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Flash drought early warning based on the trajectory of solar-induced chlorophyll fluorescence
Flash drought often leads to devastating effects in multiple sectors and presents a unique challenge for drought early warning due to its sudden onset and rapid intensification. Existing drought monitoring and early warning systems are based on various hydrometeorological variables reaching threshol...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
National Academy of Sciences
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9371720/ https://www.ncbi.nlm.nih.gov/pubmed/35914136 http://dx.doi.org/10.1073/pnas.2202767119 |
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author | Mohammadi, Koushan Jiang, Yelin Wang, Guiling |
author_facet | Mohammadi, Koushan Jiang, Yelin Wang, Guiling |
author_sort | Mohammadi, Koushan |
collection | PubMed |
description | Flash drought often leads to devastating effects in multiple sectors and presents a unique challenge for drought early warning due to its sudden onset and rapid intensification. Existing drought monitoring and early warning systems are based on various hydrometeorological variables reaching thresholds of unusually low water content. Here, we propose a flash drought early warning approach based on spaceborne measurements of solar-induced chlorophyll fluorescence (SIF), a proxy of photosynthesis that captures plant response to multiple environmental stressors. Instead of negative SIF anomalies, we focus on the subseasonal trajectory of SIF and consider slower-than-usual increase or faster-than-usual decrease of SIF as an early warning for flash drought onset. To quantify the deviation of SIF trajectory from the climatological norm, we adopt existing formulas for a rapid change index (RCI) and apply the RCI analysis to spatially downscaled 8-d SIF data from GOME-2 during 2007–2018. Using two well-known flash drought events identified by the operational US Drought Monitor (in 2012 and 2017), we show that SIF RCI can produce strong predictive signals of flash drought onset with a lead time of 2 wk to 2 mo and can also predict drought recovery with several weeks of lead time. While SIF RCI shows great early warning potential, its magnitude diminishes after drought onset and therefore cannot reflect the current drought intensity. With its long lead time and direct relevance for agriculture, SIF RCI can support a global early warning system for flash drought and is especially useful over regions with sparse hydrometeorological data. |
format | Online Article Text |
id | pubmed-9371720 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | National Academy of Sciences |
record_format | MEDLINE/PubMed |
spelling | pubmed-93717202023-02-01 Flash drought early warning based on the trajectory of solar-induced chlorophyll fluorescence Mohammadi, Koushan Jiang, Yelin Wang, Guiling Proc Natl Acad Sci U S A Physical Sciences Flash drought often leads to devastating effects in multiple sectors and presents a unique challenge for drought early warning due to its sudden onset and rapid intensification. Existing drought monitoring and early warning systems are based on various hydrometeorological variables reaching thresholds of unusually low water content. Here, we propose a flash drought early warning approach based on spaceborne measurements of solar-induced chlorophyll fluorescence (SIF), a proxy of photosynthesis that captures plant response to multiple environmental stressors. Instead of negative SIF anomalies, we focus on the subseasonal trajectory of SIF and consider slower-than-usual increase or faster-than-usual decrease of SIF as an early warning for flash drought onset. To quantify the deviation of SIF trajectory from the climatological norm, we adopt existing formulas for a rapid change index (RCI) and apply the RCI analysis to spatially downscaled 8-d SIF data from GOME-2 during 2007–2018. Using two well-known flash drought events identified by the operational US Drought Monitor (in 2012 and 2017), we show that SIF RCI can produce strong predictive signals of flash drought onset with a lead time of 2 wk to 2 mo and can also predict drought recovery with several weeks of lead time. While SIF RCI shows great early warning potential, its magnitude diminishes after drought onset and therefore cannot reflect the current drought intensity. With its long lead time and direct relevance for agriculture, SIF RCI can support a global early warning system for flash drought and is especially useful over regions with sparse hydrometeorological data. National Academy of Sciences 2022-08-01 2022-08-09 /pmc/articles/PMC9371720/ /pubmed/35914136 http://dx.doi.org/10.1073/pnas.2202767119 Text en Copyright © 2022 the Author(s). Published by PNAS. https://creativecommons.org/licenses/by-nc-nd/4.0/This article is distributed under Creative Commons Attribution-NonCommercial-NoDerivatives License 4.0 (CC BY-NC-ND) (https://creativecommons.org/licenses/by-nc-nd/4.0/) . |
spellingShingle | Physical Sciences Mohammadi, Koushan Jiang, Yelin Wang, Guiling Flash drought early warning based on the trajectory of solar-induced chlorophyll fluorescence |
title | Flash drought early warning based on the trajectory of solar-induced chlorophyll fluorescence |
title_full | Flash drought early warning based on the trajectory of solar-induced chlorophyll fluorescence |
title_fullStr | Flash drought early warning based on the trajectory of solar-induced chlorophyll fluorescence |
title_full_unstemmed | Flash drought early warning based on the trajectory of solar-induced chlorophyll fluorescence |
title_short | Flash drought early warning based on the trajectory of solar-induced chlorophyll fluorescence |
title_sort | flash drought early warning based on the trajectory of solar-induced chlorophyll fluorescence |
topic | Physical Sciences |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9371720/ https://www.ncbi.nlm.nih.gov/pubmed/35914136 http://dx.doi.org/10.1073/pnas.2202767119 |
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