• using EO for early detection and management of natural disasters affecting Mediterranean ecosystems and agriculture;
• indicators and models for assessing and forecasting climate change effects and risks in Mediterranean ecosystems and agriculture.
The Mediterranean region is considered a “Hot Spot” susceptible to the threat of climate change. Many regions are prone to desertification, reduced water and change of rainfall pattern, loss of fertile soil, and degradation of the ecological services provided. Using the Jordan Valley as a test case, the overall objective of the new EcoFuture project, funded by the PRIMA programme (under GA number 2243), is to develop a climate-change adaptation plan oriented towards improving the socio-economic welfare for people in the Mediterranean region based on Water-Energy-Food-Ecosystem (WEFE) nexus methodologies. The project builds on the research and innovation capacities of partners and local stakeholders in order to: 1) Propose a climate change adaptation plan for the Jordan Valley region, based on existing and emerging technologies, taking into account the social and economic priorities of the three involved jurisdictions (Jordan, Israel and Palestine); 2) Use techno-economic models to optimise the sustainable efficiency (economic, society and environment) performance of the Plan; 3) Use socio-economic models to assess and recommend policies in the WEFE context to improve the welfare of people in the region; 4) Perform tests in three demonstration sites in the Jordan Valley, one in each country, in order to validate the inputs to the various models; 5) Propose methodologies to extend the applicability of the results of the Jordan Valley to other regions and to other Mediterranean countries; 6) Build synergies across sectors to investigate interlinkages across the nexus; 7) Implement capacity building and training programs in response to project findings.
EcoFuture is designed to accomplish the objectives of the project in 3 phases:
- Data Collection Phase – The phase involves the collection of current and future WEFE resources data, Nature-Based Solutions (NBS) alternatives, Socio-ecological data and Governance data.
- Knowledge Creation Phase – The data collected in the first phase are analyzed using various methodologies, tools and models. This will be achieved through the development of Casual-Loop Diagrams (CLD), WEFE alternatives, Multi-criteria analysis of the selection of the optimal WEFE alternative, Hydrologic analysis of the area, Water allocation analysis, Energy Analysis, Ecosystem and Climate change assessment.
- Synthesis and Proposals Phase – This phase involved a techno-economical analysis and a foresight analysis that will be the basis for the development of a regional Strategic Plan that will assure Water security, Energy security and Food security while accounting for the impacts of climate change.
At the same time, Living Labs will take place in each territory with stakeholders that are relevant to the WEFE Nexus in order to co-design the pilot demonstration that will take place in each territory. These pilots will be the basis for capacity building and training programs for the local stakeholders.
How to cite: Nikolaidis, N., Lilli, M., Wald, S., Lehrer, D., Albalawneh, A., Jayyousi, A., Kan, I., Halasah, S., Zemah-Shamir, S., and Attili, S.: Climate-change adaptation plan in the Mediterranean region , 18th Plinius Conference on Mediterranean Risks, Chania, Greece, 30 Sep–3 Oct 2024, Plinius18-10, https://doi.org/10.5194/egusphere-plinius18-10, 2024.
The agricultural sector heavily relies on weather forecasts for informed decision-making. However, existing forecasting methods often lack localized precision, leading to significant uncertainties in predicting extreme weather events crucial for agricultural planning and management. The MAGDA H2020 project aims to address these challenges by developing a modular system deployed to farms, integrating observations from European space-based and ground-based assets to enhance tailored weather forecasts. This project represents a significant advancement by synergizing spaceborne, airborne, and ground-based measurement technologies, including GNSS and meteodrones observations, with meteorological models to benefit agriculture and water management operations. The project targets improvements in weather forecast accuracy, particularly concerning severe weather events like heavy rain, hail, windstorms. Inaccurate predictions of these events can lead to substantial crop damage, over-irrigation, or water shortages. Key challenges in Numerical Weather Models (NWM) stem from uncertainties in initial atmospheric conditions at small scales, necessitating enhanced observational data for improved model performance. Recent advancements in forecasting heavy rainfall events through data assimilation techniques show promising results. Studies have demonstrated the positive impact of integrating reflectivity data and in situ observations into meteorological models for predicting severe weather phenomena in various regions. Additionally, experiments incorporating Sentinel-derived and GNSS-derived products into high-resolution NWM have shown positive outcomes, particularly in predicting convective processes. The MAGDA project employs a cloud resolving modeling approach with a grid spacing of 2-3 km, coupled with rapid update cycles every 1-3 hours, to address uncertainties in weather prediction. The assimilation process integrates GNSS data to monitor integrated water vapor content, weather radar reflectivity to reconstruct the 3D cloud field, in situ weather stations for capturing near-surface atmospheric conditions, and meteodrones observations to collect information about the vertical profiles. By leveraging a combination of advanced technologies and data assimilation techniques, the project aims to enhance the accuracy and usefulness of weather forecasts tailored for agriculture and water management applications. The weather forecasts will be used as an input for the irrigation advisory, next to being used for generating warnings for extreme weather events. The warnings and irrigation advisories will ultimately be channeled through a Farm Management System to ensure the capability to effectively reach farmers and agricultural operators.
