1. Meteorological Observatory Lindenberg – Richard Assmann Observatory The GCOS Reference Upper Air Network: Assuring the 21 st Century Climate record? Peter Thorne, CICS-NC With thanks to GRUAN Lead Centre (DWD) and Working Group on Atmospheric Reference Observations

2. What is GRUAN? GCOS Reference Upper Air Network Network for ground-based reference observations for climate in the free atmosphere under the auspices of GCOS Initially 15 stations, envisaged to be a network of 30-40 sites across the globe See www.gruan.org for more detail Meteorological Observatory Lindenberg – Richard Assmann Observatory

3. GRUAN tasks Provide long-term high-quality upper-air climate records Constrain and calibrate data from more spatially- comprehensive global observing systems (including satellites and current radiosonde networks) Fully characterize the properties of the atmospheric column Meteorological Observatory Lindenberg – Richard Assmann Observatory

4. GRUAN goals Maintain observations over several decades for accurately estimating climate variability and change Focus on characterizing observational biases, including complete estimates of measurement uncertainty Ensure traceability of measurements by comprehensive metadata collection and documentation Ensure long-term stability by managing instrumental changes Tie measurements to SI units or internationally accepted standards Measure a large suite of co-related climate variables with deliberate measurement redundancy Meteorological Observatory Lindenberg – Richard Assmann Observatory Priority 1: Water vapor, temperature, (pressure and wind) Priority 2: Ozone, clouds, …

5. GRUAN structure GCOS/WCRP AOPC Working Group on Atmospheric Reference Observations (WG-ARO) GRUAN Lead Centre at the Lindenberg Meteorological Observatory (DWD) GRUAN sites world wide (currently 15 to be expanded to 30-40) GRUAN task teams for Radiosondes GNSS-Precipitable Water Measurement schedules and associated site requirements Ancillary measurements Site representation GRUAN Analysis Team for Network Design and Operations Research (GATNDOR) See www.gruan.org for more detail Meteorological Observatory Lindenberg – Richard Assmann Observatory

6. Why is GRUAN required? Historical observations of the atmospheric column have been made primarily for operational monitoring purposes Change has been ubiquitous, poorly managed, and rarely adequately quantified Has led to substantial ambiguity in the rate and details of climatic changes Significant impediment to understanding climate change and its causes. Meteorological Observatory Lindenberg – Richard Assmann Observatory

7. Ubiquitous change Meteorological Observatory Lindenberg – Richard Assmann Observatory

8. Tropospheric temperature trend uncertainties Meteorological Observatory Lindenberg – Richard Assmann Observatory

9. Implications Surface-troposphere trends issue has been hot since 1990 paper in Science by Spencer and Christy using terms such as precise to describe MSU. Since then 200+ papers and two dedicated reviews on the subject (NRC, CCSP) Several congressional hearings BUT … No resolution to the issue – simply a better understanding of the true degree of uncertainty Lesson 1: Never trust a single observational analysis. Structural uncertainty is key. Lesson 2: It doesnt have to be this way going forwards. We need traceable measures in future to assure the record. Lesson 2 is where GRUAN comes in … Meteorological Observatory Lindenberg – Richard Assmann Observatory

10. Focus on reference observations A GRUAN reference observation: Is traceable to an SI unit or an accepted standard Provides a comprehensive uncertainty analysis Is documented in accessible literature Is validated (e.g. by intercomparison or redundant observations) Includes complete meta data description Meteorological Observatory Lindenberg – Richard Assmann Observatory

11. Establishing reference quality Meteorological Observatory Lindenberg – Richard Assmann Observatory

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 generally expressed by 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. Meteorological Observatory Lindenberg – Richard Assmann Observatory

13. Uncertainty, Redundancy and Consistency GRUAN stations should provide redundant measurements Redundant measurements should be consistent: No meaningful consistency analysis possible without uncertainties if m 2 has no uncertainties use u 2 = 0 (agreement within errorbars) Meteorological Observatory Lindenberg – Richard Assmann Observatory

14. Uncertainty, Redundancy and Consistency Understand the uncertainties: Analyze sources: Identify, which sources of measurement uncertainty are systematic (calibration, radiation errors, …), and which are random (noise, production variability …). Document this. Synthesize best uncertainty estimate: Uncertainties for every data point, i.e. vertically resolved Use redundant observations: to manage change to maintain homogeneity of observations across network to continuously identify deficiencies Meteorological Observatory Lindenberg – Richard Assmann Observatory

15. Consistency in a finite atmospheric region Co-location / co-incidence: Determine the variability ( ) of a variable (m) in time and space from measurement or model Two observations on different platforms are consistent if This test is only meaningful, i.e. observations are co-located or co-incident if: Meteorological Observatory Lindenberg – Richard Assmann Observatory

16. Uncertainty example: Daytime temperature Vaisala RS92 Meteorological Observatory Lindenberg – Richard Assmann Observatory Sources of measurement uncertainty (in order of importance): Sensor orientation Radiative heating of sensor Unknown radiation field Ventilation Ground check Calibration Time lag

17. Uncertainty example: Comparison Vaisala RS92 with Multithermistor Minor systematic difference at night Significant systematic difference during the day But observations are consistent with the understanding of the uncertainties in the Vaisala temperature measurements Lack of uncertainties in Multithermistor measurements precludes further conclusions Meteorological Observatory Lindenberg – Richard Assmann Observatory

18. Principles of GRUAN data management Archiving of raw data is mandatory All relevant meta-data is collected and stored in a meta-data base (at the lead centre) For each measuring system just one data processing center Version control of data products. Algorithms need to be traceable and well documented. Data levels for archiving: level 0: raw data level 1: raw data in unified data format (pref. NetCDF) level 2: processed data product dissemination (NCDC) Data streams reprocessed as necessary as new knowledge accrues Meteorological Observatory Lindenberg – Richard Assmann Observatory

19. Distributed data processing Meteorological Observatory Lindenberg – Richard Assmann Observatory

20. Future steps Bring in additional data streams Frostpoint hygrometer sondes (WV in UTLS) GNSS-PW Lidar, FTIR, MWR etc. Additional sites Workshop to be held summer 2012 (let me know if interested) Need to ascertain optimal mix of sites to meet the varied demands Building user base GRUAN will only be successful if the data are used on a regular basis. Meteorological Observatory Lindenberg – Richard Assmann Observatory

21. Next challenge: How to use these measures to calibrate more globally complete networks Statistical and physical problem Geographical and temporal coincidence will be important. For satellite calibration use RTMs to convert the geophysical observations to radiance equivalents? Does sustained cal/val require launch coincident measurements? What is the cost/benefit? Who pays? Use of sites as opportunities to perform regular instrumentation suite intercomparisons? Could help in calibrating ground based remote sensing and in-situ sounding capabilities. Meteorological Observatory Lindenberg – Richard Assmann Observatory

22. Summary of GRUAN Meteorological Observatory Lindenberg – Richard Assmann Observatory GRUAN is a new approach to long term observations of upper air essential climate variables Focus on priority 1 variables to start: Water vapor and temperature Focus on reference observation: quantified uncertainties traceable well documented Understand the uncertainties: analyze sources synthesize best estimate verify in redundant observations GRUAN requires a new data processing and data storage approach