Amazon Plume Salinity Response to Ocean Teleconnections

Tyaquiçã, Pedro; Veleda, Dóris; Lefèvre, Nathalie; Araújo, Moacyr; Noriega, Carlos; Caniaux, Guy; Servain, Jacques; Silva, Thiago Sanna Freire

doi:10.3389/fmars.2017.00250

Cited by 26 publications

(27 citation statements)

References 62 publications

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“…For example, El Niño periods caused severe droughts in the years 1983, 1993, 1997/98, 2003/04, 2009/10, and 2015/16, whereas La Niña episodes caused large positive rainfall anomalies in the years 1988/89, 1996, 1999/2000, and 2011. The drought periods 2009/10 and 2015/6 and an associated increase in fire activity, which also strongly impacted the atmospheric state at the ATTO and ZF2 sites, have been documented in previous studies (e.g., Saturno et al, 2018b;Tyukavina et al, 2017).…”

Section: Bt Clusterssupporting

confidence: 68%

“…GIS layers typically differ with respect to their acquisition time frames, which mostly represent states in the past (e.g., GlobCover 2009 representing land cover in the year 2009). Moreover, land cover is subject to dynamic seasonal and phenological changes (e.g., in agricultural lands), which is not covered by all GIS data sets (e.g., Ju and Roy, 2008;Jin et al, 2023;Tyukavina et al, 2017). Thus, all corresponding GIS maps are subject to limitations and uncertainties.…”

Section: Geographic Analysis By Means Of Selected Gis Data Setsmentioning

confidence: 99%

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Land cover and its transformation in the backward trajectory footprint region of the Amazon Tall Tower Observatory

et al. 2019

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Abstract. The Amazon rain forest experiences the combined pressures from human-made deforestation and progressing climate change, causing severe and potentially disruptive perturbations of the ecosystem's integrity and stability. To intensify research on critical aspects of Amazonian biosphere–atmosphere exchange, the Amazon Tall Tower Observatory (ATTO) has been established in the central Amazon Basin. Here we present a multi-year analysis of backward trajectories to derive an effective footprint region of the observatory, which spans large parts of the particularly vulnerable eastern basin. Further, we characterize geospatial properties of the footprint regions, such as climatic conditions, distribution of ecoregions, land cover categories, deforestation dynamics, agricultural expansion, fire regimes, infrastructural development, protected areas, and future deforestation scenarios. This study is meant to be a resource and reference work, helping to embed the ATTO observations into the larger context of human-caused transformations of Amazonia. We conclude that the chances to observe an unperturbed rain forest–atmosphere exchange at the ATTO site will likely decrease in the future, whereas the atmospheric signals from human-made and climate-change-related forest perturbations will increase in frequency and intensity.

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Section: Bt Clusterssupporting

confidence: 68%

Section: Geographic Analysis By Means Of Selected Gis Data Setsmentioning

confidence: 99%

Land cover and its transformation in the backward trajectory footprint region of the Amazon Tall Tower Observatory

et al. 2019

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“…The amplitude of anomalous plume salinity associated with rainfall‐induced Amazon discharge is rather weak (~0.3 psu, Figure ) in comparison to the amplitude of anomalous SSS observed by satellites (~1 psu, Figure d). Similar SSS amplitudes have been found by Tyaquiçã et al (; note the scaling of EOF and PC in their Figure ). The relatively weak magnitude of rainfall/discharge‐induced salinity coexists with stronger salinity variations caused by transient processes, with eddy‐ocean dynamics contributing among others (e.g., Grodsky, Reverdin, et al, ).…”

Section: Resultssupporting

confidence: 89%

Delayed and Quasi‐Synchronous Response of Tropical Atlantic Surface Salinity to Rainfall

