bluuebunny/crossref_metadata_2025 huggingface dataset:
Physical climate risk assessments - how to meet clients’ requirements for non-financial reporting in a standardised process
Authors: Trefalt Simona , Klein Gereon , Ramshorn Christoph , Schlögl Sebastian , Gutbrod Karl
Published: July 2023

The climate is changing, and not for the better – this is old news and will surprise nobody. Immediate action to mitigate and adapt to climate change is necessary on all scales from single households to the continental level, including companies.  In recent years, governments worldwide have been expanding their policies to evaluate the environmental sustainability of economic activities, particularly by asking big companies to assess both their effect on the climate and the climate’s effect on them. This has, in some cases, been formalised under official regulations, such as the ”Corporate Sustainability Reporting Directive (CSRD)” or the “EU taxonomy regulation (2020/852)” of the European Union. Advances in climate prediction have been helping generate increasingly detailed and confident information on the climate means, variability, and extremes in the future, providing a basis for the assessment of climate hazards at company locations. However, stakeholders outside the atmospheric sciences will need assistance in interpreting the data and reducing it to key information related to physical hazards. The process from climate model prediction output to actionable information, used in support of decision-making, is a new climate service provided by meteoblue AG.  While the topics for which the risk should be evaluated, for instance for the EU taxonomy, are clear, several issues remain. Firstly, climate projections at a local scale are not straightforward to obtain, and they are generally not suitable for products that need to be inter-comparable worldwide. Secondly, regulations require the assessment of single topics for which even the present hazard is unknown or the uncertainty in the future evolution remains high. Thirdly, the topics go beyond what is explicitly covered by climate models. All these issues need to be appropriately addresses and resolved in standardised processes to provide a product that is valid for any possible company location worldwide. In this presentation we will focus on how we tailor climate data to meet the clients’ requirements to be able to assess the climate risks at their locations, plan accordingly and pass mandatory company audits related to climate change.  
Impact of regional forest cover on boundary-layer clouds in southwest France.
Authors: Le Moigne Patrick , Noual Gaëtan , Brunet Yves , Lac Christine
Published: July 2023

Land cover changes such as deforestation are known to have an impact on cloudiness and precipitation. However, contradictory results have been obtained depending on the latitude and scale considered, highlighting our limited understanding of the physical processes involved.
This work focuses on summer cloudiness at mesoscale in a temperate region, under the influence of a large forest (the Landes forest in France). It is based on atmosphere-surface mesoscale modeling (Meso-NH coupled to SURFEX).
Based on observed data, the model configuration at 500 m horizontal resolution is first optimized. It successfully simulates the higher summer cloud cover observed over the forest, compared to its surroundings. Then, the physical processes leading to cloud formation are characterized on a representative case. A comparative analysis of diagnostics and budgets over forest and non-forest areas shows that sensible heat flux and roughness length, both higher over the forest, are the main drivers of cloud convection. The difference in heating between the forest and its surroundings modifies the local circulations by significantly strengthening the sea breeze, as well as generating a forest breeze. In a third step, the impact of the 2009 Klaus storm, responsible for the loss of about one third of the trees in the Landes forest, is considered. On fifteen representative convective summer days, the model reproduces the decrease in summer cloud cover reported in a previous study based on satellite observations. As a complementary analysis tool, the mesoscale simulations allow to quantify the impacts of Klaus on the whole diurnal cycle of the boundary layer.
Supercell synoptic configurations and pre-convective environments in Spain
Authors: Calvo-Sancho Carlos , Díaz-Fernández Javier , Bolgiani Pedro , Martín Yago , González-Aleman Juan Jesús , López-Reyes Mauricio , Montoro-Mendoza Ana , Santos-Muñoz Daniel , Sastre Mariano , Farrán José Ignacio , Martín María Luisa
Published: July 2023

This research focuses on the analysis of several severe convective storms, specially supercells, in Spain. The study provides insights into the atmospheric variables that contribute to the development of these storms, which have the potential to result on substantial property damage and loss. The aim of the study is centred on similitudes and differences on the synoptic configurations and pre-convective environments of the selected supercells. The analysis uses a dataset of 262 supercell events for a period from 2011 to 2020. The events are categorized into two categories: supercells with hail (diameter greater than 5 cm) and those without hail, and differences in convective variables and parameters are assessed.
The ERA5 atmospheric reanalysis is selected to analyse the synoptic configurations and atmospheric profiles associated with supercell events at their genesis. Temperature, convective available potential energy, convective inhibition, wind shear, storm-relative helicity, as well as other convective variables and parameters are analysed for each event. The results suggest that supercells are more frequent along the Spanish Mediterranean coast during the summer season. In the selected supercell events, the synoptic pattern composites indicate the location of a deep trough axis over the Iberian Peninsula. Additionally, several variables show statistically significant differences between hail and non-hail events. Supercells with hail show higher median values of the most-unstable convective available potential energy than those systems without hail. The results can contribute to the improvement of forecasting and warning systems for these events, allowing authorities to take the required precautions to reduce property damage and loss.
Strategies of Climate Change Education to Promote Climate Action in Estonia
Authors: Post Piia , Toll Velle , Terasmaa Jaanus , Uibu Krista , Uiboupin Kristel , Laius Anne , Rüütel Tõnis , Tuuling Lehte , Kikkas Aigi , Altrov Anete , Arro Grete , Malleus-Kotšegarov Elina , Annist Aet , Vanamölder Kaarel , Vollmer Elis
Published: July 2023

