Volume 7 Number 3

MarineAN IMPROVED OBJECTIVE METHOD

FOR FORECASTING WIND VELOCITYOVER THE NORTH ATLANTIC OCEAN

byStuart Fife Brown (1)

Intercon weather Consultants, Inc.4700 Auth place, Suite 305

Suitland, MD 20746

ABSTRACT

A more comprehensive objective wind velocity techniqueimproves upon the CLU'rent method by more than 2096.Mean geostrophic wind errors of 36 hour 1000 mb progswere determined for 5 Jawt wind categories. The resultsrepresent the combined effect of all wind-influencingfactors and are shown to be functions of velocity andseason.

1. INTRODUCTION

In the marine environment, wind velocitycompared to other weather elemen ts occu­pies a position of prime importance. Windstrength largely determines sea state anddefines the limits of navigation to ocean­going vessels. Thus, the need for improv­ing wind forecasts is a constant challengeto the mar ine meteorologist. If windforecasts are to improve, then objectiveguidance must first improve. Today, ob­jective forecasting techniques are gener­ally accepted to be the nucleus of mostforecasting systems.

The main objective guidance for forecast­ing oceanic winds at the Weather ServiceForecast Office (WSFO) in Washington D.C.is the ser ies of 1000 rob forecast char tscommonly called surface progs. For theper iod of study, these progs were based onthe National Meteorological Center I s (NMC)Primitive Equation model (PE). The PEmodel underwent refinements and improve­ments through the years. In January of1978 the six-layer (6LPE) was replaced bythe finer scale seven-layer model (7LPE)(now replaced by the Spectral model).Quite likely the seven-layer PE was thereason for improved automated wind andwave forecasts in 1978 (2). The mean ab­solute errors (MAE) of both types of fore­casts were lower that year than for anyyear since September 1973 when the ver ifi­cation program began. MAE scores contin­ued low for automated wave forecasts in1979 for the same reason (3).

The improvement process can be carried astep further by amending the current pro­cedure of utilizing the surface prog. In-

stead of reducing geostrophic wind (Vq )by a constant 20% for friction, correc­tions varying with respect to wind magni­tude and season were found to lower MAEscores significantly. These var iableswere developed empirically and representthe combined effect of several wind-influ­encing factors to be listed later. Thispaper treats the factors collectively asthe apparent cause of forecast error char­acteristics. Studies regarding the per­formance of the Spectral model for oceanicwind forecasting have not been made. Nev­er theless, r esul ts from a I imi ted numberof forecasts seem to be compatible withconclusions based on earlier guidancemodels.

The data base for this study was developedfrom verification logs of forecasts madeby the Marine Section of the WSFO in Wash­ington D.C. (1976-1980) (4). Thedependent data covers the summer (June,July and August) and winter (December,January and February) beginning with thesummer of 1976 and ending wi th the summerof 1979. There were 3,461 wind velocityforecast verifications during this time.Indepen- dent data consists of January andJuly of 1980 with 324 verifications.

2. DESCRIPTION OF CURRENT OBJECTIVEFORECAST AND VERIFICATION SYSTEM

From 36 hour surface progs, geostrophicwinds are determined for 10 selected areason the North Atlantic Ocean. These valuesare then reduced 20% to account for sur­face friction 0.80Vg ). The differencebe tween for ecas t and Obser ved values (F-O)is compiled and a monthly MAE is compu­ted. For compar i50n, sub jective for ecas tsare also verified at washington's WSFO.Historically, these forecasts have beenconsistently 20% to 23% better than objec­tive forecasts.

The 10 selected forecast areas of theNorth Atlantic are shown in Figure 1.Each circular area has a diameter of 5°latitude. To verify, at least 2 wind ob­servations by merchant vessels must be re­ceived from within each of the circular

25

.L~J\-~F~-!M.----+A---,M!-;--=J~~J~~A~~S.----.,\O;-t-.N,--*D,-l

MONTH

ffi 8O'..-...---.-r-...---.-r-...~-r-~~-r---,UZ 10OJ[t:[t:

"souU040

~JO

~ 20OJ> 10..

Figure 2. Frequency of verified windforecas ts as per cen ta~e of total for ecastsfor areas defined 1n Figure 1. Summershown as shaded bars and winter, open barsfor period Sept 1973-oec 1979.

