Large Aperture Scintillometer Measurements Research Articles

Evapotranspiration estimates in a traditional irrigated area in semi-arid Mediterranean. Comparison of four remote sensing-based models

Quantification of actual crop evapotranspiration (ETa) over large areas is a critical issue to manage water resources, particularly in semi-arid regions. In this study, four models driven by high resolution remote sensing data were intercompared and evaluated over an heterogeneous and complex traditional irrigated area located in the piedmont of the High Atlas mountain, Morocco, during the 2017 and 2018 seasons: (1) SAtellite Monitoring of IRrigation (SAMIR) which is a software-based on the FAO-56 dual crop coefficient water balance model fed with Sentinel-2 high-resolution Normalized Difference Vegetation Index (NDVI) to derive the basal crop coefficient (Kcb); (2) Soil Plant Atmosphere and Remote Sensing Evapotranspiration (SPARSE) which is a surface energy balance model fed with land surface temperature (LST) derived from thermal data provided from Landsat 7 and 8; (3) a modified version of the Shuttleworth–Wallace (SW) model which uses the LST to compute surface resistances and (4) METRIC-GEE which is a version of METRIC model (“Mapping Evapotranspiration at high Resolution with Internalized Calibration”) that operates on the Google Earth Engine platform, also driven by LST. Actual evapotranspiration (ETa) measurements from two Eddy-Covariance (EC) systems and a Large Aperture Scintillometer (LAS) were used to evaluate the four models. One EC was used to calibrate SAMIR and SPARSE (EC1) which were validated using the second one (EC2), providing a Root Mean Square Error (RMSE) and a determination coefficient (R) of 0.53 mm/day (R=0.82) and 0.66 mm/day (R=0.74), respectively. SW and METRIC-GEE simulations were obtained respectively from a previous study and Google Earth Engine (GEE), therefore no calibration was performed in this study. The four models predict well the seasonal course of ETa during two successive growing seasons (2017 and 2018). However, their performances were contrasted and varied depending on the seasons, the water stress conditions and the vegetation development. By comparing the statistical results between the simulation and the measurements of ETa it has been shown that SAMIR and METRIC-GEE are the less scattered and the better in agreement with the LAS measurements (RMSE equal to 0.73 and 0.68 mm/day and R equal to 0.74 and 0.82, respectively). On the other hand, SPARSE is less scattered (RMSE = 0.90 mm/day, R = 0.54) than SW which is slightly better correlated (RMSE = 0.98 mm/day, R = 0.60) with the observations. This study contributes to explore the complementarities between these approaches in order to improve the evapotranspiration mapping monitored with high-resolution remote sensing data

Comparison of sensible heat flux measured by large aperture scintillometer and eddy covariance in a seasonally-inundated wetland

The eddy covariance (EC) technique has been widely used to measure ecosystem surface energy fluxes. However, with a relatively small representative area (footprint), errors are often introduced when upscaling EC data based on variables derived from large-footprint satellite products. Furthermore, EC measurements often fail to close the energy balance in ecosystems such as wetlands. As an alternative to EC, large aperture scintillometers (LAS) have been used to measure sensible heat fluxes (H) over representative areas comparable to the resolution of large-scale satellite images. However, because LAS measurements are based on semi-empirical simulations, their accuracy needs further evaluation across ecosystems. Changes in hydrology on the land surface significantly alter measurement conditions as well as the processes of energy transfer, and thus, may affect the accuracy of energy measurements from LAS. To address this issue, we compared the LAS-measured H (HLAS) to EC-derived H (HEC) in a seasonally inundated wetland within Everglades National Park. Overall, the HLAS was 7.1 ± 0.3 (SE) % greater than HEC, and the ratio of HLAS to HEC remained similar between the wet season, when the ecosystem was inundated, and the dry season. However, inundation, as a thermal buffer in the system, reduced the magnitude of H in the wet season and resulted in a smaller difference of seasonal H budget estimates between LAS and EC measurements. Because of the homogenous land surface at our site, the discrepancies between HLAS and HEC could not be explained by footprint mismatch. Compared to the energy balance closure calculated with HEC, the closure calculated with HLAS was improved by 6% during the dry season but remained similar during the wet season. Overall, we conclude that LAS can be a reliable approach to measure H in wetland ecosystems and its measurements were stable with seasonal hydrological changes.

