the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
A Global Multi-Source Tropical Cyclone Precipitation (MSTCP) Dataset
Abstract. Tropical cyclone precipitation (TCP) has significant impacts on coastal communities through its modulation of flood event frequency as well as the water supply in many regions of the world. Satellite estimates provide our most reliable observations of TCP available globally, however, satellite precipitation estimates were limited because most products only have coverage starting in 1997. In this paper, we present a global dataset of TCP using the newly developed high-resolution Multi-Source Weighted-Ensemble Precipitation, version 2 (MSWEP V2) which spans from January 1979 to date. This Global Multi-Source Tropical Cyclone Precipitation (MSTCP) dataset is comprised of two main files in the format of tables: the main and profile datasets, both from January 1979 to February 2023. The main file provides various TCP statistics per TC track for using the full record from the International Best Track Archive for Climate Stewardship (IBTrACS) dataset, including mean and maximum precipitation rates. The profile dataset comprises the azimuthally averaged precipitation every 10-km away from the center of each storm (until 500 km). The case study of Hurricane Harvey is used to show that MSWEP estimates agree well with another commonly used satellite product. The main statistics of the dataset are analyzed as well, including the differences in the dataset metrics for each of the six TC basins and for each Saffir-Simpson category for storm intensity. The dataset es freely available at: https://zenodo.org/records/10105751.
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RC1: 'Comment on essd-2023-460', Anonymous Referee #1, 05 Jan 2024
The authors produce a so-called Global Multi-Source Tropical Cyclone Precipitation (MSTCP) dataset by using two publicly available datasets: a tropical cyclone (TC) best track dataset (IBTrACS) and a new version of global precipitation product (MSWEP V2), and then performed some statistics of TC precipitation, most of which have already been investigated by using similar datasets in previous studies. Although the computation is relatively cost, the MSTCP dataset can be easily derived by professionals and thus it is not unique. In addition, the azimuthally averaged MSTCP data limit its usefulness in studying TC precipitation asymmetry. Therefore, I don't think the manuscript qualifies publication in ESSD.
Citation: https://doi.org/10.5194/essd-2023-460-RC1 - AC1: 'Reply on RC1', Jorge Garcia-Franco, 27 Jan 2024
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RC2: 'Comment on essd-2023-460', Anonymous Referee #2, 09 Jan 2024
“A Global Multi-Source Tropical Cyclone Precipitation (MSTCP) Dataset” by Morin et al.
The topic of this manuscript is greatly interesting. A good dataset of tropical Cyclone Precipitation information is vital for accurately understanding the varying Cyclones under the changing climate. ESSD is a big journal for publishing high quality datasets. However, after carefully reading this manuscript, I found there are various points confusing me, including but not limited to: (1) there is very limited descriptions on the scientific methodology, so I can not judge the reasonability; (2) the MSTCP data has not been validated in terms of its accuracy, so at what extent do I believe it; and (3) the writings are really not good enough for the big journal, ESSD, while the current manuscript is more like a document than a scientific paper. Therefore, I am very sorry for not recommending it for publication at this stage.
Citation: https://doi.org/10.5194/essd-2023-460-RC2 - AC2: 'Reply on RC2', Jorge Garcia-Franco, 27 Jan 2024
Status: closed
-
RC1: 'Comment on essd-2023-460', Anonymous Referee #1, 05 Jan 2024
The authors produce a so-called Global Multi-Source Tropical Cyclone Precipitation (MSTCP) dataset by using two publicly available datasets: a tropical cyclone (TC) best track dataset (IBTrACS) and a new version of global precipitation product (MSWEP V2), and then performed some statistics of TC precipitation, most of which have already been investigated by using similar datasets in previous studies. Although the computation is relatively cost, the MSTCP dataset can be easily derived by professionals and thus it is not unique. In addition, the azimuthally averaged MSTCP data limit its usefulness in studying TC precipitation asymmetry. Therefore, I don't think the manuscript qualifies publication in ESSD.
Citation: https://doi.org/10.5194/essd-2023-460-RC1 - AC1: 'Reply on RC1', Jorge Garcia-Franco, 27 Jan 2024
-
RC2: 'Comment on essd-2023-460', Anonymous Referee #2, 09 Jan 2024
“A Global Multi-Source Tropical Cyclone Precipitation (MSTCP) Dataset” by Morin et al.
The topic of this manuscript is greatly interesting. A good dataset of tropical Cyclone Precipitation information is vital for accurately understanding the varying Cyclones under the changing climate. ESSD is a big journal for publishing high quality datasets. However, after carefully reading this manuscript, I found there are various points confusing me, including but not limited to: (1) there is very limited descriptions on the scientific methodology, so I can not judge the reasonability; (2) the MSTCP data has not been validated in terms of its accuracy, so at what extent do I believe it; and (3) the writings are really not good enough for the big journal, ESSD, while the current manuscript is more like a document than a scientific paper. Therefore, I am very sorry for not recommending it for publication at this stage.
Citation: https://doi.org/10.5194/essd-2023-460-RC2 - AC2: 'Reply on RC2', Jorge Garcia-Franco, 27 Jan 2024
Data sets
A Global Multi-Source Tropical Cyclone Precipitation (MSTCP) Dataset Gabriel Morin, Mathieu Boudreault, and Jorge Luis García-Franco https://zenodo.org/records/10105751
Model code and software
A Global Multi-Source Tropical Cyclone Precipitation (MSTCP) Dataset Gabriel Morin, Mathieu Boudreault, and Jorge Luis García-Franco https://github.com/GabrielMorin1109/MSTCP-Dataset
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