Quantifying Climate Feedbacks Using Radiative Kernels

2008 ◽  
Vol 21 (14) ◽  
pp. 3504-3520 ◽  
Author(s):  
Brian J. Soden ◽  
Isaac M. Held ◽  
Robert Colman ◽  
Karen M. Shell ◽  
Jeffrey T. Kiehl ◽  
...  
Keyword(s):  
Climate Models ◽  
Global Climate ◽  
Temperature Response ◽  
Global Climate Models ◽  
Climate Feedbacks ◽  
Cloud Feedbacks ◽  
Cloud Forcing ◽  
Construct Maps ◽  
The Difference ◽  
Radiative Feedbacks

Abstract The extent to which the climate will change due to an external forcing depends largely on radiative feedbacks, which act to amplify or damp the surface temperature response. There are a variety of issues that complicate the analysis of radiative feedbacks in global climate models, resulting in some confusion regarding their strengths and distributions. In this paper, the authors present a method for quantifying climate feedbacks based on “radiative kernels” that describe the differential response of the top-of-atmosphere radiative fluxes to incremental changes in the feedback variables. The use of radiative kernels enables one to decompose the feedback into one factor that depends on the radiative transfer algorithm and the unperturbed climate state and a second factor that arises from the climate response of the feedback variables. Such decomposition facilitates an understanding of the spatial characteristics of the feedbacks and the causes of intermodel differences. This technique provides a simple and accurate way to compare feedbacks across different models using a consistent methodology. Cloud feedbacks cannot be evaluated directly from a cloud radiative kernel because of strong nonlinearities, but they can be estimated from the change in cloud forcing and the difference between the full-sky and clear-sky kernels. The authors construct maps to illustrate the regional structure of the feedbacks and compare results obtained using three different model kernels to demonstrate the robustness of the methodology. The results confirm that models typically generate globally averaged cloud feedbacks that are substantially positive or near neutral, unlike the change in cloud forcing itself, which is as often negative as positive.

scholarly journals A cloud feedback emulator (CFE, version 1.0) for an intermediate complexity model

2017 ◽  
Vol 10 (2) ◽  
pp. 945-958 ◽  
Author(s):  
David J. Ullman ◽  
Andreas Schmittner
Keyword(s):  
Climate Models ◽  
Climate Model ◽  
Global Climate ◽  
Cloud Feedback ◽  
Global Climate Models ◽  
Cloud Feedbacks ◽  
Intermediate Complexity ◽  
Model Cloud ◽  
Radiative Feedbacks ◽  
The University

Abstract. The dominant source of inter-model differences in comprehensive global climate models (GCMs) are cloud radiative effects on Earth's energy budget. Intermediate complexity models, while able to run more efficiently, often lack cloud feedbacks. Here, we describe and evaluate a method for applying GCM-derived shortwave and longwave cloud feedbacks from 4 × CO2 and Last Glacial Maximum experiments to the University of Victoria Earth System Climate Model. The method generally captures the spread in top-of-the-atmosphere radiative feedbacks between the original GCMs, which impacts the magnitude and spatial distribution of surface temperature changes and climate sensitivity. These results suggest that the method is suitable to incorporate multi-model cloud feedback uncertainties in ensemble simulations with a single intermediate complexity model.

scholarly journals The University of Victoria Cloud Feedback Emulator (UVic-CFE): cloud radiative feedbacks in an intermediate complexity model

2016 ◽  
Author(s):  
David Ullman ◽  
Andreas Schmittner
Keyword(s):  
Climate Models ◽  
Climate Model ◽  
Global Climate ◽  
Cloud Feedback ◽  
Global Climate Models ◽  
Cloud Feedbacks ◽  
Intermediate Complexity ◽  
Model Cloud ◽  
Radiative Feedbacks ◽  
The University