How to cite: Lagasio, M., Milelli, M., Oberto, E., Uboldi, F., Orensanz, J., Piot, M., Burcea, S., Chitu, Z., Verschuren, L., Fernández Rodriguez, A., Validi, A., Haskovic, D., Gatti, A., Fumagalli, A., and Realini, E.: Enhancing weather forecast accuracy for agricultural operations: The MAGDA Project approach., 18th Plinius Conference on Mediterranean Risks, Chania, Greece, 30 Sep–3 Oct 2024, Plinius18-30, https://doi.org/10.5194/egusphere-plinius18-30, 2024.
The Intergovernmental Panel on Climate Change (IPCC) in 2023 has projected an increase in temperatures across the Mediterranean basin in the coming years, alongside a persistent challenge of water scarcity. This forecast suggests a heightened probability of intensified and more frequent extreme climatic events, particularly droughts. Meteorological drought plays a pivotal role in influencing different forms of drought, highlighting the importance of understanding its spatiotemporal patterns at the basin level. Such an understanding holds significant implications for ensuring ecological sustainability and water resource management security. The present work aims to assess the spatial variability and the trends of the annual rainfall and meteorological drought in the Euphrates-Tigris River Basin (TEB) utilising measured and remote sensing data, which spans from January 1975 to December 2022 (a 47-year period). Drought assessment took place based on the Standardized Precipitation Index (SPI) for a 12-month timescale. We employed the 12-month SPI as the foundation for detecting drought occurrences. This timeframe offers a compromise between short- and long-term drought events, thus accurately capturing the influence of climate change on vital water resources like river flow. The findings offer valuable insights into the attributes and underlying mechanisms of meteorological droughts across the basin.
How to cite: Mohammad, H., Peli, M., and Barontini, S.: Spatio-temporal Characteristics of Meteorological Drought Events in The Euphrates-Tigris Basin during 1975–2022, 18th Plinius Conference on Mediterranean Risks, Chania, Greece, 30 Sep–3 Oct 2024, Plinius18-33, https://doi.org/10.5194/egusphere-plinius18-33, 2024.
Drought is commonly perceived as a natural hazard that evolves gradually. However, the recent increase in both the onset rate and severity of these events has drawn significant attention [1]. Both climate change and human activities contribute to the alteration of drought characteristics, affecting their development speed and intensity. For instance, climate change may indirectly influence droughts through alterations in the amount and distribution of precipitation and evapotranspiration, whereas human activities like land management can directly impact soil water content. This study employs the ISIMIP Global Water models [2, 3], driven by the hypothetical stationary ISIMIP3a climate dataset without climate change, and transient land use changes based on empirical observations [4]. We utilize soil moisture as an indicator of water deficit and a method to calculate the hydrological drought propagation speed to delineate drought characteristics. We contrast these results with those from historical simulations that include climate-related forcings based on empirical data to assess the historical long-term changes attributed to climate change. Our findings indicate that climate change significantly affects the development speed and intensity of droughts. Regions such as the rainforests of South America, Europe, and Southern Australia are identified as hotspots of more aggressive droughts, whereas areas like the East African mountains might experience milder droughts due to climate change. These variations could critically affect agricultural productivity, ecosystem health, and water availability for human consumption. The potential future acceleration of droughts underscores the importance of enhancing risk management and challenges existing drought hazard prediction research and practice.
