Evaluation of the Tropical Pacific Observing System from the Data Assimilation Perspective

Author(s):  
Y. Fujii ◽  
J. Cummings ◽  
Y. Xue ◽  
A. Schiller ◽  
T. Lee ◽  
...  
2021 ◽  
pp. 1-56
Author(s):  
Jieshun Zhu ◽  
Guillaume Vernieres ◽  
Travis Sluka ◽  
Stylianos Flampouris ◽  
Arun Kumar ◽  
...  

AbstractIn this study, a series of ocean observing system simulation experiments (OSSEs) are conducted in support of the tropical Pacific observing system (TPOS) 2020 Project (TPOS 2020) which was established in 2014, with aims to develop a more sustainable and resilient observing system for the tropical Pacific. The experiments are based on an ocean data assimilation system that is under development at the Joint Center for Satellite Data Assimilation (JCSDA) and the Environmental Modeling Center (EMC)/National Centers for Environmental Prediction (NCEP). The atmospheric forcing and synthetic ocean observations are generated from a nature run, which is based on a modified CFSv2 with a vertical ocean resolution of 1-meter near the ocean surface. To explore the efficacy of TAO/TRITON and Argo observations in TPOS, synthetic ocean temperature and salinity observations were constructed by sampling the nature run following their present distributions. Our experiments include a free run with no “observations” assimilated, and assimilation runs with the TAO/TRITON and Argo synthetic observations assimilated separately or jointly. These experiments were analyzed by comparing their long-term mean states and variabilities at different time scales [i.e., low-frequency (>90 days), intraseasonal (20~90 days), and high-frequency (<20 days)]. It was found that (1) both TAO/TRITON and especially Argo effectively improve the estimation of mean states and low-frequency variations; (2) on the intraseasonal time scale, Argo has more significant improvements than TAO/TRITON (except for regions close to TAO/TRITON sites); (3) on the high-frequency time scale, both TAO/TRITON and Argo have evident deficits (although for TAO/TRITON, limited improvements were present close to TAO/TRITON sites).


2015 ◽  
Vol 141 (692) ◽  
pp. 2481-2496 ◽  
Author(s):  
Yosuke Fujii ◽  
James Cummings ◽  
Yan Xue ◽  
Andreas Schiller ◽  
Tong Lee ◽  
...  

2017 ◽  
Vol 2017 ◽  
pp. 1-12 ◽  
Author(s):  
Xuefeng Zhang ◽  
Chaohui Sun ◽  
Chang Liu ◽  
Lianxin Zhang ◽  
Caixia Shao ◽  
...  

Observing System Simulation Experiments (OSSEs) have been conducted to evaluate the effect of Argo data assimilation on ocean reanalysis in the Pacific region. The “truth” is obtained from a 5-year model integration from 2003 to 2007 based on the MIT general circulation model with the truly varying atmospheric forcing. The “observations” are the projections of the truth onto the observational network including ocean station data, CTD, and various BTs and Argo, by adding white noise to simulate observational errors. The data assimilation method employed is a sequential three-dimensional variational (3D-Var) scheme within a multigrid framework. Results show the interannual variability of temperature, salinity, and current fields can be reconstructed fairly well. The spread of temperature anomalies in the tropical Pacific region is also able to be reflected accurately when Argo data is assimilated, which may provide a reliable initial field for the forecast of temperature and currents for the subsurface in the tropical Pacific region. The adjustment of salinity by using T-S relationship is vital in the tropical Pacific region. However, the adjustment of salinity is almost meaningless in the northwest Pacific if Argo data is included during the reanalysis.


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