% This file contains a station summary listing for a temperature % station in the Berkeley Earth database. This station is identified as: % % Berkeley ID#: 31530 % Primary Name: DUNLAP SHINGLE MILL % Record Type: TAVG % Country: United States % State: CA % Latitude: 36.73749 +/- 0.02084 % Longitude: -119.11667 +/- 0.00833 % Elevation (m): 600.90 +/- 9.05 % # of Months: 115 % % Alternate Names: DUNLAP % % IDs: coop - 42557 % coop - 42559 % ghcnd - USC00042559 % ncdc - 20002264 % ncdc - 20002273 % % Sources: US Cooperative Summary of the Day % Global Historical Climatology Network - Daily % US Cooperative Summary of the Month % Multi-network Metadata System % % Site Hash: 65aa43d8259dd2b68fd0cd793338f00b % Raw Data Hash: b4e869f095ba5050a383118a4ded6cee % Adj Data Hash: 8f5347ea8f9721f0372f0ed21cae28c7 % % 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 1936 7 NaN NaN NaN NaN NaN NaN 27.930 1.684 1936 8 NaN NaN NaN NaN NaN NaN 26.427 1.119 1936 9 NaN NaN NaN NaN NaN NaN 23.225 0.821 1936 10 NaN NaN NaN NaN NaN NaN 18.011 0.969 1936 11 NaN NaN NaN NaN NaN NaN 11.909 0.999 1936 12 NaN NaN NaN NaN NaN NaN 6.286 -0.550 1937 1 NaN NaN NaN NaN NaN NaN 2.494 -4.179 1937 2 NaN NaN NaN NaN NaN NaN 8.485 -0.588 1937 3 NaN NaN NaN NaN NaN NaN 10.284 -0.505 1937 4 NaN NaN NaN NaN NaN NaN 12.700 -0.913 1937 5 NaN NaN NaN NaN NaN NaN 19.071 1.031 1937 6 NaN NaN NaN NaN NaN NaN 21.936 -0.569 1937 7 24.444 -0.247 0 0 23.879 -0.813 27.209 0.963 1937 8 23.889 0.134 0 0 23.719 -0.036 26.028 0.719 1937 9 20.556 -0.295 0 0 20.739 -0.112 22.997 0.592 1937 10 15.667 0.179 0 0 16.305 0.818 18.372 1.331 1937 11 10.111 0.755 0 0 11.449 2.093 12.055 1.145 1937 12 7.444 2.163 0 0 9.377 4.095 8.700 1.864 1938 1 6.889 1.770 0 0 8.850 3.731 7.217 0.544 1938 2 7.000 -0.519 0 0 8.466 0.947 8.963 -0.111 1938 3 6.889 -2.346 0 0 7.693 -1.542 8.285 -2.504 1938 4 11.333 -0.727 0 0 11.472 -0.588 13.029 -0.585 1938 5 15.333 -1.153 0 0 14.871 -1.616 18.107 0.067 1938 6 20.556 -0.395 0 0 19.808 -1.143 23.070 0.565 1938 7 23.556 -1.136 0 0 22.990 -1.702 26.850 0.604 1938 8 22.889 -0.866 0 4 22.912 -0.843 25.158 -0.151 1938 9 21.444 0.594 0 0 21.420 0.569 23.642 1.237 1938 10 14.556 -0.932 0 0 14.469 -1.018 16.465 -0.576 1938 11 8.611 -0.745 0 0 8.430 -0.926 9.655 -1.255 1938 12 8.111 2.829 0 0 7.849 2.568 7.934 1.098 1939 1 6.889 1.770 0 0 6.623 1.504 7.027 0.354 1939 2 4.889 -2.630 0 0 4.690 -2.829 6.504 -2.570 1939 3 9.500 0.265 0 0 9.391 0.156 10.530 -0.260 1939 4 14.889 2.829 0 0 14.870 2.810 16.267 2.653 1939 5 16.500 0.014 0 0 16.563 0.076 18.768 0.728 1939 6 20.222 -0.729 0 0 20.323 -0.627 22.501 -0.004 1939 7 24.500 -0.192 0 0 24.577 -0.115 26.533 0.287 1939 8 25.167 1.412 0 0 25.190 1.435 26.227 0.918 1939 9 21.167 0.316 0 0 21.142 0.291 23.173 0.768 1939 10 14.667 -0.821 0 0 14.580 -0.907 17.056 0.015 1939 11 11.389 2.033 0 0 11.208 1.851 12.722 1.812 1939 