OSA2.2 | Agricultural and Forest Meteorology
Agricultural and Forest Meteorology
Convener: Branislava Lalic | Co-convener: Josef Eitzinger
| Thu, 07 Sep, 09:00–12:45 (CEST)|Lecture room B1.08
| Attendance Thu, 07 Sep, 16:00–17:15 (CEST) | Display Wed, 06 Sep, 10:00–Fri, 08 Sep, 13:00|Poster area 'Day room'
Orals |
Thu, 09:00
Thu, 16:00
Weather conditions directly influence agricultural yields. Hail, disease and drought can have devastating effects on crops. However meteorological-related risks can be reduced through better timing of harvests, application of pesticides or through use of irrigation systems. A clear picture of current and future weather conditions, along with appropriate farm actions, can increase the likelihood of improved yields.

Climate change also influences crop suitability in certain regions where livestock can be negatively affected by migrating diseases and available food. To complicate matters the agricultural sector is also trying to become more sustainable and environmentally friendly in an attempt to meet greenhouse gas emission targets.

This session intends to examine our increasing knowledge of agricultural meteorology, while also attempting to identify opportunities in our changing environment.

We invite presentations related but not limited to:
• Agrometeorological modelling (e.g. modelling agrometeorological related diseases, frost protection warning methods, drought indices etc.)
• Impact of weather and climate extremes on agriculture
• Methods of measurements and observations (e.g. ground based equipment, remote sensing products, citizen science, Big Data etc.)
• Decision support systems & the representation of uncertainty
• Interactions/feedback of farmers and other end users
• Use of future climate projections on agrometeorological models

Orals: Thu, 7 Sep | Lecture room B1.08

Chairpersons: Branislava Lalic, Josef Eitzinger
Onsite presentation
Josef Eitzinger, Sabina Thaler, Aitor Atencia, Patrick Hann, Gerhard Kubu, Ahmad M. Manschadi, Branislava Lalic, Marlene Palka, Stefan Schneider, Ana Firanj Sremac, Miroslav Trnka, and Claus Trska

Optimization of agricultural inputs in all relevant spatial and time scales by means of smart and precision farming options is considered in the project of AGROFORECAST as crucial for ensuring sustainable and resilient production in agriculture, protecting ecosystem services, enhancing biodiversity and food security as well as socio-economic conditions for the farmers. Despite increasing appreciation of the potential value of weather forecasts for agriculture, there is still a gap between what scientists consider as “useful” information and what users (e.g. farmers, advisory services, policy makers) recognize as “usable” in their decision-making processes. 

The main objective of this project was to combine stakeholder-tailored agrometeorological tools/indicators and weather forecasting of different lead times that can be used for optimizing agricultural decision-making in the face of changing climate and climate variability. A focus is laid on efficient use of inputs for crop production (water, fertilizer, agricultural chemicals) needed for smart and precision farming options while protecting (agro-) ecosystem resources and functions in order to identify suitable and, from a stakeholder perspective, acceptable adaptation and mitigation options. Beside the optimization/downscaling of seasonal forecasts, software applications (crop model and GIS-based spatial tool) for forecasting agrometeorological conditions by indicators were further developed and tested (incl. stakeholder involvement) against performance strengths and weaknesses/limitations at various locations and farmers field site. The results show that the performance of the applied tools and indicators depend mainly on a) weather forecast lead time b) regional climate conditions and c) type of impact indicators. Applications for crop management are promising in order to mitigate climate change impacts, cropping risks and negative environmental impacts in crop production (e.g. through reduced N-fertilization). Additionally, results of applications under ÖKS15 climate scenarios for selected case study sites were achieved.

How to cite: Eitzinger, J., Thaler, S., Atencia, A., Hann, P., Kubu, G., Manschadi, A. M., Lalic, B., Palka, M., Schneider, S., Sremac, A. F., Trnka, M., and Trska, C.: Tailored AGROmeteorological FORECAST for improving resilience and sustainability of Austrian farming systems under changing climate, EMS Annual Meeting 2023, Bratislava, Slovakia, 4–8 Sep 2023, EMS2023-213, https://doi.org/10.5194/ems2023-213, 2023.

Onsite presentation
Milena Marcic and Branislava Lalic

Meteorological conditions significantly impact the biofix, i.e., the time of the first flight of the first overwintering generation of codling moth (Cydia pomonella). In general, the flight activity of codling moths is influenced by a combination of temperature, humidity, and light duration and intensity, while precipitation and strong wind, particularly wind gusts, can stop insects from flying. Our research also considered the impact of atmospheric pressure on codling moth flight. 

Data describing biofix used in this study come from the codling moth monitoring in the framework of the PIS observing system. For sixteen locations during the 2012-2022 period, only 101 data sets were analyzed for the locations with the same traps and female pheromones. Since the traps were located in production orchards, to avoid the impact of insecticides on possible errors in the first detection of adults, only locations with a high insect population (with over 100 adults per trap during the season) were selected. Counting is performed daily from the beginning of April each year. Meteorological data for the study are provided from two sources: a) the PIS network of automated weather stations located in the orchards (air temperature and humidity, precipitation), and b) the synop reports from the synoptic stations (atmospheric pressure and wind gust).

Our research aims to measure biofix's uncertainty caused by adverse weather conditions (from the codling moth point of view) or events. Starting backward from when an adult is found in the trap, we analyzed the presence of weather conditions that can affect codling moth flight. As a measure of uncertainty, we use the days between trap ketch day and the last day before that when weather conditions allowed adults to fly.

How to cite: Marcic, M. and Lalic, B.: Spatial uncertainty of codling moth biofix caused by adverse weather events, EMS Annual Meeting 2023, Bratislava, Slovakia, 4–8 Sep 2023, EMS2023-566, https://doi.org/10.5194/ems2023-566, 2023.

Onsite presentation
Pierluigi Calanca, Thomas Toschini, and Chloé Wüst-Galley

In Switzerland, as elsewhere in Europe, recurrent drought has been one of the main concerns of the agricultural sector during the last few decades. The dry years of 2003, 2006, 2015, 2018 and again 2022 had serious impacts on forage production. As a result, additional imports were necessary to support in particular the dairy sector. Another consequence of the drought was an increase in the need for irrigation, which, however, could not always be met. Eventually, farmers had to accept restrictions on water withdrawals on several occasions. Climate change projection indicate that such situations could become more common in future.

