As more countries make net zero greenhouse gas emissions pledges, it is crucial to understand the effects on global climate after achieving net zero emissions. The climate has been found to continue to evolve even after the abrupt cessation of CO2 emissions, with some models simulating a small warming and others simulating a small cooling. In this study, we analyse if the temperature and precipitation changes post abrupt cessation of CO2 emissions are significant compared to natural climate variations. We find that the temperature changes are outside of natural variability for most models, whilst the precipitation changes are mostly non-significant. We also demonstrate that post-net zero temperature changes have implications for the remaining carbon budget. The possibility of further global warming post-net zero adds to the evidence supporting more rapid emissions reductions in the near-term.

Meteorological and geophysical hazards will concur and interact with coronavirus disease (COVID-19) impacts in many regions on Earth. These interactions will challenge the resilience of societies and systems. A comparison of plausible COVID-19 epidemic trajectories with multi-hazard time-series curves enables delineation of multi-hazard scenarios for selected countries (United States, China, Australia, Bangladesh) and regions (Texas). In multi-hazard crises, governments and other responding agents may be required to make complex, highly compromised, hierarchical decisions aimed to balance COVID-19 risks and protocols with disaster response and recovery operations. Contemporary socioeconomic changes (e.g. reducing risk mitigation measures, lowering restrictions on human activity to stimulate economic recovery) may alter COVID-19 epidemiological dynamics and increase future risks relating to natural hazards and COVID-19 interactions. For example, the aggregation of evacuees into communal environments and increased demand on medical, economic, and infrastructural capacity associated with natural hazard impacts may increase COVID-19 exposure risks and vulnerabilities. COVID-19 epidemiologic conditions at the time of a natural hazard event might also influence the characteristics of emergency and humanitarian responses (e.g. evacuation and sheltering procedures, resource availability, implementation modalities, and assistance types). A simple epidemic phenomenological model with a concurrent disaster event predicts a greater infection rate following events during the pre-infection rate peak period compared with post-peak events, highlighting the need for enacting COVID-19 counter measures in advance of seasonal increases in natural hazards. Inclusion of natural hazard inputs into COVID-19 epidemiological models could enhance the evidence base for informing contemporary policy across diverse multi-hazard scenarios, defining and addressing gaps in disaster preparedness strategies and resourcing, and implementing a future-planning systems approach into contemporary COVID-19 mitigation strategies. Our recommendations may assist governments and their advisors to develop risk reduction strategies for natural and cascading hazards during the COVID-19 pandemic.

Spatial analogs have previously been used to communicate climate projections by comparing the future climate of a location with an analogous recent climate at a different location which is typically hotter. In this study, spatial climate analogs were computed using observational data to identify and quantify past changes. A sigma dissimilarity metric was computed to compare the recent climates of nine major Australian cities and early 20th century climate. Evidence of climate shifts is found, particularly in locations, such as Perth, where precipitation has significantly changed in addition to the warming trend observed at all cities. Analogs designed to capture extremes, including a human health-relevant climate analog, were constructed and these also highlight significant climate shifts. This work demonstrates the utility of climate analogs for monitoring past climate changes as well as examining future change. Tailored analogs could be studied to communicate climate changes relevant to specific stakeholders.

Changes in climate are usually considered in terms of trends or differences over time. However, for many impacts requiring adaptation, it is the amplitude of the change relative to the local amplitude of climate variability which is more relevant. Here, we develop the concept of ‘signal-to-noise’ in observations of local temperature, highlighting that many regions are already experiencing a climate which would be ‘unknown’ by late 19century standards. The emergence of observed temperature changes over both land and ocean is clearest in tropical regions, in contrast to the regions of largest change which are in the northern extra-tropics - broadly consistent with climate model simulations. Significant increases and decreases in rainfall have also already emerged in different regions with the UK experiencing a shift towards more extreme rainfall events, a signal which is emerging more clearly in some places than the changes in mean rainfall.

Quantifying warming of the Earth’s climate system since the late 19th century and the ratio of regional to global warming are required when examining implications of Paris Agreement global warming targets. To estimate these terms reliably, the limitations in quality and length of observed records, differences between climate models and observations, and different results dependent on temporal and forcing contexts must be taken into account. Here we use observational datasets currently available back to 1860 and the latest set of global climate model simulations from CMIP5/6 to examine the warming of Australia in the past and projected future. We find that Australia has warmed by 1.5 °C (1.3–1.8 °C) during 1850 - 2019, at a ratio of ~1.4 times the global warming of ~1.1 °C. Models generally produce a lower ratio of Australian to global warming than in observations, which may be related to model biases or internal climate variability.

Recent climate change is characterised by rapid global warming, but the goal of the Paris Agreement is to achieve a stable climate where global temperatures remain well below 2°C above pre-industrial levels. Inferences about conditions at or below 2°C are usually made based on transient climate projections. To better understand climate change impacts on natural and human systems under the Paris Agreement, we must understand how a stable climate may differ from transient conditions at the same warming level. Here we examine differences between transient and quasi-equilibrium climates based on greenhouse gas-only model simulations at 1.5°C and 2°C global warming. We find substantial local differences between seasonal-average temperatures, with mid-latitude land regions in boreal summer considerably warmer in a transient climate than a quasi-equilibrium state at both 1.5°C and 2°C global warming. Our research demonstrates that the rate of global warming must be considered in regional projections.