Abstract. The dominant source of inter-model differences in comprehensive global climate models (GCMs) are cloud radiative effects on Earth's energy budget. Intermediate complexity models, while able to run more efficiently, often lack cloud feedbacks. Here, we describe and evaluate a method for applying GCM-derived shortwave and longwave cloud feedbacks from 4xCO2 and Last Glacial Maximum experiments to the University of Victoria Earth System Climate Model. The method generally captures the spread in top-of-the-atmosphere radiative feedbacks between the original GCMs, which impacts the magnitude and spatial distribution of surface temperature changes and climate sensitivity. These results suggest that the method is suitable to incorporate multi-model cloud feedback uncertainties in ensemble simulations with a single intermediate complexity model.

scholarly journals Aerosol absorption in global models from AeroCom Phase III

2021 ◽  
Author(s):  
Maria Sand ◽  
Bjørn H. Samset ◽  
Gunnar Myhre ◽  
Jonas Gliß ◽  
Susanne E. Bauer ◽  
...  
Keyword(s):  
Phase Ii ◽  
Climate Models ◽  
Global Climate ◽  
Global Climate Models ◽  
Phase Iii ◽  
Shortwave Radiation ◽  
Cloud Formation ◽  
Individual Species ◽  
Aerosol Absorption ◽  
The Difference

Abstract. Aerosol induced absorption of shortwave radiation can modify the climate through local atmospheric heating, which affects lapse rates, precipitation, and cloud formation. Presently, the total amount of such absorption is poorly constrained, and the main absorbing aerosol species (black carbon (BC), organic aerosols (OA) and mineral dust are diversely quantified in global climate models. As part of the third phase of the AeroCom model intercomparison initiative (AeroCom Phase III) we here document the distribution and magnitude of aerosol absorption in current global aerosols models and quantify the sources of intermodel spread. 15 models have provided total present-day absorption at 550 nm, and 11 of these models have provided absorption per absorbing species. The multi-model global annual mean total absorption aerosol optical depth (AAOD) is 0.0056 [0.0020 to 0.0097] (550 nm) with range given as the minimum and maximum model values. This is 31 % higher compared to 0.0042 [0.0021 to 0.0076] in AeroCom Phase II, but the difference/increase is within one standard deviation which in this study is 0.0024 (0.0019 in Phase II). The models show considerable diversity in absorption. Of the summed component AAOD, 57 % (range 34–84 %) is estimated to be due to BC, 30 % (12–49 %) is due to dust and 14 % (4–49 %) is due to OA, however the components are not entirely independent. Models with the lowest BC absorption tend to have the highest OA absorption, which illustrates the complexities in separating the species. The geographical distribution of AAOD between the models varies greatly and reflects the spread in global mean AAOD and in the relative contributions from individual species. The optical properties of BC are recognized as a large source of uncertainty. The model mean BC mass absorption coefficient (MACBC) value is 9.8 [3.1 to 16.6] m2 g−1 (550 nm). Observed MAC values from various locations range between 5.7–20.0 m2 g−1 (550 nm). Compared to retrievals of AAOD and absorption Ångstrøm exponent (AAE) from ground-based observations from the Aerosol Robotic Network (AERONET) stations, most models underestimate total AAOD and AAE. The difference in spectral dependency between the models is striking.

scholarly journals Comparison of south Atlantic aerosol direct radiative effect overclouds from SCIAMACHY, POLDER and OMI/MODIS

2019 ◽  
Author(s):  
Martin de Graaf ◽  
Ruben Schulte ◽  
Fanny Peers ◽  
Fabien Waquet ◽  
L. Gijsbert Tilstra ◽  
...  
Keyword(s):  
Biomass Burning ◽  
Climate Models ◽  
Global Climate ◽  
Global Climate Models ◽  
Radiation Budget ◽  
Radiative Effect ◽  
The South ◽  
East Atlantic ◽  
The Difference ◽  
Aerosol Effects

