bluuebunny/crossref_metadata_2025 huggingface dataset:
A low-cost approach to develop Weather, Water and Climate Services (WWCS) in rural areas of Tajikistan
Authors: Bellprat Omar , Spirig Christoph , Flubacher Moritz , Grandjean Jacques , Roulet Yves-Alain , Moret Lionel , Bavay Mathias , Fiddes Joel , Orlowsky Boris , Kassam Shinan , Kalandarov Hafiz , Yatimov Safarali , Akmal Akramkhanov , Strohmeier Stefan Martin , Sharma Ram , Haddad Mira , Govind Ajit , Fatih Kaya , Berod Dominique
Published: June 2022

Severe weather and climate change take a high toll on the most vulnerable population of Tajikistan. Every year, droughts, flooding or avalanches and non-optimal management practices cause food insecurity and affect the lives of exposed rural communities. Weather, Water and Climate Services (WWCS) that support agronomic decisions and early warning systems can greatly reduce socio-economic and environmental impacts on vulnerability and well-being. However, a lack of resources and local capacities have so far inhibited their development. In response to this urgent need, a consortium of Swiss federal institutions, the WMO and ICARDA, led by CARITAS Switzerland and with co-funding from the Swiss Agency for Development and Cooperation, support governmental and private sector partners in Tajikistan to develop WWCS. The project improves the observational database by deploying a large number of low-cost automated weather stations complemented by citizen observations in remote areas. These stations enable post-processing of forecasts and thereby the development of reliable services tailored to local user-needs.  The underlying hardware and software developments follow a strict open-source policy and combine technical expertise in sensor development and statistical post-processing. The approach enables therefore replicability and scaling of the services at minimal costs. Comparative measurement studies show promising accuracy and stability of the data retrieval in comparison to more standard approaches. Post-processing of ECMWF ensemble predictions, which are now publicly available at a resolution of 0.4° (~40km), proved efficient to develop reliable air temperature forecasts. Pilot WWCS based on citizen observations have already helped to increase agricultural yield at a test site.
Interventions of the State Fire Services in the Wielkopolska region (Poland) triggered by extreme precipitation 
Authors: Pińskwar Iwona , Choryński Adam , Graczyk Dariusz
Published: June 2022

Precipitation extremes have been intensifying with the warming of climate on a global scale and in most regions of the world (Sun et al., J. Clim. 2021), because in warmer air more water vapor can be stored. According to the Clausius–Clapeyron law, this sensitivity is 6–7% K−1. Analysis of the 99th percentile of precipitation for Poland for the two periods of 1989–2018 and 1959–1988 (Pińskwar, Int. J. of Climatology 2022),  indicate an increase in sensitivity (6.06%/°C and 5.26%/°C, respectively), and therefore the potential for more extreme precipitation is growing.

In this research we analyze the number of interventions of the State Fire Services in Wielkopolska Region triggered by extreme precipitation. Data (23887 interventions with longitude and latitude) were collected for the period 2010-2021 by 71 units of the Wielkopolska State Fire Service located in the region. Every intervention was linked to the nearest precipitation station (103 gauge stations data from the Institute of Meteorology and Water Management IMGW-PIB). A value of up to 20 km was considered as a representative distance (17810 interventions). Analyses revealed that the highest number of interventions occurred in 2010 (daily maximum of 530 during 24th of July 2010 with the highest 24h precipitation of 59.5mm; nearly 3% of all interventions). The three highest daily number of interventions in relation to one station occurred in 2021: 9th of July (99 interventions, with 24h precipitation of 18.6mm and 48h of 69.5 mm, on this day: 326 interventions in Wielkopolska region) and two during 22nd of June: 85 interventions by 24h precipitation of 136.9mm (Gruszczyn, near Poznan) and 82 interventions by 24h precipitation of 79.4mm (Poznan; both densely populated and impermeable areas). The distance between stations of Poznan and Gruszczyn is only 15.7km. It illustrates, how local and sometimes not recorded is extreme precipitation. For interventions, when precipitation (24h and 5-day) has been not recorded, we use the radar data from IMGW-PIB. The aim of this study is to examine, how extreme precipitation induced interventions of the units of State Fire Service and also to identify the most vulnerable regions in Wielkopolska.

