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Emulating atmosphere-ocean and carbon cycle models with a simpler model, MAGICC6 - Part 2: Applications

2011, Meinshausen, M., Raper, S.C.B., Wigley, T.M.L.

Intercomparisons of coupled atmosphere-ocean general circulation models (AOGCMs) and carbon cycle models are important for galvanizing our current scientific knowledge to project future climate. Interpreting such intercomparisons faces major challenges, not least because different models have been forced with different sets of forcing agents. Here, we show how an emulation approach with MAGICC6 can address such problems. In a companion paper (Meinshausen et al., 2011a), we show how the lower complexity carbon cycle-climate model MAGICC6 can be calibrated to emulate, with considerable accuracy, globally aggregated characteristics of these more complex models. Building on that, we examine here the Coupled Model Intercomparison Project's Phase 3 results (CMIP3). If forcing agents missed by individual AOGCMs in CMIP3 are considered, this reduces ensemble average temperature change from pre-industrial times to 2100 under SRES A1B by 0.4 °C. Differences in the results from the 1980 to 1999 base period (as reported in IPCC AR4) to 2100 are negligible, however, although there are some differences in the trajectories over the 21st century. In a second part of this study, we consider the new RCP scenarios that are to be investigated under the forthcoming CMIP5 intercomparison for the IPCC Fifth Assessment Report. For the highest scenario, RCP8.5, relative to pre-industrial levels, we project a median warming of around 4.6 °C by 2100 and more than 7 °C by 2300. For the lowest RCP scenario, RCP3-PD, the corresponding warming is around 1.5 °C by 2100, decreasing to around 1.1 °C by 2300 based on our AOGCM and carbon cycle model emulations. Implied cumulative CO2 emissions over the 21st century for RCP8.5 and RCP3-PD are 1881 GtC (1697 to 2034 GtC, 80% uncertainty range) and 381 GtC (334 to 488 GtC), when prescribing CO2 concentrations and accounting for uncertainty in the carbon cycle. Lastly, we assess the reasons why a previous MAGICC version (4.2) used in IPCC AR4 gave roughly 10% larger warmings over the 21st century compared to the CMIP3 average. We find that forcing differences and the use of slightly too high climate sensitivities inferred from idealized high-forcing runs were the major reasons for this difference.

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Emulating Atlantic overturning strength for low emission scenarios: Consequences for sea-level rise along the North American east coast

2011, Schleussner, C.F., Frieler, K., Meinshausen, M., Yin, J., Levermann, A.

In order to provide probabilistic projections of the future evolution of the Atlantic Meridional Overturning Circulation (AMOC), we calibrated a simple Stommeltype box model to emulate the output of fully coupled threedimensional atmosphere-ocean general circulation models (AOGCMs) of the Coupled Model Intercomparison Project (CMIP). Based on this calibration to idealised global warming scenarios with and without interactive atmosphere-ocean fluxes and freshwater perturbation simulations, we project the future evolution of the AMOC mean strength within the covered calibration range for the lower two Representative Concentration Pathways (RCPs) until 2100 obtained from the reduced complexity carbon cycle-climate model MAGICC 6. For RCP3-PD with a global mean temperature median below 1.0 C warming relative to the year 2000, we project an ensemble median weakening of up to 11% compared to 22% under RCP4.5 with a warming median up to 1.9 C over the 21st century. Additional Greenland meltwater of 10 and 20 cm of global sea-level rise equivalent further weakens the AMOC by about 4.5 and 10 %, respectively. By combining our outcome with a multi-model sea-level rise study we project a dynamic sea-level rise along the New York City coastline of 4 cm for the RCP3-PD and of 8 cm for the RCP4.5 scenario over the 21st century. We estimate the total steric and dynamic sea-level rise for New York City to be about 24 cm until 2100 for the RCP3-PD scenario, which can hold as a lower bound for sea-level rise projections in this region, as it does not include ice sheet and mountain glacier contributions.

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Unraveling gene regulatory networks from time-resolved gene expression data - a measures comparison study

2011, Hempel, Sabrina, Koseska, Aneta, Nikoloski, Zoran, Kurths, Jürgen, Walther, Dirk

