The hydrological cycle over southern France is an interplay between highly variable precipitation impacting the variability of soil moisture and continental runoff. The regional hydrological cycle experiences strong impacts of the Mediterranean Sea (Gulf of Lion) through the moisture advection. Moreover, the strong coupling between the atmosphere and the land surface is affecting all branches of the regional hydrological cycle, especially due to the specific structure of the orography in the region. Under the climate change scenarios potential intensification of the regional hydrological cycle, resulting in extreme hydroclimate events is a critically important phenomenon for understanding mechanisms of climate variability over the Mediterranean.
We perform the analysis of long-term daily precipitation time series over southern France (300 stations from METEO-FRANCE collection) along with modern era Reanalysis (ERA5, JRA55) and satellite datasets (TRMM, GPCP, and Persian) over the period from 1979 onwards. Diagnostics estimate linear trends and interannual variability in precipitation totals and precipitation extremes and allow for quantifying the differences in precipitation variability patterns across the different datasets, demonstrating their strengths and weaknesses. Then we associated changes in precipitation with tendencies in soil moisture derived from the GLEAM-GRACE datasets, thus quantifying regional responses of soil moisture to precipitation impacts. Finally, we analyze the representation of the observed regional hydrological cycle in historical simulations with regional (Euro-CORDEX) and global (CMIP6) climate models. We, thus, establish a statistical association between precipitation, soil moisture, and continental runoff and quantify the role of regional atmospheric circulation in forming multidecadal changes in the regional hydrological cycle.
How to cite:
Jomaa, F. and Zolina, O.: Precipitation over coastal regions of southern France and its impacts on the regional hydrological cycle, EMS Annual Meeting 2022, Bonn, Germany, 5–9 Sep 2022, EMS2022-205, https://doi.org/10.5194/ems2022-205, 2022.
Tanja Winterrath, Christian Chwala, Jens Grundmann, Andy Philipp, and Achim Six
Small, fast responding catchments are prone to flooding induced by local convective precipitation events. In such cases, the availability of high-quality information as basis for target-oriented warnings and effective protective measures in potentially affected regions is essential. More precisely, they rely on high-quality precipitation data, reliable weather and flood forecasting and last but not least information and education of persons in charge for prevention of hazards.
Within the project ‘HoWa-innovativ’ funded by the German Federal Ministry of Education and Research (BMBF) a new hydro-meteorological processing chain has been established to improve flood forecasting and warnings for small catchments. Study regions were located in the federal state of Saxony. The project consisted of three focal topics: first, the improvement of precipitation estimates by adding data from Commercial Microwave Links (CML) to the DWD gauge-adjustment of radar-based Quantitative Precipitation Estimates (QPE); second, the development of a hydrological ensemble prediction system designed for small catchments including coupling to DWD meteorological ensemble data; third, the development of a demonstrator with tailored visual information on precipitation analyses and forecasts as well as flood forecasts and its introduction to clients in disaster and flood management in specific workshops.
Small scale heavy precipitation events are difficult to detect and quantified with conventional measurements. DWD combines the areal reflectivity measurements of the radar network with quantitative gauge measurements throughout Germany to provide QPE in near real-time to clients in flood risk management. This so-called radar online adjustment (RADar-OnLine-ANeichung, RADOLAN) performs well for hourly precipitation sums. However, for small-scale, rapidly evolving convective cells the availability of corresponding gauge information is limited. In contrast to precipitation gauges, CMLs are by far more numerous and have the potential to provide near-ground precipitation information with good spatial coverage, high temporal resolution and very low latency. Within the project, the retrieval of precipitation information from CML has been optimized and prepared for automatic processing. We use CML data for the adjustment of radar-based precipitation estimates with focus on high spatial accuracy and the potential for higher temporal resolution.
This contribution gives an overview of the project results comprising the whole processing chain, while the focus will be on the new multi-sensor precipitation QPE system pyRADOLAN.
How to cite:
Winterrath, T., Chwala, C., Grundmann, J., Philipp, A., and Six, A.: A new hydro-meteorological precipitation and flood forecasting system for small catchments, EMS Annual Meeting 2022, Bonn, Germany, 5–9 Sep 2022, EMS2022-433, https://doi.org/10.5194/ems2022-433, 2022.
