Modeling and Scaling Coupled Energy, Water, and Carbon Fluxes Based on Remote Sensing: An Application to Canada’s Landmass

2007 ◽  
Vol 8 (2) ◽  
pp. 123-143 ◽  
Author(s):  
Baozhang Chen ◽  
Jing M. Chen ◽  
Gang Mo ◽  
Chiu-Wai Yuen ◽  
Hank Margolis ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Land Surface ◽  
General Circulation ◽  
Carbon Fluxes ◽  
General Circulation Models ◽  
Surface Fluxes ◽  
Heat Fluxes ◽  
Sensible Heat ◽  
Area Index ◽  
Up Scaling

Abstract Land surface models (LSMs) need to be coupled with atmospheric general circulation models (GCMs) to adequately simulate the exchanges of energy, water, and carbon between the atmosphere and terrestrial surfaces. The heterogeneity of the land surface and its interaction with temporally and spatially varying meteorological conditions result in nonlinear effects on fluxes of energy, water, and carbon, making it challenging to scale these fluxes accurately. The issue of up-scaling remains one of the critical unsolved problems in the parameterization of subgrid-scale fluxes in coupled LSM and GCM models. A new distributed LSM, the Ecosystem–Atmosphere Simulation Scheme (EASS) was developed and coupled with the atmospheric Global Environmental Multiscale model (GEM) to simulate energy, water, and carbon fluxes over Canada’s landmass through the use of remote sensing and ancillary data. Two approaches (lumped case and distributed case) for handling subgrid heterogeneity were used to evaluate the effect of land-cover heterogeneity on regional flux simulations based on remote sensing. Online runs for a week in August 2003 provided an opportunity to investigate model performance and spatial scaling issues. Comparisons of simulated results with available tower observations (five sites) across an east–west transect over Canada’s southern forest regions indicate that the model is reasonably successful in capturing both the spatial and temporal variations in carbon and energy fluxes, although there were still some biases in estimates of latent and sensible heat fluxes between the simulations and the tower observations. Moreover, the latent and sensible heat fluxes were found to be better modeled in the coupled EASS–GEM system than in the uncoupled GEM. There are marked spatial variations in simulated fluxes over Canada’s landmass. These patterns of spatial variation closely follow vegetation-cover types as well as leaf area index, both of which are highly correlated with the underlying soil types, soil moisture conditions, and soil carbon pools. The surface fluxes modeled by the two up-scaling approaches (lumped and distributed cases) differ by 5%–15% on average and by up to 15%–25% in highly heterogeneous regions. This suggests that different ways of treating subgrid land surface heterogeneities could lead to noticeable biases in model output.

scholarly journals Roles of spatially varying vegetation on surface fluxes within a small mountainous catchment

2010 ◽  
Vol 7 (1) ◽  
pp. 593-619
Author(s):  
G. N. Flerchinger ◽  
D. Marks ◽  
M. L. Reba ◽  
Q. Yu ◽  
M. S. Seyfried
Keyword(s):  
Water Balance ◽  
Latent Heat ◽  
Populus Tremuloides ◽  
Sensible Heat Flux ◽  
Growing Season ◽  
Carbon Fluxes ◽  
Surface Fluxes ◽  
Heat Fluxes ◽  
Sensible Heat ◽  
Area Index

