高级检索

留言板

尊敬的读者、作者、审稿人, 关于本刊的投稿、审稿、编辑和出版的任何问题, 您可以本页添加留言。我们将尽快给您答复。谢谢您的支持!

姓名
邮箱
手机号码
标题
留言内容
验证码

1961~2020年中国两大林区森林火险天气的多尺度特征

王文杰 钱诚 张宇 封小凡 张嘉仪

王文杰, 钱诚, 张宇, 等. 2022. 1961~2020年中国两大林区森林火险天气的多尺度特征[J]. 气候与环境研究, 27(5): 559−577 doi: 10.3878/j.issn.1006-9585.2021.21097
引用本文: 王文杰, 钱诚, 张宇, 等. 2022. 1961~2020年中国两大林区森林火险天气的多尺度特征[J]. 气候与环境研究, 27(5): 559−577 doi: 10.3878/j.issn.1006-9585.2021.21097
WANG Wenjie, QIAN Cheng, ZHANG Yu, et al. 2022. Multi-time Scale Features of Fire Weather in Two Major Forests in China during 1961–2020 [J]. Climatic and Environmental Research (in Chinese), 27 (5): 559−577 doi: 10.3878/j.issn.1006-9585.2021.21097
Citation: WANG Wenjie, QIAN Cheng, ZHANG Yu, et al. 2022. Multi-time Scale Features of Fire Weather in Two Major Forests in China during 1961–2020 [J]. Climatic and Environmental Research (in Chinese), 27 (5): 559−577 doi: 10.3878/j.issn.1006-9585.2021.21097

1961~2020年中国两大林区森林火险天气的多尺度特征

doi: 10.3878/j.issn.1006-9585.2021.21097
基金项目: 国家重点研发计划项目2018YFC1507701
详细信息
    作者简介:

    王文杰,男,1997年出生,硕士研究生,主要从事极端天气气候事件研究。E-mail: 1123684030@qq.com

    通讯作者:

    钱诚,E-mail: qianch@tea.ac.cn

  • Fosberg M A. 1978. Weather in wildland fire management: The fire weather index [C]. Proceedings of the Conference on Sierra Nevada Meteorology, South Lake Tahoe, NV: 1–4.
  • 中图分类号: P467

Multi-time Scale Features of Fire Weather in Two Major Forests in China during 1961–2020

Funds: National Key Research and Development Program of China (Grant 2018YFC1507701)
  • 摘要: 近年来,世界各地的极端林火事件已呈现出多发态势。林火作为一种复合型极端事件,它的发生和蔓延与气象条件有着密切联系,在全球变暖的背景下,研究林区森林火险天气的变化特征可以为“碳中和”背景下的森林防火工作提供科学的信息。本文以逐日森林火险气象指数(FFDI)作为火险天气的度量指标,分析了该指数的适用性及空间分布特征,进而分析了1961~2020年东北和西南两大林区FFDI及相关气象因子的线性变化趋势;最后利用集合经验模分解(EEMD)的方法揭示了两大林区防火期FFDI的多时间尺度演变特征。研究发现:在季节以及年时间尺度上,FFDI的分布具有明显的区域特征,东北地区在春季、秋季处于高值期,而西南地区则集中在春季和冬季,这与两大林区的森林防火期有很好的对应关系。各个季节FFDI呈现显著增长的站点数在10%~20%左右,春季最多(21%)。东北林区FFDI的变化趋势在四季都不显著;但相关气象因子中的日最高气温在四季都呈现显著的变暖趋势,平均风速在四季都呈现显著减弱的趋势。西南林区四季的FFDI都呈现显著(至少是0.1水平下的)增长态势,其中春、冬季防火期的趋势分别为0.09/10 a(P<0.1)和0.05/10 a(P<0.1);夏、秋、冬三个季节显著变暖又显著变干(P<0.05),朝着 “暖干化”的气候特征演变。年际变率在两大林区FFDI的演变中贡献超70%;东北春季和秋季防火期FFDI的非线性趋势分别呈先快速上升后减缓和先快速上升后转为下降的趋势;西南春季防火期FFDI的非线性趋势从上个世纪的稳定少变转为21世纪开始呈现快速上升的趋势,冬季防火期FFDI则总体呈稳步上升趋势。因此,西南林区的防火形势正变得愈发地严峻。
    1)  Fosberg M A. 1978. Weather in wildland fire management: The fire weather index [C]. Proceedings of the Conference on Sierra Nevada Meteorology, South Lake Tahoe, NV: 1–4.
  • 图  1  站点分布及两大林区(黑色方框)示意图

    Figure  1.  Spatial distribution of 552 meteorological stations selected and the northeastern and southwestern forest regions analyzed (black rectangles)

