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Anne W. Nolin and Christopher Daly

Abstract

One of the most visible and widely felt impacts of climate warming is the change (mostly loss) of low-elevation snow cover in the midlatitudes. Snow cover that accumulates at temperatures close to the ice-water phase transition is at greater risk to climate warming than cold climate snowpacks because it affects both precipitation phase and ablation rates. This study maps areas in the Pacific Northwest region of the United States that are potentially at risk of converting from a snow-dominated to a rain-dominated winter precipitation regime, under a climate-warming scenario. A data-driven, climatological approach of snow cover classification is used to reveal these “at risk” snow zones and also to examine the relative frequency of warm winters for the region. For a rain versus snow temperature threshold of 0°C the at-risk snow class covers an area of about 9200 km2 in the Pacific Northwest region and represents approximately 6.5 km3 of water. Many areas of the Pacific Northwest would see an increase in the number of warm winters, but the impacts would likely be concentrated in the Cascade and Olympic Ranges. A number of lower-elevation ski areas could experience negative impacts because of the shift from winter snows to winter rains. The results of this study point to the potential for using existing datasets to better understand the potential impacts of climate warming.

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Christopher Daly, Ronald P. Neilson, and Donald L. Phillips

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The demand for climatological precipitation fields on a regular grid is growing dramatically as ecological and hydrological models become increasingly linked to geographic information systems that spatially represent and manipulate model output. This paper presents an analytical model that distributes point measurements of monthly and annual precipitation to regularly spaced grid cells in midlatitude regions. PRISM (Precipitation-elevation Regressions on Independent Slopes Model) brings a combination of climatological and statistical concepts to the analysis of orographic precipitation. Specifically, PRISM 1) uses a digital elevation model (DEM) to estimate the “orographic” elevations of precipitation stations; 2) uses the DEM and a windowing technique to group stations onto individual topographic facets; 3) estimates precipitation at a DEM grid cell through a regression of precipitation versus DEM elevation developed from stations on the cell's topographic facet; and 4) when possible, calculates a prediction interval for the estimate, which is an approximation of the uncertainty involved. PRISM exhibited the lowest cross-validation bias and absolute error when compared to kriging, detrended kriging, and cokriging in the Willamette River basin, Oregon. PRISM was also applied to northern Oregon and to the entire western United States; detrended kriging and cokriging could not be used, because there was no overall relationship between elevation and precipitation. Cross-validation errors in these applications were confined to relatively low levels because PRISM continually adjusts its frame of reference by using localized precipitation-DEM elevation relationships.

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Dale T. Andersen, Christopher P. McKay, and Victor Lagun

Abstract

In November 2008 an automated meteorological station was established at Lake Untersee in East Antarctica, producing a 5-yr data record of meteorological conditions at the lake. This dataset includes five austral summer seasons composed of December, January, and February (DJF). The average solar flux at Lake Untersee for the four years with complete solar flux data is 99.2 ± 0.6 W m−2. The mean annual temperature at Lake Untersee was determined to be −10.6° ± 0.6°C. The annual degree-days above freezing for the five years were 9.7, 37.7, 22.4, 7.0, and 48.8, respectively, with summer (DJF) accounting for virtually all of this. For these five summers the average DJF temperatures were −3.5°, −1.9°, −2.2°, −2.6°, and −2.5°C. The maximum (minimum) temperatures were +5.3°, +7.6°, +5.7°, +4.4°, and +9.0°C (−13.8°, −12.8°, −12.9°, −13.5°, and −12.1°C). The average of the wind speed recorded was 5.4 m s−1, the maximum was 35.7 m s−1, and the average daily maximum was 15 m s−1. The wind speed was higher in the winter, averaging 6.4 m s−1. Summer winds averaged 4.7 m s−1. The dominant wind direction for strong winds is from the south for all seasons, with a secondary source of strong winds in the summer from the east-northeast. Relative humidity averages 37%; however, high values will occur with an average period of ~10 days, providing a strong indicator of the quasi-periodic passage of storms across the site. Low summer temperatures and high wind speeds create conditions at the surface of the lake ice resulting in sublimation rather than melting as the main mass-loss process.

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Gary E. Moore, Christopher Daly, Mei-Kao Liu, and Shi-Jian Huang

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A dry three-dimensional mesoscale model was used to study the diurnal cycle of mountain-valley winds in the southern San Joaquin Valley during a summer day. A scheme for interpolating potential temperature was developed to provide hourly temperature fields to initialize and force the dynamically predicted wind fields. A simplified modeling approach was used to produce steady state solutions that are dynamically consistent with the momentum equation and supplied temperature fields. Model performance was evaluated by comparing observed and predicted surface winds. Some features of the wind field flow aloft were qualitatively examined with regard to their importance in air quality studies.

