Research Papers

Diurnal cycles in Arctic surface radiative fluxes in a blended satellite-climate reanalysis data set

[+] Author Affiliations
Xuanji Wang

UW-Madison

Jeffrey Key

ORA, NOAA/NESDIS

Chuck Fowler

Colorado Center for Astrodynamics Research, University of Colorado

James Maslanik

Cooperative Institute for Research in the Environmental Sciences, University of Colorado

J. Appl. Remote Sens. 1(1), 013535 (September 13, 2007). doi:10.1117/1.2794003
History: Received October 16, 2006; Revised July 23, 2007; Accepted September 7, 2007; September 13, 2007; Online September 13, 2007
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Abstract

Surface radiative fluxes and their diurnal cycles are very important components in the surface energy budget of the Arctic, and also critical forcing variables for land surface models. An approach has been developed to derive diurnal cycles of the surface radiative fluxes for the Arctic from 6-hourly accumulated surface downward shortwave and longwave radiative fluxes in the European Center for Medium Range Weather Forecasts (ECMWF) 40- year reanalysis (ERA-40) products by "correcting" interpolated hourly values with twice-daily satellite-derived radiative fluxes. Ground-based measurements of the surface radiative fluxes at an Arctic meteorological station are used to validate the approach. Results show that the blended satellite-model products are in good agreement with the ground-based measurements. Based on this blended product, diurnal cycles of surface radiative fluxes are examined over time and space. It clearly shows that satellite-retrieved products in high spatial and temporal resolutions are more realistic and accurate, and can be used to adjust or "correct" the reanalysis products, especially for the polar region where there exist few ground based measurements for diurnal cycle studies.

© 2007 Society of Photo-Optical Instrumentation Engineers

Topics

Satellites

Citation

Xuanji Wang ; Jeffrey Key ; Chuck Fowler and James Maslanik
"Diurnal cycles in Arctic surface radiative fluxes in a blended satellite-climate reanalysis data set", J. Appl. Remote Sens. 1(1), 013535 (September 13, 2007). ; http://dx.doi.org/10.1117/1.2794003


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