bluuebunny/crossref_metadata_2025 huggingface dataset:
Exploiting regional reanalysis data for assessing long-term trends of the human thermal bioclimate in Greece
Authors: Agathangelidis Ilias , Giannaros Christos , Galanaki Elissavet , Cartalis Constantinos , Kotroni Vassiliki , Lagouvardos Konstantinos , Matzarakis Andreas
Published: July 2023

The comprehensive assessment of the human bioclimate requires considering the four principal meteorological variables that affect the thermal environment (i.e. temperature, humidity, wind speed and global solar radiation). It also requires using data at spatial scales that are relevant to the population exposure. Meeting these requirements with the use of ground-based weather stations is usually unattainable at nation-wide level. This is partially due to the incomplete spatiotemporal availability of the relevant observational data (especially of global solar radiation), as well as to the fact that the monitoring stations are often present in locations (e.g. airports) that are not representative of the human-biometeorological conditions. Gridded climate data can be used to overcome the above issues. In view of this fact, here, we exploit regional reanalysis data to perform a long-term (1991-2020) analysis of the human thermal bioclimate and its trends in Greece. To this end, the Copernicus European Regional Reanalysis (CERRA) dataset, at 5.5 km spatial resolution, is used. The CERRA dataset is combined with population data to better reflect the thermal environment experienced by the people through a population-weighted approach at regional units or combinations thereof that are based on the NUTS-3 (Nomenclature of Territorial Units for Statistics-3) classification. The population data are further used to assess the thermal-related risk in terms of annual number of exposure person-days, focusing on bioclimatic extremes. The latter are expressed by an advanced human-biometeorological index, namely the modified physiologically equivalent temperature (mPET), which is computed with the use of the RayMan Pro model. Short-term acclimatization effects are considered for mPET by adjusting the extremes’ thresholds through the application of a 30-day Gaussian filter. The present work is performed in the frame of the HEAT-ALARM project and provides preliminary results of the above described analysis, highlighting that regional reanalysis data can be valuable for climate assessments in the context of human-biometeorology, especially when combined with the consideration of population exposure aspects.
An improved E-OBS pan-European gridded data set for global radiation
Authors: de Baar Jouke , van der Schrier Gerard , Knap Wouter , van den Besselaar Else
Published: July 2023

Question. Currently, we already provide an E-OBS pan-European gridded data set for global radiation. However, improvements might be made in the reliability of the estimate in areas with a low network density, in the effective spatial resolution as well as in the reliability of the ensemble dispersion. In this work, we use lessons learnt from earlier work (Frei et al, IJC, 2015) and the E-OBS wind grid, and apply them to the radiation grid, in order to see if we can achieve these improvements. 
Approach. Our approach is to use aggregated regression kriging. First, we use linear regression to fit a monthly background field of the observed global radiation as a function of several covariates. In order to allow for the inclusion of multiple covariates, yet avoid over-fitting, we use forward selection linear regression to construct the monthly background field. Apart from covariates like longitude, latitude, distance to coast and altitude, we include monthly-varying PCA modes of reanalysis-based radiation patterns. Then, we use kriging to regress the daily anomalies with respect to the monthly background field. 
In order to provide the gridded data set as an ensemble of 20 members, we run a 20-fold bootstrapping loop over the entire gridding procedure. Because this still leads to an underestimation of the grid uncertainty – or ensemble dispersion – we apply ensemble dispersion improvement auto-tune (EDIT) as an ensemble post-processing step. 
Results. We provide a gridded data set of daily global radiation at a resolution of 0.1x0.1 and 0.25x0.25 degrees longitude and latitude. The standard data set consists of ensemble mean and ensemble inter-quantile range, however, the full ensemble can be made available upon request. A comparison against the available EUMETSAT satellite data will be made. The data set will be provided for the period 1950-present, with monthly updates, and will be available for download from the E-OBS website. 
Understanding the variability of 7Be surface concentrations in Europe: the role of teleconnection patterns
Authors: Hernández-Ceballos Miguel Ángel , Ajtić Jelena , Brattich Erika
Published: July 2023

The temporal and spatial variability of atmospheric compounds and pollutants is largely driven by a combination of local, mesoscale and synoptic meteorological conditions influencing atmospheric processes, such as horizontal and vertical dispersion, deposition, chemical reactions rates and velocity. At the same time, different anthropogenic and natural radionuclides have long been used as tracers to understand and describe surface and atmospheric processes and their influence on transport and deposition. Among these substances, 7Be, a cosmogenic radionuclide produced by  spallation reactions in the stratosphere and upper troposphere, is frequently used as tracer of different atmospheric processes. Many studies have reported how the variability of 7Be surface concentration is driven by the movement of air masses, atmospheric deposition processes, tropospheric vertical mixing, and the vertical exchange between the stratosphere and the troposphere. 
With an aim to elucidate the influence of teleconnection and tropospheric circulation dynamics, several studies have investigated the influence of the main modes of large scale and regional climate variability in Europe, such as North Atlantic Oscillation (NAO), Arctic Oscillation (AO), East Atlantic (EA), East Atlantic/Western Russia (EA/WR), Scandinavian pattern (SCAND), and Western Mediterranean Oscillation (WeMO) on the surface 7Be activity concentrations. This paper, in particular, presents a summary of recent results achieved by our team working on this topic, focusing firstly at the European scale and then to northern Europe. 
Analysing 7Be surface concentrations measured at 15 European sampling stations over 2005–2014 and combining the calculation of air mass trajectories and cluster analysis with time series of teleconnection indices, we found that extremely high values of the 7Be surface concentrations are largely connected with the negative phase of NAO and We-MO, and with the positive EA phase. These results showed a latitudinal division between the northern and southern sites, with a similar influence of teleconnection patterns, while the sites located in the central part of Europe present a larger variability in the impact of teleconnection patterns. A detailed analysis in northern Europe revealed that extreme 7Be surface concentrations observed during winter were associated with variability of the Arctic polar vortex and linked with high values of the SCAND index.
The findings provide a classification of meteorological conditions associated with high surface 7Be concentrations and thus offer a basis for forecasting these events. In a general view, the findings also help in understanding the seasonal and inter-annual atmospheric variability at different scales and its impact on airborne concentrations of radionuclides and pollutants.
Snow Loads in Norway, 1961-202
Authors: Tilley Tajet Helga Therese , Grinde Lars , Hygen Hans Olav
Published: July 2023

Snow loads are an important consideration in the design of buildings. Particularly in parts of Norway where heavy snowfall is common, it is important to know the weight from snow on houses to avoid structural damage or collapse. National standards and building regulations have been focusing on snow loads since 1949, and these regulations have been revised several times. 
 
The Norwegian Meteorological Institute (MET Norway) produces daily interpolated data sets of precipitation and temperature with a 1*1 km resolution as part of our regular service. Data from 1957 - dd are included. These data sets are then used by the Norwegian Water Resources and Energy Directorate (NVE) to generate "Snow Water Equivalent" (SWE) interpolated data sets, grids, using a hydrological model. 
 
In this study, the SWE grids are  used to produce snow loads with a 50 year return period for Norway, for two different periods 1961-1990 and 1991-2020. Three different methods for calculating the 50-year return period of snow loads are compared. In addition, the old normal period, 1961-1990, is compared with the current normal period, 1991-2020. It is typically shown that the snow load decreases in the lower-lying areas and along the coast of Norway. In higher altitude areas and in parts of Northern Norway, where there still are cold winters, the snow loads have increased. 
 
Snow loads are also extracted for each municipality center in Norway, to compare to the current national snow loads standard. This method is suggested, and about to be adopted, for future use in the design of buildings in Norway.
Impact of Climate Change on solar resource: a review of projections, uncertainties and perspectives
Authors: Gutiérrez Claudia , Somot Samuel , Álvarez-García Francisco José , Cabos William
Published: July 2023

The increase in global deployment of PV technology and the estimation of its continuous growth for the near future requires an accurate solar resource assessment for the industry and the different stakeholders. While historically that assesment  was made with satellite or in-situ observations,  studies using climate models have shown that climate projections are necessary to account for climate variability in the near or mid-future. In recent years,  many studies have been conducted analyzing climate projections of solar resource, utilizing either global and/or regional climate models, considering different time horizons and emission scenarios worldwide. Some studies have used a single regional climate model for a specific area, while others have adopted a multi-model approach, incorporating simulations from coordinated experiments like Coupled Model Intercomparison Project (CMIP) for globals or Coordinated Regional Downscalling Experiment (CORDEX) for regionals. In certain cases, disparities between global and regional model projections have been identified, with corresponding analyses published.
The objective of this study is to conduct a comprehensive review of solar resource projections worldwide. The analysis will be based on six distinct regions, and the results will summarize the projected changes in solar resource and the underlying reasons. Additionally, the agreement or discrepancy between global and regional models, as well as the main sources of uncertainty reported in the literature for each region, will be examined. This work aims to synthesize the most up-to-date knowledge on solar resource assessment using climate models , in order to help the public sector and industrial experts working to incorporate climate impacts into energy sector decision-making processes around the world.
Extreme events in the Czech Republic: Recent development and projection
Authors: Valeriánová Anna , Crhová Lenka
Published: July 2023

