% This file contains a station summary listing for a temperature % station in the Berkeley Earth database. This station is identified as: % % Berkeley ID#: 33236 % Primary Name: MARDELLA SPRINGS % Record Type: TAVG % Country: United States % State: MD % Latitude: 38.46670 +/- 0.00005 % Longitude: -75.76670 +/- 0.00005 % Elevation (m): 7.62 +/- 0.15 % # of Months: 70 % % Alternate Names: Missing Station ID - 185665 % % IDs: coop - 185665 % ghcnd - USC00185665 % ncdc - 12002338 % % Sources: US Cooperative Summary of the Day % Global Historical Climatology Network - Daily % Multi-network Metadata System % % Site Hash: 303b4e8977dcfb02055c8529bb0f1a02 % Raw Data Hash: 8670d1476e58fd633230ca490cec4ab2 % Adj Data Hash: c8c9f981632714fd5cab9330082f4a58 % % 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 1893 1 NaN NaN NaN NaN NaN NaN -2.332 -5.853 1893 2 NaN NaN NaN NaN NaN NaN 3.323 -0.628 1893 3 NaN NaN NaN NaN NaN NaN 5.536 -1.851 1893 4 NaN NaN NaN NaN NaN NaN 12.302 0.144 1893 5 NaN NaN NaN NaN NaN NaN 16.155 -0.902 1893 6 NaN NaN NaN NaN NaN NaN 21.291 -0.380 1893 7 NaN NaN NaN NaN NaN NaN 24.164 -0.216 1893 8 NaN NaN NaN NaN NaN NaN 23.625 -0.638 1893 9 NaN NaN NaN NaN NaN NaN 20.466 -0.955 1893 10 NaN NaN NaN NaN NaN NaN 15.111 -0.551 1893 11 NaN NaN NaN NaN NaN NaN 9.663 -0.917 1893 12 NaN NaN NaN NaN NaN NaN 5.987 0.382 1894 1 3.128 0.138 0 0 3.128 0.138 5.181 1.660 1894 2 2.737 -0.683 0 0 2.737 -0.683 3.520 -0.430 1894 3 8.620 1.764 0 0 8.620 1.764 9.346 1.959 1894 4 10.537 -1.089 0 0 10.537 -1.089 11.175 -0.982 1894 5 18.423 1.898 0 0 18.423 1.898 17.983 0.926 1894 6 22.704 1.564 0 0 22.704 1.564 21.890 0.219 1894 7 24.857 1.008 0 0 24.857 1.008 24.791 0.411 1894 8 21.954 -1.777 0 0 21.954 -1.777 22.674 -1.589 1894 9 22.069 1.180 0 0 22.069 1.180 22.847 1.426 1894 10 14.516 -0.614 0 0 14.516 -0.614 15.630 -0.032 1894 11 6.226 -3.822 0 0 6.226 -3.822 8.935 -1.645 1894 12 3.667 -1.407 0 0 3.667 -1.407 5.557 -0.048 1895 1 0.613 -2.377 0 0 0.613 -2.377 2.639 -0.882 1895 2 -2.756 -6.175 0 0 -2.756 -6.175 -2.400 -6.351 1895 3 6.158 -0.697 0 0 6.158 -0.697 5.927 -1.460 1895 4 11.044 -0.582 0 0 11.044 -0.582 11.823 -0.335 1895 5 16.070 -0.455 0 0 16.070 -0.455 15.852 -1.205 1895 6 23.563 2.424 0 0 23.563 2.424 22.692 1.021 1895 7 22.202 -1.647 0 0 22.202 -1.647 22.794 -1.585 1895 8 25.148 1.417 0 0 25.148 1.417 25.010 0.747 1895 9 22.318 1.429 0 0 22.318 1.429 23.257 1.836 1895 10 11.133 -3.998 0 0 11.133 -3.998 12.558 -3.103 1895 11 8.971 -1.077 0 0 8.971 -1.077 11.229 0.649 1895 12 4.504 -0.570 0 0 4.504 -0.570 6.301 0.696 1896 1 0.699 -2.291 0 0 0.699 -2.291 2.129 -1.393 1896 2 2.183 -1.237 0 0 2.183 -1.237 3.396 -0.555 1896 3 4.086 -2.770 0 0 4.086 -2.770 4.886 -2.501 1896 4 13.444 1.818 0 0 