scholarly journals Model–data fusion across ecosystems: from multi-site optimizations to global simulations

2014 ◽  
Vol 7 (3) ◽  
pp. 2961-3011 ◽  
Author(s):  
S. Kuppel ◽  
P. Peylin ◽  
F. Maignan ◽  
F. Chevallier ◽  
G. Kiely ◽  
...  
Keyword(s):  
Land Surface ◽  
Boreal Forests ◽  
Ecosystem Respiration ◽  
Co2 Concentration ◽  
Ecosystem Model ◽  
Global Scale ◽  
Model Data ◽  
Site Specific ◽  
Output Uncertainty ◽  
Averaged Model

Abstract. This study uses a variational data assimilation framework to simultaneously constrain a global ecosystem model with eddy covariance measurements of daily net carbon (NEE) and latent heat (LE) fluxes from a large number of sites grouped in seven plant functional types (PFTs). It is an attempt to bridge the gap between the numerous site-specific parameter optimization works found in the literature and the generic parameterization used by most land surface models within each PFT. The present multi-site approach allows deriving PFT-generic sets of optimized parameters enhancing the agreement between measured and simulated fluxes at most of the sites considered, with performances often comparable to those of the corresponding site-specific optimizations. Besides reducing the PFT-averaged model–data root-mean-square difference (RMSD) and the associated daily output uncertainty, the optimization improves the simulated CO2 balance at tropical and temperate forests sites. The major site-level NEE adjustments at the seasonal scale are: reduced amplitude in C3 grasslands and boreal forests, increased seasonality in temperate evergreen forests, and better model–data phasing in temperate deciduous broadleaf forests. Conversely, the poorer performances in tropical evergreen broadleaf forests points to deficiencies regarding the modeling of phenology and soil water stress for this PFT. An evaluation with data-oriented estimates of photosynthesis (GPP) and ecosystem respiration (Reco) rates indicates distinctively improved simulations of both gross fluxes. The multi-site parameter sets are then tested against CO2 concentrations measured at 53 locations around the globe, showing significant adjustments of the modeled seasonality of atmospheric CO2 concentration, whose relevance seems PFT-dependent, along with an improved interannual variability. Lastly, a global scale evaluation with remote sensing NDVI measurements indicates an improvement of the simulated seasonal variations of the foliar cover for all considered PFTs.

scholarly journals Model–data fusion across ecosystems: from multisite optimizations to global simulations

2014 ◽  
Vol 7 (6) ◽  
pp. 2581-2597 ◽  
Author(s):  
S. Kuppel ◽  
P. Peylin ◽  
F. Maignan ◽  
F. Chevallier ◽  
G. Kiely ◽  
...  
Keyword(s):  
Land Surface ◽  
Boreal Forests ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Ecosystem Respiration ◽  
Net Ecosystem Exchange ◽  
Co2 Concentration ◽  
Model Data ◽  
Site Specific ◽  
Averaged Model

Abstract. This study uses a variational data assimilation framework to simultaneously constrain a global ecosystem model with eddy covariance measurements of daily net ecosystem exchange (NEE) and latent heat (LE) fluxes from a large number of sites grouped in seven plant functional types (PFTs). It is an attempt to bridge the gap between the numerous site-specific parameter optimization works found in the literature and the generic parameterization used by most land surface models within each PFT. The present multisite approach allows deriving PFT-generic sets of optimized parameters enhancing the agreement between measured and simulated fluxes at most of the sites considered, with performances often comparable to those of the corresponding site-specific optimizations. Besides reducing the PFT-averaged model–data root-mean-square difference (RMSD) and the associated daily output uncertainty, the optimization improves the simulated CO2 balance at tropical and temperate forests sites. The major site-level NEE adjustments at the seasonal scale are reduced amplitude in C3 grasslands and boreal forests, increased seasonality in temperate evergreen forests, and better model–data phasing in temperate deciduous broadleaf forests. Conversely, the poorer performances in tropical evergreen broadleaf forests points to deficiencies regarding the modelling of phenology and soil water stress for this PFT. An evaluation with data-oriented estimates of photosynthesis (GPP – gross primary productivity) and ecosystem respiration (Reco) rates indicates distinctively improved simulations of both gross fluxes. The multisite parameter sets are then tested against CO2 concentrations measured at 53 locations around the globe, showing significant adjustments of the modelled seasonality of atmospheric CO2 concentration, whose relevance seems PFT-dependent, along with an improved interannual variability. Lastly, a global-scale evaluation with remote sensing NDVI (normalized difference vegetation index) measurements indicates an improvement of the simulated seasonal variations of the foliar cover for all considered PFTs.

