Cloud Resolving Model Simulation

The movie shows a run of the Cloud Resolving Model on a doubly periodic, 1024km by 1024km horizontal domain. The colors represent the surface temperature, and the white contours are isosurfaces of condensate amounts (liquid and ice) - animation source Caroline Muller/O'Gorman Group

GOAL:
General Circulation Models, or GCMs, used for climate prediction have a typical grid size of about 100km. This is much larger than the size of clouds, and therefore these models are too coarse to resolve clouds and convective-scale processes, such as condensation and concomitant latent hshare them with us...eat release. Convective-scale processes need to be parameterized, and the different parameterizations used in different GCMs are a large source of uncertainty in climate change predictions.

We use a Cloud Resolving Model (CRM) which runs in more idealized setting with a finer resolution (for instance in this movie, the domain is doubly periodic in x and y, and the horizontal resolution is 4km), to investigate cloud-related processes and provide guidance for parameterizations in GCMs.

MODEL:
The model that we use is the System for Atmospheric Modeling, also known as SAM, and was developed by Marat Khairoutdinov and colleagues. In the movie, we can clearly see that the domain contains several convective regions where clouds form.

In the early stage of convective regions, warm sea surface temperature anomalies yield warm, lighter near-surface air that starts rising. The ascending air cools as it reaches higher altitudes, and its water vapor starts to condensate into liquid droplets (or ice). The droplets become cloud and rain (depending on size and velocity). In the later stage of the convective life cycle, the rain that precipitates out to the surface partly reevaporates, thereby cooling the surface. This evaporation-driven cooling explains the cold surface temperatures that can be observed in the movie below tall, well-formed clouds.

OUR RESULTS:
Precipitation extremes, both wet (floods) and dry (deserts), have many societal impacts. In recent work, we used the CRM to investigate how precipitation extremes respond to warming. We found that the strongest rainfall rates increase following the low-tropospheric water vapor, at a rate of about 5.7% per Kelvin of warming (see Environ. Res. Lett. paper at http://www.mit.edu/~mullerc/Papers/OGormanMullerERL2010.pdf). We were able to account for this rate of change using an energetic analysis (see J. Clim. paper at http://www.mit.edu/~mullerc/Papers/2010Mulleretal_CRM.pdf).

Understanding the response of the hydrological cycle to climate change is a major challenge, and the subject of intense research.

Category:

Science & Technology

Tags:

• MIT
• EAPS
• PAOC
• Atmospheric
• Dynamics
• High-Resolution
• Convection
• Modeling

[usamamath]

@carolinemuller123

Hello, what model is this ? WRF ? and how did u do this movie ? with MATLAB ?

Thank you

[carolinemuller123]

@outlawis1337

Glad you like it!

The model uses a time step of 10s or less to satisfy the Courant–Friedrichs–Lewy condition. But the movie only shows snapshots taken every 100s.

Yes the grid is cubic, with a horizontal resolution of 4km (in the x and y directions), and with 64 vertical levels (first level at 37.5 m and grid spacing gradually increasing from 80 m near the surface to 400 m above 5 km).

Good luck with your masters thesis!

[outlawis1337]

Impressive! is this rendered in realtime? If so, did you used a cubic grid?

I'm asking, cause I want to make something similar for my masterthesis

best regards