Phenology-induced energy and carbon fluxes in land surface models

2020 ◽  
Author(s):  
Jan De Pue ◽  
José Miguel Barrios ◽  
Fabienne Maignan ◽  
Liyang Liu ◽  
Philippe Ciais ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Land Surface ◽  
Terrestrial Ecosystems ◽  
Carbon Fluxes ◽  
Land Surface Models ◽  
Energy Fluxes ◽  
Wide Range ◽  
Surface Models ◽  
Modelling Strategies ◽  
Phenological Cycle

<p>The annual phenological cycle is of key importance for the carbon and energy fluxes in terrestrial ecosystems. Although the processes controlling budburst and leaf senescence are fairly well known, the connection between plant phenology and the carbon fluxes remains a challenging aspect in land surface modelling (LSM). In this study, the modelling strategies of three well stablished LSM are compared. The LSM considered in this study were: ORCHIDEE, ISBA-A-gs and the model driving the LSA-SAF evapotranspiration product (https://landsaf.ipma.pt). The latter model does not simulate the carbon fluxes but focuses on the computation of evapotranspiration and energy fluxes.<br>The phenological cycle is simulated explicitly in the ORCHIDEE model, using empirical relations based on temperature sum, water availability, and other variables. In the ISBA-A-gs model, phenology and LAI development is fully photosynthesis-driven. The phenology in the LSA-SAF model is driven by remote sensing forcing variables, such as LAI observations. Alternatively, the assimilation of remote sensing LAI products is a convenient method to improve the simulated phenological cycle in land surface models. A dedicated module for this operation is available in ISBA-A-gs.<br>Simulations were performed over a wide range of climatological conditions and plant functional types. The results were then validated with in-situ measurements conducted at Fluxnet stations. In addition to the comparison between measured and modelled carbon fluxes, the validation in this study included the intra-annual variation in the simulated phenological cycle.</p>

scholarly journals Evaluating and improving the Community Land Model's sensitivity to land cover

2018 ◽  
Vol 15 (15) ◽  
pp. 4731-4757 ◽  
Author(s):  
Ronny Meier ◽  
Edouard L. Davin ◽  
Quentin Lejeune ◽  
Mathias Hauser ◽  
Yan Li ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Land Cover ◽  
Land Surface ◽  
Soil Column ◽  
Plant Functional Type ◽  
Model Parameters ◽  
Functional Type ◽  
Land Surface Models ◽  
Surface Models ◽  
Open Land

Abstract. Modeling studies have shown the importance of biogeophysical effects of deforestation on local climate conditions but have also highlighted the lack of agreement across different models. Recently, remote-sensing observations have been used to assess the contrast in albedo, evapotranspiration (ET), and land surface temperature (LST) between forest and nearby open land on a global scale. These observations provide an unprecedented opportunity to evaluate the ability of land surface models to simulate the biogeophysical effects of forests. Here, we evaluate the representation of the difference of forest minus open land (i.e., grassland and cropland) in albedo, ET, and LST in the Community Land Model version 4.5 (CLM4.5) using various remote-sensing and in situ data sources. To extract the local sensitivity to land cover, we analyze plant functional type level output from global CLM4.5 simulations, using a model configuration that attributes a separate soil column to each plant functional type. Using the separated soil column configuration, CLM4.5 is able to realistically reproduce the biogeophysical contrast between forest and open land in terms of albedo, daily mean LST, and daily maximum LST, while the effect on daily minimum LST is not well captured by the model. Furthermore, we identify that the ET contrast between forests and open land is underestimated in CLM4.5 compared to observation-based products and even reversed in sign for some regions, even when considering uncertainties in these products. We then show that these biases can be partly alleviated by modifying several model parameters, such as the root distribution, the formulation of plant water uptake, the light limitation of photosynthesis, and the maximum rate of carboxylation. Furthermore, the ET contrast between forest and open land needs to be better constrained by observations to foster convergence amongst different land surface models on the biogeophysical effects of forests. Overall, this study demonstrates the potential of comparing subgrid model output to local observations to improve current land surface models' ability to simulate land cover change effects, which is a promising approach to reduce uncertainties in future assessments of land use impacts on climate.

Evaluation of key parameters controlling phenology-induced variability of surface fluxes in land surface models

2021 ◽  
Author(s):  
Jan De Pue ◽  
José Miguel Barrios ◽  
Liyang Liu ◽  
Philippe Ciais ◽  
Alirio Arboleda ◽  
...  
Keyword(s):  
Land Surface ◽  
Gross Primary Production ◽  
Global Scale ◽  
Plant Phenology ◽  
Surface Fluxes ◽  
Terrestrial Vegetation ◽  
Land Surface Models ◽  
Area Index ◽  
Wide Range ◽  
Surface Models

<p>Over the past decades, land surface models have evolved into advanced tools which comprise detailed process descriptions and interactions at a broad range of scales. One of the challenges in these models is the accurate simulation of plant phenology. It is a key element at the nexus of the simulated hydrological and carbon cycle, where the leaf area index (LAI) plays a major role in flux partitioning, water balance and gross primary production.<br>In this study, three well-established models are used to simulate the intrinsically coupled fluxes of water, energy and carbon from terrestrial vegetation. ORCHIDEE, ISBA-CC and the LSA-SAF algorithm each have a different approach to represent plant phenology. Whereas ISBA-CC has a fairly simple biomass allocation scheme to represent the phenological cycle, ORCHIDEE relies on a dedicated phenology module, and LSA-SAF is driven by remote-sensed forcing variables, such as LAI. Simulations were performed for a wide range of hydro-climatic biomes and plant functional types at field scale. The simulated fluxes were validated using eddy-covariance measurements, and the simulated phenology was compared to remote-sensed observations.<br>These models are tools to extrapolate leaf-level processes to global scale climate predictions. The origin of the parameters controlling phenology-induced variability in these models ranges from plant-scale lab experiments to global-scale calibration. The aim of this study is to investigate the key parameters controlling phenology-induced variability in these models.</p>

scholarly journals Identification of catchment functional units by time series of thermal remote sensing images

