1. Stratospheric Temperature Variations and Trends: Recent Radiosonde Results Dian Seidel, Melissa Free NOAA Air Resources Laboratory Silver Spring, MD SPARC Temperature Trends Workshop University of Reading, 3-4 March 2005

2. Topics New Radiosonde Datasets Comparison of Stratospheric Trends Evaluation of Sources of Differences Linear Trends and Other Models Upper-Air Measurement Requirements for Climate (time permitting)

3. Topics New Radiosonde Datasets Comparison of Stratospheric Trends Evaluation of Sources of Differences Linear Trends and Other Models Upper-Air Measurement Requirements for Climate

4. NOAA Datasets CARDS became IGRA (Imke Durre, Russ Vose, NCDC) –Integrated Global Radiosonde Archive of quality controlled (not homogeneity-adjusted) soundings –Metadata update is ongoing Angell (2003) reduced network from 63 to 54 stations Lanzante-Klein-Seidel (2003a,b) adjusted for inhomogeneities –Adjustments based on station history metadata, statistical change-point identification, and evaluation of real abrupt changes –87 stations, 1948-1997

5. NOAA Datasets (cont.) LKS updated for RATPAC –Radiosonde Atmospheric Temperature Products for Assessing Climate –Joint ARL/GFDL/NCDC effort –16 levels, surface -10 hPa –Climate monitoring data product –Two basic datasets: Large-scale anomaly time series based on LKS adjustments through 1979 and first-difference method and metadata Station data with no adjustments post-1979 –General distribution after peer-review

6. Met Office Datasets HadRT (Parker et al. 1997) –Based on monthly-mean CLIMAT reports –444 stations used to create gridded product –Referenced to MSU in stratosphere HadAT (Peter Thorne et al.) –>600 stations using to create several gridded products –Homogenized using LKS results and neighborhood checks, with focus on troposphere –Includes analysis of uncertainty –9 levels, 850-30 hPa GCOS Upper-Air Network Monitoring Center (Mark McCarthy)

7. Rest of the World All-Russian Research Institute of Hydrometeorological Information (Alex Sterin) –Ongoing analysis of global and regional data Other efforts ???

8. Topics New Radiosonde Datasets Comparison of Stratospheric Trends Evaluation of Sources of Differences Linear Trends and Other Models Upper-Air Measurement Requirements for Climate

9. Signals of large-scale, short-lived stratospheric variations in different datasets are in good agreement

10. Trend sensitivity to LKS adjustments (solid)

11. HadRT and LKS agreement deteriorates with adjustments

12. Trends from Sondes, MSU & Reanalyses Large confidence intervals, but these do not address all sources of trend uncertainty More disparity among datasets than for shorter- term signals Reanalyses are outliers and are not reliable for trends Stratospheric cooling is stronger than tropospheric warming, but not more consistently estimated Sondes show more cooling than MSU Conventional wisdom is that sonde trends are too strong, but this is not firmly established.

13. RATPAC 1979-2003 Trends

14. RATPAC 1960-2003 Trends

15. Zonal Stratospheric Trends

18. Topics New Radiosonde Datasets Comparison of Stratospheric Trends Evaluation of Sources of Differences Linear Trends and Other Models Upper-Air Measurement Requirements for Climate

19. Comparing Effects of 3 Factors to Evaluate HadRT / LKS Trend Differences Data Adjustments – compare trends from adjusted and unadjusted data (see above) Spatial and temporal sampling – compare trends from subsampled datasets and complete datasets, using MSU and reanalysis as complete datasets Source radiosonde data – compare trends from 71 common stations

20. Spatial sampling differences 71 stations in common

21. HadRT and LKS trends agree better at 71 common stations than for full networks

22. (time sampling at month-to-month level only) (ADJ) Subsampling MSU makes little difference to MSU/sonde discrepancy

23. 3 factors have comparable effects on global trend differences, with adjustments dominating in the stratosphere

