José de Souza Nogueira

Carbon cycling in the Amazon fundamentally depends on the functioning of ecosystems and atmospheric dynamics, which are highly intricate. Few studies have hitherto investigated or measured the radiative effects of aerosols on the Amazon and Cerrado. This study examines the effects of atmospheric aerosols on solar radiation and their effects on net ecosystem exchange (NEE) in an area of semideciduous tropical forest in the north of Mato Grosso. Our results show that for a relative irradiance (f) 1.10–0.67, a decrease in incident solar radiation is associated with a reduction in the NEE. However, an average increase of 25 %–110 % in NEE was observed when pollution levels and aerosol optical depth (AOD) were above ≈ 1.25 and f < 0.5. The increase NEE was attributed to the increase of up to 60 % in the diffuse fraction of photosynthetically active radiation. The change in AOD and f was mainly attributable to biomass burning organic aerosols from fires. Important influences on vapor pressure deficit (VPD) as well as air temperature (T_air) and canopy (LC_T), induced by the interaction between solar radiation and high aerosol load in the observation area, were also noticed. On average, a cooling of about 3–4 ^∘C was observed for T_air and LC_T, and a decrease of up to 2–3 hPa was observed for VPD. Given the long-distance transport of aerosols emitted by burning biomass, significant changes in atmospheric optical properties and irradiance will impact the CO₂ flux of semideciduous forests distributed in the region.

Atmospheric processes and climate are closely linked to the carbon cycle in the Amazon region as a consequence of the strong biosphere-atmosphere coupling. The radiative effects of aerosols and clouds are still unknown for a wide variety of species and types of vegetation present in Amazonian biomes. This study examines the effects of atmospheric aerosols on solar radiation and their effects on Net Ecosystem Exchange (NEE) in an area of semideciduous tropical forest in the North of Mato Grosso State. Our results show a reduction in the NEE with a decrease in incident solar radiation of ≈ 40 % and relative irradiance between 1.10–0.67. However, an average increase of 35–70 % in NEE was observed when pollution levels (Aerosol Optical Depth) were above ≈ 1.25. The increase NEE was attributed to the increase of up to 60 % in the diffuse fraction of Photosynthetically Active Radiation. These results were mainly attributable to the biomass burning organic aerosols from fires. Important influences on temperature and relative humidity of the air, induced by the interaction between solar radiation and high aerosol load in the observation area, were also noticed; an average cooling of ≈ 3.0 °C and 10 %, respectively. Given the long-distance transport of aerosols emitted by burning biomass, significant changes in CO₂ flux can occur over large areas of the Amazon, with important effects on the potential for CO₂ absorption on ecosystems of semideciduous forests distributed in the region.

Resumo The purpose of this article is to establish a non-empirical theoretical model for the nocturnal cooling of Amazonian ecosystems with the aim of better understanding the thermodynamics of such ecosystems. The nocturnal features of temperature in five different ecosystems in the Brazilian Amazon region have been studied, namely deep forest, medium forest, transitional forest, savannah (Cerrado) and a seasonally flooded forest (Brazilian Pantanal). Over the course of one year, micrometeorological data, specifically air temperature and humidity, were analysed. It has been observed that temperature in all ecosystems decreases at a rate of 0.9°C/h at the beginning of the night. The above rate is coherent with the theoretical cooling rate expected in conditions of “dry” air, i.e., when humidity does not exert a significant influence on the ecosystem thermodynamics. Data analysed revealed that when relative humidity is higher than approximately 85% in the middle of the night, the cooling rate drops down more than one order of magnitude until the end of the night, in all ecosystems. This means that the water present in the air effectively releases energy into the environment. Since hypothetically the effect is produced by the coalescence of clusters of two water molecules, the amount of energy necessary to produce the effect corresponds to a coalescence rate of 10²² clusters per cubic meter per hour, a very small quantity to be properly detected by latent heat flux measurement systems.

