Parameterization issues specific to convection-permitting models

In the last decade, many meteorological centres have implemented operational regional NWP systems based on non-hydrostatic convection-permitting models (Weiss et al. 2008; Lean et al.

2008; Baldauf et al. 2011; Seity et al. 2011). In such models, the spatial resolution is supposed to be sufficient to resolve convective systems. The horizontal resolution was increased from 3-5 km in the earlier versions to 1-3 km at present with a forecast lead time up to 1-2 days. It is however clear that these resolutions are not really sufficient to resolve deep convective cells well but are able to resolve the macrosystem, and hence these models have proved able to provide skilful guidance for operational forecasting of high-impact weather at the mesoscale, such as heavy convective rainfall, fog, mid-latitude storms or tropical cyclones. They produce more realistic convective precipitation structures compared to lower resolution models using parameterized convection. New approaches have been developed for high resolution model verifications, oriented towards weather elements and severe weather events (Gilleland et al. 2010; Roberts and Lean, 2008; Mittermaier, 2014; Ebert and McBride, 2000), which confirm some benefits of convection-permitting models compared with global models. Very recently these models have started to be applied to downscale climate models (e.g. Kendon et al. 2014), with the improved representation of convection leading to different conclusions about likely changes in heavy convective rainfall in a future climate.

Convection permitting models typically do not include deep convection parameterization despite the fact that their resolution is still insufficient to resolve deep convection very well. Generally they also do not include orography-induced gravity wave parameterization but they often have similar physical parameterizations to global models for turbulence, shallow convection, micro-physics, radiation and surface processes, the physical processes operating at these scales being mostly the same. This strongly supports the concept of seamless prediction of weather and climate which consists of developing models that can be used in a more or less continuous way over a wide range of spatial and temporal scales. However, there are still specific issues regarding physical parameterizations in convection-permitting models. For instance, micro-physical processes which are crucial for the explicit evolution of deep convection are often parameterized in a more detailed manner, and the inclusion of extra species also helps with the assimilation of radar data. Several physical processes cannot be neglected any longer at kilometric scales and physics/dynamics coupling plays a bigger role because of shorter time scales (See later discussion on coupling. The following section will focus on key questions specific to physical parameterization in convection-permitting regional models.

Microphysics

The micro-physical scheme is a key component in convection-permitting models because of the role of dynamics-microphysics-radiation interactions in the evolution of convection (Grabowski and Moncrieff, 1999; Petch and Gray, 2001). Micro-physical schemes vary widely in complexity,

differing in the number of prognostic parameters used to describe condensed water particles covering a wide range of sizes and shapes (for ice crystals) and in depicting micro-physical interactions. Though 'bin' micro-physical schemes (size distribution discretised into bins) are quite successful, they are too expensive to be used operationally. Hence 'bulk' micro-physical schemes are used in convection-permitting models. The distribution of hydro-meteors is represented by several classes of particles, each class being represented with a specified type of size spectrum (e.g. exponential, gamma, log-normal, etc.) and a small number of predicted parameters, generally the first moments of the distribution (mass, number concentration, reflectivity, etc.). Micro-physical schemes within convection permitting models include generally more classes than within global models for solid condensates, such as graupel and sometimes hail. Ice micro-physics has a particularly important impact on the evolution of the convection (Liu et al. 1997; Bryan and Morrison, 2012). The use of a one moment bulk micro-physics scheme and a very basic aerosol representation has been widely used in convection-permitting operational models. There is now a clear orientation towards the development of more detailed multi-moments and multi-species schemes with aerosol coupling to improve the representation of size distributions and hence micro-physical process rates (Seifert and Beheng, 2006a,b; Phillips et al. 2007). However, the

understanding of physical processes such as the conversion parameters (snow to graupel, liquid

 

and ice auto-conversion...) and of ice particles (nucleation, shape, diffusional growth, aggregation, breakup, riming, density changes) is as yet unsatisfactory, although the work of Morrison and Milbrandt (2015) and Sulia et al. (2014) is promising. Further research is strongly needed to improve the understanding of these physical processes and their parameterization in NWP kilometric scale models. Better consistency should be achieved between micro-physics and radiation schemes for modelling cloud optical properties with precipitating particles (rain, snow, graupel, etc.) still often ignored by radiative transfer schemes despite evidence that they play a significant role (Petch, 1998).

Convection and turbulence

Some sort of parameterization of convection is still needed in kilometre scale models, which explicitly resolve only deep convective systems. Most of the convection is not explicitly resolved, for instance thermals in the PBL, shallow and medium convection in the troposphere, but also non-organised deep convective clouds. The triggering and the evolution of explicit convection rely very strongly on a consistent treatment of turbulence and thermals (dry and moist) in PBL. Some progress has been achieved in recent years for high resolution and global models with the

developments of eddy-diffusivity and mass-flux “EDMF” schemes (Hourdin et al. 2002; Siebesma et al. 2007; Pergaud et al. 2009) and higher-order closure turbulence schemes (Bogenschutz et al.

