Understanding the Human Factors 

Associated With Visual Flight Rules 

Flight Into Instrument Meteorological 

Conditions

Cristy Detwiler

Kali Holcomb

Carla Hackworth

Civil Aerospace Medical Institute

Oklahoma City, OK 73125

Scott Shappell

Clemson University

Clemson, SC 29634

May 2008

Final Report

DOT/FAA/AM-08/12

Office of Aerospace Medicine

Washington, DC 20591

OK-08-1997
NOTICE

This document is disseminated under the sponsorship 

of the U.S. Department of Transportation in the interest 

of information exchange. The United States Government 

assumes no liability for the contents thereof.

___________

This publication and all Office of Aerospace Medicine 

technical reports are available in full-text from the Civil 

Aerospace Medical Institute’s publications Web site: 

www.faa.gov/library/reports/medical/oamtechreports/index.cfm


Technical Report Documentation Page 

1. Report No. 2. Government Accession No. 3. Recipient's Catalog No. 

DOT/FAA/AM-08/12 

4. Title and Subtitle 5. Report Date 

May 2008 Understanding the Human Factors Associated With Visual Flight Rules 

Flight Into Instrument Meteorological Conditions 6. Performing Organization Code 

 

7. Author(s) 8. Performing Organization Report No. 

Detwiler C,1 Holcomb K,1 Hackworth C,1 Shappell S2 

9. Performing Organization Name and Address 10. Work Unit No. (TRAIS) 

 

11. Contract or Grant No. 

1

FAA Civil Aerospace Medical Institute 

P.O. Box 25082 

Oklahoma City, OK 73125 

2

Clemson University 

Clemson, SC 29634 

12. Sponsoring Agency name and Address 13. Type of Report and Period Covered 

Office of Aerospace Medicine 

Federal Aviation Administration 

800 Independence Ave., S.W. 

Washington, DC 20591 14. Sponsoring Agency Code 

15. Supplemental Notes 

Work was accomplished under approved task AM-B-06-HRR 521. 

16. Abstract 

Visual Flight Rules (VFR) into Instrument Meteorological Conditions (IMC) accidents are a major concern in 

the aviation industry. More than 70% of the fatal weather-related accidents involved General Aviation (GA) 

pilots operating under visual flight rules (VFR) that continued into IMC. The purpose of this study was to pair 

GA accident causal factors that had been classified with the Human Factors Analysis and Classification System 

(HFACS) categories and traditional demographic data in an effort to present a more complete picture of VFR 

flight into IMC accidents. To accomplish this, GA accidents associated with VFR flight into IMC were 

examined to determine if there were any causal factors that set these accidents apart from the rest of GA (RoGA) 

accidents. GA accident data (14 CFR Part 91) from 1990-2004 were analyzed. The dataset was divided into 

accidents that had VFR into IMC (VFR-IMC; N = 609) cited as a cause or factor versus the rest of the GA 

accidents (RoGA; N = 18,528). Analyses were performed examining the human error associated with these 

accidents. The results indicated that skill-based errors were more prevalent in RoGA than in VFR-IMC (odds 

ratio = 4.167, Ȥ

2

= 332.531, p <.001). VFR-IMC pilots were more likely to commit a decision error (odds ratio = 

2.062, Ȥ

2

= 77.961, p <.001); experience a perceptual error (odds ratio = 3.179, Ȥ

2

= 118.350, p <.001); and 

commit a violation (odds ratio = 29.960, Ȥ

2

= 2454.198, p <.001) than RoGA. The injury severity for VFR-IMC 

accidents was much greater than for RoGA (80.3% vs. 18.8%). RoGA pilots held a higher number of multiple 

certificates and earned more flight hours across the board than the VFR-IMC pilots. These data provide a more 

detailed view of the VFR into IMC accidents and will facilitate the development of future data-driven 

intervention strategies. Current interventions include weather cameras and other pilot aids for decision making 

with regard to weather. 

 

17. Key Words 18. Distribution Statement 

 

 

Weather-related accidents, Visual Flight Rules (VFR) into 

Instrument Meteorological Conditions (IMC), HFACS, 

General Aviation (GA)

Document is available to the public through the 

Defense Technical Information Center, Ft. Belvior, VA 

22060; and the National Technical Information 

Service, Springfield, VA 22161 

19. Security Classif. (of this report) 20. Security Classif. (of this page) 21. No. of Pages 22. Price 

Unclassified Unclassified 16 

Form DOT F 1700.7 (8-72) Reproduction of completed page authorized 

iii

Contents

Introduction. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1

HFACS. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2

Purpose. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2

Method . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2

Human Factors Analysis. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2

Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2

Part I. Comparisons Between VFR-IMC and RoGA . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2

. . Demographics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2

. . Human Error. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4

Part II. In-Depth Examination of VFR-IMC Accidents . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5

. . Demographics. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5

. . Human Error . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6

Discussion. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7

The Next Step .... . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9

References. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10



Glossary of Terms

Skill-based errors (SBEs). SBEs occur with little or no

conscious thought. SBEs can be thought of as “doing”

errors. For instance, littlethought goes into turning one’s

steeringwheelorshiftinggears inanautomobile. Similarly,

basic flightskillssuch asstick and ruddermovements and

visual scanning refer more to how one does something

ratherthanwhere one is going orwhy. The difficultywith

automaticbehaviors isthattheyareparticularlysusceptible

to attention and/or memory failures. As a result, SBEs

suchasthebreakdown in visualscanpatterns, inadvertent

activation/deactivation ofswitches,forgotten intentions,

and omitted items in checklists often appear. Even the

manner (or skill) with which one flies an aircraft (aggressive, tentative, or controlled) can affect safety. 

Decision errors (DE). One of the more common error

forms, DEs,represent conscious, goal-intended behavior

that proceeds as designed, yet the plan proves inadequate

or inappropriate for the situation. These errors typically

manifest themselves as poorly executed procedures,

improper choices, orsimply themisinterpretationand/or

misuse of relevant information.

