An unusual number of tropical systems in the Atlantic, captured in this TCIS visualization, were all evolving simultaneously on 15 September during the record-breaking 2020 hurricane season.

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.

The goal of this study is to characterize the dynamics and structure of tropical cyclone formation from global model analyses to determine thresholds marking the various stages of development which can be computed from the analysis data. We introduce here a new methodology for identifying disturbances that show high likelihood of becoming a tropical depression or tropical storm. We use Lagrangian frame‐independent quantities to define intrinsic coordinates for candidate disturbances prior to and post tropical depression declaration in the best‐track data (HURDAT2). We use these Lagrangian quantities also as metrics for quantifying the strength of these systems within global model analyses as they are declared depressions, storms or hurricanes in HURDAT2. The criteria proposed are more precise than similar Eulerian criteria since the minimum thresholds for development in the best‐track dataset are very close to the threshold at which no false alarms are produced in the global model analyses. Since only very loose thermodynamic thresholds are required, these criteria can be considered dynamically based and require no statistical analysis to compensate for uncertainties in moisture or convection.We describe further the structure of the developing systems using a set of objective profiles where level contours of the Lagrangian averaged rotation rate are mapped to an equivalent radius. Composites of these profiles reveal that the transition to tropical storm strength vortices is marked by the existence of a notable shear sheath outside a region of enhanced solid‐body rotation.

An analysis is presented of the failed redevelopment of ex-Gaston during the 2010 PREDICT field campaign based on the European Centre for Medium Range Weather Forecast (ECMWF) analyses. We analyze the dynamics and kinematics of ex-Gaston to investigate the role of dry, environmental air in the failed redevelopment. The flow topology defined by the calculation of particle trajectories shows that ex-Gaston's pouch was vulnerable to dry, environmental air on all days of observations. As early as 12: 00 UTC 2 September 2010, a dry layer at and above 600 hPa results in a decrease in the vertical mass flux and vertical relative vorticity. These findings support the hypothesis that entrained, dry air near 600 hPa thwarted convective updraughts and vertical mass flux, which in turn led to a reduction in vorticity and a compromised pouch at these middle levels. A compromised pouch allows further intrusion of dry air and quenching of subsequent convection, therefore hindering vorticity amplification through vortex tube stretching. This study supports recent work investigating the role of dry air in moist convection during tropical cyclogenesis.

The tropical cyclogenesis sequence of Hurricane Sandy is examined. It is shown that genesis occurs within a recirculating Kelvin cat's-eye flow of a westward-propagating tropical wave. The cat's-eye flow is able to provide a protective environment for the mesoscale vortex to grow and is characterized by gradual column moistening and increased areal coverage of deep cumulus convection. These findings are generally consistent with a recently proposed tropical cyclogenesis sequence referred to as the "marsupial paradigm.'' Sandy's cyclogenesis provides a useful illustration of the marsupial paradigm within a partially open recirculating region, with the opening located south of the pouch center. It is suggested that the opening acts to enhance the genesis process because it is adjacent to an environment characterized by warm, moist air, conditions favorable for tropical cyclogenesis. From a dynamical perspective, accretion of low-level cyclonic vorticity filaments into the developing vortex from several sources (the South American convergence zone, an easterly wave located west of the pre-Sandy wave, and cyclonic vorticity generated along Hispaniola) is documented. Organization and growth of the nascent storm is enhanced by this accretion of cyclonic vorticity. A Lagrangian trajectory analysis is used to assess potential contributions to Sandy's spinup from a Caribbean gyre and the easterly wave that formed Hurricane Tony. This analysis indicates that these features are outside of the Lagrangian flow boundaries that define the pre-Sandy wave and do not directly contribute to spinup of the vortex. Finally, the effectiveness of forecasts from the U.S. and European operational numerical weather prediction models is discussed for this case.

: The tropical cyclogenesis model described in Dunkerton et al. (2009), and tested herein for the case of Hurricane Sandy (2012), provides a comprehensive description of the dynamics and thermodynamics that lead to the formation of a tropical cyclone. The model outlines the relevant physical processes and multi-scale interactions and can be summarized by the following three hypotheses (reproduced from Dunkerton et al. 2009). H1. Proto-vortex cyclonic eddies instrumental in TC formation are intimately associated with the parent wave s critical latitude in the lower troposphere. The critical layer and Kelvin cat s eye within, formed as a result of the wave s finite-amplitude interaction with its own critical latitude, contain a region of cyclonic rotation and weak straining/shearing deformation in which synoptic waves and mesoscale vorticity anomalies, moving westward together, amplify and aggregate on a nearly zero relative mean flow. This multi-scale interaction provides a dynamical pathway to bottom-up development of the proto-vortex from below. H2. The critical-layer cat s eye of the parent wave provides a set of quasi-closed material contours inside of which air is repeatedly moistened by convection, protected to some degree from lateral intrusion of dry air and impinging vertical shear, and (thanks to its location near the critical latitude) able to keep pace with the parent wave until the protovortex has strengthened into a self-maintaining entity. H3. The parent wave is maintained and possibly enhanced by diabatically amplified eddies within the wave (proto-vortices on the mesoscale), a process favored in regions of small intrinsic phase speed.

