Description: We present the first results of the implementation of stable water isotopes in the Massachusetts Institute of Technology general circulation model (MITgcm). The model is forced with the isotopic content of precipitation and water vapor from an atmospheric general circulation model (NCAR IsoCAM), while the fractionation during evaporation is treated explicitly in the MITgcm. Results of the equilibrium simulation under pre-industrial conditions are compared to observational data and measurements of plankton tow records (the oxygen isotopic composition of planktic foraminiferal calcite). The broad patterns and magnitude of the stable water isotopes in annual mean seawater are well captured in the model, both at the sea surface as well as in the deep ocean. However, the surface water in the Arctic Ocean is not depleted enough, due to the absence of highly depleted precipitation and snowfall. A model–data mismatch is also recognizable in the isotopic composition of the seawater–salinity relationship in midlatitudes that is mainly caused by the coarse grid resolution. Deep-ocean characteristics of the vertical water mass distribution in the Atlantic Ocean closely resemble observational data. The reconstructed δ18Oc at the sea surface shows a good agreement with measurements. However, the model–data fit is weaker when individual species are considered and deviations are most likely attributable to the habitat depth of the foraminifera. Overall, the newly developed stable water isotope package opens wide prospects for long-term simulations in a paleoclimatic context.

Description: Paleoclimate reconstruction based on assimilation of proxy observations requires specification of the control variables and their background statistics. As opposed to numerical weather prediction (NWP), which is mostly an initial condition problem, the main source of error growth in deterministic Earth system models (ESMs) regarding the model low-frequency response comes from errors in other inputs: parameters for the small-scale physics, as well as forcing and boundary conditions. Also, comprehensive ESMs are non-linear and only a few ensemble members can be run in current high-performance computers. Under these conditions we evaluate two assimilation schemes, which (a) count on iterations to deal with non-linearity and (b) are based on low-dimensional control vectors to reduce the computational need. The practical implementation would assume that the ESM has been previously globally tuned with current observations and that for a given situation there is previous knowledge of the most sensitive inputs (given corresponding uncertainties), which should be selected as control variables. The low dimension of the control vector allows for using full-rank covariances and resorting to finite-difference sensitivities (FDSs). The schemes are then an FDS implementation of the iterative Kalman smoother (FDS-IKS, a Gauss–Newton scheme) and a so-called FDS-multistep Kalman smoother (FDS-MKS, based on repeated assimilation of the observations). We describe the schemes and evaluate the analysis step for a data assimilation window in two numerical experiments: (a) a simple 1-D energy balance model (Ebm1D; which has an adjoint code) with present-day surface air temperature from the NCEP/NCAR reanalysis data as a target and (b) a multi-decadal synthetic case with the Community Earth System Model (CESM v1.2, with no adjoint). In the Ebm1D experiment, the FDS-IKS converges to the same parameters and cost function values as a 4D-Var scheme. For similar iterations to the FDS-IKS, the FDS-MKS results in slightly higher cost function values, which are still substantially lower than those of an ensemble transform Kalman filter (ETKF). In the CESM experiment, we include an ETKF with Gaussian anamorphosis (ETKF-GA) implementation as a potential non-linear assimilation alternative. For three iterations, both FDS schemes obtain cost functions values that are close between them and (with about half the computational cost) lower than those of the ETKF and ETKF-GA (with similar cost function values). Overall, the FDS-IKS seems more adequate for the problem, with the FDS-MKS potentially more useful to damp increments in early iterations of the FDS-IKS.