A Method for Deriving All‐Sky Evapotranspiration From the Synergistic Use of Remotely Sensed Images and Meteorological Data

AbstractEvapotranspiration (ET) is an important component of the water and energy cycle. The present study develops a practical approach for generating all‐sky ET with the synergistic use of satellite images and meteorological data. In this approach, the ET over clear‐sky pixels is estimated from a two‐stage land surface temperature (LST)/fractional vegetation cover feature space method where the dry/wet edges are determined from theoretical calculations. For cloudy pixels, the Penman‐Monteith equation is used to calculate the ET where no valid remotely sensed LST is available. An evaluation of the method with ET collected at ground‐based large aperture scintillometer measurements at the Yucheng Comprehensive Experimental Station (YCES) in China is performed over a growth period from April to October 2010. The results show that the root‐mean‐square error (RMSE) and bias over clear‐sky pixels are 57.3 W/m2 and 18.2 W/m2, respectively, whereas an RMSE of 69.3 W/m2 with a bias of 12.3 W/m2 can be found over cloudy pixels. Moreover, a reasonable overall RMSE of 65.3 W/m2 with a bias of 14.4 W/m2 at the YCES can be obtained under all‐sky conditions, indicating a promising prospect for the derivation of all‐sky ET using currently available satellite and meteorological data at a regional or global scale in future developments.

An End-Member-Based Two-Source Approach for Estimating Land Surface Evapotranspiration From Remote Sensing Data

Evapotranspiration (ET) is one of the key variables in the water and energy exchange between land surface and atmosphere. This paper develops an end-member-based two-source approach for estimating land surface ET (i.e., the ESVEP model) from remote sensing data, considering the differing responses of soil water content at the upper surface layer to soil evaporation and at the deeper root zone layer to vegetation transpiration. The ESVEP model first diverges the soil-vegetation system net radiation into soil and vegetation components by considering the transmission of direct and diffuse shortwave radiation separately from the transmission of longwave radiation through the canopy, then calculates the four dry/wet soil/vegetation end-members with the diverged soil and vegetation net radiations, and last separates soil evaporation from vegetation transpiration based on the two-phase ET dynamics and the four end-member temperatures. The model can overall produce reasonably good surface energy fluxes and is no more sensitive to meteorology, vegetation, and remote sensing inputs than other two-source energy balance models and surface temperature versus vegetation index ( $T_{R}$ –VI) trapezoid models. A reasonable agreement could be found with a small bias of ±8 W/ $\text{m}^{2}$ and a root-mean-square error within 60 W/ $\text{m}^{2}$ (comparable to accuracies published in other studies) when both model-estimated sensible heat flux and latent heat flux from MODIS remote sensing data are validated with ground-based large aperture scintillometer measurements.

Area-averaged evapotranspiration over a heterogeneous land surface: aggregation of multi-point EC flux measurements with a high-resolution land-cover map and 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 and 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. On the basis of the HiWATER flux matrix dataset and high-resolution land-cover map, this study focused on estimating the area-averaged ET over a heterogeneous landscape with footprint analysis and multivariate regression. The procedure is as follows. Firstly, quality control and uncertainty estimation for the data of the flux matrix, including 17 eddy-covariance (EC) sites and four groups of large-aperture scintillometers (LASs), were carefully done. Secondly, the representativeness of each EC site was quantitatively evaluated; footprint analysis was also performed for each LAS path. Thirdly, based on the high-resolution land-cover map derived from aircraft remote sensing, a flux aggregation method was established combining footprint analysis and multiple-linear regression. Then, the area-averaged sensible heat fluxes obtained from the EC flux matrix were validated by the LAS measurements. Finally, the area-averaged ET of the kernel experimental area of HiWATER was estimated. Compared with the formerly used and rather simple approaches, such as the arithmetic average and area-weighted methods, the present scheme is not only with a much better database, but also has a solid grounding in physics and mathematics in the integration of area-averaged fluxes over a heterogeneous surface. Results from this study, both instantaneous and daily ET at the satellite pixel scale, can be used for the validation of relevant remote sensing models and land surface process models. Furthermore, this work will be extended to the water balance study of the whole Heihe River basin.

