CO<sub>2</sub>-equivalence metrics for surface albedo change based on the radiative forcing concept: a critical review

Abstract

Abstract. Management of Earth's surface albedo is increasingly viewed as an important climate change mitigation strategy both on (Seneviratne et al., 2018) and off (Field et al., 2018; Kravitz et al., 2018) the land. Assessing the impact of a surface albedo change involves employing a measure like radiative forcing (RF) which can be challenging to digest for decision-makers who deal in the currency of CO2-equivalent emissions. As a result, many researchers express albedo change (Δα) RFs in terms of their CO2-equivalent effects, despite the lack of a standard method for doing so, such as there is for emissions of well-mixed greenhouse gases (WMGHGs; e.g., IPCC AR5, Myhre et al., 2013). A major challenge for converting Δα RFs into their CO2-equivalent effects in a manner consistent with current IPCC emission metric approaches stems from the lack of a universal time dependency following the perturbation (perturbation “lifetime”). Here, we review existing methodologies based on the RF concept with the goal of highlighting the context(s) in which the resulting CO2-equivalent metrics may or may not have merit. To our knowledge this is the first review dedicated entirely to the topic since the first CO2-eq. metric for Δα surfaced 20 years ago. We find that, although there are some methods that sufficiently address the time-dependency issue, none address or sufficiently account for the spatial disparity between the climate response to CO2 emissions and Δα – a major critique of Δα metrics based on the RF concept (Jones et al., 2013). We conclude that considerable research efforts are needed to build consensus surrounding the RF “efficacy” of various surface forcing types associated with Δα (e.g., crop change, forest harvest), and the degree to which these are sensitive to the spatial pattern, extent, and magnitude of the underlying surface forcings.

The Importance of Hyperspectral Soil Albedo Information for Improving Earth System Model Projections

“…In this study, the shortwave radiative forcing is interpreted as a disturbance of the reflected radiances caused by variations in soil and surface albedos. Therefore, the soil albedo-induced radiative forcing as presented here should not be interpreted as estimates of radiative forcing from different climate forcing agents (Bright & Lund, 2021), but rather as a proxy of the surface shortwave energy imbalance caused by assuming a broadband background soil albedo representation versus a hyperspectral one. The albedo-induced radiative forcing ( 𝐴𝐴 RF𝛼𝛼 𝑠𝑠 ) is given by…”

“…In this study, the shortwave radiative forcing is interpreted as a disturbance of the reflected radiances caused by variations in soil and surface albedos. Therefore, the soil albedo‐induced radiative forcing as presented here should not be interpreted as estimates of radiative forcing from different climate forcing agents (Bright & Lund, 2021), but rather as a proxy of the surface shortwave energy imbalance caused by assuming a broadband background soil albedo representation versus a hyperspectral one. The albedo‐induced radiative forcing ($${\mathrm{R}\mathrm{F}}_{{\alpha }_{s}}$$) is given by $$${\mathrm{RF}}_{{\alpha }_{s}}=-{R}_{\mathrm{TOA}}^{{\downarrow}}{{\Gamma }}_{\alpha }^{{\updownarrow}}{\Delta }{\alpha }_{s}=\int \nolimits_{400\mathrm{nm}}^{2500\mathrm{nm}}-{R}_{\mathrm{TOA}}^{{\downarrow}}(\lambda ){{\Gamma }}_{a}^{{\updownarrow}}(\lambda ){\Delta }{\alpha }_{s}(\lambda )d\lambda $$$ where $${\mathrm{R}}_{\mathrm{T}\mathrm{O}\mathrm{A}}^{{\downarrow}}$$ ( λ ) (mW m −2 nm −1 ) is the TOA spectral incoming solar radiation flux following Kurucz (Kurucz, 1992) (Figure S2 in Supporting Information ), $${{\Gamma }}_{\mathrm{a}}^{{\updownarrow}}$$( λ ) is the two‐way spectral atmospheric transmissivity that is given as the product of the downward and upward spectral atmospheric transmissivities, assumed to be equal to one another, and ∆ α s ( λ ) is the difference in spectral soil albedo between the hyperspectral and the broadband cases.…”

Albedo‐Induced Global Warming Potential Following Disturbances in Global Temperate and Boreal Forests

“…where T a is the all-sky monthly mean clearness index and SW ↓ is the incoming shortwave radiation where the subscript m shows the data in month m. A negative RF Δα indicates a cooling effect due to elevated albedo of the forest after a disturbance. T a is a crucial parameter that indicated the atmospheric transmittance of downward shortwave radiation (Chen, 2021), and the square root of Ta is an empirical estimation of transmittance of upward radiative transfer (Bright & Lund, 2021). In this study, T a was calculated as:…”

“…Another metric, known as time dependent emissions equivalence (TDEE), is more sensitive to changes in the time horizon, and the cumulative value (Σ[TDEE]) can be interpreted as the accumulated CO 2 equivalent within the TH (Bright & Lund, 2021). In this regard, we modeled the potential radiation forcing scenario by using the fit of nonlinear function based on all data points (Section 2.4) to calculate TDEE following Bright and Lund (2021):…”

Albedo-Induced Global Warming Impact at Multiple Temporal Scales within an Upper Midwest USA Watershed

“…The present scientific understanding of the forcing effects of albedo due to LULCC is ranked as medium-low relative to the rich scientific evidence of the forcing effects of GHGs [1]. To cross-examine effects with the climate impact of other GHGs (i.e., biogeochemical GWI), albedo-induced warming or cooling can be converted into equivalents of carbon-dioxide (CO 2eq ) and/or carbon (C eq ) atmospheric radiative forcing via the concept of albedo-induced global warming potential (GWP ∆α , kg CO 2eq m −2 yr −1 ; [9,10]) metric-hereinafter referred to as global warming impact (GWI ∆α ), to be in line with our previous study [11]. For example, Houspanossian et al [12] found that conversion from forests to croplands, from forests to pastures, and from pastures to croplands in dry subtropical forests of South America offset 12-27 Mg C eq ha −1 during a 12-year period, or from 15% to 55% of the total C emissions due to deforestation.…”