The role of surface albedo feedback in climate

By A. Hall. 2004

550 citations recorded by the source corpus.

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Citations in the corpus

The Polar Amplification Model Intercomparison Project (PAMIP) contribution to CMIP6: investigating the causes and consequences of polar amplification (2018, unknown): “The most well established of these is the surface albedo feedback at high latitudes (Manabe and Stouffer 1994; Hall 2004) in which melting of highly reflective sea ice and snow regions results in increased absorption of solar radiation which amplifies the warming.”
Convection‐permitting modeling with regional climate models: Latest developments and next steps (2021, background): “This especially relates to the snow-albedo feedback (SAF) mechanism (Fletcher et al., 2015; Hall, 2004; Thackeray et al., 2019) and the influence of snow cover on the energy flux partitioning at the ground surface (Cohen & Rind, 1991).”
Arctic winter warming amplified by the thermal inversion and consequent low infrared cooling to space (2011, unknown): “and snow, and the associated surface-albedo feedbac”
Climate–vegetation control on the diurnal and seasonal variations of surface urban heat islands in China (2016, background): “The background climate can also indirectly affect SUHIIs through regulating other variables associated with surface energy balance, such as evapotranspiration (Wang and Dickinson 2012), surface albedo (Hall 2004), and anthropogenic heat emissions (Santamouris et al 2001).”
Polar Amplification in CCSM4: Contributions from the Lapse Rate and Surface Albedo Feedbacks (2014, methodology): “The online method wherein feedbacks are suppressed in climate models has been applied earlier in order to study the surface albedo feedback (Hall 2004; Graversen and Wang 2009; Mauritsen et al. 2013), the water vapor feedback (Schneider et al.”
Climate change projections using the IPSL-CM5 Earth System Model: from CMIP3 to CMIP5 (2013, background): “Austral amplification mostly takes place over sea ice and decreases poleward (Hall 2004).”
Influence of grain shape on light penetration in snow (2013, unknown): “Snow is involved in strong feedback loops in the climate system (Cess et al., 1991; Hall, 2004) because its optical properties depend on some snow physical characteristics (grain size, density, impurities) that themselves evolve with atmospheric conditions (Colbeck, 1982; Picard et al.”
Coupling between Arctic feedbacks and changes in poleward energy transport (2011, background): “[3] Surface albedo feedback was the first proposed mechanism for polar amplification [Sellers, 1969; Manabe and Stouffer, 1980; Hall, 2004].”
Polar amplification of surface warming on an aquaplanet in “ghost forcing” experiments without sea ice feedbacks (2005, background): “Hartmann (1994) has demonstrated that the non-linearity of the Clausius–Clapeyron relationship renders the latent cooling more sensitive to perturbations in the warm tropics, and this difference in sensitivities further contributes to forming the polar amplification pattern (a topic that has been fu”
Polar amplification in a coupled climate model with locked albedo (2009, methodology): “Hence, these experiments, which are performed using a state-of-the-art coupled model, confirm what has previously been found from experiments with models of less complexity: a polar amplification of the SAT field cannot be explained by the SAF alone (Hall 2004; Alexeev et al. 2005; Langen and Alexee”
Land–Ocean Warming Contrast over a Wide Range of Climates: Convective Quasi-Equilibrium Theory and Idealized Simulations (2013, unknown): “A number of processes contribute to polar amplification, including ice–albedo feedback, changes in ocean circulation, polar cloud cover, and atmospheric heat transport (Holland and Bitz 2003; Hall 2004; Bony et al. 2006).”
Atmospheric and Surface Contributions to Planetary Albedo (2011, background): “All models show a decrease in planetary albedo due to the lowered surface albedo associated with a contraction of the cryosphere in a warmer world, but this effect is small compared to the spread in planetary albedo due to model differences in the change in clouds.”
How Well Do We Understand and Evaluate Climate Change Feedback Processes (2006, background): “However, it has the advantage of permitting an evaluation of the impact of feedbacks on variability over a broad range of time scales, in addition to climate change (Hall and Manabe 1999; Hall 2004), which permits direct comparison with observations (e.”