FOR 2589: RealPEP

Overall Objectives of RealPEP

High-quality near-real time Quantitative Precipitation Estimation (QPE) and its prediction for the next hours (Quantitative Precipitation Nowcasting, QPN) is of high importance for many applications in meteorology, hydrology, agriculture, construction, water and sewer system management. Especially for the timely prediction of floods in small/meso-scale catchments and of intense precipitation over cities, the value of high-resolution and high-quality QPE/QPN cannot be overrated. Area-covering and high-resolution polarimetric weather radar observations provide the undisputed core information for QPE/QPN providing precipitation intensity, hydrometeor types, and wind. Despite extensive investments in such weather radars, QPE is still based primarily on rain gauge measurements, and no operational flood forecasting system actually dares to employ radar observations for QPE.

RealPEP will advance QPE/QPN to verifiably outperform rain gauge observations when employed for flood predictions in small to medium-sized catchments. To this goal radar polarimetry will be combined with attenuation estimates from commercial microwave link networks for QPE improvement. In addition, information on convection initiation and evolution from satellites and lightning counts from surface networks will be exploited for QPN improvement.
With increasing forecast horizons the predictive power of observation-based nowcasting quickly deteriorates and is outperformed by Numerical Weather Prediction (NWP) based on data assimilation, which fails, however, for the first hours due to the lead time required for model integration and spin-up.

RealPEP will merge observation-based QPN with NWP towards seamless prediction in order to provide optimal forecasts of surface precipitation from the time of observation to days ahead. Despite recent advances, hydrologic components for operational flood prediction are still conceptual, need calibration, and are often unable to objectively digest observational information on the state of the catchments. RealPEP will apply physics-based hydrological models, combined with advanced QPE/QPN/NWP and the assimilation of catchment state observations, to propose an alternative for traditional flood forecasting in small to meso-scale catchments.

P1:Quantitative Precipitation Estimantion(QPE)

Core objectives:
Improvement of PE for liquid, solid, and mixed-phase precipitation, by
  • Full expolitation of radar polarimetry
  • Improved processing of CML data
  • Merging of CML and radar data and exploiting CML for constraining polarimetric QPE algorithms

More information about QPE

Current Status

P2:Quantitative Precipitation Nowcasting(QPN)

Core objectives:
Significantly enhance lead time and skill of advection-based nowcasting via two pathways:
  • Extrapolate trends of the cells velocity, shape, intensity and size in time
  • Exploit the information of especially polarimetry-based process descriptors on future developments

More information about QPN

Current Status

P3:Quantitative Precipitation Forecasting(QPF)

Core objectives:
Enhanced QPF by assimilating precipitation relevant radar and satellite information:
  • Polarimetric moments and radar-derived mixing ratios
  • Gridded information from 3D composite
  • Nowcastet fields

More information about QPF

Current Status

P4:Flash Flood Prediction(FFP)

Core objectives:
Advance river discharge forecast, particularly flash-flood lead times:
  • Evaluate QPE/QPN/QPF data improved by P1,P2 and P3
  • Apply a physically based hydrological model
  • Improve real-time data assimilitation of discharge and soil moisture

More information about FFP

Current Status

C1:Infrastructure project

Core objectives:
  • Build and maintain a data collection and exploitation platform that mirrors the current status of best practice to organize, exhange, and implement data and algorithms between projects
  • Fundamental research in convection initiation

More information about Infrastructure

Current Status

QPE QPN QPF Hydro Infrastructure