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Monitoring Atmosphere: NDACC's Vital Role in Atmospheric Composition Research

Learn about the NDACC network monitoring changes in Earth's atmosphere with over 70 research sites globally. Explore goals, instruments, trends, and data quality assurance procedures. Discover the impact of stratospheric changes on climate.

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Monitoring Atmosphere: NDACC's Vital Role in Atmospheric Composition Research

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  1. Network for the Detectionof Atmospheric Composition Change:Tracking Changes in theEarth’s AtmosphereMichael J. Kurylo, Geir O. Braathen, and Niels LarsenOn behalf of the NDACC Science Teamand the NDACC Steering Committee Jonathon Berry

  2. What is the NDACC? • A set of more than 70 high-quality, remote-sensing research sites for • observing and understanding the physical / chemical state of the stratosphere and upper troposphere • assessing the impact of stratospheric changes on the underlying troposphere and on global climate

  3. NDACC Sites Participation by more than 20 countries and still expanding

  4. To study the temporal and spatial variability of atmospheric composition and structure Regression analysis of O3/temperature measurements at Mauna Loa (1994-2006) using fit base functions: -QBO functions (mean zonal wind m/s) -Mean ENSO Index (empirical p/Ts-based) -F10.7 Solar index QBO is dominant, but solar cycle and ENSO signatures also have been identifiedon both lidar ozone and temperature data T. le Blanc, JPL Goals of the NDACC

  5. Goals of the NDACC • To provide early detection and subsequent long-term monitoring of changes in the chemical and physical state of the stratosphere and upper troposphere; to provide the means to discern and understand the causes of such changes

  6. Upper Stratosphere Ozone Trends • (NDACC Lidar Working Group) • Multiple instruments / stations • Similar upper stratospheric ozone anomalies • Recently higher O3 values may indicate recovery • Should become clearer by 2008 (after solar min.)

  7. FTIR Column Measurements at Jungfraujoch HCl, ClONO2, and derived Cly (R. Zander & E. Mahieu) compared to model predictions (M. Chipperfield) and to surface CCly measurements (R. Prinn)

  8. Evolution of Stratospheric BrO F. Hendrick, M. De Mazière, M. Van Roozendael (BISA) P. V. Johnston, K. Kreher (NIWA)

  9. Linear trends in stratospheric column NO2 Zvenigorod (56°N, 37°E) Trend: –(73)%/decade Stratospheric column NO2 (1015 mol/cm2) Measurements Lauder (45°S, 170°E) Regression model Trend: +(61)%/decade Residual series Year El Chichon Pinatubo Michel van Roozendael, BISA

  10. Stratospheric water vapor Water vapour measurements from WVMS at Mauna Loa, and coincident measurements from MLS and HALOE. G. Nedoluha (NRL) & N. Kampfer (U. Bern)

  11. Stratospheric Aerosol Layer NOAA/MLO

  12. Temperature time series from lidar and SSU satellite measurements (40-45 km).Satellite trends 1988-2005 are small.Large statistical uncertainties for lidars trends W. Randel, NCAR

  13. Goals of the NDACC Taihoro Nukurangi Long term decrease in ozone has been responsible for 12-15% increase in the maximum summertime UV Index over Lauder, NZ. Approximately half of the ozone depletion at mid-southern latitudes has been due to the export of ozone-poor air from Antarctica. • To establish links between changes in stratospheric O3, UV radiation at the ground, tropospheric chemistry, and climate Update of McKenzie, Connor, and Bodeker, Science, 1999, 285, 1709-1711

  14. UV Index at Río Gallegos Data Level 1.5 Period: August 1, 2005 – October 31 2006 S. Godin-Beekmann

  15. Goals of the NDACC 4. To provide independent validations, calibrations, and complementary data for space-based sensors of the atmosphere SAOZ UV-Visible Measurements: Sodankylä, Finland Long-term validation is crucial! F. Goutail (CNRS) and E. Kyrö (FMI)

  16. NO2 satellite - Ground based intercomparisons from Tenerife (Northern subtropics) Manuel Gil, INTA

  17. To support process-specific field campaigns occurring at various latitudes and seasons Goals of the NDACC

  18. Arctic Ozone Loss SAOZ UV-Visible Network F. Goutail, J. P. Pommereau + SAOZ team

  19. Goals of the NDACC • To provide verified data for testing and improving multidimensional chemistry and transport models of the stratosphere and troposphere CH4 March Thule ACE Model HCl March Lauder Thule mean and std. dev. O3 July Lauder Mozart 3 chemistry climate model in comparison with FTIR and ACE measurements W. Randel, NCAR

  20. Quality Control A Commitment to Data Quality Investigators subscribe to a protocol designed to ensure that archived data are of as high a quality as possible within the constraints of measurement technology and retrieval theory. Validation Instruments and data analysis methods are evaluated and continuously monitored. Formal intercomparisons are used to evaluate algorithms and instruments.

  21. Dobson / Brewer Working Group Improvement of the data quality of the Dobson network during the past nearly 40 years. U. Koehler (OMH)

  22. Data Archiving and Availability Data submitted within one year Data public available within two years of measurement Many NDACC data available on shorter timescale via collaborative arrangement with the appropriate PI(s).

  23. NDACC Data Host FacilityHosted by NOAA More than 35,000 files in data base J. Wild & R. Lin (NOAA)

  24. Future Developments Water vapor in the UTLS Raman Lidars Balloon soundings Closer collaboration with other networks such as SHADOZ Establishment of more stations in the tropics Provision of data in near-real-time

  25. http://www.ndacc.org New informational leaflet Annual newsletters now available

  26. MATCH campaigns Ozone loss versus PSC formation potential (VPSC)VPSC: winter average volume of air cold enough for the formation of PSCs (e.g. -78oC in 18 km Altitude) Year 2008 2006 2007 2004 2002 ozone loss [ DU ] (ca. 13-25 km, January to March) 2000 2008 (preliminary) 1998 1996 1994 1992 VPSC [ 106 km3 ] update of Rex et al., GRL 2006;WMO 2007

  27. Temperature trends from lidar measurements Hohenp. comparison of lidar and SSU trends for 1988-2005 Notes: Satellite trends are small for this period. Trends are changing Large statistical uncertainties for the lidars (only shown for OHP curve, but similar for other stations). Table Mountain is an outlier (strong cooling, as seen in the time series) Hohenpeisenberg also OHP. TMF Keckhut et al.

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