To increase preparedness and help the agricultural sector, as a whole, better cope with drought under future climatic conditions, quantitative information on drought occurrence at regional to national scale is required. In this contribution, we present a drought assessment for Switzerland that addresses the following questions: (i) Spatial patterns of drought. What was the geography of drought events in the recent pat? Can we expect similar geographic patterns in the future? (ii) Seasonality and persistence of drought. Has there been a shift the temporal characteristics of drought because of climate warming? Are further shifts likely to occur in future? (iii) Irrigation requirements: Has the need for irrigation already increased in the recent past? If yes, where and by how much? What can be expected in this respect for the coming decades?

We base our analysis on high-resolution, gridded meteorological data and climate change projections, and use drought indices to characterize drought events in time and space. We further show how a simple model that relates irrigation requirements to a drought index can be employed to estimate current and future needs across Switzerland. Finally, we discuss how these results can be integrated in initiatives aiming at supporting farmers in the process of adaptation.

How to cite: Calanca, P., Toschini, T., and Wüst-Galley, C.: Spatial patterns and seasonality of drought in Switzerland under present and future climatic conditions, and irrigation water requirements, EMS Annual Meeting 2023, Bratislava, Slovakia, 4–8 Sep 2023, EMS2023-165, https://doi.org/10.5194/ems2023-165, 2023.

Onsite presentation
Marcio dos Reis Martins, Christof Ammann, and Pierluigi Calanca

Grasslands deliver a range of ecosystem services to society that are potentially threatened by climate change. Assessing climate change impacts on grassland ecosystem services is essential for developing adaptation strategies. This is particularly important for a country like Switzerland, in which grasslands represent about two thirds of its agricultural land. Among grassland ecosystem services, fodder production (provisioning) and soil carbon sequestration (regulating) are most vulnerable to drought and other extreme events. Process-based ecosystem models, such as DayCent, are suitable tools for assessing concomitant impacts of climate change on different ecosystem services. DayCent simulates fluxes of C and N among the atmosphere, vegetation, and soil and allows the prediction of the effect of increasing temperature and CO2 levels and decreasing rainfall on herbage growth and soil carbon stocks. We have been using DayCent to simulate the dynamics of herbage growth and soil organic carbon pools with varying degree of stability in managed permanent grasslands in Switzerland. For the present study, we selected an experimental grassland site located at Oensingen, Canton of Solothurn. We calibrated DayCent using inverse modeling (PEST tool) and verified the model performance based on several years of field data. We then applied the model to examine how future shifts in climatic conditions are likely to affect yields and carbon stocks, and what are the associated uncertainties. For this exercise, we developed local climate change scenarios using a stochastic weather generator (LARSWG). After reviewing the results, we discuss how process-based modeling can contribute for development of climate-smart agriculture tools, which can support better definition of agricultural policies and payment systems for grassland ecosystem services.

How to cite: dos Reis Martins, M., Ammann, C., and Calanca, P.: Assessing the impact of climate change on grassland ecosystem services using DayCent, EMS Annual Meeting 2023, Bratislava, Slovakia, 4–8 Sep 2023, EMS2023-259, https://doi.org/10.5194/ems2023-259, 2023.

Onsite presentation
Victor Cicuéndez, Carlos Yagüe, Rosa Inclán, Enrique P. Sánchez-Cañete, Carlos Román-Cascón, and César Sáenz

Mediterranean grasslands provide different ecosystem, social and economic services to the Mediterranean basin. Their dynamics are conditioned by the influence of the Mediterranean climate, which results in large inter-annual variability. Gross Primary Production (GPP) represents the carbon (C) uptake of ecosystems through photosynthesis, being the largest flux of the global C balance. Hence, GPP estimations are necessary to assess the dynamics of the global C cycle and to plan a sustainable management of these ecosystems. The study of grasslands GPP must be approached from a dynamic point of view, that is, temporal evolution at different spatial scales.

High frequency satellite data, such as Sentinel-2, have open the door to study ecosystems with a high spatial (10, 20 and 60 m) and temporal resolution (5 days). Although extensive research exists about estimating GPP in grasslands with moderate resolution sensors, such as MODIS, the estimation of GPP in this ecosystem type using Sentinel-2 images is relatively new, especially in Mediterranean sites. The GPP derived from remote sensing data must be evaluated at field scales using eddy covariance (EC) measurements from flux towers. Time series analysis (TSA) represents an excellent tool to analyze high temporal resolution data, such as EC and remote sensing data. Although TSA has been widely used in economics, it is not commonly used for the analysis of environmental variables, such as GPP.

The overall objective of this research is to estimate a GPP model for a Mediterranean grassland in central Spain close to a forest influenced by the Guadarrama mountains (El Escorial, Madrid). This is done using Sentinel-2 vegetation indices and meteorological field information obtained from a GuMNet micrometeorological station where all the surface energy balance (SEB) components (and other meteorological and soil variables) are available for several years. The specific objectives are: (1) To compare different vegetation indices to estimate GPP through the ecosystem light-use efficiency model; (2) To estimate the influence of different meteorological variables on the model; (3) To validate the remote sensing model with the measurements from an EC flux tower (GuMNet-Herrería) in terms of quantity and dynamics through time series analysis.

Some preliminary results indicate how the GPP depends strongly on the vegetation indices and on meteorological and soil variables, being the soil water content a relevant one. This approach allows to model GPP based on the information from this analysis.

How to cite: Cicuéndez, V., Yagüe, C., Inclán, R., Sánchez-Cañete, E. P., Román-Cascón, C., and Sáenz, C.: Modelling Gross Primary Production of a Mediterranean grassland using Sentinel-2 vegetation indices and meteorological field information, EMS Annual Meeting 2023, Bratislava, Slovakia, 4–8 Sep 2023, EMS2023-323, https://doi.org/10.5194/ems2023-323, 2023.

