Jörg Schwinger

Nonlinearity of Ocean Carbon Cycle Feedbacks in CMIP5 Earth System Models

Carbon cycle feedbacks are usually categorized into carbon–concentration and carbon–climate feedbacks, which arise owing to increasing atmospheric CO2 concentration and changing physical climate. Both feedbacks are often assumedtooperateindependently:thatis,thetotalfeedbackcanbeexpressed asthesumoftwoindependentcarbon fluxes that are functions of atmospheric CO2 and climate change, respectively. For phase 5 of the Coupled Model Intercomparison Project (CMIP5), radiatively and biogeochemically coupled simulations have been undertaken to better understand carbon cycle feedback processes. Results show that the sum of total ocean carbon uptake in the radiatively and biogeochemically coupled experiments is consistently larger by 19–58 petagrams of carbon (Pg C) than the uptake found in the fully coupled model runs. This nonlinearity is small compared to the total ocean carbon uptake (533–676PgC), but it is of the same order as the carbon–climate feedback. The weakening of ocean circulation and mixing with climate change makes the largest contribution to the nonlinear carbon cycle response since carbon transport to depth is suppressed in the fully relative to the biogeochemically coupled simulations, while the radiatively coupled experiment mainly measures the loss of near-surface carbon owing to warming of the ocean. Sea ice retreat and seawater carbon chemistry contribute less to the simulated nonlinearity. The authors’ results indicate thatestimatesoftheocean carbon–climate feedback derived from‘‘warming only’’ (radiativelycoupled)simulations may underestimate the reduction of ocean carbon uptake in a warm climate high CO2 world.

Gravity field determination of a Comet Nucleus: Rosetta at P/Wirtanen

One of the prime objectives of the Rosetta Radio Science Investigations (RSI) experiment is the determination of the mass, the bulk density and the low degree and order gravity of the nucleus of comet P/Wirtanen, the target object of the international Rosetta mission. The RSI experiment will use the spacecrafts radio carrier frequencies at X-band (8.4 GHz) and S-band (2.3 GHz) in order to measure slight changes of the orbit velocity via the classical Doppler effect induced by the gravity attraction of the comet nucleus. Based on an estimate of the background Doppler noise, it is expected that a mass determination (assuming a representative radius of 700 m and a bulk density of 500 kg/m^3) at an accuracy of 0.1% can be achieved if the spacecrafts orbit is iteratively reduced below 7 km altitude. The gravity field of degree and order two can be detected for reasonable tracking times below 5 km altitude. The major competing forces acting on the spacecraft are the radiation pressure and the gas mass flux from cometary activity. While the radiation pressure may be predicted, it is recommended to begin a gravity mapping campaign well before the onset of outgassing activity (>3.25 AU heliocentric distance). Radial acceleration by water outgassing is larger by orders of magnitude than the accelerations from the low degree and order gravity field and will mask the contributions from the gravity field.

Net primary productivity estimates and environmental variables in the Arctic Ocean: An assessment of coupled physical-biogeochemical models

The relative skill of 21 regional and global biogeochemical models was assessed in terms of how well the models reproduced observed net primary productivity (NPP) and environmental variables such as nitrate concentration (NO3), mixed layer depth (MLD), euphotic layer depth (Zeu), and sea ice concentration, by comparing results against a newly updated, quality-controlled in situ NPP database for the Arctic Ocean (1959–2011). The models broadly captured the spatial features of integrated NPP (iNPP) on a pan-Arctic scale. Most models underestimated iNPP by varying degrees in spite of overestimating surface NO3, MLD, and Zeu throughout the regions. Among the models, iNPP exhibited little difference over sea ice condition (ice-free versus ice-influenced) and bottom depth (shelf versus deep ocean). The models performed relatively well for the most recent decade and toward the end of Arctic summer. In the Barents and Greenland Seas, regional model skill of surface NO3 was best associated with how well MLD was reproduced. Regionally, iNPP was relatively well simulated in the Beaufort Sea and the central Arctic Basin, where in situ NPP is low and nutrients are mostly depleted. Models performed less well at simulating iNPP in the Greenland and Chukchi Seas, despite the higher model skill in MLD and sea ice concentration, respectively. iNPP model skill was constrained by different factors in different Arctic Ocean regions. Our study suggests that better parameterization of biological and ecological microbial rates (phytoplankton growth and zooplankton grazing) are needed for improved Arctic Ocean biogeochemical modeling.

