# Presentation: 723647

## Modeling of the South Eastern Pacific Climate: Progress and Challenges

***C. R. Mechoso***
*Dept. Atmospheric and Oceanic Sciences, UCLA, USA*

***Motivation***
***Our recent work on the simulation of the coupled atmosphere-ocean system with CGCM***
***Challenges and Hypotheses***
***VAMOS Ocean-Cloud-Atmosphere-Land Studies (VOCALS)***
***Summary***
- _[www.atmos.ucla.edu/~mechoso/esm](http://www.atmos.ucla.edu/~mechoso/esm)_*            **NCEP January 20, 2006*

## Major features of SEP climate

- Cold SSTs, coastal upwelling
- Cloud-topped ABLs
- Influenced by and influential on remote climates (ENSO)
- Unresolved issues in heat and nutrient budgets
- Important links between aerosol and clouds
- Poorly simulated by atmosphere-ocean GCMs

## Ocean Salinity Section at 88W

**Ocean Salinity Section at 88W**

- 20W

## CGCM Problems: NOAA CFS Model 

**CFS Errors**

**SST**

**Prec**

**CLD**

- The CFS model has significant errors in the SEP.
- There is a meridional shift in ITCZ (top), a warm SST bias (middle), and insufficient stratocumulus cloud cover (bottom).
- These errors adversely affect the skill of CFS climate forecasts (ENSO).
**What model developments are required to alleviate these errors, which are common to most CGCMs?**

##  Work at UCLA on the Simulation of the coupled atmosphere-ocean system with CGCM

- Akio Arakawa** **(1):  AGCM; Cabriel Cazes-Boezio** **(1, 7):  AGCM PBL, Coupled GCM;
- C. Roberto Mechoso (1):  P. I.;
- Chris Hill (3):  MIT OGCM;   Phil Jones (4):  POP;
- Dimitris Menemenlis (5):  MIT OGCM, ECCO;  George Philander (2):  Coupled GCM;
- Joseph A. Spahr (1):  ESMF; Slujia Zhou (6):  ESMF
*Department of Atmospheric and Oceanic Sciences, University of California Los Angeles*
*Program in Atmospheric and Oceanic Sciences, Princeton University*
*Department of Earth, Atmospheric and Planetary Sciences, MIT*
*Theoretical Fluid Dynamics Group, Los Alamos Natural Laboratory*
*NASA/Caltech Jet Propulsion Laboratory*
*Software Integration and Visualization Office, NASA GSFC and Northrop Grumman*
*On leave from Fluid Mechanics and Environmental Engineering Institute, U. of Uruguay*
-  Sponsor:  NASA Earth Science Tech. Off. (ESTO), NOAA PACS** **

## Coupled Atmosphere-Ocean Application in ESMF- Superstructure

## The PBL top is explicitly defined, and its depth is predicted from a mass budget equation, with parameterizations of the mass source due to entrainment and the mass sink due to cumulus mass flux. 

- The PBL top is explicitly defined, and its depth is predicted from a mass budget equation, with parameterizations of the mass source due to entrainment and the mass sink due to cumulus mass flux.
- The treatment of processes near the PBL top (clouds, radiative cooling near PBL top) is more tractable in this framework.
- The variable-depth PBL model is incorporated as an integral part of the GCM vertical structure. ”Horizontal" differencing taken along a coordinate surface does not have to cross the PBL top.
- • Profiles within the PBL can be well-mixed (traditional formulation) or deviate from well mixed structure (new formulation).

**Vertical Structure of UCLA (and CSU) AGCMs**

## PBL Regimes in UCLA-AGCM

**PBL Regimes in UCLA-AGCM**

- Different Regimes

## Hybrid approach to determine turbulence fluxes

- • Effects of large-scale convective eddies are represented by a  bulk PBL parameterization. Their fluxes are determined by interpolating conserved quantities such as moist static energy and total water mixing-ratio from surface to PBL top.
- • Effects of small scale diffusive eddies are represented through a K-closure formulation

*Bulk formulation determines the surface and PBL-top fluxes, *

## Main Components of bulk parameterization

**Main Components of bulk parameterization**

## PBL Test - Composite diurnal cycle during January 

## AGCM

- Observation

- Marengo et. al (2005)

- Mean simulated precipitation in Amazonia
- Mean observed precipitation in Rondonia

## Low-level Cloud Incidence

**Klein-Hartmann analysis**

**Simulation**

**Low-level Cloud Incidence**

- UCLA-AGCM; 5lonx5lat, 17 layer

## Simulations with CGCM(UCLA-AGCM/MIT-OGCM)

- • **AGCM** (Low-resolution): 5X4, 14+4 layers.
-               (High-resolution): 2.5X2, 28+4 layers.
- • **OGCM** 1X0.3 (near Eq.), 1X1 (mid and high lat), 46 layers.

