Editorial Type:
Article
Article Type:
Research Article

Creating a Serially Complete, National Daily Time Series of Temperature and Precipitation for the Western United States

Jon K. Eischeid Cooperative Institute for Research in Environmental Sciences, University of Colorado, Boulder, Colorado

Search for other papers by Jon K. Eischeid in
Current site
Google Scholar
PubMed Close
,
Phil A. Pasteris Natural Resources Conservation Service, Portland, Oregon

Search for other papers by Phil A. Pasteris in
Current site
Google Scholar
PubMed Close
,
Henry F. Diaz NOAA Climate Diagnostics Center, Boulder, Colorado

Search for other papers by Henry F. Diaz in
Current site
Google Scholar
PubMed Close
,
Marc S. Plantico NOAA National Climatic Data Center, Asheville, North Carolina

Search for other papers by Marc S. Plantico in
Current site
Google Scholar
PubMed Close
, and
Neal J. Lott NOAA National Climatic Data Center, Asheville, North Carolina

Search for other papers by Neal J. Lott in
Current site
Google Scholar
PubMed Close
Print Publication:
01 Sep 2000
DOI:
https://doi.org/10.1175/1520-0450(2000)039<1580:CASCND>2.0.CO;2
Page(s):
1580–1591
Restricted access

Abstract

The development of serially complete (no missing values) daily maximum–minimum temperatures and total precipitation time series over the western United States is documented. Several estimation techniques based on spatial objective analysis schemes are used to estimate daily values, with the &ldquost” estimate chosen as a missing value replacement. The development of a continuous and complete daily dataset will be useful in a variety of meteorological and hydrological research applications.

The spatial interpolation schemes are evaluated separately by interpolation method and calendar month. Cross validation of the results indicates a distinct seasonality to the efficiency (error) of the estimates, although no systematic bias in the estimation procedures was found. The resulting number of serially complete daily time series for the western United States (all states west of the Mississippi River) includes 2034 maximum–minimum temperature stations and 2962 total daily precipitation locations.

Corresponding author address: Dr. Jon K. Eischeid, CIRES, University of Colorado, Campus Box 449, Boulder, CO 80309-0449.

Abstract

The development of serially complete (no missing values) daily maximum–minimum temperatures and total precipitation time series over the western United States is documented. Several estimation techniques based on spatial objective analysis schemes are used to estimate daily values, with the &ldquost” estimate chosen as a missing value replacement. The development of a continuous and complete daily dataset will be useful in a variety of meteorological and hydrological research applications.

The spatial interpolation schemes are evaluated separately by interpolation method and calendar month. Cross validation of the results indicates a distinct seasonality to the efficiency (error) of the estimates, although no systematic bias in the estimation procedures was found. The resulting number of serially complete daily time series for the western United States (all states west of the Mississippi River) includes 2034 maximum–minimum temperature stations and 2962 total daily precipitation locations.

Corresponding author address: Dr. Jon K. Eischeid, CIRES, University of Colorado, Campus Box 449, Boulder, CO 80309-0449.

Save
Cover Journal of Applied Meteorology and Climatology
Journal of Applied Meteorology and Climatology

  • Barrodale, I., and F. D. K. Roberts, 1973: An improved algorithm for discrete L1 approximation. SIAM J. Numer. Anal.,10, 839–848.

  • Bennet, R. J., R. P. Haining, and D. A. Griffith, 1984: The problem of missing data on spatial surfaces. Ann. Assoc. Amer. Geogr.,74, 138–156.

  • DeGaetano, A. T., K. L. Eggleston, and W. W. Knapp, 1993: A method to produce serially complete daily maximum and minimum temperature data for the Northeast. NRCC Research Publication RR 93-2, 9 pp. [Available from NRCC, Cornell University, Ithaca, NY 14853.].

  • Eischeid, J. K., C. B. Baker, T. R. Karl, and H. F. Diaz, 1995: The quality control of long-term climatological data using objective data analysis. J. Appl. Meteor.,34, 2787–2795.

  • Gandin, L. S., and R. L. Kagan, 1974: Construction of the system of heterogeneous data objective analysis based on the method of optimal interpolation and optimal agreement (in Russian). Meteor. Gidrol.,5, 3–10.

  • Huth, R., and I. Nemešová, 1995: Estimation of missing daily temperatures: Can a weather categorization improve its accuracy? J. Climate,8, 1901–1916.

  • Kemp, W. P., D. G. Burnell, D. O. Everson, and A. J. Thomson, 1983:Estimating missing daily maximum and minimum temperatures. J. Climate Appl. Meteor.,22, 1587–1593.

  • Owenby, J. R., and D. S. Ezell, 1992: Monthly station normals of temperature, precipitation, and heating and cooling degree days, 1961–90. Climatography of the United States. No. 81, National Climatic Data Center. [Available from NCDC, Asheville, NC 28801.].

  • Paulhus, J. L. H., and M. A. Kohler, 1952: Interpolation of missing precipitation records. Mon. Wea. Rev.,80, 129–133.

  • Reek, T. S, S. R. Doty, and T. W. Owen, 1992: A deterministic approach to validation of historical daily temperature and precipitation data from the cooperative network. Bull. Amer. Meteor. Soc.,73, 753–762.

  • Schlatter, T. W., 1975: Some experiments with a multivariate objective analysis scheme. Mon. Wea. Rev.,103, 246–257.

  • Stooksbury, D. E., C. D. Idso, and K. G. Hubbard, 1999: The effects of data gaps on the calculated monthly mean maximum and minimum temperatures in the continental United States: A spatial and temporal study. J. Climate,12, 1524–1533.

  • Thiebaux, H. J., and M. A. Pedder, 1987: Spatial Objective Analysis with Applications in Atmospheric Science. Academic Press, 299 pp.

  • Young, K. C., 1992: A three-way model for interpolating monthly precipitation values. Mon. Wea. Rev.,120, 2561–2569.

All Time Past Year Past 30 Days
Abstract Views 0 0 0
Full Text Views 2417 1182 40
PDF Downloads 626 143 7