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Webinar: Improving Climate Prediction Center (CPC) Experimental S2S Sea Ice Predictions with a UFS-based System
Wednesday, 03 November 2021, 3:30
Wednesday, November 3, 2021. 3:30 PM. Webinar: Improving Climate Prediction Center (CPC) Experimental S2S Sea Ice Predictions with a UFS-based System. Wanqiu Wang, Wanqiu Wang, Yanyun Liu, Jieshun Zhu, Weiyu Yang, Aun Kumar, and David DeWitt; NOAA NWS Climate Prediction Center. Sponsored by NOAA. More information here. Register here.
Abstract: Sea ice predictions at subseasonal to seasonal (S2S) time scales have become important products for stakeholders. For example, the NWS Alaska Region requires sea-ice forecasts for the next few weeks to seasons. The Climate Prediction Center (CPC) has been providing sea ice predictions for week-2 to 9-month target periods based on an experimental sea ice prediction system (CFSm5) consisting of the Climate Forecast System (CFS) atmospheric component and the Geophysical Fluid Dynamics Laboratory Modular Ocean Model version 5 (MOM5). Sea ice in CFSm5 is initialized from a MOM5-based CPC sea ice initialization system (CSIS). Sea ice forecasts from CFSm5 are significantly better than that from the operational CFS. The NWS Alaska Region uses these CPC sea ice predictions to provide guidance to the DOI, USCG and other partners. CPCs sea ice predictions are also regularly used by Alaska Center for Climate Assessment and Policy (ACCAP) in Alaska Region Climate Outlooks. The recent successful development and improvement of the coupled Unified Forecast System (UFS) by the Dynamics and Coupled Modeling Group of the Environmental Modeling Center (EMC) provided an opportunity for CPC to upgrade the CFSm5 to a UFS-based model for the S2S sea ice predictions. In this talk, we report our progress in the use of UFS in sea ice predictions. The final goal is to provide improved real-time week-3/4 and seasonal sea ice outlooks. We will present two major efforts with the UFS: (1) Experiments to adjust cloud parameterizations to reduce model errors in sea surface temperature and sea ice coverage and (2) An evaluation of sea ice predictions based on hindcasts completed with the UFS and comparisons with operational CFS, CFSm5, and observations. The potential of using a multi-model ensemble based on UFS, CFS, and CFSm5 will also be discussed.
Bio(s): Dr. Wanqiu Wang's principal interests are improving predictions of climate anomalies in the earth atmosphere-ocean-ice-land system at subseasonal to seasonal (S2S) time scales, and diagnosing predictability of S2S climate variability and understanding of systematic biases in coupled atmosphere-ocean dynamic forecast models. Dr. Wang received a PhD. degree in atmospheric sciences from the University of Illinois at Urbana-Champaign in 1996. From 1997-2004, Dr. Wang worked at the National Centers for Environmental Prediction (NCEP) environmental modeling center (EMC). Dr. Wang joined the Climate Prediction Center (CPC) in May 2004. The focus of his work is understanding predictability and improving predictions of Tropical intraseasonal and interannual variability, and Arctic sea ice. Dr. Wang has been serving as the chief of the CPC Operational Monitoring Branch of CPC since August 2019.