% This file contains a station summary listing for a temperature % station in the Berkeley Earth database. This station is identified as: % % Berkeley ID#: 28585 % Primary Name: NOGAL NEAR % Record Type: TAVG % Country: United States % State: NM % Latitude: 33.48330 +/- 0.00005 % Longitude: -105.73330 +/- 0.00005 % Elevation (m): 2499.36 +/- 0.15 % # of Months: 75 % % Alternate Names: Missing Station ID - 296140 % % IDs: coop - 296140 % ghcnd - USC00296140 % ncdc - 30002516 % % Sources: US Cooperative Summary of the Day % Global Historical Climatology Network - Daily % Multi-network Metadata System % % Site Hash: a6b4caeadbfe62cc4736a7b1d7b61a12 % Raw Data Hash: d3ff5cd6494ca2f638b60673b5e0a9c5 % Adj Data Hash: c7b70ed9e66efa3d8e87ee2927c9521c % % 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 1918 4 NaN NaN NaN NaN NaN NaN 13.117 -0.784 1918 5 NaN NaN NaN NaN NaN NaN 17.111 -1.607 1918 6 NaN NaN NaN NaN NaN NaN 24.660 0.763 1918 7 NaN NaN NaN NaN NaN NaN 24.791 -0.465 1918 8 NaN NaN NaN NaN NaN NaN 23.123 -0.797 1918 9 NaN NaN NaN NaN NaN NaN 20.661 -0.065 1918 10 NaN NaN NaN NaN NaN NaN 15.109 0.288 1918 11 NaN NaN NaN NaN NaN NaN 6.205 -1.997 1918 12 NaN NaN NaN NaN NaN NaN 1.842 -2.274 1919 1 NaN NaN NaN NaN NaN NaN 1.389 -2.599 1919 2 NaN NaN NaN NaN NaN NaN 3.871 -2.210 1919 3 NaN NaN NaN NaN NaN NaN 8.223 -1.242 1919 4 12.224 4.198 1 0 NaN NaN 14.140 0.239 1919 5 13.327 0.486 0 0 12.567 -0.275 18.014 -0.704 1919 6 14.993 -3.028 0 0 14.233 -3.788 21.942 -1.955 1919 7 19.427 0.047 0 0 18.667 -0.713 23.443 -1.813 1919 8 19.394 1.349 0 0 18.633 0.589 23.862 -0.059 1919 9 15.818 0.969 0 0 15.058 0.208 20.164 -0.562 1919 10 10.927 1.982 0 0 10.167 1.221 14.594 -0.228 1919 11 5.813 3.488 0 0 5.053 2.728 8.216 0.015 1919 12 4.744 6.504 0 0 3.983 5.743 5.889 1.773 1920 1 2.118 4.006 0 0 1.357 3.246 4.898 0.910 1920 2 4.278 4.074 1 0 NaN NaN 7.978 1.898 1920 3 NaN NaN NaN NaN NaN NaN 8.333 -1.132 1920 4 5.370 -2.655 0 0 4.609 -3.416 11.762 -2.139 1920 5 11.219 -1.623 0 0 10.459 -2.383 18.352 -0.366 1920 6 14.758 -3.263 0 0 13.998 -4.023 22.286 -1.611 1920 7 17.825 -1.555 0 0 17.064 -2.316 24.452 -0.804 1920 8 15.789 -2.256 0 0 15.028 -3.016 22.289 -1.631 1920 9 14.222 -0.627 0 0 13.461 -1.388 20.520 -0.206 1920 10 11.170 2.225 1 0 NaN NaN 13.860 -0.962 1920 11 NaN NaN NaN NaN NaN NaN 7.799 -0.403 1920 12 0.065 1.825 0 0 -0.696 1.064 3.201 -0.915 1921 1 2.990 4.879 0 0 2.230 4.118 5.744 1.757 1921 2 2.655 2.451 0 0 1.895 1.691 6.242 0.161 1921 3 7.226 3.637 0 0 6.465 2.877 11.364 1.899 1921 4 6.687 -1.338 0 0 5.926 -2.099 12.555 -1.347 1921 5 12.242 -0.600 0 0 11.481 -1.361 18.206 -0.513 1921 6 15.873 -2.148 0 0 15.113 -2.908 23.099 -0.798 1921 7 17.276 -2.104 0 0 16.515 -2.865 23.827 -1.429 1921 8 16.773 -1.272 0 0 16.012 -2.032 23.348 -0.572 1921 9 15.705 0.856 0 0 14.944 0.095 21.882 1.156 1921 10 10.594 1.649 0 0 9.834 