Intercomparison of surface energy fluxes, soil moisture, and evapotranspiration from eddy covariance, large-aperture scintillometer, and modeling across three ecosystems in a semiarid climate

Land surface heterogeneity influences patterns of sensible and latent heat flux, which in turn affect processes in the atmospheric boundary layer. However, gridded atmospheric models often fail to incorporate the influence of land surface heterogeneity due to differences between the temporal and spatial scales of models compared to the local, sub-grid processes. Improving models requires the scaling of surface flux measurements; a process made difficult by the fact that surface measurements usually find an imbalance in the energy budget.The Chequamegon Heterogeneous Ecosystem Energy-balance Study Enabled by a High-density Extensive Array of Detectors (CHEESEHEAD19) was an observational experiment designed to investigate how the atmospheric boundary layer responds to scales of spatial heterogeneity in surface-atmosphere heat and water exchanges. The campaign was conducted from June &#8211; October 2019, measuring surface energy fluxes over a heterogeneous forest ecosystem as fluxes transitioned from latent heat-dominated summer through sensible heat-dominated fall. Observations were made by ground, airborne, and satellite platforms within the 10 x 10 km study region, which was chosen to match the scale of a typical model grid cell. The spatial distribution of energy fluxes was observed by an array of 20 eddy covariance towers and a low-flying aircraft. Mesoscale atmospheric properties were measured by a suite of LiDAR and sounding instruments, measuring winds, water vapor, temperature, and boundary layer development. Plant phenology was measured in-situ and mapped remotely using hyperspectral imaging.The dense set of multi-scale observations of land-atmosphere exchange collected during the CHEESEHEAD field campaign permits combining the spatial and temporal distribution of energy fluxes with mesoscale surface and atmospheric properties. This provides an unprecedented data foundation to evaluate theoretical explanations of energy balance non-closure, as well as to evaluate methods for scaling surface energy fluxes for improved model-data comparison. Here we show how fluxes calculated using a spatial eddy covariance technique across the 20-tower network compare to those of standard temporal eddy covariance fluxes in order to characterize of the spatial representativeness of single tower eddy covariance measurements. Additionally, we show how spatial EC fluxes can be used to better understand the energy balance over heterogeneous ecosystems.

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Impacts of grid resolution on surface energy fluxes simulated with an integrated surface-groundwater flow model

Hydrology and Earth System Sciences Discussions ◽

10.5194/hessd-12-6437-2015 ◽

2015 ◽

Vol 12 (7) ◽

pp. 6437-6466

Author(s):

P. Shrestha ◽

M. Sulis ◽

C. Simmer ◽

S. Kollet

Keyword(s):

Soil Moisture ◽

Surface Energy ◽

Groundwater Flow ◽

Soil Temperature ◽

System Modeling ◽

Surface Fluxes ◽

Heat Fluxes ◽

Grid Resolution ◽

Energy Fluxes ◽

Surface Energy Fluxes

Abstract. The hydrological component of the Terrestrial System Modeling Platform (TerrSysMP) which includes integrated surface-groundwater flow, was used to investigate the grid resolution dependence of simulated soil moisture, soil temperature, and surface energy fluxes over a sub-catchment of the Rur, Germany. The investigation was motivated by the recent developments of new earth system models, which include 3-D physically based groundwater models for the coupling of land–atmosphere interaction and subsurface hydrodynamics. Our findings suggest that for grid resolutions between 100 and 1000 m, the non-local controls of soil moisture are highly grid resolution dependent. Local vegetation, however, strongly modulates the scaling behavior especially for surface fluxes and soil temperature, which depends on the radiative transfer property of the canopy. This study also shows that for grid-resolutions above a few 100 m, the variation of spatial and temporal pattern of sensible and latent heat fluxes may significantly affect the resulting atmospheric mesoscale circulation and boundary layer evolution in coupled runs.

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The aggregate description of semi-arid vegetation with precipitation-generated soil moisture heterogeneity

Hydrology and Earth System Sciences ◽

10.5194/hess-1-205-1997 ◽

1997 ◽

Vol 1 (1) ◽

pp. 205-212 ◽

Cited By ~ 8

Author(s):

C. B. White ◽

P. R. Houser ◽

A. M. Arain ◽

Z.-L. Yang ◽

K. Syed ◽

...

