1 新疆师范大学地理科学与旅游学院，新疆 乌鲁木齐 830054；
2 新疆师范大学新疆干旱区湖泊环境与资源重点实验室，新疆 乌鲁木齐 830054； 3 新疆师范大学实验室与设备管理处，新疆 乌鲁木齐 830054
收稿日期: 2019-05-05
修回日期: 2019-11-26
网络出版日期: 2020-05-25
基金资助
塔里木河中下游胡杨林更新复壮关键技术研究（HY-2.3）资助
Variation characteristics of extreme temperature events in Bayingolin Mongol Autonomous Prefecture,Xinjiang in recent 58 years
1 College of Geographical Science and Tourism,Xinjiang Normal University,Urumqi 830054,Xinjiang,China；
2 Xinjiang Key Laboratory for Lacustrine Environment and Resources in Arid Area,Xinjiang Normal University,Urumqi 830054, Xinjiang,China； 3 Laboratory and Equipment Management Office of Xinjiang Normal University,Urumqi,China,Xinjiang 830054
Received date: 2019-05-05
Revised date: 2019-11-26
Online published: 2020-05-25
赵明玉, 武胜利, 任耀军, 吕婷, 李京龙
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近58 a新疆巴州极端气温事件变化特征[J]. 干旱区地理, 2020
The Bayingolin Mongol Autonomous Prefecture (BMAP) is an arid and ecologically fragile zone located in the southeastern part of the Xinjiang Uygur Autonomous Region,China.It is sensitive to temperature change and exhibits specific indicators of such change.Previous studies have found that global warming has intensified the occurrence of extreme weather in the region.Extreme weather events,especially extreme temperatures,have high frequency,high intensity and long duration,and threaten food security,water security and energy security.They thus have critical importance for society.Exploring the characteristics and patterns of regional extreme temperature forms the basis for predicting such events.Existing research on extreme climate change focuses on spatial and temporal laws at different scales,but the selection of index standards is different between studies.It is also crucial to note that spatial and temporal laws are inseparable from the complex dynamics of extreme temperature events.There are few studies on extreme temperature events in BMAP.In order to increase the sustainability of the region,we have analyzed periods of extreme temperature change to provide plans for the mitigation of extreme temperatures in terms of the localscale layout of agriculture in the region.Based on daily maximum and minimum temperature data observed at 7 meteorological stations in the BMAP from 1959 to 2016,combined with current measurements,15 extreme temperature indexes recommended by WMO were selected and calculated using RClimDex(1.0) software.Extreme temperature events in the study area were analyzed using a variety of statistical methods,such as unitary linear regression,anomalies,the Mann-Kendall method,sliding T test,wavelet analysis,principal component analysis,and inverse distance weighted interpolation,among others.The results were tested for their significance.The results show that,during the last 58 years,changes of cold and warm indexes in BMAP are asymmetric: the warm index shows a significant upward trend,while the cold index shows a significant downward trend.The corresponding change rates of night index (TN10P,TN90P) and day index (TX10P,TX90P) are greater in the former than in the latter.The cold index mutated in the mid-late 1980s and 1990s,while the warm index,GSL,and WSDI mutated in the mid-late 1990s.The cold index is more sensitive to climate change.The frequency of occurrence of extreme high temperature increased while the frequency of extreme low temperature decreased.The duration of the growth period of crops showed a significant increasing trend.TNx,TXx, and GSL have a main cycle of 28 years.High load index,TEM-A (0.335),TN10P (-0.313),and TN90P (0.312) are the main factors affecting overall temperature changes in the region.Since China has a vast territory,and diverse geographical and human factors,extreme temperature changes affect the country in complex ways,and different measures are required for different regions.The study of regional extreme temperature events can increase the theoretical understanding of their occurrence,benefit the mitigation of extreme temperatures in certain regions,and improve agricultural production,ecological environment,and the economy.This can provide a scientific basis for regional sustainable development.
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