scholarly journals Estimating radiative forcing with a nonconstant feedback parameter and linear response

2021 ◽  
Author(s):  
Hege‐Beate Fredriksen ◽  
Maria Rugenstein ◽  
Rune Graversen
Keyword(s):  
Linear Response ◽  
Radiative Forcing ◽  
Feedback Parameter

scholarly journals Estimating radiative forcing with a nonconstant feedback parameter and linear response

2020 ◽  
Author(s):  
Hege-Beate Fredriksen ◽  
Maria Rugenstein ◽  
Rune Graversen
Keyword(s):  
Linear Response ◽  
Radiative Forcing ◽  
Feedback Parameter

scholarly journals Estimating radiative forcing with a nonconstant feedback parameter and linear response

2021 ◽  
Author(s):  
Hege-Beate Fredriksen ◽  
Maria Rugenstein ◽  
Rune Graversen
Keyword(s):  
Linear Response ◽  
Radiative Forcing ◽  
Feedback Parameter

scholarly journals The inconstancy of the transient climate response parameter under increasing CO 2

2015 ◽  
Vol 373 (2054) ◽  
pp. 20140417 ◽  
Author(s):  
J. M. Gregory ◽  
T. Andrews ◽  
P. Good
Keyword(s):  
Radiative Forcing ◽  
Coupled Model ◽  
Surface Air Temperature ◽  
Deep Ocean ◽  
Climate Feedback ◽  
Climate Response ◽  
Ocean Heat Uptake ◽  
Transient Climate Response ◽  
Feedback Parameter ◽  
Response Parameter

In the Coupled Model Intercomparison Project Phase 5 (CMIP5), the model-mean increase in global mean surface air temperature T under the 1pctCO2 scenario (atmospheric CO 2 increasing at 1% yr −1 ) during the second doubling of CO 2 is 40% larger than the transient climate response (TCR), i.e. the increase in T during the first doubling. We identify four possible contributory effects. First, the surface climate system loses heat less readily into the ocean beneath as the latter warms. The model spread in the thermal coupling between the upper and deep ocean largely explains the model spread in ocean heat uptake efficiency. Second, CO 2 radiative forcing may rise more rapidly than logarithmically with CO 2 concentration. Third, the climate feedback parameter may decline as the CO 2 concentration rises. With CMIP5 data, we cannot distinguish the second and third possibilities. Fourth, the climate feedback parameter declines as time passes or T rises; in 1pctCO2, this effect is less important than the others. We find that T projected for the end of the twenty-first century correlates more highly with T at the time of quadrupled CO 2 in 1pctCO2 than with the TCR, and we suggest that the TCR may be underestimated from observed climate change.

scholarly journals Explaining the Spread in Global Mean Thermosteric Sea Level Rise in CMIP5 Climate Models*

2015 ◽  
Vol 28 (24) ◽  
pp. 9918-9940 ◽  
Author(s):  
Angélique Melet ◽  
Benoit Meyssignac
Keyword(s):  
Twentieth Century ◽  
Sea Level ◽  
Radiative Forcing ◽  
Climate Models ◽  
First Century ◽  
Model Ensemble ◽  
Ocean Heat Uptake ◽  
Feedback Parameter ◽  
Twenty First Century ◽  
Global Mean

Abstract The ocean stores more than 90% of the energy excess associated with anthropogenic climate change. The resulting ocean warming and thermal expansion are leading contributors to global mean sea level (GMSL) rise. Confidence in projections of GMSL rise therefore depends on the ability of climate models to reproduce global mean thermosteric sea level (GMTSL) rise over the twentieth century. This study first compares the GMTSL of the climate models from phase 5 of the Coupled Model Intercomparison Project (CMIP5) to observations over 1961–2005. Although the model ensemble mean is within the uncertainty of observations, the model ensemble exhibits a large spread. The authors then aim to explain the spread in CMIP5 climate model GMTSL over the twentieth and twenty-first centuries. It is shown that the climate models’ GMTSL rise depends linearly on the time-integrated radiative forcing F (under continuously increasing radiative forcing). The constant of proportionality μ expresses the transient thermosteric sea level response of the climate system, and it depends on the fraction of excess heat stored in the ocean, the expansion efficiency of heat, the climate feedback parameter, and the ocean heat uptake efficiency. The across-model spread in μ explains most (>70%) of the across-model spread in GMTSL rise over the twentieth and twenty-first centuries, while the across-model spread in time-integrated F explains the rest. The time-integrated F explains less variance in the across-model GMTSL rise in twenty-first-century than in twentieth-century simulations, as the spread in F is reduced over the twenty-first century because the anthropogenic aerosol forcing, which is a large source of uncertainty in F, becomes relatively smaller.

scholarly journals The Dependence of Radiative Forcing and Feedback on Evolving Patterns of Surface Temperature Change in Climate Models

