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
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The GCOS Reference Upper Air Network: Assuring the 21 st Century Climate record?
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. What is GRUAN?. GCOS Reference Upper Air Network - PowerPoint PPT Presentation
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Meteorological Observatory Lindenberg – Richard Assmann Observatory
The GCOS Reference
Upper Air Network: Assuring the 21st Century Climate
record?
Peter Thorne, CICS-NC
With thanks to GRUAN Lead Centre (DWD) and Working
Group on Atmospheric Reference Observations
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
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
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, …
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
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
Ubiquitous change
Meteorological Observatory Lindenberg – Richard Assmann Observatory
Tropospheric temperature trend uncertainties
Meteorological Observatory Lindenberg – Richard Assmann Observatory
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 doesn’t have to be this way going forwards. We need traceable measures in future to assure the record.
• Lesson 2 is where GRUAN comes in …
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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
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Establishing reference quality
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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
Uncertainty, Redundancy and Consistency
GRUAN stations should provide redundant measurements
Redundant measurements should be consistent:
No meaningful consistency analysis possible without uncertainties
if m2 has no uncertainties use u
2 = 0 (“agreement within errorbars”)
Meteorological Observatory Lindenberg – Richard Assmann Observatory
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2121 uukmm
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
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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
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21
221 uukmm
22
21 uu
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
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
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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
Distributed data processingGRUAN data flow
GRUAN sites
Data processing center
GRUAN Meta-data-base(at GRUAN lead center) raw
data archive
DATA dissemination (at NCDC)
datadocumentation
Meteorological Observatory Lindenberg – Richard Assmann Observatory
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
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
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