Development of global monthly dataset of CMIP6 climate variables for estimating evapotranspiration

Song YH 1 , Chung ES 2 , Shahid S 3 , Kim Y 4 , Kim D 5

Affiliations 

  • 1 Department of Civil Engineering, Seoul National University of Science and Technology, Nowon-gu, 01811, Seoul, South Korea
  • 2 Department of Civil Engineering, Seoul National University of Science and Technology, Nowon-gu, 01811, Seoul, South Korea. eschung@seoultech.ac.kr
  • 3 School of Civil Engineering, Universiti Teknologi Malaysia (UTM), 81310, Skudai, Johor, Malaysia
  • 4 Department of Civil and Environmental Engineering, Yonsei University, 03722, Seoul, South Korea
  • 5 Department of Civil Engineering, Hongik University, 04066, Seoul, South Korea
Sci Data, 2023 Aug 26;10(1):568.
PMID: 37633988 DOI: 10.1038/s41597-023-02475-7

Abstract

Reliable projection of evapotranspiration (ET) is important for planning sustainable water management for the agriculture field in the context of climate change. A global dataset of monthly climate variables was generated to estimate potential ET (PET) using 14 General Circulation Models (GCMs) for four main shared socioeconomic pathways (SSPs). The generated dataset has a spatial resolution of 0.5° × 0.5° and a period ranging from 1950 to 2100 and can estimate historical and future PET using the Penman-Monteith method. Furthermore, this dataset can be applied to various PET estimation methods based on climate variables. This paper presents that the dataset generated to estimate future PET could reflect the greenhouse gas concentration level of the SSP scenarios in latitude bands. Therefore, this dataset can provide vital information for users to select appropriate GCMs for estimating reasonable PETs and help determine bias correction methods to reduce between observation and model based on the scale of climate variables in each GCM.

* Title and MeSH Headings from MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine.

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