Large eddy simulation studies on convective atmospheric boundary layer
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1 Large eddy simulation studies on convective atmospheric boundary layer Antti Hellsten & Sergej Zilitinkevich Finnish Meteorological Institute
2 Outline Short introduction to atmospheric boundary layer (ABL) and convective atmospheric boundary layer (CBL) CBL research problems we are currently studying using LES An example: isolation of convective structures and estimation of their contribution to fluxes and variances
3 Introduction to ABL Atmosphere, hydrosphere, lithosphere and cryosphere are coupled through turbulent atmospheric boundary layers ABLs (dark green lenses) ABLs include 90% of biosphere and almost entire anthroposphere
4 Introduction to ABL and CBL Atmospheric boundary layer (ABL) is defined as the layer next to the ground surface in which ground directly influences the atmosphere. The most influential effects from the ground surface are vertical fluxes of momentum, heat and moisture. Also fluxes of various admixtures, both natural and anthropogenic are important ABL-processes. The depth of ABL can vary from just tens of meters in very stable conditions to several kilometers in very unstable i.e. convective conditions (CBL). Unstable convective conditions take place when ground surface is warmer than air above it.
5 Introduction to ABL and CBL ABL usually develops against stably stratified free troposphere Stability is determined from potential temperature distribution θ(z) θ is the temperature that a system of air gets when brought adiabatically to a reference height (typically ground level) Stability classes: stable: nocturnal stable or long-lived stable near neutral: conventionally or truly neutral unstable (convective): shallow and deep convection
6 Stability Stability is characterized by Obukhov length L u3* u* L= = g F S w* 3 zi with Deardorff's convective velocity scale 1 /3 w * = g F S z i where u* is the friction velocity, κ is von Karman constant, β is the coefficient of thermal expansion, g is the acceleration of gravity, Fθs is the kinematic surface heat flux and zi is the inversion height (CBL depth).
7 Structure of convective boundary layer Structure of CBL with mean geostrophic wind of 18 m/s and surface heat flux of 128 W/m2 leading to -zi/l=5.15. Spatially averaged profiles of kinematic heat flux, potential and in-situ temperatures and wind components.
8 Instantaneous fields CBL with no mean wind, -zi/l ꝏ, and very strong capping inversion. Instantaneous snapshots on a vertical plane: potential temperature (top) and vertical velocity (bottom).
9 Convective structures 20-minute time averaged fields in the same situation as on the previous slide: potential temperature (top) and vertical velocity (bottom).
10 Convective structures and stability Stability, -zi/l is the main parameter governing the CBL Large values result in cellular convection as seen in a) and b) An intermediate state is found for c) (-zi/l 10) For smaller values the formation of convective rolls are observed in d)
11 Convective structures and stability
12 CBL research problems we are studying using LES The main motivation is to get better understanding and data for developing new and better theories and parameterizations for numerical weather prediction models and climate models. Currently we study the following CBL research questions using LES: Scaling and similarity analysis of CBL Contribution of coherent structures to fluxes and variances Spectral energy transfer in CBL And we are planning to study in near future: CBL growth rate Influences of baroclinic shear
13 Contribution of coherent convective structures to fluxes and variances
14 Contribution of convective structures Our hypothesis is that buoyancy produces mainly large smooth convective structures (like e.g. Benard cells), and that these structures create smallerscale turbulence mostly by their own local shear production. The scale of convective structures is proportional to zi and that of the background turbulence should be smaller than zi.
15 Contribution of convective structures Turbulence behind convective structures (background turbulence) can be parameterized by eddy-viscosity approach in large-scale models Convective structures are very non-local by nature Therefore they cannot be parameterized by the eddyviscosity approach They are usually parameterized separately by so called mass-flux approach Because these two forms of motion are parameterized separately, we should separate their contributions to fluxes also in LES results to better develop new parameterizations and to assess existing ones
16 Contribution of convective structures Isolation of convective structures by means of shorttime averaging: As observed e.g. from cumulus clouds, structures seem to have quite long lifetime compared to most of the background turbulence. However, there is no proper spectral gap. How to select proper averaging time T? Numerical experiments show that T=0.5zi/w* seems quite a promising choice. First application to no mean wind situation, -zi/l ꝏ. (not straightforward with mean wind).
17 Contribution of convective structures Some information on the LES of this particular case: Domain size: about 10 km 10 km 2 km Resolution: 10 m in each direction, nodes Periodic BCs in horizontal directions (homogeneity) Initially very strong inversion from 1200 m to 1400 m Simulated physical time 183 minutes Short-time averaging over the last 6 minutes Instantaneous results output at time 180 minutes 256 parallel processes on Cray XT5 Throughput time about 11h
18 Contribution of convective structures Vertical velocity, six-minute averaging, T=0.53zi/w*
19 Contribution of convective structures Potential temperature, six-minute averaging, T=0.53zi/w*
20 Contribution of convective structures Spectra of kinetic energy (left) and temperature variance (right) at z=900 m.
21 Contribution of convective structures Contributions from coherent convective structures and background turbulence to heat flux with averaging time T=6 min or Tw*/zi=0.53 (left). Sensitivity of the decomposition to the averaging time (right) with: T=4 min (dotted), 6 min (solid) and 8 min (dashed).
22 Contribution of convective structures Horizontal velocity-component variance sum <uu>+<vv> (left) and vertical velocity variance <ww> (right).
23 Current status and preliminary conclusions Convective structures dominate the vertical heat flux and the velocity variances except in the surface layer. The short-time averaging STA-approach is difficult to apply to situations with mean wind. I'm currently studying the problem using spatial filtering approaches: Fourier Filter (FF) and Proper Orthogonal Decomposition (POD). FF turned out to be more suitable for this purpose. Now applied also to a mean-wind case with similar conclusions plus that also the momentum flux <uw> is strongly dominated by the structure contribution except in the surface layer.
24 Acknowledgements We want to warmly thank: European Research Council for the PBL-PMES funding Professors Igor Rogachevskij and Nathan Kleeorin at Ben Gurion University, Israel, for many good comments and suggestions. Professor Siegfried Raasch and his group at Leibniz Universität Hannover for providing the PALM LES code.
25 Some spare material
26 The PALM model PArallelised LES Model Leibniz Universität Hannover, Institut für Meteorologie und Klimatologie (IMUK) PALM is a large-eddy simulation (LES) model for atmospheric and oceanic flows which is especially designed for performing on massively parallel computer architectures.
27 Convective structures The same CBL as before. Vertical velocity on a horizontal plane at z=900 m. Instantaneous (left) and 20 min averaged (right).
28 Convective structures Again the same CBL. Vertical velocity on a horizontal plane at z=100 m.
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