Perceptual errors (PE). While DE and SBEs have dominated most accident databases and have, therefore, been

included in most error frameworks, the third and final

errorform, PE, hasreceived comparatively less attention. 

Perceiving errors arisewhen sensory input is degraded, or

“unusual” as is often the case when flying at night, in the

weather, or in other visually impoverished environments. 

Aircrew run the risk of misjudging distances, altitude,

and descent rates, as well as responding incorrectly to

a variety of visual/vestibular illusions when faced with

imperfect or incomplete information. 

Violations (V). Routine Vs tend to be habitual by

nature and are often enabled by a system of supervision

and management that tolerates such departures from

the rules (Reason, 1990). Often referred to as “bending

the rules,” the classic example is that of the individual

who drives his/her automobile consistently 5-10 mph

faster than allowed by law. While clearly against the law,

the behavior is, in effect, sanctioned by local authorities

(police) who often will not enforce the law until speeds

in excess of 10 mph over the posted limit are observed.

There are also exceptional Vs, which are isolated

departures from authority, neither typical of the indi-

vidual nor condoned by management. For example,

while authorities might condone driving 65 in a 55

mph zone, driving 105 mph in a 55 mph zone would

almost certainlyresult ina speedingticket. It is important

to note that while most exceptional Vs are appalling,

they are not considered “exceptional” because of their

extreme nature. Rather,they areregarded asexceptional

because they are neither typical of the individual nor

condoned by authority.

Adverse mental states (AMS). Being prepared mentally

is critical in aviation. AMS includetheloss of situational

awareness, mental fatigue, circadian dysrhythmia, and

pernicious attitudessuchasoverconfidence, complacency,

andmisplacedmotivationthatnegatively impactdecisions

and contribute to unsafe acts.

Adverse physiological states (APS). Equally important

however, arethose APS that precludethesafe conduct of

flight. Conditions such as spatial disorientation, visual

illusions, hypoxia, illness, intoxication, and a whole host

ofpharmacological andmedical abnormalities are known

to affect performance. It is important to understand that

conditions like spatial disorientation are physiological

states that cannot be turned on or off – they just exist. 

As a result, these APS often lead to the commission of

unsafe acts like PEs. For instance, it is not uncommon

in aviation for a pilot to become spatially disoriented

(APS) and subsequently misjudge the aircraft’s pitch or

attitude (PE), resulting in a loss of control and/or collision with the terrain.

Physical/mental limitations (PML). PML includes

those instances when necessary sensory information is

either unavailable, or if available, individuals simply do

not have the aptitude, skill, or time to safely deal with

it. There are instances when an individual simply may

not possess the necessary aptitude, physical ability, or

proficiency to operate safely. 

Crew resource management (CRM). There areoccasions

whencrewmembersmaynotfullyunderstandeachother’s

intentions. Whenthis occurs, confusion(AMS) and poor

decisions in the cockpit can result. CRM includes the

failures of both inter- and intra-cockpit communication,

aswell as communicationwithAir Traffic Control(ATC)

and other ground personnel. CRM also includes those

caseswhen individualsfailto coordinate activities before,

during, and after a flight.

Personal readiness (PR). This category includes those

occurrences when individuals have not abided by crew

rest requirements, have improperly self-medicated, or

have not ensured that they are prepared for flight

Technological environment (TE). TE encompasses

the design of equipment and controls, display/interface characteristics, checklist design, and automation. 

Automation designed to improve human performance

can have unforeseen consequences. For example, highly

reliable automation has been shown to induce AMS such

as overconfidence and complacency, resulting in pilots

following the instructions of the automation even when

“common sense” suggests otherwise.

Understanding the Human Factors Associated With Visual Flight Rules

Flight Into Instrument Meteorological Conditions

The 14 CFR Part 91 personal flight was not on a flight plan. Visual meteorological conditions prevailed at the

time of the accident....An individual representing N9523P contacted the Princeton Automated Flight Service Station

(AFSS) at 0455 on the morning of the accident. The individual requested a visual flight rules (VFR) weather briefing

from GPZ [Grand Rapids/Itasca County Airport] to STC [St. Cloud Regional Airport], departing at 0600. The caller

was advised of the current and forecasted conditions along the proposed route of flight, as well as of the Aeronautical

Meteorological Information (AIRMET) in effect at the time. An abbreviated weather briefing was requested from

Princeton AFSS at 0541. Proposed departure time was stated as 0600. During his initial statement to the briefer, the

caller noted that conditions at GPZ were marginal at the time. He noted that current conditions at GPZ were about

2,800 feet overcast and that he was “hoping to slide underneath it and then climb out.” He requested current

conditions at STC and any pilot reports. He was advised of the STC conditions and that no pilot reports were on file

across the state at that time. 

Final Report: The Cirrus SR-22 aircraft was destroyed upon impact with trees and terrain following a loss of altitude during a turn. The accident site was located in relatively level, wooded terrain. The surrounding area was sparsely

populated and heavily wooded. The accident occurred prior to civil twilight and marginal VFR weather conditions

were reported at the departure airport. Cause Report: Spatial disorientation experienced by the pilot, due to a lack of

visual references, and a failure to maintain altitude. Contributing factors were the pilot’s improper decision to attempt

flight into marginal VFR conditions, his inadvertent flight into instrument meteorological conditions, thelow lighting

condition (night) and the trees. 

—NTSB accident report: CHI03FA057

Introduction

While weather-related general aviation (GA) accidents represented a relatively small percentage of the

accidents in 2005, they accounted for nearly 14% of

the fatal accidents involving fixed-wing aircraft with a

gross weight less than 12,500 lbs. Moreover, two-thirds

of weather-related accidents resulted in a fatality. More

than 70% of thefatal weather-related accidents involved

GA pilots operating under visual flight rules (VFR) that

continued into instrument meteorological conditions

(IMC)[Aircraft Owners andPilotsAssociationAir Safety

Foundation (AOPA-ASF), 2006]. 

