CL2.1

Implementing adequate health preventing measures is essential for public health decision making, particularly in the current context of rising temperatures. Most of the early warning systems are only based on climate data, and in very few cases they truly model the actual impact of the climate phenomena.

Here we establish, for the first-time, the theoretical basis for the development of operational heat-health early warning systems that combine climate and health data. We studied the predictability of Temperature Attributable Mortality (TAM) at lead times of up to 15 days for a very large ensemble of European regions. To achieve this goal, we analysed daily counts of all-cause mortality for the period 1998-2012 in 147 NUTS2 regions in 16 European countries, representing more than 400 million people, and daily high-resolution weather forecasts from the European Centre for Medium-Range Weather Forecasts (ECMWF). We applied epidemiological models for the fitting of the temperature-mortality relationship in each of the regions, accounting for the different vulnerabilities and socio-demographic characteristics existing in Europe. We compared the predictive skill of the temperature and health forecasts on seasons and days with higher mortality risk. 

We conclude that the predictability of temperature can be used to issue skilful forecasts of TAM. In general, the predictability limit of temperature is similar to the one of TAM, which implies that the use of epidemiological models to transform the climate variables into health information does not reduce the lead time limit with significant forecast skill. Nonetheless, the spatial heterogeneity of the predictability lead time for TAM is higher than for temperature, especially in summer, where the complex shape of the temperature-mortality association amplifies the forecast errors. Overall, we find  a nearly-linear relationship between the predictability of temperature and TAM for different seasons and regions, suggesting that future improvements in the predictability of temperature could automatically lead to improvements in the predictability of TAM.

How to cite: Quijal-Zamorano, M., Petrova, D., Rodó, X., Martinez-Solanas, È., and Ballester, J.: Forecast of temperature-attributable mortality at lead times of up to 15 days for a very large ensemble of European regions, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-4107, https://doi.org/10.5194/egusphere-egu21-4107, 2021.

Renewable energy is the fastest-growing source of electricity globally, but climate variability and impacting events affecting the potential productivity of plants are obstacles to its integration and planning. Knowing a few months in advance the productivity of plants and the impact of extreme events on productivity and infrastructure can help operators and policymakers make the energy sector more resilient to climate variability, promoting the deployment of renewable energy while maintaining energy security.

The energy sector already uses weather forecasts up to 15 days for plant management; beyond this time horizon, climatologies are routinely used. This approach has inherent weaknesses, including the inability to predict extreme events, the prediction of which is extremely useful to decision-makers. Information on seasonal climate variability obtained through climate forecasts can be of considerable benefit in decision-making processes. The Climate Data Store of the Copernicus Climate Change Service (C3S) provides seasonal forecasts and a common period of retrospective simulations (hindcasts) with equal spatial temporal resolution for simulations from 5 European forecast centres (European Centre for Medium-Range Weather Forecasts (ECMWF), Deutscher Wetterdienst (DWD), Meteo France (MF), UK Met Office (UKMO) and Euro-Mediterranean Centre on Climate Change (CMCC)), one US forecasting centre (NCEP) plus the Japan Meteorological Agency (JMA) model.

In this work, we analyse the skill and the accuracy of a subset of the operational seasonal forecasts provided by Copernicus C3S, focusing on three relevant essential climate variables for the energy sector: temperature (t2m), wind speed (sfcWind, relevant to the wind energy production), and precipitation. The latter has been analysed by taking the Standard Precipitation Index (SPI) into account.

First, the methodologies for bias correction have been defined. Subsequently, the reliability of the forecasts has been assessed using appropriate reliability indicators based on comparison with ERA5 reanalysis dataset. The hindcasts cover the period 1993-2017. For each of the variables considered, we evaluated the seasonal averages based on monthly means for two seasons: winter (DJF) and summer (JJA). Data have been bias corrected following two methodologies, one based on the application of a variance inflation technique to ensure the correction of the bias and the correspondence of variance between forecast and observation; the other based on the correction of the bias, the overall forecast variance and the ensemble spread as described in Doblas-Reyes et al. (2005).

Predictive ability has been assessed by calculating binary (Brier Skill Score, BSS hereafter, and Ranked Probability Skill Score, RPSS hereafter) and continuous (Continuous Ranked Probability Skill Score, CRPSS hereafter) scores. Forecast performance has been assessed using ERA 5 reanalysis as pseudo-observations. 

In this work we discuss the results obtained with different bias correction techniques highlighting the outcomes obtained analyzing the BSS for the first and the last terciles and the first and the last percentiles (10th and 90th). This analysis has the goal to identify the regions in which the seasonal forecast can be used to identify potential extreme events.

How to cite: Palma, M., Catalano, F., Cionni, I., and Petitta, M.: Determination of seasonal forecast skill in identifying extreme events of temperature, wind speed, and SPI, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-9563, https://doi.org/10.5194/egusphere-egu21-9563, 2021.

Unfavorable and extreme climate events such as drought and heat stress affect wheat production and food security globally. Predicting such climate events in the next decade is of great interest for decision-makers, as this time horizon coincides with the strategic planning of many stakeholders in the wheat sector. To address this, we assess the forecast quality in predicting the evolution of drought and heat stress conditions using two proxy user-oriented drought and heat stress indicators: Standardized Potential Evapotranspiration Index (SPEI6) and Heat Magnitude Day Index (HMDI3) on a multi-annual timescale (forecast years 1 to 5). In particular, we present the probabilistic skill and reliability of decadal forecast to predict these indices for the months preceding wheat harvest on a global spatial scale. We use decadal forecasts from the Community Earth System Model Decadal Prediction Large Ensemble (CESM-DPLE), which contributes to the Decadal Climate Prediction Project (DCPP) of CMIP6. Following this, we demonstrate the potential applicability of these forecasts to enhance the adaptation and mitigation activities in the wheat sector by presenting the forecast of multi-year averaged SPEI6 and HMDI3 based on categorical events for the period 2016-2020 along with the corresponding observational values.

How to cite: Solaraju-Murali, B., Gonzalez-Reviriego, N., Caron, L.-P., Ceglar, A., Toreti, A., Zampieri, M., and Doblas-Reyes, F. J.: Multi-year prediction of drought and heat stress to support decision making in the wheat sector, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-10981, https://doi.org/10.5194/egusphere-egu21-10981, 2021.

Return period analysis to assess the long-term impact of climate change on olive sector in Andalusia, Spain - results from the Med-Gold project

M. Gratsea¹, K. V. Varotsos¹, J. López-Nevado², S. López-Feria², C. Giannakopoulos¹

1 Institute for Environmental Research and Sustainable Development, National Observatory of Athens, Greece

2 DCOOP Sociedad Cooperativa, Andalusia, Spain

 Abstract

Med-Gold project, aims to develop climate services for olive, grape and durum wheat crops, which are the hallmarks of the Mediterranean food system. The generated climate related information at different timescales will be exploited by the end-users for operational decision-making. The objective of this study is to employ the return period method for communicating the effect of climate change on the olive crops in the long-term in Andalusia, which is one of the most important olive growing areas worldwide. Therefore, return periods of bad years in terms of olive yield and olive fly risk are being calculated for the reference period 1971-2000 and for the near (2031-2060) and distant future (2071-2100) under the RCP4.5 and RCP8.5 emission scenarios using an ensemble of five bias-corrected Regional Climate Models. The identification of the bad years - and the corresponding thresholds - is based on observational data from five monitoring stations in Andalusia (Malaga, Granada, Sevilla, Cordoba and Jaen) and the role of certain meteorological parameters (precipitation, temperature, relative humidity) is investigated. The results indicate an overall tendency for increased occurrence probability of bad years in terms of yield due to future higher temperatures and decreased precipitation. The impact is more pronounced towards the end of the century and under the RCP8.5 future emission scenario.

