Decadal prediction experiments of Beijing Climate Center climate system model version 1.1 （BCC- CSM1.1） participated in Coupled Model Intercomparison Project Phase 5 （CMIPS） had poor skill in extratropics of the N...Decadal prediction experiments of Beijing Climate Center climate system model version 1.1 （BCC- CSM1.1） participated in Coupled Model Intercomparison Project Phase 5 （CMIPS） had poor skill in extratropics of the North Atlantic, the initialization of which was done by relaxing modeled ocean temperature to the Simple Ocean Data Assimilation （SODA） reanalysis data. This study aims to improve the prediction skill of this model by using the assimilation technique in the initialization. New ocean data are firstly generated by assimilating the sea surface temperature （SST） of the Hadley Centre Sea Ice and Sea Surface Temperature （HadlSST） dataset to the ocean model of BCC-CSM1.1 via Ensemble Optimum Interpolation （EnOI）. Then a suite of decadal reforecasts launched annually over the period 1961- 2005 is carried out with simulated ocean temperature restored to the assimilated ocean data. Comparisons between the re-forecasts and previous CMIP5 forecasts show that the re-forecasts are more skillful in mid-to-high latitude SST of the North Atlantic. Improved prediction skill is also found for the Atlantic multi-decadal oscillation （AMO）, which is consistent with the better skill of Atlantic meridional overturning circulation （AMOC） predicted by the re-forecasts. We conclude that the EnOl assimilation generates better ocean data than the SODA reanalysis for initializing decadal climate prediction of BCC-CSM1.1 model.展开更多
基金supported by the National Program on Key Basic Research Project of China(2012CB955203,2016YFA0602100,2013CB430202,2016YFA0602200 and 2016YFE0102404)Tsinghua University Initiative Scientific Research Program(20131089357)
文摘Decadal prediction experiments of Beijing Climate Center climate system model version 1.1 （BCC- CSM1.1） participated in Coupled Model Intercomparison Project Phase 5 （CMIPS） had poor skill in extratropics of the North Atlantic, the initialization of which was done by relaxing modeled ocean temperature to the Simple Ocean Data Assimilation （SODA） reanalysis data. This study aims to improve the prediction skill of this model by using the assimilation technique in the initialization. New ocean data are firstly generated by assimilating the sea surface temperature （SST） of the Hadley Centre Sea Ice and Sea Surface Temperature （HadlSST） dataset to the ocean model of BCC-CSM1.1 via Ensemble Optimum Interpolation （EnOI）. Then a suite of decadal reforecasts launched annually over the period 1961- 2005 is carried out with simulated ocean temperature restored to the assimilated ocean data. Comparisons between the re-forecasts and previous CMIP5 forecasts show that the re-forecasts are more skillful in mid-to-high latitude SST of the North Atlantic. Improved prediction skill is also found for the Atlantic multi-decadal oscillation （AMO）, which is consistent with the better skill of Atlantic meridional overturning circulation （AMOC） predicted by the re-forecasts. We conclude that the EnOl assimilation generates better ocean data than the SODA reanalysis for initializing decadal climate prediction of BCC-CSM1.1 model.
