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 Uncertainty in the relationship between climate forcing and hydrological response in UK catchments

2011 ◽  
Vol 15 (3) ◽  
pp. 897-912 ◽  
Author(s):  
N. W. Arnell
Keyword(s):  
Climate Change ◽  
Climate Models ◽  
Climate Model ◽  
Climate Forcing ◽  
Hydrological Response ◽  
Climate Scenarios ◽  
Global Mean Temperature ◽  
Mean Temperature ◽  
The Relationship ◽  
Global Mean

Abstract. This paper assesses the relationship between amount of climate forcing – as indexed by global mean temperature change – and hydrological response in a sample of UK catchments. It constructs climate scenarios representing different changes in global mean temperature from an ensemble of 21 climate models assessed in the IPCC AR4. The results show a considerable range in impact between the 21 climate models, with – for example – change in summer runoff at a 2 °C increase in global mean temperature varying between −40% and +20%. There is evidence of clustering in the results, particularly in projected changes in summer runoff and indicators of low flows, implying that the ensemble mean is not an appropriate generalised indicator of impact, and that the standard deviation of responses does not adequately characterise uncertainty. The uncertainty in hydrological impact is therefore best characterised by considering the shape of the distribution of responses across multiple climate scenarios. For some climate model patterns, and some catchments, there is also evidence that linear climate change forcings produce non-linear hydrological impacts. For most variables and catchments, the effects of climate change are apparent above the effects of natural multi-decadal variability with an increase in global mean temperature above 1 °C, but there are differences between catchments. Based on the scenarios represented in the ensemble, the effect of climate change in northern upland catchments will be seen soonest in indicators of high flows, but in southern catchments effects will be apparent soonest in measures of summer and low flows. The uncertainty in response between different climate model patterns is considerably greater than the range due to uncertainty in hydrological model parameterisation.

scholarly journals The relationship between climate forcing and hydrological response in UK catchments

2010 ◽  
Vol 7 (5) ◽  
pp. 7633-7667 ◽  
Author(s):  
N. W. Arnell
Keyword(s):  
Climate Change ◽  
Climate Models ◽  
Climate Model ◽  
Climate Forcing ◽  
Hydrological Response ◽  
Climate Scenarios ◽  
Global Mean Temperature ◽  
Mean Temperature ◽  
The Relationship ◽  
Global Mean

Abstract. This paper assesses the relationship between amount of climate forcing – as indexed by global mean temperature change – and hydrological response in a sample of UK catchments. It constructs climate scenarios representing different changes in global mean temperature from an ensemble of 21 climate models assessed in the IPCC AR4. The results show a considerable range in impact between the 21 climate models, with – for example – change in summer runoff at a 2 °C increase in global mean temperature varying between −40% and +20%. There is evidence of clustering in the results, particularly in projected changes in summer runoff and indicators of low flows, implying that the ensemble mean is not an appropriate generalised indicator of impact, and that the standard deviation of responses does not adequately characterise uncertainty. The uncertainty in hydrological impact is therefore best characterised by considering the shape of the distribution of responses across multiple climate scenarios. For some climate model patterns, and some catchments, there is also evidence that linear climate change forcings produce non-linear hydrological impacts. For most variables and catchments, the effects of climate change are apparent above the effects of natural multi-decadal variability with an increase in global mean temperature above 1 °C, but there are differences between catchments. Based on the scenarios represented in the ensemble, it is likely that the effect of climate change in northern upland catchments will be seen soonest in indicators of high flows, but in southern catchments effects will be apparent soonest in measures of summer and low flows. The uncertainty in response between different climate model patterns is considerably greater than the range due to uncertainty in hydrological model parameterisation.

scholarly journals Uncertainties in the global temperature change caused by carbon release from permafrost thawing

2012 ◽  
Vol 6 (2) ◽  
pp. 1367-1404 ◽  
Author(s):  
E. J. Burke ◽  
I. P. Hartley ◽  
C. D. Jones
Keyword(s):  
Soil Carbon ◽  
Climate Model ◽  
Mitigation Measures ◽  
High Concentration ◽  
Global Mean Temperature ◽  
Mean Temperature ◽  
Carbon Release ◽  
The Impact ◽  
Global Mean

Abstract. Under climate change thawing permafrost will cause old carbon which is currently frozen and inert to become vulnerable to decomposition and release into the climate system. This paper develops a simple framework for estimating the impact of this permafrost carbon release on the global mean temperature (P-GMT). The analysis is based on simulations made with the Hadley Centre climate model (HadGEM2-ES) for a range of representative CO2 concentration pathways. Results using the high concentration pathway (RCP 8.5) suggest that by 2100 the annual methane (CH4) emission rate is 2–59 Tg CH4 yr−1 and 50–270 Pg C has been released as CO2 with an associated P-GMT of 0.08–0.36 °C (all 5th–95th percentile ranges). P-GMT is considerably lower – between 0.02 and 0.11 °C – for the low concentration pathway (RCP2.6). The uncertainty in climate model scenario causes about 50% of the spread in P-GMT by the end of the 21st century, indicating that the effect of permafrost thaw on global mean temperature is currently controllable by mitigation measures. The distribution of soil carbon, in particular how it varies with depth, contributes to about half of the remaining spread in P-GMT by 2100 with quality of soil carbon and decomposition processes contributing a further quarter each. These latter uncertainties could be reduced through additional observations. Over the next 20–30 yr, whilst scenario uncertainty is small, improving our knowledge of the quality of soil carbon will contribute significantly to reducing the spread in the, albeit relatively small, P-GMT.

