A33J-0321
Short-term Climate imulations of African Easterly Waves with a Global Mesoscale Model

Wednesday, 16 December 2015
Poster Hall (Moscone South)
Bo-Wen Shen, San Diego State University, San Diego, CA, United States
Abstract:
Recent high-resolution global model simulations ( Shen et al., 2010a, 2010b, 2012; 2013), which
were conducted to examine the role of multiscale processes associated with tropical waves in the
predictability of mesoscale tropical cyclones (TCs), suggested that a large-scale system (e.g., tropical
waves) can provide determinism on the prediction of TC genesis, making it possible to extend the lead
time of genesis predictions. Selected cases include the relationship between (i) TC Nargis (2008) and an
Equatorial Rossby wave; (ii) Hurricane Helene (2006) and an intensifying African Easterly Wave
(AEW); (iii) Twin TCs (2002) and a mixed Rossby-gravity wave during an
active phase of the Madden Julian Oscillation (MJO); (iv) Hurricane Sandy
(2012) and tropical waves during an active phase of the MJO. In this talk, thirty-day simulations with
different model configurations are presented to examine the model’s ability to simulate AEWs and
MJOs and their association with tropical cyclogenesis. I will first discuss the simulations of the initiation and propagation of 6 consecutive AEWs in late August 2006 and the mean state of the African easterly jet (AEJ) over both Africa and downstream in the tropical Atlantic. By comparing our simulations with NCEP analysis and satellite data (e.g., TRMM), it is shown that the statistical characteristics of individual AEWs are realistically simulated with larger errors in the 5th and th AEWs. Results from the sensitivity experiments suggest the following: 1) accurate
representations of non-linear interactions between the atmosphere and land processes are crucial for
improving the simulations of the AEWs and the AEJ; 2) improved simulations of an individual AEW
and its interaction with local environments (e.g., the Guinea Highlands) could provide determinism for
hurricane formation downstream. Of interest is the potential to extend the lead time for predicting
hurricane formation (e.g., a lead time of up to 22 days) as the 4th AEW is realistically simulated; 3)
however, the dependence of AEW simulations on accurate dynamic and surface initial conditions and
boundary conditions poses a challenge in simulating their modulation on hurricane activity. In addition to the simulations of AEWs, I will also present the 30-day simulations of selected MJO cases.