Daily temperature and precipitation data from 136 stations of Southwest China (SWC) during the last five decades, from 1960 to 2007, were analysed to determine the spatial and temporal trends by using the Mann-Kendall trend test. Results show that SWC has become warmer over the last five decades, especially in the recent 20-25 years. The increasing trends in winter months are more significant than those in the months of other seasons, and spatially Tibet, Hengduan mountains area and west Sichuan Plateau have larger temperature trend in magnitude than the other regions have. A downward trend was detected in Sichuan Basin also, but the region with cooler temperature was shrinking due to the statistically significant increasing trend of temper...
Spatial and temporal changes in daily temperature and rainfall indices are analyzed for the source r...
Using the 0.5° × 0.5° gridded Chinese ground precipitation dataset from 1961~2013, spa...
Using the 0.5° × 0.5° gridded Chinese ground precipitation dataset from 1961~2013, spa...
The present study focused on statistical analysis of interannual, interdecadal variations of climate...
for seasons during 1961−2007 were analyzed based on daily observations at 587 stations. The trends w...
Climate change is potentially challenging the sustainable development in many parts of the world, es...
Monthly temperature and precipitation time-series for the Zhujiang River Basin are analyzed in order...
The global climate warming accelerated in the 1980s has become a focus in the world. Based on the mo...
Monthly precipitation and temperature trends of 160 stations in China from 1951-2002 have been analy...
In this paper, robust statistical methods (including the climatic tendency ratio, inverse distance w...
[1] Daily and monthly maximum and minimum surface air temperatures at 66 weather stations over the e...
Global surface temperature has dramatically increased in the past decades. It is critical to evaluat...
In this paper, robust statistical methods (including the climatic tendency ratio, inverse distance w...
Temporal and spatial changes in the annual and seasonal temperatures in a typical basin of the Qiant...
With the purpose of further understanding the spatio-temporal changes in precipitation, temperature ...
Spatial and temporal changes in daily temperature and rainfall indices are analyzed for the source r...
Using the 0.5° × 0.5° gridded Chinese ground precipitation dataset from 1961~2013, spa...
Using the 0.5° × 0.5° gridded Chinese ground precipitation dataset from 1961~2013, spa...
The present study focused on statistical analysis of interannual, interdecadal variations of climate...
for seasons during 1961−2007 were analyzed based on daily observations at 587 stations. The trends w...
Climate change is potentially challenging the sustainable development in many parts of the world, es...
Monthly temperature and precipitation time-series for the Zhujiang River Basin are analyzed in order...
The global climate warming accelerated in the 1980s has become a focus in the world. Based on the mo...
Monthly precipitation and temperature trends of 160 stations in China from 1951-2002 have been analy...
In this paper, robust statistical methods (including the climatic tendency ratio, inverse distance w...
[1] Daily and monthly maximum and minimum surface air temperatures at 66 weather stations over the e...
Global surface temperature has dramatically increased in the past decades. It is critical to evaluat...
In this paper, robust statistical methods (including the climatic tendency ratio, inverse distance w...
Temporal and spatial changes in the annual and seasonal temperatures in a typical basin of the Qiant...
With the purpose of further understanding the spatio-temporal changes in precipitation, temperature ...
Spatial and temporal changes in daily temperature and rainfall indices are analyzed for the source r...
Using the 0.5° × 0.5° gridded Chinese ground precipitation dataset from 1961~2013, spa...
Using the 0.5° × 0.5° gridded Chinese ground precipitation dataset from 1961~2013, spa...