Adjustment of the natural ocean carbon cycle to negative emission rates

Carbon dioxide removal (CDR) is the only geoengineering technique that allows negative emissions and the reduction of anthropogenic carbon in the atmosphere. Since the time scales of the global carbon cycle are largely driven by the exchanges with the natural oceanic stocks, the implementation of CDR actions is anticipated to create outgassing from the ocean that may reduce their efficiency. The adjustment of the natural carbon cycle to CDR was studied with a numerical Earth System Model, focusing on the oceanic component and considering two idealized families of CDR policies, one based on a target atmospheric concentration and one based on planned negative emissions. Results show that both actions are anticipated to release the anthropogenic carbon stored in the surface ocean, effectively increasing the required removal effort. The additional negative emissions are expected to be lower when the CDR policy is driven by planned removal rates without prescribing a target atmospheric CO2 concentration

Projected changes in intense precipitation over Europe at the daily and subdaily time scales.

Abstract Heavy precipitation is a major hazard over Europe. It is well established that climate model projections indicate a tendency toward more extreme daily rainfall events. It is still uncertain, however, how this changing intensity translates at the subdaily time scales. The main goal of the present study is to examine possible differences in projected changes in intense precipitation events over Europe at the daily and subdaily (3-hourly) time scales using a state-of-the-science climate model. The focus will be on one representative concentration pathway (RCP8.5), considered as illustrative of a high rate of increase in greenhouse gas concentrations over this century. There are statistically significant differences in intense precipitation projections (up to 40%) when comparing the results at the daily and subdaily time scales. Over northeastern Europe, projected precipitation intensification at the 3-hourly scale is lower than at the daily scale. On the other hand, Spain and the western seaboard exhibit an opposite behavior, with stronger intensification at the 3-hourly scale rather than the daily scale. While the mean properties of the precipitation distributions are independent of the analyzed frequency, projected precipitation intensification exhibits regional differences. This finding has implications for the extrapolation of impacts of intense precipitation events, given the daily time scale at which the analyses are usually performed

Extreme events representation in CMCC-CM2 standard and high-resolution general circulation models

The recent advancements in climate modeling partially build on the improvement of horizontal resolution in different components of the simulating system. A higher resolution is expected to provide a better representation of the climate variability, and in this work we are particularly interested in the potential improvements in representing extreme events of high temperature and precipitation. The two versions of the Centro Euro-Mediterraneo sui Cambiamenti Climatici (CMCC-CM2) model used here adopt the highest horizontal resolutions available within the last family of the global coupled climate models developed at CMCC to participate in the Coupled Model Intercomparison Projects, Phase 6 (CMIP6) effort. The main aim of this study is to document the ability of the CMCC-CM2 models to represent the spatial distribution of extreme events of temperature and precipitation, under the historical period, comparing model results to observations, the European Centre for Medium-Range Weather Forecasts (ECMWF) reanalysis (ERA5), multi-source weighted-ensemble precipitation (MSWEP) and Climate Hazards Group infrared precipitation with station data (CHIRPS) observations. For a more detailed evaluation we use both 6-hourly and daily time series, to compute indices representative of intense and extreme conditions. In terms of mean climate, the two models are able to realistically reproduce the main patterns of temperature and precipitation. The high resolution version ( ∘ horizontal resolution) of the atmospheric model provides better results than the standard resolution one (1°), not only in terms of means but also in terms of intense and extreme events of temperature defined at daily and 6-hourly frequencies. This is also the case of average and intense precipitation. On the other hand the extreme precipitation is not improved by the adoption of a higher horizontal resolution

Climate variability and change in the Euro-Mediterranean Region: results from a global AOGCM coupled with an interactive high-resolution model of the Mediterranean Sea

