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Global and regional sources and sinks of carbon across the earth's surface have been studied extensively using atmospheric carbon dioxide (CO2) observations and atmospheric chemistry-transport model (ACTM) simulations (top-down/inversion method). However, the uncertainties in the regional flux distributions remain unconstrained due to the lack of high-quality measurements, uncertainties in model simulations, and representation of data and flux errors in the inversion systems. Here, we assess the representation of data and flux errors using a suite of 16 inversion cases derived from a single transport model (MIROC4-ACTM) but different sets of a priori (bottom-up) terrestrial biosphere and oceanic fluxes, as well as prior flux and observational data uncertainties (50 sites) to estimate CO2 fluxes for 84 regions over the period 2000–2020. The inversion ensembles provide a mean flux field that is consistent with the global CO2 growth rate, land and ocean sink partitioning of −2.9 ± 0.3 (± 1σ uncertainty on the ensemble mean) and −1.6 ± 0.2 PgC yr−1, respectively, for the period 2011–2020 (without riverine export correction), offsetting about 22 %–33 % and 16 %–18 % of global fossil fuel CO2 emissions. The rivers carry about 0.6 PgC yr−1 of land sink into the deep ocean, and thus the effective land and ocean partitioning is −2.3 ± 0.3 and −2.2 ± 0.3, respectively. Aggregated fluxes for 15 land regions compare reasonably well with the best estimations for the 2000s (∼ 2000–2009), given by the REgional Carbon Cycle Assessment and Processes (RECCAP), and all regions appeared as a carbon sink over 2011–2020. Interannual variability and seasonal cycle in CO2 fluxes are more consistently derived for two distinct prior fluxes when a greater degree of freedom (increased prior flux uncertainty) is given to the inversion system. We have further evaluated the inversion fluxes using meridional CO2 distributions from independent (not used in the inversions) aircraft and surface measurements, suggesting that the ensemble mean flux (model–observation mean ± 1σ standard deviation = −0.3 ± 3 ppm) is best suited for global and regional CO2 flux budgets than an individual inversion (model–observation 1σ standard deviation = −0.35 ± 3.3 ppm). Using the ensemble mean fluxes and uncertainties for 15 land and 11 ocean regions at 5-year intervals, we show promise in the capability to track flux changes toward supporting the ongoing and future CO2 emission mitigation policies.

The El Niño–Southern Oscillation (ENSO) widely modulates the global carbon cycle. More specifically, it alters the net uptake of carbon in the tropical ocean. Over the tropical Pacific, less carbon is released during El Niño, while the opposite is the case for La Niña. Here, the skill of Earth system models (ESMs) from the latest Coupled Model Intercomparison Project (CMIP6) to simulate the observed tropical Pacific CO2 flux variability in response to ENSO is assessed. The temporal amplitude and spatial extent of CO2 flux anomalies vary considerably among models, while the surface temperature signals of El Niño and La Niña phases are generally well represented. Under historical conditions followed by the high-warming Shared Socio-economic Pathway (SSP5-8.5) scenarios, about half the ESMs simulate a reversal in ENSO–CO2 flux relationship. This gradual shift, which occurs as early as the first half of the 21st century, is associated with a high CO2-induced increase in the Revelle factor that leads to stronger sensitivity of partial pressure of CO2 (pCO2) to changes in surface temperature between ENSO phases. At the same time, uptake of anthropogenic CO2 substantially increases upper-ocean dissolved inorganic carbon (DIC) concentrations (reducing its vertical gradient in the thermocline) and weakens the ENSO-modulated surface DIC variability. The response of the ENSO–CO2 flux relationship to future climate change is sensitive to the contemporary mean state of the carbonate ion concentration in the tropics. We present an emergent constraint between the simulated contemporary carbonate concentration with the projected cumulated CO2 fluxes. Models that simulate shifts in the ENSO–CO2 flux relationship simulate positive bias in surface carbonate concentrations.

Variable fluxes of anthropogenic CO2 emissions into the land and the ocean and the remaining proportion in the atmosphere reflect on the global carbon budget variations and further modulate global climate change. A more accurate reconstruction of the global carbon budget in the past decades and a more reliable prediction of the variations in the next years are crucial for assessing the effectiveness of climate change mitigation policies and supporting global carbon stocktaking and monitoring in compliance with the goals of the Paris Agreement.In this study, we investigate reconstructions and predictions of the CO2 fluxes and atmospheric CO2 growth from ensemble prediction simulations using 5 Earth System Model (ESM) - based decadal prediction systems. These novel prediction systems driven by CO2 emissions with an interactive carbon cycle enable prognostic atmospheric CO2 and represent atmospheric CO2 growth variations in response to the strength of CO2 fluxes into the ocean and the land, which are missing in the conventional concentration-driven decadal prediction systems with prescribed atmospheric CO2 concentration.The reconstructions generated by assimilating physical ocean and atmosphere data products into the prediction systems are able to reproduce the annual mean historical variations of the CO2 fluxes and atmospheric CO2 growth. Multi-model ensemble means best match the assessments of CO2 fluxes and atmospheric CO2 growth rate from the Global Carbon Project with correlations of 0.79, 0.82, and 0.98 for atmospheric CO2 growth rate, air-land CO2 fluxes, and air-sea CO2 fluxes, respectively. The CO2 emission-driven prediction systems with an interactive carbon cycle still maintain the predictive skill of CO2 fluxes and atmospheric CO2 growth as found in conventional concentration-driven prediction systems, i.e., about 2 years for the air-land CO2 fluxes and atmospheric CO2 growth, the air-sea CO2 fluxes have higher skill up to 5 years. The ESM-based prediction systems are capable to reconstruct and predict the variations in the global carbon cycle and hence are powerful tools for supporting carbon budgeting and monitoring, especially in the decarbonization processes. Furthermore, we investigate the contribution of uncertainty in the predictions of CO2 fluxes and atmospheric CO2 growth rate from internal climate variability, different model responses, and emission-forcing reductions to identify the prominent challenge in limiting the skill of CO2 predictions.

