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As part of the Model Intercomparison Project on the climatic response to Volcanic forcing (VolMIP), several climate modeling centers performed a coordinated pre-study experiment with interactive stratospheric aerosol models simulating the volcanic aerosol cloud from an eruption resembling the 1815 Mt. Tambora eruption (VolMIP-Tambora ISA ensemble). The pre-study provided the ancillary ability to assess intermodel diversity in the radiative forcing for a large stratospheric-injecting equatorial eruption when the volcanic aerosol cloud is simulated interactively. An initial analysis of the VolMIP-Tambora ISA ensemble showed large disparities between models in the stratospheric global mean aerosol optical depth (AOD). In this study, we now show that stratospheric global mean AOD differences among the participating models are primarily due to differences in aerosol size, which we track here by effective radius. We identify specific physical and chemical processes that are missing in some models and/or parameterized differently between models, which are together causing the differences in effective radius. In particular, our analysis indicates that interactively tracking hydroxyl radical (OH) chemistry following a large volcanic injection of sulfur dioxide (SO2) is an important factor in allowing for the timescale for sulfate formation to be properly simulated. In addition, depending on the timescale of sulfate formation, there can be a large difference in effective radius and subsequently AOD that results from whether the SO2 is injected in a single model grid cell near the location of the volcanic eruption, or whether it is injected as a longitudinally averaged band around the Earth.

We present a 2700-year annually resolved chronology and snow accumulation history for the Roosevelt Island Climate Evolution (RICE) ice core, Ross Ice Shelf, West Antarctica. The core adds information on past accumulation changes in an otherwise poorly constrained sector of Antarctica. The timescale was constructed by identifying annual cycles in high-resolution impurity records, and it constitutes the top part of the Roosevelt Island Ice Core Chronology 2017 (RICE17). Validation by volcanic and methane matching to the WD2014 chronology from the WAIS Divide ice core shows that the two timescales are in excellent agreement. In a companion paper, gas matching to WAIS Divide is used to extend the timescale for the deeper part of the core in which annual layers cannot be identified. Based on the annually resolved timescale, we produced a record of past snow accumulation at Roosevelt Island. The accumulation history shows that Roosevelt Island experienced slightly increasing accumulation rates between 700 BCE and 1300 CE, with an average accumulation of 0.25±0.02 m water equivalent (w.e.) per year. Since 1300 CE, trends in the accumulation rate have been consistently negative, with an acceleration in the rate of decline after the mid-17th century. The current accumulation rate at Roosevelt Island is 0.210±0.002 m w.e. yr−1 (average since 1965 CE, ±2σ), and it is rapidly declining with a trend corresponding to 0.8 mm yr−2. The decline observed since the mid-1960s is 8 times faster than the long-term decreasing trend taking place over the previous centuries, with decadal mean accumulation rates consistently being below average. Previous research has shown a strong link between Roosevelt Island accumulation rates and the location and intensity of the Amundsen Sea Low, which has a significant impact on regional sea-ice extent. The decrease in accumulation rates at Roosevelt Island may therefore be explained in terms of a recent strengthening of the ASL and the expansion of sea ice in the eastern Ross Sea. The start of the rapid decrease in RICE accumulation rates observed in 1965 CE may thus mark the onset of significant increases in regional sea-ice extent.

Ice sheet numerical modeling is an important tool to estimate the dynamic contribution of the Antarctic ice sheet to sea level rise over the coming centuries. The influence of initial conditions on ice sheet model simulations, however, is still unclear. To better understand this influence, an initial state intercomparison exercise (initMIP) has been developed to compare, evaluate, and improve initialization procedures and estimate their impact on century-scale simulations. initMIP is the first set of experiments of the Ice Sheet Model Intercomparison Project for CMIP6 (ISMIP6), which is the primary Coupled Model Intercomparison Project Phase 6 (CMIP6) activity focusing on the Greenland and Antarctic ice sheets. Following initMIP-Greenland, initMIP-Antarctica has been designed to explore uncertainties associated with model initialization and spin-up and to evaluate the impact of changes in external forcings. Starting from the state of the Antarctic ice sheet at the end of the initialization procedure, three forward experiments are each run for 100 years: a control run, a run with a surface mass balance anomaly, and a run with a basal melting anomaly beneath floating ice. This study presents the results of initMIP-Antarctica from 25 simulations performed by 16 international modeling groups. The submitted results use different initial conditions and initialization methods, as well as ice flow model parameters and reference external forcings. We find a good agreement among model responses to the surface mass balance anomaly but large variations in responses to the basal melting anomaly. These variations can be attributed to differences in the extent of ice shelves and their upstream tributaries, the numerical treatment of grounding line, and the initial ocean conditions applied, suggesting that ongoing efforts to better represent ice shelves in continental-scale models should continue.