It is critical for decision makers to be aware of the projections of the extreme weather phenomena in future when preparing policies for adaptation and risk management.
This topic has been addressed by the project “ Prediction, Evaluation and Research for Understanding National sensitivity and impacts of drought and climate change for Czechia“  where we estimated risks of hydrometeorological phenomena and their expected changes during the 21st century.
For the territory of the Czech Republic we identified as the main risks the following phenomena related to the extremes weather: heat wave, cold wave, extreme wind, extreme precipitation (torrential and permanent), drought and the subsequent risks e.g. firerisk, severe thunderstorm and subsequent risks. In our contribution, we focused on assessment of the changes in the occurrence of heat waves and extreme wind.
To quantify changes in occurrence of heat waves the indices related to weather alerts were defined and their changes were evaluated for the period with station observations. The threshold for indices corresponds to the alerts of high level of danger for CZ. These limits were chosen with respect to impact of extreme meteorological phenomena on society and environment. The number of days with maximum temperature above 34,0 °C and days with minimum temperature above 20,0 °C have been evaluated and on top of the number of days with maximum (minimum) temperature above these thresholds we studied the length and intensity of heat waves.
When studying changes in the occurrence of extreme wind speed the threshold for the maximum wind speed 17,2 m/s has been used in accordance with International Meteorological Vocabulary, WMO-No. 182.
We evaluated the changes in frequency of extreme phenomena between the periods 1961–1990 and 1991–2020 and studied the trend. On the basis the regional climate model data we estimated the projection of occurrence of studied extreme phenomena.
Weather Sensitivity Surveys in Germany
Authors: Matzarakis Andreas , Graw Kathrin
Published: July 2023

Weather sensitivity describes reactions of the human body related to the current weather and especially to changes in weather. A clear scientific  definition of weather sensitivity does not exist. Positive impacts, as well as effects on mood, are rarely mentioned. Weather sensitivity occurs mainly in temperate latitudes or climates, as this is also where most rapid changes in weather conditions occur or are present. Scientifically based data on the prevalence of weather-associated complaints and symptoms as well as impairment of well-being have been obtained from population surveys on weather sensitivity in Germany since the 1950s. This analysis focuses on the findings from the representative population survey of 2021 and relates the results to the surveys of 2013 and 2001. The “Institut für Demoskopie Allensbach”, on behalf of the German Meteorological Service, interviewed a representative sample of 1080 German citizens. Based on respondents’ self-assessment, the proportion of individuals who said the weather had an impact on their health was 46% in 2021, compared to 50% in 2013 and 54% in 2001. Elderly and chronically ill individuals are more likely to suffer from weather sensitivity than the average population. Women are more affected than men. The most common complaints of weather sensitivity are headaches/migraines, exhaustion/general fatigue, limited activities, and abnormal fatigue. The decrease in the proportion of weather-sensitive humans may be related to greater health awareness and improved health care. Preventive measures, such as going outdoors and dosed exposure of the body to different weather, as well as avoiding other stresses, can train the body’s ability to regulate itself and help  to make it less susceptible to weather sensitivity.
Compound hydrometeorologic extremes in Northern Europe: a case study on flooding and drought in Denmark
Authors: Newell Matthew , Drews Martin , Payne Mark , Larsen Morten
Published: July 2023

Climate projections indicate a general increase in precipitation in Northern Europe accompanied by an increase in variability across a range of hydroclimate variables. In Denmark, increases in the amount of winter precipitation have resulted in several winter seasons (e.g., 2019-2020 and 2022-2023) with above-average precipitation. As a result, these periods have been marked by a vast extent of surface flooding due to the successive nature of precipitation events. Recent occurrences of drought (2018 and 2022) in Denmark, which have historically been less of a concern, have reduced water availability and resulted in impacts across sectors, with particularly large impacts on agricultural systems. The intra- and/or inter-annual occurrence of wintertime compound precipitation events and summertime flash drought events may emerge as an important constraint on agricultural productivity in Denmark. This analysis uses the Standardized Antecedent Precipitation-Evapotranspiration Index (SAPEI) to quantify periods of excess rainfall and precipitation deficits. The SAPEI can capture both periods of excess soil moisture (due to preconditioning by successive storms) and soil moisture deficits since it serves as a proxy for soil moisture. In the study, SAPEI is applied to observational records and climate projections to assess changes in the frequency of hydrometeorologic events, and to localize areas, which are specifically at risk to these extremes under current and future climates. Recent events are highlighted within the context of natural climate variability. These events are detailed to illuminate the impacts of compound wet and dry events and illustrate their importance as an important compound event in need of further research. 
ProPower: Evaluating the impact of weather forecast uncertainty in power systems management
Authors: Bents Hauke , von Bremen Lueder , Schyska Bruno , Buller Clara
Published: July 2023

