% This file contains a station summary listing for a temperature % station in the Berkeley Earth database. This station is identified as: % % Berkeley ID#: 5918 % Primary Name: MATTO GROSSO % Record Type: TAVG % Country: Brazil % Latitude: -15.00000 +/- 0.00500 % Longitude: -59.95000 +/- 0.00500 % Elevation (m): 256.00 +/- 0.50 % # of Months: 58 % % IDs: ca - 303000000014 % % Sources: Colonial Archive % % Site Hash: ad497ac644a3fe377e8bd24e52180a44 % Raw Data Hash: 3a59037c9dadd14fcde1bc4f9dbc17cd % Adj Data Hash: 3a59037c9dadd14fcde1bc4f9dbc17cd % % 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 1923 6 NaN NaN NaN NaN NaN NaN 22.443 -0.026 1923 7 NaN NaN NaN NaN NaN NaN 20.514 -1.602 1923 8 NaN NaN NaN NaN NaN NaN 23.556 -0.360 1923 9 NaN NaN NaN NaN NaN NaN 26.128 0.335 1923 10 NaN NaN NaN NaN NaN NaN 25.595 -0.677 1923 11 NaN NaN NaN NaN NaN NaN 25.532 -0.712 1923 12 NaN NaN NaN NaN NaN NaN 26.043 0.138 1924 1 NaN NaN NaN NaN NaN NaN 25.488 -0.156 1924 2 NaN NaN NaN NaN NaN NaN 25.509 -0.237 1924 3 NaN NaN NaN NaN NaN NaN 26.332 0.552 1924 4 NaN NaN NaN NaN NaN NaN 24.681 -0.171 1924 5 NaN NaN NaN NaN NaN NaN 22.830 -0.903 1924 6 24.100 1.134 0 0 24.100 1.134 23.479 1.010 1924 7 22.550 -0.063 0 0 22.550 -0.063 21.737 -0.379 1924 8 22.000 -2.413 0 0 22.000 -2.413 21.587 -2.330 1924 9 25.950 -0.341 0 0 25.950 -0.341 25.367 -0.427 1924 10 NaN NaN NaN NaN NaN NaN 25.246 -1.025 1924 11 27.500 0.758 0 0 27.500 0.758 26.815 0.571 1924 12 27.200 0.798 0 0 27.200 0.798 26.490 0.585 1925 1 26.400 0.259 0 0 26.400 0.259 25.629 -0.015 1925 2 NaN NaN NaN NaN NaN NaN 25.422 -0.324 1925 3 26.100 -0.177 0 0 26.100 -0.177 25.427 -0.352 1925 4 27.250 1.901 0 0 27.250 1.901 26.064 1.212 1925 5 24.200 -0.029 0 0 24.200 -0.029 23.461 -0.271 1925 6 21.700 -1.266 0 0 21.700 -1.266 21.344 -1.125 1925 7 21.500 -1.113 0 0 21.500 -1.113 20.925 -1.191 1925 8 NaN NaN NaN NaN NaN NaN 24.839 0.923 1925 9 25.800 -0.491 0 0 25.800 -0.491 25.548 -0.246 1925 10 25.650 -1.119 0 0 25.650 -1.119 25.244 -1.028 1925 11 NaN NaN NaN NaN NaN NaN 26.160 -0.085 1925 12 25.500 -0.902 0 0 25.500 -0.902 25.570 -0.335 1926 1 NaN NaN NaN NaN NaN NaN 25.621 -0.023 1926 2 26.900 0.657 0 0 26.900 0.657 26.505 0.759 1926 3 26.650 0.373 0 0 26.650 0.373 26.627 0.847 1926 4 25.000 -0.349 0 0 25.000 -0.349 24.634 -0.218 1926 5 23.450 -0.779 0 0 23.450 -0.779 22.829 -0.903 1926 6 24.650 1.684 0 0 24.650 1.684 24.057 1.588 1926 7 22.300 -0.313 0 0 22.300 -0.313 21.325 -0.790 1926 8 24.750 0.337 0 0 24.750 0.337 24.113 0.197 1926 9 28.150 1.859 0 0 28.150 1.859 27.129 1.335 1926 10 NaN NaN NaN NaN NaN NaN 26.858 0.586 1926 11 NaN NaN NaN NaN NaN NaN 26.840 0.595 1926 12 25.850 -0.552 0 0 25.850 -0.552 25.708 -0.197 1927 1 NaN NaN NaN NaN NaN NaN 25.349 -0.295 1927 2 NaN NaN NaN NaN NaN NaN 25.623 -0.123 1927 3 26.050 -0.227 0 0 26.050 -0.227 25.824 0.045 1927 4 25.550 0.201 0 0 25.550 0.201 24.749 -0.103 1927 5 NaN NaN NaN NaN NaN NaN 23.204 -0.528 1927 6 20.350 -2.616 0 0 20.350 -2.616 20.461 -2.009 1927 7 20.800 -1.813 0 0 20.800 -1.813 20.175 -1.940 1927 8 24.100 -0.313 0 0 24.100 -0.313 23.704 -0.212 1927 9 25.900 -0.391 0 0 25.900 -0.391 25.707 -0.087 1927 10 26.900 0.131 0 0 26.900 0.131 26.732 0.460 1927 11 NaN NaN NaN NaN NaN NaN 27.252 1.007 1927 12 26.250 -0.152 0 0 26.250 -0.152 25.942 0.037 1928 1 27.150 1.009 0 0 27.150 1.009 26.395 0.751 1928 2 26.150 -0.093 0 0 26.150 -0.093 25.947 0.201 1928 3 26.500 0.223 0 0 26.500 0.223 26.202 0.423 1928 4 NaN NaN NaN NaN NaN NaN 25.896 1.044 1928 5 25.000 0.771 0 0 25.000 0.771 24.101 0.368 1928 6 22.900 -0.066 0 0 22.900 -0.066 22.634 0.164 1928 7 22.200 -0.413 0 0 22.200 -0.413 21.284 -0.832 1928 8 22.850 -1.563 0 0 22.850 -1.563 22.173 -1.743 1928 9 25.750 -0.541 0 0 25.750 -0.541 25.255 -0.539 1928 10 NaN NaN NaN NaN NaN NaN 26.192 -0.080 1928 11 26.650 -0.092 0 0 26.650 -0.092 26.661 0.417 1928 12 25.750 -0.652 0 0 25.750 -0.652 25.555 -0.350 1929 1 26.500 0.359 0 0 26.500 0.359 25.851 0.207 1929 2 26.400 0.157 0 0 26.400 0.157 25.742 -0.004 1929 3 26.450 0.173 0 0 26.450 0.173 25.752 -0.027 1929 4 NaN NaN NaN NaN NaN NaN 24.731 -0.121 1929 5 22.150 -2.079 0 0 22.150 -2.079 21.688 -2.044 1929 6 22.700 -0.266 0 0 22.700 -0.266 22.174 -0.295 1929 7 23.450 0.837 0 0 23.450 0.837 22.333 0.217 1929 8 25.000 0.587 0 0 25.000 0.587 24.249 0.333 1929 9 26.200 -0.091 0 0 26.200 -0.091 26.040 0.246 1929 10 26.150 -0.619 0 0 26.150 -0.619 25.936 -0.336 1929 11 NaN NaN NaN NaN NaN NaN 26.324 0.080 1929 12 25.500 -0.902 0 0 25.500 -0.902 25.374 -0.530 1930 1 26.200 0.059 0 0 26.200 0.059 25.700 0.056 1930 2 26.200 -0.043 0 0 26.200 -0.043 25.644 -0.102 1930 3 26.350 0.073 0 0 26.350 0.073 26.194 0.414 1930 4 NaN NaN NaN NaN NaN NaN 25.439 0.587 1930 5 25.150 0.921 0 0 25.150 0.921 24.365 0.633 1930 6 24.950 1.984 0 0 24.950 1.984 24.318 1.849 1930 7 NaN NaN NaN NaN NaN NaN 21.720 -0.396 1930 8 NaN NaN NaN NaN NaN NaN 24.552 0.636 1930 9 26.000 -0.291 0 0 26.000 -0.291 25.936 0.143 1930 10 NaN NaN NaN NaN NaN NaN 26.228 -0.044 1930 11 NaN NaN NaN NaN NaN NaN 25.916 -0.329 1930 12 NaN NaN NaN NaN NaN NaN 26.331 0.426 1931 1 NaN NaN NaN NaN NaN NaN 26.305 0.661 1931 2 NaN NaN NaN NaN NaN NaN 26.313 0.568 1931 3 NaN NaN NaN NaN NaN NaN 25.666 -0.113 1931 4 NaN NaN NaN NaN NaN NaN 25.072 0.220 1931 5 NaN NaN NaN NaN NaN NaN 21.806 -1.926 1931 6 NaN NaN NaN NaN NaN NaN 20.846 -1.623 1931 7 NaN NaN NaN NaN NaN NaN 21.374 -0.742 1931 8 NaN NaN NaN NaN NaN NaN 23.705 -0.211 1931 9 NaN NaN NaN NaN NaN NaN 25.013 -0.780