Keyword(s):

Soil Moisture ◽

Surface Energy ◽

Meteorological Data ◽

Surface Fluxes ◽

Convective Precipitation ◽

Soil Parameters ◽

Energy Fluxes ◽

Average Surface ◽

Surface Energy Fluxes ◽

Semi Arid

Abstract. Meteorological measurements in the Walnut Gulch catchment in Arizona were used to synthesize a distributed, hourly-average time series of data across a 26.9 by 12.5 km area with a grid resolution of 480 m for a continuous 18-month period which included two seasons of monsoonal rainfall. Coupled surface-atmosphere model runs established the acceptability (for modelling purposes) of assuming uniformity in all meteorological variables other than rainfall. Rainfall was interpolated onto the grid from an array of 82 recording rain gauges. These meteorological data were used as forcing variables for an equivalent array of stand-alone Biosphere-Atmosphere Transfer Scheme (BATS) models to describe the evolution of soil moisture and surface energy fluxes in response to the prevalent, heterogeneous pattern of convective precipitation. The calculated area-average behaviour was compared with that given by a single aggregate BATS simulation forced with area-average meteorological data. Heterogeneous rainfall gives rise to significant but partly compensating differences in the transpiration and the intercepted rainfall components of total evaporation during rain storms. However, the calculated area-average surface energy fluxes given by the two simulations in rain-free conditions with strong heterogeneity in soil moisture were always close to identical, a result which is independent of whether default or site-specific vegetation and soil parameters were used. Because the spatial variability in soil moisture throughout the catchment has the same order of magnitude as the amount of rain falling in a typical convective storm (commonly 10% of the vegetation's root zone saturation) in a semi-arid environment, non-linearity in the relationship between transpiration and the soil moisture available to the vegetation has limited influence on area-average surface fluxes.

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Upscaling surface energy fluxes over the North Slope of Alaska using airborne eddy-covariance measurements and environmental response functions

10.5194/acp-2017-1166 ◽

2018 ◽

Author(s):

Andrei Serafimovich ◽

Stefan Metzger ◽

Jörg Hartmann ◽

Katrin Kohnert ◽

Donatella Zona ◽

...

Keyword(s):

Surface Energy ◽

Eddy Covariance ◽

Latent Heat ◽

Land Surface ◽

Response Functions ◽

Sensible Heat ◽

Environmental Response ◽

Energy Fluxes ◽

Surface Energy Fluxes ◽

Eddy Covariance Measurements

Abstract. The objective of this study was to upscale airborne flux measurements of sensible heat and latent heat and to develop high resolution flux maps. In order to support the evaluation of coupled atmospheric/land–surface models we investigated spatial patterns of energy fluxes in relation to land–surface properties. We used airborne eddy-covariance measurements acquired by the POLAR 5 research aircraft in June–July 2012 to analyze surface fluxes. Footprint-weighted surface properties were then related to 21 529 sensible heat flux observations and 25 608 latent heat flux observations using both remote sensing and modelled data. A boosted regression tree technique was used to estimate environmental response functions between spatially and temporally resolved flux observations and corresponding biophysical and meteorological drivers. In order to improve the spatial coverage and spatial representativeness of energy fluxes we used relationships extracted across heterogeneous Arctic landscapes to infer high-resolution surface energy flux maps, thus directly upscaling the observational data. These maps of projected sensible heat and latent heat fluxes were used to assess energy partitioning in northern ecosystems and to determine the dominant energy exchange processes in permafrost areas. This allowed us to estimate energy fluxes for specific types of land cover, taking into account meteorological conditions. Airborne and modelled fluxes were then compared with measurements from an eddy-covariance tower near Atqasuk. Our results are an important contribution for the advanced, scale-dependent quantification of surface energy fluxes and provide new insights into the processes affecting these fluxes for the main vegetation types in high-latitude permafrost areas.

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The role of improved soil moisture for the characteristics of surface energy fluxes in the ECMWF reanalyses

10.5194/hess-2017-619 ◽

2017 ◽

Author(s):

Wilhelm May

Keyword(s):

