Prof. Guifu Zhang1, Principal Investigator
Prof. Ming Xue1,2, Co-Principal Investigator
Prof. Phillip Chilson1, Co-Principal Investigator
Dr. Terry Schuur3,4, Co-Principal Investigator
Dr. Dusan Zrnic4, Co-Principal Investigator
1School of Meteorology (SOM)
2Center for Analysis and Prediction of Storms (CAPS)
3Cooperative Institute for Mesoscale Meteorological Studies (CIMMS)
University of Oklahoma, Norman, OK 73019
4National Severe Storms Laboratory,1313 Halley Circle, Norman, OK73069
Funded by NSF for 8/1/2006 - 7/31/2009
Understanding and characterizing precipitation microphysics are important for accurate quantitative precipitation estimation (QPE) and for improving quantitative precipitation forecasts (QPF). The objective of this proposal is to improve precipitation estimation and numerical forecasts of quantitative precipitation with the optimal use of observations from advanced instruments, including 2D video disdrometers, profiler and dual-polarization radars.
A 2D video disdrometer (2DVD) provides detailed information about the size, shape and density of precipitating particles. A vertically pointing wind profiler measures precipitation (or clear air) characteristics at various heights. Polarization radar measurements have shown great potential in classifying hydrometeor types and in retrieving hydrometeor drop size distributions (DSD) with a large spatial coverage. A combination of polarization radar, profiler and disdrometer measurements makes it possible to develop and verify observation-based microphysics parameterizations with case-dependent and time-evolving DSDs.
The project proposes to deploy 2DVDs at sites within the coverage of a prototype WSR-88D dual-polarization radar (KOUN in Norman, Oklahoma) and the Oklahoma City WSR-88D (KTLX) radar. This will enable the project team to (1) better understand cloud/precipitation microphysics with further study on the drop size distributions and their evolution through in-situ measurements and radar observations, (2) improve microphysics parameterization, (3) develop forward observation operators for polarization radar variables and improve QPE algorithms through optimal use of polarimetric radar data (PRD), and (4) assimilate PRD into numerical weather prediction (NWP) models for optimal retrieval of microphysical parameters, and for model initialization and forecasting. Error structures of radar measurements and retrievals will also be quantified. Observation-based and model-based microphysical retrievals will be cross-validated and verified with in-situ measurements.
The increasing needs for improved microphysics parameterization as research and operational numerical weather prediction (NWP) models start to resolve convection and precipitation explicitly and the planned upgrade of the national network of operational WSR-88D radars to dual-polarization capability in the next five years make the proposed research both urgent and timely. Further, the fact that the QPF improvement has been slow and difficult over the years provides another impetus for the proposed research.
The outcome of this research is expected to lead to more accurate QPE and better short-term QPF through better characterization and parameterization of precipitation microphysics. The rain DSD retrieval algorithms can be incorporated into the QPE algorithms of the WSR-88D radars with and without the use of dual-polarization information, replacing the commonly used simple Z-R relation. The improved QPE will greatly improve our ability to assess the risks of flooding and to improve the prediction capabilities of hydrological models. The improved parameterization schemes can be implemented and tested within community NWP models such as the Weather Research Forecast (WRF) and the Advanced Regional Prediction System (ARPS) models, with the former being implemented in the suite of operational NWP models by the National Weather Service. The expected improvement to operational precipitation forecast will undoubtedly have a significant societal impact. Research results will also be disseminated through seminars, conference presentations and formal publications in the scientific literature to ensure a broad impact. The proposed activity will also provide two graduate students with the opportunity to participate in a field program and gain research experiences in disdrometer, radar, NWP and advanced data assimilation (DA) techniques