So why would a pilot fly into adverse weather, know-

ing the hazards associated with such decisions? After all,

every pilot is taught thefundamentals of weatherearly in

training– includinghowtoavoid itbyobtainingpre-flight

weatherbriefings, aswell asrecognizinghazardousweather

conditions in-flight,eitherthroughdirect viewingoutside

the cockpit or with the use of on-board weather radar in

appropriately equipped aircraft. In fact, Title 14 of the

Code of Federal Regulations (CFR) Part 91.103 advises

that all pilots flying instrument flight rules (IFR) or out

of the airport area should be aware ofweatherreports and

forecasts prior to initiating a flight (FAA, 2006).

One explanation could be that pilots continue flying

into poor weather and simply fail to realizethe imminent

danger (Batt & O’Hare, 2005). Goh and Wiegmann

(2001) have suggested that it may be that the decision to

proceed into adverse weather is simply the end result of

poorsituationawareness,hazardousriskperception,moti-

vational factors, or simply improper decision-making. 

Ontheotherhand, itmaybethatsufficientor adequate

weather information is either unavailable or simply not

used. Extracting critical facts from multiple sources of

weather information can be challenging for even the

experienced aviator (Parson, 2006). Moreover, in the

absenceofweatherdisplays,enrouteweather information

is available only to the extent that a pilot seeks it out.

To assist pilots with preflight weather planning and

in-flight decision-making, the FAA recently released a

guideforGApilots(FAA, 2005). The goalwasto provide

guidance to pilots that have little weather experience,

since it appears that many fatal weather-related accidents

tend to occur when pilots have between 50 and 350 total

hours of flight experience (Craig, 2001). 

In theend, no singleexplanation seems to account for

all VFR flight into IMC accidents. Just as experience, as

defined by simple flight hours, cannot explain all VFR 

flight into IMC; neither can motivational factors, poor

situationawareness,lackof knowledge,orpoorpilotdecision-making alone account for these accidents. Rather, it

is probably a combination of all these issues, and perhaps

more, that contributetowhat accident investigatorsrefer

to as VFR flight into IMC (Goh & Wiegmann, 2002). 

The dilemma isthat fewstudies havefully determined

why a pilot would fly into IMC when limited, by train-

ing, to fly under VFR. This is not to say that determined
efforts by private and government organizations have not

been conducted to address this issue; it is just that most

have not investigated all of the causal and contributory

factors associated with these accidents. Instead, they

have typically focused on a few demographic variables

or more conceptual human components, such as theloss

of situation awareness. 

HFACS

Beginning in 1998, the FAA initiated an effort to

analyze all United States (U.S.) civil aviation accidents

with Human Factors Analysis and Classification System

(HFACS), a human error taxonomy used by aviation

and other high-risk industries to identify accident and

incident causal factors attributed to humans atthe operator, supervisory, and organizational levels. 

Although originally developed for use within military

aviation, in recent years HFACS has proven useful in

identifying human causal factors associated with general

and commercial aviation (Detwiler, Hackworth, Holcomb,Boquet,Pfleiderer,Wiegmann,&Shappell, 2006;

Shappell, Detwiler, Holcomb, Hackworth, Boquet, &

Wiegmann,2007;Wiegmann,Faaborg,Boquet, Detwiler,

Holcomb, & Shappell, 2005). A complete description of

HFACS is provided elsewhere (Wiegmann & Shappell,

2003); however, a summary ofthose causal factors associated with general aviation is provided in the Glossary.

Purpose

The purpose of this study was to pair GA accident

causal factors classified with HFACS with traditional

demographic data (whether a flight plan was filed, a

weather briefing was obtained, etc.) in an effort to present a more complete picture of VFR flight into IMC 

accidents. To accomplish this, GA accidents associated

withVFR flight into IMC wereexamined to determine if

there were any potential predictors or causal factors that

set these accidents apart from the rest of GA (RoGA)

accidents.

Method

GA accident data (i.e., 14 CFR Part 91)fromcalendar

years1990-2004wereobtainedfromdatabasesmaintained

by the National TransportationSafetyBoard(NTSB) and

the FAA’s National Aviation Safety Data Analysis Center

(NASDAC, now known as Aviation Safety Information Analysis and Sharing, ASIAS). Only final reports

involving fixed- and rotary-wing aircraft associated with

aircrew error were included in this study. Accidents that

were classifiedashaving “undeterminedcauses” andthose

attributed to sabotage, suicide, or criminal activity (e.g.,

stolen aircraft) were excluded.

Of the 19,137 accidents included in this study, VFR 

flight into IMC (referred to as VFR-IMC) was cited as a

cause or contributing factor by the NTSB in 609 cases. 

Theremaining 18,528 comprised the comparison group

of accidents referred to as RoGA.

Each accident within the database contains a variety

of demographics describing such situational factors as

theenvironment (weather, lighting,etc.), aircraft (make,

model, etc.), and aircrew (flight time, ratings, etc.). In

addition, accidents were selected that were associated

with specific causal/contributory factors attributed to

aircrew error.

Human Factors Analysis

Although the original HFACS framework contains

19 causal categories, most GA accidents involved only

the lower two tiers of HFACS (Unsafe Acts of Operators and Preconditions for Unsafe Acts), since rarely are

supervisory or organizational causal factors cited in the

accidentrecord. Withinthosetiers are10causal categories

that are included in this study: skill based errors (SBE),

decision errors (DE), perceptual errors (PE), violations

(V), adverse mental states (AMS), adverse physiological

states (APS), physical/mental limitations (PML), crew

resource management (CRM), personal readiness (PR),

and technological environment (TE). 

Pilots were recruited from the Oklahoma City area as

subject matter experts (SMEs). Each pilot was provided

roughly 16 hours of instruction on the HFACS framework, which included didactic lecture and practice(with

feedback) using the HFACS framework with NTSB and

NASDAC accidentreports. Aftertraining,thepilot-raters

wererandomly assigned accidents so at least two separate

pilot-raters independently analyzed each accident.

After the pilot-raters assigned their initial codes (i.e.,

SBE, DE, V, etc.), the two independent ratings were

compared. Where disagreements existed, the corresponding pilot-raters were instructed to reconcile their

differences, and the consensus code(s) was included for

further analysis. 

