2011, Perrette, M., Yool, A., Quartly, G.D., Popova, E.E.

Ice-edge blooms are significant features of Arctic primary production, yet have received relatively little attention. Here we combine satellite ocean colour and sea-ice data in a pan-Arctic study. Ice-edge blooms occur in all seasonally ice-covered areas and from spring to late summer, being observed in 77-89% of locations for which adequate data exist, and usually peaking within 20 days of ice retreat. They sometimes form long belts along the ice-edge (greater than 100 km), although smaller structures were also found. The bloom peak is on average more than 1 mg m-3, with major blooms more than 10 mg m -3, and is usually located close to the ice-edge, though not always. Some propagate behind the receding ice-edge over hundreds of kilometres and over several months, while others remain stationary. The strong connection between ice retreat and productivity suggests that the ongoing changes in Arctic sea-ice may have a significant impact on higher trophic levels and local fish stocks.

2015, Robinson, A., Perrette, M.

The NetCDF (Network Common Data Form) library has become an indispensable tool for data and model output management in geoscience. However for simple tasks, particularly in Fortran, the complexity of native NetCDF functionality can be cumbersome. The NCIO (NetCDF Input/Output) module has been designed as an interface to the NetCDF library with simplicity and ease of use in mind. While this implies that some NetCDF functionality is masked from the user, the subroutines provided here are adequate for basic serial reading and writing tasks of up to 6-D data arrays along with corresponding data attributes. The code is available online via a GitHub repository (http://www.github.com/alex-robinson/ncio), which includes an example program to illustrate the approach.

2013, Perrette, M., Landerer, F., Riva, R., Frieler, K., Meinshausen, M.

Climate change causes global mean sea level to rise due to thermal expansion of seawater and loss of land ice from mountain glaciers, ice caps and ice sheets. Locally, sea level can strongly deviate from the global mean rise due to changes in wind and ocean currents. In addition, gravitational adjustments redistribute seawater away from shrinking ice masses. However, the land ice contribution to sea level rise (SLR) remains very challenging to model, and comprehensive regional sea level projections, which include appropriate gravitational adjustments, are still a nascent field (Katsman et al., 2011; Slangen et al., 2011). Here, we present an alternative approach to derive regional sea level changes for a range of emission and land ice melt scenarios, combining probabilistic forecasts of a simple climate model (MAGICC6) with the new CMIP5 general circulation models. The contribution from ice sheets varies considerably depending on the assumptions for the ice sheet projections, and thus represents sizeable uncertainties for future sea level rise. However, several consistent and robust patterns emerge from our analysis: at low latitudes, especially in the Indian Ocean and Western Pacific, sea level will likely rise more than the global mean (mostly by 10–20%). Around the northeastern Atlantic and the northeastern Pacific coasts, sea level will rise less than the global average or, in some rare cases, even fall. In the northwestern Atlantic, along the American coast, a strong dynamic sea level rise is counteracted by gravitational depression due to Greenland ice melt; whether sea level will be above- or below-average will depend on the relative contribution of these two factors. Our regional sea level projections and the diagnosed uncertainties provide an improved basis for coastal impact analysis and infrastructure planning for adaptation to climate change.

2015, Calov, R., Robinson, A., Perrette, M., Ganopolski, A.

In this paper, we propose a new sub-grid scale parameterization for the ice discharge into the ocean through outlet glaciers and inspect the role of different observational and palaeo constraints for the choice of an optimal set of model parameters. This parameterization was introduced into the polythermal ice-sheet model SICOPOLIS, which is coupled to the regional climate model of intermediate complexity REMBO. Using the coupled model, we performed large ensemble simulations over the last two glacial cycles by varying two major parameters: a melt parameter in the surface melt scheme of REMBO and a discharge scaling parameter in our parameterization of ice discharge. Our empirical constraints are the present-day Greenland ice sheet surface elevation, the surface mass balance partition (ratio between total ice discharge and total precipitation) and the Eemian interglacial elevation drop relative to present day in the vicinity of the NEEM ice core. We show that the ice discharge parameterization enables us to simulate both the correct ice-sheet shape and mass balance partition at the same time without explicitly resolving the Greenland outlet glaciers. For model verification, we compare the simulated total and sectoral ice discharge with other estimates. For the model versions that are consistent with the range of observational and palaeo constraints, our simulated Greenland ice sheet contribution to Eemian sea-level rise relative to present-day amounts to 1.4 m on average (in the range of 0.6 and 2.5 m).

2013, Eby, M., Weaver, A.J., Alexander, K., Zickfeld, K., Abe-Ouchi, A., Cimatoribus, A.A., Crespin, E., Drijfhout, S.S., Edwards, N.R., Eliseev, A.V., Feulner, G., Fichefet, T., Forest, C.E., Goosse, H., Holden, P.B., Joos, F., Kawamiya, M., Kicklighter, D., Kienert, H., Matsumoto, K., Mokhov, I.I., Monier, E., Olsen, S.M., Pedersen, J.O.P., Perrette, M., Philippon-Berthier, G., Ridgwell, A., Schlosser, A., Schneider von Deimling, T., Shaffer, G., Smith, R.S., Spahni, R., Sokolov, A.P., Steinacher, M., Tachiiri, K., Tokos, K., Yoshimori, M., Zeng, N., Zhao, F.

Both historical and idealized climate model experiments are performed with a variety of Earth system models of intermediate complexity (EMICs) as part of a community contribution to the Intergovernmental Panel on Climate Change Fifth Assessment Report. Historical simulations start at 850 CE and continue through to 2005. The standard simulations include changes in forcing from solar luminosity, Earth's orbital configuration, CO2, additional greenhouse gases, land use, and sulphate and volcanic aerosols. In spite of very different modelled pre-industrial global surface air temperatures, overall 20th century trends in surface air temperature and carbon uptake are reasonably well simulated when compared to observed trends. Land carbon fluxes show much more variation between models than ocean carbon fluxes, and recent land fluxes appear to be slightly underestimated. It is possible that recent modelled climate trends or climate–carbon feedbacks are overestimated resulting in too much land carbon loss or that carbon uptake due to CO2 and/or nitrogen fertilization is underestimated. Several one thousand year long, idealized, 2 × and 4 × CO2 experiments are used to quantify standard model characteristics, including transient and equilibrium climate sensitivities, and climate–carbon feedbacks. The values from EMICs generally fall within the range given by general circulation models. Seven additional historical simulations, each including a single specified forcing, are used to assess the contributions of different climate forcings to the overall climate and carbon cycle response. The response of surface air temperature is the linear sum of the individual forcings, while the carbon cycle response shows a non-linear interaction between land-use change and CO2 forcings for some models. Finally, the preindustrial portions of the last millennium simulations are used to assess historical model carbon-climate feedbacks. Given the specified forcing, there is a tendency for the EMICs to underestimate the drop in surface air temperature and CO2 between the Medieval Climate Anomaly and the Little Ice Age estimated from palaeoclimate reconstructions. This in turn could be a result of unforced variability within the climate system, uncertainty in the reconstructions of temperature and CO2, errors in the reconstructions of forcing used to drive the models, or the incomplete representation of certain processes within the models. Given the forcing datasets used in this study, the models calculate significant land-use emissions over the pre-industrial period. This implies that land-use emissions might need to be taken into account, when making estimates of climate–carbon feedbacks from palaeoclimate reconstructions.