Climate change poses high risks to many natural and human systems. The science is clear: we need to act to reduce these risks. However, the lack of appropriate expertise strongly limits the effectiveness of climate action. Estonia has a high rate of climate scepticism, and there needs to be a clear national policy on educating people about climate change and climate change mitigation and adaptation.
In an EEA-financed project, "KLIIMATEADLIK - Climate Change Education to Promote Climate Action", we focus on promoting climate change education in formal and non-formal education to increase the competencies necessary for climate change mitigation and adaptation. We aim to establish climate change education at all education levels in Estonia. We develop education strategies, create learning materials and support teachers.
The first step was to understand the current situation regarding climate change education. For this, we assessed the national curricula. Climate change is mentioned as an independent topic only in natural sciences. Another problem is that only the concept of local climate is introduced. Not connecting climate topics to the global climate system makes it challenging to integrate climate change issues.
The next step was to study the status quo of teaching. We analysed the textbooks and surveyed the teachers. Unfortunately, the textbooks do not include a scientific understanding of climate change. The explanations of the causes and impacts of climate change are missing. Moreover, climate change mitigation and adaptation are not covered at all. 
Our solution is to educate teachers and prepare study materials. The study materials cover the causes and impacts of climate change together with climate change mitigation and adaptation. Educating teachers and students will translate to increased climate change awareness in Estonian society in general.
 
Creating a gridded climate database in Sierra Nevada, in the southern Iberian Peninsula
Authors: Romero-Jiménez Emilio , Cepeda-Ventura Luna , García-Valdecasas Ojeda Matilde , Rosa-Cánovas Juan José , Donaire-Montaño David , Solano-Farías Feliciano , Toro Ortiz Yenny , Gámiz-Fortis Sonia R. , Castro-Díez Yolanda , Esteban-Parra María Jesús
Published: July 2023

Mountainous regions are especially vulnerable to the effects of climate change. Therefore, it is essential to study these areas, which contain an invaluable diversity of species and resources. Meanwhile, the southern part of the Iberian Peninsula (IP), as a semi-arid region, is particularly susceptible to climate change. Consequently, the mountainous area of the IP, Sierra Nevada (SN), is an area of interest that needs more research.
Currently, there are different sources of meteorological, observational data for SN. There are several stations scattered across the area. However, certain difficult-to-access areas, located in the highest peaks of the IP, exhibit a lack of data. This issue can be solved by applying spatial interpolation techniques, such as the Regionalisierung der Niederschlagshöhen (RegNie) method. The result of this method is a gridded dataset for the complete region of study. Nevertheless, the coherence of the available observational data is not always guaranteed, so that the statistical analysis of the RegNie results may show low quality gridded data. There is an ongoing effort to create a curated database for the area, known as Climanevada, which is used in this research.
The aim of this study is to create a gridded meteorological database using the RegNie method, containing at least precipitation and temperature data, for SN and its surrounding area. To achieve this goal, the available data for the period 1990-2020 has been deeply analyzed, searching for errors or discardable data. Once this step was complete, the most adequate grid size and resolution were chosen, considering the specific physical characteristics of the area. The whole process is described in this study, together with the description of the features of the final gridded dataset.
Keywords: Sierra Nevada, precipitation, temperature, gridded data, RegNie.
ACKNOWLEDGEMENTSThis research was financed by 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; the project P20_00035 funded by FEDER/Junta de Andalucía-Consejería de Transformación Económica, Industria, Conocimiento y Universidades; and by the project PID2021-126401OB-I00 funded by MCIN/AEI/ 10.13039/501100011033/FEDER Una manera de hacer Europa.
An effect of climate fluctuation on the 1775 and 1821 rebellions in the Czech Lands
Authors: Dolák Lukáš , Brázdil Rudolf
Published: July 2023