Results

Part I. Comparisons Between VFR-IMC and RoGA 

Demographics

Aircrew Information. Similartootherreports(e.g.,Goh

& Wiegmann, 2002), we found that a higher percentage of those with a private pilot certificate (69.5%) were

involved inVFR-IMC accidents in comparison to RoGA

accidents (Table 1). RoGA pilots had more advanced

certificates (Air Transport Pilot [ATP] – 10.3%, Certified Flight Instructor [CFI] – 15.9%, and Commercial

– 33.5%) and were more likely to be instrument rated;
this is consistent with what others havefound (e.g., Goh

&Wiegmann, 2002). Perhapsequally important may be

the observation that RoGA pilots held a higher number

of multiple certificates than the VFR-IMC pilots (Table

2), suggesting that they may be trained to handle more

complex situations.

Table 1. Crew Certificate and Rating Percentages for 

VFR-IMC and RoGA Groups. 

Certificate/Rating VFR-IMC RoGA 

ATP 5.6 10.3 

CFI 6.7 15.9 

Commercial 27.1 33.5 

Private 69.5 51.2 

Recreational 0.0 0.1 

Student 2.3 9.9 

Instrument- 

 Airplane 33.0 45.8 

 Helicopter 2.6 3.7 

Note. Pilots may have more than one crew certificate and/or rating. 

Table 2. Percentage of Certificates Held 

for VFR-IMC Pilots and RoGA Pilots. 

Number of 

Certificates VFR-IMC RoGA 

1 89.1 80.7 

2 9.8 16.5 

3 1.2 2.8 

4 0.0 0.1 

0

10

20

30

40

50

60

70

80

90

100

Day Twilight Night

Lighting Conditions

Percentage of Accidents

RoGA

VFR-IMC

Figure 2. Percentage of accidents occurring during 

day, twilight, and nighttime conditions for VFR-IMC 

and RoGA accidents. 

Table 3. Median Flight Hours for VFR-IMC 

Pilots and RoGA Pilots. 

Flight Hours VFR-IMC RoGA 

Last 30 Days 10.0 12.0 

Last 90 Days 23.0 29.0 

PIC Make 131.0 93.0 

PIC Alla 408.0 621.0 

Instrument- 

 Simulated 10.0 46.0 

 Actualb

 62.5 76.0 

Total Alla 731.0 758.0 

a

The “PIC All” and “Total All” flight hours excluded any 

cases with a blank or where the database had a value of “0.” 

b

Only the hours in which it was indicated that the pilots 

possessed an instrument rating were included. 

Figure 1. Phase of flight percentages for VFR-IMC 

and RoGA accidents.

0

10

20

30

40

50

60

70

80

90

100

Taxi

Takeoff

Climb

Cruise

Descent

Approach

Landing

Maneuvering

RoGA

VFR-IMC

Phase of Flight

Percentage of Accidents

To determine if there were differences in experience

(measured by flight hours) between VFR-IMC accident

pilots versus RoGA pilots, we examined the median

hours provided in the NTSB reports. An inspection of

Table 3 reveals that with one notable exception (PilotIn-Command [PIC] of make/model of aircraft), RoGA

pilots had earned more flight hours across the board. 

However, the hours flown in the last 30 and 90 days did

not reveal large differences, suggesting that recent flight

experience alone cannot explain differences observed

between the groups. 

Phase of Flight. The highest percentage of accidentsfor

theVFR-IMC group occurred during the cruise phase of

flight,whereasmost RoGAaccidents occurredduring the

landing phase (Figure 1). Less notable differences were

observed during takeoff and maneuvering flight, with

the former being more prevalent during RoGA and the

latter during VFR-IMC.

Physical/Geographic Characteristics. Relatively fewer

VFR-IMC accidents occurred during daylight conditions (64.6%) than RoGA accidents (86.7%; Figure

2). In contrast, although comparatively fewer accidents

occurred during the night, the proportion of VFR-IMC 

accidents was noticeably larger than RoGA.
Similar to previous accident studies (Goh & Wiegmann, 2002), we found that the injury severity for

VFR-IMC accidents was greater than for RoGA (Figure

3). That is, fatalities were much more common in VFRIMC (80.3% vs. 18.8%). Even more important, there

were 954 fatalities associated with the 609 VFR-IMC 

accidents. For the 18,528 RoGA accidents, there were

6,211 fatalities. Therefore, it was not a surprise to find

that aircraft damage that was sustained in a VFR-IMC 

accident was far greater than for RoGA. 

0

10

20

30

40

50

60

70

80

90

100

Fatal Non-Fatal

Injury Severity

Percentage of Accidents

RoGA

VFR-IMC

Figure 3. Injury severity percentages for VFR-IMC 

and RoGA accidents.

0

10

20

30

40

50

60

70

80

90

100

SBE DE PE V

Unsafe Acts

Percentage of Accidents *Percentages do not add up to 100

RoGA

VFR-IMC

Figure 4. Percentages of unsafe acts for VFR-IMC 

and RoGA accidents.

0

10

20

30

40

50

60

70

80

90

100

AMS APS PML CRM PR TE

Preconditions for Unsafe Acts

Percentage of Accidents *Percentages do not add up to 100

RoGA

VFR-IMC

Figure 5. Conditions of the operator percentages for 

VFR-IMC and RoGA accidents. 

Table 4. Percentage of Accidents by the 

Number of Total HFACS Codes for VFR-IMC 

and RoGA. 

Number of HFACS 

Codes 

VFR-IMC RoGA 

1 14.8 43.8 

2 33.3 35.4 

3 25.8 14.2 

4 14.8 4.5 

5 7.4 1.3 

6 1.6 0.4 

7 1.3 0.1 

8 0.8 0.0 

9 0.2 0.0 

Human Error

Unsafe Acts of the Operator. Skill-basederrorsweremore

prevalent in RoGAthan inVFR-IMC (oddsratio=4.167,

χ2 = 332.531, p <.001). Not surprisingly, however,VFRIMC pilots were more likely to commit a decision error

(odds ratio = 2.062, χ2 = 77.961, p <.001); experience

a perceptual error (odds ratio = 3.179, χ2 = 118.350, p

<.001); and commit a violation (odds ratio = 29.960, χ2

= 2454.198, p <.001),see Figure 4. Notethat percentages

across all unsafe acts will not sum to 100 dueto multiple

unsafe acts within an accident.

