The Precipitation Imaging Package: Assessment of Microphysical and Bulk Characteristics of Snow

Abstract

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.

Snowfall-Rate Retrieval for K- and W-Band Radar Measurements Designed in Hyytiälä, Finland, and Tested at Ny-Ålesund, Svalbard, Norway

“…In this way, we will gain further insight into the spatial variability of precipitation in Svalbard and also show the broader applicability of our method. In this respect, we have also recently applied the newly developed K-band Z e -S relationship to measurements of a site in Marquette, Michigan, where MRR measurements with collocated PIP observations were available (Pettersen et al 2020). Those results (not shown) are promising and will be investigated in more detail in the future.…”

The Influence of Atmospheric Rivers on Cold‐Season Precipitation in the Upper Great Lakes Region

“…The 24‐GHz vertically‐pointing MRR measures reflectivity, Doppler velocity, and Doppler spectral width (Klugmann et al., 1996). The PIP is a video disdrometer that takes images of falling particles and provides particle size distributions, fall speeds, and precipitation rates (A. J. Newman et al., 2009; Pettersen, Bliven, et al., 2020). Phase separation of PIP precipitation into rain and snow rates is available as a higher‐order‐derived data product (Pettersen et al., 2021), including during mixed precipitation conditions, as well as from NWS observations.…”

Characteristics of Snow Particle Size Distribution in the PyeongChang Region of South Korea

“…The Precipitation Imaging Package (PIP) [28,39] is a high-speed camera that records grayscale images of particles at 380 frames per second as they fall over its field of view (64 × 48 mm). These images allow PIP to use this information to extract particle size and velocity.…”

“…Similar to rain PSD, understanding snow PSD is of great importance in remote sensing and characterizing the microphysics of snowstorms [24]. The study of snow PSD is a challenging and ongoing research topic and a few papers are available [25][26][27][28][29].…”

“…There is few size-density relationships mentioned in the previous studies which describe the density of snow [30][31][32]. However, these relationships cannot describe the density of snow events captured in the PyeongChang region, because snow particles vary greatly in different topography and events [26][27][28][30][31][32][33][34][35]. In this study, we use aerodynamic relationships to determine the density of snow, then study the characteristics of snow PSD at different density and liquid water equivalent snowfall rates (S) classes.…”