% This file contains a station summary listing for a temperature % station in the Berkeley Earth database. This station is identified as: % % Berkeley ID#: 33272 % Primary Name: HELVETIA % Record Type: TAVG % Country: United States % State: WV % Latitude: 38.50000 +/- 0.00833 % Longitude: -80.00000 +/- 0.00833 % Elevation (m): 1286.44 +/- 237.38 % # of Months: 68 % % Alternate Names: Missing Station ID - 464045 % % IDs: coop - 464045 % ghcnd - USC00464045 % ncdc - 12006075 % % Sources: US Cooperative Summary of the Day % Global Historical Climatology Network - Daily % Multi-network Metadata System % % Site Hash: ceb401873cc00b0dce1e181f01107707 % Raw Data Hash: 42131b79f226c3dc645e11bca8a440b6 % Adj Data Hash: e5a55c0d6b5ffd34a62f52676733c708 % % The data for this station is presented below in several columns and in % several forms. The temperature values are reported as "raw", % "adjusted", and "regional expectation". % % The "raw" values reflect the observations as originally ingested by % the Berkeley Earth system from one or more originating archive(s). % These "raw" values may reflect the merger of more than one temperature % time series if multiple archives reported values for this location. % Alongside the raw data we have also provided a flag indicating which % values failed initial quality control checks. A further column % dates at which the raw data may be subject to continuity "breaks" % due to documented station moves (denoted "1"), prolonged measurement % gaps (denoted "2"), documented time of observation changes (denoted "3") % and other empirically determined inhomogeneities (denoted "4"). % % In many cases, raw temperature data contains a number of artifacts, % caused by issues such as typographical errors, instrumentation changes, % station moves, and urban or agricultural development near the station. % The Berkeley Earth analysis process attempts to identify and estimate % the impact of various kinds of data quality problems by comparing each % time series to neighboring series. At the end of the analysis process, % the "adjusted" data is created as an estimate of what the weather at % this location might have looked like after removing apparent biases. % This "adjusted" data will generally to be free from quality control % issues and be regionally homogeneous. Some users may find this % "adjusted" data that attempts to remove apparent biases more % suitable for their needs, while other users may prefer to work % with raw values. % % Lastly, we have provided a "regional expectation" time series, based % on the Berkeley Earth expected temperatures in the neighborhood of the % station. This incorporates information from as many weather stations as % are available for the local region surrounding this location. Note % that the regional expectation may be a systematically a bit warmer or % colder than the weather stations by a few degrees due to differences % in mean elevation and other local characteristics. % % For each temperature time series, we have also included an "anomaly" % time series that removes both the seasonality and the long-term mean. % These anomalies may provide an easier way of seeing changes through % time. % % Reported temperatures are in Celsius and reflect monthly averages. As % these files are intended to be summaries for convenience, additional % information, including more detailed flagging and metadata, may be % available in our whole data set files. % % The Berkeley Earth analysis was run on 15-Nov-2013 19:55:48 % % Raw Data QC Continuity Adjusted Data Regional Expectation % Year, Month, Temperature, Anomaly, Failed, Breaks, Temperature, Anomaly, Temperature, Anomaly 1882 5 NaN NaN NaN NaN NaN NaN 14.756 -2.426 1882 6 NaN NaN NaN NaN NaN NaN 21.196 0.166 1882 7 NaN NaN NaN NaN NaN NaN 22.012 -1.229 1882 8 NaN NaN NaN NaN NaN NaN 21.887 -0.830 1882 9 NaN NaN NaN NaN NaN NaN 19.405 0.261 1882 10 NaN NaN NaN NaN NaN NaN 14.555 1.833 1882 11 NaN NaN NaN NaN NaN NaN 6.091 -1.144 1882 12 NaN NaN NaN NaN NaN NaN -0.277 -2.527 1883 1 NaN NaN NaN NaN NaN NaN -0.655 -1.340 1883 2 NaN NaN NaN NaN NaN NaN 4.404 2.388 1883 3 NaN