**Hindcasts with CGCM**

-   Initial conditions:  March 5th, June 5th
-   5 - member ensemble over 9 years (1993-2002)
-   15 - month long runs; 180 runs
-   Initial atmospheric states:  From long AGCM run with clim. SST.
-   Two initial ocean states: 1) JPL’s ECCO Project; 2) Long OGCM 	 	run with prescribed climatol. wind stress and SST.

## Surface wind stress (Eastern Pacific)

**Observed**

**Simulation**

**Simulation**

**Observed**

**Simulation**

**Simulation**

**Low-Resolution**

**High-Resolution**

**Surface wind stress (Eastern Pacific)**

**July**

**January**

- • High resolution results very closely match to COADS analysis.

## (4S-4N) anomalies

**SST and**
**Zonal wind stress **
**(4S-4N) anomalies**
- • ENSO like signal exists

## DJF 1997 Forecast from March 5, 1996

**DJF 1997 Forecast from March 5, 1996**

## DJF 1997 Forecast from June 5, 1996

**DJF 1997 Forecast from June 5, 1996**

## DJF 1998 Forecast from March 5, 1996

**DJF 1998 Forecast from March 5, 1996**

## Forecasts from early March (top) and early June (bottom)

- Correlations with Nino 3.4

## UCLA-AGCM coupled to MIT-OGCM

**UCLA-AGCM coupled to MIT-OGCM**
- Low-resolution AGCM (5X4; 14+4 layers)**       **

**Simulated annual mean SST**

**Observed annual mean SST**

- • Cold tongue is asymmetric relative to the Equator. Equatorial West-East SST gradient is realistic.
- • Double ITCZ in both Pacific and Atlantic Oceans.

## UCLA-AGCM coupled to MIT-OGCM

- High-resolution AGCM (2.5X2; 28+4 layers)**       **

- • Cold tongue is asymmetric relative to the Equator. Equatorial West-East SST gradient is realistic.
- • Double ITCZ in both Pacific and Atlantic Oceans still exist, but SST errors are smaller.

**Simulated annual mean SST**

**Observed annual mean SST**

## Challenge: The doubled ITCZ biasA synthetic view of this problem  is still elusive ...

- 	The consensus is that the bias is at least partly due to the underestimation of stratocumulus cloud cover by the AGCM, which results in too warm SSTs in the eastern tropical oceans. Other strategies for improvement have shown to be AGCM-specific, with different effects in different models:
**Increasing cumulus friction**
**Changing the cumulus parameterization**
**Increasing the re-evaporation efficiency**
**Improving the advective transport of water vapor above the PBL**
**Increasing both horizontal and vertical resolution**

## Surface wind stress

**Surface wind stress**

**Observed**

**Simulation**

**Simulation**

**Observed**

**Simulation**

**Simulation**

**Low-Resolution**

**High-Resolution**

**July**

**January**

## How to approach the doubled ITCZ bias? 

- 	Since  the double ITCZ bias is common to most CGCMs, one approach is to narrow down on large-scale aspects such as improving the too weak trades in the simulations.
- The simulated zonal momentum budget in the tropics has errors.** **Westerly momentum gained by the atmosphere through surface easterlies must be removed at some level above, otherwise the vertically integrated atmosphere tends to become more dominantly westerly until the easterly surface stress vanishes.
- It is possible that this removal is not well simulated due to : (a) too weak simulated standing waves, and/or (b) too weak or missing momentum redistribution from the surface to upper levels.
- 	**In this regard, a more drastic improvement may require substantial model development.  This has to be guided by the results of an in-depth analysis of model performance, particularly of the mechanisms for maintenance of zonal momentum.**

## Hadley circulation: momentum and heat transports

**    ****Ocean heat **
** ****transport**

**Dynamical warming by subsidence**

**Radiation**
**solar down**
**infrared up**

_**Hadley circulation: momentum and heat transports**_

**Latent heating in convective rain**

**warm**

**Heat transport**
**by transients**

**Westerly momentum transport (eddies)**

**Trade winds**

## The increased severity of the ITCZ bias in coupled models suggests that the OGCM contributes to it. 

- The Peru Current is one of the major eastern-boundary, subtropical upwelling regimes.  There is an equatorward surface geostrophic flow and a poleward undercurrent that is strongest in summer. This circulation pattern of the ocean is baroclinically unstable and develops mesoscale eddies that extend the current system several hundred km offshore.
- The eddies provide shoreward heat and material transport that balance the upwelling supply of cold water and the air-sea heat exchange. These structures are reinforced by standing eddies associated with alongshore coastline and bathymetric irregularities.

