The NOAA CPO Modeling, Analysis, Prediction, and Projections (MAPP) program hosted a webinar on the topic of Tropical Cyclones: Predictions and Projections on Tuesday, September 9, 2014. The announcement is provided below; you are invited to remotely join the session.
|September 9, 2014
2:00 PM – 3:00 PM ET
|Tropical Cyclones: Predictions and Projections|
|Speakers and Topics:||SJ Lin (NOAA GFDL)
Filling the gap in hurricane predictions: how climate-modeling research can help improve the extended-range weather predictions
Kerry Emanuel (MIT)
Tropical Cyclones of the Future: Results from Downscaling CMIP5 Models
Suzana Camargo (Columbia University)
Highlights of new results on tropical cyclone projections
|Remote Access:||To view the slideshow:
1. Click the link below or copy and paste the link to a browser: https://cpomapp.webex.com/cpomapp/onstage/g.php?t=a&d=620601470
2. Enter your name and e-mail address, and click “Join Now”. If necessary, enter the event passcode: 20910
To hear the audio:
Utilize the on-screen dial-in instructions visible after logging into webex
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ABSTRACTS: SJ Lin — Filling the gap in hurricane predictions: how climate-modeling research can help improve the extended-range weather predictions — Recent advancement in high-resolution climate modeling, in particular, the dramatic improvement in the simulations of hurricane and Madden-Julian Oscillations within global climate models has motivated us to explore the feasibility of using climate models for extended-range (from 1-week to 4-week) weather predictions in general, and hurricane predictions in particular. We will use two recent high-impact tropical cyclones, Hurricane Sandy and Typhoon Haiyan, as case studies. We will show that, despite lacking a state-of-the-art data assimilation system, the genesis of these intense tropical cyclones, can be skillfully predicted weeks in advance using GFDL’s high-resolution climate modeling systems. — Kerry Emanuel — Tropical Cyclones of the Future: Results from Downscaling CMIP5 Models — We rely mostly on global climate models to simulate future climate states. But the horizontal resolution of such models is insufficient to resolve the important inner cores of tropical cyclones, and there is some question whether they adequately resolve the disturbances that serve to trigger such storms. One way to deal with the first issue is to embed in the larger scale model a detailed, high resolution tropical cyclone model, driven by the large-scale conditions generated by the climate model. In my talk, I will briefly describe the technique and then show the results of applying it to the current and to future projected climate states. — Suzana Camargo — Highlights of new results on tropical cyclone projections — In this talk we’ll discuss recent results on tropical cyclone projections. First, we will show the our analysis of future changes of North Atlantic potential intensity (PI) in the historical and future multi-model CMIP5 simulations using a signal-to-noise (S/N) maximizing empirical orthogonal function (EOF), as described in Ting et al. 2014. We will show that by the mid-21st century under both rcp4.5 and rcp8.5 scenarios, the anthropogenically induced warming would put the North Atlantic PI largely above the historical mean, even considering multi-decadal natural variability. During the historical period, both aerosols and greenhouse gases contribute to forced changes in PI. The decrease in PI caused by aerosol forcing and the increase due to greenhouse gas forcing largely canceled each other, and the sharp increase in PI in the recent 30 years was dominated by the multi-decadal natural variability. We will also discuss the projected changes in the length of tropical cyclone season, which were obtained in Dwyer et al. 2014. We considered 2 sets of simulations: (i) high-resolution climate model (HiRAM) forced with SST anomalies from the CMIP3 and CMIP5 models and (ii) dynamical downscaling of the CMIP3 and CMIP5 model outputs that generates synthetic TC tracks. We measured season length using 3 different metrics. While the HiRAM model projects shorter seasons in most basins, the CMIP5 downscaling projects longer seasons. The changes in the length of TC season by basin can be largely explained by the annual mean TC frequency changes in each basin. Furthermore, while in most cases there is a projection for a timing shift of the TC annual cycle to later in the year in the North Atlantic, in the western North Pacific, the projections are opposite, i.e. a shift towards earlier in the year.