Parameterized models for estimating atmospheric longwave radiation and surface net radiation in the Brazilian semi-arid region

Abstract

This study seeks to understand and estimate atmospheric longwave irradiance ($R_{ld}$) and surface net radiation ($R_n$) using parameterized models applied to semi-arid regions of northeastern Brazil. Studies on surface energy flows are of interest to areas such as environmental and agricultural sciences, and are of great importance in analyzing and managing water resources. Thus, this research could benefit the study region, which constantly experiences periods of water scarcity that affect agricultural activities and the lives of communities. An exploration of data gathered from micrometeorological stations spanning the period from 2014 to 2016 within various caatinga vegetation areas exhibiting distinct levels of preservation. This exploration involved comparative analyses between methods available in existing literature and those proposed by the authors. The biome under study is unique to Brazil and remains relatively underexplored in terms of comprehensive research and studies. In the $R_{ld}$ analysis, parameterizations for days with clear and cloudy skies were considered, and the proposed models presented results that surpassed the results of most of the tested models in the literature. Among the models examined, the Crawford and Duchon (1999) model displayed remarkable efficiency in estimating $R_{ld}$ within the study area. Furthermore, the models were fine-tuned to estimate the surface $R_n$ for the respective areas of each micrometeorological station. These calibrations factored in both dry and rainy seasons for the $R_n$ analyses. The calibration results were satisfactory, with r² values for the proposed models greater than 0.90 for $R_{ld}$ for clear sky conditions and 0.94 for all conditions, and a high agreement was shown with values greater than 0.96 according to the criteria of Willmott et al. (2012). The results for $R_n$ show the potential of the models to contribute, for example, to measuring water loss from a vegetated surface, an essential task in agricultural planning. Among the tested models, the one developed by Crawford and Duchon (1999) proved to be very efficient in estimating the $R_{ld}$ in the study area. The models were adjusted to estimate the surface $R_n$ for the areas of each of the micrometeorological stations, taking into account the dry and rainy seasons in the $R_n$ analyses, where the calibrations could present satisfactory results with r² always close to 1 and high concordance. Implementing models such as those analyzed and proposed tends to contribute to sustainable development and management of the environment and agricultural systems. However, it is important to consider the difficulties encountered in searching for data to calibrate the models, which are scarce in the region, indicating the need for policies that stimulate investment in research and monitoring of environmental variables in the region.