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Artie Jackson, Brian Newton, Doug Hahn, and Allan Bussey

) contrail prediction technique, a program was initiated to study the weather conditions conducive to the formation of contrails by jet aircraft. The objective of the program is to measure the spatial distribution of atmospheric variables, especially water vapor, with ground-, air-, and space-based sensors, to observe simultaneously aircraft in flight to determine whether they are producing contrails, and to develop a new statistical regression-based contrail forecast algorithm that can be compared with

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Joseph R. Bocchieri, Richard L. Crisci, Harry R. Glahn, Frank Lewis, and Frank T. Globokar

technique. In another approach, Model Output Statistics (MOS) is used to develop probability forecast equationsfor ceiling and visibility. MOS consists of determining a statistical relationship between a predictand andthe forecast output of numerical prediction models. The statistical relationship is determined by screeningregression in this paper. The two numerical models used are the National Meteorological Center's (NMC)primitive equation (PE) model and the Techniques Development Laboratory

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Carl-Axel S. Staël von Holstein

periods. They wereevaluated by a scoring rule and the scores were given as feedback to the participants together with theactual outcomes. On the average the forecasts did not improve on forecasts based on climatology, and thestudy indicates some explanations for this. It also shows how the meteorologists' knowledge could be usedto produce probabilistic forecasts that are better than climatology. The study also covers empirical evalua~tion of different scoring rules and of techniques for aggregating

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Justin J. Traiteur, David J. Callicutt, Maxwell Smith, and Somnath Baidya Roy

. 1999 ; Palmer 2000 ). Recent studies have proposed improvements over the conventional ensemble averaging method. Linear averaging of outputs from individual ensemble members assumes that the individual forecasts are equiprobable and hence can underestimate uncertainty ( Taylor 2004 ; Taylor and Buizza 2006 ). To improve the quantification and further reduce the effects of uncertainty, the individual ensembles can be calibrated against observations. One such calibration technique is Bayesian model

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Norman E. Prosser and Donald S. Foster

the 0000 GMT soundings (evening). In the evening,no further heating is expected from insolation; therefore the existing potential temperatures are averaged.On the 1200 GMT soundings considerable surfaceheating may take place during the day and a maximumsurface temperature is forecast. The average potentialtemperature of the surface layer is considered to bethe one corresponding to the maximum forecast surfacetemperature. An empirical technique is used to forecastthe maximum temperature for the day

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Harry R. Glahn and Dale A. Lowry

technique which consists of determining a statistical relationship between a predictand and variables forecast by a numerical model at someprojection time(s). It is, in effect, the determination of the "weather related" statistics of a numericalmodel. This technique, together with screening regression, has been applied to the prediction of surfacewind, probability of precipitation, maximum temperature, cloud amount, and conditional probability offrozen precipitation. Predictors used include surface

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Paul L. Moore and Daniel L. Smith

to arrive at a reasonably complete echo distribution over the entire area.PEATMOS forecasts have been available on theNAFAX (National Facsimile) circuit since 1 January1972. However, they were run routinely for severalmonths before that date and the Techniques Development Laboratory kindly provided us with the forecastsfor December 1971. Winter precipitation regimes for Atlanta, Birming Code Number Character of 'Echo 0 No echo &lt

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Kristopher M. Bedka and Konstantin Khlopenkov

used increasingly for weather analysis and forecasting applications. It is produced using current GOES 4-km IRW imagery and transmitted in real time to NOAA for evaluation within the GOES-R Proving Ground ( Goodman et al. 2012 ; Gravelle et al. 2016 ). The product has provided the most value to operational settings 1) at night when VIS imagery is unavailable for indicating hazardous storm updrafts, 2) for recognition of hazardous updrafts in regions that are inadequately sampled by weather radars

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Urs Germann and Isztar Zawadzki

weather situation with airmass thunderstorms. In such situations, current nowcasting techniques rarely provide good point forecasts, and only estimates of larger-scale average rainfall amounts are distributed to the users. To filter out the small, perishable, and, thus, nonpredictable scales, Bellon and Zawadzki (1994) proposed to apply spatial averaging to the forecast maps. The length scale of the averaging increases with increasing lead time in a way that prevents the scales from being

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D. S. Wilks

1. Introduction Since the pioneering work of Barnett and Preisendorfer (1987) and Barnston (1994) , statistical seasonal forecasting primarily has been based on the relationships between sea surface temperatures (SSTs) and subsequent seasonal time averages of predictands such as near-surface temperatures. The physical basis for the predictive relationships captured by these statistical forecasting approaches is that the effects of slowly varying boundary conditions such as SSTs are

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