Workshop Overview:
In 2007 the Intergovernmental Panel on Climate Change (IPCC) reiterated that “Cloud feedbacks remain the largest source of uncertainty” in climate projections. How clouds change in response to radiative forcing effectively determines the sensitivity of the Earth’s temperature to increases in greenhouse gases. Clouds in the boundary layer, the lowermost region of the atmosphere adjacent to the Earth’s surface, are known to play the key role in climate feedbacks that lead to these large uncertainties. Yet current climate models remain far from realistically representing the cloudy boundary layer, as they are limited by the inability to adequately represent the small-scale physical processes associated with turbulence, convection and clouds.
Although some relevant information can be obtained from existing measurements and missions, we remain far from directly observing the thermodynamic structure (e.g. temperature and water content) underneath clouds. Current efforts attempt to leverage information from platforms, which were not specifically designed to support boundary layer cloud science.
Much of the uncertainty regarding cloud-climate feedbacks and consequent unreliability of climate projection is associated with this deep lack of observations of the cloudy boundary layer on a global scale. Only technology breakthroughs can lead to observations at the required scales. This Study will identify the technology developments required to obtain the space-borne measurements needed to significantly reduce this key climate projection uncertainty.
Team Leads
-
Caltech
-
Joao Teixeira
Jet Propulsion Laboratory
-
Cornell University
The study program schedule is available in .pdf here
- Chi Ao — JPL
- Simona Bordoni — Caltech
- Christopher Bretherton — University of Washington
- Moustafa T. Chahine — JPL
- David J. Diner — JPL
- Eric Fetzer — JPL
- Yong Hu — NASA LaRC
- Brian Kahn — NASA/JPL
- Seiji Kato — NASA Langley Research Center
- Stephen Klein — Lawrence Livermore National Laboratory
- Daniel Klocke — Max Planck Institute for Meteorologie
- Pavlos Kollias — McGill University
- Terry Kubar — JPL/Caltech
- Bjorn Lambrigsten — JPL
- Anthony J. Mannucci — JPL/Caltech
- Christine Nam — Max Planck Institute for Meteorologie
- Joel Norris — Scripps Institution of Oceanography/UCSD
- Gallia Painter — University of Washington
- Steve Platnick — NASA GSFC
- Michael Pritchard — University of California, San Diego
- Camille M. Risi — CIRES
- Lynn M. Russell — University of California, San Diego
- Tapio Schneider — Caltech
- Graeme L. Stephens — Colorado State University
- Hui Su — JPL
- Joao Teixeira — JPL
- Joe Turk — JPL
- Robert Wood — University of Washington
- Dong L. Wu — JPL
- Qing Yue — JPL/Caltech
- Yuk L. Yung — Caltech
Presentations
| Speaker | Affiliation | Presentation |
|---|---|---|
| Dave Diner | JPL | Advances in Multiangular and Polarimetric Imaging: Application to Boundary Layer Clouds and Aerosols (.pdf) |
| Eric Fetzer | JPL | Spaceborne hyperspectral infrared observations of the cloudy boundary layer (.pdf) |
| Yong Hu | NASA LaRC | Introduction to LIDAR Observations Relevant to Boundary Layer Cloud Studies (.pdf) |
| Seiji Kato | NASA Langley Research Center | Toward Achieving a Consistency Between Radiative Flux and Cloud Property Changes in Climate Time Scale (.pdf) |
| Pavlos Kollias | McGill University | Advancing Cloud and Precipitation Observations from Space – A Radar Perspective (.pdf) |
| Bjorn Lambrigtsen | JPL | Are Microwave Sounders Obsolete? (.pdf) |
| Anthony Mannucci | JPL/Caltech | Radio Occultation Measurements in the Cloudy Boundary Layer (.pdf) |
| Steve Platnick | NASA GSFC | Passive satellite imager capabilities for boundary layer cloud characterization: current limitations and future needs (.pdf) |
| Joe Turk | JPL | Current and Future Satellite Observations of Precipitation (.pdf) |
| Rob Wood | University of Washington | Critical Aspects of Cloudy Boundary Layers: What Do We Need to Know? (.pdf) |
| Dong Wu | JPL | A Combined GPS-RO and WindCam System for PBL Remote Sensing (.pdf) |
