Visibility and Processing R. R. Reynolds, NWS/Data Systems, Silver Spring, Md.; and E. Mandel, Federal Aviation Administration, Washington, D.C.

AlAA 19th AEROSPACE SCIENCES MEETING

January 12-15, 1981/St. Louis, Missouri ,

For permission Io copy or republish. conlacl the American institute of Aeronaullcs and Astronautics * 1290 Avenue 01 Ihe Americas. New Vork, N Y 10104

VISIBILITY AND PROCESSING

Richard R. Reynolds Notional Weather Service

Washington, D.C.

Of all the elements of interest to aviation, none is more important than visibility. At the same time., however, none is more difficu1.t to measure. The reasons that visibility is such a difficult element to measure and the efforts underway to find an acceptable solution to the measurement problem are the subjects of this p a p e r . However, the basic reason that visibility is such a tough problem is that it relates to a human. This is different than any other element. Absolute measure- ments to the required accuracies can be made f o r such elements as wind, temperature and pressure. Bradley (1979) has shown that cloud cover, while observed subject- ively today, can also be measured object- ively, if so desired, by various means. 2 Visibility, on the other hand, is subjec- tive. It relates to what a human sees but only if there is a target at that distance. There is no completely objective technique for determining what a human can see.

"After visibilities have been dcter- mined around the entire horizon circle, resolve them into a single value for repor.ting purposes. To do this, use either the greatest distance that can be seen throughout at least half the horizon circle, or if the visibility is varying rapidly during the time of the observa- tion, use the average of all observed values . ' I

There are numerous problems which make it virtually impossible for the observer to precisely carry out these instructions in practice. Some of these are :

1. inability to see around the entire horizon circle at most airports due to obstructions.

2. Lack of adequate numbers of markers and lights at appropriate dis- tances.

In today's system, visibility obser- 3. Markers and lights which do not match the requirements. ("Dark or nearly dark objects viewed against the horizon sky during the day, Or unfocused lights Of moderate i.ntensity (about 25cd) during the night. )

vations, with a minor but important exception to be discussed later, are made in two ways, with a transmissometer and by human observers. These two observations are different and have different applica- tions. The human determines the visibility applicable to the entire airport and its immediate area, while the transmissometer is used to determine Runway Visibility or Runway Visual Range both applicable only to the runwav near which the eouinment is

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4 . Insufficient time available for observers to adapt their eyes to ambient light conditions. Observers often have other duties such as briefing pilots.

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l~ocated. Besides these Droblems. and even if 'The method used by a human observer

to take a visibility observation is described in Federal Meteorological Hand- book #I (FHH #l). The definition of pre- vailing visibility as given in FMN dl is "The greatest visibility equaled or exceed- ed throughout at least half the horizon circle, which need not necessarily he continuous." The prescribed method for determining this val.ue given in FMfl til is as follows:

the observer could follow the above instructions, other factors cause problems:

1. The size of the area observed by the observer is dependent upon the visi- bility itself and, therefore, applies to a different area at different times: e . P . . I - . if-the visiblity is 1/4 mile at his location, the observer cannot determine and, therefore, cannot take into account the visibilitv at another point on the airaort. wherk the visibi.litv mav be difiereit . "Usina all available visibilitv

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markers, deiermine the greatest distances .that can be seen in all directions around the horizon circle. When the visibility is greater than the distance to the far- thest markers, estimate the greatest dis- 'tancr you can see in each direction. Base this estimate on the appearance of the visibility markers. If the markers are visible with sharp outlines and little blurring of color, the visibility is much greater than the distance to the markers.

fied, the visibility is about the same as the distance to that marker."

-, if a marker can barely be seen and identi-

ThlO paper is declared a work Of the US. ~overnrnent and therefore is in the QubllC domain.

2. The visibility determined by an observer is dependent on the observer. It has been shown that various people see different distances under the same con- ditions.

in addition, observers are apparently biased towards certain values when making visibility observations. Many investiga- tors, including Reiss and Eversole (1978), have concluded that visibility observa- tions contain significant bias. They found that observers tend to be biased

t.owards 7 miles, the distance of the furthest visibility marker, towards even numbers, and numbers evenly divided by five.

