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How representative is the Large-Scale Biosphere-Atmosphere Experiment in Amazonia (LBA) results in comparison to long-term climatology? A study using climate weather stations in Brazil

Rafael Rosolem, University of Arizona,
W. James Shuttleworth, University of Arizona,
Luis G G de Goncalves, NASA/ESSIC-UMD, (Presenting)

The Large-Scale Biosphere-Atmosphere Experiment in Amazonia has already contributed understanding of the flux exchange between the Amazonian rainforest and atmosphere as other significant components of the ecohydrometeorological system, and it will continue to do so. However, when considering LBA-derived information on whether the Amazon is a source or sink of carbon, or whether land use changes in the Amazon are affecting the local and perhaps global climate, it is important to characterize the period during which the LBA project has been carried out in terms of its climatological context. In other words, to address the question “How does the climate during the LBA data collection period compare with the long-term climatology in Amazon.” Such information is not only useful for future project planning but is crucial information for modeling purposes: the calibration or validation of models using LBA data may be influenced by the climate conditions prevalent when these data were collected. This investigates the extent to which the actual period of data collection at LBA sites is representative of the long-term climatology for the sites. The research uses long-term weather station data taken from the databases of Brazilian National Water Agency (Agencia Nacional de Aguas - ANA) and National Oceanic and Atmospheric Administration - National Climatic Data Center division (NOAA-NCDC) for stations located near the Sao Gabriel da Cachoeira, Manaus, Santarem, Caxiuana, Jaru, Sinop, and Bananal LBA sites, and compares these weather station data during the LBA data collection period with the entire dataset available for each weather station.

Science Theme:  HY (Hydrometeorology)

Presentation Type:  Poster

Abstract ID: 78

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