Techniques for using MODIS data to remotely sense lake water surface temperatures

AMS Citation:
Grim, J. A., J. C. Knievel, and E. T. Crosman, 2013: Techniques for using MODIS data to remotely sense lake water surface temperatures. Journal of Atmospheric and Oceanic Technology, 30, 2434-2451, doi:10.1175/JTECH-D-13-00003.1.
Resource Type:article
Title:Techniques for using MODIS data to remotely sense lake water surface temperatures
Abstract: This study describes a stepwise methodology used to provide daily high-spatial-resolution water surface temperatures from Moderate Resolution Imaging Spectroradiometer (MODIS) satellite data for use nearly in real time for the Great Salt Lake (GSL). Land surface temperature (LST) is obtained each day and then goes through the following series of steps: land masking, quality control based on other concurrent datasets, bias correction, quality control based on LSTs from recent overpasses, temporal compositing, spatial hole filling, and spatial smoothing. Although the techniques described herein were calibrated for use on the GSL, they can also be applied to any other inland body of water large enough to be resolved by MODIS, as long as several months of in situ water temperature observations are available for calibration. For each of the buoy verification datasets, these techniques resulted in mean absolute errors for the final MODIS product that were at least 62% more accurate than those from the operational Real-Time Global analysis. The MODIS product provides realistic cross-lake temperature gradients that are representative of those directly observed from individual MODIS overpasses and is also able to replicate the temporal oscillations seen in the buoy datasets over periods of a few days or more. The increased accuracy, representative temperature gradients, and ability to resolve temperature changes over periods down to a few days can be vital for providing proper surface boundary conditions for input into numerical weather models.
Subject(s):Sea surface temperature, Buoy observations, Data quality control, In situ oceanic observations, Remote sensing, Satellite observations
Peer Review:Refereed
Copyright Information:Copyright 2013 American Meteorological Society (AMS). Permission to use figures, tables, and brief excerpts from this work in scientific and educational works is hereby granted provided that the source is acknowledged. Any use of material in this work that is determined to be "fair use" under Section 107 or that satisfies the conditions specified in Section 108 of the U.S. Copyright Law (17 USC, as revised by P.L. 94-553) does not require the Society's permission. Republication, systematic reproduction, posting in electronic form on servers, or other uses of this material, except as exempted by the above statements, requires written permission or license from the AMS. Additional details are provided in the AMS Copyright Policies, available from the AMS at 617-227-2425 or Permission to place a copy of this work on this server has been provided by the AMS. The AMS does not guarantee that the copy provided here is an accurate copy of the published work.
OpenSky citable URL: ark:/85065/d7jh3n25
Publisher's Version: 10.1175/JTECH-D-13-00003.1
  • Joseph Grim - NCAR/UCAR
  • Jason Knievel - NCAR/UCAR
  • Erik Crosman
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