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Observations of the boundary layer (BL) processes are analyzed statistically for dry seasons of 2 years and in detail, as case studies, for 4 shallow convective days (ShCu) and 4 shallow-to-deep convective days (ShDeep) using a suite of ground-based measurements from the Observation and Modeling of the Green Ocean Amazon (GoAmazon 2014/5) Experiment. The BL stages in ShDeep days, from the nighttime to the cloudy mixing layer stage, are then described in comparison with ShCu days. Atmospheric thermodynamics and dynamics, environmental profiles, and surface turbulent fluxes were employed to compare these two distinct situations for each stage of the BL evolution. Particular attention is given to the morning transition stage, in which the BL changes from stable to unstable conditions in the early morning hours. Results show that the decrease in time duration of the morning transition on ShDeep days is associated with high humidity and well-established vertical wind shear patterns. Higher humidity since nighttime not only contributes to lowering the cloud base during the rapid growth of the BL but also contributes to the balance between radiative cooling and turbulent mixing during nighttime, resulting in higher sensible heat flux in the early morning. The sensible heat flux promotes rapid growth of the well-mixed layer, thus favoring the deeper BL starting from around 08:00 LST (UTC−4 h). Under these conditions, the time duration of morning transition is used to promote convection, having an important effect on the convective BL strength and leading to the formation of shallow cumulus clouds and their subsequent evolution into deep convective clouds. Statistical analysis was used to validate the conceptual model obtained from the case studies. Despite the case-to-case variability, the statistical analyses of the processes in the BL show that the described processes are very representative of cloud evolution during the dry season.

Aerosol-cloud interactions remain the largest uncertainty in climate projections. Ultrafine aerosol particles smaller than 50 nanometers (UAP ) can be abundant in the troposphere but are conventionally considered too small to affect cloud formation. Observational evidence and numerical simulations of deep convective clouds (DCCs) over the Amazon show that DCCs forming in a low-aerosol environment can develop very large vapor supersaturation because fast droplet coalescence reduces integrated droplet surface area and subsequent condensation. UAP from pollution plumes that are ingested into such clouds can be activated to form additional cloud droplets on which excess supersaturation condenses and forms additional cloud water and latent heating, thus intensifying convective strength. This mechanism suggests a strong anthropogenic invigoration of DCCs in previously pristine regions of the world.

The Amazon rainforest is the largest source of biogenic volatile organic compounds (BVOCs) to the atmosphere. To understand the distribution and chemistry of BVOCs, airborne and ground-based measurements of BVOCs are conducted over the Amazon rainforest in the CAFE-Brazil campaign (December 2022–January 2023), including diel (24-hour) profiles between 0.3-14 km for isoprene, its oxidation products, and total monoterpenes. Although daytime deep convective transport of BVOCs is rendered ineffective by photochemical loss, nocturnal deep-convection exports considerable BVOC quantities to high altitudes, extending the chemical influence of the rainforest to the upper troposphere, and priming it for rapid organic photochemistry and particle formation at dawn. After contrasting pristine and deforested areas, a BVOC sensitivity analysis is performed using a chemistry-climate model. Here we show that reducing BVOC emissions, decreased upper tropospheric ozone, increased lower tropospheric hydroxyl radicals, shortened the methane lifetime, with the net effect of enhancing climate warming through ozone and aerosols. Convection shapes BVOC dynamics over the Amazon rainforest, driving dawn photochemistry in the upper troposphere. Changes in BVOC emissions can strongly impact regional and global atmospheric chemistry.

This study offers an alternative presentation regarding how diurnal precipitation is modulated by convective events that developed over the central Amazon during the preceding nighttime period. We use data collected during the Observations and Modelling of the Green Ocean Amazon (GoAmazon 2014/2015) field campaign that took place from 1 January 2014 to 30 November 2015 in the central Amazon. Local surface-based observations of cloud occurrence, soil temperature, surface fluxes, and planetary boundary layer characteristics are coupled with satellite data to identify the physical mechanisms that control the diurnal rainfall in central Amazon during the wet and dry seasons. This is accomplished through evaluation of the atmospheric properties during the nocturnal periods preceding raining and non-raining events. Comparisons between these non-raining and raining transitions are presented for the wet (January to April) and dry (June to September) seasons. The results suggest that wet-season diurnal precipitation is modulated by nighttime cloud coverage and local influences such as heating induced turbulence, whereas the dry-season rain events are controlled by large-scale circulations.