Abstract. Understanding the role of ecosystems in modulating energy, water and carbon fluxes is critical to quantifying the variability in energy, carbon, and water balances across landscapes. This study compares and contrasts the seasonal surface fluxes of sensible heat, latent heat and carbon fluxes measured over different vegetation in a rangeland mountainous environment within the Reynolds Creek Experimental Watershed. Eddy covariance systems were used to measure surface fluxes over low sagebrush (Artemesia arbuscula), aspen (Populus tremuloides) and the understory of grasses and forbs beneath the aspen canopy. Peak leaf area index of the sagebrush, aspen, and aspen understory was 0.77, 1.35, and 1.20, respectively. The sagebrush and aspen canopies were subject to similar meteorological forces, while the understory of the aspen was sheltered from the wind. Estimated cumulative evapotranspiratation from the sagebrush, aspen understory, and aspen trees were 399 mm, 205 mm and 318 mm. A simple water balance of the catchment indicated that of the 700 mm of areal average precipitation, 442 mm was lost to evapotranspiration, and 254 mm of streamflow was measured from the catchment; water balance closure for the catchment was within 7 mm. Fluxes of latent heat and carbon for all sites were minimal through the winter. Growing season fluxes of latent heat and carbon were consistently higher above the aspen canopy than from the other sites. While growing season carbon fluxes were very similar for the sagebrush and aspen understory, latent heat fluxes for the sagebrush were consistently higher. Higher evapotranspiration from the sagebrush was likely because it is more exposed to the wind. Sensible heat flux from the aspen tended to be slightly less than the sagebrush site during the growing season when the leaves were actively transpiring, but exceeded that from the sagebrush in May, September and October when the net radiation was offset by evaporative cooling. Results from this study illustrate the influence of vegetation on the spatial variability of surface fluxes across mountainous rangeland landscapes.

scholarly journals Intraseasonal Variability in Coupled GCMs: The Roles of Ocean Feedbacks and Model Physics

2014 ◽  
Vol 27 (13) ◽  
pp. 4970-4995 ◽  
Author(s):  
Charlotte A. DeMott ◽  
Cristiana Stan ◽  
David A. Randall ◽  
Mark D. Branson
Keyword(s):  
Indian Ocean ◽  
General Circulation ◽  
Sensible Heat Flux ◽  
General Circulation Models ◽  
Ocean Model ◽  
Surface Fluxes ◽  
Heat Fluxes ◽  
Specific Humidity ◽  
Sensible Heat ◽  
Near Surface

The interaction of ocean coupling and model physics in the simulation of the intraseasonal oscillation (ISO) is explored with three general circulation models: the Community Atmospheric Model, versions 3 and 4 (CAM3 and CAM4), and the superparameterized CAM3 (SPCAM3). Each is integrated coupled to an ocean model, and as an atmosphere-only model using sea surface temperatures (SSTs) from the coupled SPCAM3, which simulates a realistic ISO. For each model, the ISO is best simulated with coupling. For each SST boundary condition, the ISO is best simulated in SPCAM3. Near-surface vertical gradients of specific humidity, [Formula: see text] (temperature, [Formula: see text]), explain ~20% (50%) of tropical Indian Ocean latent (sensible) heat flux variance, and somewhat less of west Pacific variance. In turn, local SST anomalies explain ~5% (25%) of [Formula: see text] [Formula: see text] variance in coupled simulations, and less in uncoupled simulations. Ergo, latent and sensible heat fluxes are strongly controlled by wind speed fluctuations, which are largest in the coupled simulations, and represent a remote response to coupling. The moisture budget reveals that wind variability in coupled simulations increases east-of-convection midtropospheric moistening via horizontal moisture advection, which influences the direction and duration of ISO propagation. These results motivate a new conceptual model for the role of ocean feedbacks on the ISO. Indian Ocean surface fluxes help developing convection attain a magnitude capable of inducing the circulation anomalies necessary for downstream moistening and propagation. The “processing” of surface fluxes by model physics strongly influences the moistening details, leading to model-dependent responses to coupling.

scholarly journals Consistency between hydrological model, large aperture scintillometer and remote sensing based evapotranspiration estimates for a heterogeneous catchment

2012 ◽  
Vol 16 (7) ◽  
pp. 2095-2107 ◽  
Author(s):  
B. Samain ◽  
G. W. H. Simons ◽  
M. P. Voogt ◽  
W. Defloor ◽  
N.-J. Bink ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Energy Balance ◽  
Latent Heat ◽  
Land Surface ◽  
Land Surface Model ◽  
Heat Fluxes ◽  
Surface Model ◽  
Sensible Heat ◽  
Catchment Scale ◽  
Large Aperture

