Exploitation of error correlation in a large analysis validation: GlobCurrent case study

Type Article
Date 2018-11
Language English
Author(s) Danielson Richard E.1, Johannessen Johnny A.1, Quartly Graham D.2, Rio Marie-Helene3, Chapron Bertrand4, Collard Fabrice5, Donlon Craig6
Affiliation(s) 1 : Nansen Environm & Remote Sensing Ctr, Bergen, Norway.
2 : Plymouth Marine Lab, Plymouth, Devon, England.
3 : Collecte Localisat Satellites, Ramonville St Agne, France.
4 : IFREMER, Plouzane, France.
5 : OceanDataLab, Locmaria Plouzane, France.
6 : European Space Agcy, Noordwijk, Netherlands.
Source Remote Sensing Of Environment (0034-4257) (Elsevier Science Inc), 2018-11 , Vol. 217 , P. 476-490
DOI 10.1016/j.rse.2018.07.016
WOS© Times Cited 4
Keyword(s) Measurement model, Ocean current, Collocation, Validation
Abstract

An assessment of variance in ocean current signal and noise shared by in situ observations (drifters) and a large gridded analysis (GlobCurrent) is sought as a function of day of the year for 1993-2015 and across a broad spectrum of current speed. Regardless of the division of collocations, it is difficult to claim that any synoptic assessment can be based on independent observations. Instead, a measurement model that departs from ordinary linear regression by accommodating error correlation is proposed. The interpretation of independence is explored by applying Fuller's (1987) concept of equation and measurement error to a division of error into shared (correlated) and unshared (uncorrelated) components, respectively. The resulting division of variance in the new model favours noise. Ocean current shared (equation) error is of comparable magnitude to unshared (measurement) error and the latter is, for GlobCurrent and drifters respectively, comparable to ordinary and reverse linear regression. Although signal variance appears to be small, its utility as a measure of agreement between two variates is highlighted. Sparse collocations that sample a dense (high resolution) grid permit a first order autoregressive form of measurement model to be considered, including parameterizations of analysis-in situ error cross-correlation and analysis temporal error autocorrelation. The former (cross-correlation) is an equation error term that accommodates error shared by both GlobCurrent and drifters. The latter (autocorrelation) facilitates an identification and retrieval of all model parameters. Solutions are sought using a prescribed calibration between GlobCurrent and drifters (by variance matching). Because the true current variance of GlobCurrent and drifters is small, signal to noise ratio is near zero at best. This is particularly evident for moderate current speed and for the meridional current component

Full Text
File Pages Size Access
15 4 MB Access on demand
10 1 MB Access on demand
Author's final draft 55 2 MB Open access
Top of the page

How to cite 

Danielson Richard E., Johannessen Johnny A., Quartly Graham D., Rio Marie-Helene, Chapron Bertrand, Collard Fabrice, Donlon Craig (2018). Exploitation of error correlation in a large analysis validation: GlobCurrent case study. Remote Sensing Of Environment, 217, 476-490. Publisher's official version : https://doi.org/10.1016/j.rse.2018.07.016 , Open Access version : https://archimer.ifremer.fr/doc/00465/57713/