Description: We present a new framework for global ocean–sea-ice model simulations based on phase 2 of the Ocean Model Intercomparison Project (OMIP-2), making use of the surface dataset based on the Japanese 55-year atmospheric reanalysis for driving ocean–sea-ice models (JRA55-do). We motivate the use of OMIP-2 over the framework for the first phase of OMIP (OMIP-1), previously referred to as the Coordinated Ocean–ice Reference Experiments (COREs), via the evaluation of OMIP-1 and OMIP-2 simulations from 11 state-of-the-science global ocean–sea-ice models. In the present evaluation, multi-model ensemble means and spreads are calculated separately for the OMIP-1 and OMIP-2 simulations and overall performance is assessed considering metrics commonly used by ocean modelers. Both OMIP-1 and OMIP-2 multi-model ensemble ranges capture observations in more than 80 % of the time and region for most metrics, with the multi-model ensemble spread greatly exceeding the difference between the means of the two datasets. Many features, including some climatologically relevant ocean circulation indices, are very similar between OMIP-1 and OMIP-2 simulations, and yet we could also identify key qualitative improvements in transitioning from OMIP-1 to OMIP-2. For example, the sea surface temperatures of the OMIP-2 simulations reproduce the observed global warming during the 1980s and 1990s, as well as the warming slowdown in the 2000s and the more recent accelerated warming, which were absent in OMIP-1, noting that the last feature is part of the design of OMIP-2 because OMIP-1 forcing stopped in 2009. A negative bias in the sea-ice concentration in summer of both hemispheres in OMIP-1 is significantly reduced in OMIP-2. The overall reproducibility of both seasonal and interannual variations in sea surface temperature and sea surface height (dynamic sea level) is improved in OMIP-2. These improvements represent a new capability of the OMIP-2 framework for evaluating process-level responses using simulation results. Regarding the sensitivity of individual models to the change in forcing, the models show well-ordered responses for the metrics that are directly forced, while they show less organized responses for those that require complex model adjustments. Many of the remaining common model biases may be attributed either to errors in representing important processes in ocean–sea-ice models, some of which are expected to be reduced by using finer horizontal and/or vertical resolutions, or to shared biases and limitations in the atmospheric forcing. In particular, further efforts are warranted to resolve remaining issues in OMIP-2 such as the warm bias in the upper layer, the mismatch between the observed and simulated variability of heat content and thermosteric sea level before 1990s, and the erroneous representation of deep and bottom water formations and circulations. We suggest that such problems can be resolved through collaboration between those developing models (including parameterizations) and forcing datasets. Overall, the present assessment justifies our recommendation that future model development and analysis studies use the OMIP-2 framework.

Description: © 2009 The Authors. This article is distributed under the terms of the Creative Commons Attribution 3.0 License. The definitive version was published in Biogeosciences 6 (2009): 3131-3147, doi: 10.5194/bg-6-3131-2009

Description: Iron availability and temperature are important limiting factors for the biota in many areas of the world ocean, and both have been predicted to change in future climate scenarios. However, the impacts of combined changes in these two key factors on microbial trophic dynamics and nutrient cycling are unknown. We examined the relative effects of iron addition (+1 nM) and increased temperature (+4°C) on plankton assemblages of the Ross Sea, Antarctica, a region characterized by annual algal blooms and an active microbial community. Increased iron and temperature individually had consistently significant but relatively minor positive effects on total phytoplankton abundance, phytoplankton and microzooplankton community composition, as well as photosynthetic parameters and nutrient drawdown. Unexpectedly, increased iron had a consistently negative impact on microzooplankton abundance, most likely a secondary response to changes in phytoplankton community composition. When iron and temperature were increased in concert, the resulting interactive effects were greatly magnified. This synergy between iron and temperature increases would not have been predictable by examining the effects of each variable individually. Our results suggest the possibility that if iron availability increases under future climate regimes, the impacts of predicted temperature increases on plankton assemblages in polar regions could be significantly enhanced. Such synergistic and antagonistic interactions between individual climate change variables highlight the importance of multivariate studies for marine global change experiments.