In this work we present and discuss the results obtained from a set of present and future climate simulations performed with a high-resolution model able to represent the dynamics of the Mediterranean Sea. The ability of the model to reproduce the basic features of the observed climate in the Mediterranean region and the beneficial effects of both atmospheric improved resolution and interactive Mediterranean Sea are assessed. In particular, the major characteristics of the variability in the Mediterranean basin and its connection with the large-scale circulation are investigated. Furthermore, the mechanisms through which global warming might affect the regional features of the climate are explored, focusing especially on the characteristics of the hydrological cycle

EFFECTS OF TROPICAL CYCLONES ON OCEAN HEAT TRANSPORT AS SIMULATED BY A HIGH RESOLUTION COUPLED GENERAL CIRCULATION MODEL

In this study the interplay between Tropical Cyclones (TCs) and the Northern hemispheric Ocean Heat Transport (OHT) is investigated. In particular, results from a numerical simulation of the 20th and 21st Century climate, following the Intergovernmental Panel for Climate Change (IPCC) 20C3M and A1B scenario protocols respectively have been analyzed. The numerical simulations have been performed using a state-of-the-art global atmosphere-ocean-sea-ice coupled general circulation model - CGCM (CMCC-MED, Gualdi et al. 2010, Scoccimarro et al. 2010) with relatively high-resolution (T159) in the atmosphere. The model is an evolution of the INGV-SXG (Gualdi et al. 2008, Bellucci et al. 2008) and the ECHAM-OPA-LIM (Fogli et al. 2009, Vichi et al. 2010) The simulated TCs exhibit realistic structure, geographical distribution (Fig.2) and interannual variability, indicating that the model is able to capture the basic mechanisms linking the TC activity with the large scale circulation. The cooling of the surface ocean observed in correspondence of the TCs is well simulated by the model (Fig.3). TC activity is shown to significantly affect the poleward OHT out of the tropics, and the heat transport into the deep tropics (Fig.4). This effect, investigated by looking at the 100 most intense Northern Hemisphere TCs, is strongly correlated with the TC-induced momentum flux at the ocean surface (Fig.7). TCs frequency and intensity appear to be substantially stationary through the whole 1950-2069 simulated period as well as the effect of the TCs on the meridional OHT

Global mean climate and main patterns of variability in the CMCC-CM2 coupled model

Euro‐Mediterranean Centre on Climate Change coupled climate model (CMCC‐CM2) represents the new family of the global coupled climate models developed and used at CMCC. It is based on the atmospheric, land and sea ice components from the Community Earth System Model coupled with the global ocean model Nucleus for European Modeling of the Ocean. This study documents the model components, the coupling strategy, particularly for the oceanic, atmospheric, and sea ice components, and the overall model ability in reproducing the observed mean climate and main patterns of interannual variability. As a first step toward a more comprehensive, process‐oriented, validation of the model, this work analyzes a 200‐year simulation performed under constant forcing corresponding to present‐day climate conditions. In terms of mean climate, the model is able to realistically reproduce the main patterns of temperature, precipitation, and winds. Specifically, we report improvements in the representation of the sea surface temperature with respect to the previous version of the model. In terms of mean atmospheric circulation features, we notice a realistic simulation of upper tropospheric winds and midtroposphere geopotential eddies. The oceanic heat transport and the Atlantic meridional overturning circulation satisfactorily compare with present‐day observations and estimates from global ocean reanalyses. The sea ice patterns and associated seasonal variations are realistically reproduced in both hemispheres, with a better skill in winter. Main weaknesses of the simulated climate are related with the precipitation patterns, specifically in the tropical regions with large dry biases over the Amazon basin. Similarly, the seasonal precipitation associated with the monsoons, mostly over Asia, is weaker than observed. The main patterns of interannual variability in terms of dominant empirical orthogonal functions are faithfully reproduced, mostly in the Northern Hemisphere winter. In the tropics the main teleconnection patterns associated with El Niño–Southern Oscillation and with the Indian Ocean Dipole are also in good agreement with observations.Published4A. Oceanografia e climaJCR Journa

Impact of increased resolution on Arctic Ocean simulations in Ocean Model Intercomparison Project phase 2 (OMIP-2)

