In this review, with supplemental data analyses, we focus on the global and regional impacts of climate change on the frequency and intensity of fire weather (conditions conducive to fire ignition and spread) and the consequences for fire activity. We find that significant increases in fire weather have occurred in most world regions during recent decades due to climate change. Corresponding increases in the area burned by fires have been seen in some regions, most notably in mesic forests, however, in many regions fire is controlled by a range of other bioclimatic and human factors whose influences mediate or override those of fire weather. Weather conditions affecting vegetation growth and the build-up of fuels, the presence of human ignitions in regions that are not naturally fire-prone, and the fragmentation of fire-prone landscapes by agriculture are key examples of factors that can locally or regionally outweigh fire weather as controls on fire activity. Climate models project that fire weather will become increasingly frequent and intense under future warming, and at an increasing rate with each additional increment of warming. The outcomes for fire activity in future will depend on other regionally important factors that control fire ignition and spread. Existing fire models represent the controls on fire incompletely and so they reproduce observed patterns of fire with only limited success. Models also disagree on historical trends, leading to low confidence in their simulations of future fire activity. Various efforts to improve the representation of fire in models are underway and should yield greater capacity to predict the future of fire activity.

In recent years, discussions of climate change have shown growing interest in “tipping elements” of the Earth system, also imprecisely referred to as “tipping points.” This refers to Earth system components like the tropical rainforests of Amazonia or the Greenland and Antarctic ice sheets which may exhibit large-scale, long-term changes upon reaching critical global warming, greenhouse gas, or other thresholds. Once such thresholds are passed, some tipping elements could in turn produce additional greenhouse gas emissions or change the Earth's energy balance in ways that moderately reinforce warming. In this review, we summarize the current state of scientific knowledge on 10 systems that some have referred to as potential tipping elements of the climate system. We describe the mechanisms important to each system, highlight the response of these systems to climate change so far, and explain the dynamics of potential future changes that these systems could undergo in response to further climate change. Overall, even considering remaining scientific uncertainties, tipping elements will influence future climate change and may involve major impacts on ecosystems, climate patterns, and the carbon cycle starting later this century. Aggressive efforts to stabilize climate change could significantly reduce such impacts.

Earth's global “climate sensitivity” is a fundamental quantitative measure of the susceptibility of Earth's climate to human influence. A landmark report in 1979 concluded that it probably lies between 1.5°C and 4.5°C per doubling of atmospheric carbon dioxide, assuming that other influences on climate remain unchanged. In the 40 years since, it has appeared difficult to reduce this uncertainty range. In this report we thoroughly assess all lines of evidence including some new developments. We find that a large volume of consistent evidence now points to a more confident view of a climate sensitivity near the middle or upper part of this range. In particular, it now appears extremely unlikely that the climate sensitivity could be low enough to avoid substantial climate change (well in excess of 2°C warming) under a high-emission future scenario. We remain unable to rule out that the sensitivity could be above 4.5°C per doubling of carbon dioxide levels, although this is not likely. Continued research is needed to further reduce the uncertainty, and we identify some of the more promising possibilities in this regard.

Land surface temperature (LST) is a crucial geophysical parameter related to surface energy and water balance of the land-atmosphere system. Satellite remote sensing provides the best way to measure LST and generate various LST products at regional and global scales. In this review, to facilitate the application of LST products in different fields, we first present the physical meaning of satellite-derived LST. Subsequently, we summarize recent advances in LST retrieval and validation methods, with a special focus on the state-of-the-art product collections, product accuracies and intercomparisons, and main problems in current LST products as well as their possible solutions. Additionally, we also review the major applications of LST products in agricultural drought monitoring, thermal environment monitoring, thermal anomaly monitoring, and climate change. Finally, we offer recommendations or perspectives to promote LST retrieval methods and their applications. This review will aid the user in gaining a thorough comprehensive understanding of satellite-derived LST products and promoting their appropriate applications.

Heat waves (HWs) are climate extremes of major societal concern whose frequency, intensity and duration will continue increasing during this century. This review synthesizes the physical understanding and the main scientific challenges. We discuss problems involved in HW definition, including the diversity of HW indicators, and the consideration of adaptive capabilities in a changing climate. We also review observed and projected trends and the associated atmospheric patterns in different areas of the globe, with special attention to the mechanisms and drivers responsible for HW occurrence. These act at different scales, from planetary to local, and include thermodynamic and dynamical processes. There is a limited and fragmentary understanding of the interactions among these processes on regional scales, and their changes under global warming. Process-based understanding will benefit HW forecasts at time horizons longer than weather predictions, attribution of HW trends and events to human activities, and regional climate projections. Improved technological capabilities, models of diverse complexity, or machine-learning techniques will help overcome these challenges.