OL..J.T"-'+'....c.;..L..L;-'-LtJ'--'-i..L..L';-L'+'~..L..L:\;l--1 2 3 4 5 6 7 8 9 10

FORECAST VERIFICATION AREA

so

0 40WIL

ffiJO>Ulf- 20Ul<l:Uw[t: 10oIL

Tables I and II show the frequency distr i­bution and magnitude of objective forecast

The necessity for recognizing seasonal in­fluence on wind velocity becomes evidentin Figure 3. Here, the average monthlytotal of gale force (34-47 knots) andstorm force (48-63 knots) wind observa­tions are shown. Obviously, there werewell-defined periods of actiVity and in­actiVity on the Nor th Atlantic from Sep­tember 1973 through December 1979.

3. PROFILE OF CURRENT OBJECTIVE FORECASTERRORS

Because of such an extensive forecast areaas portrayed in Figure 1, the number ofver ifications for any of the 10 forecast­ing locations is dependent upon season andlatitude affecting speed, track and inten­sity of storms. Figure 2 illustrates thefr equency distr ibution of forecast ver i fi­cations as a percentage of total possibleverifications. A peak in winter and asecondary peak in summer occurred at sta­tion 7 which is located near a confluenceof sh ipping lanes to Europe and the Medi­terranean. Note also that the location ofmaximum occurrences was farther south dur­ing winter than summer. This fact waslikely a consequence of commercial ship­ping avoiding the major storm tracks ofwinter. The small number of verificationsat some forecast locations may produce abias in results of this study. whetherthe results can be applied to other midand high latitude oceanic locations re­mains to be determined.

" iJf': \,

National Weather Digest

areas. The average value of the observa­tions is then compared with the objectiveforecast to determine forecast error. Inmid 1980 forecast areas and wind categor­ies were revised. Neither dependent norindependent data of this study were inclu­ded under the revised format.

Figure 1. Location and size of areas des­ignated by WSFO Washington for forecastingand verifying wind.

Figure 3. Monthly average wind verifica­tions with gale or storm force velocity(34-63 knots). Sept 1973-Dec 1979.

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Volume 7 Number 3

Table 1. Total summer occurrence and magni tude of objective forecast error for 5 knotwind categories, 1974-1979. showing corresponding mean er ror (F-O) and standard devia-tion (5.) .

FCST ERROR (F - 0) A B

(kt) -)5 -)0 -25 -20 -15 -10 - 5 0 + 5 +10 +15 +20 +25 +)0 (F-O) S.

5 2 14 70 20) 58 -5·66 4.09

10 ) 4 56 2)5 )57 8) 5 -1.87 4.27

15 5 6 56 1)2 1)) )8 5 1 +1.9) 5.25

20 1 ) ) 12 29 5) )) ) +)·54 6.20

25 1 1 11 1) 18 10 +7.04 5·81

)0 5 12 9 2 +11.4 4.20

)5 1 1 1 +11. 7 6.24

40 1 +20.0 0.0

Table II. Total winter occurrence and magnitude of objective forecast error for 5 knotwind categories, 1974-1979, showing corresponding mean error (F-O) and standard devia­tion (5.).

FCSTI- -'ER=Rc:::O:.:.R_('-'F'--.::O~) +__=A=_--E.B_

(kt) -)5 -)0 -25 -20 -15 -10 - 5 0 + 5 +10 +15 +20 +25 +)0 (F-O) Sx

0.0+20.0

2

2

11

5)

)1

15

6

4

2

6)

64

1)

81

)9

)6

72

1

20

10

5

4

1

1

5

1

2

2

1

1

1

1

1

1

1

20

45

50

55

60

5 ) 7 14 28 41 1 -9.68 5.50

6 19 )6 74 118 7) 12 -7.01 6.58

2 28 41 68 8) 45 6 -).75 7.1)

10 44 72 86 52 27 2 -1.64 6.88

40 )) 6 1 +0.67 7.26

5) )0 ) 1 +).45 8.2)

19 16 7 2 +6.87 8.)4

25 19 ) 6 +9.56 8.49

4 10 5 7 +14.6 7.61

4 4 9 ) 2 +16.7 7.))

2 2 +20.6 8.45

10

15

25

)0

)5

40

errors for summer and winter respectively.Operationally, forecasts and verificationsare made to the nearest 5 knots. Some ofthese 5 knot wind categor ies have a con­siderable range of error even though fre­quency at the extremes may be slight. Togive consideration to all occurrences, themean error for each category was deter­mined (Column A). Corresponding StandardDeviations have been listed in Column B.