Coffee break
Chairpersons: Branislava Lalic, Josef Eitzinger
Onsite presentation
Peter K. Musyimi, Abderrahmane Mendyl, Agustiyara Agustiyara, Balázs Székely, and Tamás Weidinger

Kenya has had five failed rain seasons for the last three years. In this context, there was a mass recurrent crop failure, death of livestock and wildlife, persistent water scarcity, and droughts of varying intensities. There have been a lot of challenges in assessing climate change and variability impacts in Kenya due to limited data sources. Further, assessing the local and regional effects on the hydrological cycle, food security, and available water resources remains a great regional threat. Reference evapotranspiration,  is the evaporative power climatic parameter of the atmosphere, vital for water budgets on the land surface. The study’s main goal was to analyze hourly reference evapotranspiration,  from two climatic regions using single levels ERA5 hourly dataset from 2000 to 2022. The dataset was sought from three stations from, arid, and semi-arid savannah tropical conditions regions (Voi Garissa, and Mombasa) with elevations between 57 m to 579 m, and three (Trans-Nzoia, Nyeri, and Embu) sought from humid Kenya highlands (>1350 m). Reference Evapotranspiration was calculated using Penman-Monteith (FAO56), the standard methodology developed by Food and Agriculture Organization. Results from 5 years (2018 to 2022) in Taita-Taveta County indicated that  ranged from 0.17±0.2 mm/hour in 2020 to 0.22±0.2 mm/hour in 2022. Daily averages were 4.17±1.2 mm./day to 5.2±1.1 mm/day in 2020 and 2022 respectively. The mean monthly and   was highest in March with an estimated value of 159.7±53.7 mm/month while the lowest was 120±15 mm/month in December. This is because March falls at the onset of the long rainy season in Kenya where precipitation is high while December is the last month of the short rainy season when precipitation reduces significantly. These results are vital because they enhance comparisons of the spatial climatological patterns and variability of seasonal precipitation about the evaporative power and demand variation across regions. Further, it will necessitate investigations of uncertainties from the datasets for better decision-making after comparisons with analysis from field meteorological datasets and soil moisture data measurements currently being carried out in Kenya.  Further comparison of the results with reference evapotranspiration from the original station and the Global Land Evaporation Amsterdam Model dataset will also be investigated.

How to cite: Musyimi, P. K., Mendyl, A., Agustiyara, A., Székely, B., and Weidinger, T.: Hourly reference evapotranspiration analysis using synoptic meteorological measurements and ERA5 reanalysis data from Kenyan Counties, EMS Annual Meeting 2023, Bratislava, Slovakia, 4–8 Sep 2023, EMS2023-331, https://doi.org/10.5194/ems2023-331, 2023.

Onsite presentation
Lucas Hulsman, Bert Heusinkveld, Marc Ravesloot, and Gert-Jan Steeneveld

Trees provide cooling services in urban areas in summer. Which tree species are suitable in cities in a future climate remains an open question. One of the criteria for tree species selection is winter hardiness. Winter hardiness is an indicator of the lowest temperatures that plants typically experience in an area. The United States Department of Agriculture (USDA) defines winter hardiness as the average annual minimum temperature. Hence, it is a straightforward and commonly used indicator to predict the likelihood of certain plants to experience frost damage in winter. The most recent winter hardiness map for Europe was made in 1984, and does not include the climate change from the past decades, and neglects the urban heat island effect (UHI) that causes warmer winters in urban areas, impacting winter hardiness. In this study, we developed an updated and downscaled version of the European winter hardiness maps using minimum temperature from the ECA&D E-OBS dataset version 26.0, and the European Local Climate Zone (LCZ) map with a 100x100m resolution.

The new maps represent the winter hardiness for five standard normal periods between 1951 and 2020, and represent the years 2030, 2050, and 2085 for the Netherlands using four climate scenarios. These maps show how hardiness zones have moved to the north and east over the past decades. They show that roughly 60% of Europe is now in a different hardiness zone compared to the 1951-1980 average, potentially allowing new tree species to flourish here. They also indicate that the Netherlands can move up to three hardiness zones between the present and 2085. Furthermore, these maps show that many urban areas are in different winter hardiness zones compared to the rural surroundings, which has additional consequences for the tree species that are able to flourish in urban environments.

How to cite: Hulsman, L., Heusinkveld, B., Ravesloot, M., and Steeneveld, G.-J.: Updated and downscaled European winter hardiness maps including Urban Heat Island effects for urban tree species selection., EMS Annual Meeting 2023, Bratislava, Slovakia, 4–8 Sep 2023, EMS2023-374, https://doi.org/10.5194/ems2023-374, 2023.

Online presentation
Laurynas Klimavičius

False spring is one of the preconditioned compound climate events that gained a lot of attention in recent years because of its negative impact on agriculture, fruit trees, damage to native forests, and reduction of carbon uptake. The aim of this research is to identify these events in the eastern part of the Baltic Sea region during the spring months from 1950 to 2022 and to assess their frequency, intensity and potential damage to agriculture. To do that, the date of the last spring frost (LSF) as well as the date of the start of the growing season (SGS) were found for each cell of analysed territory for each year. In this study the SGS for a particular year was defined as the first day in a period of six days when the average daily temperature (Tavg) during all these six days was at least +5.0 °C. Meanwhile, the LSF date was determined when the minimum daily air temperature (Tmin) in April-June dropped below 0°C for the last time during a particular year. Daily Tavg and Tmin data that was needed to determine SGS and LSF dates were obtained from European Centre of Medium-range Weather Forecast ERA-5 reanalysis dataset with a spatial resolution of 0.25° x 0.25°. In this study, a false spring was identified at the corresponding point of the study area if the last spring frost was identified after the start of the growing season. The study showed, that at the end of the analysed period (1950–2022), the growing season started earlier in the entire study area. This change ranged from -0.5 days per decade in the northeastern part of the study area to -2.1 days per decade in the western part of Lithuania. The LSF date during the 73-year study period has also become earlier in almost all study area points. The largest changes (-1.8 days per decade) were observed in the northern and northeastern part of the analysed territory. However, the changes of LSF date were not as rapid as those of the SGS. Therefore, during the study period, the number of false spring cases increased in 73.76% of the study area. The largest growth of such cases was observed in the eastern part of the study area and in coastal regions. There was also an increase in the amount of accumulated heat from the SGS date to the LSF date. Positive changes were found in 82.76% of the study area points, with the largest ones occurring at the border between Lithuania and Kaliningrad and in the eastern part of the study area.