1. Tramblay, Y., Koutroulis, A., Samaniego, L., Vicente-Serrano, S. M., Volaire, F., Boone, A., ... & Polcher, J. (2020). Challenges for drought assessment in the Mediterranean region under future climate scenarios. Earth-Science Reviews, 210, 103348. https://doi.org/10.1016/j.earscirev.2020.103348
2. Telteu, C. E., Müller Schmied, H., Thiery, W., Leng, G., Burek, P., Liu, X., ... & Herz, F. (2021). Understanding each other's models: A standard representation of global water models to support improvement, intercomparison, and communication. Geoscientific Model Development Discussions, 2021, 1-56. https://doi.org/10.5194/gmd-14-3843-2021
3. Müller Schmied, H., Gosling, S. N., Garnsworthy, M., Müller, L., Telteu, C.-E., … & Yokohata, T. (2024). Graphical representation of global water models, EGUsphere [preprint], https://doi.org/10.5194/egusphere-2024-1303, 2024
4. Frieler, K., Volkholz, J., Lange, S., Schewe, J., Mengel, M., Rivas López, M. D. R., ... & Bechtold, M. (2023). Scenario set-up and forcing data for impact model evaluation and impact attribution within the third round of the Inter-Sectoral Model Intercomparison Project (ISIMIP3a). EGUsphere, 2023, 1-83. https://doi.org/10.5194/gmd-17-1-2024
How to cite: Koutroulis, A., Grillakis, M., Gosling, S., Schmied, H. M., Burek, P., Kou-Giesbrecht, S., Qi, W., Pokhrel, Y., Satoh, Y., Tsanis, I., Stein, L., and Thiery, W.: Examining the contribution of climate change on global soil moisture drought characteristics, 18th Plinius Conference on Mediterranean Risks, Chania, Greece, 30 Sep–3 Oct 2024, Plinius18-46, https://doi.org/10.5194/egusphere-plinius18-46, 2024.
Soil moisture is a key hydrologic state variable driving the exchange of water and heat energy between the land surface and the atmosphere through evaporation and plant transpiration, regulating surface temperature, humidity and potentially affect precipitation though recycling processes. Soil moisture is a fundamental element of the surface water budget, determining the health or stress on land surface ecosystems and managed systems such as agriculture and agroforestry. The surface water budget, and therefore soil moisture, depends on precipitation, irrigation (when present), soil infiltration, surface runoff, baseflow, and evapotranspiration. Furthermore, soil moisture-based indices are used as indicators of agricultural droughts, and soil moisture drought is one of the preconditioning effects for the development of extreme temperatures, influenced by atmospheric dynamics.
Climate change poses a major threat to all Mediterranean countries due to the combination of significant reductions in precipitation, increases in temperature, and the higher frequency of climate extremes, especially driving water scarcity and related multi-sectoral impacts. Most Mediterranean countries already endure higher frequencies of droughts and deficits in soil moisture and water storage. In this study, future projections of soil moisture are examined using a multi-model EURO-CORDEX regional climate ensemble, in agreement with three future emission scenarios (RCP2.6, 4.5 and 8.5). The drivers of future soil moisture dynamics are also analysed along with their effects on relative humidity and evaporation rates.
As expected, the projections show a clear reduction of soil moisture throughout the entire annual cycle, in response to a significant decrease in precipitation and an increase in temperature, leading to a substantial rise in potential evapotranspiration. The overall total soil moisture decreases ranges from -5% for the RCP2.6 to -20% (-10%) for the RCP8.5 (RCP4.5), w.r.t. the present climate. Projections reveal that for the RCP4.5 (RCP8.5) for the mid-century soil moisture deficits up to 5x (6x) are projected to occur, and for the end-of-century even 7x for the RCP8.5. The annual cycle of soil moisture, both in the present and future climate, is determined by precipitation and potential evapotranspiration, and deficit is both enhanced and covers a wider monthly window in the future, especially for the RCP8.5.
This work was funded by the Portuguese Fundação para a Ciência e a Tecnologia (FCT) I.P./MCTES through national funds (PIDDAC) – UIDB/50019/2020
(https://doi.org/10.54499/UIDB/50019/2020), UIDP/50019/2020 (https://doi.org/10.54499/UIDP/50019/2020) and LA/P/0068/2020
(https://doi.org/10.54499/LA/P/0068/2020). This work was performed under the scope of project https://doi.org/10.54499/2022.09185.PTDC (DHEFEUS) and supported by national funds through FCT. DL and AR acknowledge FCT I.P./MCTES (Fundação para a Ciência e a Tecnologia) for the FCT https://doi.org/10.54499/2022.03183.CEECIND/CP1715/CT0004 and https://doi.org/10.54499/2022.01167.CEECIND/CP1722/CT0006, respectively.