Description: In climate reanalyses for multi-decadal or longer scales with coupled atmosphere-ocean General Circulation models (CGCMs) it can be assumed that the growth of prediction errors arises chiefly from imprecisely known model parameters, which have a nonlinear relationship with the climate observations (paleoclimate proxies). Also, high-resolution CGCMs for climate analysis are extremely expensive to run, which constrains the applicability of assimilation schemes. In a model framework where we assume that model dynamic parameters account for (nearly) all forecast errors at observation times, we compare two computationally efficient iterative schemes for approximate nonlinear model parameter estimation and joint flux estimation (taking the specific shape of freshwater from melting in the Greenland ice sheet), and its physically consistent state. First, a trivial adaptation of the strong constraint incremental 4D-Var formulation leads to what we refer to as the parameter space iterative extended Kalman smoother (pIKS); a Gauss-Newton scheme. Second, a so-called parameter space fractional Kalman smoother (pFKS) is an alternative controlled-step line search, which can potentially be a more stable approach. While these iterative schemes have been used in data assimilation, we revisit them together within the context of parameter estimation in climate reanalysis, as compared to the more general 4D-Var formulation. Then, the two schemes are evaluated in numerical experiments with a simple 1D energy balance model (Ebm1D) and with a fully-coupled Community Earth System Model (CESM v1.2). Firstly, with Ebm1D the pFKS obtains a cost function similar to the adjoint method with highly reduced computational cost, while an ensemble transform Kalman filter with an m = 60 ensemble size (ETKF60) behaves slightly worse. The pIKS behaves worse than the ETKF60, but an ETKF10 (m = 10) is even worst. Accordingly, with CESM we evaluate the pKFS and the ETKF60 along with an ETKF with Gaussian Anamorphosis (ETKF-GA60). From all the options, the pFKS has the lowest cost function and seems the favored overall option under heavy computational restrictions, but the ETKF obtains better estimates of the flux term.

Description: Combining ocean general circulation models with proxy data via data assimilation is a means to obtain estimates of past ocean states that are consistent with model physics as well as with proxy data. The climate during the Last Glacial Maximum (LGM, 19–23 ka) was substantially different from today. Even though boundary conditions are comparatively well known, the large-scale patterns of the ocean circulation during this time remain uncertain. Previous efforts to combine ocean models with proxy data have shown dissimilar results regarding the state of the ocean, in particular of the Atlantic Meridional Overturning Circulation. Here, we present a new LGM ocean state estimate that extents previous estimates by using global benthic as well as planktic data on the oxygen isotopic composition of calcite. It is further constrained by global seasonal and annual sea surface temperature (SST) reconstructions. The estimate shows an Atlantic Ocean that is similar to the Late Holocene Atlantic Ocean but with a reduced formation of Antarctic Bottom Water, in contrast to results of previous studies. The results indicate that SST and oxygen isotopic data alone do not require the presence of a shallower North Atlantic Deep Water and a more extensive Antarctic Bottom Water, and highlight the need for more proxy data of different types to obtain reliable ocean state estimates. Additional adjoint sensitivity experiments reveal that data from the deep North Atlantic and from the global deep Southern Ocean are most important to constrain the Atlantic Meridional Overturning Circulation.

Description: There has been a steady increase in interest in mining of deep-sea minerals in the Clarion–Clipperton Zone (CCZ) in the eastern Pacific Ocean during the last decade. This region is known to be one of the most eddy-rich regions in the world ocean. Typically, mesoscale eddies are generated by intense wind bursts channeled through gaps in the Sierra Madre mountains in Central America. Here, we use a combination of satellite and in situ observations to evaluate the relationship between deep-sea current variability in the region of potential future mining and eddy kinetic energy (EKE) in the vicinity of gap winds. A geometry-based eddy detection algorithm has been applied to altimetry sea surface height data for a period of 24 years, from 1993 to 2016, in order to analyze the main characteristic parameters and the spatiotemporal variability of mesoscale eddies in the northeast tropical Pacific Ocean (NETP). Significant differences between the characteristics of eddies with different polarity (cyclonic vs. anticyclonic) were found. For eddies with lifetimes longer than 1 d, cyclonic polarity is more common than anticyclonic rotation. However, anticyclonic eddies are larger in size, show stronger vorticity, and survive longer in the ocean than cyclonic eddies (often 90 d or more). Besides the polarity of eddies, the location of eddy formation should be taken into consideration when investigating the impacted deep-ocean region as we found eddies originating from the Tehuantepec (TT) gap winds lasting longer in the ocean and traveling farther distances in a different direction compared to eddies produced by the Papagayo (PP) gap winds. Long-lived anticyclonic eddies generated by the TT gap winds are observed to travel distances up to 4500 km offshore, i.e., as far as west of 110∘ W. EKE anomalies observed in the surface of the central ocean at distances of ca. 2500 km from the coast correlate with the seasonal variability of EKE in the region of the TT gap winds with a time lag of 5–6 months. A significant seasonal variability of deep-ocean current velocities at water depths of 4100 m was observed in multiple-year time series data, likely reflecting the energy transfer of the surface EKE generated by the gap winds to the deep ocean. Furthermore, the influence of mesoscale eddies on deep-ocean currents is examined by analyzing the deep-ocean current measurements when an anticyclonic eddy crosses the study region. Our findings suggest that despite the significant modulation of dominant current directions driven by the bottom-reaching eddy, the current magnitude intensification was not strong enough to trigger local sediment resuspension in this region. A better insight into the annual variability of ocean surface mesoscale activity in the CCZ and its effects on deep-ocean current variability can be of great help to mitigate the impact of future potential deep-sea mining activities on the benthic ecosystem. On an interannual scale, a significant relationship between cyclonic eddy characteristics and El Niño–Southern Oscillation (ENSO) was found, whereas a weaker correlation was detected for anticyclonic eddies.