    图  2  2005~2018年两大林区(a)1~12月森林火灾发生次数百分比和(b)森林火险气象指数(FFDI)逐月多年平均值、(c)东北林区和(d)西南林区FFDI与森林火灾发生次数的相关关系

    Figure  2.  (a) Ratio of forest fire occurrences from Jan to Dec and (b) multiyear average of the monthly forest fire danger index (FFDI) in the two major forest regions and the corresponding correlation between FFDI and the number of forest fire occurrences in the (c) northeastern forests and (d) southwestern forests during 2005–2018

    图  3  1981~2010年气候平均的森林火险气象指数火险等级:(a)春季;(b)夏季;(c)秋季;(d)冬季;(e)年平均

    Figure  3.  Spatial distributions of the category of climatological FFDI during 1981–2020: (a) Spring; (b) summer; (c) autumn; (d) winter; (e) annual average

    图  4  1961~2020年森林火险气象指数的变化趋势:(a)春季;(b)夏季;(c)秋季;(d)冬季;(e)年平均。实心三角形表示站点趋势在0.05水平下统计显著,空心三角形则表示站点在统计意义上并不显著。呈显著增长趋势的站点数所占百分比也列在图中

    Figure  4.  Spatial distributions of the linear trends in FFDI at 552 stations during 1961–2020: (a) Spring, (b) summer, (c) autumn, (d) winter, and (e) annual average. Solid triangles indicate that the linear trends are significant at a 5% confidence level, whereas hollow triangles indicate that the linear trends are not statistically significant. The percentages of stations whose trends are dominant in sign and statistically significant are also listed

    图  5  1961~2020年东北林区(a)春季、(b)秋季和西南林区(c)春季、(d)冬季防火期森林火险气象指数的时间序列(实线)以及对应的线性趋势(虚线)

    Figure  5.  Time series (solid lines) of FFDI in the northeastern forest region in (a) spring and (b) autumn and southwestern forest region in (c) spring and (d) winter during 1961–2020 and their linear trends (dashed line)

    图  6  1961~2020年东北林区(a)春季Tmax、(b)春季v和西南林区(c)春季Tmax、(d)冬季Tmax、(e)冬季KBDI防火期显著变化的气象因子的时间序列(实线)以及对应的线性趋势(虚线)

    Figure  6.  Time series (solid lines) of (a) daily maximum temperature (Tmax) in spring and (b) wind speed (v) in spring in Northeastern forest region and (c) Tmax in spring, (d) Tmax in winter, and (e) Keetch Byram Drought Index (KBDI) in winter in Southwestern forest region and their linear trends (dashed lines) during 1961–2020

    图  7  1961~2020年两大林区防火期森林火险气象指数序列的各EEMD分量(C1−C4)、趋势(蓝实线)和相应的线性趋势(红虚线)

    Figure  7.  EEMD components (C1−C4), trends (blue solid lines), and corresponding linear trends (red dashed lines) of FFDI in the fire seasons of the two forest regions during 1961–2020

    图  8  1961~2020年两大林区防火期相关气象因子KBDI、DF、Tmax、RH和v的EEMD趋势。为便于比较,相应FFDI的EEMD趋势也展示在最下方

    Figure  8.  EEMD trends of related meteorological factors KBDI, Drought Factor (DF), Tmax, Relative Humidity (RH), and v in the fire seasons of the two forest regions during 1961–2020. For ease of comparison, the EEMD trend of corresponding FFDI is also shown at the bottom

    表  1  1961~2020年东北林区森林火险气象指数及相关因子的线性趋势

    Table  1.   Linear trends of FFDI and related variables in the northeastern forest region during 1961–2020

    季节变量线性趋势系数/(10 a)−195%置信区间
    春季#森林火险气象指数FFDI0.01(−0.08,0.10)
    干旱指数KBDI/mm1.55c(−0.02,3.13)
    干旱因子DF0.08c(−0.01,0.15)
    日最高气温Tmax/℃0.31a(0.11,0.53)
    相对湿度RH−0.18%(−0.61%,0.23%)
    日平均风速v/m s−1−0.23a(−0.27,−0.19)
    夏季森林火险气象指数FFDI0.03(−0.05,0.09)
    干旱指数KBDI/mm0.72(−0.66,1.96)
    干旱因子DF0.04(−0.04,0.13)
    日最高气温Tmax/℃0.16a(0.07,0.28)
    相对湿度RH−0.26%(−0.59%,0.07%)
    日平均风速v/m s−1−0.10a(−0.15,−0.06)
    秋季#森林火险气象指数FFDI0.04(−0.03,0.11)
    干旱指数KBDI/mm1.09(−0.89,3.06)
    干旱因子DF0.06(−0.06,0.18)
    日最高气温Tmax/℃0.21b(0.04,0.35)
    相对湿度RH−0.35%c(−0.73%,0.06%)
    日平均风速v/m s−1−0.17a(−0.21,−0.13)
    冬季森林火险气象指数FFDI0.02(−0.01,0.05)
    干旱指数KBDI/mm1.31(−0.60,3.12)
    干旱因子DF0.10b(0.00,0.21)
    日最高气温Tmax/℃0.31b(0.06,0.57)
    相对湿度RH−0.56%b(−0.99%,−0.08%)
    日平均风速v/m s−1−0.17a(−0.22,−0.13)
    注:#表示林区的防火期;abc表示通过99%、95%、90%的信度检验。
    下载: 导出CSV