2014 ◽  
Vol 18 (12) ◽  
pp. 5345-5359 ◽  
Author(s):  
B. Müller ◽  
M. Bernhardt ◽  
K. Schulz
Keyword(s):  
Remote Sensing ◽  
Principal Component Analysis ◽  
Time Series ◽  
Land Surface ◽  
Temporal Dynamics ◽  
Principal Component ◽  
Component Analysis ◽  
Land Surface Models ◽  
Surface Models ◽  
Functional Units

Abstract. The identification of catchment functional behavior with regards to water and energy balance is an important step during the parameterization of land surface models. An approach based on time series of thermal infrared (TIR) data from remote sensing is developed and investigated to identify land surface functioning as is represented in the temporal dynamics of land surface temperature (LST). For the mesoscale Attert catchment in midwestern Luxembourg, a time series of 28 TIR images from ASTER (Advanced Spaceborne Thermal Emission and Reflection Radiometer) was extracted and analyzed, applying a novel process chain. First, the application of mathematical–statistical pattern analysis techniques demonstrated a strong degree of pattern persistency in the data. Dominant LST patterns over a period of 12 years were then extracted by a principal component analysis. Component values of the two most dominant components could be related for each land surface pixel to land use data and geology, respectively. The application of a data condensation technique ("binary words") extracting distinct differences in the LST dynamics allowed the separation into landscape units that show similar behavior under radiation-driven conditions. It is further outlined that both information component values from principal component analysis (PCA), as well as the functional units from the binary words classification, will highly improve the conceptualization and parameterization of land surface models and the planning of observational networks within a catchment.

scholarly journals Land-surface modelling in hydrological perspective – a review

2006 ◽  
Vol 3 (2) ◽  
pp. 229-241 ◽  
Author(s):  
J. Overgaard ◽  
D. Rosbjerg ◽  
M. B. Butts
Keyword(s):  
Remote Sensing ◽  
Land Surface ◽  
Potential Evapotranspiration ◽  
Land Surface Models ◽  
Atmospheric Models ◽  
Dynamic Coupling ◽  
Evaluation Procedures ◽  
Surface Models ◽  
Different Types ◽  
Land Surface Modelling

Abstract. The purpose of this paper is to provide a review of the different types of energy-based land-surface models (LSMs) and discuss some of the new possibilities that will arise when energy-based LSMs are combined with distributed hydrological modelling. We choose to focus on energy-based approaches, because in comparison to the traditional potential evapotranspiration models, these approaches allow for a stronger link to remote sensing and atmospheric modelling. New opportunities for evaluation of distributed land-surface models through application of remote sensing are discussed in detail, and the difficulties inherent in various evaluation procedures are presented. Finally, the dynamic coupling of hydrological and atmospheric models is explored, and the perspectives of such efforts are discussed.

scholarly journals Climate Impacts of Making Evapotranspiration in the Community Land Model (CLM3) Consistent with the Simple Biosphere Model (SiB)

2009 ◽  
Vol 10 (2) ◽  
pp. 374-394 ◽  
Author(s):  
Peter J. Lawrence ◽  
Thomas N. Chase
Keyword(s):  
Climate Sensitivity ◽  
Land Surface ◽  
Climate Modeling ◽  
Land Surface Models ◽  
Surface Hydrology ◽  
Community Land Model ◽  
Wide Range ◽  
Surface Models ◽  
Biosphere Model ◽  
Surface Parameterizations

Abstract In recent climate sensitivity experiments with the Community Climate System Model, version 3 (CCSM3), a wide range of studies have found that the Community Land Model, version 3 (CLM3), simulates mean global evapotranspiration with low contributions from transpiration (15%), and high contributions from soil and canopy evaporation (47% and 38%, respectively). This evapotranspiration partitioning is inconsistent with the consensus of other land surface models used in GCMs. To understand the high soil and canopy evaporation and the low transpiration observed in the CLM3, select individual components of the land surface parameterizations that control transpiration, canopy and soil evaporation, and soil hydrology are compared against the equivalent parameterizations used in the Simple Biosphere Model, versions 2 and 3 (SiB2 and SiB3), and against more recent developments with CLM. The findings of these investigations are used to develop new parameterizations for CLM3 that would reproduce the functional dynamics of land surface processes found in SiB and other alternative land surface parameterizations. Global climate sensitivity experiments are performed with the new land surface parameterizations to assess how the new SiB, consistent CLM land surface parameterizations, influence the surface energy balance, hydrology, and atmospheric fluxes in CLM3, and through that the larger-scale climate modeled in CCSM3. It is found that the new parameterizations enable CLM to simulate evapotranspiration partitioning consistently with the multimodel average of other land surface models used in GCMs, as evaluated by Dirmeyer et al. (2005). The changes in surface fluxes also resulted in a number of improvements in the simulation of precipitation and near-surface air temperature in CCSM3. The new model is fully coupled in the CCSM3 framework, allowing a wide range of climate modeling investigations without the surface hydrology issues found in the current CLM3 model. This provides a substantially more robust framework for performing climate modeling experiments investigating the influence of land cover change and surface hydrology in CLM and CCSM than the existing CLM3 parameterizations. The study also shows that changes in land surface hydrology have global scale impacts on model climatology.

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