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Michael A. Palecki and Pavel Ya. Groisman

Abstract

The U.S. Climate Reference Network (USCRN) was deployed between 2001 and 2008 for the purpose of yielding high-quality and temporally stable in situ climate observations in pristine environments over the twenty-first century. Given this mission, USCRN stations are engineered to operate largely autonomously with great reliability and accuracy. A triplicate approach is used to provide redundant measurements of temperature and precipitation at each location, allowing for observations at a specific time to be compared for quality control. This approach has proven to be robust in the most extreme environments, from extreme cold (−49°C) to extreme heat (+52°C), in areas of heavy precipitation (4700 mm yr−1), and in locations impacted by strong winds, freezing rain, and other hazards. In addition to a number of stations enduring extreme winter environments in Alaska and the northern United States, seven of the USCRN stations are located at elevations over 2000 m, including stations on Mauna Loa, Hawaii (3407 m) and on Niwot Ridge above Boulder, Colorado (2996 m). The USCRN temperature instruments and radiation shield have also been installed and run successfully at a station on the Quelccaya Ice Cap in Peru (5670 m). This paper reviews the performance of the USCRN station network during its brief lifetime and the potential utility of its triplicate temperature instrument configuration for measuring climate change at elevation.

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Daniel J. Leathers and Michael A. Palecki

Abstract

The PNA teleconnection index, a measure of the strength and phase of the Pacific/North American teleconnection pattern, is used to examine changes in the midtropospheric flow over North America on decadal, interannual, and intra-annual time scales. The index corroborates previous findings that a major change in the midtropospheric circulation took place over North America during the late 1950s. The time series of index values also demonstrates the existence of a previously unknown quasi periodicity in the configuration of midtropospheric heights over the North American sector.

A seasonal specification analysis is conducted to identify climate system components that are closely linked to the PNA teleconnection. The selection of predictor variables is based on recent modeling and observational work suggesting their probable involvement with midiatitude flow variations. These include sea surface temperatures for locations in the tropical Pacific and North Pacific, along with Asian land surface temperatures and upper-level pressure gradients associated with the East Asian jet. Results suggest that the response of the midtropospheric flow over North America to these variables has a seasonal dependence consistent with theoretical studies. In winter months the explained variance is relatively high, with both tropical and midlatitude variables influencing the specification equations. During spring, the explained variance reaches a maximum, with only midiatitude variables having significant association with PNA index variations. The summer and autumn seasons show no significant association between Pacific basin variables and PNA index variations.

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Michael A. Palecki, Stanley A. Changnon, and Kenneth E. Kunkel

The July 1999 heat wave in the Midwest was an event of relatively long duration punctuated by extreme conditions during its last 2 days. The intensity of the heat wave on 29 and 30 July rivaled that of the 1995 heat wave that killed more than 1000 people in the central United States. In 1999, however, the death toll was about one-fourth of this amount in the same region. The 1999 heat wave 2-day maximum apparent temperature was slightly less than during the 1995 heat wave at most Midwestern first-order stations. In addition, the 2-day peak was preceded by several hot days that allowed some short-term acclimatization to occur prior to the intense final days. In Chicago, conditions during the peak of the 1999 heat wave were very similar to those during the 1995 heat wave peak, especially the extreme nocturnal conditions of temperatures and humidity. Therefore, it seems unlikely that the reduction in the heat wave death toll in Chicago from about 700 in 1995 to 114 in 1999 is due solely to meteorological differences between the two heat waves. In St. Louis, the 1999 heat wave was intense for a much longer duration than the 1995 heat wave, thus partially explaining the increase in heat-related deaths there from the 1995 event to the 1999 event.

An examination of heat wave response efforts in both Chicago and St. Louis leads to the conclusion that both cities were quite effective at mitigating their respective heat wave mortality rates, which in the 1999 event were almost exactly the same in both metropolitan areas. This represents a great improvement for the city of Chicago compared to the 1995 heat wave. Suggestions are made for further improving municipal heat wave response efforts based on the 1999 experience.

