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大熊猫分布区近半个世纪逐日气温空间插值分析

臧振华 肖倩茹 杨旭煜 古晓东 张公华 董向忠 申国珍 李俊清

臧振华, 肖倩茹, 杨旭煜, 古晓东, 张公华, 董向忠, 申国珍, 李俊清. 大熊猫分布区近半个世纪逐日气温空间插值分析[J]. 北京林业大学学报, 2018, 40(4): 76-85. doi: 10.13332/j.1000-1522.20180041
引用本文: 臧振华, 肖倩茹, 杨旭煜, 古晓东, 张公华, 董向忠, 申国珍, 李俊清. 大熊猫分布区近半个世纪逐日气温空间插值分析[J]. 北京林业大学学报, 2018, 40(4): 76-85. doi: 10.13332/j.1000-1522.20180041
Zang Zhenhua, Xiao Qianru, Yang Xuyu, Gu Xiaodong, Zhang Gonghua, Dong Xiangzhong, Shen Guozhen, Li junqing. Spatial interpolation analysis on daily temperatures in the distribution range of giant panda over the past half century[J]. Journal of Beijing Forestry University, 2018, 40(4): 76-85. doi: 10.13332/j.1000-1522.20180041
Citation: Zang Zhenhua, Xiao Qianru, Yang Xuyu, Gu Xiaodong, Zhang Gonghua, Dong Xiangzhong, Shen Guozhen, Li junqing. Spatial interpolation analysis on daily temperatures in the distribution range of giant panda over the past half century[J]. Journal of Beijing Forestry University, 2018, 40(4): 76-85. doi: 10.13332/j.1000-1522.20180041

大熊猫分布区近半个世纪逐日气温空间插值分析

doi: 10.13332/j.1000-1522.20180041
基金项目: 

国家自然科学基金项目 31170500

国家重点研发计划项目 2016YFC050330304

国家重点研发计划项目 2016YFC0503100

详细信息
    作者简介:

    臧振华,博士生。主要研究方向:气候变化背景下的生物多样性保护。Email: zhenhuast@126.com 地址:100083北京市海淀区清华东路35号北京林业大学林学院

    责任作者:

    李俊清,博士,教授,博士生导师。主要研究方向:生物多样性保护、恢复生态学。Email: lijq@bjfu.edu.cn 地址:同上

  • 中图分类号: S759.94;Q958.112+6

Spatial interpolation analysis on daily temperatures in the distribution range of giant panda over the past half century

  • 摘要: 目的高时空分辨率的气温分布是准确模拟物种适宜分布区的基础。大熊猫分布区是全球35个生物多样性热点区之一,属于典型山地地形。方法为了有效消除海拔效应在气温空间插值中的误差,本研究基于线性递减率调整法(linear lapse rate adjustment, LLRA)对大熊猫分布区42个气象站点1960—2010年的日最高气温(daily maximum temperature,dTmax)、日最低气温(daily minimum temperature,dTmin)和日平均气温(daily mean temperature,dTmean)进行了空间插值,评估了LLRA插值法的准确度,并分析了近半个世纪大熊猫分布区气候变暖的格局。结果结果表明,使用LLRA法校正误差的局域递减率插值,准确度明显高于全球平均递减率和初步局域递减率;大熊猫分布区将近90%的区域dTmax、dTmin和dTmean同时显著上升,上升最快的地区主要集中在秦岭和岷山西北部;dTmax、dTmin和dTmean显著上升的中位速度分别为每100年上升1.68、2.32和1.77 ℃,超过3/4的区域dTmin上升速度大于dTmax;在气象站点代表的低于3 500 m的海拔范围内,dTmin和dTmean的变化速度随海拔上升表现出显著增加趋势,且dTmin的上升趋势大于dTmean结论本研究证明了LLRA法能有效消除海拔效应在气温空间插值时造成的误差,提高山地气温空间插值的准确度。研究发现,大熊猫分布区近半个世纪经历了显著变暖,由LLRA插值获得的逐日气温分布图可为进一步评估变暖对大熊猫分布区珍稀濒危物种的分布影响、制定相应的保护规划提供基础。

     

  • 图  1  大熊猫分布区气象站点地理位置示意图

    图中展示了大熊猫分布区六大山系的位置,以及42个气象站点的位置。

    Figure  1.  Map of the meteorological stations throughout the distribution range of giant panda

    The figure shows the geographic location of the six mountains in the distribution range of giant panda, and the 42 meteorological stations throughout the distribution range of giant panda.

    图  2  大熊猫分布区1960—2010年多年年均温度的空间分布

    插入的柱状图代表各温度范围的栅格数占大熊猫分布区总栅格数的比例,柱状图上列出了大熊猫分布区的区域多年年均温度。

    Figure  2.  Distribution of multiyear annual average temperatures during 1960-2010

    Inset histograms represent the proportion of pixels within each temperature range to the total pixels of the distribution range of giant panda. The regional multiyear annual average temperature is provided at the top of each histogram.

