contribution of lba field campaigns for the modeling of...
TRANSCRIPT
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Contribution of LBA field campaigns for the modeling
of tropical continental processes
Maria Assunção Faus da Silva Dias
Departamento de Ciências Atmosféricas
Universidade de São Paulo
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Summary
• surface processes
• clouds
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Field campaigns in the Amazon:
ABLE, ABRACOS, LBA, GoAmazon, etc..
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Long term climate variability
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P. L. Silva Dias et al 2009, chapter 11 of Past Climate Variability ... Springer
Past Climate given by Lake Level
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The Future IPCC AR5 2013
2016-2035 2046-2065 2081-2100
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Marengo, 2003
Interannual and Decadal Rainfall Variability Marengo 2004 Theor. Applied Climat.
1930 1950 1970 1990
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Interannual Variability Liebmann and Marengo, 2001, J. Climate
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Diurnal cycle Cloud Cover Area fraction Total and Cold from ISCCP Machado et al 2004 Theor. Applied Climat.
Wet season Dry season
Belem
Manaus
Brasilia
Vilhena
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• Large scale wind regimes associated to diferente cloud features
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20 km grid
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Easterly
Westerly
Carvalho et al 2000
ZCAS
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Anagnostou & Morales, 2002
Hourly rainfall rate
from TOGA radar
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Rickenbach et al. 2000
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Pereira et al, 2000
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24Feb99
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Blakeslee, 2000
Peterssen, 2000
Blakeslee,2000
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Threshold 235K (Systems)
100
120
140
160
180
200
220
0:4
5
2:4
5
4:4
5
6:4
5
8:4
5
10:
45
12:
45
14:
45
16:
45
18:
45
20:
45
22:
45
Time (UTC)
Rad
ius (
km)
Westerly
Easterly
Threshold 235K (Systems)
Convective Tops: 210K
0
2
4
6
8
10
12
14
16
18
0:4
5
2:4
5
4:4
5
6:4
5
8:4
5
10:
45
12:
45
14:
45
16:
45
18:
45
20:
45
22:
45
Time (UTC)
Nu
mb
er
of
Co
nve
cti
ve T
op
s
Westerly
Easterly
Carvalho et al, 2000
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Ramirez Gutierrez et al 2017, Raupp et al 2010
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• Key issue: the diurnal cycle of convection in the tropics is relevant • locally because it is fundamental for weather
forecasting
• globally, because of the potencial to generate low frequency oscillations in the MJO scale
• Key question: what processes influence the amplitude and phase of the diurnal cycle of convection (and rainfall) in the Amazon
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LBA started in 1998 and is still going on as LBA Phase 2
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LBA sites
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Location of the TRMM/LBA January-February 1999 (Wet Season) and SMOCC/RACCI September- November 2002 (transition Dry to Wet season)
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Short wave cloud forcing 𝑆𝑊𝐶𝐹 = 𝑆𝑊𝑑𝑜𝑤𝑛 − 𝑆𝑊𝑑𝑜𝑤𝑛 𝑐𝑙𝑒𝑎𝑟
Cloud effective albedo α𝑐𝑙𝑜𝑢𝑑 = − 𝑆𝑊𝐶𝐹
𝑆𝑊𝑑𝑜𝑤𝑛(𝑐𝑙𝑒𝑎𝑟)
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Rn LE H da Rocha et al , 2009 .J. Geophys. Res.
Shading indicates dry season
Evapotranspiration peaks in the dry season where roots are deep
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60 m
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Yamasoe et al 2006 Atmos. Chemistry and Physics
Diffuse radiation is more effectively transmitted below canopy than direct radiation; effect of aerosol and clouds
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Cloudy
Clear
8 10 12 14 16 18
20 22 0 2 4 6
𝜕θ𝑣
𝜕𝑧
> 0 stable = 0 neutral < 0 unstable
Silva Dias et al 2002 JGR
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45 m
U (
m/s
)
From ABLE2B Fitzjarrald and Moore (1990), JGR – forest tower at Duke site close to Manaus
w (
m/s
) w
(m
/s)
39 m
23 m
Time series of 1-s averaged 10 Hz data
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2009 Bound. Layer, Meteor
RAMS-based Forest Large-Eddy Simulation RAFLES Grid cell 5x5x3 m3
Domain 1,28 x 1.28x 1.41 km3 Model includes effects of leaves and stems on the drag and fluxes and also the physical barrier created by the stems and branches.
Bohrer, Katul, Walko, Avissar, 2009 Boundary-Layer Meteoro.
