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Near-infrared remote sensing of Los Angeles trace gas distributions from a mountaintop site
摘要： The Los Angeles basin is a significant anthropogenic source of major greenhouse gases (CO2 and CH4) and the pollutant CO, contributing significantly to regional and global climate change. We present a novel approach for monitoring the spatial and temporal distributions of greenhouse gases in the Los Angeles basin using a high-resolution spectroscopic remote sensing technique. A new Fourier transform spectrometer called CLARS-FTS has been deployed since May, 2010, at Jet Propulsion Laboratory (JPL)'s California Laboratory for Atmospheric Remote Sensing (CLARS) on Mt. Wilson, California, for automated long-term measurements of greenhouse gases. The instrument design and performance of CLARS-FTS are presented. From its mountaintop location at an altitude of 1673 m, the instrument points at a programmed sequence of ground target locations in the Los Angeles basin, recording spectra of reflected near-IR solar radiation. Column-averaged dry-air mole fractions of greenhouse gases (XGHG) including XCO2, XCH4, and XCO are retrieved several times per day for each target. Spectra from a local Spectralon? scattering plate are also recorded to determine background (free tropospheric) column abundances above the site. Comparisons between measurements from LA basin targets and the Spectralon? plate provide estimates of the boundary layer partial column abundances of the measured species. Algorithms are described for transforming the measured interferograms into spectra, and for deriving column abundances from the spectra along with estimates of the measurement precision and accuracy. The CLARS GHG measurements provide a means to infer relative, and possibly absolute, GHG emissions.
关键词： column abundances,remote sensing,greenhouse gases,Fourier transform spectrometer,Los Angeles basin
更新于2025-09-23 15:22:29
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High-resolution land surface modeling utilizing remote sensing parameters and the Noah UCM: a case study in the Los Angeles Basin
摘要： In the current work we investigate the utility of remote-sensing-based surface parameters in the Noah UCM (urban canopy model) over a highly developed urban area. Landsat and fused Landsat–MODIS data are utilized to generate high-resolution (30 m) monthly spatial maps of green vegetation fraction (GVF), impervious surface area (ISA), albedo, leaf area index (LAI), and emissivity in the Los Angeles metropolitan area. The gridded remotely sensed parameter data sets are directly substituted for the land-use/lookup-table-based values in the Noah-UCM modeling framework. Model performance in reproducing ET (evapotranspiration) and LST (land surface temperature) ?elds is evaluated utilizing Landsat-based LST and ET estimates from CIMIS (California Irrigation Management Information System) stations as well as in situ measurements. Our assessment shows that the large deviations between the spatial distributions and seasonal ?uctuations of the default and measured parameter sets lead to signi?cant errors in the model predictions of monthly ET ?elds (RMSE = 22.06 mm month?1). Results indicate that implemented satellite-derived parameter maps, particularly GVF, enhance the capability of the Noah UCM to reproduce observed ET patterns over vegetated areas in the urban domains (RMSE= 11.77 mm month?1). GVF plays the most signi?cant role in reproducing the observed ET ?elds, likely due to the interaction with other parameters in the model. Our analysis also shows that remotely sensed GVF and ISA improve the model’s capability to predict the LST differences between fully vegetated pixels and highly developed areas.
关键词： remote sensing,land surface modeling,Noah UCM,evapotranspiration,urban canopy model,Los Angeles Basin,land surface temperature
更新于2025-09-09 09:28:46