scholarly journals Tiling soil textures for terrestrial ecosystem modelling via clustering analysis: a case study with CLASS-CTEM (version 2.1)

2017 ◽  
Author(s):  
Joe R. Melton ◽  
Reinel Sospedra-Alfonso ◽  
Kelly E. McCusker
Keyword(s):  
Soil Texture ◽  
Land Surface ◽  
Clustering Analysis ◽  
Clustering Algorithms ◽  
Terrestrial Ecosystem ◽  
Grid Cell ◽  
Moisture Stress ◽  
Ecosystem Model ◽  
Global Scale ◽  
Terrestrial Ecosystem Model

Abstract. We investigate the application of clustering algorithms to represent sub-grid scale variability in soil texture for use in a global-scale terrestrial ecosystem model. Our model, the coupled Canadian Land Surface Scheme – Canadian Terrestrial Ecosystem Model (CLASS-CTEM), is typically implemented at a coarse spatial resolution (ca. 2.8° × 2.8°) due to its use as the land surface component of the Canadian Earth System Model (CanESM). CLASS-CTEM can, however, be run with tiling of the land surface as a means to represent sub-grid heterogeneity. We first determined that the model was sensitive to tiling of the soil textures via an idealized test case before attempting to cluster soil textures globally. To cluster a high-resolution soil texture dataset onto our coarse model grid, we use two linked algorithms (OPTICS (Ankerst et al., 1999; Daszykowski et al., 2002) and Sander et al. (2003)) to provide tiles of representative soil textures for use as CLASS-CTEM inputs. The clustering process results in, on average, about three tiles per CLASS-CTEM grid cell with most cells having four or less tiles. Results from CLASS-CTEM simulations conducted with the tiled inputs (Cluster) versus those using a simple grid-mean soil texture (Gridmean) show CLASS-CTEM, at least on a global scale, is relatively insensitive to the tiled soil textures, however differences can be large in arid or peatland regions. The Cluster simulation has generally lower soil moisture and lower overall vegetation productivity than the Gridmean simulation except in arid regions where plant productivity increases. In these dry regions, the influence of the tiling is stronger due to the general state of vegetation moisture stress which allows a single tile, whose soil texture retains more plant available water, to yield much higher productivity. Although the use of clustering analysis appears promising as a means to represent sub-grid heterogeneity, soil textures appear to be reasonably represented for global scale simulations using a simple grid-mean value.

scholarly journals Tiling soil textures for terrestrial ecosystem modelling via clustering analysis: a case study with CLASS-CTEM (version 2.1)

2017 ◽  
Vol 10 (7) ◽  
pp. 2761-2783 ◽  
Author(s):  
Joe R. Melton ◽  
Reinel Sospedra-Alfonso ◽  
Kelly E. McCusker
Keyword(s):  
Soil Texture ◽  
Land Surface ◽  
Clustering Analysis ◽  
Clustering Algorithms ◽  
Terrestrial Ecosystem ◽  
Grid Cell ◽  
Moisture Stress ◽  
Ecosystem Model ◽  
Global Scale ◽  
Terrestrial Ecosystem Model

