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Pedro A. Jimenez, Jordi Vila-Guerau de Arellano, Jorge Navarro, and J. Fidel Gonzalez-Rouco
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Juan C. Acosta Navarro, Pablo Ortega, Javier García-Serrano, Virginie Guemas, Etienne Tourigny, Rubén Cruz-García, François Massonnet, and Francisco J. Doblas-Reyes
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Svetla M. Hristova-Veleva, P. Peggy Li, Brian Knosp, Quoc Vu, F. Joseph Turk, William L. Poulsen, Ziad Haddad, Bjorn Lambrigtsen, Bryan W. Stiles, Tsae-Pyng Shen, Noppasin Niamsuwan, Simone Tanelli, Ousmane Sy, Eun-Kyoung Seo, Hui Su, Deborah G. Vane, Yi Chao, Philip S. Callahan, R. Scott Dunbar, Michael Montgomery, Mark Boothe, Vijay Tallapragada, Samuel Trahan, Anthony J. Wimmers, Robert Holz, Jeffrey S. Reid, Frank Marks, Tomislava Vukicevic, Saiprasanth Bhalachandran, Hua Leighton, Sundararaman Gopalakrishnan, Andres Navarro, and Francisco J. Tapiador

Abstract

Tropical cyclones (TCs) are among the most destructive natural phenomena with huge societal and economic impact. They form and evolve as the result of complex multiscale processes and nonlinear interactions. Even today the understanding and modeling of these processes is still lacking. A major goal of NASA is to bring the wealth of satellite and airborne observations to bear on addressing the unresolved scientific questions and improving our forecast models. Despite their significant amount, these observations are still underutilized in hurricane research and operations due to the complexity associated with finding and bringing together semicoincident and semicontemporaneous multiparameter data that are needed to describe the multiscale TC processes. Such data are traditionally archived in different formats, with different spatiotemporal resolution, across multiple databases, and hosted by various agencies. To address this shortcoming, NASA supported the development of the Jet Propulsion Laboratory (JPL) Tropical Cyclone Information System (TCIS)—a data analytic framework that integrates model forecasts with multiparameter satellite and airborne observations, providing interactive visualization and online analysis tools. TCIS supports interrogation of a large number of atmospheric and ocean variables, allowing for quick investigation of the structure of the tropical storms and their environments. This paper provides an overview of the TCIS’s components and features. It also summarizes recent pilot studies, providing examples of how the TCIS has inspired new research, helping to increase our understanding of TCs. The goal is to encourage more users to take full advantage of the novel capabilities. TCIS allows atmospheric scientists to focus on new ideas and concepts rather than painstakingly gathering data scattered over several agencies.

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Eric J. Jensen, Leonhard Pfister, David E. Jordan, Thaopaul V. Bui, Rei Ueyama, Hanwant B. Singh, Troy D. Thornberry, Andrew W. Rollins, Ru-Shan Gao, David W. Fahey, Karen H. Rosenlof, James W. Elkins, Glenn S. Diskin, Joshua P. DiGangi, R. Paul Lawson, Sarah Woods, Elliot L. Atlas, Maria A. Navarro Rodriguez, Steven C. Wofsy, Jasna Pittman, Charles G. Bardeen, Owen B. Toon, Bruce C. Kindel, Paul A. Newman, Matthew J. McGill, Dennis L. Hlavka, Leslie R. Lait, Mark R. Schoeberl, John W. Bergman, Henry B. Selkirk, M. Joan Alexander, Ji-Eun Kim, Boon H. Lim, Jochen Stutz, and Klaus Pfeilsticker

Abstract

The February–March 2014 deployment of the National Aeronautics and Space Administration (NASA) Airborne Tropical Tropopause Experiment (ATTREX) provided unique in situ measurements in the western Pacific tropical tropopause layer (TTL). Six flights were conducted from Guam with the long-range, high-altitude, unmanned Global Hawk aircraft. The ATTREX Global Hawk payload provided measurements of water vapor, meteorological conditions, cloud properties, tracer and chemical radical concentrations, and radiative fluxes. The campaign was partially coincident with the Convective Transport of Active Species in the Tropics (CONTRAST) and the Coordinated Airborne Studies in the Tropics (CAST) airborne campaigns based in Guam using lower-altitude aircraft (see companion articles in this issue). The ATTREX dataset is being used for investigations of TTL cloud, transport, dynamical, and chemical processes, as well as for evaluation and improvement of global-model representations of TTL processes. The ATTREX data are publicly available online (at https://espoarchive.nasa.gov/).

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