This study evaluates the impact of increasing resolution on Arctic Ocean simulations using five pairs of matched low- and high-resolution models within the OMIP-2 (Ocean Model Intercomparison Project phase 2) framework. The primary objective is to assess whether a higher resolution can mitigate typical biases in low-resolution models and improve the representation of key climate-relevant variables. We reveal that increasing the horizontal resolution contributes to a reduction in biases in mean temperature and salinity and improves the simulation of the Atlantic water layer and its decadal warming events. A higher resolution also leads to better agreement with observed surface mixed-layer depth, cold halocline base depth and Arctic gateway transports in the Fram and Davis straits. However, the simulation of the mean state and temporal changes in Arctic freshwater content does not show improvement with increased resolution. Not all models achieve improvements for all analyzed ocean variables when spatial resolution is increased so it is crucial to recognize that model numerics and parameterizations also play an important role in faithful simulations. Overall, a higher resolution shows promise in improving the simulation of key Arctic Ocean features and processes, but efforts in model development are required to achieve more accurate representations across all climate-relevant variables.</p

An assessment of the Arctic Ocean in a suite of interannual CORE-II simulations. Part III: Hydrography and fluxes

In this paper we compare the simulated Arctic Ocean in 15 global ocean–sea ice models in the framework of the Coordinated Ocean-ice Reference Experiments, phase II (CORE-II). Most of these models are the ocean and sea-ice components of the coupled climate models used in the Coupled Model Intercomparison Project Phase 5 (CMIP5) experiments. We mainly focus on the hydrography of the Arctic interior, the state of Atlantic Water layer and heat and volume transports at the gateways of the Davis Strait, the Bering Strait, the Fram Strait and the Barents Sea Opening. We found that there is a large spread in temperature in the Arctic Ocean between the models, and generally large differences compared to the observed temperature at intermediate depths. Warm bias models have a strong temperature anomaly of inflow of the Atlantic Water entering the Arctic Ocean through the Fram Strait. Another process that is not represented accurately in the CORE-II models is the formation of cold and dense water, originating on the eastern shelves. In the cold bias models, excessive cold water forms in the Barents Sea and spreads into the Arctic Ocean through the St. Anna Through. There is a large spread in the simulated mean heat and volume transports through the Fram Strait and the Barents Sea Opening. The models agree more on the decadal variability, to a large degree dictated by the common atmospheric forcing. We conclude that the CORE-II model study helps us to understand the crucial biases in the Arctic Ocean. The current coarse resolution state-of-the-art ocean models need to be improved in accurate representation of the Atlantic Water inflow into the Arctic and density currents coming from the shelves

Evaluation of global ocean–sea-ice model simulations based on the experimental protocols of the Ocean Model Intercomparison Project phase 2 (OMIP-2)

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 processlevel 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

Evaluation of global ocean–sea-ice model simulations based on the experimental protocols of the Ocean Model Intercomparison Project phase 2 (OMIP-2)

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.This research has been supported by the Integrated Research Program for Advancing Climate Models (TOUGOU) of the Ministry of Education, Culture, Sports, Science and Technology (MEXT), Japan (grant nos. JPMXD0717935457 and JPMXD0717935561), the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) (grant no. 274762653), the Helmholtz Climate Initiative REKLIM (Regional Climate Change) and European Union's Horizon 2020 Research & Innovation program (grant nos. 727862 and 800154), the Research Council of Norway (EVA (grant no. 229771) and INES (grant no. 270061)), the US National Science Foundation (NSF) (grant no. 1852977), the National Natural Science Foundation of China (grant nos. 41931183 and 41976026), NOAA's Science Collaboration Program and administered by UCAR's Cooperative Programs for the Advancement of Earth System Science (CPAESS) (grant nos. NA16NWS4620043 and NA18NWS4620043B), and NOAA (grant no. NA18OAR4320123).Peer ReviewedPostprint (published version