The data deposited here is a condensed set of the data used to generate the figures in the paper 'The circulation response to resolved versus parametrized orographic drag over complex mountain terrains', by Annelize van Niekerk, Irina Sandu and Simon Vosper. The data was generated using the Met Office Unified Model and the European Centre for Medium Range Weather Forecasts Integrated Forecasting System. Please contact Annelize.vanNiekerk@MetOffice.gov.uk for information on the data.
Use of machine learning algorithms in climate simulations requires such algorithms to replicate certain aspects of the physics in general circulation models.  In this study, a neural network is used to mimic the behavior of one of the subgrid parameterization schemes used in global climate models, the nonorographic gravity wave scheme.  Use of a one-dimensional mechanistic model is advocated, allowing neural network hyperparameters to be chosen based on emergent features of the coupled system with minimal computational cost, and providing a testbed prior to coupling to a climate model. A climate model simulation, using the neural network in place of the existing parameterization scheme, is found to accurately generate a quasi-biennial oscillation of the tropical stratospheric winds, and correctly simulate the nonorographic gravity wave variability associated with the El Niño–Southern Oscillation and stratospheric polar vortex variability. These internal sources of variability are essential for providing seasonal forecast skill, and the gravity wave forcing associated with them is reproduced without explicit training for these patterns.
Abstract The accuracy with which parametrizations of orographic blocking and orographic gravity wave drag (OGWD) are able to reproduce the explicitly resolved impacts on flow over complex terrain is investigated in two models: the Met Office Unified Model (MetUM) and the European Centre for Medium‐Range Weather Forecasts Integrated Forecasting System (ECMWF IFS). To this end, global and limited area short‐range forecast experiments across a range of horizontal resolutions, and their model errors relative to analyses, are assessed over two complex mountainous regions: the Himalayas and the Middle East. The impact of resolved orography on the circulation is deduced by taking the difference between high‐resolution experiments with a high (4 to 9 km) and low‐resolution (125 to 150 km) orography. This is then compared with the impact of parametrized orographic drag, deduced from global low‐resolution experiments with and without parametrized orographic drag. At resolutions ranging from tens to hundreds of kilometres, both the MetUM and ECMWF IFS exhibit too strong zonal winds relative to analyses in the lower stratosphere in the region of maximum resolved orographic gravity wave breaking, indicative of some deficiency in the parametrization of OGWD. Diagnosis of the parametrized physics and resolved dynamics tendencies across a range of OGWD parameter values reveal that this error is partly due to the manner in which the resolved dynamics interacts with the parametrized OGWD. This work introduces a method for quantifying the impacts of resolved versus parametrized orographic drag in models and highlights the importance of physics‐dynamics interactions.
We demonstrate a 1-year lagged extratropical response to the El Niño-Southern Oscillation (ENSO) in observational analyses and climate models. The response maps onto the Arctic Oscillation and is strongest in the North Atlantic, where it resembles the North Atlantic Oscillation (NAO). Unexpectedly, these 1-year lagged teleconnections are at least as strong as the better-known simultaneous winter connections. However, the 1-year lagged response is oppositein sign to the simultaneous response such that 1 year later, El Niño is followed by a positive NAO, whereas La Niña is followed by a negative NAO. The lagged response may also interfere with simultaneous ENSO teleconnections. We show here that these effects are unlikely to be caused by residual aliasing of ENSO cycles; rather, slowly migrating atmospheric angular momentum anomalies explain both the sign and the timing of the extratropical response. Our results have implications for understanding ENSO teleconnections, explaining observed extratropical climate variability and interpreting seasonal to interannual climate predictions.
The exchange of momentum between the atmosphere and the Earth’s surface makes a substantial contribution to the atmospheric momentum budget, and the representation thereof is vital for accurately simulating the atmospheric circulation in models. However, current computational constraints mean that only a fraction of the spatial scales that make up the total drag within the atmosphere are resolved, and the rest must be approximated through parameterisation schemes. What is more, many parameters within these schemes are not well constrained by observations, if at all. Ted Shepherd (University of Reading), the meeting chairman, highlighted that, despite several studies having demonstrated the large sensitivity of the circulation to drag, these processes are relatively under-explored when compared with other processes such as clouds and convection, even though both can lead to model error and uncertainty. In order to make progress in light of these difficulties, this RMetS national meeting, held at the University of Reading on 16 November, brought together research that investigates the circulation sensitivity to, and how we might better constrain, surface drag. The first speaker was Irina Sandu (ECMWF) who gave, in her introduction, a general overview of the problems faced when trying to account for unresolved orographic drag processes in models. Figure 1 shows the resolved orography across model resolutions and demonstrates the gap that must be filled by parameterisation schemes when going from climate models to numerical weather prediction. There exists a continuous spectrum of horizontal scales over which orographic drag can act and, since there is no clear scale separation between processes, their relative contributions within the momentum budget of models is ambiguous. A question of interest is then: is it just the total drag or does the partitioning between different drag processes matter for the large scale circulation? By holding the total drag constant and altering the contributions from two different orographic drag parameterisations, she showed that the impact on the large scale circulation is qualitatively similar for the two different drag parameterisations considered but that there are large quantitative differences. Ian Boutle (Met Office) discussed the impact of boundary layer drag on the development of mid-latitude cyclones. There is a general consensus that the addition of boundary layer drag acts to reduce their intensity, delays their development and alters the position of the low pressure centre. However, there is a lack of agreement on the mechanism for this since the spin down of cyclones via Ekman pumping alone is not sufficient. Ian went on to show that it is the enhanced static stability above the low pressure that acts to