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)

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

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

9. Part 1 Siberian RAOB network of Roshydromet

10. A set of RAOB stations presented in WMO list

11. Soviet Time

13. October, 1999

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

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

16. Z 700 field anomaly,March-April, 2001

18. РАЙОНИРОВАНИЕ АТР (СРОЧНЫЕ ДАННЫЕ)

19. Sufficient RAOB network

20. Optimal interpolation H500 RMS error field

22. Responded to Jan-March, 2007, RAOB

23. Table. Comparison of the optimal and operational RAOB network configurations in Siberia with account for Z500 objective analysis error (m). 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) 58.757.627.8 Mean STD (40-60 N) 42.346.942.5 Mean STD51.052.634.7

26. 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

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

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

29. Statistical Regionning due to zonal wind U700

30. Information content weights attributed to existed operational sites

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

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

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

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

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

36. Minimal GUAN network due to U700

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

38. 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.