How to cite: Lima, D. C. A., Bento, V. A., Russo, A., and Soares, P. M. M.: The extreme future of soil moisture over the Mediterranean region, 18th Plinius Conference on Mediterranean Risks, Chania, Greece, 30 Sep–3 Oct 2024, Plinius18-80, https://doi.org/10.5194/egusphere-plinius18-80, 2024.
Predicting and preparing for changes in agricultural ecosystems is crucial in an era of rapid global warming. Climate model projections are the only tool we have in assessing the risks for the global food system and they provide some foresight for decision-makers as they develop their adaptation and mitigation strategies. One big challenge in the development of these projections is that we can only evaluate them at the time of their validity, i.e., in many decades from now. However, some knowledge can be gained by assessing the vulnerability of certain crops to anomalous weather and climate conditions at shorter time scales as well. In this work, we analyze past ensemble seasonal forecasts (1 to 6 months lead time) from several weather centres across the world and evaluate their performance based on reanalysis data. The ultimate goal is to assess the impact of uncertainty and biases in seasonal weather forecasts on crop yields, with a focus on the wheat and corn production of southeastern Europe. This will be achieved through the collective efforts of meteorologists, climatologists, and agronomists in the Augures project. Apart from its applicability on an operational seasonal prediction basis, assessing the strengths and limitations of probabilistic crop yield forecasting offers valuable insights for the usability of agricultural projections at longer time horizons.
How to cite: Fragkoulidis, G., Kotroni, V., and Lagouvardos, K.: Evaluation of seasonal weather forecasts for agriculture applications in southeastern Europe, 18th Plinius Conference on Mediterranean Risks, Chania, Greece, 30 Sep–3 Oct 2024, Plinius18-133, https://doi.org/10.5194/egusphere-plinius18-133, 2024.
Precipitation and drought conditions play a key role in agriculture, so the regional and local adaptation strategies for the coming decades need information on how these climatic conditions tend to change due to global warming. For this purpose, the results of regional climate model (RCM) simulations from the EURO-CORDEX initiative are analyzed to estimate the possible future trends until the end of the 21st century. In order to take into account the uncertainty arising from the anthropogenic factors (e.g. greenhouse gas emissions, land use changes, population), three different RCP scenarios (i.e. RCP2.6, RCP4.5, RCP8.5) are taken into consideration representing immediate mitigation, mitigation from 2040, and business-as-usual future pathways, respectively. The study analyzes the changes in seasonal precipitation, seasonal number of dry days, and seasonal maximum of consecutive dry days by mid-century (2041-2060) and late-century (2081-2100) relative to the reference period (2001-2020) in Southeastern Europe, i.e. a major Mediterranean region between the Adriatic and the Black Sea. The difference between the RCM simulations enables us (i) to assess the uncertainty of the projections, and (ii) to identify robust likely changes in the region. Thus, stakeholders and decision-makers are provided with relevant information for future planning.
Acknowledgements: Research leading to this study has been supported by the European Climate Fund (G-2309-66801), the Hungarian National Research, Development and Innovation Fund (K-129162), and the National Multidisciplinary Laboratory for Climate Change (RRF-2.3.1-21-2022-00014).
How to cite: Pongrácz, R. and Szabó, P.: Projection of seasonal precipitation conditions and dry days in Southeastern Europe, 18th Plinius Conference on Mediterranean Risks, Chania, Greece, 30 Sep–3 Oct 2024, Plinius18-134, https://doi.org/10.5194/egusphere-plinius18-134, 2024.
Climate change impact assessments often require a manageable subset of climate models that accurately reflect regional specificities. This study harnesses the Coupled Model Intercomparison Project Phase 6 (CMIP6) to define a subset of models that represent the unique climate patterns of Greece. Our primary goal is to identify models that not only demonstrate the best performance over the recent past but also possess the capacity to reflect future climate spreads of the CMIP6 ensemble.
