Dual-polarimetric radar estimators of liquid water content over Germany

Abstract

While the assimilation of dual-polarimetric radar observations in weather forecast models is promising especially for short-term forecasts of precipitation, the direct assimilation of polarimetric variables is still challenging because of the rather rudimentary appreciation of particle size and shape distributions by the models. Thus, current studies recede to assimilating model state variables derived from dual-polarimetric observables, such as hydrometeor mixing ratios. This study evaluates, improves and adapts estimators for liquid water content for their application to observations of the polarimetric C-band radar network of the German national meteorological service as a first step towards their assimilation in the ICON model. T-matrix simulations are used to derive polarimetric observables from a large data set of drop size distributions (DSDs) observed over Germany. Existing estimators based on reflectivity (Z), differential reflectivity (ZDR), specific attenuation (A) and specific differential phase (KDP) applied to this data set yield mostly unsatisfactory results and motivated the search for and development of improved estimators. The latter much better approximate the simulated data, and also mostly outperform the existing estimators when applied to real radar observations over Germany, although by a smaller degree. The new KDP-based estimator could only outperform existing algorithms, when KDP for azimuth-range intervals with negative KDPs were replaced by a Z-based KDP estimation. Further potential radar observation deficiencies in determining Z, ZDR, A and KDP motivated the development of a potentially more stable hybrid estimator based on the new LWC(Z,ZDR), LWC(A) and LWC(KDP) estimators. This hybrid estimator outperforms both the adapted and existing LWC estimators in terms of the correlation coefficient.