Abstract
Land use and land cover changes (LUCC) are thought to be amongst the most important impacts exerted by humans on climate. However, relatively little research has been carried out so far on the effects of LUCC on extreme climate change other than on regional temperatures and precipitation. In this paper, we apply a regional weather research and forecasting (WRF) climate model using LUCC data from Heilongjiang Province, that was collected between the 1900s and 2010s, to explore how changes in forest cover influence extreme temperature indexes. Our selection of extreme high, low, and daily temperature indexes for analysis in this study enables the calculation of a five-year numerical integration trail with changing forest space. Results indicate that the total forested area of Heilongjiang Province decreased by 28% between the 1900s and 2010s. This decrease is most marked in the western, southwestern, and northeastern parts of the province. Our results also reveal a remarkable correlation between change in forested area and extreme high and low temperature indexes. Further analysis enabled us to determine that the key factor explaining increases in extreme high temperature indexes (i.e., calculated using the number of warm days, warm nights, as well as tropical nights, and summer days) is decreasing forest area; data also showed that this factor caused a decrease in extreme low temperature indexes (i.e., calculated using the number of cold days and cold nights, as well as frost days, and ice days) and an increase in the maximum value of daily minimum temperature. Spatial data demonstrated that there is a significant correlation between forest-to-farmland conversion and extreme temperature indexes throughout most of our study period. Spatial data demonstrated that there is a significant correlation between forest-to-farmland conversion and extreme temperature indexes throughout most of our study period. Positive correlations are also present between decreasing forest area, the more frequent occurrence of extreme high temperature events, and a rise in the maximum value of daily minimum temperature. At the same time, we found clear negative correlations between decreasing forest area and less frequent occurrence of extreme low temperature events.
Highlights
Humans exert a definitive influence on the climate system [1]
Some studies have shown that the effects of LUCC and the radiation of CO2 on extreme temperature and precipitation are almost the same [21,22]; Zhao and Pitman [23] argue that the influence of LUCC on maximum temperature is basically equivalent to the effects of CO2
In China, albedo is gradually changing from broad-leaved forest to grassland, the possibility of high surface temperatures is increasing because of a reduction in latent heat flux, mainly as a result of decreasing leaf area index (LAI), roughness, and root length
Summary
Humans exert a definitive influence on the climate system [1]. In addition to significant increases in aerosols such as greenhouse gases and sulfates, human activities have led to marked land use and land cover changes (LUCC). Some studies have shown that the effects of LUCC and the radiation of CO2 on extreme temperature and precipitation are almost the same [21,22]; Zhao and Pitman [23] argue that the influence of LUCC on maximum temperature is basically equivalent to the effects of CO2 These researchers noted that, in some parts of Europe, the conversion of deciduous forest to farmland has led to a reduction in the daily surface maximum temperature because of a decrease in stomatal resistance and an increase in latent heat flux. In China, albedo is gradually changing from broad-leaved forest to grassland, the possibility of high surface temperatures is increasing because of a reduction in latent heat flux, mainly as a result of decreasing leaf area index (LAI), roughness, and root length. Despite the current research mentioned above, relatively few studies have addressed LUCC rather than CO2 as a dominant forcing factor in the simulation of extreme climatic events
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