By Professor Gab Abramowitz

Journal articles

Rampal N; Gibson PB; Sherwood S; Abramowitz G, 2024, 'On the Extrapolation of Generative Adversarial Networks for Downscaling Precipitation Extremes in Warmer Climates', Geophysical Research Letters, 51, http://dx.doi.org/10.1029/2024GL112492

Abramowitz G; Ukkola A; Hobeichi S; Page JC; Lipson M; De Kauwe MG; Green S; Brenner C; Frame J; Nearing G; Clark M; Best M; Anthoni P; Arduini G; Boussetta S; Caldararu S; Cho K; Cuntz M; Fairbairn D; Ferguson CR; Kim H; Kim Y; Knauer J; Lawrence D; Luo X; Malyshev S; Nitta T; Ogee J; Oleson K; Ottlé C; Peylin P; de Rosnay P; Rumbold H; Su B; Vuichard N; Walker AP; Wang-Faivre X; Wang Y; Zeng Y, 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

Hobeichi S; Abramowitz G; Sen Gupta A; Taschetto AS; Richardson D; Rampal N; Ayat H; Alexander LV; Pitman AJ, 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

Shao Y; Bishop C; Abramowitz G; Hobeichi S, 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

Hobeichi S; Shao Y; Rampal N; Bittner M; Abramowitz G, 2024, 'Revisiting Tabular Machine Learning and Sequential Models to Advance Climate Downscaling', , http://dx.doi.org/10.5194/egusphere-egu24-7111

Greco IC; Sherwood SC; Raupach TH; Abramowitz G, 2024, 'A Bayesian framework for the probabilistic interpretation of radar observations and severe hailstorm reports', Weather and Forecasting, http://dx.doi.org/10.1175/waf-d-24-0019.1

Wang L; Abramowitz G; Wang YP; Pitman A; Viscarra Rossel RA, 2024, 'An ensemble estimate of Australian soil organic carbon using machine learning and process-based modelling', SOIL, 10, pp. 619 - 636, http://dx.doi.org/10.5194/soil-10-619-2024

Devanand A; Falster GM; Gillett ZE; Hobeichi S; Holgate CM; Jin C; Mu M; Parker T; Rifai SW; Rome KS; Stojanovic M; Vogel E; Abram NJ; Abramowitz G; Coats S; Evans JP; Gallant AJE; Pitman AJ; Power SB; Rauniyar SP; Taschetto AS; Ukkola AM, 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

Shao Y; Bishop CH; Hobeichi S; Nishant N; Abramowitz G; Sherwood S, 2024, 'Time Variability Correction of CMIP6 Climate Change Projections', Journal of Advances in Modeling Earth Systems, 16, http://dx.doi.org/10.1029/2023MS003640

Cranko Page J; Abramowitz G; De Kauwe MG; Pitman AJ, 2024, 'Are Plant Functional Types Fit for Purpose?', Geophysical Research Letters, 51, http://dx.doi.org/10.1029/2023GL104962

Lipson MJ; Grimmond S; Best M; Abramowitz G; Coutts A; Tapper N; Baik JJ; Beyers M; Blunn L; Boussetta S; Bou-Zeid E; De Kauwe MG; de Munck C; Demuzere M; Fatichi S; Fortuniak K; Han BS; Hendry MA; Kikegawa Y; Kondo H; Lee DI; Lee SH; Lemonsu A; Machado T; Manoli G; Martilli A; Masson V; McNorton J; Meili N; Meyer D; Nice KA; Oleson KW; Park SB; Roth M; Schoetter R; Simón-Moral A; Steeneveld GJ; Sun T; Takane Y; Thatcher M; Tsiringakis A; Varentsov M; Wang C; Wang ZH; Pitman AJ, 2024, 'Evaluation of 30 urban land surface models in the Urban-PLUMBER project: Phase 1 results', Quarterly Journal of the Royal Meteorological Society, 150, pp. 126 - 169, http://dx.doi.org/10.1002/qj.4589

Rampal N; Hobeichi S; Gibson PB; Baño-Medina J; Abramowitz G; Beucler T; González-Abad J; Chapman W; Harder P; Gutiérrez JM, 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

Rey-Costa E; Elliston B; Green D; Abramowitz G, 2023, 'Firming 100% renewable power: Costs and opportunities in Australia's National Electricity Market', Renewable Energy, 219, http://dx.doi.org/10.1016/j.renene.2023.119416

Nishant N; Hobeichi S; Sherwood S; Abramowitz G; Shao Y; Bishop C; Pitman A, 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

Devanand A; Evans JP; Abramowitz G; Hobeichi S; Pitman AJ, 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

Cranko Page J; De Kauwe MG; Abramowitz G; Pitman AJ, 2023, 'Non-Stationary Lags and Legacies in Ecosystem Flux Response to Antecedent Rainfall', Journal of Geophysical Research: Biogeosciences, 128, http://dx.doi.org/10.1029/2022JG007144

