Monday, 28 August 2023
Boundary Waters (Hyatt Regency Minneapolis)
In this study, we present our findings on the properties of melting particles utilizing the observations of the Precipitation Imaging Package (PIP), a video disdrometer located in Hyytiälä, Finland. We analyzed over a hundred melting snow events that occurred during a span of seven years, linking changes in the properties of melting particles, such as their shape and fall velocity, with the corresponding environmental conditions retrieved from mast profile observations connected to model output.
To better understand how melting affects particle properties, we also studied the particle properties as a function of the estimated melted mass fraction using a simple one-dimensional melting layer model. Our aim was to parameterize the particle properties influenced by melting. Although with this instrumentation, we are unable to observe the melting progress of individual particles, we can statistically resolve the changes in particle characteristics due to melting process by sampling particles in different stages of melting.
Currently, parameterizations of melting particles used typically in modeling, such as changes in fall velocity or shape as a function of melted mass fraction, are mainly based on just a few studies and examples. For example, the widely-used parameterization for changes in fall velocity as a function of melting is based on the study of only 45 falling aggregates (Mitra et al., 1990), and possible changes in fall behavior due to riming are not considered. Mitra et al. found that the fall velocity transition is non-linear with respect to melting fraction, exhibiting a slow linear increase for small fractions and a rapid increase for fractions larger than 0.7. Our preliminary analysis of our observations also supports this abrupt increase in fall speeds.
In the upcoming conference, we will present a more detailed analysis performed particle by particle basis to capture the threshold of melted mass fraction where this change of fall velocity occurs and show its dependence on the particle habit. Our goal is to test the parameterization in the 1D-modeled profiles and through forward-modeling compare the retrieved profiles to the radar-observed ones. Overall, our study sheds light on the properties of melting particles and provides insights for improving current parameterizations used in modeling.
To better understand how melting affects particle properties, we also studied the particle properties as a function of the estimated melted mass fraction using a simple one-dimensional melting layer model. Our aim was to parameterize the particle properties influenced by melting. Although with this instrumentation, we are unable to observe the melting progress of individual particles, we can statistically resolve the changes in particle characteristics due to melting process by sampling particles in different stages of melting.
Currently, parameterizations of melting particles used typically in modeling, such as changes in fall velocity or shape as a function of melted mass fraction, are mainly based on just a few studies and examples. For example, the widely-used parameterization for changes in fall velocity as a function of melting is based on the study of only 45 falling aggregates (Mitra et al., 1990), and possible changes in fall behavior due to riming are not considered. Mitra et al. found that the fall velocity transition is non-linear with respect to melting fraction, exhibiting a slow linear increase for small fractions and a rapid increase for fractions larger than 0.7. Our preliminary analysis of our observations also supports this abrupt increase in fall speeds.
In the upcoming conference, we will present a more detailed analysis performed particle by particle basis to capture the threshold of melted mass fraction where this change of fall velocity occurs and show its dependence on the particle habit. Our goal is to test the parameterization in the 1D-modeled profiles and through forward-modeling compare the retrieved profiles to the radar-observed ones. Overall, our study sheds light on the properties of melting particles and provides insights for improving current parameterizations used in modeling.
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