@Article{CostaGPRSGSH:2021:GaFiQu,
               author = "Costa, Rafaela Lisboa and Gomes, Heliof{\'a}bio Barros and Pinto, 
                         David Duarte Cavalcante and Rocha J{\'u}nior, Rodrigo Lins da and 
                         Silva, Fabr{\'{\i}}cio Daniel dos Santos and Gomes, Helber 
                         Barros and Silva, Maria Cristina Lemos da and Herdies, Dirceu 
                         Lu{\'{\i}}s",
          affiliation = "{Universidade Federal de Alagoas (UFAL)} and {Universidade Federal 
                         de Alagoas (UFAL)} and {Universidade Federal de Alagoas (UFAL)} 
                         and {Universidade Federal de Alagoas (UFAL)} and {Universidade 
                         Federal de Alagoas (UFAL)} and {Universidade Federal de Alagoas 
                         (UFAL)} and {Universidade Federal de Alagoas (UFAL)} and 
                         {Instituto Nacional de Pesquisas Espaciais (INPE)}",
                title = "Gap filling and quality control applied to meteorological 
                         variables measured in the northeast region of Brazil",
              journal = "Atmosphere",
                 year = "2021",
               volume = "12",
               number = "10",
                pages = "e1278",
                month = "Oct.",
             keywords = "Climate analysis, Data quality control, Missing values, time 
                         series, Verification.",
             abstract = "In this work, we used the MICE (Multivariate Imputation by Chained 
                         Equations) technique to impute missing daily data from six 
                         meteorological variables (precipitation, temperature, relative 
                         humidity, atmospheric pressure, wind speed and insolation) from 96 
                         stations located in the northeast region of Brazil (NEB) for the 
                         period from 1961 to 2014. We then applied tests with a quality 
                         control system (QCS) developed for the detection, correction and 
                         possible replacement of suspicious data. Both the applied gap 
                         filling technique and the QCS showed that it was possible to solve 
                         two of the biggest problems found in time series of daily data 
                         measured in meteorological stations: the generation of plausible 
                         values for each variable of interest, in order to remedy the 
                         absence of observations, and how to detect and allow proper 
                         correction of suspicious values arising from observations.",
                  doi = "10.3390/atmos12101278",
                  url = "http://dx.doi.org/10.3390/atmos12101278",
                 issn = "2073-4433",
             language = "en",
           targetfile = "costa_gap.pdf",
        urlaccessdate = "31 maio 2024"
}