Extraction of the global absolute temperature for Northern Hemisphere using a set of 6190 meteorological stations from 1800 to 2013

• Introduce the concept of a valid station and use for computations.
• Define indices for data quality and seasonal bias and use for data evaluation.
• Compute averages for mean and five point summary plus standard deviations.
• Indicate a monotonically decreasing data quality after the year 1969.
• Observe an overestimation of temperature after including non-valid stations.

Starting from a set of 6190 meteorological stations we are choosing 6130 of them and only for Northern Hemisphere we are computing average values for absolute annual Mean, Minimum, Q1, Median, Q3, Maximum temperature plus their standard deviations for years 1800–2013, while we use 4887 stations and 389 467 rows of complete yearly data. The data quality and the seasonal bias indices are defined and used in order to evaluate our dataset. After the year 1969 the data quality is monotonically decreasing while the seasonal bias is positive in most of the cases. An Extreme Value Distribution estimation is performed for minimum and maximum values, giving some upper bounds for both of them and indicating a big magnitude for temperature changes. Finally suggestions for improving the quality of meteorological data are presented.

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