Preconditions for Unsafe Acts.Figure5revealsthatVFRIMC pilots were more likely to experience an adverse

mental state (odds ratio = 2.906, χ2 = 79.333, p <.001)

and an adverse physiological state (odds ratio = 12.706,

χ2 = 853.764, p <.001). Although statistically significant,

the differences observed between VFR-IMC and RoGA

for physical/mental limitations (odds ratio = 1.877,

χ2 = 36.240, p <.001) and crew resource management

(odds ratio = 1.566, χ2 = 14.052, p <.001) were minor.

In general, multiplefactors cometogether to produce

anaccident. Giventhe alternativescenariosthathavebeen

offeredasprecipitatingVFR-IMC accidents,wesoughtto

findout ifmorehumanerror causalfactorswereprevalent

inVFR-IMC accidents. Our analysesrevealed thatVFRIMC accidents did have a higher percentage of HFACS

codes present in the accident. Assuming that all else is

equal(e.g., the depth and detail of the accident investigations arethesame), this would seem to suggest that there

were more causes and/or factors that were attributable

to human error in VFR-IMC scenarios than in RoGA

(Table 4). The mean number of codes for RoGA was 1.9,

whereas the average for VFR-IMC was 2.8. 
For a better understanding of thespecific human error

causal factors, we looked at the combination of HFACS

codes present within the accidents. As isevident in Table

4, approximately 85.2% of the VFR-IMC and 55.9%

of RoGA accidents had two or more HFACS codes. A

high number (73.9%) of VFR-IMC accidents received

between two and four HFACS codes. The top two most

frequent HFACS combinations are presented for VFRIMC (Table 5a) and RoGA (Table 5b) accidents.

Table 5a. Different Combinations of HFACS 

Codes Present in VFR-IMC Accidents. 

Number of 

HFACS 

Codes 

VFR-IMC N

SBE-V 69 2 DE-SBE 30

DE-SBE-V 21 3 PE-V-APS 13

PE-V-APS-PML 12 4 PE-V-AMS-APS 7

Note. There were 160 different combinations 

present in the accidents with 2 or more codes. The 

codes listed above do not necessarily depict the 

order in which they occurred in the accident 

sequence.

Table 6. VFR-IMC Age Group Distributions. 

Age Groups N Percent 

<30 58 9.6 

30.1 – 40 104 17.2 

40.1 – 50 154 25.4 

50.1 – 60 136 22.4 

60.1> 154 25.4 

Table 5b. Different Combinations of HFACS 

Codes Present in ROGA Accidents. 

Number of 

HFACS Codes 

RoGA N

SBE-SBE 2360 2 DE-SBE 1210

SBE-SBE-SBE 441 3 DE-SBE-SBE 370

SBE-SBE-SBE-PML 79 4 DE-SBE-SBE-SBE 78

Note. There were 495 different combinations present in the 

accidents with 2 or more codes. The codes listed above do 

not necessarily depict the order in which they occurred in 

the accident sequence. 

Table 7. Percentage of Fatal vs. NonFatal for Each VFR-IMC Age Group. 

Age Groups Non-Fatal Fatal 

<30 27.6 72.4 

30.1 – 40 15.4 84.6 

40.1 – 50 20.8 79.2 

50.1 – 60 22.1 77.9 

60.1> 15.6 84.4 

For accidents wheretwo HFACS codes were assigned,

SBEs were more frequently combined with Vs for the

VFR-IMC groupthananyother combination. For RoGA,

the most frequent dual combination was SBE-SBE. 

DE-SBE was thesecond-most frequent combination for

both accident groups. 

When 3 codes were assigned, the most frequent trio

for VFR-IMC was DE-SBE-V versus SBE-SBE-SBE for

RoGA. PE-V-APS-PML was the most frequent set when

4 HFACS codes were identified within VFR-IMC. For

RoGA, the most frequent occurring combination was 4

codes that consisted of 3 SBEs paired with a PML or 3

SBEs paired with a DE. 

In many VFR-IMC accidents, a violation was coded,

which may be a characteristic of this type of accident. 

Nonetheless, these findings illustrate the various human

error complexities that surround a VFR-IMC accident

versus those that occur in other conditions. To further

understand the nuances of VFR-IMC accidents, we

focused several analyses on these accidents solely.

Part II. In-Depth Examination of VFR-IMC Accidents

Demographics

Pilot Characteristics. When pilot agefortheVFR-IMC 

accidents was divided into five groups (<30, 30.1 – 40,

40.1 – 50, 50.1 – 60, and 60.1>), those 30 years and

younger had fewer accidents by comparison (Table 6). 

However, it is possible that this is simply an artifact of

fewer pilots for this age group in general. The remaining

accidents were distributed fairly evenly across the four

age groups. 

Perhaps more important, injury severity was evenly

distributed across age groups (Table 7). 

Asmentionedpreviously,pilotswithfewerflighthours

have been found to be involved in many fatal weatherrelated accidents. Indeed, Craig (2001) referred to the

range of flight hours between 50 and 350 as the “killing

zone.” We found some support for Craig’s hypothesis

in that nearly one-third of the VFR-IMC fatal accident

pilots’ total hours fell within this range. 

To determine what the VFR-IMC pilots may have

understood about the conditions that they were depart-
ing into, we examined the flight plans that were filed

and the type of weather briefing they received. In doing

this, we discovered that the majority (80.0%) did not

file a flight plan, and only 16.7% had a VFR plan on

file (Table 8).

Table 8. Types of Flight Plans Filed for the VFRIMC Accidents. 

