% This file contains a station summary listing for a temperature % station in the Berkeley Earth database. This station is identified as: % % Berkeley ID#: 36322 % Primary Name: PUNXSUTAWNEY % Record Type: TAVG % Country: United States % State: PA % Latitude: 40.95000 +/- 0.00500 % Longitude: -79.00000 +/- 0.00500 % Elevation (m): 396.20 +/- 0.05 % # of Months: 64 % % IDs: coop - 367217 % ghcnd - USC00367217 % ncdc - 20016943 % nws - PXSP1 % % Sources: US Cooperative Summary of the Day % Global Historical Climatology Network - Daily % US Cooperative Summary of the Month % Multi-network Metadata System % % Site Hash: 45e1c00310f9b438ab9f7ddd3b98d06e % Raw Data Hash: c8a532b99276c586ae2fa0c652a626d2 % Adj Data Hash: 1ac13538487c4ee507a472562762be2e % % 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 1912 6 NaN NaN NaN NaN NaN NaN 16.659 -1.747 1912 7 NaN NaN NaN NaN NaN NaN 19.993 -0.554 1912 8 NaN NaN NaN NaN NaN NaN 17.661 -2.168 1912 9 NaN NaN NaN NaN NaN NaN 17.481 1.347 1912 10 NaN NaN NaN NaN NaN NaN 10.321 0.573 1912 11 NaN NaN NaN NaN NaN NaN 5.016 1.071 1912 12 NaN NaN NaN NaN NaN NaN -0.600 1.557 1913 1 NaN NaN NaN NaN NaN NaN 0.314 4.975 1913 2 NaN NaN NaN NaN NaN NaN -5.045 -1.357 1913 3 NaN NaN NaN NaN NaN NaN 3.775 2.242 1913 4 NaN NaN NaN NaN NaN NaN 8.960 0.885 1913 5 NaN NaN NaN NaN NaN NaN 13.020 -0.755 1913 6 18.490 -0.522 1 0 NaN NaN 18.163 -0.242 1913 7 20.735 -0.417 0 0 19.952 -1.200 20.020 -0.526 1913 8 NaN NaN NaN NaN NaN NaN 19.618 -0.212 1913 9 15.324 -1.416 0 0 14.541 -2.199 15.316 -0.818 1913 10 11.065 0.711 0 0 10.282 -0.072 10.653 0.905 1913 11 5.593 1.041 1 0 NaN NaN 5.666 1.721 1913 12 -0.049 1.502 0 0 -0.832 0.719 -0.964 1.194 1914 1 -1.195 2.859 0 0 -1.978 2.076 -3.174 1.487 1914 2 -6.250 -3.169 0 0 -7.033 -3.952 -8.241 -4.553 1914 3 0.983 -1.157 0 0 0.200 -1.940 -0.533 -2.067 1914 4 NaN NaN NaN NaN NaN NaN 7.056 -1.019 1914 5 14.655 0.273 0 0 13.872 -0.510 14.426 0.651 1914 6 20.647 1.635 0 0 19.864 0.852 18.789 0.384 1914 7 21.248 0.096 1 0 NaN NaN 20.280 -0.266 1914 8 22.367 1.931 1 0 NaN NaN 19.970 0.140 1914 9 15.187 -1.554 0 0 14.404 -2.337 14.905 -1.229 1914 10 NaN NaN NaN NaN NaN NaN 11.888 2.140 1914 11 4.730 0.179 0 0 3.947 -0.604 3.697 -0.248 1914 12 -1.376 0.175 0 0 -2.159 -0.608 -4.626 -2.468 1915 1 -0.873 3.181 0 0 -1.656 2.398 -4.796 -0.136 1915 2 NaN NaN NaN NaN NaN NaN -1.800 1.888 1915 3 1.432 -0.707 0 0 0.649 -1.490 -1.618 -3.151 1915 4 13.250 4.569 0 0 12.467 3.786 10.678 2.603 1915 5 12.419 -1.962 0 0 11.636 -2.745 11.587 -2.189 1915 6 NaN NaN NaN NaN NaN NaN 16.901 -1.504 1915 7 NaN NaN NaN NaN NaN NaN 19.466 -1.081 1915 8 NaN NaN NaN NaN NaN NaN 18.214 -1.615 1915 9 NaN NaN NaN NaN NaN NaN 17.472 1.338 1915 10 NaN NaN NaN NaN NaN NaN 10.415 0.667 1915 11 NaN NaN NaN NaN NaN NaN 4.402 0.458 1915 12 NaN NaN NaN NaN NaN NaN -3.644 -1.487 1916 1 NaN NaN NaN NaN NaN NaN -0.929 3.731 1916 2 NaN NaN NaN NaN NaN NaN -6.165 -2.477 1916 3 NaN NaN NaN NaN NaN