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Pearl City, HI, United States

Reid J.S.,U.S. Navy | Xian P.,U.S. Navy | Hyer E.J.,U.S. Navy | Flatau M.K.,U.S. Navy | And 6 more authors.
Atmospheric Chemistry and Physics | Year: 2012

Much research and speculation exists about the meteorological and climatological impacts of biomass burning in the Maritime Continent (MC) of Indonesia and Malaysia, particularly during El Nino events. However, the MC hosts some of the world's most complicated meteorology, and we wish to understand how tropical phenomena at a range of scales influence observed burning activity. Using Moderate Resolution Imaging Spectroradiometer (MODIS) derived active fire hotspot patterns coupled with aerosol data assimilation products, satellite based precipitation, and meteorological indices, the meteorological context of observed fire prevalence and smoke optical depth in the MC are examined. Relationships of burning and smoke transport to such meteorological and climatic factors as the interannual El Nino-Southern Oscillation (ENSO), El Nino Modoki, Indian Ocean Dipole (IOD), the seasonal migration of the Intertropical Convergence Zone, the 30-90 day Madden Julian Oscillation (MJO), tropical waves, tropical cyclone activity, and diurnal convection were investigated. A conceptual model of how all of the differing meteorological scales affect fire activity is presented. Each island and its internal geography have different sensitivities to these factors which are likely relatable to precipitation patterns and land use practices. At the broadest scales as previously reported, we corroborate ENSO is indeed the largest factor. However, burning is also enhanced by periods of El Nino Modoki. Conversely, IOD influences are unclear. While interannual phenomena correlate to total seasonal burning, the MJO largely controls when visible burning occurs. High frequency phenomena which are poorly constrained in models such as diurnal convection and tropical cyclone activity also have an impact which cannot be ignored. Finally, we emphasize that these phenomena not only influence burning, but also the observability of burning, further complicating our ability to assign reasonable emissions. © 2012 Author(s).

Shieh O.H.,National Disaster Preparedness Training Center | Fiorino M.,National Oceanic and Atmospheric Administration | Kucas M.E.,Joint Typhoon Warning Center | Wang B.,University of Hawaii at Manoa
Weather and Forecasting | Year: 2013

One of the primary challenges for both tropical cyclone (TC) research and forecasting is the problem of intensity change. Accurately forecasting TC rapid intensification (RI) is particularly important to interests along coastlines and shipping routes, which are vulnerable to storm surge and heavy seas induced by intense tropical cyclones. One particular RI event in the western North Pacific Ocean with important scientific implications is the explosive deepening of Typhoon Vicente (2012). Vicente underwent extreme RI in the northern South China Sea just prior to landfall west of Hong Kong, China, with maximum sustained winds increasing from 50 kt (1 kt 5 0.51ms21) at 0000 UTC 23 July to 115 kt at 1500 UTC 23 July. This increase of 65 kt in 15 h far exceeds established thresholds for TC RI. Just prior to this RI episode, Vicente exhibited a near-908 poleward track shift. The relationship between the track and intensity change is described, and the authors speculate that the passage of an upper-tropospheric (UT) ''inverted'' trough was a significant influence. An analysis of real-time numerical model guidance is provided and is discussed from an operational perspective, and high-resolution global model analyses are evaluated. Numerical model forecasts of the UT trough interaction with the TC circulation were determined to be a shortcoming that contributed to the intensity prediction errors for Vicente. This case study discusses the importance of considering UT features in TC intensity forecasting and establishes current modeling capabilities for future research. © 2013 American Meteorological Society.

Knaff J.A.,The Center for Satellite Applications and Research | Slocum C.J.,Colorado State University | Musgrave K.D.,Colorado State University | Sampson C.R.,U.S. Navy | Strahl B.R.,Joint Typhoon Warning Center
Monthly Weather Review | Year: 2016

A relatively simple method to estimate tropical cyclone (TC) wind radii from routinely available information including storm data (location, motion, and intensity) and TC size is introduced. The method is based on a combination of techniques presented in previous works and makes an assumption that TCs are largely symmetric and that asymmetries are based solely on storm motion and location. The method was applied to TC size estimates from two sources: Infrared satellite imagery and global model analyses. The validation shows that the methodology is comparable with other objective methods based on the error statistics. The technique has a variety of practical research and operational applications, some of which are also discussed. © 2016 American Meteorological Society.

