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Filling Gaps in Hourly Air Temperature Data Using Debiased ERA5 Data
Missing data in hourly and daily temperature data series is a common problem in long-term data series and many observational networks. Agricultural and environmental models and climate-related tools can be used only if weather data series are complete. To support user communities, a technique for gap filling is developed based on the debiasing of ERA5 reanalysis data, the fifth generation of the European Centre for Medium-Range Weather Forecasts (ECMWF) atmospheric reanalyses of the globaldoi:10.3390/atmos10010013 fatcat:6z4htnqolvhmthz6yc36km3lee