Abstract. We investigate the application of clustering algorithms to represent sub-grid scale variability in soil texture for use in a global-scale terrestrial ecosystem model. Our model, the coupled Canadian Land Surface Scheme – Canadian Terrestrial Ecosystem Model (CLASS-CTEM), is typically implemented at a coarse spatial resolution (approximately 2. 8° × 2. 8°) due to its use as the land surface component of the Canadian Earth System Model (CanESM). CLASS-CTEM can, however, be run with tiling of the land surface as a means to represent sub-grid heterogeneity. We first determined that the model was sensitive to tiling of the soil textures via an idealized test case before attempting to cluster soil textures globally. To cluster a high-resolution soil texture dataset onto our coarse model grid, we use two linked algorithms – the Ordering Points to Identify the Clustering Structure (OPTICS) algorithm (Ankerst et al., 1999; Daszykowski et al., 2002) and the algorithm of Sander et al. (2003) – to provide tiles of representative soil textures for use as CLASS-CTEM inputs. The clustering process results in, on average, about three tiles per CLASS-CTEM grid cell with most cells having four or less tiles. Results from CLASS-CTEM simulations conducted with the tiled inputs (Cluster) versus those using a simple grid-mean soil texture (Gridmean) show CLASS-CTEM, at least on a global scale, is relatively insensitive to the tiled soil textures; however, differences can be large in arid or peatland regions. The Cluster simulation has generally lower soil moisture and lower overall vegetation productivity than the Gridmean simulation except in arid regions where plant productivity increases. In these dry regions, the influence of the tiling is stronger due to the general state of vegetation moisture stress which allows a single tile, whose soil texture retains more plant-available water, to yield much higher productivity. Although the use of clustering analysis appears promising as a means to represent sub-grid heterogeneity, soil textures appear to be reasonably represented for global-scale simulations using a simple grid-mean value.

Eddy covariance measurements of the forest floor CO2 exchange in two contrasting forest stands in boreal Sweden

2020 ◽  
Author(s):  
Jinshu Chi ◽  
Mats Nilsson ◽  
Natascha Kljun ◽  
Matthias Peichl
Keyword(s):  
Eddy Covariance ◽  
Land Surface ◽  
High Frequency ◽  
Boreal Forests ◽  
Forest Floor ◽  
Forest Stand ◽  
Site Specific ◽  
C Cycle ◽  
Trunk Space ◽  
Chamber Measurements

<p>Boreal forests cover a large portion of land surface area in the northern hemisphere and greatly affect the global carbon (C) cycle and climate. Since these forests exchange carbon dioxide (CO<sub>2</sub>) with the atmosphere in different vertical layers, many different CO<sub>2</sub> sources and sinks exist within the complex forest stand. The forest floor (soil and understory vegetation) may act as an important component of the C budget in a forest stand, however its contribution may vary from negligible to determining the inter-annual variability of ecosystem C balance. To date, there are a limited number of studies that have directly quantified the CO<sub>2</sub> fluxes over a forest floor using the eddy covariance (EC) method primarily due to challenges and potential violation of underlying assumptions when applying this method in the trunk space where turbulence characteristics are complicated, intermittent, and not in accordance with universal theories.</p><p>In this study, we installed two identical EC flux systems at two contrasting boreal forests (sparse pine stand vs. a dense mixed pine-spruce stand) in Sweden to measure the forest floor CO<sub>2</sub> exchange. We developed site-specific ideal cospectral models for the below-canopy fluxes in the trunk space under the well-mixed condition as defined by the standard deviation of the vertical wind speed. Spectral correction to the half-hourly fluxes was performed based on the newly fitted cospectral models at each site. Chamber measurements of CO<sub>2</sub> fluxes during the growing season were conducted to compare with the estimates from the below-canopy EC data.</p><p>Our below-canopy cospectral models show that more high-frequency signals (small eddies) occurred in the forest trunk space compared to the ideal above-canopy cospectral model. The high-frequency contribution was greater in the dense pine-spruce forest compared to the open pine stand. The spectral corrected CO<sub>2</sub> fluxes measured by the EC method agreed well with the concurrent chamber measurements. The EC results revealed that the forest floor of the two contrasting stands acted as net CO<sub>2</sub> sources during the 3-year period (2017-2019). This study highlights that by applying a data correction based on site-specific below-canopy cospectral models, the EC method can be used in the trunk space to accurately measure the net CO<sub>2</sub> exchange between the forest floor and the atmosphere and thus to improve our understanding of the role of the forest floor in the ecosystem-scale C budget in the boreal forest region.</p>

