Accession Number:

ADA359108

Title:

Intercomparison of Icing Aviation Impact Variable Forecasts Produced During Real-Time Mesoscale Numerical Weather Prediction

Descriptive Note:

Master's thesis

Corporate Author:

OKLAHOMA UNIV NORMAN

Personal Author(s):

Report Date:

1998-01-01

Pagination or Media Count:

205.0

Abstract:

In 1996 a three year joint effort, Project COMET-Tinker, was initiated between the University of Oklahoma OU, the Air Force Weather Agency AFWA, and the Cooperative Program for Operational Meteorology, Education, and Training COMET to evaluate the use of real-time mesoscale numerical weather prediction NWP by USAF forecasting personnel. Its goal is to examine forecasts of specific aviation impact variables AIVs which could be incorporated directly into the weather services provided by the base weather station BWS at Tinker Air Force Base AFB. During a Winter Operational Period WOP, 23 December 1997 to 31 January 1998, daily nine hour, nine kilometer resolution forecasts were made using the Advanced Regional Prediction System ARPS developed by the Center for Analysis and Prediction of Storms CAPS. Icing forecast products derived from algorithms developed by various weather agencies world-wide were generated using the model output and disseminated to the Tinker BWS via the world wide web WWW. Verification procedures developed at OU utilizing observational data from surface reporting stations, the Oklahoma Mesonet, and wind profilers, along with comparisons against upper air analysis fields from the Rapid Update Cycle RUC were used to evaluate general model performance. Forecast errors were found to be consistent with known model deficiencies and limited to the lower portions of the model domain. Pilot Reports PIREPs of in-flight icing conditions were then compared with the ARPS derived icing forecasts to determine the effectiveness of ARPS and the algorithms utilized in predicting the observed icing conditions. Evaluation of the icing forecasts showed that synoptically based algorithms performed better than those that relied on microphysical parameterizations inherent in ARPS and other mesoscale models.

Subject Categories:

  • Meteorology

Distribution Statement:

APPROVED FOR PUBLIC RELEASE