% This file contains a station summary listing for a temperature % station in the Berkeley Earth database. This station is identified as: % % Berkeley ID#: 43104 % Primary Name: GEESE ISLANDS % Record Type: TAVG % Country: United States % State: AK % Latitude: 56.71670 +/- 0.00005 % Longitude: -153.91670 +/- 0.00005 % Elevation (m): 4.57 +/- 0.15 % # of Months: 15 % % Alternate Names: Missing Station ID - 503252 % % IDs: coop - 503252 % ghcnd - USC00503252 % ncdc - 30015261 % % Sources: US Cooperative Summary of the Day % Global Historical Climatology Network - Daily % Multi-network Metadata System % % Site Hash: 58070ef120038b3d10308e0823ddf07d % Raw Data Hash: 21b592a8935a0c82d60d46c15897d22b % Adj Data Hash: f99886db0bbc97d4205242f541f4573b % % 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 1924 6 NaN NaN NaN NaN NaN NaN 9.936 1.920 1924 7 NaN NaN NaN NaN NaN NaN 10.549 -0.363 1924 8 NaN NaN NaN NaN NaN NaN 12.006 0.285 1924 9 NaN NaN NaN NaN NaN NaN 9.595 0.066 1924 10 NaN NaN NaN NaN NaN NaN 3.609 -0.960 1924 11 NaN NaN NaN NaN NaN NaN 5.058 3.269 1924 12 NaN NaN NaN NaN NaN NaN 0.202 1.676 1925 1 NaN NaN NaN NaN NaN NaN -5.836 -3.905 1925 2 NaN NaN NaN NaN NaN NaN -3.175 -1.013 1925 3 NaN NaN NaN NaN NaN NaN -0.437 1.396 1925 4 NaN NaN NaN NaN NaN NaN 0.726 -0.213 1925 5 NaN NaN NaN NaN NaN NaN 4.063 -0.555 1925 6 7.267 -0.987 1 0 NaN NaN 7.230 -0.787 1925 7 10.932 -0.217 1 0 NaN NaN 10.755 -0.157 1925 8 11.937 -0.022 0 0 11.937 -0.022 12.360 0.639 1925 9 9.965 0.199 0 0 9.965 0.199 11.114 1.585 1925 10 8.449 3.643 0 0 8.449 3.643 8.309 3.740 1925 11 3.161 1.135 0 0 3.161 1.135 3.175 1.386 1925 12 -0.994 0.243 0 0 -0.994 0.243 -2.628 -1.154 1926 1 2.098 3.792 0 0 2.098 3.792 2.199 4.131 1926 2 -0.320 1.605 1 0 NaN NaN -1.593 0.569 1926 3 2.708 4.303 0 0 2.708 4.303 1.616 3.448 1926 4 4.600 3.423 0 0 4.600 3.423 3.880 2.941 1926 5 6.302 1.446 1 0 NaN NaN 5.654 1.036 1926 6 NaN NaN NaN NaN NaN NaN 11.117 3.101 1926 7 NaN NaN NaN NaN NaN NaN 12.415 1.503 1926 8 NaN NaN NaN NaN NaN NaN 12.779 1.057 1926 9 NaN NaN NaN NaN NaN NaN 12.570 3.042 1926 10 NaN NaN NaN NaN NaN NaN 6.643 2.074 1926 11 NaN NaN NaN NaN NaN NaN 5.910 4.122 1926 12 NaN NaN NaN NaN NaN NaN -0.758 0.716 1927 1 NaN NaN NaN NaN NaN NaN 0.751 2.683 1927 2 NaN NaN NaN NaN NaN NaN -0.727 1.435 1927 3 NaN NaN NaN NaN NaN NaN -4.665 -2.833 1927 4 NaN NaN NaN NaN NaN NaN -0.320 -1.259 1927 5 NaN NaN NaN NaN NaN NaN 4.922 0.304 1927 6 NaN NaN NaN NaN NaN NaN 7.470 -0.547 1927 7 NaN NaN NaN NaN NaN NaN 10.316 -0.596 1927 8 NaN NaN NaN NaN NaN NaN 10.956 -0.766 1927 9 NaN NaN NaN NaN NaN NaN 9.037 -0.492 1927 10 NaN NaN NaN NaN NaN NaN 3.333 -1.236 1927 11 0.171 -1.855 1 0 NaN NaN -0.010 -1.798 1927 12 1.283 2.520 1 0 NaN NaN 0.202 1.676 1928 1 0.994 2.688 1 0 NaN NaN 0.621 2.553 1928 2 NaN NaN NaN NaN NaN NaN 1.109 3.271 1928 3 NaN NaN NaN NaN NaN NaN -4.015 -2.183 1928 4 NaN NaN NaN NaN NaN NaN 1.024 0.085 1928 5 NaN NaN NaN NaN NaN NaN 4.529 -0.089 1928 6 NaN NaN NaN NaN NaN NaN 8.354 0.338 1928 7 NaN NaN NaN NaN NaN NaN 10.063 -0.849 1928 8 NaN NaN NaN NaN NaN NaN 10.765 -0.957 1928 9 NaN NaN NaN NaN NaN NaN 8.778 -0.751 1928 10 NaN NaN NaN NaN NaN NaN 5.390 0.821 1928 11 NaN NaN NaN NaN NaN NaN 3.128 1.340 1928 12 NaN NaN NaN NaN NaN NaN 0.517 1.992 1929 1 NaN NaN NaN NaN NaN NaN 2.943 4.874