New airborne scanning lidar system: applications for atmospheric remote sensing

Influence of daylight and noise current on cloud and aerosol observations by spaceborne elastic scattering lidar

The influence of daylight and noise current on cloud and aerosol observations by realistic spaceborne lidar was examined by computer simulations. The reflected solar radiations, which contaminate the daytime return signals of lidar operations, were strictly and explicitly estimated by accurate radiative transfer calculations. It was found that the model multilayer cirrus clouds and the boundary layer aerosols could be observed during the daytime and the nighttime with only a few laser shots. However, high background noise and noise current make it difficult to observe volcanic aerosols in middle and upper atmospheric layers. Optimal combinations of the laser power and receiver field of view are proposed to compensate for the negative influence that is due to these noises. For the computer simulations, we used a realistic set of lidar parameters similar to the Experimental Lidar in-Space Equipment of the National Space Development Agency of Japan.

Lidar in-space technology experiment measurements of sea surface directional reflectance and the link to surface wind speed

The dependence of sea surface directional reflectance on surface wind stress suggests a method for deriving surface wind speed from space-based lidar measurements of sea surface backscatter. In particular, lidar measurements in the nadir angle range from 10 degrees to 30 degrees appear to be most sensitive to surface wind-speed variability in the regime below 10 m/s. The Lidar In-space Technology Experiment (LITE) shuttle lidar mission of September 1994 provided a unique opportunity to measure directional backscatter at selected locations by use of the landmark track maneuver and to measure fixed-angle backscatter from the ocean surfaces on a global scale. During the landmark track maneuver the shuttle orbiter orientation and roll axis are adjusted continuously to maintain the lidar footprint at a fixed location for a duration of ~1 min. Several data sets were converted to calibrated reflectance units and compared with a surface reflectance model to deduce surface wind speeds. Comparisons were made with ERS-1 scatterometer data and surface measurements.

Inference of Marine Atmospheric Boundary Layer Moisture and Temperature Structure Using Airborne Lidar and Infrared Radiometer Data

A new technique for retrieving near-surface moisture and profiles of mixing ratio and potential temperature through the depth of the marine atmospheric boundary layer (MABL) using airborne lidar and multichannel infrared radiometer data is presented. Data gathered during an extended field campaign over the Atlantic Ocean in support of the Lidar In-space Technology Experiment are used to generate 16 moisture and temperature retrievals that are then compared with dropsonde measurements. The technique utilizes lidar-derived statistics on the height of cumulus clouds that frequently cap the MABL to estimate the lifting condensation level. Combining this information with radiometer-derived sea surface temperature measurements, an estimate of the near-surface moisture can be obtained to an accuracy of about 0.8 g kg−1. Lidar-derived statistics on convective plume height and coverage within the MABL are then used to infer the profiles of potential temperature and moisture with a vertical resolution of 20 m. The rms accuracy of derived MABL average moisture and potential temperature is better than 1 g kg−1 and 1°C, respectively. The method relies on the presence of a cumulus-capped MABL, and it was found that the conditions necessary for use of the technique occurred roughly 75% of the time. The synergy of simple aerosol backscatter lidar and infrared radiometer data also shows promise for the retrieval of MABL moisture and temperature from space.