    图  3  大熊猫分布区1960—2010年逐日温度变化速度的空间分布

    插入的柱状图代表各变化速度范围的栅格数占大熊猫分布区总栅格数的比例,柱状图上列出了大熊猫分布区的区域逐日气温的变化速度。

    Figure  3.  Distribution of change rate of daily temperatures in the distribution range of giant panda during 1960-2010

    Inset histograms represent the proportion of pixels within each range of change rate of daily temperatures to the total pixels of the distribution range of giant panda. The regional change rate of daily temperatures is provided at the top of each histogram.

    图  4  大熊猫分布区逐日温度变化速度与海拔的关系

    左边的圆点反映低于3 500 m的海拔,该海拔范围是气象站能代表的海拔范围;右边的三角形反映高于3 500 m的海拔范围,大熊猫分布区仅有1个站点海拔高于3 500 m。图中给出了逐日气温变化速度和海拔之间的线性回归拟合线,实线表明回归至少在0.05的水平上显著,虚线表明回归不显著。

    Figure  4.  Relationships between the change rate of daily temperatures and elevation in the distribution range of giant panda

    The left dots show the elevations lower than 3 500 m, which can be represented by the meteorological stations; the right triangles show the elevations higher than 3 500 m, and only one meteorological station is at the elevations higher than 3 500 m throughout the distribution range of giant panda. The fitted line of simple linear regression between the change rate of daily temperatures and elevations is shown in the figure. The solid line shows that the regression is significant at least at P < 0.05 level, and the dashed line shows that the regression is not significant.

    表  1  全球平均递减率(λmean)、初步局域递减率(λunadj)和校正误差的局域递减率(λadj)在大熊猫分布区1960—2010年的插值准确度评估

    Table  1.   Estimation in interpolation accuracy of global mean lapse rate (λmean), unadjusted local lapse rate (λunadj) and adjusted local lapse rate (λadj) for the distribution range of giant panda during 1960-2010

    项目
    Item
    月份
    Month
    平均绝对误差Mean absolute error/℃ 均方根误差Root mean squared error/℃
    λmean λunadj λadj λmean λunadj λadj
    月均最高温
    Monthly average maximum temperature, mTmax
    1 2.31 1.88 1.48 3.14 2.60 2.16
    2 2.16 2.06 1.56 3.04 2.83 2.31
    3 1.87 1.93 1.48 2.71 2.67 2.17
    4 1.64 1.68 1.41 2.35 2.37 1.99
    5 1.53 1.52 1.34 2.14 2.15 1.88
    6 1.35 1.35 1.23 1.97 1.77 1.68
    7 1.24 1.12 0.99 1.78 1.56 1.44
    8 1.25 1.14 0.99 1.82 1.63 1.49
    9 1.48 1.33 1.10 2.12 1.86 1.60
    10 1.76 1.52 1.32 2.46 2.16 1.85
    11 1.94 1.65 1.39 2.65 2.26 1.90
    12 2.28 1.66 1.35 3.03 2.26 1.87
    月均最低温
    Monthly average minimum temperature, mTmin
    1 1.57 1.48 1.46 1.92 1.90 1.83
    2 1.46 1.43 1.35 1.84 1.87 1.74
    3 1.32 1.28 1.14 1.66 1.68 1.50
    4 1.19 1.09 0.98 1.47 1.41 1.27
    5 1.06 0.98 0.85 1.32 1.22 1.10
    6 0.99 0.82 0.77 1.29 1.01 0.96
    7 0.95 0.66 0.67 1.27 0.84 0.84
    8 0.98 0.71 0.71 1.30 0.91 0.91
    9 1.07 0.83 0.77 1.43 1.07 1.00
    10 1.05 1.00 0.87 1.38 1.25 1.12
    11 1.20 1.16 1.08 1.45 1.43 1.32
    12 1.46 1.30 1.29 1.73 1.64 1.60
    月均温
    Monthly average temperature, mTmean
    1 1.73 1.51 1.31 2.20 2.02 1.79
    2 1.67 1.61 1.34 2.22 2.22 1.89
    3 1.53 1.49 1.24 2.05 2.09 1.75
    4 1.36 1.25 1.11 1.77 1.76 1.52
    5 1.21 1.10 1.00 1.59 1.53 1.35
    6 1.06 0.93 0.85 1.47 1.19 1.14
    7 1.01 0.71 0.67 1.36 0.97 0.94
    8 1.00 0.75 0.71 1.37 1.04 0.99
    9 1.19 0.94 0.82 1.61 1.28 1.13
    10 1.30 1.10 0.94 1.71 1.50 1.29
    11 1.39 1.20 1.04 1.74 1.59 1.37
    12 1.64 1.31 1.15 2.02 1.69 1.51
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  • 收稿日期:  2018-01-30
  • 修回日期:  2018-03-06
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