Numerical modeling of energy and mass exchange between the atmosphere and inner land water bodies ENVIROMIS-2008, 3 of July, 2008, Tomsk, Russia V. M. - презентация

1 Numerical modeling of energy and mass exchange between the atmosphere and inner land water bodies ENVIROMIS-2008, 3 of July, 2008, Tomsk, Russia V. M. Stepanenko, D. N. Mikushin Scientific Research Computing Center of Moscow State University (SRCC MSU) The work is supported by SKIF project and RFBR grant N

2 The effects of water reservoirs on atmosphere breezes and associated tracer transport breezes and associated tracer transport severe snowfalls over large lakes in winter severe snowfalls over large lakes in winter Weather Climate the change of regional hydrological system due to global warming emission of methane by Siberian lakes emission of methane by Siberian lakes

3 Numerical water reservoir models in coupled lake – atmosphere studies 1) 3-dimensional (~oceanic) 2) 2-dimensional vertically averaged (Shlychkov, ) averaged in one lateral direction (CE-QUAL x.x model) 3) 1-dimensional single-column (GOTM model (Burchard et al.), Lake model, V. M. Stepanenko & V. N. Lykosov, 2005); laterally averaged models (O. F. Vasiliev et al., 2007) – applicable in many applications 4) ½ - dimensional models – the vertical profiles of temperature, salinity etc. are parameterized (Flake model, D. V. Mironov et al., 2006) – high computational efficiency application in operational forecast

4 Lake model (SRCC MSU) the equation for the horizontally averaged temperature: E-ε parameterization of turbulence; the equations for horizontal velocities: multilayer ice, snow and soil models (Volodina et al., 2000); the salinity/hydrosol transport the parameterization of skin - laminar layer at the surface (Fairall et al., 1996) turbulent dissipation Coriolis force horizontal pressure gradient force the friction of flow on vegetation gravitational sedimantation

5 Willis-Deardorff experiment (1974) Setup for numerical experiment: horizontally homogeneous water layer of infinite depth; linear initial temperature profile with the lapse rate - 1ºС/10 m; the constant sensible heat flux at the surface 100 W/m 2 (cooling); the horizontal velocities 0 m/s; Coriolis force is neglected

6 The terms of turbulent energy budget Lake model 1) E-ε model by Canuto et al., ) LES results (Mironov et al., 2000) The k-closure The shortcoming: does not take into account non-local effects of convective thermals does not reproduce uniform temperature profile

7 The counter-gradient heat transport by convective thermals Temperature flux (Lake model) Temperature flux (other models and LES) (Soares et al. 2004)

8 Surface temperature from Lake model and from observations Kossenblatter lake, Germany, June, 1998 Tiksi lake, Siberia, July, 2002 Monte-Novo lake, Portugal,

9 The temperature in Mogaiskoe reservoir Surface temperature time series, – Vertical temperature profile, 01:00, Important features not taken into account: Lengmuir circulations; Lengmuir circulations; non-uniform horizontal distribution of physical properties. non-uniform horizontal distribution of physical properties.

10 Lake Alqueva (Portugal)

11 Sensible heat flux ( Flake and Lake) lake Alqueva, summer 2007

12 Sensible heat fluxes (Flake and Lake) Averaging interval TESSEL+ Flake Lake Observati ons 15 days29.8 W/m W/m 2 22 W/m W/m 2 55 days30 W/m 2 27 W/m W/m W/m 2 Source code of Lake model and data for verification

13 Mesoscale atmospheric model The code of Nh3d model (Miranda & James, 1992) 3-dimensional 3-dimensional σ-coordinates σ-coordinates non-hydrostatic equation set non-hydrostatic equation set warm cloud microphysics warm cloud microphysics ISBA soil model ISBA soil model New features: shortwave (Clirad-SW) and longwave (Clirad-LW) radiation parameterization lake model lake model aerosol transport scheme aerosol transport scheme

14 Aerosol transport scheme - turbulent diffusion (1-st order closure), - Raileigh damping term Boundary conditions: at all boundaries Numerical scheme: Smolarkiewich monotonous scheme spatial discretization – 2-d order temporal discretization – 2-d order - aerosol source, - sedimentation speed,

15 Aerosol distribution in test case Ob river Resolution: x = y = 3.7 km 21 σ – levels Hanty-Mansiisk region Time integration t = 5 sec 8 days Breezes develop over water bodies and transport the tracer far from source even in calm synoptic conditions

16 The work underway: aerosol emission from Norilsk Lake Yarato Norilsk: Emission of Zn, Cu, Hg,… lakes

17 Future development of mesoscale model realization of Smolarkiewich scheme for all positive definite prognostic variables (specific humidity, cloud water etc.); incorporation of physical parameterizations of aerosol transformation in atmosphere, e.g. interaction with cloud and precipitation processes; development of cloud and rain/snow microphysics in the model inclusion of soil and snow models of Institute for Numerical Mathematics RAS (with methane processes) Future development of lake model methane ebullition parameterization

18 Parallel implementation aspects Explicit scheme! FFT + Eulerian elimination Cycles with independent iterations % - the solution of elliptical equation for geopotential (via horizontal FFT) % - the integration of thermodynamic equation (including radiation model) % - the solution of continuity equation % - computation of turbulent transport % - the integration of momentum equation 6. 6 % - the calculation of momentum fluxes 7. 5 % - the integration of water vapour and aerosol transport 8. 5 % - the soil, vegetation and lake models

19 Acknowledgements To V. N. Lykosov has initiated this research and supports it; Rui Salgado, Maria Grechushnikova and Eugenia Nikolskaya provided the observational data Pedro Soares provided the code of counter- gradient convection parameterization Dmitrii Mironov initiated useful discussions

20 Thank you! Your questions are welcome!

21 Application in education