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- Author or Editor: C. T. McElroy x
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Abstract
The authors have used CPFM (composition and photodissociative flux measurement) polarized limb radiance measurements combined with a vector radiative transfer model to estimate stratospheric aerosol number density, extinction coefficient profiles, and size distribution. The CPFM spectroradiometer is flown on board the NASA ER-2 high-altitude research aircraft. The vertical and horizontal polarization components of limb radiance, nadir radiance, and horizontal flux are measured in the wavelength range 300–770 nm from approximately 5°–10° above to 5°–10° below the local horizon. Results from two flights during April and May 1997 as part of the Photochemistry of Ozone Loss in the Arctic Region in Summer campaign are presented. Aerosol characteristics are determined by forcing the model radiances and polarization to match the measurements. Results indicate number densities at 20 km are roughly 5–6 cm−3 with an effective radius of 0.17–0.20 μm. Number, surface area, and volume densities compare favorably with two in situ particle counters also flown on the ER-2.
Abstract
The authors have used CPFM (composition and photodissociative flux measurement) polarized limb radiance measurements combined with a vector radiative transfer model to estimate stratospheric aerosol number density, extinction coefficient profiles, and size distribution. The CPFM spectroradiometer is flown on board the NASA ER-2 high-altitude research aircraft. The vertical and horizontal polarization components of limb radiance, nadir radiance, and horizontal flux are measured in the wavelength range 300–770 nm from approximately 5°–10° above to 5°–10° below the local horizon. Results from two flights during April and May 1997 as part of the Photochemistry of Ozone Loss in the Arctic Region in Summer campaign are presented. Aerosol characteristics are determined by forcing the model radiances and polarization to match the measurements. Results indicate number densities at 20 km are roughly 5–6 cm−3 with an effective radius of 0.17–0.20 μm. Number, surface area, and volume densities compare favorably with two in situ particle counters also flown on the ER-2.
The deployment of a space-based Doppler lidar would provide information that is fundamental to advancing the understanding and prediction of weather and climate.
This paper reviews the concepts of wind measurement by Doppler lidar, highlights the results of some observing system simulation experiments with lidar winds, and discusses the important advances in earth system science anticipated with lidar winds.
Observing system simulation experiments, conducted using two different general circulation models, have shown 1) that there is a significant improvement in the forecast accuracy over the Southern Hemisphere and tropical oceans resulting from the assimilation of simulated satellite wind data, and 2) that wind data are significantly more effective than temperature or moisture data in controlling analysis error. Because accurate wind observations are currently almost entirely unavailable for the vast majority of tropical cyclones worldwide, lidar winds have the potential to substantially improve tropical cyclone forecasts. Similarly, to improve water vapor flux divergence calculations, a direct measure of the ageostrophic wind is needed since the present level of uncertainty cannot be reduced with better temperature and moisture soundings alone.
The deployment of a space-based Doppler lidar would provide information that is fundamental to advancing the understanding and prediction of weather and climate.
This paper reviews the concepts of wind measurement by Doppler lidar, highlights the results of some observing system simulation experiments with lidar winds, and discusses the important advances in earth system science anticipated with lidar winds.
Observing system simulation experiments, conducted using two different general circulation models, have shown 1) that there is a significant improvement in the forecast accuracy over the Southern Hemisphere and tropical oceans resulting from the assimilation of simulated satellite wind data, and 2) that wind data are significantly more effective than temperature or moisture data in controlling analysis error. Because accurate wind observations are currently almost entirely unavailable for the vast majority of tropical cyclones worldwide, lidar winds have the potential to substantially improve tropical cyclone forecasts. Similarly, to improve water vapor flux divergence calculations, a direct measure of the ageostrophic wind is needed since the present level of uncertainty cannot be reduced with better temperature and moisture soundings alone.
