Ocean model formulation influences transient climate response

2021 ◽  
Author(s):  
Tido Semmler ◽  
Johann Jungclaus ◽  
Christopher Danek ◽  
Helge F Goessling ◽  
Nikolay Koldunov ◽  
...  
Keyword(s):  
Ocean Model ◽  
Climate Response ◽  
Model Formulation ◽  
Transient Climate Response

scholarly journals Ocean model formulation influences transient climate response

2021 ◽  
Author(s):  
Tido Semmler ◽  
Johann H Jungclaus ◽  
Christopher Danek ◽  
Helge Goessling ◽  
Nikolay V. Koldunov ◽  
...  
Keyword(s):  
Ocean Model ◽  
Climate Response ◽  
Model Formulation ◽  
Transient Climate Response

scholarly journals Transient Climate Response in Coupled Atmospheric–Ocean General Circulation Models

2013 ◽  
Vol 70 (4) ◽  
pp. 1291-1296 ◽  
Author(s):  
Mao-Chang Liang ◽  
Li-Ching Lin ◽  
Ka-Kit Tung ◽  
Yuk L. Yung ◽  
Shan Sun
Keyword(s):  
Radiative Forcing ◽  
General Circulation ◽  
General Circulation Models ◽  
Ocean Model ◽  
Climate Response ◽  
Intergovernmental Panel ◽  
Transient Climate Response ◽  
Climate System Model ◽  
Uncertainty Range ◽  
Model Version

Abstract The equilibrium climate sensitivity (ECS) has a large uncertainty range among models participating in the Intergovernmental Panel on Climate Change (IPCC) Fourth Assessment Report (AR4) and has recently been presented as “inherently unpredictable.” One way to circumvent this problem is to consider the transient climate response (TCR). However, the TCR among AR4 models also differs by more than a factor of 2. The authors argue that the situation may not necessarily be so pessimistic, because much of the intermodel difference may be due to the fact that the models were run with their oceans at various stages of flux adjustment with their atmosphere. This is shown by comparing multimillennium-long runs of the Goddard Institute for Space Studies model, version E, coupled with the Hybrid Coordinate Ocean Model (GISS-EH) and the Community Climate System Model, version 4 (CCSM4) with what were reported to AR4. The long model runs here reveal the range of variability (~30%) in their TCR within the same model with the same ECS. The commonly adopted remedy of subtracting the “climate drift” is ineffective and adds to the variability. The culprit is the natural variability of the control runs, which exists even at quasi equilibration. Fortunately, for simulations with multidecadal time horizon, robust solutions can be obtained by branching off thousand-year-long control runs that reach “quasi equilibration” using a new protocol, which takes advantage of the fact that forced solutions to radiative forcing forget their initial condition after 30–40 yr and instead depend mostly on the trajectory of the radiative forcing.

scholarly journals Role of Ocean Model Formulation in Climate Response Uncertainty

2018 ◽  
Vol 31 (22) ◽  
pp. 9313-9333 ◽  
Author(s):  
John P. Krasting ◽  
Ronald J. Stouffer ◽  
Stephen M. Griffies ◽  
Robert W. Hallberg ◽  
Sergey L. Malyshev ◽  
...  
Keyword(s):  
Radiative Forcing ◽  
Dissolved Inorganic Carbon ◽  
Ocean Model ◽  
Meridional Overturning Circulation ◽  
Climate Response ◽  
Model Formulation ◽  
Vertical Coordinate ◽  
The Impact ◽  
Climate Responses

Abstract Oceanic heat uptake (OHU) is a significant source of uncertainty in both the transient and equilibrium responses to increasing the planetary radiative forcing. OHU differs among climate models and is related in part to their representation of vertical and lateral mixing. This study examines the role of ocean model formulation—specifically the choice of the vertical coordinate and the strength of the background diapycnal diffusivity Kd—in the millennial-scale near-equilibrium climate response to a quadrupling of atmospheric CO2. Using two fully coupled Earth system models (ESMs) with nearly identical atmosphere, land, sea ice, and biogeochemical components, it is possible to independently configure their ocean model components with different formulations and produce similar near-equilibrium climate responses. The SST responses are similar between the two models (r2 = 0.75, global average ~4.3°C) despite their initial preindustrial climate mean states differing by 0.4°C globally. The surface and interior responses of temperature and salinity are also similar between the two models. However, the Atlantic meridional overturning circulation (AMOC) responses are different between the two models, and the associated differences in ventilation and deep-water formation have an impact on the accumulation of dissolved inorganic carbon in the ocean interior. A parameter sensitivity analysis demonstrates that increasing the amount of Kd produces very different near-equilibrium climate responses within a given model. These results suggest that the impact of the ocean vertical coordinate on the climate response is small relative to the representation of subgrid-scale mixing.

