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Nasa's Tropical Cloud Systems and Processes Experiment

Investigating Tropical Cyclogenesis and Hurricane Intensity Change

J. Halverson, M. Black, S. Braun, D. Cecil, M. Goodman, A. Heymsfield, G . Heymsfield, R. Hood, T. Krishnamurti, G. McFarquhar, M. J. Mahoney, J. Molinari, R. Rogers, J. Turk, C. Velden, D.-L. Zhang, E. Zipser, and R. Kakar

In July 2005, the National Aeronautics and Space Administration investigated tropical cyclogenesis, hurricane structure, and intensity change in the eastern North Pacific and western Atlantic using its ER-2 high-altitude research aircraft. The campaign, called the Tropical Cloud Systems and Processes (TCSP) experiment, was conducted in conjunction with the National Oceanic and Atmospheric Administration/Hurricane Research Division's Intensity Forecasting Experiment. A number of in situ and remote sensor datasets were collected inside and above four tropical cyclones representing a broad spectrum of tropical cyclone intensity and development in diverse environments. While the TCSP datasets directly address several key hypotheses governing tropical cyclone formation, including the role of vertical wind shear, dynamics of convective bursts, and upscale growth of the initial vortex, two of the storms sampled were also unusually strong, early season storms. Highlights from the genesis missions are described in this article, along with some of the unexpected results from the campaign. Interesting observations include an extremely intense, highly electrified convective tower in the eyewall of Hurricane Emily and a broad region of mesoscale subsidence detected in the lower stratosphere over landfalling Tropical Storm Gert.

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Gary A. Wick, Jason P. Dunion, Peter G. Black, John R. Walker, Ryan D. Torn, Andrew C. Kren, Altug Aksoy, Hui Christophersen, Lidia Cucurull, Brittany Dahl, Jason M. English, Kate Friedman, Tanya R. Peevey, Kathryn Sellwood, Jason A. Sippel, Vijay Tallapragada, James Taylor, Hongli Wang, Robbie E. Hood, and Philip Hall
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Gary A. Wick, Jason P. Dunion, Peter G. Black, John R. Walker, Ryan D. Torn, Andrew C. Kren, Altug Aksoy, Hui Christophersen, Lidia Cucurull, Brittany Dahl, Jason M. English, Kate Friedman, Tanya R. Peevey, Kathryn Sellwood, Jason A. Sippel, Vijay Tallapragada, James Taylor, Hongli Wang, Robbie E. Hood, and Philip Hall

Abstract

The National Oceanic and Atmospheric Administration’s (NOAA) Sensing Hazards with Operational Unmanned Technology (SHOUT) project evaluated the ability of observations from high-altitude unmanned aircraft to improve forecasts of high-impact weather events like tropical cyclones or mitigate potential degradation of forecasts in the event of a future gap in satellite coverage. During three field campaigns conducted in 2015 and 2016, the National Aeronautics and Space Administration (NASA) Global Hawk, instrumented with GPS dropwindsondes and remote sensors, flew 15 missions sampling 6 tropical cyclones and 3 winter storms. Missions were designed using novel techniques to target sampling regions where high model forecast uncertainty and a high sensitivity to additional observations existed. Data from the flights were examined in real time by operational forecasters, assimilated in operational weather forecast models, and applied postmission to a broad suite of data impact studies. Results from the analyses spanning different models and assimilation schemes, though limited in number, consistently demonstrate the potential for a positive forecast impact from the observations, both with and without a gap in satellite coverage. The analyses with the then-operational modeling system demonstrated large forecast improvements near 15% for tropical cyclone track at a 72-h lead time when the observations were added to the otherwise complete observing system. While future decisions regarding use of the Global Hawk platform will include budgetary considerations, and more observations are required to enhance statistical significance, the scientific results support the potential merit of the observations. This article provides an overview of the missions flown, observational approach, and highlights from the completed and ongoing data impact studies.

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L. M. Beal, J. Vialard, M. K. Roxy, J. Li, M. Andres, H. Annamalai, M. Feng, W. Han, R. Hood, T. Lee, M. Lengaigne, R. Lumpkin, Y. Masumoto, M. J. McPhaden, M. Ravichandran, T. Shinoda, B. M. Sloyan, P. G. Strutton, A. C. Subramanian, T. Tozuka, C. C. Ummenhofer, A. S. Unnikrishnan, J. Wiggert, L. Yu, L. Cheng, D. G. Desbruyères, and V. Parvathi

Abstract

The Indian Ocean Observing System (IndOOS), established in 2006, is a multinational network of sustained oceanic measurements that underpin understanding and forecasting of weather and climate for the Indian Ocean region and beyond. Almost one-third of humanity lives around the Indian Ocean, many in countries dependent on fisheries and rain-fed agriculture that are vulnerable to climate variability and extremes. The Indian Ocean alone has absorbed a quarter of the global oceanic heat uptake over the last two decades and the fate of this heat and its impact on future change is unknown. Climate models project accelerating sea level rise, more frequent extremes in monsoon rainfall, and decreasing oceanic productivity. In view of these new scientific challenges, a 3-yr international review of the IndOOS by more than 60 scientific experts now highlights the need for an enhanced observing network that can better meet societal challenges, and provide more reliable forecasts. Here we present core findings from this review, including the need for 1) chemical, biological, and ecosystem measurements alongside physical parameters; 2) expansion into the western tropics to improve understanding of the monsoon circulation; 3) better-resolved upper ocean processes to improve understanding of air–sea coupling and yield better subseasonal to seasonal predictions; and 4) expansion into key coastal regions and the deep ocean to better constrain the basinwide energy budget. These goals will require new agreements and partnerships with and among Indian Ocean rim countries, creating opportunities for them to enhance their monitoring and forecasting capacity as part of IndOOS-2.

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