摘要
青藏高原特殊的地理环境使其对全球气候变化十分敏感,所以研究其地表冻融循环和植被返青期的时空动态对于回顾和预测青藏高原对全球气候变化的响应具有重要意义。本文通过利用双指标地表冻融状态识别算法和被动微波亮温数据(SMMR、SSMI和SSMIS)来获取青藏高原长时间序列(1982年—2013年)逐日地表冻融状态,通过对GIMMS全球植被指数数据产品进行NDVI的滤波重建和返青期提取来获取青藏高原植被长时间序列(年份)的返青期;并且分析了地表冻融循环和植被返青期的变化趋势、相互关系及对青藏高原气候变化的响应特征。总体来看,在空间上,青藏高原的地表冻结集中发生在10月30日至次年4月2日,平均地表融化首日集中在5月12—27日,平均植被返青期集中在5月19—29日。植被返青期平均发生在地表融化首日后的3.94±5.58日,两者具有显著的相关关系(R=0.51,P=0.003)。青藏高原的地表融化首日和植被返青期在1982年—2013年间经历了推迟、提前再推迟的3个过程,融化时间和返青期在1982年—1987年分别以1.93±1.81 d/a和0.28±1.01 d/a的速度推迟;在1987年—2006年分别以0.67±0.20 d/a和0.13±0.16 d/a的速度提前;在2006年—2013年分别以0.97±0.84 d/a和1.04±0.52 d/a的速度推迟。中国气象局布设在青藏高原的CMA气象站的温度数据表明,高原的春季地表0 cm土壤温度呈持续上升的趋势,而植被返青期和地表融化首日并未持续提前,这可能是由几十年来高原不同地区降水等其他环境因素变化的差异造成。同时在气温持续升高期间,植被返青期的返青温度阈值也不断具有上升的趋势(R=0.72,P<0.001),这可能与植被适应气候变化的自身调节能力有关。
The Qinghai-Tibet Plateau is sensitive to global climate change because of its special geographical environment. Therefore, analyzing the temporal dynamics and spatial patterns of surface freeze-thaw cycles and vegetation green-up date to determine and predict their response to global climate change is important. A dual-index algorithm is adopted to obtain long-term series of surface freeze-thaw states from passive microwave brightness temperatures observed by SMMR, SSMI, and SSMIS during 1982—2013. The vegetation green-up date during 1982—2013 is derived based on the reconstructed NDVI from the GIMMS global vegetation index dataset by the filter algorithm. On the basis of both datasets, the areal extent,timing, seasonal variations, and inter-annual trend of surface soil freeze-thaw cycles and vegetation green-up date are examined across the Qinghai-Tibet plateau via regression and correlation analyses. Most pixels on the images of the Qinghai-Tibet Plateau showed the frozen state from October 30 to April 2 of the subsequent year. The average start date of surface thawing occurred mainly from May 12 to May 27, and the average green-up date occurred from May 19 to May29. The green-up date occurred 3.94±5.58 days after the start date of surface thawing on the average, and a significant correlation exists between them(R=0.51, P=0.003). The trends for the start date of surface thawing and green-up date underwent three stages, namely, delay, advance, and delay, from 1982 to 2013. The start date of surface thawing and the green-up date were delayed at speeds of 1.93±1.81 and 0.28±1.01 days/year from 1982 to1987, advanced at speeds of 0.67±0.20 and 0.13±0.16 days/year from 1987 to 2006, and delayed at speeds of 0.97±0.84 and 1.04±0.52 days/year from 2006 to 2013, respectively. However, the meteorological stations operated by the China Meteorological Administration indicated that the 0 cm ground surface temperature presented a continuous increasing trend, which might be caused by the changes in other environmental factors, such as heterogeneous precipitation on the Qinghai-Tibet Plateau. At the same time, the temperature threshold of vegetation green-up date showed a continuous upward trend(R=0.72, P0.001) as air temperature increased, which was possibly correlated to the capability of vegetation to self-adapt to climate change.
作者
王欣
晋锐
杜培军
梁昊
WANG Xin;JIN Rui;DU Peijun;LIANG Hao(Key Laboratory for Satellite Mapping Technology and Applications of State Administration of Surveying, Mapping and Geoinformation of China, Nanjing University, Nanjing 210023, China;Jiangsu Provincial Key Laboratory of Geographic Information Science and Technology, Nanjing University, Nanjing 210023, China;Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application, Nanjing University, Nanjing 210023, China;Key Laboratory of Remote Sensing of Gansu Province, Heihe Remote Sensing Experimental Research Station, Cold and Arid Regions Environmental and Engineering Research Institute, Chinese Academy of Sciences, Lanzhou 730000, China)
出处
《遥感学报》
EI
CSCD
北大核心
2018年第3期508-520,共13页
NATIONAL REMOTE SENSING BULLETIN
基金
国家自然科学基金(编号:41531174
41471357)
中国科学院西部之光人才计划~~
关键词
青藏高原
地表冻融循环
返青期
气候变化
Qinghai-Tibet Plateau
ground surface soil freeze-thaw cycle
green-up date
climate change