Assessing the impact of brightness temperature simulation adjustment conditions in correcting Metop-A SST over the Mediterranean Sea
Tomažic, I.; Le Borgne, P; Roquet, H (2014). Assessing the impact of brightness temperature simulation adjustment conditions in correcting Metop-A SST over the Mediterranean Sea. Remote Sens. Environ. 146: 214-233. dx.doi.org/10.1016/j.rse.2013.10.007
In: Remote Sensing of Environment. Elsevier: New York,. ISSN 0034-4257; e-ISSN 1879-0704, more
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Sea surface temperature (SST); Infra-red remote sensing; Metop-A; AVHRR;Retrieval errors |
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- Tomažic, I., more
- Le Borgne, P
- Roquet, H
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| Abstract |
Multispectral sea surface temperature (SST) algorithms applied to infrared (IR) radiometer data exhibit regional biases due to the intrinsic inability of the SST algorithm to cope with the vast range of atmospheric types, mainly influenced by water vapor and temperature profiles. Deriving a SST correction from simulated brightness temperatures (BTs), obtained by applying a Radiative Transfer Model (RTM) to Numerical Weather Prediction (NWP) atmospheric profiles and first guess SST, is one of the solutions to reduce regional biases. This solution is envisaged in the particular case of Metop-A Advanced Very High Resolution Radiometer (AVHRR) derived SST. Simulated BTs show errors, linked to RTM, atmospheric profiles or guess field errors. We investigated the conditions of adjusting simulated to observed BTs in the particular case of the Mediterranean Sea over almost one year. Our study led to define optimal spatio/temporal averaging parameters of the simulation observation differences, both during day and night, summer and colder season and for two simulation modes: operational (with reduced vertical resolution - 15 levels - NWP atmospheric profiles and two days old analysis used as first guess SST) and delayed (full vertical resolution - 91 levels - and concurrent analysis used as first guess SST). Each BT adjustment has been evaluated by comparing the corresponding corrected AVHRR SST to the AATSR SST that we adopted as validation reference. We obtained an optimized result across all defined conditions and modes for a spatial smoothing of 15 deg and a temporal averaging between 3 and 5 days. Specifically, analyses based on 10 day averages showed that a standard deviation based criterion favors spatial smoothing above 10 deg for all temporal averaging, while a bias based criterion favors shorter temporal averaging during daytime (<5 days) and higher spatial smoothing (>10 deg) for nighttime. This study has shown also the impact of diurnal warming both in deriving BT adjustment and in validation results. |
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