Thursday, 24 January 2008
Planetary boundary layer height climatology from GPS/COSMIC moisture profiles
Exhibit Hall B (Ernest N. Morial Convention Center)
The planetary boundary layer (PBL) height is a crucial parameter that describes much of the diurnal, synoptic, and climatological processes associated with the PBL in a given region, including its cloud characterization and connections between the surface and free troposphere. However, the global climatology of the PBL is poorly established due to a lack of observational data, particularly over the oceans. Adding to the challenge and complexity of this issue, both from a modeling and observation context, is the fact that the PBL top is often so finely delineated that it is difficult to resolve by the limited vertical grid system in most models and observing systems. With its high vertical resolution (~ 100 m) and ability to penetrate cloud, the GPS radio occultation measurements are potentially very valuable for inferring the PBL height. However, past data have limited usefulness due to closed-loop tracking errors in the lower troposphere and limited coverage. The situation is much improved with the launch of the six-spacecraft COSMIC constellation in 2006. Not only is the spatiotemporal coverage dramatically increased over the existing pseudo-constellation of CHAMP, SAC-C, and GRACE, but COSMIC is specifically designed to acquire the occulting GPS signal through the open-loop (OL) tracking mode. The use of OL tracking allows the GPS measurements to probe deeper into the atmosphere with better accuracy. In this talk, we will provide an updated analysis of the accuracy and uncertainty of GPS specific humidity profiles in the lower troposphere and planetary boundary layer (PBL). Comparisons with nearby radiosonde soundings as well as NCEP and ECMWF operational analyses will be presented. We will utilize the GPS moisture profiles in deriving a climatology of the PBL height in the tropics and mid-latitudes that include seasonal and diurnal variations. The effectiveness and limitations of our algorithm will be discussed.
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