Dataset Information

The influence of recent and future climate change on spring Arctic cyclones.

ABSTRACT: In recent decades, the Arctic has experienced rapid atmospheric warming and sea ice loss, with an ice-free Arctic projected by the end of this century. Cyclones are synoptic weather events that transport heat and moisture into the Arctic, and have complex impacts on sea ice, and the local and global climate. However, the effect of a changing climate on Arctic cyclone behavior remains poorly understood. This study uses high resolution (4 km), regional modeling techniques and downscaled global climate reconstructions and projections to examine how recent and future climatic changes alter cyclone behavior. Results suggest that recent climate change has not yet had an appreciable effect on Arctic cyclone characteristics. However, future sea ice loss and increasing surface temperatures drive large increases in the near-surface temperature gradient, sensible and latent heat fluxes, and convection during cyclones. The future climate can alter cyclone trajectories and increase and prolong intensity with greatly augmented wind speeds, temperatures, and precipitation. Such changes in cyclone characteristics could exacerbate sea ice loss and Arctic warming through positive feedbacks. The increasing extreme nature of these weather events has implications for local ecosystems, communities, and socio-economic activities.

SUBMITTER: Parker CL

PROVIDER: S-EPMC9646868 | biostudies-literature | 2022 Nov

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

The influence of recent and future climate change on spring Arctic cyclones.

Parker Chelsea L CL Mooney Priscilla A PA Webster Melinda A MA Boisvert Linette N LN

Nature communications 20221109 1

In recent decades, the Arctic has experienced rapid atmospheric warming and sea ice loss, with an ice-free Arctic projected by the end of this century. Cyclones are synoptic weather events that transport heat and moisture into the Arctic, and have complex impacts on sea ice, and the local and global climate. However, the effect of a changing climate on Arctic cyclone behavior remains poorly understood. This study uses high resolution (4 km), regional modeling techniques and downscaled global cli ...[more]

PMID: 36351898

Similar Datasets

Project description:Phenological models are built upon an understanding of the influence of environmental factors on plant phenology, and serve as effective tools for predicting plant phenological changes. However, the differences in phenological model predictive performance under different climate change scenarios have been rarely studied. In this study, we parameterized thirteen spring phenology models, including six one-phase models and seven two-phase models, by combining phenological observations and meteorological data. Using climatic data from two Shared Socioeconomic Pathways (SSP) scenarios, namely SSP126 (high mitigation and low emission) and SSP585 (no mitigation and high emission), we predicted spring phenology in Germany from 2021 to 2100, and compared the impacts of dormancy phases and driving factors on model predictive performance. The results showed that the average correlation coefficient between the predicted start of growing season (SOS) by the 13 models and the observed values exceeded 0.72, with the highest reaching 0.80. All models outperformed the NULL model (Mean of SOS), and the M1 model (driven by photoperiod and forcing temperature) performed the best for all the tree species. In the SSP126 scenario, the average SOS advanced initially and then gradually shifted towards a delay starting around 2070. In the SSP585 scenario, the average SOS advanced gradually at a rate of approximately 0.14 days per year. Moreover, the standard deviation of the simulated SOS by the 13 spring phenology models exhibited a significant increase at a rate of 0.04 days per year. On average, two-phase models exhibited larger standard deviations than one-phase models after approximately 2050. Models driven solely by temperature showed larger standard deviations after 2060 compared to models driven by both temperature and photoperiod. Our findings suggest investigating the release mechanisms of endodormancy phase and incorporating new insights into future phenological models to better simulate the changes in plant phenology.

Project description:Climate change and increased anthropogenic activities are expected to elevate the potential of introducing nonindigenous species (NIS) into the Arctic. Yet, the knowledge base needed to identify gaps and priorities for NIS research and management is limited. Here, we reviewed primary introduction events to each ecoregion of the marine Arctic realm to identify temporal and spatial patterns, likely source regions of NIS, and the putative introduction pathways. We included 54 introduction events representing 34 unique NIS. The rate of NIS discovery ranged from zero to four species per year between 1960 and 2015. The Iceland Shelf had the greatest number of introduction events (n = 14), followed by the Barents Sea (n = 11), and the Norwegian Sea (n = 11). Sixteen of the 54 introduction records had no known origins. The majority of those with known source regions were attributed to the Northeast Atlantic and the Northwest Pacific, 19 and 14 records, respectively. Some introduction events were attributed to multiple possible pathways. For these introductions, vessels transferred the greatest number of aquatic NIS (39%) to the Arctic, followed by natural spread (30%) and aquaculture activities (25%). Similar trends were found for introductions attributed to a single pathway. The phyla Arthropoda and Ochrophyta had the highest number of recorded introduction events, with 19 and 12 records, respectively. Recommendations including vector management, horizon scanning, early detection, rapid response, and a pan-Arctic biodiversity inventory are considered in this paper. Our study provides a comprehensive record of primary introductions of NIS for marine environments in the circumpolar Arctic and identifies knowledge gaps and opportunities for NIS research and management. Ecosystems worldwide will face dramatic changes in the coming decades due to global change. Our findings contribute to the knowledge base needed to address two aspects of global change-invasive species and climate change.

Dataset Information

The influence of recent and future climate change on spring Arctic cyclones.

Publications

The influence of recent and future climate change on spring Arctic cyclones.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets