Timely delivery and effective use of climate information is fundamental for a green recovery and a resilient, climate neutral Europe, in response to climate change and variability. Climate services address this through the provision of climate information for use in decision-making to manage risks and create opportunities. In order to develop future equitable and quality-assured climate services to all sectors of society, it is important to work on developing standardisation procedures for climate services, as well as supporting an equitable European climate services community and also enhancing the uptake of quality-assured climate services to support adaptation and mitigation to climate change and variability.

An important component of the climate service reliability and use depends on the data, specifically on the traceable quality of its input and output datasets. The output datasets need to be FAIR, also for machines, meaning the output datasets provide full provenance information about e.g. the input datasets, the processing software, the quality and accuracy, all supported by interoperable metadata, including information on uncertainty. To support those needs and objectives for climate services, we will present preliminary guidelines of good practices for vocabularies, formats, metadata and technical standards, including FAIR principles for data and software/processing. As well, preliminary best practices in provenance of processing methodologies to guarantee traceability and reproducibility of climate data and ways to communicate it in a user-friendly manner will also be shown along with climate uncertainty, risk assessment and communication. Eventually all guidelines and good practices will be shared via the Climateurope2 platform, set up under the project to support the climate services community.

Everyone interested can also join our network to actively participate in developing best practices for climate services https://climateurope2.eu/

This project (Climateurope2) has received funding from the European Union’s Horizon Europe research and innovation programme under grant agreement N°101056933.

How to cite: Pagé, C. and Muñoz, Á. G. and the Climateurope2 WP2 Team: Better Climate Services: guidelines, standards and best practices for data processing, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-16532, https://doi.org/10.5194/egusphere-egu24-16532, 2024.

Climate data portals serve as important tools for climate services providers to effectively communicate with decision-makers. With a rapid increase in the number of such portals and the datasets underlying them, critical questions arise: do users encounter similar narratives across these platforms, and does their choice of portal influence decisions on adaptation measures? This presentation conducts a comparative analysis of two prominent Canadian portals, namely Climate Data Canada and Portraits Climatiques. Both portals feature bias-adjusted CMIP6 simulations that differ in various aspects, including bias-adjustment methodology, climate of reference, ensemble composition, and emissions scenarios. The impact of these choices is explored by assessing three core variables (daily maximum temperature, daily minimum temperature, and daily precipitation) and examining five case studies from the agriculture, transport, and health sectors. Our findings reveal significant disparities between the portals in terms of climate indicator values at the end of the century, while projected changes compared to the present climate are often more similar. Moreover, we observe a strong influence of the reference dataset choice on threshold-based indicators. Despite these discrepancies, users commonly make similar final decisions when employing both platforms, as adaptation measures are not markedly sensitive to the distinctions and as other non-climate-related factors must be considered in the decision-making process. This study sheds light on differences and similarities between climate data portals, emphasizing the need for climate services organizations to transparently communicate the implications of their choices to users, in order to guide the formulation of effective adaptation strategies.

How to cite: Lavoie, J., Caron, L.-P., Logan, T., and Barrow, E.: Are users drawing the same conclusions from different climate data portals?, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-1191, https://doi.org/10.5194/egusphere-egu24-1191, 2024.

We will present the methodology for the construction, and the outcomes, of the KNMI’23 national climate scenarios for the Netherlands. The KNMI’23 national climate scenarios consist of six scenarios that cover a substantial part of the uncertainty in CMIP6 projections of future climate change in the region. They form a detailed storyline of plausible future climates in the Netherlands. The resulting data is used for impact calculations and assessments by stakeholders, and will be used to inform policy making in different sectors of Dutch society.

We have disentangled different sources of uncertainty as much as possible, partly by means of a storyline approach. Uncertainty in future emissions is covered by making scenarios conditional on different SSP scenarios (SSP1-2.6, SSP2-4.5, and SSP5-8.5). For each SSP scenario and time horizon (2050, 2100, 2150), we determine a global warming level based on the median of the constrained estimates of climate sensitivity from IPCC AR6. The remaining climate model uncertainty of the regional climate response at these warming levels is covered by two storylines, which are designed with a focus on the annual and seasonal mean precipitation response (a dry-trending and wet-trending variant for each SSP). This choice was motivated by the importance of future water management to society. For users with specific interests we provide means how to account for the impact of the uncertainty in climate sensitivity. Since CMIP6 GCM data do not provide the required spatial detail for impact modelling, we reconstruct the CMIP6 responses by resampling internal variability in a GCM-RCM initial-condition ensemble.

More information on: https://www.knmi.nl/klimaatscenarios (see ‘toolkit’ for material in English).

