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contributor authorKumar, Arun
contributor authorChen, Mingyue
date accessioned2017-06-09T17:32:57Z
date available2017-06-09T17:32:57Z
date copyright2015/08/01
date issued2015
identifier issn0027-0644
identifier otherams-87078.pdf
identifier urihttp://onlinelibrary.yabesh.ir/handle/yetl/4230707
description abstractaced with the scenario when prediction skill is low, particularly in conjunction with long-range predictions, a commonly proposed solution is that an increase in ensemble size will rectify the issue of low skill. Although it is well known that an increase in ensemble size does lead to an increase in prediction skill, the general scope of this supposition, however, is that low prediction skill is not a consequence of constraints imposed by inherent predictability limits, but an artifact of small ensemble sizes, and further, increases in ensemble sizes (that are often limited by computational resources) are the major bottlenecks for improving long-range predictions. In proposing that larger ensemble sizes will remedy the issue of low skill, a fact that is not well appreciated is that for scenarios with high inherent predictability, a small ensemble size is sufficient to realize high predictability, while for scenarios with low inherent predictability, much larger ensemble sizes are needed to realize low predictability. In other words, requirements on ensemble size (to realize the inherent predictability) and inherent predictability are complementary variables. A perceived need for larger ensembles, therefore, may also imply the presence of low predictability.
publisherAmerican Meteorological Society
titleInherent Predictability, Requirements on the Ensemble Size, and Complementarity
typeJournal Paper
journal volume143
journal issue8
journal titleMonthly Weather Review
identifier doi10.1175/MWR-D-15-0022.1
journal fristpage3192
journal lastpage3203
treeMonthly Weather Review:;2015:;volume( 143 ):;issue: 008
contenttypeFulltext


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