What is stated above may give the impression that visibility observations are unusable. Of course, we know this is not the case because these observations are used operationally world-wide on a continuous basis. What it does point out, however, is that problems exist with visibility observations and that persons using the observations should understand how they are made so that they will not be led to false conclusions. This point was well made in a comment sent to the Bulletin of the American Meteorological Society by R.eiss and Eversole (1980): "Fewer meteor- ologists than ever before have firsthand knowledge of the routinely taken weather ohservations that form the backbone of our meteorological data base." 5 It is likely that the statement would be just as valid, perhaps more so, if the word "aviators" was substituted for "meteorloeists . I c

A strong point should be made here. The above is not an attempt to fault the job performed by human observers. We belicve that it points out that even doing the best possible job there are unavoid- able problems with human visibility observations. In the course of the dis- cussion below, it will be shown how automatcd observa-tions will correct many of these deficiencies. However, it will also be shown that automated visibility observations have problems of their own.

The principal sensor in use today f o r measurement of visibility is the trans- missometer. Most often this sensor is found as part of a system that outputs Runway Visual Range (RVR), although in some cases data from the transmissometer is used to compute Runway Visibility (RVV). Values of RVR are used as the basis for allowing aircraft to land at the majority of the world's major airports.

The visibility automation problem can be divided into three distinct areas. The first area is measurement technique, the second is sensor acceptance testing, and the third is how to go about processing individual data points from the sensor into meaningful visibility information for the user.

Measurement Technique

In order to understand how visibility sensors work, it is necessary to delve a little into visibility theory. Many sources give exhaustive reviews of visibility theory for those interested, such as Middleton, (1958).

Visibility depends on four factors: the observer, the target (that object to which the visibility is being determined),

the background of the target, and the "clearness" of the atmosphere. Obviously, the targets must be large enough to be seen. Also, there must be some contrast between the target and its background; e.g. a black target against a black background is difficult to see. The ability to s e e the target is, of course, greatly affected by the state of the atmosphere; if the atmosphere is clear, visibility is unlimited. Flowever, as the atmosphere between the observer and the target becomes less clear. as a result of the Dresence of

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particles,'the ability to see the target is reduced. This is due to the fact that the particles scatter and absorb the light from the target that would otherwise reach the observer. A measure of the ability of light to penetrate the atmosphere is known as thc extinction coefficient ( S I . Koschmeider's theory yields a relationship between visibility (V), the contrast of the target against its background (C), and S , under conditions of natural light:

When the target i s an artificial light, Allard's Law is used:

where E the illuminance threshoTd=of the eye and I = the intensity of the light souroe

In equation (1) an assumption must be made regarding the value of C, to be discussed later, while in equation ( 2 ) values must be assigned for ET and I.

Using the above equations as a basis we can now return to a discussion of RVR. An RVR system consists basically of a transmissometer, a day/night switch (a sensor which determines if it is night or day), an RVR computer, and high intensity runway lights. The transmissometer con- sists of a constant lieht source and -- ~~~~

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receiver located some distance away, generally 250 or 500 feet in the United States. The receiver measures the inten- sity of the beam of light after the beam has crossed the path from the transmitter. If the atmosphere along the path is perfectly clear, the intensity of the light will not be reduced. When particles enter the path, the light received at the receiver i s reduced. The percentage of the full output of the source received at the receiver is known as the transmittance. Transmittance (T) is a measure of extinc- tion coefficient, S , and is related to S as follows:

S = - In (T) b

where b is the path length of the transmissometer.

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The calculation of RVR values are made using equations (1) and (2). At night the target is the High Intensity Runway Lights which have three settings (thus, three values for I must be used).

using both equations and the larger value of (1) and (2) taken to be the RVR. Where no High Intensity Runway Lights are installed, a transmissometer can be used to calculate RVV. The calculations are basically the same except that a standard value for the light source is assumed of much lower value than the High Intensity Runway Lights. There is no need, in the RVV case, to calculate (2) during the day because (1) will always be larger. RVR is generally a completely automated system while an observer uses a look-up table to change transmittance to RVV.