Ecosystem modeling of methane and carbon dioxide fluxes for boreal forest sites

2001 ◽  
Vol 31 (2) ◽  
pp. 208-223 ◽  
Author(s):  
Christopher Potter ◽  
Jill Bubier ◽  
Patrick Crill ◽  
Peter Lafleur
Keyword(s):  
Carbon Dioxide ◽  
Boreal Forest ◽  
Land Surface ◽  
Net Primary Production ◽  
Ground Cover ◽  
Methane Flux ◽  
Growing Season ◽  
Ecosystem Model ◽  
Heat Fluxes ◽  
Water Levels

Predicted daily fluxes from an ecosystem model for water, carbon dioxide, and methane were compared with 1994 and 1996 Boreal Ecosystem–Atmosphere Study (BOREAS) field measurements at sites dominated by old black spruce (Picea mariana (Mill.) BSP) (OBS) and boreal fen vegetation near Thompson, Man. Model settings for simulating daily changes in water table depth (WTD) for both sites were designed to match observed water levels, including predictions for two microtopographic positions (hollow and hummock) within the fen study area. Water run-on to the soil profile from neighboring microtopographic units was calibrated on the basis of daily snowmelt and rainfall inputs to reproduce BOREAS site measurements for timing and magnitude of maximum daily WTD for the growing season. Model predictions for daily evapotranspiration rates closely track measured fluxes for stand water loss in patterns consistent with strong controls over latent heat fluxes by soil temperature during nongrowing season months and by variability in relative humidity and air temperature during the growing season. Predicted annual net primary production (NPP) for the OBS site was 158 g C·m–2 during 1994 and 135 g C·m–2 during 1996, with contributions of 75% from overstory canopy production and 25% from ground cover production. Annual NPP for the wetter fen site was 250 g C·m–2 during 1994 and 270 g C·m–2 during 1996. Predicted seasonal patterns for soil CO2 fluxes and net ecosystem production of carbon both match daily average estimates at the two sites. Model results for methane flux, which also closely match average measured flux levels of –0.5 mg CH4·m–2·day–1 for OBS and 2.8 mg CH4·m–2·day–1 for fen sites, suggest that spruce areas are net annual sinks of about –0.12 g CH4·m–2, whereas fen areas generate net annual emissions on the order of 0.3–0.85 g CH4·m–2, depending mainly on seasonal WTD and microtopographic position. Fen hollow areas are predicted to emit almost three times more methane during a given year than fen hummock areas. The validated model is structured for extrapolation to regional simulations of interannual trace gas fluxes over the entire North America boreal forest, with integration of satellite data to characterize properties of the land surface.

scholarly journals A near-global, high resolution land surface parameter dataset for the variable infiltration capacity model

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Jacob R. Schaperow ◽  
Dongyue Li ◽  
Steven A. Margulis ◽  
Dennis P. Lettenmaier
Keyword(s):  
Land Surface ◽  
Global Scale ◽  
Radiation Budget ◽  
Soil Parameters ◽  
Variable Infiltration Capacity ◽  
Infiltration Capacity ◽  
Vic Model ◽  
Spatial Coverage ◽  
Land Surface Parameter ◽  
Vegetation Parameters

AbstractHydrologic models predict the spatial and temporal distribution of water and energy at the land surface. Currently, parameter availability limits global-scale hydrologic modelling to very coarse resolution, hindering researchers from resolving fine-scale variability. With the aim of addressing this problem, we present a set of globally consistent soil and vegetation parameters for the Variable Infiltration Capacity (VIC) model at 1/16° resolution (approximately 6 km at the equator), with spatial coverage from 60°S to 85°N. Soil parameters derived from interpolated soil profiles and vegetation parameters estimated from space-based MODIS measurements have been compiled into input files for both the Classic and Image drivers of the VIC model, version 5. Geographical subsetting codes are provided, as well. Our dataset provides all necessary land surface parameters to run the VIC model at regional to global scale. We evaluate VICGlobal’s ability to simulate the water balance in the Upper Colorado River basin and 12 smaller basins in the CONUS, and their ability to simulate the radiation budget at six SURFRAD stations in the CONUS.

