Evaluation of Land Surface Models in Reproducing Satellite Derived Leaf Area Index over the High-Latitude Northern Hemisphere. Part II: Earth System Models

Abstract Leaf area index (LAI), the total one-sided surface area of leaf per ground surface area, is a key component of land surface models. The authors investigate the influence of differing, plausible LAI prescriptions on heat, moisture, and carbon fluxes simulated by the Community Atmosphere Biosphere Land Exchange version 1.4b (CABLEv1.4b) model over the Australian continent. A 15-member ensemble monthly LAI dataset is generated using the Moderate Resolution Imaging Spectroradiometer (MODIS) LAI product and gridded observations of temperature and precipitation. Offline simulations lasting 29 years (1980–2008) are carried out at 25-km resolution with the composite monthly means from the MODIS LAI product (control simulation) and compared with simulations using each of the 15-member ensemble monthly varying LAI datasets generated. The imposed changes in LAI did not strongly influence the sensible and latent fluxes, but the carbon fluxes were more strongly affected. Croplands showed the largest sensitivity in gross primary production with differences ranging from −90% to 60%. Plant function types (PFTs) with high absolute LAI and low interannual variability, such as evergreen broadleaf trees, showed the least response to the different LAI prescriptions, while those with lower absolute LAI and higher interannual variability, such as croplands, were more sensitive. The authors show that reliance on a single LAI prescription may not accurately reflect the uncertainty in the simulation of terrestrial carbon fluxes, especially for PFTs with high interannual variability. The study highlights that accurate representation of LAI in land surface models is key to the simulation of the terrestrial carbon cycle. Hence, this will become critical in quantifying the uncertainty in future changes in primary production.

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Recent progresses in incorporating human land-water management into global land surface models toward their integration into Earth system models

Wiley Interdisciplinary Reviews Water ◽

10.1002/wat2.1150 ◽

2016 ◽

Vol 3 (4) ◽

pp. 548-574 ◽

Cited By ~ 48

Author(s):

Yadu N. Pokhrel ◽

Naota Hanasaki ◽

Yoshihide Wada ◽

Hyungjun Kim

Keyword(s):

Water Management ◽

Land Surface ◽

Earth System ◽

Land Surface Models ◽

System Models ◽

Surface Models ◽

Global Land ◽

Earth System Models ◽

Land Water

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Evaluation of Land Surface Models in Reproducing Satellite-Derived LAI over the High-Latitude Northern Hemisphere. Part I: Uncoupled DGVMs

Remote Sensing ◽

10.3390/rs5104819 ◽

2013 ◽

Vol 5 (10) ◽

pp. 4819-4838 ◽

Cited By ~ 55

Author(s):

Guillermo Murray-Tortarolo ◽

Alessandro Anav ◽

Pierre Friedlingstein ◽

Stephen Sitch ◽

Shilong Piao ◽

...

Keyword(s):

Northern Hemisphere ◽

High Latitude ◽

Land Surface ◽

Land Surface Models ◽

Surface Models

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Adding some discussion on (emerged) issues when using the data in land surface models of earth system models

10.5194/gmd-2019-360-sc1 ◽

2020 ◽

Keyword(s):

Land Surface ◽

Earth System ◽

Land Surface Models ◽

System Models ◽

Surface Models ◽

Earth System Models

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On the Proper Use of Satellite-Derived Leaf Area Index in Climate Modeling

Journal of Climate ◽

10.1175/2009jcli2868.1 ◽

2009 ◽

Vol 22 (16) ◽

pp. 4427-4433 ◽

Cited By ~ 4

Author(s):

Jianjun Ge

Keyword(s):

Leaf Area Index ◽

Leaf Area ◽

Land Surface ◽

Climate Modeling ◽

Heat Fluxes ◽

Sensible Heat ◽

Area Index ◽

Simulated Precipitation ◽

Surface Models ◽

Improper Use

Abstract Satellite-observed leaf area index (LAI) is increasingly being used in climate modeling. In common land surface models, LAI is specified for the vegetated part only. In contrast, satellite LAI is defined for the total area including both vegetated and nonvegetated fractions. Some recent modeling studies and model developments have not noticed this difference, which resulted in improper use of satellite LAI. This paper clarified this issue. A sensitivity test was carried out using a regional model to investigate the impacts of LAI definitions on simulated climates. This study showed that use of satellite LAI without considering the inconsistency in definition caused much smaller LAI values in the model. As a result, partitioning of surface energy into latent and sensible heat fluxes, as well as the model-simulated precipitation, was affected substantially. Overall, improper use of satellite LAI increased the model biases in simulated precipitation.

