Search Results

You are looking at 1 - 3 of 3 items for

  • Author or Editor: Saima Aijaz x
  • Refine by Access: Content accessible to me x
Clear All Modify Search
Saima Aijaz, Jeffrey D. Kepert, Hua Ye, Zhendong Huang, and Alister Hawksford

Abstract

Global ensemble prediction systems have considerable ability to predict tropical cyclone (TC) formation and subsequent evolution. However, because of their relatively coarse resolution, their predictions of intensity and structure are biased. The biases arise mainly from underestimated intensities and enlarged radii, in particular the radius of maximum winds. This paper describes a method to reduce this limitation by bias correcting TCs in the ECMWF Ensemble Prediction System (ECMWF-EPS) for a region northwest of Australia. A bias-corrected TC system will provide more accurate forecasts of TC-generated wind and waves to the oil and gas industry, which operates a large number of offshore facilities in the region. It will also enable improvements in response decisions for weather sensitive operations that affect downtime and safety risks. The bias-correction technique uses a multivariate linear regression method to bias correct storm intensity and structure. Special strategies are used to maintain ensemble spread after bias correction and to predict the radius of maximum winds using a climatological relationship based on wind intensity and storm latitude. The system was trained on the Australian best track TC data and the ECMWF-EPS TC data from two cyclone seasons. The system inserts corrected vortices into the original surface wind and pressure fields, which are then used to estimate wind exceedance probabilities, and to drive a wave model. The bias-corrected system has shown an overall skill improvement over the uncorrected ECMWF-EPS for all TC intensity and structure parameters with the most significant gains for the maximum wind speed prediction. The system has been operational at the Australian Bureau of Meteorology since November 2016.

Free access
Diana Greenslade, Mark Hemer, Alex Babanin, Ryan Lowe, Ian Turner, Hannah Power, Ian Young, Daniel Ierodiaconou, Greg Hibbert, Greg Williams, Saima Aijaz, João Albuquerque, Stewart Allen, Michael Banner, Paul Branson, Steve Buchan, Andrew Burton, John Bye, Nick Cartwright, Amin Chabchoub, Frank Colberg, Stephanie Contardo, Francois Dufois, Craig Earl-Spurr, David Farr, Ian Goodwin, Jim Gunson, Jeff Hansen, David Hanslow, Mitchell Harley, Yasha Hetzel, Ron Hoeke, Nicole Jones, Michael Kinsela, Qingxiang Liu, Oleg Makarynskyy, Hayden Marcollo, Said Mazaheri, Jason McConochie, Grant Millar, Tim Moltmann, Neal Moodie, Joao Morim, Russel Morison, Jana Orszaghova, Charitha Pattiaratchi, Andrew Pomeroy, Roger Proctor, David Provis, Ruth Reef, Dirk Rijnsdorp, Martin Rutherford, Eric Schulz, Jake Shayer, Kristen Splinter, Craig Steinberg, Darrell Strauss, Greg Stuart, Graham Symonds, Karina Tarbath, Daniel Taylor, James Taylor, Darshani Thotagamuwage, Alessandro Toffoli, Alireza Valizadeh, Jonathan van Hazel, Guilherme Vieira da Silva, Moritz Wandres, Colin Whittaker, David Williams, Gundula Winter, Jiangtao Xu, Aihong Zhong, and Stefan Zieger
Full access
Diana Greenslade, Mark Hemer, Alex Babanin, Ryan Lowe, Ian Turner, Hannah Power, Ian Young, Daniel Ierodiaconou, Greg Hibbert, Greg Williams, Saima Aijaz, João Albuquerque, Stewart Allen, Michael Banner, Paul Branson, Steve Buchan, Andrew Burton, John Bye, Nick Cartwright, Amin Chabchoub, Frank Colberg, Stephanie Contardo, Francois Dufois, Craig Earl-Spurr, David Farr, Ian Goodwin, Jim Gunson, Jeff Hansen, David Hanslow, Mitchell Harley, Yasha Hetzel, Ron Hoeke, Nicole Jones, Michael Kinsela, Qingxiang Liu, Oleg Makarynskyy, Hayden Marcollo, Said Mazaheri, Jason McConochie, Grant Millar, Tim Moltmann, Neal Moodie, Joao Morim, Russel Morison, Jana Orszaghova, Charitha Pattiaratchi, Andrew Pomeroy, Roger Proctor, David Provis, Ruth Reef, Dirk Rijnsdorp, Martin Rutherford, Eric Schulz, Jake Shayer, Kristen Splinter, Craig Steinberg, Darrell Strauss, Greg Stuart, Graham Symonds, Karina Tarbath, Daniel Taylor, James Taylor, Darshani Thotagamuwage, Alessandro Toffoli, Alireza Valizadeh, Jonathan van Hazel, Guilherme Vieira da Silva, Moritz Wandres, Colin Whittaker, David Williams, Gundula Winter, Jiangtao Xu, Aihong Zhong, and Stefan Zieger

Abstract

The Australian marine research, industry, and stakeholder community has recently undertaken an extensive collaborative process to identify the highest national priorities for wind-waves research. This was undertaken under the auspices of the Forum for Operational Oceanography Surface Waves Working Group. The main steps in the process were first, soliciting possible research questions from the community via an online survey; second, reviewing the questions at a face-to-face workshop; and third, online ranking of the research questions by individuals. This process resulted in 15 identified priorities, covering research activities and the development of infrastructure. The top five priorities are 1) enhanced and updated nearshore and coastal bathymetry; 2) improved understanding of extreme sea states; 3) maintain and enhance the in situ buoy network; 4) improved data access and sharing; and 5) ensemble and probabilistic wave modeling and forecasting. In this paper, each of the 15 priorities is discussed in detail, providing insight into why each priority is important, and the current state of the art, both nationally and internationally, where relevant. While this process has been driven by Australian needs, it is likely that the results will be relevant to other marine-focused nations.

Free access