Description: This project was supported by US NSF grants ANT 0528715 to JMR, ANT 0741411, ANT 0741428 and OCE 0825319 to DAH, ANT 0338157 to WOS, ANT 0338097 to GRD, and ANT 0338350 to RBD.

Description: Author Posting. © American Geophysical Union, 2017. This article is posted here by permission of American Geophysical Union for personal use, not for redistribution. The definitive version was published in Global Biogeochemical Cycles 31 (2017): 922–940, doi:10.1002/2016GB005615.

Description: A coupled global numerical simulation (conducted with the Community Earth System Model) is used in conjunction with satellite remote sensing observations to examine the role of top-down (grazing pressure) and bottom-up (light, nutrients) controls on marine phytoplankton bloom dynamics in the Southern Ocean. Phytoplankton seasonal phenology is evaluated in the context of the recently proposed “disturbance-recovery” hypothesis relative to more traditional, exclusively “bottom-up” frameworks. All blooms occur when phytoplankton division rates exceed loss rates to permit sustained net population growth; however, the nature of this decoupling period varies regionally in Community Earth System Model. Regional case studies illustrate how unique pathways allow blooms to emerge despite very poor division rates or very strong grazing rates. In the Subantarctic, southeast Pacific small spring blooms initiate early cooccurring with deep mixing and low division rates, consistent with the disturbance-recovery hypothesis. Similar systematics are present in the Subantarctic, southwest Atlantic during the spring but are eclipsed by a subsequent, larger summer bloom that is coincident with shallow mixing and the annual maximum in division rates, consistent with a bottom-up, light limited framework. In the model simulation, increased iron stress prevents a similar summer bloom in the southeast Pacific. In the simulated Antarctic zone (70°S–65°S) seasonal sea ice acts as a dominant phytoplankton-zooplankton decoupling agent, triggering a delayed but substantial bloom as ice recedes. Satellite ocean color remote sensing and ocean physical reanalysis products do not precisely match model-predicted phenology, but observed patterns do indicate regional variability in mechanism across the Atlantic and Pacific.

Description: NDSEG Graduate Fellowship; National Aeronautics and Space Administration Ocean Biology and Biogeochemistry Program Grant Number: NNX14L86G; NSF Poloar Programs Award Grant Number: 1440435; National Aeronautics and Space Administration Grant Number: NNX14AL86G; NDSEG; National Science Foundation Grant Number: 1440435

Description: 2017-11-30

Description: Author Posting. © American Meteorological Society, 2013]. This article is posted here by permission of American Meteorological Society for personal use, not for redistribution. The definitive version was published in Journal of Climate 26 (2013): 6775–6800, doi:10.1175/JCLI-D-12-00184.1.

Description: Ocean carbon uptake and storage simulated by the Community Earth System Model, version 1–Biogeochemistry [CESM1(BGC)], is described and compared to observations. Fully coupled and ocean-ice configurations are examined; both capture many aspects of the spatial structure and seasonality of surface carbon fields. Nearly ubiquitous negative biases in surface alkalinity result from the prescribed carbonate dissolution profile. The modeled sea–air CO2 fluxes match observationally based estimates over much of the ocean; significant deviations appear in the Southern Ocean. Surface ocean pCO2 is biased high in the subantarctic and low in the sea ice zone. Formation of the water masses dominating anthropogenic CO2 (Cant) uptake in the Southern Hemisphere is weak in the model, leading to significant negative biases in Cant and chlorofluorocarbon (CFC) storage at intermediate depths. Column inventories of Cant appear too high, by contrast, in the North Atlantic. In spite of the positive bias, this marks an improvement over prior versions of the model, which underestimated North Atlantic uptake. The change in behavior is attributable to a new parameterization of density-driven overflows. CESM1(BGC) provides a relatively robust representation of the ocean–carbon cycle response to climate variability. Statistical metrics of modeled interannual variability in sea–air CO2 fluxes compare reasonably well to observationally based estimates. The carbon cycle response to key modes of climate variability is basically similar in the coupled and forced ocean-ice models; however, the two differ in regional detail and in the strength of teleconnections.

Description: The CESM project is supported by the National Science Foundation and the Office of Science (BER) of the U.S. Department of Energy. SCD acknowledges support of Collaborative Research: Improved Regional and Decadal Predictions of the Carbon Cycle (NSFAGS- 1048827).

