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Beata Latos, Thierry Lefort, Maria K. Flatau, Piotr J. Flatau, Donaldi S. Permana, Dariusz B. Baranowski, Jaka A. I. Paski, Erwin Makmur, Eko Sulystyo, Philippe Peyrillé, Zhe Feng, Adrian J. Matthews, and Jerome M. Schmidt

Lubis and Respati (2021) that CCKWs and CCERWs increase the probability of extreme rain events over Java, as well as Ferrett et al. (2019) who link extreme precipitation in both the western and eastern parts of the Maritime Continent with high-amplitude Kelvin waves. Our results suggest that it is possible to improve operational forecasting of extreme precipitation and floods by considering the dynamics of convectively coupled equatorially trapped waves. Acknowledgments This research has been

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Ewan Short, Claire L. Vincent, and Todd P. Lane

0400 and 0700 LST. Propagation behavior was explained in terms of the land–sea breeze. Hassim et al. (2016) and Vincent and Lane (2016a) examined the diurnal cycle of precipitation around New Guinea using the Weather Research and Forecasting (WRF) Model and satellite precipitation radar data. They found that precipitation associated with convective clouds propagated offshore at two distinct speeds. Within 100–200 km of the coast, precipitation propagated at with density currents associated

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Casey R. Densmore, Elizabeth R. Sanabia, and Bradford S. Barrett

, hereafter WH04 ) Real-time Multivariate MJO (RMM) index. This index is freely available for download from the Australian Bureau of Meteorology ( www.bom.gov.au/climate/mjo/ ). The WH04 RMM index uses an EOF analysis of lower- (850 hPa) and upper-level (200 hPa) zonal winds, and outgoing longwave radiation (OLR) to identify primarily the strength and location of the enhanced convective envelope of the MJO (hereafter the active envelope). The RMM index is used widely in operational settings because of

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