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• Diurnal cycle of convection over rainforest depends on the interaction between outside and inside canopy interchanges
• Seasonal cycle of the flux of latent heat depends on the root depth
• Cloud fraction and aerosol affect below canopy radiation input and thus the thermodynamic stability and carbono budget through photosynthesis.
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The aerosol effect
• Aerosol absorb and scatter solar radiation changing the temperature structure of the lower atmosphere and surface
• Aerosol act as Cloud Condensation Nuclei (CCN) and change the processes of rainfall production • Cloud droplets : water vapor condenses on CCN.
• Large numbers of CCN = competition for available water vapor
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Koren et al 2004 Measurement of the Effect of Amazon Smoke on Inhibition of Cloud Formation. Science
2) Albrecht et 2011. (JGR) Electrification of precipitating systems over the Amazon: Physical processes of thunderstorm development . Journal of Geophysical Research increasing sinking motion with effects: - Reduced cloud fraction - Increases concentrarion of smoke particles
(reduces dispersion) - Aerosol more effective in changing rainfall
when atmosphere is not excessively polluted
1) Smoke lowers cloud fraction
2) Subsidence lowers cloud fraction and increases smoke
concentration
1)
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Andreae et al 2004.Smoking rain clouds over the Amazon - Science
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CCN300
CCN600
CCN450
CCN900
5 km
12
km
“CLEAN”
“POLLUTED” Highest max rainfall rate mm/hr
BRAMS 4 km 3D simulation - Martins, Silva Dias, Gonçalves, 2009 JGR Vertical structure of cloud+ice water mixing rate at the time of maximum liquid water path
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3: (lat,lon)= (-12.5, -55) aot(550)=3.9
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Reduction on the Convective precipitation (mm)
DP = (P - Paer)
GOES-8 IR – 20020919 20:45Z
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Surface forcing
forest, deforestation, large rivers, large urban areas
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What is the effect of changes in the surface forcing on rainfall?
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Evolução diurna, camada de mistura e circulações locais
QH QLE QR
ΔQA
Surface energy budget
QR + QH + QLE +QG + ΔQA = 0
Bowen ratio
LE
H
Q
Q
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Mixed layer evolution
0
200
400
600
800
1000
1200
1400
1600
1800
5 10 15 20
Local time
He
igh
t (m
) pasture dry
pasture wet
forest dry
forest wet
Fisch et al 2001
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Circulações entre áreas desmatadas e floresta Silva Dias, M. A. F. e P. Regnier, 1996: Simulation of Mesoscale Circulations in a Deforested Area of Rondonia in the Dry Season. In: Amazonian Deforestation and Climate. J. Gash, C. Nobre, J. Roberts, R. Victoria, Eds., John Wiley & Sons, pp. 531-547 Silva Dias, M. Longo, D. R. Fitzjarrald, A. S. Denning. River breeze circulation in Eastern Amazon: observations and modeling results. Theoretical and Applied Climatology, DOI 10.1007/s00704-004-0047-6, , v. 78, n. 1-3, p. 111-121,2004. Fisch, G. F., Tota, J. Machado, L. A T. Silva Dias, M. A. F.;Lyra, R. F. F. Nobre, C. , Dolman, A J., Gash, J. H. C. . The convective boundary layer over pasture and forest in Amazonia. . Theoretical and Applied Climatology, DOI 10.1007/s00704-004-0043-x , v. 78, n. 1-3, p. 47-59, 2004.