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Tuomas Naakka, Tiina Nygård, Elena Shevnina, Timo Vihma, and Alexey Karpechko
Winter precipitation remarkably affects river flooding risk in Europe. This study focuses on linkages between large-scale atmospheric circulation, precipitation and river discharge in western and northern Europe during extended winter period (October – April). Compared to other seasons, the effects of large-scale atmospheric circulation on precipitation are strongest in winter, when moisture transport is a major source of moisture for precipitation, and large-scale updraft is an effective mechanism to produce water condensation. This study shows that winter precipitation amount correlates with interannual variation of river stream flow in the month when the annual maximum in river streamflow occurs.
We applied Self-Organizing Maps (SOM) to categorize circulation patterns. The results show that variation of circulation patterns, based on clusters of daily 500-hPa circulation patterns produced by a SOM analysis, were able to explain a relatively large fraction of interannual variation of monthly mean precipitation in western and northern Europe. However, the explained fraction decreases towards eastern Europe. Based on the SOM analysis, four main circulation types, which strongly affect regional interannual variation of precipitation in western and northern Europe, were recognized: (i) “Westerly flow” characterized by an almost zonal circulation pattern in the 500-hPa geopotential field causes the strongest positive precipitation anomalies in a large part of western Europe. (ii) “Wester European blocking” decreased precipitation over a large part of western Europe but increased it in Scandinavia due to a northward moisture transport from the northern North Atlantic. (iii) “North Atlantic blocking” together with an upper-level trough over the Baltic Sea region allows moisture transport from the North Sea to central Europe, causing positive anomalies in precipitation in central Europe. (iv) “Azorean low” centred over the northern side of Azores allows moisture transport from the North Atlantic to reach Iberian Peninsula and the Mediterranean region, increasing precipitation in the region. Even though these circulation types are not able to exhaustively explain the entire interannual variation of precipitation in western and northern Europe, a frequent occurrence of some of these circulation types increases probability of enhanced river stream flow in the region where the circulation type causes positive precipitation anomalies.
How to cite:
Naakka, T., Nygård, T., Shevnina, E., Vihma, T., and Karpechko, A.: Effects of large-scale atmospheric circulation on precipitation and river stream flows in Europe during cold seasons, EMS Annual Meeting 2022, Bonn, Germany, 5–9 Sep 2022, EMS2022-202, https://doi.org/10.5194/ems2022-202, 2022.
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Eleonora Dallan, Bardia Roghani, Giorgia Fosser, Christoph Schaer, Marco Marani, Marco Borga, and Francesco Marra
Subdaily extreme precipitation may trigger fast hydro-geomorphic responses, such as flash floods and debris flows, which cause numerous fatalities and large damage. High-resolution climate models, called convection-permitting models (CPMs), represent convective processes more realistically than coarser resolution models. These processes are crucial for the correct representation of subdaily extremes, and thus CPMs provide higher confidence in the estimate of future extreme precipitation. However, because of their high computational cost, the existing CPM runs are available for relatively short time periods (10–20 years at most) that are too short for deriving precipitation frequency analyses with conventional extreme value methods. Recent approaches are based on many “ordinary” events rather than on just yearly maxima or a few values over a high threshold. They demonstrate the capability to provide reliably estimate of return levels associated with long return periods from short data record, thus they offer the chance to be effectively applied to the analysis of CPM data.
In the present study, we estimate the changes in subdaily precipitation extremes from COSMO-crCLIM model simulations at 2.2 km resolution, for three 10-year time slices (historical 1996-2005, near-future 2041-2050, and far future 2090-2099 – under the RCP8.5 scenario). We focus on the Eastern Alpine transect, characterized by a complex orography, where significant changes in subdaily annual maxima have been already observed. We apply an ordinary-event statistical method for the estimation of the extreme precipitation with duration ranging from 1 h to 24 h. We analyze the changes between the time periods in both the annual maxima, the quantiles, and the distribution parameters. We find that, although the storms' frequency will generally decrease in the region, the mean annual maxima will increase continuously in the near and far future, especially at shorter durations. Investigation of extreme return levels shows a similar trend, with larger changes in the far future at the shorter duration. Interestingly, the emerging spatial patterns in the changes can be associated to the orographic features of the study area: the stronger increasing changes are located in the high elevation zone, while the flat zone shows weak decrease and weak increase in the near and far future, respectively.