    表  2  1961~2020年西南林区森林火险气象指数及相关因子的线性趋势

    Table  2.   Linear trends of FFDI and related variables in the southwestern forest region during 1961–2020

    季节变量线性趋势系数/(10 a)−195%置信区间
    春季#森林火险气象指数FFDI0.09c(−0.02,0.20)
    干旱指数KBDI/mm1.37c(−0.10,2.99)
    干旱因子DF0.07(−0.04,0.16)
    日最高气温Tmax/℃0.17a(0.06,0.29)
    相对湿度RH−0.19%(−0.45%,0.12%)
    日平均风速v/m s−1−0.04b(−0.09,0)
    夏季森林火险气象指数FFDI0.05b(0.01,0.09)
    干旱指数KBDI/mm1.78b(0.29,3.09)
    干旱因子DF0.11b(0.03,0.20)
    日最高气温Tmax/℃0.19a(0.12,0.26)
    相对湿度RH−0.10%(−0.29%,0.11%)
    日平均风速v/m s−10.03(−0.04,0.09)
    秋季
    森林火险气象指数FFDI0.04b(0.00,0.07)
    干旱指数KBDI/mm1.84b(0.29,3.43)
    干旱因子DF0.11b(0.02,0.20)
    日最高气温Tmax/℃0.20a(0.11,0.30)
    相对湿度RH−0.04%(−0.32%,0.21%)
    日平均风速v/m s−10.03(−0.02,0.07)
    冬季#森林火险气象指数FFDI0.05c(−0.01,0.10)
    干旱指数KBDI/mm2.74a(0.72,4.50)
    干旱因子DF0.13b(0.02,0.24)
    日最高气温Tmax/℃0.20a(0.06,0.34)
    相对湿度RH0.02%(−0.25%,0.31%)
    日平均风速v/m s−1−0.01(−0.05,0.03)
    注:#表示林区的防火期;abc表示通过99%、95%、90%的信度检验。
    下载: 导出CSV

    表  3  1961~2020年两大林区森林火险气象指数与相应的气象因子之间的相关系数

    Table  3.   Correlation coefficients between the FFDI and corresponding meteorological factors in the two major forest regions during 1961–2020

    与FFDI的相关系数
    地区防火期KBDIDFTmaxRHv
    东北春季0.64a0.67a0.57a−0.79a0.30b
    秋季0.89a0.90a0.50a−0.89a−0.03
    西南春季0.90a0.95a0.76a−0.93a0.51a
    冬季0.81a0.85a0.67a−0.72b0.30
    注:ab分别表示通过99%、95%的信度检验。
    下载: 导出CSV

    表  4  1961~2020年两大林区森林火险气象指数的集合经验模分解(EEMD)分量周期及方差贡献率

    Table  4.   Period and variance contribution of the Ensemble Empirical Mode Decomposition (EEMD) components for FFDI series in the two major forest regions during 1961–2020

    地区防火期变量分量周期/a方差贡献率
    东北春季C12.9364.93%
    C26.6716.02%
    C31511.09%
    C4307.48%
    Res0.48%
    秋季C1349.37%
    C26.6724.71%
    C32014.16%
    C43010.70%
    Res 1.06%
    西南春季C12.8660.79%
    C25.2225.70%
    C3105.12%
    C4242.78%
    Res 5.61%
    冬季C13.0760.25%
    C26.6716.83%
    C3129.23%
    C4307.08%
    Res 6.61%
    下载: 导出CSV
  • [1] 陈锋. 2015. 云南省森林火灾对气候变化的响应及趋势预测 [D]. 北京林业大学博士学位论文, 112pp. Chen Feng. 2015. The response of forest fires to climate change and fire trend prediction in Yunnan Province [D]. Ph. D. dissertation (in Chinese), Beijing Forestry University, 112pp.
    [2] 陈锋, 林向东, 牛树奎, 等. 2012. 气候变化对云南省森林火灾的影响 [J]. 北京林业大学学报, 34(6): 7−15. doi: 10.13332/j.1000-1522.2012.06.010

    Chen Feng, Lin Xiangdong, Niu Shukui, et al. 2012. Influence of climate change on forest fire in Yunnan Province, southwestern China [J]. Journal of Beijing Forest University (in Chinese), 34(6): 7−15. doi: 10.13332/j.1000-1522.2012.06.010
    [3] 程亮, 刘东华, 梅娜. 2020. 森林火灾与哪些气象因素有关 [J]. 生命与灾害, (5): 22−25.

