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4篇 您的检索式:作者名="ZHONGDA ZENG"
    题名 作者 年代 出处 被引量
1Comparing chemical fingerprints of herbal medicines using modified window target-testing factor analysis显示文摘ZHONGDA ZENG YIZENG LIANG CHENGJIAN XU 2005Anal Bioanal Chem2005,,381:1
2Alternative moving window factor analysis for comparison analysis between complex chromatographic data显示文摘ZENG Zhongda LIANG Yizeng WANG Yali 2006J Chromatogr2006,1107,12:1
3Alternative moving window factor analysis for comparison analysis between complex chromatographic data 显示文摘Zeng Zhongda Liang Yizeng Wang Yali 2006J Chromatogr A2006,1107,:1
4Assessment of Crop Yield in China Simulated by Thirteen Global Gridded Crop Models显示文摘Global gridded crop models(GGCMs) have been broadly applied to assess the impacts of climate and environmental change and adaptation on agricultural production. China is a major grain producing country, but thus far only a few studies have assessed the performance of GGCMs in China, and these studies mainly focused on the average and interannual variability of national and regional yields. Here, a systematic national-and provincial-scale evaluation of the simulations by13 GGCMs [12 from the GGCM Intercomparison(GGCMI) project, phase 1, and CLM5-crop] of the yields of four crops(wheat, maize, rice, and soybean) in China during 1980–2009 was carried out through comparison with crop yield statistics collected from the National Bureau of Statistics of China. Results showed that GGCMI models generally underestimate the national yield of rice but overestimate it for the other three crops, while CLM5-crop can reproduce the national yields of wheat, maize, and rice well. Most GGCMs struggle to simulate the spatial patterns of crop yields. In terms of temporal variability, GGCMI models generally fail to capture the observed significant increases, but some can skillfully simulate the interannual variability. Conversely, CLM5-crop can represent the increases in wheat, maize, and rice, but works less well in simulating the interannual variability. At least one model can skillfully reproduce the temporal variability of yields in the top-10 producing provinces in China, albeit with a few exceptions. This study, for the first time, provides a complete picture of GGCM performance in China, which is important for GGCM development and understanding the reliability and uncertainty of national-and provincial-scale crop yield prediction in China.Dezhen YIN Fang LI Yaqiong LU Xiaodong ZENG Zhongda LIN Yanqing ZHOU 2024Advances in Atmospheric Sciences2024,41,3:0
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