Background Inferring regulatory interactions between genes from transcriptomics time-resolved data, yielding reverse engineered gene regulatory networks, is of paramount importance to systems biology and bioinformatics studies. Accurate methods to address this problem can ultimately provide a deeper insight into the complexity, behavior, and functions of the underlying biological systems. However, the large number of interacting genes coupled with short and often noisy time-resolved read-outs of the system renders the reverse engineering a challenging task. Therefore, the development and assessment of methods which are computationally efficient, robust against noise, applicable to short time series data, and preferably capable of reconstructing the directionality of the regulatory interactions remains a pressing research problem with valuable applications. Results Here we perform the largest systematic analysis of a set of similarity measures and scoring schemes within the scope of the relevance network approach which are commonly used for gene regulatory network reconstruction from time series data. In addition, we define and analyze several novel measures and schemes which are particularly suitable for short transcriptomics time series. We also compare the considered 21 measures and 6 scoring schemes according to their ability to correctly reconstruct such networks from short time series data by calculating summary statistics based on the corresponding specificity and sensitivity. Our results demonstrate that rank and symbol based measures have the highest performance in inferring regulatory interactions. In addition, the proposed scoring scheme by asymmetric weighting has shown to be valuable in reducing the number of false positive interactions. On the other hand, Granger causality as well as information-theoretic measures, frequently used in inference of regulatory networks, show low performance on the short time series analyzed in this study. Conclusions Our study is intended to serve as a guide for choosing a particular combination of similarity measures and scoring schemes suitable for reconstruction of gene regulatory networks from short time series data. We show that further improvement of algorithms for reverse engineering can be obtained if one considers measures that are rooted in the study of symbolic dynamics or ranks, in contrast to the application of common similarity measures which do not consider the temporal character of the employed data. Moreover, we establish that the asymmetric weighting scoring scheme together with symbol based measures (for low noise level) and rank based measures (for high noise level) are the most suitable choices.

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Greenland ice sheet model parameters constrained using simulations of the Eemian Interglacial

2011, Robinson, A., Calov, R., Ganopolski, A.

Using a new approach to force an ice sheet model, we performed an ensemble of simulations of the Greenland Ice Sheet evolution during the last two glacial cycles, with emphasis on the Eemian Interglacial. This ensemble was generated by perturbing four key parameters in the coupled regional climate-ice sheet model and by introducing additional uncertainty in the prescribed "background" climate change. The sensitivity of the surface melt model to climate change was determined to be the dominant driver of ice sheet instability, as reflected by simulated ice sheet loss during the Eemian Interglacial period. To eliminate unrealistic parameter combinations, constraints from present-day and paleo information were applied. The constraints include (i) the diagnosed present-day surface mass balance partition between surface melting and ice discharge at the margin, (ii) the modeled present-day elevation at GRIP; and (iii) the modeled elevation reduction at GRIP during the Eemian. Using these three constraints, a total of 360 simulations with 90 different model realizations were filtered down to 46 simulations and 20 model realizations considered valid. The paleo constraint eliminated more sensitive melt parameter values, in agreement with the surface mass balance partition assumption. The constrained simulations resulted in a range of Eemian ice loss of 0.4–4.4 m sea level equivalent, with a more likely range of about 3.7–4.4 m sea level if the GRIP δ18O isotope record can be considered an accurate proxy for the precipitation-weighted annual mean temperatures.

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Retrievals of chlorine chemistry kinetic parameters from Antarctic ClO microwave radiometer measurements

2011, Kremser, S., Schofield, R., Bodeker, G.E., Connor, B.J., Rex, M., Barret, J., Mooney, T., Salawitch, R.J., Canty, T., Frieler, K., Chipperfield, M.P., Langematz, U., Feng, W.

Key kinetic parameters governing the partitioning of chlorine species in the Antarctic polar stratosphere were retrieved from 28 days of chlorine monoxide (ClO) microwave radiometer measurements made during the late winter/early spring of 2005 at Scott Base (77.85° S, 166.75° E). During day-time the loss of the ClO dimer chlorine peroxide (ClOOCl) occurs mainly by photolysis. Some time after sunrise, a photochemical equilibrium is established and the ClO/ClOOCl partitioning is determined by the ratio of the photolysis frequency, J, and the dimer formation rate, kf. The values of J and kf from laboratory studies remain uncertain to a considerable extent, and as a complement to these ongoing studies, the goal of this work is to provide a constraint on that uncertainty based on observations of ClO profiles in the Antarctic. First an optimal estimation technique was used to derive J/kf ratios for a range of Keq values. The optimal estimation forward model was a photochemical box model that takes J, kf, and Keq as inputs, together with a priori profiles of activated chlorine (ClOx = ClO+2×ClOOCl), profiles of ozone, temperature, and pressure. JPL06 kinetics are used as a priori in the optimal estimation and for all other chemistry in the forward model. Using the more recent JPL09 kinetics results in insignificant differences in the retrieved value of J/kf. A complementary approach was used to derive the optimal kinetic parameters; the full parameter space of J, kf, Keq and ClOx was sampled to find the minimum in differences between measured and modelled ClO profiles. Furthermore, values of Keq up to 2.0 times larger than recommended by JPL06 were explored to test the sensitivity of the J/kf ratio to changes in Keq. The results show that the retrieved J/kf ratios bracket the range of 1.23 to 1.97 times the J/kf value recommended by JPL06 over the range of Keq values considered. The retrieved J/kf ratios lie in the lower half of the large uncertainty range of J/kf recommended by JPL06 and towards the upper portion of the smaller uncertainty range recommended by JPL09.

