Shelterbelts are increasingly used to mitigate strong wind damage, but the complex canopy structures create challenges for numerical studies of windbreak effectiveness, such as the trade-off between computational cost and accuracy of results. To address these challenges and accurately investigate the downstream wind fields, most conventional studies represent shelterbelts as rectangular porous media with a uniformly distributed aerodynamic resistance coefficient. However, due to the vertical variation in canopy diameter and the irregular distribution of leaf density, the aerodynamic resistance of natural shelterbelts becomes nonuniform accordingly. To quantify the discrepancies arising from this simplification, this study first proposes a non-destructive approach to calculate canopy porosity profiles, which are further used to derive aerodynamic resistance at different heights. Then, by comparing the results obtained from the conventional and proposed approaches in Large-Eddy Simulations, the discrepancies caused by ignoring the vertical variation in canopy structures are analyzed. Finally, these discrepancies are further investigated for double-row shelterbelts. The results show that ignoring the vertical variation in canopy diameter leads to significant differences in windbreak effectiveness, especially for the downstream velocity and pressure fields at the top and middle heights of the canopy. The proposed approach provides a computationally efficient and more accurate representation of near-surface wind fields downstream of shelterbelts, thereby contributing to the accurate prediction of local wind fields for meteorological services.

Atmospheric drought, defined here as days on which vapor pressure deficit (VPD) exceeds its 90th percentile, is usually studied in water-limited regions yet threatens vegetation where water is abundant. Using solar-induced chlorophyll fluorescence (SIF) from the contiguous SIF (CSIF) dataset, MODIS gross primary productivity (GPP), and meteorology in the Nanling Mountains, China, we quantify the dominant climatic signal and vegetation response. Extreme hot days showed no trend, whereas extreme drought days rose nearly tenfold, from 10.6 to 101.8 d yr⁻¹, partly reflecting a 2002–2003 humidity step; both VPD tails widened. Hydrological drought (via the standardized precipitation evapotranspiration index, SPEI-3) showed no regional trend, and the two trend fields were uncorrelated. A counterfactual reconstruction validated the record; humidity alone contributed +1.06 d yr⁻¹ (46% of the rise), temperature alone +0.12 (not significant), and the remainder reflects their joint covariation. Path analysis showed associations consistent with drought suppressing GPP mainly via SIF (indirect effect −0.174; direct effect not significant). Canopy greenness (near-infrared reflectance of vegetation, NIRv) was unresponsive in dry months, topsoil moisture showed no trend, and MODIS GPP moved in the opposite direction to CSIF in dry months (+2.42% versus −2.33%); both declined in the 2022 flash drought, CSIF five times more (−9.6% versus −1.9%).