Circle-A: Parametrizing Convection in the Hard Grey Zone: Modelling the Interaction of Turbulent Cloud processes with Explicit Cloud Dynamics.

"Anarchy is the mother of Order", claimed Proudhon, referring to the Anarchist movement. Many might question whether this is true of human behaviour, but it certainly is of the atmosphere. Some of the most extreme weather on earth is associated with deep convective rain storms driven by the heat released and buoyancy generated when water vapour turns into liquid cloud water or ice. These storms start out as small turbulent eddies which grow into violent thunderstorms, the most severe of which preserve their existence by a process of continual regeneration. In the right conditions, storms can organise into much larger structures such as squall lines covering hundreds of kilometres and lasting many hours. The most extreme, violent and beautiful example of organised convection is the tropical cyclone.
This ever-larger scale organisation nevertheless remains, in part, controlled by processes occurring at the smallest turbulent scales. If we represent these processes poorly in models used to predict weather and climate, we severely compromise the accuracy of their predictions. Ever-increasing computer power has given us the ability to run higher resolution models that are beginning to represent individual clouds with some realism, but we are far from directly resolving those processes that control the size, intensity, number etc. of clouds. This project is aimed at substantially improving the way we represent the effect of these processes on cloud growth and dissipation in practicable weather forecast models and climate models.
We can get so far by theoretical derivation from the fundamental equations of physics, but doing so raises more unanswered questions, such as how can we predict the distribution of water in a cloud, which is highly sensitive to motions within turbulent eddies, given only limited information of average properties over larger scales (e.g. a few km)? We can 'close' the problem by forming hypotheses about dependencies based upon arguments such as scaling and symmetry, but these need testing and calibrating. As part of the project we plan to run a number of ambitious reference simulations of controlled, idealized, convective flows, to provide data to test these hypotheses. We also propose developing a hierarchy of simplified representations of the turbulent flow directed specifically at cost effective modelling of deep convection. In particular, we plan to implement three schemes:
1. A 'Rolls-Royce' scheme, with as little approximation as possible.
2. A highly simplified scheme similar to those commonly used but and with a fresh analysis of key parameters.
3. A new scheme traceable from 1 but based on a simplification of 1 directed specifically at the representation of deep convective clouds, focussing on vertical motion and resulting condensation separately from horizontal motion.
The high resolution data will be analysed much the same way that observational data would be if available, but we also plan to make use of high-resolution models is a way which could never be achieved through observation; we plan to provide information about the 'truth' directly to lower resolution simulations as they run, either turbulent fluxes or mean variables. This can be done in a number of ways to learn about which terms are most important in driving the resolved flow. One exciting and novel way is to use techniques recently developed in the Data Assimilation Research Centre to use 'observations' (in our case, reference high-resolution simulations) to determine objectively which parametrizations best represent the 'missing' terms in a model, the omission of which lead the model to diverge from the observations.

Society and the General Public
The primary impact of this project will be directly on the accuracy and utility of Met Office weather forecasts and climate predictions via improved prediction and simulation of convection in the Met Office's Unified Model. Impacts will occur through other centres; directly through Met Office Partners in MetUM development and indirectly to other centres through promulgation of the methodology and reference data it is based on. This will have impact on end-users, from government, industry and the public, through significant improvements to their products and advice. The Met Office, in common with operational prediction centres worldwide, considers this to be a major priority, made more essential by ongoing efforts to improve the dynamical cores of models to allow best use of increased parallel computing power and, hence, higher spatial resolution, such as the Gung-Ho project in the UK (now LFRic) and the ICON project in Germany.
Weather and flood forecasting: This project will improve forecasts, certainly in regional weather forecast models and hopefully also in coarser-resolution global models. Convection is responsible for the intense rainfall that generates flash floods. The Pitt Review, written after the 2007 UK floods, stressed the need for better prediction heavy precipitation. Short-range MetUM-forecasts are now being produced in the Met Office with grid-spacing of a few km. The Environment Agency/Met Office Flood Forecasting Centre now provides a national severe rainfall and flood warning service that relies on NWP forecasts. The reliability of these forecasts is compromised by deficiencies in the representation of intense rainfall from convective systems, and a more reliable parametrization will have an immediate impact on forecast quality. The importance of parametrization of turbulence and convection cannot be understated; at present, the only remedy for deficiencies in performance is higher-resolution, which is extremely expensive. Improved parametrization will facilitate larger-domains, larger ensembles to quantify forecast uncertainty, and improved data assimilation.
Climate predictions, climate-change impact assessments: The hard grey-zone parametrizion scheme will contribute to correcting major biases in the MetUM, Recent work using the MetUM at convection-permitting resolution has shown that the climate change signal for extreme rainfall cannot be relied upon from models using current convection parametrizations. A different signal emerges from 'convection-permitting' models, but these clearly, at present, have their own significant biases.
The importance of convection goes far beyond precipitation, however. "Realistic parametrizations of cloud processes are a prerequisite for reliable current and future climate simulation" and "differences in cloud response are the primary source of inter-model differences in climate sensitivity" (IPCC, Ch. 8). The representation of convection has a number of impacts on earth-system models. Wash-out by convective rain is a primary uncertainty in the global aerosol cycle, the representation of convection is more important for the summertime Sahara dust than the land surface and rainfall changes control the future of tropical forests, such as the Amazon, where some models predict a die-back with decreased rainfall, coupling convection with the carbon cycle (IPCC, 2007, Ch. 11.6.3.2).
Academic Impact
This project will deliver new understanding of atmospheric convection that will have wide impact in the academic community, as well as improved climate and earth-system models which form the basis of further academic study. It will also deliver valuable database of high-resolution reference simulations that will be used for years to come by the UK and WGNE communities: these will likely have many uses beyond those described in this proposal, as has been found, e.g., in the NERC Cascade consortium