Select Publications
Journal articles
2025, 'Predicting Australian energy demand variability using weather data and machine learning', ENVIRONMENTAL RESEARCH LETTERS, 20, http://dx.doi.org/10.1088/1748-9326/ad9b3b
,2024, 'On the predictability of turbulent fluxes from land: PLUMBER2 MIP experimental description and preliminary results', Biogeosciences, 21, pp. 5517 - 5538, http://dx.doi.org/10.5194/bg-21-5517-2024
,2024, 'How well do climate modes explain precipitation variability?', npj Climate and Atmospheric Science, 7, http://dx.doi.org/10.1038/s41612-024-00853-5
,2024, 'Improving Multi-model Ensembles of Climate Projections through Time Variability Correction and Ensemble Dependence Transformation', , http://dx.doi.org/10.5194/egusphere-egu24-6796
,2024, 'Revisiting Tabular Machine Learning and Sequential Models to Advance Climate Downscaling', , http://dx.doi.org/10.5194/egusphere-egu24-7111
,2024, 'Examining the role of biophysical feedbacks on simulated temperature extremes during the Tinderbox Drought and Black Summer bushfires in southeast Australia', Weather and Climate Extremes, 45, http://dx.doi.org/10.1016/j.wace.2024.100703
,2024, 'Australia’s Tinderbox Drought: An extreme natural event likely worsened by human-caused climate change', Science Advances, 10, http://dx.doi.org/10.1126/sciadv.adj3460
,2024, 'Time Variability Correction of CMIP6 Climate Change Projections', Journal of Advances in Modeling Earth Systems, 16, http://dx.doi.org/10.1029/2023MS003640
,2024, 'Enhancing Regional Climate Downscaling through Advances in Machine Learning', Artificial Intelligence for the Earth Systems, 3, http://dx.doi.org/10.1175/aies-d-23-0066.1
,2023, 'Comparison of a novel machine learning approach with dynamical downscaling for Australian precipitation', Environmental Research Letters, 18, http://dx.doi.org/10.1088/1748-9326/ace463
,2023, 'What is the probability that a drought will break in Australia?', Weather and Climate Extremes, 41, http://dx.doi.org/10.1016/j.wace.2023.100598
,2023, 'Opening Pandora's box: Reducing global circulation model uncertainty in Australian simulations of the carbon cycle', Earth System Dynamics, 14, pp. 549 - 576, http://dx.doi.org/10.5194/esd-14-549-2023
,2023, 'Using Machine Learning to Cut the Cost of Dynamical Downscaling', Earth's Future, 11, http://dx.doi.org/10.1029/2022EF003291
,2023, 'Estimating Aboveground Carbon Dynamic of China Using Optical and Microwave Remote-Sensing Datasets from 2013 to 2019', Journal of Remote Sensing (United States), 3, http://dx.doi.org/10.34133/remotesensing.0005
,2022, 'Reconciling historical changes in the hydrological cycle over land', npj Climate and Atmospheric Science, 5, http://dx.doi.org/10.1038/s41612-022-00240-y
,2022, 'Bridge to the future: Important lessons from 20 years of ecosystem observations made by the OzFlux network', Global Change Biology, 28, pp. 3489 - 3514, http://dx.doi.org/10.1111/gcb.16141
,2022, 'Toward a Robust, Impact-Based, Predictive Drought Metric', Water Resources Research, 58, http://dx.doi.org/10.1029/2021WR031829
,2021, 'Exploring how groundwater buffers the influence of heatwaves on vegetation function during multi-year droughts', Earth System Dynamics, 12, pp. 919 - 938, http://dx.doi.org/10.5194/esd-12-919-2021
,2021, 'New forest aboveground biomass maps of China integrating multiple datasets', Remote Sensing, 13, http://dx.doi.org/10.3390/rs13152892
,2021, 'Robust historical evapotranspiration trends across climate regimes', Hydrology and Earth System Sciences, 25, pp. 3855 - 3874, http://dx.doi.org/10.5194/hess-25-3855-2021
,2021, 'Towards a robust, impact-based, predictive drought metric', , http://dx.doi.org/10.1002/essoar.10507062.1
,2021, 'Exploring how groundwater buffers the influence of heatwaves on vegetation function during multi-year droughts', , http://dx.doi.org/10.5194/esd-2021-31
,2020, 'Evaluating precipitation datasets using surface water and energy budget closure', Journal of Hydrometeorology, 21, pp. 989 - 1009, http://dx.doi.org/10.1175/JHM-D-19-0255.1
,2020, 'Conserving land-atmosphere synthesis suite (CLASS)', Journal of Climate, 33, pp. 1821 - 1844, http://dx.doi.org/10.1175/JCLI-D-19-0036.1
,2019, 'Linear Optimal Runoff Aggregate (LORA): A global gridded synthesis runoff product', Hydrology and Earth System Sciences, 23, pp. 851 - 870, http://dx.doi.org/10.5194/hess-23-851-2019
,2018, 'Derived Optimal Linear Combination Evapotranspiration (DOLCE): A global gridded synthesis et estimate', Hydrology and Earth System Sciences, 22, pp. 1317 - 1336, http://dx.doi.org/10.5194/hess-22-1317-2018
,Conference Papers
2015, 'Toward the development of a remote sensing and field data framework to aid management decisions in the state of Qatar coastal environment', in Qatar University Life Science Symposium-QULSS 2015 Global Changes: The Arabian Gulf Ecosystem, Hamad bin Khalifa University Press (HBKU Press), presented at Qatar University Life Science Symposium-QULSS 2015 Global Changes: The Arabian Gulf Ecosystem, http://dx.doi.org/10.5339/qproc.2015.qulss2015.13
,Preprints
2024, Machine Learning Predicts Pedestrian Wind Flow from Urban Morphology and Prevailing Wind Direction, http://dx.doi.org/10.31223/x5f717
,2024, Resolution-Agnostic Transformer-based Climate Downscaling, http://dx.doi.org/10.48550/arxiv.2411.14774
,2024, A Reliable Generative Adversarial Network Approach for Climate Downscaling and Weather Generation, http://dx.doi.org/10.22541/essoar.171352077.78968815/v2
,2024, A Robust Generative Adversarial Network Approach for Climate Downscaling and Weather Generation, http://dx.doi.org/10.22541/essoar.171352077.78968815/v1
,2024, On the predictability of turbulent fluxes from land: PLUMBER2 MIP experimental description and preliminary results, http://dx.doi.org/10.5194/egusphere-2023-3084
,2023, Australia’s Tinderbox Drought: an extreme natural event likely worsened by human-caused climate change, http://dx.doi.org/10.31223/x53q2b
,2022, Opening Pandora's box: How to constrain regional projections of the carbon cycle, http://dx.doi.org/10.5194/egusphere-2022-623
,2020, Robust historical evapotranspiration trends across climate regimes, http://dx.doi.org/10.5194/hess-2020-595
,What is the Probability that a Drought Will Break in Australia?, http://dx.doi.org/10.2139/ssrn.4251061
,Other
2024, Understanding past changes in Australian droughts and their drivers, http://dx.doi.org/10.5194/egusphere-egu24-1738
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