Estimation of Melting-Layer Cooling Rate from Dual-Polarization Radar: Spectral Bin Model Simulations

Abstract

Diabatic cooling from hydrometeor phase changes in the stratiform melting layer is of great interest to both operational forecasters and modelers for its societal and dynamical consequences. Attempts to estimate the melting-layer cooling rate typically rely on either the budgeting of hydrometeor content estimated from reflectivity Z or model-generated lookup tables scaled by the magnitude of Z in the bright band. Recent advances have been made in developing methods to observe the unique polarimetric characteristics of melting snow and the additional microphysical information they may contain. However, to date no work has looked at the thermodynamic information available from the polarimetric radar brightband signature. In this study, a one-dimensional spectral bin model of melting snow and a coupled polarimetric operator are used to study the relation between the polarimetric radar bright band and the melting-layer cooling rate. Simulations using a fixed particle size distribution (PSD) and variable environmental conditions show that the height and thickness of the bright band and the maximum brightband Z and specific differential phase shift KDP are all sensitive to the ambient environment, while the differential reflectivity ZDR is relatively insensitive. Additional simulations of 2700 PSDs based on in situ observations above the melting layer indicate that the maximum Z, ΔZ, and ZDR within the melting layer are poorly correlated with the maximum cooling rate while KDP is strongly correlated. Finally, model simulations suggest that, in addition to riming, concurrent changes in aggregation and precipitation intensity and the associated cooling may plausibly cause observed sagging brightband signatures.

Towards the connection between snow microphysics and melting layer: Insights from multi-frequency and dual-polarization radar observations during BAECC

“…Therefore, it appears that precipitation intensity is an important factor affecting the formation of the saggy bright band. This finding is inline with a recent simulation study (Carlin and Ryzhkov, 2019), which proposes that the saggy bright band can also be attributed to other factors, such as the aggregation process, the increased precipitation intensity and the sudden decrease of RH. For unrimed snow, the response of ρ hv to the melting is obviously later than X-band reflectivity, which indicates that the utilization of ρ hv for detecting the ML top should be applied with caution.…”

“…To obtain a general idea of how the ML is modulated by riming and aggregation, statistics of vertically-pointing radar observations were made. As the ML properties are modulated by precipitation intensity (Fabry and Zawadzki, 1995;Carlin and Ryzhkov, 2019), the observations were grouped by PR. In this paper, the vertical axis is shifted such that the reference height is the ML top.…”

“…For most cases, the relative humidity (RH) around the ML top is above 95% with no dependence on PR. Thus, the effect of dry air infiltration, e.g., decreasing reflectivity and ML thickness, descending dual-polarization measurements (Carlin and Ryzhkov, 2019), should be minimized. Considering the general aspects of Fig.…”

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

“…The use of simple Lagrangian spectral bin models combined with PRFOs has also proven to be very efficient for studying the mechanisms behind the "polarimetric fingerprints" of individual microphysical processes. These include models for size sorting (Kumjian and Ryzhkov [83,84]), evaporation (Kumjian and Ryzhkov [85]), freezing of raindrops in convective updrafts (Kumjian et al [86]), melting of hail (Ryzhkov et al [22]), and melting of snow (Carlin and Ryzhkov [87]). As an example, Kumjian and Ryzhkov [84] adequately reproduced the ubiquitous polarimetric signatures of size sorting, manifested as enhanced Z DR combined with low Z H and K DP in rain, using an idealized 2D bin model of raindrop fallout.…”

“…Carlin et al [108] and Carlin and Ryzhkov [87] suggested a new paradigm of using polarimetric radar data for thermodynamic retrievals of warming and cooling rates associated with latent heat release and absorption. The rate of change of the environmental temperature due to latent heating can be described by (Grim et al [109]):…”