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In this paper, a new set of daily gridded fields and area averages of temperature and precipitation is introduced that covers the contiguous United States (CONUS) from 1951 to present. With daily updates and a grid resolution of approximately 0.0417° (nominally 5 km), the product, named nClimGrid-Daily, is designed to be used particularly in climate monitoring and other applications that rely on placing event-specific meteorological patterns into a long-term historical context. The gridded fields were generated by interpolating morning and midnight observations from the Global Historical Climatology Network–Daily dataset using thin-plate smoothing splines. Additional processing steps limit the adverse effects of spatial and temporal variations in station density, observation time, and other factors on the quality and homogeneity of the fields. The resulting gridded data provide smoothed representations of the point observations, although the accuracy of estimates for individual grid points and days can be sensitive to local spatial variability and the ability of the available observations and interpolation technique to capture that variability. The nClimGrid-Daily dataset is therefore recommended for applications that require the aggregation of estimates in space and/or time, such as climate monitoring analyses at regional to national scales. Significance Statement: Many applications that use historical weather observations require data on a high-resolution grid that are updated daily. Here, a new dataset of daily temperature and precipitation for 1951–present is introduced that was created by interpolating irregularly spaced observations to a regular grid with a spacing of 0.0417° across the contiguous United States. Compared to other such datasets, this product is particularly suitable for monitoring climate and drought on a daily basis because it was processed so as to limit artificial variations in space and time that may result from changes in the types and distribution of observations used. [ABSTRACT FROM AUTHOR]

The 1981-2010 'U.S. Climate Normals' released by the National Oceanic and Atmospheric Administration's (NOAA) National Climatic Data Center include a suite of monthly, seasonal, and annual statistics that are based on precipitation, snowfall, and snow-depth measurements. This paper describes the procedures used to calculate the average totals, frequencies of occurrence, and percentiles that constitute these normals. All parameters were calculated from a single, state-of-the-art dataset of daily observations, taking care to produce normals that were as representative as possible of the full 1981-2010 period, even when the underlying data records were incomplete. In the resulting product, average precipitation totals are available at approximately 9300 stations across the United States and parts of the Caribbean Sea and Pacific Ocean islands. Snowfall and snow-depth statistics are provided for approximately 5300 of those stations, as compared with several hundred stations in the 1971-2000 normals. The 1981-2010 statistics exhibit the familiar climatological patterns across the contiguous United States. When compared with the same calculations for 1971-2000, the later period is characterized by a smaller number of days with snow on the ground and less total annual snowfall across much of the contiguous United States; wetter conditions over much of the Great Plains, Midwest, and northern California; and drier conditions over much of the Southeast and Pacific Northwest. These differences are a reflection of the removal of the 1970s and the addition of the 2000s to the 30-yr-normals period as part of this latest revision of the normals. [ABSTRACT FROM AUTHOR]

The article provides an overview of the 1981-2010 U.S. Climate Normals released by the National Oceanic and Atmospheric Administration (NOAA). It explains that this release features temperature homogenization at the monthly level and precipitation statistics. It also uses quality-controlled daily data and novel statistical methods for the calculation of daily temperature normals. Contact information is provided for interested parties.

The article reports on the availability of U.S. hourly meteorological data from 1981 to 2010 compiled by the National Oceanic and Atmospheric Administration (NOAA). It explains that these so-called hourly normals include three types of statistics and they are available for 262 locations. It explains the computational procedures used in obtaining the hourly normals and recommends their applications in the study of the diurnal cycle of a particular variable.