This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 776467.

How to cite: Gratsea, M., Varotsos, K., Lopez-Nevado, J., Lopez-Feria, S., and Giannakopoulos, C.: Return period analysis to assess the long-term impact of climate change on olive sector in Andalusia, Spain - results from the Med-Gold project, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-7767, https://doi.org/10.5194/egusphere-egu21-7767, 2021.

The French National Climate Service “Drias, futures of climate” was launched in 2012, as a response of the French scientific community to society’s need for climatic information. It is mainly composed of a website that provides easy access to the best available climate data to characterize climate change over France. Latest advances developed in 2020 include the availability of a new set of regional climate scenarios corrected by a quantile-mapping based method with correction depending on the weather regime. As for the previous set, the climate projections are based on the EURO-CORDEX ensemble, whose contents have been greatly enriched over the past years. Singular effort was done to build a robust and synthetic set that well represents the uncertainties of climate change over France. The different criteria defined to select the simulations will be presented, and the range of the projected climate change will be examined, with respect to larger ensembles.

How to cite: Corre, L., Somot, S., Soubeyroux, J.-M., Bernus, S., Drouin, A., Dubuisson, B., Etchevers, P., Gouget, V., Josse, P., Kerdoncuff, M., Samacoits, R., Tocquer, F., Pagé, C., Ribes, A., and Vautard, R.: Selecting climate projections for services: the DRIAS-2020 dataset, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-9527, https://doi.org/10.5194/egusphere-egu21-9527, 2021.

The kind of long-term regional climate information that is increasingly important for making adaptation decisions varies in temporal and spatial resolution, and this information is usually derived from Global Climate models (GCMs). However, information about future changes in regional climate also comes with high degrees of uncertainty–an important element of the information given the high decision stakes of climate change adaptation.

Given these considerations, Baldissera Pacchetti et al. (in press) have proposed a quality assessment framework for evaluating the quality of regional climate information that intends to inform decision making. Evaluating the quality of this information is particularly important for information that is passed on to decision makers in the form of climate services. The framework has five dimensions along which quality can be assessed: diversity, completeness, theory, adequacy for purpose and transparency.  

Here, we critically evaluate this framework by applying it to one example of climate information for adaptation: the UK Climate Projections of 2018 (UKCP18). There are two main motivations for the choice of UKCP18. First, this product embodies some of the main modeling strategies that drive the field of climate science today. For example, the land projections produced by UKCP18 provide probabilistic uncertainty assessments using multi-model and perturbed physics ensembles (MME and PPE), use locally developed GCMs and the models from the international Climate Model Intercomparison Project (CMIP), perform dynamical downscaling for producing information at the regional scale and further fine grain information with convection permitting models. Second, the earlier version of the UK Climate Projections (UKCP09) has received criticism from philosophers of science. The quality assessment framework proposed by Baldissera Pacchetti et al. partly aims to reveal whether the pitfalls identified by philosophers in UKCP09 persist in UKCP18.

We apply the quality assessment framework to four strands of the UKCP18 land projections and illustrate whether and to what extent each of these strands satisfies the quality dimensions of the framework. When appropriate, we show whether quality varies depending on the variable of interest within a particular strand or across strands. For example, the theory quality dimension highlights that epistemic quality along this dimension is better satisfied for estimates about variables that depend on thermodynamic principles (e.g. global average temperature) than fluid dynamical theory (e.g. precipitation) (see, e.g., Risbey and O’Kane 2011) independently of the strand under assessment. We conclude that for those dimensions that can be evaluated, UKCP18 is not sufficiently epistemically reliable to provide information of high quality for all of the products provided.

How to cite: Baldissera Pacchetti, M., Dessai, S., Bradley, S., and Stainforth, D. A.: Evaluating the quality of model-based regional climate information: the case of the UK Climate Projections 2018, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-16352, https://doi.org/10.5194/egusphere-egu21-16352, 2021.

Climate projections obtained from global and regional climate models usually exhibit biases: systematic deviations from observations. Adjusting these biases is typically the first step towards obtaining actionable climate information to be used in impact studies. However, this bias adjustment process is highly technical and demands a lot of resources, both infrastructures (e.g. access to high performance and cloud computing) —particularly for continental wide applications— and human (e.g. personnel specialised in climate data post-processing).

Climadjust (accessible through https://climadjust.com/) is a web service developed with the support of the Copernicus Climate Change Service  implementing user-friendly bias adjustment for climate projections from the C3S catalogue using customized methods and reference datasets. The service was developed by Predictia —a company with a strong focus on climate services development and climate modelling— in collaboration with the Spanish Research Council (CSIC). 

Climadjust provides scalable cloud resources to compute bias-adjusted climate projections from the ensembles of CMIP and CORDEX datasets or customized areas of interest. In this process, the users are able to (i) upload their own dataset of observations to adjust the climate projections, or choose among reference datasets such as ERA5-Land or WFDE-5, (ii) choose among six state-of-the-art Bias Adjustment techniques implemented using the open source Climate4R package, and (iii) validate the results through the standard framework developed in the European VALUE COST Action. The output is a validated netCDF file, ready to be used by the climate modellers working in climate studies.

This climate service is targeted at the end tail of the downstream market of climate services, namely climate modellers working in sectoral climate adaptation in the agriculture, hydrology, biodiversity, insurance and forestry management fields, among others. Currently, the service counts with over 100 registered users.

To promote the user uptake of the service, the project faced several barriers, such as a lack of understanding on the need of adjusting biases by the end-users, and communication barriers between the climate science community and the end-user community. The session will present the lessons learnt during the user uptake campaigns, the user needs gathered through the user engagement activities performed within it, as well as relevant use-cases of the service, developed hand in hand with the end users.

How to cite: Sáenz de la Torre, J. J., Suárez, E., Iglesias, D., Sánchez, I., Pérez, A., Tuni, M., García, M., San-Martín, D., Iturbide, M., and Gutiérrez, J. M.: Climadjust: easing the Bias Adjustment process through a user-friendly web service, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-10674, https://doi.org/10.5194/egusphere-egu21-10674, 2021.

This contribution relates to preparatory efforts for creating a transnational, multilinguistic visualisation tool of past, present, forecasted and future (weather and) climate information in Europe, targeted to a large range of users. There is no scarcity of observed or modelled climate data, especially in Europe. However, existing climate information are often hidden, poorly explained or not accessible (in their complexity and structure) for non-scientists in many countries, especially in Eastern Europe and Russia. Needed are hence clear, reliable, and concise facts to easily understand the complex topic of climate change, supported by a high spatial resolution of climate information for local concernment.

