CDXWRFtier

Tier1 variables

UNDER CONSTRUCTION

These diagnostics are required by CORDEX, but they are not mandatory. They have been also included as a way to fulfill all the CORDEX requirements. These variables require the setting of the pre-compilation flag CDXWRF to 1 and performing some complementary modifications in the module’s Registry file registry.cordex. See section 2.3 for more details.

zmlagen: generic boundary layer height

Instantaneous Planetary Boundary Layer (PBL) height is a clear example of model dependence and even scheme dependence of how a diagnostic is computed. Each PBL scheme has its own assumptions and ‘zmla’ is computed in a scheme-dependent specific way.

In order to overcome the model/scheme dependence, we implemented a generic formulation for calculating the PBL height as it was done in (García-Díez et al., 2013) after (Nielsen-Gammon et al., 2008). The method consists in defining the height of the PBL as the first level in the mixed layer (ML) where potential temperature exceeds the minimum potential ML temperature by more than 1.5 K. It has been implemented using the definitions given below:

1. Mixed layer depth (MLD) is defined as the model level (k_MLD) starting from the second model level at which the variation of the mixing ratio (QVAPOR(k), normalized with its value at the first level) exceeds some predefined threshold value (QVAPOR(1)): > δQVAPOR (here applied a δQVAPOR = 0.1)
2. Within the MLD the value with the minimum potential temperature is taken as: θmin(MLD = min[θ(1), ..., θ(k_MLD)]
3. The level of the PBL height (k zmla ) is the level at which the maximum variation of potential temperature within the MLD exceeds some predefined threshold value: θ(k_zmla)- θmin MLD > δθ, (here δθ = 1.5 K)
4. The PBL height (zmla) is obtained using the geopotential height zg at the calculated k zmla level above the ground (zagl): zmla = zagl(k zmla ) = zg(k zmla )/g − HGT , with HGT being surface elevation height above sea level. No general rule has been applied to determine the correct value of δqv used to determine MLD. It can be determined by the namelist parameters zmlagen_dqv for δqv (default value 0.1) and zmlagen_dtheta for δθ (default value 1.5 K).

Comparison of this implementation with the zmla directly provided by WRF’s Mellor-Yamada Nakanishi and Niino Level 2.5 PBL scheme (MYNN2.5 Nakanishi and Niino, 2006) is shown in figure 9. In general the generic estimation produces a higher PBL (a panel) with lower values during night (b panel). Spatial distributions between both diagnostics are pretty similar.

Convective diagnostics

Diagnostics related to convective activity are: Convective Available Potential Energy (CAPE) which accounts for all the energy that might be released convectively, Convective Inhibition (CIN) which accounts for processes which inhibit the convection, Height of the Level of Free Convection (ZLFC), Pressure at the Level of Free Convection (PLFC), and Lifted Index (LI) which accounts for the temperature difference between the environmental temperature at some higher level in the troposphere and the temperature that a parcel would have if adiabatically lifted at that level. CORDEX requires these values as statistics between output times (9freq in this case)

Since the version V3.6 of WRF, these variables can already be calculated with the module module_diag_afwa.F via the Buoyancy function. In this version of the module, this is the only available implementation. These vertically integrated diagnostics have a high computational cost. In order to minimize it, they are only computed at output time step by default.

However, if a user requires them as statistics (such as capemin, capemax, capemean), then these diagnostics are computed at all time steps. This behavior of the module is regulated via the namelist parameter convxtrm_diag (default value is 0, meaning no computation), and by setting the pre-compilation flag CDXWRF to 1 and performing some complementary modifications in module’s Registry file registry.cordex. See section 2.3 for more detail.

References

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• Yang, M. J., Braun, S. A., and Chen, D.-S. (2011). Water budget of typhoon nari (2001). Mon. Wather Rev., 139:3809–3828.

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