Ocean alkalinity is critical to the uptake of atmospheric carbon in surface waters and provides buffering capacity towards the associated acidification. However, unlike dissolved inorganic carbon (DIC), alkalinity is not directly impacted by anthropogenic carbon emissions. Within the context of projections of future ocean carbon uptake and potential ecosystem impacts, especially through Coupled Model Intercomparison Projects (CMIPs), the representation of alkalinity and the main driver of its distribution in the ocean interior, the calcium carbonate cycle, have often been overlooked. Here we track the changes from CMIP5 to CMIP6 with respect to the Earth system model (ESM) representation of alkalinity and the carbonate pump which depletes the surface ocean in alkalinity through biological production of calcium carbonate and releases it at depth through export and dissolution. We report an improvement in the representation of alkalinity in CMIP6 ESMs relative to those in CMIP5, with CMIP6 ESMs simulating lower surface alkalinity concentrations, an increased meridional surface gradient and an enhanced global vertical gradient. This improvement can be explained in part by an increase in calcium carbonate (CaCO3) production for some ESMs, which redistributes alkalinity at the surface and strengthens its vertical gradient in the water column. We were able to constrain a particulate inorganic carbon (PIC) export estimate of 44–55 Tmol yr−1 at 100 m for the ESMs to match the observed vertical gradient of alkalinity. Reviewing the representation of the CaCO3 cycle across CMIP5/6, we find a substantial range of parameterizations. While all biogeochemical models currently represent pelagic calcification, they do so implicitly, and they do not represent benthic calcification. In addition, most models simulate marine calcite but not aragonite. In CMIP6, certain model groups have increased the complexity of simulated CaCO3 production, sinking, dissolution and sedimentation. However, this is insufficient to explain the overall improvement in the alkalinity representation, which is therefore likely a result of marine biogeochemistry model tuning or ad hoc parameterizations. Although modellers aim to balance the global alkalinity budget in ESMs in order to limit drift in ocean carbon uptake under pre-industrial conditions, varying assumptions related to the closure of the budget and/or the alkalinity initialization procedure have the potential to influence projections of future carbon uptake. For instance, in many models, carbonate production, dissolution and burial are independent of the seawater saturation state, and when considered, the range of sensitivities is substantial. As such, the future impact of ocean acidification on the carbonate pump, and in turn ocean carbon uptake, is potentially underestimated in current ESMs and is insufficiently constrained.

Ocean alkalinity is critical to the uptake of atmospheric carbon in surface waters and provides buffering capacity towards associated acidification. However, unlike dissolved inorganic carbon (DIC), alkalinity is not directly impacted by anthropogenic carbon emissions. Within the context of projections of future ocean carbon uptake and potential ecosystem impacts, especially through Coupled Model Intercomparison Projects (CMIPs), the representation of alkalinity and the main driver of its distribution in the ocean interior, the calcium carbonate cycle, have often been overlooked. Here we track the changes from CMIP5 to CMIP6 with respect to the Earth system model (ESM) representation of alkalinity and the carbonate pump which depletes the surface ocean in alkalinity through biological production of calcium carbonate, and releases it at depth through export and dissolution. We report a significant improvement in the representation of alkalinity in CMIP6 ESMs relative to those in CMIP5. This improvement can be explained in part by an increase in calcium carbonate (CaCO3) production for some ESMs, which redistributes alkalinity at the surface and strengthens its vertical gradient in the water column. We were able to constrain a PIC export estimate of 51–70 Tmol yr-1 at 100 m for the ESMs to match the observed vertical gradient of alkalinity. Biases in the vertical profile of DIC have also significantly decreased, especially with the enhancement of the carbonate pump, but the representation of the saturation horizons has slightly worsened in contrast. Reviewing the representation of the CaCO3 cycle across CMIP5/6, we find a substantial range of parameterizations. While all biogeochemical models currently represent pelagic calcification, they do so implicitly, and they do not represent benthic calcification. In addition, most models simulate marine calcite but not aragonite. In CMIP6 certain model groups have increased the complexity of simulated CaCO3 production, sinking, dissolution and sedimentation. However, this is insufficient to explain the overall improvement in the alkalinity representation, which is therefore likely a result of improved marine biogeochemistry model tuning or ad hoc parameterizations. We find differences in the way ocean alkalinity is initialized that lead to offsets of up to 1 % in the global alkalinity inventory of certain models. These initialization biases should be addressed in future CMIPs by adopting accurate unit conversions. Although modelers aim to balance the global alkalinity budget in ESMs in order to limit drift in ocean carbon uptake under preindustrial conditions, varying assumptions in the closure of the budget have the potential to influence projections of future carbon uptake. For instance, in many models, carbonate production, dissolution and burial are independent of the seawater saturation state, and when considered, the range of sensitivities is substantial. As such, the future impact of ocean acidification on the carbonate pump, and in turn ocean carbon uptake, is potentially underestimated in current ESMs and insufficiently constrained.

