| 1960-2011年云南省极端气温事件的时空分布及趋势预测 |
| |
| 引用本文： | 王晓,李佳秀,石红彦,王纪伟,梁贻仓.1960-2011年云南省极端气温事件的时空分布及趋势预测[J].资源科学,2014,36(9):1816-1824. |
| |
| 作者姓名： | 王晓 李佳秀 石红彦 王纪伟 梁贻仓 |
| |
| 作者单位： | 四川民族学院, 康定 626001;新疆大学资源与环境科学学院, 乌鲁木齐 830046;西北大学城市与环境学院, 西安 710127;西北大学城市与环境学院, 西安 710127;西北大学城市与环境学院, 西安 710127 |
| |
| 基金项目： | 西北大学研究生自主创新基金项目：“陕西省生态系统服务功能及其变化研究”（编号：YZZ12005）。 |
| |
| 摘 要： | 基于云南省1960-2011年最低气温和最高气温的日数据，选取了31个气象站点，依据世界气象组织（WMO）确定的“气候变化检测和指标”，从中选取8个极端气温指数，采用反距离加权插值法、Mann-Kendall突变检验法、周期方差分析外推法、叠加趋势模型，来研究云南省极端气温事件的时空变化特征、突变检验、周期变化及对未来一个周期内变化趋势的预测。结果表明：冷昼日数、冷夜日数、冷持续日数、霜冻日数均表现为下降的变化趋势，暖昼日数、暖夜日数、暖持续日数、夏季日数均表现为上升的变化趋势，各指数空间分布各异，总体上表明云南省极端气温事件呈上升趋势。各指数发生突变的时间和周期不同，预测结果呈波动变化且与原趋势一致。
|
| 关 键 词： | 极端气温指数 周期方差分析 变化趋势 云南 |
The Temporal-Spatial Distribution and Prediction of Extreme Temperature Events in Yunnan Province from 1960 to 2011 |
| |
| WANG Xiao,LI Jiaxiu,SHI Hongyan,WANG Jiwei and LIANG Yicang.The Temporal-Spatial Distribution and Prediction of Extreme Temperature Events in Yunnan Province from 1960 to 2011[J].Resources Science,2014,36(9):1816-1824. |
| |
| Authors: | WANG Xiao LI Jiaxiu SHI Hongyan WANG Jiwei and LIANG Yicang |
| |
| Institution: | Sichuan University for Nationalities, Kangding 626001, China;School of Resources and Environmental Sciences, Xinjiang University, Urumqi 830046, China;College of Urban and Environmental Sciences, Northwest University, Xi'an 710127, China;College of Urban and Environmental Sciences, Northwest University, Xi'an 710127, China;College of Urban and Environmental Sciences, Northwest University, Xi'an 710127, China |
| |
| Abstract: | Yunnan is located in southwest China, has various climates, and temperatures in this province have recently increased significantly. Extreme temperature events in Yunnan are of great importance to preventing natural disasters. Here we examine data from 1960 to 2011 regarding daily maximum and minimum temperature across 31 observational stations. We selected eight indices of extreme temperature from the Expert Team on Climate Change Detection and Indices (WMO) and looked at the characteristics of extreme temperature events, including temporal-spatial distribution, breakpoint test, periodic change and trends prediction using Inverse Distance Weighted interpolation methods, Mann-Kendall abrupt change test, variance analysis extrapolation method and superposition trend modeling. We found that cold indices(cool days, cool nights, cold spell duration indicator and frost days)have been decreasing and the tendency rates are -0.36, -1.73, -0.61 and -1.91d/10a, respectively. Warm indices(warm days, warm nights, warm spell duration indicator and summer days)are increasing with tendency rates of 2.11, 3.83, 3.65 and 3.89 d/10a, respectively. Spatial analysis showed that the trend in cold indices is increasing gradually from east to west and south to north, and the trend in warm indices is increasing gradually from northeast to southwest. The warm nights index, cold spell duration indicator, warm spell duration indicator, cool nights, cool days, warm days, frost days and summer days breakpoints were in 1966, 1997, 1987, 1997, 2002, 1989 and 2002, respectively, and a main period of 15, 11, 7, 15, 5, 3 and 3 years, respectively. Simulation results show that each index has a fluctuant trend and is consistent with the original sequence. |
| |
| Keywords: | extreme temperature indices variance analysis extrapolation method change trends Yunnan |
|
| 点击此处可从《资源科学》浏览原始摘要信息 |
| 点击此处可从《资源科学》下载免费的PDF全文 |
|