Acknowledgements: Research has been supported by the National Science Centre of Poland [project number 2018/31/B/HS4/03223].
An Artificial Intelligence–Based Blending of Satellite products across Mediterranean Island of Sicily, Italy using GPM-IMERG V06 Final Run
Authors: Noto Leonardo , Beikahmadi Niloufar , Pumo Dario , Francipane Antonio
Published: June 2022

Precipitation is the key input variable to hydrological models and its monitoring plays a significant role in water resources planning and improving flood and drought forecasting, also under climate change impacts. In recent years, many precipitation satellite products have been developed and released to the public; among these, the Integrated Multi-satellitE Retrievals from Global Precipitation Measurement (IMERG) is designed to address limitations and uncertainties related to traditional methods.

The primary purpose of this study is to provide a comprehensive assessment of precipitation estimates retrieved from the IMERG v6 Final Run over the Mediterranean island of Sicily (Italy) at daily and half-hourly temporal and at 0.1° spatial resolution for the first time using a quality-controlled sub-hourly gauge dataset. Sicily, which is characterized by a Mediterranean climate and a complex orography, experiences rather frequent short duration and high intensity precipitation originating from the interaction of steep orography on the coasts with winds carrying humid air masses from the Mediterranean Sea.

Previous studies have highlighted that most of the available satellite-based precipitation products show poor performance for capturing rainfall events at high temporal resolution particularly in coastal areas. Based on these findings, there is a critical need to put much effort to improve retrieval algorithms to account for coastal and morphological effects, thus enhancing satellite-based precipitation estimations for those areas. With this regard, this work also aims to show that a combination of multiple products may result in more accurate estimations especially for short duration events. This merging technique, which has been carried out exploiting artificial intelligence (AI) techniques, is shown to successfully reduce the error based on the comparison with data from a local rain gauge network. The results of the study will demonstrate the proficiency of the AI based approaches for improving remote-sensed daily and sub-hourly rainfall products even in coastal areas with complex orography.
Cloud Shadows in Satellite-Based Solar irradiance Estimation: Improved Correction using EUMETSAT’s Cloud Top Height Data
Authors: Roy Arindam , Hammer Annette , Heinemann Detlev , Lünsdorf Ontje
Published: June 2022

The estimation of solar surface irradiance at high spatio-temporal resolution from geo-stationary satellite images is a well-established technique, for example by using the Heliosat method. The method has widely reduced the need for expensive ground measurements, especially in remote regions. However, the location of cloud shadows at the ground is difficult to determine and thus a significant source of errors when either the distance from the sub-satellite point or the cloud top height (CTH) increases. Although several methods have been proposed in the literature to reduce these errors, it is still an issue. We present a novel approach to correct the cloud shadow location based on the satellite-cloud-sun geometry using the CTH maps from the EUMETSAT data archive. It uses satellite viewing angles and solar position angles to determine the correct cloud shadow location for each cloudy pixel. The method is tested on cloud index (CI) maps for the months of July, August and September 2018 derived by applying the Heliosat method on the 0.6 um visible channel images from Meteosat-8 located at 41.5°E. Convective clouds with large CTHs are frequently observed over the Indian subcontinent in these three months due to the Indian summer monsoon. The global horizontal solar irradiance (GHI) obtained from the corrected CI image is validated at two BSRN stations. The normalized root mean square error (nRMSE) is reduced from 23.2% to 20.9% for the Gurgaon station and from 15.4% to 13.9% at Tiruvallur. In general, correcting the cloud shadow location on CI map improved the accuracy of the estimated GHI. Nonetheless, the method is sensitive to the accuracy of the CTH dataset and individual cases were found for which the correction reduced the accuracy.
Future summer changes in zonal surface circulation types and mid-tropospheric weather regimes over Europe
Authors: Krouma Meriem , Herrera Lormendez Pedro , Yiou Pascal , Matschullat Jörg
Published: June 2022

Surface atmospheric circulations strongly influence the day-to-day weather of a region. Their anomalous persistence over longer time periods can prompt the occurrence of events like droughts and heatwaves. As our planet continues to warm,  an increase in the frequency and intensity of these events over the European continent is expected. Using an automated method to classify surface synoptic patterns and data from a subset of GCMs from the high-emission scenario from CMIP6, we find significant future changes in the frequency of zonal atmospheric circulations during the projected summers (JJA). The likely decrease in the frequency of westerly advection results in an increase in easterly synoptic configurations over Central Europe resulting in more dry continental air masses moving through the region.

