In high-mountain environments such as the European Alps, glaciers are an important component of the water cycle. With ongoing climate change, this role seems in jeopardy though: glaciers in Switzerland, for example, have lost more than 30% of their volume since the year 2000, and future projections indicate a future with ice-free landscapes if society was to fail in taking immediate and stringent climate action.

In this contribution, the role of glaciers as water resource will be reviewed. By taking the Swiss Alps as an example, their contribution to regional water supplies and usage will be quantified. A focus will be on the glaciers’ role in providing water during dry periods, as well as the relevance of glacier melt in the context of hydropower production.

Based on both extended glaciological measurements collected in the frame of the Glacier Monitoring Switzerland (GLAMOS) program and daily glacier melt data retrieved through automated methods, we will for example quantify the meltwater contribution that glaciers had in the extremely hot summer 2022. The year saw a record-high 6% glacier volume loss and we show that individual heat waves contributed over-proportionally to this amount: 35% of the total summer ice loss, for example, occurred in the 25 hottest days, delivering a water amount that corresponds to 56% of the total summer melt seen on average for the past decade.

Such phases of extreme melt can also be challenging for water resource management. In high-alpine rivers, where annual glacier contributions to streamflow were up to 80% in 2022, existing hydropower infrastructure can for example be overwhelmed. For a country that sees some 2.1kWh of hydro-electricity being produced for every cubic meter of glacier melt, this raises questions about future management strategies, and calls for robust projections of future streamflow.

How to cite: Farinotti, D., Cremona, A., van Tiel, M., and Huss, M.: Glaciers’ role as water resource in the Swiss Alps, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-11164, https://doi.org/10.5194/egusphere-egu23-11164, 2023.

Assessments of glacier retreat impacts on water resources are often carried out using hydrological models calibrated using stream discharge time series. Because long-term discharge measurements are scarce in different regions of the world, models’ outcomes are analyzed assuming implicitly that stream discharge evolution projections at the outlet of a watershed affect the entire drainage area following a uniform pattern. In the present study, building on the learnings from the peak water analysis we performed in 2012, we explore the heterogeneity in Rio Santa sub-watersheds responses to deglaciation. The future of water resources at each watershed is projected by applying the peak water model with the latest glacier area estimations. The resulting map of the projected water availability across the Rio Santa watershed is then overlayed with previous works and literature-based water quality and demand maps.

Results show that, while glaciers are losing their hydrological influence across the Cordillera Blanca, gaps open between water availability and demand for water at different levels of the watershed. Moreover, the dry season share of polluted sub-watersheds into the Rio Santa discharge increasing due to glacier retreat, water quality evolution will add up to the challenge of sharing an already scarce resource.

Our study suggests that deglaciation in the tropical Andes affects populations and economic activities in a complex, disparate and evolutive way. Therefore, anticipating glaciers retreat redistribution of the water resources requires integrating hydrological, chemical, biological, economic, and sociological water resources aspects in locally grounded studies.  

How to cite: Baraer, M., Mark, B., and McKenzie, J.: Toward a glacier retreat driven redistribution of water resources, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-10137, https://doi.org/10.5194/egusphere-egu23-10137, 2023.

Summer 2022 broke numerous glaciological, hydrological and climatological records in Europe. Dry and warm conditions led to extreme low-water levels and problems with water supply. The hot summer in combination with little snow in winter was disastrous for the Swiss glaciers; they never lost as much volume in the century-long observational record. At the same time, this massive glacier melt meant an alleviation of the downstream hydrological drought situation. Glacier contributions to streamflow during hot and dry periods, as well as their changes due to glacier retreat are, however, poorly quantified.

In this study, we characterize the glacio-hydrometeorological extremeness of the hydrological year 2022 in Switzerland and compare it with other exceptional years in the past. Observational streamflow records from about 80 stations along glacier-fed rivers were analyzed, together with (i) temporally downscaled and spatially extrapolated glacier mass balance observations, as well as (ii) temperature and precipitation information. Results show that precipitation and temperature were exceptional, but there have been years since 1961 that were warmer or drier. However, the combined effect of low precipitation and high temperatures led to record-low summer flows throughout Switzerland, apart from the Rhone river, the upstream part of the Aare river, and a few high-elevation catchments. Catchments with a glacier cover of more than 20% even resulted in above normal summer streamflow in 2022.

