This study provides a unique procedure for validating and reconstructing temperature and precipitation data. Although developed from data in Middle Italy, the validation method is intended to be universal, subject to appropriate calibration according to the climate zones analysed. This research is an attempt to create shared applicative procedures that are most of the time only theorized or included in some software without a clear definition of the methods. The purpose is to detect most types of errors according to the procedures for data validation prescribed by the World Meteorological Organization, defining practical operations for each of the five types of data controls: gross error checking, internal consistency check, tolerance test, temporal consistency, and spatial consistency. Temperature and precipitation data over the period 1931–2014 were investigated. The outcomes of this process have led to the removal of 375 records (0.02%) of temperature data from 40 weather stations and 1286 records (1.67%) of precipitation data from 118 weather stations, and 171 data points reconstructed. In conclusion, this work contributes to the development of standardized methodologies to validate climate data and provides an innovative procedure to reconstruct missing data in the absence of reliable reference time series.
|Number of pages||16|
|Publication status||Published - 2018|
- quality control
- reconstruction of missing data