2010). The inclusion of physically-based stochastic elements in PBL schemes seems promising for the representation of the sub-grid spatial heterogeneity and the onset of explicit convection. The modelling of the convection at grey zone resolutions (around 5 km for deep convection and around 500m for shallow convection) is a growing research topic both for global and regional models. The GASS-WGNE Grey Zone project has been undertaken to gain an insight and understanding of the behaviour of models in the grey zone and to provide guidance and benchmarks for the design of new scale-aware convective parameterizations that can operate in the grey zone. The use of LES simulations on large geographical domains is promising to help diagnose the proportion of resolved and parameterized turbulence according to spatial resolution (Honnert at al. 2011) and to develop scale aware physical parameterizations.

The representation of turbulence in stable conditions (polar regions, nocturnal inversions, the free troposphere, the tropopause etc.) is also an important issue for high resolution models. The modelling of turbulence over orography or at the edge of convective clouds warrants more attention in convection permitting models than in global models. The representation of 3D turbulence will become important in mountain regions with further increases in model resolution.

Research is needed to develop and improve 3D turbulence parameterization and demonstrate its utility for hectometric resolutions.

Radiation and surface processes

Similar radiation schemes are used in low and high resolution models. However, radiation-cloud-aerosol interactions, generally not computed every time-step because of their computational cost, should be parameterized more frequently in convection permitting models which simulate shorter time scales. Radiation schemes with an intermittent level for computation of gaseous transmissions coupled with a radiation-cloud interaction at every time-step look promising. Some radiative

orographic effects such as slope, shading and sky view factor need to be parameterized in kilometre scale models (Müller and Scherer, 2005). Since full 3D radiation schemes are very demanding in computational resources and will not be affordable for many years, there is a need to parameterize some 3D radiative effects in a simple way (for instance cloud shading at the surface).

Surface processes also warrant some specific adaptations for kilometre scales models. Available climatological databases for physiography and soil properties at kilometric scales are not of uniform quality and still contain significant errors. Research is needed to improve these databases and to develop new ones at much higher resolutions (~100 m). The assimilation of satellite

observations should be promoted to provide real-time surface parameters, such as albedo, vegetation fraction or leaf area index. There is also a need for improved orographic databases at very high resolutions (~30 m) for computing sub-grid orographic parameters such as orographic roughness, slope, standard deviation, non-isotropic properties derived from the tensor of

orographic gradient correlation, sky-view parameters, etc. The implementation of urban schemes has been found to be very positive in improving the simulation of surface fluxes over large cities and the diurnal cycle of the surface temperature, although recent inter-comparison studies have shown that relatively simple schemes may perform as well in many respects as more complex ones (Best and Grimmond, 2014). Many aspects (urban moisture, momentum fluxes, town

gardens, etc.) of these schemes, including the availability and standardisation of urban parameters (a major issue), are in dire need of further study. The use of kilometre-scale, and soon

sub-kilometre-scale, models opens the way to simulate snow-pack and hydrology over mountains. The snow parameterization should be improved to describe the time evolution of the physical properties of the inner snow-pack (thermal conduction, radiative transfer) based on the time evolution of the morphological properties of the snow grains along with snow metamorphism. A parameterization of blowing snow will be important as well. The coupling with hydrological models is needed to

forecast flash-floods. There is a continuing trend for increasing the vertical resolution near the ground to improve the simulation of radiation fog, but this is in contradiction with the blending height hypothesis. Research is needed to improve coupled land-atmosphere modelling systems.

Coupling

Physics/dynamics coupling is very important in convection permitting models, because explicit convection results from a complex feed-back between the buoyancy force (dynamics) and the condensation/evaporation (physics). The order (sequential or parallel) of computing physical parameterizations (ranging from slow to fast processes) matters significantly. The way physics and dynamics are connected also has some importance, such as the location of physics tendency computations in models using a semi-Lagrangian trajectory. The tendencies computed in the physics have to be projected into the dynamical equations in a consistent way to assure the conservation of mass, momentum and energy. Implicit and explicit numerical diffusion have also a significant impact in convection permitting models (Piotrowski et al. 2009, Langhans et al. 2012).

For all these reasons, a better understanding of physics/dynamics coupling is strongly needed in these models. This should bring modelling experts working on physics and dynamics closer.

10.3 CONCLUSIONS

The problem of representing unresolved physical processes in numerical models of the atmosphere remains a crucial one and has been discussed here at some length. The ever-decreasing grid lengths of atmospheric forecast models has helped resolve some aspects of the problem but raised new challenges also. Of particular note is the difficulty in representing

convection at ‘Grey Zone’ resolutions. The importance of using large domain LES-type integrations as a surrogate for the real atmosphere has been emphasised and what might be expected from such an approach considered. It is recognised that as well as convection, challenges exist for many other processes that are parameterized in global models. The additional requirements posed when shorter and shorter space and timescales are introduced (such as in sub-kilometre limited-area models) were also reviewed and similar grey zone issues at sub-kilometre resolutions with regard to boundary layer circulations discussed.

This paper did not set out to answer these challenges but rather to identify them and indicate possible pathways forward. Collectively the scientific problems outlined in this paper will require a vast amount of research and development in the coming decade; work that is essential if our forecast systems are to continue their rapid progress.

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