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  • Author or Editor: Nolan Doesken x
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Nolan J. Doesken
and
A. Richard Renquist

Abstract

The use of wind machines for frost protection is common in several large United States fruit producing areas. However, their potential usefulness in western Colorado's high elevation orchards has been uncertain due to the existence of terrain-generated prevailing nocturnal winds. To investigate this problem, wind speeds and temperature inversions were measured in an orchard area of western Colorado during the critical spring period 1982–1986.

Results showed that temperature inversions strong enough to be beneficial in the use of wind machines at the time of the lowest temperature occurred on 4 1% of all nights sampled, on 58% of nights with below freezing temperatures and on 73% of nights with damaging freezes. A weather typing scheme was then employed to separate objectively freeze events that were primarily local in nature (good candidates for mechanical frost protection) from the more widespread advective freezes (difficult to combat with wind machines). Results showed that undisturbed weather patterns accompanied 54% of all nights but 79% of all freeze episodes. This suggests that freezes are predominantly controlled by local factors.

An hour by hour computation of the likely fan effect during all 15 damaging freeze events during the experiment showed that orchard warming would occur during at least part of the night on 93% of the nights. It is now concluded that wind machines are likely to be very beneficial in western Colorado's commercial fruit growing areas.

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Nolan J. Doesken
and
Thomas B. McKee

Abstract

A methodology has been developed to estimate winter design temperatures (temperatures exceeded a specific number of hours during the December through February winter season-an important design parameter in building construction) from synthetic distributions of hourly temperatures for locations where only daily maximum and minimum temperatures are observed. Cumulative distributions of hourly temperatures and daily minimum temperatures were examined at seven different locations in Colorado having 10 or more consecutive years of complete hourly data. A consistent relationship between the two distributions was found for these stations by representing the lower half of each distribution with a best-fit power curve and relating the fitting coefficients. From these relationships an equation was derived that generated the shape of the lower half of the cumulative distribution of hourly temperatures. The only required input parameters are the regression coefficients resulting from the power curve fitting of the observed distribution of daily minimum temperatures.

The method was tested in Colorado stations having both hourly and daily temperature data. Excellent results were obtained for Colorado. Synthesized temperatures at probabilities of up to 0.50 were generally within 0.7°C of the observed values. The method has now been employed to calculate winter design temperatures for dozens of Colorado cities where such information has previously been unavailable.

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Jamie D. Hoover
,
Nolan Doesken
,
Kelly Elder
,
Melinda Laituri
, and
Glen E. Liston

Abstract

Across the globe, wind speed trends have shown a slight decline for in situ meteorological datasets. Yet few studies have assessed long-term wind speed trends for alpine regions or how such trends could influence snow transport and distribution. Alpine-region meteorological stations are sparsely distributed, and their records are short. To increase spatial and temporal coverage, use of modeled data is appealing, but the level of agreement between modeled and in situ data is unknown for alpine regions. Data agreement, temporal trends, and the potential effects on snow distribution were evaluated using two in situ sites in an alpine region [Niwot Ridge in Colorado and the Glacier Lakes Ecological Experiments Station (GLEES) in Wyoming] and the corresponding grid cells of the North American Regional Reanalysis (NARR). Temperature, precipitation, and wind speed variables were used to assess blowing-snow trends at annual, seasonal, and daily scales. The correlation between NARR and in situ datasets showed that temperature data were correlated but that wind speed and precipitation were not. NARR wind speed data were systematically lower when compared with in situ data, yet the frequency of wind events was captured. Overall, there were not many significant differences between NARR and in situ wind speed trends at annual, seasonal, and daily scales, aside from GLEES daily values. This finding held true even when trends presented opposite signatures and slopes, which was likely a result of low trend slopes. The lack of agreement between datasets prohibited the use of NARR to broaden analyses for blowing-snow dynamics in alpine regions.

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