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We herein report a 67-year-old woman with malignant lymphomas of the bile duct that developed after regression of a pancreatic head mass. Computed tomography suggested the mass was pancreatic head cancer. Endoscopic ultrasonography showed a low-echoic mass with hyperechoic strands resembling autoimmune pancreatitis. Her serum IgG4 concentration was elevated to 674 mg/dL. After the pancreatic head mass spontaneously diminished, three masses were detected in the common bile duct. A biopsy of the major papilla revealed high-grade B-cell lymphoma with MYC, BCL2 and/or BCL6 rearrangement. Systemic chemotherapy with rituximab plus etoposide, prednisolone, vincristine, cyclophosphamide and doxorubicin resulted in complete remission.

The El Niño Southern Oscillation (ENSO) widely modulates the global carbon cycle, in particular, by altering the net uptake of carbon in the tropical ocean. Indeed, over the tropics less carbon is released by oceans during El Niño while it is the opposite for La Niña. Here, the skill of Earth System Models (ESM) from the latest Coupled Model Intercomparison Project (CMIP6) to simulate the observed tropical Pacific CO2 flux variability in response to ENSO is assessed. The temporal amplitude and spatial extent of CO2 flux anomalies vary considerably among models, while the surface temperature signals of El Niño and La Niña phases are generally well represented. Under historical conditions followed by the high warming Shared Socio-economic Pathway (SSP5-8.5) scenarios, about half the ESMs simulate a reversal in ENSO-CO2 flux relationship. This gradual shift, which occurs as early as the first half of the 21st century, is associated with a high CO2-induced increase in Revelle factor that leads to stronger sensitivity of partial pressure of CO2 (pCO2) to changes in surface temperature between ENSO phases. At the same time, uptake of anthropogenic CO2 substantially increases upper ocean dissolved inorganic carbon (DIC) concentrations, reducing its vertical gradient in the thermocline, and weakening the ENSO-modulated surface DIC variability. The response of ENSO-CO2 flux relationship to future climate change is sensitive to the contemporary mean state of the carbonate ion concentration in the tropics. Models that simulate shift in ENSO-CO2 flux relationship simulate positive bias in surface carbonate concentration.

Predicting carbon fluxes and atmospheric CO2 can constrain the expected next-year atmospheric CO2 growth rate and thereby allow to independently monitor total anthropogenic CO2 emission rates. Several studies have established predictive skill in retrospective forecasts of carbon fluxes. These studies are usually backed by perfect-model simulations of single models showing the origins of predictive skill in carbon fluxes and atmospheric CO2 concentration. Yet, a comprehensive multi-model comparison of perfect-model predictions, which can be valuable in explaining differences in retrospective predictions, is still lacking. Moreover, as of now, we don't have sufficient understanding of how well do the models predict their own integrated carbon cycles and how congruent this predictability is across models.Here, we show the predictive skill of land and ocean carbon fluxes as well as atmospheric CO2 concentration in seven Earth-System-Models. Our first results indicate predictive skill of globally aggregated carbon fluxes of 2±1 years and atmospheric CO2 of 3±2 years. However, the regional patterns, hotspots and origins of predictive skill diverge among models. This heterogeneity explains the regional differences found in existing retrospective forecasts and backs the overall consistent predictability time-scales at global scale.

