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Results of the Measurement Strategy of the GCOS Reference Upper Air Network (GRUAN) Holger Vömel,

Results of the Measurement Strategy of the GCOS Reference Upper Air Network (GRUAN) Holger Vömel, GRUAN Lead Center DWD Meteorological Observatory Lindenberg CIMO TECO 2012. Water vapor trends in the troposphere?. Motivation 1: Long term „trend“ humidity.

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Results of the Measurement Strategy of the GCOS Reference Upper Air Network (GRUAN) Holger Vömel,

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  1. Results of the Measurement Strategy of the GCOS Reference Upper Air Network (GRUAN) • Holger Vömel, • GRUAN Lead Center • DWD Meteorological Observatory Lindenberg • CIMO TECO 2012

  2. Water vapor trends in the troposphere? • Motivation 1:Long term „trend“ humidity

  3. Water vapor trends in the troposphere? Specific humidity at 300 hPa Dessler and Davis, JGR 2010

  4. Water vapor trends in the upper troposphere? e.g.: Lindenberg 8km (0:00 UT)

  5. Water vapor trends in the upper troposphere? e.g.: Lindenberg 8km (0:00 UT) Freiberg RKS-2 RKS-5 MARZ RS80 RS92

  6. Water vapor trends in the upper troposphere? e.g.: Lindenberg 8km (0:00 UT) • No trend estimate possible: Trend signals dominated by instrumental change • Observations have been done for numerical weather prediction, not for long term climate • Measurements are not traceable (Instrumental uncertainties not well characterized and systematic errors disregarded ) • Instrumental change instantaneous not managed • Meta data are incomplete • Note: Even the Vaisala RS92 data record is inconsistent

  7. GCOS Reference Upper Air Network • GRUAN in response to the need of WMO and the Global Climate Observing System for highest accuracy data possible • Ground based network for reference upper air observations for climate under GCOS and integrated into WIGOS • Currently 16 sites, with aim to expand to 30 to 40 sites worldwide • Check out www.gruan.org

  8. GRUAN goals • Maintain observations over decades • Validation of satellite systems • Characterize observational uncertainties • Traceability to SI units or accepted standards • Comprehensive metadata collection and documentation • Validate observations through deliberate measurement redundancy • Long-term stability through managed change Priority 1: Water vapor, temperature, (pressure and wind) Priority 2: Ozone, …

  9. The GCOS Reference Upper-Air Network: • What constitutes a “reference” observation?

  10. Referenceobservation • A GRUAN reference observation: • Is traceable to an SI unit or an accepted standard • Provides a comprehensive uncertainty analysis • Maintains all raw data • Is documented in accessible literature • Is validated (e.g. by intercomparison or redundant observations) • Includes complete meta data description

  11. Establishing reference quality Uncertainty of input data Traceable sensor calibration Transparent processing algorithm Best estimate + Uncertainty GRUAN Measurement Black box software Proprietary methods Disregarded systematic effects

  12. Establishing Uncertainty • Error is replaced by uncertainty • Important to distinguish contributions from systematic error and random error • A measurement is described by a range of values • A measurement is expressed as m ± u • m is corrected for systematic errors • u is random uncertainty Literature: • Guide to the expression of uncertainty in measurement (GUM, 1980) • Guide to Meteorological Instruments and Methods of Observation, WMO 2006, (CIMO Guide) • Reference Quality Upper-Air Measurements: Guidance for developing GRUAN data products, Immler et al. (2010), Atmos. Meas. Techn.

  13. Uncertainty, Redundancy and Consistency • GRUAN stations provide redundant measurements • Redundant measurements should be consistent: • No meaningful consistency analysis possible without uncertainties • if m2 has no uncertainties use only u1 (“agreement within errorbars”)

  14. Uncertainty and Raw Data • Analyze sources of uncertainty: systematic: calibration, radiation errors, … random: noise, production variability, … Document this! • Synthesize best uncertainty estimate: Uncertainties for every data point, i.e. vertically resolved • Raw data: Store all raw and all meta data to allow future reprocessing

  15. Determining the Uncertainty: Daytime temperature Vaisala RS92

  16. Uncertainty example: Daytime temperature Vaisala RS92

  17. Uncertainty example: Daytime temperature Vaisala RS92

  18. Uncertainty example: Daytime temperature Vaisala RS92 Assumptions: • On average 50% of maximum insolation • Downward direct, downward and upward diffuse radiation • Radiative streamer model for radiation field, with climatological clouds

  19. Uncertainty example: Daytime temperature Vaisala RS92 Sources of measurement uncertainty (in order of importance): • Sensor orientation • Ventilation • Unknown radiation field • Lab measurements of the radiative heating • Ground check • Calibration

  20. GRUAN Data Product: RH uncertainty • RH Uncertainty:

  21. GRUAN Data Product: RH uncertainty Good example: 28 Mar 2012:

  22. GRUAN Data Product: RH uncertainty Good example: 28 Mar 2012:

  23. GRUAN Data Product: RH uncertainty Good example: 28 Mar 2012:

  24. Redundant Observations: CFH and GRUAN RS92

  25. GRUAN Data Product: RH uncertainty Cooperation withmanufacturers needed to address these issues Bad example: 15 Mar 2012:

  26. Traceability • Manufacturer Independent Ground Checks

  27. Additional ground checks

  28. Additional ground checks Production Year:

  29. Additional ground checks GC25 (0%) SHC (100%) U1 0.33 106.00 U2 0.36 100.98 Lindenberg Ground Check 30 May 2012, 0:00

  30. U1 switched on U2 switched on

  31. Change Management

  32. Change Management • Change management is mandatory to maintain traceability, homogeneity in a time series and consistency within a network • A new system, software, or procedure must be evaluated prior to implementation • Systematic and random errors must be quantified for the new system in the same manner as for the old system • Redundant observations verify that the new system are of equal quality as the old system. • If transfer functions are required, old data will be reprocessed based on the stored raw data

  33. Summary • GRUAN is an approach to long term observations of upper air essential climate variables • Focus on priority 1 variables to start: Water vapor and temperature(starting to bring in other variables) • Reference observation means: • quantified uncertainties • traceable • well documented • Understand the uncertainties: • analyze sources • synthesize best estimate • verify in redundant observations • Management of change utilizes measurement uncertainty

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