% This file contains a station summary listing for a temperature % station in the Berkeley Earth database. This station is identified as: % % Berkeley ID#: 14461 % Primary Name: BELM % Record Type: TAVG % Country: Germany % Latitude: 52.31833 +/- 0.00014 % Longitude: 8.17046 +/- 0.00014 % Elevation (m): 104.00 +/- 0.05 % # of Months: 84 % % IDs: gsod - 103120-99999 % usaf - 103120 % wmo - 10312 % % Sources: Global Summary of the Day % World Meteorological Organization Metadata % % Site Hash: 8c753b363462708ff0d6c44b2c3df364 % Raw Data Hash: 40d66035384f47e32b749d9abfda3cfa % Adj Data Hash: 4c3f7a70d16baf318b11da913eac183a % % 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 1935 1 NaN NaN NaN NaN NaN NaN 1.502 0.508 1935 2 NaN NaN NaN NaN NaN NaN 3.385 1.783 1935 3 NaN NaN NaN NaN NaN NaN 4.675 0.098 1935 4 NaN NaN NaN NaN NaN NaN 7.790 -0.278 1935 5 NaN NaN NaN NaN NaN NaN 10.884 -1.755 1935 6 NaN NaN NaN NaN NaN NaN 17.240 1.278 1935 7 NaN NaN NaN NaN NaN NaN 17.654 0.356 1935 8 NaN NaN NaN NaN NaN NaN 17.313 0.205 1935 9 NaN NaN NaN NaN NaN NaN 14.337 0.088 1935 10 NaN NaN NaN NaN NaN NaN 9.681 -0.280 1935 11 NaN NaN NaN NaN NaN NaN 6.900 1.517 1935 12 NaN NaN NaN NaN NaN NaN 2.299 -0.071 1936 1 5.091 3.688 1 0 NaN NaN 4.358 3.364 1936 2 1.366 -0.645 1 0 NaN NaN 1.468 -0.134 1936 3 7.583 2.597 1 0 NaN NaN 6.254 1.676 1936 4 6.308 -2.169 1 0 NaN NaN 5.826 -2.242 1936 5 14.170 1.122 1 0 NaN NaN 12.917 0.277 1936 6 18.103 1.733 1 0 NaN NaN 16.913 0.951 1936 7 17.878 0.172 1 0 NaN NaN 17.076 -0.222 1936 8 16.591 -0.926 1 0 NaN NaN 17.174 0.065 1936 9 14.875 0.217 1 0 NaN NaN 13.980 -0.270 1936 10 8.096 -2.274 1 0 NaN NaN 8.097 -1.864 1936 11 5.254 -0.537 1 0 NaN NaN 5.151 -0.233 1936 12 3.846 1.068 1 0 NaN NaN 3.355 0.986 1937 1 1.093 -0.310 1 0 NaN NaN 1.115 0.121 1937 2 4.944 2.934 0 0 4.944 2.934 3.607 2.004 1937 3 4.591 -0.395 1 0 NaN NaN 3.615 -0.962 1937 4 10.101 1.625 0 0 10.101 1.625 8.840 0.772 1937 5 15.269 2.221 1 0 NaN NaN 14.994 2.354 1937 6 18.041 1.671 0 0 18.041 1.671 16.769 0.807 1937 7 17.535 -0.171 1 0 NaN NaN 17.323 0.025 1937 8 19.425 1.909 0 0 19.425 1.909 18.148 1.040 1937 9 15.046 0.388 0 0 15.046 0.388 14.177 -0.072 1937 10 11.296 0.926 0 0 11.296 0.926 11.202 1.240 1937 11 4.607 -1.184 0 0 4.607 -1.184 4.480 -0.904 1937 12 1.048 -1.730 0 0 1.048 -1.730 1.049 -1.321 1938 1 3.808 2.406 0 0 3.808 2.406 3.235 2.241 1938 2 3.315 1.305 0 0 3.315 1.305 2.521 0.918 1938 3 8.604 3.618 0 0 8.604 3.618 8.401 3.823 1938 4 7.159 -1.317 0 0 7.159 -1.317 6.308 -1.760 1938 5 12.303 -0.745 0 0 12.303 -0.745 11.645 -0.994 1938 6 17.348 0.978 0 0 17.348 0.978 16.492 0.531 1938 7 17.875 0.168 0 0 17.875 0.168 17.061 -0.237 1938 8 19.631 2.114 0 0 19.631 2.114 18.937 1.829 1938 9 15.769 1.111 0 0 15.769 1.111 15.374 1.124 1938 10 9.989 -0.381 0 0 9.989 -0.381 9.784 -0.177 1938 11 9.026 3.234 0 0 9.026 3.234 8.676 3.293 1938 12 -0.398 -3.176 0 0 -0.398 -3.176 -0.192 -2.562 1939 1 4.638 