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ADVANCED SURFACE RADAR-BASED RAINFALL ESTIMATE APPLYING NWP MODEL DATA

Workpackage number :

7

 

Start date or starting event:

+0

 

Partner code: Person-months

P1: 0

P2: 0

P3: 0

P4: 0

P5: 29

P6: 0

 

P7: 0

P8: 0

P9: 0

     

Objectives

The surface estimate of rainfall pattern based on radar reflectivity algorithms suffers, among others, from variations in both hydrometeors water phase and their vertical distributions. While other dependencies like variations in the Z-R relationship will be explored in the WP 9, this workpackage will concentrate on the reduction of "errors" due to misplaced condition posed to retrieving algorithms. A combined procedure that take into account radar data, NWP fields and weather observations will be developed to reduce: i) the impact of attenuation correction considering the correct water phase; ii) the long range rainfall errors due to overhanging precipitation (OP) not reaching the ground; iii) the impact of variations in the vertical reflectivity profile, which has been shown to be the most significant source of gauge-radar differences, especially in long range winter measurements.

 

 

Methodology/work description

A methodology to blend 3D radar reflectivity volumetric data, NWP fields and weather observations will be developed to reduce the uncertainty in the retrieved surface rainfall pattern, achieving the objectives of the workpackage. This will be done using data covering long seasonal periods: hourly polar volume reflectivities from 7 Doppler radars, hourly 3D fields from a NWP model and a very large climatological data set of hydrometeor types and simultaneous atmospheric quantities, in the following way:

  • Diagnosis of water phase at each radar volume bin based on the parameterised 3D model data. Derivation and implementation of the convolution formula to calculate phase dependent attenuation bias along the rays in the radar volumes. Calculation of seasonal statistics of the magnitude of the attenuation in low level PseudoCAPPI products and comparison of it to traditional statistics.
  • Columnar data from the nearest NWP model grid point will be used to search the best estimate statistical correlation between the measured OP above a radar and the OP and evaporation parameterised from the NWP model variables. Elimination of OP areas will be calculated over the whole radar network applying the 3D reflectivity field from radars and OP from the NWP model. Validation of the OP corrections will be performed by comparing radar estimated surface precipitation at long ranges to surface observations of prevailing weather(SYNOP, AWS).
  • Columnar data from the nearest NWP model grid point will be used to search the best estimate statistical correlation between the measured VRP above a radar and the VRP parameterised from the NWP model variables. VRP correction will be calculated over the whole radar network applying the integrated profile field from radars and from the NWP model. Validation of the VRP corrections will be performed by gauge-radar comparisons of the accumulated precipitation.

 

  1. Diagnosis of hydrometeor liquid water fraction in 3D radar volumes, based on NWP model fields; Delivery date: 13.
  2. 3D diagnosis of overhanging precipitation based on NWP model fields; Delivery date: 24.
  3. Improvement of radar derived surface precipitation using integrated OP correction from a radar network and from a NWP model; Delivery date: 24.
  4. Improvement of radar derived surface precipitation using integrated VRP correction from a radar network and from a NWP model; Delivery date: 36.

 

Contribution to Project Milestones:

M1

M2 Implementation of the program to calculate phase dependent and non-dependent attenuation along the radar beams.

M3 Derive statistics of phase dependent attenuation in the low level products. Comparison of the measured OPs and NWP model derived OPs

M4 Verification on the improvement in radar derived surface precipitation using OP correction. Implementation of the program, which enables direct comparison of observed VRPs and simultaneous 1D columns of the NWP model variables at the same point

M5 Implementation of the program which produces the VRP correction over the whole radar network.

M6 Verification on the improvement in radar derived surface precipitation using VPR correction

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