Based on historical tropical cyclone (TC) tracking data and wind data from observation stations, four comparison experiments were designed that considered TC translation speed similarity and five new ensemble schemes in an improved Dynamical-Statistical-Analog Ensemble Forecast (DSAEF) model for Landfalling Typhoon Gale (LTG), which was tested in terms of forecast capability in South China. The results showed that the improved DSAEF_LTG model with the incorporation of TC translation speed and a new ensemble scheme could improve the forecast threat score (TS) and reduce both the false alarm ratio and the missing ratio in comparison with corresponding values attained before the improvement. The TS of the new ensemble scheme model (DLTG_3) was 0.34 at threshold above Beaufort Scale 7, which was 31% better than that of the unimproved model (DLTG_1). At a threshold above Beaufort Scale 10, the TS of DLTG_3 indicated even greater improvement, reaching 0.25, i.e., 127% higher than that of DLTG_1. The results of the experiments illustrated the marked improvement achievable when using the new ensemble scheme. The reasons for the differences in the DSAEF_LTG model forecasts before and after the introduction of TC translation speed and the new ensemble scheme were analyzed for the cases of Typhoon Haima and Typhoon Hato.

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%).