% This file contains a station summary listing for a temperature % station in the Berkeley Earth database. This station is identified as: % % Berkeley ID#: 30677 % Primary Name: DUTTON % Record Type: TAVG % Country: United States % State: AR % Latitude: 35.80000 +/- 0.00833 % Longitude: -93.70000 +/- 0.00833 % Elevation (m): 484.90 +/- 0.05 % # of Months: 66 % % IDs: coop - 32188 % ncdc - 20000692 % % Sources: US Cooperative Summary of the Month % Multi-network Metadata System % % Site Hash: 576e0764d6c9d380bf3ef0b6c37ae4e4 % Raw Data Hash: 764f984d9c2465b86514c44f9423570c % Adj Data Hash: 750837f9aa27891e2c0aa3adccc48f3e % % 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 1930 1 NaN NaN NaN NaN NaN NaN -3.692 -5.178 1930 2 NaN NaN NaN NaN NaN NaN 8.729 4.728 1930 3 NaN NaN NaN NaN NaN NaN 7.199 -1.203 1930 4 NaN NaN NaN NaN NaN NaN 16.481 2.013 1930 5 NaN NaN NaN NaN NaN NaN 17.858 -0.946 1930 6 NaN NaN NaN NaN NaN NaN 22.170 -0.869 1930 7 NaN NaN NaN NaN NaN NaN 27.255 1.667 1930 8 NaN NaN NaN NaN NaN NaN 25.846 0.920 1930 9 NaN NaN NaN NaN NaN NaN 22.466 1.219 1930 10 NaN NaN NaN NaN NaN NaN 13.821 -1.379 1930 11 NaN NaN NaN NaN NaN NaN 8.576 -0.002 1930 12 NaN NaN NaN NaN NaN NaN 2.879 -0.867 1931 1 2.556 2.114 0 0 2.556 2.114 3.102 1.616 1931 2 5.500 2.543 0 0 5.500 2.543 6.422 2.421 1931 3 4.889 -2.469 0 0 4.889 -2.469 5.455 -2.947 1931 4 11.222 -2.202 0 0 11.222 -2.202 12.833 -1.635 1931 5 14.778 -2.982 0 0 14.778 -2.982 15.992 -2.812 1931 6 21.667 -0.329 0 0 21.667 -0.329 23.952 0.913 1931 7 23.889 -0.654 0 0 23.889 -0.654 25.900 0.312 1931 8 21.222 -2.660 0 0 21.222 -2.660 22.743 -2.183 1931 9 22.222 2.020 0 0 22.222 2.020 24.161 2.914 1931 10 15.778 1.622 0 0 15.778 1.622 17.783 2.583 1931 11 11.556 4.022 0 0 11.556 4.022 12.673 4.095 1931 12 NaN NaN NaN NaN NaN NaN 7.185 3.439 1932 1 4.944 4.503 0 0 4.944 4.503 4.751 3.265 1932 2 8.889 5.932 0 0 8.889 5.932 8.700 4.699 1932 3 6.167 -1.191 0 0 6.167 -1.191 5.962 -2.440 1932 4 14.778 1.354 0 0 14.778 1.354 15.949 1.480 1932 5 17.222 -0.537 0 0 17.222 -0.537 18.557 -0.247 1932 6 22.556 0.560 0 0 22.556 0.560 23.796 0.756 1932 7 25.556 1.013 0 0 25.556 1.013 26.422 0.834 1932 8 23.056 -0.827 0 0 23.056 -0.827 25.446 0.520 1932 9 21.111 0.909 0 0 21.111 0.909 21.476 0.230 1932 10 NaN NaN NaN NaN NaN NaN 14.143 -1.057 1932 11 NaN NaN NaN NaN NaN NaN 6.191 -2.386 1932 12 1.889 -0.813 0 0 1.889 -0.813 2.203 -1.543 1933 1 NaN NaN NaN NaN NaN NaN 6.525 5.039 1933 2 NaN NaN NaN NaN NaN NaN 2.412 -1.589 1933 3 NaN NaN NaN NaN NaN NaN 8.386 -0.016 1933 4 NaN NaN NaN NaN NaN NaN 14.061 -0.407 1933 5 NaN NaN NaN NaN NaN NaN 19.475 0.671 1933 6 22.778 0.782 0 0 22.778 0.782 24.621 1.581 1933 7 24.944 0.401 0 0 24.944 0.401 26.373 0.785 1933 8 22.889 -0.993 0 0 22.889 -0.993 24.091 -0.836 1933 9 22.222 