In this work, we investigate whether the future change in the zonal surface circulation types relates to predetermined weather regimes over Europe. We address this question by performing the attribution of the changes in some zonal surface circulation types. We focus on the role of the changing large-scale atmospheric circulations and their likelihood in historical and future climate conditions that we define using CMIP6 data from 1979 to 2100. We employ analogs of circulation to find the most similar patterns to the target synoptic configuration in both[1]  climatological periods. These analogs are computed from geopotential height at 500hPa (Z500) over the Euro-Atlantic region. We then compute the shifts in the probability distributions, persistence and predictability of these events. We estimate the significance of the changes in the mid-tropospheric configurations that relate to the changing easterly and westerly surface atmospheric patterns.
Projected changes in subdaily extreme precipitation over an alpine transect, at convection-permitting scale
Authors: Dallan Eleonora , Roghani Bardia , Fosser Giorgia , Schaer Christoph , Marani Marco , Borga Marco , Marra Francesco
Published: June 2022

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.
Past, present and the possible future of cold wave alarm in Croatia
Authors: Magjarević Vjeran , Srnec Lidija
Published: June 2022

Cold waves or cold spells, similar to warm ones, affect people causing increased mortality and morbidity. Thus, it is state obligation to organize and ensure the on time heat wave, but also the cold wave, warning system.

Similar to the heat wave warnings, issuing the cold waves warnings in Croatia is the responsibility of DHMZ - Croatian Meteorological and Hydrological Service (national weather service). However, while the criteria for issuing warnings on heat waves and the levels of these warnings are the same for National system and Meteoalarm system, the criteria for issuing warnings about the low temperature are not the same in those two systems. The mechanism by which the human body reacts to extreme cold is different from the reaction to extreme heat. Low temperatures greatly affect people, but also can significantly affect the energy supply, especially electricity, the freezing of liquids, etc. In other words, thresholds that become critical to health in some regions can differ significantly from the temperature values that can affect the energy sector i.e. economy, traffic, etc.

At present, criteria for the occurrence of cold waves that can be dangerous to human health in Croatia is determined using mortality data and air temperature data for the period 1983-2008. The three degrees of danger are determined by the degree of increase in mortality. As these is determined for just eight different areas in Croatia, and Croatia is geographically quite diverse country, there is a need to develop alarm on more detailed spatial scale. DHMZ is working on introducing the new system of cold alarm based on different, spatially more variable, thresholds for extreme temperatures.

In this presentation we will compare the use of the existing criteria for the occurrence of cold waves (based on the mortality and air temperature data thresholds) and the possible calculation of the cold waves occurance using some of the cold indices (e.g. ECACWDI, ECACWFI) - climate indices based on the daily temperature parameters.
Investigation of the vertical structure of the lower atmosphere during heat wave conditions
Authors: Fohrmann Till , Hense Andreas , Friederichs Petra
Published: June 2022

Research on heat waves and extreme events in general is highly motivated by their impacts on human life and the economy. Therefore, the focus is on near surface variables and less research has been done on the state of the lower atmosphere as a whole. In a study of the mega heat waves of 2003 in France and 2010 in Russia, Miralles et al. (2014) investigate which factors have to come together to enable such extremes. One interesting finding is the gradual increase in planetary boundary layer height during those events. Also, their simulations display a correlation between mean potential temperature in the lower atmosphere and the boundary layer height. For these reasons, we believe that a systematic analysis of the planetary boundary layer during heat waves may provide valuable insights into their formation and persistence. We investigate whether these features are common traits of European heat waves in general. To this end, we apply a classification and regression scheme to vertical profiles taken from COSMO-REA6 data for the summers of 2014 to 2018. The reanalysis data is also used to identify heat waves, such that a comparison of boundary layers during normal and extreme conditions is possible. We analyse the distributions of planetary boundary layer heights for every grid point to check for regional differences. For validation, we make a comparison to radio soundings taken from the DWD Open Data service. The results of our work could possibly be used to improve the discriminability of different severity levels of heat waves or to formulate a heat wave measure that is not based solely on surface variables.
Evaluating the performance of Long Short-Term Memory (LSTM) Networks for rainfall–runoff modelling in large catchments
Authors: Espitia Edgar , Heidari Fatemeh , Lin Qing , Vischer Marc , Xoplaki Elena
Published: June 2022

