bluuebunny/crossref_metadata_2025 huggingface dataset:
Climatic design conditions for buildings and impacts of climate change in Finland
Authors: Jylhä Kirsti , Lindfors Anders , Ruosteenoja Kimmo , Laukkarinen Anssi , Lahdensivu Jukka , Pakkala Toni , Kosonen Risto , Jokisalo Juha , Lanki Timo , Kollanus Virpi , Mäkelä Antti , Vinha Juha
Published: July 2023

With the aim of supporting the design of healthy, safe, and energy-efficient buildings in the changing climate of Finland, tailored hourly weather data files have been constructed and used to assess indoor conditions, energy efficiency and moisture safety of buildings. First, 30-year hourly weather datasets were compiled using observations at four measurement sites in 1989-2018. These datasets were then transformed to represent alternative future climates by modifying the observational values in accordance with CMIP5 climate model projections. The data files for the recent past and projected future initially contained the following variables: temperature, relative humidity, wind speed and direction, three solar radiation variables and precipitation. Later, the data files were supplemented with atmospheric downward longwave radiation (LWdn).
For building physics, LWdn is relevant because it is one of the factors that affect the energy balance of buildings. In the lack of sufficiently long time series of direct measurements, its past values were taken from the ERA5 reanalysis. To produce future time series of LWdn that are consistent with the future values of the other variables in the weather data sets, machine learning was utilized.
Based on the 30-year multivariable data files for the recent past and future climates, shorter periods of weather information were selected for specific purposes. These included Test Reference Years (TRY) for assessing the average annual energy use for heating and cooling; Moisture Design Years (MDY) for simulations of, e.g., mould growth in building envelope structures; Design Days for Cooling (DDC) at various risks levels; and a Heat Wave Summer (HWS) for space overheating risk, representing a year with severe heatwaves in summer.
The presentation provides examples of climate change impacts on different building types. While average temperature and wind-driven rain are projected to increase, technical aspects in the buildings strongly affect how noticeable impact this has e.g., on mould growth. Future changes in corrosion of reinforced concrete structures and freeze-thaw damage depend on the location of the buildings and the orientation of their facades as well as on durability properties of concrete. More frequent and severe heatwaves in the future increase the risks of overheating, thermal discomfort and adverse health effects, particularly among the elderly, in dwellings without efficient cooling. 
The work is linked to the Healthy Premises 2028 programme, set by the Prime Minister’s Office of Finland, and to the Climate Change and Health (CLIHE) programme of the Academy of Finland.
An overview of four use cases from a dense urban measurement network in Basel, Switzerland: Quality of the measurements, temperature and precipitation variability, and mitigation of urban heat island mitigation strategies.
Authors: Schlögl Sebastian , Bader Nico , Reiss Alexandra , Ströbel Barbara , Gutbrod Karl
Published: July 2023

Nowadays, cities worldwide cope with challenges such as air pollution, extreme air temperatures, and heavy precipitation. In the future, these problems will occur more often due to climate change. This trend will result in an unknown amount of economic damage and endanger the life and health of the cities’ populations. Therefore, heatwave management monitoring tool is required to monitor the climate in the city. 

In 2019, more than 200 low-cost IoT temperature and precipitation sensors have been installed in the Swiss city of Basel. In this study we present four use cases from the "Basel Living Lab" based on the measurement network, which are relevant for city planners, decision makers in cities and the citizens itself:  

1. Quality of the measurements
2. Temperature variability in the city 

3. Precipitation variability in the city 

4. Mitigation of urban heat island mitigation strategies 

1. The quality of the low-cost measurement network is estimated by a comparison with official MeteoSwiss stations. Therefore, low-cost sensors have been installed at the same mast as the MeteoSwiss stations as the reference. Reproducibility tests have been conducted, gaps and sensor drifts over the last 4 years have been analyzed and radiation errors have been estimated and corrected. During calm conditions in summer, the low-cost IoT measurements are up to 5 degrees higher than the reference measurements caused by heat accumulation errors which can be corrected satisfactorily with the radiation correction.  

2. The temperature variability in the city and rural surroundings show differences up to 10 degrees during night and calm conditions and on average differences around 3 degrees. The measurement data can be used to force models resolving the urban heat island effect in the city.  

3. The precipitation variability in the city shows differences up to 80 mm/day of precipitation within a few kilometers during heavy thunderstorms. 

4. A small area in Basel, so called “Triangel” was desealed and planted with 18 young trees. Measurements before and after the mitigation phase have been conducted to analyze the effect of the change in the surface conditions. Our results show a decrease in the air temperature of about 0.5 degrees due to the changing surface characteristics, which fits well with scientific studies and model results.  

