% This file contains a station summary listing for a temperature % station in the Berkeley Earth database. This station is identified as: % % Berkeley ID#: 27533 % Primary Name: LAKE COMO % Record Type: TAVG % Country: United States % State: MS % Latitude: 31.96670 +/- 0.00005 % Longitude: -89.21670 +/- 0.00005 % Elevation (m): 101.60 +/- 34.25 % # of Months: 103 % % Alternate Names: Missing Station ID - 224838 % % IDs: coop - 224838 % ghcnd - USC00224838 % ncdc - 20011226 % % Sources: US Cooperative Summary of the Day % Global Historical Climatology Network - Daily % US Cooperative Summary of the Month % Multi-network Metadata System % % Site Hash: f1df73570d2fcbcd5cd917374cc5f178 % Raw Data Hash: c7bf78c0f5a1fb018625ce5af8ef7c8e % Adj Data Hash: 21171ab894cd5a178c0b926185c631bd % % 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 1901 8 NaN NaN NaN NaN NaN NaN 26.552 -0.393 1901 9 NaN NaN NaN NaN NaN NaN 24.091 -0.548 1901 10 NaN NaN NaN NaN NaN NaN 17.786 -0.713 1901 11 NaN NaN NaN NaN NaN NaN 10.994 -2.277 1901 12 NaN NaN NaN NaN NaN NaN 7.459 -2.403 1902 1 NaN NaN NaN NaN NaN NaN 7.586 -1.147 1902 2 NaN NaN NaN NaN NaN NaN 6.758 -3.782 1902 3 NaN NaN NaN NaN NaN NaN 14.731 0.335 1902 4 NaN NaN NaN NaN NaN NaN 18.191 -0.571 1902 5 NaN NaN NaN NaN NaN NaN 24.393 1.797 1902 6 NaN NaN NaN NaN NaN NaN 27.722 1.764 1902 7 NaN NaN NaN NaN NaN NaN 27.946 0.710 1902 8 29.332 2.287 0 0 29.332 2.287 28.155 1.210 1902 9 23.500 -1.238 0 0 23.500 -1.238 24.358 -0.281 1902 10 18.278 -0.321 0 0 18.278 -0.321 17.893 -0.606 1902 11 14.556 1.185 0 0 14.556 1.185 15.081 1.810 1902 12 9.056 -0.906 0 0 9.056 -0.906 9.290 -0.572 1903 1 7.556 -1.278 0 0 7.556 -1.278 7.341 -1.393 1903 2 10.556 -0.085 0 0 10.556 -0.085 10.183 -0.358 1903 3 16.611 2.115 0 0 16.611 2.115 16.144 1.747 1903 4 16.778 -2.083 0 0 16.778 -2.083 17.609 -1.153 1903 5 20.778 -1.918 0 0 20.778 -1.918 21.144 -1.452 1903 6 23.111 -2.946 0 0 23.111 -2.946 23.902 -2.055 1903 7 27.222 -0.113 0 0 27.222 -0.113 26.634 -0.602 1903 8 27.611 0.567 0 0 27.611 0.567 26.715 -0.230 1903 9 23.722 -1.016 0 0 23.722 -1.016 23.695 -0.944 1903 10 18.833 0.235 0 0 18.833 0.235 17.865 -0.635 1903 11 12.222 -1.149 0 0 12.222 -1.149 11.935 -1.337 1903 12 7.722 -2.239 0 0 7.722 -2.239 6.711 -3.151 1904 1 7.222 -1.611 0 0 7.222 -1.611 6.442 -2.292 1904 2 12.222 1.582 0 0 12.222 1.582 11.399 0.859 1904 3 17.000 2.504 0 0 17.000 2.504 16.347 1.951 1904 4 16.444 -2.417 0 0 16.444 -2.417 17.403 -1.359 1904 5 20.333 -2.362 0 0 20.333 -2.362 21.132 -1.464 