-. During the day, calculations are made

The preceding discussion centered on the theoretical concepts which are appli- cable to any sensor measuring extinction coefficient, of which the transmissometer was first among many. The transmissom- eter. however. is not a good choice for

with time - requiring frequent calibra- tion, and the calibration is not absolute, that is, it is relative to "perfectly clear" conditions of unlimited visibility. Acheson (1980), among others, has shown that a reasonably small error in calibra- tion can cause errors of one-eighth mile under low visibilitv conditions. 1

some alternative sensor

The National Weather Service (NWS) has been using automatic weather stations for non-aviation observations for many years. These stations often serve as backups for small airports with daytime- only observers and at locations where staff is non-existent. At such locations, visibility and cloud data are of secondary interest to a weather forecaster. He does, however, need precipitation inten- sity information. It was decided that an Index of Visibility would be very useful in lieu of a precipitation intensity sensor. A simple processing module for these earlier automatic stations was developed which reported three visibility values in whole miles from 1 to 7 . The report gave the current 1-minute averaged index, plus the maximum and minimum values for the past 10 minutes. This gave the forecaster an indication of the variabil- ity of the atmosphere during the sample period. The sensor chosen for this application was a backscatter device. It was chosen because of its rugged design, long calibration interval, and modest cost. Notwithstanding the lack of fractional-mile reports, a modified version of this system, reporting just

use at a few remote alternate airpomts -, the average value, has been approvea for

where the cost of maintaining a human ob- server is prohibitive.

Figure 1 shows the scattering function of light versus the scattering angle, for various low visibility conditions. Note that, at the backscatter angle of about 160 degrees, the scattering functions are not similar. This was dramatically proven in the AV-AWOS tests (using backscatter sensors); the reported visibility in snow consistently differed from prevailing visibility by the amount predicted here. It is significant that there is only one band of angles between 20 and 50 degrees where the percentage is relatively close for all scattering phenomena. This is where the forward scatter device operates.

("1) ,0-3 ..e

SCATTERING FUNCTIONS OF LIGHT IN A I R FOR D I F F E R I N G VISUAL

RANGES

F IGURE I

An analysis of the features of the forilard and backscatter sensors show that both have single pedastal mounting (as opposed to the transmissometer), but both share the disadvantage of smaller measure- ment volumes. in the Sam range. The backscatter device has the dr ,<back of difficult calibration -

The pGice of both types is

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currently the NWS must being the unit back to a central facility. Thus, there is no "winner" in selection by cost of install- ation or maintenance. The attractiveness of the forward scatter device lies in its ability to measure low visi.bilities, regardless of the type of obscuring phenomena.

Sensor Acceptance Testing

A number of different visibility Sensors have been devised and produced based on forward, side, and back scatter principles. However, the following question remains: given a particular instrument how does one establish that it is indeed an accurate measure of extinc- tion coeffici.cnt? An answer to this question is being pursued by a task group of the !.lorking Group on Automation of Surface Observations (WG/ASO), Subcommit- tee on Systems Development under the Interdepartmental Committee f o r l'leteor- ological Services and Supporting Research. WG/ASO is made up of representatives of numerous agencies havi.ng an interest in automated observing systems. Three of these agencies (Federal Aviation Admin- istration (FAA), Air Weather Service, and NWS) have joincd in the development and procurement of a Joint Automated Weather Observation System (JAWOS) which wi.11 be used to take observations supporting meteorological and aviation operations. JAWOS, as well as other, non-federal, systems, will. require an acceptable visibility sensor that is officially acceptable to the agencies involved.

The l.IG/ASO visibili.ty task group has three basic tasks:

1. Define a scnsor or sensors which will be used as standards against which a proposed sensor can be tested.

2. Define the relationship(s) that must exist between the proposed sensor and the standardcs) in order for the proposed sensor to he found acceptahle (pass-fail criteria).

