A variational scheme for retrieving ice cloud properties from combined radar, lidar, and infrared radiometer

By Julien Delanoë, Robin J. Hogan. 2008

312 citations recorded by the source corpus.

Subfields: Atmospheric Science, Global and Planetary Change

View Paper: https://www.semanticscholar.org/paper/0f984e07e3cc8203723eafa95caf507189202997

How researchers see this paper

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

In Atmospheric Science

1. Zhien Wang
2. Andrew J. Heymsfield
3. Gerald Mace
4. Seiji Kato
5. Tristan L'Ecuyer
6. Ulrike Lohmann
7. M. Krämer
8. Robin J. Hogan

In Global and Planetary Change

1. Zhien Wang
2. Andrew J. Heymsfield
3. Seiji Kato
4. Ulrike Lohmann
5. M. Krämer
6. Gerald Mace
7. Tristan L'Ecuyer
8. Paul R. Field

Citations in the corpus

• Tropical composition, cloud and climate coupling experiment validation for cirrus cloud profiling retrieval using cloudsat radar and CALIPSO lidar (2010, methodology): “The prior knowledge can come from empirical relations derived from extensive in situ measurements, such as IWC and Ze relations [Liu and Illingworth, 2000] or normalized number concentration with temperature [Delanoë and Hogan, 2008], or from other validated algorithm estimations in the literature.”
• Combined CloudSat‐CALIPSO‐MODIS retrievals of the properties of ice clouds (2010, unknown): “It is a relatively straightforward matter to add forward models for these additional measurements within the same retrieval framework, and we have recently done this for the High Spectral Resolution Lidar of the forthcoming EarthCare satellite [ Delanoë and Hogan , 2008b].”
• Mixed-Phase Clouds: Progress and Challenges (2017, methodology): “…and CALIPSO lidar measurements have been used to effectively identify mixed-phase clouds globally (Zhang et al. 2010; Wang et al. 2013), and to provide improved microphysical property retrievals for ice (Delanoë and Hogan 2008; Deng et al. 2010, 2013; Okamoto et al. 2010; Matus and L’Ecuyer 2017).”
• Radar Scattering from Ice Aggregates Using the Horizontally Aligned Oblate Spheroid Approximation (2012, methodology): “as spheres consisting of a homogeneous mixture of ice and air and to apply Mie theory (e.g., Brown et al. 1995; Hogan and Illingworth 1999; Donovan et al. 2001; Hogan et al. 2006; Delanoë and Hogan 2008; Austin et al. 2009).”
• An observationally based evaluation of cloud ice water in CMIP3 and CMIP5 GCMs and contemporary reanalyses using contemporary satellite data (2012, methodology): “…and the extinction coefficient from the thinnest cirrus (seen only by the lidar) to the thickest ice cloud [Austin and Stephens, 2001; Hogan, 2006; Delanoë and Hogan, 2008, 2010; Mace et al., 2009; Young and Vaughan, 2009; Sassen et al., 2009; Stein et al., 2011; M. Deng et al., Evaluation of…”
• Characterizing and understanding radiation budget biases in CMIP3/CMIP5 GCMs, contemporary GCM, and reanalysis (2013, methodology): “…cloud + convective core + precipitating), where the observed cloud ice estimate is from the ensemble mean of three total ice water path observed estimates from the standard CloudSat, a version of DARDAR [Delanoë and Hogan, 2008, 2010], and a version of 2C-ICE [Deng et al., 2013] satellite products.”