The four use cases demonstrate some selected advantages of a dense measurement network in an urban environment and build a solid data basis for decision makers in cities mitigating their urban heat island effect.   
The urban climate of Amsterdam: Results of 10 years Amsterdam Atmospheric Monitoring Supersite
Authors: Steeneveld Gert-Jan , Keuken Clara , Heusinkveld Bert , Peerlings Esther , Hartogensis Oscar , Tsiringakis Aristofanis , Jongen Harro , van der Kolk Jaap
Published: July 2023

The urban climate is substantially different from its rural counterpart. This study summarizes 10 years of monitoring the urban climate of Amsterdam. Amsterdam has a unique position in the sense it is located in a delta, and located close to a large lake in the east. Moreover the city is well known for its large amount of water bodies. A network of 24 weather stations has been employed observing temperature, humidity and wind speed at 4 m height across the city. This is complemented by radio soundings, and traverse observations using a tricycle equipped with a weather station recording temperature, humidity wind speed, and all radiation components within the urban canyon. The network also contains flux measurements of turbulent fluxes of heat, moisture, momentum, carbon dioxide and methane using eddy covariance observations. The latter are especially relevant for monitoring the greenhouse footprint of the city. In addition a microwave scintillometer has been installed to monitor the sensible and latent heat flux for a footprint over the city as a whole. We present spatial behaviour of temperature (urban heat island and urban cool island) and humidity as well as canyon wind speeds. Both a clear urban heat island (UHI) and cool island has been found. The UHI extends up to 90 m. In addition, the observations reveal a systematic signal of a moisture island effect too. We find a Bowen ratio of the summertime fluxes about 3.8. Finally results from indoor weather stations installed in 100 households to monitor and understand urban heat in bed and living rooms will be presented.
Traceability of Aerosol Optical Depth measurements and links with the Aerosols, Clouds and Trace Gases Research Infrastructure (ACTRIS) / Calibration of Aerosol Remote Sensing (CARS)
Authors: Masoom Akriti , Kouremeti Natalia , Barreto Africa , Toledano Carlos , Podvin Thierry , Blarel Luc , Dubois Gael , Gröbner Julian , Kazadzis Stelios
Published: July 2023

World Optical Depth Research and Calibration Center (WORCC) is participating in the Aerosol, Clouds and Trace Gases Research Infrastructure (ACTRIS), Switzerland program as part of the  ACTRIS Calibration of Aerosol Remote Sensing (CARS). In the ACTRIS-CARS program, WORCC maintains three precision filter radiometers (PFRs) at Izanã (IZO) in Spain, Observatoire de Haute Provence (OHP) in France and University of Valladolid (VLD) in Spain which are the main calibration facilities of ACTRIS sun photometers. The aim of this collaboration is to link the AOD product from ACTRIS-CH with the AOD scale recognized by the WMO and maintained by WORCC.In this analysis, the AOD measurement comparisons were performed between ACTRIS-CARS PFR and Aerosol Robotic Network (AERONET)-Europe CIMEL sun-photometers at IZO, OHP and VLD for 2021 and 2022. The comparisons are performed in common wavelengths and also PFR AOD is extrapolated to the non-matching CIMEL wavelengths using Ångström law. The annual comparison results of PFR and CIMEL AOD at IZO showed that more than 99% of AOD differences were within the WMO uncertainty limits for all wavelengths above 340 nm. In case of OHP, more than 99% percentage of AOD differences were within the WMO uncertainty limits for all wavelengths longer than 440 nm while it was above 80% for all wavelengths except 340 nm. At VLD, the percentage of AOD differences within the WMO uncertainty limits were mostly above 99% for all wavelengths above 440 nm and above 90% for all wavelengths except 340 nm. In additions, instruments were inter-compared during the fifth filter radiometer campaign (FRC-V) held in 2021 and differences with the Davos reference triad of PFRs were mostly within the WMO limits.Acknowledgment The work has been supported by the  Aerosol, Clouds and Trace Gases Research Infrastructure – Swiss contribution funded by the State Secretariat for Education, Research, and Innovation, Switzerland.
New communication direction on social media at the Hungarian Meteorological Service
Authors: Simon Gergő
Published: July 2023

At the Hungarian Meteorological Service (HMS), the development and conscious use of social media channels began in 2018. In the recent years, there have been many developments, and content creation has started on several new platforms. We had to react to the changing habits in social media, so at the HMS we try to reach more and more people and deliver trustworthy meteorological data and forecasts to them. In order to do this, we try to use various communication styles on our social media platforms. We have three main social media channels (Facebook, Instagram and Youtube), and each platform has its own distinct role. For example, we usually publish measurements, short- and medium-range forecasts, and weather analysis on Facebook. On Instagram, we use a much more direct tone, and we try to present the whole HMS (employees, other areas of expertise), and post a lot of pictures from our followers. According to our experience, a little fun always fits in, so sometimes we use a tool of humor. Thanks to this we also reach age groups that we have not before. On our Youtube channel, we make a daily weather forecast video, which is presented by our meteorologist. Besides this, we also publish climate analyzes and summaries. For the visualization we have a self-developed, operationally used interactive visualization system, the HAWK-3. The HAWK-3 processes the numerical model data and after that we can visualize or edit it. The program can display data on maps or special meteorological charts.
Our primary goal is to present meteorological information and forecasts to the public with a modern graphical display on social media. In addition, another important objective is to break down stereotypes about the profession and present the activities of the service.
Wind to start the dishwasher? High-Resolution Wind Atlas for Finland
Authors: Tian Yu , Yang Xu , Schicker Irene , Jung Alexander
Published: July 2023

Abstract—The current climate crisis increased the demand for renewable energy sources. In northern Europe, the efficient utilization of wind power is crucial for achieving carbon neutrality. However, the spatio-temporal variability of wind energy poses a challenge to its efficient use. Wind energy may not always be available at locations and during times that match the end user’s needs.
Since transmission and storage of wind energy incur losses, it is beneficial to consume wind energy near its production sites. This highlights the importance of site selection for wind power plants, requiring corresponding estimation of wind production. To assess the potential of wind energy for private households in Finland, a high spatiotemporal resolution wind power map for Finland, accessible at powermap.fedai.link, was conducted.
An exploratory data analysis using freely available weather data provided by the Finnish Meteorological Institute (FMI) was carried out. Here, we are interested in the short-term availability of wind power to operate household appliances equipped with modest battery capacity. To this end, we considered a simple power system dictated by discrete time instants t = 0,1,....The absolute time difference between any two consecutive time instants t and t+1 is ∆t = 10min. The system includes a wind power plant that delivers the power Pt(w) at time instant t. We consider a wind power plant of type Nordex N100/25000 that is mounted at the height of 100m. The system also includes a load that is characterized by a power profile Pt′(a )for time instants t′ ∈ [Ta]. An example of the load is a household appliance such as a dishwasher. The power profile of the load has finite support of Ta time instants.

We define the candidate starting time ts as suitable if, starting from an empty battery, the process with a given load profile can be completed solely from wind energy. The battery is assumed ideal, storing any excess wind energy without leakage up to its capacity and providing any wind energy deficit without losses until it is empty. The resulting relative fractions of suitable starting times during 2021 are then depicted on a map of Finland.
Our numerical experiments show that wind power has a higher availability (larger fraction) in regions along the coastline and the northern parts of Finland. Battery capacity is also a crucial factor; the useful fractions increase as the battery capacity increases until a certain value is reached. We found that the distribution of useful starting time points over 24 hours of the day is quite uniform. In contrast, the results show significant seasonal trends in some weather stations, with March and October having more useful starting time instants than the other months.
Potential use of high-resolution X-band weather radar data in agriculture in northeast Germany
Authors: Künzel Alice , Mühlbauer Kai , Neelmeijer Julia , Itzerott Sibylle
Published: July 2023

In June 2020 a ground-based, dual-polarization Doppler X band weather radar supplied by FURUNO Germany was installed in Neubrandenburg in northeast Germany and data was recorded continuously since October 2020. Between autumn 2020 and July 2021 the scan settings were changed repeatedly in order to figure out the optimum settings of the radar. From August 2021 onwards FURUNO performs a set of scans with an update time of five minutes. Each five-minute scan includes eight elevation angles and finally a 90° scan.
The aim is to use the high spatial and temporal resolution weather radar data for real time information about precipitation events in the regional test area DEMMIN, which covers 900 km2, in future. The intensive agriculture test area is located between 30 and 50 km north of the weather radar and real-time information on local precipitation events has the potential to help farmers plan irrigation events in this area in future because irrigation will be more important in the future due to climate change.
To provide farmers with temporally and spatially highly resolved precipitation products, weather radar data must be carefully calibrated and processed. For the processing we developed the open source software WRaINfo, which is specifically designed for processing X-band weather radar data of FURUNO. Phase processing and attenuation correction are performed according to the ZPHI method. After the attenuation correction different Z-R relationships are used to obtain precipitation products.
We are analysing the results for stratiform and convective precipitation events in 2022. The precipitation products of Furuno were also compared with precipitation data of climate stations and the weather radar product RADOLAN (RW) from the German Weather Service within the scan radius of Furuno.
The study provides an overview of the detection of precipitation by means of weather radars up to the potential application in agriculture.
Improving the operational forecasts of outdoor UTCI with post-processing
Authors: Kuzmanović Danijela , Skok Gregor , Banko Jana
Published: July 2023

