Robust Analytical and Computational Explorations of Coupled Economic-Climate Models with Carbon-Climate Response

2013 ◽  
Author(s):  
Evan W. Anderson ◽  
William A. Brock ◽  
Lars Peter Hansen ◽  
Alan Sanstad
Keyword(s):  
Climate Models ◽  
Climate Response ◽  
Economic Climate

scholarly journals Climate change between the mid and late Holocene in northern high latitudes – Part 2: Model-data comparisons

2010 ◽  
Vol 6 (5) ◽  
pp. 609-626 ◽  
Author(s):  
Q. Zhang ◽  
H. S. Sundqvist ◽  
A. Moberg ◽  
H. Körnich ◽  
J. Nilsson ◽  
...  
Keyword(s):  
Sea Ice ◽  
Climate Models ◽  
Barents Sea ◽  
Arctic Region ◽  
Summer Temperature ◽  
The Arctic ◽  
High Latitudes ◽  
Climate Response ◽  
Model Data ◽  
Model Simulations

Abstract. The climate response over northern high latitudes to the mid-Holocene orbital forcing has been investigated in three types of PMIP (Paleoclimate Modelling Intercomparison Project) simulations with different complexity of the modelled climate system. By first undertaking model-data comparison, an objective selection method has been applied to evaluate the capability of the climate models to reproduce the spatial response pattern seen in proxy data. The possible feedback mechanisms behind the climate response have been explored based on the selected model simulations. Subsequent model-model comparisons indicate the importance of including the different physical feedbacks in the climate models. The comparisons between the proxy-based reconstructions and the best fit selected simulations show that over the northern high latitudes, summer temperature change follows closely the insolation change and shows a common feature with strong warming over land and relatively weak warming over ocean at 6 ka compared to 0 ka. Furthermore, the sea-ice-albedo positive feedback enhances this response. The reconstructions of temperature show a stronger response to enhanced insolation in the annual mean temperature than winter and summer temperature. This is verified in the model simulations and the behaviour is attributed to the larger contribution from the large response in autumn. Despite a smaller insolation during winter at 6 ka, a pronounced warming centre is found over Barents Sea in winter in the simulations, which is also supported by the nearby northern Eurasian continental and Fennoscandian reconstructions. This indicates that in the Arctic region, the response of the ocean and the sea ice to the enhanced summer insolation is more important for the winter temperature than the synchronous decrease of the insolation.

scholarly journals Reconciled climate response estimates from climate models and the energy budget of Earth

2016 ◽  
Vol 6 (10) ◽  
pp. 931-935 ◽  
Author(s):  
Mark Richardson ◽  
Kevin Cowtan ◽  
Ed Hawkins ◽  
Martin B. Stolpe
Keyword(s):  
Energy Budget ◽  
Climate Models ◽  
Climate Response

scholarly journals Climate response of five oak species in the eastern deciduous forest of the southern Appalachian Mountains, USA

2009 ◽  
Vol 39 (3) ◽  
pp. 507-518 ◽  
Author(s):  
James H. Speer ◽  
Henri D. Grissino-Mayer ◽  
Kenneth H. Orvis ◽  
Cathryn H. Greenberg
Keyword(s):  
Climate Models ◽  
Palmer Drought Severity Index ◽  
Severity Index ◽  
Drought Severity ◽  
Significant Variable ◽  
Climate Response ◽  
Climatic Response ◽  
White Oak ◽  
Southeastern Us ◽  
Drought Severity Index

The climatic response of trees that occupy closed canopy forests in the eastern United States (US) is important to understanding the possible trajectory these forests may take in response to a warming climate. Our study examined tree rings of 664 trees from five oak species (white ( Quercus alba L.), black ( Quercus velutina Lam.), chestnut ( Quercus prinus L.), northern red ( Quercus rubra L.), scarlet ( Quercus coccinea Münchh.)) from 17 stands in eastern Tennessee, western North Carolina, and northern Georgia to determine their climatic response. We dated the samples using skeleton plots, measured the cores, and compared the site- and regional-level tree-ring chronologies of each separate species with divisional climate data. The oldest trees in each chronology dated back to 203 years for black oak, 299 years for chestnut oak, 171 years for northern red oak, 135 years for scarlet oak, and 291 years for white oak. We successfully developed climate models via multiple regression analyses with statistically significant (P < 0.05) variables representing the Palmer Drought Severity Index and average monthly temperature for most of the site-species chronologies (average R2 = 0.15). All regional climate response models included the Palmer Drought Severity Index from either June or July as the most significant variable in the climate response, suggesting that growing-season drought is the most important factor limiting oak growth in the southeastern US. An increase in temperature and reduction in moisture is likely to reduce their competitiveness in their current locations and force these species to migrate to cooler climates, thereby greatly changing ecosystem health and stability in the southern Appalachians.

