AMI-CPS:
A Study of Climate Processes
in the Atlantic Marine ITCZ
A CLIVAR proposal Under Development
June 2004
Background
 September 2002: The US CLIVAR ITCZ Workshop (IRI)
 December 2002: Encouragement from the US CLIVAR Atlantic
Panel to plan for an AMI process study.
 October 2003: Preliminary plan developed as a joint field program of
AMMA and AMI.
 Nov-Dec 2003: Brief the US CLIVAR Atlantic Panel and
subsequently the US CLIVAR SSC on a of the AMI process study.
 February 2003: Strong support from US CLIVAR SSC to a continued
development of AMI process study plan.
 March 2004: Inclusion of the AMI study in the NOAA OGP 2005
Program Announcement.
 May 2004: Introduction of a draft science plan of the AMI Program
to the general research community at the AMS 26th Hurricane and
Tropical Meteorology Conference (Miami)
Outline of the AMI-CPS Plan:
1. Rationale and Scientific Background
o
2.
Research Objectives and Key Scientific issues
o
3.
convection-circulation interaction; local ITCZ-ocean
interaction; forcing from regional and remote convective
systems; effects of African dust and dry air
Program Components
o
4.
phenomena, societal impacts, prediction, model biases
process studies, enhanced monitoring, modeling,
diagnosis
Links to other programs
o
AMMA, TACE, VAMOS, THORPEX, CPT
The Societal Impact
Guinea Coast Population
density (color),
annual mean
rainfall (in
mm/day, contours
& gray shading),
Spring
and ITCZ annual
migration limits
Nordeste
(heavy, dashed
lines).
Sahel
Summer
AMI annual migration determines the seasonal distribution of
rainfall in densely populated regions and its interannual
variability directly affects water resources, agriculture, and
health
Tropical Atlantic Climate System
Ocean:
o Air-sea fluxes
o Cold tongue, SST
gradient, upperocean-heat-content
o Ocean circulation
Differences between the
(surface currents, eq.
Atlantic and Pacific ITCZ:
and subtropical
upwelling, STCs,
• position, intensity, and
Atmosphere:
THC)
seasonal cycle in the ITCZ;
o Atlantic marine ITCZ (AMI), Amazonian convection center, and o Transients (TIW)
• SST western
gradient;African monsoon (WAM)
o Trades and surface wind convergence
• land effects;
o Stratus deck over colder tropical oceans
• remote
influences
o Meridional
(Hadley) and zonal (Walker) circulations
o mid/low-level jets
o Transients (easterly waves, tropical storms, African dust)
Seasonal dependence of AMI
Boreal spring
Impacts: NE Brazil rainfall, African monsoon
onset; GG rainfall;
ITCZ: warm SST centered on eq with weak
gradients; strong surface wind convergence
with a relatively weak and broad marine
convective region close to the equator;
External influences: ENSO; previous winter
NAO; previous summer S. Atlantic; African
dust and dry-air outbreaks;
Boreal summer
Impacts: W. African monsoon; tropical storm
activity; rainfall in northern S. America;
ITCZ: colder SST with strong gradients;
strong and concentrated marine convection
positioned furthest from the equator;
External influences: ENSO state; ongoing S.
Atlantic circulation; Saharan Air Layer
(SAL), African easterly waves (AEW);
AMI Variability: Gradient “Mode”
external triggers
Warm SSTA
Enhanced SST gradient
Cold SSTA
WES feedback
ITCZ weakens on its southern
flank: Nordeste drought
First EOF (33%) of the March-April rainfall
from GPCP 1979-2001 (contours in mm/day).
March-April SST anomaly (colors, in °C &
white contours, every 0.2°) and surface wind
anomaly (vector, in m/sec) are determined by
regression on the time series of the rainfall
QuickTime™ and a
TIFF (LZW) decompressor
are needed to see this picture.
AMI Variability: Equatorial “Mode”
external influences
ITCZ stronger on its
southern flank: Guinea
Coast is wet
Cold tongue is
weakened
Dynamical feedbacks
Anomalous convergence
First EOF (23%) of the June-August rainfall
from GPCP 1979-2001 (contours in mm/day).