The problem of hydrologic modelling in large catchments has been addressed by conceptual physical-based models. Deep machine learning techniques such as Long Short-Term Memory (LSTM) networks have also proven to be effective for rainfall-runoff modelling. This is a promising approach to include a diversity of inputs to capture complex processes without handling the entire complexity, cost and difficulty that represent to include in conventional models. However, LSTM has not been extensively tested on large catchments and for seasonal forecasts in countries such as Germany. When a large catchment needs to be modelled, several questions arise, such as whether the performance of LSTM is suitable for rainfall-runoff without human intervention, to what extent we can rely on these results and whether the involved physical processes are appropriately represented also at higher spatial resolutions? The proposed study addresses these questions by developing a framework that employs daily meteorological observations and ancillary geographical information. First, by training a single LSTM to generate surface runoff in the study area. Secondly, to assess model performance, LISFLOOD is used as a benchmark spatially distributed semi-physical rainfall-runoff model. Finally, the performance of the model is evaluated against the Nash-Sutcliffe (NSE) and Kling-Gupta (KGE) efficiency criteria. The framework is illustrated using the Weser River Basin in Germany with a spatial resolution of 1 km and a daily time step. The proposed framework is expected to outperform calibrated physical-based models, to be suitable for seasonal forecasting, and to provide information for understanding the capabilities and limitations of the physics-based models and how the machine learning techniques take into account or are enforced to follow the physical laws.
Statistical downscaling of the 2m temperature with a generative adversarial network (GAN)
Authors: Langguth Michael , Gong Bing , Ji Yan , Mozaffari Amirpasha , Schultz Martin G.
Published: June 2022

Despite continuous improvements in numerical atmospheric models and the ever-growing computational resources, global weather forecast and climate models still operate with grid spacings between 10 and 50 km. While a further increase in spatial resolution is computationally expensive and introduces new challenges in the design of these models (e.g. gray-zone parameterizations), statistical downscaling models can overcome the mentioned issues. Inspired by the success of super-resolution applications in computer vision, deep neural networks have recently been recognized as an appealing approach for statistical downscaling of meteorological fields.

In this study, we apply a generative adversarial network (GAN) to downscale the 2m temperature over Central Europe where complex terrain introduces a high degree of spatial variability. GANs are considered superior to purely convolutional networks since the model is encouraged to generate data whose statistical properties are similar to real data. Here, the generator consists of an u-shaped encoder-decoder network which is capable of extracting features on various spatial scales. Instead of pursuing a pure super-resolution approach where coarsened data is mapped back to high resolution data, we choose a more realistic, but also more challenging test suite. Coarsened ERA5 reanalysis data, originally provided on a 0.3°-grid, is used to downscale the 2m temperature onto a 0.1°-grid with the help of short-range forecasts from the operational Integrated Forecasting System (IFS) model. Thus, our GAN model does not only have to reconstruct finer spatial features, but must also correct for model biases. 
The downscaled 2m temperature is evaluated in terms of several evaluation metrics measuring the error on grid point-level as well as the quality in terms of spatial variability and the produced probability function. We also investigate the importance of static and dynamic predictors such as the surface elevation and the temperature on different pressure levels, respectively. Our results motivate further development of deep neural networks for statistical downscaling of meteorological fields. This includes downscaling of other, inherently uncertain variables such as precipitation, operations on spatial resolutions at kilometer-scale and ultimately targets an operational application on output data from global NWP models.
Multi-decadal convection-permitting climate simulation over Svalbard and its benefit for assessing the future of cultural heritage sites
Authors: Landgren Oskar , Lutz Julia , Dobler Andreas , Isaksen Ketil
Published: June 2022

The High Arctic archipelago of Svalbard is one of the fastest-warming locations on the planet. In addition to melting snow and ice which threatens a vulnerable ecosystem, thawing permafrost destabilises slopes, coastlines and man-made structures and exposes especially cultural heritage objects. Preserving the numerous cultural heritage objects is challenging because on Svalbard they receive protected status automatically if they are older than 1946. In the PCCH-Arctic project, we study the influence of climate change on cultural heritage sites, including among others the wooden houses in Ny-Ålesund and the coal cableway in Longyearbyen. To gain meaningful climate information on specific sites we apply a high-resolution regional climate model.
Traditionally, these high-resolution convection-permitting datasets have been produced in separate time windows for historical and future periods. However, some cryospheric phenomena such as permafrost and glaciers require longer transient simulations.
We here present a high-resolution climate projection dataset covering Svalbard for the years 1991-2060 at 2.5 km horizontal resolution. The simulation is produced by the regional climate model HARMONIE Climate (HCLIM) cycle 43 featuring convection-permitting HARMONIE-AROME atmospheric physics and SURFEX land-surface model with ISBA Explicit Snow snow scheme and Simple Ice (SICE) prognostic sea ice thickness. Boundary data comes from the Norwegian Earth System model (NorESM2-MM) following the SSP5-8.5 scenario. We present projected future changes in distributions, focusing on precipitation and snow, and evaluate against ERA5 and CARRA reanalyses. We also discuss spatial variability and representation of small-scale features in a challenging landscape with steep topography and large contrasts between land, sea-ice and open ocean.
Relationships between extra-tropical cyclone intensity measures
Authors: Cornér Joona , Bouvier Clément , Sinclair Victoria
Published: June 2022

