Articles | Volume 13, issue 11
https://doi.org/10.5194/bg-13-3245-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/bg-13-3245-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Research article
| 
03 Jun 2016
Research article |
| 03 Jun 2016
A model inter-comparison study to examine limiting factors in modelling Australian tropical savannas
Rhys Whitley
CORRESPONDING AUTHOR
Department of Biological Sciences, Macquarie University, North Ryde,
NSW 2109, Australia
Jason Beringer
School of Earth and Environment, University of Western Australia,
Crawley, WA 6009, Australia
Lindsay B. Hutley
School of Environment, Charles Darwin University, Casuarina, NT 0810,
Australia
Gab Abramowitz
Climate Change Research Centre, University of New South Wales,
Kensington, NSW 2033, Australia
Martin G. De Kauwe
Department of Biological Sciences, Macquarie University, North Ryde,
NSW 2109, Australia
Remko Duursma
Hawkesbury Institute for the Environment, University of Western
Sydney, Penrith, New South Wales 2751, Australia
Bradley Evans
Faculty of Agriculture and Environment, University of Sydney,
Eveleigh, NSW 2015, Australia
Vanessa Haverd
CSIRO Ocean and Atmosphere, Canberra 2601, Australia
Longhui Li
School of Life Sciences, University of Technology Sydney, Ultimo, NSW
2007, Australia
Youngryel Ryu
Department of Landscape Architecture and Rural Systems Engineering,
Seoul National University, Seoul, South Korea
Benjamin Smith
Department of Physical Geography and Ecosystem Science, Lund
University, Lund, Sweden
Ying-Ping Wang
CSIRO Ocean and Atmosphere, Aspendale, Victoria 3195, Australia
Mathew Williams
School of GeoSciences, University of Edinburgh, Edinburgh, UK
Qiang Yu
CSIRO Ocean and Atmosphere, Canberra 2601, Australia
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Cited
32 citations as recorded by crossref.
- Dynamic global vegetation models underestimate net CO2 flux mean and inter-annual variability in dryland ecosystems N. MacBean et al. 10.1088/1748-9326/ac1a38
- Divergent impacts of VPD and SWC on ecosystem carbon-water coupling under different dryness conditions C. Zheng et al. 10.1016/j.scitotenv.2023.167007
- Comparison of the performance of latent heat flux products over southern hemisphere forest ecosystems: estimating latent heat flux error structure using in situ measurements and the triple collocation method V. Barraza Bernadas et al. 10.1080/01431161.2018.1458348
- Evaluation of soil moisture from CCAM-CABLE simulation, satellite-based models estimates and satellite observations: a case study of Skukuza and Malopeni flux towers F. Khosa et al. 10.5194/hess-24-1587-2020
- Bridge to the future: Important lessons from 20 years of ecosystem observations made by the OzFlux network J. Beringer et al. 10.1111/gcb.16141
- 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 A. Hirsch et al. 10.1029/2019MS001845
- BESS-STAIR: a framework to estimate daily, 30 m, and all-weather crop evapotranspiration using multi-source satellite data for the US Corn Belt C. Jiang et al. 10.5194/hess-24-1251-2020
- Vegetation optimality explains the convergence of catchments on the Budyko curve R. Nijzink & S. Schymanski 10.5194/hess-26-6289-2022
- Improving Estimation of Seasonal Evapotranspiration in Australian Tropical Savannas using a Flexible Drought Index W. Zhuang et al. 10.1016/j.agrformet.2020.108203
- Assessing the representation of the Australian carbon cycle in global vegetation models L. Teckentrup et al. 10.5194/bg-18-5639-2021
- Exploring the spatial relationship between airborne-derived red and far-red sun-induced fluorescence and process-based GPP estimates in a forest ecosystem G. Tagliabue et al. 10.1016/j.rse.2019.111272
- Root‐zone soil moisture variability across African savannas: From pulsed rainfall to land‐cover switches M. Räsänen et al. 10.1002/eco.2213
- Testing water fluxes and storage from two hydrology configurations within the ORCHIDEE land surface model across US semi-arid sites N. MacBean et al. 10.5194/hess-24-5203-2020
- Optimizing Carbon Cycle Parameters Drastically Improves Terrestrial Biosphere Model Underestimates of Dryland Mean Net CO2 Flux and its Inter‐Annual Variability K. Mahmud et al. 10.1029/2021JG006400