Validation of GOES-Based Insolation Estimates Using Data from the U.S. Climate Reference Network

2005 ◽  
Vol 6 (4) ◽  
pp. 460-475 ◽  
Author(s):  
Jason A. Otkin ◽  
Martha C. Anderson ◽  
John R. Mecikalski ◽  
George R. Diak
Keyword(s):  
Physical Model ◽  
Land Surface ◽  
Radiative Transfer Model ◽  
Reference Network ◽  
Transfer Model ◽  
Model Errors ◽  
Diverse Range ◽  
Simple Physical Model ◽  
Averaged Model ◽  
The U.S

Abstract Reliable procedures that accurately map surface insolation over large domains at high spatial and temporal resolution are a great benefit for making the predictions of potential and actual evapotranspiration that are required by a variety of hydrological and agricultural applications. Here, estimates of hourly and daily integrated insolation at 20-km resolution, based on Geostationary Operational Environmental Satellite (GOES) visible imagery are compared to pyranometer measurements made at 11 sites in the U.S. Climate Reference Network (USCRN) over a continuous 15-month period. Such a comprehensive survey is necessary in order to examine the accuracy of the satellite insolation estimates over a diverse range of seasons and land surface types. The relatively simple physical model of insolation that is tested here yields good results, with seasonally averaged model errors of 62 (19%) and 15 (10%) W m−2 for hourly and daily-averaged insolation, respectively, including both clear- and cloudy-sky conditions. This level of accuracy is comparable, or superior, to results that have been obtained with more complex models of atmospheric radiative transfer. Model performance can be improved in the future by addressing a small elevation-related bias in the physical model, which is likely the result of inaccurate model precipitable water inputs or cloud-height assessments.

Simulated and Observed Preindustrial to Modern Vegetation and Climate Changes*

2005 ◽  
Vol 18 (17) ◽  
pp. 3650-3671 ◽  
Author(s):  
Michael Notaro ◽  
Zhengyu Liu ◽  
Robert Gallimore ◽  
Stephen J. Vavrus ◽  
John E. Kutzbach ◽  
...  
Keyword(s):  
Land Surface ◽  
Boreal Forests ◽  
Ring Width ◽  
Warming Trend ◽  
Physiological Effect ◽  
Co2 Fertilization ◽  
Vegetation Growth ◽  
Fully Coupled ◽  
Global Surface ◽  
Vegetation And Climate

Abstract Rising levels of carbon dioxide since the preindustrial era have likely contributed to an observed warming of the global surface, and observations show global greening and an expansion of boreal forests. This study reproduces observed climate and vegetation trends associated with rising CO2 using a fully coupled atmosphere–ocean–land surface GCM with dynamic vegetation and decomposes the effects into physiological and radiative components. The simulated warming trend, strongest at high latitudes, was dominated by the radiative effect, although the physiological effect of CO2 on vegetation (CO2 fertilization) contributed to significant wintertime warming over northern Europe and central and eastern Asia. The net global greening of the model was primarily due to the physiological effect of increasing CO2, while the radiative and physiological effects combined to produce a poleward expansion of the boreal forests. Observed and simulated trends in tree ring width are consistent with the enhancement of vegetation growth by the physiological effect of rising CO2.

scholarly journals Evaluating terrestrial CO<sub>2</sub> flux diagnoses and uncertainties from a simple land surface model and its residuals

2014 ◽  
Vol 11 (2) ◽  
pp. 217-235 ◽  
Author(s):  
T. W. Hilton ◽  
K. J. Davis ◽  
K. Keller
Keyword(s):  
Carbon Dioxide ◽  
Parameter Estimation ◽  
North American ◽  
Land Surface ◽  
Atmospheric Carbon Dioxide ◽  
Ecosystem Respiration ◽  
Land Surface Model ◽  
Net Ecosystem Exchange ◽  
Surface Model ◽  
Considerable Uncertainty