0.888 15.611 0.789 1921 11 5.927 3.602 0 0 5.166 2.841 9.264 1.063 1921 12 3.453 5.213 0 0 2.693 4.453 6.730 2.614 1922 1 -0.437 1.451 0 0 -1.198 0.691 3.017 -0.970 1922 2 2.479 2.274 0 0 1.718 1.514 6.154 0.074 1922 3 3.151 -0.438 0 0 2.390 -1.198 8.287 -1.178 1922 4 6.942 -1.083 0 0 6.181 -1.844 12.687 -1.214 1922 5 12.185 -0.656 0 0 11.425 -1.417 18.610 -0.109 1922 6 17.268 -0.753 0 0 16.508 -1.513 24.345 0.448 1922 7 18.150 -1.230 0 0 17.389 -1.991 25.342 0.086 1922 8 17.445 -0.599 0 4 18.185 0.140 24.817 0.896 1922 9 14.655 -0.194 0 0 15.394 0.545 21.416 0.690 1922 10 8.475 -0.470 0 0 9.214 0.269 14.776 -0.046 1922 11 2.447 0.121 0 0 3.186 0.861 7.114 -1.088 1922 12 1.342 3.102 0 0 2.081 3.842 6.411 2.295 1923 1 2.982 4.871 0 0 3.722 5.610 6.492 2.504 1923 2 -0.288 -0.492 0 0 0.452 0.248 5.214 -0.866 1923 3 1.608 -1.981 0 0 2.348 -1.241 7.435 -2.030 1923 4 6.656 -1.369 0 0 7.396 -0.629 13.732 -0.169 1923 5 12.553 -0.289 0 0 13.293 0.451 18.559 -0.159 1923 6 15.993 -2.028 0 0 16.733 -1.288 24.006 0.108 1923 7 16.803 -2.577 0 0 17.543 -1.837 24.906 -0.350 1923 8 15.471 -2.573 0 0 16.210 -1.834 22.823 -1.098 1923 9 11.923 -2.926 0 0 12.663 -2.187 19.654 -1.071 1923 10 5.634 -3.312 0 0 6.373 -2.572 13.634 -1.187 1923 11 1.757 -0.568 0 0 2.496 0.171 7.663 -0.539 1923 12 -2.138 -0.378 0 0 -1.399 0.362 3.147 -0.969 1924 1 -2.633 -0.744 0 0 -1.893 -0.005 2.786 -1.202 1924 2 0.552 0.348 1 0 NaN NaN 6.080 -0.000 1924 3 0.900 -2.689 0 0 1.639 -1.949 7.208 -2.257 1924 4 6.202 -1.823 0 0 6.941 -1.084 12.826 -1.075 1924 5 12.234 -0.608 0 0 12.973 0.131 18.179 -0.539 1924 6 17.433 -0.588 0 0 18.173 0.152 25.878 1.980 1924 7 16.466 -2.914 0 0 17.206 -2.174 24.683 -0.573 1924 8 16.516 -1.528 0 0 17.256 -0.789 24.947 1.027 1924 9 12.428 -2.421 0 0 13.168 -1.682 20.842 0.117 1924 10 8.163 -0.783 0 0 8.902 -0.043 15.499 0.677 1924 11 4.520 2.195 0 0 5.259 2.934 10.302 2.101 1924 12 -2.234 -0.474 0 0 -1.494 0.266 3.175 -0.941 1925 1 -2.499 -0.610 0 0 -1.759 0.129 2.417 -1.570 1925 2 2.270 2.066 0 0 3.009 2.805 7.849 1.768 1925 3 5.434 1.845 0 0 6.173 2.585 11.377 1.912 1925 4 9.028 1.002 0 0 9.767 1.742 15.827 1.926 1925 5 12.731 -0.111 0 0 13.470 0.628 19.242 0.524 1925 6 15.312 -2.709 0 0 16.051 -1.970 23.612 -0.285 1925 7 16.192 -3.188 0 0 16.931 -2.449 25.012 -0.244 1925 8 14.198 -3.846 0 0 14.938 -3.107 22.479 -1.442 1925 9 NaN NaN NaN NaN NaN NaN 20.936 0.211 1925 10 NaN NaN NaN NaN NaN NaN 14.721 -0.100 1925 11 NaN NaN NaN NaN NaN NaN 7.305 -0.897 1925 12 NaN NaN NaN NaN NaN NaN 2.516 -1.600 1926 1 NaN NaN NaN NaN NaN NaN 1.275 -2.713 1926 2 NaN NaN NaN NaN NaN NaN 7.119 1.038 1926 3 NaN NaN NaN NaN NaN NaN 8.216 -1.249 1926 4 NaN NaN NaN NaN NaN NaN 12.598 -1.304 1926 5 NaN NaN NaN NaN NaN NaN 17.009 -1.709 1926 6 NaN NaN NaN NaN NaN NaN 23.663 -0.234 1926 7 NaN NaN NaN NaN NaN NaN 23.875 -1.381 1926 8 NaN NaN NaN NaN NaN NaN 23.482 -0.439