2.020 0 0 22.222 2.020 23.814 2.568 1933 10 13.222 -0.934 0 0 13.222 -0.934 15.069 -0.131 1933 11 8.667 1.133 0 0 8.667 1.133 9.766 1.188 1933 12 6.056 3.354 0 0 6.056 3.354 7.173 3.427 1934 1 4.056 3.614 0 0 4.056 3.614 3.842 2.356 1934 2 1.111 -1.846 0 0 1.111 -1.846 2.654 -1.347 1934 3 6.444 -0.913 0 0 6.444 -0.913 6.789 -1.612 1934 4 13.556 0.131 0 0 13.556 0.131 14.802 0.334 1934 5 NaN NaN NaN NaN NaN NaN 19.268 0.464 1934 6 23.556 1.560 0 0 23.556 1.560 25.923 2.883 1934 7 26.611 2.068 0 0 26.611 2.068 29.098 3.511 1934 8 25.889 2.007 0 0 25.889 2.007 27.611 2.685 1934 9 17.556 -2.647 0 0 17.556 -2.647 19.409 -1.838 1934 10 15.667 1.511 0 0 15.667 1.511 17.196 1.996 1934 11 9.667 2.133 0 0 9.667 2.133 10.586 2.009 1934 12 3.111 0.409 0 0 3.111 0.409 3.026 -0.720 1935 1 4.222 3.780 0 0 4.222 3.780 3.482 1.996 1935 2 4.889 1.932 0 0 4.889 1.932 5.076 1.075 1935 3 11.389 4.031 0 0 11.389 4.031 11.683 3.282 1935 4 NaN NaN NaN NaN NaN NaN 13.135 -1.333 1935 5 15.556 -2.204 0 0 15.556 -2.204 16.674 -2.129 1935 6 19.444 -2.551 0 0 19.444 -2.551 20.996 -2.044 1935 7 24.333 -0.210 0 0 24.333 -0.210 26.306 0.719 1935 8 24.444 0.562 0 0 24.444 0.562 25.976 1.049 1935 9 18.556 -1.647 0 0 18.556 -1.647 20.409 -0.837 1935 10 14.000 -0.156 0 0 14.000 -0.156 15.469 0.270 1935 11 6.889 -0.645 1 0 NaN NaN 7.398 -1.180 1935 12 1.000 -1.702 0 0 1.000 -1.702 1.310 -2.436 1936 1 0.778 0.336 0 0 0.778 0.336 -0.470 -1.956 1936 2 0.333 -2.624 0 0 0.333 -2.624 -0.715 -4.716 1936 3 10.667 3.309 0 0 10.667 3.309 10.909 2.508 1936 4 12.111 -1.313 0 0 12.111 -1.313 13.298 -1.170 1936 5 17.889 0.130 0 0 17.889 0.130 19.560 0.757 1936 6 22.611 0.616 0 0 22.611 0.616 25.058 2.018 1936 7 26.000 1.457 0 0 26.000 1.457 28.150 2.563 1936 8 26.500 2.618 0 0 26.500 2.618 28.530 3.603 1936 9 23.056 2.853 0 0 23.056 2.853 24.228 2.981 1936 10 13.111 -1.045 0 0 13.111 -1.045 14.278 -0.922 1936 11 6.889 -0.645 1 0 NaN NaN 7.173 -1.405 1936 12 5.111 2.409 0 0 5.111 2.409 5.640 1.894 1937 1 2.333 1.891 0 0 2.333 1.891 0.944 -0.542 1937 2 4.000 1.043 0 0 4.000 1.043 3.393 -0.608 1937 3 NaN NaN NaN NaN NaN NaN 5.844 -2.557 1937 4 NaN NaN NaN NaN NaN NaN 14.068 -0.401 1937 5 18.000 0.241 0 0 18.000 0.241 19.011 0.207 1937 6 22.667 0.671 0 0 22.667 0.671 23.953 0.913 1937 7 NaN NaN NaN NaN NaN NaN 25.326 -0.261 1937 8 NaN NaN NaN NaN NaN NaN 26.345 1.418 1937 9 NaN NaN NaN NaN NaN NaN 20.789 -0.457 1937 10 NaN NaN NaN NaN NaN NaN 14.608 -0.592 1937 11 NaN NaN NaN NaN NaN NaN 6.450 -2.127 1937 12 NaN NaN NaN NaN NaN NaN 2.720 -1.026 1938 1 NaN NaN NaN NaN NaN NaN 2.513 1.027 1938 2 NaN NaN NaN NaN NaN NaN 7.402 3.401 1938 3 NaN NaN NaN NaN NaN NaN 12.939 4.537 1938 4 NaN NaN NaN NaN NaN NaN 14.641 0.172 1938 5 NaN NaN NaN NaN NaN NaN 18.548 -0.256 1938 6 NaN NaN NaN NaN NaN NaN 22.363 -0.676