations for 2008 (a dry year), 2010 (a warm SST year), and 2017 (a wet year) using the Goddard, Milbrandt, NSSL, WSM7, WDM7, and Thompson schemes show that the model reproduces the spatial and seasonal patterns of Tmax and Tmin across the basin. Seasonal temperature patterns are robustly captured by all schemes, with biases generally limited to 2–3°C and partly shaped by mountainous terrain. Similarly, precipitation evaluations indicate that the model represents basin-wide spatial distributions and seasonal cycles with high fidelity, with remaining biases of 6–10 mm/day over the Caucasus and eastern Anatolian highlands, reflecting the observational limitations in complex topography. RMSE metrics show that the microphysics schemes vary in performance, with the Milbrandt scheme standing out for its consistently year-to-year uniform behavior. It maintains low Tmin RMSEs of 1.30–1.40°C and precipitation RMSEs of 0.87–1.15 mm/day across all three years, indicating that it reproduces temperature and precipitation fields with stable accuracy under different meteorological conditions. Hail and snow cover evaluations further reinforce this result. The Milbrandt scheme adequately represents the spatial distribution and spring/early-summer evolution of hail-prone areas across Türkiye. Simulated spring snow cover closely matches satellite observations over the Upper Euphrates Basin, located in eastern Türkiye. Additionally, preliminary results from ERA5-driven simulations strengthen these findings by realistically reproducing the long-term characteristics of temperature, precipitation, and snow cover over the BSB. Overall, the Milbrandt scheme serves as the most suitable microphysical parameterization option for the upcoming long-term fully coupled atmosphere–ocean simulations aimed at improving the representation of two-way air–sea feedbacks, which are crucial for understanding climate processes over the BSB.
Acknowledgment: The numerical calculations reported in this paper were fully performed using the EuroHPC Joint Undertaking (EuroHPC JU) supercomputer MareNostrum 5, hosted by the Barcelona Supercomputing Center (BSC). Access to MareNostrum 5 was provided through a national access call coordinated by the Scientific and Technological Research Council of Turkey (TÜBİTAK). We gratefully acknowledge BSC, TÜBİTAK, and the EuroHPC JU for providing access to these resources and supporting this research.
How to cite: Kelebek, M. B. and Önol, B.: A multi-year sensitivity analysis of microphysical parameterization in convection-permitting simulations over the Black Sea Basin, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-4031, https://doi.org/10.5194/egusphere-egu26-4031, 2026.
The climate change response from sub-hourly precipitation extremes remains poorly constrained because long, high-quality observational records at this resolution are scarce, and convection-permitting climate simulations at similarly high temporal resolution are computationally expensive. However, multiple recent observational analyses suggest that intensification with warming may be stronger for short accumulation periods than for longer events, with some regions exhibiting pronounced increases even when hourly or daily extremes show weak trends (for example, Utsumi et al., 2011; Ayat et al., 2022; Bauer and Scherrer, 2024). Given the relevance of short-duration rainfall for urban flash flooding and infrastructure design as described by Fowler et al. (2021), it is critical to assess whether an amplified intensification at sub-hourly scales is a robust feature.
Here, we investigate how extreme precipitation changes across accumulation periods from ten minutes to hours over an extended European domain, and how temperature scaling depends on event duration. We use the scClim convection-permitting simulations performed with COSMO at 2.2 km grid spacing, featuring 5-minute precipitation output over most of continental Europe (Cui et al., 2023). This unique combination of large spatial coverage and very high temporal resolution enables a consistent analysis of sub-hourly extremes across diverse climatic regimes.
We quantify changes in high percentiles of precipitation intensity for multiple accumulation periods (10 min to several hours) and relate them to near-surface temperature to diagnose scaling relative to Clausius–Clapeyron expectations.
How to cite: Lehmann, L. S., Fischer, E., Schär, C., and Knutti, R.: Do Short-Duration Rainfall Extremes Intensify Faster? Evidence From CPM Simulations Over Europe, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-17647, https://doi.org/10.5194/egusphere-egu26-17647, 2026.
