Trends in extreme temperature indices in Huang-Huai-Hai River Basin of China during 1961–2014

2017 ◽  
Vol 134 (1-2) ◽  
pp. 51-65 ◽  
Author(s):  
Gang Wang ◽  
Denghua Yan ◽  
Xiaoyan He ◽  
Shaohua Liu ◽  
Cheng Zhang ◽  
...  
Keyword(s):  
River Basin ◽  
Extreme Temperature ◽  
Temperature Indices

scholarly journals Projecting Changes in Temperature Extremes in the Han River Basin of China Using Downscaled CMIP5 Multi-Model Ensembles

Atmosphere ◽  
2020 ◽  
Vol 11 (4) ◽  
pp. 424
Author(s):  
Weiwei Xiao ◽  
Bin Wang ◽  
De Li Liu ◽  
Puyu Feng
Keyword(s):  
Climate Change ◽  
River Basin ◽  
Extreme Temperature ◽  
Future Climate ◽  
Extreme Weather Events ◽  
Future Climate Change ◽  
Han River ◽  
Han River Basin ◽  
Temperature Indices ◽  
Extreme Indices

Estimating the changes in the spatial–temporal characteristics of extreme temperature events under future climate scenarios is critical to provide reference information to help mitigate climate change. In this study, we analyzed 16 extreme temperature indices calculated based on downscaled data from 28 Global Climate Models (GCMs) that were obtained from Coupled Model Intercomparison Project Phase 5 (CMIP5) under Representative Concentration Pathway (RCP) 4.5 and 8.5 scenarios in the Han River Basin (HRB). The results indicate that the downscaled data from 28 GCMs reproduced a consistent sign of recent trends for all extreme temperature indices except the DTR for the historical period (1961–2013). We found significantly increasing trends for the warm extreme indices (i.e., TXx, TNx, TX90p, TN90p, SU, TR, and WSDI) and considerably decreasing trends for the cold extreme indices (i.e., TX10p, TN10p, CSDI, FD, ID) under both the RCP4.5 and 8.5 scenarios for 2021–2100. Spatially, great changes in warm extremes will occur in the west and southeast of the HRB in the future. The projected changes in extreme temperatures will impact the eco-environment and agricultural production. Our findings will help regional managers adopt countermeasures and strategies to adapt to future climate change, especially extreme weather events.

scholarly journals Assessment on Temporal and Spatial Variation Analysis of Extreme Temperature Indices: A Case Study of the Yangtze River Basin

2021 ◽  
Vol 18 (20) ◽  
pp. 10936
Author(s):  
Guangxun Shi ◽  
Peng Ye
Keyword(s):  
Economic Development ◽  
River Basin ◽  
Yangtze River ◽  
Yangtze River Basin ◽  
Extreme Temperature ◽  
The Yangtze River ◽  
Social And Economic Development ◽  
Present Trend ◽  
The Yangtze River Basin ◽  
Temperature Indices

Extreme temperature change is one of the most urgent challenges facing our society. In recent years, extreme temperature has exerted a considerable influence on society and the global ecosystem. The Yangtze River Basin is not only an important growth belt of China’s social and economic development, but also the main commodity grain base in China. The purpose of this study is to study the extreme temperature indices in the Yangtze River Basin. In this study, the Mann–Kendall nonparametric test and R/S analysis method are used to analyze the spatial and temporal variation characteristics of major extreme temperature indices in the Yangtze River Basin from 1970 to 2014. The main conclusions are drawn as follows: (1) The occurrence of cold days (TX10), cold nights (TN10), ice days (ID), and frost days (FD) decrease at a rate of −0.66–−2.5 d/10a, respectively, while the occurrence of warm days (TX90), warm nights (TN90), summer days (SU), and tropical nights (TR) show statistically significant increasing trends at a rate of 2.2–4.73 d/10a. (2) The trends of the coldest day (TXn), coldest night (TNn), warmest day (TXx), warmest night (TNx), and diurnal temperature range (DTR), range from −0.003 to 0.5 °C/10a. (3) Spatially, the main cold indices and warm indices increase and decrease the most in the upper and lower reaches of the Yangtze River Basin. (4) DTR and TN90 show no abrupt changes; the main cold indices changed abruptly in the 1980s and the main warm indices changed abruptly in the late 1990s and early 2000s. (5) The extreme temperature indices are affected by the atmospheric circulation and urban heat island effect in the Yangtze River Basin. Relative indices and absolute indices will continue to maintain the present trend in the future. In short, the main cold indices of extreme temperature indices show a decreasing trend, the main warm indices of extreme temperature indices show an increasing trend, and cold indices and warm indices will continue to maintain the present trend in the future in the Yangtze River Basin. Extreme temperature has an important impact on agriculture, social, and economic development. Therefore, extreme temperature prediction and monitoring must be strengthened to reduce losses caused by extreme temperature disasters and to promote the sustainable development in Yangtze River Basin.

