How well do passive microwave algorithms estimate vertical profiles of precipitation?

A previous study concluded that the use of the vertical precipitation profile helps to improve the estimation of the sub-hourly accumulation of surface precipitation (Utsumi et al., 2019). Some of the passive microwave (PMW) precipitation retrieval algorithms have the capability to estimate the vertical profile of precipitation as well as surface precipitation rate. However, PMW-based estimates of the vertical precipitation profiles have not been as thoroughly evaluated as the surface precipitation rate.

Here, we investigate the vertical precipitation profiles estimated by PMW-based algorithms; using the emissivity principal component-based algorithm (Turk et al., 2018) and the Global Precipitation Measurement (GPM) Microwave Imager (GMI) Level 2 product (GPM/GMI 2A-GPROF version V05A). PMW-based vertical profile estimates for GPM/GMI footprints are validated with collocating GPM's radar-PMW combined product (GPM/2BCMB version 06A). Case studies indicate that the general structures of the vertical precipitation profiles are well replicated by PMW-based algorithms. Global scale comparison shows that the performance of PMW algorithm for representing vertical precipitation profile tends to be better for regions with higher surface precipitation intensity, which could be due to the higher contrast between the precipitation and background signals in the PMW observations. When compared for the same surface precipitation intensity, better performance is found in mid- and high latitude regions than in tropical regions. Also, it is found that the performance of the vertical profile estimates tends to be correlated with that of the surface precipitation estimates.

[References]

Utsumi, N., H. Kim, F. J. Turk, and Ziad. S. Haddad, 2019: Improving Satellite-Based Subhourly Surface Rain Estimates Using Vertical Rain Profile Information. J. Hydrometeor., 20, 1015-1026, https://doi.org/10.1175/JHM-D-18-0225.1.

Turk, F. J., Z. S. Haddad, P. Kirstetter, Y. You, and S. Ringerud, 2018: An observationally based method for stratifying a priori passive microwave observations in a Bayesian-based precipitation retrieval framework. Quarterly Journal of the Royal Meteorological Society, https://doi.org/10.1002/qj.3203.