Figure 4objective

illustrates the distribution offorecast error with respect to

o. a8V q. Depar tur es from the smoothedcurveS were minor wi th the lar gest var ia­tions occurring at strong velocities. Atthis high range the number of verifica­tions was small. The diagram shows thatthe objective wind forecasts were over­forecast for winds 15 knots or greater insummer and 25 knots in winter, with errorslarger in summer than in winter. This be­havior seems consistent wi th the seasons;i.e., greater stability exists in summerbecause water temper a tur es ar e cool er thanthe air. Similarly, less stability is

27

National weather Dlges!

0::+10o<r<r'" 0z"'"~-IO

.­o /

• ••

5. RELIABILITY OF THE NOMOGRAM

o'--'-"O!c--'-~2"O-'~JO"""""-'--,,,o,--'--~sol,;--'---60'!'--~-7"'O~'-dao

GEOSTROPHIC WINO (kts)

Figure 5. Nomogram for converting 1000 rrbgeostrophic wind to sur face wind over theNorth Atlantic Ocean.

Of these var iables, items 2, 3 and 4 ar emore practical to anticipate and thereforeworthy of further study.

4. PROPOSED NOMOGRAM

shows im­the exist-

Wi th dependen t da ta, Tab Ie IVprovement of the Nomogram over

Figure 5 shows the forecasting aidachieved by this study, illustrating therelationship of geostrophic wind to sur­face wind. Given a geostrophic wind val­ue, the forecaster can read sur face winddirectly. The summer and winter curvesare derived from data inherent to Figure4. In the earlier diagram, observed wind,impl ied by the er ror for a 9i ven o. oavgspeed, is plotted wi th respect to the cor­responding full geostrophic wind speed.Selection of the proper curve is made onthe basis of existing air and water tem­perature differences air temperaturewarmer than water, use the ·summer- curve,etc.

A study of winds over Lake Michigan bystrong and Bellaire (7) lends suppert tothe probability that the error curves ofFigure 4 are realistic. The two authorsdescribe a linear increase of the ratio ofgeostrophic wind to ship wind (Vg/Vs )at speeds from 20 to 60 knots. (Valuesfor V~ were estimated from the Strongand Bellaire curve.) Table III indicatesthat their ratios for very unstable condi­tions (Column b) are in good agreementwith ratios derived from the winter curveof Figure 5 (Column d). Strong and Bel­laire identify very unstable conditions toexist when air temperatures are more than10°F colder than water temperatures. Inthis paper, the winter curve also repre­sents colder air than water but withoutfurther definition.

1. Observational errors and localwind speed differences

2. Geostrophic wind measurements3. Curvature of isobars4. Surface friction and stability5. Isallobaric gradient6. Difluence and confluence of iso­

bars7. Hor izontal shear of geostrophic

wind.

Figure 4. Mean error distribution of cur­rent objective wind forecast system (0.8 X1000 rob geostrophic wind) for summer andwinter, Sept 1973-Dec 1979.

-2<lO!:---'--'C;,O-'--=20;;---'-~JOi;;----'--i"';;--'--'50te---'--i60!:---'-~70

Q.8xGEOSTROPHIC WIND (kts)

present duc log winter since air is colderthan water and stronger winds aloft aremore likely to be brought to the sur face.Winds brought to the sur face would havevelocities more consistent with the 1000rob gradient and result in smaller mean er­rors. (The term "stability" used in thispaper refers to air-sea temperature dif­ferences rather than atmospheric stabili­ty). In the lower velocity range (15knots or less) a reversal of error charac­teristics takes place: under casting pro­duces larger errors duc log winter. Sincewind velocities less than 7 m/sec (13.6knots) over water become aerodynamicallysmooth, wind ener gy is not transfer rableto wavelets, the transfer medium (5).Thus, wind stress, equivalent to frictionhere, is diminished and stronger winds areobserved than forecast. The small butrelatively larger errors in winter at lowwind speeds are likely indicative of gust­iness which is proportionally larger atlow velocities.

