Computer Science – Sound
Scientific paper
Jan 2004
adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2004adspr..33.1132b&link_type=abstract
Advances in Space Research, Volume 33, Issue 7, p. 1132-1135.
Computer Science
Sound
Scientific paper
The operational climate monitoring and diagnostic community will continue to favor in using outgoing longwave radiation (OLR) estimates that have long and continuous time series such as those estimated from the High Resolution Infrared Sounder (HIRS). OLR from HIRS data could be generated since these data exist since 1979 and will continue during NPOESS era with Cross-Track Infrared Sounder (CrIS) and HIRS/4 on NPOESS and METOP satellites, respectively. OLR estimated from Earth Radiation Budget Suite (ERBS)/Clouds and the Earth's Radiant Energy System (CERES) can be used to calibrate the HIRS technique that will be used to generate continuous time series of OLR. This will ensure to have a consistent climate data involving different data sources. OLR generated from CrIS on the afternoon orbit could provide a backup in the event of ERBS's failure. There will be three evenly spaced sounders (two CrIS and one HIRS/4) that could be used to retrieve OLR allowing therefore a better definition of the diurnal variability of OLR. This paper will present results from GOES sounder data to estimate OLR using an approach similar to that used for HIRS. The instantaneous OLR estimates are compared with collocated OLR products from the CERES instruments onboard TRMM and Terra spacecraft to establish the instantaneous accuracy of the multi-spectral estimation techniques for homogeneous scenes. The hourly GOES sounder OLR estimates are used to study the diurnal cycle of OLR. The time-averaged data are used to estimate the accuracy of the ERBE/CERES and HIRS diurnal cycle models as applied to daily- and monthly-averaged products at different spatial resolutions. The study suggests that the technique can be implemented for NPOESS using the CrIS and HIRS/4 for both augmenting the temporal sampling of OLR estimates and reducing the risk of OLR EDR generation.
Ba Mamoudou B.
Ellingson Robert G.
Gruber Arnold
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