“…The strength of the wind is strongest in April and weakest in November, and those 2 months have the highest clear days. While the moist south-westerly wind dominates during the rainy season, the dry northeasterly wind controls the dry season, and the beginning of the dominance of both winds in April and November corresponds with low atmospheric cloud cover [83,84,87].…”
Section: Discussionmentioning
confidence: 99%
“…Atmospheric radiation in the wavelength region of 4-100 μm that originates from the sun and often interacts with atmospheric constituents while travelling to the earth's surface is known as downward longwave radiation (DLR) [50,83,123]. DLR is part of the energy budget balance of the earth's surface, and it is useful for evapotranspiration, plant water demand, greenhouse effect, global warming detection, solar thermal and photovoltaic applications, meteorology, climate model, ecology, hydrology, etc.…”
Section: Introductionmentioning
confidence: 99%
“…Atmospheric constituents that interact with DLR include O 2 , CO 2 , O 3 , H 2 O, CO, aerosols, etc. DLR also influences geographic parameters like the land cover, latitude, elevation and longitude [23,27,30,83,109,123].…”
Background: Though downward longwave radiation (DLR) models curb the paucity of data, they are mostly location dependent. Therefore, there is a need to evaluate their relevance given the increasing use of machine learning techniques. In this study, cloudless DLR estimates from regression models and soft computing models of neural networks (NN), support vector regression (SVR) and adaptive neuro-fuzzy inference system (ANFIS) were compared.
“…The strength of the wind is strongest in April and weakest in November, and those 2 months have the highest clear days. While the moist south-westerly wind dominates during the rainy season, the dry northeasterly wind controls the dry season, and the beginning of the dominance of both winds in April and November corresponds with low atmospheric cloud cover [83,84,87].…”
Section: Discussionmentioning
confidence: 99%
“…Atmospheric radiation in the wavelength region of 4-100 μm that originates from the sun and often interacts with atmospheric constituents while travelling to the earth's surface is known as downward longwave radiation (DLR) [50,83,123]. DLR is part of the energy budget balance of the earth's surface, and it is useful for evapotranspiration, plant water demand, greenhouse effect, global warming detection, solar thermal and photovoltaic applications, meteorology, climate model, ecology, hydrology, etc.…”
Section: Introductionmentioning
confidence: 99%
“…Atmospheric constituents that interact with DLR include O 2 , CO 2 , O 3 , H 2 O, CO, aerosols, etc. DLR also influences geographic parameters like the land cover, latitude, elevation and longitude [23,27,30,83,109,123].…”
Background: Though downward longwave radiation (DLR) models curb the paucity of data, they are mostly location dependent. Therefore, there is a need to evaluate their relevance given the increasing use of machine learning techniques. In this study, cloudless DLR estimates from regression models and soft computing models of neural networks (NN), support vector regression (SVR) and adaptive neuro-fuzzy inference system (ANFIS) were compared.
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