CL5.1.1

EDI
Climate Services - Underpinning Science

Climate services challenge the traditional interface between users and providers of climate information as it requires the establishment of a dialogue between subjects, who often have limited knowledge of each-other’s activities and practices. Increasing the understanding and usability of climate information for societal use has become a major challenge where economic growth, and social development crucially depends on adaptation to climate variability and change.

To this regard, climate services do not only create user-relevant climate information, but also stimulate the need to quantify vulnerabilities and come up with appropriate adaptation solutions that can be applied in practice.

The operational generation, management and delivery of climate services poses a number of new challenges to the traditional way of accessing and distributing climate data. With a growing private sector playing the role of service provider is important to understand what are the roles and the responsibilities of the publicly funded provision of climate data and information and services.

This session aims to gather best practices and lessons learnt, for how climate services can successfully facilitate adaptation to climate variability and change by providing climate information that is tailored to the real user need.
Contributions are strongly encouraged from international efforts (GFCS, CSP, ClimatEurope…); European Initiatives (H2020, ERA4CS, C3S, JPI-Climate…) as well as national, regional and local experiences.

Convener: Alessandro Dell'Aquila | Co-conveners: Nube Gonzalez-Reviriego, Verónica TorralbaECSECS, Christiana Photiadou, Andrej Ceglar
Presentations
| Thu, 26 May, 11:05–11:42 (CEST), 13:20–14:39 (CEST)
 
Room 1.34

Presentations: Thu, 26 May | Room 1.34

11:05–11:06
11:06–11:12
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EGU22-2407
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On-site presentation
Leopold Haimberger, Ulrich Voggenberger, and Federico Ambrogi

Within the Copernicus Climate Change Service (C3S), several efforts have been initated for providing observation data via the Climate Data Store (CDS). We report on the InSitu Comprehensive Upper Air Network service which is under review for publication via the CDS.
Compared to existing repositories of historical radiosonde and PILOT balloon data, it introduces important novelties:
1) besides long-period records, it contains also short-period records, which are valuable for climate data assimilation efforts such as ERA5
2) homogeneity adjustments for temperature, humidity and wind for all records longer than a year.
3) observation+representativity error estimates derived from ERA5 reanalysis departure statistics
4) additional data and metadata that accompany observation data, such as departure statistics and instrumentation information that can be downloaded in structured form
5) a flexible and user friendly interface, based on that of gridded data from the CDS, that allows to download data in CSV or netCDF formats, suitable for both time series analysis (long single station records) but also reanalysis purposes (all observation records for a point in time). 


Existing challenges regarding the formats to be used and regarding a sensible structuring of the metadata will be discussed. We will also outline the future extension of the service to offer gridded products out of the station records. 

How to cite: Haimberger, L., Voggenberger, U., and Ambrogi, F.: A first version of a comprehensive upper air network service back to 1905 on the Copernicus platform, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-2407, https://doi.org/10.5194/egusphere-egu22-2407, 2022.

11:12–11:18
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EGU22-5525
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On-site presentation
Sylvie Parey, Lila Collet, Joël Gailhard, Boutheina Oueslati, and Paul-Antoine Michelangeli

Impact studies, devoted to the energy demand in buildings or to the watershed hydrology, often need climate variable time series at the hourly time scale. However, climate projection outputs are mostly available at the daily time step, except for a few variables provided at the 3- or 6-hourly time step in some cases. In this paper, two ways of computing a diurnal cycle developed and used in impact studies at EDF/R&D are discussed.

The first approach has been defined to provide consistent hourly projections for four variables used to estimate the energy demand for heating/cooling of buildings at the 2050 horizon: temperature, wind speed, radiation and relative humidity at different geographical locations in France. The main idea is to use the distribution of the daily and geographical mean temperature over the whole French territory to identify an analogue day in the ERA5 reanalysis database. Then, for each variable and each location, the differences (for temperature) or ratios (for the other variables) between the daily mean and each hourly value are added to / multiplied by the daily mean value to assess local diurnal cycles. The approach is illustrated for 3 locations in France and its validation in terms of spatial and intervariable consistency is discussed, together with a highlight of the limitations and possible improvements.

The second approach uses a statistical bias correction method, namely the CDF-t (“Cumulative Distribution Function-transform”) approach (Michelangeli et al., 2009). The CDF-t was initially developed to spatially downscale and bias correct climate model projections by defining a correction function regarding the cumulative distribution functions of observed and modelled data over the reference and future time periods. In this work, it was adapted to temporally downscale climatic projections of surface thermal radiation downward from the daily to the 3-hourly time step for seven locations. It was based on daily series for the 1976-2065 time period and 3-hourly time series for 33 years scattered in the total time period. The CDF-t was applied as follow: 3-hourly time series are considered as “observations”. The 33 years displaying those data constitute the calibration time period, the remaining 57 years from the 1976-2065 time period are considered as the projection time period. Daily data are first roughly downscaled to the 3-hour time step by allocating the same daily values to all the 3-hour time steps across the 1976-2065 time period. Then the CDF-t method was applied to the 3-hour series considering the calibration and projection time periods. Results show satisfactory performances in terms on inter-annual and seasonal variability and cumulative distribution function. Mean annual bias is below 5% across the seven locations.

 

Reference:

Michelangeli, P.-A., Vrac, M., and Loukos, H. Probabilistic downscaling approaches: Application to wind cumulative distribution functions, Geophys. Res. Lett., 2009, 36, L11708, doi:10.1029/2009GL038401.

