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contributor authorA. Grosjean
contributor authorJ. L. Kueny
date accessioned2017-05-08T23:00:27Z
date available2017-05-08T23:00:27Z
date copyrightMarch, 1976
date issued1976
identifier issn0022-0434
identifier otherJDSMAA-26034#49_1.pdf
identifier urihttp://yetl.yabesh.ir/yetl/handle/yetl/88509
description abstractThis paper illustrates the use of statistical methods such as multiple correlation analysis, discriminant analysis and principal component analysis for weather forecasting. Two examples are presented: the first is a qualitative local prediction of daily precipitation for the next day, using pressure measures of the present day and of past days, by means of discriminant analysis; the second is an analysis of the 500-mbar geopotential heights over Western Europe by means of principal component analysis, followed by a quantitative synoptic prediction of the evolution of these geopotential heights for the next week to come, by means of multiple correlation analysis. For each of these two prediction problems, good predictors are chosen among a great number of candidate ones by a special stepwise selection procedure.
publisherThe American Society of Mechanical Engineers (ASME)
titleStatistical Weather Forecasting
typeJournal Paper
journal volume98
journal issue1
journal titleJournal of Dynamic Systems, Measurement, and Control
identifier doi10.1115/1.3426984
journal fristpage49
journal lastpage55
identifier eissn1528-9028
keywordsWeather forecasting
keywordsPrincipal component analysis
keywordsPressure AND Precipitation
treeJournal of Dynamic Systems, Measurement, and Control:;1976:;volume( 098 ):;issue: 001
contenttypeFulltext


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