scholarly journals Why Are Siberian Temperatures Plummeting While the Arctic Warms?

Eos ◽  
2018 ◽  
Vol 99 ◽  
Author(s):  
Kimberly Cartier
Keyword(s):  
Climate Models ◽  
Extreme Weather ◽  
The Arctic ◽  
Extreme Weather Events ◽  
Weather Events ◽  
Stratospheric Circulation

The answer involves the intricacies of stratospheric circulation, which, if better represented in climate models, could help predict extreme weather events in Siberia and elsewhere.

Climate Research and Reinsurance*

2004 ◽  
Vol 85 (5) ◽  
pp. 697-708 ◽  
Author(s):  
Richard J. Murnane
Keyword(s):  
Extreme Events ◽  
Extreme Weather ◽  
The Arctic ◽  
Extreme Weather Events ◽  
Quasi Biennial Oscillation ◽  
Research Areas ◽  
Weather Events ◽  
Mutual Interest ◽  
Insured Losses ◽  
Catastrophe Reinsurance

Extreme weather events produce some of the most deadly and costly natural disasters and are a major concern of the catastrophe reinsurance industry. For example, in 1992 Hurricane Andrew caused over $20 billion (in 2002 U.S. dollars) in insured losses, the largest loss on record due to a natural disaster. In addition, 26 of the top 30 insured losses were produced by extreme weather events, mainly landfalling hurricanes and typhoons and European windstorms. A better understanding of how extreme events vary with climate would benefit the reinsurance industry and society. The Risk Prediction Initiative hosted a workshop on Weather Extremes and Atmospheric Oscillations that examined how extreme meteorological events of interest to the reinsurance industry are influenced by the quasi-biennial oscillation (QBO), the Arctic Oscillation (AO), and the Madden–Julian oscillation (MJO). Workshop participants concluded that the stratosphere is much more relevant to predictions that aid the reinsurance industry than is generally recognized and that there is mutual interest in fostering research on the relationship between the stratospheric circulation and extreme weather events. A preliminary science–business research agenda, based on presentations and discussions during and after the workshop, highlights four areas of mutual interest to scientists and insurers. The research areas focus mainly on understanding how the QBO, AO, and MJO influence the frequency and intensity of extreme events, with particular emphasis on tropical cyclones and European windstorms. An awareness of how the catastrophe reinsurance industry operates provides insights into why specific research areas were chosen. For example, the reinsurance industry operates on the basis of annual contracts, most of which are renewed on 1 January. Thus, although skillful forecasts at any lead are of interest, skillful forecasts of extreme events are of greatest value when made in the final quarter of a calendar year.

scholarly journals Impacts of extreme weather events on transport infrastructure in Norway

2017 ◽  
Author(s):  
Regula Frauenfelder ◽  
Anders Solheim ◽  
Ketil Isaksen ◽  
Bård Romstad ◽  
Anita V. Dyrrdal ◽  
...  
Keyword(s):  
Debris Flows ◽  
Climate Models ◽  
Heavy Precipitation ◽  
Extreme Weather ◽  
Transport Infrastructure ◽  
Extreme Weather Events ◽  
Local Climate ◽  
Weather Events ◽  
Interdisciplinary Research Project ◽  
Heavy Rainfall Events

Abstract. This paper presents selected results of the interdisciplinary research project Impacts of extreme weather events on infrastructure in Norway (InfraRisk) carried out between 2010 to 2013, as part of the program NORKLIMA (2004 2013) of the Research Council of Norway (RCN). The project has systematized large amounts of existing data and generated new results that are important for our handling of risks associated with future extreme weather and natural hazards threatening the transport infrastructure in Norway. The results of the InfaRisk project range widely, from the establishment of trends in key weather elements to studies of human response to threats from extreme weather. The analyses of weather elements have provided a clearer understanding of the trends in the development of extreme weather. The studies are based on both historical data and available future scenarios (projections) from climate models. Compared to previous studies, we calculated changes in climate variables that are particularly important in relation to nature hazards. Overall, the analyses document an increase in frequency as well as intensity of both precipitation and wind. Results of projections show that the observed changes will continue throughout this century. We could also identify large regional differences, with some areas experiencing, e.g., a reduction in the intensity of heavy rainfall events. However, most of the country will experience the opposite, i.e., both increased intensity and increased frequency of heavy precipitation. Our analyses show that at least 27 per cent of Norwegian roads and 31 per cent of railroads are exposed to rock fall and snow avalanches hazards. The project has also assessed relationships between different parameters that can affect the likelihood of debris flows. Variables such as terrain slope and size of watercourses are important, while local climate, which varies widely in Norway, determines threshold values for rainfall that can trigger debris flows.

scholarly journals Multi-thousand member ensemble atmospheric simulations with global 60km resolution using climateprediction.net

