JOURNAL ARTICLE
Warming intensifies severe drought over China from 1980 to 2019.
Published In: International Journal of Climatology, 2023, v. 43, n. 4. P. 1980 1 of 3
Database: Academic Search Ultimate 2 of 3
Authored By: Huang, Yujia; Guo, Mengjing; Bai, Peng; Li, Jing; Liu, Lu; TIAN, Wei 3 of 3
Abstract
Climate warming is steadily increasing drought risk in many regions of the world. However, the contribution of warming over the past few decades to drought evolution in China remains unclear. This study used the self‐calibrating Palmer drought severity index (sc‐PDSI) and a detrending experiment to quantify the contribution of warming to severe drought (sc‐PDSI < −3.0) characteristics (intensity, frequency, and duration) over China from 1980 to 2019. Differences in drought characteristics calculated from original and detrended temperature data were attributed to warming effects. The results showed that 93.8% of areas in China have experienced a significant (p <.05) warming trend from 1980 to 2019. Warming remarkably intensified severe drought characteristics across China. Without warming, the extent, frequency, and duration of severe droughts in China would reduce by 2.04%, 2.0%, and 0.82 months. In addition, there are apparent regional differences in the response of severe drought characteristics to warming. Severe drought characteristics in high elevations and high latitudes are more sensitive to warming than in other regions. [ABSTRACT FROM AUTHOR]
Additional Information
- Source:International Journal of Climatology. 2023/03, Vol. 43, Issue 4, p1980
- Document Type:Article
- Subject Area:Environmental Sciences
- Publication Date:2023
- ISSN:0899-8418
- DOI:10.1002/joc.7957
- Accession Number:162402764
- Copyright Statement:Copyright of International Journal of Climatology is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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