Atmospheric circulation and hydroclimate impacts of alternative warming scenarios for the Eocene

• Main Authors: H. Carlson, R. Caballero
• Format: Article
• Language: English
• Published: Copernicus Publications 2017-08-01
• Series: Climate of the Past
• Online Access: https://www.clim-past.net/13/1037/2017/cp-13-1037-2017.pdf
• ISSN: 1814-9324; 1814-9332

Recent work in modelling the warm climates of the early Eocene shows that it is possible to obtain a reasonable global match between model surface temperature and proxy reconstructions, but only by using extremely high atmospheric CO₂ concentrations or more modest CO₂ levels complemented by a reduction in global cloud albedo. Understanding the mix of radiative forcing that gave rise to Eocene warmth has important implications for constraining Earth's climate sensitivity, but progress in this direction is hampered by the lack of direct proxy constraints on cloud properties. Here, we explore the potential for distinguishing among different radiative forcing scenarios via their impact on regional climate changes. We do this by comparing climate model simulations of two end-member scenarios: one in which the climate is warmed entirely by CO₂ (which we refer to as the greenhouse gas (GHG) scenario) and another in which it is warmed entirely by reduced cloud albedo (which we refer to as the <q>low CO₂–thin clouds</q> or LCTC scenario) . The two simulations have an almost identical global-mean surface temperature and equator-to-pole temperature difference, but the LCTC scenario has  ∼  11 % greater global-mean precipitation than the GHG scenario. The LCTC scenario also has cooler midlatitude continents and warmer oceans than the GHG scenario and a tropical climate which is significantly more El Niño-like. Extremely high warm-season temperatures in the subtropics are mitigated in the LCTC scenario, while cool-season temperatures are lower at all latitudes. These changes appear large enough to motivate further, more detailed study using other climate models and a more realistic set of modelling assumptions.