Details:

Journal Title:
Journal of Atmospheric and Oceanic Technology
Personal Author:
Zhao, Mengnan ; Ponte, Rui M. ; Wang, Ou ; Lumpkin, Rick
Zhao, Mengnan ; Ponte, Rui M. ; Wang, Ou ; Lumpkin, Rick Less -
NOAA Program & Office:
OAR (Oceanic and Atmospheric Research) ; AOML (Atlantic Oceanographic and Meteorological Laboratory)
OAR (Oceanic and Atmospheric Research) ; AOML (Atlantic Oceanographic and Meteorological Laboratory) Less -
Description:
Properly fitting ocean models to observations is crucial for improving model performance and understanding ocean dynamics. Near-surface velocity measurements from the Global Drifter Program (GDP) contain valuable information about upper-ocean circulation and air–sea fluxes on various space and time scales. This study explores whether GDP measurements can be used for usefully constraining the surface circulation from coarse-resolution ocean models, using global solutions produced by the consortium for Estimating the Circulation and Climate of the Ocean (ECCO) as an example. To address this problem, a careful examination of velocity data errors is required. Comparisons between an ECCO model simulation, performed without any data constraints, and GDP and Ocean Surface Current Analyses Real-Time (OSCAR) velocity data, over the period 1992–2017, reveal considerable differences in magnitude and pattern. These comparisons are used to estimate GDP data errors in the context of the time-mean and time-variable surface circulations. Both instrumental errors and errors associated with limitations in model physics and resolution (representation errors) are considered. Given the estimated model–data differences, errors, and signal-to-noise ratios, our results indicate that constraining ocean-state estimates to GDP can have a substantial impact on the ECCO large-scale time-mean surface circulation over extensive areas. Impact of GDP data constraints on the ECCO time-variable circulation would be weaker and mainly limited to low latitudes. Representation errors contribute substantially to degrading the data impacts.
Keywords:
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Ocean circulation
Climate Models
Data Assimilation
Error Analysis

Source:
Journal of Atmospheric and Oceanic Technology, 38(4)
DOI:
https://doi.org/10.1175/JTECH-D-20-0159.1
Document Type:
Journal Article
Rights Information:
Other
Compliance:
Submitted
Main Document Checksum:
[+]
urn:sha256:3b59fa7e776d5b4ebda21e761a7843192688e78818f0d8f5c170f176964c0972
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