Abstract. The catchment averaged actual evapotranspiration rate is a hydrologic model variable that is difficult to quantify. Evapotranspiration rates – up till present – cannot be continuously observed at the catchment scale. The objective of this paper is to estimate the evapotranspiration rates (or its energy equivalent, the latent heat fluxes LE) for a heterogeneous catchment of 102.3 km2 in Belgium using three fundamentally different algorithms. One possible manner to observe this variable could be the continuous measurement of sensible heat fluxes (H) across large distances (in the order of kilometers) using a large aperture scintillometer (LAS), and converting these observations into evapotranspiration rates. Latent heat fluxes are obtained through the energy balance equation using a series of sensible heat fluxes measured with a LAS over a distance of 9.5 km in the catchment, and point measurements of net radiation (Rn) and ground heat flux (G) upscaled to catchment average through the use of TOPLATS, a physically based land surface model. The resulting LE-values are then compared to results from the remote sensing based surface energy balance algorithm ETLook and the land surface model. Firstly, the performance of ETLook for the energy balance terms has been assessed at the point scale and at the catchment scale. Secondly, consistency between daily evapotranspiration rates from ETLook, TOPLATS and LAS is shown.

scholarly journals Area-averaged evapotranspiration over a heterogeneous land surface: Aggregation of multi-point EC flux measurements with high-resolution land-cover map and footprint analysis

2016 ◽  
Author(s):  
Feinan Xu ◽  
Weizhen Wang ◽  
Jiemin Wang ◽  
Ziwei Xu ◽  
Yuan Qi ◽  
...  
Keyword(s):  
Remote Sensing ◽  
High Resolution ◽  
Land Cover ◽  
Land Surface ◽  
Heat Fluxes ◽  
Sensible Heat ◽  
Flux Aggregation ◽  
Land Cover Map ◽  
Flux Measurements ◽  
Footprint Analysis

Abstract. The determination of area-averaged evapotranspiration (ET) at the satellite pixel scale/model grid scale over a heterogeneous land surface plays a significant role in developing and improving the parameterization schemes of the remote sensing based ET estimation models or general hydro-meteorological models. The Heihe Watershed Allied Telemetry Experimental Research (HiWATER) flux matrix provided a unique opportunity to build an aggregation scheme for area-averaged fluxes. Based on HiWATER flux matrix datasets and a high-resolution land cover map derived from aircraft remote sensing, this study focused on estimating the area-averaged ET over a heterogeneous landscape with footprint analysis and multivariate regression. Firstly, the representativeness of multi-point eddy covariance (EC) flux measurements was quantitatively evaluated. The results show, the model estimated flux values cannot be directly validated with the flux tower measurements because the latent- and sensible heat fluxes measured by EC are determined by the upwind surface flux emanating from separate land cover classes, and a method in retrieving area-averaged fluxes should be applied. Secondly, a flux aggregation method was established combining footprint analysis and multiple regression analysis. The area-averaged sensible heat fluxes were obtained using the method and validated by the large aperture scintillometer (LAS) measurements. Finally, the area-averaged ET of the kernel experimental area of HiWATER was estimated through the flux aggregation schemes. The aggregated results were then regarded as ground truth for the remotely-sensed ET products. These findings demonstrate that the refined flux integration technique is a better method to determine the heterogeneous surface fluxes.

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

2009 ◽  
Vol 22 (16) ◽  
pp. 4427-4433 ◽  
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.