How to cite: Klimavičius, L.: False spring events in the eastern part of the Baltic Sea region, EMS Annual Meeting 2023, Bratislava, Slovakia, 4–8 Sep 2023, EMS2023-438, https://doi.org/10.5194/ems2023-438, 2023.

Onsite presentation
Philipp Weihs, Sabina Thaler, Josef Eitzinger, Shokufeh Zamini, Karl Berger, and Mahnaz Abdollahi

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.

How to cite: Weihs, P., Thaler, S., Eitzinger, J., Zamini, S., Berger, K., and Abdollahi, M.: Influence of PV modules on the incident radiation and the yield of 3 plant varieties., EMS Annual Meeting 2023, Bratislava, Slovakia, 4–8 Sep 2023, EMS2023-442, https://doi.org/10.5194/ems2023-442, 2023.

Onsite presentation
Péter Szabó, Rita Pongrácz, and Judit Bartholy

Global warming has a significant impact on global food production, including grapes used for winemaking. European vineyards, in particular, are at risk due to changing climatic conditions affecting the grapevine growth cycle, disease outbreaks, and extreme weather conditions.

In the current research, we use the bioclimatic Huglin-index over all 22 wine regions in Hungary to assess the observed heat sums available for grapes, which correlates with sugar content (highly) and yields (significantly). Furthermore, we analyse the spring frosts after the vegetation period started affecting blooming, the heat stress over summer heatwaves affecting grape quality, and other minor climatic conditions as well. For this matter, high-resolution and homogenized daily observations are used from 1971 covering the Carpathian Basin. Results suggest that in the last 50 years, already a 27% increase was detected on average in the heat sums available for grapes, which has already started to have an impact on changing the varieties of grapes in some regions.

For the future, the Euro-CORDEX regional climate simulations offer valuable insights into expected changes in climatic patterns in Europe. These changes of the less-mitigation RCP4.5 and non-mitigation RCP8.5 scenarios are likely to result in earlier ripening, lower acidity, increased alcohol content, and higher susceptibility to pests and diseases, leading to reduced yields and smaller berries due to water stress. With immediate mitigation of RCP2.6 scenario, adaptation strategies could be avoided, such as selecting heat-tolerant grapes, changing of cultivation management, or changing vineyard locations to cooler climates. However, these measures require substantial investment and may not be feasible for all wine producers.

How to cite: Szabó, P., Pongrácz, R., and Bartholy, J.: The impacts of climate change on the Hungarian wines, EMS Annual Meeting 2023, Bratislava, Slovakia, 4–8 Sep 2023, EMS2023-538, https://doi.org/10.5194/ems2023-538, 2023.

Online presentation
Denise Assmann, Falk Böttcher, Thomas Leppelt, Thomas Kreuter, Florian Eißner, Enrico Thiel, Johannes Döhler, Michael Grunert, Hardy Pundt, and Roksolana Pleshkanovska

Within the R&D project StaPrax-Regio, highly efficient N-stabilized fertilization strategies are identified based on site-specific agrometeorological and soil characteristics. Derived strategies will be transferred to fertilization practice using innovative advisory tools. The aim of the project is a significantly improved utilization of the diverse and complex beneficial effects of N-stabilized fertilization (e.g. reduction of N losses, improved N availability in soil, promotion of root growth, improvement of seedling development) to optimize fertilizer N efficiency. Currently, this has been insufficiently achieved for winter cereals. However, the previous project StaPlaRes demonstrated that a significant increase in N use efficiency can be achieved by an optimized adaptation of N-stabilized fertilization strategies to site-specific soil and weather conditions.

The Deutscher Wetterdienst prepares agro-meteorological analyses for 85 test fields with different winter grain types in Germany: based on long-term measurements such as air temperature and precipitation as well as based on modeling with the agro-meteorological models AMBAV (AgrarMeteorologische Berechnung der aktuellen Verdunstung) and BEKLIMA (BEstandsKLIMA) for e.g. soil moisture and soil temperature. Thus, more differentiated statements about the dependencies of plant development on agro-meteorological conditions are achieved. In addition to the model evaluation with measurements ​during the project, the model data and the site analyses are used to generate regionalized statements on e.g. temperatures, precipitation and phenological development during the main fertilization period. In combination with parallel soil and plant cultivation analyses, highly efficient site-specific fertilization strategies will be identified. For this purpose, existing consulting tools (e.g. BESyD) and GIS-based maps will be used and developed further. In order to take seasonal influences into account, an agro-meteorological model is currently developed in the AMBER environment, which should serve as an additional agro-meteorological decision-making aid at an early stage (if possible a few weeks) before each upcoming fertilization application.

How to cite: Assmann, D., Böttcher, F., Leppelt, T., Kreuter, T., Eißner, F., Thiel, E., Döhler, J., Grunert, M., Pundt, H., and Pleshkanovska, R.: Nitrogen stabilization in fertilization practice: optimization by regionalization based on meteorological and edaphic parameters, EMS Annual Meeting 2023, Bratislava, Slovakia, 4–8 Sep 2023, EMS2023-3, https://doi.org/10.5194/ems2023-3, 2023.

Online presentation
Dmitry Chechin, Mirseid Akperov, and Alexander Timazhev

Among natural disasters, droughts cause the most damage and losses to the agricultural sector in Russia. Measures to minimise the damage caused by droughts depend on timely and accurate prediction of droughts. Seasonal prediction of droughts is challenging due to the non-linearity of processes in the coupled atmosphere-land system. For the same reason, it is expected that Artificial Intelligence (AI) methods may be superior to traditionally used statistical methods for drought prediction. The aim of this work is to apply and evaluate different methods of AI for seasonal drought prediction over European Russia. Several indices are used to identify droughts, such as the Standardised Precipitation Index (SPI), the Standardised Precipitation Evapotranspiration Index (SPEI) and the Selyaninov hydro-thermal coefficient (HTC). The latter index is traditionally used in agricultural meteorology in Russia and its relation to the production of various crops is well established. The indices are calculated for the period 1958-2022 using ERA5 reanalysis data. A set of predictors includes several indices characterising the large-scale atmospheric circulation over northern Eurasia (e.g. NAO, AO and others), as well as the ENSO index and the sea surface temperature anomaly over the North Atlantic. Several AI methods are used to predict the values of the drought indices based on the set of predictors for different lead times ranging from two weeks to several months. Prediction is made separately for each of the administrative regions in the European Russia with a special focus on those regions where droughts cause most damage. Another focus of the study is the relationship between droughts and atmospheric blocking events and heat waves. The application of the used AI methods for heat wave prediction is discussed.