Universal Thermal Climate Index (UTCI ) is a thermal comfort index that describes how the human body experiences ambient conditions. It has units of temperature, and it takes into account the effect of air temperature, humidity, wind, radiation, and clothes. It is increasingly used in many countries as a measure of thermal comfort for outdoor conditions, and its value is calculated together with the operational meteorological forecast. At the same time, forecasts of outdoor UTCI tend to have a relatively large error caused by the error of meteorological forecasts. In Slovenia, there is a relatively dense network of meteorological stations. Crucially, on these stations, global solar radiation measurements are performed, making estimating the true value of UTCI more reliable. We used seven years of measurements in hourly resolution from 42 stations to first verify the operational UTCI forecast for the first forecast day and, secondly, to try to improve the forecast via post-processing. The verification showed that the operational ALADIN model tends to overestimate the UTCI values. The overestimation is most pronounced in the morning when the mean error is about 8 °C. Also, a small percentage of cases have a very large error (up to 40 °C). We used two machine-learning methods to try to improve the forecasts of UTCI: linear regression and neural networks. Both methods have successfully reduced the error in the operational UTCI forecasts. Both reduced the daily mean error from about 2.6 °C to almost zero, while the daily mean absolute error decreased from 5 °C to 3 °C for the neural network and 3.5 °C for linear regression.
Using state-of-the-art generative neural networks for high-resolution NWP ensemble emulation
Authors: Brochet Clément , Moldovan Gabriel , Raynaud Laure , Plu Matthieu
Published: July 2023

Convection-permitting numerical weather prediction (NWP) models are a useful tool to forecast high-impact phenomena such as storms and heat waves. Ensemble prediction systems based on such models can then be used to quantify the associated forecast uncertainties. However, high-resolution ensemble forecasts come with a high computing cost; this limits the size of operational ensembles, and potentially reduces their relevance in critical situations.In this work we propose a new and computationally efficient way to synthesize additional ensemble members of the kilometer-scale AROME model,based on deep generative models. For that purpose, state-of-the-art style-based generative adversarial networks (StyleGAN) and denoising diffusion probabilistic models (DDPM) are examined and compared on the joint generation of 10-meter wind and 2-meter temperature forecasts. We first show that these neural networks, once properly trained, create physically consistent, realistic, multivariate ensemble members. We then propose several methods to condition the generated members on the NWP model outputs 'of the day', in order to produce large hybrid physical/statistical ensembles at a small numerical cost. In particular, we show how to leverage the latent representations learnt by the networks to control the resulting ensemble statistics. A thorough evaluation of the resulting hybrid ensembles is proposed to assess their relevance and the new information they add with respect to small, pure NWP ensembles. Finally, we compare large, deep-learning-generated ensembles to a 875-member AROME forecast on a situation corresponding to a weather alert on the Mediterranean region, and evaluate the ability of generative approaches to provide an acceptable approximation of this large NWP ensemble.
A grid dataset of daily sunshine duration for Austria since 19
Authors: Hiebl Johann , Bourgeois Quentin , Tilg Anna-Maria , Frei Christoph
Published: July 2023

Grid datasets of sunshine duration at high spatial resolution and extending over many decades are required for many quantitative applications in regional climatology and environmental change, including the modelling of droughts and snow/ice covers, the evaluation of clouds in numerical models, the mapping of solar energy potentials, and many more. Here, we present a new gridded dataset of relative sunshine duration, and derived absolute sunshine duration, developed for the territory of Austria at a grid spacing of 1 km, and extending back until 1961 at daily time resolution. The dataset complements the collection of SPARTACUS climate monitoring datasets, operationally produced by the national meteorological service of Austria. The presentation will outline the efforts made into a consistent station dataset, the methodological solution adopted in this complex topography region, and it will highlight key results from an evaluation with a user-orientated viewpoint.
The big challenges in the construction of the dataset were (a) issues of consistency in the available station data, notably the inhomogeneities related to changes in measurement devices and practices, and (b) limitations posed by the scarcity of long series and the high variation of cloudiness in the study region. The challenges were addressed by special efforts to correct evident breaks in the station series and by adopting an analysis method that combines the station data with information from satellite data. The methodology merges the data sources non-contemporaneously, i.e. using statistical patterns distilled over a short period, which allowed involving satellite data even for the early periods of our dataset.
The resulting fields contain plausible mesoscale structures, which could not be resolved by the station network alone. On average, the daily analysis explains 81 % of the spatial variance in daily sunshine duration at the stations (cross-validation). Comparison to other datasets showed that the new dataset meets a similar standard in temporal consistency, in spite of the limited data quality over such a long period. Our evaluation revealed a slight systematic underestimation (−1.5 %) and a mean absolute error of 9 %. The average error is larger during winter, at high altitudes and around the 1990s. We also find that the dataset exhibits a conditional bias, related to the involved uncertainties, which can lead to considerable systematic errors (up to 15 %) when calculating sunshine-related climate indices.
Challenges of forecast uncertainty within the warning value chain – a UK example from Storm Eunice
Authors: Neal Robert , Titley Helen , Golding Brian , Jones Caroline , Kolusu Seshagirirao , Mooney John , Robbins Joanne , Wyatt Faye
Published: July 2023