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The IPCC AR5 guidance note on consistent treatment of uncertainties: A common approach across the working groups

2011, Mastrandrea, Michael D., Mach, Katharine J., Plattner, Gian-Kasper, Edenhofer, Ottmar, Stocker, Thomas F., Field, Christopher B., Ebi, Kristie L., Matschoss, Patrick R.

Evaluation and communication of the relative degree of certainty in assessment findings are key cross-cutting issues for the three Working Groups of the Intergovernmental Panel on Climate Change. A goal for the Fifth Assessment Report, which is currently under development, is the application of a common framework with associated calibrated uncertainty language that can be used to characterize findings of the assessment process. A guidance note for authors of the Fifth Assessment Report has been developed that describes this common approach and language, building upon the guidance employed in past Assessment Reports. Here, we introduce the main features of this guidance note, with a focus on how it has been designed for use by author teams. We also provide perspectives on considerations and challenges relevant to the application of this guidance in the contribution of each Working Group to the Fifth Assessment Report. Despite the wide spectrum of disciplines encompassed by the three Working Groups, we expect that the framework of the new uncertainties guidance will enable consistent communication of the degree of certainty in their policy-relevant assessment findings.

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Carbon allocation and carbon isotope fluxes in the plant-soil-atmosphere continuum: A review

2011, Brüggemann, N., Gessler, A., Kayler, Z., Keel, S.G., Badeck, F., Barthel, M., Boeckx, P., Buchmann, N., Brugnoli, E., Esperschütz, J., Gavrichkova, O., Ghashghaie, J., Gomez-Casanovas, N., Keitel, C., Knohl, A., Kuptz, D., Palacio, S., Salmon, Y., Uchida, Y., Bahn, M.

The terrestrial carbon (C) cycle has received increasing interest over the past few decades, however, there is still a lack of understanding of the fate of newly assimilated C allocated within plants and to the soil, stored within ecosystems and lost to the atmosphere. Stable carbon isotope studies can give novel insights into these issues. In this review we provide an overview of an emerging picture of plant-soil-atmosphere C fluxes, as based on C isotope studies, and identify processes determining related C isotope signatures. The first part of the review focuses on isotopic fractionation processes within plants during and after photosynthesis. The second major part elaborates on plant-internal and plant-rhizosphere C allocation patterns at different time scales (diel, seasonal, interannual), including the speed of C transfer and time lags in the coupling of assimilation and respiration, as well as the magnitude and controls of plant-soil C allocation and respiratory fluxes. Plant responses to changing environmental conditions, the functional relationship between the physiological and phenological status of plants and C transfer, and interactions between C, water and nutrient dynamics are discussed. The role of the C counterflow from the rhizosphere to the aboveground parts of the plants, e.g. via CO2 dissolved in the xylem water or as xylem-transported sugars, is highlighted. The third part is centered around belowground C turnover, focusing especially on above- and belowground litter inputs, soil organic matter formation and turnover, production and loss of dissolved organic C, soil respiration and CO2 fixation by soil microbes. Furthermore, plant controls on microbial communities and activity via exudates and litter production as well as microbial community effects on C mineralization are reviewed. A further part of the paper is dedicated to physical interactions between soil CO2 and the soil matrix, such as CO2 diffusion and dissolution processes within the soil profile. Finally, we highlight state-of-the-art stable isotope methodologies and their latest developments. From the presented evidence we conclude that there exists a tight coupling of physical, chemical and biological processes involved in C cycling and C isotope fluxes in the plant-soil-atmosphere system. Generally, research using information from C isotopes allows an integrated view of the different processes involved. However, complex interactions among the range of processes complicate or currently impede the interpretation of isotopic signals in CO2 or organic compounds at the plant and ecosystem level. This review tries to identify present knowledge gaps in correctly interpreting carbon stable isotope signals in the plant-soil-atmosphere system and how future research approaches could contribute to closing these gaps.

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Emulating coupled atmosphere-ocean and carbon cycle models with a simpler model, MAGICC6 - Part 1: Model description and calibration

2011, Meinshausen, M., Raper, S.C.B., Wigley, T.M.L.

