Aviation Weather Forecasts Based on Advection


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Previous experiments had shown that upper-level wind flows could be used to advect surface weather parameters to produce short-range (0-15 hours) forecasts. However, to achieve scores better than persistence, allowance had to be made for stationary weather patterns and also for diurnal changes in weather conditions. Two new forecast experiments were prepared and carried out, using data from 12 cases during March 1983. First, data were edited and adjusted to reduce effects of local conditions (altitude, surface roughness), and then were advected. Finally, the adjustment was removed. The forecasts using a 500 mb space-averaged flow with modified initial conditions produced improved advection forecasts, with some parameters better than persistence and MOS (Model Output Statistics) for 2-7 hours. In the second experiment, an improved objective-analysis procedure was introduced, one based on the 'Barnes' approach, which uses one-half degree (about 45 km) resolution and previous analysis as a first guess. (Prior analyses were 1 degree, single pass, 'Cressman'-type analyses.) These improved analyses resulted in a somewhat better score for 1-3 hours (using a 'change-advection' technique), but were slightly worse at longer periods. Apparently, the small-scale patterns recovered by the improved analyses were largely either short-lived or stationary. These conditions would not lead to better advection forecasts. Further examination revealed that those parameters most difficult to resolve in the objective analyses (visibility, ceiling, and wind speed) also had the lowest forecast skill scores for persistence. Keywords: Aviation forecasting; Meteorology; Mesoscale analysis and forecasting.







Composited Local Area Forecast Techniques


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A previously developed advection forecast technique was modified to include data extracted from satellite imagery. A forecast experiment was then conducted using a data base gathered at AFGL during March 1984. This experiment was designed to test the usefulness of : (a) 3-hour forecast updates, (b) a biquadratic interpolation, and (c) cloud and precipitation information from satellite imagery. The test results confirmed earlier tests in that advection using space-averaged 500-mb winds produced the best overall scores and that in general the scores for 1 - 15 hours were better than persistence. The age of the advection flow (3, 6 or 9 hours old) did not affect forecast score, making updates useful. The biquadratic interpolation procedure produced better fits to observation than bilinear and appears to have improved forecasts. There was but a small benefit from adding satellite information to surface observations when forecasting cloud cover and hourly precipitation. the difficulties of trying to forecast even 30 to 50 percent of the time-change variance suggest that alternative approaches such as mesoscale modeling will be needed for accurate, reliable short-range forecasts.







Aviation Weather


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Accessions List


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Accessions List


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Accessions List


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Blending of Surface and Rawinsonde Data in Mesoscale Objective Analysis


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This report describes a simple technique to blend surface and rawinsonde observations in the planetary boundary layer (PBL) using a Barnes-type objective analysis. This goal is to improve the mesoscale detail of boundary layer input fields for a mesoscale numerical weather prediction model. The technique uses both surface and rawinsonde data in the boundary layer, where it is known that mesoscale details are inadequately resolved by the rawinsonde network and where the influence of the ground surface is strongest. Our challenge is to blend the signals contained in the denser surface observations that capture at least some mesoscale detail with those contained in the denser surface observations that capture at least some mesoscale detail with those contained in the boundary layer rawinsonde data. This is accomplished simply by comparing two analyses at the ground, one containing both rawinsonde data-resolvable and surface-data-resolvable information and the other, only the rawinsonde scale information. Differences between these two fields are assumed to be the signals undetected by the rawinsonde network. These mesoscale signals are then incorporated into the PBL analyses as a function of the distance from the ground. Results show a positive impact on boundary layer analyses due to the blending of surface and rawinsonde data, demonstrating that he technique is useful for providing improved mesoscale detail at and near the ground. Also discussed is the relative impact of data density and reference topography on the analysis of model parameters on terrain-following surfaces. (EDC).