    Chen Liang, Liu Donghua, Mei Na. 2020. What meteorological factors are responsible for forest fires [J]. Life Disaster (in Chinese), (5): 22−25.
    [4] Clarke H, Lucas C, Smith P. 2013. Changes in Australian fire weather between 1973 and 2010 [J]. Int. J. Climatol., 33(4): 931−944. doi: 10.1002/joc.3480
    [5] Crane W J B. 1982. Computing grassland and forest fire behaviour, relative humidity and drought index by pocket calculator [J]. Aust. Forestry, 45(02): 89−97. doi: 10.1080/00049158.1982.10674339
    [6] Dowdy A J, Mills G A, Finkele K, et al. 2010. Index sensitivity analysis applied to the Canadian Forest Fire Weather Index and the McArthur Forest Fire Danger Index [J]. Meteor. Appl., 17(3): 298−312. doi: 10.1002/met.170
    [7] Du Jizeng, Wang Kaicun, Cui Baoshan. 2021. Attribution of the extreme drought-related risk of wildfires in spring 2019 over Southwest China [J]. Bull. Amer. Meteor. Soc., 102(1): S83−S90. doi: 10.1175/BAMS-D-20-0165.1
    [8] Fang Keyan, Yao Qichao, Guo Zhengtang, et al. 2021. ENSO modulates wildfire activity in China [J]. Nat. Commun., 12(1): 1764. doi: 10.1038/s41467-021-21988-6
    [9] Flannigan M D, Krawchuk M A, de Groot W J, et al. 2009. Implications of changing climate for global wildland fire [J]. Int. J. Wild. Fire, 18(5): 483−507. doi: 10.1071/WF08187
    [10] 傅泽强, 陈动, 王玉彬. 2001. 大兴安岭森林火灾与气象条件的相互关系 [J]. 东北林业大学学报, 29(1): 12−15. doi: 10.3969/j.issn.1000-5382.2001.01.004

    Fu Zeqiang, Chen Dong, Wang Yubin. 2001. The relationship between forest fire and meteorological condition in Daxing’an Mountains [J]. J. Northeast For. Univ. (in Chinese), 29(1): 12−15. doi: 10.3969/j.issn.1000-5382.2001.01.004
    [11] Heim Jr R R. 2002. A review of twentieth-century drought indices used in the United States [J]. Bull. Amer. Meteor. Soc., 83(8): 1149−1166. doi: 10.1175/1520-0477-83.8.1149
    [12] Holgate C M, Van Dijk A I J M, Cary G J, et al. 2017. Using alternative soil moisture estimates in the McArthur Forest Fire Danger Index [J]. Int. J. Wild. Fire, 26(9): 806−819. doi: 10.1071/WF16217
    [13] 胡海清, 罗碧珍, 罗斯生, 等. 2020. 林火干扰对森林生态系统碳库的影响研究进展 [J]. 林业科学, 56(4): 160−169. doi: 10.11707/j.1001-7488.20200418

    Hu Haiqing, Luo Bizhen, Luo Sisheng, et al. 2020. Research progress on effects of forest fire disturbance on carbon pool of forest ecosystem [J]. Sci. Silvae Sin. (in Chinese), 56(4): 160−169. doi: 10.11707/j.1001-7488.20200418
    [14] Huang N E, Wu Zhaohua. 2008. A review on Hilbert-Huang transform: Method and its applications to geophysical studies [J]. Rev. Geophys., 46(2): RG2006. doi: 10.1029/2007RG000228
    [15] Huang N E, Shen Zheng, Long S R, et al. 1998. The empirical mode decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analysis [J]. Proc. Roy. Soc. A, 454(1971): 903−995. doi: 10.1098/rspa.1998.0193
    [16] Keetch J J, Byram G M. 1968. A Drought Index for Forest Fire Control [M]. Asheville: U. S. Department of Agriculture, 1–32.
    [17] Kendall M G. 1955. Rank Correlation Methods (2nd ed.) [M]. London: C. Griffin, 196pp.
    [18] Khastagir A. 2018. Fire frequency analysis for different climatic stations in Victoria, Australia [J]. Nat. Hazards, 93(2): 787−802. doi: 10.1007/s11069-018-3324-x
    [19] 李晓炜. 2011. 森林气象火险指数的区域适应性及其概率模型[D]. 中国科学院研究生院博士学位论文, 7pp.