The morning drainage-upslope transition and the evening reversal of upslope flow were realistically simulated throughout most of the valley. The variation of wind speeds throughout the valley and over the course of the day were simulated with an average bias of 9% of the average wind. Wind directions were simulated with an overall average bias of 5° and midday hourly correlation coefficients of typically r = 0.8. Model performance was below average during the morning and evening transition periods, when thermal forcing is at a minimum and valley winds are light and variable. At midday, the model produces strong upward vertical motions near the ridge crests and divergence-driven subsidences at the foot of the mountains typical of observations made in mountain-valley systems. During the morning, modeled drainage flow down the mountains results in a convergence zone in the southern and narrowest part of the valley, resulting in rising motions; down-valley flow, sometimes observed in mountain-valley systems, also occurs. The model is best suited for applications in mountain-valley regions for which wind observations are sparse and do not adequately reflect thermally driven circulation.

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Christopher Daly, Jonathan W. Smith, Joseph I. Smith, and Robert B. McKane

Abstract

High-quality, daily meteorological data at high spatial resolution are essential for a variety of hydrologic and ecological modeling applications that support environmental risk assessments and decision making. This paper describes the development, application, and assessment of methods to construct daily high-resolution (∼50-m cell size) meteorological grids for the 2003 calendar year in the Upper South Santiam Watershed (USSW), a 500-km2 mountainous catchment draining the western slope of the Oregon Cascade Mountains. Elevations within the USSW ranged from 194 to 1650 m. Meteorological elements modeled were minimum and maximum temperature; total precipitation, rainfall, and snowfall; and solar radiation and radiation-adjusted maximum temperature. The Parameter–Elevation Regressions on Independent Slopes Model (PRISM) was used to interpolate minimum and maximum temperature and precipitation. The separation of precipitation into rainfall and snowfall components used a temperature-based regression function. Solar radiation was simulated with the Image-Processing Workbench. Radiation-based adjustments to maximum temperature employed equations developed from data in the nearby H. J. Andrews Experimental Forest. The restrictive terrain of the USSW promoted cold-air drainage and temperature inversions by reducing large-scale airflow. Inversions were prominent nearly all year for minimum temperature and were noticeable even for maximum temperature during the autumn and winter. Precipitation generally increased with elevation over the USSW. In 2003, precipitation was nearly always in the form of rain at the lowest elevations but was about 50% snow at the highest elevations. Solar radiation followed a complex pattern related to terrain slope, aspect, and position relative to other terrain features. Clear, sunny days with a large proportion of direct radiation exhibited the greatest contrast in radiation totals, whereas cloudy days with primarily diffuse radiation showed little contrast. Radiation-adjusted maximum temperatures showed similar patterns. The lack of a high-quality observed dataset was a major issue in the interpolation of precipitation and solar radiation. However, observed data available for the USSW were superior to those available for most mountainous regions in the western United States. In this sense, the methods and results presented here can inform others performing similar studies in other mountainous regions.

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Nicholas Grant, Laurel Saito, Mark Weltz, Mark Walker, Christopher Daly, Kelley Stewart, and Christo Morris

Abstract

In the arid western United States, wildlife water developments, or “guzzlers,” are important water sources for wildlife, and consist of impermeable roof structures designed to intercept precipitation and small tanks for storing water. Guzzlers are typically installed in remote mid- to high-elevation basins, where precipitation data are often scarce. In this study, small-game guzzlers were examined for feasibility as potential sites for improving estimates of climatic parameters in remote Nevada catchments. Instruments measuring liquid precipitation and water level were installed at two guzzler field sites. Although one field site was vandalized during the study, field results indicated that water levels in the tank measured by Hobo pressure transducers corresponded well with precipitation events measured by the Texas Electronics tipping-bucket rain gauge, and that measured data were similar to Parameter–Elevation Regressions on Independent Slopes Model (PRISM) estimates. Minimum temperatures from the guzzler sites were similar to PRISM; however, maximum temperatures were a few degrees higher, possibly because temperature sensors were unshielded. With over 1600 guzzlers in Nevada and thousands more throughout the western United States, this study initiates exploration of the feasibility of augmenting individual guzzler sites to enhance climatic monitoring at a relatively low cost to improve the quality and density of climate observations, benefitting hydrologists, climatologists, and wildlife managers.

