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| 香格里拉未来50a主要气候环境要素变化预估——基于小波分析和多元 VAR 回归预估模型 | |
| 引用本文： | 刘盈曦,彭贵芬,陈先刚,杨宇明.香格里拉未来50a主要气候环境要素变化预估——基于小波分析和多元 VAR 回归预估模型[J].资源科学,2016,38(9):1754-1767. |
| 作者姓名： | 刘盈曦 彭贵芬 陈先刚 杨宇明 |
| 作者单位： | 1. 云南财经大学,昆明 650221 2. 云南省气象台,昆明 650034 3. 西南林业大学环境科学与工程学院,昆明 650224 4. 云南省林业科学院,昆明 650201 |
| 基金项目： | 云南财经大学科学研究基金项目（YC2013D11）;国家自然科学基金项目（41165004）;NSFC-云南联合基金重点项目（U09336 |
| 摘 要： | 采用云南省香格里拉气象站55a（1958-2012）的逐年气温、降水量、绝对湿度、相对湿度和霜日数资料,引入多元最小二乘估计模型（多元OLS）、多元向量自回归模型（多元VAR）和结构方程模型,基于Morlet连续复小波（Cmor）变换的主周期数据,探索未来50a香格里拉气温等气候环境要素的定量预估模型、变化趋势及5个主要气候环境要素的相互关系。结果表明：未来50a内香格里拉的气温以0.44℃/10a的速率升高,50a后气温将升高2℃左右;降水以围绕平均值做周期振荡为主,并以14.7mm/10a的速率增多;绝对湿度以0.06 mg/L/10a的速率增大,并有明显的周期振荡;相对湿度以-0.96%/10a的速率减小,并有周期振荡;年霜日数以-2.8d/10a的速率减少,并有周期振荡。绝对湿度、相对湿度和霜日数的变化与气温和降水的变化显著相关,气温变化对湿度和霜日数的影响大于降水量的影响,气温的持续升高是除降水外其他气候要素变化的主要原因。 |
| 关 键 词： | 香格里拉 气候环境要素 气候变化 小波分析 多元VAR 耦合分析 |
| 收稿时间： | 2016-01-10 |
| 修稿时间： | 2016-06-05 |
Climatic and environmental changes in Shangri-La in next 50 years according to wavelet analysis and multiple VAR regression prediction modeling |
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| LIU Yingxi,PENG Guifen,CHEN Xiangang,YANG Yuming.Climatic and environmental changes in Shangri-La in next 50 years according to wavelet analysis and multiple VAR regression prediction modeling[J].Resources Science,2016,38(9):1754-1767. | |
| Authors: | LIU Yingxi PENG Guifen CHEN Xiangang YANG Yuming |
| Institution: | 1. School of Finance and Economics,Yunnan University of Finance and Economics,Kunming 650221,China 2. Yunnan Meteorological Observatory,Kunming 650034,China 3. School of Environmental Science and Engineering,Southwest Forestry University, Kunming 650224, China 4. Yunnan Academy of Forestry Kunming 650201,China |
| Abstract: | Using main cycle data transformed from Molet continuous complex wavelet （CMOR） we explored Shangri-La’s five main climatic and environmental factors'（yearly temperature,precipitation,absolute huidity,relative humidity and frost days）quantitative prediction models,variation trends and multiple relations based on multiple Ordinary Least Squares （OLS）model,multiple Vector Auto-regression （VAR）modeling and Structural Equation Model（SEM）. The raw data was from the Shangri-La meteorological station in Yunnan,China from 1958 to 2012. We conclude that in next 50 years,Shangri-La’s temperature will increase at a rate of 0.44 ℃/10a,it will rise about 2℃ after 50 years,reaching about 9℃. Shangri-La’s precipitation shows periodic oscillation around its mean value,increasing at a rate of 14.7mm/10a. Shangri-La’s absolute humidity will increase at a rate of 0.06 mg/L/10a with obvious periodic oscillation. Shangri-La’s relative humidity will decrease at a rate of -0.96 %/10a with periodic oscillation. Shangri-La’s yearly frosty days will decrease at a rate of -2.8 d/10a with periodic oscillation Shangri-La’s temperature,precipitation and frost days were dependent on temperature and precipitation;temperature’s effect is greater than precipitation’s;and a continuous increase in temperature is the main reason for changes in all other climatic factors,except precipitation. |
| Keywords: | Shangri-La climatic and environmental factors climate change wavelet analysis Multiple VAR coupling analysis |
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