How to cite: Chechin, D., Akperov, M., and Timazhev, A.: Seasonal prediction of droughts over European Russia using artificial intelligence methods, EMS Annual Meeting 2023, Bratislava, Slovakia, 4–8 Sep 2023, EMS2023-550, https://doi.org/10.5194/ems2023-550, 2023.

Posters: Thu, 7 Sep, 16:00–17:15 | Poster area 'Day room'

Display time: Wed, 6 Sep 10:00–Fri, 8 Sep 13:00
Chairperson: Josef Eitzinger
Branimir Omazić, Marko Kvakić, Maja Telisman Prtenjak, and Josip Meštrić

Due to the increase in temperature in recent decades, the onset of the phenological phase in the grapevine is also getting earlier. Earlier occurrences of phenological phases make the vines more vulnerable to frost, increase the risk of temperature stress in the last stages of development, and affect the quality of the final harvest. Considering that the temperature will continue to rise in the future, further changes in the phenological cycle of the vines are also expected. Therefore, it is important to model the future appearances of phenological phases as accurately as possible. One of the ways to succeed in this is to use the crop model, such as the STICS (Simulateur mulTIdisciplinaire pour les Cultures Standard) model. STICS model has been developed since 1996 at INRA and has been widely used for grapevine phenology prediction.

In this research, the STICS model is coupled with daily output from climate models; three CORDEX Regional Climate Models’ (RCMs) simulations (CLMcom-CCLM4-8-17, SMHI-RCA4, CNRM-ALADIN5.3) for Croatian domain and varieties. All RCMs are forced by output from Global Climate Models (GCMs) with a moderate (RCP4.5) and a high-end (RCP8.5) greenhouse gas (GHG) scenarios. SMHI-RCA4 is driven by five different GCMs (CNRM-CERFACS-CNRM-CM5, ICHEC-EC-EARTH, IPSL-IPSL-CM5A-MR, MOHC-HadGEM2-ES and MPI-M-MPI-ESM-LR), CLM by four (CNRM-CERFACS-CNRM-CM5, ICHEC-EC-EARTH and MOHC-HadGEM2-ES, MPI-M-MPI-ESM-LR), and CNRM-ALADIN5.3 with one (CNRM-CERFACS-CNRM-CM5). All the simulations have horizontal grid spacing of 0.11◦. Phenological phases in the STICS model, for 4 cultivars (Graševina, Plavac Mali, Chardonnay, and Merlot) were parameterized using meteorological measurements and observations of phenological phases. Once satisfactory results have been obtained in the present climate, the STICS model was used to study the differences in the occurrence of phenological phases in the future climate compared to the controlled period 1971-2000. The results show that a shift in phenological phases is expected in the future, regardless of the cultivar. The robustness of future changes depends on the localization analyzed.

How to cite: Omazić, B., Kvakić, M., Telisman Prtenjak, M., and Meštrić, J.: Future shifting of grapevine phenological phases: Simulation using STICS model, EMS Annual Meeting 2023, Bratislava, Slovakia, 4–8 Sep 2023, EMS2023-64, https://doi.org/10.5194/ems2023-64, 2023.

Lenka Hájková, Veronika Oušková, Vojtěch Vlach, Adéla Musilová, and Martin Možný

Global climate change impacts are already monitored in ecosystems and they reveal e.g. earlier onset of spring stages and lengthening plant growing season. However, available results are mainly based on the study of wild plants, whereas only a few studies are devoted to agricultural crops. In this study, phenological data have been used to interpret the influence of climate change on phenological stages of winter wheat, spring barley, Norway maple and lime tree to compare the influence of climate change on field and forest plants and distinguish the influence of farming practices from real climate. So far, not many studies dealt with comparison of phenological shifts between agricultural crops and wild plants. The analyses were focused mainly on subsequent stages: tillering (BBCH 21) in spring barley, heading (BBCH 55) in winter wheat, first leaves (BBCH 11) in Norway maple and beginning of flowering (BBCH 61) in lime tree. The aims of this paper were to calculate the trend in phenological development of winter wheat, spring barley, Norway maple and lime tree in the period 1961–2022 in different climatic zones of the Czech Republic and find out the difference between field crops and wild plants. Mann-Kendall test and Geographic Information system were used. The results showed most significant acceleration of the first leaves in Norway maple up to -28.9 days per period and beginning of flowering in lime tree up to -28.7 days per period. In field crops, the acceleration by heading in winter wheat was up to -13.7 days per period and by tillering in spring barley it was up to -11.6 days per period. A significant trend was found especially in the middle altitudes.

Key words: spring barley, winter wheat, Norway maple, lime tree, BBCH

How to cite: Hájková, L., Oušková, V., Vlach, V., Musilová, A., and Možný, M.: Differences in the shift of phenological phases of field crops and wild plants in the Czech Republic from 1961 to 2022  , EMS Annual Meeting 2023, Bratislava, Slovakia, 4–8 Sep 2023, EMS2023-203, https://doi.org/10.5194/ems2023-203, 2023.

Ivana Krčová, Maroš Turňa, Jozef Rozkošný, Gabriela Ivaňáková, Lívia Labudová, Jakub Ridzoň, and Katarína Mikulová

The aim of this work was the analysis of the occurrence of drought, which was determined by the deficit of precipitation and the deficit of soil moisture in the time period 2015 till 2021 in the Orava region, in the comparison with the extent of damage caused by the drought and important biotic pests on the adult forests, which had been registered by the foresters of the Lesy SR, the state corporation. The Orava region was chosen because of the long-term spruce forests decline and the occurrence of more severe drought, which had been rare in the past there. The long-term soil water deficit can expressively weaken the forests, what was finally confirmed in our work. The biotic malign factors Ips typographus L., Pityogenes chalcographus L. and Armilaria sp. were chosen for their high multitudes and for their predisposition to continue in the process of the degradation of woods, as the secondary, respectively the tertiary malign factor beside the drought. The condition of forest vegetation has the long-term feedback to the bad availability of soil moisture, which depends on the specific species resistance to the drought stress. The ascertained results confirm the suitability of the chosen methodology for the drought monitoring, because its outputs are in good agreement with the reports of drought impacts by the end employers. The soil water deficit correlates with deficit of precipitation. It was registered, that the occurrence of important biotic pests in the dry periods is more frequent and the warnings and precautions are inevitable.

