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John E. Janowiak, Peter Bauer, Wanqiu Wang, Phillip A. Arkin, and Jon Gottschalck

GPCP analyses. Similarly, all of the model forecasts have biases of 1–3 mm day −1 in the zonal band between 50° and 60°S latitude relative to CMORPH but again are near zero relative to GPCP. We have more trust in the CMORPH data in this region because the region is mostly ocean and CMORPH has much passive microwave information here than do the GPCP analyses. Bias is less in the Southern Hemisphere compared to the Northern Hemisphere, although that may because the study period occurs during the

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Ronald Gelaro, Rolf H. Langland, Simon Pellerin, and Ricardo Todling

sensitivity in all forecast systems, although the amplitudes differ in some locations. The areas of maximum sensitivity are concentrated over the Northern (winter) Hemisphere midlatitude storm tracks, with secondary maxima over the subtropical eastern Pacific Ocean and southwestern United States. The Pacific storm track maximum is somewhat stronger in GDPS than in NOGAPS and GEOS-5, while the Atlantic storm track maximum is somewhat weaker. In the Southern Hemisphere, all forecast systems show a localized

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Sharanya J. Majumdar, Kathryn J. Sellwood, Daniel Hodyss, Zoltan Toth, and Yucheng Song

1. Introduction The global atmospheric observational network has traditionally comprised land-based rawinsonde balloons and satellite-borne sensors. Yet, as stated by Lorenz and Emanuel (1998) , “ … despite this wealth of data—more, in fact, than we know how to use to full advantage—large gaps remain in our picture of the global weather pattern, particularly over the less frequently visited areas of the oceans.” In an effort to fill these gaps, several field campaigns have taken place over the

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William A. Komaromi, Sharanya J. Majumdar, and Eric D. Rappin

slowly northward and posing a potential threat to Taiwan ( Fig. 2a ). Sinlaku is situated in between two large deep-layer anticyclones: one over China and the other over the western North Pacific Ocean ( Fig. 2b ). The lack of a dominant steering flow contributed to the large spread in the 5-day ECMWF ensemble forecasts of Sinlaku ( Fig. 2c ). Several of the deterministic forecasts produced a 5-day forecast over 500 km to the east of the actual track, with recurvature occurring by 4 days, 2 days too

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Benoît Vié, Olivier Nuissier, and Véronique Ducrocq

showed that initial differences can grow and propagate to affect the whole domain in a few hours. Few works have assessed the behavior of cloud-resolving ensembles in terms of probabilistic forecasts based upon a long evaluation period. During April–June 2007, as part of the National Oceanic and Atmospheric Administration (NOAA) Hazardous Weather Test Bed Spring Experiment, a real-time convection-resolving (4-km grid mesh) ensemble experiment was conducted ( Kong et al. 2007 ). The ensemble

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Warren J. Tennant, Glenn J. Shutts, Alberto Arribas, and Simon A. Thompson

decrease in the RMSE of the EM, most notable in the upper-tropospheric winds in the tropics and Southern Hemisphere ( Fig. 2 ), approaching 90% significance at 3-days’ lead in the tropics. This could be partly a result from replacing the SKEB1 where perturbations were based solely on the kinetic energy of the flow and may not have always been physically realistic, thus adding excessive noise to the system. However, the results do show that the SKEB2 perturbations have made a widespread overall

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E. A. Irvine, S. L. Gray, J. Methven, and I. A. Renfrew

Distortion Experiment (GFDex) included a field campaign that took place in February and March 2007. The aim was to advance our understanding of the flow deformation by Greenland and its effect on downstream predictability ( Renfrew et al. 2008 ). A specific objective of the campaign was to make targeted observations in the region around southern Greenland and Iceland with the aim of improving the 24–48-h weather forecasts over northern Europe. Targeted observations were made for four different cases, the

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Elizabeth Satterfield and Istvan Szunyogh

reflect the local observation density: the uncertainty is underestimated in regions of high observation density, such as Europe, Japan, and the United States, and overestimated in regions of lower observational density, such as the Southern Hemisphere and the oceanic regions. This result is an indication that our zonally constant covariance inflation factor cannot be tuned to be optimal everywhere when there are zonal changes in observation density. Thus, we conjecture that implementing a spatially

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Thomas M. Hamill, Jeffrey S. Whitaker, Michael Fiorino, and Stanley G. Benjamin

. Meanwhile, improving the accuracy of intensity forecasts has proven much more difficult ( Bender and Ginis 2000 ; Krishnamurti et al. 2005 ; Rogers et al. 2006 ; Li and Pu 2008 ; Rappaport et al. 2009 ). The National Oceanic and Atmospheric Administration (NOAA) Hurricane Forecast Improvement Project (HFIP; see online at www.nrc.noaa.gov/plans_docs/HFIP_Plan_073108.pdf ) was initiated to 1) improve the accuracy and reliability of hurricane forecasts, 2) extend the forecast lead time for

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Munehiko Yamaguchi and Sharanya J. Majumdar

) over the northwestern Pacific Ocean east of Luzon Island, Philippines, at 0000 UTC 8 September 2008. Moving toward the north-northwest, it was upgraded to tropical storm (TS) intensity over the same waters at 1800 UTC that day. Keeping its north-northwestward track, Sinlaku was upgraded to typhoon (TY) intensity and reached its peak intensity with maximum sustained winds of 100 kt and a central pressure of 935 hPa over the sea northeast of Luzon Island at 1200 UTC 10 September. Weakening its

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