12 8.778 3.496 0 0 8.516 3.234 9.334 2.498 1940 1 8.500 3.381 0 0 8.234 3.115 8.527 1.854 1940 2 8.944 1.425 0 0 8.746 1.227 10.106 1.033 1940 3 11.500 2.265 0 0 11.391 2.156 12.050 1.261 1940 4 13.222 1.162 0 0 13.203 1.144 14.564 0.950 1940 5 18.333 1.847 0 0 18.396 1.909 20.307 2.266 1940 6 23.000 2.049 0 0 23.101 2.150 24.793 2.289 1940 7 23.222 -1.469 0 0 23.299 -1.393 25.700 -0.546 1940 8 23.889 0.134 0 0 23.912 0.157 25.453 0.144 1940 9 19.111 -1.740 0 0 19.086 -1.765 20.718 -1.687 1940 10 16.167 0.679 0 0 16.080 0.593 17.604 0.562 1940 11 9.444 0.088 0 0 9.263 -0.093 10.199 -0.711 1940 12 9.333 4.052 0 0 9.072 3.790 9.461 2.625 1941 1 8.111 2.992 0 0 7.846 2.726 8.748 2.075 1941 2 9.722 2.203 0 0 9.524 2.004 10.781 1.708 1941 3 10.611 1.376 0 0 10.502 1.267 11.458 0.669 1941 4 10.667 -1.393 0 0 10.648 -1.412 12.010 -1.604 1941 5 16.944 0.458 0 0 17.007 0.521 18.680 0.640 1941 6 18.833 -2.118 0 0 18.935 -2.016 20.597 -1.908 1941 7 24.222 -0.469 0 0 24.299 -0.393 26.655 0.410 1941 8 22.111 -1.644 0 0 22.134 -1.621 23.261 -2.048 1941 9 18.111 -2.740 0 0 18.086 -2.765 20.228 -2.177 1941 10 13.667 -1.821 0 0 13.580 -1.907 15.293 -1.749 1941 11 11.556 2.199 0 0 11.374 2.018 12.141 1.231 1941 12 7.444 2.163 0 0 7.183 1.901 7.630 0.794 1942 1 7.667 2.548 0 0 7.401 2.282 7.759 1.086 1942 2 6.778 -0.742 0 0 6.579 -0.940 7.743 -1.330 1942 3 9.444 0.209 0 0 9.336 0.100 10.026 -0.763 1942 4 12.000 -0.060 0 0 11.981 -0.079 12.813 -0.801 1942 5 14.167 -2.320 0 0 14.229 -2.257 16.301 -1.740 1942 6 19.667 -1.284 0 0 19.768 -1.183 21.670 -0.835 1942 7 NaN NaN NaN NaN NaN NaN 27.211 0.965 1942 8 NaN NaN NaN NaN NaN NaN 25.431 0.122 1942 9 20.000 -0.851 0 0 19.975 -0.876 21.665 -0.739 1942 10 NaN NaN NaN NaN NaN NaN 17.867 0.825 1942 11 10.389 1.033 0 0 10.208 0.851 10.999 0.089 1942 12 7.889 2.607 0 0 7.627 2.345 7.091 0.255 1943 1 6.778 1.659 0 0 6.512 1.393 7.162 0.489 1943 2 8.556 1.036 0 0 8.357 0.838 10.007 0.934 1943 3 10.722 1.487 0 0 10.613 1.378 11.339 0.550 1943 4 13.222 1.162 0 0 13.203 1.144 14.398 0.784 1943 5 16.444 -0.042 0 0 16.507 0.021 19.037 0.996 1943 6 17.333 -3.618 0 0 17.435 -3.516 19.660 -2.845 1943 7 23.278 -1.414 0 0 23.354 -1.337 25.875 -0.370 1943 8 21.444 -2.310 0 0 21.467 -2.288 23.568 -1.741 1943 9 21.556 0.705 0 0 21.531 0.680 23.777 1.372 1943 10 15.444 -0.043 0 0 15.358 -0.129 17.346 0.305 1943 11 10.611 1.255 0 0 10.430 1.074 11.602 0.692 1943 12 7.000 1.718 0 0 6.738 1.457 7.419 0.584 1944 1 6.778 1.659 0 0 6.512 1.393 6.967 0.294 1944 2 6.222 -1.297 0 0 6.024 -1.496 7.578 -1.495 1944 3 8.944 -0.291 0 0 8.836 -0.400 10.167 -0.622 1944 4 10.222 -1.838 0 0 10.203 -1.856 11.883 -1.731 1944 5 16.111 -0.375 0 0 16.174 -0.313 18.518 0.478 1944 6 17.056 -3.895 0 0 17.157 -3.794 19.645 -2.860 1944 7 22.333 -2.358 0 0 22.410 -2.282 25.207 -1.039 1944 8 22.556 -1.199 0 0 22.579 -1.176 24.576 -0.732 1944 9 21.667 