Comparison of Split Window Algorithms for Retrieving Measurements of Sea Surface Temperature from MODIS Data in Near-Land Coastal Waters

Rosa Cavalli

doi:10.3390/ijgi7010030

Abstract

Split window (SW) methods, which have been successfully used to retrieve measurements of land surface temperature (LST) and sea surface temperature (SST) from MODIS images, were exploited to evaluate the SST data of three sections of Italian coastal waters. For this purpose, sea surface emissivity (SSE) values were estimated by adding the effects of salinity and total suspended particulate matter (SPM) concentrations, sea surface wind speed, and zenith observation angle. The total column atmospheric water vapor contents were retrieved from MODIS data. SST data retrieved from MODIS images using these algorithms were compared with SSTskin measurements evaluated from in situ data. The comparison showed that the algorithms for retrieving LST measurements minimized the error in SST data in near-land coastal waters with respect to the algorithms for retrieving SST measurements: a method for retrieving LST measurements highlighted the smallest root-mean-square deviation (RMSD) value (0.48 K) and values of maximum bias and standard deviation (σ) equal to −3.45 K and 0.41 K; the current operation algorithm for retrieving LST data highlighted the smallest values of maximum bias and σ (−1.37 K and 0.35 K) and an RMSD value of 0.66 K; and the current operation algorithm for retrieving global measurements of SST showed values of RMSD, maximum bias, and σ equal to 0.68 K, −1.90 K, and 0.40 K, respectively.

Highlights

Sea surface temperature (SST) plays a key role in life and processes in coastal waters [1,2,3,4,5,6,7,8,9,10,11,12]
SSTskin data were compared with SST1(radiosonde based), SST1(ECMWF based), SST1(collection 5), and SST2(collection 6) measurements retrieved from moderate resolution imaging spectroradiometer (MODIS) bands 31 and 32 with the operational algorithms for retrieving the global data of SST proposed by [16,17,18] (Table 2)
The SSTskin data were compared the LST1, LST2, LST3, and LST4 measurements retrieved from MODIS bands 31 and 32 with the current operation algorithm for retrieving land surface temperature (LST) measurements [38] and with the three algorithms for retrieving LST measurements proposed by [37] (Table 4)

Summary

Introduction

Sea surface temperature (SST) plays a key role in life and processes in coastal waters [1,2,3,4,5,6,7,8,9,10,11,12]. SST measurements of coastal waters retrieved from remote images have a wide variety of applications such as: the analysis of temperature influence over benthic organisms [1,3]; the assessment of potential aquaculture sites [4]; the detection of ground water discharge [5]; the hydrographic characterization of nearshore waters [6]; the monitoring of river plumes [7], thermal plume contaminations [8], and upwelling phenomena [9]; quantifying complex thermal environments on coral reefs [10,11]; and the study of the interactions between residual circulation, tidal mixing, and fresh influence [12] Many of these applications have stringent accuracy requirements [1,3,4,8,9,10,11,12]. The variations in total column atmospheric water vapor (W) content and in sea surface emissivity (SSE) values are considered negligible for retrieving global SST measurements [16,17,18,19]

Methods

Results

Conclusion