7B.2
Satellite Remote Sensing of Precipitation in Complex Terrain Analysis of TRMM PR V7 Rainfall Estimates in the Southern Appalachian Mountains

- Indicates paper has been withdrawn from meeting
- Indicates an Award Winner
Thursday, 6 February 2014: 11:15 AM
Room C210 (The Georgia World Congress Center )
Yajuan Duan, Department of Civil & Environmental Engineering, Pratt School of Engineering, Duke University, Durham, NC; and A. P. Barros

A raingauge network (GSMNP) deployed at mid to high elevations in the Southern Appalachian Mountains provides a unique opportunity to directly compare in-situ measurements and satellite-based rain rate estimates from the Tropical Rainfall Measurement Mission (TRMM) precipitation radar (PR) over a 4-year period of 2008-2012. The focus is not only on bulk statistics, but also on identifying the dependencies of retrieval algorithm performance on observing geometry, rainfall processes, and hydrometeorological regimes. In the Southern Appalachians, light rainfall accounts for 30-50% of annual freshwater input to headwater catchments, and therefore special emphasis is placed on the light rainfall detection at high elevations, which has been a known challenge such as in TRMM V6 products. Our analysis shows overall moderate improvements in the quantitative estimation of rainfall in the current TRMM V7 algorithm compared to V6, specifically better skill at detecting light rain events with good agreement with raingauge observations. Detailed case studies were conducted subsequently to characterize the vertical profiles of reflectivity and rain rate and the spatial distribution for typical cases of underestimation, overestimation, false alarm and missed detection for stratiform and convective precipitation. The results show that the dominant presence of stratiform light rainfall in the Southern Appalachians explains the substantial amount of false alarms uniformly distributed over the year, and the seasonality of missed detection statistics during the midday in the winter and early spring season. Specifically, TRMM PR 2A25 V7 tends to severely underestimate low level orographic enhancement of rainfall associated with low level fog and cloud feeder-seeder interactions. Precipitation produced by small-scale deep convective systems associated with severe local storms is also underestimated, which we attribute to non-uniform beam-filling effects that affect the reflectivity profile and consequently rainfall estimation. Interestingly, the TRMM PR 2A25 shows remarkable ability to detect intense hail that raingauges are unable to capture. Finally, the results of this study are evaluated, synthesized and generalized in terms of hydrometeorological regime toward improving retrieval in regions of complex terrain elsewhere.