The Arctic Mediterranean (AM) is the collective name for the Arctic Ocean, the Nordic Seas, and their adjacent shelf seas. Water enters into this region through the Bering Strait (Pacific inflow) and through the passages across the Greenland–Scotland Ridge (Atlantic inflow) and is modified within the AM. The modified waters leave the AM in several flow branches which are grouped into two different categories: (1) overflow of dense water through the deep passages across the Greenland–Scotland Ridge, and (2) outflow of light water – here termed surface outflow – on both sides of Greenland. These exchanges transport heat and salt into and out of the AM and are important for conditions in the AM. They are also part of the global ocean circulation and climate system. Attempts to quantify the transports by various methods have been made for many years, but only recently the observational coverage has become sufficiently complete to allow an integrated assessment of the AM exchanges based solely on observations. In this study, we focus on the transport of water and have collected data on volume transport for as many AM-exchange branches as possible between 1993 and 2015. The total AM import (oceanic inflows plus freshwater) is found to be 9.1 Sv (sverdrup, 1 Sv =106 m3 s−1) with an estimated uncertainty of 0.7 Sv and has the amplitude of the seasonal variation close to 1 Sv and maximum import in October. Roughly one-third of the imported water leaves the AM as surface outflow with the remaining two-thirds leaving as overflow. The overflow water is mainly produced from modified Atlantic inflow and around 70 % of the total Atlantic inflow is converted into overflow, indicating a strong coupling between these two exchanges. The surface outflow is fed from the Pacific inflow and freshwater (runoff and precipitation), but is still approximately two-thirds of modified Atlantic water. For the inflow branches and the two main overflow branches (Denmark Strait and Faroe Bank Channel), systematic monitoring of volume transport has been established since the mid-1990s, and this enables us to estimate trends for the AM exchanges as a whole. At the 95 % confidence level, only the inflow of Pacific water through the Bering Strait showed a statistically significant trend, which was positive. Both the total AM inflow and the combined transport of the two main overflow branches also showed trends consistent with strengthening, but they were not statistically significant. They do suggest, however, that any significant weakening of these flows during the last two decades is unlikely and the overall message is that the AM exchanges remained remarkably stable in the period from the mid-1990s to the mid-2010s. The overflows are the densest source water for the deep limb of the North Atlantic part of the meridional overturning circulation (AMOC), and this conclusion argues that the reported weakening of the AMOC was not due to overflow weakening or reduced overturning in the AM. Although the combined data set has made it possible to establish a consistent budget for the AM exchanges, the observational coverage for some of the branches is limited, which introduces considerable uncertainty. This lack of coverage is especially extreme for the surface outflow through the Denmark Strait, the overflow across the Iceland–Faroe Ridge, and the inflow over the Scottish shelf. We recommend that more effort is put into observing these flows as well as maintaining the monitoring systems established for the other exchange branches.

We present 17 velocity records derived from in situ stand-alone single-frequency Global Positioning System (GPS) receivers placed on eight marine-terminating ice sheet outlet glaciers in South, West and North Greenland, covering varying parts of the period summer 2009 to summer 2012. Common to all the observed glacier velocity records is a pronounced seasonal variation, with an early melt season maximum generally followed by a rapid mid-melt season deceleration. The GPS-derived velocities are compared to velocities derived from radar satellite imagery over six of the glaciers to illustrate the potential of the GPS data for validation purposes. Three different velocity map products are evaluated, based on ALOS/PALSAR data, TerraSAR-X/Tandem-X data and an aggregate winter TerraSAR-X data set. The velocity maps derived from TerraSAR-X/Tandem-X data have a mean difference of 1.5% compared to the mean GPS velocity over the corresponding period, while velocity maps derived from ALOS/PALSAR data have a mean difference of 9.7%. The velocity maps derived from the aggregate winter TerraSAR-X data set have a mean difference of 9.5% to the corresponding GPS velocities. The data are available from the GEUS repository at doi:10.5280/GEUS000001.

