Document Type
Article
Journal/Book Title/Conference
Journal of Geophysical Research: Atmospheres
Volume
121
Issue
9
Publisher
Blackwell Publishing Ltd
Publication Date
5-16-2016
First Page
4933
Last Page
4950
Abstract
The Advanced Technology Microwave Sounder (ATMS) onboard Suomi National Polar-orbiting Partnership satellite has 22 channels at frequencies ranging from 23 to 183 GHz for probing the atmospheric temperature and moisture under all weather conditions. As part of the ATMS calibration and validation activities, the geolocation accuracy of ATMS data must be well characterized and documented. In this study, the coastline crossing method (CCM) and the land-sea fraction method (LFM) are utilized to characterize and quantify the ATMS geolocation accuracy. The CCM is based on the inflection points of the ATMS window channel measurements across the coastlines, whereas the LFM collocates the ATMS window channel data with high-resolution land-sea mask data sets. Since the ATMS measurements provide five pairs of latitude and longitude data for K, Ka, V, W, and G bands, respectively, the window channels 1, 2, 3, 16, and 17 from each of these five bands are chosen for assessing the overall geolocation accuracy. ATMS geolocation errors estimated from both methods are generally consistent from 40 cases in June 2014. The ATMS along-Track (cross-Track) errors at nadir are within ±4.2 km (±1.2 km) for K/Ka, ±2.6 km (±2.7 km) for V bands, and ±1.2 km (±0.6 km) at W and G bands, respectively. At the W band, the geolocation errors derived from both algorithms are probably less reliable due to a reduced contrast of brightness temperatures in coastal areas. These estimated ATMS along-Track and cross-Track geolocation errors are well within the uncertainty requirements for all bands. © 2016. American Geophysical Union. All Rights Reserved.
Recommended Citation
Han, Yang; Weng, Fuzhong; Zou, Xiaolei; Yang, Hu; and Scott, Deron, "Characterization of geolocation accuracy of Suomi NPP Advanced Technology Microwave Sounder measurements" (2016). Electrical and Computer Engineering Faculty Publications. Paper 152.
https://digitalcommons.usu.edu/ece_facpub/152