scholarly journals The Norwegian Earth System Model, NorESM1-M – Part 2: Climate response and scenario projections

2012 ◽  
Vol 5 (3) ◽  
pp. 2933-2998 ◽  
Author(s):  
T. Iversen ◽  
M. Bentsen ◽  
I. Bethke ◽  
J. B. Debernard ◽  
A. Kirkevåg ◽  
...  
Keyword(s):  
Climate Model ◽  
Global Climate ◽  
Global Climate Model ◽  
Ocean Model ◽  
Climate Response ◽  
Rcp Scenarios ◽  
Transient Climate Response ◽  
Near Surface ◽  
Enso Events ◽  
Model Average

Abstract. The NorESM1-M simulation results for CMIP5 (http://cmip-pcmdi.llnl.gov/cmip5/index.html) are described and discussed. Together with the accompanying paper by Bentsen et al. (2012), this paper documents that NorESM1-M is a valuable global climate model for research and for providing complementary results to the evaluation of possible man made climate change. NorESM is based on the model CCSM4 operated at NCAR on behalf of many contributors in USA. The ocean model is replaced by a developed version of MICOM and the atmospheric model is extended with on-line calculations of aerosols, their direct effect, and their indirect effect on warm clouds. Model validation is presented in a companion paper (Bentsen et al., 2012). NorESM1-M is estimated to have equilibrium climate sensitivity slightly smaller than 2.9 K, a transient climate response just below 1.4 K, and is less sensitive than most other models. Cloud feedbacks damp the response, and a strong AMOC reduces the heat fraction available for increasing near surface temperatures, for evaporation, and for melting ice. The future projections based on RCP scenarios yield global surface air temperature increase almost one standard deviation lower than a 15-model average. Summer sea-ice is projected to decrease considerably by 2100, and completely for RCP8.5. The AMOC is projected to reduce by 12%, 15–17%, and 32% for the RCP2.6, 4.5, 6.0 and 8.5 respectively. Precipitation is projected to increase in the tropics, decrease in the subtropics and in southern parts of the northern extra-tropics during summer, and otherwise increase in most of the extra-tropics. Changes in the atmospheric water cycle indicate that precipitation events over continents will become more intense and dry spells more frequent. Extra-tropical storminess in the Northern Hemisphere is projected to shift northwards. There are indications of more frequent spring and summer blocking in the Euro-Atlantic sectors and that ENSO events weaken but appear more frequent. These indications are uncertain because of biases in the model's representation of present-day conditions. There are indications that positive phase PNA and negative phase NAO become less frequent under the RCP8.5 scenario, but also this result is considered uncertain. Single-forcing experiments indicate that aerosols and greenhouse gases produce similar geographical patterns of response for near surface temperature and precipitation. These patterns tend to have opposite sign, with important exceptions for precipitation at low latitudes. The asymmetric aerosol effects between the two hemispheres leads to a southward displacement of ITCZ. Both forcing agents thus tend to reduce northern hemispheric subtropical precipitation.

scholarly journals Relationship between physical and biogeochemical parameters and the scenario dependence of the transient climate response to cumulative carbon emissions

2020 ◽  
Vol 7 (1) ◽  
Author(s):  
Kaoru Tachiiri
Keyword(s):  
Carbon Emissions ◽  
Carbon Budget ◽  
Extreme Case ◽  
Initial Increase ◽  
Climate Response ◽  
Earth System ◽  
Transient Climate Response ◽  
Large Correlation ◽  
Before And After ◽  
Biogeochemical Parameters