In 2013, an ice core was recovered from Roosevelt Island in the Ross Sea, Antarctica, as part of the Roosevelt Island Climate Evolution (RICE) project. Roosevelt Island is located between two submarine troughs carved by paleo-ice-streams. The RICE ice core provides new important information about the past configuration of the West Antarctic Ice Sheet and its retreat during the most recent deglaciation. In this work, we present the RICE17 chronology and discuss preliminary observations from the new records of methane, the isotopic composition of atmospheric molecular oxygen (δ18O-Oatm), the isotopic composition of atmospheric molecular nitrogen (δ15N-N2) and total air content (TAC). RICE17 is a composite chronology combining annual layer interpretations, gas synchronization, and firn modeling strategies in different sections of the core. An automated matching algorithm is developed for synchronizing the high-resolution section of the RICE gas records (60–720 m, 1971 CE to 30 ka) to corresponding records from the WAIS Divide ice core, while deeper sections are manually matched. Ice age for the top 343 m (2635 yr BP, before 1950 C.E.) is derived from annual layer interpretations and described in the accompanying paper by Winstrup et al. (2017). For deeper sections, the RICE17 ice age scale is based on the gas age constraints and the ice age-gas age offset estimated by a firn densification model. Novel aspects of this work include: 1) stratigraphic matching of centennial-scale variations in methane for pre-anthropogenic time periods, a strategy which will be applicable for developing precise chronologies for future ice cores, 2) the observation of centennial-scale variability in methane throughout the Holocene which suggests that similar variations during the late preindustrial period need not be anthropogenic, and 3) the observation of continuous climate records dating back to ∼ 65 ka which provide evidence that the Roosevelt Island Ice Dome was a constant feature throughout the last glacial period.

As part of the GlobColour project, daily chlorophyll a observations, derived using remotely sensed ocean colour data from the MERIS, MODIS and SeaWiFS sensors, are produced. The ability of these products to be assimilated into a pre-operational global coupled physical-biogeochemical model has been tested, on both a hindcast and near-real-time basis, and the impact on the system assessed. The assimilation was found to immediately and considerably improve the bias, root mean square error and correlation of modelled surface chlorophyll concentration compared to the GlobColour observations, an improvement which was sustained throughout the year and in every ocean basin. Errors against independent in situ chlorophyll observations were also reduced, both at and beneath the ocean surface. However, the model fit to in situ observations was not consistently better than that of climatology, due to errors in the underlying model. The assimilation scheme used is multivariate, updating all biogeochemical model state variables at all depths. The other variables were not degraded by the assimilation, with annual mean surface fields of nutrients, alkalinity and carbon variables remaining of similar quality compared to climatology. There was evidence of improved representation of zooplankton concentration, and reduced errors were seen against in situ observations of nitrate and pCO2, but too few observations were available to conclude about global model skill. The near-real-time GlobColour products were found to be sufficiently reliable for operational purposes, and of benefit to both operational-style systems and reanalyses.

Measurements of the status and trends of key indicators for the ocean and marine life are required to inform policy and management in the context of growing human uses of marine resources, coastal development, and climate change. Two synergistic efforts identify specific priority variables for monitoring: Essential Ocean Variables (EOVs) through the Global Ocean Observing System (GOOS), and Essential Biodiversity Variables (EBVs) from the Group on Earth Observations Biodiversity Observation Network (GEO BON) (see Data Sheet 1 in Supplementary Materials for a glossary of acronyms). Both systems support reporting against internationally agreed conventions and treaties. GOOS, established under the auspices of the Intergovernmental Oceanographic Commission (IOC), plays a leading role in coordinating global monitoring of the ocean and in the definition of EOVs. GEO BON is a global biodiversity observation network that coordinates observations to enhance management of the world’s biodiversity and promote both the awareness and accounting of ecosystem services. Convergence and agreement between these two efforts are required to streamline existing and new marine observation programs to advance scientific knowledge effectively and to support the sustainable use and management of ocean spaces and resources. In this context, the Marine Biodiversity Observation Network (MBON), a thematic component of GEO BON, is collaborating with GOOS, the Ocean Biogeographic Information System (OBIS), and the Integrated Marine Biosphere Research (IMBeR) project to ensure that EBVs and EOVs are complementary, representing alternative uses of a common set of scientific measurements. This work is informed by the Joint Technical Commission for Oceanography and Marine Meteorology (JCOMM), an intergovernmental body of technical experts that helps international coordination on best practices for observing, data management and services, combined with capacity development expertise. Characterizing biodiversity and understanding its drivers will require incorporation of observations fromtraditional andmolecular taxonomy, animal tagging and tracking efforts, ocean biogeochemistry, and ocean observatory initiatives including the deep ocean and seafloor. The partnership between large-scale ocean observing and product distribution initiatives (MBON, OBIS, JCOMM, and GOOS) is an expedited, effective way to support international policy-level assessments (e.g., the Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services or IPBES), along with the implementation of international development goals (e.g., the United Nations Sustainable Development Goals). Refereed 14 Manual (incl. handbook, guide, cookbook etc) 2018-06-27