The annual relative meltwater contribution from glacierized areas ranged from a few percent up to 80% of the total streamflow among the catchments and equaled up to double the mean contribution estimated for the period 1981-2010. Although 2022 glacier volume losses broke records, only a few catchments showed a record amount of glacier melt water contribution to streamflow. This may hint that for most catchments, glacier retreat is dominating the melt response to extreme warm conditions, instead of differences in the respective meteorological conditions. This process reduces the crucial capacity of glaciers to alleviate downstream drought conditions. Overall, the study highlights the need for an integrated analysis of meteorological, hydrological and glaciological data to understand the spatiotemporal dynamics of extreme dry and warm years. 

How to cite: Van Tiel, M., Huss, M., Zappa, M., and Farinotti, D.: A glacio-hydrological perspective on the extreme year 2022 in Switzerland, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-4515, https://doi.org/10.5194/egusphere-egu23-4515, 2023.

In the cold-arid Trans-Himalayan region of Ladakh, cryospheric meltwater plays a critical role for irrigated agriculture and local livelihoods. Despite the vital importance of reliable water supply under conditions of ongoing climate change, the relative contributions from glaciers and seasonal snow cover melt, together with permafrost thaw to surface and subsurface discharge are largely unknown due to the lack of in-situ data and local hydrological modelling. This study attempts to improve the understanding of regional hydrology, based on the case study of Stok catchment, where snow and glacier meltwater feeds a village of more than 300 households. We quantified long-term (2003-2019) surface and subsurface flow using a distributed temperature index and coupled surface/subsurface flow models forced by daily in-situ, meteorological, satellite and reanalysis data. These models were calibrated with the measured discharge data from two summer periods (2018 and 2019) in order to better understand the characteristics of surface and subsurface hydrology of the catchment. We also investigated the specific contributions from the cryospheric components and from rainfall to the total flow, and water loss through sublimation. A decline in annual discharge with characteristic inter-annual variations was identified over the observation period with about half of the total accumulated flow through the subsurface. We found that snowmelt contribution was highest (~60%) followed by ice melt (~20%) and rainfall (~15%), whereas sublimation contributes to ~8% of the water loss in a hydrological year. The findings and approach of this study are important for applied hydrological studies and planning future water management strategies in the region of Ladakh.

How to cite: Soheb, M., Bastian, P., Nüsser, M., Schmidt, S., Singh, S., Kaushik, H., and Ramanathan, A.: Surface and subsurface hydrology of a high-altitude catchment in the Trans-Himalayan region of Ladakh, India, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-7664, https://doi.org/10.5194/egusphere-egu23-7664, 2023.

The mountains of Central Asia are water towers servicing the arid downstream regions and maintaining irrigation and food production. There are several sources of runoff: liquid precipitation, snowpack, glacier ice, ground ice (including rock glaciers and permafrost), and ground water. The relative contributions of different water sources to stream flow are poorly quantified and its improved understanding will reduce uncertainty in hydrological modelling and projections of changes in water resources. In 2019-21, an extensive sampling programme was conducted to quantify the relative contributions of water sources to stream flow in the Tien Shan and Pamir-Alai using stable water isotope tracers (SWI) of oxygen and hydrogen. Samples of the event-based precipitation, river discharge taken daily or twice-daily at the designated sampling points and every fortnight along the river courses, and water sources were collected in the glacierized catchments in Kazakhstan (Ulken Almaty and Kishi Almaty catchments), Kyrgyzstan (Ala-Archa and Chon-Kyzyl Suu), Tajikistan (Varzob and Kafornihon), and Uzbekistan (Chirchik). The samples were processed using Picarro isotope analyser. A data set of SWI ratios from approximately 6000 samples has been produced and analysed. It is the first comprehensive SWI database in Central Asia contributing to understanding of regional and global isoscapes and water resources. The local meteoric water line (LMWL) was developed from the event-based precipitation samples. It is approximated as δD = 7.6δ¹⁸O + 8.7. The values of SWI in precipitation exhibit a clear annual cycle and depend on precipitation type (rain, snow, and mixed). The derived seasonal SWI values are different from those available from the Water Isotopes Database being nearly twice as high in winter. Snow, glacier ice and permafrost exhibit distinct isotopic signatures although these vary between the basins. Glacier ice in the Chirchik basin appears to be more depleted than elsewhere. Rock glaciers were sampled in the Ulken Almaty basin showing SWI ratios similar to those of glacier ice but both are distinct from permafrost. These results point at the feasibility of the application of the mixing model and end-member mixing analysis approaches to the partitioning of runoff and quantifying relative contributions of different water sources in the Tien Shan and Pamir-Alai. This is a policy-relevant task under the conditions of climate change.