Global and regional sources and sinks of carbon across the earth’s surface have been studied extensively using atmospheric carbon dioxide (CO2) observations and chemistry-transport model (ACTM) simulations (top-down/inversion method). However, the uncertainties in the regional flux (+ve: source to the atmosphere; −ve: sink on land/ocean) distributions remain unconstrained mainly due to the lack of sufficient high-quality measurements covering the globe in all seasons and the uncertainties in model simulations. Here, we use a suite of 16 inversion cases, derived from a single transport model (MIROC4-ACTM) but different sets of a priori (bottom-up) terrestrial biosphere and oceanic fluxes, as well as prior flux and observational data uncertainties (50 sites) to estimate CO2 fluxes for 84 regions over the period 2000–2020. The ensemble inversions provide a mean flux field that is consistent with the global CO2 growth rate, land and ocean sink partitioning of −2.9 ± 0.3 (±1σ uncertainty on mean) and −1.6 ± 0.2 PgC yr−1, respectively, for the period 2011–2020 (without riverine export correction), offsetting about 22–33 % and 16–18 % of global fossil-fuel CO2 emissions. Aggregated fluxes for 15 land regions compare reasonably well with the best estimations for (approx. 2000–2009) given by the REgional Carbon Cycle Assessment and Processes (RECCAP), and all regions appeared as a carbon sink over 2011–2020. Interannual variability and seasonal cycle in CO2 fluxes are more consistently derived for different prior fluxes when a greater degree of freedom is given to the inversion system (greater prior flux uncertainty). We have evaluated the inversion fluxes using independent aircraft and surface measurements not used in the inversions, which raises our confidence in the ensemble mean flux rather than an individual inversion. Differences between 5-year mean fluxes show promises and capability to track flux changes under ongoing and future CO2 emission mitigation policies.

It is important to understand how the emissions of different regions, sectors, or climate forcers play a role on pathways toward the Paris Agreement temperature targets. There are however methodological challenges for attributing individual contributions due to complexities associated with a variety of climate forcers affecting the climate system on different spatial and temporal scales. Here, we use the latest historical and future emissions data for a comprehensive set of climate forcers as well as land-use datasets and apply the normalized marginal approach to quantify the forcing contributions of regions, sectors and forcing agents toward the 2C and 1.5C targets. We show that most of the worldwide regions and sectors need to maintain forcing levels not higher than present levels to attain the 1.5C target of the Paris Agreement, while slightly higher future forcing levels than present levels are allowed for the 2C target. Our results illustrate the importance of negative CO2 emissions, which contribute -0.75+/-0.44 Wm-2 and -0.42+/-0.27 Wm-2 to the 2C and 1.5C targets. Less negative forcings, or more positive forcings are also identified for the land-use albedo for the 2C and 1.5C scenarios compared to existing studies., 53 pages, 19 figures

Earth system models (ESMs) are commonly used for simulating the climate–carbon (C) cycle and for projecting future global warming. While ESMs are most often applied to century-long climate simulations, millennium-long simulations, which have been conducted by other types of models but not by ESM because of the computational cost, can provide basic fundamental properties of climate–C cycle models and will be required for estimating the carbon dioxide (CO2) concentration and subsequent climate stabilization in the future. This study used two ESMs (the Model for Interdisciplinary Research on Climate, the Earth system model version (MIROC-ESM) and the MIROC Earth system version 2 for long-term simulation (MIROC-ES2L)) to investigate millennium-scale climate and C cycle adjustment to external forcing. The CO2 concentration was doubled abruptly at the beginning of the model simulations and kept at that level for the next 1000 or 2000 years; these model simulations were compared with transient simulations where the CO2 was increased at the rate of 1% year−1 for up to 140 years (1pctCO2). Model simulations to separate and evaluate the C cycle feedbacks were also performed. Unlike the 1pctCO2 experiment, the change in temperature–cumulative anthropogenic C emission (∆T–CE) relationship was non-linear over the millennium time-scales; there were differences in this nonlinearity between the two ESMs. The differences in ∆T–CE among existing models suggest large uncertainty in the ∆T and CE in the millennium-long climate-C simulations. Ocean C and heat transport were found to be disconnected over millennium time-scales, leading to longer time-scale of ocean C accumulation than heat uptake. Although the experimental design used here was highly idealized, this long-lasting C uptake by the ocean should be considered as part of the stabilization of CO2 concentration and global warming. Future studies should perform millennium time-scale simulations using a hierarchy of models to clarify climate-C cycle processes and to understand the long-term response of the Earth system to anthropogenic perturbations.

Based on a set of climate simulations utilizing two kinds of Earth system models (ESMs) in which observed ocean hydrographic data are assimilated using exactly the same data assimilation procedure, we have clarified that the successful simulation of the observed air–sea CO2 flux variations in the equatorial Pacific is tightly linked to the reproducibility of coupled physical air–sea processes. When an ESM with a weaker ENSO (El Niño–Southern Oscillations) amplitude than that of the observations was used for historical simulations with ocean data assimilation, the observed equatorial anticorrelated relationship between the sea surface temperature (SST) and the air–sea CO2 flux on interannual to decadal timescales could not be represented. The simulated CO2 flux anomalies were upward (downward) during El Niño (La Niña) periods in the equatorial Pacific. The reason for this was that the non-negligible correction term in the governing equation of ocean temperature, which was added via the ocean data assimilation procedure, caused an anomalous, spurious equatorial upwelling (downwelling) during El Niño (La Niña) periods, which brought more (less) subsurface layer water rich in dissolved inorganic carbon (DIC) to the surface layer. On the other hand, in the historical simulations where the observational data were assimilated into the other ESM with a more realistic ENSO representation, the correction term associated with the assimilation procedure remained small enough so as not to disturb an anomalous advection–diffusion balance for the equatorial ocean temperature. Consequently, spurious vertical transport of DIC and the resultant positively correlated SST and air–sea CO2 flux variations did not occur. Thus, the reproducibility of the tropical air–sea CO2 flux variability with data assimilation can be significantly attributed to the reproducibility of ENSO in an ESM. Our results suggest that, when using data assimilation to initialize ESMs for carbon cycle predictions, the reproducibility of the internal climate variations in the model itself is of great importance.

