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Paul Tattelman

Abstract

An off-the-shelf ice detection system used primarily on aircraft was tested in a climatic chamber, and then in the field to evaluate its ability to estimate the amount of ice simultaneously accreting on various-sized cylinders. The climatic chamber test data indicate that the system output is highly correlated with the mass and thickness of the ice measured on cylinders. A method, developed for utilizing the system for objectively estimating ice accretion amounts on cylinders, based on the chamber test results, is presented. Subsequent field tests indicate the system would be excellent for objectively estimating icing amounts on a cylinder for in-cloud icing on mountaintops. A slight modification is necessary to best use the instrument to estimate icing amounts from freezing rain or drizzle. Relationships of ice accretion characteristics on cylinders 3, 13, 25 and 50 mm in diameter for differing synoptic conditions are also discussed.

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Paul Tattelman

Abstract

Approximately 100 hours of wind records with mean speeds of 20 to 100 kt (at 12 m) were obtained from the Mt. Washington Observatory. Analyses of these data indicate that the gust factor can be used to describe the relationship between mean wind speed and wind speed range for a specific interval of time.

Pooled data recorded at 14 airfields in the Northern Hemisphere were used to develop 50-, 75-, 90-, and 98-percentile gust factor curves for 5 min, 1 min, and 30 s average wind speeds. Also presented are nomograms of the 50-, 75-, 90-, and 98-percentile wind speed ranges for mean speeds of 20 to 100 kt. The results are considered applicable to most airport locations at a height of approximately 15 m above the runway.

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Paul T. Willis and Paul Tattelman

Abstract

The probability of occurrence of extreme rainfall rates is reviewed. The drop-size distributions associated with a range of high rainfall rates are examined using data from tropical storms and hurricanes. Mean drop-size distributions are presented for a range of high rainfall rates, as well as a Γ-distribution fit to the entire set of normalized drop-size distributions. This fit forms the basis for a model drop-size distribution for intense rain. The goodness of fit of the model is examined by comparing it with independent drop-camera measurements of high-rain-rate distributions from several geographic locations. The slope of exponential fits to the distributions are examined for constancy with rainfall rate, and are generally found to decrease with increasing rainfall rate.

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Paul Tattelman and Kathryn G. Scharr

Abstract

A model for estimating one-minute rainfall rates has been developed using stepwise multiple regression analysis. The model is made up of six regression equations to estimate rates that are equalled or exceeded 0.01, 0.05, 0.10, 0.50, 1.0, and 2.0 percent of the time during a month at a given location. Information required to make the estimates consists of monthly mean temperature, monthly mean precipitation, number of days in the month with precipitation (based on any of three threshold values that define a rainy day), and latitude. The model is not valid when the mean monthly temperature is ≤0°C (32°F), when there is less than one rainy day in the month, or when a precipitation index (the ratio of monthly precipitation to the number of rainy days) is less than 2 mm day −1.

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Paul Tattelman and Richard W. Knight

Abstract

A method for extracting 1-min rain rates from original weighing raingage recordings is described. The method allows the retrieval of rates for long periods at approximately 300 United States weather stations. The process combines magnification of original chart records with modern digitizing and filtering techniques to obtain the 1-min data that are ordinarily unreadable. Analyses are presented of the frequency and duration of 1-min rates for these seven locations and an eighth location, for which data were collected using a high speed recorder.

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Paul I. Tattelman and Arthur J. Kantor

Abstract

An objective method for determining probabilities of surface temperature extremes is described herein. Least-squares linear regression equations have been developed to estimate temperatures that would be equaled or surpassed 1, 5 and 10% of the hours at any given location during the warmest and coldest months of the year. These equations are based on an index calculated from three generally available parameters: 1) mean monthly temperature (usually July and January), 2) mean daily maximum temperature for the month and 3) mean daily minimum temperature for the month.

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Paul Tattelman, Kevin P. Larson, and Andrew J. Mazzella Jr.

Abstract

A model for estimating mean monthly total time occurrence for 1-min precipitation rates from monthly climatological variables has been developed. The model has two components: an estimation algorithm for the mean monthly percentage of time in which precipitation occurs and a set of algorithms to derive the mean cumulative distribution function of precipitation rates for a calendar month. Both components were developed using stepwise linear regression analysis applied to a database containing 10 years of 1-min precipitation data from 34 sites throughout the 48 contiguous states of the United States. The required climatological variables are the mean monthly temperature, the mean monthly temperature range, the mean monthly precipitation, and the mean number of days per month with precipitation (based on three commonly used threshold values to define a day with precipitation).

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