An Advanced Method for Deriving Latent Energy Flux from a Scanning Raman Lidar
- D. I. Cooper *a,
- W. E. Eichingerb,
- J. Archuletaa,
- L. Hippsc,
- C. M. U. Nealed and
- J. H. Pruegere
- a Los Alamos National Lab., MS J577, Los Alamos, NM 87545
b Iowa Inst. for Hydraulic Research, Univ. of Iowa, Iowa City, IA 52242
c Dep. of Plants, Soils and Biometeorology, Utah State Univ., Logan UT 84322
d Dep. of Biological and Irrigation Engineering, Utah State Univ., Logan UT 84322
e USDA National Soil Tilth Lab., Ames IA 50011
One of the fundamental issues with lidar-derived evapotranspiration estimates is its reliance on tower-based measurements of Monin–Obukhov similarity variables, specifically the Obukhov length (L) and the friction velocity (u *). Our study indicates that L can be derived in the atmospheric surface layer directly from lidar range-height scans by estimating the integral length scale (ILS). Data from both three-dimensional sonic anemometers mounted on towers and lidar data collected during two subsequent field experiments were analyzed using autocorrelation analysis to estimate the ILS. The ILS values were then transformed into L values using a power-law similarity model and were compared to coincident tower-based observations. The comparisons between tower-based eddy covariance sensors and lidar data show that the lidar-derived L values are within the expected uncertainty and variability of standard point sensor measured observations. An additional model for estimating the friction velocity from the Obukhov length was also derived, and both L and u * were used to calculate the latent energy flux from lidar without external measurements. The evaporative fluxes from the standard method and the new advanced method were compared with eddy covariance fluxes, and it was found that the advanced method is superior.Please view the pdf by using the Full Text (PDF) link under 'View' to the left.
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