## Issues in ocean transports

- 2001

- 2002

- 2003

- Annual-mean heat flux **into** ocean ~ 30 W m-2 at 1500 km offshore under persistent low cloud!
**How is this net warming at the surface balanced by ocean heat transports?**

- (20S 85W)

- Weller

## Hypotheses and Challenges

- H: AGCMs have difficulties in maintaining the zonal momentum budget of the vertically integrated atmosphere over the tropical oceans.
**C: Can these difficulties be overcome?**
- H: Oceanic mesoscale eddies play a major role in the transport of heat, and biogenic species, from coastal upwelling regions to further offshore.
**C:  Can numerical models of the ocean simulate such transports?**
- Upwelling, by changing the physical and chemical properties of the upper ocean, affect aerosol precursor gases and aerosol size distribution in the PBL. Variability in aerosol and cloud droplet concentration affect the variability in cloud cover and albedo on timescales of days and lengthscales of a few hundred kilometers.
**C: Can numerical models of climate simulate such variability?**

## VOCALS

**The overall goal of VOCALS is to develop and promote scientific activities leading to improved understanding, model simulations, and predictions of the southeastern Pacific (SEP) coupled ocean-atmosphere-land system, on diurnal to interannual timescales. **
- The science objectives of VOCALS include:
-   	Improving the understanding and simulation of** aerosol-cloud-drizzle interactions **in the** ****marine **PBL.
-     Improving the understanding and simulating of** the ocean budgets of heat, salinity,  and nutrients **in the SEP.
-    Characterizing, determining, and alleviating the **systematic biases** of atmosphere-ocean GCMs in the SEP.
-   	Elucidating and understanding **interactions between the SEP climate and remote climates**.

## Elements  of VOCALS in the SEP 

- SEP has research-grade buoys and strategic island
- Strong gradients in the climate system
- Imprints of aerosol and mesoscale ocean variability in the structure of PBL clouds
- Highly committed regional partners, primarily in Chile but also in Peru and Ecuador
- Possible European presence: PRIMO

## VOCALS Program

**VOCALS - REX**
- Airborne: NCAR C-130 (and others)
- SHIP: Ron Brown (and others)

**VOCALS - Modeling**
- GCMs: NCEP, NOAA, GFDL, UCLA
- RCMs: WRF, ROMS

## VOCALS-REX

**VOCALS-REX**
**Aircraft: **
**NCAR C130**
**Ships: **
**NOAA Ron Brown**
**Chilean**
**October 2007**

## VOCALS: Regional Coupled Modeling

- The scientific strategy uses data gathered in VOCALS-REX to establish eddy and frontal structures and assess model verisimilitude, and then uses the models to establish the eddy heat flux consequences.
- The aim is to provide the appropriate framework for understanding regional, small-scale processes and heat budgets.

- (From A. Miller)

## VOCALS aims to develop a Modeling Framework for Interannual Climate Predictions

**VOCALS aims to develop a Modeling Framework for Interannual Climate Predictions**

**ESMF Infrastructure**

- AGCM:  Atmosphere General Circulation Model
- OGCM:  Ocean General Circulation Model

**AGCM**

**OGCM**

- CAM
- NCEP
- GFDL
- UCLA

- POP
- MIT

**ROMS**

**RAM**

## SUMMARY

- The CGCM shows skill in ENSO hindcasts from months in advance.  The skill is higher for the UCLA AGCM/MIT OGCM combination with ECCO initial conditions for the ocean. Cases from early June have substantially higher skill than form early March.
- Biases such as the double ITCZ are reduced but not eliminated in the CGCM simulation. Higher resolution in the ocean helps.
- Approaches to further reduction of the biases are proposed, for both the AGCM and OGCM.
- The broader problem of the tropical Pacific climate, including the effect of aerosol, motivate VOCALS.  This is an international program with a field component scheduled for October 2007 and supported by a modeling component that emphasizes regional coupled models.
- Upgrades in the PBL parameterization of the UCLA AGCM have improved simulation of fluxes at the ocean’s surface and stratocumulus. The model has been coupled to the MIT OGCM and LANL POP using ESMF services.

## SUMMARY

- Upgrades in the PBL parameterization of the UCLA AGCM have improved simulation of fluxes at the ocean’s surface and Scu. The model has been coupled to the MIT OGCM and LANL POP using ESMF services.
- The CGCM shows skill in ENSO hindcasts from months in advance.  The skill is higher for the UCLA AGCM/MIT OGCM combination with ECCO initial conditions for the ocean. Cases from early June have substantially higher skill than form early March.
- Biases such as the double ITCZ are reduced but not eliminated in the CGCM simulation. Higher resolution in the ocean helps.
- Approaches to further reduction of the biases are proposed, for both the AGCM and OGCM.
- The broader problem of the tropical Pacific climate, including the effect of aerosol, motivate VOCALS.  This is an international program with a field component scheduled for October 2007 and supported by a modeling component that emphasizes regional coupled models.

## Structural differences between PBL implementations

- • Vertical coordinate surfaces are fixed
- • Profiles may deviate from well mixed ones.
- • Processes near the PBL top are difficult to simulate properly (even with moderately high vertical resolution).
- • It is difficult to keep track of budget of PBL quantities.
- • Thus, a realistic simulation of PBL cloud incidence may be difficult.
- • It is difficult to simulate PBL-free atmosphere exchange realistically.

**Vertical Structure of GCMs (e.g., NCAR, ECMWF, NCEP****)**