LAUSR

In this study, the CERES (Crop Estimation through Resource and Environment Synthesis) crop model was coupled with CLM3.5, the land module of the regional climate model RegCM4. The new coupled model was named RegCM4 CERES; and in this model, crop type was further divided into winter wheat, spring wheat, spring maize, summer maize, early rice, late rice, single rice, and other crop types based on each distribution fraction. The development of each crop sub-type was simulated by the corresponding crop model separately, with each planting and harvesting date. A simulation test using RegCM4 CERES was conducted across China from 1999 to 2008; a control test was also performed using the original RegCM4. Data on crop LAI (leaf area index), soil moisture at 10 cm depth, precipitation, and 2 m air temperature were collected to evaluate the performance of RegCM4 CERES. The evaluation provided comparison of single-station time series, regional distributions, seasonal variations, and statistical indices for RegCM4 CERES. The results revealed that the coupled model had an excellent ability to simulate the phonological changes and spatial variations in crops. The consideration of dynamic crop development in RegCM4 CERES corrected the wet bias of the original RegCM4 over North China and the cold bias over South China. However, the degree of improvement was minimal and the statistical indices for RegCM4 CERES were roughly the same as the original RegCM4.概要本文中, CERES作物模型(Crop Estimation through Resource and Environment Synthesis)与区域气候模式RegCM4的陆面模块CLM3.5实现了双向耦合. 新耦合模式被命名为RegCM4_CERES, 在该模式中, 网格内的作物类型根据实际作物分布比例被进一步划分为冬小麦、春小麦、春玉米、夏玉米、早稻、晚稻、单季稻与其他作物类型八类. 每一类作物次类型根据各自的种植、收获日期利用相应的作物模型进行独立模拟. 本文利用新建立的RegCM4_CERES模式, 针对中国区域进行了自1999年至2008年的模拟试验. 与之相对应地, 本文也利用原RegCM4模式进行了相同设置的控制试验. 台站观测的叶面积指数、10cm深土壤湿度、降水、2m高气温等要素被用于RegCM4_CERES模式的性能评估. 评估工作主要提供了RegCM4_CERES模式在单站时间序列、区域空间分布、典型区内季节变率及各统计量等方面的评估结果. 结果表明, RegCM4_CERES模式在模拟各类作物的物候变化与空间分布方面有着优秀的模拟能力. 考虑了作物生长发育过程的RegCM4_CERES模式纠正了原RegCM4模式在华北的湿偏差和华南的冷偏差, 但其改善程度十分有限, 两个模式在典型区内的统计指数几乎保持一致.