NOAA Climate Prediction Task Force and CPO Modeling, Analysis, Prediction, and Projections (MAPP) program will host a webinar on the topic of understanding of the North Atlantic Oscillation’s variability and predictability and exploiting that for improving on Thursday, October 16. The announcement is provided below; you are invited to remotely join the session.
|October 16, 2014
11:00 AM – 12:30 PM ET
|CPTF/MAPP Webinar: NAO variability, predictability, and related prediction improvements|
|Speakers and Topics:||Adam Scaife (UK Met Office)
Skilful Long Range Prediction of European and North American Winters
Tim Stockdale (ECMWF)
|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=629205299
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
Webex and the teleconference line can accommodate only 100 attendees on a first-come, first-served basis. Please try to share a connection with colleagues at your institution to preserve space for others.
(Right click and Save Link As) .wmv
ABSTRACTS: Adam Scaife – Skilful Long Range Prediction of European and North American Winters – Until recently, long-range forecast systems showed only modest levels of skill in predicting surface winter climate around the Atlantic Basin and associated fluctuations in the North Atlantic Oscillation at seasonal lead times. Here we use a new forecast system to assess seasonal predictability of winter North Atlantic climate. We demonstrate that key aspects of European and North American winter climate and the surface North Atlantic Oscillation are highly predictable months ahead. We demonstrate high levels of prediction skill in retrospective forecasts of the surface North Atlantic Oscillation, winter storminess, near-surface temperature, and wind speed, all of which have high value for planning and adaptation to extreme winter conditions. Analysis of forecast ensembles suggests that while useful levels of seasonal forecast skill have now been achieved, key sources of predictability are still only partially represented and there is further untapped predictability.
Tim Stockdale – NH winter forecast skill of AO and NAO indices: results and sampling issues