These analysis and results are useful for improving our knowledge about the projected future changes in extreme precipitation and thus for improving the strategies for risk management and adaptation.
How to cite:
Dallan, E., Roghani, B., Fosser, G., Schaer, C., Marani, M., Borga, M., and Marra, F.: Projected changes in subdaily extreme precipitation over an alpine transect, at convection-permitting scale, EMS Annual Meeting 2022, Bonn, Germany, 5–9 Sep 2022, EMS2022-510, https://doi.org/10.5194/ems2022-510, 2022.
Soil moisture is a key variable in the hydrologic cycle and affects weather and climate; thus, accurate soil moisture prediction is essential in the land surface modeling. In this study, we have used a land surface model, called the University of Torino land surface Process model for Interaction in the Atmosphere (UTOPIA), to predict the soil moisture. The UTOPIA is a one-dimensional model representing the interactions among atmosphere, land surface, vegetation and soil layers. Being UTOPIA a multilayer soil model, the user can discretize the soil into a certain number of layers: each layer needs specific physical properties related to soil moisture and temperature depending on the soil texture type. The soil texture allows to infer a useful information about the soil, such as the wilting point, field capacity, heat capacity, and eventually soil moisture. However, it is hard to obtain the accurate information of soil texture, especially in deep soil layers, due to insufficient and/or uncertain observation. Therefore, we have implemented the micro-genetic algorithm (micro-GA) within UTOPIA to optimize the soil textures by comparing the model-generated soil moistures versus the in-situ observations. The micro-GA is a global optimization algorithm based on the natural selection or survival of fitness to evolve the best potential solution. As a preliminary result, we anticipate that the optimal soil textures within the multiple layers lead a substantial improvement on soil moisture prediction. Furthermore, we will investigate the changes in latent and sensible heat fluxes which can be affect to the atmosphere model from the soil moisture improvements.
How to cite:
Lim, S., Park, S. K., and Cassardo, C.: Optimization of Soil Texture to Improve the Soil Moisture in the Land Surface Model, EMS Annual Meeting 2022, Bonn, Germany, 5–9 Sep 2022, EMS2022-418, https://doi.org/10.5194/ems2022-418, 2022.
Zengjing Song, Yijian Zeng, Mingguo Ma, Bob Su, and Monica Gracia
Water stress factor is utilized to describe drought effects on plant growth in land surface models (LSMs). Accurately representing water stress is critical to understand the impact of climate change on plant and ecosystem. Models use various approaches to describe the responses of vegetation to water stress. Some models assumed water stress causes stomata closure to attenuate gas exchange process, while others assumed water stress reduces the maximum rate of carboxylation (Vcmax) to slow photosynthesis. Only a few models considered both constraints. However, which parameterization can better capture the dry condition is still controversial. A reliable detection and attribution of the impact of water stress on plant is necessary for understanding the consequence of climate change on the ecosystem from a mechanism aspect. In this study, an empirical stomatal conductance scheme (proposed by Ball et al. in1987, called “BB_gs”) and a unified stomatal conductance model (proposed by Medlyn et al. 2011, called “ME_gs”) were coupled into STEMMUS-SCOPE model to explore the discrepancy between empirical and optimal approaches. Three scenarios were designed to represent the effect of water stress on gas exchange (gs_w), photosynthesis (Vcmax_w) and both processes (gs & Vcmax_w). The coupled model was implemented for three sites with different plant function types, including C3 grassland, C3 shrub, and C4 cropland. Results showed that the optimal stomatal conductance scheme has better performance than the empirical approach because the optimal method considers the realistic stomata regulation. The Vcmax_w scheme captured the drought effects better than other schemes. The results improved our understanding on regional ecosystem functioning under the context of climate change.