2020 ◽  
Author(s):  
Peter Watson ◽  
Sarah Sparrow ◽  
William Ingram ◽  
Simon Wilson ◽  
Drouard Marie ◽  
...  
Keyword(s):  
Climate Models ◽  
Climate Model ◽  
Global Climate ◽  
Atmospheric Model ◽  
Computing System ◽  
Extreme Weather ◽  
Global Climate Models ◽  
Extreme Weather Events ◽  
Weather Events ◽  
The Impact

<p>Multi-thousand member climate model simulations are highly valuable for showing how extreme weather events will change as the climate changes, using a physically-based approach. However, until now, studies using such an approach have been limited to using models with a resolution much coarser than the most modern systems. We have developed a global atmospheric model with 5/6°x5/9° resolution (~60km in middle latitudes) that can be run in the climateprediction.net distributed computing system to produce such large datasets. This resolution is finer than that of many current global climate models and sufficient for good simulation of extratropical synoptic features such as storms. It will also allow many extratropical extreme weather events to be simulated without requiring regional downscaling. We will show that this model's simulation of extratropical weather is competitive with that in other current models. We will also present results from the first multi-thousand member ensembles produced at this resolution, showing the impact of 1.5°C and 2°C global warming on extreme winter rainfall and extratropical cyclones in Europe.</p>

scholarly journals Development of events detector for monitoring cryoseisms in upper soils

2020 ◽  
Author(s):  
Nikita Afonin ◽  
Elena Kozlovskaya
Keyword(s):  
Neural Network ◽  
Seismic Data ◽  
Seismic Station ◽  
Extreme Weather ◽  
Saturated Soil ◽  
The Arctic ◽  
Extreme Weather Events ◽  
Field Zone ◽  
Weather Events ◽  
Water Saturated

<p>In some problems of solid Earth geophysics analysis of the huge amount of continuous seismic data is necessary. One of such problems is an investigation of so-called frost quakes or cryoseisms in the Arctic caused by extreme weather events. Weather extremes such as rapid temperature decrease in combination with thin snow cover can result in cracking of water-saturated soil and rock when the water has suddenly frozen and expanded. As cryoseisms can be hazardous for industrial and civil objects located in the near-field zone, their monitoring and analysis of weather conditions during which they occur, is necessary to access hazard caused by extreme weather events. One of the important tasks in studying cryoseisms is the development of efficient data processing routine capable to separate cryoseisms from other seismic events and noise in continuous seismic data. In our study, we present an algorithm for identification of cryoseisms that is based on classical STA/LTA algorithm for seismic event detection and neural network for their classification using selected characteristics of the records.</p><p>To access characteristics of cryoseisms, we used 3-component recordings of a swarm of strong cryoseismic events with similar waveforms that were registered on 06.06.2016 by seismic station OUL in northern Finland. The strongest event from the swarm produced a fracture on the road surface and damaged basements of buildings in the municipality of Oulu. Assuming that all events in the swarm were caused by the same mechanism (freezing of water-saturated soil), we used them as a learning sample for the neural network. Analysis of these events has shown that most of them have many similarities in selected records characteristics (central frequencies, duration etc.) with the strongest event and with each other. Application of this algorithm to the continuous seismic data recorded since the end of November 2015 to the end of February 2016, showed that the number of cryoseisms per day strongly correlates with variations of air temperature.</p>

scholarly journals Projected changes in persistent extreme summer weather events: The role of quasi-resonant amplification

2018 ◽  
Vol 4 (10) ◽  
pp. eaat3272 ◽  
Author(s):  
Michael E. Mann ◽  
Stefan Rahmstorf ◽  
Kai Kornhuber ◽  
Byron A. Steinman ◽  
Sonya K. Miller ◽  
...  
Keyword(s):  
Radiative Forcing ◽  
Climate Models ◽  
Climate Model ◽  
Coupled Model ◽  
High Amplitude ◽  
Extreme Weather ◽  
Extreme Weather Events ◽  
Anthropogenic Aerosols ◽  
Pronounced Increase ◽  
Weather Events

Persistent episodes of extreme weather in the Northern Hemisphere summer have been associated with high-amplitude quasi-stationary atmospheric Rossby waves, with zonal wave numbers 6 to 8 resulting from the phenomenon of quasi-resonant amplification (QRA). A fingerprint for the occurrence of QRA can be defined in terms of the zonally averaged surface temperature field. Examining state-of-the-art [Coupled Model Intercomparison Project Phase 5 (CMIP5)] climate model projections, we find that QRA events are likely to increase by ~50% this century under business-as-usual carbon emissions, but there is considerable variation among climate models. Some predict a near tripling of QRA events by the end of the century, while others predict a potential decrease. Models with amplified Arctic warming yield the most pronounced increase in QRA events. The projections are strongly dependent on assumptions regarding the nature of changes in radiative forcing associated with anthropogenic aerosols over the next century. One implication of our findings is that a reduction in midlatitude aerosol loading could actually lead to Arctic de-amplification this century, ameliorating potential increases in persistent extreme weather events.

scholarly journals Multiple Ecosystem Effects of Extreme Weather Events in the Arctic

Ecosystems ◽  
2020 ◽  
Author(s):  
T. R. Christensen ◽  
M. Lund ◽  
K. Skov ◽  
J. Abermann ◽  
E. López-Blanco ◽  
...  
Keyword(s):  
Extreme Weather ◽  
The Arctic ◽  
Extreme Weather Events ◽  
Ecosystem Effects ◽  
Weather Events

scholarly journals How do intermittency and simultaneous processes obfuscate the Arctic influence on midlatitude winter extreme weather events?