Objective and Background
Probabilistic forecasts have been promoted by meteorologists for years. However, the use of probabilistic forecasts in the energy sector is still limited. One reason for that is that many real-world decision processes and applications to manage the power system are not designed to integrate uncertain information.
The objective of this presentation is to introduce ProPower, the Probabilistic Power Forecast Evaluation Tool developed at DLR. The main purpose of ProPower is to assess the value of probabilistic power forecasts for PV and wind power systems compared to the usage of deterministic forecasts that do not contain any uncertainty information. Different sources of probabilistic forecasts may be ranked and tested. Finally, a robust analysis on how the value of wind and solar forecasts depends on the power system infrastructure and the power markets considered will be conducted.
Method
Usual approaches to derive the cost-optimal power dispatch within a market region and where power constraints (e.g. grid capacities) are fully considered do not account for the potential balancing costs arising from forecast errors in wind and solar. Dispatch decisions based on pure deterministic forecasts lead to sub-optimal market clearing as shown by Morales et al. [2014] for a simplistic network. To overcome this issue they proposed a stochastic market clearing model. In this model, average balancing costs are estimated from a set of scenarios of renewables feed-in that are equivalent to ensemble members from an ensemble prediction system. The ProPower tool is capable of simulating more complex power systems being mainly restricted by the computational expenses of the optimization problem. A second market clearing based on updated forecasts of higher skills has been implemented and tested. Currently, we use ECMWF ensemble forecasts [Leutbecher and Palmer, 2007] for the day-ahead market clearing and the intraday market clearing. The amount of required balancing is determined by the deviation of forecasted renewables feed-in to feed-in computed from ERA5 reanalysis.
Principal Findings
We found that stochastic market clearing reduces total power system cost by saving balancing power compared to the conventional market clearing even for more complex networks. Furthermore, the use of forecast updates in an intraday market is beneficial as extreme day-ahead forecasts errors do not need to be balanced with more expensive balancing energy at the time of power delivery.
Conclusion
The ProPower tool is capable to translate probabilistic forecast skill into benefits for the power system respecting important characteristics of the real-world power system (i.e. network constraints and layouts, varying costs for different producers, flexibility options). ProPower has the potential to analyze which forecasts errors are most expensive to balance and how valuable skillful uncertainty information from different sources is.
The SIHROCO project: Offshore wind and wave energy in the Spanish coasts. Are offshore hybrid platforms the future of energy?
Authors: Vázquez Rubén , Gutiérrez Claudia , Román-Cascón Carlos , Cabos William
Published: July 2023

In recent decades, the pressing need for energy, the depletion non-renewable energy sources, and the rise in greenhouse gas emissions into the atmosphere make it increasingly essential to advance new renewable energy technologies (or improve existing ones). In this regard, to advance more effective technologies, it is necessary to understand the state of resources and evaluate where new energy converters should evolve in the context of climate change. Offshore renewable hybrid projects are expected to grow in the next few years due to the commitment of the EU towards a net-zero carbon energy system. Spain are encouraging the development of new renewable energy technologies, particularly offshore resources. In the case of Spain, these plans include a 74% renewables share by 2030 and a 100% renewable power system by 2050.  The SIHROCO* project aims to generate useful information on which are the regions with the greatest energy potential offshore, based on hybrid platforms. In this work, we assess the state of the wind and wave energy resources for the Spanish coasts using the ERA5 reanalysis. Additionally, we aim to evaluate the complementarity of both resources to identify regions with the greatest energy potential. Locations with complementarity indices were identified by considering a particular offshore wind turbine power curve and the power matrix of the wave Dragon energy converter. In a first approach, we found the regions with the highest wind and wave energy resources to be located in the north of the Iberian Peninsula and the Canary Islands. Conversely, regions such as the Balearic Islands or the southeast coast of the Iberian Peninsula have a low capacity factor for wave energy. This study is focused as a first step to help understand the spatial and temporal variability of energy resources along the Spanish coasts, paving the way for a further study on climate change using high-resolution regional coupled atmosphere-ocean models.
 
*The SIHROCO project (I+D+I PID2021-128656OB-I00 project) is a project funded by the Spanish National Research Plan.
Automatic attribution: quick and reliable evaluation for improvement in public perception of climate changes
Authors: Hisi Andreia , Faranda Davide , Vrac Mathieu
Published: July 2023

Climate change and its effects on everyday life are a global concern. A wide range of mathematical and computational studies on climate have provided a wealth of knowledge to understand the process and strategies for effective identification of key diagnostics related to weather extremes and atypical seasons. But there is still an urgent need to provide near real-time reliable information. In particular, weather extreme events and abnormal seasonal or yearly conditions are often invoked as a hallmark of climate change by the media and mass social media. However, this link between individual events and climate change is often made impulsively without verification of the underlying physical processes involved. We created a framework that performs an extreme event attribution focused on atmospheric circulation by identifying the sea level pressure patterns in their typicality in current (factual world defined as a sliding window from the day before to the day of the event, going back 30 years) and past (counterfactual world, from 1950 to 1980) climate conditions - defined using the ERA5 dataset (from slp for several variables: tas, tp, z800, etc). This new tool allows to broaden the dialogue and public perception on climate change topics through the production and provision of authentic (near) real time climate change information on a continuous basis. This will allow researchers and the general public, as well as policy makers, to access relevant results on a daily basis for further uses such as scientific research, as well as for general public knowledge creation, and other educational purposes, tweets, climate fact sheets, videos, etc.
Which prognostic minimum temperatures are most appropriate for cold wave warnings
Authors: Magjarevic Vjeran , Srnec Lidija
Published: July 2023

