Preprints
https://doi.org/10.5194/essd-2023-532
https://doi.org/10.5194/essd-2023-532
06 Feb 2024
 | 06 Feb 2024
Status: this preprint is currently under review for the journal ESSD.

A new dataset of rain cells generated from observations of the Tropical Rainfall Measuring Mission (TRMM) precipitation radar and visible and infrared scanner and microwave imager

Zhenhao Wu, Yunfei Fu, Peng Zhang, Songyan Gu, and Lin Chen

Abstract. Rain cells are the most common units in the natural precipitation system. Enhancing the understanding of these rain cell characteristics can significantly improve the cognition of the precipitation system. Previous studies have mostly analyzed rain cells from a single radar data. In this study, we merged the precipitation parameters measured by the Tropical Rainfall Measuring Mission (TRMM) precipitation radar (PR) with the muti-channel cloud-top radiance measured by the visible and infrared scanner (VIRS) and the muti-channel brightness temperature measured by the TRMM microwave imager (TMI). The rain cells were identified within the PR orbit, and the swath truncation effect was eliminated. We used two methods for rain cell identification: the minimum bounding rectangle (MBR) method and the best fit ellipse (BFE) method, and compared the differences between these two methods in describing the rain cell characteristics. The results indicate that both methods can better reflect the geometric characteristics of rain cells. Compared with the MBR method, the BFE method can obtain a smaller rain cell area, and the filling ratio is better. However, the MBR method can simplify the data storage volume. Consequently, we employed the MBR method to analyze the precipitation structure of two typical rain cell precipitation cases. The results show that the new rain cell dataset can be used for the analysis of rain cell precipitation parameters and visible/infrared and microwave signals, which provides valuable data for comprehensive studies on the rain cell structural characteristics and furthers the understanding of precipitation mechanisms. The data which were used in this paper are freely available at https://doi.org/10.5281/zenodo.8352587 (Wu et al., 2023).

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Zhenhao Wu, Yunfei Fu, Peng Zhang, Songyan Gu, and Lin Chen

Status: open (extended)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on essd-2023-532', Anonymous Referee #1, 03 Apr 2024 reply
  • RC2: 'Comment on essd-2023-532', Anonymous Referee #2, 21 May 2024 reply
Zhenhao Wu, Yunfei Fu, Peng Zhang, Songyan Gu, and Lin Chen

Data sets

A new dataset of rain cell generated from observations of the Tropical Rainfall Measuring Mission (TRMM) precipitation radar and visible and infrared scanner and microwave imager Zhenhao Wu and Yunfei Fu https://zenodo.org/records/8352587

Zhenhao Wu, Yunfei Fu, Peng Zhang, Songyan Gu, and Lin Chen

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Short summary
We establish a new rain cell precipitation parameter and visible infrared and microwave signal dataset combining with the multi-instrument observation data on the Tropical Rainfall Measuring Mission (TRMM). The purpose of this dataset is to promote the three-dimensional study of rain cell precipitation system, and reveal the spatial and temporal variations of the scale morphology and intensity of the system.
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