How to cite: Parey, S., Collet, L., Gailhard, J., Oueslati, B., and Michelangeli, P.-A.: Retrieving diurnal cycles from daily projections for impact studies, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-5525, https://doi.org/10.5194/egusphere-egu22-5525, 2022.

11:18–11:24
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EGU22-7439
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ECS
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Virtual presentation
Johannes Mayer, Michael Mayer, and Leopold Haimberger

Climate change is accelerating, and its implications are getting more severe every year. As the exchange of energy within the climate system plays a major role during this time, it becomes pivotal to track anomalous energy transports. A precise quantification of Earth's energy balance is thus indispensable in order to understand the way climate is changing. 

We report the publication of a novel dataset providing mass-consistent global atmospheric energy and moisture budget terms for the period 1979-2020. The dataset is derived from 1-hourly analyzed state quantities of the fifth major global reanalysis produced by ECMWF using advanced numerical and diagnostic methods. It provides monthly averages of vertically integrated atmospheric water vapour and moist static plus kinetic energy transports on a 0.25° regular grid. The fields are much less noisy than similar quantities from standard ERA5 postprocessing, although they have been calculated at full horizontal resolution (T639). They show sharp gradients along coastal lines and sea-ice edges making them well suited for regional studies. Other possible applications of this dataset are, e.g., the assessment of global atmospheric energy and moisture budgets, evaluation of ocean-to-land energy and moisture transports, and meridional atmospheric energy transports. Furthermore, various surface flux terms can be estimated indirectly, such as freshwater fluxes or net heat fluxes when combined with state of the art top-of-the-atmosphere products such as CERES-EBAF. This dataset is publicly available via the Copernicus Climate Data Store (see "Refined atmospheric energy budget from ERA5").

How to cite: Mayer, J., Mayer, M., and Haimberger, L.: Refined global atmospheric energy budget from ERA5, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-7439, https://doi.org/10.5194/egusphere-egu22-7439, 2022.

11:24–11:30
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EGU22-13206
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ECS
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On-site presentation
Verónica Torralba, Stefano Materia, Carmen Álvarez-Castro, Paolo Bonetti, Alberto Maria Metelli, Marcello Restelli, and Silvio Gualdi

Hydropower is one of the industrial sectors more strongly affected by the timing and intensity of extreme climatic conditions, especially related to precipitation. Particularly, the recent expansion of the hydropower capacity in South American regions has raised the interest of this sector in seasonal forecasts that can be used to anticipate persistent precipitation anomalies (e.g. meteorological droughts) over specific basins. Some of the limitations for the generation of seasonal forecast products that can be integrated in hydropower decision-making processes are the coarse spatial resolution and the limited forecast quality (i.e. systematic errors, low skill) of the current operational seasonal forecast systems. To overcome this problem, we propose a methodology based on machine learning-informed analogs. Information-theoretic preprocessing has been used to identify the large-scale drivers of precipitation in a drainage basin located in southern Brazil, where hydroelectric energy is produced. This information allows us to exploit the ability of the dynamical seasonal forecast systems to predict these large-scale drivers in combination with the statistical link between these drivers and precipitation. We have employed the global CMCC-SPS35 seasonal forecasts at 1° spatial resolution and the CHIRPS-V2 precipitation dataset at 0.05° to produce dynamical-statistical seasonal forecasts of precipitation. The results show that downscaled forecasts exhibit higher skill and are affected by smaller biases than those obtained directly from the operational dynamical systems. This suggests that there is potential for the use of hybrid forecasts in the optimal management of South Brazilian hydropower production. 

How to cite: Torralba, V., Materia, S., Álvarez-Castro, C., Bonetti, P., Metelli, A. M., Restelli, M., and Gualdi, S.: Seasonal forecasts for hydropower: downscaling of precipitation in South American basins, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-13206, https://doi.org/10.5194/egusphere-egu22-13206, 2022.

11:30–11:36
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EGU22-7917
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Virtual presentation
Elisa Delpiazzo, Carlotta Gianni, Paolo Mazzoli, Francesco Dalla Valle, and Stefano Bagli

Demonstrating the potential economic value of seasonal forecasts is a fundamental signal to mainstream their application in real life and make them actionable instruments to cope with future climate change and to promote adaptation measures and sustainable management of natural resources.

This presentation aims to explore the potential economic value of monthly seasonal forecasts of water flows in a reservoir located in Colombia (i.e. Betania) delivering hydropower production during the period 1993-2016. To assess the economic value a maximizing simulation is applied using two alternative forecasts samples, namely the climatological mean, and the forecasts produced by the climate service SCHT (www.https://gecosistema.com/climate-tools/scht-smart-climate-hydropower-tool/). Then, the simulation has been fed with effective realizations to produce a benchmark. Finally, we get the maximum potential value, when effective realization is considered, and the potential achievable values of the alternative forecasts and their deviation with respect to the benchmark. The simulation is set as a revenue maximizing problem for a representative producer according to a series of technical constraints, such as the reservoir capacity and its volume.

Results demonstrate that SCHT forecasts have a positive value compared to the climatological mean forecasts in normal conditions. For this reason, the analysis is enriched with a sensitivity test on the technical constraints. Therefore, we produce a set of alternative scenarios considering different capacity and volume levels. For volume, we assume either 100% or 50% (net of natural discharges), and for capacity, we assume either 900 m3/s (the maximum) or 600 m3/s. The final objective is to understand whether the technical constraints affect the results and which constraints has a higher impact.

