Typhoon DDS for changing climate by a regional a–o coupled model


Citation for this dataset
Sachie Kanada. (2023). Typhoon DDS for changing climate by a regional a–o coupled model [Data set]. Data Integration and Analysis System (DIAS). https://doi.org/10.20783/DIAS.666
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IDENTIFICATION INFORMATION

Name Typhoon DDS for changing climate by a regional a–o coupled model
DOI doi:10.20783/DIAS.666
Metadata Identifier 4TYs_PGW_CReSS_NHOES20240422101118-DIAS20221121113753-en

CONTACT

CONTACT on DATASET

Name Sachie Kanada
E-mail skanada@nagoya-u.jp

CONTACT on PROJECT

Data Integration and Analysis System

Name DIAS Office
Organization Japan Agency for Marine-Earth Science and Technology
Address 3173-25, Showa-Cho, Kanazawa-ku, Yokohama-shi, Kanagawa, 236-0001, Japan
E-mail dias-office@diasjp.net

DOCUMENT AUTHOR

Name Sachie Kanada

DATASET CREATOR

Name Sachie Kanada

DATE OF THIS DOCUMENT

2024-04-22

DATE OF DATASET

  • creation : 2023-12-27

DATASET OVERVIEW

Abstract

The pseudo global warming (PGW) experiments on four historical intense typhoons under four different warming conditions were conducted using a regional high-resolution three-dimensional atmosphere–ocean coupled model, CReSS-NHOES (Aiki et al., 2015). Four historical intense typhoons that traveled northward and affected Japan, Typhoons Trami (2018), Faxai (2019), Hagibis (2019), and Haishen (2020), were selected. The PGW increments were made from the Database for Policy Decision-Making for Future Climate Change (d4PDF), which includes 100 ensembles of pre-industrial, historical, and 2 K and 4 K warmer climate experiments with a 60-km-mesh atmospheric global circulation model (Mizuta et al. 2017). See Figure S1 and Tables S1 and S2 of Kanada and Aiki (2024) for more information about the experiments and the initial and boundary conditions used. This dataset includes hourly outputs from the atmospheric and oceanic parts.

Topic Category(ISO19139)

  • climatologyMeteorologyAtmosphere

Temporal Extent

Begin Date 2018-09-26
End Date 2020-09-06
Temporal Characteristics Hourly

Geographic Bounding Box

North bound latitude 43
West bound longitude 124
Eastbound longitude 154
South bound latitude 14

Grid

Dimension Name Dimension Size (slice number of the dimension) Resolution Unit
row 0.01/0.02 (deg)
column 0.01/0.02 (deg)
vertical 10-2000 (m)

Keywords

Keywords on Dataset

Keyword Type Keyword Keyword thesaurus Name
theme Atmosphere > Atmospheric Phenomena > Typhoons, Human Dimensions > Natural Hazards > Tropical Cyclones > Typhoons GCMD_science
theme Climate GEOSS

Keywords on Project

Data Integration and Analysis System
Keyword Type Keyword Keyword thesaurus Name
theme DIAS > Data Integration and Analysis System No_Dictionary

Data Environmental Information

The datasets contain the following files and variables. out_cress (CReSS outputs): 1) Two dimensional surface data (EXID_CLIMID.sfc_ YYYY_MO_DD_HHMMUTC.z56.bin)[hourly; sea level pressure, velocity in lon and lat-directions at 10m, soil and sea surface temperature, rain fall rate, accumulated rain fall] 2) Three dimensional atmospheric data1 (EXID_CLIMID.dmp_ YYYY_MO_DD_HHMMUTC.z56.bin)[hourly; zonal, meridional and z components of velocities, pressure, potential temperature, water vapor mixing ratio] 3) Three dimensional atmospheric data2 (EXID_CLIMID.cld_ YYYY_MO_DD_HHMMUTC.z56.bin)[hourly; cloud, rain water, cloud ice, snow, graupel mixing ratio] 4) User namelist (".user.conf") out_nhoes (NHOES outputs): 5) Three dimensional oceanic data (nhoes_EXID_CLIMID.YYYY_MO_DD_HHMMUTC.z80.bin)[hourly; u, v, w, temperature, salinity, density] 1)-3)and 5) are 4byte binary (big endian) data files with corresponding Grads ctl files. The extension ".bin" is for the data file and ".ctl" is for the Grads ctl file. Trami (Directory: TRAMI2018, EXID: T1824_2606_1km), Faxai (FAXAI2019, T1915_0700_1km), Hagibis (HAGIBIS2019, T1919_1018_1km),Haishen (HAISHEN2020, T2010_0112_2km). Control (CLIMID: CNTL), pre-industrial (NAT), and 2 K (2K) and 4 K (4K) warmer climate experiments. EXID: Experiment ID, CLIMID: Climate ID, YYYY: Year MO: Month DD_HHMM: Day, hour, and minutes.

DATA POLICY

Data Policy by the Data Provider

Data Polilcy:

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.

Disclaimer:

The intellectual property rights of the dataset belong exclusively to Nagoya university. Nagoya university and anyone, including the creator (and all individuals and organizations involved in the creation of this dataset), are not responsible for any damage that may result from the use of this dataset.

Data Policy by the Project

Data Integration and Analysis System

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.

DATA SOURCE ACKNOWLEDGEMENT

Acknowledge the Data Provider

The computation was carried out on the supercomputer "Flow" at Information Technology Center, Nagoya University. This work was partially supported by Japan Society for the Promotion of Science KAKENHI Grants 20H05166 and 19H05696.

Acknowledge the Project

Data Integration and Analysis System

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. "

REFERENCES

PGW experiment:

Kanada, S., and H. Aiki, 2024: Buffering effect of atmosphere–ocean coupling on intensity changes of tropical cyclones under a changing climate. Geophysical Research Letters, 51, e2023GL105659. https://doi.org/10.1029/2023GL105659

CReSS-NHOES:

Aiki, H., M. Yoshioka, M. Kato, A. Morimoto, T. Shinoda, and K. Tsuboki, 2015: A coupled atmosphere-ocean-surface-wave modeling system for understanding air-sea interactions under tropical cyclone conditions, Bull. Coastal Oceanogr., 52, 139–148.

d4PDF:

Mizuta, R., and co-authors, 2017: Over 5000 Years of Ensemble Future Climate Simulations by 60 km Global and 20 km Regional Atmospheric Models. Bull. Amer. Meteor. Soc., 1383–1398, doi:10.1175/BAMS-D-16-0099.1.

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