Description: 2014-03-15

Description: © The Author(s), 2018. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Ecological Applications 28 (2018): 749-760, doi: 10.1002/eap.1682.

Description: The biodiversity and high productivity of coastal terrestrial and aquatic habitats are the foundation for important benefits to human societies around the world. These globally distributed habitats need frequent and broad systematic assessments, but field surveys only cover a small fraction of these areas. Satellite‐based sensors can repeatedly record the visible and near‐infrared reflectance spectra that contain the absorption, scattering, and fluorescence signatures of functional phytoplankton groups, colored dissolved matter, and particulate matter near the surface ocean, and of biologically structured habitats (floating and emergent vegetation, benthic habitats like coral, seagrass, and algae). These measures can be incorporated into Essential Biodiversity Variables (EBVs), including the distribution, abundance, and traits of groups of species populations, and used to evaluate habitat fragmentation. However, current and planned satellites are not designed to observe the EBVs that change rapidly with extreme tides, salinity, temperatures, storms, pollution, or physical habitat destruction over scales relevant to human activity. Making these observations requires a new generation of satellite sensors able to sample with these combined characteristics: (1) spatial resolution on the order of 30 to 100‐m pixels or smaller; (2) spectral resolution on the order of 5 nm in the visible and 10 nm in the short‐wave infrared spectrum (or at least two or more bands at 1,030, 1,240, 1,630, 2,125, and/or 2,260 nm) for atmospheric correction and aquatic and vegetation assessments; (3) radiometric quality with signal to noise ratios (SNR) above 800 (relative to signal levels typical of the open ocean), 14‐bit digitization, absolute radiometric calibration 〈2%, relative calibration of 0.2%, polarization sensitivity 〈1%, high radiometric stability and linearity, and operations designed to minimize sunglint; and (4) temporal resolution of hours to days. We refer to these combined specifications as H4 imaging. Enabling H4 imaging is vital for the conservation and management of global biodiversity and ecosystem services, including food provisioning and water security. An agile satellite in a 3‐d repeat low‐Earth orbit could sample 30‐km swath images of several hundred coastal habitats daily. Nine H4 satellites would provide weekly coverage of global coastal zones. Such satellite constellations are now feasible and are used in various applications.

Description: National Center for Ecological Analysis and Synthesis (NCEAS); National Aeronautics and Space Administration (NASA) Grant Numbers: NNX16AQ34G, NNX14AR62A; National Ocean Partnership Program; NOAA US Integrated Ocean Observing System/IOOS Program Office; Bureau of Ocean and Energy Management Ecosystem Studies program (BOEM) Grant Number: MC15AC00006

Description: Author Posting. © American Geophysical Union, 2018. This article is posted here by permission of American Geophysical Union for personal use, not for redistribution. The definitive version was published in Geophysical Research Letters 45 (2018): 5011-5019, doi:10.1029/2017GL076246.

Description: The Antarctic Circumpolar Current has highly energetic mesoscale phenomena, but their impacts on phytoplankton biomass, productivity, and biogeochemical cycling are not understood well. We analyze satellite observations and an eddy‐rich ocean model to show that they drive chlorophyll anomalies of opposite sign in winter versus summer. In winter, deeper mixed layers in positive sea surface height (SSH) anomalies reduce light availability, leading to anomalously low chlorophyll concentrations. In summer with abundant light, however, positive SSH anomalies show elevated chlorophyll concentration due to higher iron level, and an iron budget analysis reveals that anomalously strong vertical mixing enhances iron supply to the mixed layer. Features with negative SSH anomalies exhibit the opposite tendencies: higher chlorophyll concentration in winter and lower in summer. Our results suggest that mesoscale modulation of iron supply, light availability, and vertical mixing plays an important role in causing systematic variations in primary productivity over the seasonal cycle.

Description: 2018-11-17

Description: Author Posting. © American Meteorological Society, 2013. This article is posted here by permission of American Meteorological Society for personal use, not for redistribution. The definitive version was published in Journal of Climate 26 (2013): 9291–9312, doi:10.1175/JCLI-D-12-00566.1.