NaN -2.587 -4.120 1916 4 NaN NaN NaN NaN NaN NaN 7.338 -0.737 1916 5 15.988 1.607 1 0 NaN NaN 14.307 0.532 1916 6 16.693 -2.318 0 2 17.007 -2.005 15.780 -2.625 1916 7 22.765 1.612 0 0 23.078 1.925 21.931 1.385 1916 8 20.358 -0.078 0 0 20.671 0.236 20.435 0.606 1916 9 14.868 -1.872 1 0 NaN NaN 15.222 -0.912 1916 10 9.300 -1.054 0 0 9.613 -0.741 9.256 -0.492 1916 11 3.493 -1.058 0 0 3.807 -0.745 4.184 0.239 1916 12 -2.592 -1.041 0 0 -2.278 -0.727 -3.388 -1.230 1917 1 -3.587 0.467 0 0 -3.274 0.780 -4.705 -0.045 1917 2 -6.277 -3.195 0 0 -5.964 -2.882 -6.319 -2.631 1917 3 1.708 -0.432 0 0 2.021 -0.118 1.494 -0.039 1917 4 7.195 -1.486 0 0 7.508 -1.173 7.473 -0.602 1917 5 9.855 -4.527 0 0 10.168 -4.213 9.777 -3.998 1917 6 17.045 -1.967 0 0 17.358 -1.653 17.145 -1.260 1917 7 20.626 -0.527 0 0 20.939 -0.214 20.248 -0.298 1917 8 19.803 -0.632 0 0 20.116 -0.319 19.629 -0.200 1917 9 13.674 -3.066 0 0 13.987 -2.753 13.926 -2.208 1917 10 5.918 -4.437 0 0 6.231 -4.123 6.233 -3.515 1917 11 1.098 -3.453 0 0 1.412 -3.140 1.798 -2.147 1917 12 -8.608 -7.057 0 0 -8.295 -6.744 -8.076 -5.918 1918 1 -11.711 -7.657 0 0 -11.398 -7.344 -11.462 -6.802 1918 2 NaN NaN NaN NaN NaN NaN -4.205 -0.517 1918 3 3.576 1.436 0 0 3.889 1.749 3.781 2.248 1918 4 7.187 -1.495 0 0 7.500 -1.182 7.480 -0.595 1918 5 NaN NaN NaN NaN NaN NaN 16.784 3.009 1918 6 17.115 -1.897 0 0 17.428 -1.583 16.954 -1.451 1918 7 19.653 -1.500 0 0 19.966 -1.186 19.075 -1.471 1918 8 21.663 1.227 0 0 21.976 1.540 21.398 1.568 1918 9 12.380 -4.360 0 0 12.693 -4.047 13.042 -3.092 1918 10 11.491 1.137 0 0 11.804 1.450 11.170 1.422 1918 11 4.986 0.435 0 0 5.299 0.748 4.212 0.267 1918 12 1.914 3.465 0 0 2.228 3.779 0.559 2.717 1919 1 -0.928 3.126 0 0 -0.615 3.439 -2.186 2.474 1919 2 -1.208 1.874 1 0 NaN NaN -2.723 0.964 1919 3 3.765 1.625 0 0 4.078 1.938 3.059 1.526 1919 4 7.177 -1.505 0 0 7.490 -1.192 7.565 -0.510 1919 5 13.413 -0.969 0 0 13.726 -0.655 12.982 -0.793 1919 6 20.758 1.747 0 0 21.072 2.060 20.522 2.117 1919 7 21.606 0.454 0 0 21.920 0.767 20.841 0.294 1919 8 18.429 -2.007 0 0 18.742 -1.693 18.361 -1.468 1919 9 16.578 -0.162 0 0 16.892 0.151 16.315 0.182 1919 10 13.376 3.021 0 0 13.689 3.334 12.373 2.625 1919 11 3.557 -0.995 0 0 3.870 -0.682 3.910 -0.035 1919 12 -10.356 -8.804 1 0 NaN NaN -5.992 -3.834 1920 1 NaN NaN NaN NaN NaN NaN -8.602 -3.942 1920 2 -4.847 -1.765 0 0 -4.533 -1.452 -5.972 -2.285 1920 3 2.898 0.759 0 0 3.212 1.072 2.307 0.774 1920 4 NaN NaN NaN NaN NaN NaN 5.860 -2.215 1920 5 NaN NaN NaN NaN NaN NaN 11.887 -1.889 1920 6 NaN NaN NaN NaN NaN NaN 17.604 -0.801 1920 7 NaN NaN NaN NaN NaN NaN 18.679 -1.868 1920 8 NaN NaN NaN NaN NaN NaN 19.282 -0.548 1920 9 NaN NaN NaN NaN NaN NaN 16.377 0.243 1920 10 NaN NaN NaN NaN NaN NaN 12.261 2.513 1920 11 NaN NaN NaN NaN NaN NaN 3.432 -0.513 1920 12 NaN NaN NaN NaN NaN NaN -1.692 0.466 1921 1 NaN NaN NaN NaN NaN NaN -2.784 1.877 1921 2 NaN NaN NaN NaN NaN NaN -2.014 1.674 1921 3 NaN NaN NaN NaN NaN NaN 7.008 5.475