Mesoscale Analysis and Numerical Simulation of an Extreme Precipitation Event on the Northern Slope of the Middle Kunlun Mountains in Xinjiang, China

Under accelerating global warming, the northern slope of the Middle Kunlun Mountains in Xinjiang, China, has seen a marked rise in extreme rainfall, posing increasing challenges for flood risk management and water resources. To improve our predictive capabilities and deepen our understanding of the driving mechanisms, we combine the European Centre for Medium-Range Weather Forecasts Reanalysis-5 (ERA5) reanalysis, regional observations, and high-resolution Weather Research and Forecasting model (WRF) simulations to dissect the 14–17 June 2021, extreme rainfall event. A deep Siberia–Central Asia trough and nascent Central Asian vortex established a coupled upper- and low-level jet configuration that amplified large-scale ascent. Embedded shortwaves funnelled abundant moisture into the orographic basin, where strong low-level moisture convergence and vigorous warm-sector updrafts triggered and sustained deep convection. WRF reasonably replicated observed wind shear and radar echoes, revealing the descent of a mid-level jet into an ultra-low-level jet that provided a mesoscale engine for storm intensification. Momentum–budget diagnostics underscore the role of meridional momentum transport along sloping terrain in reinforcing low-level convergence and shear. Together, these synoptic-to-mesoscale interactions and moisture dynamics led to this landmark extreme-precipitation event.

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Publication Details

Journal
Remote Sensing
Published
2025-07-19
DOI
https://doi.org/10.3390/rs17142519
Primary Topic
Meteorological Phenomena and Simulations
Type
article
Field-Weighted Citation Impact
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article

Mesoscale Analysis and Numerical Simulation of an Extreme Precipitation Event on the Northern Slope of the Middle Kunlun Mountains in Xinjiang, China

Chenxiang Ju, Zonghui Liu, Ailiyaer Aihaiti, Junqiang Yao et al.
Remote Sensing
Meteorological Phenomena and Simulations
article

Mesoscale Analysis and Numerical Simulation of an Extreme Precipitation Event on the Northern Slope of the Middle Kunlun Mountains in Xinjiang, China

Chenxiang Ju, Zonghui Liu, Ailiyaer Aihaiti, Junqiang Yao, Qian Li, Man Li, Xia Yang, Yisilamu Wulayin, Weiwei Shao
article en

Abstract

Under accelerating global warming, the northern slope of the Middle Kunlun Mountains in Xinjiang, China, has seen a marked rise in extreme rainfall, posing increasing challenges for flood risk management and water resources. To improve our predictive capabilities and deepen our understanding of the driving mechanisms, we combine the European Centre for Medium-Range Weather Forecasts Reanalysis-5 (ERA5) reanalysis, regional observations, and high-resolution Weather Research and Forecasting model (WRF) simulations to dissect the 14–17 June 2021, extreme rainfall event. A deep Siberia–Central Asia trough and nascent Central Asian vortex established a coupled upper- and low-level jet configuration that amplified large-scale ascent. Embedded shortwaves funnelled abundant moisture into the orographic basin, where strong low-level moisture convergence and vigorous warm-sector updrafts triggered and sustained deep convection. WRF reasonably replicated observed wind shear and radar echoes, revealing the descent of a mid-level jet into an ultra-low-level jet that provided a mesoscale engine for storm intensification. Momentum–budget diagnostics underscore the role of meridional momentum transport along sloping terrain in reinforcing low-level convergence and shear. Together, these synoptic-to-mesoscale interactions and moisture dynamics led to this landmark extreme-precipitation event.

Remote SensingVol. 17(14)
China Meteorological Administration (CN), Xinjiang Astronomical Observatory (CN), Institute of Ecology and Geography (MD), Xinjiang Institute of Ecology and Geography (CN), Xinjiang Entry-Exit Inspection and Quarantine Bureau (CN), Chinese Academy of Meteorological Sciences (CN)
Natural Science Foundation of Xinjiang Province
Openalex Percentile: Top 78%
Meteorological Phenomena and Simulations
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