In order to achieve accurate shell impacts, atmospheric drag must be taken into account when aiming artillery. Firing-table programs exist which can calculate impact-displacements with respect to specific density, temperature and wind conditions found over a battlefield. The atmospheric data needed to calculate these displacements can be gathered by a radiosonde. In practice, however, atmospheric soundings cannot be made continually in battlefield situations. It is, therefore, desirable to use numerical weather prediction in place of extrapolation techniques if it can be shown that numerical forecasts are superior to extrapolated estimators during the four-hour span that usually passes between verification soundings. For this reason, there is a need to evaluate the propagation of model inaccuracy during the first four forecast hours and determine which factors might be responsible for errors induced through the use of numerical forecasts. To this end, the Battlescale Forecast Model (BFM) has been validated. In this study, prepared under the auspices of the Environmental Verification and Analysis Center (EVAC) at the University of Oklahoma, the performance of the BFM with respect to persistence was examined at time steps of 1,2,3 and 4 hours after model initialization. The BFM, a P.C.-based, mesoscale weather model developed at the Army Research Laboratory, uses hydrostatic and adiabatic approximations and a grid spacing of 10 kilometers.
The accuracy of 155 mm artillery rounds is calculated theoretically for BFM-forecasted, measured and persistence soundings. Two verification locations are considered in this study: the U.S. Army Field Artillery Center at Fort Sill, OK, and the National Weather Service Forecast Office in Norman, OK. Impact errors are calculated using firing table programs. The difference in accuracy between impacts calculated using forecasted and measured data is used to gauge the model's performance.
Preliminary results show where inaccuracies in BFM forecasts are located. In addition, specific synoptic situations have been identified which tend to produce biases and inaccuracies in BFM forecasts.
The 8th Conference on Aviation, Range, and Aerospace Meteorology