Ensemble-based data assimilation of radar observations across inner-core regions of tropical cyclones (TCs) in tandem with satellite all-sky infrared radiances across the TC domain improves TC track and intensity forecasts. This study further investigates potential enhancements in TC track, intensity, and rainfall forecasts via assimilation of all-sky microwave radiances using Hurricane Harvey (2017) as an example. Assimilating GPM constellation all-sky microwave radiances in addition to GOES-16 all-sky infrared radiances reduces the forecast errors in the TC track, rapid intensification, and peak intensity compared to assimilating all-sky infrared radiances alone, including a 24-hour increase in forecast lead-time for rapid intensification. Assimilating all-sky microwave radiances also improves Harvey’s hydrometeor fields, which leads to improved forecasts of rainfall after Harvey’s landfall. This study indicates that avenues exist for producing more accurate forecasts for TCs using available yet underutilized data, leading to better warnings of and preparedness for TC-associated hazards in the future.

The meteorological characteristics of cloudy atmospheric columns can be very different from their clear counterparts. Thus, when a forecast ensemble is uncertain about the presence/absence of clouds at a specific atmospheric column (i.e., some members are clear while others are cloudy), that column’s ensemble statistics will contain a mixture of clear and cloudy statistics. Such mixtures are inconsistent with the ensemble data assimilation algorithms currently used in numerical weather prediction. Hence, ensemble data assimilation algorithms that can handle such mixtures can potentially outperform currently used algorithms. In this study, we demonstrate the potential benefits of addressing such mixtures through a bi-Gaussian extension of the ensemble Kalman filter (BGEnKF). The BGEnKF is compared against the commonly used ensemble Kalman filter (EnKF) using perfect model observing system simulated experiments (OSSEs) with a realistic weather model (the Weather Research and Forecast model). Synthetic all-sky infrared radiance observations are assimilated in this study. In these OSSEs, the BGEnKF outperforms the EnKF in terms of the horizontal wind components, temperature, specific humidity, and simulated upper tropospheric water vapor channel infrared brightness temperatures. This study is one of the first to demonstrate the potential of a Gaussian mixture model EnKF with a realistic weather model. Our results thus motivate future research towards improving numerical Earth system predictions though explicitly handling mixture statistics.

This study aims at improving understanding of the environments supporting summer MCS initiation in the U.S. Great Plains. A self-organizing map analysis is conducted to identify four types of summer MCS initiation environments during 2004-2017: Type-1 and Type-2 feature favorable large-scale environments, Type-3 has favorable lower-level and surface conditions but unfavorable upper-level circulation, while Type-4 features the most unfavorable large-scale environments. Despite the unfavorable large-scale environment, convection-centered composites reveal the presence of favorable sub-synoptic scale environments for MCS initiation in Type-3 and Type-4. All four types of MCS initiation environments delineate a clear eastward propagating feature in many meteorological fields, such as potential vorticity, surface pressure and equivalent potential temperature, upstream up to 25 west of and ~36 hours before MCS initiation. While the propagating environments and local, non-propagating low-level moisture are important to MCS initiation at the foothill of the Rocky Mountains, MCS initiation in the Great Plains is supported by the coupled dynamical and moisture anomalies, both associated with eastward propagating waves. Hence, the MCSs initiated at the plains can produce more rainfall than those initiated at the foothill due to more abundant moisture supply. By tracking MCSs and mid-tropospheric perturbations (MPs), a unique type of sub-synoptic disturbances with Rocky Mountains origin, it is shown that ~30% of MPs is associated with MCS initiation, mostly in Type-4. Although MPs are related to a small fraction of MCS initiation, MCSs that are associated with MPs tend to produce more rainfall in a larger area with a stronger convective intensity.