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<h2>Towards the new generation of Earth's System Modeling</h2>
<i>Cristina Stan</i><p></p>

<img src="/images/research/stan1.png" border=0 align="right">

It has become an imperative that an accurate simulation of the observed features of the climate system requires numerical models allowing physical representation of small-scale processes. A growing body of evidence suggests that improvements in the conventional parameterization used for representation of small-scale processes in the traditional climate models are producing diminishing returns. Parameterizations are based on statistical assumptions, do not account for interaction between scales, and require ad-hoc tuning to compensate for the missing processes. Cloud processes and boundary-layer turbulent mixing in the atmospheric component, mixing by eddies in the ocean component and floe-scale physics in the sea-ice component of the climate models represent small-scale processes which in the current generation of climate models are represented through parameterizations. Among these, clouds introduce the largest source of uncertainty in climate simulations (Solomon et al. 2007). <p></p>

Atmospheric models designed to include cloud processes on their natural scales are emerging  (see NICAM, Tomita et al. 2005) but they have been run only in the un-coupled mode and their computational costs prohibit long-term simulations. 
A computationally feasible solution is offered by the Multi-scale Modeling Framework (MMF) approach developed by the CMMAP research team (Khairotdinov and Randall 2001, Grabowsky 2001).  Promising results from the AMIP-type simulations with SP-CAM and the availability of enhanced computer power at CISL, NCAR recommended MMF as the way forward in redesigning the traditional climate models with fewer sub-grid scale parameterized processes. Leveraging the CMMAP experience of implementing MMF in the NCAR Community Atmospheric Model (CAM), Cristiana Stan, a research scientist at the Center for Ocean-Land-Atmosphere Studies (COLA) in Calverton, Maryland built a new version of the NCAR Community Climate Model, version 3 (CCSM3) to include a representation of cloud processes through a two-dimensional cloud-process resolving model (CRM) embedded in each grid column of the atmospheric component model. The new version of the model is referred to as SP-CCSM. 
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<img src="/images/research/stan2.jpg" border=0 align="left">

Improvements in the 20-year simulation with SP-CCSM are notable with respect to both mean climate and its variability.  The root-mean-square errors in the simulation of the seasonal and annual mean distribution of rainfall are smaller in the model with the embedded CRM than in the model with a conventional parameterization of cloud processes. In the tropics, the model with a conventional parameterization of cloud processes is affected by the "double-ITCZ" problem in which the Inter-Tropical Convergence Zone (ITCZ) appears in both the summer and winter hemispheres; whereas the new model simulates the observed structure of the ITCZ. The results show that changes in the profile of convective heating in the deep tropics impact the vertical distribution of the temperature in the ocean. 

The explicit representation of cloud processes improves the model skill to reproduce the intraseasonal-to-interannual variability observed in nature. The period of El Niño and the Southern Oscillation (ENSO) in the simulation becomes more realistic and the ENSO-teleconnection patterns resemble their observed counterparts. The model with parameterized cloud processes is unable to simulate the dominant mode of intraseaseasonal variability of the tropical troposphere, the Madden-Julian Oscillation(MJO). The SP-CCSM captures the MJO modes, and this fact suggests that MJO is the component of the atmospheric stochastic noise that contributes  to the irregularity of ENSO. <p></p>

The most notable result of this experiment is that all of these improvements were obtained without re-tuning the model. While it may be fortuitous that the results were, on balance, positive, this experiment is a valuable piece of evidence for the importance of cloud processes to the climate system. 
Results from this study appeared in <i>GRL</i> volume 37, 2010 (DOI: 10.1029/2009GL040822).<p></p>

SP-CCSM and CCSM3 model comparison results
<a href="http://grads.iges.org/stan/SpCCSMT423-CCSMT42sld1/index.html" target="_blank">may be viewed at this link</a>.<p></p>

<b>References</b><ul>
<li> Grabowski,W., <i>J. Atmos. Sci</i>. <b>58</b>, 978 (2001).</li>
<li> Khairoutdinov, M. and D. A. Randall, <i>Geophys. Res. Lett</i>. <b>28</b>, 3617 (2001).</li>
<li> Solomon et al., <i>Fourth Assessment Report of IPCC</i>, Cambridge University Press, Cambridge (2007).</li>
<li> Tomita, H., H. Miura, S. Iga, T. Nasuno, and M. Satoh, <i>Geophys. Res. Lett</i>., 32, L08805, doi:10.1029/2005GL022459 (2005).</li></ul>


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