Name | d4PDF tropical cyclone track dataset |
DOI | doi:10.20783/DIAS.640 |
Metadata Identifier | d4PDF_tropical_cyclone20230727103351-DIAS20221121113753-en |
Name | Tomoya Shimura |
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Organization | Disaster Prevention Research Institute, Kyoto University |
dias@oceanwave.jp |
Name | Tomoya Shimura |
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Organization | Integrated Climate Model Advanced Research Program (TOUGOU Program) |
Name | Adrean Webb |
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Organization | Integrated Climate Model Advanced Research Program (TOUGOU Program) |
1) Global tropiocal cyclone dataset created from "database for Policy Decision making for Future climate change (d4PDF)" using the objective cyclone tracking algorithm. The 6000 years amount data for historical climate and 5400 years amount data for 4 degree warming future, were used.
2) Two different objective cyclone tracking algorithm were applied and the each dataset is provided, respectively.
3) Source dataset (d4PDF dataset) of this dataset can be obtained from http://search.diasjp.net/en/dataset/d4PDF_GCM .
4) This dataset can be useful for meteorological disaster risk assessment under climate change due to tropical cyclones.
North bound latitude | 90 |
West bound longitude | -180 |
Eastbound longitude | 180 |
South bound latitude | -90 |
Keyword Type | Keyword | Keyword thesaurus Name |
---|---|---|
theme | Atmosphere > Atmospheric Pressure > Anticyclones/Cyclones, Climate Indicators > Atmospheric/Ocean Indicators > Extreme Weather > Tropical Or Extratropical Cyclone Frequency/Intensity | GCMD_science |
theme | GLOBAL CHANGE > Impacts of global change | AGU |
file download : https://data.diasjp.net/dl/storages/filelist/dataset:640
The file naming is as follows. Historical climate: {algorithm}_HPB_m{number}.nc ・{algorithm} is the TC tracking algorithm from KU (Webb et al., 2019) and MRI (Yoshida et al., 2017) ・{number} is the number of ensemble member. Future climate: {algorithm}_HFB_4K_{SST}_m{number}.nc ・{algorithm} is the TC tracking algorithm from KU (Webb et al., 2019) and MRI (Yoshida et al., 2017) ・{SST} is the future SST condition from CC, GF, HA, MI, MP, and MR. ・{number} is the number of ensemble member.
Data Policy:
1. Individual users should not redistribute the data to any third party.
2. The source of the database should be acknowledged in scientific and technical papers, publications, press releases and other communications in case of using the data.
3. This dataset can be used for non-commercial purposes. For commercial use of this dataset, the prior explicit permission of the data provider must be obtained.
Disclaimer:
The intellectual property rights of the dataset belong exclusively to Disaster Prevention Research Institute, Kyoto university and Meteorological Research Institute of Japan Meteorological Agency. Disaster Prevention Research Institute, Kyoto university and Meteorological Research Institute of Japan Meteorological Agency are not responsible for any damage that may result from the use of this dataset.
If data provider does not have data policy, DIAS Terms of Service (https://diasjp.net/en/terms/) and DIAS Privacy Policy (https://diasjp.net/en/privacy/) apply.
If there is a conflict between DIAS Terms of Service and data provider's policy, the data provider's policy shall prevail.
- In case that tracks by Webb et al. (2019) are used
"The track data is provided by Webb et al. (2019) based on d4PDF dataset (Mizuta et al. 2017)."
- In case that tracks by Yoshida et al. (2017) are used
"The track data is provided by Yoshida et al. (2017) based on d4PDF dataset (Mizuta et al. 2017)."
Please cite following references
Webb, A., T. Shimura and N. Mori (2019) Global Tropical Cyclone Track Detection and Analysis of the d4PDF Mega-ensemble Projection, Journal of Japan Society of Civil Engineers, Ser. B2 (Coastal Engineering), 75, p. I_1207-I_1212. https://doi.org/10.2208/kaigan.75.I_1207
Yoshida, K., M. Sugi, R. Mizuta, H. Murakami and M. Ishii (2017). Future changes in tropical cyclone activity in high‐resolution large‐ensemble simulations. Geophysical Research Letters, 44(19), 9910-9917. https://doi.org/10.1002/2017GL075058
Mizuta, R., A. Murata, M. Ishii, H. Shiogama, K. Hibino, N. Mori, O. Arakawa, Y. Imada, K. Yoshida, T. Aoyagi, H. Kawase, M. Mori, Y. Okada, T. Shimura, T. Nagatomo, M. Ikeda, H. Endo, M. Nosaka, M. Arai, C. Takahashi, K. Tanaka, T. Takemi, Y. Tachikawa, K. Temur, Y. Kamae, M. Watanabe, H. Sasaki, A. Kitoh, I. Takayabu, E. Nakakita, M. Kimoto (2017) Over 5000 years of ensemble future climate simulations by 60 km global and 20 km regional atmospheric models, The Bulletin of the American Meteorological Society (BAMS), July, pp.1383-1398. https://doi.org/10.1175/BAMS-D-16-0099.1
If you plan to use this dataset for a conference presentation, paper, journal article, or report etc., please include acknowledgments referred to following examples. If the data provider describes examples of acknowledgments, include them as well.
" In this study, [Name of Dataset] provided by [Name of Data Provider] was utilized. This dataset was also collected and provided under the Data Integration and Analysis System (DIAS), which was developed and operated by a project supported by the Ministry of Education, Culture, Sports, Science and Technology. "
Webb, A., T. Shimura and N. Mori (2019) Global Tropical Cyclone Track Detection and Analysis of the d4PDF Mega-ensemble Projection, Journal of Japan Society of Civil Engineers, Ser. B2 (Coastal Engineering), 75, p. I_1207-I_1212. https://doi.org/10.2208/kaigan.75.I_1207
Yoshida, K., M. Sugi, R. Mizuta, H. Murakami and M. Ishii (2017). Future changes in tropical cyclone activity in high‐resolution large‐ensemble simulations. Geophysical Research Letters, 44(19), 9910-9917. https://doi.org/10.1002/2017GL075058
Mizuta, R., A. Murata, M. Ishii, H. Shiogama, K. Hibino, N. Mori, O. Arakawa, Y. Imada, K. Yoshida, T. Aoyagi, H. Kawase, M. Mori, Y. Okada, T. Shimura, T. Nagatomo, M. Ikeda, H. Endo, M. Nosaka, M. Arai, C. Takahashi, K. Tanaka, T. Takemi, Y. Tachikawa, K. Temur, Y. Kamae, M. Watanabe, H. Sasaki, A. Kitoh, I. Takayabu, E. Nakakita, M. Kimoto (2017) Over 5000 years of ensemble future climate simulations by 60 km global and 20 km regional atmospheric models, The Bulletin of the American Meteorological Society (BAMS), July, pp.1383-1398. https://doi.org/10.1175/BAMS-D-16-0099.1