Potential impacts of assimilating all‐sky infrared satellite radiances from GOES‐R on convection‐permitting analysis and prediction of tropical cyclones

Abstract

The potential impacts of GOES‐R satellite radiances on tropical cyclone analysis and prediction were examined through ensemble correlations between simulated infrared brightness temperatures and various model state variables. The impacts of assimilating GOES‐R all‐sky infrared brightness temperatures on tropical cyclone analysis and prediction were further demonstrated through a series of convection‐permitting observing system simulation experiments using an ensemble Kalman filter under both perfect and imperfect model scenarios. Assimilation of the high temporal and spatial resolution infrared radiances not only constrained well the thermodynamic variables, including temperature, moisture, and hydrometeors, but also considerably reduced analysis and forecast errors in the wind fields. The potential of all‐sky radiances is further demonstrated through an additional proof‐of‐concept experiment assimilating real‐data infrared brightness temperatures from GOES 13 satellite which was operational in an enhanced scanning mode during Hurricane Karl (2010).

On the Predictability and Error Sources of Tropical Cyclone Intensity Forecasts

“…(We did not examine the effects of initial structural error, as the specification of the radius of maximum wind is effectively the only free structural parameter in CHIPS, but this source of error may be important in real storms.) The high sensitivity to initial intensity error when the initial intensity is small may be owing to the striking sensitivity of the timing of rapid intensification of weak storms to shear documented by Zhang and Tao (2013) and Tao and Zhang (2015).…”

“…We interpret this as stemming from the greater potential for rapid intensification of initially weak storms compared to storms that are already not far from their potential intensities and to the great sensitivity of the timing of rapid intensification to shear when the initial intensity is small (Zhang and Tao 2013;Tao and Zhang 2015). This suggests that future work might focus on predictability of rapidly intensifying events and/or on events that achieve major hurricane intensity.…”

“…(In the highshear cases, storms can be reliably forecast to dissipate.) Zhang and Tao (2013) and Tao and Zhang (2015) showed that tropical cyclones are particularly sensitive to shear in their formative stages, with small differences in shear or initial intensity strongly affecting the timing of subsequent intensification.…”

“…In attempting to improve any type of numerical weather forecast, it is useful to be aware of fundamental and practical predictability limits imposed by the inherent chaotic nature of atmospheric behavior (Lorenz 1969;Zhang et al 2007;Rotunno and Snyder 2008;Palmer et al 2014) coupled with limitations on our ability to accurately observe our environment (Sun and Zhang 2016). One may reasonably expect models and data assimilation techniques to improve continuously over time, while the hope that observations will also improve must be tempered by finite economic and technological resources.…”

“…Within the community of scientists working on tropical cyclones, efforts have been directed toward improving dedicated tropical cyclone models (e.g., Gopalakrishnan et al 2011), real-time in situ and remote sensing observations of storms (e.g., Ruf et al 2016), assimilation of those observations into models (Zhang and Weng 2015;Weng and Zhang 2016;Zhang et al 2016), and statistical forecast models, which are still competitive with deterministic models (Kaplan et al 2015). Numerical modeling of tropical cyclones is especially challenging owing to the very high resolution required to resolve the critical eyewall region (Rotunno et al 2009), to the complex physics of boundary layers and air-sea interaction at high winds speeds (Nolan et al 2009;Green and Zhang 2014;Andreas et al 2015;Green and Zhang 2015), and to the importance of correctly modeling the response of the upper ocean to the storms (Moon et al 2007;Yablonsky and Ginis 2009).…”