Characterising and Interpreting FLuxes Over Sea-ice (CANDIFLOS)

Lead Research Organisation: University of East Anglia
Department Name: Environmental Sciences


Interactions between the atmosphere and the surface of the planet are mediated by turbulent fluxes - chaotic mixing that transports momentum, heat, moisture, and trace gases between the two. Turbulent mixing spans scales from millimetres to hundreds of meters - much smaller than the grid scale of numerical models; such sub-grid-scale processes must be parameterized (or represented) in terms of simpler model variables such as mean wind speed, air temperature, humidity, etc. These parameterizations are developed by making direct measurements of the fluxes themselves (a very difficult and expensive undertaking) and then determining their empirical relationships with the simpler (and more easily measured) variables such as wind speed, temperatures etc.

This proposal aims to address long-standing issues with the parameterization of turbulent fluxes over sea ice. The remote location and harsh conditions of both Arctic and Antarctic sea ice means that very few direct measurements of the fluxes have ever been made, and models must rely on parameterizations developed at lower latitudes, e.g. over ice-free areas of the oceans. The very different conditions that occur over sea ice - a high degree of spatial variability, strong temperature contrasts between the ice and open water in leads in the ice, and strongly stable atmospheric conditions in winter - mean that the parameterizations developed at lower latitudes are often not appropriate, and models tend to do a poor job of representing the surface fluxes. The current generation of models fails to represent the mean changes in sea ice extent compared to satellite observations over the last 35 years or so, and produce often wildly inaccurate seasonal forecasts of ice extent even just a few months in advance.

The growth and melt of sea ice is controlled by the surface energy budget, and the turbulent fluxes between the ice and the atmosphere are a critical component of that budget. The solar and terrestrial radiation fluxes dominate the budget, but the turbulent fluxes control the atmospheric boundary-layer structure, and influence the development of boundary-layer clouds which are the dominant control on the radiation fluxes. So all of these fluxes are inter-linked and consequently a failure to properly represent the air-ice turbulent fluxes has a knock-on influence on the surface radiation balance through their impact on clouds. An accurate representation of turbulent fluxes is thus essential for accurate predictions of weather, sea ice and the climate system.

On short timescales the recent reduction of Arctic sea ice, and the accompanying increase in commercial activity in the Arctic (shipping, tourism, petrochemical extraction, etc) means that there is an urgent need for accurate operational forecasts of weather, sea ice and other environmental factors on timescales from days to seasons. Delivering these will require a much improved representation of the surface exchange processes that control the atmospheric boundary layer and properties of clouds within it, and contribute to the surface energy budget, and hence ice melt/freeze, and ice drift.

Significant progress has been made over the last 5 years in developing theoretical models of the physical processes that control the surface fluxes, such as form drag at ice edges, ridges, melt ponds, and ice/water temperature contrasts. However there is a need for in situ measurements to test these parameterizations and to evaluate their performance.

This project will utilise a very extensive set of surface flux and sea-ice measurements made during two recent (2014 and 2016) cruises in the Arctic Ocean, totalling 18 weeks, to develop state-of-the-art parameterizations for momentum, heat, and water vapour that are tuned to real-world conditions. We will implement these parameterizations within the Met Office Unified Model, and evaluate their impact on the atmosphere, and on the climate system, over a range of timescales.

Planned Impact

This project will deliver immediate, direct benefits to the UK Met Office. They are project partners, actively collaborating on modelling activities. The project will provide the Met Office with much improved parameterizations of surface fluxes for use in their operational forecast, seasonal forecast, and climate models. We will also contribute an extensive set of in situ measurements, quality-controlled and analysed, to form part of a process-oriented model evaluation suite currently being developed by the Met Office. This will provide a long-term data set against which to test process representation in models (as opposed to evaluating model mean state).

The ultimate impact could affect a very wide range of stakeholders: Arctic climate is changing rapidly, warming at more than twice the global average rate and the resulting on-going reduction in sea ice extent, thickness, and volume is opening up the Arctic to increased shipping and commercial exploitation of natural resources. This increase in commercial activity brings an increased risk of accidents, e.g. oil spills, with potential consequences to the environment being far worse in the Arctic than in other regions. To facilitate commercial activity and mitigate the resulting risks there is a requirement for "accurate and up-to-date weather/ice information" (Lloyds, 2012) on timescales of hours to days for operational purposes, and to months for the planning and scheduling of activities. Unfortunately short-term Arctic sea-ice and weather forecasts are currently much less accurate than those for the mid-latitudes and climate model simulations have huge differences in the projected warming and changes in sea ice.

Our project aims to greatly improve the model representation of key surface exchange processes; this will lead to much more accurate representation of the surface energy budget, the rates of ice melt and formation, and wind-driven surface currents in the Arctic Ocean. The improvements to model fidelity should results in benefits to operational weather forecasts for the Arctic region, improved seasonal forecasts of summer ice extent, and ultimately better climate projections of Arctic sea ice behaviour and conditions decades ahead. This will be of benefit to decision making and long term planning for communities all around the Arctic, and others with a stakehold in the Arctic.

Specific benefits will include:

- Improvements to the fidelity of sea-ice drift in response to wind in operational forecast models. On time scales of days this is important for ship navigation and safety applications.
- Improved prediction of sea-ice extent and conditions in seasonal forecasts - this is important for planning purposes for shipping and other commercial activities in the Arctic Ocean.
- Improved performance of numerical weather prediction for mid-to-high latitude regions (including the UK). The Arctic can seem remote, but there are direct influences on UK weather through advection of Arctic air masses, and indirect influence through changes in the tracks of North Atlantic storms associated with changes to surface pressure field in a warmer Arctic.
- Improved fidelity of climate predictions - this is essential if an accurate assessment of future climate change is to be achieved. This need is particularly pressing for the Arctic regions due to the rapid rate of observed change, and the expected continuation (perhaps acceleration) of this change, but also impacts on predicted climate for the rest of the world.


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