1904 6 25.778 -0.280 0 0 25.778 -0.280 26.118 0.160 1904 7 25.833 -1.502 0 0 25.833 -1.502 25.763 -1.472 1904 8 26.556 -0.489 0 0 26.556 -0.489 26.143 -0.802 1904 9 26.222 1.484 0 0 26.222 1.484 26.193 1.554 1904 10 19.722 1.123 0 0 19.722 1.123 19.007 0.507 1904 11 10.889 -2.482 0 0 10.889 -2.482 12.092 -1.179 1904 12 9.444 -0.517 0 0 9.444 -0.517 9.407 -0.455 1905 1 5.833 -3.000 0 0 5.833 -3.000 5.611 -3.123 1905 2 6.111 -4.529 0 0 6.111 -4.529 5.574 -4.967 1905 3 16.667 2.171 0 0 16.667 2.171 16.010 1.613 1905 4 17.333 -1.528 0 0 17.333 -1.528 18.845 0.083 1905 5 24.333 1.638 0 0 24.333 1.638 24.184 1.588 1905 6 26.722 0.665 0 0 26.722 0.665 26.821 0.864 1905 7 26.778 -0.558 0 0 26.778 -0.558 26.423 -0.813 1905 8 27.778 0.733 0 0 27.778 0.733 26.745 -0.200 1905 9 25.944 1.206 0 0 25.944 1.206 25.679 1.041 1905 10 19.000 0.401 0 0 19.000 0.401 18.087 -0.412 1905 11 15.000 1.629 0 0 15.000 1.629 14.493 1.222 1905 12 8.111 -1.850 0 0 8.111 -1.850 7.111 -2.751 1906 1 8.889 0.056 0 0 8.889 0.056 8.529 -0.205 1906 2 8.000 -2.640 0 0 8.000 -2.640 7.984 -2.556 1906 3 11.556 -2.940 0 0 11.556 -2.940 12.201 -2.195 1906 4 18.889 0.028 0 0 18.889 0.028 18.998 0.236 1906 5 21.333 -1.362 0 0 21.333 -1.362 21.279 -1.317 1906 6 26.889 0.832 0 0 26.889 0.832 26.615 0.657 1906 7 26.944 -0.391 0 0 26.944 -0.391 26.517 -0.719 1906 8 27.778 0.733 0 0 27.778 0.733 26.899 -0.046 1906 9 26.000 1.262 0 0 26.000 1.262 26.101 1.462 1906 10 16.722 -1.877 0 0 16.722 -1.877 16.290 -2.209 1906 11 14.889 1.518 0 0 14.889 1.518 15.064 1.793 1906 12 11.889 1.928 0 0 11.889 1.928 11.887 2.026 1907 1 14.722 5.889 0 0 14.722 5.889 13.590 4.856 1907 2 12.500 1.860 0 0 12.500 1.860 11.221 0.680 1907 3 19.556 5.060 0 0 19.556 5.060 19.370 4.974 1907 4 15.667 -3.195 0 0 15.667 -3.195 16.606 -2.155 1907 5 20.111 -2.585 0 0 20.111 -2.585 20.805 -1.791 1907 6 25.183 -0.874 0 0 25.183 -0.874 25.259 -0.699 1907 7 27.556 0.220 0 0 27.556 0.220 27.171 -0.065 1907 8 27.333 0.289 0 0 27.333 0.289 27.086 0.141 1907 9 24.222 -0.516 0 0 24.222 -0.516 24.996 0.357 1907 10 18.667 0.068 0 0 18.667 0.068 18.351 -0.148 1907 11 11.667 -1.704 0 0 11.667 -1.704 11.800 -1.472 1907 12 10.000 0.039 0 0 10.000 0.039 9.454 -0.407 1908 1 9.000 0.167 0 0 9.000 0.167 8.122 -0.612 1908 2 9.111 -1.529 0 0 9.111 -1.529 8.644 -1.897 1908 3 18.222 3.726 0 0 18.222 3.726 17.966 3.570 1908 4 21.889 3.028 0 0 21.889 3.028 21.223 2.462 1908 5 22.500 -0.196 0 0 22.500 -0.196 22.636 0.040 1908 6 26.500 0.443 0 0 26.500 0.443 26.107 0.149 1908 7 27.111 -0.224 0 0 27.111 -0.224 26.522 -0.713 1908 8 26.667 -0.378 0 0 26.667 -0.378 26.530 -0.415 1908 9 NaN NaN NaN NaN NaN NaN 24.571 -0.068 1908 10 16.222 -2.377 0 0 16.222 -2.377 15.904 -2.595 1908 11 15.111 1.740 0 0 15.111 1.740 14.963 1.692 1908 12 12.000 2.039 0 0 12.000 2.039 12.167 2.306 1909 1 11.278 2.444 0 0 11.278 2.444 11.112 2.379 1909 2 12.111 1.471 0 0 12.111 1.471 10.616 0.076 1909 3 15.667 1.171 0 0 15.667 1.171 15.489 1.093 1909 4 17.722 -1.139 0 0 17.722 -1.139 18.324 -0.438 1909 5 20.556 -2.140 0 0 20.556 -2.140 20.998 -1.598 1909 6 25.944 -0.113 0 0 25.944 -0.113 26.081 0.123 1909 7 28.000 0.665 0 0 28.000 0.665 27.300 0.064 1909 8 27.333 0.289 0 0 27.333 0.289 27.272 0.327 1909 9 NaN NaN NaN NaN NaN NaN 25.164 0.526 1909 10 NaN NaN NaN NaN NaN NaN 18.227 -0.272 1909 11 15.000 1.629 0 0 15.000 1.629 15.823 2.552 1909 12 6.833 -3.128 0 0 6.833 -3.128 6.996 -2.865 1910 1 8.722 -0.111 0 0 8.722 -0.111 8.937 0.203 1910 2 8.444 -2.196 0 0 8.444 -2.196 8.670 -1.871 1910 3 17.111 2.615 0 0 17.111 2.615 17.044 2.648 1910 4 16.778 -2.083 0 0 16.778 -2.083 17.912 -0.850 1910 5 20.278 -2.418 0 0 20.278 -2.418 21.257 -1.339 1910 6 23.444 -2.613 0 0 23.444 -2.613 24.989 -0.969 1910 7 25.889 -1.447 0 0 25.889 -1.447 26.296 -0.940 1910 8 NaN NaN NaN NaN NaN NaN 27.099 0.154 1910 9 NaN NaN NaN NaN NaN NaN 25.835 1.196 1910 10 NaN NaN NaN NaN NaN NaN 19.278 0.778 1910 11 12.333 -1.038 0 0 12.333 -1.038 12.513 -0.758 1910 12 NaN NaN NaN NaN NaN NaN 8.681 -1.181 1911 1 13.222 4.389 0 0 13.222 4.389 12.104 3.370 1911 2 NaN NaN NaN NaN NaN NaN 14.378 3.838 1911 3 16.111 1.615 0 0 16.111 1.615 16.307 1.910 1911 4 19.111 0.250 0 0 19.111 0.250 19.483 0.721 1911 5 22.889 0.193 0 0 22.889 0.193 22.806 0.210 1911 6 27.444 1.387 0 0 27.444 1.387 27.572 1.614 1911 7 25.889 -1.447 0 0 25.889 -1.447 25.673 -1.563 1911 8 27.000 -0.044 0 0 27.000 -0.044 26.386 -0.559 1911 9 27.111 2.373 0 0 27.111 2.373 27.478 2.839 1911 10 20.444 1.846 0 0 20.444 1.846 20.444 1.945 1911 11 NaN NaN NaN NaN NaN NaN 11.412 -1.859 1911 12 NaN NaN NaN NaN NaN NaN 11.438 1.577 1912 1 NaN NaN NaN NaN NaN NaN 6.143 -2.591 1912 2 NaN NaN NaN NaN NaN NaN 7.100 -3.440 1912 3 NaN NaN NaN NaN NaN NaN 13.336 -1.060 1912 4 NaN NaN NaN NaN NaN NaN 19.205 0.443 1912 5 NaN NaN NaN NaN NaN NaN 22.686 0.090 1912 6 NaN NaN NaN NaN NaN NaN 24.411 -1.547 1912 7 NaN NaN NaN NaN NaN NaN 26.672 -0.563 1912 8 NaN NaN NaN NaN NaN NaN 26.703 -0.242 1912 9 NaN NaN NaN NaN NaN NaN 26.190 1.552 1912 10 NaN NaN NaN NaN NaN NaN 19.538 1.039