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Dynamic Balance of Cloud Vertical Velcoty

Dynamic Balance of Cloud Vertical Velcoty. Yuanfu Xie FAB/GSD/ESRL. A variational balance (LAPS). Written in a Lagrangian function,. Poisson Equation for λ (McGinley 1987). Take a perturbation of the Lagrangian function in terms of u, v, ω ,. Poisson Equation for λ ( cont ’).

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Dynamic Balance of Cloud Vertical Velcoty

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  1. Dynamic Balance of Cloud Vertical Velcoty Yuanfu Xie FAB/GSD/ESRL

  2. A variational balance (LAPS) Written in a Lagrangian function,

  3. Poisson Equation for λ (McGinley 1987) Take a perturbation of the Lagrangian function in terms of u, v, ω,

  4. Poisson Equation for λ (cont’) Integration by part yields Or,

  5. Issues with the Poisson Eqn • Need a efficient 3D solver; • It is complicated for vertical finite difference as vertical levels are non-uniform (McGinley 1987 uses a uniform grid; unfortunately, LAPS balance uses a uniform grid even it is not (e.g. LAPS_ci domain)!! See qbalpe.f line 2878-2881); • LAPS uses a relaxation method: • A relaxation is convergent but extremely slow; • Most iterations tries to push shorter waves except the first few iterations; • It usually results in high frequency noise (balance package shows a lot of noise in divergence). • STMAS multigrid is a designed scheme for this; • A simple trick to see if the minimization is right.

  6. Evidence of Incorrect vertical finite difference formulation New adjustment of wind LAPS balance

  7. A simple trick • After LAPS/STMAS analysis, the balance package adds cloud ω to wind. Instead of a 3D Poisson solver, a simple scheme is used to adjust wind

  8. An Approximation of the Balance • It keeps all wind information from previous analysis except adding vertical gradient of cloud omega to wind divergence; • Fish package can be easily and efficiently used for solving these 2D Poisson equations; • A quick verification for improving the forecast scores; • An simple quick fix of the balance before a more sophisticated implementation.

  9. Experiments at the CI Domain • There are two STMAS runs set on the convective initiation domain, (stmas_ci and stmas_ci_cyc) for experimenting; • The two runs are identical except the cloud and omega adjustment • Linear increment for cloud omega analysis; • Smoothed cloud omega; • Added cloud omega to the horizontal wind. • LAPS uses the linear increment and smoothed cloud omega and is better than STMAS HWT forecasts without adding the cloud omega; • More experiments are needed to evaluate the simple scheme comparing to the linear increment cloud omega and smoothed scheme.

  10. Forecast at 2011-09-04 00Z ETS Bias

  11. Forecast at 2011-09-04 00Z ETS Bias

  12. Forecast at 2011-09-04 00Z ETS Bias

  13. Divergence, cloud omega and reflectivity plots: 2011-09-04 06Z

  14. Preliminary Conclusions • LAPS balance uses an incorrect finite difference formula in Poisson equation (vertical) if the vertical is non-uniform; • The simple trick shows the minimization of balance package indeed improves ETS; but this simple trick brings in too strong reflectivity forecasts; • It adjusts wind only but not other fields and is too simple; • It shows that the relaxation scheme in the balance package can be improved; • A more sophisticated multigrid minimization technique should be considered in STMAS development. • The wide forecast bias may also warn us on the cloud omega computation; some sensitivity study is needed; • A correct 3D Poisson equation and multigrid will be applied in STMAS for improving the balance!

  15. Evidence of inconsistency between analysis anf WRF forecast 0

  16. Vertical Finite Difference • When a uniform vertical grid is used, a center finite difference is correct, such as for a stagger grid, for example, a first derivative, • This is incorrect if the vertical is not uniform.

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