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John F. Weaver and Nolan J. Doesken

Abstract

More than a decade ago, a study was published that identified a short list of precursor conditions for severe thunderstorms on the High Plains of the United States. The present study utilizes data from the summer months of ten convective seasons to estimate how well the criteria fare as a method of forecasting severe weather days in that region.

Results indicate that the technique produces a relatively high success rate in terms of detecting severe weather days for most years studied. False alarms are a bit high in an absolute sense (36% overall), but fall well within acceptable limits in the real world, where the philosophy of “better to overwarn, than underforecast” prevails.

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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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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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David Changnon, Thomas B. McKee, and Nolan J. Doesken

Abstract

Winter snowpack was investigated to determine spatial and temporal climate variability in a five-state region (Colorado, Idaho, Montana, Utah, and Wyoming) in the northern Rocky Mountains, covering the period 1951–85. Annual 1 April snowpack (SN) measurements were selected for analyses.

Three basic and persistent patterns of annual SN values surfaced: years with a consistent anomaly over the entire region (wet or dry); years with a distinct north-to-south gradient; and average years. Nearly 90% of the nonaverage annual SN patterns were explained by the frequency of seven 500-mb winter synoptic patterns.

The wet-north-dry-south gradient SN patterns occurred only before 1974, and the dry-north-wet-south gradient SN patterns did not occur before 1973. The long-term wet and dry periods experienced in the northern and southern areas of the five-state region are due to periods when one of the two north-to-south gradient SN patterns occurred and are explained by the changes in the frequency of synoptic patterns.

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Wendy A. Ryan, Nolan J. Doesken, and Steven R. Fassnacht

Abstract

Ultrasonic snow depth sensors are examined as a low cost, automated method to perform traditional snow measurements. In collaboration with the National Weather Service, nine sites across the United States were equipped with two manufacturers of ultrasonic depth sensors: the Campbell Scientific SR-50 and the Judd Communications sensor. Following standard observing protocol, manual measurements of 6-h snowfall and total snow depth on ground were also gathered. Results show that the sensors report the depth of snow directly beneath on average within ±1 cm of manual observations. However, the sensors tended to underestimate the traditional total depth of snow-on-ground measurement by approximately 2 cm. This is mainly attributed to spatial variability of the snow cover caused by factors such as wind scour and wind drift.

After assessing how well the sensors represented the depth of snow on the ground, two algorithms were created to estimate the traditional measurement of 6-h snowfall from the continuous snow depth reported by the sensors. A 5-min snowfall algorithm (5MSA) and a 60-min snowfall algorithm (60MSA) were created. These simple algorithms essentially sum changes in snow depth using 5- and 60-min intervals of change and sum positive changes over the traditional 6-h observation periods after compaction routines are applied. The algorithm results were compared to manual observations of snowfall. The results indicated that the 5MSA worked best with the Campbell Scientific sensor. The Campbell sensor appears to estimate snowfall more accurately than the Judd sensor due to the difference in sensor resolution. The Judd sensor results did improve with the 60-min snowfall algorithm. This technology does appear to have potential for collecting useful and timely information on snow accumulation, but determination of snowfall to the current requirement of 0.1 in. (0.25 cm) is a difficult task.

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Rebecca A. Bolinger, Christian D. Kummerow, and Nolan J. Doesken

Abstract

Previous research has shown that the temperature and precipitation variability in the Upper Colorado River basin (UCRB) is correlated with large-scale climate variability [i.e., El Niño–Southern Oscillation (ENSO) and Pacific decadal oscillation (PDO)]. But this correlation is not very strong, suggesting the need to look beyond the statistics. Looking at monthly contributions across the basin, results show that February is least sensitive to variability, and a wet October could be a good predictor for a wet season. A case study of a wet and a dry year (with similar ENSO/PDO conditions) shows that the occurrence of a few large accumulating events is what drives the seasonal variability, and these large events can happen under a variety of synoptic conditions. Looking at several physical factors that can impact the amount of accumulation in any given event, it is found that large accumulating events (>10 mm in one day) are associated with westerly winds at all levels, higher wind speeds at all levels, and greater amounts of total precipitable water. The most important difference between a large accumulating and small accumulating event is the presence of a strong (>4 m s−1) low-level westerly wind. Because much more emphasis should be given to this more local feature, as opposed to large-scale variability, an accurate seasonal forecast for the basin is not producible at this time.

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Peter E. Goble, Nolan J. Doesken, Imke Durre, Russ S. Schumacher, Abigail Stewart, and Julian Turner

Abstract

Every day, thousands of volunteers across the United States report the amount of precipitation they have received in the past 24 hours. This study focuses on the largest of these volunteer-submitted reports for each day, using precipitation measurements from the Community Collaborative Rain, Hail and Snow Network (CoCoRaHS) from January 2010 to December 2017 as well as observations from the U.S. Cooperative Observer Program (COOP) network from January 1981 through December 2017. Results provide clarity on spatial variability, temporal variability, and seasonal cycle of contiguous U.S daily precipitation extremes (DPEs). During 2010–17, the DPEs ranged from 11 mm on 28 March 2013 in Oregon to 635 mm on 27 August 2017 in Texas during Hurricane Harvey. Coastal states are most prone to high daily precipitation totals, especially those bordering the Gulf of Mexico or Atlantic Gulf Stream. The average DPE value varies with season; it is greater than 175 mm in late August and less than 100 mm through meteorological winter. These observations also show that location of the DPE varies with season as well. For example, 28.5% of February extremes fall in Pacific states, whereas all August extremes occur east of that region. Perhaps most importantly, these findings demonstrate strength in numbers. The large daily sample size of CoCoRaHS and COOP networks forms a basis for monitoring, mapping, and categorizing DPEs, and other aspects of extreme precipitation, with considerable spatial detail.

