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Exploring Unprecedented Extremes What: Facing the urgent challenge of extreme weather and climate-related events, our societal frameworks for 'resilience' and 'adaptation' are proving to be insufficient. This paper introduces the [...]

The Fourth Assessment Report (AR4) of the Intergovernmental Panel on Climate Change (IPCC) concluded that global warming is 'unequivocal' and that most of the observed increase since the mid-twentieth century is very likely due to the increase in anthropogenic greenhouse gas concentrations, with discernible human influences On ocean warming, continental-average temperatures, temperature extremes, wind patterns, and other physical and biological indicators, impacting both socioeconomic and ecological systems. It is now clear that we are committed to some level of global climate change, and it is imperative that this be considered when planning future climate research and observational strategies. The Global Climate Observing System program (GCOS), the World Climate Research Programme (WCRP), and the International Geosphere-Biosphere Programme (IGBP) therefore initiated a process to summarize the lessons learned through AR4 Working Groups I and II and to identify a set of high-priority modeling and observational needs. Two classes of recommendations emerged. First is the need to improve climate models, observational and climate monitoring systems, and our understanding of key processes. Second, the framework for climate research and observations must be extended to document impacts and to guide adaptation and mitigation efforts. Research and observational strategies specifically aimed at improving our ability to predict and understand impacts, adaptive capacity, and societal and ecosystem vulnerabilities will serve both purposes and are the subject of the specific recommendations made in this paper.

Efforts are being made to develop new paradigms for climate change adaptation policy at both the national and the international levels. However, progress in vulnerability and adaptation research has not been matched by advancement on practical policy initiatives. The complexity of the challenge to develop methods and means to support adaptation to climate change necessitates a diversity of approaches. This diversity is healthy, and yet it is possible to define some key characteristics and tools that can promote practical outcomes. In this paper, some methodologies that have proved successful are reviewed. These include a mapping of contextual circumstances, an appreciation for multiple perspectives, and the importance of a 'boundary object' in forging strong interactions among project participants. Further, a toolkit of approaches for natural scientists is presented. This toolkit can be used to organize work in collaboration with stakeholders and other participants and can help overcome barriers to a meaningful contribution to the policy process. Fundamentally, this challenge will require approaches that are more grounded in meaning, narration, and reflection.

We present a tracking algorithm for synoptic to meso-a-scale Arctic cyclones that differentiates between cold- and warm-core systems. The algorithm is applied to the ERA5 reanalysis north of 608N from 1950 to 2019. In this dataset, over one-half of the cyclones that meet minimum intensity and duration thresholds can be classified as cold-core systems. Systems that undergo transition, typically from cold to warm core, make up 27.2% of cyclones and are longer lived. The relatively infrequent warm-core cyclones are more intense and are most common in winter. The Arctic-wide occurrence of maritime cyclones has increased from 1979 to 2019 when compared with the period from 1950 to 1978, but the trends have high interannual variability. This shift has ramifications for transportation, fisheries, and extractive industries, as well as impacts on communities across the Arctic. [ABSTRACT FROM AUTHOR]

There is a growing demand for regional-scale climate predictions and assessments. Quantifying the impacts of uncertainty in initial conditions and lateral boundary forcing data on regional model simulations can potentially add value to the usefulness of regional climate modeling. Results from a regional model depend on the realism of the driving data from either global model outputs or global analyses; therefore, any biases in the driving data will be carried through to the regional model. This study used four popular global analyses and achieved 16 driving datasets by using different interpolation procedures. The spread of the 16 datasets represents a possible range of driving data based on analyses to the regional model. This spread is smaller than typically associated with global climate model realizations of the Arctic climate. Three groups of 16 realizations were conducted using the fifth-generation Pennsylvania State University–National Center for Atmospheric Research (PSU–NCAR) Mesoscale Model (MM5) in an Arctic domain, varying both initial and lateral boundary conditions, varying lateral boundary forcing only, and varying initial conditions only. The response of monthly mean atmospheric states to the variations in initial and lateral driving data was investigated. Uncertainty in the regional model is induced by the interaction between biases from different sources. Because of the nonlinearity of the problem, contributions from initial and lateral boundary conditions are not additive. For monthly mean atmospheric states, biases in lateral boundary conditions generally contribute more to the overall uncertainty than biases in the initial conditions. The impact of initial condition variations decreases with the simulation length while the impact of variations in lateral boundary forcing shows no clear trend. This suggests that the representativeness of the lateral boundary forcing plays a critical role in long-term regional climate modeling. The extent of impact of the driving data uncertainties on regional climate modeling is variable dependent. For some sensitive variables (e.g., precipitation, boundary layer height), even the interior of the model may be significantly affected. [ABSTRACT FROM AUTHOR]