日本地球惑星科学連合2021年大会

講演情報

[E] 口頭発表

セッション記号 A (大気水圏科学) » A-OS 海洋科学・海洋環境

[A-OS09] Climate variability and predictability on subseasonal to multidecadal timescales

2021年6月3日(木) 15:30 〜 17:00 Ch.09 (Zoom会場09)

コンビーナ:森岡 優志(海洋研究開発機構)、Hiroyuki Murakami(Geophysical Fluid Dynamics Laboratory/University Corporation for Atmospheric Research)、中野 満寿男(海洋研究開発機構)、V Ramaswamy(NOAA GFDL)、座長:V Ramaswamy(NOAA GFDL)、森岡 優志(海洋研究開発機構)

15:30 〜 15:45

[AOS09-07] GFDL's SPEAR Seasonal Prediction

★Invited Papers

*Feiyu Lu1,2、Matt Harrison2、Anthony Rosati2,3、Tom Delworth2、Xiaosong Yang2、William Cooke2,3、Liwei Jia3,2、Colleen McHugh2,4、Nathaniel Johnson2、Mitchell Bushuk2,3、Yongfei Zhang1,2、Alistair Adcroft1,2 (1.Princeton University、2.NOAA/GFDL、3.UCAR、4.SAIC)

キーワード:seasonal prediction, bias correction, SPEAR, data assimilation

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 NOAA. SPEAR is an effort to develop a seamless system for prediction and research across timescales. The ensemble-based ocean data assimilation (ODA) system is updated for Modular Ocean Model version 6 (MOM6), the ocean component of SPEAR. In this talk, we will describe the updated ODA system and discuss our choice of the coupled model initialization scheme for seasonal predictions. A bias-reduction 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 ocean data assimilation as 3-dimensional tendency terms to the MOM6 ocean component of the coupled SPEAR models. Based on retrospective seasonal forecasts, we demonstrate that OTA reduces model drift—especially SST forecast drift—in coupled model predictions and improves seasonal prediction skill for applications such as El Niño-Southern Oscillation (ENSO).