Extra-Tropical Cyclones (ETC) cause the most variability in weather and a significant portion of total insured losses in Europe. Their impacts are caused by high wind speeds, heavy precipitation and large ocean waves. The intensity of ETCs can be quantified with multiple different measures such as Mean Sea Level Pressure (MSLP), relative vorticity or storm severity indices. Currently, it is not known how the various measures of ETC intensity relate to each other. The aim of this study is to determine relationships between different intensity measures, their dependence on geographical region, and on the structure and evolution of the ETCs.

ERA5 reanalysis data from 1979 to 2021 was used to study the relationships. The analysis was restricted to the cold season (from October to March) which is when the strongest ETCs most often occur. ETCs were tracked using feature tracking software TRACK with values of 850-hPa relative vorticity every three hours as input. To focus on the most relevant ETCs affecting Europe, only tracks in the North Atlantic were chosen and stationary and short-lived systems were excluded. The intensity measures were calculated by combining the ETC tracks with parameters from ERA5 reanalysis. The intensity measures analysed include the maximum 850-hPa relative vorticity, minimum MSLP, maximum wind gusts, and a storm severity index which is based on extreme 10-metre winds and their occurrence probability. Relationships between different intensity measures were analysed for land and sea areas separately using mutual information and density heatmaps. 
 
The initial results shows that there is a correlation between maximum 850-hPa vorticity and minimum MSLP, and that this correlation is stronger over sea than land areas. However, this relationship is non-linear, with considerable spread associated with it. Additional results concerning the other measures of intensity will also be presented.
The soil warming in the Icelandic highlands
Authors: Petersen Gudrun Nina
Published: June 2022

With increasing air temperature in a warming climate the soil temperature also increases. Such changes impact flora, fauna and natural hazards. Thus, it is important to monitor soil temperature. In Iceland, the highland station Hveravellir has the longest reliable time series of soil temperature. The station is located in a barren landscape at 641 m a.s.l., but the site itself is grass covered. Soil temperature has been measured there since 1965 at 10, 20, 50 and 100 cm depth but the data is not fully digitized. Here, the time series used span 42 years, from 1977 to 2019. Annual and seasonal trends are calculated as well as the annual number of thawing degree days (TDD) and freezing degree days (FDD). During this period, there has been a considerable warming in Iceland, not only because of global warming but also because of its start coinciding with the end of a local cold period. In the soil, warming is detected in all seasons except May to June, which is the melting season, the end of which varies greatly from year to year. The most warming is found during the autumn and winter months. These results contrast with those from continental cool sites where the largest warming has been seen in the spring months. The autumn cooling starts 2–3 weeks later now than at the start of the time series, resulting in a longer summer in the soil. The number of TDD has increased and the number of FDD has decreased, both in air and in soil. At 100 cm depth TDD has increased by 80°C day dec −1 and FDD decreased by 38°C day dec −1. There is a correlation between the increase in air temperature and soil temperature, for every 1°C increase in 2 m temperature the soil temperature at 100 cm has increased by 0.6°C. The implication of this warming is firstly seen in terms of flora, fauna and agriculture, by the lengthening of the growing season, and secondly in terms of natural hazard, by increased risk of landslides due to thawing of permafrost in montainous regions.
Snow depth, relative humidity, and total cloud cover for Poland based on downscaled EuroCORDEX ensemble.
Authors: Jefimow Maciej , Strużewska Joanna , Kłeczek Maria , Sattari Anahita , Norowski Aleksander
Published: June 2022

In the frame of the project “Adaption strategies to Climate Change in Poland” the projections of snow depth, relative humidity, and total cloud cover were developed based on the EURO-CORDEX. The RCM results for an area covering central Europe with a resolution of 0.11 ° (approx. 12.5 km) were used. The analyses were carried out for the RCP 4.5 and RCP 8.5 scenarios.

To represent better the local variability the statistical correction (quantile mapping) was applied based on various historical gridded datasets (ERA5- reanalysis and IMWM- observation data from the National Meteorology Institute, for the snow depth and relative humidity, and ERA5 and EUMESAT- satellite data for total cloud cover). Ensemble analyses were undertaken to assess the projection uncertainty. For the snow cover and humidity, eleven ensemble members were used, while for the cloud cover there were fourteen models for RCP4.5 and 26 models for RCP8.5.

