Chao Gao

Prof. Dr. Chao Gao

Department of Geography & Spatial Information Techniques,Ningbo University
orcid

Research Focus & Metrics

Academic Career Length

22Years (2005-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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1 February 2010 in Journal of Climate
Verified
Journal Article
Open access
JZJianqing Zhai
Jianqing Zhai
BSBuda Su
Buda Su
VKValentina Krysanova
Valentina Krysanova
TVTobias Vetter
Tobias Vetter
Chao GaoChao Gao
Chao Gao
TJTong Jiang
Tong Jiang
Time series of the average annual Palmer drought severity index (PDSI) and standardized precipitation index (SPI) were calculated for 483 meteorological stations in China using monthly data from 1961 to 2005. The time series were analyzed for 10 large regions covering the territory of China and represented by seven river basins and three areas in the southeast, southwest, and northwest. Results show that the frequencies of both dry and wet years for the whole period are lower for southern basins than for the northern ones when estimated by PDSI but very similar for all basins when calculated by SPI. The frequencies of dry and wet years calculated for 5- and 15-yr subperiods by both indices show the upward dry trends for three northeastern basins, Songhuajiang, Liaohe, and Haihe; a downward dry trend for the northwest region; a downward wet trend for the Yellow River basin; and an upward wet trend for the northwest region. Trend detection using PDSI indicates statistically significant negative trends for many stations in the northeastern basins (Songhuajiang, Liaohe, Haihe, and Yellow) and in the middle part of the Yangtze, whereas statistically significant positive trends were found in the mountainous part of the northwest region and for some stations in the upper and lower Yangtze. A moderately high and statistically significant correlation between the percentage of runoff anomaly (PRA) and the annual average PDSI and SPI was found for six large rivers. The results confirm that PDSI and SPI indices can be used to describe the tendency of dryness and wetness severity and for comparison in climate impact assessment.

6 August 2019 in Nature Communications
Verified
Journal Article
Open access
PDF file
YWYanjun Wang
Yanjun Wang
AWAnqian Wang
Anqian Wang
JZJianqing Zhai
Jianqing Zhai
HTHui Tao
Hui Tao
TJTong Jiang
Tong Jiang
TFThomas Fischer
Thomas Fischer
The increase in surface air temperature in China has been faster than the global rate, and more high temperature spells are expected to occur in future. Here we assess the annual heat-related mortality in densely populated cities of China at 1.5 °C and 2.0 °C global warming. For this, the urban population is projected under five SSPs, and 31 GCM runs as well as temperature-mortality relation curves are applied. The annual heat-related mortality is projected to increase from 32.1 per million inhabitants annually in 1986–2005 to 48.8–67.1 per million for the 1.5 °C warming and to 59.2–81.3 per million for the 2.0 °C warming, taking improved adaptation capacity into account. Without improved adaptation capacity, heat-related mortality will increase even stronger. If all 831 million urban inhabitants in China are considered, the additional warming from 1.5 °C to 2 °C will lead to more than 27.9 thousand additional heat-related deaths, annually.

1 December 2020 in Sustainable Cities and Society
Verified
Journal Article
Closed access
YLYing Li
Ying Li
YSYanwei Sun
Yanwei Sun
JLJialin Li
Jialin Li
Chao GaoChao Gao
Chao Gao

1 July 2021 in Ecological Indicators
Verified
Journal Article
Open access
KZKaiyuan Zheng
Kaiyuan Zheng
LTLinshan Tan
Linshan Tan
YSYanwei Sun
Yanwei Sun
YWYanjuan Wu
Yanjuan Wu
ZDZheng Duan
Zheng Duan
Chao GaoChao Gao
Chao Gao

15 November 2016 in Climatic Change
Verified
Journal Article
Closed access
PDF file
BSBuda Su
Buda Su
JHJinlong Huang
Jinlong Huang
XZXiaofan Zeng
Xiaofan Zeng
Chao GaoChao Gao
Chao Gao
TJTong Jiang
Tong Jiang

31 October 2016 in Climatic Change
Verified
Journal Article
Closed access
PDF file
SHShaochun Huang
Shaochun Huang
Rohini KumarRohini Kumar
Rohini Kumar
MFMartina Flörke
Martina Flörke
TYTao Yang
Tao Yang
YHYeshewatesfa Hundecha
Yeshewatesfa Hundecha
VKValentina Krysanova
Valentina Krysanova