Abstract Heat accumulation and rising sea surface temperatures (SST) are currently major stressors for coral reefs worldwide. Coral reefs are also impacted by cool SST anomalies, although the dynamics of cold stress events are less well understood. Here, we estimate coral bleaching metrics in the Indonesian Seas using a high‐spatial‐temporal‐resolution SST data set. We reveal that cold stress events caused by positive Indian Ocean Dipole (IOD) events tend to be more intense and longer‐lasting than heat stress events. Although these events are currently not intensifying, extreme cold stress reaches magnitudes comparable to the most extreme heat stress events recorded to date. In the Indonesian Seas, heat stress events caused by El Niño have become more frequent in recent years. When followed by a negative IOD event, heat stress events are prolonged and more severe. However, reefs in Karimata and Makassar Straits are protected from heat/cold stress, offering potential thermal refugia.
We examine the interannual variability of surface air temperature throughout the Holocene and the associated mechanisms by using our new set of Holocene transient simulations spanning from 11.5 ka before present to the preindustrial period. The interannual variability of annual, winter, and summer temperature increases with a linear trend of 0.005 degrees, 0.007 degrees, and 0.005 degrees C ka(-1) globally since 11.5 ka, respectively. The temperature variability evolution can be explained by the orbital forcing in most regions, with an additional impact from the retreat of ice sheets over North America and Europe but, overall, little effect from the change in atmospheric greenhouse gas concentrations. In response to the insolation change from the early to late Holocene, primarily due to the precession, variations in energy balance components contribute to the enhanced temperature variability by a global mean of 8%-10%. Specifically, surface net heat flux and radiation flux at the top of atmosphere generally play dominant roles, while atmospheric energy convergence minus storage partially offsets them at the global scale. Regionally, cloud effects and sea surface temperature variability are important in low latitudes, while sea ice changes are the main factors in mid- to high-latitude oceans. Due to the seasonal contrast in insolation, various responses of global surface mean temperature and its meridional gradient, sea ice fraction, total cloud, and surface soil moisture result in the seasonal difference in temperature variability change, particularly in the Arctic Ocean and northern continents. The simulated temperature variability change throughout the Holocene is qualitatively consistent with most of the available proxy data, although uncertainties still exist on both sides. Significance Statement: The purpose of this article is to investigate the year-to-year variability of surface air temperature throughout the Holocene from a global perspective. This is important because enhanced temperature variability increases the risk of cold and warm extremes, causing more profound socioeconomic impacts than the mean state. Based on our new set of Holocene transient simulations spanning from 11.5 ka before present to 1850, the results display a globally increasing variability of annual and seasonal temperatures since 11.5 ka primarily due to the orbital forcing. Associated mechanisms, including cloud effects, sea surface temperature variability, and sea ice changes, are highlighted from an energy balance decomposition. This study deepens our understanding of the evolution and mechanism of global temperature variability under warming backgrounds.
Purpose This paper examines why increasing the availability of climate and weather data alone is insufficient to enable effective climate change adaptation and disaster risk reduction, particularly in low- and middle-income countries. It aims to identify the conditions required to make climate data actionable and to propose a more inclusive framework for knowledge and action. Design/methodology/approach The study adopts a conceptual, synthesis-based approach, drawing on existing literature and emerging practices in climate services. It integrates insights from research and implementation initiatives to develop six interrelated conditions that support the transformation of climate data into useable, context-specific knowledge. Findings The paper identifies six key conditions for making climate data actionable: community-centered co-production, inclusive participation, multi-stakeholder collaboration, integrated knowledge infrastructures, the use of climate storylines and strengthened local–global linkages. Together, these conditions enable more relevant and actionable climate information. Originality/value The paper contributes by synthesizing these conditions into a coherent framework and introducing the concept of “Knowledge–Action Networks.” This framework highlights the need to integrate technical, social and institutional dimensions, offering practical and conceptual value for researchers, policymakers and practitioners working on climate adaptation and disaster risk management.
The Handbook of best practices and warning messaging templates to address societal challenges related to multi-hazard effects offers guidance on a human-centric approach to natural hazards. It covers public engagement through participatory emergency planning, best practices for addressing multi-hazard challenges in the COVID and post-COVID era and translating complex information into actionable knowledge for vulnerable end-users.
The climate-related impacts of artificial intelligence (AI), including both risks posed by increased resource use and opportunities presented by new technologies, are receiving growing attention. Legal and governance frameworks will be crucial to managing these impacts. In this brief working paper, we outline legal issues emerging from the intersection between law and climate change and consider how these might develop in the future. First, we examine climate-related risks and opportunities stemming from AI and argue that policy, legal, and regulatory mechanisms are likely required to minimise risks while maximising opportunities. Next, we evaluate existing and proposed legislation across multiple jurisdictions to identify provisions which address the AI-climate nexus, finding a range of existing examples which, while relatively limited, point to certain emerging trends. Using these examples, we categorise legislative interventions focused on AI and climate change and consider the impact of each category on policy goals. We then outline how AI’s environmental impacts might interact with other legal regimes, finding a wide variety intersections between the growth of AI and climate-related legal issues. We conclude with general recommendations for future work in this area.