We will present ensemble spread analysis and RMSE for the reference period to show the credibility of climate projections. In terms of the predicted tendency in both scenarios, in the analyzed domain, snow depth in the future climate shows a downward trend, with a more visible dynamic in scenario RCP 8.5 up to 50% in terms of the number of days with snow cover by the end of XXI. In the case of relative humidity and total cloud cover, stable trends are visible, with no clear change. Also, we will address the changes in the seasonal pattern of the analyzed parameters.

 

Project results are available via the interactive portal: https://klimada2.ios.gov.pl/klimat-scenariusze-portal/

 
Radiation and cloud parametrisation in ICON on local to global scales
Authors: Schäfer Sophia , Köhler Martin , Hogan Robin , Ahlgrimm Maike , Rieger Daniel , Schlemmer Linda , Sakradzija Mirjana , Mol Wouter , van Heerwarden Chiel , Jakub Fabian
Published: June 2022

Radiation in the atmosphere provides the energy that drives atmospheric dynamics and physics on all scales, from cloud particle growth to global weather and climate. Radiation schemes in global weather and climate models make assumptions to simplify the complex interaction of radiation with the Earth system. Capturing cloud-radiation interactions is particularly challenging since clouds vary strongly on small spatial and temporal scales not resolved in the models, and interact strongly with radiation. Uncertainties in these assumptions in the radiation scheme and the cloud, aerosol, gas and surface inputs lead to uncertainties in multiple weather and climate processes, such as energy balance, cloud development and dynamics.

 

The modular radiation scheme ecRad (Hogan and Bozzo, 2018, Rieger et al. 2019) is operational in ICON at DWD since April 2021 and provides the opportunity to vary parametrisations and assumptions individually to determine their impact. Several options are available for the radiation solver, cloud vertical overlap and horizontal inhomogeneity treatment and cloud hydrometeor optical property parametrisations. The solver SPARTACUS is the only radiation solver in a global model that can treat 3D radiative effects.

 

Using global satellite and surface data and high-resolution surface radiation measurements gathered during the FESSTVaL campaign (https://fesstval.de), we evaluate the radiation and cloud parametrisations on local to global scales and investigate the sensitivity of radiation results to model assumptions and cloud properties and the role of cloud-radiation interactions. In ICON, ecRad improves the global radiation balance, model physics and forecast performance as evaluated against observations.

References: 

Hogan, R. J., & Bozzo, A. (2018), A flexible and efficient radiation scheme for the ECMWF model. Journal of Advances in Modeling Earth Systems, 10, 1990-2008. https://doi.org/10.1029/2018MS001364

Rieger, Daniel, Martin Köhler, Robin J. Hogan, Sophia A. K. Schäfer, Axel Seifert, Alberto de Lozar and Günther Zängl (2019). ecRad in ICON - Implementation Overview, Reports on ICON
Validation of the New Version of the WindCube Scan Lidar
Authors: Benzo Cristina , Thobois Ludovic
Published: June 2022

For many applications, such as ensuring efficiency of future wind farms and characterizing wind hazards at ports, airports, or industrial plants, measuring accurate and precise wind is critical. Scanning Wind Lidars provide a solution to deliver demanding wind measurements, measuring in full hemisphere at multiple ranges around its location with multiple scanning patterns (azimuthal scans, elevation scans, etc.). Since their implementation, user feedbacks called for more flexibility in measurement modes, limitation of range ambiguities, and longer acquisition distances. For these reasons, a new version of the Windcube Scan was designed to overcome these limitations. An internal and external validation was performed over the last year to ensure acceptable behaviors and measurement performances of hardware/software components of outdoor/indoor measurements for established regulations.

The internal validation conducted within Vaisala France site near Paris consists of both an indoor and outdoor validation protocol. The indoor verification test, characterized as a patented indoor bench, aims at testing radial wind speed precision with intrinsic lidar parameters such as pulse shape, energy, etc. The outdoor validation follows guidelines set by the ISO 28902-2 as the lidar wind speed was compared to an ultrasonic anemometer on a meteorological tower 2.5km away. The instantaneous wind speed measurements from both devices are then compared for precision and accuracy with proper filtering of unsuitable weather conditions.  

