Ice cloud detection from AMSU-A, MHS, and HIRS satellite instruments inferred by cloud profiling radar

Authors

Tanvir Islam, NOAA/NESDIS Center for Satellite Applications and Research, College Park, MD
Prashant K. Srivastava, University of Bristol, Bristol, UK
Qiang Dai, University of Bristol, Bristol, UK
Manika Gupta, NASA Goddard Space Flight Center, Greenbelt, MD

Date of this Version

2014

Citation

Remote Sensing Letters, 2014 Vol. 5, No. 12, 1012–1021

Comments

U.S. Government Work

Abstract

An algorithm for ice cloud detection aided by support vector machine (AID-SVM) is presented. The AID-SVM algorithm is applied and tested for the Advanced Microwave Sounding Unit-A, microwave humidity sounder (MHS), and high resolution infrared radiation sounder (HIRS) instruments onboard NOAA-19 satellite. The algorithm is based on satellite brightness temperature measurements and developed as well as validated by using collocated ice/no-ice cloud information acquired from the CloudSat cloud-profiling radar. The algorithm is tested over both ocean and land surfaces. Overall, the results exhibit very promising potential to acquire ice/no-ice cloud information using the passive satellite sensors. It is found that infrared satellite sensor such as HIRS is more efficient in detecting ice clouds than the counterpart microwave satellite sensors. Furthermore, the combined measurements using microwave/infrared synergy perform no better than the infrared-only measurements.