    Li Xiaowei. 2011. Probability models of forest fire based on risk indices in contrasting climatic zones over China [D]. Ph. D. dissertation (in Chinese), Graduate University of Chinese Academy of Sciences, 7pp.
    [20] 李德. 2013. 四川省重点地区森林火灾与气象因子的关系研究[D]. 北京林业大学硕士学位论文, 2pp.

    Li De. 2013. The relationship between forest fire and meteorological factors in the key areas of Sichuan Province [D]. M. S. thesis (in Chinese), Beijing Forestry University, 2pp.
    [21] 李德, 牛树奎, 龙先华, 等. 2013. 四川省森林火灾与气象因子的关系[J]. 西北农林科技大学学报(自然科学版), 41(6): 67–74. Li De, Niu Shukui, Long Xianhua, et al. 2013. Relationship of forest fires and meteorological factors in Sichuan Province[J]. Journal of Northwest A&F University (Natural Science Ed.) (in Chinese), 41(6): 67–74. doi: 10.13207/j.cnki.jnwafu.2013.06.015
    [22] Li F, Bond-Lamberty B, Levis S. 2014. Quantifying the role of fire in the Earth system– Part 2: Impact on the net carbon balance of global terrestrial ecosystems for the 20th century [J]. Biogeosciences, 11(5): 1345−1360. doi: 10.5194/bg-11-1345-2014
    [23] Li Zhen, Cao Lijuan, Zhu Yani, et al. 2016. Comparison of two homogenized datasets of daily maximum/mean/minimum temperature in China during 1960−2013 [J]. J. Meteor. Res., 30(1): 53−66. doi: 10.1007/s13351-016-5054-x
    [24] Li Zhen, Yan Zhongwei, Zhu Yani, et al. 2020. Homogenized daily relative humidity series in China during 1960−2017 [J]. Adv. Atmos. Sci., 37(4): 318−327. doi: 10.1007/s00376-020-9180-0
    [25] 刘永强. 2016. 植被对干旱趋势的影响 [J]. 大气科学, 40(1): 142−156. doi: 10.3878/j.issn.1006-9895.1508.15146

    Liu Yongqiang. 2016. Impacts of vegetation on drought trends [J]. Chinese Journal of Atmospheric Sciences (in Chinese), 40(1): 142−156. doi: 10.3878/j.issn.1006-9895.1508.15146
    [26] 刘魏魏, 王效科, 逯非, 等. 2016. 造林再造林、森林采伐、气候变化、CO2浓度升高、火灾和虫害对森林固碳能力的影响 [J]. 生态学报, 36(8): 2113−2122. doi: 10.5846/stxb201411022143

    Liu Weiwei, Wang Xiaoke, Lu Fei, et al. 2016. Influence of afforestation, reforestation, forest logging, climate change, CO2 concentration rise, fire, and insects on the carbon sequestration capacity of the forest ecosystem [J]. Acta Ecol Sinica (in Chinese), 36(8): 2113−2122. doi: 10.5846/stxb201411022143
    [27] 刘吉敏, 黄泓, 王学忠. 2018. 春季东北地区森林火险气象指数及其极值重现期特征 [J]. 灾害学, 33(1): 76−80. doi: 10.3969/j.issn.1000-811X.2018.01.015

    Liu Jimin, Huang Hong, Wang Xuezhong. 2018. Forest fire danger index of Northeast China region in summer and its characteristics of extreme value [J]. J. Catastrophol. (in Chinese), 33(1): 76−80. doi: 10.3969/j.issn.1000-811X.2018.01.015
    [28] Loehman R A. 2020. Drivers of wildfire carbon emissions [J]. Nat. Climate Change, 10(12): 1070−1071. doi: 10.1038/s41558-020-00922-6
    [29] Luke R H, McArthur A G. 1986. Bushfires in Australia (2nd ed.) [M]. Canberra: Australian Government Publishing Service, 359pp.
    [30] Mann H B. 1945. Nonparametric tests against trend [J]. Econometrica, 13(3): 245−259. doi: 10.2307/1907187
    [31] McArthur A G. 1967. Fire Behaviour in Eucalypt Forests [M]. Canberra: Department of Natural Development, 36pp.
    [32] 牛若芸, 翟盘茂, 佘万明. 2007. 森林火险气象指数的应用研究 [J]. 应用气象学报, 18(4): 479−489. doi: 10.3969/j.issn.1001-7313.2007.04.008

