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Global Climate Observing System (GCOS) including GRUAN Greg Bodeker Bodeker Scientific, Alexandra, New Zealand Presented at the 9 th Ozone Research Managers.

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Presentation on theme: "Global Climate Observing System (GCOS) including GRUAN Greg Bodeker Bodeker Scientific, Alexandra, New Zealand Presented at the 9 th Ozone Research Managers."— Presentation transcript:

1 Global Climate Observing System (GCOS) including GRUAN Greg Bodeker Bodeker Scientific, Alexandra, New Zealand Presented at the 9 th Ozone Research Managers Meeting, Geneva, May 2014

2 Overview What role does ozone play in GCOS?What role does ozone play in GCOS? What should the international ozone research community be doing to support the activities of GCOS and meet the needs of GCOS?What should the international ozone research community be doing to support the activities of GCOS and meet the needs of GCOS? GRUAN – The GCOS Reference Upper Air NetworkGRUAN – The GCOS Reference Upper Air Network What are the defining operational parameters of GRUAN?What are the defining operational parameters of GRUAN? Outcomes of the 2012 GRUAN Network Expansion Workshop regarding locations for ozone monitoring.Outcomes of the 2012 GRUAN Network Expansion Workshop regarding locations for ozone monitoring.

3 Ozone and GCOS OceanicAtmosphericTerrestrial GCOS Essential Climate Variables (ECVs) Surface: Air temperature, precipitation, air pressure, surface radiation budget, wind speed and direction, water vapour. Upper-air: Earth radiation budget (including solar irradiance), upper-air temperature (including MSU radiances), wind speed and direction, water vapour, cloud properties. Composition: Carbon dioxide, methane, ozone, other long- lived greenhouse gases, aerosol properties.

4 GCOS recommendations for producing a climate data record for an ECV There are the 20 GCOS Climate Monitoring Principles: Of particular importance for ozone are: Impact of new systems or changes to existing systems should be assessed prior to implementation e.g. change in absorption cross-sections. Importance of collecting and archiving meta data. Quality and homogeneity of data should be regularly assessed. Operation of historically-uninterrupted stations and observing systems should be maintained. Good geographical coverage especially in regions where changes are occurring or are expected to occur e.g. the tropics now for ozone. A suitable period of overlap for new and old satellite systems should be ensured for a period adequate to determine inter- satellite biases.

5 GCOS guidelines for the generation of data sets and products (GCOS-143) Full description of all steps taken in construction of CDR. Application of appropriate calibration/validation. Statement of expected accuracy, stability and resolution. Assessment of long-term stability and homogeneity of the product. Scientific review process related to product construction. Global coverage of CDR where possible. Version management of CDRs, particularly in connection with improved algorithms and periodic reprocessing. Access to CDR including all inputs and documentation. Timeliness of data release to the user community Facility for user feedback Application of a quantitative maturity index if possible Publication in international peer-reviewed journal.

6 GCOS Reference Upper Air Network Network for ground-based reference observations for climate in the free atmosphere in the frame of GCOS Currently ~15 stations, envisaged to be a network of sites across the globe What is GRUAN?

7 See for further information AOPC Task and analysis teams Measurement sites Guidance on research requirements Guidance on operational requirements Guidance on operational requirements ReportingGuidance WG-GRUAN Lead Center UNEPIOCICSUWMO WCRP GCOS SC CIMO/CBS/CAS/CCL GRUAN Governance

8 The goals of GRUAN The purpose of GRUAN is to: Provide long-term high quality climate records;Provide long-term high quality climate records; Constrain and calibrate data from more spatially-comprehensive global observing systems (including satellites and current radiosonde networks); andConstrain and calibrate data from more spatially-comprehensive global observing systems (including satellites and current radiosonde networks); and Fully characterize the properties of the atmospheric column.Fully characterize the properties of the atmospheric column. Four key user groups of GRUAN data products are identified: The climate detection and attribution community.The climate detection and attribution community. The satellite community.The satellite community. The atmospheric process studies community.The atmospheric process studies community. The numerical weather prediction (NWP) community.The numerical weather prediction (NWP) community.

9 More about goals of GRUAN Multi-decade measurement programmes. Characterize observational biases. Robust, traceable estimates of measurement uncertainty. Ensure traceability through comprehensive meta-data collection and documentation. Ensure long-term stability by managing measurement system changes. Tie measurements to SI units or internationally accepted standards. Measure a large suite of co-related climate variables with deliberate measurement redundancy Priority 1: Temperature, pressure, water vapour Priority 2: Ozone, methane …

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

11 Uncertainty, redundancy and consistency Understand the uncertainties: Describe/Analyze sources - identify, which sources of measurement uncertainty are systematic (calibration, radiation errors), and which are random (noise, production variability …). Document this. Quantify/Synthesize best uncertainty estimate: Uncertainties for every data point, i.e. vertically resolved Use redundant observations to verify that the evaluated net uncertainty is in agreement with the required target uncertainty. Also use redundant observations to: to manage change to maintain homogeneity of observations across network to continuously identify deficiencies

12 Establishing reference quality Best estimate and uncertainty Traceable sensor calibration Uncertainty of input data Transparent processing algorithm Black box software Disregarded systematic effects Proprietary methods X X X

13 GRUAN Network Expansion workshop June 2012 in Fürstenwalde. Define the scientific basis to guide the expansion of GRUAN from its then 15 sites (Ny Ålesund now added), to the expected over the next few years. The emphasis was on defining the criteria by which network expansion should occur and to consider prospective sites. Little or no consideration given to what they should measure or how they should measure it. Bring the workshop White Papers to a nearly completed state. Entrain additional expertise into GRUAN. Use quantitative & objective approach to determine how to augment the current GRUAN network with additional sites and to provide recommendations for new sites identified during the workshop & in the resultant White Papers.

14 The number of years of measurements required to detect a trend at the 95% confidence level with a probability of 0.9 can be approximated by (Whiteman et al., 2011): An example of quantitative analysis where σ N is the standard deviation of the total noise in the time series, i.e. the standard deviation of the residuals after the application of the trend regression model, ω 0 is the trend magnitude, and φ N is the autocorrelation of the noise. Consider how this applies to total column ozone…

15 21 st century trends in total column ozone Calculated from the median values of 21 chemistry- climate models

16 Standard deviation of the monthly means Calculated from the Bodeker Scientific global total column ozone database:

17 First order autocorrelation coefficient Calculated from the Bodeker Scientific global total column ozone database:

18 Optimal location Ushuaia

19 Where else?

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21

22 You get the idea

23 Conclusions GRUAN is a new approach to long term observations of upper air essential climate variables Focus on reference observation: quantified uncertainties quantified uncertainties traceable traceable well documented well documented Understand the uncertainties: analyze sources analyze sources synthesize best estimate synthesize best estimate verify in redundant observations verify in redundant observations Objective criteria can be used to optimize the location for detecting expected trends in total column ozone → but this is of course not the only criterion for where to locate sites.


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