This journal article describes the first climate-based model used to predict outbreaks of dengue fever. Researchers from the University of Miami and the University of Costa Rica used climate data and vegetation indices from Costa Rica to predict disease outbreaks with 83 per cent accuracy.

Globally, there are up to 100 million cases of dengue fever, and its more dangerous form, dengue haemorrhagic fever, every year. The spread of dengue fever is set to rise as the world's climate changes. The importance of this model is that it could be used as the basis for an early warning system to prevent the spread of the disease by warning populations that are at risk.

The indices used in the model include variables such as El Niño Southern Oscillations and sea surface temperature, which affect populations of the Aedes aegypti mosquito that spreads the infection.

A population's immunity to disease can greatly affect outbreaks of vector-borne disease, and isolating the influence of climate variability has proven difficult. This research study sets out to evaluate the effect of climate by accounting for population immunity.

The authors collated data on cholera cases from a predominant strain in the rural area of Matlab, Bangladesh, from 1966–2002. They used a model to incorporate immunity from previous infections and also potential cross-immunity from previous infections by other strains. They found that both forms of immunity were long-lasting — over 10 years in some cases. Yet the variation in transmission did not always match variations in immunity; at several points, it coincided with severe weather change such as monsoon rains or river overflow.

The authors suggest that forecasting disease will require considering climate variability alongside population susceptibility.

The authors of this article analysed simulation results from a regional climate model for the northern Indian Ocean to predict likely changes in the strength and frequency of tropical cyclones in the Bay of Bengal from 2041–2060.

They find that rising concentrations of greenhouse gases will lead to more frequent cyclones in the region, particularly during the post-monsoon period. In addition, the number of intense cyclones and storm surges will increase. These results are consistent with other trend analyses that show intensification of cyclones in the bay during the last century.

But the research described in this paper only deals with simulations from one future climate scenario. To obtain better regional climate projections, the authors suggest it is necessary to examine simulations from more scenarios.

The authors report new data showing that the western side of the north Greenland ice sheet is thinning much more than anticipated from previous studies.