Abstract
Accurate measurements of sea surface temperature retrieved from remote images is a fundamental need for monitoring ocean and coastal waters. This study proposes a method for retrieving accurate measurements of SST in coastal waters. The method involves the estimation of effect of total suspended particulate matter (SPM) concentration on the value of sea surface emissivity (SSE) and the inclusion of this effect in SSE value that is put into SST calculation. Data collected in three Italian coastal waters were exploited to obtain SSTskin and SSE values and to analyze SPM effects on SSE value. The method was tested on MODIS images. Satellite measurements of SST obtained with current operational algorithm, which does not require SSE value as explicit input, were compared with in situ values of SSTskin and RMSD is equal to 1.13 K. Moreover, SST data were retrieved with an algorithm for retrieving SST measurements from MODIS data, which allows the inclusion of SSE value with SPM effect. These data were compared with in situ values of SSTskin, and RMSD is equal to 0.68 K.
Highlights
Coastal waters are very important for human populations because we derive a lot of benefits from these habitats: food, renewable and nonrenewable resources, and services such as transportation, waste disposal, and recreation
The method involves the estimation of effect of total suspended particulate matter (SPM) concentration on the value of sea surface emissivity (SSE) and the inclusion of this effect in SSE value that is put into Sea surface temperature (SST) calculation
In order to confirm that these values are emissivity of each surface water characterized by its salinity and by SPM concentration equal to 0 mg/L, values estimated with Niclos and Caselles [75] equations were compared with SSE in 11 μm and 12 μm (i.e., Moderate Resolution Imaging Spectroradiometers (MODIS) bands 31 and 32) tabulated by Masuda et al [30]
Summary
Coastal waters are very important for human populations because we derive a lot of benefits from these habitats: food (e.g., most caught fish come from the coastal waters and adjacent upwelling areas), renewable and nonrenewable resources (e.g., hydrocarbons and extracted sand and gravel), and services such as transportation, waste disposal, and recreation. The split window algorithm for retrieving SST from MODIS images which was proposed by Niclos et al [35] incorporates separate terms for column water vapor and SSE value. Based on Cox and Munch [45], the authors highlighted that the greatest effect of surface wind on emissivity is observed with surface wind speed greater than 15 m/s and zenith observation angle greater than 50◦ [30] All these papers were mainly focused on open sea waters, whereas only a few studies [46,47,48,49,50] were concentrated on SSE behavior in coastal waters. This study develops and tests a method for retrieving accurate measurements of SST in the coastal waters This method is based on the inclusion of column water vapor value and the effect. The position of all cruise observations was chosen in accordance with Mueller et al [52] protocol and knowledge of these areas of study
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