- Modeling gas exchange and biomass production in West African Sahelian and Sudanian ecological zones J. Rahimi et al. 10.5194/gmd-14-3789-2021
- Comparison of Nighttime With Daytime Evapotranspiration Responses to Environmental Controls Across Temporal Scales Along a Climate Gradient Q. Han et al. 10.1029/2021WR029638
- Does maximization of net carbon profit enable the prediction of vegetation behaviour in savanna sites along a precipitation gradient? R. Nijzink et al. 10.5194/hess-26-525-2022
- FluxnetLSM R package (v1.0): a community tool for processing FLUXNET data for use in land surface modelling A. Ukkola et al. 10.5194/gmd-10-3379-2017
- New turbulent resistance parameterization for soil evaporation based on a pore‐scale model: Impact on surface fluxes in CABLE M. Decker et al. 10.1002/2016MS000832
- Challenges and opportunities in land surface modelling of savanna ecosystems R. Whitley et al. 10.5194/bg-14-4711-2017
- Evaluating CMIP5 Model Agreement for Multiple Drought Metrics A. Ukkola et al. 10.1175/JHM-D-17-0099.1
- A fiery wake-up call for climate science B. Sanderson & R. Fisher 10.1038/s41558-020-0707-2
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- Inappropriateness of space-for-time and variability-for-time approaches to infer future dryland productivity changes W. Zhan et al. 10.3389/fenvs.2022.1010269
- Multi-scale evaluation of global gross primary productivity and evapotranspiration products derived from Breathing Earth System Simulator (BESS) C. Jiang & Y. Ryu 10.1016/j.rse.2016.08.030
- Land surface models systematically overestimate the intensity, duration and magnitude of seasonal-scale evaporative droughts A. Ukkola et al. 10.1088/1748-9326/11/10/104012
- Preface: OzFlux: a network for the study of ecosystem carbon and water dynamics across Australia and New Zealand E. van Gorsel et al. 10.5194/bg-15-349-2018
- Examining the role of environmental memory in the predictability of carbon and water fluxes across Australian ecosystems J. Cranko Page et al. 10.5194/bg-19-1913-2022
- Using phenology to unravel differential soil water use and productivity in a semiarid savanna B. Steiner et al. 10.1002/ecs2.4762
- Influence of modifications (from AoB2015 to v0.5) in the Vegetation Optimality Model R. Nijzink et al. 10.5194/gmd-15-883-2022
- Dryland productivity under a changing climate L. Wang et al. 10.1038/s41558-022-01499-y
- Large‐scale prerain vegetation green‐up across Africa T. Adole et al. 10.1111/gcb.14310
32 citations as recorded by crossref.
- Dynamic global vegetation models underestimate net CO2 flux mean and inter-annual variability in dryland ecosystems N. MacBean et al. 10.1088/1748-9326/ac1a38
- Divergent impacts of VPD and SWC on ecosystem carbon-water coupling under different dryness conditions C. Zheng et al. 10.1016/j.scitotenv.2023.167007
- Comparison of the performance of latent heat flux products over southern hemisphere forest ecosystems: estimating latent heat flux error structure using in situ measurements and the triple collocation method V. Barraza Bernadas et al. 10.1080/01431161.2018.1458348
- Evaluation of soil moisture from CCAM-CABLE simulation, satellite-based models estimates and satellite observations: a case study of Skukuza and Malopeni flux towers F. Khosa et al. 10.5194/hess-24-1587-2020
- Bridge to the future: Important lessons from 20 years of ecosystem observations made by the OzFlux network J. Beringer et al. 10.1111/gcb.16141
- 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 A. Hirsch et al. 10.1029/2019MS001845
- BESS-STAIR: a framework to estimate daily, 30 m, and all-weather crop evapotranspiration using multi-source satellite data for the US Corn Belt C. Jiang et al. 10.5194/hess-24-1251-2020
- Vegetation optimality explains the convergence of catchments on the Budyko curve R. Nijzink & S. Schymanski 10.5194/hess-26-6289-2022
- Improving Estimation of Seasonal Evapotranspiration in Australian Tropical Savannas using a Flexible Drought Index W. Zhuang et al. 10.1016/j.agrformet.2020.108203