Rebellions of peasants against nobility or social order during the 18th–19th centuries in Central Europe were usually the consequences of previous long-term societal problems. Furthermore, the general social dissatisfaction might have been often amplified by negative impacts of climate fluctuation, unfavourable weather or hydrometeorological extremes. Here, we analyse the causes of two outstanding rebellions in 1775 and 1821 in the Czech Lands with respect to climate and weather variability as well as social, economic and political issues. Analysis of both rebellions is allowed based on rich documentary evidence available for the Czech Lands in the studied period (chronicles, weather diaries, grain prices etc.). Temperature and precipitation fluctuations, the occurrence of drought and wet periods, the impacts of the Tambora eruption or changes in grain prices during 1750–1830 were taken into account.  Despite some joint causes of both uprisings (unfavourable weather, poverty, harsh corvée conditions, high taxes), each of both rebellions was characterised by its special reasons. While rainy weather, poor harvest, high grain prices and subsequent famine preceded the 1775 rebellion, the emerging agrarian crisis and sudden grain price fluctuations caused by the Tambora eruption and grain overproduction in 1818 contributed to the 1821 rebellion. The previous results of climate fluctuation will also be completed by recently published datasets and analysed from the new point of view. Moreover, former approaches to studying the causes of both rebellions will be discussed with regard to the modern ones. The results of this study contribute to a better understanding of past negative climate and weather impacts on human society and help to fill the gap in interdisciplinary research.
Seminars for operational MET personnel at Croatia Control
Authors: Jurković Jadran , Ćoso Ladislav , Šoljan Vinko
Published: July 2023

Croatia Control ltd is a national air navigation provider and MET service is a part of the company. Observations, forecasts and warnings are made by aeronautical meteorological forecasters (AMF) and observers (AMO). To maintain the level of education at a very high level, regular refresh seminars have been held for all licensed personnel since 2008.
Almost one week is reserved for the education of forecasters, within spring and autumn seminars,  and two days yearly for observers. Topics balance meteorological theory and practice through lectures on the latest developments in science, measurements and models, the technology of work, operational manuals etc. Exercises are always warmly welcomed. Because of Croatia’s specific climate diversity due to its position between central Europe and the Mediterranean, we have to cover meteorologically very different topics: convection, winter precipitation, fog and low clouds, sea breeze, mountain waves, downslope wind storms and turbulence.
Most of the talks are given by support and education personnel inside the company, while some are even prepared and given by more experienced operational forecasters. Additionally, invited speakers give lectures–usually from the National meteorological institute (DHMZ), Faculty of Science Zagreb, inside company (e.g. ATM support) and others.
For some events, we invite aviation forecasters from neighbouring countries: Slovenia, Bosnia and Herzegovina, Serbia, Montenegro, and North Macedonia. Our lectures are helpful to others, and their participation helps all to improve communication which is present for internationally coordinated products and warnings for aviation. Feedback surveys after seminars and from regular assessments of forecasters are used to improve our in-house education continuously.
Spatio-temporal nowcasting using a deep convolutional RNN model with imbalanced regression loss accounting for extreme wind speed events
Authors: Schicker Irene , Scheepens Daan
Published: July 2023

The amount of wind farms and wind power production in Europe, both on- and off-shore, has increased rapidly in the past years. To ensure grid stability, on-time (re)scheduling of maintenance tasks and to mitigate fees in energy trading, accurate predictions of wind speed and wind power are needed. Furthermore, accurate predictions of extreme wind events are of high importance to wind farm operators as timely knowledge of these can both prevent damages and offer economic preparedness. This is especially relevant for both the lowlands of Austria with a very high amount of wind energy production and the Alpine sites which are more prone to environmental conditions.
This work explores the skills of a recently adapted deep convolutional recurrent neural network (RNN) regression model for spatially high resolved data-driven nowcasting of extreme wind speed events through the manipulation of the loss function. We adapted a multi-layered convolutional long short-term memory (ConvLSTM) network with a variety of imbalanced regression loss functions that have been proposed in the literature: Inversely weighted, linearly weighted and squared error-relevance area (SERA) loss (Scheepens et al., 2022). Forecast performance is investigated for various intensity thresholds of extreme events and a comparison is made with the commonly used mean squared error (MSE) and mean absolute error (MAE) loss. As domain, we focus on the eastern part of Austria, the largest wind power production region in Austria. The ConvLSTM is applied to the 1 x 1 km spatially resolved INCA analysis fields which have been extrapolated to a standard hub height of 100 m a.g.l. Results show that the ConvLSTM is able to outperform the INCA nowcasts (extrapolated, too, to standard hub height).
Implementation of observed changes in soils under no-till and conventional management in selected crop models
Authors: Bohuslav Jakub , Kersebaum Kurt-Christian , Nendel Claas , Hlavinka Petr , Žalud Zdeněk , Trnka Miroslav
Published: July 2023

