Advances in statistical post-processing, blending, and verification of deterministic and probabilistic forecasts
Co-organized by AS1/CL5/HS13
Convener:
Maxime Taillardat
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Co-conveners:
Stéphane Vannitsem,
Jochen Broecker,
Sebastian Lerch,
Stephan Hemri,
Daniel S. Wilks,
Julie Bessac
Orals
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Wed, 26 Apr, 14:00–15:45 (CEST) Room -2.31
Posters on site
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Attendance Tue, 25 Apr, 14:00–15:45 (CEST) Hall X4
Posters virtual
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Attendance Tue, 25 Apr, 14:00–15:45 (CEST) vHall ESSI/GI/NP
At the same time, a lot of efforts are put in combining multiple forecasting sources in order to get reliable and seamless forecasts on time ranges from minutes to weeks. Such blending techniques are currently developed in many meteorological centers. These forecasting systems are indispensable for societal decision making, for instance to help better prepare for adverse weather. Thus, there is a need for objective statistical framework for "forecast verification'', i.e. qualitative and quantitative assessment of forecast performance.
In this session, we invite presentations dealing with both theoretical developments in statistical post-processing and evaluation of their performances in different practical applications oriented toward environmental predictions, and new developments dealing with the problem of combining or blending different types of forecasts in order to improve reliability from very short to long time scales.
14:00–14:05
5-minute convener introduction
Assessing predictive performance
Forecast post-processing
14:35–14:45
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EGU23-946
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ECS
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On-site presentation
14:55–15:05
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EGU23-2592
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ECS
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On-site presentation
15:05–15:15
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EGU23-10153
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On-site presentation
15:15–15:25
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EGU23-14712
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ECS
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On-site presentation
15:25–15:35
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EGU23-17348
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On-site presentation
Assessing predictive performance
Forecast post-processing
X4.98
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EGU23-15152
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ECS
X4.102
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EGU23-13327
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ECS
Forecast post-processing