June-August SST anomaly (colors, in °C &
white contours, every 0.2°) and surface wind
anomaly (vector, in m/sec) are determined by
regression on the time series of the rainfall
QuickTime™ and a
TIFF (LZW) decompressor
are needed to see this picture.
Model Biases: I
Rainfall averaged over the tropical Atlantic Basin (15-35°W) - climatology and 1st
EOF of interannual variability (1979-2001)
OBS
Southward
displaced spring
ITCZ
CCM3
Weak summer ITCZ
Model Biases: II
Below: In situ data assimilation at ECMWF
(S1 & S2 systems), anomaly correlation to
altimeter observations (Eq. E. Pacific; Eq.
W. Pacific; Tropical Atlantic; Eq. Indian (T.
Stockdale, ECMWF)
Above: Coupled model systematic error in
equatorial SST simulation
AMI
Predictability
o There is substantial potential
o
o
o
predictability in the TA region but
actual prediction remains a
problem.
GCMs, coupled models in
particular, display large biases in
simulating the climate of the
tropical Atlantic.
Statistical schemes to predict the
anomalies in AMI location and
strength have limited success.
Difficulties linked to sensitivity of
AMI intensity and location to
relatively small changes in surface
and upper air conditions and the
unique blend between local and
external mechanisms that affect
these conditions.
AGCM skill in determining rainfall when SST is
known Red = correlation > 0.6 (Goddard and Mason,
2002).
Associated pattern of SST and land rainfall errors
when using SST persistence for prediction in an
AGCM with a one-season lead (Goddard and Mason,
2002).
Precipitation prediction foiled by
sudden change in GG SST
IRI two-tiered forecast
IRI prediction
August 2002:
Warm GG
SST - forecast
of positive
rainfall
anomaly
issues
SST September 2002: An
unpredictable, abrupt shift to
cold GG SST & negative
rainfall anomaly
ECMWF coupled forecast
Forecasts of Atlantic SST
o
o
o
Model does not capture cold season
anomaly in east eq. Atlantic (ATL2)
North sub-tropical is not too bad but
range of prediction small
South Sub-tropical Atlantic is fine
(T. Stockdale, ECMWF)
Eastern eq. Atl.
North TA
South TA
Bad SST prediction results in large
error in AMI rainfall
ECMWF coupled forecast
T. Stockdale, ECMWF
The AMI-CPS Program: Overall Goal
Advance understanding and simulation
of AMI seasonal and interannual
variability in order to improve
prediction of tropical Atlantic climate
variability and its societal impacts
Rationale for AMI process studies I:
The need of in situ observations
In situ observations in the tropical Atlantic marine
environment are needed to help
 advance understanding of the mechanisms
governing the variability and predictability of AMI
 quantify errors in model simulations and data
reanalysis products
 assist in model improvement and development
 improve climate prediction in the TA region
EPIC2001
RH
Example of uncertainties
in global reanalyses I
E. Pacific 95°W – 125°W
hPa
ERA40 (w x 20)
hPa
NCEP (w x 20)
RH
(b)
NCEP
hPa
v at the equator
ERA40
hPa
Example of uncertainties in
global reanalyses II
(a)
RH
Rationale for AMI process studies II:
Enhance scientific insights from EPIC2001
Experience and knowledge gained from the EPIC2001
field experiment provide guidance to AMI process
studies; AMI process studies can further test and
confirm results from EPIC2001, for example:
 convective forcing (Raymond et al. 2003)
 cloud structure (Peterson et al. 2003)
 shallow meridional circulation (Zhang et al. 2004)
 momentum balance in the boundary layer
(McGauley et al. 2004)
Courtesy of
Walter Peterson
The AMI EEA Field Program:
Specific Objectives in Boreal Summer
To Better Describe and Understand:
 Effects of African dust and dry-air outbreaks (e.g., SAL) on
mean AMI precipitation –EPIC2001
the relative importance of aerosol
vs. water vapor
 Role of transients (e.g., AEWs) in determining the mean
properties of the AMI precipitation - position and intensity
 Interaction between mesoscale structures of AMI convection
and the large-scale meridional circulation – deep vs. shallow
meridional cells
 Role the shallow meridional circulation in air-sea
interaction - testing the Zhang et al (2003) hypothesis
Rationale for AMI process studies III:
The unique problems of AMI
Observing the following unique features of the AMI
will provide new knowledge on climate processes
related to the ITCZ not available from any previous
process studies:
 interaction between external and internal influences
on the ITCZ.
