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- Author or Editor: Jan Kleissl x
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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 Imaging Spectroradiometer (MODIS) satellite imagery. Findings from this study are discussed in the context of researchers' and practitioners' data assimilation needs.
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 Imaging Spectroradiometer (MODIS) satellite imagery. Findings from this study are discussed in the context of researchers' and practitioners' data assimilation needs.
The Canopy Horizontal Array Turbulence Study (CHATS) took place in spring 2007 and is the third in the series of Horizontal Array Turbulence Study (HATS) experiments. The HATS experiments have been instrumental in testing and developing subfilterscale (SFS) models for large-eddy simulation (LES) of planetary boundary layer (PBL) turbulence. The CHATS campaign took place in a deciduous walnut orchard near Dixon, California, and was designed to examine the impacts of vegetation on SFS turbulence. Measurements were collected both prior to and following leafout to capture the impact of leaves on the turbulence, stratification, and scalar source/sink distribution. CHATS utilized crosswind arrays of fast-response instrumentation to investigate the impact of the canopy-imposed distribution of momentum extraction and scalar sources on SFS transport of momentum, energy, and three scalars. To directly test and link with PBL parameterizations of canopy-modified turbulent exchange, CHATS also included a 30-m profile tower instrumented with turbulence instrumentation, fast and slow chemical sensors, aerosol samplers, and radiation instrumentation. A highresolution scanning backscatter lidar characterized the turbulence structure above and within the canopy; a scanning Doppler lidar, mini sodar/radio acoustic sounding system (RASS), and a new helicopter-observing platform provided details of the PBL-scale flow. Ultimately, the CHATS dataset will lead to improved parameterizations of energy and scalar transport to and from vegetation, which are a critical component of global and regional land, atmosphere, and chemical models. This manuscript presents an overview of the experiment, documents the regime sampled, and highlights some preliminary key findings.
The Canopy Horizontal Array Turbulence Study (CHATS) took place in spring 2007 and is the third in the series of Horizontal Array Turbulence Study (HATS) experiments. The HATS experiments have been instrumental in testing and developing subfilterscale (SFS) models for large-eddy simulation (LES) of planetary boundary layer (PBL) turbulence. The CHATS campaign took place in a deciduous walnut orchard near Dixon, California, and was designed to examine the impacts of vegetation on SFS turbulence. Measurements were collected both prior to and following leafout to capture the impact of leaves on the turbulence, stratification, and scalar source/sink distribution. CHATS utilized crosswind arrays of fast-response instrumentation to investigate the impact of the canopy-imposed distribution of momentum extraction and scalar sources on SFS transport of momentum, energy, and three scalars. To directly test and link with PBL parameterizations of canopy-modified turbulent exchange, CHATS also included a 30-m profile tower instrumented with turbulence instrumentation, fast and slow chemical sensors, aerosol samplers, and radiation instrumentation. A highresolution scanning backscatter lidar characterized the turbulence structure above and within the canopy; a scanning Doppler lidar, mini sodar/radio acoustic sounding system (RASS), and a new helicopter-observing platform provided details of the PBL-scale flow. Ultimately, the CHATS dataset will lead to improved parameterizations of energy and scalar transport to and from vegetation, which are a critical component of global and regional land, atmosphere, and chemical models. This manuscript presents an overview of the experiment, documents the regime sampled, and highlights some preliminary key findings.