Characterizing the Footprint of Eddy Covariance System and Large Aperture Scintillometer Measurements to Validate Satellite-Based Surface Fluxes

To validate satellite-based surface fluxes by ground measurements properly, several numerical simulations were carried out at a homogeneous alpine meadow site and mixed cropland site, considering various atmospheric conditions and different land cover distribution types. By comparing various pixel selection methods, the results showed that footprint was significant in insuring a consistent spatial scale between ground measurements and satellite-based surface fluxes, particularly for heterogeneous surface and high-resolution remote sensing data. Because large aperture scintillometer measurements cover larger areas than eddy covariance (EC) system measurements, the spatial heterogeneity at a subpixel scale in complicated surface should be further considered in validating coarse satellite data. Thus, more accurate validation data and scaling methods must be developed, such as measuring surface fluxes at the satellite pixel scale by a flux measurement matrix or airborne EC measurements.

Multiscale Validation of the 8-day MOD16 Evapotranspiration Product Using Flux Data Collected in China

Accurate estimates of terrestrial evapotranspiration (ET) are critical and significant to the field for modeling water and energy transfer between the land surface and atmosphere. This paper evaluates the 8-day MOD16 actual ET product using the ground-based eddy covariance (EC) system and large aperture scintillometer (LAS) measurements collected from 2008 to 2011 at seven sites in North and Northwest China. Overall, the 8-day MOD16 ET reproduces the temporal patterns of both the LAS and EC measurements but tends to underestimate and overestimate these measurements at high and low ET levels, respectively. It is also of limited use when surface is irrigated because under such condition significant underestimation is observed. Using the LAS measurements that also include a large source area does not generate a better agreement than using the EC measurements which comprise a small source area. The 8-day MOD16 ET averaged over ${3} \times {3\;km}^{{2}}$ MODIS pixels agree better with both the EC and LAS measurements than that extracted at the ${1} \times {1}\;{km}^{{2}}$ MODIS pixel. For the EC validation, the relative bias and the relative root-mean-square error (RMSE) vary between 5% and $- 59\% $ and between 35% and 120%, respectively, for the LAS validation, the relative bias and the relative RMSE vary between 6% and $- 69\% $ and between 55% and 108%, respectively. The agreement between one site and another is not consistent and varies greatly. More validation work is recommended to testing the general applicability of the MOD16 ET product at a large number of sites worldwide.

A new method for measuring the imaginary part of the atmospheric refractive index structure parameter in the urban surface layer

Abstract. The atmospheric refractive index consists of both real and imaginary parts. The intensity of refractive index fluctuations is generally expressed as the refractive index structure parameter, with the real part reflecting the strength of atmospheric turbulence and the imaginary part reflecting absorption in the light path. A large aperture scintillometer (LAS) is often used to measure the structure parameter of the real part of the atmospheric refractive index, from which the sensible and latent heat fluxes can further be obtained, whereas the influence of the imaginary part is ignored or considered noise. In this theoretical analysis study, the relationship between logarithmic light intensity variance and the atmospheric refractive index structure parameter (ARISP), as well as that between the logarithmic light intensity structure function and the ARISP, is derived. Additionally, a simple expression for the imaginary part of the ARISP is obtained which can be conveniently used to determine the imaginary part of the ARISP from LAS measurements. Moreover, these relationships provide a new method for estimating the outer scale of turbulence. Light propagation experiments were performed in the urban surface layer, from which the imaginary part of the ARISP was calculated. The experimental results showed good agreement with the presented theory. The results also suggest that the imaginary part of the ARISP exhibits a different diurnal variation from that of the real part. For the wavelength of light used (0.62 μm), the variation of the imaginary part of the ARISP is related to both the turbulent transport process and the spatial distribution characteristics of aerosols.