Anthropogenic climate change is projected to lead to ocean warming, acidification, deoxygenation, reductions in near-surface nutrients, and changes to primary production, all of which are expected to affect marine ecosystems. Here we assess projections of these drivers of environmental change over the twenty-first century from Earth system models (ESMs) participating in the Coupled Model Intercomparison Project Phase 6 (CMIP6) that were forced under the CMIP6 Shared Socioeconomic Pathways (SSPs). Projections are compared to those from the previous generation (CMIP5) forced under the Representative Concentration Pathways (RCPs). A total of 10 CMIP5 and 13 CMIP6 models are used in the two multi-model ensembles. Under the high-emission scenario SSP5-8.5, the multi-model global mean change (2080–2099 mean values relative to 1870–1899) ± the inter-model SD in sea surface temperature, surface pH, subsurface (100–600 m) oxygen concentration, euphotic (0–100 m) nitrate concentration, and depth-integrated primary production is +3.47±0.78 ∘C, -0.44±0.005, -13.27±5.28, -1.06±0.45 mmol m−3 and -2.99±9.11 %, respectively. Under the low-emission, high-mitigation scenario SSP1-2.6, the corresponding global changes are +1.42±0.32 ∘C, -0.16±0.002, -6.36±2.92, -0.52±0.23 mmol m−3, and -0.56±4.12 %. Projected exposure of the marine ecosystem to these drivers of ocean change depends largely on the extent of future emissions, consistent with previous studies. The ESMs in CMIP6 generally project greater warming, acidification, deoxygenation, and nitrate reductions but lesser primary production declines than those from CMIP5 under comparable radiative forcing. The increased projected ocean warming results from a general increase in the climate sensitivity of CMIP6 models relative to those of CMIP5. This enhanced warming increases upper-ocean stratification in CMIP6 projections, which contributes to greater reductions in upper-ocean nitrate and subsurface oxygen ventilation. The greater surface acidification in CMIP6 is primarily a consequence of the SSPs having higher associated atmospheric CO2 concentrations than their RCP analogues for the same radiative forcing. We find no consistent reduction in inter-model uncertainties, and even an increase in net primary production inter-model uncertainties in CMIP6, as compared to CMIP5.

Purpose of Review The changes or updates in ocean biogeochemistry component have been mapped between CMIP5 and CMIP6 model versions, and an assessment made of how far these have led to improvements in the simulated mean state of marine biogeochemical models within the current generation of Earth system models (ESMs). Recent Findings The representation of marine biogeochemistry has progressed within the current generation of Earth system models. However, it remains difficult to identify which model updates are responsible for a given improvement. In addition, the full potential of marine biogeochemistry in terms of Earth system interactions and climate feedback remains poorly examined in the current generation of Earth system models. Summary Increasing availability of ocean biogeochemical data, as well as an improved understanding of the underlying processes, allows advances in the marine biogeochemical components of the current generation of ESMs. The present study scrutinizes the extent to which marine biogeochemistry components of ESMs have progressed between the 5th and the 6th phases of the Coupled Model Intercomparison Project (CMIP).

Under strong surface wind forcing during winter, direct current observations in the northern Sea of Japan show the existence of strong near-inertial currents in the deep water that is characterized by the extremely homogeneous vertical structures of temperature and salinity. However, the mechanism generating internal waves in the deep water of the northern Sea of Japan has not been well understood. In this study, to clarify the dynamical link between the surface wind forcing and near-inertial currents in the deep water of the northern Sea of Japan, we drive a general circulation model taking into account realistic wind stress, ocean bottom and land topography. In the northern Sea of Japan, the numerical results show that vertically coherent horizontal currents with a speed of ~ 0.05 m s−1 are excited throughout the homogeneous deep water. A two-layer model successfully reproduces the pattern of the horizontal current velocities shown by the general circulation model, indicating that internal waves emanate westward from the northwestern coast of Japan through coastal adjustment to the strong wind forcing event and, while propagating into the ocean interior, they excite evanescent near-inertial response throughout the lower layer below the interface.