scholarly journals Change in mean and extreme temperature at Yingkou station in Northeast China from 1904 to 2017

2021 ◽  
Vol 164 (3-4) ◽  
Author(s):  
Xiaoying Xue ◽  
Guoyu Ren ◽  
Xiubao Sun ◽  
Panfeng Zhang ◽  
Yuyu Ren ◽  
...  
Keyword(s):  
Northeast China ◽  
Extreme Temperature ◽  
Maximum Temperature ◽  
Data Set ◽  
The Past ◽  
Significant Downward Trend ◽  
Cold Events ◽  
Temperature Indices ◽  
Increasing Trends ◽  
Change In Mean

AbstractThe understanding of centennial trends of extreme temperature has been impeded due to the lack of early-year observations. In this paper, we collect and digitize the daily temperature data set of Northeast China Yingkou meteorological station since 1904. After quality control and homogenization, we analyze the changes of mean and extreme temperature in the past 114 years. The results show that mean temperature (Tmean), maximum temperature (Tmax), and minimum temperature (Tmin) all have increasing trends during 1904–2017. The increase of Tmin is the most obvious with the rate of 0.34 °C/decade. The most significant warming occurs in spring and winter with the rate of Tmean reaching 0.32 °C/decade and 0.31 °C/decade, respectively. Most of the extreme temperature indices as defined using absolute and relative thresholds of Tmax and Tmin also show significant changes, with cold events witnessing a more significant downward trend. The change is similar to that reported for global land and China for the past six decades. It is also found that the extreme highest temperature (1958) and lowest temperature (1920) records all occurred in the first half of the whole period, and the change of extreme temperature indices before 1950 is different from that of the recent decades, in particular for diurnal temperature range (DTR), which shows an opposite trend in the two time periods.

scholarly journals Temporal Trends and Spatial Patterns of Temperature and Its Extremes over the Beijing-Tianjin Sand Source Region (1960–2014), China

2018 ◽  
Vol 2018 ◽  
pp. 1-26
Author(s):  
Wei Wei ◽  
Baitian Wang ◽  
Kebin Zhang ◽  
Zhongjie Shi ◽  
Genbatu Ge ◽  
...  
Keyword(s):  
Source Region ◽  
Temporal Trends ◽  
Extreme Temperature ◽  
Spatiotemporal Variability ◽  
Mountain Area ◽  
Increasing Trend ◽  
Cold Tolerant ◽  
Temperature Indices ◽  
Slope Estimator ◽  
Sand Source

In order to examine temperature changes and extremes in the Beijing-Tianjin Sand Source Region (BTSSR), ten extreme temperature indices were selected, categorized, and calculated spanning the period 1960–2014, and the spatiotemporal variability and trends of temperature and extremes on multitimescales in the BTSSR were investigated using the Mann-Kendall (M-K) test, Sen’s slope estimator, and linear regression. Results show that mean temperatures have increased and extreme temperature events have become more frequent. Annual temperature has recorded a significant increasing trend over the BTSSR, in which 51 stations exhibited significant increasing trends (p<0.05); winter temperature recorded the most significant increasing trend in the northwest subregion. All extreme temperature indices showed warming trends at most stations; a higher warming slope in extreme temperature mainly occurred along the northeast border and northwest border and in the central-southern mountain area. As extreme low temperature events decrease, vegetation damage due to freezing temperatures will reduce and low cold-tolerant plants may expand their distribution range northward to revegetate barren areas in the BTSSR. However, in water-limited areas of the BTSSR, increasing temperatures in the growing season may exacerbate stress associated with plants relying on precipitation due to higher temperatures combining with decreasing precipitation.

