AMI-CPS: A Study of Climate Processes in the Atlantic Marine ITCZ

1. AMI-CPS:A Study of Climate Processes in the Atlantic Marine ITCZ A CLIVAR proposal Under Development June 2004

2. 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)

3. Outline of the AMI-CPS Plan: • Rationale and Scientific Background • phenomena, societal impacts, prediction, model biases • Research Objectives and Key Scientific issues • convection-circulation interaction; local ITCZ-ocean interaction; forcing from regional and remote convective systems; effects of African dust and dry air • Program Components • process studies, enhanced monitoring, modeling, diagnosis • Links to other programs • AMMA, TACE, VAMOS, THORPEX, CPT

4. The Societal Impact Population density (color), annual mean rainfall (in mm/day, contours & gray shading), and ITCZ annual migration limits (heavy, dashed lines). Guinea Coast Sahel Summer Spring Nordeste AMI annual migration determines the seasonal distribution of rainfall in densely populated regions and its interannual variability directly affects water resources, agriculture, and health

5. Differences between the Atlantic and Pacific ITCZ: • position, intensity, and seasonal cycle in the ITCZ; • SST gradient; • land effects; • remote influences Tropical Atlantic Climate System Ocean: • Air-sea fluxes • Cold tongue, SST gradient, upper-ocean-heat-content • Ocean circulation (surface currents, eq. and subtropical upwelling, STCs, THC) • Transients (TIW) Atmosphere: • Atlantic marine ITCZ (AMI), Amazonian convection center, and western African monsoon (WAM) • Trades and surface wind convergence • Stratus deck over colder tropical oceans • Meridional (Hadley) and zonal (Walker) circulations • mid/low-level jets • Transients (easterly waves, tropical storms, African dust)

6. Boreal spring Boreal summer Seasonal dependence of AMI 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; 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);

7. 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 EOF.

8. 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 EOF.

9. Model Biases: I Rainfall averaged over the tropical Atlantic Basin (15-35°W) - climatology and 1st EOF of interannual variability (1979-2001) OBS CCM3 Weak summer ITCZ Southward displaced spring ITCZ

10. 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

11. AMI Predictability • There is substantial potential 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).

12. 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

13. 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) ECMWF coupled forecast Forecasts of Atlantic SST North TA Eastern eq. Atl. South TA

14. Bad SST prediction results in large error in AMI rainfall ECMWF coupled forecast T. Stockdale, ECMWF

15. 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

16. 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

17. EPIC2001 RH ERA40 (w x 20) hPa NCEP (w x 20) hPa RH Example of uncertainties in global reanalyses I E. Pacific 95°W – 125°W

18. (a) ERA40 hPa (b) NCEP hPa RH Example of uncertainties in global reanalyses II v at the equator

19. 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)

20. Courtesy of Walter Peterson EPIC2001 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 – 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

21. 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;

22. 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: • Convection-circulation interaction • Effects of African dust, aerosol, and dry air on convection and precipitation in the ITCZ • ITCZ-upper ocean-monsoon interaction • Mechanisms of remote influences

23. Key issues for the AMI-CPS Program • Convection-Circulation Interaction • 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)

24. Hypothesis on the Entrainment Braking Mechanism 10-12 km 1 - 4 km Eq Eq ITCZ ITCZ

25. Key issues for the AMI-CPS Program 2. Effects of African dust, aerosol, and dry air on convection in the ITCZ • How differently do African mineral dust and biomass-burning aerosol affect cloud in the ITCZ? • Can the difference between the radiative and CCN effects of African dust/aerosol on cloud in the ITCZ be quantified? • 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)

26. African aerosol (a) (b) (c) (d) (Husar et al. 1997) (Dunion and Velden 2004)

27. African aerosol (Prospero and Lamb 2003)

28. 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) African rainfall SST (Goddard and Mason 2002;Giannini et al. 2003; Biasutti et al. 2003)

29. Key issues for the AMI-CPS Program 3. ITCZ-Cold Tongue-Monsoon Interaction • What is the role of the monsoon heat low in its effect on the springtime evolution of the ITCZ/cold tongue complex? • 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? • What are the relative importance of surface fluxes, upwelling, and advection in the evolution and maintenance of the equatorial cold tongue? • What are the relative roles of convection in the ITCZ and African monsoon in determining the surface wind driving these oceanic processes? • Why does the rapid development of the cross-equatoral meridional wind occur only in May? • How are the cold tongue and convection in the ITCZ related?

30. NCEP (w x 20) West Africa 5˚E - 15˚W

31. 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 cross-equatorial 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.

32. Key issues for the AMI-CPS Program 4. Mechanisms of Remote Influences • 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)

33. Lag correlation between Nino SST and tropospheric temperature (Chiang and Sobel 2002)

34. 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;

35. 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.

36. 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.

37. An example of a springtime AMI field campaign (the EPIC2001 model) EGEE CRUISES Climate Transect: enhanced soundings and surface observations Airplane dropsondes AMMA 2006 Ron Brown ATR with dropsondes o o o o o o o o o o o o o o o o o o o o o o o o o o o o Enhanced PIRATA array o o o o AMMA Surface Flux mooring Surface drifters CMM array Lagrangian floats ATLAS moorings ADCP mooring Ron Brown Section SOP-I

38. 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.

39. Program Components • Process Studies • Enhanced Monitoring • Modeling • Diagnosis

40. Enhanced Monitoring (courtesy of AMMA)

41. 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

42. Diagnostics • Global reanalyses: errors and biases • Satellite data: statistics of convective structures (ISCCP, TRMM, CLOUDSAT), aerosol (TOMS, GOES, MODIS), water vapor (NVAP, GOES, AQUA)

43. 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

44. 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

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