!“Oh meu Deus! Oh meu Deus! Vou chegar tarde!” Coelho Branco

1. !“Oh meu Deus! Oh meu Deus! Vou chegar tarde!” Coelho Branco

2. "River proximity and topographic effects on precipitation in the eastern Amazon Basin" David Fitzjarrald Atmospheric Sciences Research Center University at Albany, SUNY With modeling: Julia Cohen, Universidade Federal de Pará, Brasil Surface network: Ricardo Sakai, Matthew Czikowsky, ASRC, UAlbany Osvaldo Moraes, Otávio Acevedo, Universidade Federal de Santa Maria, Brasil Rodrigo da Silva, Universidade Federal do Oeste do Pará, Brasil

3. ‘Explain all that,' said the Mock Turtle. `No, no! The adventures first,' said the Gryphon in an impatient tone: `explanations take such a dreadful time.' Chapter 10, “the Lobster Quadrille” Alice in Wonderland Gryphon Mock Turtle Observationalists (It’s the real thing, but maybe not relevant.) Modelers (It’s not the real thing, but aren’t the pictures nice?)

4. Cheshire Cat: “Well! I've often seen a cat without a grin,” thought Alice; but a grin without a cat! It's the most curious thing I ever saw in my life!” Remote sensing specialists (satellite images) It’s not the real thing either!

5. “Who cares for you?” said Alice, (she had grown to her full size by this time.) “You're nothing but a pack of cards!” “Quem se importa com vocês?”, disse Alice (ela tinha chegado a seu tamanho normal a esa altura). “Voces não passam de um baralho de cartas!” An old guy ends up out of touch with the new ‘death of causality’ science --- ’data-model-RS fusion’ ‘data assimilation’ How can you win or lose?

6. Leibman and Allured (BAMS 2005). Daily gridded data made from this station data base. How processed do you want your “data”?

7. Does it matter that the climate stations are all along the rivers?

8. Strong rainfall seasonality at Santarém: Pbel Pbel - Pstm Ustm Tstm S O index Precipitation

9. 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 ‘instability lines’ on precipitation at STM: provides a nocturnal rainfall maximum? Where? Time of ‘maximum precipitation rate’ (From Kousky et al. 2006, CMORPH analyses)

10. Measuring convective precipitation in the Amazon (anywhere?) is still a challenge. Tools: • Conventional rain gauge network: daily totals, some stations with hourly data (Hidro, INMET) • LBA-ECO special observations • CMORPH remotely sensed rainfall (Joyce et al.) Passive microwave, ‘CMORPH uses IR only as a transport vehicle, i.e. IR data are NOT used to make estimates of rainfall when passive microwave data are not available. • BRAMS model

11. Confluence of the Amazon and Tapajós rivers. 15-20 km wide Average GOES low cloudiness May 2001 Known bias in clouds from the river breeze effect. What kind of rainfall bias is there? Molion (≈1980’s) Detected breeze at Manaus back in 1985, 1987 (ABLE-2). Oliveira & Fitzjarrald (1990 ab); (LBA, CIRSAN, Santarem) Silva Dias et al. (2001) Lu et al. (2005)

12. Molion and Dallarosa (1988)--river breeze suppresses rain at a, b, g, e, f ….

13. 1998: `No, no! The adventures first,' said the Gryphon in an impatient tone…

15. LBA-ECO weather stations Installed July 1998 Original Belterra LBA station km117 station

18. FLONA Tapajós wedge gauges--substantial overestimation relative to tipping buckets…

19. Belterra station as the intercomparison point: TB & conventional measurements Daily totals Monthly totals Find the daily averaged rainfall and then scale up to months, seasons.

20. Which station is ‘representative’? 1. Need to know what kind of rainfall is occurring & how much. 2. Astronauts are useful!

21. More extreme events very near the Amazon channel…

22. Gridded rainfall data looks like that seen along the river, but there is less rainfall inland--where is the ‘breeze suppression’?

