% This file contains a station summary listing for a temperature % station in the Berkeley Earth database. This station is identified as: % % Berkeley ID#: 30566 % Primary Name: SAC & FOX AGENCY % Record Type: TAVG % Country: United States % State: OK % Latitude: 35.66670 +/- 0.00005 % Longitude: -96.66670 +/- 0.00005 % Elevation (m): 274.32 +/- 0.15 % # of Months: 266 % % Alternate Names: Missing Station ID - 347820 % % IDs: coop - 347820 % ghcnd - USC00347820 % ncdc - 12004239 % % Sources: US Cooperative Summary of the Day % Global Historical Climatology Network - Daily % Multi-network Metadata System % % Site Hash: b028e7ebae204642aac6dda9c68de247 % Raw Data Hash: 21f17fedc613b0b17bfa975105de7b21 % Adj Data Hash: a631b234f1ca88c8e0836fefec3950ef % % 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 1892 1 NaN NaN NaN NaN NaN NaN -0.686 -2.307 1892 2 NaN NaN NaN NaN NaN NaN 5.777 1.136 1892 3 NaN NaN NaN NaN NaN NaN 5.983 -3.336 1892 4 NaN NaN NaN NaN NaN NaN 14.827 -0.725 1892 5 NaN NaN NaN NaN NaN NaN 18.244 -2.179 1892 6 NaN NaN NaN NaN NaN NaN 24.702 -0.800 1892 7 NaN NaN NaN NaN NaN NaN 26.868 -1.510 1892 8 NaN NaN NaN NaN NaN NaN 26.001 -1.659 1892 9 NaN NaN NaN NaN NaN NaN 22.475 -0.631 1892 10 NaN NaN NaN NaN NaN NaN 16.680 -0.072 1892 11 NaN NaN NaN NaN NaN NaN 8.099 -1.032 1892 12 NaN NaN NaN NaN NaN NaN 0.942 -2.920 1893 1 3.000 0.592 0 0 3.396 0.989 1.367 -0.255 1893 2 3.175 -2.252 0 0 3.542 -1.884 1.890 -2.750 1893 3 9.574 -0.532 0 0 9.913 -0.193 8.645 -0.675 1893 4 16.833 0.495 0 0 17.256 0.918 16.347 0.795 1893 5 16.487 -4.722 0 0 17.043 -4.167 18.484 -1.939 1893 6 23.889 -2.399 0 0 24.368 -1.920 25.399 -0.103 1893 7 26.344 -2.820 0 0 26.558 -2.606 28.376 -0.001 1893 8 24.032 -4.414 0 0 24.157 -4.289 24.844 -2.816 1893 9 23.519 -0.374 0 0 23.869 -0.023 23.521 0.415 1893 10 NaN NaN NaN NaN NaN NaN 16.617 -0.136 1893 11 NaN NaN NaN NaN NaN NaN 7.063 -2.068 1893 12 NaN NaN NaN NaN NaN NaN 5.875 2.013 1894 1 NaN NaN NaN NaN NaN NaN 1.299 -0.323 1894 2 NaN NaN NaN NaN NaN NaN 0.280 -4.361 1894 3 12.832 2.726 0 0 13.170 3.065 10.228 0.908 1894 4 17.572 1.234 0 0 17.995 1.657 16.991 1.439 1894 5 NaN NaN NaN NaN NaN NaN 20.109 -0.314 1894 6 NaN NaN NaN NaN NaN NaN 25.658 0.156 1894 7 NaN NaN NaN NaN NaN NaN 27.415 -0.962 1894 8 NaN NaN NaN NaN NaN NaN 26.750 -0.910 1894 9 NaN NaN NaN NaN NaN NaN 23.090 -0.016 1894 10 17.852 0.313 0 0 18.432 0.894 17.382 0.630 1894 11 NaN NaN NaN NaN NaN NaN 8.771 -0.359 1894 12 6.479 1.831 0 0 6.925 2.277 4.455 0.592 1895 1 0.370 -2.037 0 0 0.767 -1.641 -0.900 -2.521 1895 2 -0.230 -5.656 0 0 0.137 -5.289 -1.765 -6.405 1895 3 10.594 0.488 0 0 10.933 0.827 8.904 -0.416 1895 4 17.796 1.458 0 0 18.219 1.881 17.461 1.909 1895 5 20.305 -0.904 0 0 20.860 -0.349 20.898 0.475 1895 6 24.333 -1.955 0 0 24.812 -1.476 25.205 -0.297 1895 7 25.907 -3.256 0 0 26.121 -3.042 26.176 -2.202 1895 8 25.932 -2.514 0 0 26.057 -2.389 26.669 -0.991 1895 9 24.563 0.671 0 0 24.914 1.022 24.650 1.544 1895 10 13.692 -3.847 0 0 14.273 -3.266 13.427 -3.326 1895 11 7.874 -2.043 0 0 8.440 -1.476 6.918 -2.212 1895 12 4.480 -0.168 0 0 4.926 0.278 2.890 -0.973 1896 1 4.636 2.229 0 0 5.032 2.625 3.002 1.381 1896 2 6.559 1.132 0 0 6.926 1.500 5.420 0.780 1896 3 9.481 -0.624 0 0 9.820 -0.285 6.629 -2.690 1896 4 18.741 2.403 0 0 19.164 2.826 18.527 2.975 1896 5 22.563 1.354 0 0 23.118 1.909 23.167 2.744 1896 6 24.148 -2.140 0 0 24.627 -1.661 25.347 -0.155 1896 7 26.828 -2.336 0 0 27.042 -2.122 27.453 -0.925 1896 8 28.996 0.550 0 0 29.121 0.675 28.572 0.912 1896 9 22.407 -1.485 0 0 22.758 -1.134 21.976 -1.130 1896 10 14.211 -3.327 0 0 14.792 -2.747 15.105 -1.648 1896 11 8.815 -1.102 0 0 9.381 -0.535 7.214 -1.917 1896 12 6.724 2.076 0 0 7.170 2.522 6.156 2.293 1897 1 0.926 -1.482 0 0 1.322 -1.085 -0.103 -1.725 1897 2 4.861 -0.565 0 0 5.229 -0.197 4.374 -0.266 1897 3 10.968 0.862 0 0 11.307 1.201 9.124 -0.196 1897 4 15.185 -1.153 0 0 15.608 -0.730 14.766 -0.786 1897 5 18.943 -2.266 0 0 19.498 -1.711 18.726 -1.697 1897 6 24.370 -1.918 0 0 24.849 -1.439 24.976 -0.526 1897 7 27.168 -1.996 0 0 27.382 -1.782 28.073 -0.304 1897 8 25.609 -2.837 0 0 25.734 -2.712 26.192 -1.468 1897 9 23.477 -0.415 0 0 23.828 -0.064 23.731 0.625 1897 10 18.638 1.099 0 0 19.219 1.680 18.620 1.868 1897 11 9.204 -0.713 0 0 9.770 -0.146 8.594 -0.536 1897 12 NaN NaN NaN NaN NaN NaN 1.326 -2.536 1898 1 NaN NaN NaN NaN NaN NaN 2.751 1.129 1898 2 7.302 1.875 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-4.568 1915 1 3.757 1.350 0 0 3.465 1.057 1.807 0.185 1915 2 7.718 2.292 0 0 7.447 2.021 6.034 1.394 1915 3 4.656 -5.450 0 0 4.406 -5.700 2.891 -6.428 1915 4 17.968 1.630 0 0 17.656 1.318 16.986 1.434 1915 5 19.450 -1.759 0 0 19.041 -2.169 18.097 -2.326 1915 6 23.855 -2.433 0 0 23.502 -2.786 23.250 -2.252 1915 7 26.165 -2.999 0 0 26.007 -3.157 26.039 -2.339 1915 8 21.410 -7.036 0 0 21.318 -7.128 23.093 -4.567 1915 9 24.083 0.190 1 0 NaN NaN 22.999 -0.107 1915 10 17.083 -0.456 0 0 16.654 -0.885 16.968 0.215 1915 11 12.792 2.875 0 0 12.374 2.458 11.618 2.488 1915 12 6.469 1.821 0 0 6.140 1.492 5.310 1.448 1916 1 3.703 1.296 0 0 3.411 1.004 0.133 -1.488 1916 2 4.674 -0.752 0 0 4.403 -1.023 3.534 -1.106 1916 3 13.869 3.764 0 0 13.619 