climate and climate variability along the extratropical andes cordillera (western slope) rené d....
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Climate and climate variability along the extratropical Andes cordillera (western slope)
René D. Garreaud, Mark Falvey,Maisa Rojas and Patricio Aceituno
Department of GeophysicsUniversidad de Chile
CONCORD-Mendoza-3/6 Abril 2006
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Climate and climate variability along the extratropical Andes cordillera (western slope)
• Present day climate (rainfall)• Present day climate variability: ENSO• Present day climate variability: Longer-time• Future scenarios (work in progress)
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The big picture… storm track over the South PacificSatellite (TRMM,SSMI data)
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1 10 100 1000 mm/year
Latit
ude
Mean Annual Rainfall. Chilean stations.
h < 2000m ASL
h > 2000m ASL
Coastal desert
Frontal
Altiplano
Frontal +orographic
0 3 6 km
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A closer look over Central ChileWintertime (MJJAS) precipitation – 93 stations – 10 years
Rainfall pattern dominated by N-S gradient in rainfall…mostly due to southward increase in the number of rainy days
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Rain shadow
OrographicEnhancement (1:3)Intensity?
(R/R) (H/H) 3/10
(R/R) (F/F) 3/1
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TRMM PR (compuesta de imágenes entre 0800 y 1200 UTC)Pluviómetro
June 3, 2002 June 3, 2002
Lack of surface precipitation data… what about remote sensing?TRMM: State of the art in rainfall RS (forget GPI)
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Estimación de RW de TRMM para 2002 - 2003
TRMM mean wintertime rainfall (2002-2003)Nice below 2000 m (despite of lack of data)
Sadly bad above 2000 m….calibration algorithm not suitable for solid preciptation
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x ~ y ~ 1-25 km z ~ 50-200 m t ~ 3-180 segundos
Lx ~ L y ~ 100-5000 km Lz ~ 15 km
z
y
x
Ly
Lx
Lz
Met. Models currently used in many institutions for numerical weather prediction…
Lack of surface precipitation data… what about regional models?
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MM5-DGF3 Dominios Anidados
D1
D2
D3
15 km de resolución horizontal
Condición inicial y las condiciones de los bordes de pronostico global
de NCEP
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MM5-DGF mean wintertime rainfall (2002-2004)Nice N-S gradients
Too much (?) precipitation in the lee slope
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Summary
Even in a densely populated area (as Central Chile) we do not know actual precipitation over the Andes. Remote sensing + Models can help, but more ground truth is needed…
TRMMMM5
PluviómetroTRMM (con corrección empírica)
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Stronger upper-Level ST Jet
Climo. Storm Track
EN years Storm Track
H
Blocking High
WeakenedST High
H
Drier/WarmerDJF
Wetter-OND
Wetter-JJA
Drier-DJF
Colder
Interannual variability - Major ENSO impacts
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ENSO Impacts on RainfallWe know look for inter-event variability
JJA
ON
DJF
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Annual means Monthly means / annual cycle
Extreme events
Required data Annual means Monthly means Daily values
Sfc. Air Temp. (Tx,Tn)
90% 10% 70%
Upper air Temp. (0ºC Height)
80% 30% 20%
Rainfall / snowfall
80% 30% 50%
Enviromental variables (e.g., river flow,…)
? ? ?
Longer-time variability (Trends, shifts, oscillations) in the XX Century:
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T.Máxima Anual Indice 1 (Arica-Iquique-Antofagasta)
20
21
22
23
24
1961 1966 1971 1976 1981 1986 1991 1996 2001
º C
T.Máxima Anual Indice 2 (Copiapo-Vallenar-L.Serena)
20
21
22
23
24
1961 1966 1971 1976 1981 1986 1991 1996 2001
º C
T.Máxima Anual Indice 3 (Q.Normal-Curico-Chillán-Concepción)
19
20
21
22
1961 1966 1971 1976 1981 1986 1991 1996 2001
ºC
T.Mínima Anual Indice 4 (Temuco-Valdivia-Osorno)
4
5
6
7
8
9
1961 1966 1971 1976 1981 1986 1991 1996 2001
º C
Stgo – Curicó-Chillán - Concepción Temuco – Valdivia - Osorno
Copiapó – Vallenar – La SerenaArica – Iquique - Antofagasta
Maximum air temperature (annual means):
Fuente de datos : DMC
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T. mínima anual Indice 3: Stgo - Curicó - Chillán - Concepción
5
6
7
8
9
10
1961 1966 1971 1976 1981 1986 1991 1996 2001
º C
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a) Cold nights b) Warm nights
Figure 1. Trend maps of annual values of cold nights (a) and warm nights (b) indicated in [days/dec] over 1961-2003. Upward (black) and downward (gray) pointing triangles indicate positive and negative trends, respectively. Size of triangles is proportional to the magnitude of the trend.
n.s 5 10 15
-15 -10 -5
n.s 5 10 15
-15 -10 -5
a) Cold nights b) Warm nights
Figure 1. Trend maps of annual values of cold nights (a) and warm nights (b) indicated in [days/dec] over 1961-2003. Upward (black) and downward (gray) pointing triangles indicate positive and negative trends, respectively. Size of triangles is proportional to the magnitude of the trend.
a) Cold nights b) Warm nights
Figure 1. Trend maps of annual values of cold nights (a) and warm nights (b) indicated in [days/dec] over 1961-2003. Upward (black) and downward (gray) pointing triangles indicate positive and negative trends, respectively. Size of triangles is proportional to the magnitude of the trend.
n.s 5 10 15
-15 -10 -5
n.s 5 10 15
-15 -10 -5
Villarroel et al, 2006
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Carrasco et al. 2005
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TENDENCIA DE LA PRECIPITACION ANUAL - 1950-2000
-200
-150
-100
-50
0
50
100
150
30
32
33
34
35
37
38
39
40
42
45
53
Latitud Sur
mm
/10
añ
os
Ref: Quintana, 2004
Rainfall trends – MAP – 1950-2000
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Frequency of days with precip. in the upper tercile in southern Chile
Periodo de referencia: 1930 – 2000Promedio móvil sobre periodos de 10 años.
Ref: Quintana, 2004
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Quinta Normal (Santiago)Probability of days with rainfall in excess of 30 mm
using 10-year windows
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Future Scenarios
Use high-resolution Regional (area-limited) Climate Models (MM5, Precis, etc) laterally forced by coarse-resolution GCM outputs (e.g., HadCM, CCM3, ECHAM).
GCMs are run under using CO2, other greenhouse gases and aerosol concentrations in the near future (2000-2100) as projected for different scenarios (A2, B2, etc.) defined by IPCC.
Some issues of concern:
• Garbage in – Garbage out. Check GC and Reg. Models against current climate…climate variability (e.g., ENSO) even more important than mean values• Model parameterizations• No CO2 effect in regional models (at least until now)
I agree I don’t agree
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Conclusions
Current climate rainfall distribution over the Andes is mostly unknown (educated guesses only). Temperature distribution is better known (more easily extrapolated). Surface network is needed.
Basic knowledge of ENSO impacts on rainfall. Focus now in inter-event variability.
20th Century climate history partially described (in the lowlands). Need for a more comprehensive, broader analysis (ANILLO).
Regional climate simulation for future scenarios in progress (ANILLO)