24. Roles of Factors Vary Regionally

25. Topics New Radiosonde Datasets Comparison of Stratospheric Trends Evaluation of Sources of Differences Linear Trends and Other Models Upper-Air Measurement Requirements for Climate

26. Alternative models may provide better fits (Seidel and Lanzante, 2004) Models evaluated using Bayesian Information Criterion Net stratospheric temperature change depends on model selected –Linear -1.13 K –Sloped steps -0.88 K –Censored, flat steps - 0.83 –Censored, linear -0.99 Different models suggest different physical interpretations

27. Topics New Radiosonde Datasets Comparison of Stratospheric Trends Evaluation of Sources of Differences Linear Trends and Other Models Upper-Air Measurement Requirements for Climate

28. Issues Affecting Climate Statistics and Trends Measurement Precision Sampling Frequency –Number of observations/day –Number of observations/month Long-term measurement stability Network size Locations of network stations

29. Tests with NCEP Reanalysis Data Start with 6-hourly data, at 6 pressure levels, at 15 locations, for 1948-2003 Subsample, or introduce artificial changes Compare with unaltered data –Monthly means and variances –Multi-decadal trends

30. Precision Effects on Monthly Means Means are within 0.05K for precision <0.5 K

31. Reduced Diurnal Sampling: Effect varies with size and shape of diurnal cycle Going from 4 to 2 obs/day makes significant change in monthly means in only 2.3% of cases (mainly near surface and in stratosphere) For only 1/day, means change in 13-17% of cases Conclusion: 2 obs/day may be enough

32. Number of Observations Per Month Observations every other day give monthly means accurate to within 2 K or better trends that are not statistically different in 90% of cases

33. Effects of Data Stability on Trends - 1 event Reliable trend estimates require measurement stability within 0.5 K over 20-50 years.

34. Effects of multiple changes = More errors But the first event causes most of the error

35. Spatial sampling errors in trends from hypothetical networks from reanalysis– decrease with increasing size Error = trend in subsampled minus trend in complete network 50 200 500 850

36. Spatial sampling errors in trends from actual radiosonde networks using reanalysis- no decrease with increasing size 50 200 500 850

37. Take-Away Points New Radiosonde Datasets – several, unpublished Comparison of Stratospheric Trends – increasing cooling with height, with large uncertainties Evaluation of Sources of Differences – everything matters, but especially homogeneity adjustments in the stratosphere Linear Trends and Other Models – reasonable to consider nonmonotonic changes Upper-Air Measurement Requirements for Climate – input from this group would be very welcome!

38. Take-Away Points New Radiosonde Datasets – several, unpublished Comparison of Stratospheric Trends – increasing cooling with height, with large uncertainties Evaluation of Sources of Differences – everything matters, but especially homogeneity adjustments in the stratosphere Linear Trends and Other Models – reasonable to consider nonmonotonic changes Upper-Air Measurement Requirements for Climate – input from this group would be very welcome!

39. Take-Away Points New Radiosonde Datasets – several, unpublished Comparison of Stratospheric Trends – increasing cooling with height, with large uncertainties Evaluation of Sources of Differences – everything matters, but especially homogeneity adjustments in the stratosphere Linear Trends and Other Models – reasonable to consider nonmonotonic changes Upper-Air Measurement Requirements for Climate – input from this group would be very welcome!

40. Take-Away Points New Radiosonde Datasets – several, unpublished Comparison of Stratospheric Trends – increasing cooling with height, with large uncertainties Evaluation of Sources of Differences – everything matters, but especially homogeneity adjustments in the stratosphere Linear Trends and Other Models – reasonable to consider nonmonotonic changes Upper-Air Measurement Requirements for Climate – input from this group would be very welcome!

41. Take-Away Points New Radiosonde Datasets – several, unpublished Comparison of Stratospheric Trends – increasing cooling with height, with large uncertainties Evaluation of Sources of Differences – everything matters, but especially homogeneity adjustments in the stratosphere Linear Trends and Other Models – reasonable to consider nonmonotonic changes Upper-Air Measurement Requirements for Climate – input from this group would be very welcome!