Process Drivers, Inter-Model Spread, and the Path Forward: A Review of Amplified Arctic Warming

Arctic amplification (AA) is a coupled atmosphere-sea ice-ocean process. This understanding has evolved from the early concept of AA, as a consequence of snow-ice line progressions, through more than a century of research that has clarified the relevant processes and driving mechanisms of AA. The predictions made by early modeling studies, namely the fall/winter maximum, bottom-heavy structure, the prominence of surface albedo feedback, and the importance of stable stratification have withstood the scrutiny of multi-decadal observations and more complex models. Yet, the uncertainty in Arctic climate projections is larger than in any other region of the planet, making the assessment of high-impact, near-term regional changes difficult or impossible. Reducing this large spread in Arctic climate projections requires a quantitative process understanding. This manuscript aims to build such an understanding by synthesizing current knowledge of AA and to produce a set of recommendations to guide future research. It briefly reviews the history of AA science, summarizes observed Arctic changes, discusses modeling approaches and feedback diagnostics, and assesses the current understanding of the most relevant feedbacks to AA. These sections culminate in a conceptual model of the fundamental physical mechanisms causing AA and a collection of recommendations to accelerate progress towards reduced uncertainty in Arctic climate projections. Our conceptual model highlights the need to account for local feedback and remote process interactions within the context of the annual cycle to constrain projected AA. We recommend raising the priority of Arctic climate sensitivity research, improving the accuracy of Arctic surface energy budget observations, rethinking climate feedback definitions, coordinating new model experiments and intercomparisons, and further investigating the role of episodic variability in AA

Análise discriminante canônica aplicada a dados de reflectância espectral foliar de videiras, oriundos de sensor proximal.

O sensoriamento remoto proximal ou em nível de folha, com sensores equipados de centenas ou milhares de bandas, contribui com perfis espectrais detalhados sobre estado vegetativo das plantas

Avaliação espectral de doenças fúngicas em videiras.

Os espectrorradiometros são sensores de alta resolução espectral, com a finalidade de se obter informações sobre o comportamento espectral de alvos, na forma de um gráfico de reflectância em função do comprimento de onda

Contribution of sea-ice loss to Arctic amplification is regulated by Pacific Ocean decadal variability

The pace of Arctic warming is about double that at lower latitudes – a robust phenomenon known as Arctic amplification (AA)1. Many diverse climate processes and feedbacks cause AA2-7, including positive feedbacks associated with diminished sea ice6,7. However, the precise contribution of sea-ice loss to AA remains uncertain7,8. Through analyses of both observations and model simulations, we show that the contribution of sea-ice loss to wintertime AA appears dependent on the phase of the Pacific Decadal Oscillation (PDO). Our results suggest that for the same pattern and amount of sea-ice loss, consequent Arctic warming is larger during the negative PDO phase, relative to the positive phase, leading to larger reductions in the poleward gradient of tropospheric thickness and to more pronounced reductions in the upper-level westerlies. Given the oscillatory nature of the PDO, this relationship has the potential to increase skill in decadal-scale predictability of Arctic and sub-Arctic climate. Our results indicate that Arctic warming in response to the ongoing long-term sea-ice decline9,10 is greater (reduced) during periods of negative (positive) PDO phase. We speculate that the observed recent shift to the positive PDO phase, if maintained and all other factors being equal, could act to temporarily reduce the pace of wintertime Arctic warming in the near future.J.A.S. was funded by a UK Natural Environment Research Council (NERC) grants NE/J019585/1 and NE/M006123/1. J.A.F. was supported by an NSF/ARCSS grant (1304097) and NASA grant (NNX14AH896). The model simulations were performed on the ARCHER UK National Supercomputing Service. We thank the NOAA ESRL and Met Office Hadley Centre for provision of observational and reanalysis data sets. We also thank D. Ackerley for helping to diagnose the cause of model crashes, C. Deser for commenting on the manuscript prior to submission, and two anonymous reviewers for constructive criticism

A common framework for approaches to extreme event attribution

The extent to which a given extreme weather or climate event is attributable to anthropogenic climate change is a question of considerable public interest. From a scientific perspective, the question can be framed in various ways, and the answer depends very much on the framing. One such framing is a risk-based approach, which answers the question probabilistically, in terms of a change in likelihood of a class of event similar to the one in question, and natural variability is treated as noise. A rather different framing is a storyline approach, which examines the role of the various factors contributing to the event as it unfolded, including the anomalous aspects of natural variability, and answers the question deterministically. It is argued that these two apparently irreconcilable approaches can be viewed within a common framework, where the most useful level of conditioning will depend on the question being asked and the uncertainties involved

Frequent new particle formation over the high Arctic pack ice by enhanced iodine emissions

In the central Arctic Ocean the formation of clouds and their properties are sensitive to the availability of cloud condensation nuclei (CCN). The vapors responsible for new particle formation (NPF), potentially leading to CCN, have remained unidentified since the first aerosol measurements in 1991. Here, we report that all the observed NPF events from the Arctic Ocean 2018 expedition are driven by iodic acid with little contribution from sulfuric acid. Iodic acid largely explains the growth of ultrafine particles (UFP) in most events. The iodic acid concentration increases significantly from summer towards autumn, possibly linked to the ocean freeze-up and a seasonal rise in ozone. This leads to a one order of magnitude higher UFP concentration in autumn. Measurements of cloud residuals suggest that particles smaller than 30 nm in diameter can activate as CCN. Therefore, iodine NPF has the potential to influence cloud properties over the Arctic Ocean

Blocking and its response to climate change

Purpose of review: Atmospheric blocking events represent some of the most high-impact weather patterns in the mid-latitudes, yet they have often been a cause for concern in future climate projections. There has been low confidence in predicted future changes in blocking, despite relatively good agreement between climate models on a decline in blocking. This is due to the lack of a comprehensive theory of blocking and a pervasive underestimation of blocking occurrence by models. This paper reviews the state of knowledge regarding blocking under climate change, with the aim of providing an overview for those working in related fields. Recent Findings: Several avenues have been identified by which blocking can be improved in numerical models, though a fully reliable simulation remains elusive (at least, beyond a few days lead time). Models are therefore starting to provide some useful information on how blocking and its impacts may change in the future, although deeper understanding of the processes at play will be needed to increase confidence in model projections. There are still major uncertainties regarding the processes most important to the onset, maintenance and decay of blocking and advances in our understanding of atmospheric dynamics, for example in the role of diabatic processes, continue to inform the modelling and prediction efforts. Summary: The term ‘blocking’ covers a diverse array of synoptic patterns, and hence a bewildering range of indices has been developed to identify events. Results are hence not considered fully trustworthy until they have been found using several different methods. Examples of such robust results are the underestimation of blocking by models, and an overall decline in future occurrence, albeit with a complex regional and seasonal variation. In contrast, hemispheric trends in blocking over the recent historical period are not supported by different methods, and natural variability will likely dominate regional variations over the next few decades