Abstract. The Direct Radiative Effect (DRE) of aerosols above clouds has been found to be significant over the south-east Atlantic Ocean during the African biomass burning season due to elevated smoke layers absorbing radiation above the cloud deck. So far, global climate models have been unsuccessful in reproducing the high DRE values measured by various satellite instruments. Meanwhile, the radiative effects by aerosols have been identified as the largest source of uncertainty in global climate models. In this paper, three independent satellite datasets of DRE during the biomass burning season in 2006 are compared to constrain the south-east Atlantic radiation budget. The DRE of aerosols above clouds is derived from the spectrometer SCIAMACHY, the polarimeter POLDER, and from collocated measurements by the spectrometer OMI and imager MODIS. All three confirm the high DRE values during the biomass season, underlining the relevance of local aerosol effects. Differences between the instruments can be attributed mainly to sampling issues. When these are accounted for, the remaining differences can be completely explained by the higher cloud optical thickness derived from POLDER compared to the other instruments. Additionally, a neglect of AOT at SWIR wavelengths in the method used for SCIAMACHY and OMI/MODIS accounts for 26 % of the difference between POLDER and OMI/MODIS DRE.

Attributing the global increase in permafrost temperatures to human induced climate change

2021 ◽  
Author(s):  
Lukas Gudmundsson ◽  
Josefine Kirchner ◽  
Anne Gädeke ◽  
Eleanor Burke ◽  
Boris K. Biskaborn ◽  
...  
Keyword(s):  
Climate Change ◽  
Large Scale ◽  
Climate Models ◽  
Global Climate ◽  
Volcanic Eruptions ◽  
Global Climate Models ◽  
Anthropogenic Climate Change ◽  
Permafrost Degradation ◽  
Climate Feedbacks ◽  
Permafrost Temperature

<p>Permafrost temperatures are increasing at the global scale, resulting in permafrost degradation. Besides substantial impacts on Arctic and Alpine hydrology and the stability of landscapes and infrastructure, permafrost degradation can trigger a large-scale release of carbon to the atmosphere with possible global climate feedbacks. Although increasing global air temperature is unanimously linked to human emissions into the atmosphere, the attribution of observed permafrost warming to anthropogenic climate change has so far mostly relied on anecdotal evidence. Here we apply a climate change detection and attribution approach to long permafrost temperature records from 15 boreholes located in the northern Hemisphere and simulated soil temperatures obtained from global climate models contributing to the sixth phase of the Coupled Model Intercomparison Project (CMIP6). We show that observed and simulated trends in permafrost temperature are only consistent if the effect of human emissions on the climate system is considered in the simulations. Moreover, the analysis also reveals that neither simulated pre-industrial climate variability nor the effects natural drivers of climate change (e.g. impacts of large volcanic eruptions) suffice to explain the observed trends. While these results are most significant for a global mean assessment, our analysis also reveals that simulated effects of anthropogenic climate change on permafrost temperature are also consistent with the observed record at the station scale. In summary, the quantitative combination of observed and simulated evidence supports the conclusion that anthropogenic climate change is the key driver of increasing permafrost temperatures with implications for carbon cycle-climate feedbacks at the planetary scale.</p>

scholarly journals Insights into low-latitude cloud feedbacks from high-resolution models

2015 ◽  
Vol 373 (2054) ◽  
pp. 20140415 ◽  
Author(s):  
Christopher S. Bretherton
Keyword(s):  
Boundary Layer ◽  
Climate Models ◽  
Global Climate ◽  
Cloud Feedback ◽  
Global Climate Models ◽  
Limited Area ◽  
Slight Reduction ◽  
Low Latitude ◽  
Cloud Feedbacks ◽  
Cloud Regimes

