Knowledge Resource Center for Ecological Environment in Arid Area
| 遥感地表变量在黄河源区陆-气相互作用数值模拟中的应用研究 | |
| 史小康 | |
| 出版年 | 2010 |
| 学位类型 | 博士 |
| 导师 | 文军 |
| 学位授予单位 | 中国科学院大学 |
| 中文摘要 | 本文利用WRF-Noah模式结合卫星遥感地表变量对黄河源区进行了较详细的陆-气相互作用数值模拟研究，并对数据同化方法也进行了相关研究。\n\n 在陆-气相互作用研究方面：（1）利用WRF模式开展模拟试验表明不同下垫面对地表反照率-降水的响应程度不同，最大的是黄河源区下游的草场区域；采用MODIS地表反照率产品在月尺度上能够更准确地模拟降水量。（2）黄河源区植被非均匀分布及退化对对流环境有重要影响：晴天时，植被覆盖度大值区外围植被覆盖度梯度最大的地方有利于对流的发生，雨天时，植被覆盖度大值区可以出现辐合中心，有利于增强对流强度；晴天和雨天边界层发展的差异进一步说明植被覆盖在晴天相比雨天有更大的作用；雨天时，植被覆盖度的增加可使得大气中水汽含量、低云量增加，云底高度降低，暖雨过程作用增大；使用MODIS数据获得的新植被覆盖度资料改善了近地表温湿物理量的模拟效果。\n 在遥感土壤湿度数据的同化研究方面：（1）将颜锋华等土壤湿度反演理论模型耦合到WRF-Noah模式，并采用牛顿松弛逼近法同化反演获得的土壤湿度数据，扩大了模式利用亮温资料的能力，对沙漠地区土壤湿度的模拟改善最为明显，也改善了土壤湿度模拟值随时间的变化趋势。（2）设计了一个基于EnKF和单点Noah陆面模型的同化方案，考虑了初始场、气象强迫场和模式参数误差对同化效果的影响。发现模式参数误差对土壤湿度同化的性能有很大的影响；同化高时间分辨率的遥感土壤湿度资料有利于改善同化效果。（3）应用并改进了Reichle等自适应EnKF算法，发现当beta参数取值为1.02时，数据同化效果最好；通过迭代求解初始时刻模式误差方差和观测误差方差，改进了该算法的收敛速度。 |
| 英文摘要 | In this paper, the land-atmosphere interactions in the Source Water Region of the Yellow River (SWRYR) was simulated by using the WRF-Noah numerical model with assimilating some satellite-derived land surface variables, and the simulation results and assimilation algorithms were discussed in detail. The main research conclusions are listed as follows:\n In the side of land-atmosphere interactions: (1) For the same changes of land surface albedo in the SWRYR, the simulated changes of precipitation amounts were different, especially in the downriver grassland; When the MODIS derived albedo data was used in the WRF model, the simulated accuracy of monthly precipitations was improved. (2) The distribution and variation of vegetation fractional coverage showed different impacts on the convective environments and precipitations in the fair and rainy weather cases. In the fair weather case, there was a radiative flow center in the highly vegetation coverage regions, and the places where had the biggest gradient of vegetation fraction were apt to the generation of convections; In the rainy case, there was a convergent center in the highly vegetation coverage regions, which could prompt the strength of convections. Development of the boundary layer suggested that the vegetation fraction played a more important role in the fair weather case. In the rainy case, the increasing of vegetation fraction enhanced the vapor ratio in atmosphere, and thus more hydrometeors. Meanwhile, the content of low cloud increased and the bottom of low cloud declined. When the new MODIS vegetation fractional coverage data was applied, the RMSEs of simulated 2 m height air temperature and relative humidity were both decreased.\n In the other side of assimilation algorithms: (1) An estimation model of soil moisture from the AMSR-E brightness temperature data was coupled into the WRF-Noah numerical model by using the Newtonian relaxation method for improving the model’s simulation ability for soil moisture. It was found that the simulated soil moisture values were improved most in desert areas and the differences between simulated and observed soil moisture were decreased slightly. (2) A one-dimensional land data assimilation scheme was proposed based on the ensemble Kalman filter (EnKF) and the Noah LSM, In these simulations, the errors in initial conditions, meteorological forcing data and model parameters were considered, and we found that the inappropriate assumptions of model parameter error degraded the assimilation results mostly and high-time resolution data of satellite derived soil moisture was helpful for getting the better soil moisture profiles. (3)The Reichle’s adaptive EnKF method was applied in Noah LSM for adjusting the model error covariance and the observation error covariance from the rude values to their true values, respectively. When the beta parameter equaled to 1.02, the Reichle procedure got the best results. And the convergence rate of Reichle procedure was improved by using better initial error covariance achieved by iterative computations at the initial time. |
| 中文关键词 | 黄河源区 ; WRF-Noah模式 ; 数值模拟 ; 遥感 ; 数据同化 |
| 语种 | 中文 |
| 国家 | 中国 |
| 来源学科分类 | 大气物理学与大气环境 |
| 来源机构 | 中国科学院西北生态环境资源研究院 |
| 资源类型 | 学位论文 |
| 条目标识符 | http://119.78.100.177/qdio/handle/2XILL650/286853 |
| 推荐引用方式 GB/T 7714 | 史小康. 遥感地表变量在黄河源区陆-气相互作用数值模拟中的应用研究[D]. 中国科学院大学,2010. |
| 条目包含的文件 | 条目无相关文件。 | |||||
| 个性服务 |
| 推荐该条目 |
| 保存到收藏夹 |
| 导出为Endnote文件 |
| 谷歌学术 |
| 谷歌学术中相似的文章 |
| [史小康]的文章 |
| 百度学术 |
| 百度学术中相似的文章 |
| [史小康]的文章 |
| 必应学术 |
| 必应学术中相似的文章 |
| [史小康]的文章 |
| 相关权益政策 |
| 暂无数据 |
| 收藏/分享 |
除非特别说明，本系统中所有内容都受版权保护，并保留所有权利。