0.816 0 0 21.642 0.791 23.270 0.865 1944 10 16.111 0.624 0 0 16.025 0.537 18.307 1.266 1944 11 9.111 -0.245 0 0 8.930 -0.426 9.622 -1.288 1944 12 8.111 2.829 0 0 7.849 2.568 7.698 0.863 1945 1 5.389 0.270 0 0 5.123 0.004 5.649 -1.024 1945 2 7.556 0.036 0 0 7.357 -0.162 9.173 0.100 1945 3 7.056 -2.180 0 0 6.947 -2.288 7.987 -2.803 1945 4 12.000 -0.060 0 0 11.981 -0.079 13.749 0.135 1945 5 14.889 -1.598 0 0 14.952 -1.535 17.081 -0.959 1945 6 20.000 -0.951 0 0 20.101 -0.850 22.144 -0.361 1945 7 25.222 0.531 0 0 25.299 0.607 27.909 1.663 1945 8 23.500 -0.255 0 0 23.523 -0.232 25.074 -0.235 1945 9 NaN NaN NaN NaN NaN NaN 23.591 1.187 1945 10 16.611 1.124 0 0 16.525 1.037 18.082 1.040 1945 11 NaN NaN NaN NaN NaN NaN 10.107 -0.803 1945 12 NaN NaN NaN NaN NaN NaN 7.227 0.392 1946 1 NaN NaN NaN NaN NaN NaN 5.963 -0.710 1946 2 NaN NaN NaN NaN NaN NaN 7.801 -1.272 1946 3 8.167 -1.068 0 0 8.058 -1.177 10.231 -0.558 1946 4 12.167 0.107 0 0 12.148 0.088 15.245 1.631 1946 5 14.833 -1.653 0 0 14.896 -1.591 18.180 0.140 1946 6 18.111 -2.840 0 0 18.212 -2.739 21.399 -1.105 1946 7 23.667 -1.025 0 0 23.743 -0.948 26.523 0.277 1946 8 23.333 -0.422 0 0 23.356 -0.399 25.739 0.431 1946 9 19.444 -1.406 0 0 19.420 -1.431 22.657 0.253 1946 10 12.222 -3.265 0 0 12.136 -3.351 14.868 -2.173 1946 11 6.944 -2.412 0 0 6.763 -2.593 8.658 -2.252 1946 12 6.778 1.496 0 0 6.516 1.234 6.544 -0.291 1947 1 4.000 -1.119 0 0 3.734 -1.385 4.476 -2.197 1947 2 10.000 2.481 0 0 9.801 2.282 10.033 0.960 1947 3 11.556 2.320 0 0 11.447 2.212 12.199 1.410 1947 4 NaN NaN NaN NaN NaN NaN 15.088 1.475 1947 5 NaN NaN NaN NaN NaN NaN 20.679 2.639 1947 6 NaN NaN NaN NaN NaN NaN 22.133 -0.372 1947 7 NaN NaN NaN NaN NaN NaN 24.607 -1.639 1947 8 NaN NaN NaN NaN NaN NaN 23.516 -1.793 1947 9 NaN NaN NaN NaN NaN NaN 23.822 1.417 1947 10 NaN NaN NaN NaN NaN NaN 17.066 0.025 1947 11 NaN NaN NaN NaN NaN NaN 8.456 -2.455 1947 12 NaN NaN NaN NaN NaN NaN 5.690 -1.145 1948 1 NaN NaN NaN NaN NaN NaN 8.982 2.309 1948 2 NaN NaN NaN NaN NaN NaN 7.690 -1.383 1948 3 NaN NaN NaN NaN NaN NaN 8.606 -2.183 1948 4 13.000 0.940 1 0 NaN NaN 12.850 -0.764 1948 5 15.167 -1.320 1 0 NaN NaN 16.151 -1.890 1948 6 20.778 -0.173 1 0 NaN NaN 21.573 -0.932 1948 7 23.556 -1.136 1 0 NaN NaN 25.194 -1.052 1948 8 24.288 0.533 1 0 NaN NaN 23.786 -1.522 1948 9 25.661 4.810 1 0 NaN NaN 22.153 -0.252 1948 10 NaN NaN NaN NaN NaN NaN 16.930 -0.111 1948 11 NaN NaN NaN NaN NaN NaN 9.717 -1.193 1948 12 NaN NaN NaN NaN NaN NaN 4.711 -2.125 1949 1 NaN NaN NaN NaN NaN NaN 2.114 -4.559 1949 2 NaN NaN NaN NaN NaN NaN 6.363 -2.710 1949 3 NaN NaN NaN NaN NaN NaN 9.263 -1.526 1949 4 NaN NaN NaN NaN NaN NaN 15.495 1.881 1949 5 NaN NaN NaN NaN NaN NaN 17.683 -0.357 1949 6 NaN NaN NaN NaN NaN NaN 23.156 0.651 1949 7 NaN NaN NaN NaN NaN NaN 26.093 -0.152 1949 8 NaN NaN NaN NaN NaN NaN 23.210 -2.099 1949 9 NaN NaN NaN NaN NaN NaN 23.148 0.743