Evaluation of two end-member-based models for regional land surface evapotranspiration estimation from MODIS data

The importance of accurate estimations of regional and global evapotranspiration (ET) has been recognized worldwide in the fields of hydrology, water resource management, meteorology, and global climate change. Given the different structures of the end-member-based surface energy balance algorithm for land (SEBAL) and surface temperature–vegetation index (Ts–VI) triangle models, which nonetheless use essentially the same definitions of dry and wet pixels, questions arise regarding the nature of the differences between the two models’ estimated sensible heat fluxes and latent heat fluxes and what controls the heat flux differences. This study aims to investigate how the SEBAL model and the Ts–VI triangle method differ from each other in the regional evaporative fraction (EF) and ET estimates through analytical deduction and model applications. Because both the SEBAL model and the Ts–VI triangle model are of limited use when deep-layer soil moisture is moderately to significantly stressed, MODIS remote sensing data from 23 clear-sky overpass times between January 2010 and late October 2011, covering a wide range of soil moisture content and fractional vegetation cover conditions, are acquired to assess the two models over a non-water stressed study area on the North China plain. The results show that the SEBAL model is able to produce satisfactory sensible heat flux (H) and latent heat flux (LE) estimates compared with ground-based large aperture scintillometer measurements at the Yucheng station, with small biases of 4.1W/m2 and 2.3W/m2 and root mean square errors (RMSEs) of 46.4W/m2 and 48.6W/m2, respectively. However, the Ts–VI triangle model produces much worse H and LE estimates, with biases of 98.5W/m2 and −92.2W/m2 and RMSEs of 119.3W/m2 and 115.5W/m2, respectively. Variations of pixel-by-pixel surface available energy and momentum roughness length over the study area are responsible for the differences of the H and LE estimates between the two models. The SEBAL model produces larger EF and ET for most pixels than the Ts–VI triangle method when the same group of dry and wet pixels is applied, especially for pixels characterized by medium to high vegetation fractions or surface soil moisture contents. The Ts–VI triangle method is more sensitive to the surface temperatures of the dry and wet pixels than the SEBAL model. The findings from this study benefit the proper selection of end-member-based models for regional ET estimation and aid in quantifying the resultant uncertainties in the model-derived surface energy components.

Intercomparison of surface energy flux measurement systems used during the HiWATER‐MUSOEXE

AbstractAgreement among instruments is very important for the Multi‐Scale Observation Experiment on Evapotranspiration over heterogeneous land surfaces of The Heihe Watershed Allied Telemetry Experimental Research (HiWATER‐MUSOEXE), particularly in regard to radiation and turbulent flux measurements. Before HiWATER‐MUSOEXE was conducted, 20 eddy covariance (EC) system sets, 18 radiometer sets, and seven large aperture scintillometers (LASs) sets were intercompared over the Gobi desert between 14 and 24 May 2012. For radiometers, the four‐component radiation measurements exhibited good agreement—the average root‐mean‐square error (RMSE) and mean relative error (MRE) for the net radiation were 10.38 W m−2 and 1.24%, respectively. With regard to the EC systems, the best consistency for sensible heat fluxes was found among CSAT3 sonic anemometers and Li7500A/Li7500/EC150 combinations (average RMSE, 12.30 W m−2 and MRE, −1.36%), followed by Gill sonic anemometers and Li7500A/Li7500 combinations when a proper angle of attack correction method was applied (average RMSE, 16.75 W m−2 and MRE, −5.52%). The sensible heat flux measured using different LASs agreed well with high correlation coefficients—the average RMSE and MRE values were 10.26 W m−2 and 5.48% for boundary layer scintillometer (BLS) 900, 16.32 W m−2 and 10.47% for BLS450, and 14.38 W m−2 and −3.72% for ZZLAS, respectively. The EC and LAS measurements were compared and agreed well over homogeneous underlying surfaces, which also indicated that the EC and LAS measurements would be comparable in the follow‐up experiment. The intercomparison results can be used to determine instrument placement and are very helpful for subsequent data analysis.

Measurements of evapotranspiration from eddy-covariance systems and large aperture scintillometers in the Hai River Basin, China

Summary Evapotranspiration (ET) observations were made for 3 years (2008–2010), using eddy covariance (EC) systems and large aperture scintillometers (LAS), in typical underlying surfaces across the Hai River Basin: orchards (Miyun, MY), cropland in the suburbs (Daxing, DX), and cropland in the plains (Guantao, GT). Reliable data were obtained after carefully data processing, and the seasonal and interannual variability in ET was quantitatively analyzed. The annual ET during 2008–2010 ranged from 510–730 mm for the EC measurements and 430–560 mm for the LAS measurements. The differences in ET among the years and sites were connected with differences in soil moisture and crop growing conditions. The difference in the source areas of EC and LAS measurements and the heterogeneity in their source areas are the primary causes of the discrepancy between EC and LAS measurements. The EC and LAS measurements are compared to the field water balance method calculation and MOD16 ET (the MODIS ET product from the MODIS Global Evapotranspiration Project), respectively. The average difference was 0.85% (mean relative error) and 33.80 mm (root mean square error) between the EC measurements and field water balance method calculations, and 7.72% and 47.08 mm between LAS measurements and MOD16 ET from 2008 to 2010 at the three sites. We found a decreasing tendency for ET in the past 15 years across the Hai River Basin, especially after the year of 2005.

