NTSB CAROL · Event
Event SEA07LA250
Aircraft involved
Probable cause & findings
The pilot's failure to maintain control of the glider while maneuvering on final approach to landing, which resulted in an collision with a tree. A factor was the wind gust.
Factual narrative
On August 31, 2007, approximately 1350 mountain daylight time, a Schweizer SGS 2-33 glider, N5731S, sustained substantial damage following a loss of control and subsequent impact with trees while on approach to landing at the Morgan County Airport (42U), Morgan, Utah. The certificated commercial pilot received minor injuries, and the student pilot sustained serious injuries. Visual meteorological conditions prevailed for the instructional flight, which was being operated in accordance with 14 CFR Part 91, and a flight plan was not filed. The local flight departed 42U about 1300. In a statement submitted to the NTSB investigator-in-charge, the flight instructor reported that on short final to Runway 21 the aircraft encountered a gust of wind, which lifted the tail and rolled the glider to the right. The flight instructor stated that by the time he was able to level the wings he was right of the runway centerline and headed toward a group of large bushes/trees, which were also off the right side of the runway. The flight instructor further stated that the airplane's right wing subsequently impacted a tree, which resulted in the airplane flipping over and coming to rest inverted; the impact force to the right wing resulted in substantial damage to the glider. The flight instructor estimated that the wind at the time of the accident was from 240 degrees and between 10 to 15 knots. On short final the glider encountered a gust of wind, which lifted the tail and rolled the aircraft to the right. The glider's right wing subsequently impacted a tree off the right side of the runway, flipping it over before coming to rest inverted. The wind at the time of the accident was estimated to be from 240 degrees and between 10 to 15 knots. Source: NTSB Aviation Accident Database (Pre-2008 Archive) Retrieved: 2026-02-12
Verbatim from NTSB's published report. Source file
NTSB_2007_SEA07LA250.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 (loss of control). Sourced from NASA NTRS, NTSB Safety Studies, FAA CAMI, AOPA Air Safety Institute, Embry-Riddle Scholarly Commons, arXiv, and the Semantic Scholar academic graph.
- Embry-Riddle Scholarly Commons 2025 · Journal article (JAAER)
A Scoping Review of Aviation Loss of Control Inflight Research
Loss of control – inflight (LOC-I) contributes to aircraft accidents at unacceptably high rates. Significant industry efforts and research have aimed to improve LOC-I prevention, detection, and recove…
- SKYbrary (Eurocontrol) 2024 · SKYbrary article
Loss of Control In-Flight (LOC-I) — SKYbrary Knowledge Base
SKYbrary comprehensive knowledge-base entry on Loss of Control In-Flight — definitions, contributing factors, accident case studies (Air France 447, Colgan 3407), and prevention strategies.
- NTSB Aircraft Accident Reports 2022 · Accident report
Loss of Control on Takeoff in Icing Conditions — Citation 560XL
Cessna Citation 560XL fatal takeoff icing accident, March 2018. Investigation of a Citation 560XL loss-of-control takeoff accident in icing conditions.
- Semantic Scholar 2021 · Article (Aviation)
ANALYSIS OF GENERAL AVIATION FIXED-WING AIRCRAFT ACCIDENTS INVOLVING INFLIGHT LOSS OF CONTROL USING A STATE-BASED APPROACH
Inflight loss of control (LOC-I) is a significant cause of General Aviation (GA) fixed-wing aircraft accidents. The United States National Transportation Safety Board’s database provides a rich source…
- NASA NTRS 2021 · Presentation
Use of Design of Experiments in Determining Neural Network Architectures for Loss of Control Detection
Abstract—We describe empirical methods for selecting a neural network architecture to implement belief state inference on generic commercial transport aircraft.
- NASA NTRS 2021 · Conference Paper
Use of Design of Experiments in Determining Neural Network Architectures for Loss of Control Detection
We describe empirical methods for selecting a neural network architecture to implement belief state inference on generic commercial transport aircraft.
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