In recent years, there has been an increasing emphasis on reducing greenhouse gas emissions in agriculture with no-till management (NT) instead of traditional conventional tillage (CT). The NT management has been adopted as a promising strategy to improve physical and organic pools in the soil profile and dynamics of agriculture. The CT leads due to the mixing of the soil, to higher disturbance of soil aggregates, faster decomposition of biomass, and thus increasing emission of carbon dioxide. Therefore, NT has been envisaged as the method for increasing soil organic carbon (SOC) content in the upper layers of soil. The accumulation of SOC in arable land would prevent the release of carbon from the soil into the atmosphere, and its added effect on global warming.
To assess the potential of NT for increase SOC we carried out a meta-analysis of 36 studies with 91 sites in a temperate climate. The main two parameters for comparison were the content of SOC and bulk density (BD) in the upper 30 cm of soil and when possible other soil parameters (e.g. total nitrogen). The study further assessed the NT vs. CT for different soil compositions and therefore five soil texture categories were established i.e. sand, sandy loam, silt loam, clay loam, and clay. The differences in soil parameter shift for each soil category when CT is replaced by NT have been determined.
In the next step of this study, two crop models HERMES and MONICA were tested for sensitivity to tillage practice. Although these models are based on the relationship between plants, soil, and atmosphere, when providing outputs with high quality, both models report only slight differences in the absence of plowing. The determined results from the meta-analysis were used for models calibration.
A ML approach for Post-processing of NWP model on the European Weather Cloud
Authors: Di Giacomo Marco , Giuliano Papale Lorenzo , Marcucci Francesca , Papa Mario , Golino Raffaele , Del Frate Fabio
Published: July 2023

In the present study, the research activities aiming at investigating the use of modern Machine Learning algorithms for the early detection of convective systems are shown.The study conceived and carried out at the Italian Air-Force Meteorological Centre, co-funded in the framework of the EUMETNET-SRNWP-EPS Project, focuses on the post-processing of NWP model output to provide to the forecasters an improved Decision Support System specifically designed for aviation hazards and severe weather phenomena, such as thunderstorms. In detail, the NWP fields generated from operational Limited Area Models (COSMO-IT, 2.2 km horizontal resolution) running at CNMCA (Centro Nazionale Meteorologia e Climatologia Aerospaziale, Italian AirForce Met Service) and ECMWF, were processed and fed, as input features, to a properly designed decision tree. Different targets were defined to train the ML model, starting from independent observation datasets, which include radar, lightning and satellite-derived observations. The products mentioned above and the input features were co-located in space and time to assess the correlation between the signal (the information content of NWP products) and the weather phenomenon (e.g., convective instability). The ML tool operates in near real-time mode for the prediction/test phase and offline mode for the training/validation phase. It runs on the European Weather Cloud (EWC), the cloud-based collaboration platform for European meteorological application development. In this context, the customizable computational capabilities of the EWC allowed us to manage the extensive dataset and reduce the model training time. Then the trained models were validated by considering external observations (i.e., the METAR dataset, which provides airports' messages concerning the main meteorological phenomena and parameters observed by weather stations, such as thunderstorms. Moreover, some case studies will be shown and, as a benchmark of the potential improvement, a comparison with classical (multi-variate, static-threshold decision-tree) post-processing applications, routinely used by the Meteorological Watch Office of the Centre, is included in the evaluation study.
Temporal variation of relationships between circulation modes and temperature during the 20th century
Authors: Hynčica Martin , Huth Radan
Published: July 2023

Circulation modes undergo substantial decadal variability, which also affects spatiotemporal impact of modes on climatic variables on long time scales. Previous studies focused either to one circulation mode or to limited geographical area. Here, the topic is substantially extended as we provide an overview of long-term variations of nine circulation modes in winter and their impact on relationships eith temperaure during the 20th century over the Northern Extratropics. Circulation modes are identified by rotated Principal Component Analysis of 500 hPa geopotential heights in the ERA-20C reanalysis; gridded surface climatic data are gained from the CRUTS dataset. Temporal variations of relationships are evaluated by 15-year running correlations between circulation modes and climatic variables at all land gridpoints. Time series of running correlations with all nine circulation modes at all gridpoints are clustered using the partitioning around medoids (PAM) method into 18 clusters for temperature. Both composite maps and temperature anomalies in the 850 height during specific periods of strengthened, weakened, and normal relationships with climatic variables are used for determination of mechanisms responsible for the variation of relationships. The main mechanisms are changes in the location, shape, and intensity of centres, and formation or split of centres. These mechanisms affect mainly the intensity and direction of advection, which translate into the magnitude of relationships. Possible causes of changes in circulation modes are linked with El Niño‐Southern Oscillation (ENSO), shifts of the Pacific Decadal Oscillation (PDO), and long-term changes in the sea ice extent. The results of this study may be used for climate modelling.
Scale dependent land-atmosphere coupling strength in regional climate modelling
Authors: Breuer Hajnalka , Varga Ákos János
Published: July 2023

