MOSAiC Boundary Layer

The Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) initiative is a major international programme motivated by the rapid changes in Arctic climate observed over the last few decades. This is driven by an accelerated rise in the mean temperature of the Arctic; which is warming at 2-3 times the mean global rate. The most visible change is the dramatic reduction in sea ice extent, particularly of the summer minimum, which is decreasing at a rate of 13% per decade.

These rapid changes are the result of a combination of feedback processes - the best known is the ice albedo feedback, whereby the loss of ice exposes the land or sea surface beneath, lowering the area mean albedo and allowing more solar radiation to be absorbed, which warms the surface and enhances ice melt. Other feedbacks relate to the vertical profiles of atmospheric temperature and humidity, cloud properties, and large-scale atmospheric circulation.

While climate models also show enhanced warming in the Arctic, they do not reproduce many of the observed details of the change; for example they do not reproduce the very rapid decline in the summer sea ice minimum observed over the last 10 years, and there are big differences between models. This has a significant impact on our ability to predict the future state of climate system. Poor model performance results from multiple leading-order deficiencies in their representation of physical processes in the Arctic system. MOSAiC aims to address these through a large-scale coordinated approach, making simultaneous measurements of the many interdependent processes relevant to climate over a full calendar year. This approach is necessary because of the strong linkages and feedbacks between different parts of the Arctic climate system and the strong seasonality in many processes. The observational campaign will take place on, and around, the icebreaker Polarstern, which will be frozen in at the edge of the pack ice at the end of the summer melt. This provides ready access to both multi-year ice within the pack and to freshly forming ice just outside it. Measurements will be made of all components of the surface energy budget on both the upper and lower sides of the ice, along with ice thickness, temperature, physical properties, topography, and deformation over time. The processes controlling the energy budget, including synoptic-scale forcing, cloud properties, turbulent mixing, and the interactions between them, will be studied in detail.

The measurements will be complemented by an extensive modelling programme, spanning a full range from small scale process studies up to global climate modelling.

The last study to attempt anything remotely comparable to MOSAiC was the Surface Heat Budget of the Arctic (SHEBA) project, which undertook a much more limited set of measurements over 11 months in 1997-1998. The area where SHEBA took place is now ice-free every summer, emphasising the changes that have taken place since then.

This proposal is a core contribution to the atmospheric science component of MOSAiC. We will make detailed measurements of lower atmosphere mean and turbulent dynamics for the duration of the measurement campaign. Several remote sensing systems (Doppler sodar and lidar) will be deployed to make continuous measurements mean wind profiles throughout the boundary layer. Retrievals of the vertical turbulence structure will allow the complex interactions between clouds, the boundary layer, and the surface to be understood and thus the primary controls on the surface energy budget and ice melt and formation to be better represented in models. Such detailed measurements of the vertical dynamic structure of the boundary layer will be unique in the Arctic, no comparable data set exists. In addition to our science they underpin many aspects of MOSAiC science being undertaken by other groups, and are considered essential by the MOSAiC atmospheric science coordinators.

This project has a specific focus on turbulent processes in the Arctic boundary layer, and their interaction with both sea ice and clouds. Our initial goal is to make a substantial step change in our understanding of these processes - currently poorly represented in models. We will then implement the new understanding in parameterizations better suited to the Arctic environment. The ultimate impacts of this work will be in improved weather forecasts, seasonal sea ice prediction, and climate projections.

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 understanding of, and ultimately the model representation of, multiple processes controlling the interactions between clouds and the surface. This will ultimately lead to much more accurate representation of the surface energy budget, the rates of ice melt and formation, and the motion and evolution of sea ice in the Arctic Ocean. The improvements to model fidelity should result 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 stake hold in the Arctic.

Specific benefits include:
- 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.