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WP 3: DATA ASSIMILATION SMHI/FMI Status report

WP 3: DATA ASSIMILATION SMHI/FMI Status report 3rd CARPE DIEM meeting, University of Essex, Colchester, 9-10 January 2003. Structure SMHI/FMI plans for work and deliverables HIRLAM 3D-Var radar wind assimilation Status Future plans. WP 3: Data assimilation (30 pm):

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WP 3: DATA ASSIMILATION SMHI/FMI Status report

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  1. WP 3: DATA ASSIMILATION SMHI/FMI Status report 3rd CARPE DIEM meeting, University of Essex, Colchester, 9-10 January 2003 • Structure • SMHI/FMI plans for work and deliverables • HIRLAM 3D-Var radar wind assimilation • Status • Future plans

  2. WP 3: Data assimilation (30 pm): • Implementation of observation operator for radial winds in the HIRLAM 3D- and 4D-Var. Quality control and ambiguity removal. Estimation of observation error statistics, case studies and OSE. • Software modules for 4D-Var (month 24). • Impact studies of radar radial winds and assessment for suitability of use in operational NWP (month 30).

  3. The HIRLAM 3D-Var . . . . .

  4. The HIRLAM 3D-Var Cost function: where Background state (+6 h forecast from previous assimilation cycle) Estimated from extended experiments at ECMWF and SMHI. R is diagonal. Derived from a sample of differences between +24 h and +48 h HIRLAM forecasts valid at the same time. Observation operators developed for SYNOP, SHIP, DRIBU, TEMP, PILOT and AIREP, satellite cloud drift winds, satellite radiances, scatterometers, GPS atmospheric delays, radar winds.

  5. The radar radial wind observation operator Interpolation of the model wind field to the horizontal position of the observation. Calculation of model level heights. Vertikal interpolation to height of observation (4/3 earth radius approx.), followed by projection of interpolated model wind field on radar beam line. Gaussian weight function applied on model profile (4/3 earth radius approx. for height of central axis), followed by projection of interpolated model wind field on radar beam line. Gaussian weight function applied on model profile (height of central axis explicitly calculated from model state), followed by projection of interpolated model wind field on radar beam line. (1) (2) (3) Projection: Horizontal: Slanted:

  6. Extension to HIRLAM 4D-Var

  7. All observation operator versions (1)-(3) evaluated through Single observation impact experiments Horizontal impact of a radar radial wind observation increment of 10 m/s in the east west direction. The radial wind is at the height of 3746 m and is from the radar of Norrköping. Wind analysis increments at model level 20. Isoline spacing is 1 m/s. Temperature analysis increments at model level 20. Isoline spacing is 0.1 K.

  8. Further evaluation of observation operator (1) Ten-day assimilation experiment: 1-10 December, 1999 Integration area and radar sites Verification of time-series of +24 h wind forecasts (against observations) Observation fit statistics

  9. Further evaluation of second observation operator (2) 14-day study: 1-14 June, 1999 Broadening of radar pulse taken into account in observation operator through Gaussian weight function: - range dependent response function Scatter diagram of radial wind superobservations as a function of model counterpart. Observation fit statistics

  10. Further evaluation of observation operator (3) Case study Snell’s law: With αi (incidence angle) known and n (refractive index) calculated from model state: Comparison of pulse propagation path for a particular case: Old 4/3 earth radius pathapprox. vs new path based on Snell’s law

  11. Publications

  12. Future plans • Evaluation of third observation operator (3) • Extended OSE using de-aliased radial winds superobservations from Finnish and Swedish radars and the latest version of the HIRLAM 3D-Var. (some results will be presented at mid-term workshop) • Investigation of observation errors • Comparison experiments and Poor Mans Ensemble experiments • Case studies using HIRLAM 4D-Var

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