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Estimating changes in global vegetation cover (1850-2100) for use in climate models

机译:估算用于气候模型的全球植被覆盖度(1850-2100)的变化

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Historical changes in global cropland area based on estimates of Ramankutty and Foley ( 1999), and projections of future changes under IPCC SRES development scenarios taken from the IMAGE 2 model, were combined with a simple classification of present- day satellite data. These data were used to estimate annual changes in area fractions occupied by primary plant functional types ( PFTs) between 1850 and 2100 using two different approaches. The linear interpolation approach assumed that natural vegetation area varies in inverse proportion to cropland area. The rule- based approach added simple transition rules to define the sequence by which natural PFTs are converted to agriculture ( e. g., grassland before forest) and by which abandoned cropland reverts to natural vegetation. In both approaches, constraints were imposed to ensure the simulated PFT composition was consistent with available information. The resulting time series data can be used in coupled biosphere- atmosphere models, and in uncoupled global climate models, to represent time- varying land cover.
机译:根据Ramankutty和Foley(1999)的估计,全球耕地面积的历史变化,以及根据IMAGE 2模型得出的IPCC SRES发展情景下的未来变化预测,均与当前卫星数据的简单分类相结合。这些数据用于通过两种不同的方法来估算1850年至2100年之间主要植物功能类型(PFT)所占面积的年度变化。线性插值方法假设自然植被面积与耕地面积成反比。基于规则的方法增加了简单的过渡规则,以定义将自然PFT转换为农业(例如,森林之前的草地)以及将废弃的农田恢复为自然植被的顺序。在这两种方法中,都施加了约束条件以确保模拟的PFT组成与可用信息一致。所得的时间序列数据可用于耦合的生物圈-大气模型和非耦合的全球气候模型,以表示随时间变化的土地覆盖。

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