How to cite: Saidaliyeva, Z., Shahgedanova, M., Yapiyev, V., Wade, A., Akbarov, F., Esenaman, M., Kapitsa, V., Kassatkin, N., Kayumova, D., Rakhimov, I., Satylkanov, R., Sayakbaev, D., Severskiy, I., Petrov, M., Usubaliev, R., and Umirzakov, G.: Isotopic composition as a tracer of different source contributions to stream flow in the glacierized catchments of Central Asia, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-10181, https://doi.org/10.5194/egusphere-egu23-10181, 2023.

The water balance of high-alpine glacierized catchments is largely dominated by snow and ice processes. When modelling the hydrological response of such catchments, a reliable representation of snow/ice accumulation and melt should be ensured, especially when studying the effects of climate change. Even though numerous state-of-the-art hydrological models are able to adequately represent the contribution of snow melt into the total runoff with the use of complex approaches (e.g. energy balance models), glacier dynamics are still based on conceptual or empirical methods, which exhibit some limitations compared to more sophisticated models (e.g. explicit ice-flow dynamics).
The Water Flow and Balance Simulation Model (WaSiM) is a process-based hydrological model that includes an empirical volume-area scaling approach for describing the glacier’s evolution. Although acceptable estimates can be obtained with this approach, an integration to a more complex glacier representation is still missing. For this reason, a coupling scheme between WaSiM and the Open Global Glacier Model (OGGM) is developed, hence accounting for explicit ice-flow dynamics.
The workflow consists mainly on three steps: i) a first WaSiM run to obtain monthly values of temperature and precipitation that serve as input for the ii) second step, which is running OGGM. Finally, iii) a dynamic model run of WaSiM with the updated output from OGGM (annual glacier outlines and ice thickness) is performed. Within this last step, the glacier’s volume internally calculated by WaSiM (i.e. with the VA-scaling approach) is replaced by OGGM’s output, while performing a simultaneous multi-data set automatic calibration. In this calibration, only WaSiM parameters are adjusted and simulation results are compared against glacier mass balances (OGGM) and observed runoff. The performance of the calibration is then evaluated in terms of a weighted multi-objective function. Although the best fit between observed and simulated runoff is achieved when considering only runoff observations (single-data calibration), glacier components are better represented when calibrating the coupled model with the multi-data set (i.e. also including glacier mass balances). Therefore, a trade-off is made between general model performance and accurate runoff prediction. 
This coupling scheme is aimed for hydrological modellers with no additional expertise on glacier modelling, since OGGM is set up according to its default parameters. Finally, it could serve as a tool not only to predict the hydrological response of any glacierized catchment (even without any available glacier data), but also to make predictions under future climate projections with a more reliable representation of glaciers. 

How to cite: Pesci, M. H. and Förster, K.: Process-based water balance modelling with explicit ice-flow dynamics and multi-data set calibration: the WaSiM-OGGM coupling scheme, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-7688, https://doi.org/10.5194/egusphere-egu23-7688, 2023.

