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contributor authorDrosdowsky, Wasyl
contributor authorWheeler, Matthew C.
date accessioned2017-06-09T17:36:26Z
date available2017-06-09T17:36:26Z
date copyright2014/02/01
date issued2013
identifier issn0882-8156
identifier otherams-87975.pdf
identifier urihttp://onlinelibrary.yabesh.ir/handle/yetl/4231703
description abstractforecast product focusing on the onset of the north Australian wet season using a dynamical ocean?atmosphere model is developed and verified. Onset is defined to occur when a threshold rainfall accumulation of 50 mm is reached from 1 September. This amount has been shown to be useful for agricultural applications, as it is about what is required to generate new plant growth after the usually dry period of June?August. The normal (median) onset date occurs first around Darwin in the north and Cairns in the east in late October, and is progressively later for locations farther inland away from these locations. However, there is significant interannual variability in the onset, and skillful predictions of this can be valuable. The potential of the Predictive Ocean?Atmosphere Model for Australia (POAMA), version 2, for making probabilistic predictions of onset, derived from its multimember ensemble, is shown. Using 50 yr of hindcasts, POAMA is found to skillfully predict the variability of onset, despite a generally dry bias, with the ?percent correct? exceeding 70% over about a third of the Northern Territory. In comparison to a previously developed statistical method based solely on El Niño?Southern Oscillation, the POAMA system shows improved skill scores, suggesting that it gains from additional sources of predictability. However, the POAMA hindcasts do not reproduce the observed long-term trend in onset dates over inland regions to an earlier date despite being initialized with the observed warming ocean temperatures. Understanding and modeling this trend should lead to further enhancements in skill.
publisherAmerican Meteorological Society
titlePredicting the Onset of the North Australian Wet Season with the POAMA Dynamical Prediction System
typeJournal Paper
journal volume29
journal issue1
journal titleWeather and Forecasting
identifier doi10.1175/WAF-D-13-00091.1
journal fristpage150
journal lastpage161
treeWeather and Forecasting:;2013:;volume( 029 ):;issue: 001
contenttypeFulltext


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