Machine-learning-based evidence and attribution mapping of 100,000 climate impact studies

This study presents a new dataset of annual temperature projections for different overshoot pathways (when the 1.5 °C of global warming limit is exceeded). The data offers a unique opportunity to study local and regional climate change impacts of a range of overshoot scenarios, including when temperature thresholds might be exceeded, and by how much.

This study in Nature show that definitions of net zero now in widespread use will not actually stop global warming. The paper demonstrates that relying on natural carbon sinks, such as in forests or oceans, to 'offset' ongoing fossil fuel emissions will lead to continued warming.

New study finds the devastating floods in Nepal late September were exacerbated by rapid urbanisation and climate change. The analysis found the relentless rain, which fell on saturated ground in the late monsoon, was made at least 10% heavier and 70% more likely by climate change.

Seasonal forecasting of atmospheric parameters is important in various fields including agriculture. This study tests how machine learning can complement dynamic models using Tanzanian seasonal forecasts and finds this process uses far less computational power.

With international efforts on climate action still not on track to limit warming to 1.5°C, technological fixes that aim to intentionally alter the Earth’s climate, such as solar geoengineering, might seem like appealing options for tackling global warming. But they come with questions in terms of feasibility, impacts and risks, governance and geopolitics, and who may or may not benefit.

With climate extremes hitting nations across the globe, disproportionately burdening vulnerable developing countries, funding for loss and damage is an acute need. Attribution science can provide useful information for decision makers.

For 1.5°C pathways with limited overshoot, most of the mitigation between now and 2030 should come from emissions reductions (70%), with reductions from cutting non-CO2 emissions (20%) and land-based carbon dioxide removals such as afforestation and preventing deforestation (10%) making up the remainder. 

This April and May, large regions of central Asia were hit by a series of storms resulting in heavy downpours and flash flooding. Researchers assessed what extent human-induced climate change altered the likelihood and intensity of the weather conditions that caused the floods.