Geoengineering as an optimization problem

By George Ban-Weiss, K. Caldeira. 2010

119 citations recorded by the source corpus.

There is increasing evidence that Earth’s climate is currently warming, primarily due to emissions of greenhouse gases from human activities, and Earth has been projected to continue warming throughout this century. Scientists have begun to investigate the potential for geoengineering options for reducing surface temperatures and whether such options could possibly contribute to environmental risk reduction. One proposed method involves deliberately increasing aerosol loading in the stratosphere to scatter additional sunlight to space. Previous modeling studies have attempted to predict the climate consequences of hypothetical aerosol additions to the stratosphere. These studies have shown that this method could potentially reduce surface temperatures, but could not recreate a low-CO2 climate in a high-CO2 world. In this study, we attempt to determine the latitudinal distribution of stratospheric aerosols that would most closely achieve a low-CO2 climate despite high CO2 levels. Using the NCAR CAM3.1 general circulation model, we find that having a stratospheric aerosol loading in polar regions higher than that in tropical regions leads to a temperature distribution that is more similar to the low-CO2 climate than that yielded by a globally uniform loading. However, such polar weighting of stratospheric sulfate tends to degrade the degree to which the hydrological cycle is restored, and thus does not markedly contribute to improved recovery of a low-CO2 climate. In the model, the optimal latitudinally varying aerosol distributions diminished the rms zonal mean land temperature change from a doubling of CO2 by 94% and the rms zonal mean land precipitation minus evaporation change by 74%. It is important to note that this idealized study represents a first attempt at optimizing the engineering of climate using a general circulation model; uncertainties are high and not all processes that are important in reality are modeled.

Subfields: Astronomy and Astrophysics, Atmospheric Science, Global and Planetary Change

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Citations in the corpus

Stratospheric Aerosol Injection as a Deep Reinforcement Learning Problem (2019, background): “Investigation of optimal SAI control within the climate community is currently constrained to low-dimensional injection pattern parametrisations (Ban-Weiss & Caldeira, 2010) or manual grid search over edge cases of interest (Jackson, 2015).”
The impact of abrupt suspension of solar radiation management (termination effect) in experiment G2 of the Geoengineering Model Intercomparison Project (GeoMIP) (2013, background): “…precipitation is roughly constant during the geoengineering period (BNUESM) is the one which shows the greatest degree of warming during this period, a demonstration of how global SRM cannot maintain both global-mean temperature and precipitation simultaneously [e.g., Ban-Weiss and Caldeira, 2010].”
The Climate Response to Stratospheric Aerosol Geoengineering Can Be Tailored Using Multiple Injection Locations (2017, methodology): “The ability to optimize climate response has previously been explored only with idealized latitude-dependent solar reductions (Ban-Weiss & Caldeira, 2010; Kravitz et al., 2016; MacMartin et al., 2013).”
Geoengineering: The world's largest control problem (2014, unknown): “(7)) is a good approximation [33,34].”
Impacts, effectiveness and regional inequalities of the GeoMIP G1 to G4 solar radiation management scenarios (2015, background): “Although the climate system is a nonlinear system, and many climate responses are nonlinear, several studies (Ban-Weiss and Caldeira, 2010; Moreno-Cruz et al., 2012; MacMartin et al., 2013) have shown thatmodeled temperature and precipitation responses over the radiative forcing ranges of their…”
An overview of the Earth system science of solar geoengineering (2016, background): “For example, starting from a scenario of elevated CO2 concentrations, it is not possible to simultaneously restore both global mean precipitation and temperature to the values of a lower CO2 scenario using any pattern of solar forcing alone (see Section Climate Response to Sunshade Geoengineering).(”
A multi-model assessment of regional climate disparities caused by solar geoengineering (2014, background): “Some examples of non-uniform solar geoengineering include non-uniform distributions of solar reductions (Ban-Weiss and Caldeira 2010, MacMartin et al 2013) or marine cloud brightening techniques (Jones et al 2011, Latham 2012, Rasch et al 2009).”