4.1 Article

Spatial Variations of Climate-Driven Trends of Water Vapor Pressure and Relative Humidity in Northwest China

期刊

出版社

KOREAN METEOROLOGICAL SOC
DOI: 10.1007/s13143-018-0062-7

关键词

Temperature trend; Precipitation trend; Water vapor pressure; Relative humidity; Semi-arid and arid regions of China

资金

  1. Western Light Foundation of the Chinese Academy of Sciences (CAS) [XBBS-2014-15]
  2. National Natural Science Foundation of China [U1403281, 41371011, 41671030]

向作者/读者索取更多资源

The interaction between climate change trends and water cycle variables is complex. The spatial distributions and trends of hydroclimatic variables (precipitation, temperature, water vapor pressure, and relative humidity) at 65 stations in Xinjiang in 1961-2011 were analyzed. Five meteorological stations were selected for a detailed analysis of the changes in climatic factors. We explored the relationship between water vapor pressure, relative humidity, temperature, and precipitation using nonparametric methods [the block bootstrap (B-B) method, Mann-Kendall (MK) test, and a generalized additive model (GAM)] for data from 1940 to 2011. The results showed that temperature, precipitation, and water vapor pressure at most stations increased over the period studied, while relative humidity decreased in the north of Xinjiang, and increased in the south. The results indicated that the temperature and water vapor pressure were elevated. At the same time, there was a large spatiotemporal heterogeneity of precipitation and relative humidity among the five stations. The water vapor pressure had a significant positive relationship with temperature and relative humidity, but the temperature trend with relative humidity displayed a negative relationship. The relationship of the precipitation and temperature trends with water vapor and relative humidity was either positive or negative. The most significant controlling factor for the climate variables was relative humidity, which was governed by water vapor pressure in the study area. Further investigations are needed to better understand the climatic influences in other complex physiographic landscapes, and to determine reliable mechanisms to more effectively integrate water cycle variables, high resolution data, and climatic modeling.

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