scholarly journals FAIR v1.3: a simple emissions-based impulse response and carbon cycle model

2018 ◽  
Vol 11 (6) ◽  
pp. 2273-2297 ◽  
Author(s):  
Christopher J. Smith ◽  
Piers M. Forster ◽  
Myles Allen ◽  
Nicholas Leach ◽  
Richard J. Millar ◽  
...  
Keyword(s):  
Climate Change ◽  
Greenhouse Gases ◽  
Radiative Forcing ◽  
Climate Models ◽  
Climate Model ◽  
Future Climate Change ◽  
Climate Response ◽  
Transient Climate Response ◽  
Carbon Cycle Model ◽  
Future Projections

Abstract. Simple climate models can be valuable if they are able to replicate aspects of complex fully coupled earth system models. Larger ensembles can be produced, enabling a probabilistic view of future climate change. A simple emissions-based climate model, FAIR, is presented, which calculates atmospheric concentrations of greenhouse gases and effective radiative forcing (ERF) from greenhouse gases, aerosols, ozone and other agents. Model runs are constrained to observed temperature change from 1880 to 2016 and produce a range of future projections under the Representative Concentration Pathway (RCP) scenarios. The constrained estimates of equilibrium climate sensitivity (ECS), transient climate response (TCR) and transient climate response to cumulative CO2 emissions (TCRE) are 2.86 (2.01 to 4.22) K, 1.53 (1.05 to 2.41) K and 1.40 (0.96 to 2.23) K (1000 GtC)−1 (median and 5–95 % credible intervals). These are in good agreement with the likely Intergovernmental Panel on Climate Change (IPCC) Fifth Assessment Report (AR5) range, noting that AR5 estimates were derived from a combination of climate models, observations and expert judgement. The ranges of future projections of temperature and ranges of estimates of ECS, TCR and TCRE are somewhat sensitive to the prior distributions of ECS∕TCR parameters but less sensitive to the ERF from a doubling of CO2 or the observational temperature dataset used to constrain the ensemble. Taking these sensitivities into account, there is no evidence to suggest that the median and credible range of observationally constrained TCR or ECS differ from climate model-derived estimates. The range of temperature projections under RCP8.5 for 2081–2100 in the constrained FAIR model ensemble is lower than the emissions-based estimate reported in AR5 by half a degree, owing to differences in forcing assumptions and ECS∕TCR distributions.

scholarly journals The representation of solar cycle signals in stratospheric ozone – Part 1: A comparison of satellite observations

2016 ◽  
Author(s):  
A. Maycock ◽  
K. Matthes ◽  
S. Tegtmeier ◽  
R. Thiéblemont ◽  
L. Hood
Keyword(s):  
Solar Cycle ◽  
Climate Models ◽  
Stratospheric Ozone ◽  
Satellite Observations ◽  
Solar Variability ◽  
Temperature Measurements ◽  
Climate Response ◽  
Mixing Ratio ◽  
Substantial Impact ◽  
The Impact

Abstract. The impact of changes in incoming solar ultraviolet irradiance on stratospheric ozone forms an important part of the climate response to solar variability. To realistically simulate the climate response to solar variability using climate models, a minimum requirement is that they should include a solar cycle ozone component that has a realistic amplitude and structure, and which varies with season. For climate models that do not include interactive ozone chemistry, this component must be derived from observations and/or chemistry–climate model simulations and included in an externally prescribed ozone database that also includes the effects of all major external forcings. Part 1 of this two part study presents the solar-ozone responses in a number of updated satellite datasets for the period 1984–2004, including the Stratospheric Aerosol and Gas Experiment (SAGE) II version 6.2 and version 7.0 data, and the Solar Backscatter Ultraviolet Instrument (SBUV) version 8.0 and version 8.6 data. A number of combined datasets, which have extended SAGE II using more recent satellite measurements, are also analysed for the period 1984–2011. It is shown that SAGE II derived solar-ozone signals are sensitive to the independent temperature measurements used to convert ozone number density to mixing ratio units. A change in these temperature measurements in the recent SAGE II v7.0 data leads to substantial differences in the mixing ratio solar-ozone response compared to the previous v6.2, particularly in the tropical upper stratosphere. We also show that alternate satellite ozone datasets have issues (e.g., sparse spatial and temporal sampling, low vertical resolution, and shortness of measurement record), and that the methods of accounting for instrument offsets and drifts in merged satellite datasets can have a substantial impact on the solar cycle signal in ozone. For example, the magnitude of the solar-ozone response varies by around a factor of two across different versions of the SBUV VN8.6 record, which appears to be due to the methods used to combine the separate SBUV timeseries. These factors make it difficult to extract more than an annual-mean solar-ozone response from the available satellite observations. It is therefore unlikely that satellite ozone measurements alone can be applied to estimate the necessary solar cycle ozone component of the prescribed ozone database for future coupled model intercomparison projects (e.g., CMIP6).

