Next Article in Journal
Fractal Dimensions of Biomass Burning Aerosols from TEM Images Using the Box-Grid and Nested Squares Methods
Next Article in Special Issue
The Spring Drought in Yunnan Province of China: Variation Characteristics, Leading Impact Factors, and Physical Mechanisms
Previous Article in Journal
Assessment of Antarctic Amplification Based on a Reconstruction of Near-Surface Air Temperature
Previous Article in Special Issue
Evaluation of the CAS-ESM2-0 Performance in Simulating the Global Ocean Salinity Change
 
 
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Evaluation of an Ocean Reanalysis System in the Indian and Pacific Oceans

Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China
*
Author to whom correspondence should be addressed.
Atmosphere 2023, 14(2), 220; https://doi.org/10.3390/atmos14020220
Submission received: 10 December 2022 / Revised: 13 January 2023 / Accepted: 19 January 2023 / Published: 20 January 2023
(This article belongs to the Special Issue Climate Change on Ocean Dynamics)

Abstract

This paper describes an ocean reanalysis system in the Indian and Pacific oceans (IPORA) and evaluates its quality in detail. The assimilation schemes based on ensemble optimal interpolation are employed in the hybrid coordinate ocean model to conduct a long-time reanalysis experiment during the period of 1993–2020. Different metrics including comparisons with satellite sea surface temperature, altimetry data, observed currents, as well as other reanalyses such as ECCO and SODA are used to validate the performance of IPORA. Compared with the control experiment without assimilation, IPORA greatly reduces the errors of temperature, salinity, sea level anomaly, and current fields, and improves the interannual variability. In contrast to ECCO and SODA products, IPORA captures the strong signals of SLA variability and reproduces the linear trend of SLA very well. Meanwhile, IPORA also shows a good consistence with observed currents, as indicated by an improved correlation and a reduced error.
Keywords: ocean reanalysis; ensemble optimal interpolation; data assimilation; independent observations; validation ocean reanalysis; ensemble optimal interpolation; data assimilation; independent observations; validation

Share and Cite

MDPI and ACS Style

Yan, C.; Zhu, J. Evaluation of an Ocean Reanalysis System in the Indian and Pacific Oceans. Atmosphere 2023, 14, 220. https://doi.org/10.3390/atmos14020220

AMA Style

Yan C, Zhu J. Evaluation of an Ocean Reanalysis System in the Indian and Pacific Oceans. Atmosphere. 2023; 14(2):220. https://doi.org/10.3390/atmos14020220

Chicago/Turabian Style

Yan, Changxiang, and Jiang Zhu. 2023. "Evaluation of an Ocean Reanalysis System in the Indian and Pacific Oceans" Atmosphere 14, no. 2: 220. https://doi.org/10.3390/atmos14020220

APA Style

Yan, C., & Zhu, J. (2023). Evaluation of an Ocean Reanalysis System in the Indian and Pacific Oceans. Atmosphere, 14(2), 220. https://doi.org/10.3390/atmos14020220

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop