TY - JOUR
T1 - Simulated polarimetric fields of ice vapor growth using the adaptive habit model. Part II
T2 - A case study from the FROST experiment
AU - Sulia, Kara J.
AU - Kumjian, Matthew R.
N1 - Funding Information:
The authors thank Pat Kennedy, Steve Rutledge, Francesc Junyent, and Jim George (all at CSU) for aiding with the collection and processing of the CSU-CHILL data during FROST. Chris Davis (NCAR) and the ASP program are thanked for support of the FROST experiment. The authors would also like to extend their sincerest gratitude to the three anonymous reviewers who provided the necessary comments and discussion to help shape this work into its current form. KS was supported through an appointment under the SUNY 2020 Initiative. MK was supported by the National Science Foundation underGrant AGS-1143948 and the Department of Energy under Grant DE-SC0013953.
Publisher Copyright:
© 2017 American Meteorological Society.
PY - 2017/6/1
Y1 - 2017/6/1
N2 - A new adaptive habit model (AHM) grows ice crystals through vapor deposition while evolving ice particle properties, including shape and effective density. The AHM provides an opportunity to investigate observed microphysical processes through the computation of polarimetric variables and corroboration with microphysical model output. This study is unique because the polarimetric scattering calculations are computed using predicted microphysical parameters rather than a priori assumptions that are imposed within the scattering calculations in the forward simulator, allowing for a more effective comparison to radar observations. Through the simulation of a case in the Front Range of the Rocky Mountains in Colorado using the Advanced Research version of the Weather Research and Forecasting Model, it is found that the AHM approximates ice mass, shape, cloud vertical structure, and temporal evolution as reflected through polarimetric quantities compared to observations. AHM reflectivity magnitudes are similar to those observed with radar and are an improvement over spherical ice crystal assumptions. Further analyses are completed to examine the effect of microphysical processes on the evolution of the differential reflectivity and specific differential phase, both of which are simulated using the AHM. Simulations reveal a polarimetric response to ice crystal mass, number, size, density, and aspect ratio. While results reveal the need for model improvements (e.g., parameterizations for aggregation rate), testing forward-simulated radar fields against observations is a first step in the validation of model microphysical and precipitation processes.
AB - A new adaptive habit model (AHM) grows ice crystals through vapor deposition while evolving ice particle properties, including shape and effective density. The AHM provides an opportunity to investigate observed microphysical processes through the computation of polarimetric variables and corroboration with microphysical model output. This study is unique because the polarimetric scattering calculations are computed using predicted microphysical parameters rather than a priori assumptions that are imposed within the scattering calculations in the forward simulator, allowing for a more effective comparison to radar observations. Through the simulation of a case in the Front Range of the Rocky Mountains in Colorado using the Advanced Research version of the Weather Research and Forecasting Model, it is found that the AHM approximates ice mass, shape, cloud vertical structure, and temporal evolution as reflected through polarimetric quantities compared to observations. AHM reflectivity magnitudes are similar to those observed with radar and are an improvement over spherical ice crystal assumptions. Further analyses are completed to examine the effect of microphysical processes on the evolution of the differential reflectivity and specific differential phase, both of which are simulated using the AHM. Simulations reveal a polarimetric response to ice crystal mass, number, size, density, and aspect ratio. While results reveal the need for model improvements (e.g., parameterizations for aggregation rate), testing forward-simulated radar fields against observations is a first step in the validation of model microphysical and precipitation processes.
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U2 - 10.1175/MWR-D-16-0062.1
DO - 10.1175/MWR-D-16-0062.1
M3 - Article
AN - SCOPUS:85020107027
VL - 145
SP - 2303
EP - 2323
JO - Monthly Weather Review
JF - Monthly Weather Review
SN - 0027-0644
IS - 6
ER -