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Construction of surface boundary conditions for regional climate modeling in China by using the remote sensing data

机译:利用遥感数据构建中国区域气候建模的地表边界条件

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The continuing rise in atmospheric CO2 is considered as a main cause of the future changes in global climate. Predicted climate changes include an increase in mean annual air temperature and alterations in precipitation pattern and cloud cover. Elevated atmospheric CO2 and climate changes are expected to influence the ecosystems. The regional climate models (RCMs) will likely remain primary tools for climate prediction in the foreseeable future. The importance of RCMs is increasing in addressing scientific problems associated with climate variability, changes, and impacts at regional scales. The RCMs have been also used in climate impact studies on ecosystems, especially in agricultural crops by generating climate scenarios for input to crop models. With a large volume of satellite remote sensing data of the earth terrestrial surface becoming available, precisely monitoring the dynamics of the land surface state variables for agricultural and land use management becomes possible6. With the effort to study the climate crop interactions we plan to use a CWRF model (a climate extension of the Weather Research and Forecasting model-WRF) developed by the Illinois State Water Survey to form the climate scenarios. The WRF model is based upon the most advanced supercomputing technologies and promises greater efficiency in computation and flexibility in new module incorporation. This extension inclusively incorporates all WRF functionalities for numerical weather predictions while enhancing the capability for climate applications. To represent the surface-atmosphere interactions the CWRF requires specification of surface boundary conditions (SBCs) over both land and oceans. A comprehensive set of SBCs based on best observational data is desired for CWRF general applications for all effective, dynamically coupled or uncoupled, combinations of the surface modules, as well as for any specific region of the world. This report followed the approach of Liang et al. presents a preliminary work to construct vegetative SBCs for the CWRF modeling effort in China domain by using remote sensing data from TM, AVHRR, MODIS which are freely available. The full list of the CWRF SBCs was defined by Liang.
机译:大气二氧化碳的持续增长被认为是全球气候未来变化的主要原因。预测的气候变化包括平均年度空气温度和降水模式和云盖的变化的增加。预计大气二氧化碳和气候变化升高会影响生态系统。区域气候模型(RCMS)可能会在可预见的未来留在气候预测中的主要工具。在解决与气候变异性,变化和区域尺度的影响相关的科学问题方面,RCMS的重要性正在增加。 RCMS也用于气候影响研究生态系统,尤其是农作物在农业作物中,通过为裁剪模型产生气候情景。随着地球陆地表面的大量卫星遥感数据可用,精确地监测农业和土地利用管理的土地表面变量的动态变量可能6。随着研究气候作物的互动,我们计划使用伊利诺伊州水上调查制定的CWRF模型(天气研究和预测模型-WRF的气候延长),以形成气候情景。 WRF模型基于最先进的超级计算技术,并承诺在新模块掺入中的计算和灵活性效率更高。该延伸包层包含对数值天气预报的所有WRF功能,同时增强气候应用的能力。表示表面气氛相互作用CWRF在陆地和海洋上需要规范表面边界条件(SBC)。对于所有有效,动态耦合或解耦,表面模块的组合以及世界的任何特定区域,CWRF一般应用需要一种基于最佳观测数据的全面的SBCS。这份报告遵循梁等人的方法。通过使用自由可用的TM,AVRR,MODIS,构建中国域中的CWRF建模努力的初步工作来构建中国域中的CWRF建模努力。 CWRF SBCS的完整列表由梁定义。

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