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Ronald D. Leeper, Jared Rennie, and Michael A. Palecki

Abstract

The U.S. Cooperative Observer Program (COOP) network was formed in the early 1890s to provide daily observations of temperature and precipitation. However, manual observations from naturally aspirated temperature sensors and unshielded precipitation gauges often led to uncertainties in atmospheric measurements. Advancements in observational technology (ventilated temperature sensors, well-shielded precipitation gauges) and measurement techniques (automation and redundant sensors), which improve observation quality, were adopted by NOAA’s National Climatic Data Center (NCDC) into the establishment of the U.S. Climate Reference Network (USCRN). USCRN was designed to provide high-quality and continuous observations to monitor long-term temperature and precipitation trends, and to provide an independent reference to compare to other networks. The purpose of this study is to evaluate how diverse technological and operational choices between the USCRN and COOP programs impact temperature and precipitation observations. Naturally aspirated COOP sensors generally had warmer (+0.48°C) daily maximum and cooler (−0.36°C) minimum temperatures than USCRN, with considerable variability among stations. For precipitation, COOP reported slightly more precipitation overall (1.5%) with network differences varying seasonally. COOP gauges were sensitive to wind biases (no shielding), which are enhanced over winter when COOP observed (10.7%) less precipitation than USCRN. Conversely, wetting factor and gauge evaporation, which dominate in summer, were sources of bias for USCRN, leading to wetter COOP observations over warmer months. Inconsistencies in COOP observations (e.g., multiday observations, time shifts, recording errors) complicated network comparisons and led to unique bias profiles that evolved over time with changes in instrumentation and primary observer.

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Ronald D. Leeper, Michael A. Palecki, and Egg Davis

Abstract

The U.S. Climate Reference Network (USCRN) monitors precipitation using a well-shielded Geonor T-200B gauge. To ensure the quality and continuity of the data record, the USCRN adopted an innovative approach to monitor precipitation using redundant technology: three vibrating-wire load sensors measuring the liquid depth of a weighing-bucket gauge. In addition to detecting and flagging suboptimally operating sensors, quality assurance (QA) approaches also combine the redundant observations into a precipitation measurement. As an early adopter of this technology, USCRN has pioneered an effort to develop QA strategies for such precipitation systems.

The initial USCRN approach to calculating precipitation from redundant depth observations, pairwise calculation (pairCalc), was found to be sensitive to sensor noise and gauge evaporation. These findings led to the development of a new approach to calculating precipitation that minimized these nonprecipitation impacts using a weighted average calculation (wavgCalc). The two calculation approaches were evaluated using station data and simulated precipitation scenarios with a known signal. The new QA system had consistently lower measures of error for simulated precipitation events. Improved handling of sensor noise and gauge evaporation led to increases in network total precipitation of 1.6% on average. These results indicate the new calculation system will improve the quality of USCRN precipitation measurements, making them a more reliable reference dataset with the capacity to monitor the nation’s precipitation trends (mean and extremes). In addition, this study provides valuable insight into the development and evaluation of QA systems, particularly for networks adopting redundant approaches to monitoring precipitation.

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Daniel J. Leathers, Brent Yarnal, and Michael A. Palecki

Abstract

The Pacific/North American (PNA) teleconnection index, a measure of the strength and phase of the PNA teleconnection pattern, is related to the variations of the surface climate of the United States from 1947 through 1982 for the autumn, winter, and spring months when the PNA is a main mode of Northern Hemisphere midtropospheric variability. The results demonstrate that the PNA index is highly correlated with both regional temperature and precipitation. The strongest, most extensive correlations between the index and temperature are observed in winter, but large areas of the country show important associations during the spring and autumn as well. Although the centers of highest correlation migrate systematically with changes in the circumpolar vortex over the course of the annual cycle, the southeastern and northwestern parts of the United States possess consistently high index-temperature correlations.

Correlations between the PNA index and precipitation are weaker and less extensive than those for temperature, but large coherent regions of high correlations are observed across the nation. Winter and early spring exhibit the strongest relationships because spatially coherent synoptic-scale systems, related to the long-wave pattern, control precipitation. The late spring and early autumn seasons have the least extensive and weakest correlations due to the importance of less organized smaller-scale convective rainfall events.

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James R. Angel, Michael A. Palecki, and Steven E. Hollinger

Abstract

Soil erosion is a major global challenge. An increased understanding of the mechanisms driving soil erosion, especially the storms that produce it, is vital to reducing the impact on agriculture and the environment. The objective of this work was to study the spatial distribution and time trends of the soil erosion characteristics of storms, including the maximum 30-min precipitation intensity (I 30), storm kinetic energy of the falling precipitation (KE), and the storm erosivity index (EI) using a long-term 15-min precipitation database. This is the first time that such an extensive climatology of soil erosion characteristics of storms has been produced. The highest mean I 30, KE, and EI values occurred in all seasons in the southeastern United States, while the lowest occurred predominantly in the interior west. The lowest mean I 30, KE, and EI values typically occurred in winter, and the highest occurred in summer. The exception to this was along the West Coast where winter storms exhibited the largest mean KE and EI values. Linear regression was used to identify trends in mean storm erosion characteristics for nine U.S. zones over the 31-yr study period. The south-central United States showed increases for all three storm characteristics for all four seasons. On the other hand, higher elevations along the West Coast showed strong decreases in all three storm characteristics across all seasons. The primary agricultural region in the central United States showed significant increases in fall and winter mean EI when there is less vegetative cover. These results underscore the need to update the storm climatology that is related to soil erosion on a regular basis to reflect changes over time.