Flight Plan Filed N Percent 

Company VFR 14 2.3 

IFR 18 3.0 

None 487 80.0 

Unknown 1 0.2 

VFR/IFR 1 0.2 

VFR 88 14.4 

Table 9. Documented Weather Briefings for 

VFR-IMC Pilots. 

Weather Briefing Percent 

Abbreviated 0.5 

Full 31.3 

Partial-limited by briefer 1.0 

Partial-limited by pilot 9.3 

Unknown 57.2 

Table 10. Top 3 NTSB Subject Codes for Each 

Unsafe Act Within the VFR-IMC Accidents. 

Unsafe Acts Percenta

Skill-based Errors

Clearance 19.4 

Altitude/Clearance 19.0 

Aircraft Control 16.1 

Decision Errors 

VFR Flight into IMC 43.0 

In-Flight Planning/Decision 20.2 

Weather Evaluation 6.8 

Perceptual Error 

Aircraft Control 77.5 

Altitude 5.4 

Descent 2.7 

Violations 

VFR Flight into IMC 85.9 

Flight into Known Adverse Weather 3.6 

Design Stress Limits of A/C 3.2 

a

Percent of each subject code within each of the unsafe acts 

(e.g. – 19.4% of the SBEs involved clearance). 

Table 11. Percentage of Modifier Codes for 

Accidents With VFR Flight Into IMC as a Subject 

Code and Assigned as a Decision Error and/or 

Violation.

Modifier Code Decision Error 

N (%) 

Violation 

N (%) 

Unknown 2 (1.3) 5 (1.1) 

Attempted 2 (1.3) 80 (17.5) 

Continued 6 (4.0) 221 (48.3) 

Inadvertent 135 (89.4) 2 (0.4) 

Intentional — 60 (13.1) 

Inadequate — 1 (0.2) 

Initiated — 28 (6.1) 

Performed — 57 (12.4) 

Encountered 6 (4.0) 4 (0.9) 

It may seem unusual to see an IFR flight plan filed for

a VFR-IMC accident. Each of the situations had special

nuancesthatexplain this “anomaly.” Forexample, an IFR 

flight plan was filed but cancelled prior to the accident,

an IFR flight plan was filed but the pilot was not instrument-rated, or the pilot requested an IFR flight plan in

the air and was waiting for an IFR clearance.

The NTSB was only able to document that pilots

received some type of weather briefing in 42.1% of the

VFR-IMC accidents (Table 9). For the most part, however, it was unknown whether the remaining 57.2% of

the pilots had received any weather information.

Human Error

Unsafe Acts of the Operator. Skill-based errors were

associated with 40.6% of the VFR-IMC accidents. A

more detailed investigation revealed that the main SBE 

wasfailuretomaintainclearancefromterrainor obstacles

(Table 10). Decision errors were associated with 44.7%

of the accidents. Not surprisingly, the primary DE was

inadvertent VFR flight into IMC (Table 11), followed

by in-flight planning/decision-making. Perceptualerrors

were found in 17.4% of the VFR-IMC accidents and

primarily involved the inability to maintain aircraft control. This could betheresult of pilotsexperiencing spatial

disorientation. Violations were associated with 77.2%

of the VFR-IMC accidents. This was not unexpected

as the majority of these were continued VFR flight into

IMC (Table 11), followed by flight into known adverse

weather. 

Preconditions for Unsafe Acts. VFR-IMC pilots

experienced an adverse mental state within 13.3% of the

accidents. More specifically, the pilot’s overconfidence

in personal ability was at the top of the list. Adverse

physiological stateswere apparent in 22.3% of accidents. 

In nearly all (92.1%) of the accidents where an adverse

physiological state was a factor, the precursor was spatial

disorientation. Physical/mental limitation factors played

a role in 19.4% of the VFR-IMC accidents, with lack
of experience present in the vast majority of these situations. Crew resource management factored into 14.3%

of the accidents, of which preflight planning and preparation accounted for 67.4% of these accidents. Personal

readiness and TEs were factors in less than 1% of the

accidents. Table 12 lists the top 2 NTSB subject codes

for each precondition for unsafe acts within the VFRIMC accidents.

Discussion

Weather-related accidents, particularly those associated with VFR flight into IMC, continue to be a threat

to GA safety, given that 80% of the VFR-IMC accidents

resulted in a fatality. This outcome is not unique to the

U.S., as Batt and O’Hare (2005) have found that 76%

of the GA accidents involving VFR flight into IMC in

Australia also resulted in at least one fatality. 

The goal of this study was to further understand the

cause ofVFR flight into IMC by examining demographic

andhumanfactors associatedwiththesetypesof accidents. 

Particular emphasis was placed on how the pattern of

humanerrormaydifferbetweenthose accidents associated

with VFR flight into IMC and those in the rest of GA.

Similar to other reports (Goh & Wiegmann, 2002),

we found that the majority of VFR-IMC accidents

involved non-instrument rated private pilots. Perhaps

not altogether surprising, it was interesting to note that

in comparison, pilots involved in other types of GA

accidents(i.e., RoGA) hadmore certificateratings overall

and were more likely to be instrument rated.

This is not to say that non-instrument rated pilots

are prone to VFR flight into IMC. Assuming flights are

Table 12. Top 2 NTSB Subject Codes for Each 

Precondition for Unsafe Acts Within the VFRIMC Accidents. 

Preconditions for Unsafe Acts Percenta

Adverse Mental States 

Overconfidence in Personal 

Ability 

31.8 

Pressure 28.4 

Adverse Physiological States 

Spatial Disorientation 92.1 

Became Lost/Disoriented 5.0 

Physical/Mental Limitations 

Lack of Experience 93.0 

Lack of Certification 3.1 

Crew Resource Management 

Preflight Planning/ Preparation 67.4 

Preflight Briefing Service 18.0 

a

Percent of each subject code within each of the preconditions 

for unsafe acts (e.g. – 92.1% of APS involved spatial 

disorientation). 

properly planned andweather adequately evaluated,even

thenon-instrumentratedpilotshouldbe abletofly safely. 