scholarly journals Effects of Urbanization on Regional Extreme-Temperature Changes in China, 1960–2016

2020 ◽  
Vol 12 (16) ◽  
pp. 6560 ◽  
Author(s):  
Junliang Qiu ◽  
Xiankun Yang ◽  
Bowen Cao ◽  
Zhilong Chen ◽  
Yuxuan Li
Keyword(s):  
Northeast China ◽  
Urban Climate ◽  
Extreme Temperature ◽  
Maximum Temperature ◽  
Temperature Changes ◽  
Low Latitudes ◽  
Different Seasons ◽  
Extreme Minimum Temperature ◽  
Temperature Indices ◽  
Urbanization In China

Urbanization in China has been expanding dramatically since 1978, significantly affecting the extreme temperature changes in cities, which is a vital indicator of urban climate change. To assess urban-related effect on regional extreme-temperature changes in China, this study employed high-resolution land use data to divide meteorological stations into rural stations, suburban stations, and urban stations, and evaluated the annual and seasonal changes in extreme minimum temperature (TNN), mean temperature (Tavg) and extreme maximum temperature (TXX) at each meteorological station. The result revealed that extreme temperature indices (TNN, TXX) and Tavg increased significantly from 1960 to 2016 with varied degrees in different seasons and different regions. Extreme temperature indices in high latitudes increased more rapidly than in low latitudes; while the trends in summer are slower than in other seasons. Urbanization effects on the trends of TNN, Tavg and TXX were all statistically significant, but urbanization effects on TNN and Tavg were more significant than TXX. The urbanization effects were more significant in low altitudes, especially in North, South, Northwest and Northeast China. In North, Northwest and Northeast China, the urban-related effects on temperature increase were mainly observed in spring and winter, but in South China, the urban-related effects were more evident in summer. This study is valuable for sustainable urban planning in China.

scholarly journals Near-term prediction of impact-relevant extreme temperature indices

2014 ◽  
Vol 132 (1) ◽  
pp. 61-76 ◽  
Author(s):  
H. M. Hanlon ◽  
G. C. Hegerl ◽  
S. F. B. Tett ◽  
D. M. Smith
Keyword(s):  
Extreme Temperature ◽  
Term Prediction ◽  
Temperature Indices ◽  
Near Term

Extreme Precipitation and Temperature over the U.S. Pacific Northwest: A Comparison between Observations, Reanalysis Data, and Regional Models*

2011 ◽  
Vol 24 (7) ◽  
pp. 1950-1964 ◽  
Author(s):  
Valérie Dulière ◽  
Yongxin Zhang ◽  
Eric P. Salathé
Keyword(s):  
Pacific Northwest ◽  
Extreme Precipitation ◽  
Global Climate Model ◽  
Extreme Temperature ◽  
Reanalysis Data ◽  
Grid Spacing ◽  
Regional Models ◽  
Temperature Indices ◽  
The U.S ◽  
Precipitation And Temperature

Abstract Extreme precipitation and temperature indices in reanalysis data and regional climate models are compared to station observations. The regional models represent most indices of extreme temperature well. For extreme precipitation, finer grid spacing considerably improves the match to observations. Three regional models, the Weather Research and Forecasting (WRF) at 12- and 36-km grid spacing and the Hadley Centre Regional Model (HadRM) at 25-km grid spacing, are forced with global reanalysis fields over the U.S. Pacific Northwest during 2003–07. The reanalysis data represent the timing of rain-bearing storms over the Pacific Northwest well; however, the reanalysis has the worst performance at simulating both extreme precipitation indices and extreme temperature indices when compared to the WRF and HadRM simulations. These results suggest that the reanalysis data and, by extension, global climate model simulations are not sufficient for examining local extreme precipitations and temperatures owing to their coarse resolutions. Nevertheless, the large-scale forcing is adequately represented by the reanalysis so that regional models may simulate the terrain interactions and mesoscale processes that generate the observed local extremes and frequencies of extreme temperature and precipitation.

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