/**
\page GFS_GWDPS GFS Orographic Gravity Wave Drag Scheme
\section des_gwdps Description
 The GFS orographic gravity wave drag parameterization calculates the
 effect of gravity waves produced by flow over irregularities at the
 Earth's surface such as mountains and valleys and highly dynamic
 atmospheric processes such as jet streams and fronts on the
 horizontal wind. At present, global models must be run with horizontal resolutions
 that cannot typically resolve atmospheric phenomena shorter than
 ~10-100 km or greater for weather prediction and ~100-1000 km or
 greater for climate predicition. Many atmospheric processes have
 shorter horizontal scales than these "subgrid-scale" processes
 interact with and affect the larger-scale atmosphere in important
 ways.

 Atmospheric gravity waves are one such unresolved processes. These
 waves are generated by lower atmospheric sources. e.g., flow over
 irregularities at the Earth's surface such as mountains and valleys,
 uneven distribution of diabatic heat sources asscociated with
 convective systems, and highly dynamic atmospheric processes such
 as jet streams and fronts. The dissipation of these waves produces
 synoptic-scale body forces on the atmospheric flow, known as
 "gravity wave drag"(GWD), which affects both short-term evolution
 of weather systems and long-term climate. However, the spatial
 scales of these waves (in the range of ~5-500 km horizontally) are
 too short to be fully captured in models, and so GWD must be
 parameterized. In addition, the role of GWD in driving the global
 middle atmosphere circulation and thus global mean wind/temperature
 structures is well established. Thus, GWD parametrizations are now
 critical components of virtually all large-scale atmospheric models.
 GFS physics includes parameterizations of gravity waves from two
 important sources: mountains and convection. This parameterization
 address the former.

 Atmospheric flow is significantly influenced by orography creating
 lift and frictional forces. The representation of orography and its
 influence in numerical weather prediction models are necessarily
 divided into the resolvable scales of motion and treated by
 primitive equations, the remaining sub-grid scales to be treated by
 parameterization. In terms of large scale NWP models, mountain
 blocking of wind flow around sub-grid scale orograph is a process
 that retards motion at various model vertical levels near or in the
 boundary layer. Flow around the mountain encounters larger
 frictional forces by being in contact with the mountain surfaces
 for longer time as well as the interaction of the atmospheric
 environment with vortex shedding which occurs in numerous
 observations. Lott and Miller (1997) \cite lott_and_miller_1997,
 incorporated the dividing streamline and mountain blocking in
 conjunction with sub-grid scale vertically propagating gravity wave
 parameterization in the context of NWP. The dividing streamline is
 seen as a source of gravity waves to the atmosphere above and
 nonlinear subgrid low-level mountain drag effect below.

 Gravity-wave drag is simulated as described by Alpert et al. (1988) \cite alpert_et_al_1988. 
 The parameterization includes
 determination of the momentum flux due to gravity waves at the
 surface, as well as upper levels. The surface stress is a nonlinear
 function of the surface wind speed and the local Froude number,
 following Pierrehumbert (1986) \cite pierrehumbert_1986. Vertical
 variations in the momentum flux occur when the local Richardson
 number is less than 0.25 (the stress vanishes), or when wave
 breaking occurs (local Froude number becomes critical); in the
 latter case, the momentum flux is reduced according to Lindzen (1981) \cite lindzen_1981 
 wave saturation hypothesis.
 Modifications are made to avoid instability when the critical layer
 is near the surface, since the time scale for gravity-wave drag is
 shorter than the model time step. The treatment of the GWD in the lower troposphere is enhanced
 according to Kim and Arakawa (1995) \cite kim_and_arakawa_1995 .
 Orographic Std Dev (HPRIME), Convexity(OC), Asymmetry (OA4) and Lx
 (CLX4) are input topographic statistics needed (see Appendix in Kim and Arakawa (1995) \cite kim_and_arakawa_1995) .

 Mountain blocking influences are incorporated following  
 Lott and Miller (1997) \cite lott_and_miller_1997 parameterization with
 minor changes, including their dividing streamline concept. The
 model subgrid scale orography is represented by four parameters,
 after Baines and Palmer (1990) \cite baines_and_palmer_1990, the
 standard deviation (HPRIME), the anisotropy (GAMMA), the slope
 (SIGMA) and the geographical orientation of the orography (THETA).
 These are calculated off-line as a function of model resolution in
 the fortran code ml01rg2.f, with script mlb2.sh (see Appendix:
 Specification of subgrid-scale orography in Lott and Miller (1997) \cite lott_and_miller_1997).

 The orographic GWD parameterizations automatically scales
 with model resolution. For example, the T574L64 version of GFS uses
 four times stronger mountain blocking and one half the strength of
 gravity wave drag than the T383L64 version.


\section intra_gwdps Intraphysics Communication
\ref arg_table_gwdps_run

\section gen_al_gwdps General Algorithm
\ref gen_gwdps

*/