13.444 1.818 13.068 0.910 1896 5 19.695 3.170 0 0 19.695 3.170 19.118 2.061 1896 6 22.074 0.935 0 0 22.074 0.935 21.215 -0.456 1896 7 25.815 1.967 0 0 25.815 1.967 24.487 0.107 1896 8 24.426 0.695 0 0 24.426 0.695 24.118 -0.145 1896 9 19.547 -1.342 0 0 19.547 -1.342 20.466 -0.954 1896 10 12.579 -2.551 0 0 12.579 -2.551 13.416 -2.246 1896 11 11.148 1.100 0 0 11.148 1.100 12.838 2.258 1896 12 2.007 -3.067 0 0 2.007 -3.067 3.616 -1.989 1897 1 0.370 -2.620 0 0 0.370 -2.620 1.843 -1.678 1897 2 2.698 -0.721 0 0 2.698 -0.721 3.806 -0.145 1897 3 7.063 0.208 1 0 NaN NaN 8.330 0.943 1897 4 11.519 -0.108 0 0 11.519 -0.108 11.831 -0.327 1897 5 16.864 0.338 0 0 16.864 0.338 16.197 -0.860 1897 6 21.296 0.157 0 0 21.296 0.157 20.338 -1.333 1897 7 25.000 1.152 0 0 25.000 1.152 24.238 -0.141 1897 8 23.853 0.122 0 0 23.853 0.122 23.416 -0.847 1897 9 20.833 -0.056 0 0 20.833 -0.056 21.261 -0.160 1897 10 15.667 0.536 0 0 15.667 0.536 16.206 0.544 1897 11 9.563 -0.485 0 0 9.563 -0.485 11.108 0.528 1897 12 4.552 -0.522 0 0 4.552 -0.522 6.162 0.557 1898 1 2.816 -0.174 0 0 2.816 -0.174 4.951 1.430 1898 2 3.591 0.172 0 0 3.591 0.172 3.427 -0.524 1898 3 9.852 2.996 0 0 9.852 2.996 9.790 2.403 1898 4 10.134 -1.492 0 0 10.134 -1.492 10.365 -1.792 1898 5 16.738 0.213 0 0 16.738 0.213 16.316 -0.741 1898 6 21.023 -0.116 1 0 NaN NaN 21.323 -0.347 1898 7 24.426 0.578 0 0 24.426 0.578 24.677 0.298 1898 8 26.389 2.658 1 0 NaN NaN 25.250 0.987 1898 9 NaN NaN NaN NaN NaN NaN 22.474 1.053 1898 10 13.111 -2.019 1 0 NaN NaN 16.315 0.653 1898 11 7.341 -2.707 0 0 7.341 -2.707 9.569 -1.010 1898 12 2.758 -2.316 0 0 2.758 -2.316 5.095 -0.510 1899 1 2.579 -0.411 0 0 2.579 -0.411 3.553 0.032 1899 2 0.139 -3.280 0 0 0.139 -3.280 -0.477 -4.428 1899 3 6.264 -0.591 0 0 6.264 -0.591 6.882 -0.505 1899 4 11.791 0.165 0 0 11.791 0.165 11.450 -0.707 1899 5 17.370 0.845 0 0 17.370 0.845 16.481 -0.576 1899 6 22.808 1.669 0 0 22.808 1.669 22.767 1.096 1899 7 NaN NaN NaN NaN NaN NaN 24.112 -0.268 1899 8 23.164 -0.567 1 0 NaN NaN 23.892 -0.371 1899 9 19.547 -1.342 0 0 19.547 -1.342 20.606 -0.815 1899 10 14.980 -0.150 0 0 14.980 -0.150 16.343 0.681 1899 11 6.777 -3.271 1 0 NaN NaN 10.504 -0.076 1899 12 7.917 2.843 0 0 7.917 2.843 5.226 -0.379 1900 1 NaN NaN NaN NaN NaN NaN 3.815 0.294 1900 2 NaN NaN NaN NaN NaN NaN 2.623 -1.328 1900 3 NaN NaN NaN NaN NaN NaN 5.254 -2.133 1900 4 NaN NaN NaN NaN NaN NaN 11.686 -0.471 1900 5 NaN NaN NaN NaN NaN NaN 17.100 0.044 1900 6 NaN NaN NaN NaN NaN NaN 21.989 0.319 1900 7 NaN NaN NaN NaN NaN NaN 25.426 1.047 1900 8 NaN NaN NaN NaN NaN NaN 26.168 1.906 1900 9 NaN NaN NaN NaN NaN NaN 23.661 2.240 1900 10 NaN NaN NaN NaN NaN NaN 17.962 2.300 1900 11 NaN NaN NaN NaN NaN NaN 12.511 1.931 1900 12 NaN NaN NaN NaN NaN NaN 4.727 -0.878