The tau-omega model is expanded to properly simulate L-band microwave emission of the soil–snow–vegetation continuum through a closed-form solution of Maxwell’s equations, considering the intervening dry snow layer as a loss-less medium. The error standard deviations of a least-squared inversion are 0.1 and 3.5 for VOD and ground permittivity, over moderately dense vegetation and a snow density ranging from 100 to 400 kgm, considering noisy brightness temperatures with a standard deviation of 1 kelvin. Using the Soil Moisture Active Passive (SMAP) satellite observations, new global estimates of VOD and ground permittivity are presented over the Arctic boreal forests and permafrost areas. In the absence of dense observations of ground permittivity and VOD, the retrievals are causally validated using ancillary variables including ground temperature, above-ground biomass, tree height, and net ecosystem exchange of carbon dioxide. Time-series analyses promise that the new data set can expand our understanding of the land–atmosphere interactions and exchange of carbon fluxes over Arctic landscapes.

中文翻译：

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使用 SMAP 卫星数据对冰雪覆盖的北方森林和永久冻土景观的 L 波段植被光学深度和土壤介电常数进行全球估计

tau-omega 模型经过扩展，可以通过麦克斯韦方程组的封闭解来正确模拟土壤-雪-植被连续体的 L 波段微波发射，并将中间的干雪层视为无损介质。考虑到标准偏差为 1 开尔文的噪声亮度温度，在中等茂密的植被和 100 至 400 kgm 的雪密度范围内，VOD 和地面介电常数的最小二乘反演的误差标准偏差为 0.1 和 3.5。利用土壤湿度主动被动 (SMAP) 卫星观测，对北极北方森林和永久冻土地区的 VOD 和地面介电常数进行了新的全球估计。在缺乏对地面介电常数和 VOD 的密集观测的情况下，使用辅助变量（包括地面温度、地上生物量、树高和二氧化碳净生态系统交换）对反演进行因果验证。时间序列分析有望扩大我们对陆地-大气相互作用和北极景观碳通量交换的理解。