Estimation of spatially distributed latent heat flux over complex terrain from a Raman lidar

Eichinger, W. E.; Cooper, D. I.; Kao, Jim; Chen, L.C; Hipps, L. E.; Prueger, John H.

doi:10.1016/s0168-1923(00)00183-0

Cited by 29 publications

(29 citation statements)

References 24 publications

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“…This 1 h mean profile close to the ground is similar to what was measured by Eichinger et al (2000) with a scanning Raman lidar. However, with the WVDIAL technique a larger range can be investigated.…”

Section: Performance and Analyses Of The Low-level Rhi Scanssupporting

confidence: 83%

“…The horizontal variations of the moisture fields can be detected with scanning lidar. Scanning WVRL measurements were used, for example, to observe the WV structures in the ABL (Goldsmith et al, 1998;Eichinger et al, 1999;Whiteman et al, 2006;Froidevaux et al, 2013;Matsuda, 2013) or to estimate latent heat fluxes at the surface (Eichinger et al, 2000). However, the SNR is still limited during daytime (Turner at al., 2002), making high-resolution scans under daylight conditions more difficult than with WVDIAL; and 3-D measurements of WVRL have not been demonstrated yet.…”

Section: F Späth Et Al: 3-d Water Vapor Field In the Atmospheric Bomentioning

confidence: 99%

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3-D water vapor field in the atmospheric boundary layer observed with scanning differential absorption lidar

et al. 2016

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Abstract. High-resolution three-dimensional (3-D) water vapor data of the atmospheric boundary layer (ABL) are required to improve our understanding of land-atmosphere exchange processes. For this purpose, the scanning differential absorption lidar (DIAL) of the University of Hohenheim (UHOH) was developed as well as new analysis tools and visualization methods. The instrument determines 3-D fields of the atmospheric water vapor number density with a temporal resolution of a few seconds and a spatial resolution of up to a few tens of meters. We present three case studies from two field campaigns. In spring 2013, the UHOH DIAL was operated within the scope of the HD(CP) 2 Observational Prototype Experiment (HOPE) in western Germany. HD(CP) 2 stands for High Definition of Clouds and Precipitation for advancing Climate Prediction and is a German research initiative. Range-height indicator (RHI) scans of the UHOH DIAL show the water vapor heterogeneity within a range of a few kilometers up to an altitude of 2 km and its impact on the formation of clouds at the top of the ABL. The uncertainty of the measured data was assessed for the first time by extending a technique to scanning data, which was formerly applied to vertical time series. Typically, the accuracy of the DIAL measurements is between 0.5 and 0.8 g m −3 (or < 6 %) within the ABL even during daytime. This allows for performing a RHI scan from the surface to an elevation angle of 90 • within 10 min. In summer 2014, the UHOH DIAL participated in the Surface Atmosphere Boundary Layer Exchange (SABLE) campaign in southwestern Germany. Conical volume scans were made which reveal multiple water vapor layers in three dimensions. Differences in their heights in different directions can be attributed to different surface elevation. With low-elevation scans in the surface layer, the humidity profiles and gradients can be related to different land cover such as maize, grassland, and forest as well as different surface layer stabilities.

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Section: Performance and Analyses Of The Low-level Rhi Scanssupporting

confidence: 83%

Section: F Späth Et Al: 3-d Water Vapor Field In the Atmospheric Bomentioning

confidence: 99%

3-D water vapor field in the atmospheric boundary layer observed with scanning differential absorption lidar

et al. 2016

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“…Linear regression between the water vapour mixing ratio profiles and the similarity functions are used to estimate E at hundreds of points over the surface. The method to estimate E from LIDAR data and Monin-Obukhov similarity theory is presented in Eichinger et al (2000). The main advantage of using LIDAR over other methods is that it provides a spatially integrated measure of water vapour flux over mixed terrain and canopy rather than simply a point measurement for a particular area.…”

Section: Lidar and Other Laser-based Methodsmentioning

confidence: 99%

A review of models and micrometeorological methods used to estimate wetland evapotranspiration

