The idea behind the marine cloud-brightening (MCB) geoengineering technique is that seeding marine stratocumulus clouds with copious quantities of roughly monodisperse sub-micrometre sea water particles might significantly enhance the cloud droplet number concentration, and thereby the cloud albedo and possibly longevity. This would produce a cooling, which general circulation model (GCM) computations suggest could—subject to satisfactory resolution of technical and scientific problems identified herein—have the capacity to balance global warming up to the carbon dioxide-doubling point. We describe herein an account of our recent research on a number of critical issues associated with MCB. This involves (i) GCM studies, which are our primary tools for evaluating globally the effectiveness of MCB, and assessing its climate impacts on rainfall amounts and distribution, and also polar sea-ice cover and thickness; (ii) high-resolution modelling of the effects of seeding on marine stratocumulus, which are required to understand the complex array of interacting processes involved in cloud brightening; (iii) microphysical modelling sensitivity studies, examining the influence of seeding amount, seed-particle salt-mass, air-mass characteristics, updraught speed and other parameters on cloud–albedo change; (iv) sea water spray-production techniques; (v) computational fluid dynamics studies of possible large-scale periodicities in Flettner rotors; and (vi) the planning of a three-stage limited-area field research experiment, with the primary objectives of technology testing and determining to what extent, if any, cloud albedo might be enhanced by seeding marine stratocumulus clouds on a spatial scale of around 100×100 km. We stress that there would be no justification for deployment of MCB unless it was clearly established that no significant adverse consequences would result. There would also need to be an international agreement firmly in favour of such action.

The general principle behind the marine cloud brightening (MCB) climate engineering technique is that seeding marine stratocumulus clouds with substantial concentrations of roughly monodisperse sub-micrometre-sized seawater particles might significantly enhance cloud albedo and longevity, thereby producing a cooling effect. This paper is concerned with preliminary studies of the possible beneficial application of MCB to three regional issues: (1) recovery of polar ice loss, (2) weakening of developing hurricanes and (3) elimination or reduction of coral bleaching. The primary focus is on Item 1. We focus discussion herein on advantages associated with engaging in limited-area seeding, regional effects rather than global; and the levels of seeding that may be required to address changing current and near-term conditions in the Arctic. We also mention the possibility that MCB might be capable of producing a localized cooling to help stabilize the West Antarctic Ice Sheet.

Weather shocks, such as heatwaves, droughts, and excess rainfall, are a major cause of crop yield losses and food insecurity worldwide. Statistical or process-based crop models can be used to quantify how yields will respond to these events and future climate change. However, the accuracy of weather-yield relationships derived from crop models, whether statistical or process-based, is dependent on the quality of the underlying input data used to run these models. In this context, a major challenge in many developing countries is the lack of accessible and reliable meteorological datasets. Gridded weather datasets, derived from combinations ofin situgauges, remote sensing, and climate models, provide a solution to fill this gap, and have been widely used to evaluate climate impacts on agriculture in data-scarce regions worldwide. However, these reference datasets are also known to contain important biases and uncertainties. To date, there has been little research to assess how the choice of reference datasets influences projected sensitivity of crop yields to weather. We compare multiple freely available gridded datasets that provide daily weather data over the Indian sub-continent over the period 1983–2005, and explore their implications for estimates of yield responses to weather variability for key crops grown in the region (wheat and rice). Our results show that individual gridded weather datasets vary in their representation of historic spatial and temporal temperature and precipitation patterns across India. We show that these differences create large uncertainties in estimated crop yield responses and exposure to variability in growing season weather, which in turn, highlights the need for improved consideration of input data uncertainty in statistical studies that explore impacts of climate variability and change on agriculture.

Increases in coral bleaching events over the last few decades have been largely caused by rising sea surface temperatures (SST), and continued warming is expected to cause even greater increases through this century. We use a Global Climate Model to examine the potential of marine cloud brightening (MCB) to cool oceanic surface waters in three coral reef provinces. Our simulations indicate that under doubled CO₂ conditions, the substantial increases in coral bleaching conditions from current values in three reef regions (Caribbean, French Polynesia, and the Great Barrier Reef) were eliminated when MCB was applied, which reduced the SSTs at these sites roughly to their original values.