ISSUES ON MODELING THE WARM SEASON CLIMATE

IN SOUTH AMERICA

The South American Monsoon System (SAMS)The diurnal cycle in AmazoniaThe double ITCZ bias in GCMs

C.R. Mechoso, H.-Y. Ma, I. Richter, G. Cazes-BoezioDepartment of Atmospheric and Oceanic Sciences

Y. XueDepartment of Geography

University of California, Los Angeles, USA

R. Terra, M. MendinaInstitute of Fluid Mechanics

University of the Republic, Uruguay

CLARIS Implementation MeetingBologna, Italy, July 7-9, 2005

SAMS - Divergence and HeatingJanuary - February

Zonal Wavenumbers 2-6T. -C Chen, J. Climate 2003

SAMS and NAMSAscent to the east - Descent to the west

CMAP Precipitation and NCEP 850mb wind

WARM SEASON - South America

Model Description• UCLA AGCM, version 7.1• Resolution: high 2.5ºlon x 2ºlat x 29 levels

low 5ºlon x 4ºlat x 15 levels• Harshvardhan (1987) radiation scheme; Fu anf Liou

with aerosol scheme, SSiB• Prognostic version (Pan and Randall 1998) of the

Arakawa-Schubert (1974) cumulus parameterization with convective downdrafts

• The PBL top is a coordinate surface; a cloudy sublayer develops if this top is above condensationlevel (Deardorff 1972, Suarez et al.1983; Li et al. 1999, 2002).

• Climatological monthly-mean SSTs prescribed

Low Resolution High Resolution

South America

Evolution

of

SAMS

(Observation: Courtesy Bill Lau)

QuickTime™ and aTIFF (LZW) decompressor

are needed to see this picture.

GPCP

TRMM

AGCM

PERSIANN Diurnal Rainfall (DJF 2002)

0 0.6 1.2 (mm/h)

Local time: 01 hr Local time: 03 hr Local time: 05 hr Local time: 07 hr

Local time: 09 hr Local time: 11 hr Local time: 13 hr Local time: 15 hr

Local time: 17 hr Local time: 19 hr Local time: 21 hr Local time: 23 hr

Simulated Diurnal Cycle of Precipitation - January

(UCLA AGCM v7.1H; 2.5x2x29)

Amazonia Africa

(5 lon x 4 lat x 15L)

Relative Phases of the Diurnal CycleRelative Phases of the Diurnal Cycle

Diurnal cycle in Manaus,

Brazil, January

UCLA AGCM - Revised PBL

parameterization

0 3 6 9 12 15 18 21 240.0

0.1

0.2

0.3

0.4

0.5

0 3 6 9 12 15 18 21 24

-100

0

100

200

300

400

500

0 3 6 9 12 15 18 21 24

PBL thickness Ground temperature

TKE Precipitation

Latent and sensible heat flux Short and long wave radiation

LH

SH

local time (hr) local time (hr)

0.6

SW

LW

0 3 6 9 12 15 18 21 24

0 3 6 9 12 15 18 21 24 0 3 6 9 12 15 18 21 240

20

40

60

80

100

120

140

160

0.0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

290

295

300

305

310

-200

0

200

400

600

800

1000

0 3 6 9 12 15 18 21 240.0

0.1

0.2

0.3

0.4

0.5

0 3 6 9 12 15 18 21 24

-100

0

100

200

300

400

500

0 3 6 9 12 15 18 21 24

PBL thickness Ground temperature

TKE Precipitation

Latent and sensible heat flux Short and long wave radiation

LH

SH

local time (hr) local time (hr)

Mean diurnal cycles at 60W-10S for January

0.6

SW

LW

0 3 6 9 12 15 18 21 24

0 3 6 9 12 15 18 21 24 0 3 6 9 12 15 18 21 240

20

40

60

80

100

120

140

160

0.0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

290

295

300

305

310

-200

0

200

400

600

800

1000

Diurnal cycle at

60W, 10S

Shading corresponds to PBL

clouds

PBL Top

midnight

The Diurnal Cycle: CRM (2D) Simulation

Highly concentrated turbulent moisture convergence near the top of the PBL, which rapidly deepens

throughout the morning

In the afternoon, the convergence tends to spread over deeper layers, with the maximum still rising