    Niu Ruoyun, Zhai Panmao, She Wanming. 2007. Applied research on forest fire danger weather index [J]. J. Appl. Meteor. Sci. (in Chinese), 18(4): 479−489. doi: 10.3969/j.issn.1001-7313.2007.04.008
    [33] Noble I R, Gill A M, Bary G A V. 1980. McArthur’s fire–danger meters expressed as equations [J]. Aust. J. Ecol., 5(2): 201−203. doi: 10.1111/j.1442-9993.1980.tb01243.x
    [34] Qian Cheng. 2016. Disentangling the urbanization effect, multi-decadal variability, and secular trend in temperature in eastern China during 1909–2010 [J]. Atmos. Sci. Lett., 17(2): 177−182. doi: 10.1002/asl.640
    [35] Qian Cheng, Zhou Tianjun. 2014. Multidecadal variability of North China aridity and its relationship to PDO during 1900–2010 [J]. J. Climate, 27(3): 1210−1222. doi: 10.1175/JCLI-D-13-00235.1
    [36] Qian Cheng, Fu Congbin, Wu Zhaohua, et al. 2009. On the secular change of spring onset at Stockholm [J]. Geophys. Res. Lett., 36(12): L12706. doi: 10.1029/2009GL038617
    [37] Qian Cheng, Wu Zhaohua, Fu Congbin, et al. 2011. On changing El Niño: A view from time-varying annual cycle, interannual variability, and mean state [J]. J. Climate, 24(24): 6486−6500. doi: 10.1175/JCLI-D-10-05012.1
    [38] Qian Cheng, Zhang Xuebin, Li Zhen. 2019. Linear trends in temperature extremes in China, with an emphasis on non-Gaussian and serially dependent characteristics [J]. Climate Dyn., 53(1): 533−550. doi: 10.1007/s00382-018-4600-x
    [39] 任国玉, 郭军, 徐铭志, 等. 2005. 近50年中国地面气候变化基本特征 [J]. 气象学报, 62(6): 942−956. doi: 10.3321/j.issn:0577-6619.2005.06.011

    Ren Guoyu, Guo Jun, Xu Mingzhi, et al. 2005. Climate changes of China’s mainland over the past half century [J]. Acta Meteor. Sinica (in Chinese), 62(6): 942−956. doi: 10.3321/j.issn:0577-6619.2005.06.011
    [40] Sen P K. 1968. Estimates of the regression coefficient based on Kendall’s Tau [J]. J. Amer. Stat. Assoc., 63(324): 1379−1389. doi: 10.1080/01621459.1968.10480934
    [41] 施雅风, 沈永平, 胡汝骥. 2002. 西北气候由暖干向暖湿转型的信号、影响和前景初步探讨 [J]. 冰川冻土, 24(3): 219−226. doi: 10.3969/j.issn.1000-0240.2002.03.001

    Shi Yafeng, Shen Yongping, Hu Ruji. 2002. Preliminary study on signal, impact and foreground of climatic shift from warm−dry to warm−humid in Northwest China [J]. J. Glaciol. Geocryol. (in Chinese), 24(3): 219−226. doi: 10.3969/j.issn.1000-0240.2002.03.001
    [42] Song Ge, Huang Bohua, Ren Rongcai, et al. 2021. Basinwide connections of upper-ocean temperature variability in the equatorial Indian Ocean [J]. J. Climate, 34(12): 4675−4692. doi: 10.1175/JCLI-D-20-0419.1
    [43] Szentimrey T. 1999. Multiple analysis of series for homogenization (MASH) [C]//Proceedings of the 2nd Seminar for Homogenization of Surface Climatological Data. Geneva: WMO, 27−46.
    [44] 苏秀程, 王磊, 李奇临, 等. 2014. 近50a中国西南地区地表干湿状况研究 [J]. 自然资源学报, 29(1): 104−116. doi: 10.11849/zrzyxb.2014.01.010

    Su Xiucheng, Wang Lei, Li Qilin, et al. 2014. Study of surface dry and wet conditions in Southwest China in recent 50 years [J]. J. Nat. Resour. (in Chinese), 29(1): 104−116. doi: 10.11849/zrzyxb.2014.01.010
    [45] 田晓瑞, McRae D J, Jin Jizhong, 等. 2010a. 大兴安岭地区森林火险变化及FWI适用性评估 [J]. 林业科学, 46(5): 127−132.