Heat Flux ◽

Soil Moisture ◽

Surface Energy ◽

Moisture Content ◽

Regional Differences ◽

Soil Moisture Content ◽

Sensible Heat Flux ◽

Sensible Heat ◽

Energy Fluxes ◽

Surface Energy Fluxes

Abstract. In this study, the role that more realistic soil moisture has for the characteristics of surface energy fluxes in two sets of reanalyses performed at ECMWF is investigated. These are the standard set of reanalyses ERA-Interim (ERAInt) and the ERA-Interim/Land reanalyses of the land surface conditions (ERAInt/Land). In the latter, the ECMWF's land surface model has been forced with the meteorological fields from ERAInt, including an adjustment of precipitation based on the monthly mean values from the Global Precipitation Climatology Project data set. Adjusting precipitation has a distinct impact on the soil moisture content in the two sets of reanalyses. ERAInt is characterized by a general tendency to underestimate (overestimate) soil moisture in regions with a relatively high (low) soil moisture content. The differences in soil moisture between ERAInt and ERAInt/Land vary only slightly in the course of the year. This is not the case for precipitation, where the differences between the two sets of reanalyses vary markedly between different seasons. The direct impact of the regional differences in precipitation between ERAInt and ERAInt/Land on the corresponding deviations in soil moisture varies considerably by region. One reason is that the regional differences in precipitation vary by season, while the regional differences in soil moisture typically persist throughout the year. Another reason is that the specific nature of the interaction between precipitation and soil moisture diverges between different regions, depending on the climate conditions and on the degree to which the soil is saturated with moisture. The differences in soil moisture between the two sets of reanalyses have notable effects on the characteristics of surface energy fluxes. The nature of these effects differs by region and also by season, that is the coupling between soil moisture and the latent or the sensible heat flux is positive in one region or season, respectively, and negative in another one. In any case, the differences in the soil moisture content typically affect the latent and the sensible heat flux in opposite ways. Increases (decreases) in latent heat flux typically coincide with decreases (increases) in sensible heat flux. By this, the differences in soil moisture have a substantial impact on the partitioning of latent and sensible heat flux. The effect of the soil moisture differences on the evaporative fraction, for instance, is mainly governed by the impact on the latent heat flux because of the opposite effects on latent and sensible heat fluxes and, hence, only a weak impact on the total surface energy flux. The effect on the Bowen ratio, on the other hand, is for the most part controlled by the impact on the sensible heat flux, with higher (lower) values of the Bowen ratio in regions with increased (decreased) sensible heat flux.

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Relating remotely‐sensed vegetation and soil moisture indices to surface energy fluxes in vicinity of an atmospheric dryline

Remote Sensing Reviews ◽

10.1080/02757250009532383 ◽

2000 ◽

Vol 18 (1) ◽

pp. 53-82 ◽

Cited By ~ 3

Author(s):

Robert M. Rabin ◽

Barbara A. Burns ◽

Chris Collimore ◽

George R. Diak ◽

William Raymond

Keyword(s):

Soil Moisture ◽

Surface Energy ◽

Remotely Sensed ◽

Energy Fluxes ◽

Surface Energy Fluxes

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Quantification of surface energy fluxes from a small water body using scintillometry and eddy covariance

Water Resources Research ◽

10.1002/2013wr013899 ◽

2014 ◽

Vol 50 (1) ◽

pp. 494-513 ◽

Cited By ~ 28

Author(s):

Ryan McGloin ◽

Hamish McGowan ◽

David McJannet ◽

Freeman Cook ◽

Andrey Sogachev ◽

...

Keyword(s):

Surface Energy ◽

Eddy Covariance ◽

Water Body ◽

Energy Fluxes ◽

Surface Energy Fluxes ◽

Small Water ◽

Small Water Body

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Upscaling surface energy fluxes over the North Slope of Alaska using airborne eddy-covariance measurements and environmental response functions

Atmospheric Chemistry and Physics ◽

10.5194/acp-18-10007-2018 ◽

2018 ◽

Vol 18 (13) ◽

pp. 10007-10023 ◽

Cited By ~ 3

Author(s):

Andrei Serafimovich ◽

Stefan Metzger ◽

Jörg Hartmann ◽

Katrin Kohnert ◽

Donatella Zona ◽

...

Keyword(s):

Surface Energy ◽

Eddy Covariance ◽

Latent Heat ◽

Land Surface ◽

Response Functions ◽

Sensible Heat ◽

Environmental Response ◽

Energy Fluxes ◽

Surface Energy Fluxes ◽

Eddy Covariance Measurements

Abstract. The objective of this study was to upscale airborne flux measurements of sensible heat and latent heat and to develop high-resolution flux maps. In order to support the evaluation of coupled atmospheric–land-surface models we investigated spatial patterns of energy fluxes in relation to land-surface properties. We used airborne eddy-covariance measurements acquired by the Polar 5 research aircraft in June–July 2012 to analyze surface fluxes. Footprint-weighted surface properties were then related to 21 529 sensible heat flux observations and 25 608 latent heat flux observations using both remote sensing and modeled data. A boosted regression tree technique was used to estimate environmental response functions between spatially and temporally resolved flux observations and corresponding biophysical and meteorological drivers. In order to improve the spatial coverage and spatial representativeness of energy fluxes we used relationships extracted across heterogeneous Arctic landscapes to infer high-resolution surface energy flux maps, thus directly upscaling the observational data. These maps of projected sensible heat and latent heat fluxes were used to assess energy partitioning in northern ecosystems and to determine the dominant energy exchange processes in permafrost areas. This allowed us to estimate energy fluxes for specific types of land cover, taking into account meteorological conditions. Airborne and modeled fluxes were then compared with measurements from an eddy-covariance tower near Atqasuk. Our results are an important contribution for the advanced, scale-dependent quantification of surface energy fluxes and they provide new insights into the processes affecting these fluxes for the main vegetation types in high-latitude permafrost areas.

Download Full-text