Open AccessRadar-Based Quantitative Precipitation Estimation for the Cool Season in Complex Terrain: Case Studies from the NOAA Hydrometeorology Testbed
Author(s) -
Jian Zhang,
Yujie Qi,
David E. Kingsmill,
Kenneth W. Howard
Publication year - 2012
Publication title -
journal of hydrometeorology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.733
H-Index - 123
eISSN - 1525-755X
pISSN - 1525-7541
DOI - 10.1175/jhm-d-11-0145.1
Subject(s) - quantitative precipitation estimation , hydrometeorology , radar , environmental science , precipitation , meteorology , terrain , remote sensing , quantitative precipitation forecast , computer science , geology , geography , telecommunications , cartography
This study explores error sources of the National Weather Service operational radar-based quantitative precipitation estimation (QPE) during the cool season over the complex terrain of the western United States. A new, operationally geared radar QPE was developed and tested using data from the National Oceanic and Atmospheric Administration Hydrometeorology Testbed executed during the 2005/06 cool season in Northern California. The new radar QPE scheme includes multiple steps for removing nonprecipitation echoes, constructing a seamless hybrid scan reflectivity field, applying vertical profile of reflectivity (VPR) corrections to the reflectivity, and converting the reflectivity into precipitation rates using adaptive Z–R relationships. Specific issues in radar rainfall accumulations were addressed, which include wind farm contaminations, blockage artifacts, and discontinuities due to radar overshooting. The new radar QPE was tested in a 6-month period of the 2005/06 cool season and showed significant improvements over the current operational radar QPE (43% reduction in bias and 30% reduction in root-mean-square error) when compared with gauges. In addition, the new technique minimizes various radar artifacts and produces a spatially continuous rainfall product. Such continuity is important for accurate hydrological model predictions. The new technique is computationally efficient and can be easily transitioned into operations. One of the largest remaining challenges is obtaining accurate radar QPE over the windward slopes of significant mountain ranges, where low-level orographic enhancement of precipitation is not resolved by the operational radars leading to underestimation. Additional high-resolution and near-surface radar observations are necessary for more accurate radar QPE over these regions.