A New GFSv15 based Climate Model Large Ensemble and Its Application to Understanding Climate Variability, and Predictability Journal Article uri icon

Overview

abstract

  • NOAA Climate Prediction Center (CPC) has generated a 100-member ensemble; of Atmospheric Model Intercomparison Project (AMIP) simulations from; 1979 to present using the GFSv15 with FV3 dynamical core. The intent of; this study is to document a development in an infrastructure capability; with a focus to demonstrate the quality of these new simulations is on; par with the previous GFSv2 AMIP simulations. These simulations are part; of CPC’s efforts to attribute observed seasonal climate variability to; SST forcings and get updated once a month by available observed SST.; The performance of these simulations in replicating observed climate; variability and trends, together with an assessment of climate; predictability and the attribution of some climate events is documented.; A particular focus of the analysis is on the US climate trend, Northern; Hemisphere winter height variability, US climate response to three; strong El Niño events, the analysis of signal to noise ratio (SNR), the; anomaly correlation for seasonal climate anomalies, and the South Asian; flooding of 2022 summer, and thereby samples wide aspects that are; important for attributing climate variability. Results indicate that the; new model can realistically reproduce observed climate variability and; trends as well as extreme events, better capturing the US climate; response to extreme El Niño events and the 2022 summer South Asian; record-breaking flooding than GFSv2. The new model also shows an; improvement in the wintertime simulation skill of US surface climate,; mainly confined in the Northern and Southeastern US for precipitation; and in the east for temperature.

publication date

  • June 14, 2023

has restriction

  • green

Date in CU Experts

  • June 15, 2023 2:21 AM

Full Author List

  • Zhang T; Yang W; Quan X; Zhu J; Jha B; Kumar A; Hoerling MP; Barsugli J; Wang W

author count

  • 9

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