NaN NaN NaN NaN NaN 4.159 -2.599 1883 4 NaN NaN NaN NaN NaN NaN 11.258 -1.123 1883 5 14.755 -0.835 0 0 14.755 -0.835 16.658 -0.524 1883 6 20.363 0.924 0 0 20.363 0.924 21.344 0.314 1883 7 21.110 -0.540 0 0 21.110 -0.540 22.950 -0.290 1883 8 19.155 -1.971 0 0 19.155 -1.971 21.296 -1.421 1883 9 16.567 -0.985 0 0 16.567 -0.985 17.992 -1.152 1883 10 13.635 2.505 0 0 13.635 2.505 12.847 0.124 1883 11 6.762 1.118 0 0 6.762 1.118 8.193 0.958 1883 12 2.407 1.749 0 0 2.407 1.749 2.841 0.591 1884 1 -3.297 -2.391 0 0 -3.297 -2.391 -2.698 -3.382 1884 2 4.885 4.461 0 0 4.885 4.461 4.725 2.709 1884 3 5.179 0.013 0 0 5.179 0.013 6.733 -0.024 1884 4 8.148 -2.641 0 0 8.148 -2.641 11.012 -1.368 1884 5 14.283 -1.307 0 0 14.283 -1.307 17.375 0.193 1884 6 18.926 -0.513 0 0 18.926 -0.513 20.212 -0.819 1884 7 19.355 -2.294 0 0 19.355 -2.294 21.905 -1.336 1884 8 19.068 -2.058 0 0 19.068 -2.058 21.787 -0.931 1884 9 17.611 0.059 0 0 17.611 0.059 20.962 1.818 1884 10 12.401 1.271 0 0 12.401 1.271 14.767 2.044 1884 11 4.387 -1.257 0 0 4.387 -1.257 6.514 -0.721 1884 12 2.276 1.618 0 0 2.276 1.618 2.216 -0.033 1885 1 -0.609 0.298 0 0 -0.609 0.298 -0.325 -1.010 1885 2 -3.254 -3.678 0 0 -3.254 -3.678 -3.130 -5.146 1885 3 0.090 -5.076 0 0 0.090 -5.076 2.069 -4.688 1885 4 8.611 -2.178 0 0 8.611 -2.178 11.980 -0.401 1885 5 13.692 -1.898 0 0 13.692 -1.898 16.137 -1.045 1885 6 19.037 -0.402 0 0 19.037 -0.402 20.758 -0.272 1885 7 20.932 -0.717 0 0 20.932 -0.717 23.341 0.101 1885 8 19.593 -1.533 0 0 19.593 -1.533 22.047 -0.671 1885 9 15.611 -1.941 0 0 15.611 -1.941 18.442 -0.701 1885 10 8.692 -2.439 0 0 8.692 -2.439 10.841 -1.881 1885 11 4.176 -1.467 0 0 4.176 -1.467 6.222 -1.013 1885 12 1.398 0.740 0 0 1.398 0.740 1.997 -0.253 1886 1 -0.651 0.256 0 0 -0.651 0.256 -2.492 -3.176 1886 2 -1.448 -1.873 0 0 -1.448 -1.873 -0.897 -2.913 1886 3 3.728 -1.438 0 0 3.728 -1.438 5.872 -0.886 1886 4 10.926 0.137 0 0 10.926 0.137 12.996 0.616 1886 5 14.857 -0.733 0 0 14.857 -0.733 16.631 -0.550 1886 6 18.463 -0.976 0 0 18.463 -0.976 20.233 -0.798 1886 7 20.197 -1.452 0 0 20.197 -1.452 22.099 -1.142 1886 8 19.928 -1.198 0 0 19.928 -1.198 21.979 -0.738 1886 9 16.648 -0.904 0 0 16.648 -0.904 19.747 0.604 1886 10 9.892 -1.238 0 0 9.892 -1.238 12.409 -0.313 1886 11 4.241 -1.403 0 0 4.241 -1.403 6.541 -0.694 1886 12 -1.559 -2.217 0 0 -1.559 -2.217 -1.351 -3.601 1887 1 -0.502 0.405 0 0 -0.502 0.405 -0.714 -1.399 1887 2 5.556 5.131 0 0 5.556 5.131 4.452 2.436 1887 3 3.100 -2.065 0 0 3.100 -2.065 4.777 -1.980 1887 4 8.833 -1.955 0 0 8.833 -1.955 11.263 -1.117 1887 5 17.473 1.883 0 0 17.473 1.883 19.045 1.864 1887 6 18.852 -0.587 0 0 18.852 -0.587 20.798 -0.232 1887 7 23.333 1.684 1 0 NaN NaN 24.518 1.278 1887 8 19.409 -1.717 0 0 19.409 -1.717 21.836 -0.882 1887 9 15.815 -1.737 0 0 15.815 -1.737 17.977 -1.167 1887 10 9.534 -1.597 0 0 9.534 -1.597 11.365 -1.358 1887 11 5.249 -0.395 0 0 5.249 -0.395 6.682 -0.554 1887 12 1.918 1.260 0 0 1.918 1.260 1.333 -0.916 1888 1 0.466 1.373 0 0 0.466 1.373 -0.488 -1.173 1888 2 NaN NaN NaN NaN NaN NaN 2.477 0.461 1888 3 3.297 -1.868 0 0 3.297 -1.868 4.489 -2.269 1888 4 9.037 -1.752 0 0 9.037 -1.752 12.038 -0.342 1888 5 14.537 -1.053 0 0 14.537 -1.053 16.444 -0.737 1888 6 19.187 -0.252 0 0 19.187 -0.252 21.130 0.100 1888 7 19.944 -1.705 0 0 19.944 -1.705 22.297 -0.944 1888 8 19.889 -1.237 0 0 19.889 -1.237 22.866 0.148 1888 9 14.852 -2.700 0 0 14.852 -2.700 16.984 -2.160 1888 10 8.333 -2.797 0 0 8.333 -2.797 10.060 -2.662 1888 11 5.981 0.338 0 0 5.981 0.338 8.129 0.893 1888 12 0.430 -0.228 0 0 0.430 -0.228 1.722 -0.527 1889 1 1.722 2.629 0 0 1.722 2.629 2.452 1.768 1889 2 NaN NaN NaN NaN NaN NaN -0.890 -2.905 1889 3 NaN NaN NaN NaN NaN NaN 6.481 -0.277 1889 4 NaN NaN NaN NaN NaN NaN 12.500 0.120 1889 5 NaN NaN NaN NaN NaN NaN 17.016 -0.165 1889 6 NaN NaN NaN NaN NaN NaN 20.230 -0.801 1889 7 NaN NaN NaN NaN NaN NaN 22.848 -0.393 1889 8 NaN NaN NaN NaN NaN NaN 20.801 -1.917 1889 9 NaN NaN NaN NaN NaN NaN 17.776 -1.368 1889 10 NaN NaN NaN NaN NaN NaN 10.025 -2.697 1889 11 NaN NaN NaN NaN NaN NaN 7.285 0.050 1889 12 NaN NaN NaN NaN NaN NaN 7.317 5.067 1890 1 NaN NaN NaN NaN NaN NaN 6.082 5.397