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

本研究将结合数据综合和地表模拟，为北极地表状态变量（雪水当量、土壤湿度、土壤温度）、水分和能量通量（感热、潜热、地热、辐射）的陆地排水组合尽可能最佳的时间序列（20年以上）。强迫场的发展将部分得益于美国国家科学基金会正在进行的一项名为Arctic- rim的努力，该努力旨在对北极陆地水文预算进行历史分析和监测。目前的工作既补充了arctic - rim，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研究感热通量和蒸发蒸腾的时空变化、地表对降水的反馈以及夏季北极锋面区的发展。本研究将尝试通过将新的ERA-40大气再分析项目的输出与网格化的原位观测和卫星数据流相结合，在泛北极地区产生尽可能高质量的模式强迫。主要的挑战包括在不同的本地空间和时间分辨率下保持变量时间序列之间的物理一致性，并提供真实的日周期。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地表面模式，所有这些模式都已在陆地表面参数化方案相互比较项目（PILPS）实验2e下进行了广泛的北极应用测试。每个输出变量的多模型LSM集成平均值应该优于使用任何一个LSM单次运行所提供的值。这些数据还将有助于模式验证工作，例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估数据的来源。该项目将通过研究生和博士后的支持来促进教育目标。这项研究和相关项目的结果将作为科罗拉多大学北极气候系统研讨会课程的一部分。

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.