scholarly journals A Stochastic Analysis of the Impact of Small-Scale Fluctuations on the Tropospheric Temperature Response to CO2 Doubling

2010 ◽  
Vol 23 (9) ◽  
pp. 2307-2319 ◽  
Author(s):  
Rita Seiffert ◽  
Jin-Song von Storch
Keyword(s):  
Climate Models ◽  
Climate Model ◽  
Small Scale ◽  
Tropospheric Temperature ◽  
Climate Response ◽  
Restoring Force ◽  
Global Mean Temperature ◽  
Mean Temperature ◽  
The Impact ◽  
Global Mean

Abstract The climate response to increased CO2 concentration is generally studied using climate models that have finite spatial and temporal resolutions. Different parameterizations of the effect of unresolved processes can result in different representations of small-scale fluctuations in the climate model. The representation of small-scale fluctuations can, on the other hand, affect the modeled climate response. In this study the mechanisms by which enhanced small-scale fluctuations alter the climate response to CO2 doubling are investigated. Climate experiments with preindustrial and doubled CO2 concentrations obtained from a comprehensive climate model [ECHAM5/Max Planck Institute Ocean Model (MPI-OM)] are analyzed both with and without enhanced small-scale fluctuations. By applying a stochastic model to the experimental results, two different mechanisms are found. First, the small-scale fluctuations can change the statistical behavior of the global mean temperature as measured by its statistical damping. The statistical damping acts as a restoring force that determines, according to the fluctuation–dissipation theory, the amplitude of the climate response to a change in external forcing (here, CO2 doubling). Second, the small-scale fluctuations can affect processes that occur only in response to the CO2 increase, thereby altering the change of the effective forcing on the global mean temperature.

scholarly journals Estimating the Permafrost-Carbon Climate Response in the CMIP5 Climate Models Using a Simplified Approach

2013 ◽  
Vol 26 (14) ◽  
pp. 4897-4909 ◽  
Author(s):  
Eleanor J. Burke ◽  
Chris D. Jones ◽  
Charles D. Koven
Keyword(s):  
Climate Change ◽  
Radiative Forcing ◽  
Climate Models ◽  
Coupled Model ◽  
Climate Feedback ◽  
Cmip5 Models ◽  
Future Climate Change ◽  
Permafrost Region ◽  
Climate Response ◽  
Simplified Approach

Abstract Under climate change, thawing permafrost may cause a release of carbon, which has a positive feedback on the climate. The permafrost-carbon climate response (γPF) is the additional permafrost-carbon made vulnerable to decomposition per degree of global temperature increase. A simple framework was adopted to estimate γPF using the database for phase 5 of the Coupled Model Intercomparison Project (CMIP5). The projected changes in the annual maximum active layer thicknesses (ALTmax) over the twenty-first century were quantified using CMIP5 soil temperatures. These changes were combined with the observed distribution of soil organic carbon and its potential decomposability to give γPF. This estimate of γPF is dependent on the biases in the simulated present-day permafrost. This dependency was reduced by combining a reference estimate of the present-day ALTmax with an estimate of the sensitivity of ALTmax to temperature from the CMIP5 models. In this case, γPF was from −6 to −66 PgC K−1(5th–95th percentile) with a radiative forcing of 0.03–0.29 W m−2 K−1. This range is mainly caused by uncertainties in the amount of soil carbon deeper in the soil profile and whether it thaws over the time scales under consideration. These results suggest that including permafrost-carbon within climate models will lead to an increase in the positive global carbon climate feedback. Under future climate change the northern high-latitude permafrost region is expected to be a small sink of carbon. Adding the permafrost-carbon response is likely to change this region to a source of carbon.

