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[] The predictability of Northern Hemispheric blocking events using an ensemble mean forecast system.

1 Department of Soil, Environmental, and Atmospheric Sciences, University of Missouri, Columbia, MO, USA
2 Department of Mathematics and Meteorology, Northland College, Ashland, WI, USA
* Author to whom correspondence should be addressed.
17 July 2017
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Abstract

Some weather extremes can be the result of atmospheric blocking, which can be responsible for the the stagnation of weather patterns. These large-scale quasi-stationary mid-latitude flow regimes can result in significant temperature and precipitation anomalies in the regions that the blocking event impacts. The ability to predict periods of anomalous weather conditions due to atmospheric blocking is a major problem for medium-range forecasting. Analyzing the NCEP Ensemble 500-mb pressure heights (240 hrs.) ten-day forecasts, and using the University of Missouri blocking archive to identify blocking event, the forecasted duration and intensity of model blocking events are compared to observed blocks. Comparing these differences using four case studies occurring over a one-year period across the Northern Hemisphere has shown the continued need for improvement of the duration and intensity of blocking events. Additionally, a comparison of the block intensity to a diagnostic known as the Integrated Regional Enstrophy (IRE) was performed in order to determine if there is a correlation between these quantities. Having a better understanding of knowing how long each block will last and their associated anomalies can help society prepare for the damage they can cause. Knowing how to correctly identify blocks is important in improving forecast issues.

Keywords

ensembles, integrated regional enstrophy, block formation, block intensity, prediction

Cite this article as

Reynolds, D.; Lupo, A.; Jensen, A.; Market, P. The predictability of Northern Hemispheric blocking events using an ensemble mean forecast system.. In Proceedings of the 2nd Int. Electron. Conf. Atmos. Sci., 16–31 July 2017; Sciforum Electronic Conference Series, Vol. 2, 2017 ; doi:10.3390/ecas2017-04128

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Copyright by the author(s). This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC-BY) license (http://creativecommons.org/licenses/by/4.0/).

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