Enhancing rainfall estimation accuracy with machine learning, cloud masking, and multi-source data: A case study of four coastal provinces in central Vietnam. [PDF]
Vu Duy D +4 more
europepmc +1 more source
Drought spatiotemporal propagation and direct driving variables are assessed at multiple time steps with high spatial resolution using various drought indices (SPI, SPEI and SPDI) and entropy based mutual information under an ensemble of climate change projections over Tunisia. ABSTRACT Projecting drought occurrence and spatiotemporal propagation under
Haykel Sellami
wiley +1 more source
Human-induced climate change amplification on storm dynamics in Valencia's 2024 catastrophic flash flood. [PDF]
Calvo-Sancho C +10 more
europepmc +1 more source
Best bet forages species for different edapho-climatic conditions [PDF]
Cardoso Arango, Juan Andrés +1 more
core
Projected Annual and Monsoonal Precipitation Trends of CMIP6 Over Peninsular Malaysia
In this study, we examined historical and projected precipitation temporal trends across Peninsular Malaysia using ground‐based records and CMIP6 models from NEX‐GDDP. Analysing data from 518 reliable gauges over 1973–2022, it identified spatial and monsoonal variations.
Nurul Afiqah Mohamad Arbai +1 more
wiley +1 more source
Ensemble and temporal feature-based framework for rainfall classification in Bangladesh. [PDF]
Tamim MS +4 more
europepmc +1 more source
The graphical abstract presents observed (1963–2023) and projected changes in hydroclimatic extremes in Rio Grande do Norte, Brazil. It integrates dry‐spell duration (CDD) and extreme precipitation (R95pTOT) using CMIP6 multimodel ensembles under SSP1‐2.6, SSP2‐4.5, and SSP5‐8.5.
Daris Correia dos Santos
wiley +1 more source
Research on a dynamic early warning model based on refined threshold analysis: Case study of the Tanjiawan Landslide. [PDF]
Wang W, Yi W, Huang X, Wang Y, Wang Z.
europepmc +1 more source
Performance Evaluation of the MPAS Model in Simulating Southeast Asian Rainfall Characteristics
This study evaluates the performance of the Model for Prediction Across Scales–Atmosphere (MPAS) in reproducing key rainfall characteristics over Southeast Asia (SEA) during 2000–2020, using the MSWEP dataset as reference. MPAS realistically captures the observed meridional rainfall gradient, with higher rainfall in the south and lower in the north, as
Nguyen Thanh Hung +4 more
wiley +1 more source