However,weshouldrecognizethatnon-instrumentrated

pilots aretaught to avoid weather and havelimited flight

training in simulated instrument conditions. Arguably,

this does not prepare non-instrument rated pilots if they

find themselves in true instrumentmeteorological conditions (Michael Lenz, personal communication). 

The next logical question is whether or not pilots associated with VFR flight into IMC even knew they were about

to encounter hazardous weather. What we do know is that

all pilots flying out ofthe airport area arerequired to educate

themselves abouttheweather conditions andforecastsforthe

area (FAA, 2006). Therefore, it seems reasonable to expect

thateven pilots involved in VFR flight into IMC accidents

were knowledgeable of existing weather conditions. 

Unfortunately, we do not know if the 57.2% of the

pilots that were involved inVFR-IMC accidents actually

obtained a weather briefing. Still, at least 42.1% did get

a weather briefing, according to the accident reports,

and theoretically understood thelikelihood of an adverse

weather encounter en route. In fact, it is quite possible

that the number of pilots obtaining somesort of weather

information prior to flight is higher than reported by the

NTSB, given that many pilots examine weather on the

Internet or listen to an Automatic Terminal Information

Service (ATIS) briefing  something that neither we

nor the NTSB could confirm. When taken together, it

is difficult to know exactly what the pilots actually knew,

and perhapsmore importantly, understood regarding the

conditions they were departing into at the time. 

Althoughthe accidentdata examinedherewouldseem

to suggest that preflight planning and preparation play

an important role in a number of VFR-IMC accidents,

it is difficult to know from the accident record exactly

what weather information the pilot obtained before and

during flight. As a result, we are currently conducting

a follow-up study that involves interviewing GA pilots

that encounter adverse weather. Ideally, by interviewing

pilots directly, we hope to obtain a better understanding

of GA pilot weather decisions. 

Regardless of whether or not pilots involved in VFRIMC accidentsreceived and understood theweatherthey

encountered, most of the accidents occurred en route,

which adds further complexity to the issue of what pilots

knew about the weather at that time. Previous research

(Knecht, in press) has documented the range of weather

products and providers that pilots use in flight planning

and suggests that weather-related accidents are, at least

inpart, information-driven. GAaircraft oncross-country

flights travel at speeds that expose them to the limits of

pre-departure forecasting. It is certainly plausible that

weather at pilots’ destinations may be worse than fore-
casted (Knecht & Lenz, in review). Because of this, these

pilots are exposed to changing weather conditions over

extended space and time. 

In 2005, the NTSB compared GA weather-related accident flights with a matched control group of non-accident

flights and found that pilots on flights of more than 300

nauticalmiles(nm)were4.7timesmorelikely tobe involved

in an accident than pilots on flights of 50 nm or less.

It is important to note that systems and products that

providetimely andaccurateweather informationtopilots

areexpected to be a key part of any intervention aimed at

reducingVFR-IMC. Onesuchproduct isenrouteweather

information availablefromFlightWatch. Unfortunately,

the extent of its utilization and other weather products

used by GA pilots varies widely.

Althoughweather is anobvious concernwhendiscuss-

ing VFR-IMC, flight experience has also been proposed

as an explanation for a number of fatal weather-related

accidents(Craig, 2001). Somesupport of Craig’s hypothesis was found in the data presented here; in that, nearly

one-third of the VFR-IMC fatal accident pilots’ total

hours fell within this range(50 to 350 hours) – although

somewhat lower than the percentage Craig reported. 

Thereason for thelower percentage in this study may be

because we have focused solely on VFR-IMC accidents,

which are a subset of all weather-related accidents. Thus,

whenwelook atweather-related accidents as awhole, the

percentage of fatal accidents is likely to increase.

Often going hand-in-hand with experience, pilot age

may be a viable explanation for VFR-IMC accidents. 

However, our analyses revealed little differences between

the age groups. Interestingly,the NTSB(2005)suggested

that age at certification is a much better predictor regard-

ing weather-related accident involvement than age at the

time ofthe accident. In fact,they arguefurtherthat pilots

who begin their flying careerwhile young arelesslikely to

be involved in a weather-related accident than those who

begin later. They posit that for those that enter aviation

early in life, there may be differences in motivation for

flying and plans for aviation as a career.

Asseen elsewhere,(e.g.,Goh &Wiegmann, 2002)the

majority of theVFR-IMC accidents occurred during the

cruise phase of flight. After all, at least during thetake-off

phase of flight, VFR conditions likely prevail. To some

extent,thesame canbesaidforthelandingphase offlight. 

Typically, it is during cruise that a pilot is more likely

to encounter IMC and be forced to make a decision to

continue or divert to an alternate landing site. 

Additionally, we found a higher proportion of VFRIMC accidents occurred at night. Therefore, it is possible

that pilotsmay not haverecognized or have been unaware

of the severe weather in their path.

Obviously, variables such as age, experience, training,

weather briefings, and phase of flight can prove useful in

the development and targeting of intervention strategies. 

For instance, it can be argued that one way to reduce

accidents associated with VFR flight into IMC is to

provide pilots with better in-flight weather information

through enhanced displays and datalinks.

However, the solution to many human factors issues

facing GApilotstodaymay requiremorethan traditional

approaches such as technological improvements. After

all, no single intervention will likely be the panacea,

and in some cases may actually lead to more problems

than it resolves. For example, Beringer and Ball (2004)

demonstrated that when deciding to fly into, under, or

through theweather, pilotsweremorelikely to do sowith

avionics that had higher resolution. Likewise, Williams,

Yost,Holland, and Tyler(2002)foundthatpilots admitted

that they would be more willing to take a chance and risk

flying closer to the weather when using the displays than

without. They also found that the increase in avionics in

the cockpit caused pilots to rely more on the equipment

than their basic flying skills, in addition to more “headsdown” time in the cockpit. 

So whiletechnological approaches are appealing, they

may provide pilots with an overconfidence of how close

they can get to weather and to navigate through it. On

the other hand, Ball (in review) found that some pilots

canbetrainedtouseweather informationstrategically as a

meansto avoid,ratherthanto tacticallynavigatethrough,

dangerous environments. Clearly, weather information,

with the right training and understanding, can benefit

GA pilots at all levels – although some degree of caution

should be employed when flying in weather. 

