NDLI: A Robust Fixed Rank Kriging Method for Improving the Spatial Completeness and Accuracy of Satellite SST Products

Content Provider	IEEE Xplore Digital Library
Author	Yuxin Zhu Kang, E. Yanchen Bo Qingxin Tang Jiehai Cheng Yaqian He
Copyright Year	1980
Abstract	Sea surface temperature (SST) plays a vital role in the Earth's atmosphere and climate systems. Complete and accurate SST observations are in great demand for forecasting tropical cyclones and projecting climate change. Satellite remote sensing has been used to retrieve SST globally, but missing values and biased observations impose difficulties on practical applications of these satellite-derived SST data. Conventional spatial statistics methods such as kriging have been widely used to fill the gaps. However, when such conventional methods are used to analyze a massive satellite data set of size n, the inversion of the n × n covariance matrix may require O(n³) computations, which make the computation very intensive or even infeasible. The fixed rank kriging (FRK) performs dimension reduction through multiresolution wavelet analysis so that it can dramatically reduce the computation cost of various kriging methods. However, the FRK cannot directly be used for incomplete data over spatially irregular regions such as SSTs, and the potential bias in the satellite data is not addressed. In this paper, we construct a data-driven bias-correction model for the correction of the bias in satellite SSTs and develop a robust FRK (R-FRK) method so that the dimension reduction can be used to the satellite data in irregular regions with missing data. We implement the bias-correction model and the R-FRK to the level-3 mapped night Moderate Resolution Imaging Spectroradiometer SSTs. The accuracy of the resulting predictions is assessed using the colocated drifting buoy SST observations, in terms of mean bias (bias), root-mean-squared error, and R squared (R²). The spatial completeness is assessed by the availability of ocean pixels. The assessment results show that the spatially.
Sponsorship	IEEE Geoscience and Remote Sensing Society IEEE URSI
Starting Page	5021
Ending Page	5035
Page Count	15
File Size	2703899
File Format	PDF
ISSN	01962892
Volume Number	53
Issue Number	9
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2015-01-01
Publisher Place	U.S.A.
Access Restriction	One Nation One Subscription (ONOS)
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Satellites MODIS Spatial resolution Covariance matrices Meteorology Ocean temperature robust fixed rank kriging (FRK) Basis function data-driven bias-correction model Moderate Resolution Imaging Spectroradiometer (MODIS) sea surface temperature (SST)
Content Type	Text
Resource Type	Article
Subject	Earth and Planetary Sciences Electrical and Electronic Engineering

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