How to cite: van der Wiel, K., Beersma, J., van den Brink, H., Krikken, F., Selten, F., Severijns, C., Sterl, A., van Meijgaard, E., Reerink, T., and van Dorland, R.: KNMI’23 climate scenarios for the Netherlands: storyline scenarios of regional climate change, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-3465, https://doi.org/10.5194/egusphere-egu24-3465, 2024.

Climate variability and change are societal challenges, necessitating urgent and comprehensive responses across many sectors. To confront these challenges effectively, these sectors must devise and execute adaptation and mitigation strategies. Such strategies should focus on minimising contributing factors to climate change and bolstering resilience against its repercussions. The urgency of these measures stems from the recognition that climate change permeates virtually every facet of our environment and daily life, calling for a concerted and enduring effort to safeguard our planet for future generations. A critical component of this endeavour is understanding the influence of meteorological and climatic conditions on specific sectors.
We have embraced a co-creation methodology that actively includes stakeholders to tackle the complexities of climate variability and change, as Font et al. (2021) suggested. This methodology is particularly pertinent to critical infrastructures at various levels. Our inclusive approach gathers many participants, from high-ranking executive managers to hydrogeology specialists. This diversity in perspectives and expertise guarantees that the solutions devised are comprehensive and precisely tailored to meet the distinct needs and contexts of the mobility infrastructures affected by climate change. Such a collaborative process cultivates innovation while fostering a sense of ownership and commitment among all stakeholders, thereby enhancing the effectiveness and durability of the solutions.
Our case study, executed in the Italian regions of Campania and Lazio, demonstrates the varied risks present in these areas and how they change over time and space. For this study, we utilized ERA5 land data, specifically downscaled to reconstruct historical climate scenario, and Cordex data for future climate projections. This presentation aims to transcend the mere explanation of climate data and show the whole process and journey to transform data into a climate service to assist decision-making in the mobility infrastructure sector. It is conveyed through an intuitive and reactive visual medium via a Shiny application crafted for accessibility to a diverse audience. This application proficiently exhibits the various calculated co-created indices over multiple intervals, rendering tailored information and making it more user-friendly and engaging for non-academic and non-climate-related users. Such a presentation style is instrumental in enhancing comprehension of climate change impacts and aiding in informed decision-making

How to cite: Olano Pozo, J. X., Boqué-Ciurana, A., Skrynyk, O., Brichese, M., Panico, F., Calicchio, M., Pantaneschi, S., Balart, A., Dermitt, D., di Meglio, M., Foria, F., Miceli, G., and Aguilar, E.: C2risk: Co-creating climate management tools for mobility infrastructures, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-8182, https://doi.org/10.5194/egusphere-egu24-8182, 2024.

How to cite: Boqué-Ciurana, A., Saladié, Ò., Garcia-Lozano, C., Borràs, G., Giné, G., Labairu, I., Martí, C., Rovira Soto, M. T., Tonda, M., and Aguilar, E.: Climate Services and Behavioral Change: Enhancing Resilience in Mediterranean Tourism through co-creation , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-8456, https://doi.org/10.5194/egusphere-egu24-8456, 2024.

The UN 2030 Sustainable Development Agenda included achieving Zero Hunger as one of its prominent goals. According to Food and Agriculture Organization for the United Nations (FAO), this objective is far from being achieved, as over 735 million people faced hunger in. The geographical distribution of food insecurity is not even across the globe, with greater impact over less developed countries where subsistence agriculture is a major livelihood. Weather, climate, climate variability and climate change alter in time and space the phenological stages of crops and, therefore, agricultural planning and production. One of the most widely used tools to convey weather and climate information to final agricultural users are weather-based crop calendars. They use time series of daily accumulated rainfall to provide actionable information on the timing of phenological stages, specifically on the times for planting (start of the season) and harvesting (end of the season) for different crops and different agroclimatic zones. The creation of a Crop Calendar requires quality controlled and homogeneous rainfall series to detect the onset and cessation of the rainy season, plus crop-specific information, like drought resilience and crop cycle length. Rainy season onset and cessation are determined using threshold-based methods, which combine rainfall accumulation over several days and additional criteria to avoid false alarms, such as the presence/absence of consecutive dry days. The rainy season onset and cessation for each year are calculated and their timeseries fit to a probability distribution to evaluate the climatological expectations for early/normal/late onsets and cessations. The final crop calendar results from assimilating the first/early/normal/late onsets of the rainy season to the span of possibilities for the sowing dates. The harvest dates are defined as the sowing dates plus the crop cycle length for each variety and agroecological zone. In this contribution, we present a series of tools developed with the support of the World Meteorological Organization (WMO) and the Climate Risk and Early Warning Systems Initiative (CREWS) project in West Africa and the Enhancing Adaptive Capacity of Andean Communities through Climate Services (ENANDES) project in South America, following a “from data to service” approach and including a series of training events. The process is illustrated using rainfall series from Togo.

