% This file contains a station summary listing for a temperature % station in the Berkeley Earth database. This station is identified as: % % Berkeley ID#: 29057 % Primary Name: CARTHAGE % Record Type: TAVG % Country: United States % State: AR % Latitude: 34.06667 +/- 0.00833 % Longitude: -92.55000 +/- 0.00833 % Elevation (m): 94.76 +/- 16.78 % # of Months: 69 % % IDs: coop - 31255 % ncdc - 20000462 % % Sources: US Cooperative Summary of the Month % Multi-network Metadata System % % Site Hash: c05776de76b85f7eeaec71d4d1f527cb % Raw Data Hash: 47592fb75ac6b6b5f0907fae087165d2 % Adj Data Hash: ac12f25282e28e58a5fe3896092bd634 % % 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 1931 3 NaN NaN NaN NaN NaN NaN 8.092 -2.926 1931 4 NaN NaN NaN NaN NaN NaN 14.854 -1.698 1931 5 NaN NaN NaN NaN NaN NaN 18.262 -2.629 1931 6 NaN NaN NaN NaN NaN NaN 25.472 0.477 1931 7 NaN NaN NaN NaN NaN NaN 27.331 0.017 1931 8 NaN NaN NaN NaN NaN NaN 24.673 -2.051 1931 9 NaN NaN NaN NaN NaN NaN 25.717 2.593 1931 10 NaN NaN NaN NaN NaN NaN 19.518 2.650 1931 11 NaN NaN NaN NaN NaN NaN 14.003 3.519 1931 12 NaN NaN NaN NaN NaN NaN 8.831 2.778 1932 1 NaN NaN NaN NaN NaN NaN 7.201 2.891 1932 2 NaN NaN NaN NaN NaN NaN 10.734 3.992 1932 3 10.222 -1.016 0 0 10.571 -0.667 8.687 -2.331 1932 4 17.333 0.561 0 0 17.682 0.910 17.690 1.138 1932 5 20.667 -0.445 0 0 21.015 -0.096 20.659 -0.232 1932 6 25.889 0.674 0 0 26.238 1.023 26.084 1.089 1932 7 28.556 1.021 0 0 28.904 1.370 27.953 0.639 1932 8 27.444 0.500 0 0 27.793 0.849 27.617 0.892 1932 9 22.389 -0.956 0 0 22.738 -0.607 23.428 0.304 1932 10 16.500 -0.588 0 0 16.849 -0.239 15.894 -0.974 1932 11 8.667 -2.037 0 0 9.015 -1.688 8.152 -2.331 1932 12 5.111 -1.161 0 0 5.460 -0.813 4.396 -1.656 1933 1 10.111 5.581 0 0 10.460 5.930 8.856 4.546 1933 2 NaN NaN NaN NaN NaN NaN 4.861 -1.881 1933 3 NaN NaN NaN NaN NaN NaN 11.095 0.077 1933 4 15.444 -1.328 0 0 15.793 -0.979 16.134 -0.418 1933 5 22.000 0.889 0 0 22.349 1.238 21.728 0.837 1933 6 25.056 -0.159 0 0 25.404 0.190 25.673 0.678 1933 7 26.778 -0.757 0 0 27.127 -0.408 27.500 0.186 1933 8 26.333 -0.611 0 0 26.682 -0.262 26.203 -0.521 1933 9 25.889 2.544 0 0 26.238 2.893 25.741 2.616 1933 10 16.667 -0.421 0 0 17.015 -0.072 17.186 0.318 1933 11 11.111 0.407 0 0 11.460 0.756 11.863 1.379 1933 12 9.556 3.283 0 0 9.904 3.632 9.733 3.680 1934 1 6.611 2.081 0 0 6.960 2.430 6.599 2.290 1934 2 5.111 -1.851 0 0 5.460 -1.502 5.557 -1.185 1934 3 9.333 -1.905 0 0 9.682 -1.556 9.638 -1.380 1934 4 16.833 0.061 0 0 17.182 0.410 17.140 0.588 1934 5 21.111 -0.000 0 0 21.460 0.349 20.878 -0.013 1934 6 27.111 1.896 0 0 27.460 2.245 27.431 2.437 1934 7 28.667 1.132 0 0 29.015 1.481 29.755 2.441 1934 8 29.778 2.833 0 0 30.127 3.182 29.582 2.858 1934 9 21.889 -1.456 0 0 22.238 -1.107 21.888 -1.237 1934 10 16.833 -0.254 0 0 17.182 0.094 19.248 2.381 1934 11 