3. Define an acceptable test brd configuration(s) that would provide data necessary to carry out 2.

As far as a standard visibility sensor is concerned, the choice is limited. A first choice is the standard transmjssom- eter which was discussed above. This instrument has the advantage o f being an accepted operational sensor. The inherent accuracy of the transmissometer is consid- ered to be about 20% at visibilities of 10 times the baseline (the distance between transmitter and receiver). The accuracies are somewhat better down to twice the baseline and degraded quickly above 10 times the baseline. For this reason, the standard transmissometer may be an acceptable standard up to visibili-

ties of a mile to a mile and a half. Above a mile and a half, other devices must be used. A possibility is a telephotometcr. This instrument is basically a devicc which can very accurately measure the contrast of an object against the horizon background from which visibility can be calculated. A third possibility which also offers the potential of obtaini.ng data at higher visibilities is to builci a long basel~inf transmissometer.

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Whichever standard or standards m e chosen, the next task is to develop a pass-fail criteria for the device being tested against the standard. Decisions have to be made as to how close the viiluf of S measured by the device under test must be to the standard produced value of S in order to be found acceptable. Grcfit care in handling the data must he takcn due to the different nature of the i . n s l : ru - ments, particularly, the sampling volumn sizes and the fact that two instruments do not sample exactly the same volume of rhe atmosphere. It has been shown that two identical sensors placed next to each o l ' h e ~ can show large variance in visibility values.

Processing

Much effort was expended in the third area by the NWS and FAA during the Aviation Automated Weather Observations System (AV-AWOS) Program. The final report on the AV-AWOS Program ( F M - R D - 7 9 - 6 3 ) (M;irch 1979) details methods, acceptable to N W of processing data from single and multiple sensor visibi.lity and cloud sensor arr,ays into useable data for a surface aviation observation. 2 Some small changes have been and will continue to be made in th<'sc algorithms but they basically remain thr same as in the cited report.

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In essence, these algorithms provide a means to take indi.vidua1 data poi.nts from a sensor or sensors measuring a smcill volume of the atmosphere and integratr. i ~ h e data in time and space (if more than one sensor is involved) and output a visibi~lity value whi.ch approximates a "prevailing" visibility.

In the AV-AWOS tests at Newport News, VA., three backscatter visibility scniori were used. The sensors were placed on the vertices of a triangle with legs of cappr'cjx- imately three mi.les. The nominal center of 'the triangle was the location of t h e human observer. One of the purposcs of the effort was to determine the optimum averaging techniques for the visibility sensor da.ta. It was determined that running 10-minute averages responded to significant visibility changes quickly without responding to small scale varia- tions which were not significant. Results showed that human observations of visihil-

to within 2 1 mile only approximately 7 / 3 ity and the automated observations aereed v

of the time. The reasons for this dis- crepancy are the limitations on the human observations, and some problems with the backscatter visibility sensor as discussed earlier.

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Summary and Conclusion

Visibi.li.ty observations, human as well as automated, have been discussed. it was shown that human observations of visibility have problems which will not apply to automatic observations, but that automatic observations have problems of a different nature. 'Thus, while human observations vary with observer, site, and timc, the automated observation will pro- vide the same output every time the conditions are equal. On the other hand, automated observations rely on a limited sample volume when compared to the human observation.

'The advantages and disadvantages of various sensor technologies were discussed, together with the steps required to suc- cessfully field an operational system for automatical1.y measuring visibility.

it appears that an automatic visibil- ity measurement can best be based on a sensor IJsing the forward scatter principle. There is, however, significant work to be carried out in selection of an operational sensor.

-i References

1) Acheson, D.'J'., 1980: Transmissometer 1:rror Analysis. National Weather Service Equipment Development Labora- tory L.ah Note No. 10, 6 pp.

2) Bradley, J.M., Lefkowitz, and R. Lewis, 1979 : Aviation Automated Observation System (AV-AWOS) . 1J.S. Department of Transportation Report No. TM-RD-79-63, 5 5 pp.

3 ) Middleton. W.L.K.. 1'358; Vision 'Through thc Atmosphere, 'University of 'Toronto rrcss.

4 ) Rciss, N.M., and R . A . Eversole, 1978: Rectification of Prevailing Visibility Statistics. Atmos. Environ., 17, 9115-950.

5) Keiss, N.M., and R.A. Eversole, 1980: Comments on "Climate Without 19 MPII." Bull. Amer. Metcor. Soc., 61, 38-39.