Underestimation of deep convective cloud tops by thermal imagery

By S. Sherwood, J. Chae, Patrick Minnis, Matthew J. McGill. 2004

139 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Atmospheric Science, Global and Planetary Change

View Paper: https://www.semanticscholar.org/paper/ab40fce8d67f655df6ff69333d4d19fdcd94b2be

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

1. William B. Rossow

In Atmospheric Science

1. H. Chepfer
2. G. Cesana
3. Q. Fu
4. S. Fueglistaler
5. T. Dunkerton
6. B. Getzewich
7. W. Paul Menzel
8. Steven A. Ackerman

In Global and Planetary Change

1. H. Chepfer
2. G. Cesana
3. Q. Fu
4. Steven A. Ackerman
5. T. Dunkerton
6. B. Getzewich
7. W. Paul Menzel
8. Andrew K. Heidinger

Citations in the corpus

• Assessment of Global Cloud Datasets from Satellites: Project and Database Initiated by the GEWEX Radiation Panel (2013, background): “The “radiometric height” may lie as much as a few kilometers below the “physical height” of the cloud top, depending on the cloud extinction profile and vertical extent (e.g., Liao et al. 1995; Wang et al. 1999; Sherwood et al. 2004; Holz et al. 2006; Minnis et al. 2008b; Stubenrauch et al. 2010).”
• Tropical tropopause layer (2009, background): “Cloud top heights derived from thermal imagery are found to suffer from a systematic low bias [Sherwood et al., 2004] and miss the highest parts of convective clouds because of the relatively low spatial resolution.”