The high spatial complexities of soil temperature modelling over semiarid land have challenged the calibration—predication framework, whose composited objective lacks comprehensive evaluation. Therefore, this study, based on the Noah land surface model and its full parameter table, utilizes two global searching algorithms and eight kinds of objective with dimensional—varied metrics, combined with dense site soil moisture and temperature observations of central Tibet, to explore different metrics’ performances on the spatial heterogeneity and uncertainty of regional land surface parameters, calibration efficiency and effectiveness, as well as spatiotemporal complexities in surface forecasting. Results have shown that metrics’ diversity has shown greater influence on the calibration—predication framework than the global searching algorithms themselves. Besides being significantly better than other metrics, the enhanced multi objective metric (EMO) and the enhanced Kling-Gupta efficiency (EKGE) have their own advantages and disadvantages in simulations and parameters respectively. Especially, EMO that composited with four metrics as correlated coefficient, root mean square error, mean absolute error, and Nash–Sutcliffe efficiency, has shown relatively balanced performance in surface forecasting when compared to EKGE. In general, the calibration—predication framework that benefited from EMO could greatly reduce the spatial complexities in soil temperature modelling of the semiarid land.

Geostationary atmospheric motion vectors (e.g., FY4A AMVs) are routine mid-upper atmospheric observations used in numerical weather prediction (NWP) models, yet their complex spatiotemporal errors and assimilation limitations, i.e., high-temporal/coarse-spatial data and large-scale-adjustment/direct-assimilation scheme, leave unclear impacts of AMVs assimilation on nowcasting forecasts. To this end, a Nudging-Forced-3DVar (NFV) scheme is designed within a multi-scale (i.e., 12-, 4-, and 1-km) regional NWP framework to exploit AMVs characteristics; ablation experiments for the Zhengzhou “7·20” rainstorm isolate Nudging and 3DVar impacts on assimilation and nowcasting. Results show: 1) large-scale Nudging and high-resolution 3DVar both improve mid-upper analyses, with the former ingesting more observations; 2) Nudging retains large-scale background updates but yields significant misses, whereas 3DVar intensifies rainfall extremes yet blurs fine structures; 3) NFV merges their strengths, modulating deep convection through upper-level systems and markedly improving rainfall spatiotemporal patterns. Therefore, NFV is recommended for the FY4A AMVs’ future numerical nowcasting, which provides useful guidance for regional application of geostationary 3D-winds.

The global shipping industry is evolving towards deep integration of digital transformation, intelligent upgrading, and green development. Meanwhile, recent geopolitical shifts have introduced heightened uncertainties into international shipping, compounding the challenges and escalating the demands for weather routing services for ocean-going ships. This paper provides a systematic review and expert perspective on China’s current status and key challenges in ocean-going weather routing services. Based on operational insights from China’s national meteorological service synthesized with a review of current trends and the literature, it further explores the future development of China’s ocean-going weather routing services and technologies from multiple dimensions: enhancing maritime weather observation capabilities, developing advanced weather routing service models, upgrading autonomous and controllable global satellite communication systems, promoting intelligent navigation technologies to facilitate shipping’s low-carbon transition, and expanding meteorological support capabilities for Arctic shipping routes. The analysis identifies critical gaps and proposes strategic directions, offering a unique contribution to understanding the trajectory of weather routing services within China’s specific national context from the perspective of its primary national service provider.