Developing a monthly radiative kernel for surface albedo change from satellite climatologies of Earth's shortwave radiation budget: CACK v1.0

Bright, Ryan M.; O’Halloran, T. L.

doi:10.5194/gmd-12-3975-2019

Cited by 26 publications

(37 citation statements)

References 55 publications

(93 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In our case, this perturbation is a modification of albedo arising from land-cover changes, in particular deforestation or re/afforestation, which affects the amount of reflected shortwave radiation leaving the Earth system at the top of the atmosphere. By how much this amount changes depends on a so-called radiative kernel (Soden et al, 2008), defined in this case as the differential response in outgoing shortwave radiation at the top of the atmosphere to an incremental change in surface albedo ' (Bright and O'halloran, 2019):…”

Section: Computation Of the Radiative Forcing Of Historical Conversions Between Trees And Crops/grassesmentioning

confidence: 99%

Biases in the albedo sensitivity to deforestation in CMIP5 models and their impacts on the associated historical Radiative Forcing

Lejeune¹,

Davin²,

Duveiller³

et al. 2020

Preprint

View full text Add to dashboard Cite

Abstract. Climate model biases in the representation of albedo variations between land cover types contribute to uncertainties on the climate impact of land cover changes since pre-industrial times, and especially on the associated Radiative Forcing. The recent publications of new observation-based datasets offer opportunities to investigate these biases and their impact on historical albedo changes in simulations from the fifth phase of the Coupled Model Intercomparison Project (CMIP5). Conducting such an assessment is however complicated by the non-availability of albedo values for specific land cover types, as well as the limited number of simulations isolating the land use forcing in CMIP. In this study, we demonstrate the suitability of a new methodology to extract the albedo of trees and crops/grasses in standard climate model simulations. We then apply it to historical runs from 13 CMIP5 models and compare the obtained results to satellite-derived reference data. This allows us to identify substantial biases in the representation of the albedo of trees, crops/grasses, and the albedo change due to the transition between these two land cover types in the analysed models. Additionally, we reconstruct the local albedo changes induced by historical conversions between trees and crops/grasses for 15 CMIP5 models. This allows us to derive estimates of the Radiative Forcing from land cover changes since pre-industrial times ranging between 0 and −0.22 W/m2, with a mean value of −0.07 W/m2. Constraining the albedo response to transitions between trees and crops/grasses from the models with satellite-derived data leads to an increase in this range, however after excluding two models with unrealistic conversion rates from trees to crops/grasses we obtain a revised model mean estimate of −0.11 W/m2 (with individual model results between −0.04 and −0.16 W/m2). These numbers are at the lower end of the range provided by the IPCC AR5 (−0.15 ± 0.10 W/m2). The approach described in this study can be applied on other model simulations, such as those from CMIP6, especially as a diagnostic enabling the reproduction of the model evaluation part has been included in the ESMValTool v2.0.

show abstract

Section: Computation Of the Radiative Forcing Of Historical Conversions Between Trees And Crops/grassesmentioning

confidence: 99%

Biases in the albedo sensitivity to deforestation in CMIP5 models and their impacts on the associated historical Radiative Forcing

Lejeune¹,

Davin²,

Duveiller³

et al. 2020

Preprint

View full text Add to dashboard Cite

show abstract

“…However, the spread of the four sets of kernels considered was larger than the difference between the lowest kernels and our values. The kernels are associated with other uncertainties, for example, the atmospheric state climatology of a climate model might not be representative of current conditions (Bright & O'Halloran, 2019) or interactions between albedo and clouds on submonthly timescales may be omitted (Soden et al, 2008).…”

Section: Discussionmentioning

confidence: 99%

“…The denominator represents an infinite number of reflections between the surface with albedo α and the atmosphere with reflectivity r . RF from albedo change (RF α , W/m 2 ) can then be expressed using the partial derivative of Equation (4) in relation to α (Equation 5; Bright & O'Halloran, 2019). The effect of multiple reflection, which increases solar irradiance at surfaces with higher albedo and reinforces RF α , is thereby included:

{RF}_{α} = - \frac{\partial R_{TOA ↑}}{\partial α} Δ α = - R_{TOA ↓} \frac{τ_{false↓} τ_{false↑}}{{false(1 - α r_{↑} false)}^{2}} Δ α .

…”

Section: Methodsmentioning

confidence: 99%

Including albedo in time‐dependent LCA of bioenergy

et al. 2020

View full text Add to dashboard Cite

Albedo change during feedstock production can substantially alter the life cycle climate impact of bioenergy. Life cycle assessment (LCA) studies have compared the effects of albedo and greenhouse gases (GHGs) based on global warming potential (GWP). However, using GWP leads to unequal weighting of climate forcers that act on different timescales. In this study, albedo was included in the time-dependent LCA, which accounts for the timing of emissions and their impacts. We employed field-measured albedo and life cycle emissions data along with time-dependent models of radiative transfer, biogenic carbon fluxes and nitrous oxide emissions from soil. Climate impacts were expressed as global mean surface temperature change over time (∆T) and as GWP. The bioenergy system analysed was heat and power production from short-rotation willow grown on former fallow land in Sweden. We found a net cooling effect in terms of ∆T per hectare (−3.8 × 10 -11 K in year 100) and GWP 100 per MJ fuel (−12.2 g CO 2 e), as a result of soil carbon sequestration via high inputs of carbon from willow roots and litter. Albedo was higher under willow than fallow, contributing to the cooling effect and accounting for 34% of GWP 100 , 36% of ∆T in year 50 and 6% of ∆T in year 100. Albedo dominated the short-term temperature response (10-20 years) but became, in relative terms, less important over time, owing to accumulation of soil carbon under sustained production and the longer perturbation lifetime of GHGs. The timing of impacts was explicit with ∆T, which improves the relevance of LCA results to climate targets. Our method can be used to quantify the first-order radiative effect of albedo change on the global climate and relate it to the climate impact of GHG emissions in LCA of bioenergy, alternative energy sources or land uses. K E Y W O R D Salbedo, bioenergy, climate impact, greenhouse gases, land use change, LCA, life cycle assessment, willow

show abstract

“…Estimates of the local annual mean instantaneous shortwave RF (in W/m 2 ) at the top‐of‐the‐atmosphere following a surface albedo change (or difference) are based on a simple radiative transfer parameterization described in Bright and O'Halloran (2019):