How to cite:
Song, Z., Zeng, Y., Ma, M., Su, B., and Gracia, M.: Investigating plant’s stomatal and non-stomatal responses to water stress via STEMMUS-SCOPE model, EMS Annual Meeting 2022, Bonn, Germany, 5–9 Sep 2022, EMS2022-310, https://doi.org/10.5194/ems2022-310, 2022.
Coffee break
Chairperson: Fatima Pillosu
Integrated environmental forecasting systems for decision support
Christel Prudhomme, Gabriele Arduini, Gianpalo Balsamo, Andy Brown, Souhail Boussetta, Hannah Cloke, patricia de Rosnay, Shaun Harrigan, Cinzia Mazzetti, Florian Pappenberger, Irina Sandu, and Ervin zsoter
Traditional Numerical Weather Prediction Systems focus on the modelling of the atmosphere, ocean and land processes, ignoring some more complex hydrological processes including the simulation of river discharge. In this talk, we describe how integrating simple one-way coupling of hydrological processes within a land surface and atmosphere modelling system can help understanding key biases and limitations in the simulations, using the ECMWF ECLand platform as an example.
Hydrological processes are generally defined within Earth System Modelling by vertical infiltration and evaporation fluxes without long-term land storage other that snowpack. In the real world, however, horizontal water movements and water land storage mean that river discharge measured in a catchment outlet is a natural integrator of water balance processes both in time and space. Over the last three years, ECMWF conducted multiple experiments to generate river discharge timeseries with different configurations of ECLand, the earth system modular platform of its Integrated Forecast System. The experiments used CaMAFlood, a global river hydrodynamic model, to transform daily runoff generated by HTESSEL, the Land Surface component of the ECLand, into river discharge multi-annual reanalysis time series. Simulations were verified against observations from the Global Runoff Data Centre worldwide for catchments selected for the limited impact of anthropogenic influence. Results showed the power of river discharge to amplify any discrepancy between modelled and observed timeseries and identified some weakness in the existing operational configuration of ECMWF’s IFS, including, for example, the impact of Data Assimilation on water balance closure and long-term trends in reanalysis datasets such as ERA5, or how multi-layer snow modelling could affect water processes in permafrost areas.
The work demonstrates the power of a holistic Earth System Modelling approach integrating river discharge as a diagnostic tool for land surface processes verification, paving the way for a future more complex coupling of atmosphere and land components.
How to cite:
Prudhomme, C., Arduini, G., Balsamo, G., Brown, A., Boussetta, S., Cloke, H., de Rosnay, P., Harrigan, S., Mazzetti, C., Pappenberger, F., Sandu, I., and zsoter, E.: EC-Land Hydro: the benefits of integrating hydrology in earth system modelling, EMS Annual Meeting 2022, Bonn, Germany, 5–9 Sep 2022, EMS2022-692, https://doi.org/10.5194/ems2022-692, 2022.
Segolene Berthou, Alex Arnold, Juan Manuel Castillo, Huw Lewis, Sana Mahmood, and Claudio Sanchez
In partnership with other UK institutions, the UK Met Office has developed a regional environmental prediction system at km scale, over two domains: the Northwest European shelf and the Indian region. This provides a flexible research capability with which to study the interactions between atmosphere, land, river, ocean, wave and biogeochemistry processes resolved at km-scale, and the effect of environmental feedbacks on the evolution and impacts of multi-hazard weather events. The UKC3 coupled system incorporates models of the atmosphere (Met Office Unified Model), land surface with river routing (JULES), shelf-sea ocean (NEMO), ocean surface waves (WAVEWATCH III) and biogeochemistry (ERSEM) coupled together using OASIS3-MCT libraries and the FabM coupler. This research framework has enabled to uncover interesting scientific results and to improve to both atmospheric and marine weather prediction. Recent developments have further enabled to run the system in ensemble forecast mode and in climate mode. We present advances allowed by this system, such as:
benefits of ocean/wave coupled system for marine forecasting
Improvements of summer temperature forecasts by using SST prediction from the marine prediction system
improvements to winter storm wind forecasting when coupling the atmosphere with the wave models, resulting in changes to the atmospheric drag scheme
changes to tropical cyclone prediction from atmosphere-ocean coupling mostly, coupled system enabling a more rigorous treatment of the near-surface energy budget
Benefits and challenges of integrated hydrology
dampening of UK heatwaves by tidal processes over the northwest European shelf
effects of representing marine diurnal cycle on the diurnal cycle of convection over the maritime continent
impacts of an SST perturbation scheme in ensemble forecasting system
first atmosphere/ocean climate runs at km-scale over the Northwest European self.
