Ashwin Mahesh

Atmospheric multiple scattering effects on GLAS altimetry. II. Analysis of expected errors in Antarctic altitude measurements

For pt.I see ibid., vol.39, no.1, p.92-101 (2001). The altimetry bias in the Geoscience Laser Altimeter System (GLAS) or other laser altimeters resulting from atmospheric multiple scattering is studied in relationship to current knowledge of cloud properties over the Antarctic Plateau. Estimates of seasonal and interannual changes in the bias are presented. Results show the bias in altitude from multiple scattering in clouds would be a significant error source without correction. The selective use of low-optical-depth clouds or cloud-free observations, as well as improved analysis of the return pulse such as by the Gaussian method used here, is necessary to minimize the surface altitude errors. The magnitude of the bias is affected by variations in cloud height, cloud effective particle size, and optical depth. Interannual variations in these properties as well as in cloud cover fraction could lead to significant year-to-year variations in the altitude bias. Although cloud-free observations reduce biases in surface elevation measurements from space, over Antarctica these may often include near-surface blowing snow, also a source of scattering-induced delay. With careful selection and analysis of data, laser altimetry specifications can be met.

Cloud radiative forcing at the top of the atmosphere during FIRE ACE derived from AVHRR data

Cloud radiative forcing at the top of the atmosphere is derived from narrowband visible and infrared radiances from NOAA-12 and NOAA-14 advanced very high resolution radiometer (AVHRR) data taken over the Arctic Ocean during the First ISCCP Regional Experiment Arctic Cloud Experiment (FIRE ACE) during spring and summer 1998. Shortwave and longwave fluxes at the top of the atmosphere (TOA) were computed using narrowband-to-broadband conversion formulae based on coincident Earth Radiation Budget Experiment (ERBE) broadband and AVHRR narrowband radiances. The NOAA-12/NOAA-14 broadband data were validated using model calculations and coincident broadband flux radiometer data from the Surface Heat Budget of the Arctic Ocean experiment and from aircraft data. The AVHRR TOA albedos agreed with the surface- and aircraft-based albedos to within one standard deviation of ±0.029 on an instantaneous basis. Mean differences ranged from −0.012 to 0.023 depending on the radiometer and platform. AVHRR-derived longwave fluxes differed from the model calculations using aircraft- and surface-based fluxes by −0.2 to −0.3 W m−2, on average, when the atmospheric profiles were adjusted to force agreement between the observed and the calculated downwelling fluxes. The standard deviations of the differences were less than 2%. Mean total TOA albedo for the domain between 72°N and 80°N and between 150°W and 180°W changed from 0.695 in May to 0.510 during July, while the longwave flux increased from 217 to 228 W m−2. Net radiation increased from −89 to −2 W m−2 for the same period. Net cloud forcing varied from −15 W m−2 in May to −31 W m−2 during July, while longwave cloud forcing was nearly constant at ∼8 W m−2. Shortwave cloud forcing dominated the cloud effect, ranging from −22 W m−2 during May to −40 W m−2 in July. The mean albedos and fluxes are consistent with previous measurements from the ERBE, except during May when the albedo and longwave flux were greater than the maximum ERBE values. The cloud-forcing results, while similar to some earlier estimates, are the most accurate values hitherto obtained for regions in the Arctic. When no significant melting was present, the clear-sky longwave flux showed a diurnal variation similar to that over land under clear skies. These data should be valuable for understanding the Arctic energy budget and for constraining models of atmosphere and ocean processes in the Arctic.

Aerosol and cloud measurements at 532 and 1064 nm by the GLAS polar orbiting lidar instrument

The first polar orbiting satellite lidar instrument, the Geoscience Laser Altimeter System (GLAS), was launched in 2003 and is approaching six months of data operations. As part of the NASA Earth Observing System (EOS) project, the GLAS instrument is intended as a laser sensor fulfilling complementary requirements for several Earth science disciplines including atmospheric and surface applications on the Ice, Cloud and Land Elevation Satellite. In this paper we present examples of atmospheric measurement results and explain data products now accessible for the science community

Atmospheric measurements by the geoscience laser altimeter system: initial results

The Geoscience Laser Altimeter System launched in early 2003 is the first satellite instrument in space to globally observe the distribution of clouds and aerosol through laser remote sensing. The instrument is a basic backscatter lidar that operates at two wavelengths, 532 and 1064 nm. The mission data products for atmospheric observations include the cali- brated, observed, attenuated backscatter cross section for cloud and aerosol; height detection for multiple cloud layers; plane- tary boundary layer height; cirrus and aerosol optical depth and the height distribution of aerosol and cloud scattering cross sec- tion profiles. The data will enhance knowledge in several areas of atmospheric science, in particular the distribution, transport and influence of atmospheric aerosol. Measurements of the coverage and height of polar and cirrus cloud should be signifi- cantly more accurate than previous global measurement. Initial results from the first several months of operation show the de- tailed height structure of clouds and aerosol on a global basis as expected.

An overview of the GLAS real-time atmospheric processing algorithms and results from the analysis of simulated GLAS data sets

A new era in atmospheric remote sensing is about to begin. Global monitoring of clouds and aerosols from space using a backscatter lidar system will greatly add to our knowledge in areas such as polar cloud climatology, aerosol loading and transport, and the planetary boundary layer. The Geoscience Laser Altimeter System (GLAS) will produce nearly 5 GB of data per day. A challenge is to create autonomous algorithms that will analyze the data in near-real time. This paper briefly discusses the algorithms and presents results of testing with simulated GLAS data sets.