Boatman (2001) noted that pilots are taught to be

confident when flying. For less-experienced pilots who

may underestimate the risks of flying in marginal VFR 

conditions, overconfidence in their abilities may conflict

with good decisions in these circumstances. Indeed, we

found that pilots’ overconfidence in their personal ability

was a factor in VFR-IMC accidents.

For years, government and private organizations have

attempted to educate pilots to make informed decisions

when it comesto flying inweather. Work by the FAA(2005)

provides guidance to pilots through a decision-making

framework. It discusses three steps (perceive, process, and

perform) during flight. AOPA-ASF has a variety of free

on-line courses that pilots can take that educate them on

different weather topics. 

In 1989, the NTSB identified many of the same

causes and factors that were found to be an issue in our

analyses. Given thesimilarities, onemight generalizethat

the intervention strategies that have been put in placefor

nearly the past 2 decades have been ineffective. 
Informing pilots of the pitfalls of VFR-IMC with the

hope ofeducating themaboutthe consequences oftaking

risks, the importance of gaining a clear understanding of

the weather within their flight path from departure to

landing, andremindingpilotsthat it istheirresponsibility

to be aware of weather when leaving the airport traffic

area are integral steps to stop the chain ofevents that can

result in a VFR flight into IMC accident. 

Though the suggestion may seem radical, one solution proposed during a brainstorming activity was to

require all pilots to obtain a weather briefing and to file

a flight plan before departure. Limiting this requirement

to those leaving the airport traffic pattern would help

ensure that prior to taking off all pilots were briefed on

the available weather. This assumes that all pilots have

the requisite skills to process the weather information

they are provided.

Knecht, Harris, and Shappell (2005) described the

many findings surrounding the difficulties associated

with pilots assessing the risk of weather. While trying to

ascertain the influence of a variety of motivators for why

GA pilots would depart into marginal conditions, they

found that personality alone did not influence take-off. 

Social-cognitivists (Mischel & Shoda, 1995) have long

argued that understanding personality within a context

is the best predictor for behavior. When money was not

manipulated to be a motivator, Knecht, et al. (2005)

found the interactive effect of visibility and ceiling

encouraged pilots to stay on the ground. One caveat to

consider is half of their participants were instrumentrated, so that additional knowledge may have assisted

decision-making. Nonetheless, the authors concluded

that two groups of weather-risk pilots emerged: 1) those

without an understanding of the risks of weather, and

2) pilots who have little instrument time. Ensuring that

pilots have and understand the weather before departing

sounds like a simple solution, but how can that be done

consistently? It is plausible that if all pilots are required

to document weather awareness prior to departure and

learn howto perceive and processweather,this additional

information could reduce accidents. Knecht and Lenz(in

review) point out that VFR pilots are trained to avoid

bad weather; therefore, when they find themselves in

the midst of poor conditions, they are inexperienced in

navigating their way through it. As noted, the FAA has

made guidance availabletopilots aboutthe complications

and threats of flying in weather. 

We now have a better understanding of the human

error associated with VFR-IMC accidents. But how can

this information help us prevent these accidents from

occurring in the first place? In a separate study, we are

examining the various initiatives in place that are aimed

at reducing VFR-IMC accidents. We plan to present the

various initiatives with the complementing descriptions

of the errors that they are aimed at reducing.

The Next Step ...

Clearly, the data described here paint amore complete

picture of VFR flight into IMC and offer a glimpse at

potential interventionsto addressthisthreattoGAsafety. 

However, many questions remain. For instance, which

of the interventions suggested would have the greatest

impact on VFR flight into IMC? Are similar programs

currently underway within the FAA that can be leveraged in this regard? Are there gaps in existing GA safety

programs that need to be addressed if we are to reduce

VFR flight into IMC?

These are but a few of the questions that must be

answered ifthe prevalence ofVFR-IMC accidents isto be

reduced. The next step in any system safety process after

the hazard has been identified and sufficiently defined is

the identification, development, and assessment of putative interventions. To someextent, thiseffort has already

begun, as described above. However, a second effort is

currently underway that will use the Human Factors

Intervention matriX (HFIX) to identify existing safety

programs that have been implemented in civil aviation

that can be modified or redirected to address VFR flight

into IMC and other threats to GA. 

As depicted in Figure 6, HFIX pits the HFACS causal

categories, as identified within HFACS (e.g., decision

errors,skill-basederrors,perceptualerrors, and violations),

against five common approaches to accident intervention identified within the literature (Shappell & Wiegmann, 2006). Specifically, HFIX employs intervention

approachesthattarget changewithin the 1) organization,

2) human, 3) technology, 4) mission, and 5) physical

environment. Whereas it is not uncommon for organizations to focus on one or two approaches, depending

on the makeup of its staff, HFIX looks at the breadth of

interventions across all five approaches. 

Decision

Errors

Skill-based

Errors

Perceptual

Errors

Violations

Organizational/ 

Administrative

Human/ 

Crew

Technology/ 

Engineering

Task/

Mission

Operational/

Physical 

Environment

Figure 6. The “Human Factors Intervention matriX” (HFIX).
10

Our current effort involves mapping existing and

prospective interventions identified by programs such

as Joint Safety Intervention Teams, Joint Safety Action

Teams, the National Aviation Research Plan, and other

resources into the HFIX matrix. Using HFIX, it will be

possible to identify which programs would significantly

reduce a given type of human error and where gaps in

the current safety strategy exist. The goal is to provide

the FAA with a ready reference of interventions that

target specific types of human error (e.g., VFR flight

into IMC), rather than a type of accident (controlled

flight into terrain) or general error form (e.g., decision

errors), as has been done in the past. Ideally, this datadriven intervention approach will target specific human

errors known to adversely affect general aviation safety. 

Ultimately, this will lead to changes that will improve

safety and decrease fatalities.

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