Snowmelt runoff is a significant component in the glacierized and snow-covered basins of the western Himalaya. Modelling is the most useful tool to quantify snowmelt contribution in mountainous rivers, but the paucity of in-situ observations makes the model calibration quite challenging and therefore model parameters are often adopted from the neighboring river basins. In the present study, we applied Snowmelt Runoff Model (SRM) in the Chandra-Bhaga Basin and Chhota Shigri Glacier Catchment in the western Himalaya. We systematically checked the transferability of the model parameters between the catchment and basin. Using snow cover area (SCA), precipitation, and temperature as inputs, the daily discharge for the Chhota Shigri Catchment and Chandra-Bhaga Basin was reconstructed over 2003–2018. The mean annual discharge was found as 1.2 ± 0.2 m³/s and 55.9 ± 12.1 m³/s over 2003-2018 for the Chhota Shigri Catchment and Chandra-Bhaga Basin, respectively. The discharge in the Chhota Shigri Catchment was mainly controlled by summer temperature and summer SCA, whereas in the Chandra-Bhaga Basin summer SCA and summer precipitation controlled the discharge. At both the catchment and basin scale, the decadal comparison revealed an increase (11% and 9%) and early commencement (10 days and 20 days) of the maximum monthly discharge over 2011-2018 compared to 2003-2010. In the Chhota Shigri Catchment, the model output is almost equally sensitive to the 'degree day factor' and 'runoff coefficient for snow,' but most sensitive to the 'runoff coefficient for snow' in the Chandra-Bhaga Basin. Even though the SRM parameters were calibrated in a data-rich Chhota Shigri Glacier Catchment, their application in the Chandra-Bhaga Basin led to a large discharge overestimation at the basin scale and was not transferable even in the same basin. We suggest to be cautious while adopting/transferring model parameters for SRM from other basins, particularly for the ungauged basins.

How to cite: Vinze, P. and Azam, M. F.: Evaluation of Parameter Transferability of Snowmelt Runoff Model in Chandra-Bhaga Basin, India, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-534, https://doi.org/10.5194/egusphere-egu23-534, 2023.

The Colorado River, which supplies water to the Western United States (WUS) and Mexico, is fed primarily from snow melting out of the Rocky Mountains. Currently, snowmelt contribution to streamflow is forecast using a calibrated temperature index model (SNOW-17). This approach is simple, and computationally efficient, but loses efficacy when snow conditions are outside the calibration period as temperature index models do not represent all of the physical processes that control accumulation and melt rates. For example, in the southern headwaters of the Colorado River forecasting errors have been related to surface darkening and accelerated melt following episodic dust on snow events. Here, we present an ongoing project to develop and mature a spatially distributed snow energy balance model, informed with numerical weather prediction (NWP) and remote sensing, to support operational decision making. This effort is a collaboration between the University of Utah's Snow Hydrology Research to Operations (Snow HydRO) Laboratory, the USDA-ARS Northwest Watershed Research Center (NWRC), and the Colorado Basin River Forecast Center (CBRFC). The model, iSnobal, is forced with the High Resolution Rapid Refresh (HRRR) NWP and is assessed against in situ observations and snow depth maps from the Airborne Snow Observatory in representative headwater basins. Initial testing of the HRRR-iSnobal combination showed that it can simulate snow accumulation, in terms of both patterns and magnitude, but that snowmelt rates were too slow. This was attributed to inaccurate radiation balance, specifically shortwave radiation due to the traditional treatment of net shortwave, including a 'time since snowfall' albedo decay curve. To account for spatial and temporal variability in snow albedo, daily observations from the spatially and temporally complete MODIS fractional snow products (MODSCAG+MODDRFS) were incorporated to update net solar radiation inputs. The updates were tested in different ways including direct albedo updates, direct decay curve component updates, and basin specific calibration decay curves. Although all remote sensing based update approaches improved snowmelt timing, direct updates had the greatest improvement in years with more intense snow darkening. This presentation will include a summary of current results, updates on incorporation into operational forecasting, and highlight plans for future developments.

How to cite: Skiles, M., Meyer, J., Ragar, D., Kormos, P., and Hedrick, A.: Development of an operational snow energy balance model informed by numerical weather prediction and remote sensing for the Western United States, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-10634, https://doi.org/10.5194/egusphere-egu23-10634, 2023.