We identified two superordinated target groups: 1) decision makers, demanding easily accessible and digestible, as well as for decision making processes usable climate information and 2) educational institutions and the general public, who will profit from more intuitive ways teaching and informing about climate change. We here present results of a user survey carried out in five countries (in native language) and of key stakeholder interviews within the same countries.

In the surveys, we approached potential users within different countries to explore what climate data they need, in which complexity, spatio-temporal detail, actuality and visualisation style. We also aimed to explore if similar actors of different countries may have similar or different needs, and how we may prepare an optimal product useful for a large range of users located in different countries. Follow-up key stakeholder interviews helped us deepening the level of understanding of user needs. Such interviews allowed us to go into more details than the questionnaire. It also enabled us to present the users content of existing webpages presenting climate information, to identify what the users like, dislike or miss in existing tools - e.g., in terms of data visualisation, handling, comparison and comprehensiveness. Coordinating country partners served as multipliers to reach users in their national language and to evaluate the results. Those activities disseminated the ideas of our planned platform in those countries and between different users there.

How to cite: Hoy, A., Ustrnul, Z., Wypych, A., Gordov, E., Gordova, Y., and Leander, E.: User involvement to prepare a Pan-European climate visualisation platform targeted at decision makers and educational purposes, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-1140, https://doi.org/10.5194/egusphere-egu21-1140, 2021.

Meteorological institutes all over the world are publishing new “climate normals” in 2021, as prescribed by the World Meteorological Organization. These “climate normals”, averages over the period 1991-2020, generally have higher temperatures than the previous climate normals over the period 1981-2010 or earlier 30-year periods. As a consequence, in weather forecasts from 2021 the expected temperatures for the coming days and weeks are less often “above normal”, compared to earlier years. In the Netherlands there has been already a lot of discussion about these “climate normals”. Several people, including climate researchers and weather providers, object to them, since they say that these “normals” obscure climate change. Especially the word “normals” is what bothers them, since the current state of the climate should not be considered normal. At KNMI we understand this problem, although we also see the importance of providing regular updates of the description of the “current” climate. Many aspects in society are designed and operated taking into account the averages and extremes in the current climate. Climate is an important aspect in almost any sector, from water management, agriculture to super markets and theme parks. Several visualizations (climate dashboard and weather and climate plume) are developed at the Royal Netherlands Meteorological Institute (KNMI) that combine information on “climate normals”, past and future climate change and weather forecasts.

During the presentation examples of the above described visualizations are shown and the advantages and disadvantages are described. Suggestions are presented on how to communicate about “climate normals” and climate change.

How to cite: Bessembinder, J., Overbeek, B., and Siegmund, P.: Climate normals and climate change: how to communicate these together?, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-4032, https://doi.org/10.5194/egusphere-egu21-4032, 2021.

The visual communication of climate information is one of the cornerstones of climate services. Characteristics that make a climate service self-explanatory rely on the visual modes it employs, e.g. maps, graphs or infographics, and the visual channels applied for the translation of multidimensional data, e.g. combination of colours, shapes or slopes. 

Climate scientists have traditionally used predetermined types of visualisations to present climate data, including flood maps, heat maps or choropleth maps. However, such a tradition neglects a plethora of stakeholders (e.g. businesses, policy makers, citizens) that are increasingly involved in climate adaptation and that are less familiar with the traditional ways of presenting these data. In this sense, there is a need to advance towards climate services visualisations that can guide climate change adaptation decisions by helping users to interpret and use the information as simply and quickly as possible.

Effective visualisations should achieve a balance between the amount of represented data, its robustness (i.e. the representation of scientific confidence and consensus) and saliency (i.e. the relevance of the information to user needs). Therefore, choices regarding the representation of probabilities (e.g. using terciles or information on extreme events), the representation of uncertainty (e.g. showing the ensemble range or filtering by a skill threshold), the type of visual encoding (e.g. selection of the colour palette, use of shapes and sizes) as well as the terminology and language used, are some aspects that can significantly impact the way users interpret climate data.

We describe the main challenges for the visualisation of climate services identified during a visualisation workshop with representatives from 22 climate services projects involved in the Climateurope network, an EU-funded coordination and support action. In break-out group discussions, participants shared their experiences in the development of effective climate services visualisations and the lessons learned. Findings show that the chosen representation of uncertainty and probabilities tends to be case specific and that there is a preference for interactive visualisations where information is gradually disclosed. Minimising the use of technical concepts in visualisations was highlighted as an objective that requires further attention. The analysis of the obtained results provides a picture of the current status of the climate services visualisation field in Europe and gives recommendations for the development of the next generation of climate services.

How to cite: Terrado, M., Urquiza, D., Octenjak, S., Nicodemou, A., Bojovic, D., Calvo, L., and Christel, I.: Visualisation in climate services: status and recommendations, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-7750, https://doi.org/10.5194/egusphere-egu21-7750, 2021.

The Thermal Assessment Tool has been developed within the framework of a Copernicus Climate Change Service (C3S) contract, titled Climate Change Dashboards for Decision Makers, to provide an interactive and informative dashboard to allow users to visualize the frequency and severity of risk events related to cold snaps and heatwaves. The tool is based on historical, seasonal forecast and long-term projections datasets, available through C3S Climate Data Store (CDS). It reduces the need for repetitive complex climate data analysis, thereby saving time and effort in the decision-making process.

Climate change has already impacted ecosystems and humans, and it is foreseeing that will lead to an increase in the number and intensity of extreme weather events, including heatwaves and cold snaps. These may bring temperatures that are significantly warmer or colder than average that may cause impacts such as thermal discomfort, lack of productivity, more energy consumption and/or health problems. To reduce or at least mitigate these impacts added-value information regarding the risks of extreme temperatures is needed to make proper decisions to prepare, protect and prevent the city and citizens.

For this purpose, the Thermal Assessment Tool provides a customized dashboard that allows users to visualize heatwaves, cold snaps and thermal comfort based on long-term projections and seasonal forecasts. The tool also presents an interactive map and a time series visualization identifying the magnitude of these three variables. This reduces the need for repetitive complex climate data analysis, thereby saving time and effort in the decision-making processes. Information on the frequency and severity of future extreme temperature events can also assist with planning.

The tool showcases how to analyze, process and simplify large volumes of data through different maps and plots that make it easier to understand climate indicators (about the past, present or future). Local governments and other decision-makers, as well as actors in housing development and management, urban planning, and insurance can refer to the tool to complement their usual information systems with additional quality-assured insights that they can act on.

Acknowledgments: We would like to thank the C3S for funding this project and the participants in the various workshops mentioned below: Ayuntamiento de Bilbao, Ihobe y la Oficina Española de Cambio Climático.

