Enhanced Process Understanding of the Coupled Arctic Atmosphere-Ice-Ocean System through MOSAiC The Multidisciplinary drifting Observatory for the Study of Arctic Climate Matthew Shupe – Univ. of Colorado/NOAA On Behalf of the MOSAiC Science Team 9 December 2015

Dukhovskoy et al. 2006 www.iarc.uaf.edu Francis et al. 2009 The Arctic sea-ice pack looks like a mosaic itself, and the Arctic climate system is comprised of a mosaic of complex, interdependent processes. These are complex and potentially changing as the surface interface in the central Arctic is changing.

Central Arctic Energy Budget 2006 Incoming solar radiation Outgoing LW Reflected solar emitted by atmosphere Absorbed by atmosphere 2010 Atmosphere back radiation Turbulence Reflected surface Large-scale advection Energy is an important aspect of the coupled system. We know how some of this system works, but there are some confounding details, particularly how these details are changing. Decadal sea-ice decline can be explained by about 1 W/m2 of excess energy in the system, but we struggle to represent the key processes at that level. Can we characterize these fluxes in a 1st year ice environment? Can we appropriately represent heterogeneity and inter-disciplinary processes? Absorbed by ice 2012 Sea ice Emitted-Absorbed by ice Sea ice Transmitted Turbulence Ocean

Coupling Mixed-phase clouds accompany warm moist advection aloft; Impacts BL structure. Liquid clouds increase LWdown by 40-70 W/m2 >> Significant change in surface energy budget. Points: One cannot really understand the variability in the sea-ice temperatures without understanding variability in SEB that is related to atmospheric conditions leading to liquid water clouds. Thermal structure of snow and ice responds >> Conduction of heat through ice responds

Critical Model Shortcomings Inhibit our Understanding IPCC: “Further, understanding of the polar climate system is still incomplete due to its complex atmosphere-land-cryosphere-ocean-ecosystem interactions involving a variety of distinctive feedbacks…. A serious problem is the lack of observations against which to assess models, and for developing process knowledge……” Among the primary causes of biases in simulated sea ice: High-latitude winds Vertical and horizontal mixing in the ocean Surface heat flux errors Atmospheric boundary layer High-latitude cloudiness Cloud feedbacks remain one of the largest contributors to model uncertainty, globally. Role of clouds in the Arctic is relatively unknown (IPCC couldn’t even comment on it one way or another because of so little information). Aerosol implications are complicated by long transport distances, limited local sources, mixed-phase processees IPCC emphasizes the need to further develop models that can represent the drastic changes that are occurring, particularly handling issues such as abrupt changes, feedbacks, non-linear responses, etc.

Central Arctic Basin ice pack MOSAiC Plan Drifting, interdisciplinary process study in central Arctic (1st-year) sea ice: Central observatory: intensive atmos-ice-ocean-ecosystem observations Distributed Network: Heterogeneity on model grid-box scale Coordinated, multi-scale analysis & modeling activities, Links with YOPP Sea ice is the integrator of fluxes in the system 2019-2020, annual cycle Central Arctic Basin ice pack 4

MOSAiC Science Drivers Leading Science Question: “What are the causes and consequences of an evolving and diminished Arctic sea ice cover?” Sea-ice energy budget Ice movement & deformation Clouds / Precip / Aerosols BioGeoChemistry and Ecosystems Large-scale linkages Typically the arctic system is studied only as individual disciplines. Our experiments are often designed that way, such that we don’t have the cross-disciplinary measurements to develop the coupled system processes needed in models. MOSAiC is designed to help address this gap. The top-level question is about sea-ice. But importantly it is about the sea-ice lifecycle, which integrates the forcings/fluxes that flow through the coupled system. Ultimately, the balance/budget of these forcings must be changing in order for the observed sea-ice decline to occur.

ocean and ice biogeochem Measurements atmospheric profiling, BL, & dynamics gases, aerosols, clouds & precip. aircraft + UASs surface energy budget buoys, AUVs, gliders ocean and ice biogeochem These are just example measurements. A complete list will be developed based on the specific science objectives. ice thermodynamics, dynamics, optics ocean state, profiling, & dynamics leads & ocean surface

90o Contaminated turbulence zone Initial open water Dominant wind BC Snow surveys / ice optics / mass balance SHIP NATIONAL PARK 500 m Ice hut Power line HUT OCEAN CITY small CTD µstructure profiler/ net sampling – 1 or 2 holes SODAR ITP Ocean flux ARM IMB Sampling here as ice forms Met tower HUT Acoustic camera Big holes CTD Ocean eddy Net sampling ROV ICE CORE FARM Ice optics 90o Contaminated turbulence zone Structures Met hut – wood ARM - container Ocean - tent Ice - tent Snow surveys / ice optics / mass balance + ice sites at ~2km BC BC

Planning the Constellation Ice and coupled-system obs at multiple scales Deformation at many scales Spatial coverage with UAS

If you think MOSAiC is needed, let your program managers know! MOSAiC into the Future Finalize Science Plan – Start 2016 Implementation Plan – March 2016 US interagency proposals – 2016 EU Proposals – 2016 MOSAiC Open Science Meeting – 2016-2017 Field deployment – September 2019 If you think MOSAiC is needed, let your program managers know! Thanks! We have a science plan writing team assembled – composed of 16 people representing a variety of nations, observation and model perspectives, and the IASC Atmos., Marine, and Cryosphere WGs. The team is currently working to collaboratively write the science plan based on information gathered from past workshops. www.mosaicobservatory.org