Earth system modeling is currently undergoing an exciting transformation, thanks to new technical capabilities that allow for significant spatial refinement. For the first time, these capabilities allow us to explicitly simulate extreme precipitation and its effects on climate-relevant timescales on a global scale. Thus, new Earth system data from high-resolution modeling approaches offer an exciting foundation for new analyses and research. In our study, we examine the distribution and changes in extreme precipitation from global simulations. We obtained this data from the ICON Earth system model simulations conducted within the nextGEMS project, which aims to create future projections up to the year 2050 with a grid spacing of approximately 5 km. Our analysis focuses on the portion of precipitation contributing to the top ten percent of globally accumulated precipitation. Using the open-source tool tobac we identify and track the resulting precipitation cells over time. Our analysis reveals that warming causes the most extreme precipitation cells to become more intense. At the same time, the data shows a significant decrease in the total number of cells, resulting in fewer, more intense extremes. Finally, we discuss these findings in relation to changes in the spatial distribution of the cells and changed environmental conditions.
How to cite: Senf, F., Hartog, L., and Jones, W.: Fewer but More Intense: Future Changes in Extreme Precipitation Cells from Global Kilometer-Scale Climate Modeling, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-9810, https://doi.org/10.5194/egusphere-egu26-9810, 2026.
Anthropogenic climate change is projected to intensify hydrometeorological hazards in megacities, with Istanbul emerging as a highly vulnerable hotspot due to its complex topography, strong air–sea interactions, and rapidly urbanizing structure with its growing population of 16 million people. Therefore, high-resolution extreme precipitation simulations are crucial in risk assessment and adaptation planning in Istanbul. In this study, we performed high-resolution convection-permitting simulations over the Black Sea Basin using the WRF model at 3 km horizontal resolution to assess the future evolution of extreme precipitation in Istanbul. The simulations cover a reference period (2005–2014) and two future periods (2041–2050 and 2061–2070) under the SSP3-7.0 scenario. In addition, three future extreme precipitation events (November 2043, December 2050, and October 2064) are dynamically downscaled by nesting a 1-km domain within the 3-km Black Sea domain and applying an ensemble of microphysical parameterization schemes (ETA, Goddard, Kessler, Lin, Milbrandt, Morrison, NSSL, WSM6, WDM6, and Thompson) to better quantify short-duration, localized hazards. Model evaluation indicates that WRF successfully reproduces the precipitation patterns of the reference period. Future projections show that while moderate precipitation remains relatively unchanged, extreme daily totals intensify substantially, with maximum 24-hour precipitation increasing from 210 mm in the reference period to 290 mm and 435 mm in the 2041–2050 and 2061–2070 periods, respectively. Percentile-based indices similarly indicate more frequent and more intense extreme precipitation events, particularly across northern Istanbul. Microphysics-based 1-km ensemble simulations demonstrate that extreme events in future decades may produce both intense 3–6 hour and prolonged 12–24 hour precipitation episodes, elevating the risk of flash urban flooding and longer-duration flood impacts across extensive parts of Istanbul. The spatial extent of areas receiving more than 100 mm of precipitation within 24 hours is substantial, covering 30–36% of the city in the 2043 event (Lin scheme), 25–32% in the 2050 event (WDM6 scheme), and reaching up to 69% in the 2064 event (Kessler scheme). The simulations using the NSSL microphysics scheme in the October 2064 case produce more than 800 mm of 24-hour total precipitation. Furthermore, the Milbrandt scheme yields hail accumulations exceeding 50 mm in the same event, particularly over the vicinity of Istanbul Airport. Overall, these findings indicate that extreme precipitation in Istanbul will become more intense, more widespread, and more frequent under future climate conditions, highlighting the importance of km-scale ensemble simulations for reliably characterizing high-impact precipitation and hail hazards. The high-resolution, city-scale modeling framework developed in this study provides essential scientific input for urban planning and climate adaptation strategies in the Istanbul megacity.
Acknowledgments: This study was funded by the Istanbul Metropolitan Municipality, Disaster Coordination Center. The numerical calculations reported in this paper were fully performed at TUBITAK ULAKBIM, High Performance and Grid Computing Center (TRUBA resources).