External validation prompted collaboration with MeteoSwiss and DWD, both pioneers in the PROBE European project for large-scale remote-sensing deployment and data-sharing. Both organizations received the new version of WindCube Scan for a beta test. They gathered wind data at their sites and compared radial data to other remote sensing devices. All scanning patterns (PPI, RHI, DBS, VAD, fixed) were tested to verify the performances of different resolutions, data retrieval, and wind speed precision.

The results of this validation thus far show positive performance and noticeable improvements of the new version of the Windcube Scan. Additionally, the external validation collaboration with other PROBE members highlights the importance of fortifying and understanding remote sensing device precision and data collection methods for large-scale observational network integration.
On the crossing-point forecast
Authors: Ben Bouallegue Zied
Published: June 2022

The crossing-point forecast (CPF) is a new concept in the field of probabilistic forecasting. A CPF is defined by the intersection between a forecast cumulative distribution and the corresponding climatology distribution. Focusing on this intersection point, a probabilistic forecast is summarized into a single number conveying information about a "probabilistic worst-case scenario" with respect to climatology. Is the predicted chance of suffering a loss, due to the occurrence of an (exceedance) event, higher than that event’s climatological frequency? The crossing-point forecast indicates the limit case for which the answer is positive.

The outcome corresponding to a CPF, called “crossing-point observation”, is directly related to the return period of the event that materializes. A simple error function that applies to the forecast and observed crossing-points is formulated. The resulting score is closely related to the diagonal score: it is proper and equitable which makes its application appealing for the comparison of competing forecasts. The proposed scoring function is consistent for the crossing-point forecast in a similar way as the root mean squared error is consistent for the distributional mean forecast or the mean absolute error is consistent for the 50%-quantile forecast.

In weather forecasting, the information provided by CPF could be highly relevant for vulnerable users and more generally for users with interest for high-impact events. We propose here a comparison with the Extreme Forecast Index (EFI) using the ensemble forecast of the Integrated Forecasting System run at ECMWF and the corresponding model climatology. The EFI is designed to provide forecasters with general initial guidance on potential extreme weather events. Both EFI and CPF are derived using the same ingredients which makes their comparison particularly relevant. Based on case studies and verification metrics, we illustrate the complementarity of the two types of forecasts.
Empirical-Statistical downscaling with EPISODES – status and current developments
Authors: Lorenz Philip , Schellander-Gorgas Theresa , Hoff Amelie , Kreienkamp Frank
Published: June 2022

Empirical-statistical downscaling (ESD) methods are sparing regarding computational costs compared to dynamical downscaling models. Due to this advantage ESD can be applied in a short time frame and in a demand-based manner. It enables, e.g., the creation of ensembles of downscaled climate projections, which can be assessed either as stand-alone data set or to enhance ensembles based on dynamical methods. This helps improve the robustness of climatological statements for the purpose of climate impact research.

EPISODES is an ESD method for the regionalisation of output of general circulation models (GSMs). The initial development of EPISODES has been done at Deutscher Wetterdienst (DWD) for the area of Germany. Results of EPISODES results of CMIP5 projections are available for public download at the Earth System Grid Federation (ESGF). In the meantime, EPISODES has been extended for the downscaling of climate predictions on different timescales (decadal, seasonal, sub-seasonal) to meet the needs of climate data users for high spatial resolution datasets. Furthermore, is has been applied to a number of CMIP6 global projections.

In co-operation with the Zentralanstalt für Meteorologie und Geodynamik (ZAMG) EPISODES is currently further developed and adjusted for handling besides the German area also the Alpine region. In addition to the interest of ZAMG to carry out downscaling with EPISODES for Austria, the complete coverage of the catchment areas of the Rhine, Elbe and Danube is a common interest of this cooperation.

The presentation will give an overview of the current status of EPISODES, show results, and provide an insight into recent developments.
A L1 transformational operator for the objective evaluation of the EarthCARE Cloud Profiling Radar data products
Authors: Pfitzenmaier Lukas , Kollias Pavlos , Puigdomènech Bernat , Lamer Katja , Battaglia Alessandro , Löhnert Ulrich
Published: June 2022

The value of permanent, multi-sensor surface-based observatories that collect continuous long-term observations for satellite L2 data products has grown significantly the last 10-15 years.  Examples of such established surface-based networks include: The Aerosol, Clouds and Trace Gases Research Infrastructure (ACTRIS) network, the US Department of Energy Atmospheric Radiation Measurements (ARM) observatories and the recently established 94-GHz Miniature Network for EarthCARE Reference Measurements (FRM4Radar). At the same time, there is a significant increase in the availability of airborne platforms (e.g., DLR Halo, French Falcon and the NASA airborne program) with comprehensive instrument payloads that mimic the satellite primary measurements.