Sampson C.R.,U.S. Navy | Schumacher A.B.,Colorado State University | Knaff J.A.,National Oceanic and Atmospheric Administration | DeMaria M.,National Oceanic and Atmospheric Administration | And 5 more authors.
Weather and Forecasting | Year: 2012

The Department of Defense uses a Tropical Cyclone Conditions of Readiness (TC-CORs) systemto prepare bases and evacuate assets and personnel in advance of adverse weather associated with tropical cyclones (TCs). TC-CORs are recommended by weather facilities either on base or at central sites and generally are related to the timing and potential for destructive (50 kt; 1 kt ≈ 0.5144 m s -1) sustained winds. Recommendations are then considered by base or area commanders along with other factors for setting the TC-CORs. Ideally, the TC-CORs are set sequentially, from TC-COR IV (destructive winds within 72 h), through TC-COR III (destructive winds within 48 h) and TC-COR II (destructive winds within 24 h), and finally to TC-COR I (destructive winds within 12 h), if needed. Each TC-COR, once set, initiates a series of preparations and actions. Preparations for TC-COR IV can be as unobtrusive as obtaining emergency supplies, while preparations and actions leading up to TC-COR I are generally far more costly, intrusive, and labor-intensive activities. The purpose of this paper is to describe an objective aid that provides TC-COR guidance for meteorologists to use when making recommendations to base commanders. The TC-COR guidance is based on wind probability thresholds from an operational wind probability product run at the U.S. tropical cyclone forecast centers. An analysis on 113 independent cases from various bases shows the skill of the objective aid and how well it compares with the operational TC-CORs. A sensitivity analysis is also performed to demonstrate some of the advantages and pitfalls of raising or lowering the wind probability thresholds used by this objective aid. © 2012 American Meteorological Society.

News Article | April 19, 2016
Site: www.rdmag.com

Three NASA satellites provided data on powerful Tropical Cyclone Fantala as it lingered north of Madagascar in the Southern Indian Ocean. NASA-NOAA's Soumi NPP satellite provided a night-time and infrared view, NASA's Aqua satellite provided a look at cloud top temperatures and extent, and NASA-JAXA's Global Precipitation Measurement or GPM core satellite measured the storm's intense rainfall. On April 17, 2016 Fantala's estimated maximum sustained winds reached 150 knots (173 mph) making it the most powerful South Indian Ocean tropical Cyclone of 2016. This increase in intensity made Fantala a category five tropical cyclone on the Saffir-Simpson Hurricane wind scale. Two images of Super Tropical Cyclone Fantala were taken from the Visible Infrared Imaging Radiometer Suite (VIIRS) instrument aboard NOAA-NASA's Suomi NPP satellite on April 17. A night-time view and infrared view both showed the 16-nautical-mile-wide eye. The infrared image was false-colored and showed powerful thunderstorms circling the center. Fantala became this powerful while moving over the open waters of the South Indian Ocean to a position north of Madagascar. GPM's Microwave Imager (GMI) and Dual-Frequency Precipitation Radar (DPR) data were used to show the locations and intensity of precipitation within Fantala. The GPM core observatory satellite flew above tropical cyclone Fantala's eye on April 16, 2016 when the tropical cyclone had winds of 130 knots (150 mph). At that time rain was measured by GPM's radar (DPR) falling at an extreme rate of close to 300 mm (11.8 inches) per hour in the southwestern side of Fantala's eye wall. The powerful storms located there were found by GPM's radar (DPR) to reach heights of almost 16 km (9.9 miles). The GPM core observatory satellite had another fairly good view of extremely powerful tropical cyclone Fantala on April 18, 2016 at 0126 UTC (Apr. 17 at 9:26 p.m. EDT) when maximum sustained winds were estimated at 150 knots (173 mph). This satellite view showed that Fantala was dropping very heavy rain over large areas of the Indian Ocean north of Madagascar. Data from GPM's GMI were used to estimate that rain was falling at a rate of over 65 mm (2.6 inches) southwest of the tropical Cyclone's eye. GPM's radar (DPR) found rain falling at over 186 mm (7.3 inches) per hour in an intense feeder band on the eastern side of the tropical cyclone. Two false-colored infrared images of Fantala from the Atmospheric Infrared Sounder or AIRS instrument that flies aboard NASA's Aqua satellite were taken on Apr. 17 and Apr. 18. In this infrared temperature data from both days, AIRS showed cloud top temperatures of thunderstorms in the storm's eyewall colder than -81.6 (-63.1C). These storms have the potential to generate heavy rainfall, which was identified in the GPM data. By April 19, 2016 at 0900 UTC (5 a.m. EDT), Fantala finally weakened a Category 3 hurricane on the Saffir-Simpson Scale, from a Category 5. Currently, maximum sustained winds were near 105 knots (120.8 mph/194.5 kph) and continued to weaken. The storm has already curved to the east-southeast and was moving at 4 knots (4.6 mph/7.4 kph). It was centered near 9.3 degrees south and 50.0 degrees east, about 774 miles northwest of Port Louis, Mauritius. The Joint Typhoon Warning Center noted that the storm will track to the southeast for the next couple of days before turning back to the west, and toward Madagascar.

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