Description: The authors compare Community Earth System Model results to marine observations for the 1990s and examine climate change impacts on biogeochemistry at the end of the twenty-first century under two future scenarios (Representative Concentration Pathways RCP4.5 and RCP8.5). Late-twentieth-century seasonally varying mixed layer depths are generally within 10 m of observations, with a Southern Ocean shallow bias. Surface nutrient and chlorophyll concentrations exhibit positive biases at low latitudes and negative biases at high latitudes. The volume of the oxygen minimum zones is overestimated. The impacts of climate change on biogeochemistry have similar spatial patterns under RCP4.5 and RCP8.5, but perturbation magnitudes are larger under RCP8.5. Increasing stratification leads to weaker nutrient entrainment and decreased primary and export production (〉30% over large areas). The global-scale decreases in primary and export production scale linearly with the increases in mean sea surface temperature. There are production increases in the high nitrate, low chlorophyll (HNLC) regions, driven by lateral iron inputs from adjacent areas. The increased HNLC export partially compensates for the reductions in non-HNLC waters (~25% offset). Stabilizing greenhouse gas emissions and climate by the end of this century (as in RCP4.5) will minimize the changes to nutrient cycling and primary production in the oceans. In contrast, continued increasing emission of CO2 (as in RCP8.5) will lead to reduced productivity and significant modifications to ocean circulation and biogeochemistry by the end of this century, with more drastic changes beyond the year 2100 as the climate continues to rapidly warm.

Description: The CESM project is supported by the National Science Foundation and the Office of Science (BER) of the U.S. Department of Energy. S.C.D. acknowledges support of Collaborative Research: Improved Regional and Decadal Predictions of the Carbon Cycle (NSF AGS-1048827). This work was supported by NSF grants (ARC-0902045 and AGS-1021776 to Moore and AGS- 1048890 to Moore, Lindsay, and Doney).

Description: 2014-06-01

Description: © The Author(s), 2021. This article is distributed under the terms of the Creaive Commons Attribution License. The definitive version was published in Eveleth, R., Glover, D. M., Long, M. C., Lima, I. D., Chase, A. P., & Doney, S. C. . Assessing the skill of a high-resolution marine biophysical model using geostatistical analysis of mesoscale ocean chlorophyll variability from field observations and remote sensing. Frontiers in Marine Science, 8, (2021): 612764, https://doi.org/10.3389/fmars.2021.612764.

Description: High-resolution ocean biophysical models are now routinely being conducted at basin and global-scale, opening opportunities to deepen our understanding of the mechanistic coupling of physical and biological processes at the mesoscale. Prior to using these models to test scientific questions, we need to assess their skill. While progress has been made in validating the mean field, little work has been done to evaluate skill of the simulated mesoscale variability. Here we use geostatistical 2-D variograms to quantify the magnitude and spatial scale of chlorophyll a patchiness in a 1/10th-degree eddy-resolving coupled Community Earth System Model simulation. We compare results from satellite remote sensing and ship underway observations in the North Atlantic Ocean, where there is a large seasonal phytoplankton bloom. The coefficients of variation, i.e., the arithmetic standard deviation divided by the mean, from the two observational data sets are approximately invariant across a large range of mean chlorophyll a values from oligotrophic and winter to subpolar bloom conditions. This relationship between the chlorophyll a mesoscale variability and the mean field appears to reflect an emergent property of marine biophysics, and the high-resolution simulation does poorly in capturing this skill metric, with the model underestimating observed variability under low chlorophyll a conditions such as in the subtropics.

Description: This work was supported in part by the National Aeronautics and Space Administration (NASA) as part of the North Atlantic Aerosol and Marine Ecosystems Study (NAAMES; NASA grant 80NSSC18K0018). The CESM project is supported by the National Science Foundation and the Office of Science (BER) of the United States Department of Energy. Computing resources were provided by the Climate Simulation Laboratory at NCAR’s Computational and Information Systems Laboratory (CISL), sponsored by the National Science Foundation and other agencies. This research was enabled by CISL compute and storage resources.

