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Development of global monthly dataset of CMIP6 climate variables for estimating evapotranspirationopen access

Authors
Song, Young HoonChung, Eun-SungShahid, ShamsuddinKim, YeonjooKim, Dongkyun
Issue Date
Aug-2023
Publisher
Nature Research
Citation
Scientific Data, v.10, no.1
Journal Title
Scientific Data
Volume
10
Number
1
URI
https://scholarworks.bwise.kr/hongik/handle/2020.sw.hongik/31614
DOI
10.1038/s41597-023-02475-7
ISSN
2052-4463
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. © 2023, Springer Nature Limited.
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