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Dynamic normal mode initialization (DNI) is applied to low and high resolution versions of the AFGL global spectral mode. This scheme is tested against the operational nonlinear normal mode initialization (NMI) procedure using both adiabatic and diabatic forms of the model tendencies. The DNI-based forecasts are comparable in accuracy to the NMI-based forecasts, with small differences between the adiabatic and diabatic versions of each. DNI initial conditions were somewhat more damped in the divergence fields than were the NMI fields. This is believed to be due to the frequency response characteristics of the DNI's forward-backward time scheme, which tended to partially damp resolvable wavelengths.
The flexible resolution/truncation baseline version of the AFGL global spectral model as adapted to the CRAY-1 is described. A series of low-resolution (6 layer, rhomboidal 15) and high-resolution (12 layer, rhomboidal 30) forecasts were run and compared to test the performance of the model. In general, higher resolution resulted in improved forecast skill in the 24-to-96-hour range. The only exception to this is the humidity forecast, which shows minimal skill. This characteristic is rather insensitive to the resolution partly because of the poor quality of analyzed humidity fields used for initial data and verification. The original gridded (2.5 X 2.5 deg) topography has been replaced by a smoothed terrain field that has been passed through a nine-point smoother, interpolated to the model's Gaussian grid, and then spectrally truncated. Finally, the effects of initialization have been studied by comparing a series of forecasts subjected to several initialization methods. For forecasts beyond 24 hours, the model is able to supress spurious gravity waves through the combined effects of the semi-implicit time scheme and the subgrid scale diffusion. The impact of normal mode initialization is seen mainly in the very short-range forecasts (less than 24 hours) and is thus important for providing smooth first-guess fields for the analysis/data assimilation cycle. Keywords: Atmospheric models; Spectral models; Weather forecasting; Numerical weather prediction; Global atmospheric circulation.
Much of the work has concentrated on interactions between the soil model and the model of the atmospheric boundary layer and the behavior of the boundary-layer package within the Air Force Global Spectral Model. Such studies have underscored the importance of the formulation of surface properties and transport within the underlying soil. Work during the contract period also focussed on elimination of several inadequacies of boundary-layer modelling. The inclusion of the statistical impact of subgrid variations of surface properties leads to a surface exchange coefficient which varies more smoothly with stability and does not decrease as rapidly with very stable conditions. Such modifications reduce the nocturnal cooling which is usually overestimated in boundary-layer models. Other improvements of the boundary-layer model in stable conditions have resulted from increasing the critical Richardson number in the boundary-layer depth formulation and adopting the Kondo formulation for the eddy diffusivity. The development of a formulation for boundary-layer cumulus has allowed inclusion of cloud-induced drying. Although this formulation leads to significant improvement of the boundary-layer predictions in cloudy situations, the general problem is far from solved. Keywords: Atmospheric boundary layer; Surface energy balance; Soil model; Stable layer parameterization; Surface fluxes. (jhd).
Using forecast relative humidity (RH) from a global model, several pre-existing diagnostic RH-to-cloud schemes were tested to forecast global fractional cloud cover in a postprocessor format. Since none of the schemes tested provided a superior cloud forecast when compared to Air Force Global Weather Central's (AFGWC) operational 5LAYER cloud forecasts, a new RH-to-cloud scheme was developed by relating cumulative frequencies of forecast RH to cumulative frequencies of analyzed cloud cover from the AFGWC RTNEPH cloud analysis. This scheme creates a series of forecast time-dependent RH-to-cloud curves that can be temporally updated to account for changes in season, cloud analysis, or forecast model, The global model used was a spectral-type developed by the Geophysics Laboratory (GL) using parameterized diabatic physics presently incorporated in the operational GSM (global spectral model) at AFGWC.
The procedures and results of a study undertaken to evaluate and assess the impacts of three new parameterization schemes for the GL global spectral model as a 3-4 day range forecast model are described. The tree parameterization schemes are one each for the boundary-layer physics, moist convection and heating due to solar and terrestrial radiations. These schemes are incorporated either singly or jointly into a rhomboidal-30, 12-layer global spectral model for four-day simulations using FGGE III- a data as input. Evaluation and assessment are made on the basis of two kinds of global statistics: mean and root-mean-square errors, and on their magnitudes and distributions. The statistics are generated for both the primary, that is, prognostic, variables, and supplementary variables such as zonal-mean and zonal-eddies energy densities. The new moist convection scheme has been found to increase convective activity significantly and maintain it throughout the four-day period. It also warms and dries the middle troposphere, but produces rainfall far in excess of the climatology. The radiation parameterization has been found to cool the atmosphere and reduce its specific humidity. It counterbalances enhanced heating and moistening brought about by the new boundary-layer and moist convection schemes and eliminates the systematic warming of the old model.