Trends in the daily and extreme temperatures in the Qiantang River basin, China

Abstract

Temporal and spatial changes in the annual and seasonal temperatures in a typical basin of the Qiantang River were analysed based on the time series databases of daily temperatures from 14 meteorological stations. Both the Mann-Kendall (MK) trend test and simple linear regression analyses were employed to detect trends in the mean and extreme temperatures. The temperature changes during the three periods of 1960-1990, 1960-2000 and 1960-2006 were investigated at each meteorological station and over the entire basin as an average. The spatial and temporal changes were characterized by significant warming throughout the region, with the minimum temperature (Tn) increasing the most, particularly after 1990. Various percentiles of extreme temperatures, as well as their corresponding frequencies, were chosen to explore the trends of extreme climate change in this region. Linear regression analyses showed a significant warming trend in cold events both on an annual and seasonal basis, especially in the winter. Conversely, the hot events were dominated by an insignificant warming trend (p > 0.05). When comparing the time series before and after 1990, trend shifts were apparent in both the mean and extreme temperatures, particularly in the spring and winter. In addition to the large-scale circulation, regional factors may have influenced the observed climate change in the studied region. Climate change has already influenced human society by, for example, increasing the frequency of haze in the study region. We conclude that the warming here is mainly attributed to changes in the minimum temperature.

The Large‐Scale Circulation Patterns Responsible for Extreme Precipitation Over the North China Plain in Midsummer

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Trends in observed mean and extreme precipitation within the Yellow River Basin, China

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Long-term relationships between climate oscillation and basin-scale hydrological variability during rainy season in eastern Northeast Brazil

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