How to cite: Lajarín, B., Peña, N., Paz, J., Morris, E. P., Vega, G. C., Casal, E., Dubuisson, M., Teixeira, L., and Feliu, E.: Thermal Assessment Tool: A climate service to visualize trends of risk events related to cold snaps and heatwaves, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-10901, https://doi.org/10.5194/egusphere-egu21-10901, 2021.

During the project MED-GOLD, whose aim is to co-develop pilot climate services for three staple Mediterranean agri-food systems: grape, olive and durum wheat, key challenges emerged in the process of identifying useful climate indicators and actionable definitions of the reliability of climate information. To address such conflicting notion of the reliability of climate information, a participatory workshop was organised with providers (mainly climate scientists) and users of climate data and information (representatives from agri-food companies but also providers of agromet services for farmers) to facilitate an open discussion and find ways of moving forward methodologically and practically towards the development of prototype services. We found that the scientists and users had very different conceptions and interpretations of terms such as skill and reliability of climate information. Furthermore, such disparate understandings created a level of friction between what the scientists understood as scientifically robust and credible climate information and what the users required in terms of saliency of the climate information developed in order to effectively support their decisions. Through an iterative and open discussion, scientists and users agreed the decision making landscape and on a notion of reliability of climate predictions connected to the type of decisions that climate information would support. We will describes the process of developing a common understanding on working definitions of the reliability of climate predictions in the MED-GOLD project and, provide a practical example of the application of this definition to a real case study focused on durum wheat cultivation in Italy.

How to cite: Calmanti, S., Bruno Soares, M., Dell’Aquila, A., Ponti, L., De Felice, M., González-Reviriego, N., Marcos-Matamoros, R., Terrado, M., Graça, A., Fontes, N., Teixeira, M., Monotti, C., López Nevado, J., and Manstretta, V.: Overcoming conflicting notions of climate forecasts reliability and skill in the agricultural sector: lessons from the MED-GOLD project, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-16350, https://doi.org/10.5194/egusphere-egu21-16350, 2021.

Due to the pervasive nature of climate change impacts, and their relevance for human welfare, climate services delivering advanced knowledge of climate change and variation are crucial. They aid informed decision-making at relevant spatial and timescale and to improve prevention, preparation, adaptation, and minimize residual damages. It is also imperative to evaluate the climate services with a view to quantify the economic value added of these services. Particularly crucial is to assess how the decision-making process of the service end users would unfold with and without the service to identify its differential impact on properly selected indicators of performance.

The co-generation (also called co-creation) in products and services was made popular by the business literature in the early 2000s and represents a conceptual shift from an emphasis on output to an emphasis on a mutually satisfying relational process between developers and users in service creation. It mainly consists of four stages, namely co-design, co-development, co-delivery, and co-evaluation. The stage of co-evaluation refers to the development and application of agreed upon criteria for the measurement of results. The criteria will touch upon both substantial and procedural issues. From a user perspective, it will be important to evaluate relevance, impact/benefits, utility, credibility, and costs (financial and human resources) in using climate services. These elements are important to assess the effectiveness and uptake of the service and possibly refine it towards these goals. From a developer perspective, important aspects to evaluate will include, for instance, the scientific quality of the service or its skill.

This presentation introduces the lessons learnt in the context of the H2020 project CLARA (Climate forecast enabled knowledge services) on how to effectively implement the interactions among researchers, end users and service developers to unveil the economic value added of climate services.

How to cite: Delpiazzo, E.: Co-Evaluation as a step in the Co-Generation of Climate Services.  An analysis of the CLARA experience, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-7364, https://doi.org/10.5194/egusphere-egu21-7364, 2021.

Knowledge networks are collections of individuals who work together across organizational, spatial and disciplinary boundaries to develop and share a body of knowledge. Climate services are tools and applications that help support decision-making by transforming climate data into information tailored to specific users. They call for co-development practices to facilitate successful collaboration between different stakeholders. Knowledge networks for climate services are intermediaries that can facilitate the interaction between upstream (providers) and downstream (users) actors operating at various scales (local, national, regional and supranational). Such knowledge networks can therefore assist decision-making processes of a wide set of users by creating networking opportunities and disseminating usable climate information. The aim of this work is to frame and assess the efficiency of knowledge networks for climate services in promoting innovation and facilitate its diffusion. We used semi-structured interviews with knowledge networks managers to collect information about their purpose, process and audience.  We then assess the efficiency of knowledge networks by performing content analysis of interviews with knowledge network managers and by checking for the existence of inconsistencies or gaps with the initial objectives. We find that knowledge networks for climate services pursue four objectives: coordination, innovation promotion, science-policy interface and support to members. We also find that knowledge networks are well-recognised players in disseminating knowledge and opportunities to climate services practitioners and policy makers. However, we observe a lack of adequate tools to monitor the activities of different members. On the communication side, knowledge networks for climate services mostly interact with developers of climate services but face challenges in sharing members’ activities with users. Our work fills a significant knowledge gap and helps providing new tools of performance assessment in absence of a clearly defined methodology. The identification of bottlenecks and under-performing mechanisms in the climate information services sphere allows the elaboration of strategies to improve the status quo and facilitates the diffusion of innovations such as climate services.

How to cite: Larosa, F. and Bruno-Soares, M.: The role of knowledge networks in facilitating the creation of climate information services, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-7570, https://doi.org/10.5194/egusphere-egu21-7570, 2021.

The need of filling the gap between medium-range weather (up to 10-15 days) and seasonal forecasts (3–6 months) has led to several operational weather and climate centres to include the subseasonal forecasting in their predictions. Although this kind of information is starting to be explored by some stakeholders, such as renewable energy, water management, agriculture or disaster prevention, there are still much more sectors who can exploit this information. In this contribution, we will present how this type of climate information is used by the retail sector, in particular by a well known French sporting goods retailer within their operations over Spain. Having reliable climate forecasts weeks in advance would allow to manage the stock, redistribute it along with different warehouses and take different advertising campaigns and prices policies to avoid both the extra-cost that implies keeping what is not sold and running out of products. A recent proof of the influence of climate on sporting goods sales has been evidenced by the large increase in sales of mountain and snow equipment during Filomena’s episode, which violently hit the south-west, centre and north-east of the Iberian Peninsula in January 2021. Trustworthy subseasonal forecasts could be equally useful during other times of the year to make some decisions, such as extending or shortening the summer sports season. To illustrate the potential of these types of climate predictions, a case study for the Filomena event in January 2021 is presented. The sub-seasonal NCEP-CFS v2 prediction system has been used to compute the probability of each tercile category for surface temperature (above-normal, below-normal or normal - where normal is the average over a reference period). Forecasts for weekly temperature were calibrated using as reference the ERA-5 reanalysis dataset and the regions with negative skill were masked. It is interesting to point out how the predictions issued three weeks in advance already indicated that surface temperature would be below normal over Spain.

How to cite: Martínez Botí, A., Palma, L., Roura, F., Manrique-Suñén, A., González-Reviriego, N., Marcos, R., González, S., López, A., and Soret, A.: Climate services for the retail sectors: the Filomena’s case, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-15813, https://doi.org/10.5194/egusphere-egu21-15813, 2021.