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Nitrogen cycling in CMIP6 land surface models: progress and limitations

Biogeosciences ◽

10.5194/bg-17-5129-2020 ◽

2020 ◽

Vol 17 (20) ◽

pp. 5129-5148 ◽

Cited By ~ 1

Author(s):

Taraka Davies-Barnard ◽

Johannes Meyerholt ◽

Sönke Zaehle ◽

Pierre Friedlingstein ◽

Victor Brovkin ◽

...

Keyword(s):

Carbon Dioxide ◽

Nitrogen Cycle ◽

Land Surface ◽

Atmospheric Carbon Dioxide ◽

Earth System ◽

Land Surface Models ◽

System Models ◽

Surface Models ◽

Atmospheric Carbon ◽

Earth System Models

Abstract. The nitrogen cycle and its effect on carbon uptake in the terrestrial biosphere is a recent progression in earth system models. As with any new component of a model, it is important to understand the behaviour, strengths, and limitations of the various process representations. Here we assess and compare five land surface models with nitrogen cycles that are used as the terrestrial components of some of the earth system models in CMIP6. The land surface models were run offline with a common spin-up and forcing protocol. We use a historical control simulation and two perturbations to assess the model nitrogen-related performances: a simulation with atmospheric carbon dioxide increased by 200 ppm and one with nitrogen deposition increased by 50 kgN ha−1 yr−1. There is generally greater variability in productivity response between models to increased nitrogen than to carbon dioxide. Across the five models the response to carbon dioxide globally was 5 % to 20 % and the response to nitrogen was 2 % to 24 %. The models are not evenly distributed within the ensemble range, with two of the models having low productivity response to nitrogen and another one with low response to elevated atmospheric carbon dioxide, compared to the other models. In all five models individual grid cells tend to exhibit bimodality, with either a strong response to increased nitrogen or atmospheric carbon dioxide but rarely to both to an equal extent. However, this local effect does not scale to either the regional or global level. The global and tropical responses are generally more accurately modelled than boreal, tundra, or other high-latitude areas compared to observations. These results are due to divergent choices in the representation of key nitrogen cycle processes. They show the need for more observational studies to enhance understanding of nitrogen cycle processes, especially nitrogen-use efficiency and biological nitrogen fixation.

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Projections of leaf area index in earth system models

Earth System Dynamics ◽

10.5194/esd-7-211-2016 ◽

2016 ◽

Vol 7 (1) ◽

pp. 211-229 ◽

Cited By ~ 44

Author(s):

Natalie Mahowald ◽

Fiona Lo ◽

Yun Zheng ◽

Laura Harrison ◽

Chris Funk ◽

...

Keyword(s):

Climate Change ◽

Leaf Area Index ◽

Leaf Area ◽

Climate Change Impacts ◽

Earth System ◽

Area Index ◽

System Models ◽

Clear Cut ◽

The Tropics ◽

Earth System Models

Abstract. The area of leaves in the plant canopy, measured as leaf area index (LAI), modulates key land–atmosphere interactions, including the exchange of energy, moisture, carbon dioxide (CO2), and other trace gases and aerosols, and is therefore an essential variable in predicting terrestrial carbon, water, and energy fluxes. Here our goal is to characterize the LAI projections from the latest generation of earth system models (ESMs) for the Representative Concentration Pathway (RCP) 8.5 and RCP4.5 scenarios. On average, the models project increases in LAI in both RCP8.5 and RCP4.5 over most of the globe, but also show decreases in some parts of the tropics. Because of projected increases in variability, there are also more frequent periods of low LAI across broad regions of the tropics. Projections of LAI changes varied greatly among models: some models project very modest changes, while others project large changes, usually increases. Modeled LAI typically increases with modeled warming in the high latitudes, but often decreases with increasing local warming in the tropics. The models with the most skill in simulating current LAI in the tropics relative to satellite observations tend to project smaller increases in LAI in the tropics in the future compared to the average of all the models. Using LAI projections to identify regions that may be vulnerable to climate change presents a slightly different picture than using precipitation projections, suggesting LAI may be an additional useful tool for understanding climate change impacts. Going forward, users of LAI projections from the CMIP5 ESMs evaluated here should be aware that model outputs do not exhibit clear-cut relationships to vegetation carbon and precipitation. Our findings underscore the need for more attention to LAI projections, in terms of understanding the drivers of projected changes and improvements to model skill.

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