Acknowledgements
I would like to thank Associate Professor Ravinesh Deo and Dr Sujan Ghimire for their generous feedback and advice throughout the duration of this project and for the opportunity to work on such a challenging research topic.
The data for this project was sourced from the Centre for Environmental Data Analysis in the United Kingdom (CEDA) and from the Scientific Information for Landowners database (SILO) provided by the Queensland Government. Such initiatives, offering quality publicly available data resources for the purposes of research, provide a valuable service to the broader community. In our digital age, the importance of credible, open resources such as these cannot be overstated.
I would like to thank my family, my wife Julie, who patiently, and with good humour, has indulged my problem solving with my “outside voice”, whilst we take our dog, Iggy, for his afternoon walk. As well as to my brother Geoff and cousin Mel, who have generously allowed me to practice delivering seminars over video conference, as part of the preparation for presentation and offered their valued feedback and encouragement. As well as to Annette, whose spirited conversations provide insight into her own experience of the challenges in communicating research and has renewed my enthusiasm for the task at hand.
I’m also thankful to my supervisor at work, Steven, who approved my all too brief period of leave, permitting me a short period of time to focus solely on this challenging project.
Downscaling Global Climate Models with Convolutional and Long-Short-Term Memory Networks for Solar Energy Applications by C.P. Davey is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.