How to cite:
Berthou, S., Arnold, A., Castillo, J. M., Lewis, H., Mahmood, S., and Sanchez, C.: Advances enabled by a Regional Environmental Prediction system developed in the UK, EMS Annual Meeting 2022, Bonn, Germany, 5–9 Sep 2022, EMS2022-664, https://doi.org/10.5194/ems2022-664, 2022.
Fredrik Wetterhall, Umberto Modigliani, Francesca Moschini, Bojan Kasic, and Stefano Ferri
The project “South-East European Multi-Hazard Early Warning Advisory System” (SEE-MHEWS-A) is a collaborative effort to strengthen the existing early warning capacity in south-eastern Europe. The project was initiated in 2016 by the World Meteorological Organization (WMO) and has been supported by the U.S. Agency for International Development (USAID), World Bank and the European Commission and has now developed from a concept into implementation of a quasi-operational multi-hazard forecasting and decision making system. The SEE-MHEWS-A project will benefit the national meteorological and hydrological services of WMO Members from the region - that is Albania, Bosnia-Herzegovina, Bulgaria, Croatia, Cyprus, Greece, Hungary, Israel, Jordan, Lebanon, North Macedonia, Republic of Moldova, Montenegro, Romania, Serbia, Slovenia, Turkey and Ukraine. The system contains a full multi-model hydrometeorological chain with four limited area numerical weather prediction models (LAM) that provide input to three hydrological models. The LAM's are COSMO, ICON, NMMB and ALARO. The hydrological models are LISFLOOD, HBV and WFLOW. The pilot also consists of a meteorological nowcasting system, and the outputs are visualized on a web-based interactive platform. SEE-MHEWS-A will provide operational forecasters with effective and tested tools for forecasting hazardous weather events and their possible impacts in order to improve the accuracy of warnings and their relevance to stakeholders and users. The project has so far led to an increase in sharing of observations, information and expertise between the countries in the area. It has also allowed for development of innovative ways of presenting the hydrometeorological information to support forecasting and decision-support activities in the region.
How to cite:
Wetterhall, F., Modigliani, U., Moschini, F., Kasic, B., and Ferri, S.: Creating a coupled multi-model hydrometeorological forecasting and decision support system, EMS Annual Meeting 2022, Bonn, Germany, 5–9 Sep 2022, EMS2022-222, https://doi.org/10.5194/ems2022-222, 2022.
17:00–17:15
Poster Pitches
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Juan Quiros, Bastian Siegmann, Alexander Damm, and Uwe Rascher
Climate conditions directly impact on vegetation growth, this is quite clear; yet, “how vegetation functioning alters climate?” is an open query rising many questions. Understanding the impact of vegetation functioning on climate is important to better comprehend climatological processes and thus to improve models, due to the influence of plants on the carbon and water cycles. For decades it was impossible to have information about plant functioning in the (regional to global) scale of climatological models, nevertheless, the advent of satellite-based remote sensing (RS) methods for the retrieval of sun-induced chlorophyll fluorescence (SIF, as a proxy of photosynthesis) made it feasible. For instance, using satellite SIF and precipitation data, Green et al. (2017; DOI 10.1038/ngeo2957) recently provided one of the first contributions in such direction. The authors reported that regional biosphere-atmosphere feedbacks can explain up to 30% of precipitation variance, mainly because of the role of plants in the regulation of the water flux from the soil towards the atmosphere. As a complement to such studies with focus on the vegetation-atmosphere link, in two recent studies we analyzed the relation that SIF has with the soil water content (SWC) at airborne and satellite scales. At airborne scale we found that (i) the SIF-SWC relation is crop- and growth stage-dependent, and that (ii) SIF showed a faster response to water limitations compared to conventional (reflectance-based) RS products. On the satellite level we found a strong impact of the SIF-SWC relation on the gross primary productivity (GPP) during a heat wave at European scale. With these contributions from the RS area, we aim to provide novel information that can help the meteorological research community to better understand how vegetation functioning can alter climatological processes, with potential applications in the improvement of climate models.