 effects on African dust and dry-air outbreaks on
convection and precipitation in the ITCZ;
 interaction among the ITCZ, equatorial SST, and the
West African Monsoon;
The AMI-CPS Program:
Objectives and Approaches
Objectve I: Improve our understanding of
processes key to predictability of the AMI
on seasonal to interannual timescales.
– Focus on four key scientific issues:
(1) Convection-circulation interaction
(2) Effects of African dust, aerosol, and dry air on
convection and precipitation in the ITCZ
(3) ITCZ-upper ocean-monsoon interaction
(4) Mechanisms of remote influences
Key issues for the AMI-CPS Program
1. Convection-Circulation Interaction
o
o
o
What are the main factors determining the cloud characteristics in the ITCZ
that are systematic different from other tropical regions (e.g., W. Pacific warm
pool, African monsoon region)? - Nesbitt et al. (2002); Schumacher and
Houze (2003)
Is the vertical distribution of cloud in the ITCZ bimodal as suggested by the
EPIC2001 observations, instead of trimodal as in the W. Pacific warm pool? Johnson et al. (2001); Walter Peterson; James Mather
If so, what are responsible for this difference?
What are the roles of ITCZ convection in the single vs. dual large-scale
meridional circulation cells and in surface wind? - Tomas and Webster (1997);
Wu (2003); Zhang et al. (2004)
Hypothesis on the Entrainment Braking Mechanism
10-12 km
1 - 4 km
Eq
ITCZ
Eq
ITCZ
Key issues for the AMI-CPS Program
2. Effects of African dust, aerosol, and dry air on
convection in the ITCZ
o How differently do African mineral dust and biomass-burning aerosol
affect cloud in the ITCZ?
o Can the difference between the radiative and CCN effects of African
dust/aerosol on cloud in the ITCZ be quantified?
o Can the different effects of African dust/aerosol and dry air on cloud in
the ITCZ be quantified?
– Carlson and Prospero (1972); Dunion and Velden (2004)
African aerosol
(a)
(b)
(c)
(d)
(Dunion and
Velden 2004)
(Husar et al. 1997)
African aerosol
(Prospero and Lamb 2003)
Hypotheses on the Effects of African Dust:
African dust/aerosol/dry-air outbreaks are integrated
components of the climate system in the tropical
Atlatic.
ITCZ
?
African dust
(Prospero and Lamb 2003
Moulin and Chiappello 2004)
SST
African rainfall
(Goddard and Mason 2002; Giannini et al. 2003;
Biasutti et al. 2003)
Key issues for the AMI-CPS Program
3. ITCZ-Cold Tongue-Monsoon Interaction
o What is the role of the monsoon heat low in its effect on the springtime
evolution of the ITCZ/cold tongue complex?
o How does the annual migration of the ITCZ/cold tongue complex affect the
low-level circulation and the associated water vapor transport for the monsoon
rainfall?
o What are the relative importance of surface fluxes, upwelling, and advection
in the evolution and maintenance of the equatorial cold tongue?
o What are the relative roles of convection in the ITCZ and African monsoon in
determining the surface wind driving these oceanic processes?
o Why does the rapid development of the cross-equatoral meridional wind occur
only in May?
o How are the cold tongue and convection in the ITCZ related?
NCEP (w x 20)
West Africa 5˚E - 15˚W
Hypotheses on the monsoon effect
The low-level return flow of the shallow meridional
circulation associated with the Saharan heat low
prevents the acceleration of the the surface crossequatorial meridional wind stress. Deep convection
over land associated with the monsoon onset cut off
the low-level return flow, release the entrainment brake
near the equator, and therefore accelerate the
meridional wind stress.
