Global Soil Wetness Project Phase 3 Atmospheric Boundary Conditions (Experiment 1)


1. IDENTIFICATION INFORMATION

Name Global Soil Wetness Project Phase 3 Atmospheric Boundary Conditions (Experiment 1)
Edition Version 1
Abbreviation GSWP3.E1-ABC
DOI doi:10.20783/DIAS.501
Metadata Identifier GSWP3_EXP1_Forcing20230727092724-DIAS20221121113753-en

2. CONTACT

2.1 CONTACT on DATASET

Name Hyungjun Kim
Organization Institute of Industrial Science, The University of Tokyo
Address Be607, 4-6-1 Komaba, Tokyo, Tokyo, 153-8505, Japan
TEL +81-3-5452-6382
FAX +81-3-5452-6383
E-mail hjkim@iis.u-tokyo.ac.jp

2.2 CONTACT on PROJECT

2.2.1 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

3. DOCUMENT AUTHOR

Name Hyungjun Kim
Organization Institute of Industrial Science, The University of Tokyo
E-mail hjkim@iis.u-tokyo.ac.jp

4. DATASET CREATOR

Name Hyungjun Kim
Organization Institute of Industrial Science, The University of Tokyo
E-mail hjkim@iis.u-tokyo.ac.jp

5. DATE OF THIS DOCUMENT

2023-07-27

6. DATE OF DATASET

  • creation : 2017-06-01

7. DATASET OVERVIEW

7.1 Abstract

retrospective atmospheric boundary conditions (9 variables: Rainfall, Snowfall, 2m Air Temperature, 2m Specific Humidity, Surface Pressure, Downward Shortwave Radiation, Downward Longwave Radiation, 10m Wind Speed, and Cloud Cover Fraction) for 1901-2010 in 3-hourly resolution are generated. 20th Century Reanalysis (20CR) [compo2011] [Compo el al., 2011] on global 2° resolution is dynamically downscaled into T248 (~0.5°) grid using a spectral nudging technique [Yoshimura and Kanamitsu 2008] in a Global Spectral Model (GSM) [Figure 2]. This successfully keeps the low frequency signal of original reanalysis, providing additional high frequency signals, which are lacking in previous products [e.g., Weedon et al., 2011]. It is essential to investigate phenomena at higher spatiotemporal scales such as extreme events. In order to relieve known artifacts (e.g., ripple patterns and persistent overcast in high latitude region), additional techniques, such as single ensemble correction [Yoshimura and Kanamitsu, 2013] and vertically weighted damping [Hong and Chang, 2012], are applied. Model biases in the downscaled 20CR are corrected using observational data (e.g., GPCC for precipitation, SRB for short/long wave radiation, and CRU for air temperature and daily temperature range). In addition to previously introduced bias correction algorithms [e.g., Weedon et al., 2011], variability in higher temporal (<month) resolution is carefully corrected [Kim et al., in preparation]. Also, wind-induced precipitation undercatch correction is applied considering different types of gauges and their global distribution [Hirabayashi et al., 2008]. Through the above mentioned data generation strategy, GSWP3 has further reliability and consistency over the century long target timespan with higher spatiotemporal resolutions.

7.2 Topic Category(ISO19139)

  • climatologyMeteorologyAtmosphere

7.3 Temporal Extent

Begin Date 1901-01-01
End Date 2010-12-31
Temporal Characteristics 3hourly

7.4 Geographic Bounding Box

North bound latitude 90
West bound longitude -180
Eastbound longitude 180
South bound latitude -90

7.5 Grid

Dimension Name Dimension Size (slice number of the dimension) Resolution Unit
time 321416 180 (minute)
row 360 0.5 (deg)
column 720 0.5 (deg)

7.6 Geographic Description

7.7 Keywords

7.7.1 Keywords on Dataset

Keyword Type Keyword Keyword thesaurus Name
discipline GSWP3, Forcing Data, Surface Climate, Surface Meteorology others

7.7.2 Keywords on Project

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

7.8 Online Resource

7.9 Data Environmental Information

7.10 Distribution Information

name version specification
netCDF4 E1V1

8. DATA PROCESSING

9. DATA REMARKS

10. DATA POLICY

10.1 Data Policy by the Data Provider

Limited Access until Project Accomplishment (CC-BY 4.0 afterward; planned)

10.2 Data Policy by the Project

10.2.1 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.

11. LICENSE

12. DATA SOURCE ACKNOWLEDGEMENT

12.1 Acknowledge the Data Provider

12.2 Acknowledge the Project

12.2.1 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. "

13. REFERENCES