Geoscience Reference
In-Depth Information
Data sources such as GPS can be problematical because they are vertically integrated
measurements depending on the accuracy of the specification of the forecast background
errors, and interaction with other data sources to allocate changes to humidity in the vertical
can have dramatic impacts on forecast precipitation. The use of high vertical and horizontal
spatial and temporal resolution Doppler radar winds and reflectivity or rain rate data, and
improvements in specification of forecast background errors, can lead to changes and
improvements in the impact of different data sources and the accuracy of the precipitation
in the early hours of the forecast.
NWP systems can suffer from imbalances in the initial conditions leading to spin-up or spin-
down of precipitation in the initial stages of the forecast. Work to improve this will help to
improve skill in the early hours of the nowcasts. Improvements in the skill of the forecast
model itself in terms of precipitation biases are likely to help both the forecast and the
ability to assimilate observations. We tend to use radar derived rain rates to verify the NWP
forecasts, for assimilate into the models and to improve the formulation of the model.
However, the radar data can have quality issues, for example relating to attenuation, and
improvements in quality control and data processing are needed to ensure that the radar
data are of high quality.
The entire UK network of weather radars will gradually be updated to produce Doppler
radial winds and also dual-polarization data and radar refractivity measurements. The use
of radar data in NWP high resolution variational data assimilation has the potential to
improve on current extrapolation-based nowcasts. To achieve this we need high quality
radar data, fast processing (techniques and computer power), careful specification of
observation and forecast background error covariances and correlations through the
scientific design of the data assimilation system, and a good representation of the dynamical
and microphysical processes in the NWP forecast model.
In future it is hoped to exploit ensemble techniques in both the data assimilation and
production of forecasts. If there is sufficient computer power available for hourly NWP
forecasts to 12 hours, this will provide the potential for 6 hours of 1 hourly lagged ensemble
forecasts and a measure of the predictability of the nowcasts.
6. Application of radar-based precipitation nowcasts to hydrological
forecasting and warning
6.1 Overview
Documented uses of radar data in hydro-meteorology are many and varied. They include
numerous studies of the space-time structure of radar inferred precipitation fields (e.g.
Harris et al., 2001), the compilation of precipitation climatologies (Panziera et al., 2011), the
estimation of Probable Maximum Precipitation (Cluckie, Pessoa & Yu, 1991; Collier &
Hardaker, 1996), reservoir design and safety (Cluckie & Pessoa, 1988), design storm
modelling (Seed, 2003), urban drainage and waste water management (Cluckie & Tyson,
1989; Schellart et al., 2009), river flow management (Lewin, 1986) and hydroelectric power
generation (Baker, 1986).
In addition to the above, operational radar-based precipitation nowcasts can be of great
value in fluvial (river) flood prediction because they extend the lead time of flood warnings