The warning value chain is a concept whereby the process of producing a warning is represented by a chain of sources of expertise (components), connected by bridges that convey bidirectional information exchanges. Uncertainties exist at all stages of the warning value chain. For example, uncertainties exist in the current (observational) state of the atmosphere used to initialise the numerical weather prediction models. This in turn contributes towards weather forecast uncertainties (e.g., ensemble-generated forecast probabilities and run-to-run variability). Weather forecast uncertainties then feed into the hazard and impact forecasts where they can be amplified – such as through uncertainties in defining hazard footprints or impact assessments. Often it comes down to operational meteorologists to examine the varying levels of forecast uncertainty across several value chain components and assess the real likelihood of high impact weather and its potential impacts. This presentation will focus on the challenges of forecast uncertainty within the value chain, using the forecasts and warnings associated with Storm Eunice which affected southern parts of the UK in February 2022 as an example. The Met Office Weather Impacts team recently used the warning value chain questionnaire produced by the WMO’s High Impact Weather (HIWeather) Warning Value Chain Flagship Project, to carry out a detailed warning value chain assessment for this event, where evidence was considered from across the value chain. Results showed that all components of the value chain performed well overall, and it was clearly a highly successful set of warnings as shown by the large reach and public/emergency response. However, several recommendations were still made and challenges resulting from forecast uncertainty were evident across many value chain components. A focus of this presentation will be on how operational meteorologists interpreted the changing forecast signal and how this affected warning issuance and communication.
MeteoEurope1km: a high-resolution daily gridded meteorological dataset for Europe for the 1991–2020 period
Authors: Sekulic Aleksandar , Kilibarda Milan , Bursac Petar
Published: July 2023

Daily gridded meteorological datasets are an important source of information for analysis of historical weather and many other research areas since they have no gaps in the spatio-temporal domain they cover. Most of the daily gridded meteorological datasets represent reanalysis or estimations from different remote sensing sensors or are generated by downscaling procedures. There are none or a very few high resolution datasets on regional or global scale that are based on observational data and space-time geostatistics, i.e. that takes into account spatio-temporal correlation between observations. The only such dataset for Europe is the E-OBS dataset at 10 km spatial resolution, but it uses spatial correlation only. Therefore, a daily gridded meteorological dataset for Europe at 1 km spatial resolution, named MeteoEurope1km, is created, initially covering the 1991–2020 period. Spatio-temporal regression kriging (STRK), an interpolation method that combines multiple linear regression for trend modeling and space-time kriging for the estimation of the residuals, is used for interpolation of maximum, minimum, and mean daily temperature. Combination of GHCN-daily, ECA&D, and SYNOP observations from OGIMET service is used as an observational dataset, with previous removal of duplicated stations and outliers, while geometric temperature trend, digital elevation model and topographic wetness index are used as auxiliary variables. Accuracy assessment (leave-one-station-out cross-validation) shows high accuracy of the STRK models for daily temperature. Coefficient of determination for all three parameters is greater than 97% and root mean square error is less than 1.5°C. Future work will be oriented towards increasing the temporal extent of the MeteoEurope1km to the 1961–present period, interpolation of other daily meteorological variables, and improving performance of STRK models for daily temperature at higher altitudes, since the accuracy is lower due to a well known problem with lack of stations. The same methodology will be applied for interpolation of daily sea level pressure, while spatial machine learning methods, such as Random Forest Spatial Interpolation, will be used for interpolation of daily precipitation because of its complex nature.
Apparent contradiction in the projected climatic water balance for Austria: wetter condition on average versus higher probability of meteorological droughts
Authors: Haslinger Klaus , Schöner Wolfgang , Abermann Jakob , Laaha Gregor , Andre Konrad , Olefs Marc , Koch Roland
Published: July 2023