How to cite: Önol, B., Kelebek, M. B., and Sahinoglu, S.: Microphysics-based 1-km city-scale ensemble simulations of future extreme precipitation events over Istanbul, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-11191, https://doi.org/10.5194/egusphere-egu26-11191, 2026.
A set of 7-month-long simulations for 5 different years has been performed with the convection-permitting regional climate model Harmonie-Climate in the extremely fine resolution of 750 m grid distance. The simulations are double-nested with an intermediate 5 km domain covering Denmark, the North Sea and Baltic Sea as well as southern Norway and Sweden. The high-resolution domain covers Denmark and the very south of Sweden.
We investigate precipitation, temperature, and other variables, comparing the two nests with observation and with the EURO-CORDEX ensemble in order to estimate the added value from such costly very-high-resolution model simulations wrt. climate services, specifically Klimaatlas, the Danish
National Climate Atlas. Extreme precipitation has been compared for a set of model simulations covering a wide range of resolutions. While the realism of models increases with resolution in general, the properties of extreme precipitation does not scale entirely as expected.
How to cite: Christensen, O. B. and Payne, M. R.: Usefulness of very-high-resolution simulations for a national climate service, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-11223, https://doi.org/10.5194/egusphere-egu26-11223, 2026.
The main objective of this study is to analyze the performance and sensitivity of the ICOsahedral Nonhydrostatic (ICON) regional climate model at convection-permitting resolutions in reproducing temperature and precipitation patterns over Western Türkiye. Because the computational cost of ICON scales strongly with horizontal resolution, domain size, and simulation length, conducting multi-decadal integrations for each parameterization choice is typically prohibitive. To facilitate efficient sensitivity testing, this study prioritizes single-year simulations, which allow rapid iteration of physical parameterizations relative to multi-decadal integrations. To balance computational efficiency with climatic relevance, we selected a representative baseline year that best represents the 1960–2024 climatology, based on observational metric. This selection was determined by evaluating 64 years of meteorological data (1960–2024) to find the year that most closely aligned with long-term regional averages of 212 stations. Based on this comparison, 2015 was selected as the representative year with the long-term mean temperature of 13.3 °C compared to 13.9 °C in 2015, and the long-term mean precipitation of 615.464 mm compared to 614.58 mm in 2015. With 2015’s temperature and precipitation values nearly mirroring the multi-decadal mean, it provides a robust platform for executing physical-parameter testing more efficiently than full long-term integrations. Consequently, the ICON simulations in this study use 2015 as the baseline year.
To provide realistic large-scale atmospheric forcing, initial and boundary conditions are prescribed from the ERA5 reanalysis data which offers high-resolution, temporally consistent fields and has been widely demonstrated to represent synoptic variability relevant to Western Türkiye. Because regional model simulations are strongly influenced by unresolved (sub-grid) processes, we implement a structured sensitivity assessment within the ICON modeling system. Parameterization schemes governing deep convection, cloud microphysics, and radiative transfer are varied in a controlled experimental design to quantify their influence on simulated hydroclimate. The objective is to identify the physical configuration that minimizes systematic errors in temperature and precipitation and yields a robust representation of coastal-inland and topography-driven gradients characteristic of Western Türkiye. Therefore, the simulation outputs of each model configuration are evaluated against observations from 221 meteorological stations obtained from the General Directorate of Meteorology. Model and observation comparisons are performed at monthly and seasonal scales, and skill is summarized using RMSE and mean bias, alongside correlation and index of agreement to assess the consistency of simulated spatial patterns and temporal evolution across seasons.
Keywords: ICOsahedral Nonhydrostatic (ICON) Model; Türkiye; Regional Climate Modelling
How to cite: Önel, G., Moral, A. C., and Ünal, Y.: Sensitivity Analysis of ICOsahedral Nonhydrostatic (ICON) Simulations at Convection Permitting Resolutions over Western Türkiye , EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-13404, https://doi.org/10.5194/egusphere-egu26-13404, 2026.
