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Mesoclimate near the Tapajós-Amazon confluence

Mesoclimate near the Tapajós-Amazon confluence David R. Fitzjarrald (1) , Ricardo K. Sakai (1) , Osvaldo M. M. Moraes (2) , Otávio C. Acevedo (2) , Matthew J. Czikowsky (1) Jungle Research Group Atmospheric Sciences Research Center, University at Albany, SUNY, NY, USA

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Mesoclimate near the Tapajós-Amazon confluence

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  1. Mesoclimate near the Tapajós-Amazon confluence • David R. Fitzjarrald(1), Ricardo K. Sakai(1), Osvaldo M. M. Moraes(2), • Otávio C. Acevedo(2), Matthew J. Czikowsky(1) • Jungle Research Group • Atmospheric Sciences Research Center, University at Albany, SUNY, NY, USA • Universidade Federal de Santa Maria, RS, Brazil

  2. LBA research sites LBA-ECO Santarém

  3. Large scale influences on mesoclimate.

  4. Pbelem DPBelStm T U SOI Prec

  5. River breeze bias

  6. E W Fujita’s transmission factors; wind roses

  7. The ‘river of air’ moves into the basin day and night. A CBL over the river is 200-300 m thick. Implications for the ultimate fate of CO2 emitted from river.

  8. Radiative fluxes

  9. Radiative fluxes at the km67 site PARdn Kdn Ldn Lup Q*

  10. Appreciably more global solar radiation near the river… Clocks are OK! Diurnal asymmetry in mean Kdn results from similar asymmetry in cloudiness.

  11. Use the half-hourly statistics to infer cloud effects…

  12. Max Mean Min Wet season

  13. Max Mean Min Dry season

  14. Precipitation Connect the dots to get the rivers

  15. Diurnal patterns of precipitation depend on proximity to river STM weather stations CMORPH, Kousky et al. 2006

  16. 18-21 UTC 00-03 UTC 12-15 UTC 06-09 UTC 06-09 UTC 12-15 UTC 00-03 UTC 18-21 UTC Influence of large scale ‘mega squall lines’ on precipitation Time of ‘maximum precipitation rate’ (From Kousky et al. 2006, CMORPH analyses)

  17. convective synoptic Rain Dial (UT) Afternoon precipitation from local convective activity

  18. Wet season

  19. Dry season

  20. River breeze important near the river (where the climate stations are) Radiative flux bias at climate stations along river can be +30% Precipitation bias can be -20% to -30% Be careful how much you believe the gridded precipitation data. (Always ask how remote sensing products have been ‘ground-truthed’.) Interesting nocturnal CBL over river may have implications for the recycling of CO2 emitted from the water.

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