In order to overcome limitations of climate projections from Global Climate Models (GCMs), such as coarse spatial resolution and biases, in this study, the Statistical Down-Scaling Model (SDSM) is used to downscale daily precipitation and maximum and minimum temperature (T-max and T-min) required by impact assessment models.

During austral summer (DJF) 2017/18, the New Zealand region experienced an unprecedented coupled ocean-atmosphere heatwave, covering an area of 4 million km2. Regional average air temperature anomalies over land were +2.2 °C, and sea surface temperature anomalies reached +3.7 °C in the eastern Tasman Sea.

The tropics have suffered substantial forest loss, and elevated deforestation rates have been closely linked to large-scale land acquisitions(LSLA).

Each year wildland fires kill and injure trees on millions of forested hectares globally, affecting plant and animal biodiversity, carbon storage, hydrologic processes, and ecosystem services. The underlying mechanisms of fire-caused tree mortality remain poorly understood, however, limiting the ability to accurately predict

The goal of limiting global mean warming to well below 2 °C, and possibly to 1.5 °C, emerged in the Paris Agreement, motivated by the belief that achieving these targets 'would significantly reduce the risks and impacts of climate change'.

Understanding coping and adaptation behaviour of different population groups in the context of global environmental change has become increasingly important, especially in regions with high vulnerability such as Sub-Saharan drylands.

Extreme climate events such as droughts and heat waves exert strong impacts on ecosystems and human well-being. Estimations of the risks of climate extremes typically focus on one variable in isolation. In this study, we present a method to examine the likelihood of concurrent extreme temperature and precipitation modes at the interannual scale, including compound cool/dry and cool/wet events during the cold season as well as compound hot/dry and hot/wet events during the warm season.

The characteristics of tropical cyclones (TCs) and their response to climate change is an issue of broad concern.

This study examines the expected mitigation of greenhouse gases (GHG) and black carbon (BC) emissions associated to the transition from traditional biomass to clean fuels and clean woodburning cookstoves (CCS) in the Mexican residential sector for the period 2014-2030. We developed a spatial-explicit model at a county-level to understand the GHG trade-offs associated to different spatial-temporal CCS and clean fuels dissemination strategies. A business as usual (BAU) and three alternative scenarios with different targets for CCS and LPG dissemination were constructed.

Although natural terrestrial ecosystems have sequestered ~25% of anthropogenic CO2 emissions, the long-term sustainability of this key ecosystem service is under question. Forests have traditionally been viewed as robust carbon (C) sinks; however, extreme heat-waves, drought and wildfire have increased tree mortality, particularly in widespread semi-arid regions, which account for ~41% of Earth's land surface.