The development of rainfall retrievals from radar at Darwin

Submitter:

Jackson, Robert — Argonne National Laboratory
Collis, Scott Matthew — Argonne National Laboratory

Area of research:

Cloud Processes

Journal Reference:

Jackson R, S Collis, V Louf, A Protat, D Wang, S Giangrande, E Thompson, B Dolan, and S Powell. 2021. "The development of rainfall retrievals from radar at Darwin." Atmospheric Measurement Techniques, 14(1), 10.5194/amt-14-53-2021.

Science

We used four years of ground disdrometer observations to develop rainfall rate estimators for ARM scanning precipitation radars at the ARM Tropical Western Pacific site.

Impact

We were able to develop a rainfall estimator that is applicable for developing rainfall estimates from ARM radars sampling storms in the tropics.

Summary

We tested several different rainfall estimators on the C-band polarization radar data by comparing rainfall estimates from the rainfall estimators against the rainfall rate measurements from the ground-based disdrometer. We found that Colorado State University's blended rainfall rate algorithm, with adjustments to the coefficients used by the algorithm made in accordance with the disdrometer observations, provided the best estimate of rainfall for these storms.

Normalized frequency distribution 10-min averages of rainfall rate estimated from the lowest gate from CPOL over VDIS using different estimators as a function of 10-min averages of rainfall rate recorded by the VDIS. Estimators used to estimate rainfall rate from CPOL are shown in each panel. Solid lines denote medians, and dashed lines are the 5th and 95th percentiles of the estimated rainfall rate from CPOL.