Strong convective activity produces precipitation with a peak in the early

afternoon

0.0

0.1

0.2

0.3

0.4

0.5

0 3 6 9 12 15 18 21 24

Precipitation0.6

0.0

0.1

0.2

0.3

0.4

0.5

0 3 6 9 12 15 18 21 24

Precipitation0.6

AGCM

Observation

Marengo et. al (2005)

Mean simulated precipitation in Amazonia

Mean observed precipitation in Rondonia

Easterly regime

Leading Mode of VariabilityIn the Warm Season

COLACFS

CCSMObs

Annual Coupled GCM Mean Sea Surface Temperatures Errors

Courtesy: Ben Kirtman

The recent revision of PBL parameterization in the UCLA AGCM has eliminated SST errors in subtropical stratocumulus regions.

However, the “double ITCZ” bias persists!

Annual Mean SSTSimulated

Observed (Reynolds)

UCLA AGCM/MITogcm

“Double ITCZ” Bias

Hypothesis 1: Poor heat transport by ocean eddied from upwelling regions - Insufficient OGCM resolution?

Hypothesis 2: Poor simulation of the zonal circulation - Difficulties in the simulation of resolved and subgrid processes?

Annual Mean SST Model

Observation

UCLA AGCM - MIT OGCM

Geopotential height (10 gpm) and stream lines at 200 hPa

January-February 1988

NCEP AGCM; Triangular truncation (T-42); 18 Sigma layers(C) Two-layer soil model, (S1) Explicit vegetation model

NOTE: The two schemes use the same initial soil moisture, monthly meansurface albedo, and surface roughness length Xue et al. (J. Climate 2005)

Monsoon Sensitivity to Vegetation Processes

OBS C1 S1

October

December

10-day mean precipitation [mm/day]

Sensitivity of monsoon evolution to vegetation processes

The South American monsoon system…

• …comprises an upper-level anticyclone/ low-level heat low structure; large-scale zone with ascent to the east and descent to the west over the ocean. Here stratocumulus clouds enhanced by subsidence and upwelling develop.

• …shows intraseasonal variations that appear associated with continental-scale modes. In Amazonia these variations have been referred to as “westerly and easterly regimes”

• …has interannual variations that appear influenced by synooptic systems from mid latitudes.

• …tends to have stronger precipitation during El Niño events and weaker during La Niña.

• …has low predictability, with weak ENSO impacts and importance of conditions at the land surface

Modeling Issues - SAMS

• Mean climatology: Onset, Role of land surface processes.

• Intraseasonal variability: Westerly and easterly regimes. Principal modes of variability

• PBL processes and simulation of the diurnal cycle.

• The eastern Tropical Pacific: Stratocumulus clouds and double ITCZ bias. Coastal modelling?

• The western Atlantic: SST anomalies and Brazil/Plata Basin rainfall

• Effects of aerosol?

A few thoughts on Model Metrics1. OVERALL

• GCMS (in their current framework) can be improved (in my lifetime)• Focus on processes rather than on particular fields• AGCM verification requires coupled to OGCM

2. DIURNAL CYCLE

• PBL behavior (vertical profiles of several quantities: Potential temp, moist static energy, total and liquid water vapor, turbulence….)

• Interaction between PBL and free-atmosphere (entrainment at the PBL top, links with convection, downdrafts...)

3. GENERAL CIRCULATION

• Zonal circulation (how is it maintained? What processes are missing-badly represented?)

• Convection and Radiation: Vertical distribution of heating (this is not independent of motion!)

4. MONSOON SYSTEMS

• Comprehensive approach (not one system, not just the updraft…)• Different time-space scale and interactions