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

New Mexico Scintillometer Network: Supporting Remote Sensing and Hydrologic and Meteorological... 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 (~0.15 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. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Bulletin of the American Meteorological Society American Meteorological Society

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

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Publisher
American Meteorological Society
Copyright
Copyright © American Meteorological Society
ISSN
1520-0477
D.O.I.
10.1175/2008BAMS2480.1
Publisher site
See Article on Publisher Site

Abstract

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 (~0.15 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.

Journal

Bulletin of the American Meteorological SocietyAmerican Meteorological Society

Published: Feb 27, 2009

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