A mountain ridge model for quantifying oblique mountain wave propagation and distribution

Abstract

Abstract. Following the current understanding of gravity waves (GWs) and especially mountain waves (MWs), they have high potential of horizontal propagation from their source. This horizontal propagation and therefore the transport of energy is usually not well represented in MW parameterizations of numerical weather prediction and general circulation models. The lack thereof possibly leads to shortcomings in the model's prediction as e.g. the cold pole bias in the Southern Hemisphere and the polar vortex breaking down too late. In this study we present a mountain wave model (MWM) for quantification of the horizontal propagation of orographic gravity waves. This model determines MW source location and associates their parameters from a fit of idealized Gaussian shaped mountains to topography data. Propagation and refraction of these MWs in the atmosphere is modeled using the ray-tracer GROGRAT. Ray-tracing each MW individually allows for an estimation of momentum transport due to both vertical and horizontal propagation. This study presents the MWM itself and gives validations of MW induced temperature perturbations to ECMWF IFS numerical weather prediction data and estimations of gravity wave momentum flux (GWMF) compared to HIRDLS satellite observations. The MWM is capable of reproducing the general features and amplitudes of both of these data sets and, in addition, is used to explain some observational features by investigating MW parameters along their trajectories.

Emulating lateral gravity wave propagation in a global chemistry-climate model (EMAC v2.55.2) through horizontal flux redistribution

“…This is realised by redistributing orographic GWMF at one single altitude by use of tailor-made redistribution maps. The ray-tracing model GROGRAT coupled to a mountain ridge parameterisation (see Rhode et al, 2023) is applied to generate these maps. The latter are 4-dimensional probability functions describing GW redistribution via horizontal propagation as a mapping from a source latitude-longitude grid to a target latitude-longitude grid (therefore the four dimensions are source-latitude, -longitude and target-latitude, -longitude).…”

“…First, we apply an algorithm to detect and parameterise mountain ridges from topographic data to retrieve MW parameters and to analyse the MW spectrum and distribution that needs to be initialised in the ray-tracing model. The approach applied here is described in detail in the companion paper Rhode et al (2023) and it is similar to the one performed by Bacmeister (1993) and Bacmeister et al (1994). The used topography data set 'ETOPO1' (Amante and Eakins, 2009) features a 1 arcmin resolution.…”

“…For initialisation, MWs are assumed to always launch perpendicular to the source ridge. For more details and a validation of this approach, see Rhode et al (2023).…”

“…For a first evaluation of the GW redistribution in EMAC, we conducted test simulations for July 2006 in the T42L90MA resolution. This is the same period as investigated in the companion paper validating the MWM (Rhode et al, 2023). For this, the greenhouse gases, sea surface temperatures as well as the sea ice concentrations are prescribed.…”

“…To overcome this issue, while retaining computational efficiency and flexibility, we here present a solution that emulates lateral GW propagation through redistribution of the orographic GWMF in a CCM at a single altitude with tailor-made redistribution functions. These global redistribution functions describe a general propagation pattern of MWs and are generated by use of a mountain wave model (MWM), which was developed particularly for this purpose and is described in detail by Rhode et al (2023). There, the authors showed the capability of the model to reproduce lateral propagation patterns found in satellite and high-resolution simulations.…”