Saharan dust exerts profound impacts on the genesis and intensification of tropical cyclones (TCs). Such impacts on various stages of the TCs have yet to be explored. In this study, we utilize the Cloud‐Resolving weather research and forecasting model (WRF) to investigate the relative importance of the microphysical and radiative effects of dust on two hurricanes (Earl and Danielle) at different life stages under similar dynamical conditions in 2010. Both TCs were embedded in a dusty environment throughout their lifetime. A new dust ice nucleation scheme was implemented into the aerosol‐aware Texas A&M University two‐moment microphysical scheme in WRF. Moreover, the dust radiative effect was included in the Goddard Shortwave Scheme of WRF. Our sensitivity experiments show that the radiative effect of dust (DRAD) amplified the mid‐level ridge in the Central Atlantic Ocean through temperature perturbation, changing the tracks of Danielle and Earl. Further analyses reveal an early shift of Danielle's maximum intensity for 12 hours but a significantly suppressed Earl in DRAD. In addition, the microphysical effect of dust had little impact on the large‐scale dynamical fields and storm tracks. The inclusion of dust as ice nucleation particles results in more variations in the intensity of Danielle and Earl than in other scenarios. This is owing to the higher maximum diabatic heating rate in the rainband region that perturbs the size of the TC. This study shows the dominant dust radiative effects on both intensity and track of the storm. In addition, there is evidence that dust suppresses the early stage TC but provides favorable conditions for matured TC. Both findings have profound implications for hurricane forecast and address the importance of accounting for detailed cloud microphysics and aerosol‐TC interactions in the operational forecasting models.
Tropical cyclone (TC) forecast verification techniques have traditionally focused on track and intensity, as these are some of the most important characteristics of TCs and are often the principal verification concerns of operational forecast centers. However, there is a growing need to verify other aspects of TCs as process-based validation techniques may be increasingly necessary for further track and intensity forecast improvements as well as improving communication of the broad impacts of TCs including inland flooding from precipitation. Here we present a set of TC-focused verification methods available via the Model Evaluation Tools (MET) ranging from traditional approaches to the application of storm-centric coordinates and the use of feature-based verification of spatially defined TC objects. Storm-relative verification using observed and forecast tracks can be useful for identifying model biases in precipitation accumulation in relation to the storm center. Using a storm-centric cylindrical coordinate system based on the radius of maximum wind adds additional storm-relative capabilities to regrid precipitation fields onto cylindrical or polar coordinates. This powerful process-based model diagnostic and verification technique provides a framework for improved understanding of feedbacks between forecast tracks, intensity, and precipitation distributions. Finally, object-based verification including land masking capabilities provides even more nuanced verification options. Precipitation objects of interest, either the central core of TCs or extended areas of rainfall after landfall, can be identified, matched to observations, and quickly aggregated to build meaningful spatial and summary verification statistics.
more » « less- PAR ID:
- 10444498
- Publisher / Repository:
- American Meteorological Society
- Date Published:
- Journal Name:
- Weather and Forecasting
- Volume:
- 38
- Issue:
- 9
- ISSN:
- 0882-8156
- Page Range / eLocation ID:
- p. 1589-1603
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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