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China has a marked continental monsoon climate characterized by dry and wet hazards that have destructive impacts on grape yields and quality. The purpose of this study was to analyze the spatiotemporal characteristics of dryness/wetness in the wine regions of China and explore the links between these variations and large-scale climatic factors. The crop-specific standardized precipitation evapotranspiration index (SPEI) was used to characterize the dryness/wetness using meteorological data collected at 168 meteorological stations located in or near the wine regions from 1981–2015. Results showed that most wine regions of China experienced a wetting trend. The drought and wet event characteristics were region- and site-specific. The main wine regions of China (e.g., Xinjiang, Helan Mountain and Hexi Corridor) were characterized by relatively high drought severity; the extreme drought frequencies of the three regions were higher as well (11.5%, 3.3%, and 3.6%, respectively). Xinjiang was also characterized by a high wetness severity and an extremely high wetness frequency of 16%, but the wetness severity decreased over time. A 4–6-year periodical oscillation was commonly detected over the wine regions. The dryness/wetness characteristics were highly associated with the Southern Oscillation Index, Niño 3.4 and the Indian Ocean Dipole, with highest correlation coefficients of −0.40, 0.36 and 0.43 at lag times of 11, 8, and 11 months, respectively. The serious dry and wet events that occurred in 2001 and 1998, respectively, were speculated to be associated with anomalous atmospheric circulation patterns. These results can be used to inform grapevine stakeholders at various levels (e.g., farmer and industry) for developing strategies to mitigate and adapt dryness/wetness events in the wine regions of China. It is expected that the approach proposed in this study can also be applicable to wine regions of other countries. [ABSTRACT FROM AUTHOR]

High-resolution meteorological data products are crucial for agrometeorological studies. Here, we study the accuracy of an important gridded dataset, the near-surface temperature dataset from the 5 km × 5 km resolution China dataset of meteorological forcing for land surface modeling (published by the Beijing Normal University). Using both the gridded dataset and the observed temperature data from 590 meteorological stations, we calculate nine universal meteorological indices (mean, maximum, and minimum temperatures of daily, monthly, and annual data) and five agricultural thermal indices (first frost day, last frost day, frost-free period, and ≥0 °C and ≥10 °C active accumulated temperature, i.e., AAT0 and AAT10) of the 11 temperature zones over mainland China. Then, for each meteorological index, we calculate the root mean square errors (RMSEs), correlation coefficient and climate trend rates of the two datasets. The results show that the RMSEs of these indices are usually lower in the north subtropical, mid-subtropical, south subtropical, marginal tropical and mid-tropical zones than in the plateau subfrigid, plateau temperate, and plateau subtropical mountains zones. Over mainland China, the AAT0, AAT10, and mean and maximum temperatures calculated from the gridded data show the same climate trends with those derived from the observed data, while the minimum temperature and its derivations (first frost day, last frost day, and frost-free period) show the opposite trends in many areas. Thus, the mean and maximum temperature data derived from the gridded dataset are applicable for studies in most parts of China, but caution should be taken when using the minimum temperature data. [ABSTRACT FROM AUTHOR]