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Network for the Detection of Atmospheric Composition Change: Tracking Changes in the Earth’s Atmosphere Michael J. Kurylo, Geir O. Braathen, and Niels Larsen On behalf of the NDACC Science Team and the NDACC Steering Committee. Jonathon Berry. What is the NDACC?.

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Jonathon berry

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

What is the ndacc

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

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Participation by more than 20 countries and still expanding

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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

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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

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  • 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.)

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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)

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Evolution of Stratospheric BrO

F. Hendrick, M. De Mazière, M. Van Roozendael (BISA) P. V. Johnston, K. Kreher (NIWA)

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Linear trends in stratospheric column NO2

Zvenigorod (56°N, 37°E)

Trend: –(73)%/decade

Stratospheric column NO2 (1015 mol/cm2)


Lauder (45°S, 170°E)

Regression model

Trend: +(61)%/decade

Residual series


El Chichon


Michel van Roozendael, BISA

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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)

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Stratospheric Aerosol Layer


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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

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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

Uv index at r o gallegos

UV Index at Río Gallegos

Data Level 1.5

Period: August 1, 2005 – October 31 2006

S. Godin-Beekmann

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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)

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NO2 satellite - Ground based intercomparisons from Tenerife (Northern subtropics)

Manuel Gil, INTA

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To support process-specific field campaigns occurring at various latitudes and seasons

Goals of the NDACC

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Arctic Ozone Loss

SAOZ UV-Visible Network

F. Goutail, J. P. Pommereau + SAOZ team

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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



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

Quality control

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.


Instruments and data analysis methods are evaluated and continuously monitored.

Formal intercomparisons are used to evaluate algorithms and instruments.

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Dobson / Brewer Working Group

Improvement of the data quality of the Dobson network during the past nearly 40 years.

U. Koehler (OMH)

Data archiving and availability

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).

Ndacc data host facility hosted by noaa

NDACC Data Host FacilityHosted by NOAA

More than 35,000 files in data base

J. Wild & R. Lin (NOAA)

Future developments

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

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New informational leaflet

Annual newsletters now available

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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)







ozone loss [ DU ]

(ca. 13-25 km, January to March)


2008 (preliminary)





VPSC [ 106 km3 ]

update of Rex et al., GRL 2006;WMO 2007

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Temperature trends from lidar measurements


comparison of lidar and

SSU trends for 1988-2005


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



Keckhut et al.

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