Glacial melt is the primary source of freshwater for the fragile microbial ecosystem in the McMurdo Dry Valleys (MDV) of Antarctica. These glaciers are cold-based, with internal temperatures around -18°C, however, air temperatures hover around 0°C for several weeks in the summer and föhn wind events can rapidly raise ice surface temperatures to the melting point. Thus, episodical glacial melt is sensitive to small changes in the climate.  

The aim of this research is to adapt a detailed snowpack model embedded in a distributed hydrological model to simulate the surface energy balance and run-off of a glacier in the MDV. To do this, the snowpack model in the WRF-Hydro-Crocus modelling scheme, which has been used for avalanche forecasting and temperate glaciers, is adapted to the MDV. Several modifications are made to model calculations and parameters to allow the model to successfully simulate surface energy balance and runoff in this environment. For example, the parameters for the Crocus albedo scheme are adjusted to obtain band profiles for snow, firn and ice that replicate observed albedo and remain internally consistent between surface types. The modelling system is then validated against data from an automatic weather station, eddy covariance measurements and stream discharge. It is shown to be suitable for future efforts to model the full hydrological cycle of glacial meltwater in this region.

How to cite: Pletzer, T., Cullen, N., Conway, J., Eidhammer, T., and Katurji, M.: Adapting a snowpack model to simulate cold-based glacial hydrological processes in the McMurdo Dry Valleys, Antarctica, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-9243, https://doi.org/10.5194/egusphere-egu23-9243, 2023.

The latest advances and availability of satellite observations have great potential for improving hydrological model simulations of the water cycle. The recent study by Tong et al. (2021) showed that satellite observations of snow cover and soil moisture could improve river runoff simulations of conceptual hydrologic models with lumped model parameters. Still, the value and potential of spatial patterns of satellite observations for hydrologic model parametrization need to be better understood. This study aims to evaluate and compare different multiple-objective calibration strategies that use model inputs and satellite observations for the model calibration in lumped, spatially distributed and stepwise ways. We aim to test the potential of daily MODIS (Moderate Resolution Imaging Spectroradiometer) snow cover and ASCAT (Advanced Scatterometer) soil water index images observed over 204 Austrian catchments in 2000-2014. Results show that stepwise calibration strategies that first calibrate the snow model parameters to satellite snow cover data followed by calibrating the remaining model parameters outperform (particularly in lowlands) the classical calibration strategies estimating model parameters in one single calibration step. The use of distributed snow cover and soil moisture patterns in model calibration improves the snow and soil moisture simulation performance of the model. The use of MODIS snow cover data has a more significant contribution to the overall improvement in model performance than ASCAT soil moisture data.

References:

Tong, R., Parajka, J., Salentinig, A., Pfeil, I., Komma, J., Széles, B., Kubáň, M., Valent, P., Vreugdenhil, M., Wagner, W., and Blöschl, G.: The value of ASCAT soil moisture and MODIS snow cover data for calibrating a conceptual hydrologic model, Hydrol. Earth Syst. Sci., 25, 1389-1410, 10.5194/hess-25-1389-2021, 2021.

How to cite: Tong, R., Parajka, J., Tian, F., Széles, B., Greimeister-Pfeil, I., Vreugdenhil, M., Komma, J., and Blöschl, G.: The value of distributed snow cover and soil moisture data for multi-objective calibration of a conceptual hydrologic model, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-10420, https://doi.org/10.5194/egusphere-egu23-10420, 2023.

Flood hazard assessment and its relationship with extreme rainfall probabilities is a well-addressed topic in the literature, but not enough in mountain areas, where the climate change effect can hit much more than in other physical contexts. In mountain basins, the lack of systematic data and the complexity of the rain/snow phenomena make investigations even more necessary to figure out the consequences of global warming.

This study explores how the partial contributing area effect due to snow accumulation, on the one hand, and the basin runoff coefficient, on the other hand, shape the relationship between rainfall and flood probabilities in high elevation areas. To this aim, the FloodAlp geomorphoclimatic model (Allamano P. et al., 2009) is used.

The model is based on the derived distribution approach, producing as a result a simplified flood frequency curve based on the intra-annual variability of the portion of the catchment area covered by snow, according to simple descriptions of the seasonal variation of the freezing elevation and of the hypsographic curve of the basin.