Temporal variability of the winter input of wind energy flux (wind power) and its relationship to internal wave fields were examined in the North Pacific. The dominant long-term variability of the wind power input, estimated from a mixed layer slab model, was inferred from an empirical orthogonal function analysis, and it was found that variability partly corresponded to the strength and movement of the Aleutian low. Responses of the internal wave field to the input of wind power were examined for two winters with a meridional float array along 170°W at a sampling interval of 2 dbar. Time series of the vertical diffusivities inferred from density profiles were enhanced during autumn and winter. After comparing diffusivities inferred from densities sampled at 2- and 20-dbar intervals, Argo floats with a vertical resolution of 20 dbar were used to detect spatial and temporal variability of storm-related mixing between 700 and 1000 dbar in the North Pacific over a period of 10 years. Horizontal maps of inferred seasonal diffusivities suggested that the diffusivities were enhanced in autumn and winter. However, it is unlikely that there is a simple linear relationship between the input of wind power and the inferred mixing.

Using the outputs of projections under the highest emission scenario of the representative concentration pathways performed by Earth system models (ESMs), we evaluate the ocean acidification rates of subsurface layers of the western North Pacific, where the strongest sink of atmospheric CO2 is found in the mid-latitudes. The low potential vorticity water mass called the North Pacific Subtropical Mode Water (STMW) shows large dissolved inorganic carbon (DIC) concentration increase, and is advected southwestward, so that, in the sea to the south of Japan, DIC concentration increases and ocean acidification occurs faster than in adjacent regions. In the STMW of the Izu-Ogasawara region, the ocean acidification occurs with a pH decrease of ~0.004 year−1 , a much higher rate than the previously estimated global average (0.0023 year−1), so that the pH decreases by 0.3–0.4 during the twenty-first century and the saturation state of calcite (ΩCa) decreases from ~4.8 down to ~2.4. We find that the ESMs with a deeper mixed layer in the Kuroshio Extension region show a larger increase in DIC concentration within the Izu-Ogasawara region and within the Ryukyu Islands region. Comparing model results with the mixed layer depth obtained from the Argo dataset, we estimate that DIC concentration at a depth of ~200 m increases by 1.4–1.6 μmol kg−1 year−1 in the Izu-Ogasawara region and by 1.1–1.4 μmol kg−1 year−1 in the Ryukyu Islands region toward the end of this century.

The warming rate of global-mean surface temperature slowed down during 1998-2012. Previous studies pointed out role of increasing ocean heat uptake during this global warming slowdown, but its mechanism remains under discussion. Our numerical simulations, in which wind stress anomaly in the equatorial Pacific is imposed from reanalysis data, suggest sub-surface warming in the equatorial Pacific took place during initial phase of the global warming slowdown (1998–2002), as previously reported. It is newly clarified that the Ekman transport from tropics to subtropics is enhanced during the later phase of the slowdown (after 2002) and enhanced subtropical Ekman downwelling causes accelerated heat storage below depth of 700 m in the subtropical Southern Ocean, leading to the post-2002 global warming slowdown. Observational data of ocean temperature also support this scenario. This study provides clear evidence that deeper parts of the Southern Ocean play a critical role in the past-2002 warming slowdown.

The Zeng and Beljaars (2005) sea surface temperature prognostic scheme, developed to represent diurnal warming, is extended to represent rain-induced freshening and cooling. Effects of rain on salinity and temperature in the molecular skin layer (first few hundred micrometers) and the near-surface turbulent layer (first few meters) are separately parameterized by taking into account rain-induced fluxes of sensible heat and freshwater, surface stress, and mixing induced by droplets penetrating the water surface. Numerical results from this scheme are compared to observational data from two field studies of near-surface ocean stratifications caused by rain, to surface drifter observations and to previous computations with an idealized ocean mixed layer model, demonstrating that the scheme produces temperature variations consistent with in situ observations and model results. It reproduces the dependency of salinity on wind and rainfall rate and the lifetime of fresh lenses. In addition, the scheme reproduces the observed lag between temperature and salinity minimum at low wind speed and is sensitive to the peak rain rate for a given amount of rain. Finally, a first assessment of the impact of these fresh lenses on ocean surface variability is given for the near-equatorial western Pacific. In particular, the variability due to the mean rain-induced cooling is comparable to the variability due to the diurnal warming so that they both impact large-scale horizontal surface temperature gradients. The present parameterization can be used in a variety of models to study the impact of rain-induced fresh and cool lenses at different spatial and temporal scales.

Atmospheric supply of iron (Fe) to the ocean has been suggested to regulate marine productivity in large parts of the world’s ocean. However, there are still large uncertainties regarding how the atmospheric inputs of dissolved Fe (DFe) influence the seawater DFe concentrations and thus net primary production (NPP). Here, we use an atmospheric chemistry model and two ocean biogeochemistry models with high (Model H) and low (Model L) sensitivities to atmospheric sources of DFe to explore the responses of ocean biogeochemistry to different types of atmospheric inputs of DFe: mineral dust and combustion aerosols. When both Fe content in mineral dust of 3.5% and Fe solubility of 2% are prescribed in sensitivity simulations, the ocean models overestimate DFe concentration in the surface ocean downwind from the North African and East Asian dust plumes. Considering different degrees of atmospheric Fe processing reduces the overestimates of DFe concentration in the North Atlantic and North Pacific. The two ocean biogeochemistry models show substantially different magnitudes of responses to the atmospheric input of DFe. The more detailed Model H shows a much higher sensitivity of NPP to the change in combustion aerosols than to mineral dust, regardless of relative inputs of the sedimentary sources. This finding suggests that pyrogenic Fe-containing aerosols are more important sources of atmospheric bioavailable Fe for marine productivity than would be expected from the small amount of DFe deposition, especially in the Pacific and Southern oceans.

