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Nonlinear analysis/forecasting and chemical monitoring

Nonlinear analysis/forecasting and chemical monitoring. Formation and training of researchers Antonello Pasini CNR - Institute of Atmospheric Pollution Rome - ITALY.

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Nonlinear analysis/forecasting and chemical monitoring

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  1. Nonlinear analysis/forecasting and chemical monitoring Formation and training of researchers Antonello Pasini CNR - Institute of Atmospheric Pollution Rome - ITALY 26 July - 4 August 2000

  2. The Institute of Atmospheric Pollution of the National Research Council of Italy (CNR) proposes an activity of formation and know-how transfer to researchers of Small Island States in the field of climate/global change: • Topic 1: nonlinear analysis/forecasting by means of neural network modeling. • Topic 2: chemical monitoring techniques with emphasis to remote pollution. 26 July - 4 August 2000

  3. Neural network modelingPreliminary considerations • The atmosphere-ocean-biosphere system is complex and nonlinear. 26 July - 4 August 2000

  4. Neural network modelingPreliminary considerations • At present, GCMs show good results, but not fully reliable regional forecasts. 26 July - 4 August 2000

  5. Neural network modelingPreliminary considerations • These models require specialized man-power and high-cost supercomputers  GCMs are not easily managed by developing countries. 26 July - 4 August 2000

  6. Neural network modeling • In this situation, a non-dynamical statistical method can be useful either for influence analysis and for localized forecasting. • Neural networks learn from past data and are able to generalize to unknown situations. • Recently, they have been applied to environmental problems. 26 July - 4 August 2000

  7. Neural network modelingThe biological inspiration 26 July - 4 August 2000

  8. Neural network modeling • A weighted sum converges at each neuron of hidden and output layers… • … where a nonlinear activation function is calculated. 26 July - 4 August 2000

  9. Neural network modeling • After a training on a statistical significant data set, the network is able to fix its connection weights... • … thus giving us a diagnostic or prognostic relationship between inputs and output. 26 July - 4 August 2000

  10. Neural network modelingHow to use a neural network model in the field of climate change? • Three options: - Influence analysis; - forecasting from observations; - post-processing of a GCM’s output. 26 July - 4 August 2000

  11. Neural network modelingInfluence analysis • Estimation of forcing relevance on climate change and global heating related to temperature scenarios: - at global level; - at regional level. • Reconstruction and forecast of heating. 26 July - 4 August 2000

  12. Neural network modelingForecasting from observations • Departing from relevant meteo-climatic observations, a neural model is able to forecast SST or other physical variables. • Attempts at forecasting future scenarios (CO2 doubling problem) are now in progress. 26 July - 4 August 2000

  13. Neural network modelingForecasting from observations 26 July - 4 August 2000

  14. Neural network modelingPost-processing of a GCM’s output • Neural networks may be used in order to improve forecasts of GCMs on a local or regional scale. • Typical variables to be predicted are temperature and precipitation. • Model errors become lower. 26 July - 4 August 2000

  15. Neural network modelingConclusive considerations • Dynamical treatment (via GCMs) of climate change topics leads to good results even with difficult parameterizations. • Neural modeling offers a way for analyzing these topics with a fully nonlinear non-dynamical tool. • Neural models require simple workstations or PCs and can be managed by few experts. 26 July - 4 August 2000

  16. Neural network modelingConclusive considerations • We think that the formation of one or more neural modelers is a good opportunity for the Small Island States in order to meet the advanced research in the topic of climate change and to analyze and forecast phenomena that strongly affect life and development. 26 July - 4 August 2000

  17. Neural network modelingSuggested outline of training • Basic training (20-30 days) in neural modeling at an AOSIS University (e.g. USP) for a wide audience. • Advanced training (3-12 months) and application to local data to be, eventually, held at the CNR - Institute of Atmospheric Pollution (Italy) for two AOSIS researchers. 26 July - 4 August 2000

  18. Neural network modelingEssential bibliography • Hsieh and Tang - Bull. Am. Met. Soc. 79, 1855-1870, 1998. • Gardner and Dorling - Atmos. Environm. 32, 2627-2636, 1998. • Walter et al. - Met. Zeitschr. 7, 171-180, 1998. • Tangang et al. - J. Clim. 11, 29-41, 1998. 26 July - 4 August 2000

  19. Neural network modelingEssential bibliography • Tangang et al. - J. Geophys. Res. 103 (C4), 7511-7522, 1998. • Marzban and Stumpf - Wea. Forecast. 13, 151- 163, 1998. • Pasini and Potestà - in Neural Nets: WIRN Vietri-96 (Springer), 263-269, 1997. • Pasini et al. - submitted to J. Geophys. Res. D, 2000. 26 July - 4 August 2000