We apply a new parameterisation of the Greenland ice sheet (GrIS) feedback between surface mass balance (SMB: the sum of surface accumulation and surface ablation) and surface elevation in the MAR regional climate model (Edwards et al., 2014) to projections of future climate change using five ice sheet models (ISMs). The MAR (Modèle Atmosphérique Régional: Fettweis, 2007) climate projections are for 2000–2199, forced by the ECHAM5 and HadCM3 global climate models (GCMs) under the SRES A1B emissions scenario. The additional sea level contribution due to the SMB–elevation feedback averaged over five ISM projections for ECHAM5 and three for HadCM3 is 4.3% (best estimate; 95% credibility interval 1.8–6.9%) at 2100, and 9.6% (best estimate; 95% credibility interval 3.6–16.0%) at 2200. In all results the elevation feedback is significantly positive, amplifying the GrIS sea level contribution relative to the MAR projections in which the ice sheet topography is fixed: the lower bounds of our 95% credibility intervals (CIs) for sea level contributions are larger than the "no feedback" case for all ISMs and GCMs. Our method is novel in sea level projections because we propagate three types of modelling uncertainty – GCM and ISM structural uncertainties, and elevation feedback parameterisation uncertainty – along the causal chain, from SRES scenario to sea level, within a coherent experimental design and statistical framework. The relative contributions to uncertainty depend on the timescale of interest. At 2100, the GCM uncertainty is largest, but by 2200 both the ISM and parameterisation uncertainties are larger. We also perform a perturbed parameter ensemble with one ISM to estimate the shape of the projected sea level probability distribution; our results indicate that the probability density is slightly skewed towards higher sea level contributions.

We present a new parameterisation that relates surface mass balance (SMB: the sum of surface accumulation and surface ablation) to changes in surface elevation of the Greenland ice sheet (GrIS) for the MAR (Modèle Atmosphérique Régional: Fettweis, 2007) regional climate model. The motivation is to dynamically adjust SMB as the GrIS evolves, allowing us to force ice sheet models with SMB simulated by MAR while incorporating the SMB–elevation feedback, without the substantial technical challenges of coupling ice sheet and climate models. This also allows us to assess the effect of elevation feedback uncertainty on the GrIS contribution to sea level, using multiple global climate and ice sheet models, without the need for additional, expensive MAR simulations. We estimate this relationship separately below and above the equilibrium line altitude (ELA, separating negative and positive SMB) and for regions north and south of 77° N, from a set of MAR simulations in which we alter the ice sheet surface elevation. These give four "SMB lapse rates", gradients that relate SMB changes to elevation changes. We assess uncertainties within a Bayesian framework, estimating probability distributions for each gradient from which we present best estimates and credibility intervals (CI) that bound 95% of the probability. Below the ELA our gradient estimates are mostly positive, because SMB usually increases with elevation: 0.56 (95% CI: −0.22 to 1.33) kg m−3 a−1 for the north, and 1.91 (1.03 to 2.61) kg m−3 a−1 for the south. Above the ELA, the gradients are much smaller in magnitude: 0.09 (−0.03 to 0.23) kg m−3 a−1 in the north, and 0.07 (−0.07 to 0.59) kg m−3 a−1 in the south, because SMB can either increase or decrease in response to increased elevation. Our statistically founded approach allows us to make probabilistic assessments for the effect of elevation feedback uncertainty on sea level projections (Edwards et al., 2014).