In continuous regional climate simulations, the equilibrium between land-surface and atmospheric processes plays a key role both in near surface temperature and in precipitation estimations. A too strong coupling can cause the upper soil layer to dry out in larger amounts than it supposed to, which leads to reduced precipitation and temperature overestimation in summer. The amount of available soil moisture is critical both on summer heat wave strength and on precipitation formation. The strength of coupling determines the partition between sensible and latent heat fluxes which in return influences both temperature and precipitation.
In this study we use 1-year long simulations at 50 km and at 5 km horizontal resolution to analyze the coupling strength between the land surface and the atmosphere with the WRF model. Both simulations refer to the same year and the initial and boundary conditions are given based on the ERA5 reanalysis dataset. The simulation is initialized based on ERA5 only at the beginning, then only the boundary conditions are updated to create continuous, regional climate modelling like environment. The 50 km resolution simulation covers most of Europe, while the 5 km simulation covers the Carpathian region.
The coupling strength and the effect of surface is analyzed through changing the land cover from the USGS to the CORINE one. The study will focus on the Carpathian region as local summer precipitation formation is highly dependent on local factors rather and not on large-scale weather systems. Though land-atmosphere coupling mostly affects the surface based latent and sensible heat fluxes, the resolution of the simulations affects the amount of the coupling strength through the advection.
Post-processing activities in Destination Earth On-demand Extremes
Authors: Kann Alexander ,   WP4-Team of Destination Earth On-Demand Extreme (DE_330)
Published: July 2023

In phase 1 of Destination Earth On-demand Extremes, the capabilities of an on-demand digital twin designed for extreme weather phenomena is currently implemented. The DT workflow consists of an automatic event detection module which triggers a hyperresolution NWP model run on a flexible domain and resolution (depending on the phenomena), followed by error-correction and uncertainty estimation with post-processing techniques and impact models for different applications (renewables, air quality, hydrology). The post-processing framework, as part of the production chain, exploits existing event detection methods by searching for precursors of expected extremes, e.g. applying EFI and SOT index or storm tracking methods and investigates their applicability for triggering the on-demand workflow. Downstream the on-demand hyperresolution NWP model run, post-processing procedures are tailored to specific applications, event type, region and data availability, and complement the hyperresolution model simulations by error correction and probability estimation. These method are flexibly implemented, depending on the availability of NWP data and observational data for training purposes and will include baseline algorithms like neighborhood approach for areas with sparse observations as well as deep learning methods for regions with large samples of observation data. The presentation gives an overview of the current implementation status and its methods and techniques. First demonstrators will be discussed on behalf of selected events and use cases, including technical and scientific challenges. The usability of the hyperresolution NWP model and downstream applications for key users in Civil Protection, Marine Safety and Agriculture will be highlighted and perspectives for future achievements will be outlined.
Tropospheric moisture content variability as a factor of drought intensity in Central Europe
Authors: Wypych Agnieszka
Published: July 2023

Water vapour content in the troposphere, regarding its close and complex relationship with air temperature, plays a crucial role in numerous processes in the ocean-atmosphere system. Contemporary global warming forces an increase in the water vapor absorption capacity by about 6-7% per 1K therefore in areas where a constant supply of water vapor is possible (oceans) simultaneously with the temperature growth, evaporation processes intensify and the specific humidity of the air increases. Over the land, especially with the continental nature of the climate, where evaporation possibilities are limited and atmospheric circulation is the main moisture source, a reduction in relative humidity and an increase in humidity deficit and increasing drought risk as a consequence has been observed. 

The aim of the study is to estimate the intensity of meteorological drought in Central Europe under present and future climate conditions resulting from increasing available water capacity of the troposphere.  

Variability of tropospheric moisture content up to 700 hPa pressure level will be examined, including its various characteristics in the period 1961-2022 and its future projections to 2100 using ERA5 and EUROCORDEX RCP 4.5 and RCP 8.5 scenarios data respectively. 

Drought risk will be assessed using moisture deficit information as well as its impact on particular drought indices. 
The preliminary results clearly confirm the increasing risk of moisture deficit in 21st century caused by increasing water vapor absorption capacity resulting from the temperature growth and no extra moisture sources in Central Europe.  
Statistical post-processing of Wind Speed Gridded Forecasting Based on Deep Learning
Authors: Xuan Yang , Kan Dai , Yuejian Zhu
Published: July 2023

