⚠ PREVIEW / DEMO ONLYThe entries below are illustrative examples — NOT real operational after-action data. Real AARs appear here once users save scenario outcomes in the Scenario Workbench.
Save scenarios and document outcomes to build an institutional knowledge base. Compare modeled predictions against actual results to improve future estimates. AARs feed back into the Playbook as validated templates.
DEMODEMO-AAR-001(example date)KEWR GDP — Heavy convective ZNYEffective
[DEMO] GDP issued for KEWR running 14:00–22:00Z. CBs moved north by 18:00Z allowing early release. GDP achieved ~85% of targeted delay savings.
Lessons learned: [DEMO] Early GDP reduced AM cascade. Release timing aligned well with convective movement. Recommend pre-positioning GDP 30 min earlier next cycle.
DEMODEMO-AAR-002(example date)KORD Ground Stop — EquipmentPartial
[DEMO] Ground Stop for KORD when STARS automation degraded. Lasted 45 min before backup restored. En-route demand from ZAU overloaded in interim.
Lessons learned: [DEMO] GS notification delay caused excess queue at KDTW/KMDW. Pre-coordinate MIT-20 on PARCH/HASTE for KORD GS events.
Creating a Real AAR
1. Run a scenario in the Workbench → 2. Save it → 3. After the event, return to the saved scenario → 4. Add "Outcome" and "Lessons Learned" notes → 5. Mark as AAR complete. Completed AARs can be promoted to Playbook templates.