Teckentrup L; De Kauwe MG; Abramowitz G; Pitman AJ; Ukkola AM; Hobeichi S; François B; Smith B, 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

Grose MR; Narsey S; Trancoso R; Mackallah C; Delage F; Dowdy A; Di Virgilio G; Watterson I; Dobrohotoff P; Rashid HA; Rauniyar S; Henley B; Thatcher M; Syktus J; Abramowitz G; Evans JP; Su CH; Takbash A, 2023, 'A CMIP6-based multi-model downscaling ensemble to underpin climate change services in Australia', Climate Services, 30, http://dx.doi.org/10.1016/j.cliser.2023.100368

Hobeichi S; Nishant N; Shao Y; Abramowitz G; Pitman A; Sherwood S; Bishop C; Green S, 2023, 'Using Machine Learning to Cut the Cost of Dynamical Downscaling', Earth's Future, 11, http://dx.doi.org/10.1029/2022EF003291

Pitman AJ; Fiedler T; Ranger N; Jakob C; Ridder N; Perkins-Kirkpatrick S; Wood N; Abramowitz G, 2022, 'Acute climate risks in the financial system: examining the utility of climate model projections', Environmental Research: Climate, 1, pp. 025002 - 025002, http://dx.doi.org/10.1088/2752-5295/ac856f

Hobeichi S; Abramowitz G; Ukkola AM; De Kauwe M; Pitman A; Evans JP; Beck H, 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

Page JC; De Kauwe MG; Abramowitz G; Cleverly J; Hinko-Najera N; Hovenden MJ; Liu Y; Pitman AJ; Ogle K, 2022, 'Examining the role of environmental memory in the predictability of carbon and water fluxes across Australian ecosystems', Biogeosciences, 19, pp. 1913 - 1932, http://dx.doi.org/10.5194/bg-19-1913-2022

Ukkola AM; Abramowitz G; De Kauwe MG, 2022, 'A flux tower dataset tailored for land model evaluation', Earth System Science Data, 14, pp. 449 - 461, http://dx.doi.org/10.5194/essd-14-449-2022

Hobeichi S; Abramowitz G; Evans JP; Ukkola A, 2022, 'Toward a Robust, Impact-Based, Predictive Drought Metric', Water Resources Research, 58, http://dx.doi.org/10.1029/2021WR031829

Chang Z; Hobeichi S; Wang YP; Tang X; Abramowitz G; Chen Y; Cao N; Yu M; Huang H; Zhou G; Wang G; Ma K; Du S; Li S; Han S; Ma Y; Wigneron JP; Fan L; Saatchi SS; Yan J, 2021, 'New forest aboveground biomass maps of China integrating multiple datasets', Remote Sensing, 13, http://dx.doi.org/10.3390/rs13152892

Ukkola AM; Abramowitz G; De Kauwe MG, 2021, 'A flux tower dataset tailored for land model evaluation', , http://dx.doi.org/10.5194/essd-2021-181

Hobeichi S; Abramowitz G; Evans JP, 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

Page J; De Kauwe M; Abramowitz G, 2021, 'Exploring the role of lags and legacies in the productivity of Australian ecosystems', , http://dx.doi.org/10.5194/egusphere-egu21-3684

Renner M; Kleidon A; Clark M; Nijssen B; Heidkamp M; Best M; Abramowitz G, 2020, 'How well can land-surface models represent the diurnal cycle of turbulent heat fluxes?', Journal of Hydrometeorology, 22, pp. 77 - 94, http://dx.doi.org/10.1175/JHM-D-20-0034.1

Ukkola AM; De Kauwe MG; Roderick ML; Abramowitz G; Pitman AJ, 2020, 'Robust Future Changes in Meteorological Drought in CMIP6 Projections Despite Uncertainty in Precipitation', Geophysical Research Letters, 47, http://dx.doi.org/10.1029/2020GL087820

Sabot MEB; De Kauwe MG; Pitman AJ; Medlyn BE; Verhoef A; Ukkola AM; Abramowitz G, 2020, 'Plant profit maximization improves predictions of European forest responses to drought', New Phytologist, 226, pp. 1638 - 1655, http://dx.doi.org/10.1111/nph.16376

Massari C; Brocca L; Pellarin T; Abramowitz G; Filippucci P; Ciabatta L; Maggioni V; Kerr Y; Fernandez Prieto D, 2020, 'A daily 25 km short-latency rainfall product for data-scarce regions based on the integration of the Global Precipitation Measurement mission rainfall and multiple-satellite soil moisture products', Hydrology and Earth System Sciences, 24, pp. 2687 - 2710, http://dx.doi.org/10.5194/hess-24-2687-2020