Cloud feedbacks are a leading source of uncertainty in the climate sensitivity simulated by global climate models (GCMs). Low-latitude boundary-layer and cumulus cloud regimes are particularly problematic, because they are sustained by tight interactions between clouds and unresolved turbulent circulations. Turbulence-resolving models better simulate such cloud regimes and support the GCM consensus that they contribute to positive global cloud feedbacks. Large-eddy simulations using sub-100 m grid spacings over small computational domains elucidate marine boundary-layer cloud response to greenhouse warming. Four observationally supported mechanisms contribute: ‘thermodynamic’ cloudiness reduction from warming of the atmosphere–ocean column, ‘radiative’ cloudiness reduction from CO 2 - and H 2 O-induced increase in atmospheric emissivity aloft, ‘stability-induced’ cloud increase from increased lower tropospheric stratification, and ‘dynamical’ cloudiness increase from reduced subsidence. The cloudiness reduction mechanisms typically dominate, giving positive shortwave cloud feedback. Cloud-resolving models with horizontal grid spacings of a few kilometres illuminate how cumulonimbus cloud systems affect climate feedbacks. Limited-area simulations and superparameterized GCMs show upward shift and slight reduction of cloud cover in a warmer climate, implying positive cloud feedbacks. A global cloud-resolving model suggests tropical cirrus increases in a warmer climate, producing positive longwave cloud feedback, but results are sensitive to subgrid turbulence and ice microphysics schemes.

Predicting climate model response to changing emissions

2021 ◽  
Author(s):  
Laura Mansfield ◽  
Peer Nowack ◽  
Apostolos Voulgarakis
Keyword(s):  
High Performance ◽  
Climate Models ◽  
Climate Model ◽  
Global Climate ◽  
Temperature Response ◽  
Global Climate Models ◽  
Training Data ◽  
Model Response ◽  
Complex Models ◽  
High Performance Computers

<p>In order to make predictions on how the climate would respond to changes in global and regional emissions, we typically run simulations on Global Climate Models (GCMs) with perturbed emissions or concentration fields. These simulations are highly expensive and often require the availability of high-performance computers. Machine Learning (ML) can provide an alternative approach to estimating climate response to various emissions quickly and cheaply. </p><p>We will present a Gaussian process emulator capable of predicting the global map of temperature response to different types of emissions (both greenhouse gases and aerosol pollutants), trained on a carefully designed set of simulations from a GCM. This particular work involves making short-term predictions on 5 year timescales but can be linked to an emulator from previous work that predicts on decadal timescales. We can also examine uncertainties associated with predictions to find out where where the method could benefit from increased training data. This is a particularly useful asset when constructing emulators for complex models, such as GCMs, where obtaining training runs is costly. </p>

Long-term variability of shortwave absorption under abrupt-4xCO2 climate forcing and its visible and near-IR contributions

2020 ◽  
Author(s):  
Maria Z. Hakuba ◽  
Alejandro Bodas-Salcedo ◽  
Graeme Stephens
Keyword(s):  
Global Warming ◽  
Near Infrared ◽  
Climate Models ◽  
Global Climate ◽  
Global Climate Models ◽  
Climate Forcing ◽  
Shortwave Radiation ◽  
Hemispheric Differences ◽  
Climate Feedbacks

<p>While ongoing global warming is largely the result of reduced outgoing longwave radiation (OLR), climate feedbacks associated with changes in atmospheric water vapor and surface albedo are expected to enhance the absorption of shortwave radiation (ASR) and to sustain global warming on centennial time scales beyond the OLR modulations. These feedbacks as well as positive cloud feedbacks reduce the reflected shortwave (SW) flux at the top-of-atmosphere (TOA) and are a result of scattering and absorbing processes that differ by their near-infrared (NIR) and visible (VIS) contributions. Since direct measurements of broadband NIR (~0.7-5 mm) and VIS (~0.2-0.7 mm) radiation flux do not exist, we utilize UKESM1 simulations to study SW, NIR, and VIS climate feedbacks under preindustrial and abrupt-4xCO<sub>2</sub> climate forcing.</p><p>Besides its global long-term behavior, the spatial variability and key physical controls of ASR are not well characterized either. A prominent example is the unexplained hemispheric symmetry in planetary albedo that is consistently missed by current global climate models yielding unrealistic precipitation and circulation patterns. Although energetically equivalent, the observed hemispheric albedos differ spectrally, reflecting the uneven distribution of clouds and land masses. We use the same UKESM1 simulations to contrast inter-hemispheric differences in SW, NIR and VIS, and their relation to changes in clouds, the gaseous atmosphere and surface properties to shed light on processes relevant to the present-day symmetry, model biases, and potential future changes.</p>

