scholarly journals Evaluation of the Tropical Pacific Observing System from the ocean data assimilation perspective

2015 ◽  
Vol 141 (692) ◽  
pp. 2481-2496 ◽  
Author(s):  
Yosuke Fujii ◽  
James Cummings ◽  
Yan Xue ◽  
Andreas Schiller ◽  
Tong Lee ◽  
...  
Keyword(s):  
Data Assimilation ◽  
Tropical Pacific ◽  
Ocean Data Assimilation ◽  
Tropical Pacific Observing System ◽  
The Tropical Pacific

Roles of TAO/TRITON and Argo in tropical Pacific observing system: An OSSE study for multiple time scale variability

2021 ◽  
pp. 1-56
Author(s):  
Jieshun Zhu ◽  
Guillaume Vernieres ◽  
Travis Sluka ◽  
Stylianos Flampouris ◽  
Arun Kumar ◽  
...  
Keyword(s):  
Data Assimilation ◽  
Time Scale ◽  
High Frequency ◽  
Low Frequency ◽  
Environmental Modeling ◽  
Tropical Pacific ◽  
Multiple Time ◽  
Ocean Data Assimilation ◽  
Tropical Pacific Observing System ◽  
The Tropical Pacific

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).

The NCEP GODAS Ocean Analysis of the Tropical Pacific Mixed Layer Heat Budget on Seasonal to Interannual Time Scales

2010 ◽  
Vol 23 (18) ◽  
pp. 4901-4925 ◽  
Author(s):  
Boyin Huang ◽  
Yan Xue ◽  
Dongxiao Zhang ◽  
Arun Kumar ◽  
Michael J. McPhaden
Keyword(s):  
Data Assimilation ◽  
Mixed Layer ◽  
Heat Budget ◽  
La Niña ◽  
Sst Variability ◽  
Ocean Data Assimilation ◽  
La Nina ◽  
Mixed Layer Heat Budget ◽  
Data Assimilation System ◽  
The Tropical Pacific

Abstract The mixed layer heat budget in the tropical Pacific is diagnosed using pentad (5 day) averaged outputs from the Global Ocean Data Assimilation System (GODAS), which is operational at the National Centers for Environmental Prediction (NCEP). The GODAS is currently used by the NCEP Climate Prediction Center (CPC) to monitor and to understand El Niño and La Niña in near real time. The purpose of this study is to assess the feasibility of using an operational ocean data assimilation system to understand SST variability. The climatological mean and seasonal cycle of mixed layer heat budgets derived from GODAS agree reasonably well with previous observational and model-based estimates. However, significant differences and biases were noticed. Large biases were found in GODAS zonal and meridional currents, which contributed to biases in the annual cycle of zonal and meridional advective heat fluxes. The warming due to tropical instability waves in boreal fall is severely underestimated owing to use of a 4-week data assimilation window. On interannual time scales, the GODAS heat budget closure is good for weak-to-moderate El Niños. A composite for weak-to-moderate El Niños suggests that zonal and meridional temperature advection and vertical entrainment/diffusion all contributed to the onset of the event and that zonal advection played the dominant role during decay of the event and the transition to La Niña. The net surface heat flux acts as a damping during the development stage, but plays a critical role in the decay of El Niño and the transition to the following La Niña. The GODAS heat budget closure is generally poor for strong La Niñas. Despite the biases, the GODAS heat budget analysis tool is useful in monitoring and understanding the physical processes controlling SST variability associated with ENSO. Therefore, it has been implemented operationally at CPC in support of NOAA’s ENSO forecasting.

Evaluation of tropical Pacific observing systems using NCEP and GFDL ocean data assimilation systems

2015 ◽  
Vol 49 (3) ◽  
pp. 843-868 ◽  
Author(s):  
Yan Xue ◽  
Caihong Wen ◽  
Xiaosong Yang ◽  
David Behringer ◽  
Arun Kumar ◽  
...  
Keyword(s):  
Data Assimilation ◽  
Tropical Pacific ◽  
Ocean Data Assimilation ◽  
Observing Systems

scholarly journals Evaluation of the Impact of Argo Data on Ocean Reanalysis in the Pacific Region

2017 ◽  
Vol 2017 ◽  
pp. 1-12 ◽  
Author(s):  
Xuefeng Zhang ◽  
Chaohui Sun ◽  
Chang Liu ◽  
Lianxin Zhang ◽  
Caixia Shao ◽  
...  
Keyword(s):  
Data Assimilation ◽  
General Circulation ◽  
Tropical Pacific ◽  
Northwest Pacific ◽  
Pacific Region ◽  
Ocean Reanalysis ◽  
Argo Data ◽  
The Pacific ◽  
The Impact ◽  
The Tropical Pacific

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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