23. convective synoptic Rain Dial (UT) Rain Dial: Afternoon precipitation: local convective activity Nocturnal rainfall: instability line rainfall

26. “Well! I've often seen a cat without a grin,” thought Alice; but a grin without a cat! Remote sensing of precipitation: Using CMORPH

28. We found the CMORPH rainfall wasn’t too bad in the Amazon (not so great in NY) CMORPH: 213 mm Gauges: 185 mm CMORPH Czikowsky et al. (2010)

29. Gradients in mean total annual rainfall

30. Dry season average CMORPH rainfall top: day; bottom: night

31. Wet season average CMORPH rainfall top: day; bottom: night

32. Squall Lines : 2000 to 2006 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

34. Climatology : Rain (%) (15 to 0 UTC) Rain (%) (00 to 09 UTC)

35. ‘Explain all that,' said the Mock Turtle. • BRAMS = Brazilian developments on the Regional Atmospheric (RAMS) (Cotton et al., 2003). [simulations performed by Prof. Júlia Cohen, UFPa, Brasil • The model’s initialization was variable, each 6 hours, with the analysis of CPTEC’s global model, the radiosondes and the available surface data. • The integration period was 36 hours, initiating on June, 02, 2006, at 12 UTC. • surface vegetation, radiation, cloud microphysics modules. • Grell’s deep convective parameterization and shallow convection parameterization. • Control and Topography Experiments now. In future, examine role of background flow on river breeze convergence & local rainfall Júlia Cohen model runs.

36. Points X = 82,113,140 • Points Y = 60,89,113 • Points Z = 27,27,27 • Points in soil = 8 3 Grids River and Topography (m) Grid 2 Grid increments ( 72 , 24, 8 km) Grid 3

37. Total rain (12 UTC on 2 June to 00 UTC June 4)  with Topography Climatology : Total rain since costal to STMS

39. Total rain (12 UTC on 2 June to 00 UTC June 4)  with Topography Climatology : Total rain since costal to STMS

41. Hints of convergence after squall passage at Vila Franca

42. Left to do: Large land use change boundaries sharp, but ‘vegetation breeze’ is subordinate to the river breeze. Or, isthere any veggie breeze? Does such a breeze still occur on days following rain?

43. Tethered balloon Sodar at km 77 77 67 T Wind speed 67 77 PAR Old Growth Site (67) / Pasture site (77) comparison Hard to find the driving temperature difference for a vegetation breeze… Long-term average Sdw(km67)≈0.95 Sdw(km77)

45. continuing work Grid 4 look at how the breeze circulations may enhance rainfall inland (daytime) & how convergence over the river confluence may do so (night).

46. continuing work: remote sensing CloudSat (how does one use thin slices of information?) afternoon pass (blue) to get composites of breeze circulation cloud structure overnight pass (red) to cross the squall lines obliquely

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

48. Conclusions • • Observed: Near-river stations do indeed miss the afternoon convective rain as would be expected if a river breeze influence dominates. • • Observed: This deficiency is more than compensated by additional nocturnal rainfall. This effect is local; for areas only a few kilometers inland from the rivers, nocturnal squall lines contribute less than half of total precipitation. • • Still hypothesis: Breeze circulations associated with the Amazon River (with a wind component approximately normal to the mean flow) affect rainfall more than does the Tapajós breeze (which approximately opposes the prevailing wind). • • Observed/Modeled: Even subtle topography modulates squall lines and enhances rainfall. • Describing the proper mixture of precipitation types should be a concern for those assessing model sensitivity, especially since the reanalysis rainfall data are believed to be flawed.

49. questions • Are mesoscale circulations, related to the large lake-like expanse of water at the confluence responsible for the nocturnal precipitation preference? • As squall lines approach this region, does enhanced moist inflow augmented by southerly channeling up the Tapajós and easterly channeling along the Amazon fuel the storm as it approaches? • On normal afternoons, how far inland must one go to get the precipitation ‘representative’ of the region? Fitzjarrald, D. R., R. K. Sakai, O. L. L. Moraes, R. Cosme de Oliveira, O. C. Acevedo, M. J. Czikowsky, and T. Beldini (2008), Spatial and temporal rainfall variability near the Amazon-Tapajós confluence, J. Geophys. Res., 113, G00B11, doi:10.1029/2007JG000596, [printed 114(G1), 2009].