Gab Abramowitz

Associate Professor




I'm interested in models of natural systems and especially trying to understand when models are useful for making inferences about a natural system. I work with climate, hydrology and ecology models, primarily in evaluation, benchmarking and uncertainty assessment. I work in the Climate Change Research Centre at UNSW, am a Chief Investigator with the ARC Centre of Excellence for Climate Extremes and an Associate Investigator with the ARC Centre of Excellence for Climate System Science.



Research Goals

  • To understand the scope and extent of inference we can make with climate model projections
  • To quantify the expectations of performance we should have from models of natural systems
  • To develop meaningful model evaluation strategies for models of systems with significant internal variability

Research in Detail

Together with students and other researchers, I use a range of climatological, hydrological and ecological observations to try to understand the circumstances in which model simulations are useful, assess the uncertainty in model predictions and help develop international standards for model evaluation and benchmarking. My two main foci at the moment are land surface model benchmarking and model dependence assessment in multi-model ensemble climate prediction.

I am currently co-chair of the GEWEX Global Land-Atmosphere System Study panel, chair the OzEWEX Model Evaluation and Benchmarking working group and am a member of the management committee for the Community Atmosphere Biosphere Land Exchange (CABLE) model, Australia's community land surface model. I also lead development of the Protocol for the Analysis of Land Surface models (PALS) web application, which provides automated land surface, hydrological and ecological model evaluation and benchmarking tools as well as observational data sets.

Climate scientists use ensembles of climate models to get a collection of independent estimates of a prediction problem. Yet climate research teams share literature, data sets and even sections of model code. To what extent do different climate models constitute independent estimates? What is the most appropriate statistical framework with which to define independence? What are the implications of ignoring model dependence?

Supervision Opportunities/Areas

If you are interested in persuing a PhD or Honours project and you think this type of area might interest you, I'd love to hear from you. I'm particularly interested if you have ideas of your own that you'd like to pursue, but there are many potential projects in areas like uncertainty quantification in natural systems modelling, land surface model benchmarking and evaluation or an application of machine learning to climate science that we might discuss. If you have a background in maths, physics or computing there are likely plenty of options.

Students who are successful obtaining PhD scholarships (e.g. an Australian Postgraduate Award or International Postgraduate Research Scholarship) may be offered additional "top-up" funding, on a case-by-case basis.

Advice for prospective students

While you may not have a clear idea of your research topic yet, a PhD project will ultimately be yours to investigate, develop and communicate. Your supervisor will help you make sure that you arrive at a topic that is achievable in 3-4 years, scientifically rigorous, and most importantly, interesting for you. If the topics I've talked about above don't seem quite right, there is a great collection of other academics in the CCRC who might be able to help you. We're all friendly, so please come and talk to us.

The Climate Change Research Centre is a great place to do your PhD. We have a large PhD student cohort that is academically and socially engaged, with students from a wide range of academic and cultural backgrounds. We have an induction process that includes being assigned a student "buddy", to make sure you're aware of everything that might be relevant for you, including a range of social events run by students. As part of the Kensington campus we are only 10 minutes from the centre of Sydney.