Grodsky

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2018

JGR Oceans

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Zonally elongated patterns of tropical Atlantic rainfall variability associated with the Atlantic meridional (dipole) and the El Niño‐Southern Oscillation (ENSO) modes extend over the ocean and adjacent land and lead to a complex sea surface salinity (SSS) response. SSS response to local ocean rainfall is quasi‐instantaneous, while SSS response to land rainfall is delayed through river hydrology. Amazon rainfall associated with the Atlantic meridional mode concentrates over coastal north‐east Brazil and results in a fast Amazon response. In contrast, ENSO rainfall occupies vast inland areas and results in 3‐ to 7‐month delayed Amazon discharge response. Although ocean profile analyses represent well interannual SSS forced by open ocean rainfall, they miss interannual SSS in the plume. Including thermosalinograph transect data improves the representation of plume SSS, but its dynamic is better captured by ocean reanalyses. In Simple Ocean Data Assimilation, the plume SSS anomaly persists several months following the peak of land rainfall and is mixed out by seasonally accelerating winds in boreal winter. Its discharge‐correlated magnitude is only a modest few tenths of PSU. Perhaps, such weak projection of continental discharge variations on simulated SSS is not surprising due to other factors contributing in this dynamically active western boundary area. Significant transient variability in local currents not associated with rainfall/discharge variability is a factor explaining why ocean analyses based on occasional profile observations fail in resolving the rain‐induced SSS in the Amazon plume.

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“…It may be due to the precipitation‐driven equatorial SSS anomalies, later advected by the North Brazil Current. Also, Tyaquiçã et al () suggest from a statistical analysis that SSS anomalies extending until 10°N can be produced by interannual variations in the Amazon flow, more clearly related to ENSO than Atlantic modes. Our model uses climatological runoff.…”

Section: Summary and Discussionmentioning

confidence: 99%

Sea Surface Salinity Signature of the Tropical Atlantic Interannual Climatic Modes

et al. 2018

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The characteristic sea surface salinity (SSS) patterns associated with the tropical Atlantic meridional and equatorial interannual modes are extracted from in situ observations, by a statistical analysis performed on the 1980-2012 period. These SSS signatures of the interannual climatic modes are reproduced in a regional numerical simulation. For each mode, oceanic and/or atmospheric processes driving the SSS signature are identified through a mixed-layer salt budget in the validated model. During a positive meridional mode in spring, a northward shift of the Intertropical Convergence Zone and related precipitation maximum creates a south-north dipole of positive-negative SSS anomalies around the equator. Western boundary currents strengthen and advect relatively fresh equatorial waters, which creates negative SSS anomalies in the north and south west tropical Atlantic. Meridional and vertical advection create positive SSS anomalies off the Congo River. During a positive equatorial mode in summer, a southward shift of the Intertropical Convergence Zone-related rainfall maximum creates a south-north dipole of negative-positive SSS anomalies between the equator and 10°N. Meridional advection also contributes to the positive SSS anomalies between 5°N and 10°N. Vertical advection and diffusion at the mixed-layer base create positive SSS anomalies between 5°S and the equator. Horizontal advection creates large SSS anomalies in the North Brazil Current retroflection region, negative along the coast and positive further offshore. The SSS signatures of the meridional and equatorial modes described above are well captured by the Soil Moisture-Ocean Salinity satellite during the 2010 and 2012 events.Plain Language Summary This study shows that both meridional and equatorial interannual climatic modes impact the sea surface salinity (SSS) in tropical Atlantic through atmospheric and/or oceanic processes. The atmospheric forcing, related to Intertropical Convergence Zone migration, controls the equatorial region, while the advection, due to modulation of current dynamics, vertical SSS gradient, and mixing at the base of mixed layer, drives SSS in the region under the influence of river plumes.

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Amazon Plume Salinity Response to Ocean Teleconnections

Cited by 26 publications

References 62 publications

Land cover and its transformation in the backward trajectory footprint region of the Amazon Tall Tower Observatory

Land cover and its transformation in the backward trajectory footprint region of the Amazon Tall Tower Observatory

Delayed and Quasi‐Synchronous Response of Tropical Atlantic Surface Salinity to Rainfall

Sea Surface Salinity Signature of the Tropical Atlantic Interannual Climatic Modes

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