World Library  


Add to Book Shelf
Flag as Inappropriate
Email this Book

Analysing Spatio-temporal Patterns of the Global No2-distribution Retrieved from Gome Satellite Observations Using a Generalized Additive Model : Volume 9, Issue 17 (08/09/2009)

By Hayn, M.

Click here to view

Book Id: WPLBN0003995046
Format Type: PDF Article :
File Size: Pages 19
Reproduction Date: 2015

Title: Analysing Spatio-temporal Patterns of the Global No2-distribution Retrieved from Gome Satellite Observations Using a Generalized Additive Model : Volume 9, Issue 17 (08/09/2009)  
Author: Hayn, M.
Volume: Vol. 9, Issue 17
Language: English
Subject: Science, Atmospheric, Chemistry
Collections: Periodicals: Journal and Magazine Collection, Copernicus GmbH
Historic
Publication Date:
2009
Publisher: Copernicus Gmbh, Göttingen, Germany
Member Page: Copernicus Publications

Citation

APA MLA Chicago

Beirle, S., Wagner, T., Hamprecht, F. A., Platt, U., Menze, B. H., & Hayn, M. (2009). Analysing Spatio-temporal Patterns of the Global No2-distribution Retrieved from Gome Satellite Observations Using a Generalized Additive Model : Volume 9, Issue 17 (08/09/2009). Retrieved from http://www.ebooklibrary.org/


Description
Description: Institut für Mathematik, University of Potsdam, Potsdam, Germany. With the increasing availability of observational data from different sources at a global level, joint analysis of these data is becoming especially attractive. For such an analysis – oftentimes with little prior knowledge about local and global interactions between the different observational variables at hand – an exploratory, data-driven analysis of the data may be of particular relevance.

In the present work we used generalized additive models (GAM) in an exemplary study of spatio-temporal patterns in the tropospheric NO2-distribution derived from GOME satellite observations (1996 to 2001) at global scale. We focused on identifying correlations between NO2 and local wind fields, a quantity which is of particular interest in the analysis of spatio-temporal interactions. Formulating general functional, parametric relationships between the observed NO2 distribution and local wind fields, however, is difficult – if not impossible. So, rather than following a model-based analysis testing the data for predefined hypotheses (assuming, for example, sinusoidal seasonal trends), we used a GAM with non-parametric model terms to learn this functional relationship between NO2 and wind directly from the data.

The NO2 observations showed to be affected by wind-dominated processes over large areas. We estimated the extent of areas affected by specific NO2 emission sources, and were able to highlight likely atmospheric transport pathways. General temporal trends which were also part of our model – weekly, seasonal and linear changes – showed to be in good agreement with previous studies and alternative ways of analysing the time series. Overall, using a non-parametric model provided favorable means for a rapid inspection of this large spatio-temporal NO2 data set, with less bias than parametric approaches, and allowing to visualize dynamical processes of the NO2 distribution at a global scale.


Summary
Analysing spatio-temporal patterns of the global NO2-distribution retrieved from GOME satellite observations using a generalized additive model