Marine risk embraces an assessment of likelihoods and consequences of impacts from climate fluctuations in order to identify time and regions vulnerable to climate hazards. This information can support sustainable and safe marine activities. The marine risk assessment is a part of the marine service provided by the DNV GL (short for Det Norske Veritas and Germanischer Lloyd). In their current risk application, likelihoods of extreme conditions on the sea are based on historical observations and atmospheric reanalyses. We assess predicted likelihoods of extreme conditions over 1990-2017 in the boreal summer (prediction months 2-4) from the seasonal forecast system provided by the German Meteorological Service (DWD). We chose summer as it represents the time of the open-water season, when the highest marine activity in the Barents Sea takes place. We selected three indicators from the marine risk assessment. Two of them represent meteorological properties such as wind speed and 2-meter temperature (T2m). The third indicator – the wind chill index (WCI) is a combination of the previous two and represents heat loss from the human body to its surroundings during cold and windy weather. As expected, the prediction skill assessment suggests different levels of predictability for the three indicators, with T2m having the highest skill followed by WCI and wind speed. The prediction skill represents the "trust layer" superimposed on the predicted likelihoods and used as input fields for marine risk assessment. From the likelihood maps for the test period of summer 2020 follows that large areas of the Barents Sea represent favorable conditions for marine operations considering high prediction skill and low likelihood for extreme WCI (>1000 W/m²) and T2m (<0 °C) conditions in July and August. The wind speed (>13.9 m/s) is poorly predictable beyond the first lead month. Thus, if risk assessment is based on a suite of climate indicators with the heterogeneous prediction skill, the total risk assessment might be limited by the skill of the indicator with the lowest prediction skill. However, not all climate indicators are equally contributing to the risk assessment. The study describes a workflow for application of seasonal climate predictions and points to a few lessons learned, which can be useful to future climate services.

How to cite: Polkova, I., Schaffer, L., Aarnes, Ø., and Baehr, J.: Seasonal climate predictions for marine risk assessment in the Barents Sea, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-4399, https://doi.org/10.5194/egusphere-egu21-4399, 2021.

In Finland, the ski industry is facing an increased vulnerability to climate change and variability, especially in southern and central regions. The late start and the early end of snowing season and the difficulties in artificial snow production due to high winter temperatures have significant impacts on winter tourism. As part of INDECIS project, Finnish Meteorological Institute developed and tested seasonal forecasts with Finnish ski centers, providing support in maintenance practices. In the beginning of the pilot, a workshop was organized representatives of the ski resorts, where the most useful indices were selected, uncertainties related to variables used in the development of indices were presented to the users and the visualization and delivery of climate outlooks were agreed. In this presentation, we will assess the quality of snow forecast and present the developed seasonal snow outlooks. 

The ECMWF long-range forecasts (SEAS5) were quality assessed and several bias-adjusted methods analysed. Finally, the raw snow forecast was bias-adjusted using the EMOS method. The forecasts were the monthly mean snow depth, and the probability of ≥1 cm of monthly mean snow depth. The forecasts were evaluated using the CRPSS. The results depend much on the season. For example, Lead month 0 and month 1 forecasts in February showed skill over most of Finland, while Lead month 0 and month 1 forecasts in November were not as skilful. 

The developed seasonal climate outlooks were tested by the users during November 2019-April 2020; following the test period a feedback survey was conducted with the users. How the perceived usefulness of forecasts transfers to the decisions made by the users is not so straight-forward. According to the feedback received only one user of the four repliers changed their plans based on the provided outlooks, and half of the respondents couldn't say if they changed their activities in any way.

How to cite: Hyvärinen, O. and Vajda, A.: Tailored seasonal snow forecasts for ski centers in Finland, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-9917, https://doi.org/10.5194/egusphere-egu21-9917, 2021.

Agriculture is exposed to numerous risks related to climate change. Extreme weather events, such as droughts, heat waves, intensive rainfall and floods, as well as slow changes (increased temperatures, changes in precipitation regime and generally increased climate variability) affect the year-to-year stability of quality and quantity of the plant production.

Serbia is located in one of the regions that are recognized as hot spots where climate change unfolds faster than the global average. A survey completed by more than 100 agricultural producers in Serbia showed that in the last 20 years they were affected by mostly negative impact of climate change and suffered reduced quality and/or quantity of yields, mostly from droughts, high summer temperatures, spring frosts and storms with strong winds and hail.

Adaptation measures applied to reduce the risks of extreme weather events are mainly those subsidized by the Government (anti-hail nets, irrigation systems, etc.), recommended by the Agriculture Advisory Service or other independent expert (tillage methods, sowing time, time and water amount used for irrigation, use of fertilizers, etc.), as well as those learn from their own past experience (selection of varieties, crop rotation).

Most respondents regularly follow short-term weather forecasts from various sources and plan field activities accordingly. They are mainly familiar with the monthly forecast issued by the Republic Hydrometeorological Service of Serbia (RHMSS), which is also published by several newspapers. This forecast is based on the statistical method of analogies and the producers believe that they cannot rely on it in long-term planning. In general, they lack confidence in the long-term weather forecasts, mainly due to the fact that over the past years Serbian media were overwhelmed with tendentious seasonal forecasts from unreliable sources.

On the other hand, the survey showed that many producers would appreciate and use the seasonal weather outlooks if it was tailored according to their specific needs considering species they cultivate and local climate characteristics. They would like clearly presented information, in simple graph or map form, followed by textual advices on agro-technical measures they could adopt in order to reduce foreseen weather-related risks.

Integrated Agro-meteorological Prediction System (IAPS) is a project financed by the Science Fund of the Republic of Serbia through the Program for excellent project of young researchers (PROMIS) that aims to reduce the risk of weather-related events and increase climate resilience of Serbian agriculture, as well as to advance the use of climate information by producers and agricultural advisers in long-term planning. The idea is to create a coupled system od dynamically downscaled seasonal weather forecasts and crop models, accompanied with a set of products specifically tailored to support long-term decision making in agriculture. At the end of the project, the developed system and its products will be offered to RHMSS to include in the operative forecast system.

Acknowledgement: This research is supported by the Science Fund of the Republic of the Republic of Serbia, through PROMIS project “Integrated Agro-Meteorological Prediction System” (IAPS), grant no 6062629.

How to cite: Vujadinović Mandić, M., Vuković Vimić, A., Ćosić, M., Ranković-Vasić, Z., Djurdjević, V., and Nikolić, D.: Supporting Long-Term Decision Making in Plant Production in Serbia, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-2709, https://doi.org/10.5194/egusphere-egu21-2709, 2021.

