Nadja Steiner

Multinational effort studies differences among arctic ocean models

The Arctic Ocean is an important component of the global climate system. The processes occurring in the Arctic Ocean affect the rate of deep and bottom water formation in the convective regions of the high North Atlantic and influence ocean circulation across the globe. This fact is highlighted by global climate modeling studies that consistently show the Arctic to be one of the most sensitive regions to climate change. But an identification of the differences among models and model systematic errors in the Arctic Ocean remains unchecked, despite being essential to interpreting the simulation results and their implications for climate variability. For this reason, the Arctic Ocean Model Intercomparison Project (AOMIP), an international effort, was recently established to carry out a thorough analysis of model differences and errors. The geographical focus of this effort is shown in Figure 1.

Comparing modeled streamfunction, heat and freshwater content in the Arctic Ocean

Within the framework of the Arctic Ocean Model Intercomparison Project results from several coupled sea ice–ocean models are compared in order to investigate vertically integrated properties of the Arctic Ocean. Annual means and seasonal ranges of streamfunction, freshwater and heat content are shown. For streamfunction the entire water column is integrated. For heat and freshwater content integration is over the upper 1000 m. The study represents a step toward identifying differences among model approaches and will serve as a base for upcoming studies where all models will be executed with common forcing. In this first stage only readily available outputs are compared, while forcing as well as numerical parameterizations differ. The intercomparison shows streamfunctions differing in pattern and by several Sverdrups in magnitude. Differences occur as well for the seasonal range, where streamfunction is subject to large variability.

Changing polar environments: Interdisciplinary challenges

In the past few decades, there has been enormous growth in scientific studies of physical, chemical, and biological interactions among reservoirs in polar regions. This has come, in part, as a result of a few significant discoveries: There is dramatic halogen chemistry that occurs on and above the sea ice in the springtime that destroys lower tropospheric ozone and mercury [Simpson et al., 2007; Steffen et al., 2008], the sunlit snowpack is very photochemically active [Grannas et al., 2007], biology as a source of organic compounds plays a pivotal role in these processes, and these processes are occurring in the context of rapidly changing polar regions under climate feedbacks that are as of yet not fully understood [Serreze and Barry, 2011]. Stimulated by the opportunities of the International Polar Year (IPY, 2007-2009), a number of large-scale field studies in both polar environments have been undertaken, aimed at the study of the complex biotic and abiotic processes occurring in all phases (see Figure 1). Sea ice plays a critical role in polar environments: It is a highly reflective surface that interacts with radiation; it provides a habitat for mammals and micro-organisms alike, thus playing a key role in polar trophic processes and elemental cycles; and it creates a saline environment for chemical processes that facilitate release of halogenated gases that contribute to the atmospheres ability to photochemically cleanse itself in an otherwise low-radiation environment. Ocean-air and sea ice-air interfaces also produce aerosol particles that provide cloud condensation nuclei.

Effects of subgrid-scale snow thickness variability on radiative transfer in sea ice

Snow is a principal factor in controlling heat and light fluxes through sea ice. With the goal of improving radiative and heat flux estimates through sea ice in regional and global models without the need of detailed snow property descriptions, a new parameterization including subgrid-scale snow thickness variability is presented. One-parameter snow thickness distributions depending only on the gridbox-mean snow thickness are introduced resulting in analytical solutions for the fluxes of heat and light through the snow layer. As the snowpack melts, these snow thickness distributions ensure a smooth seasonal transition of the light field under sea ice. Spatially homogenous melting applied to an inhomogeneous distribution of snow thicknesses allows the appearance of bare sea ice areas and melt ponds before all snow has melted. In comparison to uniform-thickness snow used in previous models, the bias in the under sea-ice light field is halved with this parameterization. Model results from a one-dimensional ocean turbulence model coupled with a thermodynamic sea ice model are compared to observations near Resolute in the Canadian High Arctic. The simulations show substantial improvements not only to the light field at the sea ice base which will affect ice algal growth but also to the sea ice and seasonal snowpack evolution. During melting periods, the snowpack can survive longer while sea ice thickness starts to reduce earlier.

Estimation of Arctic windspeeds and stresses with impacts on ocean–ice snow modeling

Abstract Climatologically averaged windspeed distributions, observed on ships and drift stations over the Arctic Ocean, are evaluated to form a basis for discussing different estimations of climatological mean reanalysis windspeeds and stresses. The various reanalysis speed and stress estimations show differences in magnitude as well as spatial pattern, where especially the NCEP-provided windstress seems overestimated. The discussion is supplemented by a sensitivity study, where various windstress estimations are applied to force a coupled ocean–ice snow model. Differences with respect to ice conditions, surface salinity, freshwater and heat contents, integrated over the top 1000 m, are evaluated. Over the range of windspeed and stress estimates, ice thickness varies by 1.5 m, differences in freshwater content are about 4 m in the Canada Basin and deviations in the vertically integrated heat content reach up to 2.8 GJ m −2 in the Eurasian and 1.0 GJ m −2 in the Canada Basin. It is shown that the difference in windstress magnitude takes over an important role. A reduction of the windstress magnitude by 25% leads to a decrease in ice thickness of almost 1.0 m in the Canada Basin and reduces Fram Strait ice export by about 450 km 3 year −1 . It also leads to a decrease of about 2 m in the vertically integrated freshwater content of the central Canada Basin and an increase of 0.4 GJ m −2 in the corresponding heat content.

Correction [to “Changing polar environments: Interdisciplinary challenges”]

Changing polar environments: Interdisciplinary challenges (Eos 93:11 (117-118) DOI: 10.1029/2012EO110001)