Description: © The Author(s), 2022. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Jenouvrier, S., Long, M. C., Coste, C. F. D., Holland, M., Gamelon, M., Yoccoz, N., & Saether, B.-E. Detecting climate signals in populations across life histories. Global Change Biology, 28, (2022): 2236– 2258, https://doi.org/10.1111/gcb.16041.

Description: Climate impacts are not always easily discerned in wild populations as detecting climate change signals in populations is challenged by stochastic noise associated with natural climate variability, variability in biotic and abiotic processes, and observation error in demographic rates. Detection of the impact of climate change on populations requires making a formal distinction between signals in the population associated with long-term climate trends from those generated by stochastic noise. The time of emergence (ToE) identifies when the signal of anthropogenic climate change can be quantitatively distinguished from natural climate variability. This concept has been applied extensively in the climate sciences, but has not been explored in the context of population dynamics. Here, we outline an approach to detecting climate-driven signals in populations based on an assessment of when climate change drives population dynamics beyond the envelope characteristic of stochastic variations in an unperturbed state. Specifically, we present a theoretical assessment of the time of emergence of climate-driven signals in population dynamics (ToEpop). We identify the dependence of (ToEpop)on the magnitude of both trends and variability in climate and also explore the effect of intrinsic demographic controls on (ToEpop). We demonstrate that different life histories (fast species vs. slow species), demographic processes (survival, reproduction), and the relationships between climate and demographic rates yield population dynamics that filter climate trends and variability differently. We illustrate empirically how to detect the point in time when anthropogenic signals in populations emerge from stochastic noise for a species threatened by climate change: the emperor penguin. Finally, we propose six testable hypotheses and a road map for future research.

Description: We acknowledge the support of NASA 80NSSC20K1289 to SJ, ML, and MH; NSF OPP 1744794 to SJ and NSF OPP 2037561 to SJ and MH.

Description: Author Posting. © American Geophysical Union, 2021. This article is posted here by permission of American Geophysical Union for personal use, not for redistribution. The definitive version was published in Journal of Geophysical Research: Oceans 126(8), (2021): e2021JC017510, https://doi.org/10.1029/2021JC017510.

Description: The air-sea exchange of oxygen (O2) is driven by changes in solubility, biological activity, and circulation. The total air-sea exchange of O2 has been shown to be closely related to the air-sea exchange of heat on seasonal timescales, with the ratio of the seasonal flux of O2 to heat varying with latitude, being higher in the extratropics and lower in the subtropics. This O2/heat ratio is both a fundamental biogeochemical property of air-sea exchange and a convenient metric for testing earth system models. Current estimates of the O2/heat flux ratio rely on sparse observations of dissolved O2, leaving it fairly unconstrained. From a model ensemble we show that the ratio of the seasonal amplitude of two atmospheric tracers, atmospheric potential oxygen (APO) and the argon-to-nitrogen ratio (Ar/O2), exhibits a close relationship to the O2/heat ratio of the extratropics (40–70°). The amplitude ratio, A APO/A ArN2, is relatively constant within the extratropics of each hemisphere due to the zonal mixing of the atmosphere. A APO/A ArN2 is not sensitive to atmospheric transport, as most of the observed spatial variability in the seasonal amplitude of δAPO is compensated by similar variations in δ(Ar/N2). From the relationship between O2/heat and A APO/A ArN2 in the model ensemble, we determine that the atmospheric observations suggest hemispherically distinct O2/heat flux ratios of 3.3 ± 0.3 and 4.7 ± 0.8 nmol J-1 between 40 and 70° in the Northern and Southern Hemispheres respectively, providing a useful constraint for O2 and heat air-sea fluxes in earth system models and observation-based data products.

Description: The recent atmospheric measurements of the Scripps program have been supported via funding from the NSF and the National Oceanographic and Atmospheric Administration (NOAA) under grants 1304270 and OAR-CIPO-2015-2004269. M. Manizza and R. F. Keeling thank NSF for financial support via the OCE-1130976 grant. M. Manizza thanks additional financial support from NSF via the ARRA OCE-0850350 grant. S. C. Doney acknowledges support from NSF PLR-1440435. Keith Rodgers acknowledges support from IBS-R028-D1. Gael Forget and the ECCO group kindly provided the ECCOv4 heat fluxes.

Description: 2022-01-22