Description and evaluation of NorESM1-F: A fast version of theNorwegian Earth System Model (NorESM)

A new computationally efficient version of the Norwegian Earth System Model (NorESM) is presented. This new version (here termed NorESM1-F) runs about 2.5 times faster (e.g. 90 model years per day on current hardware) than the version that contributed to the fifth phase of the Coupled Model Intercomparison project (CMIP5), i.e., NorESM1-M, and is therefore particularly suitable for multi-millennial paleoclimate and carbon cycle simulations or large ensemble simulations. The speedup is 5 primarily a result of using a prescribed atmosphere aerosol chemistry and a tripolar ocean-sea ice horizontal grid configuration that allows an increase of the ocean-sea ice component time steps. Ocean biogeochemistry can be activated for fully coupled and semi-coupled carbon cycle applications. This paper describes the model and evaluates its performance using observations and NorESM1-M as benchmarks. The evaluation emphasises model stability, important large-scale features in the ocean and sea ice components, internal variability in the coupled system, and climate sensitivity. Simulation results from NorESM1-F 10 in general agree well with observational estimates, and show evident improvements over NorESM1-M, for example, in the strength of the meridional overturning circulation and sea ice simulation, both important metrics in simulating past and future climates. Whereas NorESM1-M showed a slight global cool bias in the upper oceans, NorESM1-F exhibits a global warm bias. In general, however, NorESM1-F has more similarities than dissimilarities compared to NorESM1-M, and some biases and deficiencies known in NorESM1-M remain. 15

Southern Ocean controls of the vertical marine δ 13 C gradient – a modelling study

δ13C, the standardised 13C / 12C ratio expressed in per mille, is a widely used ocean tracer to study changes in ocean circulation, water mass ventilation, atmospheric pCO2, and the biological carbon pump on timescales ranging from decades to tens of millions of years. δ13C data derived from ocean sediment core analysis provide information on δ13C of dissolved inorganic carbon and the vertical δ13C gradient (i.e. 1δ13C) in past oceans. In order to correctly interpret δ13C and 1δ13C variations, a good understanding is needed of the influence from ocean circulation, air–sea gas exchange and biological productivity on these variations. The Southern Ocean is a key region for these processes, and we show here that 1δ13C in all ocean basins is sensitive to changes in the biogeochemical state of the Southern Ocean. We conduct a set of idealised sensitivity experiments with the ocean biogeochemistry general circulation model HAMOCC2s to explore the effect of biogeochemical state changes of the Southern and Global Ocean on atmospheric δ13C, pCO2, and marine δ13C and 1δ13C. The experiments cover changes in air–sea gas exchange rates, particulate organic carbon sinking rates, sea ice cover, and nutrient uptake efficiency in an unchanged ocean circulation field. Our experiments show that global mean 1δ13C varies by up to about ±0.35 ‰ around the pre-industrial model reference (1.2 ‰) in response to biogeochemical change. The amplitude of this sensitivity can be larger at smaller scales, as seen from a maximum sensitivity of about−0.6 ‰ on ocean basin scale. The ocean’s oldest water (North Pacific) responds most to biological changes, the young deep water (North Atlantic) responds strongly to air–sea gas exchange changes, and the vertically well-mixed water (SO) has a low or even reversed 1δ13C sensitivity compared to the other basins. This local 1δ13C sensitivity depends on the local thermodynamic disequilibrium and the 1δ13C sensitivity to local POC export production changes. The direction of both glacial (intensification of 1δ13C) and interglacial (weakening of 1δ13C) 1δ13C change matches the direction of the sensitivity of biogeochemical processes associated with these periods. This supports the idea that biogeochemistry likely explains part of the reconstructed variations in1δ13C, in addition to changes in ocean circulation.