The Amazon rainforest is one of Earth’s most diverse ecosystems, playing a key role in maintaining regional and global climate stability. However, recent changes in land use, vegetation, and the climate have disrupted biosphere-atmosphere interactions, leading to significant alterations in the water, energy, and carbon cycles. These disturbances have far-reaching consequences for the entire Earth system. Here, we quantify the relative contributions of deforestation and global climate change to observed shifts in key Amazonian climate parameters. We analyzed long-term atmospheric and land cover change data across 29 areas in the Brazilian Legal Amazon from 1985 to 2020, using parametric statistical models to disentangle the effects of forest loss and alterations of temperature, precipitation, and greenhouse gas mixing ratios. While the rise in atmospheric methane (CH 4 ) and carbon dioxide (CO 2 ) mixing ratios is primarily driven by global emissions (>99%), deforestation has significantly increased surface air temperatures and reduced precipitation during the Amazonian dry season. Over the past 35 years, deforestation has accounted for approximately 74% of the  ~ 21 mm dry season −1 decline and 16.5% of the 2°C rise in maximum surface air temperature. Understanding the interplay between global climate change and deforestation is essential for developing effective mitigation and adaptation strategies to preserve this vital ecosystem. In this study, the distinct impacts of deforestation and global climate change on the Brazilian Amazon are quantified for the period 1985-2020. Deforestation amplifies the temperature increase and dominates the decrease in rainfall in the dry season.

This study introduces a first glance at Amazonian aerosols in the N–Dg–σ phase space. Aerosol data, measured from May 2021 to April 2022 at the Amazon Tall Tower Observatory (ATTO), were fitted by a multi-modal lognormal function and separated into three modes: the sub-50 nm, the Aitken (50–100 nm), and the accumulation modes. The fit results were then evaluated in the N–Dg–σ phase space, which represents a three-dimensional space based on the three lognormal fit parameters. These parameters represent, for a given mode i, the number concentration (Ni), the median geometric diameter (Dg,i), and the geometric standard deviation (σi). Each state of a particle number size distribution (PNSD) is represented by a single dot in this space, while a collection of dots shows the delimitation of all PNSD states under given conditions. The connections in ensembles of data points show trajectories caused by pseudo-forces, such as precipitation regimes and vertical movement. We showed that all three modes have a preferential arrangement in this space, reflecting their intrinsic behaviors in the atmosphere. These arrangements were interpreted as volumetric figures, elucidating the boundaries of each mode. Time trajectories in seasonal and diurnal cycles revealed that fits with the sub-20 nm mode are associated with rainfall events that happen in the morning and in the afternoon. But in the morning they grow rapidly into the Aitken mode, and in the afternoon they remain below 50 nm. Also, certain modes demonstrated well-defined curves in the space, e.g., the seasonal trajectory of the accumulation mode follows an ellipsoid, while the diurnal cycle of the sub-50 nm mode in the dry season follows a linear trajectory. As an effect of the precipitation on the PNSDs and vice versa, N and Dg were found to increase for the sub-50 nm mode and to decrease for the Aitken and accumulation modes after the precipitation peak. Afternoons with precipitation were preceded by mornings with larger particles of the accumulation mode, whose Dg was ∼ 10 nm larger than in days without precipitation. Nevertheless, this large Dg in the morning seems to influence subsequent rainfall only in the dry season, while in the wet season both N and Dg seem to have the same weight of influence. The observed patterns of the PNSDs in the N–Dg–σ phase space showed to be a promising tool for the characterization of atmospheric aerosols, to contribute to our understanding of the main processes in aerosol–cloud interactions, and to open new perspectives on aerosol parameterizations and model validation.

