scholarly journals Improving the ISBA<sub>CC</sub> land surface model simulation of water and carbon fluxes and stocks over the Amazon forest

2015 ◽  
Vol 8 (2) ◽  
pp. 1293-1336
Author(s):  
E. Joetzjer ◽  
C. Delire ◽  
H. Douville ◽  
P. Ciais ◽  
B. Decharme ◽  
...  
Keyword(s):  
Land Surface ◽  
Model Simulation ◽  
Meta Analysis ◽  
Land Surface Model ◽  
Carbon Fluxes ◽  
Surface Model ◽  
Amazon Forest ◽  
Autotrophic Respiration ◽  
Soil Water Stress ◽  
Use Efficiency

Abstract. We evaluate the ISBACC land surface model over the Amazon forest, and propose a revised parameterization of photosynthesis, including new soil water stress and autotrophic respiration functions. The revised version allows the model to better capture the energy, water and carbon fluxes when compared to five Amazonian fluxtowers. The performance of ISBACC is slightly site-dependent but similar to the widely evaluated land surface model ORCHIDEE, based on different assumptions. Changes made to the autotrophic respiration functions, including a vertical profile of leaf respiration, leads to simulate yearly carbon use efficiency and carbon stocks consistent with an ecophysiological meta analysis conducted on three Amazonian sites. Despite these major improvements, ISBACC struggles to capture the apparent seasonality of the carbon fluxes derived from the fluxtower estimations. However, there is still no consensus on the seasonality of carbon fluxes over the Amazon, stressing a need for more observations as well as a better understanding of the main drivers of autotrophic respiration.

scholarly journals Improving the ISBA<sub>CC</sub> land surface model simulation of water and carbon fluxes and stocks over the Amazon forest

2015 ◽  
Vol 8 (6) ◽  
pp. 1709-1727 ◽  
Author(s):  
E. Joetzjer ◽  
C. Delire ◽  
H. Douville ◽  
P. Ciais ◽  
B. Decharme ◽  
...  
Keyword(s):  
Land Surface ◽  
Model Simulation ◽  
Meta Analysis ◽  
Land Surface Model ◽  
Carbon Fluxes ◽  
Surface Model ◽  
Amazon Forest ◽  
Autotrophic Respiration ◽  
Soil Water Stress ◽  
Use Efficiency

Abstract. We evaluate the ISBACC (Interaction Soil Biosphere Atmosphere Carbon Cycle) land surface model (LSM) over the Amazon forest, and propose a revised parameterization of photosynthesis, including new soil water stress and autotrophic respiration (RA) functions. The revised version allows the model to better capture the energy, water and carbon fluxes when compared to five Amazonian flux towers. The performance of ISBACC is slightly site dependent although similar to the widely evaluated LSM ORCHIDEE (Organizing Carbon and Hydrology In Dynamic Ecosystems – version 1187), which is based on different assumptions. Changes made to the autotrophic respiration functions, including a vertical profile of leaf respiration, lead to yearly simulated carbon use efficiency (CUE) and carbon stocks which is consistent with an ecophysiological meta-analysis conducted on three Amazonian sites. Despite these major improvements, ISBACC struggles to capture the apparent seasonality of the carbon fluxes derived from the flux tower estimations. However, there is still no consensus on the seasonality of carbon fluxes over the Amazon, stressing a need for more observations as well as a better understanding of the main drivers of autotrophic respiration.

scholarly journals Multidataset Study of Optimal Parameter and Uncertainty Estimation of a Land Surface Model with Bayesian Stochastic Inversion and Multicriteria Method

2004 ◽  
Vol 43 (10) ◽  
pp. 1477-1497 ◽  
Author(s):  
Youlong Xia ◽  
Mrinal K. Sen ◽  
Charles S. Jackson ◽  
Paul L. Stoffa
Keyword(s):  
Land Surface ◽  
Root Zone ◽  
Model Simulation ◽  
Optimal Parameter ◽  
Land Surface Model ◽  
Heat Fluxes ◽  
Surface Model ◽  
Optimal Parameters ◽  
Stochastic Inversion ◽  
The Impact

Abstract This study evaluates the ability of Bayesian stochastic inversion (BSI) and multicriteria (MC) methods to search for the optimal parameter sets of the Chameleon Surface Model (CHASM) using prescribed forcing to simulate observed sensible and latent heat fluxes from seven measurement sites representative of six biomes including temperate coniferous forests, tropical forests, temperate and tropical grasslands, temperate crops, and semiarid grasslands. Calibration results with the BSI and MC show that estimated optimal values are very similar for the important parameters that are specific to the CHASM model. The model simulations based on estimated optimal parameter sets perform much better than the default parameter sets. Cross-validations for two tropical forest sites show that the calibrated parameters for one site can be transferred to another site within the same biome. The uncertainties of optimal parameters are obtained through BSI, which estimates a multidimensional posterior probability density function (PPD). Marginal PPD analyses show that nonoptimal choices of stomatal resistance would contribute most to model simulation errors at all sites, followed by ground and vegetation roughness length at six of seven sites. The impact of initial root-zone soil moisture and nonmosaic approach on estimation of optimal parameters and their uncertainties is discussed.

scholarly journals Assimilation of Remotely Sensed Leaf Area Index into the Noah-MP Land Surface Model: Impacts on Water and Carbon Fluxes and States over the Continental United States

2019 ◽  
Vol 20 (7) ◽  
pp. 1359-1377 ◽  
Author(s):  
Sujay V. Kumar ◽  
David M. Mocko ◽  
Shugong Wang ◽  
Christa D. Peters-Lidard ◽  
Jordan Borak
Keyword(s):  
United States ◽  
Leaf Area Index ◽  
Leaf Area ◽  
Land Surface ◽  
Land Surface Model ◽  
Carbon Fluxes ◽  
Surface Model ◽  
Vegetation Changes ◽  
Area Index ◽  
Terrestrial Water

