High sensitivity of Aeolus UV surface returns to surface reflectivity.

Area of Science:

• Earth and Space Science
• Atmospheric Science
• Remote Sensing

Background:

• Global ultraviolet (UV) surface reflectivity is typically derived from passive remote sensing, integrating reflected UV light over various directions.
• Existing methods rely on daylight observations and may not capture directional surface properties effectively.

Purpose of the Study:

• To demonstrate the capability of active remote sensing, specifically Aeolus lidar surface returns (LSR), for retrieving unidirectional UV surface reflectivity on a global scale.
• To establish a novel method for characterizing surface reflectivity using active sensing technology.

Main Methods:

• Utilized Aeolus lidar surface returns (LSR) data to assess sensitivity to surface characteristics.
• Compared gridded LSR data with Lambertian Equivalent Reflectivity (LER) climatologies from TROPOMI and GOME-2.
• Analyzed correlations between LSR and LER across global and regional scales for 36 distinct regions.

Main Results:

• Aeolus LSR successfully reproduced monthly surface reflectivity changes in the Sahara, consistent with TROPOMI and GOME-2 LER climatologies.
• Achieved high correlations (r > 0.90) between gridded LSR and LER at global and regional scales.
• Identified distinct land cover gradients from LSR signals, including water/land, vegetation/arid areas, and snow/no snow distinctions. A moderate negative agreement was found between LSR and vegetation index over vegetated areas (r < -0.60).

Conclusions:

• The study demonstrates the success of the first active remote sensing approach for retrieving unidirectional UV surface reflectivity using Aeolus.
• This active sensing method offers advantages over passive instruments, enabling the detection of land and snow cover changes, particularly in high latitudes and during nighttime observations.