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CIRSAN/LBA Large rivers
http://www.lba.iag.usp.br
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29,0
29,5
30,0
30,5
31,0
31,5
32,0
08:00 11:00 14:00 17:00
Local time (hours)
Wa
ter
tem
pe
ratu
re (
de
g.C
)
0.1m
0.3 m
0.7 m
1.0 m
c
23 July 2001 Tapajós
(from Pindobal to Boim and back)
26
27
28
29
30
31
32
10:00 10:30 11:00 11:30 12:00
Local time (hours)
Wa
ter
tem
pe
ratu
re (
de
g.C
)
0.1m
0.3 m
0.7 m
1.0 m
28 July 2001 Tapajós & Amazonas
(red line: temperature where the two rivers merge)
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TRMM rainfall
Dos Santos et al
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Vertical cross sections
• Grid 2
• Tapajós and Amazonas with different temperatures
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RUN 2 – 23 M ABOVE THE SURFACE
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RUN 2 – 23 M ABOVE THE SURFACE
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RUN 2 – 23 M ABOVE THE SURFACE
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RUN 2 – 23 M ABOVE THE SURFACE
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Vertical cross sections
• Grid 2
• Tapajós and Amazonas with different temperatures
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u and w – streamlines perpendicular to the Tapajós river
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u and w – streamlines perpendicular to the Tapajós river
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u and w – streamlines perpendicular to the Tapajós river
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u and w – streamlines perpendicular to the Tapajós river
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u and w – streamlines perpendicular to the Tapajós river
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u and w – streamlines perpendicular to the Tapajós river
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u and w – streamlines perpendicular to the Tapajós river
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u and w – streamlines perpendicular to the Tapajós river
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Deforestation impact clouds and rainfall
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TRMM-LBA Region: Forest vs. Non-Forest
SPOL
Profiler
TOGA FOREST
NON-FOREST
Carey et al 2001
RONDÔNIA
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TRMM-LBA Region: Topography
“Elevated” >= 223 m
“Non-Elevated” < 223 m
Carey et al 2001
Rondônia - topography
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6:20 7:20 8:20 9:20 10:20 11:20 12:20
Local Time
Time of first radar echoes
S-Pol Jan/Feb 1999
easterlies
westerlies
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0,0
20,0
40,0
60,0
80,0
Fre
qu
en
cy
(%)
Forest -
Below
Average
Forest -
Above
Average
Past ure -
Below
Average
Past ure -
Above
Average
Vegetation Altitude at Location of Convection
Initiation
Wet Season - All Cases
TOGA
SPOL
Pereira et al 2000
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0,6
0,7
0,8
0,9
1
1,1
1,2
0 20 40 60 80 100Deforestation (%)
Rela
tive
Pre
cipi
tati
on
. Avissar et al 2002
Conceptual impact of deforestation on relative precipitation
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Durieux, Machado & Laurent, 2003: The effect of
deforestation on cloud cover...
Deforest (D)
Florest (R)
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Dry Season More shallow clouds over deforested areas during the afternoon, and less deep convection at night
Low Cloud Cover
High Cloud Cover
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Wet Season Convection
stronger at night
over deforested
areas High Cloud Cover
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"More precipitation over deforested areas in the wet season, less in the dry season: increased seasonality - may be a norhtward shift of the equatorial-tropical transition zone" -
+ -
savanization...
Durieux et al, 2003
+
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Dry season Wet Season October 2002 February 2002
Deforestation plots
Saad et al
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How the pollution of large urban areas affect clouds around Manaus? • GoAmazon, CHUVA: Martin et al 2016, 2017, Cechini et al
2016
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Convective transports, aerosol cloud interactions
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Biomass burning emissions -> CATT – BRAMS Coupled Aerosol and Tracer Transport to the Brazilian developments on the Regional Atmospheric Modeling System Plume rise, regional and remote transports of biomass burning emissions surface – boundary layer adjusted to LBA data
• ABLE 2: Pickering et al (1992), Pereira et al (1991); Swap et
al 1991, 1992
• LBA: Longo et al 1999, Freitas et al 1996, 2000, 2005, 2007, 2009, 2017
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Time series of aerosol optical thickness measured from 2000 to 2017 using the AERONET sunphotometer network in several sites in Amazonia. AERONET Level 2 data with inversion algorithm 3.0. (Compilation done by Rafael Palácios, 2017)
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Local smoke plume (deforestation fires) (picture from M. Andreae)
smoke
smoke
smoke
Regional smoke plume
~5 millions km2 (Prins et al. 1998)
> 5000 fires GOES-8 WF_ABBA
15:35
Biomass Burning Emissions
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Amazon, a green ocean in the wet season, very continental in the transistion from dry to wet season. Role of large scale and thermodynamics vs role of aerosol as CCN
• LBA, SMOCC, RACCI: Williams et al 2002, Andreae et al 2004, Albrecht et al 2011
• CHUVA, GoAmazon, ACRIDICON: Saraiva et al 2016, Nunes et al 2016, Giangrande et al 2017, Cechini et al 2017
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Saraiva et al 2016 WET DRY TRANS
CO
ASTA
L
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Giangrande et al 2017 GoAmazon 2014/2015
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WET SEASON DRY SEASON
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Evolução nos modelos conceituais do sistema integrado biosfera-atmosfera
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Land-surface atmosphere interaction in the Amazon Basin: a complex system
Betts and Silva Dias, 2010, JAMES
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GOES-10 26-27 April 2007
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Dinâmica da nuvem Termodinâmica de nuvem
Microfísica de nuvens Interações nuvens e radiação Interações com aerossóis e
química atmosférica Interações biosfera-atmosfera
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