scholarly journals A new dataset for systematic assessments of climate change impacts as a function of global warming

2012 ◽  
Vol 5 (4) ◽  
pp. 3533-3572 ◽  
Author(s):  
J. Heinke ◽  
S. Ostberg ◽  
S. Schaphoff ◽  
K. Frieler ◽  
C. Müller ◽  
...  
Keyword(s):  
Climate Change ◽  
Temperature Change ◽  
Climate Models ◽  
Climate Model ◽  
Climate Change Impacts ◽  
Climate Change Scenarios ◽  
Political Debate ◽  
Global Mean Temperature ◽  
Mean Temperature ◽  
Global Mean

Abstract. In the ongoing political debate on climate change, global mean temperature change (ΔTglob) has become the yardstick by which mitigation costs, impacts from unavoided climate change, and adaptation requirements are discussed. For a scientifically informed discourse along these lines systematic assessments of climate change impacts as a function of ΔTglob are required. The current availability of climate change scenarios constrains this type of assessment to a narrow range of temperature change and/or a reduced ensemble of climate models. Here, a newly composed dataset of climate change scenarios is presented that addresses the specific requirements for global assessments of climate change impacts as a function of ΔTglob. A pattern-scaling approach is applied to extract generalized patterns of spatially explicit change in temperature, precipitation and cloudiness from 19 AOGCMs. The patterns are combined with scenarios of global mean temperature increase obtained from the reduced-complexity climate model MAGICC6 to create climate scenarios covering warming levels from 1.5 to 5 degrees above pre-industrial levels around the year 2100. The patterns are shown to sufficiently maintain the original AOGCMs' climate change properties, even though they, necessarily, utilize a simplified relationships between ΔTglob and changes in local climate properties. The dataset (made available online upon final publication of this paper) facilitates systematic analyses of climate change impacts as it covers a wider and finer-spaced range of climate change scenarios than the original AOGCM simulations.

A new approach for assessing climate change impacts in ecotron experiments

2019 ◽  
Author(s):  
Inne Vanderkelen ◽  
Jakob Zschleischler ◽  
Lukas Gudmundsson ◽  
Klaus Keuler ◽  
Francois Rineau ◽  
...  
Keyword(s):  
Climate Change ◽  
Regional Climate Model ◽  
Climate Model ◽  
Global Climate Model ◽  
Regional Climate ◽  
Climate Change Impacts ◽  
New Approach ◽  
Global Mean Temperature ◽  
Mean Temperature ◽  
Global Mean

Abstract. Ecotron facilities allow accurate control of many environmental variables coupled with extensive monitoring of ecosystem processes. They therefore require multivariate perturbation of climate variables, close to what is observed in the field and projections for the future, preserving the co-variances between variables and the projected changes in variability. Here we present a new experimental design for studying climate change impacts on terrestrial ecosystems and apply it to the UHasselt Ecotron Experiment. The new methodology consists of generating climate forcing along a gradient representative of increasingly high global mean temperature anomalies and uses data derived from the best available regional climate model (RCM) projection. We first identified the best performing regional climate model (RCM) simulation for the ecotron site from the Coordinated Regional Downscaling Experiment in the European Domain (EURO-CORDEX) ensemble with a 0.11° (12.5 km) resolution based on two criteria: (i) highest skill of the simulations compared to observations from a nearby weather station and (ii) representativeness of the multi-model mean in future projections. Our results reveal that no single RCM simulation has the best score for all possible combinations of the four meteorological variables and evaluation metrics considered. Out of the six best performing simulations, we selected the simulation with the lowest bias for precipitation (CCLM4-8-17/EC-EARTH), as this variable is key to ecosystem functioning and model simulations deviated the most for this variable, with values ranging up to double the observed values. The time window is subsequently selected from the RCM projection for each ecotron unit based on the global mean temperature of the driving Global Climate Model (GCM). The ecotron units are forced with 3-hourly output from the RCM projections of the five-year period spanning the year in which the global mean temperature crosses the predefined values. With the new approach, Ecotron facilities become able to assess ecosystem responses on changing climatic conditions, while accounting for the co-variation between climatic variables and their projection in variability, well representing possible compound events. The gradient approach will allow to identify possible threshold and tipping points.