High-resolution climate information is essential for robust climate change impact assessments, particularly in insular regions where strong land–sea contrasts, steep orography, and mesoscale processes dominate local climate variability. This study presents a systematic intercomparison of convection-permitting regional climate simulations (CPMs) and machine-learning (ML) downscaling approaches for future climate projections over the Azores and Madeira archipelagos, using CMIP6 projections as large-scale boundary conditions.
The dynamical component consists of kilometre-scale (3 km) WRF simulations driven by ERA5 and CMIP6 EC-Earth3-Veg outputs. These CPMs explicitly resolve deep convection and mesoscale circulation, enabling a physically consistent representation of precipitation, temperature, wind, and associated extremes. Model performance is evaluated against station observations, demonstrating substantial added value relative to the driving GCMs, particularly for precipitation variability, extreme rainfall, and coastal–orographic gradients. Future projections point to a warming of around 5ºC in the SSP5 scenario by the end of the century in both regions, with Madeira losing 10% of the annual precipitation while Azores should gain around 10%. In parallel, ML-based downscaling models trained on multi-model CMIP6 ensembles and local observations are used to generate high-resolution projections for the same regions and scenarios. These approaches efficiently reproduce mean climate signals and large-scale spatial patterns, allowing the exploration of a broader range of model uncertainty at a fraction of the computational cost. The intercomparison reveals clear methodological contrasts. CPMs provide physically consistent representations of local processes and extremes but are affected by substantial local biases, whereas ML approaches strongly reduce systematic errors, while making physical interpretability more challenging. Conversely, ML downscaling offers strong advantages in ensemble size, scenario coverage, and computational scalability. Overall, the results highlight that CPMs and ML-based approaches should not be viewed as interchangeable. Instead, their differing strengths imply distinct roles in future climate projection workflows, with CPMs remaining essential for process-based and extremes-focused studies, and ML methods offering complementary value for uncertainty assessment and rapid scenario analysis in climate services and adaptation planning.
This work is supported by FCT, I.P./MCTES through national funds (PIDDAC): LA/P/0068/2020 - https://doi.org/10.54499/LA/P/0068/2020, UID/50019/2025, https://doi.org /10.54499/UID/PRR/50019/2025, UID/PRR2/50019/2025. The authors would like also to acknowledge the project “Elaboração do Plano Municipal de Ação Climática de Barcelos (PMACB).
How to cite: M.M. Soares, P., Tomé, R., and Lemos, G.: Intercomparison of Convection-Permitting and Machine-Learning Downscaling for Future Climate Projections over Atlantic Island Regions, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-12373, https://doi.org/10.5194/egusphere-egu26-12373, 2026.
The CORDEX Flagship Pilot study on Convective phenomena at high resolution over Europe and the Mediterranean, comprises a set of high- and very-high kilometre-scale resolution simulations over central Europe. This unprecedented multi-model ensemble, driven by the ERA-Interim reanalysis, constitutes a benchmark and reflects the growth in computational resources in recent years. The present study applies the Distribution Added Value (DAV) metric to assess and evaluate the quality of the precipitation distribution from convection-permitting regional climate models (CPRCM) relative to both their driving simulations counterparts and coarser-resolution ERA-Interim. The gains associated to CPRCMs are substantial, particularly when evaluated against higher-resolution observational products and station measurements. Widespread gains exceeding 10 % are obtained throughout the domain, with the coastal mediterranean demonstrating higher values. The benefits are also evident for precipitation extremes relevant to convective processes, for values above the observational 95th and 99th daily percentiles at both resolutions, with gains well above a DAV of 40 % for most situations. However, limitations in the observational datasets, which are unable to adequately capture the high-intensity events, may favour the evaluation of lower-resolution simulations and hinder a robust assessment for both precipitation full distribution and precipitation extremes. Furthermore, the improvements of CPRCMs relative to intermediate-resolution simulations are more limited for all cases, as the former depend on information inherited from the latter and the performance of the regional climate models is already comparatively high. The analysis also focuses on hourly precipitation, enabling a direct evaluation of the added value from high-resolution modelling in representing the short-duration precipitation characteristics and extremes.
