Intercomparison of wind and wave data from the ECMWF Reanalysis Interim and the NCEP Climate Forecast System Reanalysis

The recent release of the ECMWF Reanalysis Interim (ERA-I) and NCEP Climate Forecast System Reanalysis (CFSR) allows for studies of global climate and its cycles with unprecedented detail. While the developers have performed verification and validation, there is little information on their relative...

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Bibliographic Details
Published in:Ocean Modelling
Main Authors: Stopa, Justin E., Cheung, Kwok Fai
Language:unknown
Published: 2022
Subjects:
Online Access:http://www.osti.gov/servlets/purl/1769047
https://www.osti.gov/biblio/1769047
https://doi.org/10.1016/j.ocemod.2013.12.006
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Summary:The recent release of the ECMWF Reanalysis Interim (ERA-I) and NCEP Climate Forecast System Reanalysis (CFSR) allows for studies of global climate and its cycles with unprecedented detail. While the developers have performed verification and validation, there is little information on their relative performance in particular related to their use in ocean modeling. This study focuses on the intercomparison of wind and wave reanalysis datasets from ERA-I and CFSR utilizing the same set of altimetry and buoy observations and error metrics to assess their consistency in time and space. Both products have good spatial homogeneity with consistent levels of errors in the Northern and Southern Hemispheres. ERA-I proves to be homogenous through time, while CFSR exhibits an abrupt decrease in the level of errors in the Southern Ocean beginning 1994. ERA-I generally underestimates the wind speed and wave height with lower standard deviations in comparison to observations, but maintains slightly better error metrics. Despite having a slightly positive bias, CFSR provides a better description of the variability of the observations and improved performance in the upper percentiles associated with extreme events. Altogether ERA-I has better homogeneity through time deeming it more reliable for modeling of long-term processes; however caution must be applied with analysis of the upper percentiles.