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GFDL's SPEAR Seasonal Prediction System: Initialization and Ocean Tendency Adjustment (OTA) for Coupled Model Predictions

Authors :
Feiyu Lu
Matthew J. Harrison
Anthony Rosati
Thomas L. Delworth
Xiaosong Yang
William F. Cooke
Liwei Jia
Colleen McHugh
Nathaniel C. Johnson
Mitchell Bushuk
Yongfei Zhang
Alistair Adcroft
Source :
Journal of Advances in Modeling Earth Systems, Vol 12, Iss 12, Pp n/a-n/a (2020)
Publication Year :
2020
Publisher :
American Geophysical Union (AGU), 2020.

Abstract

Abstract The next‐generation seasonal prediction system is built as part of the Seamless System for Prediction and EArth System Research (SPEAR) at the Geophysical Fluid Dynamics Laboratory (GFDL) of the National Oceanic and Atmospheric Administration (NOAA). SPEAR is an effort to develop a seamless system for prediction and research across time scales. The ensemble‐based ocean data assimilation (ODA) system is updated for Modular Ocean Model Version 6 (MOM6), the ocean component of SPEAR. Ocean initial conditions for seasonal predictions, as well as an ocean state estimation, are produced by the MOM6 ODA system in coupled SPEAR models. Initial conditions of the atmosphere, land, and sea ice components for seasonal predictions are constructed through additional nudging experiments in the same coupled SPEAR models. A bias correction scheme called ocean tendency adjustment (OTA) is applied to coupled model seasonal predictions to reduce model drift. OTA applies the climatological temperature and salinity increments obtained from ODA as three‐dimensional tendency terms to the MOM6 ocean component of the coupled SPEAR models. Based on preliminary retrospective seasonal forecasts, we demonstrate that OTA reduces model drift—especially sea surface temperature (SST) forecast drift—in coupled model predictions and improves seasonal prediction skill for applications such as El Niño–Southern Oscillation (ENSO).

Details

Language :
English
ISSN :
19422466
Volume :
12
Issue :
12
Database :
Directory of Open Access Journals
Journal :
Journal of Advances in Modeling Earth Systems
Publication Type :
Academic Journal
Accession number :
edsdoj.09f23caa6e744f68bee36f34b3b174ce
Document Type :
article
Full Text :
https://doi.org/10.1029/2020MS002149