Collaborative Research: A Land Surface Model Hind-Cast for the Terrestrial Arctic Drainage System

这项研究将结合联合收割机数据合成和陆地表面建模，为北极陆地排水的陆地表面状态变量（雪水当量、土壤湿度、土壤温度）以及水分和能量通量（感热、潜热和地热;辐射）收集尽可能好的时间序列（20年以上）。强迫场的开发将部分借鉴NSF正在进行的一项名为“北极-RIMS”的工作，该工作旨在对北极陆地水文收支进行历史分析和监测。目前的努力既补充了北极区域信息系统，又为下一代监测和预测能力奠定了基础。生成的时间序列将用于解决显热通量和蒸散的时空变化，陆面对降水的反馈，以及夏季北极锋区的发展。这项研究将试图通过将新的ERA-40大气再分析项目的输出与网格化的现场观测和卫星数据流相结合，在泛北极区域产生尽可能高质量的强迫模型。主要的挑战包括在不同的本地空间和时间分辨率的变量的时间序列之间保持物理一致性，并提供现实的昼夜周期。 所提出的工作的一个特别新颖的方面将是使用多模型集成方法。将使用五种不同的陆面模型，所有这些模型都在陆面参数化方案相互比较项目实验2 e下进行了广泛的北极应用测试。每个输出变量的多模式最小二乘模型集合平均值应上级于任何一个最小二乘模型的单次运行所提供的值，这些数据也将有助于模式验证工作，如北极区域气候模式相互比较项目，并为大气模式相互比较项目提供高纬度评价数据来源。该项目将通过支持一名研究生和博士后来促进教育目标。这项研究和相关项目的结果将作为在科罗拉多大学教授的北极气候系统研讨班的一部分。

This study will combine data synthesis and land surface modeling to assemble the best possible time series (20+ years) for the Arctic terrestrial drainage of land surface state variables (snow water equivalent, soil moisture, soil temperature) and moisture and energy fluxes (sensible, latent, and ground heat; radiation). Development of forcing fields will draw in part from an ongoing NSF effort known as Arctic-RIMS, geared at historical analysis and monitoring of the Arctic terrestrial hydrologic budget. The present effort both complements Arctic-RIMS and lays groundwork for a next-generation monitoring and prediction capability. The generated time series will be used to address spatial-temporal variability in sensible heat flux and evapo-transpiration, land surface feedbacks on precipitation, and development of the summer Arctic frontal zone. This study will attempt to produce the best possible quality model forcing over the pan-Arctic domain by blending output from the new ERA-40 atmospheric reanalysis project with gridded in-situ observations and satellite data streams. Major challenges include maintaining physical consistency between time series of variables at different native spatial and temporal resolutions and providing realistic diurnal cycles. A particularly novel aspect of the proposed work will be use of a multi-model ensemble approach. Five different Land Surface Models will be used, all of which have been extensively tested for Arctic applications under the Project for Intercomparison of Land-Surface Parameterization Schemes (PILPS) Experiment 2e. The multi-model LSM ensemble average for each output variable should be superior to the values provided by a single run with any one LSM.The data will also be useful for model validation efforts, such as the Arctic Regional Climate Model Inter-comparison Project, and in providing a source of high latitude evaluation data for the Atmospheric Model Inter-comparison Project. The project will contribute to educational goals through support of a graduate student and post-docs. Results from this study and related projects will be used as part of seminar course on the Arctic climate system to be taught at University of Colorado.