How to cite: Delpiazzo, E., Gianni, C., Mazzoli, P., Dalla Valle, F., and Bagli, S.: Potential economic value of seasonal forecasts of water flows for hydropower production., EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-7917, https://doi.org/10.5194/egusphere-egu22-7917, 2022.

11:36–11:42
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EGU22-12180
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ECS
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Presentation form not yet defined
Sara Dal Gesso, Marco Venturini, and Marcello Petitta

In the agriculture sector, climate-related economic losses have reached an average of €73 bn a year worldwide. It is, hence, of utmost importance to act now to build a climate-resilient agricultural system by forecasting the future climate risk and implementing adaptation actions. Agriculture insurance plays a crucial role in promoting the resilience of the agricultural sector to external shocks, as it covers the production and financial risks of farmers, and related shortfall risks of interconnected stakeholders throughout the food chain. For a climate-proof agriculture, the insurance industry needs to evolve. Offering traditional coverage is becoming insufficient, with climate change unfolding its impact on the severity and frequency of extreme events.

We present a climate service for monitoring and forecasting the climate risk on crop and livestock production tailored to the needs of insurers providing agricultural coverage. The climate service has been developed and validated within the ESA-funded project TERRA - climaTe sERvices for a Resilient Agriculture, thanks to the engagement of key stakeholders in the whole value chain. The service is a risk assessment and monitoring tool based on a climate-enhanced vulnerability index. Such an index seamlessly integrates satellite data, reanalysis products and seasonal forecasts. In particular, it combines the level-2 variables from sentinel 1, 2 and 3, available through the Copernicus Global Land Service, in a unified vulnerability index, that is integrated with the reanalysis products and seasonal forecasts available through the Climate Data Store of the Copernicus Climate Change Service. The climate-enhanced vulnerability index is applied to the specific case of forage production in Italy.

How to cite: Dal Gesso, S., Venturini, M., and Petitta, M.: Synergizing earth observations and seasonal forecasts within an innovative climate index: the case of forage production in Italy , EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-12180, https://doi.org/10.5194/egusphere-egu22-12180, 2022.

Lunch break
13:20–13:21
13:21–13:27
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EGU22-5469
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ECS
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Virtual presentation
Iulia Anton, Roberta Paranunzio, Salem Gharbia, Luca Baldini, Tasneem Ahmed, Filippo Giannetti, Carlo Brandini, Alberto Ortolani, Cecil Meulenberg, Elisa Adirosi, She Hawke, Francesco Pilla, and Jose Gregorio Iglesias Rodriguez

The demand for tailored climate data by different users is growing worldwide together with the awareness of the challenges posed to society and the environment by climate change. The extreme weather events intensification, sea-level rise, and coastal erosion are urgent challenges to be addressed by European coastal cities. The overreaching scope of the H2020 SCORE (Smart Control of the Climate Resilience in European Coastal Cities) project is to develop a framework for the definition and uptake of integrated Ecosystem-Based Approaches (EBA) and smart digital tools by establishing a network of 10 coastal city' living labs' (CCLLs) to increase the climate resilience of European coastal cities. To achieve this, the first steps are focused on i) the identification and selection of reference datasets for the historical baseline characterization and the projections for the next decades, ii) the downscaling of climate projections in order to produce a dataset of environmental parameters with the suitable temporal and spatial resolution for the project CCLLs' application needs, and iii) the development of statistical tools for data analysis, modeling and testing to assess the occurrence of major coastal hazards and the future evolution trends of the coastline. For this purpose, open, free, and reliable climate data are needed.

Based on some essential requirements, a procedure to select, from the main European climate services, fit-for-purpose climate and marine data of interest for SCORE users has been set up. Moreover, a step-by-step procedure on how to access and handle these data has been provided.  One of the main issues encountered while exploring the vast range of different climate services and datasets available consists in the articulation of the users' needs. In particular, the best coverage in terms of variables of interest for modeling and Spatio-temporal resolution must be ensured, while guaranteeing a good users' experience in terms of easy accessibility and the provision of information on (meta)data quality, standards, and conventions. The fragmentation of marine data repositories during the previous decades, along with their limited historical temporal coverage are other main challenges encountered. In addition, notwithstanding the availability of datasets downscaled from global to regional models, the spatio-temporal resolution of most part of datasets requires undertaking some statistical or physical downscaling procedures for their use in local impact studies.

We thus construct our analysis on those databases and services which are officially available through and/or supported by EU institutions like, e.g., the Copernicus Climate Change Service (C3S) and the Climate Data Store (CDS), the Copernicus Marine Environment Monitoring Service (CMEMS) portal or the European Marine Observation and Data Network (EMODnet) initiative.    The various criteria defined to select the most appropriate climate services and related datasets for the SCORE activities will be presented as well as a few case studies as examples of possible climate information communication strategies, to help the end-user practically understand and tackle the challenges when interacting with the dataset-interface and in data handling procedures.

How to cite: Anton, I., Paranunzio, R., Gharbia, S., Baldini, L., Ahmed, T., Giannetti, F., Brandini, C., Ortolani, A., Meulenberg, C., Adirosi, E., Hawke, S., Pilla, F., and Iglesias Rodriguez, J. G.: Challenges in retrieving and using climate services' data for local-scale impact studies: insights from the SCORE project, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-5469, https://doi.org/10.5194/egusphere-egu22-5469, 2022.

