Analysis of Model QPF Errors During the 2-4 December 2000 Snowstorm in North Carolina

QPF;numerical weather prediction;mesoscale modeling;quasigeostrophic analysis

Caldwell, Raymond Jason ; Gary M. Lackmann, Committee Chair,Jerry M. Davis, Committee Member,Allen J. Riordan, Committee Member,Caldwell, Raymond Jason ; Gary M. Lackmann ; Committee Chair ; Jerry M. Davis ; Committee Member ; Allen J. Riordan ; Committee Member

University:North Carolina State University

关键词: QPF;    numerical weather prediction;    mesoscale modeling;    quasigeostrophic analysis;   

Others  :  https://repository.lib.ncsu.edu/bitstream/handle/1840.16/2195/etd.pdf?sequence=1&isAllowed=y

美国|英语

来源: null

【 摘 要 】

Model forecasts of an early season snowstorm for 2 – 4 December 2000 followed the historical blizzard of 24 – 25 January 2000 that dumped 20.3 inches of snowfall at the Raleigh-Durham International Airport. Much like the January 2000 storm, operational models exhibited a significant lack of skill, particularly in the realm of quantitative precipitation forecasting. As early as 1800 UTC 1 December, operational models from the National Centers for Environmental Prediction (NCEP), including the 32-kilometer Eta, generated liquid equivalent precipitation totals approaching two inches for the Raleigh–Durham metropolitan area. Later forecasts indicated as much as 2.77 inches of precipitation would fall. In reality, only a trace of precipitation was observed at the Raleigh–Durham airport. A local, real–time version of the fifth-generation, mesoscale modeling system (MM5) was operational at the time of the event and provided a much-improved forecast scenario compared to the NCEP Eta model. Remarkably, the initial conditions and lateral boundary conditions in the MM5 were identical to those used to initialize the Eta model at 1200 UTC 2 December. In this study, an examination of the potential sources of error in the quantitative precipitation forecast is performed to challenge prior studies that suggest that data quality issues with sea surface temperature analyses led to spurious precipitation generation. The study includes a case study of the 2 – 4 December snowstorm, model sensitivity experiments, and quasi-geostrophic analysis to identify and diagnose the quantitative precipitation errors in the Eta model and the superior forecast guidance available from the local MM5 model.The case study showed that several potential sources of model error existed including missing upper air soundings, sea surface temperatures, model design, and misdiagnosed topographic flow. This study will test the hypothesis that errors at the 500–hPa level led to limited precipitation early in the period and, hence, produced errors in the cold air damming, coastal front, and cyclogenesis in later periods responsible for the heaviest precipitation in model forecasts. Results from sensitivity experiments with the MM5 model failed to exhibit significant differences in the representation of topographically induced phenomena or the westward extent of the precipitation shield into central North Carolina. The Eta model produced an anomalously strong 850 hPa jet at the North Carolina coast which transported warm air and moisture inland over the region. Better representation of the initial 500–hPa shortwave trough and associated vorticity maximum in the MM5 model is shown in the results to strengthen the low-level damming episode and shift the coastal front farther offshore. The results of this study provide basis for further investigation into both models and concludes that the effect of the upper–level forcing on the evolution of the low-level topographically induced flow and the surface–based forcing of upper–level dynamics can be of equal magnitude and importance in winter season precipitation forecasting. Results of this study will be coupled with local efforts to improve forecasting through conceptual model development by providing operational forecasting with the knowledge that individual models can have independent and opposing response to initial condition errors based on the physical and dynamical make–up of the mesoscale modeling system.