Since 2005, NOAA has conducted the annual Intensity Forecasting Experiment (IFEX), led by scientists from the Hurricane Research Division at NOAA’s Atlantic Oceanographic and Meteorological Laboratory. They partner with NOAA’s Aircraft Operations Center, who maintain and operate the WP-3D and Gulfstream IV-SP (G-IV) Hurricane Hunter aircraft, and NCEP’s National Hurricane Center and Environmental Modeling Center, who task airborne missions to gather data used by forecasters for analysis and forecasting and for ingest into operational numerical weather prediction models. The goal of IFEX is to improve tropical cyclone (TC) forecasts using an integrated approach of analyzing observations from aircraft, initializing and evaluating forecast models with those observations, and developing new airborne instrumentation and observing strategies targeted at filling observing gaps and maximizing the data’s impact in model forecasts. This summary article not only highlights recent IFEX contributions toward improved TC understanding and prediction, but also reflects more broadly on the accomplishments of the program during the 16 years of its existence. It describes how IFEX addresses high-priority forecast challenges, summarizes recent collaborations, describes advancements in observing systems monitoring structure and intensity, as well as in assimilation of aircraft data into operational models, and emphasizes key advances in understanding of TC processes, particularly those that lead to rapid intensification. The article concludes by laying the foundation for the next generation of IFEX as it broadens its scope to all TC hazards, particularly rainfall, storm-surge inundation, and tornadoes, that have gained notoriety during the last few years after several devastating landfalling TCs.

This study evaluates precipitation properties involved in tropical cyclogenesis by analyzing a multiyear, global database of passive microwave overpasses of the pregenesis stage of developing disturbances and nondeveloping disturbances. Precipitation statistics are quantified using brightness temperature proxies from the 85–91-GHz channels of multiple spaceborne sensors, as well as retrieved rain rates. Proxies focus on the overall raining area, areal coverage of deep convection, and the proximity of precipitation to the disturbance center. Of interest are the differences in those proxies for developing versus nondeveloping disturbances, how the properties evolve during the pregenesis stage, and how they differ globally. The results indicate that, of all of the proxies examined, the total raining area and rain volume near the circulation center are the most useful precipitation-related predictors for genesis. The areal coverage of deep convection also differentiates developing from nondeveloping disturbances and, similar to the total raining area, generally also increases during the pregenesis stage, particularly within a day of genesis. As the threshold convective intensity is increased, pregenesis cases are less distinguishable from nondeveloping disturbances. Relative to the western Pacific and Indian Oceans, the Atlantic and eastern North Pacific Oceans have less precipitation and deep convection observed during genesis and the smallest differences between developing and nondeveloping disturbances. This suggests that the total raining area and areal coverage of deep convection associated with tropical disturbances are better predictors of tropical cyclogenesis fate in the Pacific and Indian Oceans than in the Atlantic and eastern North Pacific.

Tropical cyclones can form over open ocean where in situ observations are limited, so forecasters rely on satellite observations to monitor their development and track. We explore the utility of an operational satellite sounding product for tropical forecasting by characterizing the products retrieval skill during research flights. Scientists from both the NOAA-Unique Combined Atmospheric Processing System (NUCAPS) research team and tropical cyclone communities collaborated to target relevant tropical cyclones during the campaign. This effort produced 130 dropsondes that are well-timed with satellite sounder overpasses over three different tropical cyclones and one Saharan Air Layer outbreak. For the combined infrared and microwave retrieval, the NUCAPS temperature has a root mean square error (RMSE) of 1.2 K near the surface (1000–600 mb) and 0.8 K in the mid-troposphere (600–300 mb), which is in line with global product requirements. The water vapor mixing ratio RMSE was 26% near the surface and 46% in the mid-troposphere. NUCAPS microwave-only retrievals can also be useful for cloudy scenes, with surface RMSE values of 4 K (temperature) and 23% (water vapor). Using information content analysis, we estimated that the vertical resolution near the surface was 1.7 km for the temperature retrievals and 2.2 km for the water vapor retrievals in this study. We discuss the feasibility of implementing NUCAPS in an operational forecasting setting, which requires rapid data delivery to forecaster software tools.