scholarly journals Power-law behavior in millennium climate simulations

2012 ◽  
Vol 3 (1) ◽  
pp. 391-416
Author(s):  
S. V. Henriksson ◽  
P. Räisänen ◽  
J. Silen ◽  
H. Järvinen ◽  
A. Laaksonen
Keyword(s):  
Power Law ◽  
El Niño ◽  
El Nino ◽  
Temperature Record ◽  
Frequency Range ◽  
Global Mean Temperature ◽  
Mean Temperature ◽  
Starting Point ◽  
The Impact ◽  
Global Mean

Abstract. Using a method of discrete Fourier transform with varying starting point and length of time window and the long time series provided by millennium Earth System Model simulations, we get good fits to power laws between two characteristic oscillatory timescales of the model climate: multidecadal (50–80 yr) and El Nino (3–6 yr) timescales. For global mean temperature, we fit β ~ 0.35 in a relation S(f) ~ f−β in a simulation without external climate forcing and β over 0.7 in a simulation with external forcing included. We also fit a power law with β ~ 8 to the narrow frequency range between El Nino frequencies and the Nyquist frequency. Regional variability in best-fit β is explored and the impact of choosing the frequency range on the result is illustrated. When all resolved frequencies are used, land areas seem to have lower βs than ocean areas on average, but when fits are restricted to frequencies below 1/(6 yr), this difference disappears, while regional differences still remain. Results compare well with measurements both for global mean temperature and for the Central England temperature record.

scholarly journals Climate Warming in Response to Emission Reductions Consistent with the Paris Agreement

2018 ◽  
Vol 2018 ◽  
pp. 1-9 ◽  
Author(s):  
Fang Wang ◽  
Katarzyna B. Tokarska ◽  
Jintao Zhang ◽  
Quansheng Ge ◽  
Zhixin Hao ◽  
...  
Keyword(s):  
Climate Warming ◽  
Temperature Increase ◽  
Climate Model ◽  
Ghg Emissions ◽  
Paris Agreement ◽  
The Arctic ◽  
Emission Reductions ◽  
Global Mean Temperature ◽  
Mean Temperature ◽  
Global Mean

To limit global warming to well below 2°C in accord with the Paris Agreement, countries throughout the world have submitted their Intended Nationally Determined Contributions (INDCs) outlining their greenhouse gas (GHG) mitigation actions in the next few decades. However, it remains unclear what the resulting climate change is in response to the proposed INDCs and subsequent emission reductions. In this study, the global and regional warming under the updated INDC scenarios was estimated from a range of comprehensive Earth system models (CMIP5) and a simpler carbon-climate model (MAGICC), based on the relationship of climate response to cumulative emissions. The global GHG emissions under the updated INDC pledges are estimated to reach 14.2∼15.0 GtC/year in 2030, resulting in a global mean temperature increase of 1.29∼1.55°C (median of 1.41°C) above the preindustrial level. By extending the INDC scenarios to 2100, global GHG emissions are estimated to be around 6.4∼9.0 GtC/year in 2100, resulting in a global mean temperature increase by 2.67∼3.74°C (median of 3.17°C). The Arctic warming is projected to be most profound, exceeding the global average by a factor of three by the end of this century. Thus, climate warming under INDC scenarios is projected to greatly exceed the long-term Paris Agreement goal of stabilizing the global mean temperature at to a low level of 1.5‐2.0°C above the pre-industrial. Our study suggests that the INDC emission commitments need to be adjusted and strengthened to bridge this warming gap.

scholarly journals Solar geoengineering to limit the rate of temperature change

2014 ◽  
Vol 372 (2031) ◽  
pp. 20140134 ◽  
Author(s):  
Douglas G. MacMartin ◽  
Ken Caldeira ◽  
David W. Keith
Keyword(s):  
Climate Change ◽  
Climate Model ◽  
Rate Of Change ◽  
Change Analysis ◽  
Rates Of Change ◽  
Global Mean Temperature ◽  
Mean Temperature ◽  
Solar Geoengineering ◽  
Allowable Rate ◽  
Global Mean

Solar geoengineering has been suggested as a tool that might reduce damage from anthropogenic climate change. Analysis often assumes that geoengineering would be used to maintain a constant global mean temperature. Under this scenario, geoengineering would be required either indefinitely (on societal time scales) or until atmospheric CO 2 concentrations were sufficiently reduced. Impacts of climate change, however, are related to the rate of change as well as its magnitude. We thus describe an alternative scenario in which solar geoengineering is used only to constrain the rate of change of global mean temperature; this leads to a finite deployment period for any emissions pathway that stabilizes global mean temperature. The length of deployment and amount of geoengineering required depends on the emissions pathway and allowable rate of change, e.g. in our simulations, reducing the maximum approximately 0.3°C per decade rate of change in an RCP 4.5 pathway to 0.1°C per decade would require geoengineering for 160 years; under RCP 6.0, the required time nearly doubles. We demonstrate that feedback control can limit rates of change in a climate model. Finally, we note that a decision to terminate use of solar geoengineering does not automatically imply rapid temperature increases: feedback could be used to limit rates of change in a gradual phase-out.

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