Courses I teach

CLIM1001: Introduction to Climate Change

GENS0401: Introduction to Climate Change

CLIM3001: Climate Systems Science


Conference Papers
Wang B; Liu DL; Macadam I; Alexander LV; Abramowitz G; Yu Q, 2015, 'Multi-model ensemble projections of future extreme temperature change using a statistical downscaling method in eastern Australia', in Weber T; McPhee MJ; Anderssen RS (eds.), 21ST INTERNATIONAL CONGRESS ON MODELLING AND SIMULATION (MODSIM2015), MODELLING & SIMULATION SOC AUSTRALIA & NEW ZEALAND INC, Gold Coast, AUSTRALIA, pp. 1565 - 1571, presented at 21st International Congress on Modelling and Simulation (MODSIM) held jointly with the 23rd National Conference of the Australian-Society-for-Operations-Research / DSTO led Defence Operations Research Symposium (DORS, Gold Coast, AUSTRALIA, 29 November 2015 - 04 December 2015,
Journal articles
Hobeichi S; Abramowitz G; Evans J, 2020, 'Conserving Land-Atmosphere Synthesis Suite (CLASS)', JOURNAL OF CLIMATE, vol. 33, pp. 1821 - 1844,
Hobeichi S; Abramowitz G; Evans J; Beck HE, 2019, 'Linear Optimal Runoff Aggregate (LORA): A global gridded synthesis runoff product', Hydrology and Earth System Sciences, vol. 23, pp. 851 - 870,
Abramowitz G; Herger N; Gutmann E; Hammerling D; Knutti R; Leduc M; Lorenz R; Pincus R; Schmidt GA, 2019, 'ESD Reviews: Model dependence in multi-model climate ensembles: Weighting, sub-selection and out-of-sample testing', Earth System Dynamics, vol. 10, pp. 91 - 105,
Herger N; Abramowitz G; Knutti R; Angélil O; Lehmann K; Sanderson BM, 2018, 'Selecting a climate model subset to optimise key ensemble properties', Earth System Dynamics, vol. 9, pp. 135 - 151,
Herger N; Angélil O; Abramowitz G; Donat M; Stone D; Lehmann K, 2018, 'Calibrating Climate Model Ensembles for Assessing Extremes in a Changing Climate', Journal of Geophysical Research: Atmospheres, vol. 123, pp. 5988 - 6004,
Hobeichi S; Abramowitz G; Evans J; Ukkola A, 2018, 'Derived Optimal Linear Combination Evapotranspiration (DOLCE): A global gridded synthesis et estimate', Hydrology and Earth System Sciences, vol. 22, pp. 1317 - 1336,
Whitley R; Beringer J; Hutley LB; Abramowitz G; De Kauwe MG; Evans B; Haverd V; Li L; Moore C; Ryu Y; Scheiter S; Schymanski SJ; Smith B; Wang YP; Williams M; Yu Q, 2017, 'Challenges and opportunities in land surface modelling of savanna ecosystems', Biogeosciences, vol. 14, pp. 4711 - 4732,
Whitley R; Beringer J; Hutley LB; Abramowitz G; De Kauwe MG; Duursma R; Evans B; Haverd V; Li L; Ryu Y; Smith B; Wang YP; Williams M; Yu Q, 2016, 'A model inter-comparison study to examine limiting factors in modelling Australian tropical savannas', Biogeosciences, vol. 13, pp. 3245 - 3265,
Mendoza PA; Clark MP; Barlage M; Rajagopalan B; Samaniego L; Abramowitz G; Gupta H, 2015, 'Are we unnecessarily constraining the agility of complex process-based models?', Water Resources Research, vol. 51, pp. 716 - 728,
Abramowitz G; Bishop CH, 2015, 'Climate model dependence and the ensemble dependence transformation of CMIP projections', Journal of Climate, vol. 28, pp. 2332 - 2348,
Vargas R; Sonnentag O; Abramowitz G; Carrara A; Chen JM; Ciais P; Correia A; Keenan TF; Kobayashi H; Ourcival JM; Papale D; Pearson D; Pereira JS; Piao S; Rambal S; Baldocchi DD, 2013, 'Drought Influences the Accuracy of Simulated Ecosystem Fluxes: A Model-Data Meta-analysis for Mediterranean Oak Woodlands', Ecosystems, vol. 16, pp. 749 - 764,
Sasse TP; McNeil B; Abramowitz G, 2013, 'A new constraint on global air-sea CO2 fluxes using bottle carbon data', Geophysical Research Letters, vol. 40, pp. 1594 - 1599,
Hall M; Medlyn BE; Abramowitz G; Franklin O; Räntfors M; Linder S; Wallin G, 2013, 'Which are the most important parameters for modelling carbon assimilation in boreal Norway spruce under elevated [CO2] and temperature conditions?', Tree Physiology, vol. 33, pp. 1156 - 1176,
Bishop CH; Abramowitz G, 2013, 'Climate model dependence and the replicate Earth paradigm', Climate Dynamics, vol. 41, pp. 885 - 900,
Sasse TP; McNeil BI; Abramowitz G, 2012, 'A novel method for diagnosing seasonal to inter-annual surface ocean carbon dynamics from bottle data using neural networks', Biogeosciences Discussions, vol. 9, pp. 15329 - 15380,
Abramowitz G; Pouyanne L; Ajami H, 2012, 'On the information content of surface meteorology for downward atmospheric long-wave radiation synthesis', Geophysical Research Letters, vol. 39, pp. L04808,
Abramowitz G, 2012, 'Towards a public, standardized, diagnostic benchmarking system for land surface models', Geoscientific Model Development, vol. 5, pp. 819 - 827,
Gupta HV; Clark MP; Vrugt JA; Abramowitz G; Ye M, 2012, 'Towards a comprehensive assessment of model structural adequacy', Water Resources Research, vol. 48, pp. W08301,
Sasse TP; McNeil BI; Abramowitz G, 2012, 'A novel method for diagnosing seasonal to inter-annual surface ocean carbon dynamics from bottle data using neural networks', Biogeosciences Discussions, vol. 9, pp. 15329 - 15380,
Abramowitz G, 2010, 'Model independence in multi-model ensemble prediction', Australian Meteorological and Oceanographic Journal, vol. 59, pp. 3 - 6,
Abramowitz G; Gupta H, 2008, 'Toward a model space and model independence metric', Geophysical Research Letters, vol. 35,
Abramowitz G, 2005, 'Towards a benchmark for land surface models', Geophysical Research Letters, vol. 32, pp. L22702,
Haughton N; Abramowitz G; Pitman AJ, 'On the Predictability of Land Surface Fluxes from Meteorological Variables', Geoscientific Model Development Discussions, pp. 1 - 27,
Laws RM; Raupach MR; Abramowitz G; Dharssi I; Haverd V; Pitman AJ; Renzullo V; Van DA; Wang , 2013, The Community Atmosphere Biosphere Land Exchange (CABLE) model Roadmap for 2012-2017, The Centre for Australian Weather and Climate Research, Melbourne, CAWCR technical report, 057,
Kowalczyk EA; Wang Y; Law RM; McGregor JL; Abramowitz G, 2006, The CSIRO Atmosphere Biosphere Land Exchange (CABLE) model for use in climate models and as an offline model, CSIRO, The CSIRO Atmosphere Biosphere Land Exchange (CABLE) model for use in climate models and as an offline model, Research Technical Paper 013
Working Papers
Knutti R; Abramowitz G; Collins M; Eyring V; Glecker PJ; Hewitson B; Mearns L, 2010, Good Practice Guidance Paper on Assessing and Combining Multi Model Climate Projections, University of Bern, Switzerland, Meeting Report of the IPCC Working Group I Technical Support Unit,