Current scientific knowledge on the future response of the climate system to human-induced perturbations is comprehensively captured by various model intercomparison efforts. In the preparation of the Fourth Assessment Report (AR4) of the Intergovernmental Panel on Climate Change (IPCC), intercomparisons were organized for atmosphere-ocean general circulation models (AOGCMs) and carbon cycle models, named "CMIP3" and "C4MIP", respectively. Despite their tremendous value for the scientific community and policy makers alike, there are some difficulties in interpreting the results. For example, radiative forcings were not standardized across the various AOGCM integrations and carbon cycle runs, and, in some models, key forcings were omitted. Furthermore, the AOGCM analysis of plausible emissions pathways was restricted to only three SRES scenarios. This study attempts to address these issues. We present an updated version of MAGICC, the simple carbon cycle-climate model used in past IPCC Assessment Reports with enhanced representation of time-varying climate sensitivities, carbon cycle feedbacks, aerosol forcings and ocean heat uptake characteristics. This new version, MAGICC6, is successfully calibrated against the higher complexity AOGCMs and carbon cycle models. Parameterizations of MAGICC6 are provided. The mean of the emulations presented here using MAGICC6 deviates from the mean AOGCM responses by only 2.2% on average for the SRES scenarios. This enhanced emulation skill in comparison to previous calibrations is primarily due to: making a "like-with-like comparison" using AOGCM-specific subsets of forcings; employing a new calibration procedure; as well as the fact that the updated simple climate model can now successfully emulate some of the climate-state dependent effective climate sensitivities of AOGCMs. The diagnosed effective climate sensitivity at the time of CO2 doubling for the AOGCMs is on average 2.88 °C, about 0.33 °C cooler than the mean of the reported slab ocean climate sensitivities. In the companion paper (Part 2) of this study, we examine the combined climate system and carbon cycle emulations for the complete range of IPCC SRES emissions scenarios and the new RCP pathways.

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Climate change under a scenario near 1.5° C of global warming: Monsoon intensification, ocean warming and steric sea level rise

2011, Schewe, J., Levermann, A., Meinshausen, M.

We present climatic consequences of the Representative Concentration Pathways (RCPs) using the coupled climate model CLIMBER-3α, which contains a statistical-dynamical atmosphere and a three-dimensional ocean model. We compare those with emulations of 19 state-of-the-art atmosphere-ocean general circulation models (AOGCM) using MAGICC6. The RCPs are designed as standard scenarios for the forthcoming IPCC Fifth Assessment Report to span the full range of future greenhouse gas (GHG) concentrations pathways currently discussed. The lowest of the RCP scenarios, RCP3-PD, is projected in CLIMBER-3α to imply a maximal warming by the middle of the 21st century slightly above 1.5 °C and a slow decline of temperatures thereafter, approaching today's level by 2500. We identify two mechanisms that slow down global cooling after GHG concentrations peak: The known inertia induced by mixing-related oceanic heat uptake; and a change in oceanic convection that enhances ocean heat loss in high latitudes, reducing the surface cooling rate by almost 50%. Steric sea level rise under the RCP3-PD scenario continues for 200 years after the peak in surface air temperatures, stabilizing around 2250 at 30 cm. This contrasts with around 1.3 m of steric sea level rise by 2250, and 2 m by 2500, under the highest scenario, RCP8.5. Maximum oceanic warming at intermediate depth (300–800 m) is found to exceed that of the sea surface by the second half of the 21st century under RCP3-PD. This intermediate-depth warming persists for centuries even after surface temperatures have returned to present-day values, with potential consequences for marine ecosystems, oceanic methane hydrates, and ice-shelf stability. Due to an enhanced land-ocean temperature contrast, all scenarios yield an intensification of monsoon rainfall under global warming.

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Exploring brain function from anatomical connectivity

2011, Zamora-López, Gorka, Zhou, Changsong, Kurths, Jürgen

The intrinsic relationship between the architecture of the brain and the range of sensory and behavioral phenomena it produces is a relevant question in neuroscience. Here, we review recent knowledge gained on the architecture of the anatomical connectivity by means of complex network analysis. It has been found that cortico-cortical networks display a few prominent characteristics: (i) modular organization, (ii) abundant alternative processing paths, and (iii) the presence of highly connected hubs. Additionally, we present a novel classification of cortical areas of the cat according to the role they play in multisensory connectivity. All these properties represent an ideal anatomical substrate supporting rich dynamical behaviors, facilitating the capacity of the brain to process sensory information of different modalities segregated and to integrate them toward a comprehensive perception of the real world. The results here exposed are mainly based on anatomical data of cats’ brain, but further observations suggest that, from worms to humans, the nervous system of all animals might share these fundamental principles of organization.