2021 ◽  
Author(s):  
James E Overland ◽  
Thomas J. Ballinger ◽  
Judah Cohen ◽  
Jennifer A. Francis ◽  
Edward Hanna ◽  
...  
Keyword(s):  
Extreme Weather ◽  
The Arctic ◽  
Extreme Weather Events ◽  
Weather Events

scholarly journals Population dynamics of an island population of water voles Arvicola amphibius (Linnaeus, 1758) with one major predator, the eagle owl Bubo bubo (Linnaeus, 1758), in northern Norway

Polar Biology ◽  
2021 ◽  
Author(s):  
Karl Frafjord
Keyword(s):  
Population Dynamics ◽  
Extreme Weather ◽  
The Arctic ◽  
Extreme Weather Events ◽  
Sheep Grazing ◽  
Bubo Bubo ◽  
Northern Norway ◽  
Arvicola Amphibius ◽  
Weather Events ◽  
Eagle Owl

AbstractPredator–prey relationships are of great significance to ecosystems, and their effects on the population dynamics of voles and lemmings (Microtinae) in Boreal and Arctic environments have long been of particular interest. A simple ecosystem with one major prey and one major predator could be an ideal setting for a study of their interactions. This is the situation on several small islands on the coast of northern Norway just below the Arctic Circle, with populations of water voles Arvicola amphibius preyed upon by the eagle owl Bubo bubo. The population dynamics of the water vole was studied by trapping and tagging in 2003–2018, eagle owl pellets were collected for analyses, eagle owl breeding attempts were recorded, and some weather variables collected from official recordings. After having been introduced well into the study period, the number of sheep Ovis aries was also recorded. Water voles were the main prey of the eagle owl, with 89% occurrence in pellets, with an overrepresentation of adults and males. Both predation, sheep grazing and extreme weather events influenced the vole population. Predator exclusion, as happened in three summers due to an intensive radio tracking study, especially increased the number of surviving young (in particular from the early cohorts) and the mass of adults. Extreme weather events, such as flooding in summer and deeply frozen ground in winter, most significantly reduced vole populations. Sheep grazing may exacerbate the effects of predation. A similar multitude of factors may affect populations of other rodent species as well.

scholarly journals Integrating archival analysis, observational data, and climate projections to assess extreme event impacts in Alaska

2020 ◽  
Vol 163 (2) ◽  
pp. 669-687
Author(s):  
Nathan P. Kettle ◽  
John E. Walsh ◽  
Lindsey Heaney ◽  
Richard L. Thoman ◽  
Kyle Redilla ◽  
...  
Keyword(s):  
Observational Data ◽  
Information Needs ◽  
Climate Model ◽  
Climate Adaptation ◽  
Extreme Event ◽  
Extreme Weather ◽  
The Arctic ◽  
Extreme Weather Events ◽  
Climate Projections ◽  
Weather Events

AbstractUnderstanding potential risks, vulnerabilities, and impacts to weather extremes and climate change are key information needs for coastal planners and managers in support of climate adaptation. Assessing historical trends and potential socio-economic impacts is especially difficult in the Arctic given limitations on availability of weather observations and historical impacts. This study utilizes a novel interdisciplinary approach that integrates archival analysis, observational data, and climate model downscaling to synthesize information on historical and projected impacts of extreme weather events in Nome, Alaska. Over 300 impacts (1990–2018) are identified based on analyses of the Nome Nugget newspaper articles and Storm Data entries. Historical impacts centered on transportation, community activities, and utilities. Analysis of observed and ERA5 reanalysis data indicates that impacts are frequently associated with high wind, extreme low temperatures, heavy snowfall events, and winter days above freezing. Downscaled output (2020–2100) from two climate models suggests that there will be changes in the frequency and timing of these extreme weather events. For example, extreme cold temperature is projected to decrease through the 2040s and then rarely occurs afterwards, and extreme wind events show little change before the 2070s. Significantly, our findings also reveal that not all weather-related extremes will change monotonically throughout the twenty-first century, such as extreme snowfall events that will increase through the 2030s before declining in the 2040s. The dynamical nature of projected changes in extreme events has implications for climate adaptation planning.

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