This study developed a new Model for Interdisciplinary Research on Climate, Earth System version2 for Long-term simulations (MIROC-ES2L) Earth system model (ESM) using a state-of-the-art climate model as the physical core. This model embeds a terrestrial biogeochemical component with explicit carbon–nitrogen interaction to account for soil nutrient control on plant growth and the land carbon sink. The model’s ocean biogeochemical component is largely updated to simulate biogeochemical cycles of carbon, nitrogen, phosphorus, iron, and oxygen such that oceanic primary productivity can be controlled by multiple nutrient limitations. The ocean nitrogen cycle is coupled with the land component via river discharge processes, and external inputs of iron from pyrogenic and lithogenic sources are considered. Comparison of a historical simulation with observation studies showed the model could reproduce reasonable historical changes in climate, the carbon cycle, and other biogeochemical variables together with reasonable spatial patterns of distribution of the present-day condition. The model demonstrated historical human perturbation of the nitrogen cycle through land use and agriculture, and it simulated the resultant impact on the terrestrial carbon cycle. Sensitivity analyses in preindustrial conditions revealed modeled ocean biogeochemistry could be changed regionally (but substantially) by nutrient inputs from the atmosphere and rivers. Through an idealized experiment of a 1 %CO2 increase scenario, we found the transient climate response (TCR) in the model is 1.5 K, i.e., approximately 70 % that of our previous model. The cumulative airborne fraction (AF) is also reduced by 15 % because of the intensified land carbon sink, resulting in an AF close to the multimodel mean of the Coupled Model Intercomparison Project Phase 5 (CMIP5) ESMs. The transient climate response to cumulative carbon emission (TCRE) is 1.3 K EgC−1, i.e., slightly smaller than the average of the CMIP5 ESMs, suggesting optimistic model performance in future climate projections. This model and the simulation results are contributing to the Coupled Model Intercomparison Project Phase 6 (CMIP6). The ESM could help further understanding of climate–biogeochemical interaction mechanisms, projections of future environmental changes, and exploration of our future options regarding sustainable development by evolving the processes of climate, biogeochemistry, and human activities in a holistic and interactive manner.

To evaluate uncertainty in the transient climate response (TCR) associated with microscale deep-ocean mixing processes induced by internal tidal wave breaking, a set of idealized climate model experiments with two different implementations of deep-ocean mixing is conducted under increasing atmospheric CO2 concentration 1% per year. The difference in TCR between the two experiments is 0.16 °C, which is about half as large as the multimodel spread of TCR in the Fifth Assessment Report of the Intergovernmental Panel on Climate Change. The TCR difference can be attributed to the difference in the preindustrial climatological state. In the case where deep-ocean mixing works to enhance ocean stratification in the Pacific intermediate-to-deep layers, because the Pacific water mass is transported to the Southern Ocean by the Pacific meridional overturning circulation, the subsurface stratification in the Southern Ocean is also enhanced and deep wintertime convection there is suppressed. Our study shows that in this case during CO2 increase, ocean heat uptake from the atmosphere to deeper layers is suppressed and TCR is estimated to be higher than the other case. Diminished accumulation of oceanic heat in the deep layer also leads to the sea level depression of ∼0.4 m in the Southern Ocean when atmospheric CO2 concentration has quadrupled. Together with convective and cloud-radiative processes in the atmosphere and oceanic mesoscale processes, microscale deep-ocean mixing can be one of the major candidates in explaining uncertainty in future climate projections.

The deep and bottom waters of the Japan Sea (depth ≳ 1000 m) are characterized by low temperature and weak stratification. In the Japan Basin, especially, the bottom water (depth ≳ 2500 m), called the Japan Sea bottom water (JSBW), with a thickness of over 1000 m, is mostly homogeneous. Several studies in recent decades have suggested that the potential temperature of the JSBW is gradually increasing, even though the thick homogeneous vertical structure is being maintained. Although downward mixing of heat from the upper layer was believed to be responsible for this characteristic feature, our microstructure measurements found that the intensity of turbulence in the JSBW is too weak to explain the formation of the gradually warming thick homogeneous layer. By use of a one-dimensional numerical model we demonstrated that this characteristic feature of the JSBW can be reasonably explained on the basis of a combination of geothermal heating from the seabed and an appropriate horizontal supply of cold water to the bottom layer.

