What Polarimetric Weather Radars Offer to Cloud Modelers: Forward Radar Operators and Microphysical/Thermodynamic Retrievals

Abstract

The utilization of polarimetric weather radars for optimizing cloud models is a next frontier of research. It is widely understood that inadequacies in microphysical parameterization schemes in numerical weather prediction (NWP) models is a primary cause of forecast uncertainties. Due to its ability to distinguish between hydrometeors with different microphysical habits and to identify “polarimetric fingerprints” of various microphysical processes, polarimetric radar emerges as a primary source of needed information. There are two approaches to leverage this information for NWP models: (1) radar microphysical and thermodynamic retrievals and (2) forward radar operators for converting the model outputs into the fields of polarimetric radar variables. In this paper, we will provide an overview of both. Polarimetric measurements can be combined with cloud models of varying complexity, including ones with bulk and spectral bin microphysics, as well as simplified Lagrangian models focused on a particular microphysical process. Combining polarimetric measurements with cloud modeling can reveal the impact of important microphysical agents such as aerosols or supercooled cloud water invisible to the radar on cloud and precipitation formation. Some pertinent results obtained from models with spectral bin microphysics, including the Hebrew University cloud model (HUCM) and 1D models of melting hail and snow coupled with the NSSL forward radar operator, are illustrated in the paper.

Microphysical Processes Producing High Ice Water Contents (HIWCs) in Tropical Convective Clouds during the HAIC-HIWC Field Campaign: Evaluation of Simulations Using Bulk Microphysical Schemes

“…The WRF model version 4.1.3 (Skamarock et al, 2019) is used to simulate the tropical oceanic MCS event on 26 May 2015. Two one-way nested domains with 3 and 1 km horizontal grid spacing and 51 vertical levels are adopted (Fig.…”

The future of Earth system prediction: Advances in model-data fusion

“…Examples that have been heavily used are radar simulators that include polarimetry and velocity ( 66 – 68 ) and satellite simulators that include infrared and passive microwave ( 69 – 71 ). These simulators support model evaluations targeting specific processes, particularly microphysical processes, that produce “fingerprints” in observations ( 72 ) that can be used to better understand and constrain processes and properties ( 73 , 55 ).…”

Climatology of the Vertical Profiles of Polarimetric Radar Variables and Retrieved Microphysical Parameters in Continental/Tropical MCSs and Landfalling Hurricanes

“…The error of the log(N t ) estimate varies between 0.7 and 1.0 (in log units). A more detailed discussion on the accuracy of the polarimetric retrievals ( 5)-( 10) can be found in Ryzhkov and Zrnic (2019), Ryzhkov et al (2020), and Bukovcic et al (2018Bukovcic et al ( , 2020.…”

“…The radar retrieval equations for computing microphysical variables in rain and ice which we utilize in our study can be found in Ryzhkov and Zrnic (2019, Chapter 11), Ryzhkov et al. (2020), Bukovcic et al. (2018, 2020), and Carlin et al.…”

“…A very important polarimetric variable, specific differential phase K DP , is estimated from a radial profile of Φ DP as a half of the radial derivative of Φ DP . Polarimetric radar measurements can be efficiently utilized for retrievals of key microphysical variables, such as precipitation fluxes, liquid water content (LWC) or ice water content (IWC), particle characteristic sizes, and their number concentrations.Polarimetric weather radars also offer a unique opportunity to optimize numerical weather prediction (NWP) models (Ryzhkov et al, 2020). The inability of existing microphysical parameterization schemes in the NWP models to adequately capture the complexity of various microphysical processes is commonly blamed as a main source of forecast uncertainties (e.g., Fan et al, 2017;Morrison et al, 2015Morrison et al, , 2020.…”