3 results
6 - System Evaluation
- Edited by Tom Carrieres, Mark Buehner, Jean-Franҫois Lemieux, Leif Toudal Pedersen, Technical University of Denmark, Lyngby
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- Book:
- Sea Ice Analysis and Forecasting
- Published online:
- 12 October 2017
- Print publication:
- 05 October 2017, pp 144-173
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Summary
Sea ice APS evaluation builds on techniques developed for other applications, but presents some additional challenges due to the nature of sea ice itself and observational limitations.While APS predict ice conditions as continuous, sometimes bounded quantities, verifying observations may only be available as categorical quantities, which necessitates the use of contingency tables. Evaluation of continuous scalars, such as ice concentration and thickness, uses common statistical measures such as bias and variance. Sea ice velocity and ice edge require specialized evaluation approaches which account for their spatial characteristics. Several aspects of sea ice evaluation practice remain as challenges for future developments in sea ice and evaluation research.
5 - Automated Sea Ice Prediction Systems
- Edited by Tom Carrieres, Mark Buehner, Jean-Franҫois Lemieux, Leif Toudal Pedersen, Technical University of Denmark, Lyngby
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- Book:
- Sea Ice Analysis and Forecasting
- Published online:
- 12 October 2017
- Print publication:
- 05 October 2017, pp 109-143
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Summary
A number of sea ice automated prediction systems are currently providing operational output to national ice service organizations. The Los Alamos CICE sea ice model is widely used in these systems but there is more variety in other areas, such as ocean forcing and model initialization. RIPS is a regional implementation of CICE that supports the CIS and includes a sophisticated 3DVar data assimilation system and a number of other innovations. GIOPS is a global ice-ocean prediction system that has been developed in close collaboration with Mercator-Ocean and satisfies a growing need in Canada for a multi-purpose global marine core service. TOPAZ is the Arctic regional component of the Copernicus Marine Environment Monitoring Service and uses the HYCOM ocean model and LIM sea ice model with an Ensemble Kalman Filter (EnKF) data assimilation system. The ACNFS/GOFS system supports the NIC and its global mandate using the CICE sea ice model and the HyCom ocean model. CanSIPS targets Canadian marine clients by providing extended range forecasts using of an global ensemble fully coupled atmosphere-ice-ocean model.
Chapter 3 - Changes in Climate Extremes and their Impacts on the Natural Physical Environment
- from Section III
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- By Sonia I. Seneviratne, Neville Nicholls, David Easterling, Clare M. Goodess, Shinjiro Kanae, James Kossin, Yali Luo, Jose Marengo, Kathleen McInnes, Mohammad Rahimi, Markus Reichstein, Asgeir Sorteberg, Carolina Vera, Xuebin Zhang, Matilde Rusticucci, Vladimir Semenov, Lisa V. Alexander, Simon Allen, Gerardo Benito, Tereza Cavazos, John Clague, Declan Conway, Paul M. Della-Marta, Markus Gerber, Sunling Gong, B. N. Goswami, Mark Hemer, Christian Huggel, Bart van den Hurk, Viatcheslav V. Kharin, Akio Kitoh, Albert M.G. Klein Tank, Guilong Li, Simon Mason, William McGuire, Geert Jan van Oldenborgh, Boris Orlowsky, Sharon Smith, Wassila Thiaw, Adonis Velegrakis, Pascal Yiou, Tingjun Zhang, Tianjun Zhou, Francis W. Zwiers
- Edited by Christopher B. Field, Vicente Barros, Thomas F. Stocker, Qin Dahe
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- Book:
- Managing the Risks of Extreme Events and Disasters to Advance Climate Change Adaptation
- Published online:
- 05 August 2012
- Print publication:
- 28 May 2012, pp 109-230
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Summary
Executive Summary
This chapter addresses changes in weather and climate events relevant to extreme impacts and disasters. An extreme (weather or climate) event is generally defined as the occurrence of a value of a weather or climate variable above (or below) a threshold value near the upper (or lower) ends (‘tails’) of the range of observed values of the variable. Some climate extremes (e.g., droughts, floods) may be the result of an accumulation of weather or climate events that are, individually, not extreme themselves (though their accumulation is extreme). As well, weather or climate events, even if not extreme in a statistical sense, can still lead to extreme conditions or impacts, either by crossing a critical threshold in a social, ecological, or physical system, or by occurring simultaneously with other events. A weather system such as a tropical cyclone can have an extreme impact, depending on where and when it approaches landfall, even if the specific cyclone is not extreme relative to other tropical cyclones. Conversely, not all extremes necessarily lead to serious impacts. [3.1]
Many weather and climate extremes are the result of natural climate variability (including phenomena such as El Niño), and natural decadal or multi-decadal variations in the climate provide the backdrop for anthropogenic climate changes. Even if there were no anthropogenic changes in climate, a wide variety of natural weather and climate extremes would still occur. [3.1]
A changing climate leads to changes in the frequency, intensity, spatial extent, duration, and timing of weather and climate extremes, and can result in unprecedented extremes. Changes in extremes can also be directly related to changes in mean climate, because mean future conditions in some variables are projected to lie within the tails of present-day conditions. Nevertheless, changes in extremes of a climate or weather variable are not always related in a simple way to changes in the mean of the same variable, and in some cases can be of opposite sign to a change in the mean of the variable. Changes in phenomena such as the El Nino-Southern Oscillation or monsoons could affect the frequency and intensity of extremes in several regions simultaneously. [3.1]