inhibit the intensification of the cyclone. Accurately forecasting the intensity and position of mid-latitude cyclones is important for socio-economic reasons, and this deeper understanding of their behaviour in the presence of drag highlights the importance of realistically representing boundary layer drag processes. Continuing on the topic of boundary layer drag, Inna Polichtchouk (University of Reading) used a hierarchy of models to investigate the impact of ocean drag on the large-scale circulation. The exchange coefficients that control the air–sea momentum, heat and moisture transfer are very uncertain in the weak flow speed regions, due in part to a lack of observational constraints. She demonstrated that changes to these coefficients at weak flow speeds have a substantial impact on the zonal winds, the meridional overturning circulation and the precipitation in an aquaplanet model. These results carry through to more comprehensive atmosphere only and slab ocean models, demonstrating that the circulation sensitivity to uncertain drag parameters is both robust and capable of producing a wide range of climatological circulations, as is seen in the CMIP5 ensemble. Alan Gadian (NCAS, University of Leeds) gave attention to the drag that arises through the transport of momentum by atmospheric gravity waves. These waves are important both for clear air turbulence, which can cause severe damage to aircraft, and, since they are capable of reaching very high altitudes, for the mixing of chemical species in the stratosphere. Alan discussed the variety of mechanisms that generate atmospheric gravity waves, such as orography and convective systems, and how the atmospheric background state impacts their propagation and dissipation. More unique observational studies using lidar and radiosondes, such as those performed by Alan and colleagues over South Georgia, will enrich our understanding of how, where and when these waves propagate. This will, in turn, aid the validation of drag processes within models. While direct observations of drag are highly prized, Simon Vosper (Met Office) showed that high resolution modelling over orography is proving to be an increasingly fruitful way of constraining drag for parameterisations at lower resolution. The effective resolution of the model, which is the number of grid points required to fully represent processes as opposed to the grid point resolution, is much coarser than that used to calculate sub-grid scale variables for parameterisations. By retuning the low-resolution model to account for this, Simon showed that the orographic drag parameterisation is capable of reproducing the resolved orographic drag, and its variability, from the high resolution model to a great degree of accuracy. However, this retuning is not globally consistent since it does not work for more complex regions of orography. These results suggest that the treatment of large scale orography, such as that found in New Zealand or the Rockies, by the parameterisation is very different from that of small isolated mountains, as found in South Georgia. It is clear from the panel discussion and the work presented by the speakers that surface drag processes are key in disentangling the origins of model circulation uncertainty. By continuing to gain understanding and constraining the mechanisms of surface drag, through high resolution simulations, observational campaigns or otherwise, we can improve model fidelity and provide better model projections across all timescales.
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.
<p><strong>Angular momentum is fundamental to the structure and variability of the atmosphere and hence regional weather and climate. Total atmospheric angular momentum (AAM) is also directly related to the rotation rate of the Earth and hence the length of day. However, the long-range predictability of fluctuations in the length of day, atmospheric angular momentum and the implications for climate prediction are unknown. Here we show that fluctuations in AAM and the length of day are predictable out to more than a year ahead and that this provides an atmospheric source of long-range predictability of surface climate. Using ensemble forecasts from a dynamical climate model we demonstrate predictable signals in the atmospheric angular momentum field that propagate slowly and coherently polewards into the northern and southern hemisphere due to wave-mean flow interaction within the atmosphere. These predictable signals are also shown to precede changes in extratropical surface climate via the North Atlantic Oscillation. These results provide a novel source of long-range predictability of climate from within the atmosphere, greatly extend the lead time for length of day predictions and link geodesy with climate variability.</strong></p>
Abstract Angular momentum is fundamental to the structure and variability of the atmosphere and therefore has an important influence on regional weather and climate. Total atmospheric angular momentum is also directly related to the rotation rate of the Earth and, hence, the length of day. However, the long-range predictability of fluctuations in the length of the day and atmospheric angular momentum is unknown. Here we show that fluctuations in atmospheric angular momentum and the length of day are predictable out to more than a year ahead and that this provides an atmospheric source of long-range predictability for surface climate. Using ensemble forecasts from a dynamical climate model, we demonstrate long-range predictability of signals in the atmospheric angular momentum field that propagate slowly and coherently polewards due to wave–mean flow interaction within the atmosphere. These predictable signals are also shown to precede changes in extratropical climate via the North Atlantic Oscillation and the extratropical jet stream. These results extend the lead time for length-of-day predictions, provide a source of long-range predictability from within the atmosphere and provide a link between geodesy and climate prediction.
Abstract Atmospheric predictability from subseasonal to seasonal time scales and climate variability are both influenced critically by gravity waves (GW). The quality of regional and global numerical models relies on thorough understanding of GW dynamics and its interplay with chemistry, precipitation, clouds, and climate across many scales. For the foreseeable future, GWs and many other relevant processes will remain partly unresolved, and models will continue to rely on parameterizations. Recent model intercomparisons and studies show that present-day GW parameterizations do not accurately represent GW processes. These shortcomings introduce uncertainties, among others, in predicting the effects of climate change on important modes of variability. However, the last decade has produced new data and advances in theoretical and numerical developments that promise to improve the situation. This review gives a survey of these developments, discusses the present status of GW parameterizations, and formulates recommendations on how to proceed from there.
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