How to cite: Krčová, I., Turňa, M., Rozkošný, J., Ivaňáková, G., Labudová, L., Ridzoň, J., and Mikulová, K.: Analysis of drought stress in the forests of Orava region during period 2015-2021, EMS Annual Meeting 2023, Bratislava, Slovakia, 4–8 Sep 2023, EMS2023-207, https://doi.org/10.5194/ems2023-207, 2023.

Ivana Krčová, Maroš Turňa, Lívia Labudová, Gabriela Ivaňáková, Jakub Ridzoň, and Juraj Holec

The drought is much discussed phenomena in the latest years, because of its more frequent occurrence and the stronger intensity. For this reason, the monitoring of dry conditions is very important. The Slovak Hydrometeorological Institute (SHMI) monitors the meteorological and soil drought since 2015, and then in 2017, the monitoring of the surface water level and monitoring of the water resources with the drought impacts on the agriculture and forestry was added in 2017. The products are public and freely available on the SHMI webpage. The monitoring aims on the evolution of climatic conditions regarding to the beginning, the development and intensity of drought. The monitoring of meteorological drought is updating on weekly basis and the additional product is the forecast of drought for following 10 days. The used indices are SPEI and SPI. Both indices are calculated using flowing window with accumulation period of 30 days. Nowadays, the monitoring is only for selected 41 meteorological stations, but it is planned to convert it to grid resolution 1 km and on daily basis. The monitoring of soil drought is produced on weekly basis in the cooperation with CzechGlobe, from Brno, Czech Republic. The soil data are computed by SoilClim model in 0.5x0.5 km grid. The one part of soil drought monitoring is the characterisation of drought impacts on local scale. Drought impacts are evaluated in forestry and agriculture by experts. The model results and the answers from questionnaire are annually summarized and compared themselves. In this case the cooperation among experts from various departments is inevitable.

How to cite: Krčová, I., Turňa, M., Labudová, L., Ivaňáková, G., Ridzoň, J., and Holec, J.: Drought monitoring in Slovakia, EMS Annual Meeting 2023, Bratislava, Slovakia, 4–8 Sep 2023, EMS2023-212, https://doi.org/10.5194/ems2023-212, 2023.

Sabina Thaler, Josef Eitzinger, Herbert Formayer, Christian Gützer, Stephan Hörbinger, Valéry Masson, Erich Mursch-Radlgruber, Katharina Perny, Jürgen Preiss, Tobias Pröll, Johann Peter Rauch, Melissa Sadriu, Stefan Schmidt, Robert Schoetter, Debora Szocska, Max Wittkowski, Heidelinde Trimmel, David Wöß, and Philipp Weihs

Heat stress during heat waves in urban areas can have devastating effects on human health. To mitigate this heat stress, major efforts are being made to plant more vegetation and remove sealed surfaces. But many green roofs and facades are not irrigated, which in turn leads to drought stress for plants during prolonged periods of heat in the summer without precipitation. As a result, evapotranspiration from vegetated areas is reduced and the desired cooling effect is not achieved. During dry periods, the agricultural environment also cannot develop its full cooling effect even during the day.

In the project Imp_DroP (Impact of longer Drought Periods on Climate in Greater Vienna: appropriate Mitigation measures), the cooling potential of green spaces in and around Vienna is to be determined via evapotranspiration and future irrigation requirements. Thus, four measurement sites were established on green roofs in different local climate zones of Vienna for two years in spring 2022. At each of the selected sites, two lysimeters were installed for extensive and intensive green roofs, as well as soil moisture sensors in the upper and lower soil layers.

These measurement data from 2022 are used in a further step for the calibration of the crop growth model AquaCrop, and the data collected in 2023 are taken for validation. Therefore, soil moisture can be simulated for selected dry periods on green roofs. For the surrounding agricultural areas of Vienna, soil moisture is simulated using the ARIS model.

All collected data are applied in a final step to initialize, run and validate the coupled WRF-TEB model. Here, the atmospheric conditions as well as the urban microclimate for current and future summer drought episodes are simulated to estimate the expected thermal stress for the Viennese population.

How to cite: Thaler, S., Eitzinger, J., Formayer, H., Gützer, C., Hörbinger, S., Masson, V., Mursch-Radlgruber, E., Perny, K., Preiss, J., Pröll, T., Rauch, J. P., Sadriu, M., Schmidt, S., Schoetter, R., Szocska, D., Wittkowski, M., Trimmel, H., Wöß, D., and Weihs, P.: Cooling potential of green spaces in the Vienna metropolitan area during extended periods of drought, EMS Annual Meeting 2023, Bratislava, Slovakia, 4–8 Sep 2023, EMS2023-343, https://doi.org/10.5194/ems2023-343, 2023.

Agnieszka Sulikowska, Ewa Grabska-Szwagrzyk, and Agnieszka Wypych

Air temperature is a crucial driver of many plant developmental processes, among which the initiation of spring activity is the most prominent. Recent climate warming has been found to alter plant phenology in many European regions. However, ultimate conclusions regarding this relationship are still challenging as quantitative estimates are strongly diverging. Moreover, the results concerning the role of temperature extremes, i.e., unusually warm or cold periods, are equivocal. Studying these complex links is of utmost importance as changes in plant phenology affect basic ecosystem functions, including water, carbon, and energy fluxes, as well as plant-animal interactions and ecosystem productivity. Recent progress in research based on satellite phenology indicates that it is a powerful tool to monitor terrestrial vegetation and its responses to climate drivers. It provides qualitatively different traits than ground-based observations, but these two sources of information complement each other well. The use of new generations of satellites with high spatial and temporal resolution helps to gain a better insight into the climate-phenology relations.