13:27–13:33
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EGU22-12892
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Highlight
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Presentation form not yet defined
Lessons learnt from the 2018 Evaluation of the European Climate Adaptation Platform, Climate-ADAPT (Climate-ADAPT), on the sharing of knowledge for a climate-resilient Europe 
(withdrawn)
Kati Mattern, Hanne van den Berg, Hans-Martin Füssel, Aleksandra Kazmierczak, Blaz Kurnik, and Christiana Photiadou
13:33–13:39
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EGU22-5499
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Highlight
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On-site presentation
Quentin Lejeune, Peter Pfleiderer, Thessa Beck, Inga Menke, Chahan Kropf, Inga Sauer, and Carl Schleussner

This online climate impact tool was developed as part of a collaboration with the Network for Greening the Financial System (NGFS) aiming at improving the understanding of how physical risks from climate change impact the macro-economic and financial systems. Interactions with stakeholders from the NGFS enabled to identify how tailored climate impact information could facilitate this understanding by fulfilling the following criteria: (i) provision of projections for other scenarios that those classically used in climate science, more tailored to the financial and macro-economic systems, (ii) for many sectoral indicators with a specific interest for economic damages from climate impacts, (iii) with a comprehensive estimate of the associated uncertainty and especially its upper bound, and (iv) in a spatially explicit way but also aggregated over administrative units.

As a result, the Climate Impact Explorer provides impact projections aggregated over all continents, countries and their provinces for many sectoral and economic damage indicators, as well as several global warming levels and various emissions scenarios, including those co-developed with the NGFS. The associated uncertainty ranges encompass both the global climate sensitivity to emissions and the response of local impacts to global warming. The tool also displays maps of projected impacts for 1.5, 2, 2.5 and 3°C of global warming over all countries in the world. All time series plots, maps and underlying data can be freely downloaded.

No dedicated simulations were run to produce the underlying data, instead we made use of the 0.5°x0.5° impact projections from ISIMIP2b, as well as existing runs by the CLIMADA model at a resolution of 5 arcmins for the economic damage indicators. The employed methodology can be applied to any emissions scenarios for which the resulting global warming trajectories are available.

The tool has already been used by central banks and other financial institutions or companies, and has proved of high interest for stakeholders from developing countries where little impact information is available. Efforts are currently ongoing to use information from the Climate Impact Explorer for stress testing of macro-economies to climate physical risks. This should hopefully lead to further improve the understanding of data needs and overall help increase the resilience of economies and the financial system to climate change.

How to cite: Lejeune, Q., Pfleiderer, P., Beck, T., Menke, I., Kropf, C., Sauer, I., and Schleussner, C.: The Climate Impact Explorer, a free online tool providing sectoral impact projections for a wide range of scenarios down to the subnational level, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-5499, https://doi.org/10.5194/egusphere-egu22-5499, 2022.

13:39–13:45
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EGU22-6197
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Virtual presentation
Nils Hempelmann, Carmen Alvarez-Castro, Christopher Kadow, Stephan Kindermann, Carsten Ehbrecht, Étienne Plésiat, and Ilias Pechlivanidis

Producing and providing useful information for climate services requires vast volumes of data to come together which requires technical standards. Especially in the case of extreme climate events, where scientific methods for appropriate assessments, detection or even attribution are facing high complexity for the data processing workflows, therefore the production of climate information services requires optimal technical systems to underpinn climate services with science. These climate resilience information systems like the Climate Data Store (CDS) of the Copernicus Climate Change Service (C3S) can be enhanced when scientific workflows for extreme event detection are optimized as information production service, accordingly deployed to be usable by extreme event experts to facilitate their work through a frontend. Deployment into federated data processing systems like CDS requires that scientific methods and their algorithms be wrapped up as technical services following standards of application programming interfaces (API) and, as good practice, even FAIR principles. FAIR principles means to be Findable within federated data distribution architectures, including public catalogues of well documented scientific analytical processes. Remote storage and computation resources should be operationally Accessible to all, including low bandwidth regions and closing digital gaps to ‘Leave No One Behind’. including Data inputs, outputs, and processing API standards are the necessary conditions to ensure the system is Interoperable. And they should be built from Reusable building blocks that can be realized by modular architectures with swappable components, data provenance systems, and rich metadata.
Here we present challenges and preliminary prototypes for service which are based on OGC API standards for processing (https://ogcapi.ogc.org/processes/) open geospatial consortium (OGC). We are presenting blueprints on how AI-based scientific workflows can be ingested into climate resilience information systems to enhance climate services related to extreme weather and impact events. The importance of API standards will be pointed out to ensure reliable data processing in federated spatial data infrastructures. Examples will be taken from the EU H2020 Climate Intelligence (CLINT; https://climateintelligence.eu/) project, where extreme events components will be developed for C3S. Within this project, appropriate technical services will be developed as building blocks ready to deploy into digital data infrastructures like C3S but also European Science Cloud, or the DIAS. This deployment flexibility results out of the standard compliance and FAIR principles. In particular, a service employing state-of-the-art deep learning based inpainting technology to reconstruct missing climate information of global temperature patterns will be developed. This OGC-standard based web processing service (WPS) will be used as a prototype and extended in the future to other climate variables. Developments focus on heatwaves and warm nights, extreme droughts, tropical cyclones and compound and concurrent events, including their impacts, whilst the concepts are targeting generalised opportunities to transfer any kind of scientific workflow to a technical service underpinning scientific climate service. The blueprints are taking into account how to chain the data processing from data search and fetch, event index definition and detection as well as identifying the drivers responsible for the intensity of the extreme event to construct storylines guiding to the event.

