In 2023, the rapid increase in global temperature of around 0.25 °C caught the scientific community by surprise. Its cause has been investigated largely by exploring variations on a long-term trend, with little success. Building on previous work, this paper proposes an alternative explanation—on decadal timescales, observed temperature shows a complex, nonlinear response to forcing, stepping through a series of steady-state regimes. The 2023 event is nominated as the latest in the sequence. Step changes in historical and modeled global mean surface temperatures (GMSTs) were detected using the bivariate test. Each time series was then separated into gradual (trends) and rapid components (shifts) and tested using probative criteria. For sea surface, global and land surface temperatures from the NOAA Global Surface Temperature Dataset V6.0 1880–2022, the rapid component of total warming was 94% of 0.72 °C, 78% of 1.16 °C and 74% of 1.93 °C, respectively. These changes are too large to support the gradual warming hypothesis. The recent warming was initiated in March 2023 by sea surface temperatures (SSTs) in the southern hemisphere, followed by an El Niño signal further north. Global temperatures followed, then land. A preceding regime shift in 2014 and subsequent steady-state 2015–2022 was also initiated and sustained by SSTs. Analysis of the top 100 m annual average ocean temperature from 1955 shows that it forms distinct regimes, providing a substantial ‘heat bank’ that sustains the changes overhead. Regime shifts are also produced by climate models. Archived data show these shifts emerged with coupling of the ocean and atmosphere. Comparing shifts and trends with equilibrium climate sensitivity (ECS) in an ensemble of 94 CMIP5 RCP4.5 models 2006–2095 showed that shifts had 2.9 times the influence on ECS than trends. Factors affecting this relationship include ocean structure, initialization times, physical parameters and model skill. Single model runs with skill ≥75 showed that shifts were 6.0 times more influential than trends. These findings show that the dominant warming mechanism is the sudden release of heat from the ocean rather than gradual warming in the atmosphere. The model ensemble predicted all regime changes since the 1970s within ±1 year, including 2023. The next shift is projected for 2036, but current emissions are tracking higher than projected by RCP4.5. Understanding what these changes mean for the estimation of current and future climate risks is an urgent task.

The Forest Fire Danger Index (FFDI) is the main measure used in Australia for estimating fire risk. Recent work by the authors showed that the FFDI forms stable state regimes, nominated as fire climate regimes. These regimes shifted to greater intensity in southern and eastern Australia around the year 2000 and, a decade later, further north. Reductions in atmospheric moisture were the primary contributor. These changes have not been fully incorporated into future projections. This paper compares the recent regime shifts with the most recent national projections of FFDI, published in 2015. They show that for most states and regions, the 2030 upper limit is approached or exceeded by the recent shift, except for two states with large arid zones, South Australia and Western Australia. Methods for attributing past changes, constructing projections, and the inability of climate models to reproduce the recent decreases in atmospheric moisture, all contribute to these underestimates. To address these shortcomings, we make some suggestions to modify efforts aiming to develop seamless predictions and projections of future fire risk.

This paper introduces and analyzes fire climate regimes, steady-state conditions that govern the behavior of fire weather. A simple model representing fire climate was constructed by regressing high-quality regional climate averages against the station-averaged annual Forest Fire Danger Index (FFDI) for Victoria, Australia. Four FFD indices for fire years 1957–2021 were produced for 10 regions. Regions with even coverage of station-averaged total annual FFDI (ΣFFDI) from 1971–2016 exceeded Nash–Sutcliffe efficiencies of 0.84, validating its widespread application. Data were analyzed for shifts in mean, revealing regime shifts that occurred between 1996 and 2003 in the southern states and 2012–2013 in Queensland. ΣFFDI shifted up by ~25% in SE Australia to 8% in the west; by approximately one-third in the SE to 7% in the west for days above high fire danger; by approximately half in the SE to 11% in the west for days above very high, with a greater increase in Tasmania; and by approximately three-quarters in the SE to 9% in the west for days above severe FFDI. Attribution of the causes identified regime shifts in the fire season maximum temperature and a 3 p.m. relative humidity, with changing drought factor and rainfall patterns shaping the results. The 1:10 fire season between Regimes 1 and 2 saw a three to seven times increase with an average of five. For the 1:20 fire season, there was an increase of 2 to 14 times with an average of 8. Similar timing between shifts in the Australian FFDI and the global fire season length suggests that these changes may be global in extent. A trend analysis will substantially underestimate these changes in risk.

Change in natural and human systems are almost invariably measured using trends. Cause and effect are known to take other forms but these are rarely investigated and, if they are, the burden of proof tends to be greater. When dealing with complex systems, analysts (and their critics) need to be more discriminating.

