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THE OPTIMISING OF REGIONAL RADIOSONDE NETWORKS

THE OPTIMISING OF REGIONAL RADIOSONDE NETWORKS. Oleg Pokrovsky Main Geophysical Observatory, Karbyshev str.7, St. Petersburg, 194021, Russian Federation. Outlines:. (a)    Identify statistically homogeneous areas;

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THE OPTIMISING OF REGIONAL RADIOSONDE NETWORKS

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  1. THE OPTIMISING OF REGIONAL RADIOSONDE NETWORKS Oleg Pokrovsky Main Geophysical Observatory, Karbyshev str.7, St. Petersburg, 194021, Russian Federation

  2. Outlines: • (a)    Identify statistically homogeneous areas; • (b)   Calculate the statistical weights of the information of each RAOB station ; • (c)    Derive an optimized network configuration for the upper-air stations, including GUAN stations; • (d)   Calculate error fields for main meteorological parameters (Z500, T500, U700, V700, relative air humidity Q850 used in NWP models) related to the optimized network configuration.

  3. Approach

  4. Kalman Filter (1) where where:

  5. Kalman Filter (2)

  6. Information Weights of Sites Statistical Invariant: Information weight of i-th site

  7. Optimization Criteria function - Optimization: Criteria examples: 1) A: 2) D:

  8. Part 1 Siberian RAOB network of Roshydromet

  9. A set of RAOB stations presented in WMO list

  10. Soviet Time

  11. October, 1999

  12. Catastrophic Flood in Siberia River Lena, May, 2001

  13. Persisted Atmospheric Circulation Regime during February-May, 2001 Source: SATOB data

  14. Z700 field anomaly,March-April, 2001

  15. РАЙОНИРОВАНИЕ АТР (СРОЧНЫЕ ДАННЫЕ)

  16. Sufficient RAOB network

  17. Optimal interpolation H500 RMS error field

  18. Optimal interpolation H500 RMS error field Responded to Jan-March, 2007, RAOB

  19. Contribution of measurement data in covariance matrix reduction RAOB –40 (non-regular, Jan-Mar, 2007) RAOB-34 (Jan-Mar, 0Z&12Z, 2007) RAOB-42 (Optimal design) Mean STD (60-80 N) 58.7 57.6 27.8 Mean STD (40-60 N) 42.3 46.9 42.5 Mean STD 51.0 52.6 34.7 Table. Comparison of the optimal and operational RAOB network configurations in Siberia with account for Z500 objective analysis error (m).

  20. Conclusions (Part 1): • Number of Siberian RAOB sites was increased during last years • Most of recovered stations are located in southern part of Siberia close to China border provided by many vertical profiles from Chinese RAOB • Few stations were added in medium latitude belt and in high latitudes • Present configuration of Siberian RAOB network does not provide necessary accuracy in analysis of height, temperature and, particularly, wind fields in in high latitudes

  21. Part 2A CASE STUDY: RA I - AFRICA

  22. RAOB network in RA-I: red-operational(2004); black-nominal in WMO list

  23. Statistical Regionning due to zonal wind U700

  24. Information content weights attributed to existed operational sites

  25. Relative error (with account for seasonal variability) fields for Z500 objective analysis

  26. Relative error (with account for seasonal variability) fields for U700 objective analysis

  27. Scenario for RA-I RAOB extension with account for maximization of information content: red-new 13 stations; black-operational network (46 stations)

  28. Relative error (with account for seasonal variability) fields for Z500 objective analysis: extended network

  29. Relative error (with account for seasonal variability) fields for U700 objective analysis:extended network

  30. Minimal GUAN network due to U700

  31. Relative error (with account for multi-year variability) monthly fields attributed to GUAN for U700

  32. Conclusions (Part 2) • Missing data areas with respect to operational RAOB station list for RA-I are very significant. Only 46 from nominal 262 sites carried out measurements in January-April, 2004. • Error fields corresponding to major meteorological variables reveal many gap regions, where the relative errors of meteorological field representation reach 0.7-0.8 levels. • Search algorithm allows us to develop a scenario for existed operational RAOB network extension from 46 to 59 stations by recover measurements at 13 stations, which provide a substantial improvement of error fields for all meteorological variables in missing data areas • Existing GUAN network has some gaps in Central Africa, which are a reason of anomaly in objective analysis error fields. An alternative set of ten GUAN sites provides more uniform information coverage of Africa with respect to monthly fields.

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