How to cite: Hempelmann, N., Alvarez-Castro, C., Kadow, C., Kindermann, S., Ehbrecht, C., Plésiat, É., and Pechlivanidis, I.: Deployment of scientific climate services for extreme events investigations, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-6197, https://doi.org/10.5194/egusphere-egu22-6197, 2022.

13:45–13:51
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EGU22-6372
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Highlight
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On-site presentation
Christian Pagé, Alessandro Spinuso, Abel Aoun, Lars Bärring, and Klaus Zimmermann

End users of climate change information are relying on climate services and tools in order to produce meaningful information for specific applications. Data volumes as well as the number of datasets are increasing very rapidly, and the ability to select, process and download all needed data is getting complex, technical and very time-consuming. It is especially true since those datasets are often distributed among several data centres and into a large quantity of files.

Several platform are being developed to hide this complexity to users and provide a seamless access to climate data, as well as to provide on-demand data analysis capabilities. We can cite, for example, the Copernicus Data Store (CDS https://cds.climate.copernicus.eu), along with its toolbox to perform online data analysis. Another platform is developed within the H2020 IS-ENES3 project, called climate4impact (C4I 2.0 https://dev.climate4impact.eu ). It is using an enhanced Jupyter-Lab environment called SWIRRL (Software for Interactive Reproducible Research Labs https://gitlab.com/KNMI-OSS/swirrl ) along with a collection of Jupyter notebooks (https://gitlab.com/is-enes-cdi-c4i/notebooks) as useful set of example on how to use the data.

Finally, the portal provides interactive pages for the evaluation of climate models (using ESMValTool) to guide users on selecting climate datasets. 

The notebooks that can be executed in C4I, are developed using a very convenient software library, which is made available via SWIRRL, to calculate climate indices and indicators called icclim (v5.0 https://github.com/cerfacs-globc/icclim ). This library, which is also in the process of being integrated into the C3S, is a flexible python software package to calculate climate indices and indicators. This tool adhere as much as possible to metadata conventions such as the Climate & Forecasting Conventions (CF-1.x) as well as the clix-meta (https://github.com/clix-meta) work that is being done in IS-ENES3. Proper provenance information still needs to be added. The ultimate goal is to be as close as possible to all FAIR aspects. icclim is designed with performance and optimisation in mind, because the goal is to provide on-demand calculations for users. It provides the implementation of most of the international standard climate indices such as ECAD, ETCCDI, ET-SCI, including the correct methodology for calculating percentile indices using the bootstrapping method. It has been validated against R.Climdex as well (https://cran.r-project.org/web/packages/climdex.pcic/index.html). This new 5.x version of icclim is based on functions from the xclim (https://github.com/Ouranosinc/xclim) python library, which was inspired by earlier versions of icclim, but using xarray and dask for data access and processing.

In this presentation, the climate4impact 2.0 platform will be described along with the icclim climate indices tool. Important metadata aspects will also be discussed (clix-meta). A few examples using the jupyter notebook collection will be shown.

 

This project (IS-ENES3) has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement N°824084.

How to cite: Pagé, C., Spinuso, A., Aoun, A., Bärring, L., and Zimmermann, K.: Better Tailoring of Climate Information for End Users using Targeted Interfaces and Tools, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-6372, https://doi.org/10.5194/egusphere-egu22-6372, 2022.

13:51–13:57
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EGU22-6593
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Virtual presentation
Josh Lieberman, Nils Hempelmann, Ag Stephens, Carsten Ehbrecht, Trevor Smith, Tom Landry, Cameron Wilson, and Eduardo Pechorro

Cloud-based big earth data workflow architectures for operational decision making across communities need to follow FAIR (Findable, Accessible, Interoperable, Reusable) principles in order to be effective. This presentation highlights mature implementations of OGC standards-based building blocks for climate data processing and service provision that are deployed in leading climate services information server systems such as the COPERNICUS Climate Change Service C3S. OGC Web Processing Services (WPS) form the bases of component operations in these implementations, from simple polygon subsetting to climate indices calculation and complex hydrological modelling. Interoperable building blocks also handle security functions such as user registration, client-site utilities, and data quality compliance. 

A particular focus will be the ROOCS (Remote Operations on Climate Simulations) project, a set of tools and services to provide "data-aware" processing of ESGF  (Earth System Grid Federation) and other standards-compliant climate datasets from modelling initiatives such as CMIP6 and CORDEX. One example is the WPS service ‘Rook’, that enables remote operations, such as spatio-temporal subsetting, on climate model data. It exposes all  the operations available in the ‘daops’ library based on Xarray. Finch is a WPS-based service for remote climate index calculations, also used for the analytics of ClimateData.ca, that dynamically wraps Xclim, a Python-based high-performance distributed climate index library. Finch automatically builds catalogues of available climate indicators, fetches data using “lazy”-loading, and manages asynchronous requests with Gunicorn and Dask. Raven-WPS provides parallel web access to a dynamically-configurable ‘RAVEN’ hydrological modelling framework with numerous pre-configured hydrological models (GR4J-CN, HBV-EC, HMETS, MOHYSE) and terrain-based analyses. Coupling GeoServer-housed terrain datasets with climate datasets, RAVEN can perform analyses such as hydrological forecasting without requirements of local access to data, installation of binaries, or local computation.