- Assessing the representation of the Australian carbon cycle in global vegetation models L. Teckentrup et al. 10.5194/bg-18-5639-2021
- Exploring the spatial relationship between airborne-derived red and far-red sun-induced fluorescence and process-based GPP estimates in a forest ecosystem G. Tagliabue et al. 10.1016/j.rse.2019.111272
- Root‐zone soil moisture variability across African savannas: From pulsed rainfall to land‐cover switches M. Räsänen et al. 10.1002/eco.2213
- Testing water fluxes and storage from two hydrology configurations within the ORCHIDEE land surface model across US semi-arid sites N. MacBean et al. 10.5194/hess-24-5203-2020
- Optimizing Carbon Cycle Parameters Drastically Improves Terrestrial Biosphere Model Underestimates of Dryland Mean Net CO2 Flux and its Inter‐Annual Variability K. Mahmud et al. 10.1029/2021JG006400
- Modeling gas exchange and biomass production in West African Sahelian and Sudanian ecological zones J. Rahimi et al. 10.5194/gmd-14-3789-2021
- Comparison of Nighttime With Daytime Evapotranspiration Responses to Environmental Controls Across Temporal Scales Along a Climate Gradient Q. Han et al. 10.1029/2021WR029638
- Does maximization of net carbon profit enable the prediction of vegetation behaviour in savanna sites along a precipitation gradient? R. Nijzink et al. 10.5194/hess-26-525-2022
- FluxnetLSM R package (v1.0): a community tool for processing FLUXNET data for use in land surface modelling A. Ukkola et al. 10.5194/gmd-10-3379-2017
- New turbulent resistance parameterization for soil evaporation based on a pore‐scale model: Impact on surface fluxes in CABLE M. Decker et al. 10.1002/2016MS000832
- Challenges and opportunities in land surface modelling of savanna ecosystems R. Whitley et al. 10.5194/bg-14-4711-2017
- Evaluating CMIP5 Model Agreement for Multiple Drought Metrics A. Ukkola et al. 10.1175/JHM-D-17-0099.1
- A fiery wake-up call for climate science B. Sanderson & R. Fisher 10.1038/s41558-020-0707-2
- A flux tower dataset tailored for land model evaluation A. Ukkola et al. 10.5194/essd-14-449-2022
- Inappropriateness of space-for-time and variability-for-time approaches to infer future dryland productivity changes W. Zhan et al. 10.3389/fenvs.2022.1010269
- Multi-scale evaluation of global gross primary productivity and evapotranspiration products derived from Breathing Earth System Simulator (BESS) C. Jiang & Y. Ryu 10.1016/j.rse.2016.08.030
- Land surface models systematically overestimate the intensity, duration and magnitude of seasonal-scale evaporative droughts A. Ukkola et al. 10.1088/1748-9326/11/10/104012
- Preface: OzFlux: a network for the study of ecosystem carbon and water dynamics across Australia and New Zealand E. van Gorsel et al. 10.5194/bg-15-349-2018
- Examining the role of environmental memory in the predictability of carbon and water fluxes across Australian ecosystems J. Cranko Page et al. 10.5194/bg-19-1913-2022
- Using phenology to unravel differential soil water use and productivity in a semiarid savanna B. Steiner et al. 10.1002/ecs2.4762
- Influence of modifications (from AoB2015 to v0.5) in the Vegetation Optimality Model R. Nijzink et al. 10.5194/gmd-15-883-2022
- Dryland productivity under a changing climate L. Wang et al. 10.1038/s41558-022-01499-y
- Large‐scale prerain vegetation green‐up across Africa T. Adole et al. 10.1111/gcb.14310
Saved (preprint)
Latest update: 23 Nov 2024
Short summary
In this study we assess how well terrestrial biosphere models perform at predicting water and carbon cycling for savanna ecosystems. We apply our models to five savanna sites in Northern Australia and highlight key causes for model failure. Our assessment of model performance uses a novel benchmarking system that scores a model’s predictive ability based on how well it is utilizing its driving information. On average, we found the models as a group display only moderate levels of performance.
In this study we assess how well terrestrial biosphere models perform at predicting water and...
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