As previously stated, the distribution ofobjective forecast errors is regarded tobe a function of the combined effect ofvarious wind-determining factors. No at­tempt will be made to evaluate the weightof any separate influence. The followinglist provides the reader of possible con­tributing factors (6):

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Volume 7 Number 3

Table IV. Mean absolute error (MAE) per­formance of proposed objective system(NOMO MAE) compared with current system(PE MAE) and sUbjective forecasts (SUBJMAE'> •

The Nomogram was tested on an independentdata sample as well and found to have asimilar per formance. The independent da taincluded January and July of 1980 with thefollowing MAE performance:

STRONG .. BELLAIRE NOMOGRAM

a b c d

Vg V. vglvs Vo vglvo

20 18·5 1.08 19·8 0.995

)0 22·5 1. )) 2).) 1.27

40 25·0 1.6 26.8 1.48

SO 27·0 1.85 )0.4 1. 65

60 )1.0 1.94 )).8 1.77

ing objective method. The PEls mean abso­lute errors for January and July (Column2) are compared with errors that would beobtained by using the Nomogram (Column3). The Nomogram's annual average is23.8% better than the PEls. The table in­dicates that improvement was realized forboth seasons in each year of the study.Interestingly, Table IV also shows thatthe average MAE of the Nomogram - 4.05 inColumn 3 - approximates the average sub­jective MAE of the washington forecastingstaff - 4.08 in Column 6. Normally sub­jective forecasts have been better thanobjective ones.

ACKNOWLEDGEMENT

The author is indebted to Mr. N. ArthurPore whose comments and suggestions signi­ficantly enhanced the quality of thismanuscript. Also, sincere appreciationand gratitude is directed to the staff ofthe National Weather Service Forecast Of­fice in Washington D.C., particularly Mr.Charles E. Archambault and Mr. Brian G.Smith. Their cooperation and assistancein acquiring forecast verification datawas invaluable.

4. Manile Forecast Verification Logs, 1976-1980,National \oVeather service Forecast Office, Washington D.C.

5. ~ Jill, 1969: On lVind-wave Intemctions. Tech.Report 23-27, Office of Naval Rellearch, Dept. of theNavy.

6. HarY1book on Wave Anal)5~~ am Forecasting, 1976:Mnd-Field Analysis, Chapter 2, \r\brld MeteorologicalOrganization, WMQ-No. 446, 9pp.

7. Strong, A. E., F. R. Bellaire, 1965: The Effect of AirStability on Wind and Waves. Pub. No. 13, Great LakesRe8earch Division, U. of Michigan, pp. 283-289.

Subjective forecasts at WSFO Washingtonhave been consistently better than object­ive forecasts in the past. Since the per­formance of the new objective system isequivalent to that of subjective forecastsnow, perhaps subjective forecasts in thefuture can be improved accordingly.

1. Mr. Brown was serving as a marine forecaster at WSFOWashington at U1e time of his retirement in 1980. He haswritten a numoor of papers relating to marine weather,and saw e.rtensiw duty with the Atlantic Weather Patrolearlier in his career. Cw-rently, he is a IXJrtner with[ntercon Weather Consultants.

2. Pore, N. A., S. F. Brown, 19800.: Improvement in theNational Weather service's North AUantic \-Vfnd and m:zveForecasts. Preprints Second Conference On CoastalMeteorology, Los Angeles, Amer. Meteor Soc., pp. 54-57.

3. Pore, N. A., S. F. Brown, 1980b: Improvement in theNational Weather service's NorU1 Atlantic WaveForecasts. National Weather Digest, Vol. 5, No.4, pp.39-42.

6. CONCLUSIONS

By using the Nomogram developed in thisstudy, mean absolute errors were more than20% lower than values obtained by theexisting objective method. These resultsappl ied to both dependen t and independentdata samples. The reliability of the pro­posed system eas ily lends itself to compu­ter application. For weak or strong gra­dient areas where observations are scarce,the technique can be used to make fore­casts with confidence. The computer-po­tential of this proposed system also al­lows determination of individual nomogramsfor each of the 10 forecasting areas ifdesired.

REFERENCES AND FOOTNOTES

PERCENTIMPROVE­

MENT28.515.523.5

NOMO.MAE

5.604.104.85

PE MAE7.8)4.856.34

January 1980July 1980Average

Table III. Relationship of geostrophicwind (';;!) to ship wind (Vs ) or sur facewind ( ) with respect to Strong andBellaire Ps stUdy and author IS Nomogram.

2 J • 5 •MON!YR

" IMPRVMTPE N,*O OP NOMOGRAM SUBJMAE MAE SlIM WIN MAE

J\IL ,. ).69 2.81 2).8 2·97

JA1l ?? 8.)6 5·51 )4.1 5·58

JUI. ?? 4·54 J.JJ 26.7 ).49

JA1l 78 6.19 5·10 17.6 4.68

J\IL ,6 )·57 ).29 ,.6 J.01

JAN 79 6·)5 5·J) 16.4 5·42

J\IL 79 4·54 2·9.5 )5·0 ).42

AVERAGE 5·)2 4.0.5 2).) 22·7 4.08

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