The EO Exploitation Platform Common Architecture (EOEPCA) describes an app-to-the-data paradigm where users select, deploy and run application workflows on remote platforms where the data resides. Following OGC Best Practices for EO Application Packages, Weaver executes workflows that chain together various applications and WPS inputs/outputs. It can also deploy near-to-data applications using Common Workflow Language (CWL) application definitions. Weaver was developed especially with climate services use cases in mind.

The architectural patterns illustrated by these examples will be exercised and tested in the upcoming OGC Climate Services Pilot initiative, whose  outputs will be also  incorporated into disaster risk indicators developed in the upcoming OGC Disaster Pilot 2022.

Further reading:

https://docs.google.com/document/d/1IrwlEiR-yRLcoI9fGh2B1leH4KU0v0SUMWQqiaxc1BM/edit



 

How to cite: Lieberman, J., Hempelmann, N., Stephens, A., Ehbrecht, C., Smith, T., Landry, T., Wilson, C., and Pechorro, E.: FAIR building blocks for climate resilience information systems, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-6593, https://doi.org/10.5194/egusphere-egu22-6593, 2022.

13:57–14:03
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EGU22-8444
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ECS
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On-site presentation
Ruben Hage, Angelique Lansu, Borjana Bogatinoska, and Joop de Kraker

To support climate change adaptation and mitigation measures of the Paris Agreement and Glasgow follow-up, practitioners co-designing measures within their community of practice require geodata to support decision making. Geodata has the qualities of being current and local, but is not always easily accessible. Climate applications, like climate services, can increase accessibility and ensure that data is ready-to-use, hence bridging the gap between geodata and practitioners. Such applications should meet the needs of a range of potential users, and it is therefore important for practitioners to be involved in their development. One way of ensuring adequate involvement is through participatory sessions where practitioners and developers co-create ‘user stories’ as means to identify requirements for the applications. This approach is by no means novel; user centric design has been applied in the development process of a wide range of applications. Nevertheless, it is worthwhile to investigate how user stories can be developed in such a way that they are of high quality and therefore useful as input for application development. Given the increased need for climate services such as climate change applications, this question is particularly important for applications that support climate action.

This empirical study addresses the information gap faced by geo data application developers concerning user needs. Through a series of participatory workshops with practitioners and developers, data on user-formulated needs covering a wide range of user types and Earth Observation application domains was collected. This concerns user stories that were co-created as input for the development of a range of decision support applications for the H2020 EIFFEL project. The aim of EIFFEL is to offer the Earth Observation community the capacity to exploit existing GEOSS datasets in order to support decision-making for climate change mitigation and adaptation. Central to the project are the development and uptake of 5 pilot applications on Climate Change adaptation and mitigation measures. The EIFFEL pilots cover the following GEO Societal Benefit Areas (SBAs): (1) water and land use management, (2) sustainable agriculture, (3) transport management, (4) sustainable urban development, and (5) disaster resilience.

By identifying the needs of practitioners, it is possible for developers to develop useful applications that are tailored to said needs. The online participatory workshops resulted in relevant data with regards to these needs. During these workshops, participants were invited to co-create user stories for the applications by identifying (1) the user, (2) climate change challenges faced, (3) goals, and (4) core tasks for every story. This data was interpreted by the researchers and subjected to further review in order to develop fully-fledged user stories for each pilot application. This process resulted in a total of 18 user stories for all pilot applications, with around 4 stories per SBA. Knowledge gaps to be addressed are on how this approach to user story creation helps to co-design climate applications that prove to enhance the access to and practical use of climate-relevant geodata. After all, the purpose of climate services is to make relevant climate information accessible to the user.

How to cite: Hage, R., Lansu, A., Bogatinoska, B., and de Kraker, J.: Co-designing user stories for geodata applications to support climate action in 5 GEO Societal Benefit Areas , EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-8444, https://doi.org/10.5194/egusphere-egu22-8444, 2022.

14:03–14:09
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EGU22-8582
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On-site presentation
Alessandro Dell'Aquila, António Graça, Marta Teixeira, Natacha Fontes, Nube Gonzalez-Reviriego, Raul Marcos-Matamoros, Chihchung Chou, Marta Terrado, Christos Giannakopoulos, Konstantinos Varotsos, Federico Caboni, Riccardo Locci, Martina Nanu, Sara Porru, Giulia Argiolas, Marta Bruno Soares, and Michael Sanderson

MED-GOLD is a four-year research and innovation project, whose main aim was to co-develop climate services for three staples of the Mediterranean food system, namely grapes, olives and durum wheat. This paper describes the methodology adopted for the co-development of the pilot climate service for the wine sector, focusing on the Douro Demarcated Region (DDR) in northern Portugal. 

In the first step, the MED-GOLD Champion Sogrape Vinhos identified  the key management decisions, the climatic information of interest and users’ needs for the wine sector in the DDR. From this information, the relevant bioclimatic indicators (and the key essential climate variables - ECVs) were identified and obtained. Afterwards, two compound risk indices, the Sanitary and Heat Risk indices, were also calculated as a combination of some of the aforementioned bioclimatic indicators. This methodological work was validated against the empirical climate characterization for the region of interest, of several ‘bad’ and ‘good’ years  chosen by users according to their recollections of grape and wine production outcomes, namely overall quality and yields. In addition, the overall strategy for selection of these years is presented. Then, the two components of the service based on seasonal predictions and longer-term climate projections are described. 