Drexler

Snyder

Spano

et al. 2004

Hydrological Processes

316

238

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Abstract:Within the past decade or so, the accuracy of evapotranspiration (ET) estimates has improved due to new and increasingly sophisticated methods. Yet despite a plethora of choices concerning methods, estimation of wetland ET remains insufficiently characterized due to the complexity of surface characteristics and the diversity of wetland types. In this review, we present models and micrometeorological methods that have been used to estimate wetland ET and discuss their suitability for particular wetland types. Hydrological, soil monitoring and lysimetric methods to determine ET are not discussed.Our review shows that, due to the variability and complexity of wetlands, there is no single approach that is the best for estimating wetland ET. Furthermore, there is no single foolproof method to obtain an accurate, independent measure of wetland ET. Because all of the methods reviewed, with the exception of eddy covariance and LIDAR, require measurements of net radiation (R n ) and soil heat flux (G), highly accurate measurements of these energy components are key to improving measurements of wetland ET.Many of the major methods used to determine ET can be applied successfully to wetlands of uniform vegetation and adequate fetch, however, certain caveats apply. For example, with accurate R n and G data and small Bowen ratio (ˇ) values, the Bowen ratio energy balance method can give accurate estimates of wetland ET. However, large errors in latent heat flux density can occur near sunrise and sunset when the Bowen ratioˇ³ 1Ð0. The eddy covariance method provides a direct measurement of latent heat flux density ( E) and sensible heat flux density (H), yet this method requires considerable expertise and expensive instrumentation to implement. A clear advantage of using the eddy covariance method is that E can be compared with R n -G-H, thereby allowing for an independent test of accuracy. The surface renewal method is inexpensive to replicate and, therefore, shows particular promise for characterizing variability in ET as a result of spatial heterogeneity. LIDAR is another method that has special utility in a heterogeneous wetland environment, because it provides an integrated value for ET from a surface. The main drawback of LIDAR is the high cost of equipment and the need for an independent ET measure to assess accuracy. If R n and G are measured accurately, the Priestley-Taylor equation can be used successfully with site-specific calibration factors to estimate wetland ET. The 'crop' cover coefficient (K c ) method can provide accurate wetland ET estimates if calibrated for the environmental and climatic characteristics of a particular area. More complicated equations such as the Penman and Penman-Monteith equations also can be used to estimate wetland ET, but surface variability and lack of information on aerodynamic and surface resistances make use of such equations somewhat questionable.

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“…Previously, a scanning, solar-blind Raman lidar system operating at 248 nm (Eichinger et al 1999) was used for daytime turbulence measurements in the surface layer (e.g., Eichinger et al 2000Eichinger et al , 2006Cooper et al 2003). However, due to the limited range of this system (a few 100 m) caused by ozone absorption in this wavelength range, measurements up to the CBL top are not possible resulting in very limited information about entrainment processes.…”

Section: Introductionmentioning

confidence: 99%

Can Water Vapour Raman Lidar Resolve Profiles of Turbulent Variables in the Convective Boundary Layer?

Wulfmeyer

Pal

Turner

et al. 2010

Boundary-Layer Meteorol

111

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High-resolution water vapour measurements made by the Atmospheric Radiation Measurement (ARM) Raman lidar operated at the Southern Great Plains Climate Research Facility site near Lamont, Oklahoma, U.S.A. are presented. Using a 2-h measurement period for the convective boundary layer (CBL) on 13 September 2005, with temporal and spatial resolutions of 10 s and 75 m, respectively, spectral and autocovariance analyses of water vapour mixing ratio time series are performed. It is demonstrated that the major part of the inertial subrange was detected and that the integral scale was significantly larger than the time resolution. Consequently, the major part of the turbulent fluctuations was resolved. Different methods to retrieve noise error profiles yield consistent results and compare well with noise profiles estimated using Poisson statistics of the Raman lidar signals. Integral scale, mixing-ratio variance, skewness, and kurtosis profiles were determined including error bars with respect to statistical and sampling errors. The integral scale ranges between 70 and 130 s at the top of the CBL. Within the CBL, up to the third order, noise errors are significantly smaller than sampling errors and the absolute values of turbulent variables, respectively. The mixing-ratio variance profile rises monotonically from ≈0.07 to ≈3.7 g 2 kg −2 in the entrainment zone. The skewness is nearly zero up to 0.6 z/z i , becomes −1 around 0.7-0.8 z/z i , crosses zero at about 0.95 z/z i , and reaches about 1.7 at 1.1 z/z i (here, z is the height and z i is the CBL depth). The noise errors are too large to derive fourth-order moments with sufficient accuracy. Consequently, to the best of our knowledge, the ARM Raman lidar is the first water vapour Raman lidar with demonstrated capability to retrieve profiles of turbulent variables up to the third order during daytime throughout the atmospheric CBL.

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Estimation of spatially distributed latent heat flux over complex terrain from a Raman lidar

Cited by 29 publications

References 24 publications

3-D water vapor field in the atmospheric boundary layer observed with scanning differential absorption lidar

3-D water vapor field in the atmospheric boundary layer observed with scanning differential absorption lidar

A review of models and micrometeorological methods used to estimate wetland evapotranspiration

Can Water Vapour Raman Lidar Resolve Profiles of Turbulent Variables in the Convective Boundary Layer?

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