Since 1987, the National Oceanic and Atmospheric Administration’s (NOAA’s) National Climatic Data Center (NCDC) has used observations from the U.S. Historical Climatology Network (USHCN) to quantify national- and regional-scale temperature changes in the conterminous United States (CONUS). To that end, USHCN temperature records have been “corrected” to account for various historical changes in station location, instrumentation, and observing practice. The USHCN is actually a designated subset of the NOAA Cooperative Observer Program (COOP) Network the USHCN sites having been selected according to their spatial coverage, record length, data completeness, and historical stability. The USHCN, therefore, consists primarily of long-term COOP stations whose temperature records have been adjusted for systematic, nonclimatic changes that bias temperature trends.
Figure 1. Distribution of U.S. Cooperative Observer Network stations in the CONUS. U.S. HCN version 2 sites are indicated as red triangles.
USHCN datasets have been developed at NOAA's NCDC in collaboration with the Department of Energy's Carbon Dioxide Information Analysis Center (CDIAC) in a project that dates to the mid-1980s (Quinlan et al. 1987). At that time, in response to the need for an accurate, unbiased, modern historical climate record for the United States, personnel at the Global Change Research Program of the U.S. Department of Energy and at NCDC defined a network of 1219 stations in the contiguous United States whose observation would comprise a key baseline dataset for monitoring U.S. climate. Since then, the U S HCN dataset has been updated several times (e.g., Karl et al., 1990; Easterling et al., 1996). The USHCN version 2 serial monthly data release is the most recent update to the USHCN adjusted datasets.
Version 2 data were produced using a new set of quality control and homogeneity assessment algorithms. A brief summary of version 2 processing steps is provided below. A more comprehensive summary, including discussions of the sources and magnitude of bias in the raw (unadjusted) data, is provided in Menne et al. (2009). An assessment specifically addressing the reliability of the USHCN temperature trends in light of station siting concerns is also provided below and in more detail by Menne et al. (2010). The methodology used in previous releases of the version 1 monthly data is described on the USHCN Version 1 web site.; please note, however, that the version 1 USHCN data are no longer updated.
The data from each HCN station were subject to the following quality control and homogeneity testing and adjustment procedures.
First, daily maximum and minimum temperatures and total precipitation were extracted from a number of different NCDC data sources and subjected to a series of quality evaluation checks. The three sources of daily observations included DSI-3200, DSI-3206 and DSI-3210. Daily maximum and minimum temperature values that passed the evaluation checks were used to compute monthly average values. However, no monthly temperature average or total precipitation value was calculated for station-months in which more than 9 were missing or flagged as erroneous. Monthly values calculated from the three daily data sources then were merged with two additional sources of monthly data values to form a comprehensive dataset of serial monthly temperature and precipitation values for each HCN station. Duplicate records between data sources were eliminated. Following the merging procedure, the monthly values from all stations were subject to an additional set of quality evaluation procedures, which removed between 0.1 and 0.2% of monthly temperature values and less than 0.02% of monthly precipitation values.
Next, monthly temperature values were adjusted for the time-of-observation bias (Karl et al. 1986; Vose et al., 2003). The Time of Observation Bias (TOB) arises when the 24-hour daily summary period at a station begins and ends at an hour other than local midnight. When the summary period ends at an hour other than midnight, monthly mean temperatures exhibit a systematic bias relative to the local midnight standard (Baker, 1975). In the U.S. Cooperative Observer Network, the ending hour of the 24-hour climatological day typically varies from station to station and can change at a given station during its period of record. The TOB-adjustment software uses an empirical model to estimate and adjust the monthly temperature values so that they more closely resemble values based on the local midnight summary period. The metadata archive is used to determine the time of observation for any given period in a station's observational history.
Following the TOB adjustments, the homogeneity of the TOB-adjusted temperature series is assessed. In previous releases of the U.S. HCN monthly dataset, homogeneity adjustments were performed using the procedure described in Karl and Williams (1987). This procedure was used to evaluate non-climatic discontinuities (artificial changepoints) in a station's temperature or precipitation series caused by known changes to a station such as equipment relocations and changes. Since knowledge of changes in the status of observations comes from the station history metadata archive maintained at NCDC, the original U.S. HCN homogenization algorithm was known as the Station History Adjustment Program (SHAP).
Unfortunately, station histories are often incomplete so artificial discontinuities in a data series may occur on dates with no associated record in the metadata archive. Undocumented station changes obviously limit the effectiveness of SHAP. To remedy the problem of incomplete station histories, the version 2 homogenization algorithm addresses both documented and undocumented discontinuities.
The potential for undocumented discontinuities adds a layer of complexity to homogeneity testing. Tests for undocumented changepoints, for example, require different sets of test-statistic percentiles than those used in analogous tests for documented discontinuities (Lund and Reeves, 2002). For this reason, tests for undocumented changepoints are inherently less sensitive than their counterparts used when changes are documented. Tests for documented changes should, therefore, also be conducted where possible to maximize the power of detection for all artificial discontinuities. In addition, since undocumented changepoints can occur in all series, accurate attribution of any particular discontinuity between two climate series is more challenging (Menne and Williams, 2005).