Many remote sensing‐based evapotranspiration (RSBET) algorithms have been proposed in the past decades and evaluated using flux tower data, mainly over North America and Europe. Model evaluation across South America has been done locally or using only a single algorithm at a time. Here, we provide the first evaluation of multiple RSBET models, at a daily scale, across a wide variety of biomes, climate zones, and land uses in South America. We used meteorological data from 25 flux towers to force four RSBET models: Priestley–Taylor Jet Propulsion Laboratory (PT‐JPL), Global Land Evaporation Amsterdam Model (GLEAM), Penman–Monteith Mu model (PM‐MOD), and Penman–Monteith Nagler model (PM‐VI). was predicted satisfactorily by all four models, with correlations consistently higher () for GLEAM and PT‐JPL, and PM‐MOD and PM‐VI presenting overall better responses in terms of percent bias (%). As for PM‐VI, this outcome is expected, given that the model requires calibration with local data. Model skill seems to be unrelated to land‐use but instead presented some dependency on biome and climate, with the models producing the best results for wet to moderately wet environments. Our findings show the suitability of individual models for a number of combinations of land cover types, biomes, and climates. At the same time, no model outperformed the others for all conditions, which emphasizes the need for adapting individual algorithms to take into account intrinsic characteristics of climates and ecosystems in South America.

The Surface Energy Balance Algorithm for Land (SEBAL) framework in Graphics Processing Units (GPU) using Cuda and OpenCL

The Brazilian savanna (Cerrado) has been heavily impacted by agricultural activities over the last four to five decades, and reliable estimates of reference evapotranspiration (ET_o) are needed for water resource management and irrigation agriculture. The Penman–Monteith (PM) is one of the most accepted models for ET_o estimation, but it requires many inputs that are not commonly available. Therefore, assessing the FAO guidelines to compute ET_o when meteorological data are missing could lead to a better understanding of which variables are critically important for reliable estimates of ET_o and how climatic variables are related to water requirements and atmospheric demands. In this study, ET_o was computed for a grass-dominated part of the Cerrado from April 2010 to August 2019. We tested 12 different scenarios considering radiation, relative humidity, and/or wind speed as missing climatic data using guidelines given by the FAO. Our results presented that wind speed and actual vapor pressure do not affect ET_o estimates as much as the other climatic variables; therefore, in the Cerrado’s conditions, wind speed and relative humidity measurements are less required than temperature and radiation data. When radiation data were missing, the computed ET_o was overestimated compared to the benchmark. FAO procedures to estimate the net radiation presented good results during the wet season; however, during the dry season, their results were overestimated because the method could not estimate negative R_n. Our results indicate that radiation data have the highest impact on ET_o for our study area and presumably for regions with similar climatic conditions. In addition, those FAO procedures for estimating radiation are not suitable when radiation data are missing.

The Pantanal is the largest floodplain of the globe occupying 138,183 km2 in Brazil. The fundamental ecological factor of interaction between the Pantanal ecosystems is the flooding regime. Connected to properties of the soil-plant-atmosphere system, knowledge on the soil water content becomes increasingly necessary. The high temporal and spatial variability of water content in the soil caused by the vast heterogeneity of soil texture, vegetation, topography and climate makes it a difficult physical variable to be measured. However, its spatial and temporal variability can be determined by recent modern techniques of remote sensing based on data obtained by microwave or infrared sensors. Thus, the aim of this study was to evaluate the accuracy of vegetation and soil water indexes through satellite images from Landsat 5 in the northern Brazilian Pantanal. The study was conducted in a pasture, experimental site in the Northern Pantanal in Mato Grosso state. Soil moisture was measured using a TDR probe installed at 10 cm depth in the period from 2009 to 2011. For comparison, spectral indexes and the surface temperature provided by Geological Survey (USGS) were used, these indexes are derived from bands ratios of satellite reflectance products Landsat 5 TM. The data evaluation was performed using some indicators: accuracy - Willmott index, Root Mean Square Error and the Mean Absolute Error. This study demonstrated that the application of remote sensing in the management of water resources is very promising. The indexes correlated with soil moisture measurement. Among the soil water indexes the NBR-2 showed related to soil moisture measurement. For both types of soils EVI had the highest determination coefficient, lowest errors and highest Willmott’s index of agreement.