Mon Dec 15, F. Flechtner
• Sorted by Date • Sorted by Last Name of First Author •
Zhou, Jun, Cui, Lilu, Li, Yu, Yao, Chaolong, Meng, Jiacheng, Zou, Zhengbo, and Lu, Yuheng, 2025. GRACE/GFO and Swarm Observation Analysis of the 2023–2024 Extreme Drought in the Amazon River Basin. Remote Sensing, 17(16):2765, doi:10.3390/rs17162765.
• from the NASA Astrophysics Data System • by the DOI System •
@ARTICLE{2025RemS...17.2765Z,
author = {{Zhou}, Jun and {Cui}, Lilu and {Li}, Yu and {Yao}, Chaolong and {Meng}, Jiacheng and {Zou}, Zhengbo and {Lu}, Yuheng},
title = "{GRACE/GFO and Swarm Observation Analysis of the 2023{\textendash}2024 Extreme Drought in the Amazon River Basin}",
journal = {Remote Sensing},
keywords = {GRACE/GFO, Swarm, regional drought, extreme climate, atmospheric circulation, water vapor transport},
year = 2025,
month = aug,
volume = {17},
number = {16},
eid = {2765},
pages = {2765},
abstract = "{The Amazon River Basin (ARB) experienced an extreme drought from summer
2023 to spring 2024, driven by complex interactions among
multiple climatic and environmental factors. A detailed
investigation into this drought is crucial in understanding the
entire process of the drought. Here, we employ drought indices
derived from the Gravity Recovery and Climate Experiment
(GRACE), GRACE Follow-On (GFO), and Swarm missions to
reconstruct the drought's progression, combined with reanalysis
datasets and extreme-climate indices to analyze atmospheric and
hydrological mechanisms. Our findings reveal a six-month drought
from September 2023, reaching a drought peak of ‑1.29 and a
drought severity of ‑5.62, with its epicenter migrating
systematically from the northwestern to southeastern basin,
spatially mirroring the 2015{\textendash}2016 extreme drought
pattern. Reduced precipitation and abnormal warming were the
direct causes, which were closely linked to the 2023 El Ni{\~n}o
event. This event disrupted atmospheric vertical movements.
These changes led to abnormally strong sinking motions over the
basin, which interacted synergistically with anomalies in land
cover types caused by deforestation, triggering this extreme
drought. This study provides spatiotemporal drought diagnostics
valuable for hydrological forecasting and climate adaptation
planning.}",
doi = {10.3390/rs17162765},
adsurl = {https://ui.adsabs.harvard.edu/abs/2025RemS...17.2765Z},
adsnote = {Provided by the SAO/NASA Astrophysics Data System}
}
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