Derivation of Structure Parameters of Temperature and Humidity in the Convective Boundary Layer from Large-Eddy Simulations and Implications for the Interpretation of Scintillometer Observations

We derive the turbulent structure parameters of temperature $$C_{T}^2$$ and humidity $$C_q^2$$ from high-resolution large-eddy simulations (LES) of a homogeneously-heated convective boundary layer. Boundary conditions and model forcing were derived from measurements at Cabauw in The Netherlands. Three different methods to obtain the structure-parameters from LES are investigated. The shape of the vertical structure-parameter profiles from all three methods compare well with former experimental and LES results. Depending on the method, deviations in the magnitude up to a factor of two are found and traced back to the effects of discretization and numerical dissipation of the advection scheme. Furthermore, we validate the LES data with airborne and large-aperture scintillometer (LAS) measurements at Cabauw. Virtual path measurements are used to study the variability of $$C_{T}^2$$ in the mixed layer and surface layer and its implications for airborne and LAS measurements. A high variability of $$C_{T}^2$$ along a given horizontal path in the LES data is associated with plumes (high values) and downdrafts (low values). The path average of $$C_{T}^2$$ varies rapidly in time due to the limited path length. The LES results suggest that measured path averages require sufficient temporal averaging and an adequate ratio of path length to height above the ground for the LAS in order to approach the domain average of $$C_{T}^2$$ .

Validation of the SEBS-derived sensible heat for FY3A/VIRR and TERRA/MODIS over an alpine grass region using LAS measurements

In this study, sensible heat (H) calculation using remote sensing data over an alpine grass landscape is conducted from May to September 2010, and the calculation is validated using LAS (large aperture scintillometers) measurements. Data from two remote sensing sensors (FY3A-VIRR and TERRA-MODIS) are analysed. Remote sensing data, combined with the ground meteorological observations (pressure, temperature, wind speed, humidity) are fed into the SEBS (Surface Energy Balance System) model. Then the VIRR-derived sensible heat (VIRR_SEBS_H) and MODIS-derived sensible heat (MODIS_SEBS_H) are compared with the LAS-estimated H, which are obtained at the respective satellite overpass time. Furthermore, the similarities and differences between the VIRR_SEBS_H and MODIS_SEBS_H values are investigated. The results indicate that VIRR data quality is as good as MODIS data for the purpose of H estimation. The root mean square errors (rmse) of the VIRR_SEBS_H and MODIS_SEBS_H values are 45.1098W/m2 (n=64) and 58.4654W/m2 (n=71), respectively. The monthly means of the MODIS_SEBS_H are marginally higher than those of VIRR_SEBS_H because the satellite overpass time of the TERRA satellite lags by 25min to that of the FT3A satellite. Relative evaporation (EFr), which is more time-independent, shows a higher agreement between MODIS and VIRR. Many common features are shared by the VIRR_SEBS_H and the MODIS_SEBS_H, which can be attributed to the SEBS model performance. In May–June, H is over-estimated with more fluctuations and larger rmse, whereas in July–September, H is under-estimated with fewer fluctuations and smaller rmse. Sensitivity analysis shows that potential temperature gradient (delta_T) plays a dominant role in determining the magnitude and fluctuation of H. The largest rmse and over-estimation in H occur in June, which could most likely be attributed to high delta_T, high wind speed, and the complicated thermodynamic state during the transitional period when bare land transforms to dense vegetation cover.