Since 2017, under the coordination of the Ministry of Health of the Republic of Croatia, Croatian Meteorological and Hydrological Service (DHMZ) issues Warnings on the cold that can affect health – cold wave warnings. To determine whether there is a need for issuing a cold wave warning or not, forecasters at DHMZ are comparing forecasted minimum daily air temperatures and given temperature thresholds. Those threshold values of the daily minimum air temperatures are determined empirically, based on mortality data from a 25-year period (1983 – 2008) for eight Croatian regions. There are three levels of warnings, moderate, high, and very high. The level of warning is determined four days in advance for each of the eight regions. As the minimum daily air temperature is a meteorological parameter that is daily forecasted it is suitable for regular updates of cold wave warnings.
Forecasters at DHMZ Weather Forecasting Division use various NWP products for forecasting the daily minimum temperatures. The final decision of the exact forecast value is partially subjective, depending on the experience which solely can recognize situations where some local effect strongly influences the air temperature. This research aims to validate those decisions. By grabbing into the past, we will compare the prognostic values of daily minimum temperatures from a few sources (e.g. ECMWF model, Aire Limitée Adaptation dynamique Développement InterNational (Aladin) model) for various Croatian regions with the measured values from the representative meteorological stations. The comparison will also include the final forecasted daily minimum temperatures used to determine cold wave warnings.
Although it is likely that in the (not so distant) future, due to climate change, the threshold values for the minimum daily air temperature will not be exceeded often, through this work we will try to improve the early warning system (cold wave alarm) in Croatia, as one of the most important climate change adaptation tools.
Aspects of wind power forecasting over the Finnish wind fleet considered as a single wind farm
Authors: Atlaskin Evgeny , Lindfors Anders
Published: July 2023

The share of wind energy sources in Finland was reasonably expanded over last years. It is foreseen that wind power generation will exceed 30 % of the total electricity production in Finland by 2030. The growing share of wind resources, however, brings more variability to the electricity grid raising the risk of imbalances between electricity production and consumption. The larger wind share also has stronger impact on electricity prices in Finland that are set daily at the Nordic energy trading stock Nordpool. To estimate wind power generation for coming days a probabilistic wind power forecasting system has been developed at the Finnish Meteorological Institute (FMI).
The system is based on the Meteorological Ensemble Prediction System (MEPS) HARMONIE, running operationally by the group of Nordic countries under MetCoOp cooperation project. Information on wind farms is provided by the Finnish Wind Power Association (FWPA). FWPA data essentially enables wind calculations for every Wind Turbine (WT) location. MEPS-based wind speed is interpolated to the WT hub heights at their locations and further corrected by applying a wake propagation model. The key advantages of the method are 1) the method exempts from the necessity of calculating wake interaction between adjacent wind farms, 2) wind direction variations within large-scale wind farms are considered.
The method requires both power curve and thrust coefficient (CT) curve of installed WT models for calculating respectively power and wake-related losses. Power curves for new WT models are typically not available in open databases, whereas CT curves are generally not available for most installed WT models. A statistical solution was developed at FMI to approximate both power and CT curves. The method well approximates power and CT curves of most of the models installed by 2022. New WT models of 4 MW or larger capacity are often equipped with a system that reduces power generation at wind speeds exceeding c.a. 15-18 m/s towards cut-off to prevent abrupt shutdown of the rotor. This feature of WTs was addressed in approximating both power and CT curves, with preliminary results demonstrating reasonable improvement, specifically for CT curves.
The FMI power forecasting system is somewhat struggling to properly include all new WT installations, because of the rapidly expanding installed capacity in Finland.  Correction of the forecast is done using data on actual aggregated power generation and installed capacity provided by Fingrid, the Finnish Transmission System Operator. The overall agreement between forecasted and actual wind power production is satisfactory. However, a detailed analysis reveals some seasonal and diurnal behavior, which can be approximated as a function of month, day’s hour and forecast lead time. Power losses associated with downtime and icing can be accounted for by applying short-range correction.
Coastal buoys, uses in the coastal maritime field.
Authors: Madariaga Navarro June , Ibáñez Herrera María , Maruri Machado María de las Mercedes
Published: July 2023

