Statistical approach to validation of satellite atmospheric retrievals

Nikita Pougatchev; Gail Bingham; Dian Seidel; Franz Berger

doi:10.1117/12.737943

25 October 2007 Statistical approach to validation of satellite atmospheric retrievals

Nikita Pougatchev, Gail Bingham, Dian Seidel, Franz Berger

Proceedings Volume 6745, Remote Sensing of Clouds and the Atmosphere XII; 674511 (2007) https://doi.org/10.1117/12.737943
Event: SPIE Remote Sensing, 2007, Florence, Italy

Abstract

A mathematical model for statistical estimate of the bias and noise in satellite retrievals of atmospheric profiles and a case study are presented. The model allows accurate validation of actual performance of the remote sensing system while in orbit by comparing its measurements to correlative data sets, e. g. radiosonde network. The model accounts for the following factors: (i) The satellite and validating systems sample volumes of the atmosphere at times and locations that are not exactly co-located. (ii) The validated and validating systems have different characteristics, e. g. different vertical resolution and noise level. All the above factors cause apparent difference between the data to be compared. The presented model makes the comparison accurate by allowing for the differences. To demonstrate its practicability we present the case study that involves the radiosonde data from three stations: ARM Tropical Western Pacific (0.5° S, 167° E), ARM Southern Great Planes (37° N, 98° W), and Lindenberg (52° N, 14° E). For each station we considered temperature profile validation scenario and estimated associated errors. The model can be used for interpretation of the validation results when the above mentioned sources of discrepancies are significant, as well as for evaluation of validation data sources, e.g. GRUAN (GCOS Reference Upper-Air Network).

Citation Download Citation

Nikita Pougatchev, Gail Bingham, Dian Seidel, and Franz Berger "Statistical approach to validation of satellite atmospheric retrievals", Proc. SPIE 6745, Remote Sensing of Clouds and the Atmosphere XII, 674511 (25 October 2007); https://doi.org/10.1117/12.737943

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