The main aim of this study is to assess the effect of air temperature conditions on the start of the spring activity of deciduous trees in Poland during 2018-2023. Data used in the study include the E-OBS (v27.0e) gridded daily mean, maximum and minimum temperatures, and the Sentinel-2 imagery over March-June. The tree species chosen for the analysis are common beech (Fagus sylvatica), silver birch (Betula pendula), and two species of oak (Quercus), which are among the most abundant in Poland. Several hundred single species stands were delimited across the area of Poland to study inter- and intraspecific differences in temperature-phenology relations. General temperature conditions during six individual seasons were assessed using the growing degree days (GDD) for 0°C and 5°C base temperatures. Special attention was paid to extremely warm or cold events, i.e., warm and cold spells, defined using percentile-based thresholds. Their effects were evaluated regarding their intensity and timing within the season. Trees’ response to temperature conditions was assessed using satellite-derived start-of-season (SOS) metric based on derivatives calculated from two indices: MTCI (MERIS Terrestrial Chlorophyll Index) and EVI (Enhanced Vegetation Index).

This preliminary study provided insights into complex links between temperature conditions and spring phenology of deciduous trees, showing that responses to climate drivers, especially extreme events, are species-dependent. Large inter-annual variability in phenology has also been shown – estimated SOS varied between studied seasons by more than 20 days. The results also proved the Sentinel-2 data to be useful in the monitoring of individual tree species phenology.

How to cite: Sulikowska, A., Grabska-Szwagrzyk, E., and Wypych, A.: Air temperature impact on springtime tree phenology in Poland based on satellite data, EMS Annual Meeting 2023, Bratislava, Slovakia, 4–8 Sep 2023, EMS2023-401, https://doi.org/10.5194/ems2023-401, 2023.

Csilla Vincze, Ádám Leelőssy, and Róbert Mészáros

Beekeeping is a special agricultural field that provides essential resource to other agriculture through pollination services; while it creates value with honey production. Beekeeping is also one of the most weather-sensitive agricultural field. Weather influences honey production in three ways: (1) with seasonal scale weather patterns influencing phenological growth; (2) short-term (daily) weather influence on nectar production and (3) direct weather influence on bee flight.

In this study, a linear time series model is presented to predict honey production describing weather as external variable. Honey production time series was derived from hourly values of total bee and honey weight per hive, measured with hive scales located in apiaries in Debrecen, Hungary in the black locust blooming periods of 2021–2022. Data was pre-processed to remove the seasonal blooming pattern and the typical two-peak diurnal pattern of gathering by bees. Meteorological data was obtained from nearby monitoring sites of the Hungarian Meteorological Service. Mean and maximum temperatures, as well as global radiation was used as external variable in the time series regression model. Consecutive 1-day hindcasts of honey production were evaluated against observation data. Model RMSE was found to be approximately 0.6 sigma (in standardized units) over a range of model settings. However, the fitted regression coefficients had large error and were barely significant.

The method presents a statistical approach to create hive-specific daily forecasts of honey production for hives equipped with scales. The definition of the seasonal pattern (i.e. phenology) is a crucial step to create a stationary time series for predictive modeling.

How to cite: Vincze, C., Leelőssy, Á., and Mészáros, R.: Applying a regression model to estimate honey production from weather variables, EMS Annual Meeting 2023, Bratislava, Slovakia, 4–8 Sep 2023, EMS2023-418, https://doi.org/10.5194/ems2023-418, 2023.

Rostislav Fiala, Martin Meszaros, Petr Hora, and Grazyna Knozova

The agrometeorological model named AVISO is developed and operated at the Czech Hydrometeorological Institute as a tool for calculation the evapotranspiration and soil profile water content. The model uses modified evapotranspiration equation developed by Penman and Monteith. The basic calculated surfaces are water level, bare soil, grass and a few field crops. As part of the research project, some AVISO model procedures and canopy parameters were modified for usage in fruit orchard. Data and observation from apple, cherry and apricot orchards from 2020 to 2022 were used to set up the model and to validate the model results. By determining the hydrolimits of the soil and the characteristics of the root zone of the trees, the water capacity of the model soil profile was estimated. The AVISO model results were compared with measured soil moisture, which was converted to the average soil profile saturation determined in percentage of available water capacity. When tuning the model, emphasis was placed on the decreasing part of the soil water content curve interpreting the intensity of evapotranspiration. In many iterations of the calculation, the results of the model were compared with the measurements using the correlation coefficient, the average bias and the mean absolute error. The average model-measurement correlation values for months in the growing season (April–September) in 2020 and 2021 were between 0.30 and 0.99. The bias error values were between -13.14 and +38.31 mm. The second comparison option was to use the precipitation sums for time periods determined by the almost identical moisture at the beginning and the end of the period. The amount of precipitation in the given section thus theoretically coincided with the sum of evapotranspiration. Correlations of model evapotranspiration and evapotranspiration calculated on the basis of this simple precipitation balance reached values of up to 0.9 for some variants of orchards. Despite some weaknesses, the model results are satisfactory in some experimental stands, especially in apple orchards. The modified model was used to calculate the long term average water balance of apple trees within the territory of the Czech Republic for the growing season for the period 1991-2020. Composition of seven maps was produced - six maps for monthly data and one for entire growing season. The values of water balance for summer months are in range from -77 to +125 mm, sum for growing season is in range from -323 to +563 mm. The lowest values indicating the threat of drought are in the South Moravia region. Among other things, improved model and maps can help to optimize water management and irrigation in orchards.

How to cite: Fiala, R., Meszaros, M., Hora, P., and Knozova, G.: Regionalization of the apple tree water balance based on modified agrometeorological model, EMS Annual Meeting 2023, Bratislava, Slovakia, 4–8 Sep 2023, EMS2023-432, https://doi.org/10.5194/ems2023-432, 2023.

Jakub Bohuslav, Kurt-Christian Kersebaum, Claas Nendel, Petr Hlavinka, Zdeněk Žalud, and Miroslav Trnka

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.

How to cite: Bohuslav, J., Kersebaum, K.-C., Nendel, C., Hlavinka, P., Žalud, Z., and Trnka, M.: Implementation of observed changes in soils under no-till and conventional management in selected crop models, EMS Annual Meeting 2023, Bratislava, Slovakia, 4–8 Sep 2023, EMS2023-481, https://doi.org/10.5194/ems2023-481, 2023.