2015 ◽  
Vol 28 (4) ◽  
pp. 1630-1648 ◽  
Author(s):  
Timothy Andrews ◽  
Jonathan M. Gregory ◽  
Mark J. Webb
Keyword(s):  
Surface Temperature ◽  
Temperature Change ◽  
Radiative Forcing ◽  
General Circulation ◽  
Climate Feedback ◽  
Climate Feedbacks ◽  
Surface Temperature Change ◽  
Feedback Parameter ◽  
Surface Warming ◽  
Global Mean

Abstract Experiments with CO2 instantaneously quadrupled and then held constant are used to show that the relationship between the global-mean net heat input to the climate system and the global-mean surface air temperature change is nonlinear in phase 5 of the Coupled Model Intercomparison Project (CMIP5) atmosphere–ocean general circulation models (AOGCMs). The nonlinearity is shown to arise from a change in strength of climate feedbacks driven by an evolving pattern of surface warming. In 23 out of the 27 AOGCMs examined, the climate feedback parameter becomes significantly (95% confidence) less negative (i.e., the effective climate sensitivity increases) as time passes. Cloud feedback parameters show the largest changes. In the AOGCM mean, approximately 60% of the change in feedback parameter comes from the tropics (30°N–30°S). An important region involved is the tropical Pacific, where the surface warming intensifies in the east after a few decades. The dependence of climate feedbacks on an evolving pattern of surface warming is confirmed using the HadGEM2 and HadCM3 atmosphere GCMs (AGCMs). With monthly evolving sea surface temperatures and sea ice prescribed from its AOGCM counterpart, each AGCM reproduces the time-varying feedbacks, but when a fixed pattern of warming is prescribed the radiative response is linear with global temperature change or nearly so. It is also demonstrated that the regression and fixed-SST methods for evaluating effective radiative forcing are in principle different, because rapid SST adjustment when CO2 is changed can produce a pattern of surface temperature change with zero global mean but nonzero change in net radiation at the top of the atmosphere (~−0.5 W m−2 in HadCM3).

scholarly journals Estimation of the climate feedback parameter by using radiative fluxes from CERES EBAF

2013 ◽  
Vol 4 (1) ◽  
pp. 25-47
Author(s):  
P. Björnbom
Keyword(s):  
Radiative Forcing ◽  
Phase Plane ◽  
Southern Oscillation ◽  
Radiant Energy ◽  
Radiative Flux ◽  
Climate Feedback ◽  
Time Interval ◽  
Feedback Parameter ◽  
Temperature Anomalies ◽  
Straight Lines

Abstract. Top-of-the-Atmosphere (TOA) net radiative flux anomalies from Clouds and Earth's Radiant Energy Systems (CERES) Energy Balanced and Filled (EBAF) and surface air temperature anomalies from HadCRUT3 were compared for the time interval September 2000–May 2011. In a phase plane plot with the radiative flux anomalies lagging the temperature anomalies with 7 months the phase plane curve approached straight lines during about an eight months long period at the beginning and a five year period at the end of the interval. Both of those periods, but more clearly the latter one, could be connected to the occurrence of distinct El Niño Southern Oscillation (ENSO) episodes. This result is explained by using a hypothesis stating that non-radiative forcing connected to the ENSO is dominating the temperature changes during those two periods and that there is a lag between the temperature change and the radiative flux feedback. According to the hypothesis the slopes of the straight lines equal the value of the climate feedback parameter. By linear regression based on the mentioned five year period the value of the climate feedback parameter was estimated to 5.5 ± 0.6 W m−2 K−1 (± two standard errors).

Tropospheric Adjustment Induces a Cloud Component in CO2 Forcing

2008 ◽  
Vol 21 (1) ◽  
pp. 58-71 ◽  
Author(s):  
Jonathan Gregory ◽  
Mark Webb
Keyword(s):  
Radiative Forcing ◽  
Climate Models ◽  
Surface Air Temperature ◽  
Co2 Concentration ◽  
Climate Feedback ◽  
Climate Projections ◽  
Feedback Parameter ◽  
Tropospheric Adjustment ◽  
Effective Radiative Forcing ◽  
Global Mean

Abstract The radiative forcing of CO2 and the climate feedback parameter are evaluated in several climate models with slab oceans by regressing the annual-mean global-mean top-of-atmosphere radiative flux against the annual-mean global-mean surface air temperature change ΔT following a doubling of atmospheric CO2 concentration. The method indicates that in many models there is a significant rapid tropospheric adjustment to CO2 leading to changes in cloud, and reducing the effective radiative forcing, in a way analogous to the indirect and semidirect effects of aerosol. By contrast, in most models the cloud feedback is small, defined as the part of the change that evolves with ΔT. Comparison with forcing evaluated by fixing sea surface conditions gives qualitatively similar results for the cloud components of forcing, both globally and locally. Tropospheric adjustment to CO2 may be responsible for some of the model spread in equilibrium climate sensitivity and could affect time-dependent climate projections.