In this paper future changes of surface water availability in Austria are investigated. We use an ensemble of downscaled and bias-corrected regional climate model simulations of the EURO-CORDEX initiative under moderate mitigation (RCP4.5) and Paris agreement (RCP2.6) emission scenarios. The climatic water balance and its components (rainfall, snow melt, glacier melt and atmospheric evaporative demand) are used as indicators for surface water availability and we focus on different altitudinal classes (lowland, mountainous and high alpine) to depict a variety of processes in complex terrain. Apart from analysing the mean changes of these components we also pursue a hazard risk approach by estimating future changes in return periods of meteorological drought events of a given magnitude as observed in the reference period. The results show in general wetter conditions over the course of the 21st century over Austria on an annual basis compared to the reference period 1981-2010 (e.g. RCP4.5 +107 mm, RCP2.6 +63 mm for the period 2071-2100). Considering seasonal differences, winter and spring are getting wetter due to an increase in precipitation and a higher fraction of rainfall as a consequence of rising temperatures. In summer only little changes in the mean of the climatic water balance conditions are visible across the model ensemble (e.g. RCP4.5 ±0mm, RCP2.6 -2 mm for the period 2071-2100). On the contrary, by analysing changes in return periods of drought events, an increasing risk of moderate and extreme drought events during summer is apparent, a signal emerging within the climate system along increasing warming.
Local climate protection in science
Authors: Vallon Magdalena
Published: July 2023

Mitigating and adapting to climate change is an urgent and complex issue. This is particularly challenging for those who have to make the actual decisions on how to start and which measures to prioritise. Especially in the public sector, regulations are made at the European or national level, but implementation is the responsibility of local authorities such as cities, villages and municipal companies, which adds a complex task to their scarce financial and human resources. The South German Climate Office at the Karlsruhe Institute of Technology (KIT) aims to provide advice and disseminate knowledge on climate change to society and the public sector through various projects. One current project is the development of a graph database, in which a variety of climate protection measures are implemented. The key elements are: firstly, a proper and neutral assessment of each measure according to scientific standards; secondly, a quantification of different aspects of the measure to facilitate prioritisation; and thirdly, using the nature of the graph database to link different measures to each other and to their climate targets.
The project was prompted by a request from a public service to use scientific expertise to help the public navigate the overwhelming flood of information.  In a joint series of workshops with municipalities, municipal companies and KIT, a number of key issues (energy, mobility, water management) and decision factors (climate impact, social acceptance, financial burden, timeframe) were identified. These define the first framework for the database and the evaluation of climate protection measures. A team of scientists from different institutes (KIT-IIP, KIT-ITAS, KIT-IfV, KIT-IMK, KIT-Division IV) covering the thematic side as well as the social factor evaluates the measures according to their expertise and implements them in the database. Through intensive consultation with the Association of Municipal Companies and partner cities and municipal companies, the database is tested for practical suitability. The aim of the project is to facilitate decision-making in the municipal sector on climate change mitigation measures, thereby reducing the burden on financial and human resources and increasing the proportion of decisions made on the basis of neutral, scientifically sound information
Influence of PV modules on the incident radiation and the yield of 3 plant varieties.
Authors: Weihs Philipp , Thaler Sabina , Eitzinger Josef , Zamini Shokufeh , Berger Karl , Abdollahi Mahnaz
Published: July 2023

Agrivoltaic (APV) approaches use PV modules mounted at a sufficient height above the ground to allow synergistic use of agricultural production and energy generation. With this approach, the loss of agricultural land can be minimized. The connections between APV systems and the influence on the micro- and local climate and the yield of the underlying crops have not been sufficiently researched until now. First, APV shading reduces incoming solar radiation, which can lead to a reduction in yield. Second, shading however, also reduces evapotranspiration and can therefore prove to be advantageous, especially during dry periods. The presence of PV panels (by analogy with trees) protects plants from excessive heating and lowers the soil temperature, thereby balancing the microclimate.
In the present study, the influence of different APV designs on the microclimate and plant growth was estimated using model simulations.
 
The effects of different APV designs (e.g. length, width, inclination, row spacing....) on incident solar radiation under the modules were calculated using a method based on image processing of hemispherical "fisheye" photographs. In this way, global radiation above and below the PV modules was calculated for a period of 10 years.
Simulated global radiation and meteorological data were then used to simulate crop growth of 3 varieties (maize, winter wheat and barley). Simulations were performed using the plant growth model DSSAT. In general, some yield reduction was obtained below the PV modules. Yield reduction was strongly correlated with radiation sums. However, some varieties , especially maize, showed an increase in yield in hot, dry years.
Frost risk climate change projections for sweet cherry (Prunus avium L.) in Slovenia
Authors: Žnidaršič Zala , Gregorič Gregor , Sušnik Andreja , Pogačar Tjaša
Published: July 2023

