Moist thermal sw #390
Moist thermal sw #390
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…ud isn't accumulating
…racers and blows up
…egative vapour/rain
…lePhysics class so that it works with a time-varying saturation curve. Also adding the option for convective feedback to the ReversiblePhysics class.
… fraction of the moist species is converted. Take absolute value in theta initial condition.
…illations between moist species.
…step oscillations) with a fraction that can be time-varying
…g the initial conditions to a file
…of 0.02, fix bug so that beta2 is 1
…s an argument to ReversibleAdjustment, use beta1 as variable name for proportion in InstantRain (in line with ReversibleAdjustment), assign to b in evaluate.
gusto/physics.py
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| dependent on a prognostic field. | ||
| time_varying_saturation (bool, optional): set this to True if the | ||
| saturation curve is changing in time. Defaults to False. | ||
| L (float, optional): The air expansion factor multiplied by the |
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Should we call this L_v instead of L?
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Yes, I think that makes more sense.
| L (float, optional): The air expansion factor multiplied by the | ||
| latent heat due to phase change divided by the specific heat | ||
| capacity. For the atmosphere we take L to be 10, following A.2 | ||
| in Zerroukat and Allen (2015). Defaults to None but must be |
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Just to check, should this be (2015) or (2020) as the comment above is their paper from (2020)?
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Should be 2015 - thanks!
| Defaults to None, in which case the timestep dt is used. | ||
| parameters (:class:`Configuration`, optional): parameters containing | ||
| the values of constants. Defaults to None, in which case the | ||
| parameters are obtained from the equation. |
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This is very nicely commented, thanks!
| water_t_T = total[-1] | ||
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| assert abs(water_t_0 - water_t_T) / water_t_0 < 1e-12, \ | ||
| f'Total amount of water should be conserved by {process}' |
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Test looks really good! My only question is if we should called it test_sw_saturation_adjustment.py instead? (And also rename test_condensation.py as test_saturation_adjustment.py?
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Yes, I think that's a better name. I've changed the name of both tests.
This PR adds the capability for the moist thermal shallow water equations. It:
SWSaturationAdjustment, to do condensation and evaporation between two moist species in the shallow water equations. This class takessaturation_curveas an argument, and where the water vapour exceeds the saturation curve a specified fraction of the excess vapour is converted to cloud. Conversely, in a sub-saturated atmosphere where cloud is present, a specified fraction of the cloud will evaporate. Ifthermal_feedbackis true then these processes affect the buoyancy equation - evaporation should cause an increase in buoyancy and condensation a decrease.SWSaturationAdjustmentwhich tests both the evaporation and condensation ability by running two different scenarios.moist_thermal_williamson5example to theshallow_waterdirectory. This is based on test 2 in Zerroukat and Allen (2015), which is a version of test 5 from Williamson et al (flow over a mountain) with additional thermodynamic variables.gammaparameter inInstantRaintobeta1to make clearer the distinction between convective feedback (beta1) and thermal feedback (beta2). Adds agamma_rparameter toInstantRainto allow the conversion of a specified fraction of vapour above the saturation threshold to rain.