The enhanced vulnerability of insular regions to climate change highlights the importance of undertaking adaptation and mitigation strategies according to the specific singularities of the islands. Islands are highly dependent on energy imports and the transition to a system with higher shares of renewable energies, in order to reduce greenhouse gas emissions in these regions, can also reduce the external energy dependence. In this context, the assessment of the impact of climate change on renewable energy resources during the 21st century is crucial for policymakers and stakeholders, due to the increasing vulnerability of the system to climate variability. The aim of this work is to provide an overview of wind and photovoltaic (PV) resources, their variability and complementarity between them, as well as their future changes, in the Euro-Mediterranean and Canary islands. Due to the limitations in land surface availability in the islands for the installation of renewable energy capacity, the analysis is extended to offshore wind and photovoltaic energy, which may have an important role in the future increases of renewable energy share. Variability is assessed through the analysis of energy droughts (low-productivity periods). In addition, a case study for optimization of wind and solar combination over the Canary islands is performed. In that sense, a sensitivity test is developed to find the optimal combination of PV and wind that reduce energy droughts and the persistence of that conditions at a local scale. To that end, we use climate variables from a series of regional climate simulations derived from Euro-CORDEX and MENA-CORDEX for the RCP2.6 and RCP8.5 emission scenarios and for the periods 2046-2065 and 2081-2100. The obtained results are very dependent on the region analyzed. Whereas an overall decrease is projected in wind resource over the Mediterranean islands for the future, an increase is projected for the Canarian archipelago. Changes in PV productivity are small in any case, as well as variability changes. These results, which are part of the SOCLIMPACT H2020 project, highlight the importance of targeting climate information and give condensed and valuable data to facilitate climate-related policy decision making for decarbonization and Blue Growth in the islands.

How to cite: Gutiérrez, C., de la Vara, A., González-Alemán, J. J., and Gaertner, M. Á.: Impact of climate change on renewable energy over the Mediterranean and Canary Islands: SOCLIMPACT H2020 project., EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-4218, https://doi.org/10.5194/egusphere-egu21-4218, 2021.

In 2018, the UN estimated that around 55% of the world’s population currently live within urban areas, with this value projected to rise to 60% by 2030 (United Nations, 2018). High levels of urbanisation, coupled with an increasing trend in extreme weather under future climate change scenarios, combine to create significant challenges to increasing urban resilience for the future (Masson et al., 2020).

Urban climate services provide tools to support decision making at a range of scales across the city, from day-to-day operations to informing urban design over longer timescales (Grimmond et al., 2015). Whilst urban climate services may be developed at a range of scales (Grimmond et al., 2020), this presentation looks at a prototype climate service which provides long-term climate change projections at the city-specific scale. The ‘City Pack’ was developed through a process of co-production, in which project development aims to move away from a one-way push of scientific information, to a two-way collaborative process of knowledge construction and sharing (Vincent et al., 2019).

This ‘City Pack’ service was co-developed by the Met Office and Bristol City Council following an assessment of the Council’s climate information needs. The City Pack comprises of three non-technical factsheets which explain how the climate of Bristol has changed and will continue to change into the 21^st Century based on the UKCP climate projections. The City Pack’s primary aims are to raise awareness of how a cities climate may change in the future and to inform the development of city resilience whilst also providing a tool to be used by city stakeholders to raise awareness of climate change across the council. The audience for the City Pack therefore includes city officials, city planners and the general public. The Bristol City Pack has since provided an evidence base for the Bristol City Council Climate Change Risk Assessment and informed Bristol’s Climate Strategy. In addition, the City Pack has been used to engage with the council’s wider stakeholders and also as a communication and training tool. As such, whilst the co-production of a climate service may be time and resource intensive, the process may also be rewarded with the production of a highly tailored and user-relevant tool.

Following the success of the prototype ‘City Pack’ service for Bristol City Council, the Met Office are continuing to produce City Packs for additional cities across the UK, and also in China. The project is seeking to ascertain if services which are co-produced with and bespoke to one set of stakeholders, may provide an equally valuable service for other cities and if so, how can we make these services scalable.

How to cite: Fuller, E., Scannell, C., Ramsey, V., Parfitt, R., and Golding, N.: The City Pack - the co-production of an urban climate service providing local summaries of a city's future climate , EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-6236, https://doi.org/10.5194/egusphere-egu21-6236, 2021.

WeCTOU (http://wectou.meteoromania.ro/) which delivers climate and environmental information tailored for tourism at 160 locations in Romania is a provider of climate services developed and operated by National Meteorological Administration.  European Commission and the European Centre for Medium-Range Weather Forecasts (ECMWF) through the Copernicus Climate Change Service (C3S) have provided the financial support. WeCTOU aims to extend its climate services and in this context, we have taken into account the needs of stakeholders interested in winter tourism in Romanian mountains using observations from national meteorological network together with reanalysis and model products extracted from the Climate Data Store developed at the ECMWF. Stakeholders interested in winter tourism in Romanian mountains span a wide range of categories from central and local administration to representatives of hospitality industry and individuals. In 2019, the Romanian Ministry of Economy, Energy and Business Environment, also responsible of tourism certified 195 ski slopes located in 20 Romanian counties. We use the ensemble distribution of number of days with snow depth larger than 30 cm from future projections covering the period 2021-2040 under climate change scenarios to provide a first guess assessment of future profitability of Romanian ski resorts compared with the reference period 1976-2005. This type of indicator together with climate products related to snow making are important for identifying opportunities for future investments in winter tourism. They are also important in general urban planning for localities which have to change their profile from winter resort to one which serve guests year-round.  Especially for tourists and hospitality industry, we use future projections of indicators relative to present conditions (2021-2040 vs. 1976-2005) such as the ensemble distribution of number of days with snow layers having depths larger than 30 cm during winter holidays (22 Dec- 04 Jan). Also, we have shown how testing all these winter climate services with the interested stakeholders has guided us during the incremental developing stages to shape the final design.   

How to cite: Bojariu, R., Velea, L., Irimescu, A., Craciunescu, V., and Puiu, S.: Climate services for winter tourism in Romanian mountains, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-11216, https://doi.org/10.5194/egusphere-egu21-11216, 2021.

Sea surface temperature conditions in the central-eastern tropical Pacific indicated a mild El Niño event in October 2018, which continued throughout the spring of 2019. The global El Niño Southern Oscillation (ENSO) forecast consensus was that these generally weak warm patterns would persist at least until the end of the summer. El Niño and its impact on local climatic conditions in southern coastal Ecuador influence the inter-annual transmission of dengue fever in the region. In this study, we use an ENSO model to issue forecasts of El Niño for the year 2019, which are then used to predict local climate variables, precipitation and minimum temperature, in the city of Machala, Ecuador. All these forecasts are incorporated in a dengue transmission model, specifically developed and tested for this area, to produce out-of-sample predictions of dengue risk. Predictions are issued at the beginning of January 2019 for the whole year, thus providing the longest forecast lead time of 12 months. Preliminary results indicated that the mild El Niño event did not provide the optimum climate conditions for dengue transmission, with the model predicting a very low probability of a dengue outbreak during the typical peak season in Machala in 2019. This is contrary to 2016, when a large El Niño event resulted in excess rainfall and warmer temperatures in the region, and a dengue outbreak occurred 3 months earlier than expected. This event was successfully predicted using a similar prediction framework to the one applied here. With the present study, we continue our  efforts to build and test a climate service tool to issue early warnings of dengue outbreaks in the region.

