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Network for the Detection of Atmospheric Composition Change: Tracking Changes in the Earths Atmosphere Michael J. Kurylo, Geir O. Braathen, and Niels Larsen.

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Presentation on theme: "Network for the Detection of Atmospheric Composition Change: Tracking Changes in the Earths Atmosphere Michael J. Kurylo, Geir O. Braathen, and Niels Larsen."— Presentation transcript:

1 Network for the Detection of Atmospheric Composition Change: Tracking Changes in the Earths Atmosphere Michael J. Kurylo, Geir O. Braathen, and Niels Larsen On behalf of the NDACC Science Team and 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 Participation by more than 20 countries and still expanding NDACC Sites

4 1.To study the temporal and spatial variability of atmospheric composition and structure Goals of the NDACC Regression analysis of O3/temperature measurements at Mauna Loa ( ) 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 identified on both lidar ozone and temperature data T. le Blanc, JPL

5 2.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 Goals of the NDACC

6 Upper Stratosphere Ozone Trends (NDACC Lidar Working Group) Multiple instruments / stations Similar upper stratospheric ozone anomalies Recently higher O 3 values may indicate recovery Should become clearer by 2008 (after solar min.)

7 FTIR Column Measurements at Jungfraujoch HCl, ClONO 2, and derived Cl y (R. Zander & E. Mahieu) compared to model predictions (M. Chipperfield) and to surface CCl y measurements (R. Prinn)

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

9 Pinatubo El Chichon Trend: –(7 3)%/decade Trend: +(6 1)%/decade Stratospheric column NO 2 (10 15 mol/cm 2 ) Year Zvenigorod (56°N, 37°E) Lauder (45°S, 170°E) Measurement s Regression model Residual series Linear trends in stratospheric column NO 2 Michel van Roozendael, BISA

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

11 Stratospheric Aerosol Layer NOAA/MLO

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

13 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. Update of McKenzie, Connor, and Bodeker, Science, 1999, 285, To establish links between changes in stratospheric O3, UV radiation at the ground, tropospheric chemistry, and climate Goals of the NDACC

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

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

16 NO 2 satellite - Ground based intercomparisons from Tenerife (Northern subtropics) Manuel Gil, INTA

17 5.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


20 W. Randel, NCAR Thule mean and std. dev. Model ACE CH 4 March Thule HCl March Lauder O3 July Lauder Mozart 3 chemistry climate model in comparison with FTIR and ACE measurements 6.To provide verified data for testing and improving multidimensional chemistry and transport models of the stratosphere and troposphere Goals of the NDACC

21 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.

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

23 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).

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

25 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

26 New informational leaflet Annual newsletters now available


28 MATCH campaigns Ozone loss versus PSC formation potential (V PSC ) V PSC : winter average volume of air cold enough for the formation of PSCs (e.g. -78 o C in 18 km Altitude) Year V PSC [ 10 6 km 3 ] ozone loss [ DU ] (ca km, January to March) (preliminary) update of Rex et al., GRL 2006; WMO 2007

29 comparison of lidar and SSU trends for 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 TMF OHP. Hohenp. Temperature trends from lidar measurements Keckhut et al.

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