Comparative Study on Sea Surface Temperature Estimation with Thermal Infrared Radiometer Data among Conventional MCSST, Split Window and Conjugate Gradient Based Methods

Kohei Arai

doi:10.14569/ijarai.2013.020802

Abstract

Comparative study on Sea Surface Temperature: SST estimations among the conventional Multi-Channel Seat Surface Temperature: MCSST, split window method and the proposed Conjugate Gradient based method: CGM with Thermal Infrared Radiometer: TIR data through simulations is conducted. Utilizing the proposed linearized inversion of radiative transfer equation, SST can be estimated. SST estimation accuracy of the proposed method is compared to the conventional regression based method (Split Window and MCSST method). Through the simulation study, it is found that the proposed CGM based method is superior to the conventional regression based method.

Highlights

Sea Surface Temperature: SST estimation with thermal infrared radiometer onboard satellites is well known and widely used in a variety of research fields, in particular climate changes, global warming, etc
Multi Channel Sea Surface Temperature: MCSST is the method for SST estimation with NOAA/AVHRR (National Oceanic and Atmospheric Administration / Advanced Very High Resolution Radiometer) data
Only the difference between MCSST and Split Window methods is the regression coefficients, Split Window method is superior to the MCSST method because the regression coefficients are different among the atmospheric models for Split Window method; MCSST method uses the same coefficients for all atmospheric models

Summary

INTRODUCTION

Sea Surface Temperature: SST estimation with thermal infrared radiometer onboard satellites is well known and widely used in a variety of research fields, in particular climate changes, global warming, etc. SST estimation methods are proposed [1]-[4]. Most of these are based on regressive analysis and use several spectral bands in Thermal Infrared: TIR wavelength region. Based on radiative transfer equation, inversion based SST estimation method is proposed [8]. D. Iteration Method for SST, Precipitable Water, and Representative Radiance The unknown factors are as follows,. Sea surface temperature, precipitable water, and representative radiance. In the TIR wavelength region, precipitable water is major absorbing continuants in the atmosphere. The second derivatives of radiance is represented as follows, Namely, once regression analysis is made, SST can be estimated with TIR spectral band data (TIRi).

Conventional MCSST

Evaluated Averaged SST Estimation Error

CONCLUSION