The challenges of applying deep learning (DL) to correct forecast biases with non-Gaussian distribution elements on numerical weather prediction (NWP) are discussed in this paper. In order to address the issue of the UNet model with the Mean Absolute Error (MAE) loss function not being able to correct the bias of strong winds, a new loss function called MAE_MR is proposed. The UNet model with the MAE_MR loss function, compared to the traditional statistical post-processing methods, such as the Kalman filter (KF) and random forest (RF), is applied to correct the biases of wind speed gridded forecasts made by the European Centre for Medium-Range Weather Forecasts (ECMWF) highest-resolution model (HRES) for a forecast lead-time of 1-7 days in the eastern part of China. The MAE of wind speed and the accuracy of wind force based on the Beaufort scale are utilized as metrics to assess the performance of wind forecasting. The accuracy is defined as the ratio of one-to-one grid wind force matching between the forecast and actual value. The results show that the accuracy of the UNet model with the MAE_MR loss function (UNet (MAE_MR)) for wind forces on the Beaufort scale ranging from 1 to 3, 4, 5, and 6 or higher is improved by 11.2%, 17.0%, 11.6%, and 6.4%, respectively, compared to the raw HRES forecast. Additionally, the UNet (MAE_MR) model demonstrates a 22.1% improvement in the MAE of wind speed compared to the raw HRES forecast, while the RF and KF methods show increases of 15.4% and 4.3%, respectively. A case study of a strong wind event showed that the UNet (MAE_MR) has a significant advantage in correcting the forecast bias for strong winds compared to the traditional post-processing methods. In addition, the importance of predictors for the deep learning model is analyzed through sensitivity tests.
Supported by National Key Research and Development Program of China (2021YFC3000905), Key Innovation Team of China Meteorological Administration (CMA2022ZD04).
A stochastic stability equation for unsteady turbulence in the stable boundary layer
Authors: Vercauteren Nikki , Boyko Vyacheslav
Published: July 2023

Limited computer resources lead to a simplified representation of unresolved small-scale processes in weather and climate models, through parameterisation schemes. Among the parameterised processes, turbulent fluxes exert a critical impact on the exchange of heat, water and carbon between the land and the atmosphere. Turbulence theory was, however, developed for homogeneous and flat terrain, with stationary conditions. The theory fails in unsteady flow contexts or with heterogeneous landscapes, but no alternative, viable theory is available. This is not only a source of error in forecasts or climate scenarios, but also a source of model uncertainty which should be characterised and considered when using weather and climate models.
Modelling turbulence is particularly challenging in conditions of stable stratification, which can be associated with intermittent or unsteady turbulence leading to model uncertainty. The study develops a modeling approach to represent unsteady mixing possibly associated with turbulence intermittency and with non-turbulent, sub-mesoscale motions that are typically unresolved by numerical weather prediction or climate models. The approach introduces a stochastic parametrisation of turbulence by randomising the stability correction used in the classical Monin Obhukov similarity theory. This randomisation alters the turbulent momentum diffusion and accounts for sporadic events that cause unsteady mixing. A data-driven stability correction equation is developed, parametrised and validated with the goal to be modular and easily combined with existing Reynolds-averaged Navier-Stokes (RANS) models. Field measurements are processed using a statistical model-based clustering technique, which simultaneously models and classifies the nonstationary stable boundary layer. The obtained stochastic stability correction includes the effect of the static stability of the flow on the resolved flow variables, and additionally includes random perturbations that account for localised intermittent bursts of turbulence. The approach is general and effectively accounts for the stochastic mixing effects of unresolved processes of possibly unknown origin. Its implementation in a single-column RANS model is tested for several numerical examples, demonstrating the effectivity to simulate intermittent mixing, without altering the mean behaviour when compared to a standard RANS model.
Evaluation of WRF parameterizations for extreme wind events over the eastern coast of Spain
Authors: Utrabo-Carazo Eduardo , Alvarez  Imaz Miagros , Dillon Maria Eugenia , Garcia Skabar Yanina , Aguilar Enric , Azorin-Molina Cesar
Published: July 2023

Extreme wind speed events cause more than half of the economic losses associated with natural disasters in Europe, and they are becoming more frequent and severe due to climate change. A better understanding of these extreme events is essential to reduce their associated risks. The overall aim of this research is to study the performance of different parametrizations (micro physics and planetary boundary layer) of the WRF model for the simulation of extreme wind speed and gusts events on the eastern coast of the Iberian Peninsula (IP), Spain. Two typical extreme wind events are simulated: (i) a cold front passage in winter (January 4th, 2022), and (ii) a downburst in summer (August 15th, 2021). Three 2-way nested domains are defined, the two largest ones (horizontal resolutions of 9- and 3-km) centered on the IP and the third one (1-km) centered on the Valencian region. The simulations are initialized with data from the ERA5 reanalysis and the boundary conditions in the coarser domain are updated hourly. The evaluation of the simulations is assessed by means of observed data provided by the Spanish State Meteorological Agency (AEMET) including automatic station network data, radar and satellite images and atmospheric soundings. The model accurately simulates the passage of the cold front, matching the time and magnitude of the observed wind speed and gusts. However, the WRF model does not reproduce the downburst, at least at the observed location. In general, the simulations are more sensitive to the choice of the boundary layer parameterization than to the microphysics parameterization.
Wave Breaking Events and their link to Rossby Wave Packets and Atmospheric Blockings during Southern Hemisphere Summer
Authors: Perez Iago , Barreiro Marcelo , Ehstand Noemié , Hernández-García Emilio , López Cristobal
Published: July 2023

