Initial Validation of a Convective Weather Avoidance Model (CWAM) in Departure Airspace Mikhail Rubnich and Rich DeLaura 30th Digital Avionics Systems Conference October, 18th 2011 MIT Lincoln Laboratory 999999-1 XYZ 10/22/2011
Contents • Goals and motivations • Automatic avoidance detection algorithm description • Analysis of results • Conclusions and future work MIT Lincoln Laboratory 999999-2 XYZ 10/22/2011
Contents • Goals and motivations • Automatic avoidance detection algorithm description • Analysis of results • Conclusions and future work MIT Lincoln Laboratory 999999-3 XYZ 10/22/2011
Motivations • The Route Availability Planning Tool (RAPT) - decision support tool used to help controllers in route management has problems with over-warning and occasional under- warning when weather impacts are in terminal airspace • RAPT is using Convective Weather Avoidance Model (CWAM) and an airspace use model • Therefore, CWAM in terminal airspaces needs to be validated MIT Lincoln Laboratory 999999-4 XYZ 10/22/2011
Weather Avoidance Field * description Enroute boundary Transition Echo top (storm height) Convective Terminal boundary Weather Avoidance Model Departure Domain Weather Avoidance Field (WAF) (probability of pilot deviation ) VIL (precipitation intensity) MIT Lincoln Laboratory 999999-5 * DeLaura, R., and Evans, J., “An Exploratory Study of Modeling Enroute Pilot Convective Storm Flight Deviation Behavior,” XYZ 10/22/2011 Proceedings of the 12 th Conference on Aviation, Range, and Aerospace Meteorology , Atlanta, 2006
Chicago and New York Airspaces New York Airspace Chicago Airspace 30 minute cumulative traffic Key: Departures Arrivals MIT Lincoln Laboratory 999999-6 XYZ 10/22/2011
Methodology • Trajectories from Enhanced Traffic Management System ( ETMS ), WAF calculated using observed weather from Corridor Integrated Weather System (CIWS) • Calculated weather avoidance ratio using automatic avoidance detection algorithm using 5 test days ( Chicago) and 8 test days ( New York ) from 2010 • 489 weather avoidances and 523 weather intersections ( Chicago ), 1084 weather avoidances and 1337 weather intersections ( New York ) were identified and analyzed • WAF calibration using observed avoidance ratio MIT Lincoln Laboratory 999999-7 XYZ 10/22/2011
Contents • Goals and motivations • Automatic avoidance detection algorithm description • Analysis of results • Conclusions and future work MIT Lincoln Laboratory 999999-8 XYZ 10/22/2011
Automatic avoidance detection algorithm description Identify the maximum intersected WAF Identify instances of ‘storm avoidance’ (weather avoidance along the departure trajectory path) using the ‘ray’ method Identify avoidance of weather on the departure fix, if the filed departure fix is within 140 km. of the airport MIT Lincoln Laboratory 999999-9 XYZ 10/22/2011
Algorithm Description ( intersection ) Identify the maximum intersected WAF WAF intersection WAF contours Maximum intersected WAF MIT Lincoln Laboratory 999999-10 XYZ 10/22/2011
Algorithm Description ( ‘ray’ method ) Identify instances of ‘storm avoidance’ (weather avoidance along the departure trajectory path) using the ‘ray’ method Ray algorithm to Avoidance identify storm avoidance detected Maximum avoided WAF Minimum avoided WAF No Avoidance detected Maximum intersected WAF MIT Lincoln Laboratory 999999-11 XYZ 10/22/2011
Algorithm Description ( departure fix ) Identify avoidance of weather on the departure fix, if the filed departure fix is within 140 km. of the airport fix Avoidance detected Avoidance of impacted departure fix Minimum avoided WAF Departure fix trajectory Maximum avoided WAF Flight plan fix Maximum intersected WAF = 0 Avoidance detected trajectory MIT Lincoln Laboratory 999999-12 XYZ 10/22/2011
Algorithm Description ( illustrations of classifications ) Fix avoidance detection Storm avoidance detection Weather intersection Avoidance probability 1.0 Maximum WAF avoided Airport Departure Minimum fix 0.5 WAF avoided Airport Maximum Contour Departure WAF avoided Minimum fix detection WAF avoided Inferred 0.0 Departure heading Airport fix MIT Lincoln Laboratory 999999-13 XYZ 10/22/2011
Algorithm Description ( validation ) • Visualizations of 547( NY ) and 257( Chicago ) automated avoidance classifications were reviewed to validate the algorithm. • The error rate was estimated at ~16%. • Typical error modes were identified MIT Lincoln Laboratory 999999-14 XYZ 10/22/2011