Description: We developed a coupling scheme for the Community Earth System Model version 1.2 (CESM1.2) and the Model of Early Diagenesis in the Upper Sediment of Adjustable complexity (MEDUSA), and explored the effects of the coupling on solid components in the upper sediment and on bottom seawater chemistry by comparing the coupled model's behaviour with that of the uncoupled CESM having a simplified treatment of sediment processes. CESM is a fully coupled atmosphere–ocean–sea-ice–land model and its ocean component (the Parallel Ocean Program version 2; POP2) includes a biogeochemical component (the Biogeochemical Elemental Cycling model; BEC). MEDUSA was coupled to POP2 in an offline manner so that each of the models ran separately and sequentially with regular exchanges of necessary boundary condition fields. This development was done with the ambitious aim of a future application for long-term (spanning a full glacial cycle; i.e. ∼105 years) climate simulations with a state-of-the-art comprehensive climate model including the carbon cycle, and was motivated by the fact that until now such simulations have been done only with less-complex climate models. We found that the sediment–model coupling already had non-negligible immediate advantages for ocean biogeochemistry in millennial-timescale simulations. First, the MEDUSA-coupled CESM outperformed the uncoupled CESM in reproducing an observation-based global distribution of sediment properties, especially for organic carbon and opal. Thus, the coupled model is expected to act as a better “bridge” between climate dynamics and sedimentary data, which will provide another measure of model performance. Second, in our experiments, the MEDUSA-coupled model and the uncoupled model had a difference of 0.2 ‰ or larger in terms of δ13C of bottom water over large areas, which implied a potentially significant model uncertainty for bottom seawater chemical composition due to a different way of sediment treatment. For example, an ocean model that does not treat sedimentary processes depending on the chemical composition of the ambient water can overestimate the amount of remineralization of organic matter in the upper sediment in an anoxic environment, which would lead to lighter δ13C values in the bottom water. Such a model uncertainty would be a fundamental issue for paleo model–data comparison often relying on data derived from benthic foraminifera.

Description: We present a global atlas of downcore foraminiferal oxygen and carbon isotope ratios available at https://doi.org/10.1594/PANGAEA.936747 (Mulitza et al., 2021a). The database contains 2106 published and previously unpublished stable isotope downcore records with 361 949 stable isotope values of various planktic and benthic species of Foraminifera from 1265 sediment cores. Age constraints are provided by 6153 uncalibrated radiocarbon ages from 598 (47 %) of the cores. Each stable isotope and radiocarbon series is provided in a separate netCDF file containing fundamental metadata as attributes. The data set can be managed and explored with the free software tool PaleoDataView. The atlas will provide important data for paleoceanographic analyses and compilations, site surveys, or for teaching marine stratigraphy. The database can be updated with new records as they are generated, providing a live ongoing resource into the future.