How to cite:
Quiros, J., Siegmann, B., Damm, A., and Rascher, U.: Vegetation and climate: initial concepts about the relation between the sun-induced chlorophyll fluorescence (SIF) and the soil water content (SWC), EMS Annual Meeting 2022, Bonn, Germany, 5–9 Sep 2022, EMS2022-612, https://doi.org/10.5194/ems2022-612, 2022.
Peter Kalverla, Imme Benedict, Ruud van der Ent, Chris Weijenborg, and Rein Haarsma
Atmospheric moisture tracking is a valuable technique for understanding the physical processes that drive (extreme) precipitation and drought in our changing climate. By following where precipitated moisture originally evaporated (backtracking) or where evaporated moisture eventually precipitates (forward tracking) we can gain valuable insights into the connection of large-scale weather systems and hydrometeorological events, land-atmosphere interactions, or the impact of land-use changes on water availability.
The WAM-2layers model is a Eulerian moisture tracking code that solves the water balance equation for tagged moisture in gridded model output data. Originally developed by Ruud van der Ent, the code has been reused by various others, and still more have expressed interest. With the increasing resolution of weather and climate models, however, data handling and performance have become a serious constraint.
In a new optimization project with the Netherlands eScience Center, we aim to tackle these computational challenges and develop an improved version of WAM-2layers. The updated code should be flexible and easy to use with input data from different sources including ERA5. This will enable a series of sensitivity experiments to establish best practices and case studies to answer new research questions. As a proof of concept, the optimized code will be used to study the extreme precipitation event that lead to heavy floods in the Eiffel and the Ardennes in July of 2021.
At the EMS conference, we will show the first results of the optimization project. This abstract focuses on the technical aspects and how others can reuse or contribute to the code. In a companion abstract (Benedict et al.) we will present some scientific results.
How to cite:
Kalverla, P., Benedict, I., van der Ent, R., Weijenborg, C., and Haarsma, R.: User-friendly moisture tracking with WAM-2layers, EMS Annual Meeting 2022, Bonn, Germany, 5–9 Sep 2022, EMS2022-105, https://doi.org/10.5194/ems2022-105, 2022.
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Lorenzo Sangelantoni, Rossella Ferretti, Gianluca Redaelli, and Stefan Sobolowski
Soil moisture-atmosphere feedback plays an important role in shaping summer temperature variability and eventually in modulating duration, intensity, and predictability of heat waves.
Recent studies point out a modulation of summer temperatures introduced by the new generation of km-scale (or convection-permitting, CP) regional climate models (RCMs), compared to convection-parameterized RCMs. Modifications are likely originated from changes in soil moisture-precipitation feedback. This generally turns into an extension of dry spell length (DSL) determining warmer conditions in response to an altered partitioning of surface heat fluxes.
In this study, two potentially relevant factors behind modifications in land-atmosphere interactions at the two resolutions are investigated on a seasonal temporal scale. The first, is the underestimation of summer season convective phenomena, as an outcome of a poor sensitivity to triggering factors and driving longer DSL in km-scale simulations. The second is represented by differences in soil moisture memory between RCM and CPRCM.
We perform simulations with the ECMWF-ERA5 driven WRF-4.2.1 model consisting of a two-step dynamical downscaling at ~15 km (non-CP scale) and ~ 3km (CP scale) respectively. The greater alpine region and extended summer seasons (May to September) represent spatial and temporal domains.
The underestimation of the summer season convection will be explored considering simulations at (i) 15 km with parameterized convection, (ii) 3 km with explicit convection (CPRCM_exp) and (iii) 3 km with parameterized convection (CPRCM_par) according to different numerical schemes. This is to explore whether parameterizing deep convection at CP scale mitigates poor convection-triggering processes sensitivity caused by weak large scale forcing.