Waves are one of the variables that most condition coastal maritime activities. Coastal observation systems are concentrated in ports, where economic activity is centred. Recent studies assess the effects of climate change on productivity or impacts on structures and their negative repercussions on the economy. But it is not only seaports that are affected, but there are also many coastal maritime activities in the food, tourism, energy and private sectors, etcetera, whose economy is highly conditioned by the ocean-meteorology and its changes.  In the Basque Country, many towns face the sea and the highest density centres are on or near the sea.
Through the study of observations of coastal phenomena we can improve our warning systems and provide useful information for the management of coastal maritime activities.
In order to optimise and improve the safety of these workplaces, knowledge of the ocean-meteorological conditions is required to adapt the work and make it safer. Knowledge of the environment requires the implementation of observation networks, modelling of the environment and integration of existing observations. The Basque coast and beaches have a great morphological variability from west to east, making it a very attractive study area. Furthermore, land-sea interactions are complex because they are intermediate, complex areas, where very local phenomena occur, observed with different networks, administration, and competences.
The University of the Basque Country, in collaboration with the Tecnalia research centre and the Basque Government emergency and meteorology department, is planning, studying, and implementing the installation of a coastal buoy in order to obtain better information on sea conditions in an area with a high level of coastal maritime activity, in front of busy beaches and close to the perimeter of the port of Bilbao.
The collaboration between the manufacturer (Zunibal S.L.), university (UPV/EHU), research centre (TECNALIA) and Basque Government (DAEM) for the exploitation of the information and study of the time series and how to use the information in different applications, are presented in this work.
Climate Change Projections of Agricultural Droughts in Europe: A Comparison between Standardized Drought Indices
Authors: García-Valdecasas Ojeda Matilde , Rosa-Cánovas Juan José , Donaire-Montaño David , Romero-Jiménez Emilio , Castro-Díez Yolanda , Esteban Parra María Jesús , Gámiz-Fortis Sonia R.
Published: July 2023

Drought is one of the most devastating natural hazards, affecting ecosystems, communities, and their economies worldwide. According to the last IPCC report, is expected, indeed, an increase in severity and frequency of drought under a changing climate, at least over Mediterranean regions. However, is still more uncertain the effect of climate change in other regions in the world.
To analyze the effect of this extreme phenomenon, many drought indices have been developed in recent years based on different hydroclimatic variables and depending on the type of drought under study. Among these indices it is worth mentioning, for meteorological droughts, the Standardized Precipitation Index (SPI) or the Standardized Precipitation Evapotranspiration Index (SPEI), agricultural drought indices such as the Standardized Soil moisture Index (SSI), or those that make use of different variables or multivariate indices such as the Multivariate Standardized Drought Index (MSDI) that combines soil moisture and precipitation, and the Standardized Precipitation Evapotranspiration Soil Moisture Index (SPESMI), an adaptation of the MSDI that incorporates the effect of potential evapotranspiration on the water balance.
This work aims to analyze from meteorological to agricultural droughts projections over Europe using standardized drought indices. For this, we evaluate drought characteristics (i.e., duration and intensity of drought events) for the different drought indicator at scales from 1 to 48 months using an ensemble of climate change regional projections from EURO-CORDEX under a business-as-usual climate change scenario. Changes for the future were analyzed for global warming corresponding to 1.5º, 2º, 3º and 4ºC of temperature above pre-industrial levels. The results of this analysis could offer useful information for adaptation strategies to climate change.
Keywords: standardized drought indices, agricultural droughts, Europe, climate change. projections.
Acknowledgments: This research was financed by the project P20_00035 funded by FEDER/Junta de Andalucía-Consejería de Transformación Económica, Industria, Conocimiento y Universidades, the project “Thematic Center on Mountain Ecosystem & Remote sensing, Deep learning-AIe-Services University of Granada-SierraNevada”(LifeWatch-2019-10-UGR-01), which has been co-funded by the Ministry of Science and Innovation through the FEDER funds from the Spanish Pluriregional Operational Program2014-2020 (POPE), LifeWatch-ERIC action line, and by the project PID2021-126401OB-I00 funded by MCIN/AEI/ 10.13039/501100011033/FEDER Una manera de hacer Europa.
Storage and transport processes in an idealized valley with a LES reference
Authors: Bašić Ivan , Singh Shweta , Schmidli Juerg
Published: July 2023