AbstractThe transient climate response to cumulative carbon emissions (TCRE) is a key metric in estimating the remaining carbon budget for given temperature targets. However, the TCRE has a small scenario dependence that can be non-negligible for stringent temperature targets. To investigate the parametric correlations and scenario dependence of the TCRE, the present study uses a 512-member ensemble of an Earth system model of intermediate complexity (EMIC) perturbing 11 physical and biogeochemical parameters under scenarios with steady increases of 0.25%, 0.5%, 1%, 2%, or 4% per annum (ppa) in the atmospheric CO2 concentration (pCO2), or an initial increase of 1% followed by an annual decrease of 1% thereafter. Although a small difference of 5% (on average) in the TCRE is observed between the 1-ppa and 0.5-ppa scenarios, a significant scenario dependence is found for the other scenarios, with a tendency toward large values in gradual or decline-after-a-peak scenarios and small values in rapidly increasing scenarios. For all scenarios, correlation analysis indicates a remarkably large correlation between the equilibrium climate sensitivity (ECS) and the relative change in the TCRE, which is attributed to the longer response time of the high ECS model. However, the correlations of the ECS with the TCRE and its scenario dependence for scenarios with large pCO2 increase rates are slightly smaller, and those of biogeochemical parameters such as plant respiration and the overall pCO2–carbon cycle feedback are larger, than in scenarios with gradual increases. The ratio of the TCREs under the overshooting (i.e., 1-ppa decrease after a 1-ppa increase) and 1-ppa increase only scenarios had a clear positive relation with zero-emission commitments. Considering the scenario dependence of the TCRE, the remaining carbon budget for the 1.5 °C target could be reduced by 17 or 22% (before and after considering the unrepresented Earth system feedback) for the most extreme case (i.e., the 67th percentile when using the 0.25-ppa scenario as compared to the 1-ppa increase scenario). A single ensemble EMIC is also used to indicate that, at least for high ECS (high percentile) cases, the scenario dependence of the TCRE should be considered when estimating the remaining carbon budget.

Equilibrium Climate Sensitivity and Transient Climate Response biased low in historical simulations of CMIP6 models

2021 ◽  
Author(s):  
Yue Dong ◽  
Kyle C. Armour ◽  
Cristian Proistosescu ◽  
Timothy Andrews ◽  
David S. Battisti ◽  
...  
Keyword(s):  
Climate Sensitivity ◽  
Climate Response ◽  
Transient Climate Response ◽  
Equilibrium Climate Sensitivity

Large ensemble assessment of how the global surface warming response to cumulative carbon differs for negative and positive carbon emissions  

2021 ◽  
Author(s):  
Negar Vakilifard ◽  
Katherine Turner ◽  
Ric Williams ◽  
Philip Holden ◽  
Neil Edwards ◽  
...  
Keyword(s):  
Carbon Emissions ◽  
Radiative Forcing ◽  
Climate Model ◽  
Climate Feedback ◽  
Climate Response ◽  
Ocean Heat Uptake ◽  
Transient Climate Response ◽  
Surface Warming ◽  
Radiative Processes ◽  
Negative Emission

<p>The controls of the effective transient climate response (TCRE), defined in terms of the dependence of surface warming since the pre-industrial to the cumulative carbon emission, is explained in terms of climate model experiments for a scenario including positive emissions and then negative emission over a period of 400 years. We employ a pre-calibrated ensemble of GENIE, grid-enabled integrated Earth system model, consisting of 86 members to determine the process of controlling TCRE in both CO<sub>2</sub> emissions and drawdown phases. Our results are based on the GENIE simulations with historical forcing from AD 850 including land use change, and the future forcing defined by CO<sub>2</sub> emissions and a non-CO<sub>2</sub> radiative forcing timeseries. We present the results for the point-source carbon capture and storage (CCS) scenario as a negative emission scenario, following the medium representative concentration pathway (RCP4.5), assuming that the rate of emission drawdown is 2 PgC/yr CO<sub>2</sub> for the duration of 100 years. The climate response differs between the periods of positive and negative carbon emissions with a greater ensemble spread during the negative carbon emissions. The controls of the spread in ensemble responses are explained in terms of a combination of thermal processes (involving ocean heat uptake and physical climate feedback), radiative processes (saturation in radiative forcing from CO<sub>2</sub> and non-CO<sub>2</sub> contributions) and carbon dependences (involving terrestrial and ocean carbon uptake).  </p>