Recent work attributing decadal regime changes in temperature to radiative forcing is extended to atmospheric moisture. Temperature, and specific and relative humidity (T, q, RH) from the HadISDH data set were analyzed for regime shifts using the bivariate test. Most shifts in q and T for global and northern hemisphere (NH), and tropical land occurred within a year of each other. Only one shift of q was recorded in the southern hemisphere (SH). RH increased in the NH in 1990–91 and decreased in a series of shifts from the late 1990s, while in the SH decreased from 2001. The tropics have remained neutral, shifting negative over land and positive over the ocean. The global decreases in 2001 and 2011 was −0.56%. Global RH from 32 climate models from the CMIP5 RCP4.5 archive all contained regime shifts but only 4 reached or exceeded the observed decreases by 2100, the earliest in 2056. Regime shifts in RH and fire danger over Australia are consistent with the SH decreases in RH, shifting within one year of global fire season length in 2002, showing that impacts are also being underestimated by current analyses. Methods for nonlinear attribution and the contributing processes for nonlinear change are discussed. These results show that developing a better understanding of nonlinear change in moisture-related climate risk is an urgent task.

Abstract. Historical warming forms a sequence of steady-state regimes punctuated by abrupt shifts. These changes are regulated by a heat engine spanning the tropical Pacific Ocean teleconnected to a broader climate network. The eastern-central Pacific maintains steady-state conditions, delivering heat to the Western Pacific warm pool. They form a heat pump with heat moving from the cold to the warm reservoir, sustained by kinetic energy. The two reservoirs exchange heat on a range of timescales, with oscillatory behaviour that intensifies under forcing. The heat engine is part of a network of oscillations and circulation interacting on a range of timescales. The process is self-regulating: steady-state regimes persist until they become unstable due to an over- or under-supply of heat for dissipation, shifting warmer or cooler to a new stable state. Pre-industrial climate was in free mode, characterised by a loosely-coupled ocean-atmosphere with limited circulation, moving into forced mode in the latter 20th century, characterised by tighter coupling and stronger circulation through the tropical Pacific with more active teleconnections globally. Continued forcing produces a stepladder-like pattern of warming. Most shifts coincide with phase changes in decadal oscillations, switching from slower to faster modes of dissipation. El Niño events combine with regime shifts to propagate heat from the oceans to land and from the tropics to higher latitudes. The most recent shift commenced in the warm pool in December 2012, ending the so-called hiatus (1997–2013), global mean surface temperatures warming abruptly by ~0.25 °C in 2014–15.

This report provides an overview of the three and a half year project undertaken between emergency management organisations, the community and Victoria University. Its purpose was to provide an evidence based framework to support more effective implementation and understanding of diversity and inclusion management and measurement and the benefits of this. This project had three research foci, the community, economic and organisational which were was carried out in three phases: (1) understanding the context, (2) development of the framework, and (3) testing. Each phase was subject to annual review and the program was adjusted in response to the outcomes of those reviews. The project used a transdisciplinary approach called ‘working from the inside out’ methodology to provide the framework for its activities (see p17 for details). It features collaborative research codesigned with end-users. The transdisciplinary aspect integrates different knowledge systems and the key features are: systemic assessments, integration into decision-making systems, translation, learning, adjustment and communication with end-users. A mixed methods approach was undertaken that incorporated case studies, semi-structured interviews, focus groups, decision-making assessments, desktop reviews of organisational documents, informal and formal literature, and ongoing review and feedback with end-users. This report documents the process, key findings, research outputs and impacts. Report no. 655

Abstract. This paper explores whether climate is complicated or complex by examining the performance of a heat engine in the tropical Pacific, the Pacific Ocean heat engine, which is linked to a teleconnected network of circulation and oscillations. Sustained radiative forcing is widely expected to produce gradual change but instead produces step-wise regime shifts. The engine is a heat pump with cold-to-hot circulation maintained by kinetic energy produced by the Coriolis Effect. It is a fundamental response of a coupled ocean-atmosphere system to asymmetric circulation. This paper surveys emergent behaviours in climate models linked to such shifts. It explores how well models represent the heat engine, compares regime changes in models and observations, and examines how geostrophic controls on meridional heat transport set critical boundary conditions. The results reinforce the description of climate as a self-regulating system governed by the principle of least action. Teleconnected steady-state regimes are physically-induced by the need to maintain boundary-limited dissipation rates between the hemispheres, the equator and the poles. A sufficient imbalance of energy at the planetary surface produces regime shifts that switch between slow and fast dissipation pathways. The strength of coupling measured via heat engine characteristics is weaker in models than in the observed climate, failing to distinguish clearly between free and forced modes. The capacity of the coupled ocean-atmosphere system to maintain homeostasis allows Earth’s climate to be classified physically rather than statistically, the basic unit of climate being the steady-state regime.