Description: The Last Glacial Maximum (LGM, ∼ 21 000 years ago) has been a major focus for evaluating how well state-of-the-art climate models simulate climate changes as large as those expected in the future using paleoclimate reconstructions. A new generation of climate models has been used to generate LGM simulations as part of the Paleoclimate Modelling Intercomparison Project (PMIP) contribution to the Coupled Model Intercomparison Project (CMIP). Here, we provide a preliminary analysis and evaluation of the results of these LGM experiments (PMIP4, most of which are PMIP4-CMIP6) and compare them with the previous generation of simulations (PMIP3, most of which are PMIP3-CMIP5). We show that the global averages of the PMIP4 simulations span a larger range in terms of mean annual surface air temperature and mean annual precipitation compared to the PMIP3-CMIP5 simulations, with some PMIP4 simulations reaching a globally colder and drier state. However, the multi-model global cooling average is similar for the PMIP4 and PMIP3 ensembles, while the multi-model PMIP4 mean annual precipitation average is drier than the PMIP3 one. There are important differences in both atmospheric and oceanic circulations between the two sets of experiments, with the northern and southern jet streams being more poleward and the changes in the Atlantic Meridional Overturning Circulation being less pronounced in the PMIP4-CMIP6 simulations than in the PMIP3-CMIP5 simulations. Changes in simulated precipitation patterns are influenced by both temperature and circulation changes. Differences in simulated climate between individual models remain large. Therefore, although there are differences in the average behaviour across the two ensembles, the new simulation results are not fundamentally different from the PMIP3-CMIP5 results. Evaluation of large-scale climate features, such as land–sea contrast and polar amplification, confirms that the models capture these well and within the uncertainty of the paleoclimate reconstructions. Nevertheless, regional climate changes are less well simulated: the models underestimate extratropical cooling, particularly in winter, and precipitation changes. These results point to the utility of using paleoclimate simulations to understand the mechanisms of climate change and evaluate model performance.

Description: Three time-slice carbon cycle simulations for the last glacial maximum (LGM) constrained by the CO2 concentration in the atmosphere and the increase in the mean concentration of dissolved inorganic carbon in the deep ocean were carried out with a fully coupled comprehensive climate model (the Community Earth System Model version 1.2). The three modelled LGM ocean states yielded different physical features in response to artificial freshwater forcing, and, depending on the physical states, suitable amounts of carbon and alkalinity were added to the ocean to satisfy constraints from paleo-data. In all the simulations, the amount of carbon added was in line with the inferred transfers of carbon among various reservoirs during the evolution from the LGM to the pre-industrial (PI) period, suggesting that the simulated glacial ocean states are compatible with the PI one in terms of the carbon budget. The increase in total alkalinity required to simulate ocean states that were deemed appropriate for the LGM was in broad quantitative accord with the scenario of post-glacial shallow water deposition of calcium carbonate, although a more precise assessment would demand further studies of various processes such as the land chemical weathering and deep-sea burial of calcium carbonates, which have affected the alkalinity budget throughout history since the LGM. On the other hand, comparisons between the simulated distributions of paleoceanographic tracers and corresponding reconstructions clearly highlighted the different water-mass geometries and favoured a shallower Atlantic meridional overturning circulation (AMOC) for the LGM as compared to PI.

Description: We present a climatology of the near-sea-surface temperature (NSST) anomaly and the sea-ice extent during the Last Glacial Maximum (LGM, 23 000–19 000 years before present) mapped on a global regular 1∘×1∘ grid. It is an extension of the Glacial Atlantic Ocean Mapping (GLAMAP) reconstruction of the Atlantic NSST based on the faunal and floral assemblage data of the Multiproxy Approach for the Reconstruction of the Glacial Ocean Surface (MARGO) project and several recent estimates of the LGM sea-ice extent. Such a gridded climatology is highly useful for the visualization of the LGM climate, calculation of global and regional NSST averages, and estimation of the equilibrium climate sensitivity, as well as a boundary condition for atmospheric general circulation models. The gridding of the sparse NSST reconstruction was done in an optimal way using the Data-Interpolating Variational Analysis (DIVA) software, which takes into account the uncertainty in the reconstruction and includes the calculation of an error field. The resulting Glacial Ocean Map (GLOMAP) confirms the previous findings by the MARGO project regarding longitudinal and meridional NSST differences that were greater than today in all oceans. Taken at face value, the estimated global and tropical cooling would imply an equilibrium climate sensitivity at the lower end of the currently accepted range. However, because of anticipated changes in the seasonality and thermal structure of the upper ocean during the LGM as well as uneven spatial sampling, the estimated cooling and implied climate sensitivity are likely to be biased towards lower values.