Climate Response of the Equatorial Pacific to Global Warming

2009 ◽  
Vol 22 (18) ◽  
pp. 4873-4892 ◽  
Author(s):  
Pedro N. DiNezio ◽  
Amy C. Clement ◽  
Gabriel A. Vecchi ◽  
Brian J. Soden ◽  
Benjamin P. Kirtman ◽  
...  
Keyword(s):  
Heat Transport ◽  
Climate Models ◽  
Heat Budget ◽  
Walker Circulation ◽  
Warm Pool ◽  
Equatorial Pacific ◽  
Radiative Heating ◽  
Climate Response ◽  
Intergovernmental Panel ◽  
Near Surface

Abstract The climate response of the equatorial Pacific to increased greenhouse gases is investigated using numerical experiments from 11 climate models participating in the Intergovernmental Panel on Climate Change’s Fourth Assessment Report. Multimodel mean climate responses to CO2 doubling are identified and related to changes in the heat budget of the surface layer. Weaker ocean surface currents driven by a slowing down of the Walker circulation reduce ocean dynamical cooling throughout the equatorial Pacific. The combined anomalous ocean dynamical plus radiative heating from CO2 is balanced by different processes in the western and eastern basins: Cloud cover feedbacks and evaporation balance the heating over the warm pool, while increased cooling by ocean vertical heat transport balances the warming over the cold tongue. This increased cooling by vertical ocean heat transport arises from increased near-surface thermal stratification, despite a reduction in vertical velocity. The stratification response is found to be a permanent feature of the equilibrium climate potentially linked to both thermodynamical and dynamical changes within the equatorial Pacific. Briefly stated, ocean dynamical changes act to reduce (enhance) the net heating in the east (west). This explains why the models simulate enhanced equatorial warming, rather than El Niño–like warming, in response to a weaker Walker circulation. To conclude, the implications for detecting these signals in the modern observational record are discussed.

GFDL's CM2 Global Coupled Climate Models. Part IV: Idealized Climate Response

2006 ◽  
Vol 19 (5) ◽  
pp. 723-740 ◽  
Author(s):  
R. J. Stouffer ◽  
A. J. Broccoli ◽  
T. L. Delworth ◽  
K. W. Dixon ◽  
R. Gudgel ◽  
...  
Keyword(s):  
Climate Change ◽  
Air Temperature ◽  
Climate Models ◽  
Climate Model ◽  
Surface Air Temperature ◽  
Co2 Concentration ◽  
Atmospheric Co2 ◽  
Climate Response ◽  
Atmospheric Co2 Concentration ◽  
Group I

Abstract The climate response to idealized changes in the atmospheric CO2 concentration by the new GFDL climate model (CM2) is documented. This new model is very different from earlier GFDL models in its parameterizations of subgrid-scale physical processes, numerical algorithms, and resolution. The model was constructed to be useful for both seasonal-to-interannual predictions and climate change research. Unlike previous versions of the global coupled GFDL climate models, CM2 does not use flux adjustments to maintain a stable control climate. Results from two model versions, Climate Model versions 2.0 (CM2.0) and 2.1 (CM2.1), are presented. Two atmosphere–mixed layer ocean or slab models, Slab Model versions 2.0 (SM2.0) and 2.1 (SM2.1), are constructed corresponding to CM2.0 and CM2.1. Using the SM2 models to estimate the climate sensitivity, it is found that the equilibrium globally averaged surface air temperature increases 2.9 (SM2.0) and 3.4 K (SM2.1) for a doubling of the atmospheric CO2 concentration. When forced by a 1% per year CO2 increase, the surface air temperature difference around the time of CO2 doubling [transient climate response (TCR)] is about 1.6 K for both coupled model versions (CM2.0 and CM2.1). The simulated warming is near the median of the responses documented for the climate models used in the 2001 Intergovernmental Panel on Climate Change (IPCC) Working Group I Third Assessment Report (TAR). The thermohaline circulation (THC) weakened in response to increasing atmospheric CO2. By the time of CO2 doubling, the weakening in CM2.1 is larger than that found in CM2.0: 7 and 4 Sv (1 Sv ≡ 106 m3 s−1), respectively. However, the THC in the control integration of CM2.1 is stronger than in CM2.0, so that the percentage change in the THC between the two versions is more similar. The average THC change for the models presented in the TAR is about 3 or 4 Sv; however, the range across the model results is very large, varying from a slight increase (+2 Sv) to a large decrease (−10 Sv).

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