How to cite: Petrova, D., Rodó, X., Sippy, R., Ballester, J., Mejía, R., Beltrán-Ayala, E., Borbor-Cordova, M., Vallejo, G. M., A. Olmedo, A., Stewart-Ibarra, A., and Lowe, R.: The 2018–2019 weak El Niño: Predicting the risk of a dengue outbreak in Machala, Ecuador, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-14259, https://doi.org/10.5194/egusphere-egu21-14259, 2021.

The H2020 MED-GOLD Living Lab ”Turning climate information into value for traditional Mediterranean agri-food systems” was implemented as a solution to deal with the coronavirus pandemic and the resulting travel restrictions. Originally planned as a summer school in Cagliari in Italy, this training event was held online over five weeks between May and June 2020. This work describes the main features of the MED-GOLD Living Lab 2020, including the necessary steps and the strategy adopted to turn the originally planned physical summer school into an online event. 

The MED-GOLD Living Lab 2020 was dedicated to early career scientists and professionals in the areas of climate science, agriculture, economy, social sciences and communication. The Living Lab has been conducted as an on-line event for five weeks, from May 25 to June 25, with weekly interactive webinars by speakers across different disciplines and on-line working groups with multidisciplinary teams, supported by scientists from the MED-GOLD experts as mentors.

Participants have been challenged by real users of climate information to develop prototype climate services for the agri-food sector, building on the knowledge and skills shared during the event.

Early career scientists and professionals with a wide range of individual profiles have been encouraged to apply and join the multidisciplinary teams: climate scientists, agronomists, software developers (R, Python), economists, social scientists, communication and visual communication experts.

The purpose of the Living Lab was to demonstrate to the participants the MED-GOLD concepts and methodologies to develop climate services as well as become familiar with climate data and tools made available through the Copernicus Climate Data Store (CDS).

An online feedback form was distributed to participants in the last day of the living lab. Overall the feedback received was very positive with all respondents stating that they would recommend this living lab to others. The majority of respondents were positive about the overall content, design and delivery of the living lab. 

However, the interactive aspects of the Living Lab could be further improved not only to ensure that the interactions between participants (e.g. to pursue their work group are effective but also in terms of ensuring that the time at which the living lab runs fits with participants’ own commitments. Potential ways of overcoming these could be to e.g. allocate a specific slot during the living lab programme for group work as well as to identify specific dates/time slots to run future living labs together with participants.

The majority enjoyed the opportunity to engage with real-problems and stakeholders, working in multidisciplinary teams and engaging with experts in climate services.

Taking into account the circumstances of the COVID-19 emergency and based on the feedback by the participants, the Living lab was a  successful experiment that could be replicated and further enhanced for the second training event, MED-GOLD Living Lab 2021 planned for late spring 2021.

How to cite: Dell'Aquila, A., Calmanti, S., Ponti, L., Bruno Soares, M., Pasqui, M., Sanderson, M., and Caboni, F.: MED-GOLD Living Lab 2020: the story of an online training event, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-9904, https://doi.org/10.5194/egusphere-egu21-9904, 2021.

The Operational Water Service of C3S (developed by the Swedish Meteorological and Hydrological Institute (SMHI)) aims to help a broad range of water managers with water allocation, flood management, ecological status and industrial water use, to adapt their strategies in order to adapt to climate variability and change. The aim is to speed up the workflow in climate-change adaptation by using seasonal hydrological forecasts and climate-impact indicators. This is done by offering an interactive web application with refined data, guidance and practical showcases to water managers across Europe. Policy makers will find a comprehensive overview for Europe with key messages and consultants can use the service for developing climate impact assessments and adaptation strategies.

The development of the current operational climate service for water management is based on the experience from two previous proof-of-concepts and will also be aligned with the hydrological model system of the Copernicus Emergency Management Service (CEMS).  The service is uses data from the Climate Data Store and the operational hydrological seasonal forecasting system runs entirely in the European Centre for Medium range Weather Forecasts (ECMWF) technical environment, although developed by SMHI.

The operational Water Service of C3S will be launched during the spring of 2021, and a series of activities and user interactions will be organised to ensure that the applications developed for the service fulfil the users’ needs. Here, we present the development process of the operational service and key outcomes from co-design interactions and resulting applications. The key issues identified by the user community were: i) clear visualisation and graphical representation of skill in seasonal forecasts and confidence in climate projections, ii) need of detailed documentation and process transparency in hydrological models and production of data, iii) user guidance and tutorials are needed for better understanding of the applications, and iv) workflows and scripts for indicator production in new applications for developers of information systems.

How to cite: Photiadou, C., Berg, P., Bozhinova, D., Eronn, A., Ludwig, F., del Pozo Garcia, M. P. G., and Pechlivanidis, I.: Operational Water Service for Copernicus Climate Change Service: development at European scale, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-10924, https://doi.org/10.5194/egusphere-egu21-10924, 2021.

The next generation of climate services needs not only tailoring to specific user needs but also to provide access to key information in a usable way that satisfies the needs of different users’ profiles. This holds especially for web-based services. Here, we present the outcomes from developing such a new interactive prototype, known as Climate Information (https://climateinformation.org/). The service provides data for robust climate analysis to underpin decision-making when planning measures to compensate for climate impact. Readily available climate indicators will help defining future problems, assess climatic stressors, and analyse current and future risks. This makes a climate case, which is the basis for developing interventions and propose investments. The main goal of the platform is to facilitate the communication on climate information between climate modelling communities and adaptation or mitigation initiatives from vulnerable countries that are applying for funds from the Green Climate Fund (GCF).

A participatory process was ensured during four workshops in four pilot countries, organised by the World Meteorological Organisation (WMO), with the active involvement of national and international experts. During this process it was made clear, that there is a strong need for knowledge in climate science in all countries, while in most countries there was also an increasing need of capacity in hydrological modelling and water management.

The active interaction during the workshops was found necessary to facilitate the dialogue between service developers and users. The co-development process is not always institutionalised in many vulnerable countries and the capacity level restricts national entities to only act via international intermediaries. The level of knowledge and capacity in climate and hydrological science in the pilot countries varied significantly, which was an important obstacle when establishing a direct access modality to support different organisations. The diversity of user groups made it difficult to identify a “one-size-fits-all” for the web platform. Instead, a set of interactive tools was developed. Our interactions with the users, which covers a part of a co-development process, facilitated the dialogue between service developers and users. Understanding the users, transparency on potentials and limitations of climate services, and capacity development in climate science and methods were required components in the development of the service.

How to cite: Gyllensvärd, F., Photiadou, C., Arheimer, B., Bosshard, T., Capell, R., Elenius, M., Gallo, I., Klehmet, K., Little, L., Ribeiro, I., Santos, L., and Sjökvist, E.: Designing a Climate Service for Planning Climate Actions in Vulnerable Countries, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-11031, https://doi.org/10.5194/egusphere-egu21-11031, 2021.

Under the context of the H2020 S2S4E project, industrial and research partners co-developed a fully-operational Decision Support Tool (DST) providing during 18 months near real-time subseasonal and seasonal  forecasts tailored to the specific needs of the renewable energy sector. The tool aimed to breach the last mile gap between climate information and the end-user by paying attention to the interaction with agents from the sector, already used to work with weather information, and willing to extend their forecasting horizon by incorporating climate predictions into their daily operations.