11.333 0.629 0 0 11.682 0.978 12.261 1.777 1934 12 4.944 -1.328 0 0 5.293 -0.979 5.577 -0.475 1935 1 6.111 1.581 0 0 6.460 1.930 6.374 2.064 1935 2 7.222 0.261 0 0 7.571 0.609 7.675 0.934 1935 3 15.111 3.873 0 0 15.460 4.222 14.553 3.535 1935 4 16.722 -0.050 0 4 16.363 -0.409 15.993 -0.560 1935 5 20.000 -1.111 0 0 19.641 -1.470 18.978 -1.913 1935 6 24.611 -0.604 0 0 24.252 -0.963 23.703 -1.292 1935 7 28.000 0.466 0 0 27.641 0.107 27.852 0.538 1935 8 27.778 0.833 0 0 27.419 0.474 27.789 1.065 1935 9 22.944 -0.400 0 0 22.585 -0.759 22.597 -0.527 1935 10 18.111 1.023 0 0 17.752 0.664 17.833 0.966 1935 11 10.889 0.185 0 0 10.530 -0.174 10.000 -0.484 1935 12 3.778 -2.495 0 0 3.419 -2.854 3.532 -2.520 1936 1 4.111 -0.419 0 0 3.752 -0.778 2.992 -1.318 1936 2 4.333 -2.628 0 0 3.974 -2.987 2.654 -4.088 1936 3 14.333 3.095 0 0 13.974 2.736 13.609 2.591 1936 4 16.333 -0.439 0 0 15.974 -0.798 15.532 -1.020 1936 5 21.833 0.722 0 0 21.474 0.363 21.245 0.354 1936 6 26.667 1.452 0 0 26.308 1.093 26.934 1.939 1936 7 27.778 0.243 0 0 27.419 -0.116 28.130 0.815 1936 8 29.222 2.278 0 0 28.863 1.919 29.446 2.722 1936 9 26.722 3.378 0 0 26.363 3.019 26.201 3.076 1936 10 16.111 -0.977 0 0 15.752 -1.336 15.966 -0.902 1936 11 9.444 -1.259 0 0 9.085 -1.618 8.983 -1.500 1936 12 8.056 1.783 0 0 7.697 1.424 7.502 1.449 1937 1 7.000 2.470 0 0 6.641 2.111 4.630 0.320 1937 2 8.111 1.149 0 0 7.752 0.790 6.672 -0.070 1937 3 9.889 -1.349 0 0 9.530 -1.708 8.842 -2.176 1937 4 16.444 -0.328 0 0 16.085 -0.687 16.494 -0.058 1937 5 21.667 0.555 0 0 21.308 0.196 21.274 0.383 1937 6 25.889 0.674 0 0 25.530 0.315 25.984 0.990 1937 7 NaN NaN NaN NaN NaN NaN 26.925 -0.390 1937 8 NaN NaN NaN NaN NaN NaN 27.679 0.954 1937 9 NaN NaN NaN NaN NaN NaN 22.728 -0.396 1937 10 NaN NaN NaN NaN NaN NaN 15.920 -0.948 1937 11 NaN NaN NaN NaN NaN NaN 8.830 -1.653 1937 12 NaN NaN NaN NaN NaN NaN 6.078 0.026 1938 1 NaN NaN NaN NaN NaN NaN 5.420 1.110 1938 2 11.000 4.038 0 0 10.641 3.679 10.069 3.328 1938 3 16.611 5.373 0 0 16.252 5.014 15.231 4.212 1938 4 17.667 0.895 0 0 17.308 0.536 16.675 0.123 1938 5 21.667 0.555 0 0 21.308 0.196 20.872 -0.020 1938 6 NaN NaN NaN NaN NaN NaN 24.625 -0.369 1938 7 28.500 0.966 0 0 28.141 0.607 27.946 0.632 1938 8 28.556 1.611 0 0 28.197 1.252 28.210 1.486 1938 9 24.667 1.322 0 0 24.308 0.963 24.277 1.152 1938 10 NaN NaN NaN NaN NaN NaN 19.332 2.464 1938 11 NaN NaN NaN NaN NaN NaN 10.033 -0.451 1938 12 NaN NaN NaN NaN NaN NaN 6.484 0.432 1939 1 NaN NaN NaN NaN NaN NaN 6.879 2.570 1939 2 NaN NaN NaN NaN NaN NaN 6.233 -0.508 1939 3 NaN NaN NaN NaN NaN NaN 12.568 1.550 1939 4 NaN NaN NaN NaN NaN NaN 15.315 -1.237 1939 5 NaN NaN NaN NaN NaN NaN 20.534 -0.358 1939 6 NaN NaN NaN NaN NaN NaN 25.690 0.695 1939 7 NaN NaN NaN NaN NaN NaN 28.122 0.807 1939 8 NaN NaN NaN NaN NaN NaN 26.867 0.143 1939 9 NaN NaN NaN NaN NaN NaN 26.687 3.562