Ocean model formulation influences climate sensitivity

2021 ◽  
Author(s):  
Tido Semmler ◽  
Johann Jungclaus ◽  
Christopher Danek ◽  
Helge F Goessling ◽  
Nikolay Koldunov ◽  
...  
Keyword(s):  
Sea Ice ◽  
Climate Sensitivity ◽  
North Atlantic ◽  
Heat Content ◽  
Ocean Model ◽  
Max Planck ◽  
Coupled Models ◽  
Ocean Heat Uptake ◽  
Marine Research ◽  
Transient Climate Response

<p>The climate sensitivity is known to be mainly determined by the atmosphere model but here we discover that the ocean model can change a given transient climate response (TCR) by as much as 20% while the equilibrium climate sensitivity (ECS) change is limited to 10%. In our study, two different coupled CMIP6 models (MPI-ESM and AWI-CM) in two different resolutions each are compared. The coupled models share the same atmosphere-land component ECHAM6.3, which has been developed at the Max-Planck-Institute for Meteorology (MPI-M). However, as part of MPI-ESM and AWI-CM, ECHAM6.3 is coupled to two different ocean models, namely the MPIOM sea ice-ocean model developed at MPI-M and the FESOM sea ice-ocean model developed at the Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research (AWI). A reason for the different TCR is different ocean heat uptake through greenhouse gas forcing in AWI simulations compared to MPI-M simulations. Specifically, AWI-CM simulations show stronger surface heating than MPI-ESM simulations while the MPI-M model accumulates more heat in the deeper ocean. The vertically integrated ocean heat content is increasing stronger in MPI-M model configurations compared to AWI model configurations in the high latitudes. Strong vertical mixing in MPI-M model configurations compared to AWI model configurations seems to be key for these differences. The strongest difference in vertical ocean mixing occurs inside the Weddell Gyre, but there are also important differences in another key region, the northern North Atlantic. Over the North Atlantic, these differences materialize in a lack of a warming hole in AWI model configurations and the presence of a warming hole in MPI-M model configurations. All these differences occur largely independent of the considered model resolutions.</p>

scholarly journals Bayesian estimation of Earth's climate sensitivity and transient climate response from observational warming and heat content datasets

2021 ◽  
Vol 12 (2) ◽  
pp. 709-723
Author(s):  
Philip Goodwin ◽  
B. B. Cael
Keyword(s):  
Climate Sensitivity ◽  
Future Climate ◽  
Climate Feedback ◽  
Future Climate Change ◽  
Climate Projections ◽  
Climate Response ◽  
Ocean Heat Uptake ◽  
Transient Climate Response ◽  
Posterior Probability Distribution ◽  
The Impact

Abstract. Future climate change projections, impacts, and mitigation targets are directly affected by how sensitive Earth's global mean surface temperature is to anthropogenic forcing, expressed via the climate sensitivity (S) and transient climate response (TCR). However, the S and TCR are poorly constrained, in part because historic observations and future climate projections consider the climate system under different response timescales with potentially different climate feedback strengths. Here, we evaluate S and TCR by using historic observations of surface warming, available since the mid-19th century, and ocean heat uptake, available since the mid-20th century, to constrain a model with independent climate feedback components acting over multiple response timescales. Adopting a Bayesian approach, our prior uses a constrained distribution for the instantaneous Planck feedback combined with wide-ranging uniform distributions of the strengths of the fast feedbacks (acting over several days) and multi-decadal feedbacks. We extract posterior distributions by applying likelihood functions derived from different combinations of observational datasets. The resulting TCR distributions when using two preferred combinations of historic datasets both find a TCR of 1.5 (1.3 to 1.8 at 5–95 % range) ∘C. We find the posterior probability distribution for S for our preferred dataset combination evolves from S of 2.0 (1.6 to 2.5) ∘C on a 20-year response timescale to S of 2.3 (1.4 to 6.4) ∘C on a 140-year response timescale, due to the impact of multi-decadal feedbacks. Our results demonstrate how multi-decadal feedbacks allow a significantly higher upper bound on S than historic observations are otherwise consistent with.

Sign in / Sign up

Export Citation Format

Share Document