Published June 15, 2019 | Version public
Journal Article

A multilayer cloud detection algorithm for the Suomi-NPP Visible Infrared Imager Radiometer Suite (VIIRS)

  • 1. ROR icon Nanjing University of Information Science and Technology
  • 2. ROR icon China Meteorological Administration
  • 3. ROR icon Institute of Remote Sensing and Digital Earth
  • 4. ROR icon California Institute of Technology

Abstract

A new multilayer (ML) cloud detection algorithm based on three shortwave infrared (SWIR) and two longwave infrared (LWIR) channels is developed and applied to the Visible Infrared Imager Radiometer Suite (VIIRS) onboard the Suomi-NPP satellite. The algorithm identifies ML clouds, i.e., ice clouds overlying water clouds, based on satellite multispectral observations in the 1.38, 1.6, 2.25, 8.5, and 11 μm channels. We perform synthetic radiative transfer simulations to understand the sensitivities of the aforementioned channels on ML and single-layer (SL) clouds. Active CALIOP observations are used to evaluate the algorithm. Compared with the collocated CALIOP results, the algorithm can determine SL and ML clouds correctly with success rates of approximately 80% and 60%, respectively, and has similar performance to that of the current MODIS operational ML cloud detection algorithm. The misclassification of ML clouds as SL clouds is primarily caused by thin ice clouds that are practically undetectable using LWIR tests. Furthermore, the algorithm is extended to analyze data from radiometers onboard the geostationary Himawari-8 and FengYun-4A satellites, and results similar to those of VIIRS are obtained.

Additional Information

© 2019 Elsevier. Received 11 July 2018, Revised 22 February 2019, Accepted 23 February 2019, Available online 6 April 2019. This research is supported by the National Key Research and Development Program of China (2018YFC1506502), the National Natural Science Foundation of China (41571348 and 41771395), Young Elite Scientists Sponsorship Program by CAST (2017QNRC001), the Six Talent Peaks Project in Jiangsu Province (2017-JY-053), and the Open Project Fund of Key Laboratory of Radiometric Calibration and Validation for Environmental Satellites, NSMC/CMA.

Additional details

Identifiers

Eprint ID
94558
DOI
10.1016/j.rse.2019.02.024
Resolver ID
CaltechAUTHORS:20190408-101258817

Related works

Funding

National Key Research and Development Program of China
2018YFC1506502
National Natural Science Foundation of China
41571348
National Natural Science Foundation of China
41771395
Chinese Association for Science and Technology
2017QNRC001
Six Talent Peaks Project in Jiangsu Province
2017-JY-053
Open Project Fund of Key Laboratory of Radiometric Calibration and Validation for Environmental Satellites

Dates

Created
2019-04-09
Created from EPrint's datestamp field
Updated
2021-11-16
Created from EPrint's last_modified field