The Critical Need for Hindcast Infrastructure in Climate Science and Sectoral Applications
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Details
- Title
- The Critical Need for Hindcast Infrastructure in Climate Science and Sectoral Applications
- Creators
- Weston Anderson - University of Maryland, College ParkMarybeth C. Arcodia - Colorado State UniversityDillon Amaya - NOAA Physical Sciences LaboratoryEmily Becker - University of MiamiJohn A. Callahan - NOAA Center for Operational Oceanographic Products & ServicesJason C. Furtado - University of OklahomaBenjamin Kirtman - University of MiamiSanjiv Kumar - Auburn UniversityMichelle L. L’Heureux - NOAA Climate Prediction CenterSarah M. Larson - North Carolina State UniversityDan Li - Boston UniversityMaria J. Molina - University of Maryland, College ParkMatthew Newman - NOAA Physical Sciences LaboratoryKathleen Pegion - University of OklahomaAndrew Robertson - Columbia UniversityErin Towler - NOAA Physical Sciences LaboratoryBaoqiang Xiang - University Corporation for Atmospheric Research
- Publication Details
- Bulletin of the American Meteorological Society, Vol.107(3)
- Publisher
- AMER METEOROLOGICAL SOC; BOSTON
- Number of pages
- 13
- Grant note
- NOAA: NA24OARX431C0065-T1-01 Regional and Global Model Analysis program area of the U.S. Department of Energy's (DOE) Office of Biological and Environmental Research (BER) as part of the Program for Climate Model Diagnosis and Intercomparison Project
The authors thank the U.S. CLIVAR Predictability, Prediction, and Applications Panel for its efforts to engage on the topic, as well as to the experts who contributed their time presenting at panel meetings, including Dr. William Merryfield, Dr. Jadwiga (Yaga) Richter, and Dr. Anca Brookshaw. M. C. A was funded, in part, by NOAA Grant NA24OARX431C0065-T1-01 and by the Regional and Global Model Analysis program area of the U.S. Department of Energy's (DOE) Office of Biological and Environmental Research (BER) as part of the Program for Climate Model Diagnosis and Intercomparison Project. The scientific results and conclusions, as well as any view or opinions expressed herein, are those of the authors and do not necessarily reflect the views of NWS, NOAA, or the Department of Commerce.
- Academic Unit
- Rosenstiel School Administration; Rosenstiel School; Institute for Data Science and Computing; Rosenstiel - Atmospheric Sciences
- Language
- English
- Resource Type
- Journal article
- Record Identifier
- 991032861007702976