HCN
The United States Historical Climate Network is a high-quality station data set developed by the NOAA National Climatic Data Center. Participating stations were selected based on their length of record, minimal missing data, and minimal station changes such as location or time of observation changes. Monthly mean temperature and precipitation values were developed using quality control to identify outliers; temperature adjustments to account for different times of observation, different instrumentation, or station moves, gap filling; and adjustment for urban warming bias.
References:
Karl, T.R., C.N. Williams, Jr., F.T. Quinlan, and T.A. Boden, 1990: United States Historical Climatology Network (HCN) Serial Temperature and Precipitation Data, Environmental Science Division, Publication No. 3404, Carbon Dioxide Information and Analysis Center, Oak Ridge National Laboratory, Oak Ridge, TN, 389 pp.
Easterling, D. R., T. R. Karl, E.H. Mason, P. Y. Hughes, and D. P. Bowman. 1996. United States Historical Climatology Network (U.S. HCN) Monthly Temperature and Precipitation Data. ORNL/CDIAC-87, NDP-019/R3. Carbon Dioxide Information Analysis Center, Oak Ridge National Laboratory, U.S. Department of Energy, Oak Ridge, Tennessee.
See also http://cdiac.esd.ornl.gov/epubs/ndp/ushcn/newushcn.html.
HCN/Daily
The daily version of United States Historical Climate Network consists of daily observations (in contrast to the monthly HCN observations). Stations were selected as the most reliable, internally consistent, and unbiased from the HCN data set. However, for the purposes of expanded the spatial coverage across the US, the selection criteria were not strictly adhered to. Unlike the HCN data set, no adjustments were made to account for changing observing conditions.
References:
Easterling, D. R., T. R. Karl, J. H. Lawrimore, and S. A. Del Greco. 1999. United States Historical Climatology Network Daily Temperature, Precipitation, and Snow Data for 1871-1997. ORNL/CDIAC-118, NDP-070. Carbon Dioxide Information Analysis Center, Oak Ridge National Laboratory, U.S. Department of Energy, Oak Ridge, Tennessee.
SNOTEL
The Snow Telemetry (SNOTEL) data network provides snow and weather information from stations located in the mountainous regions of the western US. These stations have been operating for few years than the HCN stations; early stations have been in operation for ~20 years. These stations are at higher elevations that the typical HCN station, however, and so provide additional insight about climate patterns in mountainous regions. The SNOTEL temperatures have been adjusted in the following manner: Suspect observation are identified from extreme values (+/-40 deg C), the same recorded values for three days in a row, and Tmin > Tmax. Short gaps (<= 10 days) are then filled through linear interpolation.
References:
See http://www.wcc.nrcs.usda.gov/factpub/sntlfct1.html.
See http://www.wcc.nrcs.usda.gov/snow.
VEMAP
The Vegetation Mapping and Analysis Project (VEMAP) was designed to estimate changes in biogeography and biogeochemical cycling from 1895-2100 in the conterminous United States (VEMAP Members 1995). A preliminary step to running biogeochemical and biogeographical models was to develop a time series of weather data for a grid across the region at 0.5 degree spatial resolution (Kittel et al. 2004). To accomplish this for the historical period (to 1993), VEMAP utilized monthly minimum and maximum temperatures and precipitation from USHCN, cooperative network weather, and SNOTEL stations. Although the USHCN stations provided the best data for assessing long-term variability, in regions where stations were sparse the additional sources were used, thus sacrificing temporal quality for spatial quality and possibly limiting the data set's usefulness for evaluating historical trends (Kittel et al. 2004). The PRISM model was used to spatially interpolate the station information to the VEMAP 0.5 degree grid and accounted for topographic effects.
References:
Kittel, T. G. F., N. A. Rosenbloom, J. A. Royle, C. Daly, W. P. Gibson , H. H. Fisher, P. Thornton, D. N. Yates, S. Aulenbach, C. Kaufman, R. McKeown, D. Bachelet, D. S. Schimel, and VEMAP2 Participants. 2004. VEMAP Phase 2 bioclimatic database. I. Gridded historical (20th century) climate for modeling ecosystem dynamics across the conterminous USA. Climate Research 27:151-170.
VEMAP Members. 1995. Vegetation/ecosystem modeling and analysis project: Comparing biogeography and biogeochemistry models in a continental-scale study of terrestrial ecosystem responses to climate change and CO2 doubling. Global Biogeochemical Cycles 9:407-438.
Calculations
When an ecoprovince is selected, temperatures across the ecoprovince are calculated by first computing anomalies for each location, then spatially averaging the anomalies. Spatial mean temperatures are calculated as the average of the temporal mean temperatures at each location.
First plot. Temperature time series is plotted. Colors correspond to data source; see bottom of the window for data source information. Currently, temperature anomalies only are plotted; mean temperatures for a given data source are printed at the bottom of the window. A LOWESS smoothing line (thick line) of 20 points is also plotted to show long-term behavior.
Second plot. A map of the region selected is displayed showing ecoprovinces (gray indicated desired ecoprovince, if selected), locations of points from each data source (small plusses, by data source color), and if appropriate, the latitude/longitude of the input location (black plus).
Two additional plots are displayed if an ecoprovince was selected:
Third plot. A time series of the number of stations or locations contributing to the time series shown in the first plot, by data source. Changing number of locations may indicate variability in the time series of the first plot not associated with changing climate.
Fourth plot. A frequency distribution of elevation across the selected ecoprovince from a 1-km digital elevation model (DEM). Plotted on top are elevations of locations that contributed to the time series in the first plot. If a large number of locations contributed, the elevations are plotted as an additional frequency distribution on top of the DEM distribution.
Bottom of window. The data source names, mean values, and mean elevations are shown in the corresponding color.
Page last modified June 2005