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The Critical Need for Hindcast Infrastructure in Climate Science and Sectoral Applications
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DOI：10.1175/BAMS-D-24-0311.1.png)
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Abstract
En 中文
Forecasting the impacts of climate extremes is challenging but critical to a range of sectors, including agriculture, water management, public health and safety, infrastructure, energy, national defense, and ecology. Foundational to these forecasts are hindcast model archives, which are routinely used for applications produced for the private sector and agencies, including the National Aeronautics and Space Administration (NASA), the National Oceanic and Atmospheric Administration (NOAA), the U.S. Department of State, and the U.S. Department of Defense. Forecast and hindcast archives underpin scientific inquiry funded by these agencies, particularly in relation to forecasting weather and climate extremes, as well as by the U.S. National Science Foundation (NSF). In this article, we catalog the sector-specific decision support systems that depend upon hindcast archives and survey the current state of hindcast archive infrastructure. We find that despite the tremendous amount of investment and the dependent decision support systems, the U.S. hindcast archive is relatively fragile and underfunded, especially when compared with the Copernicus system in Europe. We conclude with recommendations for improving hind-cast archive infrastructure to support routine sector-specific applications and improve resilience to climate extremes. SIGNIFICANCE STATEMENT: Forecasting the impacts of climate extremes is critical to a range of sectors, including agriculture, water management, public health and safety, infrastructure, energy, national defense, and ecology. Archives of model forecast runs are critical to these efforts. We outline how archives of model forecasts are critical for routine applications produced for the private sector and for a range of government agencies. Indeed, having a robust model forecast archive allows scientists to understand potential model biases in different weather types and also assess the potential of these models to accurately forecast extreme weather events. We find that despite the number of sectors that depend on accurate forecasts, the United States has a relatively fragile and underfunded archive infrastructure when compared with the equivalent system in Europe.
Keywords:
Forecasting
Hindcasts
Decision making
Decision support
Policy
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