Abstract. Global terrestrial atmosphere–ecosystem carbon dioxide fluxes are well constrained by the concentration and isotopic composition of atmospheric carbon dioxide. In contrast, considerable uncertainty persists surrounding regional contributions to the net global flux as well as the impacts of atmospheric and biological processes that drive the net flux. These uncertainties severely limit our ability to make confident predictions of future terrestrial biological carbon fluxes. Here we use a simple light-use efficiency land surface model (the Vegetation Photosynthesis Respiration Model, VPRM) driven by remotely sensed temperature, moisture, and phenology to diagnose North American gross ecosystem exchange (GEE), ecosystem respiration, and net ecosystem exchange (NEE) for the period 2001 to 2006. We optimize VPRM parameters to eddy covariance (EC) NEE observations from 65 North American FluxNet sites. We use a separate set of 27 cross-validation FluxNet sites to evaluate a range of spatial and temporal resolutions for parameter estimation. With these results we demonstrate that different spatial and temporal groupings of EC sites for parameter estimation achieve similar sum of squared residuals values through radically different spatial patterns of NEE. We also derive a regression model to estimate observed VPRM errors as a function of VPRM NEE, temperature, and precipitation. Because this estimate is based on model-observation residuals it is comprehensive of all the error sources present in modeled fluxes. We find that 1 km interannual variability in VPRM NEE is of similar magnitude to estimated 1 km VPRM NEE errors.

scholarly journals Biotic stress accelerates formation of climate-relevant aerosols in boreal forests

2015 ◽  
Vol 15 (21) ◽  
pp. 12139-12157 ◽  
Author(s):  
J. Joutsensaari ◽  
P. Yli-Pirilä ◽  
H. Korhonen ◽  
A. Arola ◽  
J. D. Blande ◽  
...  
Keyword(s):  
Boreal Forests ◽  
Large Scale ◽  
Transport Model ◽  
Cloud Condensation Nuclei ◽  
Fold Increase ◽  
Global Scale ◽  
Satellite Observations ◽  
Insect Outbreaks ◽  
Voc Emissions ◽  
Scale Modelling

Abstract. Boreal forests are a major source of climate-relevant biogenic secondary organic aerosols (SOAs) and will be greatly influenced by increasing temperature. Global warming is predicted to not only increase emissions of reactive biogenic volatile organic compounds (BVOCs) from vegetation directly but also induce large-scale insect outbreaks, which significantly increase emissions of reactive BVOCs. Thus, climate change factors could substantially accelerate the formation of biogenic SOAs in the troposphere. In this study, we have combined results from field and laboratory experiments, satellite observations and global-scale modelling in order to evaluate the effects of insect herbivory and large-scale outbreaks on SOA formation and the Earth's climate. Field measurements demonstrated 11-fold and 20-fold increases in monoterpene and sesquiterpene emissions respectively from damaged trees during a pine sawfly (Neodiprion sertifer) outbreak in eastern Finland. Laboratory chamber experiments showed that feeding by pine weevils (Hylobius abietis) increased VOC emissions from Scots pine and Norway spruce seedlings by 10–50 fold, resulting in 200–1000-fold increases in SOA masses formed via ozonolysis. The influence of insect damage on aerosol concentrations in boreal forests was studied with a global chemical transport model GLOMAP and MODIS satellite observations. Global-scale modelling was performed using a 10-fold increase in monoterpene emission rates and assuming 10 % of the boreal forest area was experiencing outbreak. Results showed a clear increase in total particulate mass (local max. 480 %) and cloud condensation nuclei concentrations (45 %). Satellite observations indicated a 2-fold increase in aerosol optical depth over western Canada's pine forests in August during a bark beetle outbreak. These results suggest that more frequent insect outbreaks in a warming climate could result in substantial increase in biogenic SOA formation in the boreal zone and, thus, affect both aerosol direct and indirect forcing of climate at regional scales. The effect of insect outbreaks on VOC emissions and SOA formation should be considered in future climate predictions.

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