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Michael A. Palecki, James R. Angel, and Steven E. Hollinger

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Climate studies of precipitation have generally focused on daily or longer time scales of precipitation accumulation. The main objective of this work was to identify the precipitation characteristics of storms based on 15-min precipitation data, including storm total precipitation, storm duration, mean storm intensity, and maximum 15-min intensity. A group of precipitation characteristics was subjected to a cluster analysis that identified nine regions of the conterminous United States with homogeneous seasonal cycles of mean storm precipitation characteristics. Both mean and extreme statistics were derived for each characteristic and season for each zone. Continuous probability density functions were generated that appropriately fit the empirical distributions of storm total precipitation and maximum 15-min intensity. The storm characteristics, in turn, were a function of seasonal water availability from source regions, atmospheric water vapor capacity, and storm precipitation mechanism. This is the first time that such an extensive climatology of storm precipitation characteristics has been produced. A preliminary trend analysis of the 1972–2002 storm characteristic data by zone showed substantial changes that tended to be geographically coherent, with noteworthy differences between the western and eastern United States. The western United States displayed a trend toward decreasing storm total precipitation and storm duration in most seasons, while storm intensity increased. The eastern United States experienced a general pattern of increasing storm total precipitation and storm duration during winter, as well as a tendency for maximum 15-min precipitation intensity to increase.

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Ronald D. Leeper, Jesse E. Bell, and Michael A. Palecki

Abstract

The interpretation of in situ or remotely sensed soil moisture data for drought monitoring is challenged by the sensitivity of these observations to local soil characteristics and seasonal precipitation patterns. These challenges can be overcome by standardizing soil moisture observations. Traditional approaches require a lengthy record (usually 30 years) that most soil monitoring networks lack. Sampling techniques that combine hourly measurements over a temporal window have been used in the literature to generate historical references (i.e., climatology) from shorter-term datasets. This sampling approach was validated on select U.S. Department of Agriculture Soil Climate Analysis Network (SCAN) stations using a Monte Carlo analysis, which revealed that shorter-term (5+ years) hourly climatologies were similar to longer-term (10+ year) hourly means. The sampling approach was then applied to soil moisture observations from the U.S. Climate Reference Network (USCRN). The sampling method was used to generate multiple measures of soil moisture (mean and median anomalies, standardized median anomaly by interquantile range, and volumetric) that were converted to percentiles using empirical cumulative distribution functions. Overall, time series of soil moisture percentile were very similar among the differing measures; however, there were times of year at individual stations when soil moisture percentiles could have substantial deviations. The use of soil moisture percentiles and counts of threshold exceedance provided more consistent measures of hydrological conditions than observed soil moisture. These results suggest that hourly soil moisture observations can be reasonably standardized and can provide consistent measures of hydrological conditions across spatial and temporal scales.

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Ronald D. Leeper, John Kochendorfer, Timothy A. Henderson, and Michael A. Palecki

Abstract

A field experiment was performed in Oak Ridge, Tennessee, with four instrumented towers placed over grass at increasing distances (4, 30, 50, 124, and 300 m) from a built-up area. Stations were aligned in such a way to simulate the impact of small-scale encroachment on temperature observations. As expected, temperature observations were warmest for the site closest to the built environment with an average temperature difference of 0.31° and 0.24°C for aspirated and unaspirated sensors, respectively. Mean aspirated temperature differences were greater during the evening (0.47°C) than during the day (0.16°C). This was particularly true for evenings following greater daytime solar insolation (20+ MJ day−1) with surface winds from the direction of the built environment where mean differences exceeded 0.80°C. The impact of the built environment on air temperature diminished with distance with a warm bias only detectable out to tower B′ located 50 m away. The experimental findings were comparable to a known case of urban encroachment at a U.S. Climate Reference Network station in Kingston, Rhode Island. The experimental and operational results both lead to reductions in the diurnal temperature range of ~0.39°C for fan-aspirated sensors. Interestingly, the unaspirated sensor had a larger reduction in diurnal temperature range (DTR) of 0.48°C. These results suggest that small-scale urban encroachment within 50 m of a station can have important impacts on daily temperature extrema (maximum and minimum) with the magnitude of these differences dependent upon prevailing environmental conditions and sensing technology.

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