Key issues for the AMI-CPS Program
4. Mechanisms of Remote Influences
o
o
Can remote forcing (e.g., ENSO) change the upper-tropospheric large-scale
conditions for convection and thereby change the characteristics of convection
in the ITCZ (e.g., deep vs. shallow, convective vs. stratiform rain) and
associated patterns of the large-scale circulation?
Can remote forcing (e.g., NAO) directly change the surface pressure gradient
and surface wind in the tropical Atlantic?
– Chiang and Sobel (2002); Chiang et al. (2002)
Lag correlation between Nino SST and tropospheric
temperature (Chiang and Sobel 2002)
Hypotheses on remote influences
A. Direct responses in surface wind to:
- changes in surface pressure gradient;
B. Direct responses in convection to:
- large-scale descent associated with the overturning cir;
- changes in temperature;
- advection of moisture;
The AMI-CPS Program:
Objectives and Approaches
Objective II: Provide quantitative information and
knowledge that contribute to the long-term
efforts of model development and improvement.
– Place at the center of the AMI-CPS Program process
studies that aim at collecting unprecedented in situ
observations needed to quantify errors and
uncertainties in model products (numerical simulations
and data assimilation) and to expose deficiencies in
models responsible for their errors and uncertainties.
Criteria for AMI process studies:
Data to be collected must help
 interpret long-term time series (e.g., global model
reanalyses, satellite data);
 improve models.
An example of a springtime AMI field campaign
(the EPIC2001 model)
Climate Transect: enhanced
soundings and surface observations
Airplane dropsondes
AMMA 2006
Ron Brown
o
o
o
o
o
o
o
o
ATR with dropsondes
o
o
o
o
o
o
o
o
o
o
o
o
o
o
o
o
o
o
o
o
Enhanced PIRATA array
EGEE CRUISES
CMM array
ATLAS moorings
o
o
o
o
Surface drifters
ADCP mooring
AMMA Surface Flux mooring
Lagrangian floats
Ron Brown Section SOP-I
The AMI-CPS Program:
Objectives and Approaches
Objective III: Establish a research mode that
targets short-term climate prediction problems of
a specific phenomenon by a climate process team
(CPT) of observations, modeling, diagnostics,
and prediction.
– Include, in addition to process studies, components
of enhanced monitoring, modeling, diagnosis,
prediction.
Program Components
• Process Studies
• Enhanced Monitoring
• Modeling
• Diagnosis
Enhanced Monitoring
(courtesy of AMMA)
Modeling
Quantify and reduce model biases. Assess the impact of
enhanced observations on determining model states for
simulation and predictions
• Research models: A hierarchy of atmosphere and
ocean models (single column, mixed layer, cloud
resolving, regional, and global)
• Prediction models: Two tiered and coupled
• Data assimilation and special regional reanalysis for
the tropical Atlantic
Diagnostics
• Global reanalyses: errors and biases
• Satellite data: statistics of convective structures
(ISCCP, TRMM, CLOUDSAT), aerosol (TOMS,
GOES, MODIS), water vapor (NVAP, GOES, AQUA)
Links to Other Programs
• The AMI field campaign and enhanced monitoring
activities have been and will continue to be joint
ventures with AMMA.
• The AMI enhanced monitoring activities will serve as
a commencement of TACE.
• The AMI field campaign can provide real time
observations for THORPEX.
• The AMI CPT will work together with the Climate
Feedback CPT.
• AMI-CPS will seek links to future VAMOS studies
Future Activities (tentative)
• Summer 2004: Conclude the draft science plan, make
it available online and solicit comments.
• Fall - Winter 2004: Complete the science plan; hold a
workshop if necessary.
• Spring 2005: Present the science plan to funding
agencies (etc. OGP, NSF, NASA).
• Fall 2005: Form research teams and an
implementation plan, and submit proposals.
• Spring 2007: A field campaign in the eastern
equatorial Atlantic
END