five

Estimation of Melting-Layer Cooling Rate from Dual-Polarization Radar: Spectral Bin Model Simulations Journal of Applied Meteorology and Climatology

收藏
NOAA Institutional Repository2025-04-04 更新2026-04-25 收录
下载链接:
https://doi.org/10.1175/JAMC-D-18-0343.1
下载链接
链接失效反馈
官方服务:
资源简介:
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. Grant no. NA11OAR4320072
提供机构:
NOAA
创建时间:
2025-04-04
二维码
社区交流群
二维码
科研交流群
商业服务