Excerpt
Aldrin, M. and Haff, I. H.: Generalised additive modelling of air pollution, traffic volume and meteorology, Atmos. Environ., 39(11), 2145–2155, 2005.; Beirle, S., Platt, U., Wenig, M., and Wagner, T.: Weekly cycle of NO2 by GOME measurements: a signature of anthropogenic sources, Atmos. Chem. Phys., 3, 2225–2232, 2003.; Beirle, S.: Estimating source strengths and lifetime of Nitrogen Oxides from satellite data, PhD thesis, Ruperto-Carola University of Heidelberg, Germany, 2004.; Beirle, S., Platt, U., Wenig, M., and Wagner, T.: NOx production by lightning estimated with GOME, Adv. Space Res., 34(4), 793–797, 2004.; Boersma, K. F., Eskes, H. J., and Brinksma, E. J.: Error analysis for tropospheric NO2 retrieval from space, J. Geophys. Res., 109, D04311, doi:10.1029/2003JD003962, 2004.; Boersma, K. F., Jacob, D. J., Eskes, H. J., Pinder, R. W., Wang, J., and van der A, R. J.: Intercomparison of SCIAMACHY and OMI tropospheric NO2 columns: Observing the diurnal evolution of chemistry and emissions from space, J. Geophys. Res, 113, D16S26, doi:10.1029/2007JD008816, 2008.; Boersma, K. F., Jacob, D. J., Trainic, M., Rudich, Y., DeSmedt, I., Dirksen, R., and Eskes, H. J.: Validation of urban NO2 concentrations and their diurnal and seasonal variations observed from the SCIAMACHY and OMI sensors using in situ surface measurements in Israeli cities, Atmos. Chem. Phys., 9, 3867–3879, 2009.; Lee, T. C. M.: Smoothing parameter selection for smoothing splines: a simulation study, Comput. Stat. Data An., 42(1–2), 139–148, 2003.; Bovensmann, H., Burrows, J. P., Buchwitz, M., Frerick, J., Noël, S., Rozanov, V. V., Chance, K. V., and Goede, A. P. H.: SCIAMACHY: Mission Objectives and Measurement Modes, J. Atmos. Sci., 56(2), 127–150, 1999.; Burrows, J. P., Weber, M., Buchwitz, M., Rozanov, V., Ladstätter-Weiß enmayer, A., Richter, A., DeBeek, R., Hoogen, R., Bramstedt, K., Eichmann, K., Eisinger, M., and Perner, D.: The Global Ozone Monitoring Experiment (GOME): Mission concept and first results, J. Atmos. Sci., 56(2), 151–175, 1999.; Craven, P. and Wahba, G.: Smoothing noisy data with spline functions, Numer. Math., 31(4), 377–403, 1979.; Dominici, F., McDermott, A., Zeger, S. L., and Samet, J. M.: On the Use of Generalized Additive Models in Time-Series Studies of Air Pollution and Health, Am. J. Epidemiol., 156(3), 193–203, 2002.; ESA: Global Ozone Monitoring Experiment (GOME), Users Manual, ESA Publications Devision, SP-1182, edited by: Bednarz, F., ISBN: 92-9092-327, 1995.; Grzegorski, M., Wenig, M., Platt, U., Stammes, P., Fournier, N., and Wagner, T.: The Heidelberg iterative cloud retrieval utilities (HICRU) and its application to GOME data, Atmos. Chem. Phys., 6, 4461–4476, 2006.; Hastie, T. J. and Tibshirani, R. J.: Generalized Additive Models, Stat. Sci., 1(3), 297–318, 1986.; Hastie, T. J., and Tibshirani, R. J.: Generalized Additive Models, Monographs on Statistics and Applied Probability, 43, Chapman & Hall/CRC, New York, USA, 1990.; Jacob, D. J.: Introduction to Atmospheric Chemistry, Princeton University Press, 1999.; Kållberg, P., Simmons, A., Uppala, S., and Fuentes, M.: The ERA-40 Archive, ERA-40 Project Report Series No. 17, ECMWF, 2004.; Kim, J. and Hong, J.: A GAM for Daily Ozone Concentration in Seoul, Key Eng. Mat., 277/279, 497–502, 2005.; Jaeglé, L., Martin, R. V., Chance, K., Steinberg, L., Kurosu, T. P., Jacob, D. J., Modi, A. I., Yoboué, V., Sigha-Nkamdjou, L., and Galy-Lacaux, C.: Satellite mapping of rain-induced nitric oxide emissions from soils, J. Geophys. Res., 109, D21310, doi:10.1029/2004JD004787, 2004.; Kunhikrishnan, T., Lawrence, M. G., von Kuhlmann, R., Richter, A., Ladstätter-Wei{ß}enmayer, A., and Burrows, J. P.: Semiannual NO2 plumes during the monsoon transition periods over the central Indian Ocean, Geophys. Res. Lett., 31, L08110, doi:10.1029/2003GL019269

 

Click To View

Additional Books


  • Influence of Co2 Observations on the Opt... (by )
  • Gem/Pops: a Global 3-d Dynamic Model for... (by )
  • Comparison of Two Different Sea-salt Aer... (by )
  • Cloud Condensation Nuclei in Pristine Tr... (by )
  • Assimilation of Tes Co Into a Global Ctm... (by )
  • Direct Measurement of Particle Formation... (by )
  • Observations of Ozone Production in a Di... (by )
  • Characteristics of Water-vapour Inversio... (by )
  • Analysis of Non-regulated Vehicular Emis... (by )
  • Global Terrestrial Isoprene Emission Mod... (by )
  • Physical Properties of High Arctic Tropo... (by )
  • Technical Note: Description and Assessme... (by )
Scroll Left
Scroll Right

 



Copyright © World Library Foundation. All rights reserved. eBooks from World eBook Library are sponsored by the World Library Foundation,
a 501c(4) Member's Support Non-Profit Organization, and is NOT affiliated with any governmental agency or department.