期刊
JOURNAL OF ADVANCES IN MODELING EARTH SYSTEMS
卷 13, 期 11, 页码 -出版社
AMER GEOPHYSICAL UNION
DOI: 10.1029/2021MS002529
关键词
decadal prediction; coupled initialization; data assimilation; AMOC; model development; forecast assessment
资金
- National Oceanic and Atmospheric Administration
- NOAA Cooperative Agreement with CIRES [NA17OAR4320101]
The study developed a decadal coupled reanalysis/initialization system using GFDL's new coupled model SPEAR, which significantly improved the model's prediction skill by restoring atmospheric parameters to observations. Results showed that different initialization approaches and atmospheric forcings had an impact on the prediction, with SPEAR model demonstrating superior performance in predicting multi-decadal trends and North Atlantic subpolar gyre SST.
Using GFDL's new coupled model SPEAR, we have developed a decadal coupled reanalysis/initialization system (DCIS) that does not use subsurface ocean observations. In DCIS, the winds and temperature in the atmosphere, along with sea surface temperature (SST), are restored to observations. Under this approach the ocean component of the coupled model experiences a sequence of surface heat and momentum fluxes that are similar to observations. DCIS offers two initialization approaches, called A1 and A2, which differ only in the atmospheric forcing from observations. In A1, the atmospheric winds/temperature are restored toward the JRA reanalysis; in A2, surface pressure observations are assimilated in the model. Two sets of coupled reanalyses have been completed during 1961-2019 using A1 and A2, and they show very similar multi-decadal variations of the Atlantic Meridional Overturning Circulation (AMOC). Two sets of retrospective decadal forecasts were then conducted using initial conditions from the A1 and A2 reanalyses. In comparison with previous prediction system CM2.1, SPEAR-A1/A2 shows comparable skill of predicting the North Atlantic subpolar gyre SST, which is highly correlated with initial values of AMOC at all lead years. SPEAR-A1 significantly outperforms CM2.1 in predicting multi-decadal SST trends in the Southern Ocean (SO). Both A1 and A2 have skillful prediction of Sahel precipitation and the associated ITCZ shift. The prediction skill of SST is generally lower in A2 than A1 especially over SO presumably due to the sparse surface pressure observations.
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