Rain Rate Retrieval Algorithm for Conical-Scanning Microwave Imagers Aided by Random Forest, RReliefF, and Multivariate Adaptive Regression Splines (RAMARS)

Tanvir Islam, Prashant Srivastava, Qiang Dai, Manika Gupta, Lu Zhuo

Research output: Contribution to journalArticle (Academic Journal)peer-review

9 Citations (Scopus)
433 Downloads (Pure)

Abstract

This paper proposes a rain rate retrieval algorithm for conical-scanning microwave imagers (RAMARS), as an alternative to the NASA Goddard profiling (GPROF) algorithm, that does not rely on any a priori information. The fundamental basis of the RAMARS follows the concept of the GPROF algorithm, which means, being consistent with the Tropical Rainfall Measuring Mission (TRMM) precipitation radar rain rate observations, but independent of any auxiliary information. The RAMARS is built upon the combination of state-of-the-art machine learning and regression techniques, comprising of random forest algorithm, RReliefF, and multivariate adaptive regression splines. The RAMARS is applicable to both over ocean and land as well as coast surface terrains. It has been demonstrated that, when comparing with the TRMM Precipitation Radar observations, the performance of the RAMARS algorithm is comparable with the 2A12 GPROF algorithm. Furthermore, the RAMARS has been applied to two cyclonic cases, hurricane Sandy in 2012, and cyclone Mahasen in 2013, showing a very good capability to reproduce the structure and intensity of the cyclone fields. The RAMARS is highly flexible, because of its four processing components, making it extremely suitable for use to other passive microwave imagers in the global precipitation measurement (GPM) constellation.
Original languageEnglish
Pages (from-to)2186-2193
Number of pages8
JournalIEEE Sensors Journal
Volume15
Issue number4
Early online date5 Feb 2015
DOIs
Publication statusPublished - Apr 2015

Keywords

  • Brightness temperature (TB)
  • passive microwave (PMW)
  • precipitation estimation
  • precipitation radar
  • global precipitation measurement (GPM)
  • constellation
  • radiometer
  • hurricane

Fingerprint Dive into the research topics of 'Rain Rate Retrieval Algorithm for Conical-Scanning Microwave Imagers Aided by Random Forest, RReliefF, and Multivariate Adaptive Regression Splines (RAMARS)'. Together they form a unique fingerprint.

Cite this