Rossby Wave packets (RWPs) are atmospheric perturbations located at the upper troposphere of mid-latitudes which, sometimes, terminate in Rossby Wave Breaking (RWB) events. If RWB events reach certain spatial and temporal scale, they are considered to be synoptically identical to atmospheric blockings, which are linked to heatwaves and droughts. Thus, understanding RWB events linked to RWPs propagation and their link with atmospheric blocking development is key to enhance extreme weather events detection 10-30 days in advance. Hence, in this study we assess the occurrence of RWB events after the propagation of short-lived RWPs (RWPs with a lifespan below or equal to 8 days, or SLRWPs) or long-lived RWPs (RWPs with a lifespan above 8 days, or LLRWPs), whether SLRWPs or LLRWPs are linked to large-scale RWB events that could form an atmospheric blocking event, and, lastly, study the proportion of blocking situations that occur near RWB events. To do so, we applied a tracking algorithm to detect RWPs in the Southern Hemisphere during summertime between 1979-2020, developed a wave breaking algorithm to identify and follow RWB events, and searched for atmospheric blocking events with different intensities. Results show that LLRWPs and SLRWPs displayed large-scale RWB events around 40% of the time, which tend to last around 1-2 days, which is not sufficient to identify them as blocking situations. Nearly 17% of blockings show a RWB event nearby whenever they manifest, but barely 5% of blockings are linked to RWB caused by RWPs propagation, therefore, propagating RWPs do not seem to be strongly linked to atmopsheric blocking development. Lastly, the occurrence of large-scale RWB events associated with SLRWPs are influenced by El Niño-Southern Oscillation and the Southern Annular Mode.
Snow cover response to temperature and precipitation variability in Central European mountain ranges
Authors: Wypych Agnieszka , Ustrnul Zbigniew , Sałaja Julia
Published: July 2023

Mountainous areas are uniquely susceptible to climate change, making them good indicators of these changes. Research results from different parts of the world indicate recent warming of mountainous regions, particularly located since the 1980s, with different intensity in particular vertical zones. Temperature growth is not followed by significant trends in annual precipitation totals however it brings the change in precipitation annual structure and types what influences the occurrence and persistence of snow cover.
As snow cover is a key element of the Earth’s system with the impact on hydrology, climate, and ecological environment any changes in snowpack patterns will have a complex effect. The aim of the study is to examine the variability of snow cover variables (snow depth and snow cover duration) and they sensitivity to the main atmospherical drivers (temperature and precipitation) including inter-annual variations, and trends over various time scales.
The research has been conducted for mountain areas in Central Europe, defined as the terrain with the elevation above 500 m a.s.l. in the domain of 5°E - 25°E and 47°N-55°N. The analyses cover the period 1981-2022 and are based on various meteorological data sources, i.e. in-situ snow depth observations and near ground temperature and precipitation measurements (serving as reference data) as well as regional reanalysis ERA5-Land and CERRA-Land.
The primarily research results confirm the significant impact of temperature and precipitation change on snow cover characteristics with the differentiation of its intensity dependent on geographical and terrain variables as the altitude, landform, slope and exposition. Nevertheless multiannual variability of snowpack persistence with its decreasing trend over the whole research area has been observed.
Detailed understanding of the timing of snow accumulation and snow ablation is necessary as it controls the mountain runoff rate during the spring, water infiltration and groundwater storage as well as the transpiration rate, crucial elements of hydrological cycle.
Land heat uptake: from Last Millenium proxy and model simulations to observational and CMIP6 products
Authors: García-Pereira Félix , González-Rouco Jesús Fidel , Melo-Aguilar Camilo , Steinert Norman Julius , de Vrese Philipp , Jungclaus Johann , Lorenz Stephan , Hagemann Stefan , García-Bustamante Elena , Roldán-Gómez Pedro José
Published: July 2023

Observational studies based on borehole temperature profiles provide estimates of the land component contribution to the terrestrial energy budget to be 5 %, while CMIP5 (Coupled Model Intercomparison Project Phase 5) based estimates scale it down to 2 %. This discrepancy might have sensitive implications for the anthropogenically-driven energy surplus partition between the different components. At least part of this difference is likely due to state-of-the-art Land Surface Models (LSMs) in current Earth System Models (ESMs) being too shallow, thus constraining land heat uptake.

