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

Young Hoon Song; Eun Sung Chung; Shamsuddin Shahid; Yeonjoo Kim; Dongkyun Kim

doi:10.1038/s41597-023-02475-7

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

Young Hoon Song, Eun Sung Chung, Shamsuddin Shahid, Yeonjoo Kim, Dongkyun Kim

Department of Civil and Environmental Engineering

Research output: Contribution to journal › Article › peer-review

10 Citations (Scopus)

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.

Original language	English
Article number	568
Journal	Scientific Data
Volume	10
Issue number	1
DOIs	https://doi.org/10.1038/s41597-023-02475-7
Publication status	Published - 2023 Dec

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© 2023, Springer Nature Limited.

All Science Journal Classification (ASJC) codes

Statistics and Probability
Information Systems
Education
Computer Science Applications
Statistics, Probability and Uncertainty
Library and Information Sciences

UN SDGs

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10.1038/s41597-023-02475-7

Cite this

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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.",

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AU - Kim, Dongkyun

PY - 2023/12

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

Abstract

Bibliographical note

All Science Journal Classification (ASJC) codes

UN SDGs

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