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Regional and mesoscale influences on precipitation in the eastern Amazon Basin

Regional and mesoscale influences on precipitation in the eastern Amazon Basin. Julia Cohen Department of Meteorology / Federal University of Para, Brazil David Fitzjarrald Atmospheric Sciences Research Center / University at Albany, SUNY, USA. Area and some rivers.

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Regional and mesoscale influences on precipitation in the eastern Amazon Basin

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  1. Regional and mesoscale influences on precipitation in the eastern Amazon Basin Julia Cohen Department of Meteorology / Federal University of Para, Brazil David Fitzjarrald Atmospheric Sciences Research Center / University at Albany, SUNY, USA

  2. Area and some rivers

  3. Which station is ‘representative’? Need to know what kind of rainfall is occurring & how much. From Fitzjarrald et al, 2009

  4. convective synoptic Rain Dial (UT) Rain Dial Afternoon precipitation: local convective activity Nocturnal rainfall: instability line rainfall From Fitzjarrald et al, 2009

  5. Time of ‘maximum precipitation rate’ (From Kousky et al. 2006, CMORPH analyses)

  6. Squall Lines Climatology : 2000 to 2006 Data : Infrared Images Classification : CCL: Costal Convective Line ( Propagation < 170 km) SL1: Squall Line Type 1 ( 170 Km < Propagation < 400 km) SL2: Squall Line Type 2 ( Propagation > 400 km) SL2 – STM – Moved around Santarem = 56%

  7. Precipitation CMORPH = (0.25o) CPC Morphing Technique ("CMORPH") (Joyce et al, 2004) Precipitation have been derived from low orbiter satellite microwave observations. http://www.cpc.noaa.gov/products/janowiak/cmorph_description.html Influence of large scale ‘Squall Lines’ on precipitation at STM: provides a nocturnal rainfall maximum? Where?

  8. Rain (mm) by SL2 : CMORPH 15 to 00 UTC 00 to 09UTC 15 to 09UTC

  9. Rain (%) by SL2 : CMORPH 15 to 00 UTC 00 to 09UTC 15 to 09UTC

  10. From Fitzjarrald et al, 2009

  11. Numerical Experiment Description • BRAMS = Brazilian developments on the Regional Atmospheric Modeling System(RAMS) (Cotton et al., 2003). • Models of surface and vegetation, radiation, Cloud microphysics. • Grell’s deep convective and shallow convection parameterization. • Squall Line & Fluvial Breeze Grid increments ( 72 , 24, 8, 2 km)

  12. Rain & wind Rain & Thetae Δθe = 6 to 8K Grid 3 : June, 3 08 UTC Lat 0.6S

  13. Precipitation and air temperature observed and simulation mm oC UTC

  14. Total rain (12 UTC on 2 June to 00 UTC June 4)  with Topography Grid 2 (Δ = 24 Km) Climatology : Total rain since costal to STMS

  15. Grid 2 (Δ = 24 Km)

  16. Grid 2 (Δ = 24 Km)

  17. Grid 3 (Δ = 8 Km)

  18. Confluence of the Amazon and Tapajos rivers. 15-20 km wide Known cloudiness bias from the river breeze effect. (LBA, CIRSAN, Santarem) : . Silva Dias et al. (2004) . Lu et al. (2005)

  19. July, 23 2005 | July, 24 2005

  20. Divergence and wind at 96.7 meter Grid 4 (Δ = 2 Km) 15 UTC 18 UTC 21UTC

  21. Conclusions Squall lines reaching Santarém at night contributed up to 24% Even weak topography is important to squall propagation speed and rainfall intensity at STM. • Squall line precipitation important but not dominant in STM. Breeze at east side Tapajos river and south side of the Amazon River. Amazon breeze reached further inland more that did the Tapajos breeze.

  22. continuing work: SIPAM Doppler radar and reviving the rain gauge network around STM

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