The final step was the development of the MED-GOLD Dashboard, an interactive tool that displays detailed historical climate data, seasonal predictions and climate projections. The dashboard is a map-based, user-focused visualization interface to aid easy access to and understanding of the data computed in an ICT platform. The dashboard was iteratively co-designed with the users to ensure their needs were met.

How to cite: Dell'Aquila, A., Graça, A., Teixeira, M., Fontes, N., Gonzalez-Reviriego, N., Marcos-Matamoros, R., Chou, C., Terrado, M., Giannakopoulos, C., Varotsos, K., Caboni, F., Locci, R., Nanu, M., Porru, S., Argiolas, G., Bruno Soares, M., and Sanderson, M.: Monitoring climate related risk and opportunities for wine sector: the MED-GOLD Pilot Service , EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-8582, https://doi.org/10.5194/egusphere-egu22-8582, 2022.

14:09–14:15
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EGU22-13357
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Virtual presentation
Chihchung Chou, Raül Marcos-Matamoros, Lluís Palma Garcia, Núria Pérez-Zanón, Marta Teixeira, Sara Silva, Natacha Fontes, Antonio Graça, Alessandro Dell'Aquila, Sandro Calmanti, and Nube González-Reviriego

To strengthen the seasonal forecast adoption on the vine management, this work introduces an observation-forecast blending approach to wine-sector indicators over the Iberian Peninsula. Five bioclimatic indicators (temperature and precipitation based) were considered as highly important from the perspective of wine-sector users, and the predictions were prepared for each month of the growing season by combining with previous observations as the indicator period progressed. The performance of this approach was then assessed, for each initialization date throughout the entire growing season, with Pearson’s correlation coefficient and Fair Ranked Probability Skill Score. The results show a marked increase in the skill metrics during the growing season from the early combinations for all the indicators. This progressive improvement of the forecasting skill provides the users with an opportunity to ponder anticipation and confidence when finding the best moment to make a specific decision and, thus, to improve their management. Meanwhile, the environmental impact could be reduced with the thoughtful application derived from the customised knowledge of climate information

How to cite: Chou, C., Marcos-Matamoros, R., Palma Garcia, L., Pérez-Zanón, N., Teixeira, M., Silva, S., Fontes, N., Graça, A., Dell'Aquila, A., Calmanti, S., and González-Reviriego, N.: Advanced seasonal predictions for vine management based on bioclimatic indicators tailored to the wine sector, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-13357, https://doi.org/10.5194/egusphere-egu22-13357, 2022.

14:15–14:21
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EGU22-9940
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Presentation form not yet defined
Laura Zamboni and John White

We've reached an inflection point in our relationship with the climate. Accelerating climate volatility is threatening the assets we rely on. To adapt, we need to be smarter, more prescient, more decisive, and more collaborative than ever before. We need new instruments and new insights. We need what we call Climate Intelligence.

 

Cervest creates Climate Intelligence for every person, asset, and decision. Climate Intelligence transforms how we build, manage, and de-risk our most valuable assets. Climate Intelligence enables us to adapt and decarbonize at scale to build an equitable and resilient future for our planet.

 

Cervest is at a turning point: we have concluded the first round of development whereby the initial offerings our scientists developed have been explored by major enterprises worldwide and incorporated in their decisions and reporting. A co-creation phase has been part of the process whereby we elicited users’ feedbacks. Learnings from this phase both confirmed some of our expectations and revealed needs we had not fully appreciated, many of which are leading to the deepening of our market education efforts as well as scientific-product developments. 

 

We find that to proactively adapt and decarbonize, it is essential to establish fruitful collaborations among different actors, and more specifically between Cervest and publicly funded institutions. It is within such collaborations that a swift exchange of information, data and expertise clarifies roles and responsibilities, ultimately accelerating our common drive to support adaptation and mitigation. 

We will share the lessons we have learned and, following the conveners’ call, our view of what is desirable from the public sector, ultimately engaging with academics.

How to cite: Zamboni, L. and White, J.: Cervest as the provider of Climate Intelligence: learnings from our users, collaborations with academics, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-9940, https://doi.org/10.5194/egusphere-egu22-9940, 2022.

14:21–14:27
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EGU22-11738
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ECS
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Virtual presentation
Vladimir Metelitsa

There is an increasing demand for tailored climate services to assist informed decision-making. The scientific basis is there, with high-quality relevant models available for nearly any facet and topic within climate science. However, usage of these models requires a high degree of subject matter knowledge. Conversely, many simplified tools and reports either lose the interactivity that models offer or still require at least a working knowledge of the field. My project explores the potential of Augmented Reality (AR) to provide interactive and easy-to-use climate services to non-scientists. AR could allow for a whole new class of users to participate in the climate change debate, by offering them to assess climate impacts of different climate scenarios and trade-offs between various response measures. One of the key benefits of mobile AR is its accessibility, since it does not require any special dedicated equipment, working on almost all smartphones and being familiar to many users who already experienced AR in other popular applications.


Two different AR approaches are used as the methodology. In-situ augmented reality is explored as a way to allow the user to assess climate impacts on their location, giving a more personal experience. Seeing the impacts on their own environment is more likely to leave an impression and influence users to make changes. On-table collaborative augmented reality simulations are used to provide a bird’s eye view of a larger area and to allow multiple-users to engage in the experience in a workshop style. In both approaches, the users are able to switch between different RCP climate scenarios and/or apply response measures, and instantly see the impacts of the change.

