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GMTB Common Community Physics Package (CCPP) Scientific Documentation
Version 1.0
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GMTB Common Community Physics Package (CCPP) Scientific Documentation
Version 1.0
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In recent years, the leading NWP centers have extended the vertical range of their NWP and DA systems from the surface up through the stratosphere (~10-50 km altitude) and lower mesosphere (~50-65 km). Some have also added stratospheric ozone ( \(O_3\)) as a prognostic trace constituent to their models. Examples include the Integrated Forecast System (IFS) of the European Centre for Medium Range Weather Forecasts (ECMWF) ([83]; [18]), and the NCEP GFS (NCEP 2003). The addition of stratospheric ozone as a prognostic variable is expected to improve overall forecast and analyses skill of other fields, such as temperature and wind. The primary reasons for this are:
With the extension of NWP/DA systems into the upper stratosphere, assimilation and advection alone cannot yield accurate ozone forecasts - photochemical effects must also be included. Due to the complexity of ozone photochemistry, it is not currently feasible to implement full ozone photochemistry within a high-resolution operational global NWP system. Instead, the operational GFS currently parameterizes photochemical production and destruction based on monthly mean coefficients provided by Naval Research Laboratory CHEM2D chemistry model through an ozone photochemistry parameterization (OPP), known as CHEM2D-OPP ([61]). CHEM2D-OPP consists of four coefficients describing the residual ozone photochemical tendency as the difference between the production and loss rates \((P-L)\) and its sensitivity to local changes in ozone mixing ratio \(r\), temperature \(T\), and overhead ozone column amount \(\Sigma\) (see Figs. 1, 2, 5, and 6 in [61]). The local time rate of change of ozone mixing ratio due to photochemistry is then:
\[ \frac{\partial r}{\partial t}=(P-L)\left[r,T,\Sigma\right] \color{red} {(1)} \]
Linearization of the ozone photochemical tendency above has become a standard method for NWP and climate models. The latest generation of linearized ozone photochemistry scheme approximate the unknown function \((P-L)\left[r,T,\Sigma\right]\) by defining it about some reference state \(r_0\), \(T_0\), \(\Sigma_0\), then expanding it about this reference state using a first-order Taylor series expansion.
\[ \frac{\partial r(\lambda,\phi,p,t)}{\partial t}=(P-L)_0+\frac{\partial (P-L)}{\partial r}\bracevert_0(r-r_0)+\frac{\partial (P-L)}{\partial T}\bracevert_0(T-T_0)+\frac{\partial (P-L)}{\partial \Sigma}\bracevert_0(\Sigma-\Sigma_{0}) \color{red} {(2)} \]
where \(\lambda\) represents longtitude, \(\phi\) represents latitude, and \(p\) represents pressure as the model vertical coordinate. The subscript "0" attached to \((P-L)\) and its partial derivatives refers to their values at the reference state \(r_0\), \(T_0\), \(\Sigma_0\), and are all zonally averaged quantities. The reference-state production and loss, \((P-L)_0\), and the various partial derivative terms about the state (the last three terms on the right) are computed offline using CHEM2D model photochemistry. These coefficients are then stored in tabular form as functions of latitude, pressure, and month, with suitable linear interpolation to the desired location (global_o3prdlos.f77). However, when implementing (2) in GFS physics suite, the perturbation terms \((r-r_0, T-T_0, \Sigma-\Sigma_0)\) are computed with respect to a zonal mean climatological reference state used to derive the partial derivatives in (2). such discrepancies can potentially introduce systematic, non-physical biases into the photochemical parameterization ([61]).
1.8.11