Impact of multiple radar reflectivity data assimilation on the numerical simulation of a flash flood event during the HyMeX campaign
An analysis to evaluate the impact of multiple radar reflectivity data with a three-dimensional variational (3-D-Var) assimilation system on a heavy precipitation event is presented. The main goal is to build a regionally tuned numerical prediction model and a decision-support system for environ...
| Main Authors: | , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Copernicus Publications
2017-11-01
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| Series: | Hydrology and Earth System Sciences |
| Online Access: | https://www.hydrol-earth-syst-sci.net/21/5459/2017/hess-21-5459-2017.pdf |
| Summary: | An analysis to evaluate the impact of multiple radar reflectivity
data with a three-dimensional variational (3-D-Var) assimilation
system on a heavy precipitation event is presented. The main goal is
to build a regionally tuned numerical prediction model and
a decision-support system for environmental civil protection
services and demonstrate it in the central Italian regions,
distinguishing which type of observations, conventional and not (or
a combination of them), is more effective in improving the accuracy
of the forecasted rainfall. In that respect, during the first
special observation period (SOP1) of HyMeX (Hydrological cycle in
the Mediterranean Experiment) campaign several intensive observing
periods (IOPs) were launched and nine of which occurred in
Italy. Among them, IOP4 is chosen for this study because of its low
predictability regarding the exact location and amount of
precipitation. This event hit central Italy on 14 September 2012
producing heavy precipitation and causing several cases of damage to
buildings, infrastructure, and roads. Reflectivity data taken from
three C-band Doppler radars running operationally during the event
are assimilated using the 3-D-Var technique to improve high-resolution
initial conditions. In order to evaluate the impact of the
assimilation procedure at different horizontal resolutions and to
assess the impact of assimilating reflectivity data from multiple
radars, several experiments using the Weather Research and Forecasting
(WRF) model are performed. Finally, traditional verification scores such
as accuracy, equitable threat score, false alarm ratio, and frequency
bias – interpreted by analysing their uncertainty through bootstrap
confidence intervals (CIs) – are used to objectively compare the
experiments, using rain gauge data as a benchmark. |
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| ISSN: | 1027-5606 1607-7938 |