Hobeichi S; Abramowitz G; Contractor S; Evans J, 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

Lipson MJ; Grimmond S; Best MJ; Abramowitz G; Pitman AJ; Ward HC, 2020, 'Urban-PLUMBER: A new evaluation and benchmarking project for land surface models in urban areas', , http://dx.doi.org/10.5194/egusphere-egu2020-20987

Ukkola AM; De Kauwe MG; Roderick ML; Abramowitz G; Pitman AJ, 2020, 'Robust future changes in meteorological drought in CMIP6 projections despite uncertainty in precipitation', , http://dx.doi.org/10.1002/essoar.10502465.1

Hobeichi S; Abramowitz G; Evans J, 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

Hirsch AL; Kala J; Carouge CC; De Kauwe MG; Di Virgilio G; Ukkola AM; Evans JP; Abramowitz G, 2019, 'Evaluation of the CABLEv2.3.4 Land Surface Model Coupled to NU-WRFv3.9.1.1 in Simulating Temperature and Precipitation Means and Extremes Over CORDEX AustralAsia Within a WRF Physics Ensemble', Journal of Advances in Modeling Earth Systems, 11, pp. 4466 - 4488, http://dx.doi.org/10.1029/2019MS001845

Herger N; Abramowitz G; Sherwood S; Knutti R; Angélil O; Sisson SA; Angelil O, 2019, 'Ensemble optimisation, multiple constraints and overconfidence: a case study with future Australian precipitation change', Climate Dynamics, 53, pp. 1581 - 1596, http://dx.doi.org/10.1007/s00382-019-04690-8

Massari C; Brocca L; Pellarin T; Abramowitz G; Filippucci P; Ciabatta L; Maggioni V; Kerr Y; Fernandez Prieto D, 2019, 'A daily/25 km short-latency rainfall product for data scarce regions based on the integration of the GPM IMERG Early Run with multiple satellite soil moisture products', , http://dx.doi.org/10.5194/hess-2019-387

Van Der Horst SVJ; Pitman AJ; De Kauwe MG; Ukkola A; Abramowitz G; Isaac P, 2019, 'How representative are FLUXNET measurements of surface fluxes during temperature extremes?', Biogeosciences, 16, pp. 1829 - 1844, http://dx.doi.org/10.5194/bg-16-1829-2019

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, 10, pp. 91 - 105, http://dx.doi.org/10.5194/esd-10-91-2019

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, 23, pp. 851 - 870, http://dx.doi.org/10.5194/hess-23-851-2019

Eyring V; Cox PM; Flato GM; Gleckler PJ; Abramowitz G; Caldwell P; Collins WD; Gier BK; Hall AD; Hoffman FM; Hurtt GC; Jahn A; Jones CD; Klein SA; Krasting JP; Kwiatkowski L; Lorenz R; Maloney E; Meehl GA; Pendergrass AG; Pincus R; Ruane AC; Russell JL; Sanderson BM; Santer BD; Sherwood SC; Simpson IR; Stouffer RJ; Williamson MS, 2019, 'Taking climate model evaluation to the next level', Nature Climate Change, 9, pp. 102 - 110, http://dx.doi.org/10.1038/s41558-018-0355-y

Hobeichi S; Abramowitz G; Evans J; Beck HE, 2018, 'Linear Optimal Runoff Aggregate (LORA): A global gridded synthesis runoff product', , http://dx.doi.org/10.5194/hess-2018-386

Haughton N; Abramowitz G; De Kauwe MG; Pitman AJ, 2018, 'Does predictability of fluxes vary between FLUXNET sites?', Biogeosciences, 15, pp. 4495 - 4513, http://dx.doi.org/10.5194/bg-15-4495-2018

Herger N; Angélil O; Abramowitz G; Donat M; Stone D; Lehmann K; Angelil O, 2018, 'Calibrating Climate Model Ensembles for Assessing Extremes in a Changing Climate', Journal of Geophysical Research: Atmospheres, 123, pp. 5988 - 6004, http://dx.doi.org/10.1029/2018JD028549

Ukkola AM; Pitman AJ; De Kauwe MG; Abramowitz G; Herger N; Evans JP; Decker M, 2018, 'Evaluating CMIP5 model agreement for multiple drought metrics', Journal of Hydrometeorology, 19, pp. 969 - 988, http://dx.doi.org/10.1175/JHM-D-17-0099.1

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, 22, pp. 1317 - 1336, http://dx.doi.org/10.5194/hess-22-1317-2018

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, 9, pp. 135 - 151, http://dx.doi.org/10.5194/esd-9-135-2018

Haughton N; Abramowitz G; Pitman AJ, 2018, 'On the predictability of land surface fluxes from meteorological variables', Geoscientific Model Development, 11, pp. 195 - 212, http://dx.doi.org/10.5194/gmd-11-195-2018

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