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Spatiotemporal variability of pCO2 of the Amazon River by ocean color remote sensing: from river to the plume

Grant number: 20/08148-0
Support type:Scholarships in Brazil - Post-Doctorate
Effective date (Start): September 01, 2020
Effective date (End): August 31, 2022
Field of knowledge:Physical Sciences and Mathematics - Oceanography - Chemical Oceanography
Principal researcher:Jeffrey Edward Richey
Grantee:Aline de Matos Valerio
Home Institution: Centro de Energia Nuclear na Agricultura (CENA). Universidade de São Paulo (USP). Piracicaba , SP, Brazil
Associated research grant:18/18491-4 - Biogeochemical blindspots along the lower Amazon River continuum: from land to the atmosphere and ocean, AP.SPEC

Abstract

Rivers transfer carbon dioxide (CO2) from water to the atmosphere, largely due to the degradation of organic matter from the soil and floodplains. In turn, coastal areas under the influence of river waters, such as the region adjacent to the mouth of the Amazon River, are recognized for sequestering CO2 from the atmosphere, as a result of primary production that is promoted by the supply of river nutrients. In situ measurements obtained from ships, although accurate, may be insufficient to characterize CO2 flow patterns in large geographic areas. An approach integrating remote sensing data makes it possible to characterize the variability and dynamics of the CO2 flow at the ocean-atmosphere interface. In this context, the objective of this postdoctoral project is to develop a regional algorithm for estimating the partial pressure of carbon dioxide (pCO2) by satellite that also represents the transition waters between the fluvial regime with low salinity and high turbidity and the regime contrasting oceanic. This algorithm will be calibrated for different orbital sensors and validated with in situ measurements obtained at the mouth of the Amazon River, in adjacent coastal waters and in the plume of the Amazon River. A time series of monthly compositions of orbital sensor data with better statistical adjustment of the regional pCO2 estimation algorithm will be used to analyze the temporal variability and spatial distribution of pCO2 in the Western Tropical Atlantic Ocean region. The variability of pCO2 will be analyzed by the Census X-11 method, decomposing the time series on seasonal, sub-annual and inter-annual scales, in addition to indicating the trend. From the pCO2 products generated by satellite, an unsupervised classification will be performed using the k-means algorithm to analyze the spatial distribution of pCO2 in the region and study period.

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