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  1. Abstract

    The presence of an aerosol layer in the upper troposphere/lower stratosphere (UT/LS) in South America was identified with the Modern-Era Retrospective Analysis for Research and Applications version 2 (MERRA-2). This layer, which we shall refer to as the South American tropopause aerosol layer (SATAL), was identified over the Amazon basin at altitudes between 11 and 14 km. It exhibits a seasonal behavior similar to the Asian tropopause aerosol layer (ATAL) and the North American tropopause aerosol layer (NATAL). The SATAL is observed from October to March, coinciding with the presence of the South American monsoon. It forms first in the eastern Amazon basin in October, then moves to the southern Amazon, where it weakens in December–January and finally dissipates in February–March. We hypothesize that two main factors influence the SATAL formation in the UT/LS: 1) the source of aerosols from Africa and 2) the updraft mass flux from deep convective systems during the active phase of the South American monsoon system that transports aerosols to the UT/LS. Further satellite observations of aerosols and field campaigns are needed to provide useful information to find the origin and composition of the aerosols in the UT/LS during the South American monsoon.

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    Free, publicly-accessible full text available January 1, 2025
  2. Abstract

    Northerly low-level jets (LLJ) along the eastern Andes are important conduits of moisture transport and play central roles in modulating precipitation in South America. This study further investigates the variability of the LLJ during extended austral summers. A new method characterizes the spatial extent of the LLJ and finds four distinct types: Central, Northern, Andes and Peru. We show the existence of specific evolutions such that the LLJ may initiate in the central region, expands along the Andes and terminates in the northern region. Conversely, the LLJ may propagate from north-to-south. The spatiotemporal evolution of the LLJ is remotely forced by Rossby wave trains propagating from the Pacific Ocean towards South America, and the different phases of the wave trains favor the occurrences of Central, Northern or Andes types. Occurrences of Central and Northern types are more frequent in El Niño and La Niña years, respectively. The persistence of precipitation is shown to be directly related to the persistence of the LLJ. Lastly, the Madden-Julian Oscillation plays an important role in generating wave trains modulating the frequency of LLJ, especially the Central type.

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  3. Abstract

    Water is redistributed from evaporation sources to precipitation sinks through atmospheric moisture transport. In the Brazilian Amazon, the spatial and temporal variability of dry season moisture sources for key agricultural regions has not been investigated. This study investigates moisture sources for dry season rainfall in the state of Rondônia in Brazil, especially during drought years. Using a precipitationshed framework, we quantified the variability of moisture contributions to rainfall in the state of Rondônia (Brazilian Amazon) and the influence of synoptic circulation patterns. Ocean evaporation accounts for 58% of mean dry season precipitation while continental recycling contributed 42%. During drought years, although forests maintain or increase evapotranspiration, the moisture contribution of both ocean and forests to dry season rainfall decreases due to the synoptic circulation changes, reducing the moisture transport into Rondônia.

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  4. The Brazilian Amazon provides important hydrological cycle functions, including precipitation regimes that bring water to the people and environment and are critical to moisture recycling and transport, and represents an important variable for climate models to simulate accurately. This paper evaluates the performance of 13 Coupled Model Intercomparison Project Phase 6 (CMIP6) models. This is done by discussing results from spatial pattern mapping, Taylor diagram analysis and Taylor skill score, annual climatology comparison, cumulative distribution analysis, and empirical orthogonal function (EOF) analysis. Precipitation analysis shows: (1) This region displays higher rainfall in the north-northwest and drier conditions in the south. Models tend to underestimate northern values or overestimate the central to northwest averages. (2) The southern Amazon has a more defined dry season (June, July, and August) and wet season (December, January, and February) and models simulate this well. The northern Amazon dry season tends to occur in August, September, and October and the wet season occurs in March, April, and May, and models are not able to capture the climatology as well. Models tend to produce too much rainfall at the start of the wet season and tend to either over- or under-estimate the dry season, although ensemble means typically display the overall pattern more precisely. (3) Models struggle to capture extreme values of precipitation except when precipitation values are close to 0. (4) EOF analysis shows that models capture the dominant mode of variability, which was the annual cycle or South American Monsoon System. (5) When all evaluation metrics are considered, the models that perform best are CESM2, MIROC6, MRIESM20, SAM0UNICON, and the ensemble mean. This paper supports research in determining the most up-to-date CMIP6 model performance of precipitation regime for 1981–2014 for the Brazilian Amazon. Results will aid in understanding future projections of precipitation for the selected subset of global climate models and allow scientists to construct reliable model ensembles, as precipitation plays a role in many sectors of the economy, including the ecosystem, agriculture, energy, and water security. 
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  5. Rainfall in the Amazon is influenced by atmospheric circulation dynamics on multiple spatiotemporal scales. Anthropogenic influences such as deforestation, land-use changes, and global climate change are also critical factors in determining rainfall in South America. Modeling studies have projected a drier climate with the ongoing deforestation in the Amazon, but observational evaluation of the variability of rainfall and deforestation patterns has been limited. This study analyzes spatiotemporal trends in rainfall between 1981 and 2020 and relationships with deforestation age in the Brazilian Legal Amazon (BLA). An improved rainfall dataset is derived by calibrating the Climate Hazards Group Infrared Precipitation with Stations (CHIRPS) data with observations from a rain gauge network in the BLA. Trend analysis is employed to identify significant changes in precipitation over the BLA. Satellite-based land cover data Mapbiomas and ET datasets are used to evaluate similar trends. While large spatial variability is observed, the results show coherent relationships between negative dry-season rainfall trends and old-age deforested areas. Deforestation aged up to a decade enhanced rainfall and older deforested regions have reduced rainfall during the dry season. These results suggest substantial changes in the hydroclimate of the BLA and increased vulnerability to future land cover change. 
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