This study examines the contributions of sunshine duration, snow cover extent, and the atmospheric circulation to variations of the cold-season diurnal temperature range (DTR) in eight regions of the contiguous United States. The goal of the research is to facilitate the interpretation of long-term changes in the DTR in light of the possible anthropogenic role in these trends. For the cold seasons (Nov–Mar) between 1958/59 and 1994/95, daily surface observations at more than 200 stations from the First Summary of the Day (FSOD) dataset as well as selected daily fields from the NCEP–NCAR 40-Year Reanalysis Project are analyzed using compositing, correlation, and regression techniques. For each region, a sea level pressure anomaly pattern is identified that is linearly related to daily variations in the DTR. It is found that the presence of positive sea level pressure anomalies over a region, clear skies, and the absence of snow on the ground all favor high values of the regionally averaged DTR. The strength of these associations varies geographically because of the effects of nonlinear relationships, the frequency of snow cover, and the complexity of local dynamics. The cold-season trends of several variables for the period 1965/66–1994/95 are also analyzed. During the 30-yr period of record, the central and southern United States experienced a decrease in the DTR, while the northeast, Pacific coast, and portions of the interior west experienced an increase. Variations in the DTR-related sea level pressure patterns and sunshine duration explain significant fractions of the DTR increase in the coastal Northwest and the DTR decrease in the south-central states. The DTR trends over the rest of the country are largely unrelated to linear trends in sunshine duration, snow cover, or the sea level pressure field. The spatial pattern of DTR trends is reproduced when homogeneity-adjusted data from the Global Historical Climatology Network are us... [ABSTRACT FROM AUTHOR]

ABSTRACT In light of numerous studies documenting a decline in the diurnal temperature range (DTR) over much of the globe, some authors have in recent years examined the annual march of the DTR in an effort to understand better the factors that influence the DTR's seasonal variations. These papers show that, over the southern two-thirds of the eastern United States, the DTR's climatology features peaks in spring and autumn and minima in winter and mid-to-late summer. However, the factors responsible for these characteristics remain uncertain. In this study, the DTR climatology of the eastern United States is analyzed in detail using daily surface and 850-mb data, with emphasis on possible relationships to seasonal changes in vegetation. It is shown that the warm season dip in the DTR deepens and widens from north to south across the study area, in accordance with a lengthening of the growing season. Furthermore, the dip is particularly prominent in the annual march of the DTR on mostly sunny days, indicating that seasonal variations in cloudiness are not responsible for this feature. The climatologies of daily maximum and daily minimum temperatures are found to be very different from each other: the former flattens out after the springtime peak in the DTR whereas the latter exhibits a pronounced mid-to-late summer maximum. These findings suggest that, by inhibiting daytime surface heating, evapotranspiration from vegetation contributes significantly to the dip in the DTR during the warm season in the eastern United States. [ABSTRACT FROM AUTHOR]

The paper presents an analysis of the dependence of summertime daily maximum temperature on antecedent soil moisture using daily surface observations from a selection of stations in the contiguous United States and daily time series of soil moisture computed with a simple local water balance model. The computed soil moisture time series are offered as an alternative to Palmer's soil moisture anomaly (Z) index, the Palmer Drought Severity Index (PDSI), and other such time series. In contrast to other water balance models that have been designed for the computation of soil moisture time series, the model herein is driven by daily rather than monthly data, uses the Priestley-Taylor method in lieu of Thornthwaite's method to calculate potential evapotranspiration, allows for runoff during dry periods as well as when soil moisture is not at field capacity, includes a crude scheme for taking into account the effects of snowmelt on the water balance, and permits geographical variations in soil water capacity. The Priestley-Taylor method is considered to yield more realistic estimates of evapo-transpiration than Thornthwaite's method since it accounts for net radiation and represents a special case of the widely used Penman-Monteith method. Total runoff is parameterized according to the Variable Infiltration Capacity model. Based on a comparison with soil moisture measurements at Peoria, Illinois, the model appears to simulate the variability of soil moisture anomalies (W[sup']) reasonably well. Analysis of the relationship between W[sup'] and daily maximum temperatures (T[submax]) shows that in the central and eastern United States during the summer, the entire frequency distribution of standardized T[submax] is shifted toward higher values following a 'low-W[sup']' day (i.e., a day on which W[sup'] falls into the bottom quartile of its frequency distribution). The shift is most pronounced at the high end of the temperature distribution, indicating that as the... [ABSTRACT FROM AUTHOR]