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Walter A. Petersen, Lawrence D. Carey, Steven A. Rutledge, Jason C. Knievel, Nolan J. Doesken, Richard H. Johnson, Thomas B. McKee, Thomas Vonder Haar, and John F. Weaver

On the evening of 28 July 1997 the city of Fort Collins, Colorado, experienced a devastating flash flood that caused five fatalities and over 200 million dollars in damage. Maximum accumulations of rainfall in the western part of the city exceeded 10 in. in a 6-h period. This study presents a multiscale meteorological overview of the event utilizing a wide variety of instrument platforms and data including rain gauge, CSU–CHILL multiparameter radar, Next Generation Radar, National Lightning Detection Network, surface and Aircraft Communication Addressing and Reporting System observations, satellite observations, and synoptic analyses.

Many of the meteorological features associated with the Fort Collins flash flood typify those of similar events in the western United States. Prominent features in the Fort Collins case included the presence of a 500-hPa ridge axis over northeastern Colorado; a weak shortwave trough on the western side of the ridge; postfrontal easterly upslope flow at low levels; weak to moderate southwesterly flow aloft; a deep, moist warm layer in the sounding; and the occurrence of a quasi-stationary rainfall system. In contrast to previous events such as the Rapid City or Big Thompson floods, the thermodynamic environment of the Fort Collins storm exhibited only modest instability, consistent with low lightning flash rates and an absence of hail and other severe storm signatures.

Radar, rain gauge, and lightning observations provided a detailed view of the cloud and precipitation morphology. Polarimetric radar observations suggest that a coupling between warm-rain collision coalescence processes and ice processes played an important role in the rainfall production. Dual-Doppler radar and mesoscale wind analyses revealed that the low-level flow field associated with a bow echo located 60 km to the southeast of Fort Collins may have been responsible for a brief easterly acceleration in the low-level winds during the last 1.5 h of the event. The enhanced flow interacted with both topography and the convection located over Fort Collins, resulting in a quasi-stationary convective system and the heaviest rainfall of the evening.

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John L. Campbell, Lindsey E. Rustad, Sarah Garlick, Noah Newman, John S. Stanovick, Ian Halm, Charles T. Driscoll, Brian L. Barjenbruch, Elizabeth Burakowski, Steven D. Hilberg, Kristopher J. Sanders, Jason C. Shafer, and Nolan J. Doesken

Abstract

Ice storms are important winter weather events that can have substantial environmental, economic, and social impacts. Mapping and assessment of damage after these events could be improved by making ice accretion measurements at a greater number of sites than is currently available. There is a need for low-cost collectors that can be distributed broadly in volunteer observation networks; however, use of low-cost collectors necessitates understanding of how collector characteristics and configurations influence measurements of ice accretion. A study was conducted at the Hubbard Brook Experimental Forest in New Hampshire that involved spraying water over passive ice collectors during freezing conditions to simulate ice storms of different intensity. The collectors consisted of plates composed of four different materials and installed horizontally; two different types of wires strung horizontally; and rods of three different materials, with three different diameters, and installed at three different inclinations. Results showed that planar ice thickness on plates was 2.5–3 times as great as the radial ice thickness on rods or wires, which is consistent with expectations based on theory and empirical evidence from previous studies. Rods mounted on an angle rather than horizontally reduced the formation of icicles and enabled more consistent measurements. Results such as these provide much needed information for comparing ice accretion data. Understanding of relationships among collector configurations could be refined further by collecting data from natural ice storms under a broader range of weather conditions.

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Timothy J. Lang, L. Jay Miller, Morris Weisman, Steven A. Rutledge, Llyle J. Barker III, V. N. Bringi, V. Chandrasekar, Andrew Detwiler, Nolan Doesken, John Helsdon, Charles Knight, Paul Krehbiel, Walter A. Lyons, Don MacGorman, Erik Rasmussen, William Rison, W. David Rust, and Ronald J. Thomas

During May–July 2000, the Severe Thunderstorm Electrification and Precipitation Study (STEPS) occurred in the High Plains, near the Colorado–Kansas border. STEPS aimed to achieve a better understanding of the interactions between kinematics, precipitation, and electrification in severe thunderstorms. Specific scientific objectives included 1) understanding the apparent major differences in precipitation output from supercells that have led to them being classified as low precipitation (LP), classic or medium precipitation, and high precipitation; 2) understanding lightning formation and behavior in storms, and how lightning differs among storm types, particularly to better understand the mechanisms by which storms produce predominantly positive cloud-to-ground (CG) lightning; and 3) verifying and improving microphysical interpretations from polarimetric radar. The project involved the use of a multiple-Doppler polarimetric radar network, as well as a time-of-arrival very high frequency (VHF) lightning mapping system, an armored research aircraft, electric field meters carried on balloons, mobile mesonet vehicles, instruments to detect and classify transient luminous events (TLEs; e.g., sprites and blue jets) over thunderstorms, and mobile atmospheric sounding equipment. The project featured significant collaboration with the local National Weather Service office in Goodland, Kansas, as well as outreach to the general public. The project gathered data on a number of different cases, including LP storms, supercells, and mesoscale convective systems, among others. Many of the storms produced mostly positive CG lightning during significant portions of their lifetimes and also exhibited unusual electrical structures with opposite polarity to ordinary thunderstorms. The field data from STEPS is expected to bring new advances to understanding of supercells, positive CG lightning, TLEs, and precipitation formation in convective storms.

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