Correction of approximation errors with Random Forests applied to modelling of cloud droplet formation

Geoscientific Model Development

Volumn 6, Issue 6, 2013, Pages 2087-2098

  Lipponen, A ^a   Kolehmainen, V ^a   Romakkaniemi, S ^a   Kokkola, H ^b  

^a UNIVERSITY OF EASTERN FINLAND   (Finland)

^b FINNISH METEOROLOGICAL INSTITUTE   (Finland)

Author keywords

[No Author keywords available]

Indexed keywords

ACCURACY ASSESSMENT; ATMOSPHERIC MODELING; CLOUD DROPLET; CORRECTION; ERROR ANALYSIS; NUMERICAL MODEL; PARAMETERIZATION; PARTICLE SIZE; SIZE DISTRIBUTION;

EID: 84890446484     PISSN: 1991959X     EISSN: 19919603     Source Type: Journal    
DOI: 10.5194/gmd-6-2087-2013     Document Type: Article

References (34)

1. Abdul-Razzak, H., Ghan, S. J., and Rivera-Carpio, C.: A parameterization of aerosol activation 1. single aerosol type, J. Geophys. Res., 103, 6123-6131, doi:10.1029/97JD03735, 1998. (Pubitemid 28392665)
2. Abdul-Razzak, H. and Ghan, S. J.: A parameterization of aerosol activation 2. Multiple aerosol types, J. Geophys. Res., 105, 6837- 6844, doi:10.1029/1999JD901161, 2000.
3. Abdul-Razzak, H. and Ghan, S. J.: A parameterization of aerosol activation 3. Sectional representation, J. Geophys. Res., 107, AAC 1-1-AAC 1-6, doi:10.1029/2001JD000483, 2002.
4. Arridge, S., Kaipio, J., Kolehmainen, V., Schweiger, M., Somersalo, E., Tarvainen, T., and Vauhkonen, M.: Approximation errors and model reduction with an application in optical diffusion tomography, Inverse Probl., 22, 175-195, doi:10.1088/0266-5611/22/1/010, 2006. (Pubitemid 43185096)
5. Bechtel, B. and Daneke, C.: Classification of local climate zones based on multiple earth observation data, IEEE J. Sel. Top. Appl., 5, 1191-1202, doi:10.1109/JSTARS.2012.2189873, 2012.
6. Bergman, T., Kerminen, V.-M., Korhonen, H., Lehtinen, K. J., Makkonen, R., Arola, A., Mielonen, T., Romakkaniemi, S., Kulmala, M., and Kokkola, H.: Evaluation of the sectional aerosol microphysics module SALSA implementation in ECHAM5-HAM aerosol-climate model, Geosci. Model Dev., 5, 845-868, doi:10.5194/gmd-5-845-2012, 2012.
7. Breiman, L.: Random Forests, Mach. Learn., 45, 5-32, doi:10.1023/A: 1010933404324, 2001. (Pubitemid 32933532)
8. Chen, C., Liaw, A., and Breiman, L.: Using random forests to learn imbalanced data, Technical Report 666, Statistics Department of University of California, Berkeley, USA, 2004.
9. Clegg, S. L., Brimblecombe, P., and Wexler, A. S.: Thermodynamical model of the system H+-NH+ 4 -SO2- 4 -NO- 3 -H2O at tropospheric temperatures, J. Phys. Chem. A, 102, 2137-2154, 1998.
10. Forster, P., Ramaswamy, V., Artaxo, P., Berntsen, T., Betts, R., Fahey, D., Haywood, J., Lean, J., Lowe, D., Myhre, G., Nganga, J., Prinn, R., Raga, G., Schulz, M., and Van Dorland, R.: Changes in atmospheric constituents and in radiative forcing, in: Climate Change 2007: The Physical Science Basis, Contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change, edited by: Solomon, S., Qin, D., Manning, M., Chen, Z., Marquis, M., Averyt, K., Tignor, M., and Miller, H., Cambridge University Press, Cambridge, UK and New York, NY, USA, 2007.
11. Fountoukis, C. and Nenes, A.: Continued development of a cloud formation parameterization for global climate models, J. Geophys. Res., 110, D11212, doi:10.1029/2004JD005591, 2005. (Pubitemid 41268811)
12. Haykin, S. O.: Neural networks and learning machines, Prentice Hall, New York, 2009.
13. Jacobson, M. Z.: GATOR-GCMM: a global through urban scale air pollution and weather forecast model. 1. Model design and treatment of subgrid soil, vegetation, roads, rooftops, water, sea ice, and snow, J. Geophys. Res., 106, 5385-5402, doi:10.1029/2000JD900560, 2001.
14. Kaipio, J. and Somersalo, E.: Statistical and Computational Inverse Problems, Springer, New York, 2005.
15. Kokkola, H., Romakkaniemi, S., Kulmala, M., and Laaksonen, A.: A cloud microphysics model including trace gas condensation and sulfate chemistry, Boreal Environ. Res., 8, 413-424,2003. (Pubitemid 38038850)
16. Kokkola, H., Korhonen, H., Lehtinen, K. E. J., Makkonen, R., Asmi, A., Järvenoja, S., Anttila, T., Partanen, A.-I., Kulmala, M., Järvinen, H., Laaksonen, A., and Kerminen, V.-M.: SALSA - a Sectional Aerosol module for Large Scale Applications, Atmos. Chem. Phys., 8, 2469-2483, doi:10.5194/acp-8- 2469-2008, 2008.
