71 resultados para Meteorology


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National Key Research and Development Program [2010CB833500]; National Natural Science Foundation of China [30590381]; Chinese Academy of Sciences [KZCX2-YW-432]

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National Key Research and Development Program [2010CB833500]; Natural Science Foundation of China [30590381]; Knowledge Innovation Project of Chinese Academy of Sciences [KZCX2-YW-432]

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National Natural Science Foundation of China (NSFC) [30670384, 30590381]

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Chinese Academy of Sciences [KZCX2-YW-315-2]; National Natural Science Foundation of China [40701021, 40625002]

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Change in thermal conditions can substantially affect crop growth, cropping systems, agricultural production and land use. In the present study, we used annual accumulated temperatures > 10 degrees C (AAT10) as an indicator to investigate the spatio-temporal changes in thermal conditions across China from the late 1980s to 2000, with a spatial resolution of 1 x 1 km. We also investigated the effects of the spatio-temporal changes on cultivated land use and cropping systems. We found that AAT10 has increased on a national scale since the late 1980s, Particularly, 3.16 x 10(5) km(2) of land moved from the spring wheat zone (AAT10: 1600 to 3400 degrees C) to the winter wheat zone (AAT10: 3400 to 4500 degrees C). Changes in thermal conditions had large influences on cultivated land area and cropping systems. The areas of cultivated land have increased in regions with increasing AAT10, and the cropping rotation index has increased since the late 1980s. Single cropping was replaced by 3 crops in 2 years in many regions, and areas of winter wheat cultivation were shifted northward in some areas, such as in the eastern Inner Mongolia Autonomous Region and in western Liaoning and Jilin Provinces.

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<span class="MedBlackText">The remote sensing based Production Efficiency Models (PEMs), springs from the concept of &quot;Light Use Efficiency&quot; and has been applied more and more in estimating terrestrial Net Primary Productivity (NPP) regionally and globally. However, global NPP estimates vary greatly among different models in different data sources and handling methods. Because direct observation or measurement of NPP is unavailable at global scale, the precision and reliability of the models cannot be guaranteed. Though, there are ways to improve the accuracy of the models from input parameters. In this study, five remote sensing based PEMs have been compared: CASA, GLO-PEM, TURC, SDBM and VPM. We divided input parameters into three categories, and analyzed the uncertainty of (1) vegetation distribution, (2) fraction of photosynthetically active radiation absorbed by the canopy (fPAR) and (3) light use efficiency (e). Ground measurements of Hulunbeier typical grassland and meteorology measurements were introduced for accuracy evaluation. Results show that a real-time, more accurate vegetation distribution could significantly affect the accuracy of the models, since it's applied directly or indirectly in all models and affects other parameters simultaneously. Higher spatial and spectral resolution remote sensing data may reduce uncertainty of fPAR up to 51.3%, which is essential to improve model accuracy. </span>