Page 93 - 《高原气象》2021年第5期
P. 93

高     原      气     象                                 40 卷
              1054
             值较大的区域。                                            Donat M G,Lowry A L,Alexander L V,et al,2016. More extreme
                 (3) 对中巴经济走廊地区极端降水重现期估                             precipitation in the world's dry and wet regions[J]. Nature Cli‐
                                                                   mate Change,6(5):508-513. DOI:10. 1038/nclimate2941.
             计显示,广义极值分布能够较好的用来拟合中巴经
                                                                Eckstein D,Künzel V,Schäfer L,et al,2019. Global climate risk in‐
             济走廊地区日最大降水量;不同重现期极端降水重
                                                                   dex 2020. Who suffers most from extreme weather events?
             现水平的空间分布表明,极端降水表现出较强的区                                Weather-related loss events in 2018 and 1999 to 2018[M]. Ber‐
             域性,随着重现期的逐渐增加,35°N 地区高重现水                             lin:Germanwatch,Germany.
             平的区域范围逐渐减少,30°N 地区在 25 年一遇中                        Fan X H,Wang M B,2010. Change trends of air temperature and pre‐
             出现高重现水平区域,且在 50 年一遇重现期中区                              cipitation over Shanxi Province,China[J]. Theoretical and Ap‐
             域范围逐渐增大。                                              plied Climatology,103(3/4):519-531. DOI:10. 1007/s00704-
                                                                   010-0319-2.
                  本文探究了中巴经济走廊地区 1961-2015 年
                                                                Fischer E M,Knutti R,2016. Observed heavy precipitation increase
             极端降水量、强度、频率的时空变化特征并采用广
                                                                   confirms theory and early models[J]. Nature Climate Change,6
             义极值分布估算了不同重现期下极端降水的重现                                (11):986-991. DOI:10. 1038/nclimate3110.
             水平。从分析结果可以看出极端降水的变化存在                              Fisher R A,Tippett L H C,1928 Limiting forms of the frequency dis‐
             明显的时空差异。值得一提的是由 Germanwatch最                          tribution of the largest or smallest member of a sample[J]. Pro‐
             新发布的《2020年全球气候风险指数》显示,巴基斯                             ceedings of the Cambridge Philosophical Society, 24(2):
             坦受气候变化程度影响排名全球第五(Eckstein et                          180-190.
                                                                Li F Y,Collins W D,Wehner M F,et al,2011. Impact of horizontal
             al,2019)。鉴于极端降水强度、频率变化对中巴经
                                                                   resolution on simulation of precipitation extremes in an aqua-plan‐
             济走廊影响日益严重,未来应进一步开展极端降水
                                                                   et version of Community Atmospheric Model(CAM3)[J]. Tellus,
             的成因、时空演变预估及风险评估研究。                                    63A(5):884-892. DOI:10. 1111/j. 1600-0870. 2011. 00544. x.
                                                                Hijmans R J,Cameron S E,Parra J L,et al,2005. Very high-resolu‐
             参考文献:
                                                                   tion interpolated climate surfaces for global land areas[J]. Interna‐
             Abbas F,Ahmad A,Safeeq M,et al,2014. Changes in precipitation  tional Journal of Climatology,25(15):1965-1978. DOI:10.
                 extremes over arid to semiarid and subhumid Punjab,Pakistan  1002/joc. 1276.
                [J]. Theoretical and Applied Climatology,116(3/4):671-680.  Hussain M S,Lee S,2013. The regional and the seasonal variability
                 DOI:10. 1007/s00704-013-0988-8.                   of extreme precipitation trends in Pakistan[J]. Asia-Pacific Jour‐
             Abid M,Schneider U A,Scheffran J,2016. Adaptation to climate  nal of Atmospheric Sciences,49(4):421-441. DOI:10. 1007/
                 change and its impacts on food productivity and crop income:  s13143-013-0039-5.
                 Perspectives of farmers in rural Pakistan[J]. Journal of Rural  IPCC,2013. Intergovernmental Panel on Climate Change Climate
                 Studies,47:254-266. DOI:10. 1016/j. jrurstud. 2016. 08. 005.  Change Fifth Assessment Report(AR5)[M]. Cambridge:Lon‐
             Ahmed K F,Wang G,Silander J,et al,2013. Statistical downscaling  don Cambridge University Press,UK.
                 and bias correction of climate model outputs for climate change  Iqbal M F,Athar H,2018. Validation of satellite-based precipitation
                 impact assessment in the U. S. northeast[J]. Global and Planetary  over diverse topography of Pakistan[J]. Atmospheric Research,
                 Change,100:320-332. DOI:10. 1016/j. gloplacha. 2012. 11. 003.  201:247-260. DOI:10. 1016/j. atmosres. 2017. 10. 026.
             Allen M R,Ingram W J,2002. Constraints on future changes in cli‐  Jenkinson A F,1955. The frequency distribution of the annual maxi‐
                 mate and the hydrologic cycle[J]. Nature,419(6903):224-232.  mum(or minimum)values of meteorological elements[J]. Quar‐
                 DOI:10. 1038/nature01092.                         terly Journal of the Royal Meteorological Society,81(348):
             Ashiq M W,Zhao C,Ni J,et al,2010. GIS-based high-resolution  158-171. DOI:10. 1002/qj. 49708134804.
                 spatial interpolation of precipitation in mountain-plain areas of  Nandintsetseg B,Greene J S,Goulden C E,2007. Trends in extreme
                 Upper Pakistan for regional climate change impact studies[J].  daily precipitation and temperature near Lake Hvsgl,Mongolia
                 Theoretical and Applied Climatology,99(3/4):239-53. DOI:  [J]. International Journal of Climatology,27(3):341-347.
                 10. 1007/s00704-009-0140-y.                       DOI:10. 1002/joc. 1404.
             Atta UR R,Khan A N,2013. Analysis of 2010-flood causes,nature  Price D T,Mckenney D W,Nalder I A,et al,2000. A comparison of
                 and magnitude in the Khyber Pakhtunkhwa,Pakistan[J]. Natural  two statistical methods for spatial interpolation of Canadian
                 Hazards,66(2):887-904. DOI:10. 1007/s11069-012-0528-3.  monthly mean climate data[J]. Agricultural and Forest Meteorolo‐
             Bhatti A S,Wang G J,Ullah W,et al,2020. Trend in extreme precipi‐  gy,101(2/3):81-94. DOI:10. 1016/S0168-1923(99)00169-0.
                 tation indices based on long term in situ precipitation records over  Qureshi A H,2015. China/Pakistan economic corridor:A critical na‐
                 Pakistan[J]. Water,12(3):797. DOI:10. 3390/w12030797.  tional and international law policy-based perspective[J]. Chinese
             Coles S,2016. An introduction to statistical modeling of extreme val‐  Journal of International Law,14(4):777-799. DOI:10. 1093/
                 ues[M]. New York:Springer Verlag,36-78.           chinesejil/jmv045.
   88   89   90   91   92   93   94   95   96   97   98