Uncertainty in the Representation of Orography in Weather and Climate Models and Implications for Parameterized Drag

Abstract

The representation of orographic drag remains a major source of uncertainty for numerical weather prediction (NWP) and climate models. Its accuracy depends on contributions from both the model grid‐scale orography and the subgrid‐scale orography (SSO). Different models use different source orography data sets and different methodologies to derive these orography fields. This study presents the first comparison of orography fields across several operational global NWP models. It also investigates the sensitivity of an orographic drag parameterization to the intermodel spread in SSO fields and the resulting implications for representing the Northern Hemisphere winter circulation in a NWP model. The intermodel spread in both the grid‐scale orography and the SSO fields is found to be considerable. This is due to differences in the underlying source data set employed and in the manner in which this data set is processed (in particular how it is smoothed and interpolated) to generate the model fields. The sensitivity of parameterized orographic drag to the intermodel variability in SSO fields is shown to be considerable and dominated by the influence of two SSO fields: the standard deviation and the mean gradient of the SSO. NWP model sensitivity experiments demonstrate that the intermodel spread in these fields is of first‐order importance to the intermodel spread in parameterized surface stress, and to current known systematic model biases. The revealed importance of the SSO fields supports careful reconsideration of how these fields are generated, guiding future development of orographic drag parameterizations and reevaluation of the resolved impacts of orography on the flow.

What can we learn about orographic drag parametrisation from high‐resolution models? A case study over the Rocky Mountains

“…On the other hand, the blocked layer depth () is still able to scale with the subgrid mountain height. The sensitivity of the surface stress and gravity wave momentum flux to the and fields used in global NWP models is demonstrated in Elvidge et al, (), and the transition of the gravity wave stress between subcritical () and supercritical () flow regimes is discussed and illustrated in their fig. c.…”

“…Previous studies have shown that the partitioning between the orographic and boundary layer drag is very different between the two models (Zadra et al, ; Sandu et al, ). These differences are likely a result of a combination of subjective tuning, differences in formulation and, as recently demonstrated by Elvidge et al, (), the representation of subgrid orographic fields. The implications of these differences between the UM's and the IFS's treatment of parametrised orographic drag for the total drag and its variability over the northern Rocky Mountains will be considered.…”

“…The UM has less resolved orographic gravity wave drag compared with the IFS, and this difference is compensated for by the fact that the UM has more parametrised orographic gravity wave drag. Elvidge et al, (2019) showed that the filtering of the resolved orography in the UM, which likely affects the amplitude of the resolved orographic gravity waves, is much stronger than that employed in the IFS. This may explain why the UM has less resolved orographic gravity wave drag compared with the IFS.…”

Verification of a seeder–feeder orographic precipitation enhancement scheme accounting for low‐level blocking

“…One of the major findings of Elvidge et al . () is that the UM currently has smoother mean orography than other centres. Upcoming changes to the orography ancillary generation method (van Niekerk, personal communication [2019]) include a significant reduction in smoothing of both the resolved and sub‐grid orography fields, which should improve model representation of orographic volume for poorly resolved mountains, allowing for better representation of orographic drag and precipitation enhancement.…”

“…Work is currently ongoing to investigate the reasons for excessive drag due to subgrid low-level orographic blocking, which has the effect of producing too much ascent and therefore precipitation upstream of major orography and not enough over the mountains themselves. One of the major findings of Elvidge et al (2019) is that the UM currently has smoother mean orography than other centres. Upcoming changes to the orography ancillary generation method (van Niekerk, personal communication [2019]) include a significant reduction in smoothing of both the resolved and sub-grid orography fields, which should improve model representation of orographic volume for poorly resolved mountains, allowing for better representation of orographic drag and precipitation enhancement.…”