Two-dimensional modeling for lineal and areal probabilities of weather conditions

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050 1 4 ‡aQC807.5 ‡b.U55 no.875
074 ⊔ ⊔ ‡a421-E-6 (microfiche)
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088 ⊔ ⊔ ‡aAFGL TR 84-126
100 1 ⊔ ‡aBurger, Charles F., ‡eauthor.
245 1 0 ‡aTwo-dimensional modeling for lineal and areal probabilities of weather conditions / ‡cCharles F. Burger, Irving I. Gringorten.
260 ⊔ ⊔ ‡aHanscom AFB, Massachusetts : ‡bAtmospheric Sciences Division, Air Force Geophysics Laboratory, ‡c[1984]
300 ⊔ ⊔ ‡a58 pages : ‡billustrations ; ‡c28 cm
336 ⊔ ⊔ ‡atext ‡btxt ‡2rdacontent
337 ⊔ ⊔ ‡aunmediated ‡bn ‡2rdamedia
338 ⊔ ⊔ ‡avolume ‡bnc ‡2rdacarrier
490 0 ⊔ ‡aEnvironmental research papers ; ‡vno. 875
490 0 ⊔ ‡aAFGL-TR ; ‡v84-0126
500 ⊔ ⊔ ‡a"10 April 1984."
500 ⊔ ⊔ ‡aDistributed to depository libraries in microfiche.
500 ⊔ ⊔ ‡aCover title.
504 ⊔ ⊔ ‡aIncludes bibliographical references (page 45).
513 ⊔ ⊔ ‡aScientific.
520 ⊔ ⊔ ‡aSingle-point probabilities of weather conditions, which are easily estimated from climatic records, have been extended to lines and areas by means of Monte Carlo simulation. Simulation was accomplished using the Boehm Sawtooth Wave (BSW) model. This model was chosen because of its speed and simplicity, and because it has a spatial correlation function similar to that of many weather elements. The BSW model generates fields (or maps) of normally distributed values called Equivalent Normal Deviates (ENDs). The procedure was to obtain the cumulative probability distribution for threshold END values. To do this, a large number of maps had to be generated, 25,000 in all, to approximate the true probability distributions. This was done for 12 different sized square areas and lines. The results were put in graphical form by plotting the probabilities as a function of areal and lineal size, and fitting them to curves through hand analysis. The curves were then fitted by equations, making it possible to obtain solutions quickly by computer. Thus, a model has been produced that can be used to estimate the probability that a certain weather condition will cover a given area or length, or fraction of an area or length.
536 ⊔ ⊔ ‡d62101F, ‡d6670, ‡d09, ‡d10.
538 ⊔ ⊔ ‡aMode of access: Internet.
650 ⊔ 7 ‡aWeather forecasting. ‡2fast ‡0(OCoLC)fst01173142
650 ⊔ 7 ‡aProbability forecasts (Meteorology) ‡2fast ‡0(OCoLC)fst01077754
650 ⊔ 7 ‡aMonte Carlo method. ‡2fast ‡0(OCoLC)fst01025819
650 ⊔ 0 ‡aMonte Carlo method.
650 ⊔ 0 ‡aWeather forecasting.
650 ⊔ 0 ‡aProbability forecasts (Meteorology)
700 1 ⊔ ‡aGringorten, Irving I., ‡eauthor.
710 2 ⊔ ‡aU.S. Air Force Geophysics Laboratory. ‡bAtmospheric Sciences Division, ‡esponsor.
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