Detailed Information

Process-oriented evaluation of climate and weather forecasting models

Cited 42 time in Web of Science Cited 44 time in Scopus

Maloney, Eric D.; Gettelman, Andrew; Ming, Yi; Davidneelin, J.; Barrie, Daniel; Mariotti, Annarita; Chen, C.-C.; Coleman, Danielle R. B.; Kuo, Yi-Hung; Singh, Bohar; Annamalai, H.; Berg, Alexis; Booth, James F.; Camargo, Suzana J.; Dai, Aiguo; Gonzalez, Alex; Hafner, Jan; Jiang, Xianan; Jing, Xianwen; Kim, Daehyun; Kumar, Arun; Moon, Yumin; Naud, Catherine M.; Sobel, Adam H.; Suzuki, Kentaroh; Wang, Fuchang; Wang, Junhong; Wing, Allison A.; Xu, Xiaobiao; Zhao, Ming

Issue Date
American Meteorological Society
Bulletin of the American Meteorological Society, Vol.100 No.9, pp.1665-1686
Realistic climate and weather prediction models are necessary to produce confidence in projections of future climate over many decades and predictions for days to seasons. These models must be physically justified and validated for multiple weather and climate processes. A key opportunity to accelerate model improvement is greater incorporation of process-oriented diagnostics (PODs) into standard packages that can be applied during the model development process, allowing the application of diagnostics to be repeatable across multiple model versions and used as a benchmark for model improvement. A POD characterizes a specific physical process or emergent behavior that is related to the ability to simulate an observed phenomenon. This paper describes the outcomes of activities by the Model Diagnostics Task Force (MDTF) under the NOAA Climate Program Office (CPO) Modeling, Analysis, Predictions and Projections (MAPP) program to promote development of PODs and their application to climate and weather prediction models. MDTF and modeling center perspectives on the need for expanded process-oriented diagnosis of models are presented. Multiple PODs developed by the MDTF are summarized, and an open-source software framework developed by the MDTF to aid application of PODs to centers' model development is presented in the context of other relevant community activities. The paper closes by discussing paths forward for the MDTF effort and for community process-oriented diagnosis.
Files in This Item:
There are no files associated with this item.
Appears in Collections:

Related Researcher

  • College of Natural Sciences
  • Department of Earth and Environmental Sciences
Research Area Climate Change, Earth & Environmental Data, Severe Weather, 기후과학, 위험기상, 지구환경 데이터과학


Item View & Download Count

  • mendeley

Items in S-Space are protected by copyright, with all rights reserved, unless otherwise indicated.