Here, a simple L1 transformational operator that can convert L1 suborbital (surface-based or airborne) measurements to the EarthCARE CPR L1 observations is described. The L1 transformational operator ensures that the orbital-suborbital comparison accounts for differences in the sampling geometry, measurement uncertainty, and instrument sensitivity. Furthermore, the operator account for the impact of the surface echo on satellite-based radar observations. Examples of the application of the operator on surface-based observations measurement from the ESA FMR4Radar network are presented. Such long-time data sets are the optimal foundation for a statistical analysis of the CPR performance. The analysis will emphasis on clouds and precipitation processes near ground. In addition, it is show how important ground-based networks are that they can play an important role in the evaluation of future CPR satellite missions. The L1 transformational operator can be easily expanded other spaceborne radar systems. Our plans include the application of the L1 transformation operator to high resolution cloud resolving model output.
Dynamic Vulnerability of built infrastructure - How previous storm events effect the damage of residential buildings in Germany.
Authors: Trojand Andreas , Rust Henning , Ulbrich Uwe
Published: June 2022

Severe storm events are one of the most damaging natural hazards in Central Europe and thereby under special focus in disaster risk management. One key element of risk reduction is the vulnerability. While in risk assessments vulnerability is often assumed as constant, in reality different drivers lead to dynamic developments. To take the step from constant to dynamic vulnerability a detailed understanding of the processes and impacts of these influences is necessary. One crucial driver on vulnerability is the hazard itself. In theory vulnerability is likely to increase immediately after an event (De Reiter et al. 2020), whereas on long term the mean vulnerability decreases due to improved reconstruction (UNISDR, 2018).

In this study we quantify the effects of storm events on the dynamics of vulnerability, with a focus on the impact of the intensity of previous events as well as the duration between events. In a first step vulnerability curves are derived from the relation of storm events and damage using generalized linear models. For the damage the loss ratio (loss/insured sum), extracted from a 23 yearlong data set of daily storm and hail damages for insured residential buildings in Germany on county level provided by the German Insurance Association, is used. The storm event is described by the three parameter daily maximum wind gust, duration of the storm event and gust factor, all calculated from ERA5 reanalysis. The threshold for the occurrence of an event is the exceedance of the 98th percentile of the wind gust. In the next step the generalized linear model is extended with the storm intensity of the previous event and the duration between two events as additional covariates. First results confirm the thesis of vulnerability decrease due to previous events. In further analyses, the results will be quantified in more detail and key findings of the vulnerability dynamics will be elaborated.
EC-Land Hydro: the benefits of integrating hydrology in earth system modelling
Authors: Prudhomme Christel , Arduini Gabriele , Balsamo Gianpalo , Brown Andy , Boussetta Souhail , Cloke Hannah , de Rosnay patricia , Harrigan Shaun , Mazzetti Cinzia , Pappenberger Florian , Sandu Irina , zsoter Ervin
Published: June 2022

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.
Validation, Evaluation, and Localization of Climate Change Signal – The Use of IS-ENES3 Analysis Platform Initiative
Authors: Halenka Tomas , Holtanova Eva , Belda Michal
Published: June 2022

To analyse, assess and localize the climate change signal for climate change impact assessment including the analysis of the uncertainty is demanding task especially with respect to the amount of data necessary. Indeed, when trying to get more detailed and reliable information with uncertainty assessment for specific localized region full spread of available data might be of importance, i.e. global ensemble of GCMs simulations (for several scenarios, i.e. CMIP results) on one side, and regional downscaling simulations for some of the GCMs on the other side. It is really hard to download all the data locally, to select necessary variables you need at you region of interest and to make all the analyses you require to support your impact study. Well, there are some options for data selection on servers side, however, some tools are available today to make all the analysis remotely on the data side, i.e. directly on the HPC computers next to the data archives. This is what the initiative of EC Horizon2020 project IS-ENES3 called Analysis Platform, which is provided for free on the basis os some kind „internal“ projects, of course not funded, but allocating the resources for an applicants use.

In the contribution, we will present the potential of this new paradigm in processing and analysing data when studying results of CMIP6 and CMIP5 comparison for the region of Central Europe, together with the comparison to EuroCORDEX 0.11 simulations, with the validation against local observational data. This data are further used to localize the information into the scale of modelling study in the framework of local project PERUN, where CP simulations are in progress.