On the magnitude of the stratospheric radiative feedback in global warming

2020 ◽  
Author(s):  
Yi Huang ◽  
Yuwei Wang
Keyword(s):  
Global Warming ◽  
Climate Models ◽  
Global Climate ◽  
Global Climate Models ◽  
Radiation Budget ◽  
Stratospheric Water Vapor ◽  
Stratospheric Temperature ◽  
Radiative Feedbacks ◽  
Stratospheric Cooling ◽  
The Impact

<p>Global warming is amplified by radiative feedbacks. Compared to the feedback in the troposphere, the feedback in the stratosphere is less understood. The stratospheric water vapor (SWV), one of the primary feedbacks in the stratosphere, is argued to be an important contributor to global warming. This, however, is at odds with the finding that the overall stratospheric feedback does not amount to a significant value in global climate models (GCMs). The key to reconciling these seemingly contradictory arguments is to understand the stratospheric temperature (ST) change since the impact of SWV on the top-of-atmosphere (TOA) radiation budget results more from its cooling of the stratosphere than its direct radiative impact on the TOA radiation. Here, we develop a method to decompose the ST change and to quantify the effects of different climate responses associated with SWV on the TOA radiation budget. We find that although the SWV feedback by itself would lead to strong stratospheric cooling, this cooling is strongly offset by the radiative coupling between the stratosphere and troposphere. Such compensation results in an insignificant overall stratospheric feedback. SWV-locking experiments verify that the SWV feedback does not significantly modify the overall climate sensitivity in the GCM global warming simulations.</p>

scholarly journals Azimuthally Averaged Wind and Thermodynamic Structures of Tropical Cyclones in Global Climate Models and Their Sensitivity to Horizontal Resolution

2020 ◽  
Vol 33 (4) ◽  
pp. 1575-1595 ◽  
Author(s):  
Yumin Moon ◽  
Daehyun Kim ◽  
Suzana J. Camargo ◽  
Allison A. Wing ◽  
Adam H. Sobel ◽  
...  
Keyword(s):  
Tropical Cyclones ◽  
Climate Models ◽  
Inner Core ◽  
Global Climate ◽  
Horizontal Resolution ◽  
Heat Fluxes ◽  
Global Climate Models ◽  
Turbulent Heat ◽  
Turbulent Heat Fluxes ◽  
Radiative Feedbacks

AbstractCharacteristics of tropical cyclones (TCs) in global climate models (GCMs) are known to be influenced by details of the model configurations, including horizontal resolution and parameterization schemes. Understanding model-to-model differences in TC characteristics is a prerequisite for reducing uncertainty in future TC activity projections by GCMs. This study performs a process-level examination of TC structures in eight GCM simulations that span a range of horizontal resolutions from 1° to 0.25°. A recently developed set of process-oriented diagnostics is used to examine the azimuthally averaged wind and thermodynamic structures of the GCM-simulated TCs. Results indicate that the inner-core wind structures of simulated TCs are more strongly constrained by the horizontal resolutions of the models than are the thermodynamic structures of those TCs. As expected, the structures of TC circulations become more realistic with smaller horizontal grid spacing, such that the radii of maximum wind (RMW) become smaller, and the maximum vertical velocities occur off the center. However, the RMWs are still too large, especially at higher intensities, and there are rising motions occurring at the storm centers, inconsistently with observations. The distributions of precipitation, moisture, and radiative and surface turbulent heat fluxes around TCs are diverse, even across models with similar horizontal resolutions. At the same horizontal resolution, models that produce greater rainfall in the inner-core regions tend to simulate stronger TCs. When TCs are weak, the radial gradient of net column radiative flux convergence is comparable to that of surface turbulent heat fluxes, emphasizing the importance of cloud–radiative feedbacks during the early developmental phases of TCs.

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