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Global long-term monitoring of the ozone layer - a prerequisite for predictions.
- Source :
- International Journal of Remote Sensing; Aug2009, Vol. 30 Issue 15/16, p4295-4318, 24p, 2 Diagrams, 3 Charts, 7 Graphs
- Publication Year :
- 2009
-
Abstract
- Although the Montreal Protocol now controls the production and emission of ozone depleting substances, the timing of ozone recovery is unclear. There are many other factors affecting the ozone layer, in particular climate change is expected to modify the speed of re-creation of the ozone layer. Therefore, long-term observations are needed to monitor the further evolution of the stratospheric ozone layer. Measurements from satellite instruments provide global coverage and are supplementary to selective ground-based observations. The combination of data derived from different space-borne instruments is needed to produce homogeneous and consistent long-term data records. They are required for robust investigations including trend analysis. For the first time global total ozone columns from three European satellite sensors GOME (ERS-2), SCIAMACHY (ENVISAT), and GOME-2 (METOP-A) are combined and added up to a continuous time series starting in June 1995. On the one hand it is important to monitor the consequences of the Montreal Protocol and its amendments; on the other hand multi-year observations provide the basis for the evaluation of numerical models describing atmospheric processes, which are also used for prognostic studies to assess the future development. This paper gives some examples of how to use satellite data products to evaluate model results with respective data derived from observations, and to disclose the abilities and deficiencies of atmospheric models. In particular, multi-year mean values derived from the Chemistry-Climate Model E39C-A are used to check climatological values and the respective standard deviations. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 01431161
- Volume :
- 30
- Issue :
- 15/16
- Database :
- Complementary Index
- Journal :
- International Journal of Remote Sensing
- Publication Type :
- Academic Journal
- Accession number :
- 43494516
- Full Text :
- https://doi.org/10.1080/01431160902825016