Quantifying chaos in the atmosphere

2000 ◽  
Vol 24 (4) ◽  
pp. 499-514 ◽  
Author(s):  
Richard Washington
Keyword(s):  
Boundary Layer ◽  
Land Surface ◽  
General Circulation ◽  
Large Scale ◽  
Internal Variability ◽  
General Circulation Models ◽  
Model Atmosphere ◽  
Heat Fluxes ◽  
Sea Surface Temperature Anomalies ◽  
The Uk

The atmosphere is known to be forced by a variety of energy sources, including radiation and heat fluxes emanating from the boundary layer associated with sea-surface temperature anomalies and land-surface features. The atmosphere is also subject to internal variability which is essentially unforced and is thought to be a basic characteristic of fluids. Whereas much work has been done in quantifying the links between external forcing of the atmosphere and its long-term response as well as the influence of boundary layer forcing in determining organized, large-scale modes of planetary-scale circulation, less is known about the importance of internal variability or chaos in determining the evolution of weather and climate. General circulation models (GCMs) now provide for this possibility. Multiple evolutions of the climate system may be computed in GCM simulations. Where these simulations are identical except for the conditions by which the model is initialized, the degree of departure in the evolution of climate from one model run to the next corresponds precisely to the degree of internal variability or chaos present in the model atmosphere. A methodology for quantifying this chaotic forcing is considered and is applied to century-long integrations of the UK Meteorological Office model HADAM2A.

scholarly journals Consistency between hydrological model, large aperture scintillometer and remote sensing based evapotranspiration estimates for a heterogeneous catchment

2011 ◽  
Vol 8 (6) ◽  
pp. 10863-10894 ◽  
Author(s):  
B. Samain ◽  
G. W. H. Simons ◽  
M. P. Voogt ◽  
W. Defloor ◽  
N.-J. Bink ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Energy Balance ◽  
Latent Heat ◽  
Land Surface ◽  
Land Surface Model ◽  
Heat Fluxes ◽  
Surface Model ◽  
Sensible Heat ◽  
Catchment Scale ◽  
Daily Time

Abstract. The catchment averaged actual evapotranspiration rate is a hydrologic model variable that is difficult to quantify. Evapotranspiration rates can – up till present – not be continuously observed at the catchment scale. The objective of this paper is to estimate the evapotranspiration rates (or its energy equivalent, the latent heat fluxes LE) for a heterogeneous catchment of 102.3 km2 in Belgium using three fundamentally different algorithms. One possible manner to observe this variable could be the continuous measurement of sensible heat fluxes (H) across large distances (in the order of kilometers) using a Large Aperture Scintillometer (LAS), and inverting these observations into evapotranspiration rates. Latent heat fluxes are obtained through the energy balance equation using a series of sensible heat fluxes (H) measured with a LAS over a distance of 9.5 km in the catchment, and point measurements of net radiation (Rn) and ground heat flux (G) upscaled to catchment average through the use of TOPLATS, a physically based land surface model. The resulting LE-values are then validated by comparing them to results from the remote sensing based surface energy balance algorithm ETLook and the land surface model. Firstly, it is demonstrated that ETLook is able to estimate the energy balance terms for daily time steps at the point scale and at the catchment scale. Secondly, consistency between daily evapotranspiration rates from ETLook, TOPLATS and LAS is shown. As such, ETLook provides the opportunity to estimate continuous series of the energy balance terms of a large area for daily time steps and can thus e.g. be used as a validation tool for LAS-measurements, whereas LAS is able to estimate the latent heat fluxes (evapotranspiration rates) for a large and heterogeneous catchment at an hourly time step which can be used for the forcing or validation of hydrologic models.

New results of the Land Atmosphere Feedback Experiment (LAFE)

2021 ◽  
Author(s):  
Volker Wulfmeyer ◽  
David D. Turner
Keyword(s):  
Remote Sensing ◽  
Latent Heat ◽  
Land Surface ◽  
Transport Processes ◽  
Surface Fluxes ◽  
Heat Fluxes ◽  
Model Verification ◽  
Sensing Systems ◽  
Remote Sensing Systems ◽  
The Impact

