Research Square (Research Square), Год журнала: 2025, Номер unknown
Опубликована: Апрель 28, 2025
Язык: Английский
Research Square (Research Square), Год журнала: 2025, Номер unknown
Опубликована: Апрель 28, 2025
Язык: Английский
Agricultural and Forest Meteorology, Год журнала: 2025, Номер 367, С. 110519 - 110519
Опубликована: Март 30, 2025
Язык: Английский
Процитировано
1Water, Год журнала: 2025, Номер 17(7), С. 1099 - 1099
Опубликована: Апрель 7, 2025
Analyzing drought evolution requires dynamic three-dimensional methods to capture spatiotemporal continuity. Existing approaches oversimplify patch connectivity by relying on overlapping logic, thereby neglecting evolution. We propose a novel identification method incorporating spatial autocorrelation and anisotropy. Using the ERA5 dataset multi-model ensemble mean (MEM) of CMIP6, we investigate meteorological characteristics migration patterns in China during 1961–2010 (historical) 2031–2080 (future, SSP2-4.5/SSP5-8.5). Results indicate future frequency may decline over 70% compared historical levels, but severity, duration, affected area, distance could increase significantly. Most droughts (96.3% for SSP2-4.5; 95.0% SSP5-8.5) are projected spring summer. Drought trajectories predominantly shift northeastward (33% 38% SSP5-8.5), with hotspots transitioning from upper Yangtze River Basin Yellow Basin. These findings enhance understanding dynamics support development improved monitoring frameworks. The methodology projections provide critical insights risk management adaptive water resource planning under climate change.
Язык: Английский
Процитировано
0Climate Dynamics, Год журнала: 2025, Номер 63(4)
Опубликована: Апрель 1, 2025
Язык: Английский
Процитировано
0Research Square (Research Square), Год журнала: 2025, Номер unknown
Опубликована: Апрель 28, 2025
Язык: Английский
Процитировано
0