NTSB CAROL · Event
Event LAX92FA151
Aircraft involved
Probable cause & findings
THE PILOT'S DELAYED INFLIGHT DECISION TO REVERSE COURSE TO AVOID FORECAST ADVERSE WEATHER CONDITIONS. CONTRIBUTING TO THE ACCIDENT WAS ICING CONDITIONS AND LIGHTNING.
Factual narrative
ABOUT 30 MIN BEFORE THE ACCIDENT, THE PLT RECEIVED AN IN-FLT WX BRIEF FROM EN ROUTE FLIGHT ADVISORY SERVICE (EFAS). THE PLT INDICATED TO THE EFAS THAT HE RECEIVED AN AIRMET REGARDING ICING CONDITIONS ALONG HIS ROUTE. THE PLT WAS THEN BRIEFED ON THUNDERSHOWERS, FREQUENT LIGHTNING CLOUD TO GND, AND PLT REPORTS OF MOD TURB AND LT MIXED ICING. THE PLT CONTINUED ON HIS FLT ROUTE AND 25 MIN AFTER HIS WX BRIEFING REPORTED AIRFRAME ICING CONDITIONS TO ATC. ATC ADVISED THE PLT OF MORE SEVERE WX AHEAD AND RECOMMENDED THE LT REVERSE COURSE. LESS THAN ONE MIN LATER, THE PLT REPORTED BEING STRUCK BY LIGHTNING. ATC AMENDED THE PLT'S CLEARANCE INSTRUCTING HIM TO REVERSE COURSE WITH A LEFT TURN HEADING 330 DEG. THE PLT READ BACK THE CLEARANCE. AFTERWARDS BOTH RADAR AND RADIO CONTACT WAS LOST. RADAR DATA REVEALED THE AIRPLANE ENTERED A LEFT TURN AND CLIMBED 200 FT. THE AIRPLANE THEN DESCENDED ABOUT 1,200 FT IN 35 SECONDS. THE ACCIDENT AIRPLANE WAS NOT EQUIPPED WITH DE-ICING SYSTEMS. Source: NTSB Aviation Accident Database (Pre-2008 Archive) Retrieved: 2026-02-12
Verbatim from NTSB's published report. Source file
NTSB_1992_LAX92FA151.txt.
Findings + structured fields enriched from FAA avall.mdb.
Full investigation docket on
data.ntsb.gov ↗.
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Related research
What the literature says.
Academic papers and agency reports matching this event's aircraft type or causal vocabulary (icing). Sourced from NASA NTRS, NTSB Safety Studies, FAA CAMI, AOPA Air Safety Institute, Embry-Riddle Scholarly Commons, arXiv, and the Semantic Scholar academic graph.
- NASA NTRS 2026 · Contractor Report (CR)
Icing Physics Studies Using the 3D SIDRM Test Article: 2023 Icing Tests Analysis
In-flight icing is an important safety issue and is a factor that affects aircraft design and performance. Newer regulations are driving a need for improvements in airframe and engine icing simulation…
- arXiv 2025 · arXiv preprint
Multi-Agent Deep Reinforcement Learning for UAV-Assisted 5G Network Slicing: A Comparative Study of MAPPO, MADDPG, and MADQN
The growing demand for robust, scalable wireless networks in the 5G-and-beyond era has led to the deployment of Unmanned Aerial Vehicles (UAVs) as mobile base stations to enhance coverage in dense urb…
- Embry-Riddle Scholarly Commons 2025 · Journal article (JAAER)
A Mathematical Model on the Temporal Dynamics of Aviation Competitive Pricing
This study investigates the competitive dynamics of airport pricing using U.S. airport data to validate the findings. It employs linear and nonlinear ordinary differential equation models to analyze t…
- NASA NTRS 2025 · Presentation
NASA Icing Update – March 2025
This NASA Icing Update was prepared for presentation to the SAE International AC-9C Inflight Icing Technology Committee. This update includes the following topics: planned Rotational Icing Scaling tes…
- arXiv 2024 · arXiv preprint
An energy-stable phase-field model for droplet icing simulations
A phase-field model for three-phase flows is established by combining the Navier-Stokes (NS) and the energy equations, with the Allen-Cahn (AC) and Cahn-Hilliard (CH) equations and is demonstrated ana…
- NASA NTRS 2024 · Presentation
NASA Icing Update – Oct 2024
This presentation provides a status update on select NASA icing research activities for the SAE AC-9C Icing Technical Committee Meeting on Oct 21, 2024.
Browse the full corpus — academia portal ↗