Validation of remotely sensed evapotranspiration over the Hai River Basin, China

Ground‐based validation is crucial for ensuring the accuracy of remotely sensed evapotranspiration (RS_ET) and extending its application. This paper proposes an innovative validation method based on multisource evapotranspiration (ET) from ground measurements, with the validation results including the accuracy assessment, error source analysis, and uncertainty analysis of the validation process. It is a potentially useful approach to evaluate the accuracy and analyze the spatiotemporal properties of RS_ET at both the basin and local scales, and is appropriate to validate RS_ET in diverse resolutions at different time‐scales. An independent RS_ET validation using such a method was presented over the Hai River Basin in 2002–2009, China. In general, validation at the basin scale showed good agreements between the 1 km annual RS_ET and the validation data such as the water balance ET (root‐mean‐square error (RMSE): 50.73 mm), MODIS ET products (RMSE: 79.84 mm), precipitation, and land use types. At the local scale, multiscale ET measurements from large aperture scintillometer (LAS) and eddy covariance system (EC) with a footprint model were used for validation over three typical landscapes. In most cases, the 1 km RS_ET resulted in slight overestimation with the LAS measurements (RMSE: 10.75 mm for monthly results, 0.78 mm for daily results), while the 30 m RS_ET was underestimated compared to the EC measurements (RMSE: 16.28 mm for monthly results, 0.99 mm for daily results). Furthermore, error sources of RS_ET and uncertainties of the validation process were investigated in detail. The results showed that the proposed validation method was reasonable and feasible.

An intercomparison of three remote sensing-based energy balance models using Large Aperture Scintillometer measurements over a wheat–corn production region

This paper compares three remote sensing-based models for estimating evapotranspiration (ET), namely the Surface Energy Balance System (SEBS), the Two-Source Energy Balance (TSEB) model, and the surface temperature–vegetation index Triangle (TVT). The models used as input MODIS/TERRA products and ground measurements collected during the wheat and corn growth period in a subhumid climate at a measurement station in Yucheng, China. MODIS land surface temperature (LST) and leaf area index (LAI) products, corrected using ground-truth observations, were used in the three models. The TSEB model output of sensible (H) and latent (LE) heat fluxes were in good agreement with Large Aperture Scintillometer (LAS)-measured H and LE derived by residual (RMSD < 45 W/m 2). Reasonable agreement was also obtained with the SEBS model output yielding RMSD for H of ~ 40 W/m 2 and LE ~ 55 W/m 2. However, the TVT model output resulted in poor agreement with the LAS-estimated H and LE with RMSD-values > 110 W/m 2. Using the uncorrected MODIS LST and LAI products resulted in a deterioration of the agreement in H and LE with LAS-estimated values for both the TSEB and SEBS models, whereas TVT performance improved marginally. These results indicate that the TSEB model yielded the closest agreement with the LAS-estimated fluxes using either the corrected or uncorrected MODIS inputs (LST and LAI). The SEBS model also computed reasonable H and LE values but was significantly more sensitive to errors in MODIS LST and LAI inputs than the TSEB model. In the TVT model, output of H and LE was unacceptable in either scenario of MODIS input which was attributable to errors in selection of the dry edge. With the TVT method, accurate determination of the dry edge end member is critical in regional ET estimation, but for humid and subhumid regions this end member may often be quite difficult to identify or encompass within a satellite scene.

A comparison of eddy-covariance and large aperture scintillometer measurements with respect to the energy balance closure problem

Abstract. We analyzed the seasonal variations of energy balance components over three different surfaces: irrigated cropland (Yingke, YK), alpine meadow (A'rou, AR), and spruce forest (Guantan, GT). The energy balance components were measured using eddy covariance (EC) systems and a large aperture scintillometer (LAS) in the Heihe River Basin, China, in 2008 and 2009. We also determined the source areas of the EC and LAS measurements with a footprint model for each site and discussed the differences between the sensible heat fluxes measured with EC and LAS at AR. The results show that the main EC source areas were within a radius of 250 m at all of the sites. The main source area for the LAS (with a path length of 2390 m) stretched along a path line approximately 2000 m long and 700 m wide. The surface characteristics in the source areas changed with the season at each site, and there were characteristic seasonal variations in the energy balance components at all of the sites. The sensible heat flux was the main term of the energy budget during the dormant season. During the growing season, however, the latent heat flux dominated the energy budget, and an obvious "oasis effect" was observed at YK. The sensible heat fluxes measured by LAS at AR were larger than those measured by EC at the same site. This difference seems to be caused by the so-called energy imbalance phenomenon, the heterogeneity of the underlying surfaces, and the difference between the source areas of the LAS and EC measurements.

