2015 Regional Climate Projections: Hunter, Central and Lower North Coast Region of New South Wales

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This technical report provides details of the process undertaken to test the voracity of the 2009 climate change modelling undertaken by the University of Newcastle and Macquarie University for HCCREMS.

1 Category

In 2009 the Hunter and Central Coast Regional Environmental Management Strategy (HCCREMS) released research identifying historic and projected climate variability for the Hunter, Central and Lower North Coast region of NSW (Blackmore & Goodwin 2009). This research was completed for HCCREMS by the University of Newcastle and Macquarie University and utilised a weather typing approach to statistical downscaling.

In 2014 HCCREMS commissioned the University of Newcastle to review these 2009 climate projections utilising more recently available climatic data. This aimed to identify the on-going veracity of the methodology and to identify any likely variations from the original climate projections. This report:

  1. Describes the methodology employed to undertake the review, including the production of individual interpolated surfaces (spatial gridded datasets) for key climate variables for the 1990, 2015, 2040, 2060 and 2080 time horizons. These depict seasonal climate conditions for maximum temperature, minimum temperature and precipitation for each time horizon.
  2. Presents the results of the evaluation and analysis of current Bureau of Meteorology (BOM) data for key climate variables for the Hunter, Central and Lower North Coast region of NSW. These results extend on previous work (Verdon & Goodwin, 2007; Blackmore & Goodwin, 2008 & 2009) to consider trends in observed climate data from 1 March 2007 to 1 October 2014.
  3. Presents the outcomes of updated climate projections that draw upon the evaluation and analysis of the more recent BOM data that has been completed. Projections have been downscaled to selected BOM stations within the region. These projections are provided as spatial grid datasets that reflect the linear trends that have been developed via this methodology.

Date: 2015

Others Involved:

Dr Karen Blackmore, School of Design, Communication and Information Technology Newcastle Innovation (The University of Newcastle)