State Key Laboratory of Severe Weather

A process-oriented framework for daily dynamic monitoring of summer maize drought: From meteorological stress to agricultural impact

CONTEXT The progression of crop drought from meteorological deficit to agricultural damage is a continuous, stage-specific process. However, prevailing drought monitoring approaches, including single-type indices (e.g., SPI) and integrated composite indices (e.g., CDI), either fa...

Small bias, large errors: a dual-perspective evaluation of numerical model near-surface wind direction over beijing megacity

Abstract Accurate surface wind fields are essential for understanding moisture transport and heavy rainfall forecasts, yet the ability of kilometer-scale numerical models to capture wind direction over heterogeneous surfaces remains poorly quantified. Using the EARS1km reanalysis...

Evaluation for Optimal Model Selection and Bias-Corrected Projections of Daytime and Nighttime Extreme Heat in China Using the SimmEX Dataset

Global warming has intensified extreme heat events, posing growing climate risks. As a climate-sensitive region, China has experienced compound daytime and nighttime extreme heat, threatening health, ecosystems, and socioeconomic development. Accurate projections of future extrem...

Impacts of South Asian aerosol inflow over Mount Qomolangma on downstream cloud–precipitation processes through a long-range ice-crystal “seeding” effect

Mount Qomolangma (MQ) serves as a natural laboratory for investigating aerosol–cloud–precipitation interactions over the Tibetan Plateau (TP). Using satellite and comprehensive ground-based observations, we identify pronounced ice-cloud activation associated with transported exog...

China regional 3 km downscaling based on residual Corrective Diffusion model

A fundamental challenge in numerical weather prediction is efficiently producing high-resolution forecasts. A widely adopted solution is to downscale coarser global model outputs. This study focuses on statistical downscaling, which uses historical data to learn mappings between...

Capturing Typhoon Rapid Intensification and Abrupt Recurvature Using an IAU‐Based 4DVar Scheme

Abstract Dynamic imbalances in model initialization severely constrain the predictability of the rapid intensification (RI) and abrupt track recurvature of tropical cyclones (TCs). In this study, the effectiveness of an incremental analysis update (IAU)‐based four‐dimensional var...