    Tian Xiaorui, McRae D J, Jin Jizhong, et al. 2010a. Changes of forest fire danger and the evaluation of the FWI system application in the Daxing’anling region [J]. Sci. Silvae Sin. (in Chinese), 46(5): 127−132.
    [46] 田晓瑞, 赵凤君, 舒立福, 等. 2010b. 西南林区卫星监测热点及森林火险天气指数分析 [J]. 林业科学研究, 23(4): 523−529. doi: 10.13275/j.cnki.lykxyj.2010.04.022

    Tian Xiaorui, Zhao Fengjun, Shu Lifu, et al. 2010b. Hotspots from satellite monitoring and forest fire weather index analysis for Southwest China [J]. For. Res. (in Chinese), 23(4): 523−529. doi: 10.13275/j.cnki.lykxyj.2010.04.022
    [47] 田晓瑞, 舒立福, 赵凤君, 等. 2012. 未来情景下西南地区森林火险变化 [J]. 林业科学, 48(1): 121−125. doi: 10.11707/j.1001-7488.20120120

    Tian Xiaorui, Shu Lifu, Zhao Fengjun, et al. 2012. Forest fire danger changes for Southwest China under future scenarios [J]. Sci. Silvae Sin. (in Chinese), 48(1): 121−125. doi: 10.11707/j.1001-7488.20120120
    [48] Tian Xiaorui, Zhao Fengjun, Shu Lifu, et al. 2014. Changes in forest fire danger for South−Western China in the 21st century [J]. Int. J. Wild. Fire, 23(2): 185−195. doi: 10.1071/WF13014
    [49] 田晓瑞, 舒立福, 赵凤君, 等. 2017. 气候变化对中国森林火险的影响 [J]. 林业科学, 53(7): 159−169. doi: 10.11707/j.1001-7488.20170716

    Tian Xiaorui, Shu Lifu, Zhao Fengjun, et al. 2017. Impacts of climate change on forest fire danger in China [J]. Sci. Silvae Sin. (in Chinese), 53(7): 159−169. doi: 10.11707/j.1001-7488.20170716
    [50] 田晓瑞, 宗学政, 舒立福, 等. 2020. ENSO事件对中国森林火险天气的影响 [J]. 应用生态学报, 31(5): 1487−1495. doi: 10.13287/j.1001-9332.202005.015

    Tian Xiaorui, Zong Xuezheng, Shu Lifu, et al. 2020. Impacts of ENSO events on forest fire weather of China [J]. Chinese J. Appl. Ecol. (in Chinese), 31(5): 1487−1495. doi: 10.13287/j.1001-9332.202005.015
    [51] 王明玉. 2009. 气候变化背景下中国林火响应特征及趋势 [D]. 中国林业科学研究院博士学位论文, 249pp. Wang Mingyu. 2009. Characteristics of forest fire response and trend under the scenarios of climate change in China [D]. Ph. D. dissertation (in Chinese), Chinese Academy of Forestry, 249pp. doi: 10.7666/d.D602898
    [52] Wang X L, Swail V R. 2001. Changes of extreme wave heights in Northern Hemisphere oceans and related atmospheric circulation regimes [J]. J. Climate, 14(10): 2204−2221. doi:10.1175/1520-0442(2001)014<2204:COEWHI>2.0.CO;2
    [53] 王遵娅, 丁一汇, 何金海, 等. 2004. 近50年来中国气候变化特征的再分析 [J]. 气象学报, 62(2): 228−236. doi: 10.3321/j.issn:0577-6619.2004.02.009

    Wang Zunya, Ding Yihui, He Jinhai, et al. 2004. An updating analysis of the climate change in China in recent 50 years [J]. Acta Meteor. Sinica (in Chinese), 62(2): 228−236. doi: 10.3321/j.issn:0577-6619.2004.02.009
    [54] Wu Zhaohua, Huang N E. 2009. Ensemble empirical mode decomposition: A noise-assisted data analysis method [J]. Adv. Adapt. Data Anal., 1(1): 1−41. doi: 10.1142/S1793536909000047
    [55] 谢睿恒, 王爱慧, 华维. 2020. 1961~2013年中国蒸发皿蒸发量时空分布特征及其影响因素 [J]. 气候与环境研究, 25(5): 483–498. Xie Ruiheng, Wang Aihui, Hua Wei. 2020. Temporal and spatial distribution characteristics and influencing factors of pan evaporation in China from 1961 to 2013 [J]. Clim. Environ. Res. (in Chinese), 25(5): 483−498. doi: 10.3878/j.issn.1006-9585.2019.19130
    [56] Xu Ming, Chang C P, Fu Congbin, et al. 2006. Steady decline of East Asian monsoon winds, 1969–2000: Evidence from direct ground measurements of wind speed [J]. J. Geophys. Res., 111(D24): D24111. doi: 10.1029/2006JD007337
    [57] 许恩银, 王维枫, 聂影, 等. 2020. 中国林业碳贡献区域分布及潜力预测 [J]. 中国人口·资源与环境, 30(5): 36−45.