This paper applies misspecification (M-S) testing to the detection of abrupt changes in climate regimes as part of undertaking severe testing of climate shifts versus trends. Severe testing, proposed by Mayo and Spanos, provides severity criteria for evaluating statistical inference using probative criteria, requiring tests that would find any flaws present. Applying M-S testing increases the severity of hypothesis testing. We utilize a systematic approach, based on well-founded principles that combines the development of probative criteria with error statistical testing. Given the widespread acceptance of trend-like change in climate, especially temperature, tests that produce counter-examples need proper specification. Reasoning about abrupt shifts embedded within a complex times series requires detection methods sensitive to level changes, accurate in timing, and tolerant of simultaneous changes of trend, variance, autocorrelation, and red-drift, given that many of these measures may shift together. Our preference is to analyse the raw data to avoid pre-emptive assumptions and test the results for robustness. We use a simple detection method, based on the Maronna-Yohai (MY) test, then re-assess nominated shift-points using tests with varied null hypotheses guided by M-S testing. Doing so sharpens conclusions while avoiding an over-reliance on data manipulation, which carries its own assumptions.

The paper addresses an interesting topic on whether the climate is complex or complicated. After a very nice introduction and focus on the problem, the authors mostly refer to the companion paper (under review on ESD) for answering this question. The manuscript is well-posed in terms of concepts and references, it provides a good review on some outstanding problems in climate science. However, there are some unclear points that should be clarified before the manuscript becomes acceptable for publication. Furthermore, more quantitative results should be considered to support the authors' statements, instead of only considering qualitative discussions.

A key driver for building diversity and inclusion (D&I) in emergency management organisations (EMOs) is to better represent diverse cohorts and ensure EMOs and their communities become more resilient to natural hazards. While EMOs have made some progress, dynamic transformation is required to effectively manage the rapidly changing contexts they and their communities face. Central to this is the need to expand the current service–client relationship to become a more inclusive partnership model that builds resilience. This paper reports on Phase 2 of the Bushfire and Natural Hazards Cooperative Research Centre project Diversity and inclusion: Building strength and capability, which aimed to develop a DI [2] Identification and development of specific strategic and people-based capabilities and skills; [3] Management of risks arising as a result of DI and [4] A process to measure and manage progress and assess the benefits derived from investment.

This report covers three areas: • It reports on a workshop entitled ‘Into the future: building capabilities and skills for inclusive and diverse organisations’ held on 5 December 2018 at Victoria University. • It introduces and describes D&I-related risks as they apply to EMOs. • It links attributes, capabilities and skills to the management of these risks and day-to-day activities. It also contains insights from six focus group interviews with members of brigades and units from EMOs in Victoria, New South Wales and South Australia. The workshop ‘Into the future: building capabilities and skills for inclusive and diverse organisations’ held in December 2018 at Victoria University, aimed to explore these issues. In particular, it aimed to understand: • The attributes, skills and capabilities needed to support D&I practice and implementation of activities • How these might change in the future, and • How D&I related to current tasks at the service delivery level. managed. A key finding of the workshop was that D&I shocks can result as a substantial organisational risk. These risks may occur due to inaction in the face of issues that arise from poorly managed or poorly implemented D&I activities. The consequences of these risks can have a profound effect on organisational sustainability and community safety. These risks have been present for some time but are not explicitly recognised or managed in formal risk processes within EMOs. Their pervasive nature and ability to amplify existing risks or to create new risks indicates a need to more clearly define these risks and to ensure they are being properly owned. This report provides some of the groundwork for understanding what these risks are and how they manifest in an organisational context. Its aim is to provide a starting point for EMOs to think about how to incorporate D&I risk more formally into their operational frameworks.

Abstract. Climate change is routinely represented as a smoothly changing signal surrounded by statistical noise. However, on decadal timescales, warming proceeds as a sequence of steady-state regimes punctuated by abrupt shifts. Here we present evidence that this process is regulated by a heat engine spanning the tropical Pacific Ocean. The eastern-central Pacific maintains steady-state conditions, collecting heat and delivering it to the Western Pacific warm pool. This acts as distributor, transporting heat upwards and to the poles. The heat engine is networked within the climate system, linking different oscillations and circulations as heat energy is dissipated. The process is self-regulating. Steady-state regimes will persist until they become unstable and need more or less power depending on the direction of forcing. Under greenhouse gas forcing, shifts initiated within the heat engine propagate broadly across the shallow ocean, followed by warming over land and at higher latitudes. The heat engine was in free mode during the early 20th century, dominated by decadal variability. From the 1960s, it switched into forced mode, initiating a stepladder-like pattern of warming in regional and global climate. The most recent shift commenced in the warm pool in December 2012, ending the so-called hiatus (1997–2013). During 2014–15, surface temperatures warmed abruptly by ~ 0.25 °C globally and > 0.5 °C over northern hemisphere land and high latitudes. With increasing forcing, the heat engine will shift more frequently. Rapid decreases in greenhouse gas emissions will slow the process and potentially, could stabilise it. Managing unavoidable change requires developing the capacity to predict shifts in advance. Planning for rapid changes in extreme events is an urgent priority.