Accumulated temperature above 100℃ (Σ t) and minimum annual temperature (Tm) are the major indexes for demarcating agroclimatic thermal zones. The paper calculated the return period (τ) of Σ t and Tm, and the shif...Accumulated temperature above 100℃ (Σ t) and minimum annual temperature (Tm) are the major indexes for demarcating agroclimatic thermal zones. The paper calculated the return period (τ) of Σ t and Tm, and the shift ofΣ t-and Tm-isopleths with T. The results show: (1) According to the magnitude of shift of Σ t-and Tm-isopleths, in Northeast China, Inner Mongolia and northern Xinjiang the fluctuation of thermal resources in growing season from year to year is the greatest and strongly impacts the yield of annual thermophilous crops, but in the Changjiang River basin the fluctuation of the low temperature in winter is the greatest and seriously injures the perennial subtropical tree crops. ( 2) In the anomalous cool summer year with t = 30, the northern boundaries of the southern subtropical, northern subtropical and warm temperate zones and the southern boundary of the frigid temperate zone in China could be expected to shift southward 150, 220, 250 and 300 km from their normal positions,展开更多
A mean annual loss rate(MALR) is a measure of the damaging degree of different crops to agroclimatic calamities such as waterlogging, strong win4 hail and dry-hot wind. It is useful for assessing regional insurance Pr...A mean annual loss rate(MALR) is a measure of the damaging degree of different crops to agroclimatic calamities such as waterlogging, strong win4 hail and dry-hot wind. It is useful for assessing regional insurance Premium. Based on the meteorological data observed from 1961 to 1993 in Hebei province and the damaging grades of some crops to meteorological disasters, we establish the index systems of agroclimatic calamities and then calculate the MALR with hierarchical models. Finally, GIS-based spatial maps on MALR has been employed to exhibit regional differentiation of mean annual loss rate of crops.展开更多
To understand the potential impacts of projected climate change on the vulnerable agriculture in Central Asia(CA),six agroclimatic indicators are calculated based on the 9-km-resolution dynamical downscaled results of...To understand the potential impacts of projected climate change on the vulnerable agriculture in Central Asia(CA),six agroclimatic indicators are calculated based on the 9-km-resolution dynamical downscaled results of three different global climate models from Phase 5 of the Coupled Model Intercomparison Project(CMIP5),and their changes in the near-term future(2031-50)are assessed relative to the reference period(1986-2005).The quantile mapping(QM)method is applied to correct the model data before calculating the indicators.Results show the QM method largely reduces the biases in all the indicators.Growing season length(GSL,day),summer days(SU,day),warm spell duration index(WSDI,day),and tropical nights(TR,day)are projected to significantly increase over CA,and frost days(FD,day)are projected to decrease.However,changes in biologically effective degree days(BEDD,°C)are spatially heterogeneous.The high-resolution projection dataset of agroclimatic indicators over CA can serve as a scientific basis for assessing the future risks to local agriculture from climate change and will be beneficial in planning adaption and mitigation actions for food security in this region.展开更多
In the global climatic change, China's climatic change will be more compliCated and itS compact on the agroclimatic resources and agricultural production will also be more obvious. Therefore, it is absolutely nec...In the global climatic change, China's climatic change will be more compliCated and itS compact on the agroclimatic resources and agricultural production will also be more obvious. Therefore, it is absolutely necessary to take the agroclimatic resources as a comprehensive climatic information syStem for evaluating the impact of climatic change on agriculture and exploring the corresPOndent ways to deal with it. This article studies the compact of climatic change on China's thermal resources and make a correlation analySis of the climatic COndition and the agroclimatic thermal resources in order to establish a regression equation and made simulant computation with Monte Cario Method. In addition, it analyses the change of the thermal resources possibly resulted from climatic change, evaluates its impact on agricultural, and finally sets up the corresPOndent countermeasures.展开更多
文摘Accumulated temperature above 100℃ (Σ t) and minimum annual temperature (Tm) are the major indexes for demarcating agroclimatic thermal zones. The paper calculated the return period (τ) of Σ t and Tm, and the shift ofΣ t-and Tm-isopleths with T. The results show: (1) According to the magnitude of shift of Σ t-and Tm-isopleths, in Northeast China, Inner Mongolia and northern Xinjiang the fluctuation of thermal resources in growing season from year to year is the greatest and strongly impacts the yield of annual thermophilous crops, but in the Changjiang River basin the fluctuation of the low temperature in winter is the greatest and seriously injures the perennial subtropical tree crops. ( 2) In the anomalous cool summer year with t = 30, the northern boundaries of the southern subtropical, northern subtropical and warm temperate zones and the southern boundary of the frigid temperate zone in China could be expected to shift southward 150, 220, 250 and 300 km from their normal positions,
文摘A mean annual loss rate(MALR) is a measure of the damaging degree of different crops to agroclimatic calamities such as waterlogging, strong win4 hail and dry-hot wind. It is useful for assessing regional insurance Premium. Based on the meteorological data observed from 1961 to 1993 in Hebei province and the damaging grades of some crops to meteorological disasters, we establish the index systems of agroclimatic calamities and then calculate the MALR with hierarchical models. Finally, GIS-based spatial maps on MALR has been employed to exhibit regional differentiation of mean annual loss rate of crops.
基金supported by the Strate-gic Priority Research Program of Chinese Academy of Sciences(Grant No.XDA20020201)the General Project of the National Natural Science Foundation of China(Grant No.41875134).
文摘To understand the potential impacts of projected climate change on the vulnerable agriculture in Central Asia(CA),six agroclimatic indicators are calculated based on the 9-km-resolution dynamical downscaled results of three different global climate models from Phase 5 of the Coupled Model Intercomparison Project(CMIP5),and their changes in the near-term future(2031-50)are assessed relative to the reference period(1986-2005).The quantile mapping(QM)method is applied to correct the model data before calculating the indicators.Results show the QM method largely reduces the biases in all the indicators.Growing season length(GSL,day),summer days(SU,day),warm spell duration index(WSDI,day),and tropical nights(TR,day)are projected to significantly increase over CA,and frost days(FD,day)are projected to decrease.However,changes in biologically effective degree days(BEDD,°C)are spatially heterogeneous.The high-resolution projection dataset of agroclimatic indicators over CA can serve as a scientific basis for assessing the future risks to local agriculture from climate change and will be beneficial in planning adaption and mitigation actions for food security in this region.
文摘In the global climatic change, China's climatic change will be more compliCated and itS compact on the agroclimatic resources and agricultural production will also be more obvious. Therefore, it is absolutely necessary to take the agroclimatic resources as a comprehensive climatic information syStem for evaluating the impact of climatic change on agriculture and exploring the corresPOndent ways to deal with it. This article studies the compact of climatic change on China's thermal resources and make a correlation analySis of the climatic COndition and the agroclimatic thermal resources in order to establish a regression equation and made simulant computation with Monte Cario Method. In addition, it analyses the change of the thermal resources possibly resulted from climatic change, evaluates its impact on agricultural, and finally sets up the corresPOndent countermeasures.
