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Reanalysis -Achievements and Challenges -

Reanalysis -Achievements and Challenges -. Professor Lennart Bengtsson ESSC , University of Reading MPI for Meteorology , Hamburg. Reanalysis -Achievements and Challenges -. Introduction and Background Impact of humidity observations Observations and forecast skill Climate trends

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Reanalysis -Achievements and Challenges -

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  1. Reanalysis -Achievements and Challenges- Professor Lennart BengtssonESSC, University of ReadingMPI for Meteorology, Hamburg COLA 20-years 18 June 2004

  2. Reanalysis -Achievements and Challenges- • Introduction and Background • Impact of humidity observations • Observations and forecast skill • Climate trends • Challenges for the future

  3. Results of Reanalyses

  4. ERA40 • Covering the 45-year period 1957-2002 • Resolution T159/L60 • Using 3DVar • Includes all available observations • Main emphasis at ECMWF: predictability • Most serious problem: tropical ocean precipitation

  5. Vorticity generation and storm tracks Kevin Hodges, ESSC COLA 20-years 18 June 2004

  6. ERA40, 850Cyclonic Genesis (# density per month) NH, DJF SH, JJA MJJASON

  7. ERA40, 850Cyclonic Track Density (# density per month) SH, JJA NH, DJF MJJASON

  8. ERA40, 850Cyclonic Tracks NH, 1999/2000 DJF SH, 2000 JJA 2000, MJJASON

  9. Impact of humidity observations Bengtsson et al., 2004a Tellus COLA 20-years 18 June 2004

  10. Total Dec. Jan. Feb. Land P-E ERA40 12.8 4.3 4.9 3.6 Land P-E ERA40 (no moisture) 12.8 4.0 5.1 3.7 Ocean P-E ERA40 0.9 -0.6 1.6 -0.1 Ocean P-E ERA40 (no moisture) -13.4 -5.1 -4.1 -4.2 Global water balanceDJF 90/91 unit:1000qkm

  11. Daily assimilated water vapor, Feb. 1991Full line ERA40, dashed ERA40, nohum

  12. Stormtrack validation

  13. Observed and assimilated tropical storm tracks

  14. Global forecasts DJF 90/91 • 7- day forecasts, every 6hr. • Latest ECMWF model T159/L60 • Extra-tropics 20-90N and 20-90S • 500hPa Z, normalized SD for the period • Tropics 20N-20S • Wind vector field 850 and 250hPa

  15. Z500 NH SH

  16. Z500, MeanERA40 DJF 90/91

  17. Z500, 5 day Verification ERA40 noHum

  18. Tropics, Winds 850hPa 250hPa

  19. Tropics, Wind (850hPa) Mean ERA40, 5 day noHum, 5 day

  20. Reanalysis with reduced observing systems Bengtsson et al., 2004b Tellus COLA 20-years 18 June 2004

  21. Methodology • We have mimicked earlier observing systems by redoing the ERA40 assimilation for limited periods. • This has been done at the ECMWF computer system from ESSC at Reading University

  22. Experimental periods • DJF 1990/1991 • JJA 2000 • DJF 2000/2001

  23. We have done four main experiments • 1. ERA 40 - all humidity observations • 2. Exp 1 - all space observations • 3. Exp 2 - all upper air observations • 4. Exp 1 - all upper air observations

  24. Control -Terrestrial system Control -Surface system Control - Satellite system Control-No observation Normalized RMS for DJF 90/91

  25. Observed and assimilated QBOVertical wind profiles and zonal wind at 50 hPafull line:obs, dashed line: sat. system, dotted line: control

  26. NH, MSLP, Cyclones Tracks Intensities

  27. SH, MSLP, Cyclones Tracks Intensities

  28. Z500 NH SH

  29. Climate trend calculations Bengtsson et al., 2004 JGR COLA 20-years 18 June 2004

  30. Annual mean global values of relative humidity f (in %) vertically averaged for 850-300 hPa and vertically integrated absolute humidity q (in kg/m2).

  31. Integrated Water Vapor1979-1999 ECHAM5: T106/L31 using AMIP2 boundary conditions Preliminary results: Globally averaged results vary between 25.10 mm (1985) and 26.42 mm (1998) Mean value for the 1990s is 1% higher than in the 1980s Interannual variations are similar to ERA-40 Variations follow broadly temperature observations from MSU (tropospheric channel) under unchanged relative humidity (1°C is equivalent to some 6%).

  32. Potential problems in calculating climate trends • Assimilating model may have systematic biases • Observing systems have undergone major changes both in instrumentation and observational coverage • Instrumental changes and observational representation to be considered

  33. Can Climate Trends be Calculated from Re-Analysis Data? • We have investigated using ERA40: • Tropospheric temperature (MSU (TLT)) • Atmospheric water content (IWV) • Total kinetic energy

  34. Coupled data-assimilation • An MPI experiment from 1997 • ( Oberhuber et al., 1998, JGR)

  35. Concluding remarks Reanalysis data sets have provided important understanding of climate variability of the last 50 years • Changes in the global observing system especially in 1979 make it difficult to assess climate trends • The effect of such changes can be quantitatively estimated but requires dedicated re-reanalyses with selected observations • It is required to better identify the key observations in 4D data-assimilation • Reanalyses of the full ocean-atmosphere-land system should be done with coupled models and not by separate models. • Reanalysis experiments are needed to guide a better design of the the global observing systems for weather and climate prediction

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