Retrieving cloud geometrical extents from MIPAS/ENVISAT measurements with a 2-D tomographic approach

Area of Science:

• Atmospheric science
• Remote sensing
• Cloud physics

Background:

• Accurate cloud vertical profiles are crucial for understanding Earth's energy balance but remain a key challenge in atmospheric science.
• Satellite instruments like MIPAS (Michelson Interferometer for Passive Atmospheric Sounding) can detect radiation from clouds, offering potential for improved atmospheric property retrieval.
• Existing 1-D models often approximate clouds as infinite horizontal layers, potentially underestimating Cloud Top Height (CTH).

Purpose of the Study:

• To develop and validate a 2-D retrieval model for simulating cloud effects on MIPAS measurements.
• To investigate the sensitivity of MIPAS spectra to cloud vertical and horizontal extents and position.
• To improve the retrieval accuracy of Cloud Top Height (CTH) and horizontal cloud dimensions.

Main Methods:

• Developed a 2-D retrieval model to simulate cloud effects on broad spectral intervals, accounting for atmospheric variability in the satellite orbit plane.
• Analyzed MIPAS spectral data to assess sensitivity to cloud geometry.
• Compared 2-D retrieval results with coincident CALIOP (Cloud-Aerosol Lidar with Orthogonal Polarisation) measurements for validation.

Main Results:

• The 2-D model revealed MIPAS spectra are sensitive to both vertical and horizontal cloud extents and position.
• One-dimensional models were found to underestimate CTH.
• The 2-D approach enabled retrieval of both CTH and horizontal dimensions for optically thin Polar Stratospheric Clouds (PSCs).

Conclusions:

• A 2-D approach is superior to 1-D models for retrieving cloud properties from MIPAS data.
• The developed 2-D model successfully retrieved CTH and horizontal dimensions for PSCs.
• Retrieved PSC properties showed excellent agreement with coincident CALIOP measurements, validating the 2-D method.