Comparisons of Two Cloud-Detection Schemes for Infrared Radiance Observations

Xu Dong-Mei, Huang Xiang-Yu, Liu Zhi-Quan, Min Jin-Zhong

Research output: Contribution to journalArticlepeer-review

3 Scopus citations

Abstract

The cloud-detection procedure developed by McNally and Watts (MW03) was added to the Weather Research and Forecasting Data Assimilation System. To provide some guidelines for setting up cloud-detection schemes, this study compares the MW03 scheme to the Multivariate and Minimum Residual (MMR) scheme for both simulated and real Advanced Infrared Sounder (AIRS) radiances. Results show that there is a high level of consistency between the results from simulated and real AIRS data. As expected, both cloud-detection schemes perform well in finding the cloud-contaminated channels based on the channels' peak levels. The clouddetection results from MW03 are sensitive to the prescribed brightness temperature innovation threshold and brightness temperature gradient threshold. When increasing the brightness temperature innovation threshold for MW03 to roughly eight times the default threshold, the two cloud-detection schemes produce consistent data rejection distributions overall for high channels. MMR generally retains more data for long-wave channels. For both cloud-detection schemes, there is a high level of consistency between the cloud-free pixels and the visible/ near-IR (Vis/NIR) cloud mask.

Original languageEnglish
Pages (from-to)358-363
Number of pages6
JournalAtmospheric and Oceanic Science Letters
Volume7
Issue number4
DOIs
StatePublished - Jan 1 2014
Externally publishedYes

Keywords

  • AIRS
  • brightness temperature departure
  • cloud detection
  • WRF data assimilation system

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