Browse

You are looking at 1 - 2 of 2 items for :

  • NASA Hurricane and Severe Storm Sentinel (HS3) x
  • Journal of the Atmospheric Sciences x
  • Refine by Access: All Content x
Clear All
E. P. Nowottnick
,
P. R. Colarco
,
S. A. Braun
,
D. O. Barahona
,
A. da Silva
,
D. L. Hlavka
,
M. J. McGill
, and
J. R. Spackman

Abstract

During the 2012 deployment of the NASA Hurricane and Severe Storm Sentinel (HS3) field campaign, several flights were dedicated to investigating Hurricane Nadine. Hurricane Nadine developed in close proximity to the dust-laden Saharan air layer and is the fourth-longest-lived Atlantic hurricane on record, experiencing two strengthening and weakening periods during its 22-day total life cycle as a tropical cyclone. In this study, the NASA GEOS-5 atmospheric general circulation model and data assimilation system was used to simulate the impacts of dust during the first intensification and weakening phases of Hurricane Nadine using a series of GEOS-5 forecasts initialized during Nadine’s intensification phase (12 September 2012). The forecasts explore a hierarchy of aerosol interactions within the model: no aerosol interaction, aerosol–radiation interactions, and aerosol–radiation and aerosol–cloud interactions simultaneously, as well as variations in assumed dust optical properties. When only aerosol–radiation interactions are included, Nadine’s track exhibits sensitivity to dust shortwave absorption, as a more absorbing dust introduces a shortwave temperature perturbation that impacts Nadine’s structure and steering flow, leading to a northward track divergence after 5 days of simulation time. When aerosol–cloud interactions are added, the track exhibits little sensitivity to dust optical properties. This result is attributed to enhanced longwave atmospheric cooling from clouds that counters shortwave atmospheric warming by dust surrounding Nadine, suggesting that aerosol–cloud interactions are a more significant influence on Nadine’s track than aerosol–radiation interactions. These findings demonstrate that tropical systems, specifically their track, can be impacted by dust interaction with the atmosphere.

Full access
Erin B. Munsell
,
Fuqing Zhang
,
Jason A. Sippel
,
Scott A. Braun
, and
Yonghui Weng

Abstract

The dynamics and predictability of the intensification of Hurricane Edouard (2014) are explored through a 60-member convection-permitting ensemble initialized with an ensemble Kalman filter that assimilates dropsondes collected during NASA’s Hurricane and Severe Storm Sentinel (HS3) investigation. The 126-h forecasts are initialized when Edouard was designated as a tropical depression and include Edouard’s near–rapid intensification (RI) from a tropical storm to a strong category-2 hurricane. Although the deterministic forecast was very successful and many members correctly forecasted Edouard’s intensification, there was significant spread in the timing of intensification among the members of the ensemble.

Utilizing composite groups created according to the near-RI-onset times of the members, it is shown that, for increasing magnitudes of deep-layer shear, RI onset is increasingly delayed; intensification will not occur once a critical shear threshold is exceeded. Although the timing of intensification varies by as much as 48 h, a decrease in shear is observed across the intensifying composite groups ~6–12 h prior to RI. This decrease in shear is accompanied by a reduction in vortex tilt, as the precession and subsequent alignment process begins ~24–48 h prior to RI. Sensitivity experiments reveal that some of the variation in RI timing can be attributed to differences in initial intensity, as the earliest-developing members have the strongest initial vortices regardless of their environment. Significant sensitivity and limited predictability exists for members with weaker initial vortices and/or that are embedded in less conducive environments, under which the randomness of moist convective processes and minute initial differences distant from the surface center can produce divergent forecasts.

Full access