Abstract:

Observed daily temperature and precipitation from 121 meteorological stations and satellite-based 8-day average gross primary productivity (GPP) from MOD17A2 are utilized to develop the linear correlation models between 8-day accumulated average temperature, maximum temperature, minimum temperature, precipitation and accumulated GPP in the monsoon zone in Northern China during 2000–2013. Based on the derived thresholds and coefficients of these models, variability in the starting date of GPP accumulation, length of GPP accumulating period, ending date of GPP accumulation as well as GPP accumulation rate on forest, grassland and cropland ecosystems are investigated under two Representative Concentration Pathways (RCP4.5 and RCP8.5) of the Regional Spectral Model (RSM). Finally, the substantial impacts of climate changes including maximum, average, minimum temperature and precipitation on ecosystem productivity are evaluated. Results suggest that average and minimum temperature can predict GPP more accurately than maximum temperature and precipitation. Besides, the starting and ending dates of GPP accumulation are sensitive to the variability in four climatic factors whereas the GPP accumulation period and rate are more sensitive to the variability in average and maximum temperature. Additionally, future climate changes tend to prolong the GPP accumulation period and increase the GPP accumulation rate, thus increasing GPP.

Key words:  temperature, precipitation, gross primary productivity, variability in accumulation

摘要：

利用中国北方季风区121个地表气象观测站2000—2013年逐日气温和降水资料及MODIS遥感8天平均总初级生产量数据(MOD17A2), 分别建立了14年内8天累积平均、最低、最高气温和降雨量与累积总初级生产量的线性气候相关模型。基于模型所得区间的阈值和参数, 计算区域模式RSM本底时期10年(1996—2005年)及未来 10年(2041—2050年)两种排放情景RCP4.5和RCP8.5下, 森林、草地和农田生态系统总初级生产量累积开始日期、累积时期、累积结束日期及累积速率变化, 分析平均、最高、最低气温和降水量变化对总初级生产量累积的影响, 并综合评价气候变化对生态系统总初级生产量累积的影响。结果表明: 平均气温和最低气温对总初级生产量的模拟精度高于最高气温和降雨量; 总初级生产量累积开始和结束日期对4 类气候因子的变化均较敏感, 而累积时期和累积速率仅对平均气温和最高气温的变化较敏感; 未来气候变化将延长累积时期, 增加累积速率, 并提高总初级生产量。

关键词: 气温, 降水, 总初级生产量, 累积变化