Radar Quantitative
Precipitation Estimation（QPE） can provide continuous, high-resolution and
wide-coverage precipitation products which have become critical means of
meteorological monitoring. Although the current methods in different regions
have made considerable progress, the effect of QPE in complex terrain areas
still needs to be strengthened. Aiming at the QPE in the complex terrain area of
the northeast slope of the Qinghai-Tibet Plateau, this paper establishes a
real-time-dynamic-correction algorithm used geographic terrain factors based on
a quasi-stable moving-window based on existing estimation algorithms: fixed
empirical Z-I relationship, cloud classification empirical Z-I relationship,
and echo classification statistics Z-I relationship. The estimation performance
evaluation was conducted using the precipitation events in Linxia during the
flood season from 2017 to 2018. The results demonstrate that the estimated
precipitation value without the correction algorithm is often smaller than the
actual observation value, and the corrected average precipitation value is more
consistent with the actual observation value. For small rainfall events, the
cumulative distribution function (CDF) obtained by different estimation
algorithms deviates greatly from the actual observation. As the precipitation
level gradually increases, the CDF of estimated precipitation gradually
approaches the actual observation. It is more stable in the estimation
performance of the correction algorithm based on the statistics Z-I
relationship of the echo classification. The error of precipitation estimation
by different algorithms is quite different and the uncorrected algorithm mainly
underestimates to all precipitation events. The overall estimation deviation of
the correction algorithm both based on Z-I relationship of echo classification
statistics and Z-I relationship of fixed experience is relatively small. The uncorrected
algorithm has the advantage to estimate the main precipitation area of
convective-precipitation-weather events, but it has a poor ability to estimate
the precipitation intensity, and the estimated effect is a boost after the
correction. In particular, the correction algorithm based on cloud
classification experience Z-I relationship has better estimation ability for
convective precipitation weather events, especially the estimation ability of
short-duration heavy rainfall is significantly better than other algorithms.
The uncorrected algorithm has weaker precipitation estimates for stable
precipitation weather events, and the corrected estimates get closer to
observations.
LIU Weicheng, SHA Honge, XIAO Wei, GOU Shang, WANG Jixin, ZHANG Wei
.
Radar Quantitative Precipitation Estimation in
Complex Terrain Based on Dynamic Adjustment of Geographical Terrain Factors[J]. Plateau Meteorology, 0
: 1
.
DOI: 10.7522/j.issn.1000-0534.2021.00022