Anna Buchholcerova

Tropospheric ozone is a reactive compound originating from both biogenic and anthropogenic emissions and stratospheric intrusions. Open-top chamber studies and fumigation experiments have already proven an adverse effect of its elevated concentrations on vegetation including changes in microscopical structures, leaf bronzing, and most important the decrease in growth increment. Ozone distribution in the troposphere is irregular in both time and space and its daily and annual course is affected by several factors (such as solar radiation and precursor concentrations). Ozone concentrations increase with altitude, which might lead to the assumption, that the mountain flora is more endangered by ozone effects than the flora at the lower altitude. The studies focusing on ozone effects on vegetation are oriented predominantly on the crop and timber production species and the research in the natural environment beyond this production is marginal. One of the ways to estimate ozone impact on vegetation is ozone dose calculation PODY. The determining factor of ozone dose modeling is stomatal conductance (gsto, mmol m-2s-1), which describes the degree of stomata opening and therefore regulates the ozone uptake by the stomata. This variable is weather- and environment-dependent. The stomatal conductance was estimated by the stochastic model and Jarvis model, which is recommended by United Nations Economic Commission for Europe. The expected air temperature increase might influence the ozone doses mostly by the change in stomatal conductance and by the prolongated growth season of plants. The poster will provide the basic evaluation of air temperature increments on ozone doses for forest species in High Tatra Mts. for future projections.

How to cite: Buchholcerova, A.: Modeling of the impact of the air temperature increments on the stomatal conductance and ozone doses in the mountain area of High Tatra Mts., Slovakia, EMS Annual Meeting 2023, Bratislava, Slovakia, 4–8 Sep 2023, EMS2023-518, https://doi.org/10.5194/ems2023-518, 2023.

Branislava Lalic, Michael Scriney, Stevan Savic, and Mark Roantree

The current state of weather-induced agricultural losses, water use for irrigation, the appearance of new invasive species and disease vectors (strongly depending on micrometeorological conditions), new environmental zoning of plant diseases and pests, deforestation, increased urbanization, rural-to-urban migration and increased urban energy consumption for cooling and heating impose scientific and societal demands for FAIR micrometeorological data.


It is important to remember the FAIR acronym for: Findability, Accessibility, Interoperability, and Reusability. This means that data and metadata should be easily discoverable by humans or machines, accessible under specific conditions or restrictions, conform to recognized formats and standards to be combined and exchanged, and licensed according to community norms, allowing users to know what kinds of reuse are permitted. While open data is the ultimate goal, it is important to have in mind that the FAIR concept implies open metadata only. Measurement results should be stored on a repository chosen by the data owner with a DOI and prefered licence, from closed to fully open with numerous options. More information can be found, for example at Open Data Commons (https://opendatacommons.org/licenses/).



The lack of FAIR data costs Europe a minimum of €10.2bn per year - approximately 78% of the Horizon 2020 budget per year (PwC EU Services, 2018). If data met the FAIR principle, it would improve data discovery and access, enable re-use, enhance understanding, especially across domains, reach as many people as possible, be cited more often, and open new routes to build cooperation.


To support owners of micrometeorological data to make their data FAIR, the FAIR Micromet Portal (FMP2.0) was developed within the CA20108 COST Action. FMP2.0 is designed and built to guide owners through FAIR principles, in a step-by-step manner, to make large volumes of data FAIR compliant. More details about FMP2.0 and its functionalities can be found in Roantree et al. (2023).


PwC EU Services, 2018: The cost of not having FAIR research data. DOI 10.2777/02999

Roantree, M., Lalic, B., Savic, S., Milosevic, D., and Scriney, M., 2023: Constructing a Searchable Knowledge Repository for FAIR Climate Data, EGU General Assembly2023, Vienna, Austria, 24–28 Apr

2023, EGU23-7786. https://doi.org/10.5194/egusphere-egu23-7786, 2023.

How to cite: Lalic, B., Scriney, M., Savic, S., and Roantree, M.: FAIRness wizard: FAIR Micromet Portal FMP2.0, EMS Annual Meeting 2023, Bratislava, Slovakia, 4–8 Sep 2023, EMS2023-563, https://doi.org/10.5194/ems2023-563, 2023.

Branislava Lalic and Ana Firanj Sremac

In a fast-changing global economy, possessing knowledge and skills plays a crucial role in determining individual, institutional, and societal competitiveness and the capacity to drive innovation. The FAIR Micromet Portal FMP2.0  (Roantree et al., 2023;  denoted as FKP) and CA20108 FAIRNESS network aim to enhance transferable skills in measurement planning and implementation challenges (creative thinking and problem-solving) and interdisciplinary approaches (the ability to combine work across different fields), with the expectation of improved outcomes.


These skills are highly valued by employers and in great demand in the labor market, making them important drivers of individual career development. However, there often exists a significant diversity among Ph.D. students and new employees (young researchers) regarding functional knowledge and skills, which may result in certain gaps. Identifying whether these gaps relate to soft, hard, or transferable knowledge and skills is essential. A lack of transferable skills can significantly hinder further career development. To address this issue, we have designed a transferrable skills questionnaire to help young researchers and experts assess their transferable skills related to micrometeorological measurements and decide which ones to enhance. The selected skills include micrometeorological instrumentation (principles of work, selection and installation), experiment design (designing micrometeorological measurements in rural and urban areas; anticipating and overcoming the most frequent issues; data and metadata selection), data assimilation (managing different data formats and units), critical control (quality control; identifying different data gaps in micrometeorological data and metadata), and gap filling (different methodologies in filling gaps in data and metadata).

In this study, we present the results of the self-assessment of the first hundred participants.


Roantree, M., Lalic, B., Savic, S., Milosevic, D., and Scriney, M., 2023: Constructing a Searchable Knowledge Repository for FAIR Climate Data, EGU General Assembly2023, Vienna, Austria, 24–28 Apr 2023, EGU23-7786. https://doi.org/10.5194/egusphere-egu23-7786.


How to cite: Lalic, B. and Firanj Sremac, A.: Micrometeorological measurements and data management as transferrable skills, EMS Annual Meeting 2023, Bratislava, Slovakia, 4–8 Sep 2023, EMS2023-569, https://doi.org/10.5194/ems2023-569, 2023.