How to cite: Aguilar, E., Boqué, A., Olano, J., Gascon, T., Gray, S., and Agniga, K.: Creating tools for the generation of weather-based crop calendars to support climate services. , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-15388, https://doi.org/10.5194/egusphere-egu24-15388, 2024.

The ClimXtreme program, funded by the German Ministry of Education and Research, focuses on the assessment of the frequency and intensity of historical extreme events and their impacts in Central Europe, their association with dynamical and thermodynamical processes and how these extreme events might change according to enhanced anthropogenic climate forcing.

The program currently aims at the development of a basis for stakeholder decision making that consists of data, software, and information tailored to their needs. By means of dedicated hazard specific stakeholder interaction groups, relevant stakeholders and researchers will develop the knowledge base through a two-way process. Social scientists will explore and develop the communication process with stakeholders.

Within the research program, a post-event assessment group will be formed aiming at rapid response of the project to extreme events occurring during project runtime. The group will make use of the developed knowledge base, apply pre-defined methods and workflows to assess current extreme events with diverse perspectives which are represented in ClimXtreme.

Both the concept and selected recent results of the ClimXtreme program will be highlighted.

How to cite: Grieger, J., Ulbrich, U., Buschow, S., Lucio Eceiza, E. E., Feldmann, H., Friederichs, P., Kaspar, F., Kunz, T., Niermann, D., and Pinto, J. G.: Impacts of climate change and weather extremes in Europe: building a knowledge base for decision support, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-17514, https://doi.org/10.5194/egusphere-egu24-17514, 2024.

While dynamical seasonal prediction models offer many benefits, it is challenging for most National Hydrological and Meteorological Services (NMHSs) to develop and operate their own expensive models. Given the limited human and computing resources in South Korea’s modeling communities, increasing our capacity to share small resources and generate joint efforts for a better climate prediction system is thus essential. The Korean Meteorological Administration (KMA) adopted the Global Seasonal Forecasting System version 6 (GloSea6) from the United Kingdom Met Office (UKMO), and has being operated the prediction system for the real-time climate forecasting since 2022 March. The domestic and multi-institutional efforts are currently underway to advance the prediction system in collaboration with academic societies and the APEC Climate Center (APCC), which is a research partner of the KMA. By motivated by great needs for joint collaborative system between academy, research institute and organization, and NMHSs, as well as strengthened strategy of operationalization, we have once recalled the research-to-operation (R2O) process and finally invented the R2O structure customized for the dynamical prediction and modelling environments in South Korea (K-R2O). K-R2O represents technically sound and unique process from research and development to operation through testbed which individual components are carried out by different parties. The role of testbed and framework of standard verification for model development identified in K-R2O is highlighted. Lesson learned and further guidance for K-R2O are also discussed for many NMHSs facing similar situation to South Korea.

How to cite: Sohn, S.-J.: Sharing Small Resources and Making Joint Efforts for the Improvement of Climate Prediction Model in South Korea, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-7390, https://doi.org/10.5194/egusphere-egu24-7390, 2024.

A comprehensive toolbox has been developed to support urban adaptation to heat waves (HWs) in the context of the current climate and climate change. The toolbox consists of the following components: (1) full methodology for analysing the interactions between urban heat islands (UHIs) and HWs in the context of climate change; it is exemplified for the city of Bucharest, Romania, but the methodologies used can be easily applied to other cities; (2) a web-based tool that allows users to explore the impacts of different climate change scenarios on the interactions between UHIs and HWs;  for example, users can input changes in land cover, population growth, and temperature and see how these changes affect the UHI-HW relationship in a particular city;  (3) guidelines and specific measures to better cope with the UHI and HW stress under current and future climate conditions, tailored to the specific context of each city; adaptation and mitigation options are included (i.e., more greenery and lesser disruption of the natural water cycle supporting current policies for climate change resilience).

The support toolbox based on an interactive Shiny application built in R and Python provides a comprehensive set of tools and resources, which allows urban planners, policymakers, and stakeholders to make informed decisions about how to adapt to and mitigate the effects of HWs. The interactive features of the application enable users to intuitively visualize and interact with urban adaptation data, thereby facilitating a deeper understanding of the problem and potential solutions.

This study received funding from the project Synergies between Urban Heat Island and Heat Wave Risks in Romania: Climate Change Challenges and Adaptation Options (SynUHI) PN-III-P4-PCE-2021-1695.

How to cite: Dumitrescu, A., Cheval, S., Chițu, Z., Falcescu, V., Gabrian, Ș., and Dinicilă, Ș.: Support Toolbox for Urban Adaptation to Heat Waves in Romania, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-17578, https://doi.org/10.5194/egusphere-egu24-17578, 2024.

