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The Precipitation Imaging Package: Assessment of Microphysical and Bulk Characteristics of Snow
Atmosphere ( IF 2.5 ) Pub Date : 2020-07-24 , DOI: 10.3390/atmos11080785
Claire Pettersen , Larry F. Bliven , Annakaisa von Lerber , Norman B. Wood , Mark S. Kulie , Marian E. Mateling , Dmitri N. Moisseev , S. Joseph Munchak , Walter A. Petersen , David B. Wolff

Remote-sensing observations are needed to estimate the regional and global impacts of snow. However, to retrieve accurate estimates of snow mass and rate, these observations require augmentation through additional information and assumptions about hydrometeor properties. The Precipitation Imaging Package (PIP) provides information about precipitation characteristics and can be utilized to improve estimates of snowfall rate and accumulation. Here, the goal is to demonstrate the quality and utility of two higher-order PIP-derived products: liquid water equivalent snow rate and an approximation of volume-weighted density called equivalent density. Accuracy of the PIP snow rate and equivalent density is obtained through intercomparison with established retrieval methods and through evaluation with colocated ground-based observations. The results confirm the ability of the PIP-derived products to quantify properties of snow rate and equivalent density, and demonstrate that the PIP produces physically realistic snow characteristics. When compared to the National Weather Service (NWS) snow field measurements of six-hourly accumulation, the PIP-derived accumulations were biased only +2.48% higher. Additionally, this work illustrates fundamentally different microphysical and bulk features of low and high snow-to-liquid ratio events, through assessment of observed particle size distributions, retrieved mass coefficients, and bulk properties. Importantly, this research establishes the role that PIP observations and higher-order products can serve for constraining microphysical assumptions in ground-based and spaceborne remotely sensed snowfall retrievals.

中文翻译:

降水成像软件包:雪的微物理和体积特征评估

需要遥感观测来估计雪的区域和全球影响。但是,为了获取雪量和雪率的准确估计值,这些观测结果需要通过附加信息和有关水凝物特性的假设进行补充。降水成像软件包(PIP)提供有关降水特征的信息,可用于改善降雪率和累积量的估算。在这里,目标是证明两种更高级别的PIP衍生产品的质量和实用性:液态水当量雪率和体积加权密度的近似值(当量密度)。通过与已建立的取回方法进行对比,并与位于同一地点的地面观测进行评估,可以得出PIP降雪率和当量密度的准确性。结果证实了PIP衍生产品量化降雪率和等效密度特性的能力,并证明了PIP具有物理上真实的降雪特征。与国家气象局(NWS)六个小时积雪的雪场测量结果相比,PIP产生的积雪仅高出+ 2.48%。此外,这项工作通过评估观察到的粒度分布,检索到的质量系数和体积特性,说明了低和高雪液比事件的根本不同的微观物理特征和体积特征。重要的是,这项研究确立了PIP观测和高阶产品可以用于约束地面和星载遥感降雪检索中的微物理假设的作用。
更新日期:2020-07-24
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