Séneca, a 2100-year-long fully-coupled forced simulation (Past2k + historical period + SSP585 future scenario, P2k+) using version 1.2 of the Max Planck Institute Earth System Model (MPI-ESM1.2-LR) with a deep BBCP (1417 m) is used to assess the behavior of subsurface temperatures and heat storage at long-term scales. It was run using Tier 3 forcing protocol defined in Paleoclimate Model Intercomparison Project Phase 4 (PMIP4) within the Coupled Model Intercomparison Project Phase 6 (CMIP6). Results show that Séneca land heat uptake by the end of the historical period is 4 times higher than for a P2k+ PMIP4- CMIP6 standard (about 10 m) simulation, also well above estimates provided by CMIP6 models. However, deepening the BBCP had no effect on surface temperature variability. This finding provides a strong basis for the use of a one-dimensional conductive forward model to obtain more reliable estimates of land heat uptake from complementary surface temperature sources, such as gridded observational datasets and reanalysis products. Furthermore, it enables the correction of shallow land surface model-based CMIP6 heat uptake estimates. The values obtained from this new approach (9-14 ZJ in 1971-2018) are in close agreement with the values derived from the MPI-ESM deep simulation (10 ZJ), but still below the last borehole-based estimates (19-25 ZJ).
The footprint of COST733
Authors: Tveito Ole Einar
Published: July 2023

Weather and/or circulation type classification has engaged meteorologists and climatologists for a long time. Classification usually means to group something that can appear as complex and chaotic into something discrete, structured and easy to understand based on characteristic features of the process to be grouped. In atmospheric sciences classifications have a long tradition, and got a renaissance in the 1990’ies as helpful tools to understand the impacts of a changing climate. This required a transition from the traditional manual and subjective classifications such as the German Grosswetterlagen and the British Lamb Weather Types to objective and automatic methods that could run on computers, and a large number of classifications were developed using the opportunities given by computers and tools offered by statistical software. The high number of different methods applied for classification of circulation types implied challenges to the meteorological-climatological communities since most circulation type classifications were adapted to a specific region, and not necessarily easily transferable to another region and they were focused on a specific (environmental) problem, and the spatial and temporal scale are adapted to this purpose. Comparison and evaluation of  the various weather types classifications per se as well as the applications using these classifications was therefore difficult. 
COST Action 733 was initiated aiming to meet the need for a coordinated European effort to produce one or a few standard methods designed to facilitate such comparisons, and to establish a unified, transferable approach to synoptic classifications. COST733 was active between 2005 and 2010, collecting, evaluating and comparing a wide range of synoptic classification methods for various applications. It was a large network of more than 60 scientists. During the course of the actions more than 80 scientific papers were published. 
The main outcome and contribution to the scientific community of the action was however the jointly developed cost733class-software that includes the circulation classification methods selected for evaluation and comparison. This software has been widely used by a large number of scientists world wide over the last 10 years, and has set the standard for  addressing classification of weather types.  During the last 5 years COST733 has been mentioned by more than 300 scientific contributions. In this presentation we will take a short  retrospect of COST733 and look at its role as an inspiration and tool for continued research involving circulation type classifications.
Interactive 3-D visualization for rapid exploration of numerical weather prediction data – recent updates to Met.3D
Authors: Rautenhaus Marc , Beckert Andreas , Modali Kameswarrao , Vogt Thorwin
Published: July 2023

Visualization is an important and ubiquitous tool in the daily work of atmospheric researchers and weather forecasters to analyse data from simulations and observations. Visualization research has made much progress in recent years, for instance, with respect to techniques for ensemble data, interactivity, 3-D depiction, and feature-detection. Met.3D is an open-source research software aiming at making novel interactive, 3-D, feature-based, and ensemble visualization techniques accessible to the meteorological community (code repository, conda package, and documentation available at https://met3d.wavestoweather.de). Since its first public release in 2015, Met.3D has been used in multiple visualization research projects targeted at atmospheric science applications, and has evolved into a feature-rich visual analysis tool facilitating rapid exploration of atmospheric simulation data. The software is based on the concept of “building a bridge” between “traditional” 2-D visual analysis techniques and interactive 3-D techniques powered by modern graphics hardware. It allows users to analyse data using combinations of feature-based displays (e.g., atmospheric fronts and jet streams), “traditional” 2-D maps and cross-sections, meteorological diagrams, ensemble displays, and 3-D visualization including direct volume rendering, isosurfaces and trajectories, all combined in an interactive 3-D context.
Met.3D has in recent years been advanced within the German research projects “Waves to Weather (W2W)” and “Climate, Climatic Change, and Society (CLICCS)”. In this presentation, we will present the current state of the Met.3D software and discuss recent updates we consider beneficial for the weather forecasting community, including use of open forecast data and interactive visual analysis of forecast 3-D cloud fields and other volumetric data.