Trace gas simulations and inverse modelling on the regional scale require an accurate representation of atmospheric boundary layer (ABL) processes. Thus, complex terrain, such as the Swiss Midlands, poses challenges like uncertainties in local turbulent transport, advection, and diffusion. Current operational numerical weather prediction models still provide limited accuracy for the simulation of vertical mixing processes over such regions. Horizontal transport and vertical mixing in the ABL induced by local circulations directly impacts the vertical profiles of trace gases emitted at the surface. A bias in these processes may introduce significant errors in the estimate of trace gas concentrations, especially for the accumulation of greenhouse gases (GHG) during nighttime stable conditions. Since the potential sources of error in representation of stable boundary layers (SBL) include the boundary layer scheme and numerical mixing, an accurate representation of vertical mixing of trace gases in all types of boundary layers is needed. Therefore, in the present work, high-resolution simulations using Cloud Model 1 (CM1) in Large Eddy Simulation (LES) configuration and with idealized topography, representative of the rolling terrain around the tall tower at Beromünster, are performed. This study contributes to an improved understanding of the relevant storage and transport processes of accumulation of passive tracer in nocturnal cold pools, and their morning depletion, along with sensitivities to initial atmospheric stratifications and upper-level wind. The model setup also includes virtual towers located at valley floor, over the slope and the mountain ridge. Together with the sensitivity experiments, along-valley, time averaged model outputs will be presented. 
Nitrogen stabilization in fertilization practice: optimization by regionalization based on meteorological and edaphic parameters
Authors: Assmann Denise , Böttcher Falk , Leppelt Thomas , Kreuter Thomas , Eißner Florian , Thiel Enrico , Döhler Johannes , Grunert Michael , Pundt Hardy , Pleshkanovska Roksolana
Published: July 2023

Within the R&D project StaPrax-Regio, highly efficient N-stabilized fertilization strategies are identified based on site-specific agrometeorological and soil characteristics. Derived strategies will be transferred to fertilization practice using innovative advisory tools. The aim of the project is a significantly improved utilization of the diverse and complex beneficial effects of N-stabilized fertilization (e.g. reduction of N losses, improved N availability in soil, promotion of root growth, improvement of seedling development) to optimize fertilizer N efficiency. Currently, this has been insufficiently achieved for winter cereals. However, the previous project StaPlaRes demonstrated that a significant increase in N use efficiency can be achieved by an optimized adaptation of N-stabilized fertilization strategies to site-specific soil and weather conditions.
The Deutscher Wetterdienst prepares agro-meteorological analyses for 85 test fields with different winter grain types in Germany: based on long-term measurements such as air temperature and precipitation as well as based on modeling with the agro-meteorological models AMBAV (AgrarMeteorologische Berechnung der aktuellen Verdunstung) and BEKLIMA (BEstandsKLIMA) for e.g. soil moisture and soil temperature. Thus, more differentiated statements about the dependencies of plant development on agro-meteorological conditions are achieved. In addition to the model evaluation with measurements ​during the project, the model data and the site analyses are used to generate regionalized statements on e.g. temperatures, precipitation and phenological development during the main fertilization period. In combination with parallel soil and plant cultivation analyses, highly efficient site-specific fertilization strategies will be identified. For this purpose, existing consulting tools (e.g. BESyD) and GIS-based maps will be used and developed further. In order to take seasonal influences into account, an agro-meteorological model is currently developed in the AMBER environment, which should serve as an additional agro-meteorological decision-making aid at an early stage (if possible a few weeks) before each upcoming fertilization application.
Update and new insights on marine heat waves in the Mediterranean
Authors: Juza Melanie , De Alfonso Marta , Mora-Fernandez Angels , Díaz Lara , Chevillard Carla , Zarokanellos Nikolaos , Reyes Emma , Tintoré Joaquin
Published: July 2023

Society is facing unprecedented challenges arising from climate change impacts. Among them, marine heat waves (MHWs) are prolonged periods of extreme ocean temperatures with major ecological and socio-economic impacts. The Mediterranean is the largest semi-enclosed sea, with 46.000 km of coastline and many islands, being also considered a hot-spot of biodiversity with many endemic species. It is also one of the most vulnerable regions to climate change and responds rapidly to global warming with strong spatial variations between sub-basins. In this study, we will update and provide new insights on MHWs in the Mediterranean, from sub-regional to local scales, from surface to subsurface, and from the open ocean to coastal waters using multi-platform remote sensing and in situ observations.Continuous satellite-based sea surface temperature monitoring allows to detect MHWs at the surface and to estimate their spatio-temporal variations at sub-regional and local scales over the last four decades. At the same time, the Mediterranean network of moored buoys installed in shallow waters allows addressing the coastal ocean response to such extreme events over the last 10 years or more. Additionally, profiling floats in the whole basin and ocean gliders along endurance lines in key ‘choke points’ provide valuable information at the subsurface on sub-regional and local scales, respectively, about both the physical and biogeochemical properties from the coast to the open sea. Results on the thermal stress situation will be provided updating the results from Juza et al. (2022) from satellite and profiling floats observations. In particular, we will address the unprecedented MHW recent events (2022 and 2023) characteristics, providing also new insights with the use of coastal moorings and gliders and through the integration of available physical and biogeochemical data.The multi-platform observations used in this study are open access and distributed by national and European marine data portals such as the Spanish Balearic Islands Coastal Observing and Forecasting System (SOCIB), the U.K. Meteorological Office and the E.U. Copernicus Marine Service. Particularly, historical and near real-time ocean data available in the latter are being also used in the web-based application (www.apps.socib.es/subregmed-marine-heatwaves) implemented by SOCIB. This user-friendly visualization tool helps to detect MHWs in real time and to monitor their long-term variations, aiming at supporting the marine conservation and policy decision-makings for climate change mitigation.
Weather data supply for high altitude pseudo satellites (HAPS): A use case of a new prototype universal Web-API for probabilistic height-resolved weather datasets
Authors: Anger Falk , Niebuhr Heiko , Metzinger Isabel , Lang Jürgen , Wetter Thomas , Beckmann Björn-Rüdiger , Zinkhan Dirk , Jerg Matthias
Published: July 2023