32 The point of view of FDA

As part of a comprehensive study investigating how subsurface drainage systems affect the energy and water balances on land surfaces, a large aperture scintillometer (LAS) was used to determine the sensible heat and momentum fluxes over a corn (Zea mays) field. To keep the flux footprint of the observation within the 22 ha field boundary, the LAS had to be placed at a height no greater than 1.8 m above displacement height. As a result, the surface layer was mostly near-neutral at the LAS path height. Sensible heat fluxes were derived from the LAS measurements (HLAS) using four different Monin–Obukhov Similarity Theory (MOST) functions for temperature (fT). While correlating well with the sensible heat fluxes measured by the Eddy covariance system (HEC), the values of HLAS were systematically higher if the rule of thumb formula for estimating the roughness length (z0) was used. The use of this rule of thumb formula led to higher estimates than the EC measurements of the frictional velocity u*, to which HLAS is particularly sensitive under near-neutral conditions. With a modified formula for z0, a better agreement between HLAS and HEC is achieved for all the fT functions tested. Using the fT function (W71) proposed by Wyngaard et al. (1971) and the improved estimate of z0, HLAS agreed with HEC within 32 W m−2 and with a regression slope of 1.0 ± 0.05.

Evaluation of MOST functions and roughness length parameterization on sensible heat flux measured by large aperture scintillometer over a corn field

As part of a comprehensive study investigating how subsurface drainage systems affect the energy and water balances on land surfaces, a large aperture scintillometer (LAS) was used to determine the sensible heat and momentum fluxes over a corn ( Zea mays) field. To keep the flux footprint of the observation within the 22 ha field boundary, the LAS had to be placed at a height no greater than 1.8 m above displacement height. As a result, the surface layer was mostly near-neutral at the LAS path height. Sensible heat fluxes were derived from the LAS measurements ( H LAS) using four different Monin–Obukhov Similarity Theory (MOST) functions for temperature ( f T ). While correlating well with the sensible heat fluxes measured by the Eddy covariance system ( H EC), the values of H LAS were systematically higher if the rule of thumb formula for estimating the roughness length ( z 0) was used. The use of this rule of thumb formula led to higher estimates than the EC measurements of the frictional velocity u *, to which H LAS is particularly sensitive under near-neutral conditions. With a modified formula for z 0, a better agreement between H LAS and H EC is achieved for all the f T functions tested. Using the f T function (W71) proposed by Wyngaard et al. (1971) and the improved estimate of z 0, H LAS agreed with H EC within 32 W m −2 and with a regression slope of 1.0 ± 0.05.

New Mexico Scintillometer Network: Supporting Remote Sensing and Hydrologic and Meteorological Models

In New Mexico, a first-of-its-kind network of seven large aperture scintillometer (LAS) sites was established in 2006 to measure sensible heat fluxes over irrigated fields, riparian areas, deserts, lava flows, and mountain highlands. Wireless networking infrastructure and auxiliary meteorological measurements facilitate real-time data assimilation. LAS measurements are advantageous in that they vastly exceed the footprint size of commonly used ground measurements of sensible and latent heat fluxes (~100 m2), matching the pixel size of satellite images or grid cells of hydrologic and meteorological models (~0.1–5 km2). Consequently, the LAS measurements can be used to validate, calibrate, and force hydrologic, remote sensing, and weather forecast models. Initial results are presented for 1) variability and error of sensible heat flux measurements by scintillometers over heterogeneous terrain and 2) the validation of the Surface Energy Balance Algorithm for Land (SEBAL) applied to Moderate Resolution Imagin...

Large Aperture Scintillometer Intercomparison Study

Two field studies with six large aperture scintillometers (LASs) were performed using horizontal and slant paths. The accuracy of this novel and increasingly popular technique for measuring sensible heat fluxes was quantified by comparing measurements from different instruments over nearly identical transects. Random errors in LAS measurements were small, since correlation coefficients between adjacent measurements were greater than 0.995. However, for an ideal set-up differences in linear regression slopes of up to 21% were observed with typical inter-instrument differences of 6%. Differences of 10% are typical in more realistic measurement scenarios over homogeneous natural vegetation and different transect heights and locations. Inaccuracies in the optics, which affect the effective aperture diameter, are the most likely explanation for the observed differences.