Convective Meteorology (Mesoscale Dynamics)

Improvement to Moisture Adjustment in Cloud Analysis and its Impact on Storm Prediction

Chong-Chi Tong
OU School of Meteorology / Center for Analysis and Prediction of Storms / Advanced Radar Research Center

13 March 2015, 2:00 PM

National Weather Center, Room 5600
120 David L. Boren Blvd.
University of Oklahoma
Norman, OK

The effectiveness of complex cloud analysis has been demonstrated on improving various types of weather system. In addition to the hydrometeor fields analyzed using reflectivity (Z) observation that sufficiently shortens the model spin-up time required for developing storms from a clear-air initial, couple in-cloud fields such as temperature and moisture are also adjusted based on semi-empirical physical constraints through the cloud analysis procedure.

According to the results of our earlier study which quantitatively examined the impact of initial accuracy of various thermodynamic state variables on predicting a Great Plains MCS using Observing System Simulation Experiments (OSSEs), the greatest impact was found given by the moisture (qv): even with perfect hydrometeor fields in the initial condition (IC), their benefit could be significantly reduced owing to the poor initial moisture field. The criticality of the qv adjustment in cloud analysis on improving model forecasts is thus revealed.

In this study, we first examine the effect of the current in-cloud qv adjustment, which simply saturates all the cloudy regions based on presence of significant radar echo. Verified by the truth simulation of our OSSE framework, the analyzed qv field based on this simple strategy has a remarkably large error, and furthermore results in rapid error growths in forecasting most variables (e.g., winds, temperature, qv, mixing ratios of multiple species) and dramatic overforecast in Z intensity. By directly inserting the truth relative humidity (RH) field into the cloudy regions, the potential of an improved qv adjustment is investigated. It is found the overall prediction is significantly improved by this better specified qv field.

Information of vertical velocity (w) could be incorporated to help determine qv field for the empirical physic that air is usually saturated (unsaturated) in updraft (downdraft) regions. As the sufficient w field can be provided by the Doppler wind analysis, in this study the truth w is borrowed to develop a modified qv adjustment. Regardless of the limit on reducing the qv analysis error owing to 1) the unstrict relation between w and RH and 2) accuracy of temperature field, our modified qv adjusting strategy is demonstrated not only avoiding over-moistening analysis, but also providing better forecast in most variables over those given by the current qv adjustment. On predicting intense convections (30 dBZ and above), the significant advantage of the modified qv adjustment over the non-qv-adjusted experiment can last up to four hours; however, its performance is not as good as the simple saturating adjustment in terms of equitable threat score (ETS) for its underforecast tendency.

For accommodations based on disability, or more details, please call 325-6561. All visitors without NOAA or University of Oklahoma identification must register at the registration desk on arrival. Visitor parking is available for all University visitors. However, faculty/staff/students must have a current multi-purpose parking permit. Additional parking is available at the Lloyd Noble Center (LNC) for those individuals who do not have a parking permit. You do not need a permit to park in one of 1,200 spaces reserved for CART bus riders, although you must ride the CART shuttle to park in the reserved area. This area is on the north central side of the Lloyd Noble Center. Elsewhere at the LNC, permits are required.

The University of Oklahoma is a smoke-free / tobacco-free campus.

Convective Meteorology (Mesoscale Dynamics) Seminar Series website