Within the framework of the OBeLiSk project funded by the  Federal Aeronautical Research Programme (LuFo VI-1), we investigate the integration of stratospheric drones into the air space with special focus on weather challenges and data supply. While on one hand the stratospheric drones, so-called high altitude pseudo satellites (HAPS), form a special use case, the challenge to supply suitable weather data for new air space users is a much wider and more general field of interest.
Having a glider-like design with a wide wingspan makes the HAPS very weather-susceptible. They fly very slowly, thus achieving only small climb rates. Hence, ascend and descent take long time and play an important role in the operational concept of the HAPS. For this reason, special focus must be put on the distance between earth’s surface and the first kilometer above ground, where both, other air traffic but also weather conditions feature lots of constraints. Laterally well resolved weather data in this range is not only key for the HAPS, but ultimately addresses a much wider spectrum of users. Since, however, data sets and their supply ways to the customer in this field are still sparsely available, new dataset products as well as suitable web application programming interfaces (web-APIs) are needed.
Moreover, particularly strategic flight planning for the next days requires probabilistic weather information since deterministic weather forecast lacks reliability in this regime. But, probabilistic ensemeble-data consists of vast amounts of data that can be challenging to handle. We present a new prototype probabilistic weather data set with detailed height level resolution based on the ICON-D2 NWP model of the Deutsche Wetterdienst. We combine this with the prototype of a new web-API that allows the evaluation of general probabilistic weather data in different height levels in a universal and user-driven fashion. With this contribution we address new air space users but also customers interested in near-surface probabilistic weather information.
Classification of extra-tropical cyclones with cluster analysis based on measures of intensity
Authors: Cornér Joona , Bouvier Clément , Sinclair Victoria
Published: July 2023

Extra-Tropical Cyclones (ETC) cause most of the variability in weather in Europe and are associated with strong winds, heavy rainfall and storm surges which cause damage to infrastructure and can even lead to human fatalities. Although ETCs vary considerably from one system to another, the classification of ETCs based on their common features is a standard practice in meteorology. Classifications simplify the study of ETCs and thus improve understanding and predictability of them. Due to a large number of factors affecting the development and structure of ETCs, various classifications have been established. ETC classifications are based on e.g. conceptual or idealized models, forcing factors, dynamical and synoptic features, or impacts. In this study we construct a dataset of dynamical and impact-based measures of ETC intensity. The aim is to create a classification of ETCs by using this dataset as input in a cluster analysis.
ETCs and their intensity measures were studied using ERA5 reanalysis data from 1979 to 2022. Only the cold season (October--March) was considered in the analysis since that is when the strongest ETCs occur most often. ETC tracks were produced by using 850-hPa relative vorticity as input to the feature tracking software TRACK. To focus on the most relevant ETCs affecting Europe, only tracks in the North Atlantic and Europe were included and stationary and short-lived systems were excluded. Analysed intensity measures included 850-hPa relative vorticity, Mean Sea Level Pressure (MSLP), 850-hPa, 925-hPa and 10-m wind speed, 10-m wind gust, instantaneous Storm Severity Index (SSI), accumulated SSI and wind footprint. Sparse Principal Component Analysis (PCA) was performed to analyse the dependency of the intensity measures on one another and to select input features for the cluster analysis. The cluster analysis was performed using Gaussian Mixture Modelling (GMM).
Sparse PCA with four principal components indicated that all wind speed measures were grouped together as the first component and 850-hPa wind speed was grouped with 850-hPa relative vorticity as the third component. Wind footprint and MSLP were alone in the second and fourth components, respectively. The SSI measures were not represented, which means they did not explain variance in the dataset but formed a separate group of features. By including 850-hPa relative vorticity, MSLP, 850-hPa wind speed, wind footprint and instantaneous SSI, each group of features was represented in the cluster analysis. The number of clusters in the GMM was increased incrementally by one until each cluster was clearly separate from the others in at least one dimension. With seven clusters, weak ETCs, ETCs with high SSI, and ETCs with similar vorticity, MSLP and wind speed but unequal wind footprint and vice versa, were able to be separated into their own classes and their characteristics investigated.