Abstract Accurate representation of vegetation states is required for the modeling of terrestrial water–energy–carbon exchanges and the characterization of the impacts of natural and anthropogenic vegetation changes on the land surface. This study presents a comprehensive evaluation of the impact of assimilating remote sensing–based leaf area index (LAI) retrievals over the continental United States in the Noah-MP land surface model, during a time period of 2000–17. The results demonstrate that the assimilation has a beneficial impact on the simulation of key water budget terms, such as soil moisture, evapotranspiration, snow depth, terrestrial water storage, and streamflow, when compared with a large suite of reference datasets. In addition, the assimilation of LAI is also found to improve the carbon fluxes of gross primary production (GPP) and net ecosystem exchange (NEE). Most prominent improvements in the water and carbon variables are observed over the agricultural areas of the United States, where assimilation improves the representation of vegetation seasonality impacted by cropping schedules. The systematic, added improvements from assimilation in a configuration that employs high-quality boundary conditions highlight the significant utility of LAI data assimilation in capturing the impacts of vegetation changes.

scholarly journals Towards Effective Drought Monitoring in the Middle East and North Africa (MENA) Region: Implications from Assimilating Leaf Area Index and Soil Moisture into the Noah-MP Land Surface Model for Morocco

2021 ◽  
Author(s):  
Wanshu Nie ◽  
Sujay V. Kumar ◽  
Kristi R. Arsenault ◽  
Christa D. Peters-Lidard ◽  
Iliana E. Mladenova ◽  
...  
Keyword(s):  
Soil Moisture ◽  
North Africa ◽  
Land Surface ◽  
Land Surface Model ◽  
Warning System ◽  
Carbon Fluxes ◽  
Surface Model ◽  
Severe Drought ◽  
Mena Region ◽  
Area Index

Abstract. The Middle East and North Africa (MENA) region has experienced more frequent and severe drought events in recent decades, leading to increasingly pressing concerns over already strained food and water security. An effective drought monitoring and early warning system is thus critical to support risk mitigation and management by countries in the region. Here we investigate the potential for assimilation of leaf area index (LAI) and soil moisture observations to improve representation of the overall hydrological and carbon cycles and drought by an advanced land surface model. The results reveal that assimilating soil moisture does not meaningfully improve model representation of the hydrological and biospheric processes for this region, but rather it degrades simulation of interannual variation of evapotranspiration (ET) and carbon fluxes, mainly due to model weaknesses in representing dynamic phenology. However, assimilating LAI leads to greater improvement, especially for transpiration and carbon fluxes, by constraining the timing of simulated vegetation growth response to evolving climate conditions. LAI assimilation also helps to correct for the erroneous interaction between the dynamic phenology and irrigation during summertime, effectively reducing a large positive bias in ET and carbon fluxes. Independently assimilating LAI or soil moisture alters the categorization of drought, with the differences being greater for more severe drought categories. We highlight the vegetation representation in response to changing land use and hydroclimate as one of the key processes to be captured for building a successful drought early warning system for the MENA region.

scholarly journals Evaluating the performance of the land surface model ORCHIDEE-CAN on water and energy flux estimation with a single- and a multi- layer energy budget scheme

2016 ◽  
Author(s):  
Yiying Chen ◽  
James Ryder ◽  
Vladislav Bastrikov ◽  
Matthew J. McGrath ◽  
Kim Naudts ◽  
...  
Keyword(s):  
Energy Budget ◽  
Land Surface ◽  
Model Simulation ◽  
Canopy Structure ◽  
Land Surface Model ◽  
Single Layer ◽  
Surface Model ◽  
Forest Types ◽  
Layer Model ◽  
Single Layer Model

Abstract. Canopy structure is one of the most important vegetation characteristics for land-atmosphere interactions, as it determines the energy and scalar exchanges between the land surface and the overlying air mass. In this study we evaluated the performance of a newly developed multi-layer energy budget in the land surface model ORCHIDEE-CAN (Organising Carbon and Hydrology In Dynamic Ecosystems – CANopy), which simulates canopy structure and can be coupled to an atmospheric model using an implicit coupling procedure. We aim to provide a set of acceptable parameter values for a range of forest types. Top-canopy and sub-canopy flux observations from eight sites were collected in order to conduct this evaluation. The sites crossed climate zones from temperate to boreal and the vegetation types included deciduous, evergreen broad leaved and evergreen needle leaved forest with a maximum LAI (all-sided) ranging from 3.5 to 7.0. The parametrization approach proposed in this study was based on three selected physical processes – namely the diffusion, advection and turbulent mixing within the canopy. Short-term sub-canopy observations and long-term surface fluxes were used to calibrate the parameters in the sub-canopy radiation, turbulence and resistances modules with an automatic tuning process. The multi-layer model was found to capture the dynamics of sub-canopy turbulence, temperature and energy fluxes. The performance of the new multi-layer model was further compared against the existing single-layer model. Although, the multi-layer model simulation results showed little or no improvements to both the nighttime energy balance and energy partitioning during winter compared with a single-layer model simulation, the increased model complexity does provide a more detailed description of the canopy micrometeorology of various forest types. The multi-layer model links to potential future environmental and ecological studies such as the assessment of in-canopy species vulnerability to climate change, the climate effects of disturbance intensities and frequencies, and the consequences of biogenic volatile organic compounds (BVOC) emissions from the terrestrial ecosystem.

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