Current livestock practices do not meet current real-world social and environmental requirements, pushing farmers away from rural areas and only sustaining high productivity through the overuse of fossil fuels, causing numerous environmental side effects. In this narrative review, we explore how the Voisin Rational Grazing (VRG) system responds to this problem. VRG is an agroecological system based on four principles that maximise pasture growth and ruminant intake, while, at the same time, maintaining system sustainability. It applies a wide range of regenerative agricultural practices, such as the use of multispecies swards combined with agroforestry. Planning allows grazing to take place when pastures reach their optimal resting period, thus promoting vigorous pasture regrowth. Moreover, paddocks are designed in a way that allow animals to have free access to water and shade, improving overall animal welfare. In combination, these practices result in increased soil C uptake and soil health, boost water retention, and protect water quality. VRG may be used to provide ecosystem services that mitigate some of the current global challenges and create opportunities for farmers to apply greener practices and become more resilient. It can be said that VRG practitioners are part of the initiatives that are rethinking modern livestock agriculture. Its main challenges, however, arise from social constraints. More specifically, local incentives and initiatives that encourage farmers to take an interest in the ecological processes involved in livestock farming are still lacking. Little research has been conducted to validate the empirical evidence of VRG benefits on animal performance or to overcome VRG limitations.

We describe the existence of an Amazonian low-level jet (ALLJ) that can affect the propagation and life cycle of convective systems from the northeast coast of South America into central Amazonia. Horizontal winds from reanalysis were analyzed during March–April–May (MAM) of the two years (2014–15) of the GoAmazon2014/5 field campaign. Convective system tracking was performed using GOES-13 infrared imagery and classified into days with high and weak convective activity. The MAM average winds show a nocturnal enhancement of low-level winds starting near the coast in the early evening and reaching 1600 km inland by late morning. Mean 3-hourly wind speeds maximize at 9–10 m s −1 near 900 hPa, but individual days can have nighttime low-level winds exceeding 12 m s −1 . Based on objective low-level wind criteria, the ALLJ is present 10%–40% of the time over the Amazon during MAM depending on the location and time of day. The evolution of the ALLJ across the Amazon impacts the frequency of occurrence of cloud clusters and the intensity of the moisture flux. In addition, the ALLJ is associated with the enhancement of northeasterly flow in the midtroposphere during active convective days, when vertical momentum transport may be occurring in the organized cloud clusters. During the weakly active convective period, the ALLJ is weaker near the coast but stronger across the central Amazon and appears to be linked more directly with the South American low-level jet.

We have investigated how aerosols affect the height above cloud base of rain and ice hydrometeor initiation and the subsequent vertical evolution of cloud droplet size and number concentrations in growing convective cumulus. For this purpose we used in situ data of hydrometeor size distributions measured with instruments mounted on HALO aircraft during the ACRIDICON–CHUVA campaign over the Amazon during September 2014. The results show that the height of rain initiation by collision and coalescence processes (Dr, in units of meters above cloud base) is linearly correlated with the number concentration of droplets (Nd in cm−3) nucleated at cloud base (Dr ≈ 5 ⋅ Nd). Additional cloud processes associated with Dr, such as GCCN, cloud, and mixing with ambient air and other processes, produce deviations of  ∼  21 % in the linear relationship, but it does not mask the clear relationship between Dr and Nd, which was also found at different regions around the globe (e.g., Israel and India). When Nd exceeded values of about 1000 cm−3, Dr became greater than 5000 m, and the first observed precipitation particles were ice hydrometeors. Therefore, no liquid water raindrops were observed within growing convective cumulus during polluted conditions. Furthermore, the formation of ice particles also took place at higher altitudes in the clouds in polluted conditions because the resulting smaller cloud droplets froze at colder temperatures compared to the larger drops in the unpolluted cases. The measured vertical profiles of droplet effective radius (re) were close to those estimated by assuming adiabatic conditions (rea), supporting the hypothesis that the entrainment and mixing of air into convective clouds is nearly inhomogeneous. Additional CCN activation on aerosol particles from biomass burning and air pollution reduced re below rea, which further inhibited the formation of raindrops and ice particles and resulted in even higher altitudes for rain and ice initiation.