Algorithm Description ( error analysis ) Imaginary closure of WAF contour fragmentation fragmented WAF contour Contour Avoidance fragment probability 1.0 0.5 Intersection ray Incorrect contour was Incorrect contour was selected as a cause selected as a cause of avoidance due to of avoidance due to WAF contour WAF contour 0.0 fragmentation fragmentation Overestimating the observed avoidance probability for the lower forecast probability associated with the fragment, while underestimating the observed avoidance probability associated with the higher forecast probability associated with the higher region MIT Lincoln Laboratory 999999-15 XYZ 10/22/2011
Algorithm Description (error analysis) Small misclassified deviations Avoidance probability 1.0 0.5 0.0 MIT Lincoln Laboratory 999999-16 XYZ 10/22/2011
Algorithm Description (error analysis) Misclassified congestion avoidance maneuvers a. Trajectory slowed to avoid b. Trajectory held to avoid departure fix congestion departure fix congestion Avoidance probability Misclassified avoidance 1.0 WAF contour 0.5 Misclassified avoidance WAF contour 0.0 MIT Lincoln Laboratory 999999-17 XYZ 10/22/2011
Contents • Goals and motivations • Algorithm description • Analysis of results • Conclusions and future work MIT Lincoln Laboratory 999999-18 XYZ 10/22/2011
Avoidance probability calibration (results) Calibration of predicted avoidance probabilities a. Chicago b. New York 1 1 Observed avoidance probability 294 0.9 0.9 642 0.8 0.8 39 75 54 52 0.7 0.7 143 180 78 154 0.6 0.6 0.5 0.5 204 79 127 88 409 278 254 283 0.4 0.4 0.3 0.3 0.2 0.2 0.1 0.1 0 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 Predicted avoidance probability Calibration of departure CWAM from Chicago (a) and New York (b) MIT Lincoln Laboratory 999999-19 XYZ 10/22/2011
Avoidance of small, isolated, weak thunderstorms ( results ) Calibration of predicted avoidance probabilities a. Chicago b. New York 1 1 Observed avoidance probability 294 0.9 0.9 642 0.8 0.8 39 52 75 54 0.7 0.7 143 180 78 154 0.6 0.6 0.5 0.5 204 127 88 79 283 409 278 254 0.4 0.4 0.3 0.3 0.2 0.2 0.1 0.1 0 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 Predicted avoidance probability a. Chicago b. New York Avoidance probability 1.0 Avoided region 0.5 Avoided region 0.0 MIT Lincoln Laboratory 999999-20 XYZ 10/22/2011
Results (Chicago vs. New York ) Calibration of predicted avoidance probabilities a. Chicago b. New York 1 1 Observed avoidance probability 294 0.9 0.9 642 0.8 0.8 39 52 75 54 0.7 0.7 143 180 78 154 0.6 0.6 0.5 0.5 79 204 127 88 278 254 283 409 0.4 0.4 0.3 0.3 0.2 0.2 0.1 0.1 0 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 Predicted avoidance probability • In New York, only 72% of encounters with maximum WAF probabilities >= 0.9 were avoidances, while that percentage was 88% in Chicago • Possible explanation: lower avoidance rate for New York may be explained by more constrained airspace and stricter avoidance rules in NY airspace MIT Lincoln Laboratory 999999-21 XYZ 10/22/2011
Results (Avoidance strategy ) b. Trajectory following large storm boundary a. Trajectory following small storm boundary Avoidance probability 1.0 0.5 c. Trajectory following ‘best feasible option’ through weather 0.0 • An avoidance trajectory that avoided the storm core but encountered less severe weather in the vicinity. OR • Avoid all weather and to fly in clear air. MIT Lincoln Laboratory 999999-22 XYZ 10/22/2011
Results (Avoidance strategies) Maximum intersected WAF for all flights with maximum avoided WAF = 0.9 45 40 New York Chicago 35 Percentage of flights 30 30 25 25 20 20 15 15 10 10 5 5 0 0 0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 Maximum intersected WAF Maximum intersected WAF • ~30%(Chicago)/40%(New York) of flights that avoided WAF of 0.9 avoided all weather • ~ 60%/Chicago)/65%(New York) flights avoided WAF with values >= 0.3. This suggests that pilots will avoid weather near a storm that they would otherwise fly through if that weather were isolated and not associated with the storm MIT Lincoln Laboratory 999999-23 XYZ 10/22/2011
Contents • Goals and motivations • Algorithm description • Analysis of results • Conclusions and future work MIT Lincoln Laboratory 999999-24 XYZ 10/22/2011
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