References
Andrews, J.W. 1993. Impact of weather event uncertainty upon an optimum ground-holding strategy. Air-Traffic Control Quarterly 1(1): 59–84.
Belair, S., and J.Mailhot. 2001. Impact of horizontal resolution on the numerical simulation of a midlatitude squall line: Implicit versus explicit condensation. Mon. Weather Rev. 129:2362–2376.
Benjamin, S.G., J.M.Brown, K.J.Brundage, B.E.Schwartz, T.G. Smirnova, and T.L.Smith. 1998. The operational RUC-2. Preprints, 16th Conference on Weather Analysis and Forecasting, Phoenix, AZ, American Meteorological Society, pp. 249–252.
Black, T.L. 1994. The new NMC mesoscale Eta model: Description and forecast examples. Weather Forecast 9:265–278.
Carpenter, R.L., Jr., K.K.Droegemeier, G.M.Bassett, S.S.Weygandt, D. E.Jahn, S.Stevenson, W.Qualley, and R.Strasser. 1999. Storm-scale numerical weather prediction for commercial and military aviation, Part 1: Results from operational tests in 1998. Preprints, 8th Conference on Aviation, Range, and Aerospace Meteorology, January 10–15, American Meteorological Society, Dallas, TX, pp. 209–211.
Droegemeier, K.K. 1997. The numerical prediction of thunderstorms: Challenges, potential benefits, and results from realtime operational tests. WMO Bulletin 46:324–336.
Evans, J. 2001. Tactical Weather Decision Support to Complement “Strategic” Traffic Flow Management for Convective Weather. Fourth International Air Traffic Management R&D Seminar ATM-2001, Santa Fe, NM. Available online at http://atm2001.eurocontrol.fr/ [accessed December 11, 2002].
Forman, B.E., M.M.Wolfson, R.G.Hallowell, and M.P.Moore. 1999. Aviation user needs for convective weather forecasts. Preprints, Eighth Conference on Aviation, Range, and Aerospace Meteorology, Dallas, TX, American Meteorological Society, pp. 526–530.
IPCC (International Panel on Climate Change). 1999. IPCC Special Report: Aviation and the Global Atmosphere. J.E.Penner, D.H.Lister, D.J. Griggs, D.J.Dokken, and M.McFarland, eds. Cambridge University Press, Cambridge, UK.
Lorenz, E.N. 1969. The predictability of a flow which possesses many scales of motion. Tellus 21:289–307.
Mass, C.F., D.Ovens, K.Westrick, and B.A.Colle. 2002. Does increasing horizontal resolution produce more skillful forecasts? B. Am. Meteorol. Soc. 83:407–430.
Molinari, J. 1993. An overview of cumulus parameterizations in mesoscale models. Pp. 155–158 in The Representation of Cumulus Convection in Numerical Models. American Meteorological Society, Boston.
Sun, J., and N.A.Crook. 1998. Dynamical and microphysical retrieval from Doppler radar observations using a cloud model and its adjoint. Part II: Retrieval experiments of an observed Florida convective storm. J. Atmos. Sci. 55:835–852.
Sun, J., and N.A.Crook. 2001. Real-time low-level wind and temperature analysis using WSR-88D data. Weather Forecast. 16:117–132.
Wang, D., K.K.Droegemeier, D.Jahn, K.M.Xu, M.Xue, and J.Zhang. 2001. NIDS-based intermittent diabatic assimilation and application to storm-scale numerical weather prediction. Preprints, 14th Conference on Numerical Weather Prediction, July 30-August 2, American Meteorological Society, Fort Lauderdale, Fla., pp. J125–J128.
Weygandt, S.S., A.Shapiro, and K.K.Droegemeier. 2002. Retrieval of initial forecast fields from single-Doppler observations of a supercell thunderstorm. Part II: Thermodynamic retrieval and numerical prediction. Mon. Weather Rev 130:454–476.
Wilkes, D.S. 1995. Statistical Methods in the Atmospheric Sciences. San Diego: Academic Press, 467pp.
Xue, M., D.H.Wang, J.D.Gao, K.Brewster, and K.K.Droegemeier. 2003. The Advanced Regional Prediction System (ARPS), storm-scale numerical weather prediction and data assimilation. Meteorol. Atmos. Phys.