How to cite: Metelitsa, V.: Augmented Reality for the Visualization of the Impacts of Climate Change and Response Measures, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-11738, https://doi.org/10.5194/egusphere-egu22-11738, 2022.

14:27–14:33
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EGU22-12229
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Highlight
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Virtual presentation
Cheikh Kane

To support the development of climate-resilient pathways, several developing countries are urged to strengthen their scientific base to generate climate and weather information, products and services. This is usually achieved by developing the capacity of national hydro-meteorological services (NMHS) and warning services, to support in turn adaptation planning for intermediary and final users.

In West Africa, several countries, have adopted National Framework of Climate Services (NFCS), with the support of the Global Framework of Climate Services (GFCS) secretariat. They operationalize these NFCS by implementing national or regional climate and weather information-based programs, supported by different international agencies. The ultimate goal of these programs is to enhance the service delivery and warnings to communities, by strengthening the “last mile” connectivity.

Burkina Faso, Chad, Cote d'Ivoire, Liberia, Mali, Niger, Senegal, as well as the Economic Community of West African Sates (ECOWAS) organization itself benefit from the support of international agencies, to tackle the food insecurity and recurrent storm flooding issues they face. By enhancing the institutional capacities of their NHMS and other relevant institutions, including their disaster management authorities and early warning system for food security management agencies, the projects intend to solve the climate related food security crises, improve the short range forecasts for high impact weather and, generally speaking boost the uptake of climate information by the different stakeholders from different socio-economic sectors.

The underlying theory of change (ToC) for these programs is based on a systematic causal chain assuming that the improvement and modernization of the hydro meteorological systems and services of the countries, will result in the provision to communities and national users with adapted, accurate and timely weather, climate and hydrological information; taking advantage of these improvements, the national/regional enhanced institutions will then efficiently consider the demands of stakeholders at all levels of the country and adapt their offer accordingly.

This research is assessing the implementation of some NFCSs and "hydromet programs" running in West Africa. The preliminary results show that the causal chain of the ToC is not so straightforward. Even if opportunities exist in the region, challenges are still big. They range from lack of knowledge of the spectrum and diversity of stakeholders, their specific needs and demands that would inform their action, the broader sensitization to the use of the climate information and collection of their feedback on the services. These challenges suggest in particular that, the allocation of resources to weather in the public sector is unlikely to become more effective until the so called "weather prediction enterprise", takes an integrated perspective on weather forecasts, impacts and policy that provides decision makers with reliable information on the costs and benefits of alternative courses and make it easier for “outsiders” to penetrate that community, due to the required expertise.

How to cite: Kane, C.: National Frameworks for Climate Services in West Africa: Are we on the right pathway? , EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-12229, https://doi.org/10.5194/egusphere-egu22-12229, 2022.

14:33–14:39
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EGU22-8383
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ECS
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On-site presentation
Spyridon Paparrizos, Samuel Sutanto, Baba M. Jamaldeen, Abdulai Kantunsong Issahaku, Gordana Kranjac-Berisavljevic, Bizoola Z. Gandaa, Lisanne Nauta, Iwan Supit, and Erik van Slobbe

In Ghana, most of the farmers are engaged in small-scale rainfed farming where the success is influenced by how the farmers are able to march their decisions to the prevailing weather conditions. Climate information services (CIS), which includes weather forecasts, can help farmers to reduce their vulnerability to climate extremes and allow them to maximize agricultural productivity. Current services in Ghana and elsewhere in the world, however, only provides information on the recent and forecasted meteorological variables, primarily precipitation and temperature. Having access to other practical knowledge, such as soil moisture content would help farmers further in the decision-making process. Soil moisture is a key component for better farm management practices, because the plant establishment and growth are directly impacted by the soil moisture content. Therefore, this study aims to assess the importance of soil moisture information in farmers’ agricultural decision-making and to understand how this information is being perceived, assessed, and applied. An exploratory research, combined with field visits, farmer interviews, including questionnaires, and focus group discussions was carried out in three local farming communities i.e. Gbulung, Napakzoo, and Yapalsi in the outskirts of Tamale, northern Ghana. Results show that farmers clearly understand the importance of soil moisture for agriculture decision-making in every farming stages. Many farmers expressed that soil moisture information is highly important for fertilizer application and sowing. This information, however, is not well received by the farmers, causing farmers to rely on their indigenous knowledge to monitor the soil moisture conditions. Soil moisture forecast is ranked as the second critical information for farmers after precipitation. Capacity building and frequent interactions at farmer field schools and trainings could increase the farmer’s understanding and awareness of the role of soil moisture in agricultural decision-making. Moreover, farmers show an interest in a CIS embedded with a soil moisture forecast advisory module (CIS-SM) that could help them to increase the water-use efficiency and in the end, reduce the pressure on available water resources for agriculture.

How to cite: Paparrizos, S., Sutanto, S., Jamaldeen, B. M., Issahaku, A. K., Kranjac-Berisavljevic, G., Gandaa, B. Z., Nauta, L., Supit, I., and van Slobbe, E.: The role of soil moisture information in developing robust climate services for smallholder farmers: evidence from Ghana , EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-8383, https://doi.org/10.5194/egusphere-egu22-8383, 2022.