Estimating the Contribution of Sea Ice Response to Climate Sensitivity in a Climate Model

2014 ◽  
Vol 27 (22) ◽  
pp. 8597-8607 ◽  
Author(s):  
Ken Caldeira ◽  
Ivana Cvijanovic
Keyword(s):  
Climate Change ◽  
Sea Ice ◽  
Climate Sensitivity ◽  
Radiative Forcing ◽  
Climate Model ◽  
Ocean Model ◽  
Radiative Properties ◽  
Climate Feedback ◽  
Climate Effect ◽  
Feedback Parameter

Abstract The response of sea ice to climate change affects Earth’s radiative properties in ways that contribute to yet more climate change. Here, a configuration of the Community Earth System Model, version 1.0.4 (CESM 1.0.4), with a slab ocean model and a thermodynamic–dynamic sea ice model is used to investigate the overall contribution to climate sensitivity of feedbacks associated with the sea ice loss. In simulations in which sea ice is not present and ocean temperatures are allowed to fall below freezing, the climate feedback parameter averages ~1.31 W m−2 K−1; the value obtained for control simulations with active sea ice is ~1.05 W m−2 K−1, indicating that, in this configuration of CESM1.0.4, sea ice response accounts for ~20% of climate sensitivity to an imposed change in radiative forcing. In this model, the effect of sea ice response on the longwave climate feedback parameter is nearly half as important as its effect on the shortwave climate feedback parameter. Further, it is shown that the strength of the overall sea ice feedback can be related to 1) the sensitivity of sea ice area to changes in temperature and 2) the sensitivity of sea ice radiative forcing to changes in sea ice area. An alternative method of disabling sea ice response leads to similar conclusions. It is estimated that the presence of sea ice in the preindustrial control simulation has a climate effect equivalent to ~3 W m−2 of radiative forcing.

scholarly journals The Climate Sensitivity and Its Components Diagnosed from Earth Radiation Budget Data

2006 ◽  
Vol 19 (1) ◽  
pp. 39-52 ◽  
Author(s):  
Piers Mde F. Forster ◽  
Jonathan M. Gregory
Keyword(s):  
Climate Change ◽  
Time Series ◽  
Surface Temperature ◽  
Climate Sensitivity ◽  
Radiative Forcing ◽  
Radiation Budget ◽  
Climate Feedback ◽  
Feedback Parameter ◽  
Earth Radiation Budget ◽  
Earth Radiation

Abstract One of the major uncertainties in the ability to predict future climate change, and hence its impacts, is the lack of knowledge of the earth’s climate sensitivity. Here, data are combined from the 1985–96 Earth Radiation Budget Experiment (ERBE) with surface temperature change information and estimates of radiative forcing to diagnose the climate sensitivity. Importantly, the estimate is completely independent of climate model results. A climate feedback parameter of 2.3 ± 1.4 W m−2 K−1 is found. This corresponds to a 1.0–4.1-K range for the equilibrium warming due to a doubling of carbon dioxide (assuming Gaussian errors in observable parameters, which is approximately equivalent to a uniform “prior” in feedback parameter). The uncertainty range is due to a combination of the short time period for the analysis as well as uncertainties in the surface temperature time series and radiative forcing time series, mostly the former. Radiative forcings may not all be fully accounted for; however, an argument is presented that the estimate of climate sensitivity is still likely to be representative of longer-term climate change. The methodology can be used to 1) retrieve shortwave and longwave components of climate feedback and 2) suggest clear-sky and cloud feedback terms. There is preliminary evidence of a neutral or even negative longwave feedback in the observations, suggesting that current climate models may not be representing some processes correctly if they give a net positive longwave feedback.

Photographic Equidensitometry of High Voltage Electron Images of Thick Noncrystalline Materials

1972 ◽  
Vol 30 ◽  
pp. 594-595
Author(s):  
Keinosuke Kobayashi
Keyword(s):  
High Voltage ◽  
Linear Response ◽  
Thickness Distribution ◽  
Contour Map ◽  
Mass Thickness ◽  
Voltage Electron ◽  
High Voltage Electron ◽  
Homogeneous Particle ◽  
Photographic Emulsions ◽  
Logarithmic Relation

Equidensitometry as developed by E. Lau and W. Krug has been little used in the analysis of ordinary electron photomicrographs, yet its application to the high voltage electron images proves merits of this procedure. Proper sets (families) of equidensities as shown in the next page are able to reveal the contour map of mass thickness distribution in thick noncrystalline specimens. The change in density of the electron micrograph is directly related to the mass thickness of corresponding area in the specimen, because of the linear response of photographic emulsions to electrons and the logarithmic relation between electron opacity and mass thickness of amorphous object.This linearity is verified by equidensitometry of a spherical solid object as shown in Fig. 1a. The object is a large (1 μ) homogeneous particle of polystyrene. Fig. 1b is a composite print of three equidensities of the 1st order prepared from Fig. 1a.

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