3.236 0 0 4.638 3.236 3.924 2.930 1939 2 4.036 2.025 0 0 4.036 2.025 3.243 1.641 1939 3 4.170 -0.816 0 0 4.170 -0.816 3.955 -0.623 1939 4 9.820 1.344 0 0 9.820 1.344 8.932 0.864 1939 5 12.561 -0.487 0 0 12.561 -0.487 11.907 -0.733 1939 6 17.393 1.023 0 0 17.393 1.023 17.040 1.079 1939 7 17.557 -0.149 0 0 17.557 -0.149 17.437 0.139 1939 8 18.294 0.777 0 0 18.294 0.777 18.349 1.241 1939 9 14.756 0.098 0 0 14.756 0.098 14.737 0.487 1939 10 7.154 -3.216 0 0 7.154 -3.216 7.255 -2.707 1939 11 7.031 1.239 0 0 7.031 1.239 6.870 1.487 1939 12 0.527 -2.251 0 0 0.527 -2.251 0.432 -1.938 1940 1 -7.464 -8.867 0 0 -7.464 -8.867 -7.720 -8.714 1940 2 -1.851 -3.861 0 0 -1.851 -3.861 -2.957 -4.560 1940 3 4.892 -0.093 0 0 4.892 -0.093 4.503 -0.075 1940 4 9.235 0.759 0 0 9.235 0.759 8.448 0.380 1940 5 13.375 0.326 0 0 13.375 0.326 13.170 0.530 1940 6 16.785 0.415 0 0 16.785 0.415 16.771 0.809 1940 7 16.376 -1.330 0 0 16.376 -1.330 16.214 -1.084 1940 8 15.554 -1.963 0 0 15.554 -1.963 15.244 -1.864 1940 9 13.269 -1.389 0 0 13.269 -1.389 12.893 -1.356 1940 10 8.504 -1.866 0 0 8.504 -1.866 8.378 -1.584 1940 11 7.080 1.289 0 0 7.080 1.289 6.777 1.393 1940 12 -0.500 -3.278 0 0 -0.500 -3.278 -0.334 -2.704 1941 1 -3.557 -4.960 0 0 -3.557 -4.960 -3.925 -4.919 1941 2 1.147 -0.864 0 0 1.147 -0.864 0.487 -1.115 1941 3 4.842 -0.144 0 0 4.842 -0.144 4.395 -0.183 1941 4 6.976 -1.501 0 0 6.976 -1.501 6.078 -1.991 1941 5 10.315 -2.733 0 0 10.315 -2.733 9.858 -2.781 1941 6 17.580 1.210 0 0 17.580 1.210 17.034 1.073 1941 7 20.050 2.344 0 0 20.050 2.344 19.189 1.891 1941 8 15.462 -2.054 0 0 15.462 -2.054 15.346 -1.762 1941 9 13.941 -0.717 0 0 13.941 -0.717 13.460 -0.789 1941 10 9.527 -0.843 0 0 9.527 -0.843 9.338 -0.624 1941 11 3.800 -1.992 0 0 3.800 -1.992 3.581 -1.802 1941 12 3.538 0.760 0 0 3.538 0.760 3.767 1.398 1942 1 -6.043 -7.445 0 0 -6.043 -7.445 -6.341 -7.336 1942 2 -4.708 -6.719 0 0 -4.708 -6.719 -5.050 -6.652 1942 3 3.009 -1.977 0 0 3.009 -1.977 2.445 -2.133 1942 4 8.724 0.247 0 0 8.724 0.247 7.961 -0.108 1942 5 12.394 -0.654 0 0 12.394 -0.654 12.165 -0.475 1942 6 14.620 -1.750 0 0 14.620 -1.750 14.275 -1.687 1942 7 16.084 -1.622 0 0 16.084 -1.622 15.806 -1.492 1942 8 18.108 0.591 0 0 18.108 0.591 18.358 1.250 1942 9 15.063 0.405 0 0 15.063 0.405 15.200 0.950 1942 10 11.812 1.442 0 0 11.812 1.442 11.841 1.879 1942 11 5.070 -0.721 0 0 5.070 -0.721 5.051 -0.332 1942 12 4.444 1.666 0 0 4.444 1.666 4.261 1.891 1943 1 NaN NaN NaN NaN NaN NaN 1.514 0.520 1943 2 NaN NaN NaN NaN NaN NaN 4.080 2.477 1943 3 NaN NaN NaN NaN NaN NaN 6.720 2.142 1943 4 NaN NaN NaN NaN NaN NaN 9.844 1.776 1943 5 NaN NaN NaN NaN NaN NaN 13.186 0.546 1943 6 NaN NaN NaN NaN NaN NaN 14.971 -0.991 1943 7 NaN NaN NaN NaN NaN NaN 17.627 0.329 1943 8 NaN NaN NaN NaN NaN NaN 17.916 0.808 1943 9 NaN NaN NaN NaN NaN NaN 14.060 -0.189 1943 10 NaN NaN NaN NaN NaN NaN 10.883 0.922 1943 11 NaN NaN NaN NaN NaN NaN 4.337 -1.047 1943 12 NaN NaN NaN NaN NaN NaN 1.702 -0.667