In our assessment we evaluate the full array of 40 CMIP6 models available in the KNMI Climate Explorer using a suite of performance metrics. The evaluation spans the accuracy of historical simulations against the CHELSA observational datasets (Karger et al., 2021). Model capacity for future climate projections is informed by recent advancements in model performance assessments specifically for Europe (Palmer et al., 2023), ensuring that selected models are robust across different climatic scenarios. We further consider model dependence based on recent concepts (Merrifield et al., 2023).
In the same context, we specifically focus on the representativeness of the selected driving models for the ongoing EURO-CORDEX CMIP6 downscaling initiative, which serves as the primary source of information for climate change impact assessment studies in Greece.
We conclude with recommendations of refined subsets of CMIP6 models meeting performance and representativeness criteria for climate model output users. This methodology not only aids in delineating between model performances but also facilitates a more nuanced understanding of their projection capabilities in the rapidly evolving climate modeling landscape.
Acknowledgments
The present work was performed within the project “Support the upgrading of the operation of the National Network on Climate Change (CLIMPACT)” of the General Secretariat of Research and Technology under Grant “2023ΝΑ11900001”.
References
Karger, D.N., Lange, S., Hari, C., Reyer, C. P. O., Zimmermann, N.E. (2021): CHELSA-W5E5 v1.0: W5E5 v1.0 downscaled with CHELSA v2.0. ISIMIP Repository. https://doi.org/10.48364/ISIMIP.836809
Merrifield, A., Brunner, L., Lorenz, R., Humphrey, V., & Knutti, R. (2023). Climate model Selection by Independence, Performance, and Spread (ClimSIPS v1.0.1) for regional applications. Geoscientific Model Development. https://doi.org/10.5194/gmd-16-4715-2023.
Palmer, T.E. et al. (2023) ‘Performance-based sub-selection of CMIP6 models for impact assessments in Europe’, Earth System Dynamics, 14(2), pp. 457–483. doi:10.5194/esd-14-457-2023.
How to cite: Tsilimigkras, A., Voulgarakis, A., Lazaridis, M., and Koutroulis, A.: Sub-Selection of CMIP6 Models tailored for Climate Impact Assessments in Greece, 18th Plinius Conference on Mediterranean Risks, Chania, Greece, 30 Sep–3 Oct 2024, Plinius18-50, https://doi.org/10.5194/egusphere-plinius18-50, 2024.
The frequency and intensity of extreme events are expected to increase due to climate change, leading to significant impacts on several sectors of human society. The return period method is a valuable tool for quantifying the likelihood of weather events with adverse impacts, and can be used by policymakers for long-term planning and decision making. In this work, two indicative case studies are presented, where the return period methodology and the related occurrence probabilities are used to predict the change in the frequency of occurrence of severe events related to precipitation, in the near and distant future. The first case study refers to the agricultural sector and presents the occurrence probabilities of dry winters in the near (2031-2060) and distant (2071-2100) future, under the RCP4.5 and RCP8.5 emission scenarios, using an ensemble mean of five bias corrected RCMs in two characteristic areas of olive cultivation, Spain (Andalusia) and Greece (Peloponnese). Reductions in winter precipitation are related to significant decreases in olive yields. Our analysis revealed increased probability in the occurrence of drier winters in the future, which may lead to yield shortfalls in both areas of the study. The second case study focuses on extreme precipitation that may affect the hydrological sector. Changes in the return periods of extreme rainfall events are calculated until 2100 under three emission scenarios (RCP2.6, 4.5, 8.5) using an ensemble of three bias corrected RCMs in an area close to Inachos river banks, Western Greece. Extreme precipitation events in this area are related to severe river floods. The analysis showed that a flood with a 50-year return period tends to decrease significantly to 20-25 years, depending on the emission scenario. The return period results provided the necessary information for the calculation of the ‘rainfall IDF curves’, contributing to the flood hazard assessment study that has been carried out for the specific area .
How to cite: Gratsea, M., Kitsara, G., Machaira, P., Kostopoulou, E., and Giannakopoulos, C.: Use of the return period methodology for the prediction of weather events with adverse impacts - case studies for the agricultural and hydrological sectors, 18th Plinius Conference on Mediterranean Risks, Chania, Greece, 30 Sep–3 Oct 2024, Plinius18-81, https://doi.org/10.5194/egusphere-plinius18-81, 2024.
