% This file contains a station summary listing for a temperature % station in the Berkeley Earth database. This station is identified as: % % Berkeley ID#: 26832 % Primary Name: GARNIERS (NEAR) % Record Type: TAVG % Country: United States % State: FL % Latitude: 30.46667 +/- 0.00833 % Longitude: -86.60000 +/- 0.00833 % Elevation (m): 5.50 +/- 0.05 % # of Months: 83 % % Alternate Names: GARNIERS NEAR % % IDs: coop - 83366 % ncdc - 20004632 % % Sources: US Cooperative Summary of the Month % Multi-network Metadata System % % Site Hash: 7c76384335b8341206eececa71d8eae3 % Raw Data Hash: 4040ed4ef17fbf2b90f519cdff1c14bb % Adj Data Hash: f0da3973a389912b9cecb9d8fd357d75 % % 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 14.018 -0.122 1930 2 NaN NaN NaN NaN NaN NaN 16.228 1.714 1930 3 NaN NaN NaN NaN NaN NaN 14.856 -2.009 1930 4 NaN NaN NaN NaN NaN NaN 20.127 0.086 1930 5 NaN NaN NaN NaN NaN NaN 23.981 0.463 1930 6 NaN NaN NaN NaN NaN NaN 25.955 -0.245 1930 7 NaN NaN NaN NaN NaN NaN 27.731 0.580 1930 8 NaN NaN NaN NaN NaN NaN 26.926 -0.433 1930 9 NaN NaN NaN NaN NaN NaN 27.225 0.672 1930 10 NaN NaN NaN NaN NaN NaN 21.377 -1.152 1930 11 NaN NaN NaN NaN NaN NaN 18.185 -0.312 1930 12 NaN NaN NaN NaN NaN NaN 13.371 -2.231 1931 1 9.444 -2.864 0 0 9.746 -2.563 13.009 -1.131 1931 2 11.222 -1.460 0 0 11.524 -1.158 14.169 -0.345 1931 3 12.722 -2.311 0 0 13.024 -2.009 14.065 -2.800 1931 4 16.944 -1.266 0 0 17.246 -0.964 18.356 -1.685 1931 5 21.333 -0.353 0 0 21.635 -0.051 22.125 -1.393 1931 6 26.000 1.631 0 0 26.302 1.933 26.551 0.351 1931 7 27.111 1.792 0 0 27.413 2.093 27.493 0.342 1931 8 25.889 0.362 0 0 26.190 0.663 26.523 -0.836 1931 9 26.111 1.390 0 0 26.413 1.692 27.890 1.338 1931 10 21.500 0.803 0 0 21.802 1.105 23.977 1.448 1931 11 16.889 0.224 0 0 17.190 0.526 21.036 2.539 1931 12 16.556 2.785 0 0 16.857 3.087 20.649 5.047 1932 1 NaN NaN NaN NaN NaN NaN 17.789 3.648 1932 2 NaN NaN NaN NaN NaN NaN 19.638 5.124 1932 3 12.389 -2.644 0 0 12.690 -2.342 14.840 -2.024 1932 4 18.667 0.457 0 0 18.968 0.758 20.064 0.023 1932 5 21.667 -0.020 0 0 21.968 0.282 22.651 -0.867 1932 6 25.444 1.076 0 0 25.746 1.377 26.586 0.385 1932 7 27.556 2.236 0 0 27.857 2.538 28.465 1.314 1932 8 26.222 0.695 0 0 26.524 0.997 27.277 -0.082 1932 9 24.889 0.168 0 0 25.190 0.470 26.828 0.275 1932 10 18.889 -1.808 0 0 19.190 -1.507 21.729 -0.799 1932 11 12.222 -4.443 0 0 12.524 -4.141 15.953 -2.543 1932 12 13.444 -0.326 0 0 13.746 -0.024 18.043 2.441 1933 1 12.667 0.358 0 0 12.968 0.659 16.571 2.431 1933 2 12.111 -0.571 0 0 12.413 -0.270 14.983 0.469 1933 3 14.444 -0.588 0 0 14.746 -0.287 17.008 0.143 1933 4 18.333 0.123 0 0 18.635 0.425 20.024 -0.018 1933 5 24.333 2.647 0 0 24.635 2.949 25.508 1.990 1933 6 24.833 0.465 0 0 25.135 0.766 26.060 -0.141 1933 7 26.778 1.458 0 0 27.079 1.760 26.863 -0.288 1933 8 26.278 0.751 0 0 26.579 1.052 27.441 0.082 1933 9 26.778 2.057 0 0 27.079 2.359 28.997 2.444 1933 10 20.556 -0.142 0 0 20.857 0.160 23.477 0.948 1933 11 NaN NaN NaN NaN NaN NaN 18.538 0.041 1933 12 15.222 1.452 0 0 15.524 1.753 19.634 4.032 1934 1 12.778 0.469 0 4 12.579 0.270 15.535 1.395 1934 2 9.889 -2.793 0 0 9.690 -2.992 12.733 -1.781 1934 3 14.111 -0.922 0 0 13.912 -1.121 16.044 -0.821 1934 4 18.556 0.346 0 0 18.357 0.147 19.941 -0.101 1934 5 23.222 1.536 0 0 23.023 1.337 23.275 -0.244 1934 6 26.556 2.187 0 0 26.357 1.988 26.877 0.677 1934 7 27.556 2.236 0 0 27.357 2.037 27.235 0.084 1934 8 27.000 1.473 0 0 26.801 1.274 27.331 -0.027 1934 9 25.056 0.335 0 0 24.857 0.136 26.749 0.197 1934 10 22.111 1.414 0 0 21.912 1.215 24.088 1.559 1934 11 16.000 -0.665 0 0 15.801 -0.864 19.747 1.250 1934 12 11.111 -2.659 0 0 10.912 -2.858 15.080 -0.522 1935 1 11.556 -0.753 0 0 11.356 -0.952 14.797 0.656 1935 2 11.667 -1.016 0 0 11.468 -1.215 14.162 -0.352 1935 3 17.222 2.189 0 0 17.023 1.990 19.143 2.278 1935 4 19.111 0.901 0 0 18.912 0.702 20.349 0.308 1935 5 23.944 2.258 0 0 23.745 2.059 24.130 0.612 1935 6 26.222 1.854 0 0 26.023 1.654 26.291 0.090 1935 7 27.333 2.014 0 0 27.134 1.815 26.923 -0.228 1935 8 27.333 1.806 0 0 27.134 1.607 27.521 0.162 1935 9 25.000 0.279 0 0 24.801 0.080 26.077 -0.475 1935 10 21.389 0.692 0 0 21.190 0.493 23.279 0.750 1935 11 15.944 -0.720 0 0 15.745 -0.920 18.744 0.248 1935 12 8.000 -5.771 0 0 7.801 -5.970 12.026 -3.577 1936 1 11.333 -0.976 0 0 11.134 -1.175 14.179 0.039 1936 2 10.444 -2.238 0 0 10.245 -2.437 12.822 -1.692 1936 3 16.222 1.189 0 0 16.023 0.990 17.925 1.061 1936 4 18.556 0.346 0 0 18.357 0.147 19.397 -0.645 1936 5 23.000 1.314 0 0 22.801 1.115 23.547 0.029 1936 6 26.556 2.187 0 0 26.357 1.988 26.979 0.779 1936 7 27.333 2.014 0 0 27.134 1.815 27.345 0.194 1936 8 27.222 1.695 0 0 27.023 1.496 27.372 0.013 1936 9 26.889 2.168 0 0 26.690 1.969 28.088 1.535 1936 10 21.722 1.025 0 0 21.523 0.826 23.903 1.374 1936 11 14.056 -2.609 0 0 13.856 -2.808 17.864 -0.633 1936 12 13.056 -0.715 0 0 12.856 -0.914 16.402 0.800 1937 1 18.111 5.802 0 0 17.912 5.603 20.505 6.365 1937 2 12.111 -0.571 0 0 11.912 -0.770 14.322 -0.192 1937 3 12.889 -2.144 0 0 12.690 -2.343 15.093 -1.772 1937 4 18.500 0.290 0 0 18.301 0.091 19.392 -0.649 1937 5 23.111 1.425 0 0 22.912 1.226 23.844 0.326 1937 6 27.111 2.742 0 0 26.912 2.543 26.742 0.541 1937 7 27.389 2.070 0 0 27.190 1.871 27.059 -0.092 1937 8 27.500 1.973 0 0 27.301 1.774 27.200 -0.159 1937 9 24.722 0.001 0 0 24.523 -0.198 26.088 -0.465 1937 10 18.222 -2.475 0 0 18.023 -2.674 21.676 -0.853 1937 11 NaN NaN NaN NaN NaN NaN 16.461 -2.035 1937 12 NaN NaN NaN NaN NaN NaN 14.624 -0.979 1938 1 11.111 -1.198 0 0 10.912 -1.397 14.387 0.247 1938 2 13.667 0.984 0 0 13.468 0.785 16.293 1.779 1938 3 17.889 2.856 0 0 17.690 2.657 20.248 3.383 1938 4 16.556 -1.654 0 0 16.357 -1.853 19.826 -0.216 1938 5 NaN NaN NaN NaN NaN NaN 23.730 0.212 1938 6 NaN NaN NaN NaN NaN NaN 26.138 -0.063 1938 7 NaN NaN NaN NaN NaN NaN 26.485 -0.666 1938 8 NaN NaN NaN NaN NaN NaN 27.967 0.608 1938 9 NaN NaN NaN NaN NaN NaN 26.456 -0.096 1938 10 NaN NaN NaN NaN NaN NaN 22.354 -0.175 1938 11 NaN NaN NaN NaN NaN NaN 18.945 0.448 1938 12 NaN NaN NaN NaN NaN NaN 15.192 -0.411 1939 1 NaN NaN NaN NaN NaN NaN 15.947 1.806 1939 2 NaN NaN NaN NaN NaN NaN 16.359 1.845 1939 3 NaN NaN NaN NaN NaN NaN 18.273 1.409 1939 4 NaN NaN NaN NaN NaN NaN 19.713 -0.328