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Mauro Di Luzio, Gregory L. Johnson, Christopher Daly, Jon K. Eischeid, and Jeffrey G. Arnold

Abstract

This paper presents and evaluates a method for the construction of long-range and wide-area temporal spatial datasets of daily precipitation and temperature (maximum and minimum). This method combines the interpolation of daily ratios/fractions derived from ground-based meteorological station records and respective fields of monthly estimates. Data sources for the described implementation over the conterminous United States (CONUS) are two independent and quality-controlled inputs: 1) an enhanced compilation of daily observations derived from the National Climatic Data Center digital archives and 2) the Parameter–Elevation Regressions on Independent Slopes Model (PRISM) maps. The results of this study show that this nonconventional interpolation preserves the spatial and temporal distribution of both the PRISM maps (monthly, topography-sensitive patterns) and the original daily observations. Statistics of a preliminary point comparison with the observed values at high-quality and independent reference sites show a reasonable agreement and a noticeable improvement over the nearest station method in orographically sensitive areas. The implemented datasets provide daily precipitation and temperature values at 2.5-min (around 4 km) resolution for 1960–2001. Combining seamless spatial and temporal coverage and topographic sensitivity characteristics, the datasets offer the potential for supporting current and future regional and historical hydrologic assessments over the CONUS.

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Christopher Daly, Wayne P. Gibson, George H. Taylor, Matthew K. Doggett, and Joseph I. Smith

The Cooperative Observer Program (COOP), established over 100 years ago, has become the backbone of temperature and precipitation data that characterize means, trends, and extremes in U.S. climate. However, significant and widespread biases in the way COOP observers measure daily precipitation have been discovered. These include 1) underreporting of light precipitation events (daily totals of less than 0.05 in., or 1.27 mm), and 2) overreporting of daily precipitation amounts evenly divisible by five- and/or ten-hundredths of an inch, that is, 0.10, 0.25, 0.30 in., etc. (2.54, 6.35, 7.62 mm, etc.). Observer biases were found to be highly variable in space and time, which has serious implications for the spatial and temporal trends and variations of commonly used precipitation statistics. In addition, it was found that few COOP stations had sufficiently complete data to allow the calculation of stable precipitation statistics for a stochastic weather simulation model. Out of more than 12,000 COOP stations nationally, only 784 (6%) passed data completeness and observer bias screening tests for the climatological period 1971–2000. Of the 1221 COOP stations selected for the U.S. Historical Climate Network (USHCN), which provides much of the country's official data on climate trends and variability over the past century, only 221 stations (18%) passed these tests. More effective training materials and regular communication with COOP observers could reduce observer bias in the future. However, it is unlikely that observer bias can be eliminated. One solution is to automate the COOP precipitation measurement system, but this is an expensive option, and may increase other biases associated with automated precipitation measurement. Further analyses are needed to better quantify and characterize observer bias, and to develop methods for dealing with its effects.

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Christopher Daly, Mark P. Widrlechner, Michael D. Halbleib, Joseph I. Smith, and Wayne P. Gibson

Abstract

In many regions of the world, the extremes of winter cold are a major determinant of the geographic distribution of perennial plant species and of their successful cultivation. In the United States, the U.S. Department of Agriculture (USDA) Plant Hardiness Zone Map (PHZM) is the primary reference for defining geospatial patterns of extreme winter cold for the horticulture and nursery industries, home gardeners, agrometeorologists, and plant scientists. This paper describes the approaches followed for updating the USDA PHZM, the last version of which was published in 1990. The new PHZM depicts 1976–2005 mean annual extreme minimum temperature, in 2.8°C (5°F) half zones, for the conterminous United States, Alaska, Hawaii, and Puerto Rico. Station data were interpolated to a grid with the Parameter-Elevation Regressions on Independent Slopes Model (PRISM) climate-mapping system. PRISM accounts for the effects of elevation, terrain-induced airmass blockage, coastal effects, temperature inversions, and cold-air pooling on extreme minimum temperature patterns. Climatologically aided interpolation was applied, based on the 1971–2000 mean minimum temperature of the coldest month as the predictor grid. Evaluation of a standard-deviation map and two 15-yr maps (1976–90 and 1991–2005 averaging periods) revealed substantial vertical and horizontal gradients in trend and variability, especially in complex terrain. The new PHZM is generally warmer by one 2.8°C (5°F) half zone than the previous PHZM throughout much of the United States, as a result of a more recent averaging period. Nonetheless, a more sophisticated interpolation technique, greater physiographic detail, and more comprehensive station data were the main causes of zonal changes in complex terrain, especially in the western United States. The updated PHZM can be accessed online (http://www.planthardiness.ars.usda.gov).

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