Investigation of hydrometeor classification uncertainties through the POLARRIS polarimetric radar simulator
Abstract
POLarimetric Radar Retrieval and Instrument Simulator (POLARRIS) is a framework that has been developed to simulate radar observations from cloud resolving model (CRM) output and subject model data and observations to the same retrievals, analysis and visualization. This framework not only enables validation of bulk microphysical model simulated properties, but also offers an opportunity to study the uncertainties associated with retrievals such as hydrometeor classification (HID). For the CSU HID, membership beta functions (MBFs) are built using a set of simulations with realistic microphysical assumptions about axis ratio, density, canting angles, size distributions for each of ten hydrometeor species. These assumptions are tested using POLARRIS to understand their influence on the resulting simulated polarimetric data and final HID classification. Several of these parameters (density, size distributions) are set by the model microphysics, and therefore the specific assumptions of axis ratio and canting angle are carefully studied. Through these sensitivity studies, we hope to be able to provide uncertainties in retrieved polarimetric variables and HID as applied to CRM output. HID retrievals assign a classification to each point by determining the highest score, thereby identifying the dominant hydrometeor type within a volume. However, in nature, there is rarely just one a single hydrometeor type at a particular point. Models allow for mixing ratios of different hydrometeors within a grid point. We use the mixing ratios from CRM output in concert with the HID scores and classifications to understand how the HID algorithm can provide information about mixtures within a volume, as well as calculate a confidence in the classifications. We leverage the POLARRIS framework to additionally probe radar wavelength differences toward the possibility of a multi-wavelength HID which could utilize the strengths of different wavelengths to improve HID classifications. With these uncertainties and algorithm improvements, cases of convection are studied in a continental (Oklahoma) and maritime (Darwin, Australia) regime. Observations from C-band polarimetric data in both locations are compared to CRM simulations from NU-WRF using the POLARRIS framework.
- Publication:
-
AGU Fall Meeting Abstracts
- Pub Date:
- December 2017
- Bibcode:
- 2017AGUFM.A34A..05D
- Keywords:
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- 3310 Clouds and cloud feedbacks;
- ATMOSPHERIC PROCESSES;
- 3354 Precipitation;
- ATMOSPHERIC PROCESSES;
- 3360 Remote sensing;
- ATMOSPHERIC PROCESSES;
- 1853 Precipitation-radar;
- HYDROLOGY