Waliser and Zhou Satellite Equatorial Crossing Time-Corrected Monthly Tropical OLR and HRC Datasets
d684000
This historical dataset is recommended for ancillary use only and not as a primary research dataset. It has likely been superseded by a newer, improved dataset.
Abstract:
Gridded analyses of OLR (Outgoing Longwave Radiation) and HRC (Highly Reflective Cloud) anomalies wherein the bias due to changing equatorial crossing times has been estimated and removed. The OLR data is available for 30N to 30S and the HRC is available for 24N to 24S. This dataset also contains long term monthly climatologies for both OLR and HRC.
Note that this dataset is obsolete and users should use dataset ds684.1 instead.
Temporal Range:
1971-01 to 1996-07
Variables:
Longwave Radiation |
Temporal Frequencies:
Every month (Mean)
, Annual Climatology
Data Types:
Grid
Spatial Coverage:
Longitude Range: Westernmost=180W Easternmost=180E
Latitude Range: Southernmost=30S Northernmost=30N Detailed coverage information Detailed coverage information 2.0° x 2.0° from 0.0E to 2.0W and 24N to 24S (144 x 25 Longitude/Latitude) 2.5° x 2.5° from 1.25E to 1.25W and 30N to 30S (144 x 25 Longitude/Latitude)
Latitude Range: Southernmost=30S Northernmost=30N Detailed coverage information Detailed coverage information 2.0° x 2.0° from 0.0E to 2.0W and 24N to 24S (144 x 25 Longitude/Latitude) 2.5° x 2.5° from 1.25E to 1.25W and 30N to 30S (144 x 25 Longitude/Latitude)
Data Contributors:
SUNYSB/SOMAS/ITPA
Institute for Terrestrial and Planetary Atmospheres, School of Marine and Atmospheric Sciences, Stony Brook University
Publications:
Waliser, D.E. and W. Zhou, 1997: Removing Satellite Equatorial Crossing Time Biases from the OLR and HRC Datasets. J. Clim., 10(9), 2125-2146.
Total Volume:
15.43 MB
(Entire dataset)
Volume details by dataset product
Volume details by dataset product
Outgoing Longwave Radiation data: 3.84 MB
Highly Reflective Cloud data: 7.58 MB
Data Formats:
Binary (see dataset documentation)
Related RDA Datasets:
Metadata Record:
Data License:
This work is licensed under a Creative Commons Attribution 4.0 International License.
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