17. Kolehmainen, V., Schweiger, M., Nissilä, I., Tarvainen, T., Arridge, S., and Kaipio, J.: Approximation errors and model reduction in three-dimensional diffuse optical tomography, J. Opt. Soc. Am. A, 10, 2257-2267, doi:10.1364/JOSAA.26.002257, 2009.
18. Kolehmainen, V., Tarvainen, T., Arridge, S., and Kaipio, J.: Marginalization of uninteresting distributed parameters in inverse problems - application to diffuse optical tomography, International Journal for Uncertainty Quantification, 1, 1-17, doi:10.1615/Int.J.UncertaintyQuantification.v1.i1.10, 2011.
19. Lehikoinen, A., Finsterle, S., Voutilainen, A., Heikkinen, L., Vauhkonen, M., and Kaipio, J.: Approximation errors and truncation of computational domains with application to geophysical tomography, Inverse Probl. Imag., 1, 371-389, doi:10.3934/ipi.2007.1.371, 2007.
20. Liu, X., Easter, R. C., Ghan, S. J., Zaveri, R., Rasch, P., Shi, X., Lamarque, J.-F., Gettelman, A., Morrison, H., Vitt, F., Conley, A., Park, S., Neale, R., Hannay, C., Ekman, A. M. L., Hess, P., Mahowald, N., Collins, W., Iacono, M. J., Bretherton, C. S., Flanner, M. G., and Mitchell, D.: Toward a minimal representation of aerosols in climate models: description and evaluation in the Community Atmosphere Model CAM5, Geosci. Model Dev., 5, 709-739, doi:10.5194/gmd-5-709-2012, 2012.
21. Munro, N. P., Cairns, D. A., Clarke, P., Rogers, M., Stanley, A. J., Barrett, J. H., Harnden, P., Thompson, D., Eardley, I., Banks, R. E., and Knowles, M. A.: Urinary biomarker profiling in transitional cell carcinoma, Int. J. Cancer, 119, 2642-2650, 2006. (Pubitemid 44691320)
22. Nenes, A. and Seinfeld, J.: Parameterization of cloud dropletformation in global climate models, J. Geophys. Res., 108, 4415, doi:10.1029/2002JD002911, 2003.
23. Nissinen, A., Heikkinen, L., Kolehmainen, V., and Kaipio, J.: Compensation of errors due to discretization, domain truncation and unknown contact impedances in electrical impedance tomography, Meas. Sci. Technol., 20, 105504, doi:10.1088/0957- 0233/20/10/105504, 2009.
24. Nissinen, A., Kolehmainen, V., and Kaipio, J.: Compensation of modelling errors due to unknown domain boundary in electrical impedance tomography, IEEE T. Med. Imaging, 30, 231-242, 2011.
25. Pal, M.: Random Forest classifier for remote sensing classification, Int. J. Remote Sens., 26, 217-222, doi:10.1080/01431160412331269698, 2005. (Pubitemid 40198661)
26. Pedregosa, F., Varoquaux, G., Gramfort, A., Michel, V., Thirion, B., Grisel, O, Blondel, M., Prettenhofer, P., Weiss, R., Dubourg, V., Vanderplas, J., Passos, A., Cournapeau, D., Brucher, M., Perrot, M., and Duchesnay, E.: Scikit-learn: Machine Learning in Python, J. Mach. Learn. Res., 12, 2825-2830, 2011.
27. Rodriguez, M. and Dabdub, D. J.: IMAGES-SCAPE2: A modeling study of size and chemically resolved aerosol thermodynamics in a global chemical transport model, J. Geophys. Res., 109, D02203, doi:10.1029/2003JD003639, 2004.
28. Rojas, R.: Neural Networks: A Systematic Introduction, Springer- Verlag, Berlin, 1996.
29. Romakkaniemi, S., Kokkola, H., and Laaksonen, A.: Parameterization of the nitric acid effect on CCN activation, Atmos. Chem. Phys., 5, 879-885, doi:10.5194/acp-5-879-2005, 2005. (Pubitemid 40560467)
30. Romakkaniemi, S., Arola, A., Kokkola, H., Birmili, W., Tuch, T., Kerminen, V.-M., Rïsänen, P., Smith, J. N., Korhonen, H., and Laaksonen, A.: Effect of aerosol size distribution changes on AOD, CCN and cloud droplet concentration: Case studies from Erfurt and Melpitz, Germany, J. Geophys. Res., in press, doi:10.1029/2011JD017091, 2012.
31. Sorjamaa, R., Svenningsson, B., Raatikainen, T., Henning, S., Bilde, M., and Laaksonen, A.: The role of surfactants in Köhler theory reconsidered, Atmos. Chem. Phys., 4, 2107-2117, doi:10.5194/acp-4-2107-2004, 2004. (Pubitemid 40008486)
32. Tesfamariam, S. and Liu, Z.: Earthquake induced damage classification for reinforced concrete buildings, Struct. Saf., 32, 154-164, doi:10.1016/j. strusafe.2009.10.002, 2010.
33. Weisenstein, D. K., Penner, J. E., Herzog, M., and Liu, X.: Global 2- D intercomparison of sectional and modal aerosol modules, Atmos. Chem. Phys., 7, 2339-2355, doi:10.5194/acp-7-2339-2007, 2007. (Pubitemid 46737117)
34. Yao, D., Yang, J., and Zhan, X.: A novel method for disease prediction: hybrid of Random Forest and multivariate adaptive regression splines, J. Computers, 8, 170-177, doi:10.4304/jcp.8.1.170- 177, 2013.