Abstract
Abstract. The Met Office currently runs two operational ocean forecasting configurations for the North West European Shelf: an eddy-permitting model with a resolution of 7 km (AMM7) and an eddy-resolving model at 1.5 km (AMM15). Whilst qualitative assessments have demonstrated the benefits brought by the increased resolution of AMM15, particularly in the ability to resolve finer-scale features, it has been difficult to show this quantitatively, especially in forecast mode. Applications of typical assessment metrics such as the root mean square error have been inconclusive, as the high-resolution model tends to be penalised more severely, referred to as the double-penalty effect. This effect occurs in point-to-point comparisons whereby features correctly forecast but misplaced with respect to the observations are penalised twice: once for not occurring at the observed location, and secondly for occurring at the forecast location, where they have not been observed. An exploratory assessment of sea surface temperature (SST) has been made at in situ observation locations using a single-observation neighbourhood-forecast (SO-NF) spatial verification method known as the High-Resolution Assessment (HiRA) framework. The primary focus of the assessment was to capture important aspects of methodology to consider when applying the HiRA framework. Forecast grid points within neighbourhoods centred on the observing location are considered as pseudo ensemble members, so that typical ensemble and probabilistic forecast verification metrics such as the continuous ranked probability score (CRPS) can be utilised. It is found that through the application of HiRA it is possible to identify improvements in the higher-resolution model which were not apparent using typical grid-scale assessments. This work suggests that future comparative assessments of ocean models with different resolutions would benefit from using HiRA as part of the evaluation process, as it gives a more equitable and appropriate reflection of model performance at higher resolutions.
Highlights
When developing and improving forecast models, an important aspect is to assess whether model changes have truly improved the forecast
High-Resolution Assessment (HiRA) neighbourhoods typically contain the same number of grid points in the zonal and meridional directions which will lead to discrepancies in the area selected when comparing models with different grid aspect ratios, depending on whether the comparison is based on neighbourhoods with a similar longitudinal or similar latitudinal size
A nearest-neighbour approach has been shown, as this is the method that would be used for HiRA when applying it at the grid scale
Summary
When developing and improving forecast models, an important aspect is to assess whether model changes have truly improved the forecast. Whereas a higherresolution model has the ability and requirement to forecast greater variation, detail and extremes, a coarser model cannot resolve the detail and will, by its nature, produce smoother features with less variation resulting in smaller errors This can lead to the situation that despite the higher-resolution model looking more realistic it may verify worse There is neighbourhood verification, many of which are equivalent to low-band-pass filters In these methods, forecasts are assessed at multiple spatial or temporal scales to see how model skill changes as the scale is varied. Atmospheric science has been using high-resolution convective-scale models for over a decade and have experience in assessing forecast skill on these scales, so it is appropriate to trial these methods on eddy-resolving ocean model data.
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