# Presentation: 685644

## Mars General Circulation Model Intercomparison

- Participating Models:
- GFDL John Wilson
- Hokkaido Yoshiyuki Takahashi
- LMD Francois Forget
- Caltech/JPL (WRF) Michael Mischna
- CCSR/NIES  Takeshi Kuroda
- York University (GM3) Youseff Moudden
- MPI (MAOAM) Alex Medvedev

- Second Mars Atmosphere Modeling and Observations Workshop, Granada, Spain, Feb. 27, 2006

## ** Log-pressure vertical coordinate

| Model  | Horizontal Resolution | Vertical Levels  | Dust Visible optical properties |  |  |
| --- | --- | --- | --- | --- | --- |
| GFDL | 60x36  | 22 | w=0.92
g= 0.65 |  | As for LMD |
| LMD | 65x49 | 32 | w=0.92
g= 0.55 |  | 3 IR channels |
| Hokkaido | 120x60 | 48 | Ockert-Bell |  | As for LMD |
| MAOAM | 32x36 | 70/100 ** |  | No CO2 cycle  |  |
| CCSR | 64x32 | 33 | Ockert-Bell |  | 9 visible
10 IR bands
 |
| WRF | 64x36 | 25 | w=0.92
g= 0.55 |  | Dust IR: Haberle  |
| York | 40x20 | 102 |  | No CO2 cycle |  |
| Ames  | 60x36 ?? | 24 | Ockert-Bell |  |  |
|  |  |  |  |  |  |

## Requested Model Data 

-    (optional diurnal composites: for thermal tides)
- Diurnally-composited Ps, Ts and surface stress fields (12-24x/sol)
- Model data centered on 3 Seasons:
-       *L**s*= 90, 180, 270
- 3 Dust Cases: 
- = 0.2, 1.0 and “mgs scenario”
-  zonally uniform dust; ideally with vertical distribution given by Conrath parameter 0.01
-  Aerosol optical properties vary between models.

**Requested Model Data**

## Aims

- Assess qualitative aspects of the zonal mean circulation;                          	winds, temperature and mass transport streamfunction
- Influence of horizontal and vertical resolution; particularly for surface stress.
- Impact of different radiation parameterizations

## Models all indicate a warm bias in polar temperatures during the Ls=180 season with respect to MGS TES observations. 

- Surface Temperature:  2 models didn’t enforce TCO2 for surface temperatures
- 1 model had very strong solar heating: evidently from solar absorption by dust. This had a major influence on all zonally-averaged fields.
- 1 model apparently had a deeper dust distribution than suggested
- Surface stress magnitudes are quite variable in strength and location
- Models all indicate a warm bias in polar temperatures during the Ls=180 season with respect to MGS TES observations.

## o    τ=0.2

- o    τ=0.2
- *     τ=1.0

## Semidiurnal Surface Pressure Amplitude

- Results from model intercomparison; 2003 Granada meeting

- Tide amplitude vs dust column optical depth:
- Tide is a measure of globally integrated thermal forcing due to surface heat flux and  absorption by dust

## τ= 1.0

- τ= 1.0
- τ= 0.2

## *  τ =0.2

- Summary of Semidiurnal Tide Amplitude
- 3 Seasons  and 2 dust loadings

- *  τ =0.2
- o  τ= 1.0

-     *L**s*=90                *L**s*=180                    *L**s*=270

## Slide 10

## Slide 11

## Slide 12

## Influence of Dust on Surface Temperature

- Tsfc :       Tsfc( = 1)  - Tsfc( =0.2)
*L**s*= 270

- Dust increases minimum (am) temperature

- Dust decreases maximum (pm) temperature

- weak positive greenhouse effect:  3-5 K

## Dust influence is a function of surface thermal inertia:  strongest when TI is smallest.

## 200

**Notes:**
All models show a warm temperature bias at low levels in the polar regions

## 200

- 180

## 180

## 20

## Slide 19

## Slide 20

**Notes:**
Influence of vertical resolution:      more prominent easterly jet with higher vertical resolution:   York has relatively low horizontal resoution

## Slide 21

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## Temperature and Streamfunction

- Ls= 180

- Ls= 270

- Streamfuncton:  108 kg/s

## Slide 30

## Ls= 270;   τ= 1.0

- WRF

- Japan

- LMD

*Temperature and Streamfunction*
*L**s*= 270;   τ= 1.0

## Slide 32

## Slide 33

## Thermal Tides

- Solar forcing;   heat transport from the surface
-                absorption of solar radiation by aerosols
- Propagation:   Influence of zonal mean circulation
- Dissipative process:  provides a means of wave influence 	on the zonal mean circulation
- First-order agreement between all models except MAOAM:
- Large amplitude tide forcing and dissipation in the MAOAM model is evidently responsible for strong polar temperatures

## Slide 35

## Surface Stress

- Examined plots of the spatial distribution of the maximum surface stress in a diurnal composite time series
- Surface stress will vary with model horizontal and vertical resolution and boundary layer parameterization

## Slide 37

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## Slide 42