To model the basin hypsometric features, we propose the use of a two-parameter Strahler function, which is a more accurate and alternative formulation to the simple one-parameter function originally used in the model. The role of the extreme rainfall frequency analysis is also explicitly analysed, by applying the model using rainfall extremes recorded both in the daily and 24-hours windows. In this application, the only parameter that requires calibration is the runoff coefficient. Considering recordings of annual maximum daily discharges, the runoff coefficients for more than 100 gauged basins in north-western Italy have been calibrated. Comparisons are then possible between the shapes of rainfall and flood frequency distributions within the sample analysed, that also take into account the basin geomorphoclimatic features. Results of this application address the selection of relevant characteristics in relation to the impact of climate change on mountain floods as a result of changes in temperatures and in the statistics of rainfall extremes.

How to cite: Evangelista, G., Monforte, I., Demateis Raveri, M., and Claps, P.: Relationship between rainfall and flood frequency curves in high elevation areas, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-16657, https://doi.org/10.5194/egusphere-egu23-16657, 2023.

In high elevation Alpine areas, characterised by high snow accumulation and radiation-driven melt processes, the formation of peculiar ablation features called sun cups can be observed. Sun cups likely influence the energy and mass balance of the wet snowpack by locally reducing the snow albedo, leading to an enhanced ablation in the hollows. To our knowledge, these phenomena are to date poorly explored in the literature and little to no attempts have yet been made to study their evolution in time and correlate them with meteorological forcings and energy fluxes over the wet snowpack.

The dynamics of the sun cups was investigated at the high elevation Alpine site of Weissfluhjoch (Davos, Switzerland) over the Spring of 2022. At the site, the snow surface was mapped on an hourly basis by means of a fixed, automated high-resolution 3D terrestrial laser scanner. Snow height maps were obtained by processing the registered point clouds.

Sun cups were individually and automatically detected over the snow surface maps by a delineation algorithm in Python. The evolution of sun cups in time was studied with respect to their maximum depth and cross-section.

The maximum depth and cross-section evolution of sun cups showed a high correlation with the measured albedo, especially when they are fully-formed. This finding suggests that peculiar snow surface formations that can be detected by means of remote sensing systems can give valuable additional information about the ongoing processes within the wet snowpack, paving the way to a radar-assisted modelling of the snowmelt dynamics. In an era of increasing concern over the availability of water resources, a better understanding and modelling of snowmelt dynamics is of major importance, especially in remote areas where accurate predictions are required for operational purposes (e.g. hydropower and irrigation).

How to cite: Carletti, F., Brouet, L., Lehning, M., and Bavay, M.: Influence of sun cups on surface albedo of wet Alpine snowpack, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-14338, https://doi.org/10.5194/egusphere-egu23-14338, 2023.

Accurate characterization of peak snow water storage is essential for assessing warm-season water availability in regions reliant on snowmelt-driven runoff. However, knowledge of peak snow water storage in data-sparse regions, such as High Mountain Asia (HMA), is still lacking due to overreliance on model-based estimates. Here, estimates of peak snow storage from eight global snow products were evaluated over HMA, using a newly developed High Mountain Asia Snow Reanalysis (HMASR) dataset as a reference. The particular focus of this work was on peak annual snow storage, as it is the first-order determinant of warm-season water supply in snow-dominated basins.

The results suggest large uncertainty in the eight global snow products in High Mountain Asia, with the climatological peak storage found to be 161 km³ ± 102 km³ across products. Compared to HMASR, most global snow products underestimate peak snow storage in HMA, with an average 33% underestimation. Large inter-product variability in cumulative snowfall (335 km³ ± 148 km³) is found to explain most of the peak snow storage uncertainty (>80%). Significant snowfall loss to ablation during accumulation season (51% ± 9%) also plays an important role in peak snow storage uncertainty, and deserves more investigation in future work.

How to cite: Liu, Y., Fang, Y., Li, D., and Margulis, S. A.: How well do global snow products characterize snow storage in High Mountain Asia?, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-4012, https://doi.org/10.5194/egusphere-egu23-4012, 2023.