With this purpose, the tool gathered a heterogeneous dataset of seven different essential climate variables and nine energy indicators, providing for each of them bias-adjusted probabilistic information paired with a reference skill metric. To achieve this, data from state-of-the-art prediction systems and reanalysis needed to be downloaded and post-processed, fulfilling a set of quality requirements that ensure the proper functioning of the operational service. During the design, implementation, and testing phases, a wide range of scientific and technical choices had to be made, making clear the difficulties of transferring scientific research to a user-oriented real-time service. A brief showcase will be presented, exemplifying the different tools, methodologies, and best practices applied to the data workflow, together with a case study performed in Oracle’s cloud infrastructure. We expect that by making a clear description of the process and the problems encountered, we will provide a valuable experience for both, upcoming attempts of similar implementations, and the organizations providing data from climate models and reanalysis.

How to cite: Palma, L., Manrique, A., Lledó, L., Nicodemou, A., Bretonnière, P.-A., Pérez-Zanón, N., Ho, A., and Soret, A.: Lessons learned from the implementation of the near real-time S2S4E Decision Support Tool, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-15537, https://doi.org/10.5194/egusphere-egu21-15537, 2021.

Sand and Dust Storms (SDS) are extreme meteorological phenomena associated with high amounts of atmospheric mineral dust. SDS are an essential element of the Earth’s natural biogeochemical cycles but are also partly caused by human factors including anthropogenic climate change and unsustainable land and water management; in turn, SDS contribute to climate change and air pollution. SDS have become a serious global concern in recent decades due to their significant impacts on the environment, health, agriculture, livelihoods, and the economy. The impacts are felt throughout the developed and developing world and their mitigation is aligned with several of the United Nations’ Sustainable Development Goals. There has been an ever-increasing need for accurate information and predictions on SDS—particularly over desert regions such as the Sahara and in the Middle East—to support early warning systems as well as preparedness and mitigation plans, in addition to growing interest from diverse stakeholders and policymakers in the solar energy, health, environment and aviation sectors. 

The ongoing ERA4CS ‘Dust Storms Assessment for the development of user-oriented Climate services in Northern Africa, the Middle East and Europe’ (DustClim) project is enhancing our knowledge of the ways SDS affect society by producing and delivering an advanced dust regional model reanalysis for N. Africa, the Middle East and Europe, based on the MONARCH chemical weather prediction system (Pérez et al. 2011; Di Tomaso et al. 2017) and satellite retrievals over dust source regions, and by developing dust-related services tailored to strategic planning, operations, and policy-making in the air quality, aviation, and solar energy sectors.  

In this contribution, we will present how the resulting dust reanalysis is used as the basis to understand the mid-to-long-term impacts and implications of operating (and regulating) in risky sand and dust environments, namely: (1) the mineral dust component of air quality and its health and regulatory implications; (2) aircraft and airport operations, maintenance and planning; (3) strategic investment and operations optimization in solar energy. We will present our development approach that integrates scientific, industrial and regulatory knowledge, addressing ‘objective threats’ in dialogue with industry partners and public stakeholders (Votsis et al. 2020). Finally, we present an overview of the developed portfolio of SDS climate services for the three aforementioned sectors.

Acknowledgment

The authors acknowledge DustClim project, part of ERA4CS, an ERA-NET initiated by JPI Climate, and funded by FORMAS (SE), DLR (DE), BMWFW (AT), IFD (DK), MINECO (ES), ANR (FR) with co-funding by the European Union (435690462); PRACE (eDUST, eFRAGMENT1, eFRAGMENT2); RES (AECT-2020-3-0013) for awarding access to MareNostrum at BSC and for technical support.

References

Di Tomaso, E. et al. (2017): Assimilation of MODIS Dark Target and Deep Blue observations in the dust aerosol component of NMMB-MONARCH version 1.0, Geosci. Model Dev., 10, 1107-1129, doi:10.5194/gmd-10-1107-2017.

Pérez, C. et al. (2011): An online mineral dust aerosol model for meso to global scales: Model description, annual simulations and evaluation, Atmos. Chem. Phys., 11, 13001-13027, doi: 10.5194/acp-11-13001-2011.

Votsis, A. et al. (2020): Operational risks of sand and dust storms in aviation and solar energy: the DustClim approach, FMI's Climate Bulletin: Research Letters 1/2020, doi: 10.35614/ISSN-2341-6408-IK-2020-02-RL.

How to cite: Votsis, A., Basart, S., Barnaba, F., Di Tomaso, E., Lindfors, A., Mona, L., Mytilinaios, M., Formenti, P., Rautio, T., Wang, Y., Werner, E., and Pérez García-Pando, C.: Addressing the impacts of sand and dust storms in North Africa, the Middle East and Europe for air quality, aviation and solar energy: the DustClim approach to climate services, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-12819, https://doi.org/10.5194/egusphere-egu21-12819, 2021.

Successful adaptation to climate change worldwide will require many local climate change risk assessments. However, appropriate and tailored climate services and information tools are lacking, particularly in developing countries. Co-produced, user-driven climate services are a recognized means for effective generation and provisioning of relevant climate information and support the utilization by decision-makers, enabling them to account for climate change in their risk portfolios. In the CO-MICC project (ERA4CS), a data and knowledge portal is co-developed with stakeholders based on global-scale multi-model simulations of hydrological variables. In a participatory manner, we focussed on (1) eliciting the relevant hydrological hazard indicators, (2) representing their uncertainty quantitatively in a way that is both scientifically correct and utilizable to the diverse users of the hazard information, and (3) creating guidance on how to integrate the uncertain global information into regional-scale assessments of water-related climate change risk and adaptation assessments. Adapting the tandem framework of the Swedish Environmental Institute (SEI), participatory stakeholder dialogues including seven workshops with stakeholders from focus regions in Europe and Northern Africa, and finally with globally-acting companies serve to integrate the various experiences, needs and expectations of various regions and users. Participants included local researchers, experts from meteorological services and decision-makers from regional and national hydrological agencies. Together, we co-produced relevant model output variables and appropriate end-user products encompassing static and dynamically generated information in a web portal. The global-scale information products include interactive maps, diagrams, time series graphs, and suitably co-developed statistics, with appropriate visualization of uncertainty. In complement, the knowledge tool provides transparent meta-information, tutorials and handbook guidelines to utilize the provided information in models of local participatory risk assessments. While CO-MICC enables access to this information to a broad range of stakeholders from around the world (policy makers, NGOs, the private sector, the research community, the public in general) for their region of interest, it additionally sheds light on the optimal design and methods of co-development processes.

How to cite: Kneier, F., Cáceres, D., Dietrich, S., Schwanenberg, D., Köthe, H., and Döll, P.: Co-developing a data and knowledge portal to support stakeholder risk assessments with uncertain, global, multi-model based information on hydrological hazards of climate change, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-12926, https://doi.org/10.5194/egusphere-egu21-12926, 2021.