Accounting for radiative forcing from albedo change in future global land-use scenarios

Abstract

We demonstrate the effectiveness of a new method for quantifying radiative forcing from land use and land cover change (LULCC) within an integrated assessment model, the Global Change Assessment Model (GCAM). The method relies on geographically differentiated estimates of radiative forcing from albedo change associated with major land cover transitions derived from the Community Earth System Model. We find that conversion of 1 km 2 of woody vegetation (forest and shrublands) to non-woody vegetation (crops and grassland) yields between 0 and −0.71 nW/m 2 of globally averaged radiative forcing determined by the vegetation characteristics, snow dynamics, and atmospheric radiation environment characteristic within each of 151 regions we consider globally. Across a set of scenarios designed to span a range of potential future LULCC, we find LULCC forcing ranging from −0.06 to −0.29 W/m 2 by 2070 depending on assumptions regarding future crop yield growth and whether climate policy favors afforestation or bioenergy crops. Inclusion of this previously uncounted forcing in the policy targets driving future climate mitigation efforts leads to changes in fossil fuel emissions on the order of 1.5 PgC/yr by 2070 for a climate forcing limit of 4.5 Wm −2 , corresponding to a 12-67 % change in fossil fuel emissions depending on the scenario. Scenarios with significant afforestation must compensate for albedo-induced warming through additional emissions reductions, and scenarios with significant deforestation need not mitigate as aggressively due to albedo-induced cooling. In all scenarios considered, inclusion of albedo forcing in policy targets increases forest and shrub cover globally.Climatic Change

FAIR v1.3: a simple emissions-based impulse response and carbon cycle model

“…Land use forcing is a result of surface albedo change (Andrews et al, 2017) and changes in evapotranspiration patterns (Jones et al, 2015), which is often due to deforestation for agriculture (Myhre and Myhre, 2003). Cropland has a higher albedo than the forest that it replaces, reflecting more incident solar radiation and therefore resulting in a negative ERF; additionally, deforestation in boreal regions may unmask snow-covered ground, again increasing albedo.…”

“…As a zero-dimensional model, FAIR does not include geographical dependence of individual forcing effects, which may differ significantly between forcing pathways (for example the scenarios typically used to drive integrated assessment models). Inclusion of evapotranspiration effects, which again differ between tropical and boreal regions (Jones et al, 2015), is challenging as they do not directly relate to an emitted species or a change in radiative forcing (Pielke et al, 2002). Nevertheless, we conclude that this simple treatment is acceptable, firstly as the range of land use forcing uncertainty is relatively large (so much that the sign of the forcing is not known with confidence; Myhre et al, 2013b), secondly because at least in the best estimate the forcing is a small fraction of the present-day total, and thirdly because the future trajectory of the land use forcing in the RCP datasets is very similar to that predicted by FAIR, suggesting that a dependence on cumulative land use CO 2 emissions is an important component of the land use forcing in MAGICC.…”

“…If gridded land use data are available, the transitions to and from forested land each year can be convoluted with the marginal contribution to land use forcing per square kilometre deforestation (e.g. from Jones et al, 2015).…”

Emission pathways to achieve 2.0°C and 1.5°C climate targets

“…Thus, the individual costs of the different anthropogenic emissions are not reflected in this assessment. Third, uncertainties existing in the socioeconomic development, future emission mitigation technologies, and climate change impacts, especially those from aerosols, the cloud albedo and the land-use albedo [Boucher et al, 2013;Ciais et al, 2013b;Hartmann et al, 2013;Myhre et al, 2013;Jones et al, 2015], cannot be reflected in this study because only the best-guess levels representing the socioeconomic development and GMT change are used. For example, a relatively large uncertainty range of [−0.85 to +0.15] W m −2 was identified for the radiation forcing of the aerosol-radiation interaction in AR5 [Myhre et al, 2013].…”

Integrated human-earth system modeling—state of the science and future directions

“…This is in contrast to other earth systemonly feedbacks that have been explored and quantified in ESMs for decades. Early work, for example, looked at cloud (Cess et al 1989) and boreal fire (Randerson et al 2006, Stocks et al 1998 feedback effects, while more recent studies have explored permafrost (Koven et al 2015) and ocean (Randerson et al 2015) climatecarbon feedbacks, as well as albedo changes from snow Qu and Hall (2014) and land-use change (Jones et al 2015). Understanding such feedbacks yields insight into the coupled carbon-climate system and its likely future evolution (Arora et al 2013).…”