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Animation of the Antarctic Ozone Loss

Why Study Atmospheric Ozone?

Ozone is a naturally occurring gas in the atmosphere. Most ozone (about 90%) is found in the stratosphere, which is the region between about 6-10 miles and about 31 miles above Earth's surface. The remaining ozone (about 10%) is in the troposphere, which is the lowermost region of the atmosphere between Earth's surface and the stratosphere.

The ozone layer in the stratosphere shields life on Earth from the harmful effects of the solar ultraviolet radiation. The ozone layer is currently in a fragile state because of the depletion caused by man-made chemicals, especially chlorofluorocarbons.

Near the surface of the Earth, in the troposphere, ozone has increased from man-made pollution. However, high surface ozone levels are harmful for human health and decrease crop yields.

Ozone is related to the climate change. Ozone absorption of ultraviolet radiation from the Sun warms the stratosphere. Ozone emits and absorbs infrared radiation and contributes substantially to the Earth's energy balance.

Above reasons motivate efforts to determine global ozone distribution and its evolution from pre-industrial times to present, and predict future ozone changes. Vertical distribution of ozone is very important in order to determine impacts that ozone changes have on climate and human health. For more information see Scientific Assessment of Ozone Depletion: 2002.

What Ozone Related Work is done at the GMAO?

The GMAO ozone group works on combining of ozone data from satellite instruments with ozone fields from global models in order to produce global three-dimensional estimates of ozone distribution. A data assimilation system was developed for this purpose. The assimilation includes total ozone column data from either TOMS or SBUV/2 instruments, which both make nadir-viewing measurements of backscattered solar radiation. The stratospheric ozone profiles are constrained by assimilation of partial column ozone column data from SBUV/2 instrument, and sometimes from limb viewing MIPAS instrument or from POAM solar occultation measurements.

The GMAO produces assimilated ozone fields in near-real time by combining data from the operational NOAA 16 SBUV/2 instrument with ozone forecasts from a parameterized ozone chemistry and transport model (CTM) (Stajner et al. 2004). The focus of this product is on the stratospheric ozone distribution. Analyses prior to April/May 2001 included Earth Probe TOMS total columns and NOAA 14 SBUV/2 stratospheric partial columns data (Riishojgaard et al. 2000; Stajner et al. 2001). Time series of differences between incoming observations and forecasts from the near-real time system are routinely monitored. Temporal changes in these time series were shown to be sensitive indicators of changes in quality of ozone data from Earth Probe TOMS, NOAA 14 and NOAA 16 SBUV/2 satellite instruments (Stajner et al. 2004).

Research efforts are focusing on improving the ozone representation in the lower stratosphere through assimilation of data with better vertical resolution or by modifying error covariance models used in the assimilation. The assimilation of MIPAS data was shown to improve the ozone analyses, especially in the lower stratosphere (Wargan et al. 2004). The assimilation of POAM data improved the quality of wintertime Antarctic ozone (Stajner and Wargan 2004).

Tropospheric ozone columns and profiles are produced in research mode by assimilating satellite ozone data into the GMAO's general circulation model (GCM), which we modified to include parameterized schemes for gas-phase stratospheric ozone chemistry, heterogeneous ozone loss ("ozone hole" processes), and tropospheric ozone chemistry.

Assimilation of ozone data from new instruments on the EOS Aura satellite is expected to improve the representation of ozone throughout stratosphere and troposphere. In addition, it will enable investigations of radiative impacts of ozone in the GMAO's GCM and implications for the quality of 10-day or longer forecasts. We are also working on removing climatological constraints in the assimilation of retrieved data from nadir-viewing instruments. Two approaches are investigated using either averaging kernels or a linearized foreward model.

Page author: Ivanka Stajner
Email: istajner@gmao.gsfc.nasa.gov
Content last updated: 2 September 2004