This work is supported by FCT, I.P./MCTES through national funds (PIDDAC): LA/P/0068/2020 - https://doi.org/10.54499/LA/P/0068/2020, UID/50019/2025, https://doi.org /10.54499/UID/PRR/50019/2025, UID/PRR2/50019/2025. The authors would like also to acknowledge the project “Elaboração do Plano Municipal de Ação Climática de Barcelos (PMACB).
How to cite: Careto, J., Soares, P., and Cardoso, R. and the FPS-Convection Team: Added value of convection-permitting models for precipitation in the CORDEX FPS-Convection ensemble, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-15160, https://doi.org/10.5194/egusphere-egu26-15160, 2026.
In this work we tunned three NWP models - ICON, WRF and MPAS - for simulation of severe thunderstorms considering convection permitting mechanism. This feature implies explicitly solving atmospheric convective processes, rather than using approximations, especially in vertical air movements that drive storms. Nowadays, it is well known that NWP models solve weather events such as precipitation and wind gusts with relatively high accuracy by means of equations describing the physical processes of the atmosphere. These processes comprise heat transfers, moisture exchanges, turbulent movements, interactions with the surface, and radiation. Convection is an important process in the atmosphere, as it contributes to the formation of circulation from large scales (hundreds of kilometers) to local intense precipitation due to storms. In weather forecasting models, these physical processes are solved by mathematical equations at grid points with horizontal spacing ranging from a few kilometers to hundreds of kilometers. However, not always models can adequately capture the underlined features of them. Regions with complex geography, such as mountains and coastlines, are especially challenging for NWP models to accurately describe storm systems, primarily due to abrupt variations in air movements and interactions between land and sea. In order to mitigate these imperfections, mathematical solutions known as parametrizations are used to estimate the effects of convective atmospheric moisture on cloud systems represented by the model. Generally, this convection mechanism in models operates on grids larger than 5 km. However, for short-term forecasting, typically using smaller grid sizes (typically between 1 to 3 km), it is useful to explicitly describe the thermodynamic cycle of convective processes, which is handled in a hybrid manner where deep convection in large clouds is explicitly solved by the model, while shallow convection with small sub-grid clouds that do not produce precipitation is parametrized. The ICON, WRF and MPAS models have the capability to explicitly solve deep atmospheric convection, which is a crucial feature for the applications of short-term forecasting of severe convective events. Therefore, we configure a two-way nested simulation, hybrid convection scheme and by considering a large domain grid of about 7 km mesh and an inner grid of about 3 km mesh, for ICON and WRF and a 3 km target grid mesh for the MPAS, which covers Central, Southeast and South parts of Brazilian's regions. We then applied this configuration to 3 strong thunderstorms events, which were propagate from South Brazil to Sao Paulo state, happened on October 2024, September 2025 and November 2025. AWS observations and images from GOES-19 satellite were used to evaluate the simulations. The results indicate that precipitation forecasts are more organized with explicit convection compared to when parametrized with shallow convection. Additionally, the improvement of simulation variables within the inner grid was made possible by the convection-permitting mechanism, which explicitly solves large-scale convective clouds and only parametrizes shallow sub-grade processes that do not produce precipitation or are very weak. The experiments were crucial as they involve significant improvements for forecasting storms, enhancing the model NWP's nowcasting and monitoring severe events.
How to cite: B. da Silveira, R., R. Bonatti, G., Toshio Inouye, R., R. Paz, S., and D. Tomaz, K.: Convection-permitting mechanism to enhance the thunderstorm forecasting over Sao Paulo state in Brazil, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-19023, https://doi.org/10.5194/egusphere-egu26-19023, 2026.
How to cite: Wang, Y.-C., Aldama Campino, A., Döscher, R., Wang, F., and Lind, P.: Bridging Ensemble Robustness and Process Realism: Event-Based Convection-Permitting Modeling of Extreme Events in Emilia-Romagna, Italy, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-19645, https://doi.org/10.5194/egusphere-egu26-19645, 2026.