3.514 11.569 2.250 1916 4 14.477 -1.861 0 0 14.165 -2.173 12.903 -2.649 1916 5 21.787 0.578 0 0 21.377 0.168 20.757 0.334 1916 6 23.965 -2.323 0 0 23.612 -2.676 24.034 -1.468 1916 7 27.234 -1.930 0 0 27.076 -2.088 28.349 -0.029 1916 8 28.666 0.220 0 0 28.574 0.128 28.703 1.043 1916 9 23.038 -0.854 0 0 22.780 -1.113 22.246 -0.860 1916 10 17.299 -0.240 0 0 16.871 -0.668 16.971 0.218 1916 11 NaN NaN NaN NaN NaN NaN 9.329 0.198 1916 12 4.176 -0.473 0 0 3.847 -0.802 2.451 -1.411 1917 1 4.454 2.047 0 0 4.162 1.755 2.697 1.076 1917 2 3.959 -1.467 0 0 3.688 -1.738 2.914 -1.726 1917 3 12.326 2.220 0 0 12.076 1.970 9.433 0.113 1917 4 15.527 -0.811 0 0 15.215 -1.123 14.418 -1.134 1917 5 17.790 -3.419 0 0 17.381 -3.828 16.468 -3.955 1917 6 25.193 -1.095 0 0 24.840 -1.448 25.316 -0.186 1917 7 28.875 -0.289 0 0 28.717 -0.447 29.139 0.761 1917 8 25.392 -3.054 0 0 25.300 -3.146 25.324 -2.336 1917 9 22.815 -1.077 0 0 22.556 -1.336 22.508 -0.598 1917 10 14.309 -3.230 0 0 13.881 -3.658 13.587 -3.166 1917 11 12.063 2.146 0 0 11.645 1.729 10.442 1.312 1917 12 1.707 -2.942 0 0 1.378 -3.271 -0.536 -4.398 1918 1 -3.097 -5.504 0 0 -3.389 -5.797 -4.888 -6.509 1918 2 6.646 1.220 0 0 6.375 0.949 5.310 0.670 1918 3 14.423 4.318 0 0 14.173 4.068 11.966 2.647 1918 4 14.507 -1.831 0 0 14.195 -2.143 12.895 -2.657 1918 5 22.584 1.375 0 0 22.174 0.965 21.368 0.945 1918 6 27.212 0.925 0 0 26.859 0.572 27.659 2.157 1918 7 27.447 -1.717 0 0 27.289 -1.875 27.777 -0.601 1918 8 29.729 1.283 0 0 29.637 1.191 29.893 2.233 1918 9 20.752 -3.141 0 0 20.493 -3.399 19.947 -3.159 1918 10 19.602 2.063 0 0 19.173 1.634 18.244 1.491 1918 11 10.521 0.605 0 0 10.104 0.187 8.444 -0.686 1918 12 5.405 0.756 0 0 5.076 0.428 4.494 0.632 1919 1 4.973 2.565 0 0 4.681 2.273 1.863 0.242 1919 2 5.259 -0.167 0 0 4.988 -0.438 3.971 -0.669 1919 3 9.457 -0.649 0 0 9.207 -0.899 9.312 -0.008 1919 4 13.304 -3.034 0 0 12.992 -3.346 14.670 -0.882 1919 5 19.542 -1.667 0 0 19.132 -2.077 18.561 -1.862 1919 6 24.497 -1.791 0 0 24.144 -2.144 23.763 -1.739 1919 7 27.277 -1.887 0 0 27.119 -2.045 28.026 -0.352 1919 8 NaN NaN NaN NaN NaN NaN 28.220 0.561 1919 9 NaN NaN NaN NaN NaN NaN 23.809 0.703 1919 10 NaN NaN NaN NaN NaN NaN 15.642 -1.111 1919 11 NaN NaN NaN NaN NaN NaN 7.044 -2.086 1919 12 NaN NaN NaN NaN NaN NaN 0.562 -3.300 1920 1 NaN NaN NaN NaN NaN NaN 0.661 -0.961 1920 2 NaN NaN NaN NaN NaN NaN 5.230 0.590 1920 3 NaN NaN NaN NaN NaN NaN 9.611 0.292 1920 4 NaN NaN NaN NaN NaN NaN 13.305 -2.247 1920 5 NaN NaN NaN NaN NaN NaN 20.021 -0.402 1920 6 NaN NaN NaN NaN NaN NaN 24.201 -1.300 1920 7 NaN NaN NaN NaN NaN NaN 26.842 -1.536