The principal hypotheses of a new model of tropical cyclogenesis, known as the marsupial paradigm, were tested in the context of Atlantic tropical disturbances during the National Science Foundation (NSF)-sponsored Pre-Depression Investigation of Cloud Systems in the Tropics (PREDICT) experiment in 2010. PREDICT was part of a tri-agency collaboration, along with the National Aeronautics and Space Administration's Genesis and Rapid Intensification Processes (NASA GRIP) experiment and the National Oceanic and Atmospheric Administration's Intensity Forecasting Experiment (NOAA IFEX), intended to examine both developing and nondeveloping tropical disturbances. During PREDICT, a total of 26 missions were flown with the NSF/NCAR Gulfstream V (GV) aircraft sampling eight tropical disturbances. Among these were four cases (Fiona, ex-Gaston, Karl, and Matthew) for which three or more missions were conducted, many on consecutive days. Because of the scientific focus on the Lagrangian nature of the tropical cyclogenesis process, a wave-relative frame of reference was adopted throughout the experiment in which various model- and satellite-based products were examined to guide aircraft planning and real-time operations. Here, the scientific products and examples of data collected are highlighted for several of the disturbances. The suite of cases observed represents arguably the most comprehensive, self-consistent dataset ever collected on the environment and mesoscale structure of developing and nondeveloping predepression disturbances.

Two approaches are developed and tested to improve the unweighted position consensus for 96-, 108-, and 120-h tropical cyclone track guidance in the western North Pacific. A weighted position guidance technique uses a weighting factor for each model that is inversely proportional to how far the 60-, 66-, and 72-h positions of that model are from the corresponding positions of the 11-member position consensus. The weighted position consensus of 96-, 108-, and 120-h track errors for a sample of 24 storms during the 2006 season are consistently smaller than for the unweighted position consensus.In the second approach, a weighted motion vector consensus is developed that uses the same weighting factors as in the weighted position consensus, except that the weights are applied to 12-h motion vectors between 84 and 120 h. This weighted motion vector consensus has substantially smaller errors than the unweighted position consensus, and results in smoother tracks when one or more of the model tracks drops out of the consensus. It is proposed that the weighted motion vector consensus would provide improved guidance for the 96-, 108-, and 120-h tropical cyclone track forecasts.

The Joint Typhoon Warning Center has been issuing 96- and 120-h track forecasts since May 2003. It uses four dynamical models that provide guidance at these forecast intervals and relies heavily on a consensus of these four models in producing the official forecast. Whereas each of the models has skill, each occasionally has large errors. The objective of this study is to provide a characterization of these errors in the western North Pacific during 2004 for two of the four models: the Navy Operational Global Atmospheric Prediction System (NOGAPS) and the U. S. Navy's version of the Geophysical Fluid Dynamics Laboratory model (GFDN). All 96- and 120-h track errors greater than 400 and 500 n mi, respectively, are examined following the approach developed recently by Carr and Elsberry. All of these large-error cases can be attributed to the models not properly representing the physical processes known to control tropical cyclone motion, which were classified in a series of conceptual models by Carr and Elsberry for either tropical-related or midlatitude-related mechanisms. For those large-error cases where an error mechanism could be established, midlatitude influences caused 83% (85%) of the NOGAPS (GFDN) errors. The most common tropical influence is an excessive direct cyclone interaction in which the tropical cyclone track is erroneously affected by an adjacent cyclone. The most common midlatitude-related errors in the NOGAPS tracks arise from an erroneous prediction of the environmental flow dominated by a ridge in the midlatitudes. Errors in the GFDN tracks are caused by both ridge-dominated and trough-dominated environmental flows in the midlatitudes. Case studies illustrating the key error mechanisms are provided. An ability to confidently identify these error mechanisms and thereby eliminate likely erroneous tracks from the consensus would improve the accuracy of 96- and 120-h track forecasts.

Because the Joint Typhoon Warning Center (JTWC) has only four dynamical models for guidance in making 96- and 120-h track forecasts, an opportunity exists for improving the consensus forecast by the proper removal of a likely erroneous forecast to form a selective consensus (SCON). Forecast fields from all four models [ the U. S. Navy Operational Global Atmospheric Prediction System (NOGAPS), the U. S. Navy version of the Geophysical Fluid Dynamics Laboratory model (GFDN), the Met Office (UKMO) model, and the Global Forecast System (GFS)] were available during the 2005 western North Pacific season to evaluate for the first time the error mechanisms leading to large track errors. As shown previously for the NOGAPS and GFDN models during the 2004 season, error sources related to the midlatitude circulations accounted for about 90% of all large 120-h track errors by all four models during the 2005 season. This dominance of midlatitude-related error source is a major shift from the 72-h errors, which include more errors related to tropical circulations. In the GFS model, 95% of the large errors occurred because of an incorrect depiction of the vertical structure of the tropical cyclone. A systematic error in the GFDN model was identified in which a false anticyclogenesis was predicted downstream of the Tibetan Plateau, which accounted for over 50% of the large GFDN track errors. The consensus spread versus consensus error relationship is examined to isolate those 20%-25% of cases with large spreads and large errors that are candidates for forming an SCON. If the model tracks that contributed to the large errors are eliminated, the average improvement of the SCON forecasts relative to the nonselective consensus is 222 ( 239) n mi during 2005 ( 2004), and the corresponding average improvement relative to the JTWC forecasts is 382 ( 203) n mi. This application of SCON is considered the potential "forecastability" in that it represents the optimum use of the present numerical guidance for consensus forecasting.