Sweet cherry (Prunus avium L.) is an important fruit tree for Slovenia, often threatened by spring frosts, especially the early flowering varieties. In recent decades, the occurrence of frost events has steadily increased, which has negatively affected cherry fruit production, especially in the Submediterranean part of Slovenia. Although fruit trees can tolerate severe cold during their dormant stage, the resistance of flower buds gradually decreases with phenological development in spring. Therefore, spring frost events that occur after the beginning of the growing season pose a major risk to fruit trees. An analysis of the probability of frost events in Slovenian cherry orchards was performed based on historical temperature data from the E- OBS database and climate model projections, in particular regionally downscaled EURO-CORDEX projections (ensemble of 6 models) for scenarios RCP4.5 and RCP8.5. The presented analysis is based on two phenological models for calculation of budburst - the growing degree days (GDD) model and the BRIN model. The projections showed an overall increase in frost risk for the majority of models and all selected sweet cherry varieties during the periods 2011–2040 and 2041–2071 compared to the reference period 1981–2010. For the end of the century (period 2071–2100), all of the ensemble projections showed a large increase in frost risk for the analyzed sweet cherry varieties. The projected increase in frost risk under the RCP4.5 scenario was calculated to be the highest for the Early Bigi variety, while under the RCP8.5 scenario the largest increase was calculated for the Germersdorf variety - a more than 40-fold increase in spring frost risk compared to the reference period.
Compound droughts in Switzerland under current and future climate
Authors: Martius Olivia , von Matt Christoph , Gudmundsson Lukas , Muelchi Regula
Published: July 2023

Periods with very low discharge, anomalously low precipitation or anomalously low soil moisture content are all considered droughts, although different types. The differentiation is relevant from an impact perspective. For example, low discharge (hydrological drought) is challenging for transportation and fish, low precipitation (meteorological drought) is challenging for energy production and agriculture, and low soil moisture for agriculture and soil subsidence. If the different types of droughts occur simultaneously impacts may compound, e.g. if discharge is low irrigation water can no longer be taken from rivers.
We quantify the co-occurrence of the three different drought types in Switzerland in the extended summer season under current and future climate conditions using the Swiss climate change scenarios (CH2018, CH2018-hydro). These scenarios are a set of 44 GCM-RCM model chains based on CMIP5. Temperature and precipitation information from these scenarios is then used to run a hydrological model for more than 80 catchments in Switzerland to generate discharge time-series but select only catchments that are not strongly influenced by glaciers and snow melt.
Compound drought days are prevalent under current climate conditions both north and south of the Alps (on average more than 3 days per year).  Compound drought days tend to affect several catchments across the country at the same time and the simultaneously affected area increases with climate change. We find a significant and substantial (more than a doubling) increase in the number of compound drought days in all catchments both north and south of the Alps under RCP8.5 forcing conditions. Under an effective mitigation forcing (RCP2.6) the increase is not significant.
Everything could be science communication tool
Authors: Špoler Čanić Kornelija , Grljak Ivana
Published: July 2023

In this work, we would share our experience in science communication through various (un)conventional tools that we have utilized over the past five years. While some of these tools may seem familiar, such as promotional materials with logos like umbrellas and ties commonly used by firms for their clients, we have strived to imbue them with additional value as communication tools for promoting the work of DHMZ and educating the public. Additionally, we have created several videos, ranging from homemade productions using freely available online tools to professional videos crafted by students from the Academy of Dramatic Arts.
One of the main challenges we encountered during video production was communicating that the activities of DHMZ are not limited to weather forecasting, but also encompass research and services that may not be as visible to the general public but are integral to a wide range of human activities. Starting in 2019, we also began publishing a calendar. Initially, the idea was to showcase stunning photographs from Croatian photographers who participated in the WMO competition. However, over time, the calendar has evolved into a powerful communication tool.
This year, we have also produced a brochure. While our initial intent was to simply highlight our work, the brochure has transformed into a comprehensive monograph filled with additional information about our research activities and results. The brochure, also, bridges the offline and online worlds by utilizing QR codes that guide readers of the printed brochure to content on the website.
We believe that effective science communication is crucial in bridging the gap between scientific knowledge and its impact on society, and we are committed to exploring innovative ways to effectively communicate the value of our work to diverse audiences.
Revisiting HISTALP Precipitation dataset
Authors: Chimani Barbara , Bochniček Oliver , Brunetti Michele , Ganekind Manfred , Holec Juraj , Izsák Beatrix , Lakatos Mónika , Perčec Tadić Melita , Manara Veronica , Maugeri Maurizio , Stastny Pavel , Szentes Olivér , Zardi Dino
Published: July 2023

