TY - JOUR
T1 - A moment-based polarimetric radar forward operator for rain microphysics
AU - Kumjian, Matthew R.
AU - Martinkus, Charlotte P.
AU - Prat, Olivier P.
AU - Collis, Scott
AU - Van Lier-Walqui, Marcus
AU - Morrison, Hugh C.
N1 - Funding Information:
Acknowledgments. This work was funded by U.S. DOE Atmospheric System Research Grant DE-SC0016579. The National Center for Atmospheric Research is sponsored by the National Science Foundation. Disdrometer data were obtained from the Atmospheric Radiation Measurement (ARM) Climate Research Facility Data Archive in Oak Ridge, Tennessee, United States, compiled and maintained by M. Bartholomew. Argonne National Laboratory’s work was supported by the U.S. Department of Energy, Office of Science, Office of Biological and Environmental Research, under Contract DE-AC02-06CH11357. We thank the anonymous reviewers for their helpful suggestions and comments that improved the clarity of the manuscript.
Publisher Copyright:
© 2019 American Meteorological Society.
PY - 2019/1/1
Y1 - 2019/1/1
N2 - There is growing interest in combining microphysical models and polarimetric radar observations to improve our understanding of storms and precipitation. Mapping model-predicted variables into the radar observational space necessitates a forward operator, which requires assumptions that introduce uncertainties into model-observation comparisons. These include uncertainties arising from the microphysics scheme a priori assumptions of a fixed drop size distribution (DSD) functional form, whereas natural DSDs display far greater variability. To address this concern, this study presents a moment-based polarimetric radar forward operator with no fundamental restrictions on the DSD form by linking radar observables to integrated DSD moments. The forward operator is built upon a dataset of >200 million realistic DSDs from one-dimensional bin microphysical rain-shaft simulations, and surface disdrometer measurements from around the world. This allows for a robust statistical assessment of forward operator uncertainty and quantification of the relationship between polarimetric radar observables and DSD moments. Comparison of ''truth'' and forward-simulated vertical profiles of the polarimetric radar variables are shown for bin simulations using a variety of moment combinations. Higher-order moments (especially those optimized for use with the polarimetric radar variables: the sixth and ninth) perform better than the lower-order moments (zeroth and third) typically predicted by many bulk microphysics schemes.
AB - There is growing interest in combining microphysical models and polarimetric radar observations to improve our understanding of storms and precipitation. Mapping model-predicted variables into the radar observational space necessitates a forward operator, which requires assumptions that introduce uncertainties into model-observation comparisons. These include uncertainties arising from the microphysics scheme a priori assumptions of a fixed drop size distribution (DSD) functional form, whereas natural DSDs display far greater variability. To address this concern, this study presents a moment-based polarimetric radar forward operator with no fundamental restrictions on the DSD form by linking radar observables to integrated DSD moments. The forward operator is built upon a dataset of >200 million realistic DSDs from one-dimensional bin microphysical rain-shaft simulations, and surface disdrometer measurements from around the world. This allows for a robust statistical assessment of forward operator uncertainty and quantification of the relationship between polarimetric radar observables and DSD moments. Comparison of ''truth'' and forward-simulated vertical profiles of the polarimetric radar variables are shown for bin simulations using a variety of moment combinations. Higher-order moments (especially those optimized for use with the polarimetric radar variables: the sixth and ninth) perform better than the lower-order moments (zeroth and third) typically predicted by many bulk microphysics schemes.
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U2 - 10.1175/JAMC-D-18-0121.1
DO - 10.1175/JAMC-D-18-0121.1
M3 - Article
AN - SCOPUS:85060913484
VL - 58
SP - 113
EP - 130
JO - Journal of Applied Meteorology and Climatology
JF - Journal of Applied Meteorology and Climatology
SN - 1558-8424
IS - 1
ER -