The soil moisture memory is assessed through autocorrelation analysis applied to three simulations: one standard and two idealized soil-moisture-perturbed-initialization defining anomalously dry- and wet-initialization experiments. Here, ground-water-aware configuration of Noah-MP land surface model (LSM) will be compared to a more simplified LSM configuration.
Preliminary results for the 2003 summer season show differences in precipitation statistics between the two different resolutions and between CPRCM_exp/CPRCM_par. We observe an increase in wet-hour frequency, an increase and different spatial pattern of precipitation 99th percentile in CPRCM_par.
Concerning soil moisture memory, initial differences are preserved in the two resolutions for the first month run. After that, differences decay in the CPRCM, where all the three simulations converge to similar soil moisture at the end of the run. Differently, RCM preserves a larger difference of soil moisture until the end of the run indicating a longer memory of the initial state, particularly in the wet-initialization experiment.
Several reference products will be considered to evaluate resulting modulations, namely if a km-scale deep convection parameterization can be beneficial and if the shorter soil moisture memory resulting in the km-scale simulations represents an improvement.
Outcomes might offer insights on the km-scale influence on seasonal time-scale prediction of soil-atmosphere-interaction-driven extreme events.
How to cite:
Sangelantoni, L., Ferretti, R., Redaelli, G., and Sobolowski, S.: Summer season convection inhibition and soil moisture memory in km-scale climate simulations, EMS Annual Meeting 2022, Bonn, Germany, 5–9 Sep 2022, EMS2022-155, https://doi.org/10.5194/ems2022-155, 2022.
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Christina Asmus, Peter Hoffmann, Joni-Pekka Pietikäinen, Jürgen Böhner, and Diana Rechid
Land management practices modify the land surface by changing its biogeophysical and biogeochemical properties, leading to heterogeneous surface and soil conditions. One example for this is irrigation, which is widely used to overcome unsuitable climatic conditions in agriculture to protect plants from water stress. Irrigation leads to a heterogeneous and time-varying soil moisture distribution. Soil moisture conditions are known to feedback with the atmosphere. Previous studies analyzed the soil moisture-precipitation feedback and focused on the development conditions of convection. However, uncertainties in the magnitude and sign of this feedback remain due to the representation of convection in the climate model. Therefore, convection-permitting simulations are crucial to understanding the link between soil moisture and convection.
In our study, we investigate this link by taking into account sudden soil moisture changes through irrigation and the resulting heterogeneity of soil moisture distribution. Our aim is to understand how irrigation influences development conditions for convection in the atmosphere. For this purpose, we conduct convection-permitting simulations at high resolution with a focus on the Po valley in Northern Italy. We use the non-hydrostatic version of the regional climate model REMO which in our setup is interactively coupled to its mosaic-based vegetation module iMOVE. For REMO-iMOVE we developed and implemented a new irrigation parameterization based on a fractional approach which makes it suitable for the representation of heterogeneous soil moisture distribution.
We will present the effects of irrigation on the development of convection in the Po valley by analyzing selected atmospheric variables from simulations with and without irrigation.
How to cite:
Asmus, C., Hoffmann, P., Pietikäinen, J.-P., Böhner, J., and Rechid, D.: Analyzing the influence of irrigation on convection – Case study for Northern Italy using convection-permitting simulations, EMS Annual Meeting 2022, Bonn, Germany, 5–9 Sep 2022, EMS2022-275, https://doi.org/10.5194/ems2022-275, 2022.
"ecPoint" is a statistical post-processing technique that anticipates sub-grid variability and biases in numerical weather prediction (NWP) model outputs, de facto downscaling them from grid-box to point-scale. ecPoint-Rainfall is the branch of the ecPoint family of products that post-processes ECMWF ensemble (ENS) rainfall forecasts. Global verification over a 1-year period has shown that, versus rain gauge observations, ecPoint-Rainfall provides more reliable and skilful rainfall forecasts than raw ENS (up to 10-day lead times and especially in case of extremes, e.g. rainfall >= 50 mm/12h).