  20. Chemical monitoringPreliminary considerations • Small changes in the releases to the atmosphere of some gases can have unexpected and long-lasting global effects. • Atmospheric chemistry determines the extent to which source gases may be important. • In general, the less reactive a gas, the more global the scale of the problem. 26 July - 4 August 2000

  21. Chemical monitoringPreliminary considerations • In the atmosphere complex interactions of physical processes and chains of chemical reactions are involved. 26 July - 4 August 2000

  22. Chemical monitoringPreliminary considerations • In general, in climate change studies, we consider the effects of changes in gas and aerosol concentrations on physical parameters (temperature, sea level, etc.). • But changes in the chemical composition of the atmosphere may produce changes (and problems) also in the natural environment (soil, forests, lagoons, etc.). 26 July - 4 August 2000

  23. Chemical monitoringPreliminary considerations • Even in remote areas we can observe transport phenomena or, at least, influences of surface interactions with the atmosphere. 26 July - 4 August 2000

  24. Chemical monitoringPreliminary considerations • Another element of concern is the increase in oxidizing capacity of the atmosphere… • … recognized even in marine and remote environments with forests. 26 July - 4 August 2000

  25. Chemical monitoringPreliminary considerations • The tropical forests are emitters of VOCs, precursors of oxidized compounds. • The background of ozone has shown a doubling in the last 20 years. • Phytotoxic effects? 26 July - 4 August 2000

  26. Chemical monitoring • The Institute of Atmospheric Pollution is widely involved in researches concerning remote or semi-remote areas (Himalaya, North and South Polar regions, semi-remote sites in Europe). • Many innovative sampling and analytical procedures were developed for monitoring low concentrations of chemical species (either gas and particulate matter). 26 July - 4 August 2000

  27. Chemical monitoring • Several automatic instruments (some of them developed in our Institute) are used for monitoring low concentrations of primary and secondary pollutants. • Particular attention is paid to secondary pollutants and to particulate matter PM10 and PM2.5. Ad hoc instruments were developed for their detection. 26 July - 4 August 2000

  28. Chemical monitoring • These instruments include an automatic monitor for particulate matter and annular denuders (+ filter packs) for detecting secondary pollutants either in gas and particulate phase. • DOAS (Differential Optical Absorption System) and passive samplers (very useful in remote areas) are also used. 26 July - 4 August 2000

  29. Chemical monitoring 26 July - 4 August 2000

  30. Chemical monitoring • These instruments are intended for monitoring species which are dangerous for surface ecosystems, including: - tropospheric ozone, - particulate matter of secondary origin, - VOCs and photo-oxidants, - acidity containing compounds, - organic compounds, - heavy metals (mercury). 26 July - 4 August 2000

  31. Chemical monitoring • The analysis of data from non-automatic instruments involves techniques such as gas-chromatography and mass spectrometry (great expertise at our Institute). 26 July - 4 August 2000

  32. Chemical monitoringConclusive considerations • The study of time and space variability of these compounds helps to clarify either long-range transport phenomena and the increase in background concentrations. • These pieces of information are important for assessing changes in radiative balance of earth, but also for early warning on global changes in chemical cycles. 26 July - 4 August 2000

  33. Chemical monitoringConclusive considerations • These latter changes occurring in the atmosphere may influence ecosystems in a dangerous way. • This is particularly serious in areas which are universally considered as natural heritage of the entire World. 26 July - 4 August 2000

  34. Chemical monitoringSuggested outline of training • Training on instruments and techniques for chemical monitoring (6-12 months) to be held at the Institute of Atmospheric Pollution (Italy) for two/three AOSIS researchers. • Final in situ campaign (15-20 days) at an AOSIS island, in order to apply learned techniques in the local environment. 26 July - 4 August 2000

  35. Chemical monitoringEssential bibliography • Allegrini et al. - Int. J. Environm. Anal. Chem. 55, 267-283, 1994. • Allegrini et al. - J. Chromatography A846, 265-268, 1999. • Hillamo et al. - Int. J. Environm. Atmosph. Chem. 71, 353-372, 1998. 26 July - 4 August 2000

  36. Chemical monitoringEssential bibliography • Beine et al. - Atmosph. Environm. 30, 1067-1079, 1996. • Herring et al. - J. Atmosph. Chem. 27, 155-178, 1997. • Beine - Chemosphere: Global Science Change 1, 145-151, 1999. 26 July - 4 August 2000

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