@Article{AimiZBSHRRDMVBHR:2021:EvAtDo,
               author = "Aimi, Daniele and Zimmer, Tamires and Buligon, Lidiane and Souza, 
                         Vanessa de Arruda and Hernandez, Roilan and Romio, Leugim Corteze 
                         and Rubert, Gisele Cristina Dotto and Diaz, Marcelo Bortoluzzi and 
                         Maldaner, Silvana and Veeck, Gustavo Pujol and Bremm, Tiago and 
                         Herdies, Dirceu Luis and Roberti, Debora Regina",
          affiliation = "{Universidade Federal de Santa Maria (UFSM)} and {Universidade 
                         Federal de Santa Maria (UFSM)} and {Universidade Federal de Santa 
                         Maria (UFSM)} and {Universidade Federal de Santa Maria (UFSM)} and 
                         {Universidade Federal de Santa Maria (UFSM)} and {Universidade 
                         Federal do Pampa (UNIPAMPA)} and {Universidade Federal de Santa 
                         Maria (UFSM)} and {Universidade Federal de Santa Maria (UFSM)} and 
                         {Universidade Federal de Santa Maria (UFSM)} and {Universidade 
                         Federal de Santa Maria (UFSM)} and {Universidade Federal de Santa 
                         Maria (UFSM)} and {Instituto Nacional de Pesquisas Espaciais 
                         (INPE)} and {Universidade Federal de Santa Maria (UFSM)}",
                title = "Evaluation of atmospheric downward longwave radiation in the 
                         brazilian pampa region",
              journal = "Atmosphere",
                 year = "2021",
               volume = "12",
               number = "1",
                pages = "1--17",
                month = "Jan.",
             keywords = "atmospheric downward longwave radiation, Pampa biome, statistical 
                         analyses, modeling.",
             abstract = "Atmospheric downward longwave radiation flux (L\↓) is a 
                         variable that directly influences the surface net radiation and 
                         consequently, weather and climatic conditions. Measurements of 
                         L\↓ are scarce, and the use of classical models depending 
                         on some atmospheric variables may be an alternative. In this 
                         paper, we analyzed L\↓ measured over the Brazilian Pampa 
                         biome. This region is located in a humid subtropical climate zone 
                         and characterized by well defined seasons and well distributed 
                         precipitation. Furthermore, we evaluated the performance of the 
                         eleven classical L\↓ models for clear sky with one-year 
                         experimental data collected in the Santa Maria experimental site 
                         (SMA) over native vegetation and high relative humidity throughout 
                         the year. Most of the L\↓ estimations, using the original 
                         coefficients, underestimated the experimental data. We performed 
                         the local calibration of the L\↓ equations coefficients 
                         over an annual period and separated them into different sky cover 
                         classifications: clear sky, partly cloudy sky, and cloudy sky. The 
                         calibrations decreased the errors, especially in cloudy sky 
                         classification. We also proposed the joint calibration between the 
                         clear sky emissivity equations and cloud sky correction function 
                         to reduce errors and evaluate different sky classifications. The 
                         results found after these calibrations presented better 
                         statistical indexes. Additionally, we presented a new empirical 
                         model to estimate L\↓ based on multiple regression analysis 
                         using water vapor pressure and air temperature. The new equation 
                         well represents partial and cloudy sky, even without including the 
                         cloud cover parameterization, and was validated with the following 
                         five years in SMA and two years in the Cachoeira do Sul 
                         experimental site (CAS). The new equation proposed herein presents 
                         a root mean square error ranging from 13 to 21 Wm\−2 and 
                         correlation coefficient from 0.68 to 0.83 for different sky cover 
                         classifications. Therefore, we recommend using the novel equation 
                         to calculate L\↓ over the Pampa biome under these specific 
                         climatic conditions.",
                  doi = "10.3390/atmos12010028",
                  url = "http://dx.doi.org/10.3390/atmos12010028",
                 issn = "2073-4433",
             language = "en",
           targetfile = "aimi_evaluation.pdf",
        urlaccessdate = "20 maio 2024"
}