MOTIVATIONS

It is a well established fact, that lakes play an important role on the local weather, even at a regional scale for larger lakes, and thus on climate. The hydrological regime of lakes is a function of current climate that makes efficient to use them as indicators of paleoclimate. The large lakes are crucially important for regional economies, so that their ecological state changing under climate evolution and anthropogenic impact is of strong interest.

The interaction between atmosphere and lakes is still represented in a rudimentary way in mathematical models of weather and climate. Until recently (before the pioneering work by Bonan in 1995) many studies of this interaction have been based on one-way coupling, i.e. lake models running with precomputed (measured) atmospheric forcing and atmospheric models using oversimplified surface scheme specifications for lake-rich regions.

Currently, the horizontal grid spacing of atmospheric models allows a number of lakes to be explicitly resolved. Hence, physically-sound lake parameterizations are needed in numerical weather prediction (NWP) and climate models. However, these parameterizations must be computationally efficient, especially in NWP. A reasonable compromise between these two requirements is 1-D lake models. A number of studies has proven that they are satisfactory applicable for a wide range of lakes.

At present, many lake models have been embedded to surface schemes of atmospheric models (Bonan, 2002; Mironov, 2008; Goyette et al., 2000; etc.). These models cover a range of formulations among which we find 1-D resolving and models with parameterized vertical temperature profile (Mironov, 2008). The resolving models may use either sophisticated eddy diffusivity schemes (typically k-ε or its extensions) or diagnostic formulations, involving dependence on Richardson number.

Despite some intercomparison studies of 1-D lake models for particular lakes (i.e. Perroud and Goyette, submitted), there is still a large degree of uncertainty on what lake model types are optimal for certain environmental applications, and what are the important physical processes, that are crucial to take into account in that models in order to well reproduce the lake-atmosphere interaction.

Recent projects on intercomparison of surface schemes in weather and climate models (PILPS, SNOWMIP, SNOWMIP2) under the auspices of WMO/PCMDI have demonstrated that this kind of study is efficient in answering questions raised above. The LakeMIP project is going to inherit to a large degree the methodologies of these projects.

DESCRIPTION OF THE PROJECT

The main goals are aiming at the identification of the key processes that should be represented in different applications of lake models (e.g. climate and weather simulation, lake physics and ecology), and the development/improvement of their physical parameterizations.

During the first phase of the project (LakeMIP1) the number of participants (lake models) is limited to ten for manageability.

The current list of participants, institutions, countries (models) is as follows:

1. Marjorie Perroud, University of Geneva, Switzerland (Simstrat model)

2. Viktor Stepanenko, Moscow State University, Russia (Viktor Stepanenko model)

3. Andrey Martynov, Université du Québec à Montréal, Canada (Flake, Hostetler’s model)

4. Dmitrii Mironov, Deutscher Wetterdienst, Germany (FLake)

5. Xing Fang, Auburn University in Alabama, USA (MINLAKE96)

6. Klaus D. Joehnk,CSIRO Land and Water, Black Mountain, Canberra, ACT, Australia, (Klaus Joehnk model)

7. Murray Mackay, Environment Canada, Canada (Murray Mackay model)

8. Others !

CITED REFERENCES

Bonan, G. B., 1995: Sensitivity of a GCM simulation to inclusion of inland water surfaces, J. Clim., 8, 2691–2704.

Bonan, G. B., K. W. Oleson, M. Vertenstein, S. Levis, X. Zeng, Y. Dai, R. E. Dickinson, and Z.-L. Yang, 2002: The land surface climatology of the Community Land Model coupled to the NCAR Community Climate Model. J. Clim., 15, 3123-3149.

Mironov D. V., 2008. Parameterization of lakes in numerical weather prediction. Description of a lake model. COSMO Technical Report, No. 11, Deutscher Wetterdienst, Offenbach am Main, Germany, 41 pp.

Goyette, S., N. A. McFarlane, and G. M. Flato, 2000: Application of the Canadian Regional Climate Model to the Laurentian Great Lakes region: Implementation of a lake model. Atmos. Ocean, 38, 481-503.

Perroud, M., S. Goyette, A. Martynov, M. Beniston, O. Anneville : Simulation of multiannual thermal profiles in deep Lake Geneva: a one-dimensional lake-model intercomparison study. Limnol. Oceanogr., 54, 1574-1594.

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