Surface soil moisture and vegetation optical depth (VOD), as an indicator of vegetation wet biomass, from passive microwave remote sensing have been increasingly applied in global ecology and climate research. Both soil moisture and VOD are retrieved from satellite brightness temperature measurements assuming a zeroth order radiative transfer model, commonly known as the tau-omega model. In this model the emission of a vegetated surface is dependent on soil moisture, vegetation absorption and vegetation scattering. Vegetation scattering is normally represented by the single scattering albedo, ω, and is commonly assumed to be a time-invariant calibration parameter to achieve high accuracy in soil moisture estimation. Therefore, little is known about ω dynamics in the context of its ecological information content. Furthermore, VOD and ω are functions of more fundamental absorption and scattering coefficients κ_a and κ_s. In this study, we retrieve both VOD and ω as well as κ_a and κ_s in two separate tau-omega model frameworks using known soil moisture information. Our sensitivity analysis confirms that vegetation attenuation has a strong impact on the sensitivity of the retrieval to noise. If vegetation attenuation approaches zero, ω is weakly constrained, which leads to strong ω dynamics. If vegetation attenuation is very high, VOD, κ_a and κ_s are increasingly less constrained and susceptible to noise, while ω becomes quasi time-invariant. Coinciding with our sensitivity study, global retrievals from SMAP brightness temperatures exhibit large ω dynamics in drylands and deserts, decreasing rapidly with increasing vegetation cover. In drylands ω might peak during the dry season at the seasonal VOD minimum. With increasing vegetation attenuation, ω dynamics start to follow leaf phenology before they transition to a nearly time-invariant ω in forested areas. VOD, κ_a and κ_s follow the dynamics of wet biomass and peak after the maximum of leaf area index and precipitation. Our results suggest that zeroth order scattering is generally time-invariant over a majority of the global vegetated areas. In general, time dynamic ω and κ_s might provide additional information on the state of the vegetation canopy, which can be valuable for biosphere studies and relevant for the parameterization of vegetation scattering in soil moisture retrievals.

表层土壤水分和植被光学深度（VOD）作为植被湿生物量的指标，被动微波遥感在全球生态和气候研究中得到越来越多的应用。土壤水分和 VOD 都是从卫星亮度温度测量中获取的，假设采用零阶辐射传递模型，通常称为 tau-omega 模型。在该模型中，植被表面的排放取决于土壤湿度、植被吸收和植被散射。植被散射通常由单次散射反照率ω 表示，并且通常被假定为时不变校准参数，以实现土壤水分估计的高精度。因此，我们对ω知之甚少动态在其生态信息内容的背景下。此外，VOD 和ω是更基本的吸收和散射系数κ _a和κ _{s 的}函数。在这项研究中，我们使用已知的土壤水分信息在两个单独的 tau-omega 模型框架中检索 VOD 和ω以及κ _a和κ _s。我们的敏感性分析证实，植被衰减对检索对噪声的敏感性有很大影响。如果植被衰减接近于零，则ω受到弱约束，从而导致ω强动力学。如果植被衰减非常高，VOD、κ _a和κ _s的约束越来越少并且容易受到噪声的影响，而ω变得准时不变。与我们的敏感性研究一致，从 SMAP 亮度温度的全球反演在旱地和沙漠中表现出很大的ω动态，随着植被覆盖度的增加而迅速下降。在旱地，ω可能在旱季达到季节性 VOD 最小值。随着植被衰减的增加，ω动力学开始遵循叶片物候，然后才过渡到森林区域中几乎不随时间变化的ω。VOD、κ _a和κ _s遵循湿生物量的动态变化，并在叶面积指数和降水量达到最大值后达到峰值。我们的结果表明，零阶散射在大多数全球植被区域上通常是时不变的。通常，时间动态ω和κ _s可能提供有关植被冠层状态的附加信息，这对于生物圈研究很有价值，并且与土壤水分反演中植被散射的参数化相关。