Classification of precipitating clouds using satellite infrared observations and its implications for rainfall estimation

Damwon So, Dong Bin Shin

Research output: Contribution to journalArticlepeer-review

12 Citations (Scopus)


Precipitation estimates from satellite infrared (IR) radiometers are typically based on cloud top temperatures. However, these temperatures are weakly related to surface rainfall, particularly for shallow or warm clouds. This study classifies precipitating clouds into five cloud groups. The classification uses three brightness temperature differences (BTDs) and one BTD difference (ΔBTD) from Himawari-8 Advanced Himawari Imager (AHI): BTD1 (6.2–11.2 µm), BTD2 (8.6–11.2 µm), BTD3 (11.2–12.4 µm), and ΔBTD (BTD2 − BTD3). BTD1 is found to be effective for separating shallow and non-shallow clouds in reference to the Global Precipitation Measurement Dual-frequency Precipitation Radar (DPR) level 2 data. Once this separation is complete, non-shallow clouds are further classified. The negative and positive values of ΔBTD usually indicate more water and more ice in clouds, respectively, distinguishing non-shallow clouds with tall and taller cloud heights. Subsequently, BTD1 is applied to non-shallow-tall/taller clouds. Because these clouds can be considered as optically thick, BTD1 identifies the relative coldness of the cloud top based on the extent of water vapour over the cloud top. The final classification yields four non-shallow cloud types: non-shallow-tall-cold, non-shallow-tall-colder, non-shallow-taller-cold, and non-shallow-taller-colder clouds. The relationships between IR brightness temperatures and surface rainfall obtained from the classified cloud groups over four latitude bands reveal clear differences, implying that separating cloud types and accounting for regional differences are desirable to improve the accuracy of IR-based precipitation measurements.

Original languageEnglish
Pages (from-to)133-144
Number of pages12
JournalQuarterly Journal of the Royal Meteorological Society
Publication statusPublished - 2018 Nov

Bibliographical note

Funding Information:
This work was supported by “Development of Cloud/ Precipitation Algorithms” project, funded by ETRI, which is a subproject of “Development of Geostationary Meteorological Satellite Ground Segment (NMSC-2017-01)” programme funded by NMSC (National Meteorological Satellite Centre) of KMA (Korea Meteorological Administration).

Publisher Copyright:
© 2018 The Authors. Quarterly Journal of the Royal Meteorological Society published by John Wiley & Sons Ltd on behalf of the Royal Meteorological Society.

All Science Journal Classification (ASJC) codes

  • Atmospheric Science


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