The recent sixth IPCC report highlighted the lack of studies on the impacts of climate change in the Global South. While paradoxically these countries have the weakest resilience capacity to adapt to these forthcoming changes. In this context, a co-construction workshop was organized in 2022 to define the multi-sectoral needs of different academic or institutional actors working on the impacts of climate change. Bridging together meteorological and hydrological agencies, universities, research centers, and private companies from Africa, Europe, South Asia, and South America, this workshop allowed defining the types of data and their modalities of access, that are the most adapted to conduct impact studies of climate change in different domains. The main difficulties in accessing climate data identified for researchers working on climate change impacts were related to the lack of technical capability to retrieve and process the worldwide databases of climate models data and also the need for expertise to exploit this wealth of data efficiently. Following this workshop, a climate services platform was implemented in 2023 (https://climatsuds.ird.fr/) to access a large dataset of bias-corrected CMIP6 climate models simulations, as well as a set of climate indices relevant for impacts assessment (heavy rains, extreme heat..) and impact models outputs (ISIMIP2a) in different sectors (water, vegetation, agriculture, and health). The web platform enables data extraction by point, by country, or by free polygons, visualization in graphic formats, and export to NetCDF or CSV files. Besides data access functionalities, the web portal will gradually integrate different training resources for the users and new datasets according to their needs. 

How to cite: Tramblay, Y., Sultan, B., Amoussou, E., Arias, P. A., Bodian, A., Fita Borrell, L., Brouillet, A., Condom, T., Dezetter, A., Diedhou, A., Driouech, F., Hanich, L., Junquas, C., Roux, E., Sané, Y., Scarcelli, N., and Ngo-Duc, T.: A web portal dedicated to climate change impact studies in the Global South: ClimatSuds.ird.fr, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-9656, https://doi.org/10.5194/egusphere-egu24-9656, 2024.

To support decision-making processes, Germany's National Meteorological Service, Deutscher Wetterdienst (DWD) is developing an operational seamless climate prediction service. Climate predictions from subseasonal to the decadal time scales are consistently presented on a single platform, the DWD climate predictions website (http://www.dwd.de/climatepredictions) [1]. To strengthen the idea of seamless climate information, we are working on a seamless timeseries, which contextualizes climate predictions with observations from the past and future climate projections.

National users from different sectors (e.g. water, energy, forestry, agriculture) regularly take part in the discussion and evaluation process of the DWD climate prediction website. Design and content of the climate service were developed as a co-design with national users.

To meet users’ needs regarding spatial resolution, climate predictions on all timescales are downscaled using the empirical-statistical downscaling EPISODES [2]. Presented on the website are bias corrected weekly (subseasonal), 3-month (seasonal) 1- and 5-year (decadal) means of temperature and precipitation on global and national scale. DWD always presents its climate predictions in combination with the corresponding prediction skill.

We provide climate predictions in two categories of different complexity. The “basic climate predictions” offer simplified climate predictions, which will be presented on an interactive platform soon. In a second “expert climate predictions” section, we offer more detailed information on global, European, and national climate predictions.

The newest user-oriented addition on the website will be climate predictions and the corresponding evaluations of soil moisture. This new product is calculated with the AMBAV model [3], which retrieves its input variables from DWD’s high-resolution climate predictions. Additionally, user surveys have shown high interest in climate extremes. Currently DWD is working on the publication of several extreme indices concerning drought and heat. Plans for further extensions include multi-year seasonal predictions and multi-model predictions.

[1] A. Paxian, B. Mannig, M. Tivig, K. Reinhardt, K. Isensee, A. Pasternack, A. Hoff, K. Pankatz, S. Buchholz, S. Wehring, P. Lorenz, K. Fröhlich, F. Kreienkamp, B. Früh (2023). The DWD climate predictions website: towards a seamless outlook based on subseasonal, seasonal and decadal predictions. Climate Services 30, 100379. https://doi.org/10.1016/j.cliser.2023.100379.

[2] Kreienkamp, F., Paxian, A., Früh, B., Lorenz, P., Matulla, C., 2018. Evaluation of the Empirical-Statistical Downscaling method EPISODES. Clim. Dyn. 52, 991–1026 (2019). https://doi.org/10.1007/s00382-018-4276-2.

[3] https://www.dwd.de/DE/fachnutzer/landwirtschaft/dokumentationen/allgemein/ambav-20_doku.html

How to cite: Mannig, B., Paxian, A., Tivig, M., Wehring, S., Leppelt, T., Pasternack, A., Castino, F., Stanley, K., and Früh, B.: Climate Predictions @ DWD – towards a seamless climate prediction website, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-17496, https://doi.org/10.5194/egusphere-egu24-17496, 2024.