    Xu Enyin, Wang Weifeng, Nie Ying, et al. 2020. Regional distribution and potential forecast of China’s forestry carbon contributions [J]. China Popul. Resour. Environ. (in Chinese), 30(5): 36−45.
    [58] 于文颖, 周广胜, 赵先丽, 等. 2010. 黑龙江省大兴安岭林区森林气象火险指数的适用性研究 [J]. 安徽农业科学, 38(26): 14496−14501. doi: 10.3969/j.issn.0517-6611.2010.26.122

    Yu Wenying, Zhou Guangsheng, Zhao Xianli, et al. 2010. Study on the adaptability of forest fire danger weather index in Daxing’Anling forest region [J]. J. Anhui Agric. Sc. (in Chinese), 38(26): 14496−14501. doi: 10.3969/j.issn.0517-6611.2010.26.122
    [59] 杨光, 舒立福, 邸雪颖. 2012. 气候变化影响下大兴安岭地区21世纪森林火险等级变化预测 [J]. 应用生态学报, 23(12): 3236−3242. doi: 10.13287/j.1001-9332.2012.0405

    Yang Guang, Shu Lifu, Di Xueying. 2012. Prediction on the changes of forest fire danger rating in Great Xing’an Mountain region of Northeast China in the 21st century under effects of climate change [J]. Chinese J. Appl. Ecol. (in Chinese), 23(12): 3236−3242. doi: 10.13287/j.1001-9332.2012.0405
    [60] 曾雪莹, 潘新民, 王燕, 等. 2019. 新疆林业气象灾害风险调查与服务效益评估 [J]. 林业调查规划, 44(5): 50−55. doi: 10.3969/j.issn.1671-3168.2019.05.011

    Zeng Xueying, Pan Xinmin, Wang Yan, et al. 2019. Risk investigation of forestry meteorological disaster and benefit evaluation of forestry meteorological service in Xinjiang [J]. Forest Invent. Plan. (in Chinese), 44(5): 50−55. doi: 10.3969/j.issn.1671-3168.2019.05.011
    [61] 张嘉仪, 钱诚. 2020. 1960~2018年中国高温热浪的线性趋势分析方法与变化趋势 [J]. 气候与环境研究, 25(3): 225–239. Zhang Jiayi, Qian Cheng. 2020. Linear trends in occurrence of high temperature and heat waves in China for the 1960–2018 period: Method and analysis results [J]. Clim. Environ. Res. (in Chinese), 25(3): 225−239. doi: 10.3878/j.issn.1006-9585.2020.19134
    [62] Zhang Xuebin, Vincent L A, Hogg W D, et al. 2000. Temperature and precipitation trends in Canada during the 20th century [J]. Atmos. Ocean, 38(3): 395−429. doi: 10.1080/07055900.2000.9649654
    [63] Zhang Qiang, Yang Jinhu, Wang Wei, et al. 2021. Climatic warming and humidification in the arid region of Northwest China: Multi-scale characteristics and impacts on ecological vegetation [J]. J. Meteor. Res., 35(1): 113−127. doi: 10.1007/s13351-021-0105-3
    [64] 赵凤君, 舒立福. 2007. 气候异常对森林火灾发生的影响研究 [J]. 森林防火, (1): 21−23. doi: 10.3969/j.issn.1002-2511.2007.01.009

    Zhao Fengjun, Shu Lifu. 2007. Climate anomaly and its influence on occurring forest fire under global warming [J]. For. Fire Prevent. (in Chinese), (1): 21−23. doi: 10.3969/j.issn.1002-2511.2007.01.009
    [65] Zhao Fengjun, Liu Yongqiang, Shu Lifu. 2020. Change in the fire season pattern from bimodal to unimodal under climate change: The case of Daxing’anling in Northeast China [J]. Agric. For. Meteorol., 291: 108075. doi: 10.1016/j.agrformet.2020.108075
    [66] Zscheischler J, Westra S, van den Hurk B J J M. 2018. Future climate risk from compound events [J]. Nat. Climate Change, 8(6): 469−477. doi: 10.1038/s41558-018-0156-3
  • 加载中
图(8) / 表(4)
计量
  • 文章访问数:  322
  • HTML全文浏览量:  60
  • PDF下载量:  35
  • 被引次数: 0
出版历程
  • 收稿日期:  2021-06-03
  • 网络出版日期:  2021-09-13
  • 刊出日期:  2022-09-25

目录

    /

    返回文章
    返回