Subseasonal predictions for climate services, a recipe for operational implementation
The implementation of operational climate service prototypes, which encompasses the co-design and delivery of real-time actionable products with/to stakeholders, contributes to efficiently leveraging operational climate predictions into actionable climate information by providing practical insight o...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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Elsevier
2023-04-01
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| Series: | Climate Services |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2405880723000201 |
| _version_ | 1797801704972877824 |
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| author | Andrea Manrique-Suñén Lluís Palma Nube Gonzalez-Reviriego Francisco J. Doblas-Reyes Albert Soret |
| author_facet | Andrea Manrique-Suñén Lluís Palma Nube Gonzalez-Reviriego Francisco J. Doblas-Reyes Albert Soret |
| author_sort | Andrea Manrique-Suñén |
| collection | DOAJ |
| description | The implementation of operational climate service prototypes, which encompasses the co-design and delivery of real-time actionable products with/to stakeholders, contributes to efficiently leveraging operational climate predictions into actionable climate information by providing practical insight on the actual use of climate predictions. This work showcases a general guideline for implementing an operational climate service based on subseasonal predictions. At this timescale, many strategic decisions can benefit from timely predictions of climate variables. Still, the use of subseasonal predictions is not fully exploited. Here, we describe the key aspects considered to set up an operational climate service from the conception to the production phase. These include the choice of the subseasonal systems, the data sources and the methodology employed for post-processing the predictions. To illustrate the process with a real case, we present the detailed workflow design of the implementation of a climate service based on subseasonal predictions and describe the bias adjustment and verification methodologies implemented. This work was developed in the H2020 S2S4E project, where industrial and research partners co-developed a fully-operational Decision Support Tool (DST) providing 18 months of real-time subseasonal and seasonal forecasts tailored to the specific needs of the renewable energy sector. The operational workflow can be adapted to serve forecast products to other sectors, as has been proved in the H2020 vitiGEOSS project, where the workflow was modified to provide downscaled subseasonal predictions to specific locations. We consider this a valuable contribution to future developments of similar service implementations and the producers of the climate data. |
| first_indexed | 2024-03-13T04:54:33Z |
| format | Article |
| id | doaj.art-5b0276fc652040ba9753caddb9ee2be0 |
| institution | Directory Open Access Journal |
| issn | 2405-8807 |
| language | English |
| last_indexed | 2024-03-13T04:54:33Z |
| publishDate | 2023-04-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Climate Services |
| spelling | doaj.art-5b0276fc652040ba9753caddb9ee2be02023-06-18T05:02:52ZengElsevierClimate Services2405-88072023-04-0130100359Subseasonal predictions for climate services, a recipe for operational implementationAndrea Manrique-Suñén0Lluís Palma1Nube Gonzalez-Reviriego2Francisco J. Doblas-Reyes3Albert Soret4Barcelona Supercomputing Center (BSC), Carrer de Jordi Girona 29, 08034 Barcelona, SpainBarcelona Supercomputing Center (BSC), Carrer de Jordi Girona 29, 08034 Barcelona, Spain; Corresponding author.Barcelona Supercomputing Center (BSC), Carrer de Jordi Girona 29, 08034 Barcelona, SpainBarcelona Supercomputing Center (BSC), Carrer de Jordi Girona 29, 08034 Barcelona, Spain; Institució Catalana de Recerca i Estudis Avançats (ICREA), Passeig de Lluís Companys 23, 08010 Barcelona, SpainBarcelona Supercomputing Center (BSC), Carrer de Jordi Girona 29, 08034 Barcelona, SpainThe implementation of operational climate service prototypes, which encompasses the co-design and delivery of real-time actionable products with/to stakeholders, contributes to efficiently leveraging operational climate predictions into actionable climate information by providing practical insight on the actual use of climate predictions. This work showcases a general guideline for implementing an operational climate service based on subseasonal predictions. At this timescale, many strategic decisions can benefit from timely predictions of climate variables. Still, the use of subseasonal predictions is not fully exploited. Here, we describe the key aspects considered to set up an operational climate service from the conception to the production phase. These include the choice of the subseasonal systems, the data sources and the methodology employed for post-processing the predictions. To illustrate the process with a real case, we present the detailed workflow design of the implementation of a climate service based on subseasonal predictions and describe the bias adjustment and verification methodologies implemented. This work was developed in the H2020 S2S4E project, where industrial and research partners co-developed a fully-operational Decision Support Tool (DST) providing 18 months of real-time subseasonal and seasonal forecasts tailored to the specific needs of the renewable energy sector. The operational workflow can be adapted to serve forecast products to other sectors, as has been proved in the H2020 vitiGEOSS project, where the workflow was modified to provide downscaled subseasonal predictions to specific locations. We consider this a valuable contribution to future developments of similar service implementations and the producers of the climate data.http://www.sciencedirect.com/science/article/pii/S2405880723000201Subseasonal climate forecastingClimate servicesOperational climate predictionClimate adaptationEnergyAgriculture |
| spellingShingle | Andrea Manrique-Suñén Lluís Palma Nube Gonzalez-Reviriego Francisco J. Doblas-Reyes Albert Soret Subseasonal predictions for climate services, a recipe for operational implementation Climate Services Subseasonal climate forecasting Climate services Operational climate prediction Climate adaptation Energy Agriculture |
| title | Subseasonal predictions for climate services, a recipe for operational implementation |
| title_full | Subseasonal predictions for climate services, a recipe for operational implementation |
| title_fullStr | Subseasonal predictions for climate services, a recipe for operational implementation |
| title_full_unstemmed | Subseasonal predictions for climate services, a recipe for operational implementation |
| title_short | Subseasonal predictions for climate services, a recipe for operational implementation |
| title_sort | subseasonal predictions for climate services a recipe for operational implementation |
| topic | Subseasonal climate forecasting Climate services Operational climate prediction Climate adaptation Energy Agriculture |
| url | http://www.sciencedirect.com/science/article/pii/S2405880723000201 |
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