We herein report the case of a 65-year-old man with pericardial involvement associated with autoimmune pancreatitis. Chest CT imaging showed pericardial thickening. The patient responded to corticosteroid therapy, and the pericardial thickening resolved. Multiple organs are involved in immunoglobulin G4 (IgG4)- related disease (IgG4-RD); however, only a few cases of IgG4-related chronic constrictive pericarditis have been reported. To our knowledge, this is the first reported case of IgG4-RD with pericardial involvement at an early stage. This case indicates that recognizing pericardial complications in autoimmune pancreatitis is important and that CT imaging may be useful for obtaining the diagnosis and providing follow-up of pericardial lesions in cases of IgG4-RD. © 2015 The Japanese Society of Internal Medicine.

The atmospheric mixed layer obtained using the Mellor–Yamada model grows slower and becomes shallower than observed, which motivated Nakanishi and Niino (J Meteorol Soc Jpn 87:895–912, 2009) to present a modified version of the Mellor–Yamada model. In this study, incorporating each of the Mellor–Yamada and the Nakanishi–Niino models into an ocean general circulation model, we evaluate its performance in the ocean. Comparing the numerical results with the observed ones in the western North Pacific, the Nakanishi–Niino model is shown to exhibit a better performance than the Mellor–Yamada model under strong wind forcing and sea surface cooling during winter and after passage of typhoons during summer.

We examine how the development of the agro-processing industry contributed to poverty reduction in Thailand. The effects on farmers’ income are emphasized because most of the poor in Thailand are farmers. The development of the agro-processing industry could improve farmers’ income through two channels: (i) the purchase of agricultural products; and (ii) the employment of the poor farmers at factories. We show that the development of the agro-processing industry, which also played a leading role in the high economic growth of the Thai economy, contributed to poverty reduction through both of the two channels. It was hence pro-poor.

The pattern and magnitude of the global ocean overturning circulation is believed to be strongly controlled by the distribution of diapycnal diffusivity below 1000 m depth. Although wind stress fluctuation is a candidate for the major energy sources of diapycnal mixing processes, the global distribution of wind-induced diapycnal diffusivity is still uncertain. It has been believed that internal waves generated by wind stress fluctuations at middle and high latitudes propagate equatorward until their frequency is twice the local inertial frequency and break down via parametric subharmonic instabilities, causing diapycnal mixing. In order to check the proposed scenario, we use a vertically two-dimensional primitive equation model to examine the spatial distribution of “mixing hotspots” caused by wind stress fluctuations. It is shown that most of the wind-induced energy fed into the ocean interior is dissipated within the top 1000 m depth in the wind-forced area and the energy dissipation rate at low latitudes is very small. Consequently, the energy supplied to diapycnal mixing processes below 1000 m depth falls short of the level required to sustain the global ocean overturning circulation.

Two efficiency measures of Chinese industry were estimated at the provincial level from 1994 to 2002, using a directional output distance function. One is a traditional efficiency measure that considers only desirable output, while the other considers both desirable and undesirable outputs simultaneously. A comparison of the two measures revealed that efficiency levels are biased only if desirable output is considered. Five coastal provinces/municipalities that have attracted a large amount of foreign direct investment are found to be the most efficient when only desirable output is considered, and also when both desirable and undesirable outputs are considered. However, omitting undesirable output tends to lead to an overestimate of industrial efficiency levels in Shandong, Sichuan, and Hebei provinces. We also found that a province's industrial structure has significant effects on its efficiency levels.

This article examines the allocative efficiency of water quality management activities to protect endangered salmonid species in a heterogeneous watershed in the Pacific Northwest. Using an integrated hydrological, biological, and economic modeling framework, the relative efficiency of alternative policy targets such as temperature reductions and enhanced fish populations is investigated. Results indicate that the heterogeneous nature of riparian conditions and stream morphology influence the choice of management activities. Localized effects of management efforts on temperature are important to achieve small temperature reductions. However, as the desired magnitude of temperature reductions increases, the cumulative (longitudinal) effects become more important, and management efforts in more distant reaches are more efficient than efforts nearer the point of monitoring. Finally, if the underlying objective is to increase fish populations, targeting conservation efforts based on physical criteria such as water temperatures or other total maximum daily load regulations may lead to substantial inefficiencies. Copyright 2006, Oxford University Press.

Changes in the natural environment that are the result of human activities are becoming evident. Since these changes are interrelated and can not be investigated without interdisciplinary collaboration between scientific fields, Earth system science (ESS) is required to provide a framework for recognizing anew the Earth system as one composed of its interacting subsystems. The concept of ESS has been partially realized by Earth system models (ESMs). In this paper, we focus on modeling in ESS, review related findings mainly from the latest assessment report of the Intergovernmental Panel on Climate Change, and introduce tasks under discussion for the next phases of the following areas of science: the global nitrogen cycle, ocean acidification, land-use and land-cover change, ESMs of intermediate complexity, climate geoengineering, ocean CO2 uptake, and deposition of bioavailable iron in marine ecosystems. Since responding to global change is a pressing mission in Earth science, modeling will continue to contribute to the cooperative growth of diversifying disciplines and expanding ESS, because modeling connects traditional disciplines through explicit interaction between them.