<p>The Land-Atmosphere Feedback Experiment (LAFE) deployed several state-of-the-art scanning lidar and remote sensing systems to the Atmospheric Radiation Measurement (ARM) Program Southern Great Plains (SPG) site during August 2017. A novel synergy of remote sensing systems was applied for simultaneous measurements of land-surface fluxes and horizontal and vertical transport processes in the atmospheric boundary layer (ABL). The impact of spatial inhomogeneities of the soil-vegetation continuum on L-A feedback was studied using the scanning capability of the instrumentation as well as soil, vegetation, and surface flux measurements. Thus, both the variability of surface fluxes and ABL dynamics and thermodynamics over the SGP site was studied for the first time. The objectives of LAFE are as follows:</p><p>I. Determine turbulence profiles and investigate new relationships among  gradients, variances, and fluxes<br>II. Map surface momentum, sensible heat, and latent heat fluxes using a synergy of scanning wind, humidity, and temperature lidar systems<br>III. Characterize land-atmosphere feedback and the moisture budget at the SGP site via the new LAFE sensor synergy<br>IV: Verify large-eddy simulation model runs and improve turbulence representations in mesoscale models.</p><p>In this presentation, the status of LAFE research and recent achievements of the science objectives are presented and discussed. Concerning I., long-term profiling capabilities of turbulent properties have been developed and will be presented such as continuous measurements of latent heat flux profiles for a duration of one month. Concerning II., we present a combination of tower and remote sensing measurements to study surface layer profiles of wind, temperature, and humidity. A first evaluation of the results demonstrates significant deviations from Monin-Obukhov similarity theory. Concerning III., Convective Triggering Potential (CTP)-Humidity Index (HIlow) metrics are presented at the SGP site to characterize L-A feedback and a new technique for determination of water-vapor advection, as important part of its budget. Last but not least, concerning IV., we present an advanced ensemble model design with turbulence permitting resolution for case studies and model verification from the convection-permitting to the turbulent scales in a realistic mesoscale environment. Using this framework, we introduce a strategy to apply the observations for the test and development of turbulence parameterizations. These results confirm that LAFE will make significant contributions to process understanding and the parameterization of the next generation of high-resolution weather forecast, climate, and earth system models.</p>

scholarly journals An Assessment of Drought Stress in Tea Estates Using Optical and Thermal Remote Sensing

2021 ◽  
Vol 13 (14) ◽  
pp. 2730
Author(s):  
Animesh Chandra Das ◽  
Ryozo Noguchi ◽  
Tofael Ahamed
Keyword(s):  
Remote Sensing ◽  
Drought Stress ◽  
Land Surface ◽  
Climatic Factors ◽  
Standardized Precipitation Index ◽  
Landsat 8 ◽  
Drought Frequency ◽  
Moisture Index ◽  
Area Index ◽  
Drought Period

Drought is one of the detrimental climatic factors that affects the productivity and quality of tea by limiting the growth and development of the plants. The aim of this research was to determine drought stress in tea estates using a remote sensing technique with the standardized precipitation index (SPI). Landsat 8 OLI/TIRS images were processed to measure the land surface temperature (LST) and soil moisture index (SMI). Maps for the normalized difference moisture index (NDMI), normalized difference vegetation index (NDVI), and leaf area index (LAI), as well as yield maps, were developed from Sentinel-2 satellite images. The drought frequency was calculated from the classification of droughts utilizing the SPI. The results of this study show that the drought frequency for the Sylhet station was 38.46% for near-normal, 35.90% for normal, and 25.64% for moderately dry months. In contrast, the Sreemangal station demonstrated frequencies of 28.21%, 41.02%, and 30.77% for near-normal, normal, and moderately dry months, respectively. The correlation coefficients between the SMI and NDMI were 0.84, 0.77, and 0.79 for the drought periods of 2018–2019, 2019–2020 and 2020–2021, respectively, indicating a strong relationship between soil and plant canopy moisture. The results of yield prediction with respect to drought stress in tea estates demonstrate that 61%, 60%, and 60% of estates in the study area had lower yields than the actual yield during the drought period, which accounted for 7.72%, 11.92%, and 12.52% yield losses in 2018, 2019, and 2020, respectively. This research suggests that satellite remote sensing with the SPI could be a valuable tool for land use planners, policy makers, and scientists to measure drought stress in tea estates.

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