| 1. |
- Tilmes, Simone, et al.
(författare)
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The hydrological impact of geoengineering in the Geoengineering Model Intercomparison Project (GeoMIP)
- 2013
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Ingår i: Journal of Geophysical Research. - : American Geophysical Union (AGU). - 0148-0227 .- 2156-2202 .- 2169-897X. ; 118:19, s. 11036-11058
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Tidskriftsartikel (refereegranskat)abstract
- The hydrological impact of enhancing Earth's albedo by solar radiation management is investigated using simulations from 12 Earth System models contributing to the Geoengineering Model Intercomparison Project (GeoMIP). We contrast an idealized experiment, G1, where the global mean radiative forcing is kept at preindustrial conditions by reducing insolation while the CO2 concentration is quadrupled to a 4×CO2 experiment. The reduction of evapotranspiration over land with instantaneously increasing CO2 concentrations in both experiments largely contributes to an initial reduction in evaporation. A warming surface associated with the transient adjustment in 4×CO2 generates an increase of global precipitation by around 6.9% with large zonal and regional changes in both directions, including a precipitation increase of 10% over Asia and a reduction of 7% for the North American summer monsoon. Reduced global evaporation persists in G1 with temperatures close to preindustrial conditions. Global precipitation is reduced by around 4.5%, and significant reductions occur over monsoonal land regions: East Asia (6%), South Africa (5%), North America (7%), and South America (6%). The general precipitation performance in models is discussed in comparison to observations. In contrast to the 4×CO2 experiment, where the frequency of months with heavy precipitation intensity is increased by over 50% in comparison to the control, a reduction of up to 20% is simulated in G1. These changes in precipitation in both total amount and frequency of extremes point to a considerable weakening of the hydrological cycle in a geoengineered world.
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| 2. |
- Shrivastava, Manish, et al.
(författare)
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Recent advances in understanding secondary organic aerosol : Implications for global climate forcing
- 2017
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Ingår i: Reviews of Geophysics. - 8755-1209. ; 55:2, s. 509-559
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Tidskriftsartikel (refereegranskat)abstract
- Anthropogenic emissions and land use changes have modified atmospheric aerosol concentrations and size distributions over time. Understanding preindustrial conditions and changes in organic aerosol due to anthropogenic activities is important because these features (1) influence estimates of aerosol radiative forcing and (2) can confound estimates of the historical response of climate to increases in greenhouse gases. Secondary organic aerosol (SOA), formed in the atmosphere by oxidation of organic gases, represents a major fraction of global submicron-sized atmospheric organic aerosol. Over the past decade, significant advances in understanding SOA properties and formation mechanisms have occurred through measurements, yet current climate models typically do not comprehensively include all important processes. This review summarizes some of the important developments during the past decade in understanding SOA formation. We highlight the importance of some processes that influence the growth of SOA particles to sizes relevant for clouds and radiative forcing, including formation of extremely low volatility organics in the gas phase, acid-catalyzed multiphase chemistry of isoprene epoxydiols, particle-phase oligomerization, and physical properties such as volatility and viscosity. Several SOA processes highlighted in this review are complex and interdependent and have nonlinear effects on the properties, formation, and evolution of SOA. Current global models neglect this complexity and nonlinearity and thus are less likely to accurately predict the climate forcing of SOA and project future climate sensitivity to greenhouse gases. Efforts are also needed to rank the most influential processes and nonlinear process-related interactions, so that these processes can be accurately represented in atmospheric chemistry-climate models.
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