Flash flood forecasting could be a natural downstream application for ecPoint-Rainfall. One of this field's challenges is indeed finding reliable and skilful forecasts for localized rainfall extremes, which tend to be the primary cause of flash flood events. Radar-derived rainfall estimates can feed into nowcasting systems (which provide forecasts with lead times up to a few hours), whilst km-scale NWP models can provide reasonable guidance for localized extreme rainfall for slightly longer leads (e.g. up to 24 hours). However, such small lead times limit the mitigating actions that end-users can take. ecPoint-Rainfall targets longer leads.
ecPoint-Rainfall forecasts have been verified against flash flood observations in Ecuador to understand whether they can better predict flash floods compared to other medium-range rainfall forecasts (e.g. raw ECMWF ENS). It will be shown that, in the context of flash flood reports, in regions dominated by small scale convective systems (e.g. Ecuador's Andean region), ecPoint-Rainfall outperforms ENS. In contrast, in areas dominated by large-scale convective systems (e.g. coastal areas of Ecuador), the performance of the two forecasting systems is comparable. This talk will discuss these findings and how they are helping with the creation of global medium-range, ecPoint-Rainfall-based flash flood warnings.
How to cite:
Pillosu, F. and the Flash Flood Team: Predicting flash floods in Ecuador and beyond, EMS Annual Meeting 2022, Bonn, Germany, 5–9 Sep 2022, EMS2022-685, https://doi.org/10.5194/ems2022-685, 2022.
Santiago Gaztelumendi, Ivan R.Gelpi, Aurelio Diaz de Arcaya, Jose Daniel Gomez de Segura, Roberto Hernandez, Eduardo Garcia, Julio Cesar Salazar, Christian Stocker, and Jose Antonio Aranda
Floods are among the world’s deadliest natural disasters with significant social, economic and environmental impacts. In Basque Country, as in other parts of the World with similar geomorphological and hydrometeorological characteristics, flooding events are produced on relatively short spatial and temporal scales (flash floods) making flood modeling a particularly difficult challenge. Major flash floods episodes in Basque Country are produced when rivers react to intense and persistent rainfall that are produced on saturated soils scenarios, occasionally with extra water from snow-melting processes. In this context, nowcasting and very short term forecasting tools (up to 12 hours) are essential in order to manage impact events in real time and to provide different operational products and warning guidance for hydrological, meteorological and civil protection authorities.
In this contribution, we present different aspects in relation to a project, that we have begun in 2021, to implement an operational hydrological nowcasting system for the Basque Country to address the different issues associated with flash floods in the territory and to improve local warning effectiveness. This project is promoted by Basque Government, financed with Basque Water Agency funds in collaboration with the Basque Meteorology Agency (Emergencies and Meteorology Directorate – Security Department). Technical development is performed by meteorological and hydrological experts from Tecnalia (BRTA- Basque Research and Tecnology Alliance) and IHCantabria. One of the aims of this project, in addition to the specific nowcasting technical results, is the generation of hydro-meteorological synergies, where experts from both disciplines can join forces, to combine and exploit expertise, and to accelerate the implementation process of local hydro-meteorological operational systems.
In this paper we focus, not only in technical aspects related with the nowcasting tool we are developing, but in the implementation process itself, where meteorological and hydrological experts join forces and focus on practical local solutions. We introduce the general scheme of the system, describing the functionalities of the main modules and detailing the technical solutions incorporated to deal with the different hydrological and meteorological analysis and prediction needs at different espatio-temporal scales. We describe the pre-processing and post-processing modules paying special attention to the integrated hydro-meteorological analysis and visualization tools. Likewise, we include the description of the validation and verification strategies of the system. We summarize our experience and present some conclusions from workshops and others joint hydro-meteo working sessions that have taken place during the project. In these sessions, the hydrological and meteorological experts have exchanged impressions, forging a joint vision, defining specifications and agreeing on the characteristics that must have a fully useful system for the operational needs and responsibilities of both agencies.
How to cite:
Gaztelumendi, S., R.Gelpi, I., Diaz de Arcaya, A., Gomez de Segura, J. D., Hernandez, R., Garcia, E., Salazar, J. C., Stocker, C., and Aranda, J. A.: The Basque hydrologic nowcasting project, EMS Annual Meeting 2022, Bonn, Germany, 5–9 Sep 2022, EMS2022-590, https://doi.org/10.5194/ems2022-590, 2022.
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