HISTALP is a long-term climatological database for the Greater Alpine Region, including monthly data of precipitation, temperature, sunshine duration and air pressure. The activities leading to this dataset started in 1997 with the final database being in place in 2003. Since then annual updates of the data are done. The dataset is freely available for research and education and frequently used in different climate related studies.
Due to the long existence of the HISTALP dataset, a new homogenisation activity was due in order to ensure the homogeneity of the updated time series. This was done in the course of the creation of a new version of the gridded precipitation dataset of the Greater Alpine region (LAPrec, https://surfobs.climate.copernicus.eu/dataaccess/access_laprec.php) within an international Copernicus project. Before starting the homogenisation activity, the existing data was revisited and an exchange with the data owners on the original data took place. This lead to corrected, historical original data as well as to the replacement of some stations used in HISTALP. Homogenisation was mainly done within the four climate regions of HISTALP (www.zamg.ac.at/histalp), with some special networks e.g. for especially long time series. The results were compared to the former version of homogenised HISTALP-precipitation data as well as to national homogenised datasets.
The analyses of the resulting dataset on trends and data range support the idea of a generally good quality of the homogenisation. For all comparisons with other homogenised datasets the timing of the homogenisation had to be taken in to account, additional differences were to be expected due to the availability and selection of reference series, choice of homogenisation method and availability of metadata (especially for interactive methods). The results of the comparison show that in the national homogenisations more breaks were detected than in the HISTALP one. This was to be expected due to the higher number of highly correlated reference series. Overall, the comparison gives confidence in the HISTALP dataset and its homogenisation. Nevertheless, for a small number of stations strong differences between the different homogenisations have been detected. Those will be assessed by a future step.
Climate data for use in building design – Past and Future weather files for overheating risk assessment in Ireland.
Authors: Griffin Seánie , Lambkin Keith , Mateus Carla
Published: July 2023

Met Éireann recently concluded a project to update climate maps and data to support building design standards and perform risk assessments for overheating of buildings. One of the work packages in this project focused on the production of representative weather files for building energy modelling. These are input files containing 365 days of hourly data from a range of weather variables that have the potential to have an impact on the ambient conditions within a building, such as temperature, humidity, solar radiation, wind and pressure. They come in the form of Test Reference Years (TRY), which capture average climatic conditions, and Design Summer Years (DSY), which represent hot summer with overheating events. These were produced at six Irish locations.
Established methodologies were followed for the calculation of past weather files based on hourly observations at synoptic weather stations/airports, with a TRY and 3 DSYs selected at each location. A standardised set of Irish climate projections produced by the TRANSLATE project was used to generate future weather files for a range of future climate scenarios. It is a multi-model ensemble comprising of EURO-CORDEX simulations and higher resolution regional projections produced by the Irish Centre for High-End Computing (ICHEC). TRANSLATE contains 27 different climate scenarios, formed from 3 different time periods, 3 emission scenarios and 3 model sensitivities. The “delta-change” methodology was employed to produce the files at the required hourly resolution, with a TRY and 3 DSYs produced for each future climate scenario.
These data will enable Irish building designers to make more informed decisions regarding the risk of overheating, both for current conditions and the potential changes that will occur due to the warming climate.
Mapping of radar-based heavy rainfall risk in Germany for assessing the impact of extreme precipitation events
Authors: Walawender Ewelina , Lengfeld Katharina , Winterrath Tanja , Weigl Elmar
Published: July 2023

In a currently changing climate the frequency of extreme rainfall events in Central Europe is expected to alter, even despite dry episodes will be more common. Heavy rainfall with its dynamic and sometimes unpredictable character can provoke numerous hazards, like flash-floods, landslides and soil erosion, causing damages and huge economic costs, as well as direct threat to human life. Thus, it is important to not only monitor current rainfall events and warn against their occurrence, but also to understand the possible impact each event may provoke and provide communities with information on risked areas.
The aim of this study is to evaluate an overall heavy rainfall risk for the area of Germany. Following the IPCC definition of risk, we consider its three main determinants: hazard, exposure and vulnerability.
At first, two radar-based datasets have been used to map overall heavy rain hazard: the high-resolution radar climatology RADKLIM and the Catalogue of Radar-based Heavy Rainfall Events (CatRaRE), both developed by the Deutscher Wetterdienst (DWD) and currently available for the last 22 years (2001-2022). Frequency and hot-spots of past heavy rainfall events have been investigated e.g. based on their return period, extremity or area.
In order to determine the exposure, imperviousness degree and topographic position index (TPI) are combined together. For the monitoring of current risk, data on antecedent precipitation and soil moisture are additionally incorporated. Finally, potential vulnerability has been estimated on the basis of socioeconomic factors and past losses.
In addition, by combining the meteorological and non-meteorological variables of all past CatRaRE events together with data on insurance losses or fire-brigades’ operations, the impact of analogue upcoming events could be defined.
We will present the first results of a heavy rainfall risk mapping for the area of Germany, including all three risks components: hazard, exposure and vulnerability. We will also give examples of using the risk map as a basis for assessing the impact of operationally detected and/or predicted precipitation events.