The U.S. HCN version 2 "pairwise" homogenization algorithm addresses these and other issues according to the following steps, which are described in detail in Menne and Williams (2009). At present, only temperature series are evaluated for artificial changepoints.
Following the homogenization process, estimates for missing data are calculated using a weighted average of values from highly correlated neighboring values. The weights are determined using a procedure similar to the SHAP routine. This program, called FILNET, uses the results from the TOB and homogenization algorithms to obtain a more accurate estimate of the climatological relationship between stations. The FILNET program also estimates data across intervals in a station record where discontinuities occur in a short time interval, which prevents the reliable estimation of appropriate adjustments.
In the original HCN, the regression-based approach of Karl et al. (1988) was employed to account for urban heat islands. In contrast, no specific urban correction is applied in HCN version 2 because the change-point detection algorithm effectively accounts for any "local" trend at any individual station. In other words, the impact of urbanization and other changes in land use is likely small in HCN version 2. Figure 2 - the minimum temperature time series for Reno, Nevada - provides anecdotal evidence in this regard. In brief, the black line represents the unadjusted data, and the blue line represents fully adjusted data. The unadjusted data clearly indicate that the station at Reno experienced both major step changes (e.g., a move from the city to the airport during the 1930s) and trend changes (e.g., a possible growing urban heat island beginning in the 1970s). In contrast, the fully adjusted (homogenized) data indicate that both the step-type changes and the trend changes have been effectively addressed through the change-point detection process used in HCN version 2.
Figure 2. (a) Mean annual unadjusted and fully adjusted minimum temperatures at Reno, Nevada. Error bars indicating the magnitude of uncertainty (±1 standard error) were calculated via 100 Monte Carlo simulations that sampled within the range of the pairwise estimates for the magnitude of each inhomogeneity; (b) difference between minimum temperatures at Reno and the mean from its 10 nearest neighbors.
Recent photographic documentation of poor siting conditions at stations in the USHCN has led to questions regarding the reliability of surface temperature trends over the conterminous U.S. (CONUS). To evaluate the potential impact of poor siting/instrument exposure on CONUS temperatures, Menne et al. (2010) compared trends derived from poor and well-sited USHCN stations using both unadjusted and bias-adjusted data. Results indicate that there is a mean bias associated with poor exposure sites relative to good exposure sites in the unadjusted USHCN version 2 data; however, this bias is consistent with previously documented changes associated with the widespread conversion to electronic sensors in the USHCN during the last 25 years (see e.g., Menne et al. 2009). Moreover, the sign of the bias is counterintuitive to photographic documentation of poor exposure because associated instrument changes have led to an artificial negative (“cool”) bias in maximum temperatures and only a slight positive (“warm”) bias in minimum temperatures.
Adjustments applied to USHCN Version 2 data largely account for the impact of instrument and siting changes, although a small overall residual negative (“cool”) bias appears to remain in the adjusted USHCN version 2 CONUS average maximum temperature. Nevertheless, the adjusted USHCN CONUS temperatures are well aligned with recent measurements from the U.S. Climate Reference Network (USCRN). This network was designed with the highest standards for climate monitoring and has none of the siting and instrument exposure problems present in USHCN. The close correspondence in nationally averaged temperature from these two networks is further evidence that the adjusted USHCN data provide an accurate measure of the U.S. temperature.
The Menne et al. (2010) results underscore the need to consider all changes in observation practice when determining the impacts of siting irregularities. Further, the influence of non-standard siting on temperature trends can only be quantified through an analysis of the data which do not indicate that the CONUS average temperature trends are inflated due to poor station siting.
Four sets of USCHN stations were used in the Menne et al. (2010) analysis. Set 1 includes stations identified as having good siting by the volunteers at surfacestations.org. Set 2 is a subset of set 1 consisting of the set 1 stations whose ratings are in general agreement with an independent assessment by NOAA’s National Weather Service. Set 3 are those stations with moderate to poor siting ratings according to surfacestations.org. Set 4 is a subset of set 3 consisting of the set 3 stations whose ratings are in agreement with an independent assessment by NOAA’s National Weather Service. For further information, please see Menne et al. (2010). The set of Maximum Minimum Temperature Sensor (MMTS) stations and Cotton Region Shelter (Stevenson Screen) sites used in Menne et al. (2010) are also available (see the "readme.txt" file as described below for a description of the station list format). Access to the unadjusted, time of observation adjusted, and fully adjusted USHCN version 2 temperature data is described below.
U.S. HCN version 2 monthly data are available via ftp at ftp://ftp.ncdc.noaa.gov/pub/data/ushcn/v2/monthly/. Please see the "readme.txt" file in this directory for information on downloading and reading U.S HCN v2 data. Version control information is provided in the "status.txt" file.
http://www.ncdc.noaa.gov/oa/climate/research/ushcn/index.php