Universität zu Köln

Bocquet, M., Elbern, H., Eskes, H., Hirtl, M., Zabkar, R., Carmichael, G. R., Flemming, J., Inness, A., Pagowski, M., Perez Camano, J. L., Saide, P. E., San Jose, R., Sofiev, M., Vira, J., Baklanov, A., Carnevale, C., Grell, G. and Seigneur, C. (2015). Data assimilation in atmospheric chemistry models: current status and future prospects for coupled chemistry meteorology models. Atmos. Chem. Phys., 15 (10). S. 5325 - 5359. GOTTINGEN: COPERNICUS GESELLSCHAFT MBH. ISSN 1680-7324

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Abstract

Data assimilation is used in atmospheric chemistry models to improve air quality forecasts, construct re-analyses of three-dimensional chemical (including aerosol) concentrations and perform inverse modeling of input variables or model parameters (e.g., emissions). Coupled chemistry meteorology models (CCMM) are atmospheric chemistry models that simulate meteorological processes and chemical transformations jointly. They offer the possibility to assimilate both meteorological and chemical data; however, because CCMM are fairly recent, data assimilation in CCMM has been limited to date. We review here the current status of data assimilation in atmospheric chemistry models with a particular focus on future prospects for data assimilation in CCMM. We first review the methods available for data assimilation in atmospheric models, including variational methods, ensemble Kalman filters, and hybrid methods. Next, we review past applications that have included chemical data assimilation in chemical transport models (CTM) and in CCMM. Observational data sets available for chemical data assimilation are described, including surface data, surface-based remote sensing, airborne data, and satellite data. Several case studies of chemical data assimilation in CCMM are presented to highlight the benefits obtained by assimilating chemical data in CCMM. A case study of data assimilation to constrain emissions is also presented. There are few examples to date of joint meteorological and chemical data assimilation in CCMM and potential difficulties associated with data assimilation in CCMM are discussed. As the number of variables being assimilated increases, it is essential to characterize correctly the errors; in particular, the specification of error cross-correlations may be problematic. In some cases, offline diagnostics are necessary to ensure that data assimilation can truly improve model performance. However, the main challenge is likely to be the paucity of chemical data available for assimilation in CCMM.

Item Type:	Journal Article
Creators:	Creators Email ORCID ORCID Put Code Bocquet, M. UNSPECIFIED UNSPECIFIED UNSPECIFIED Elbern, H. UNSPECIFIED UNSPECIFIED UNSPECIFIED Eskes, H. UNSPECIFIED UNSPECIFIED UNSPECIFIED Hirtl, M. UNSPECIFIED UNSPECIFIED UNSPECIFIED Zabkar, R. UNSPECIFIED UNSPECIFIED UNSPECIFIED Carmichael, G. R. UNSPECIFIED UNSPECIFIED UNSPECIFIED Flemming, J. UNSPECIFIED UNSPECIFIED UNSPECIFIED Inness, A. UNSPECIFIED UNSPECIFIED UNSPECIFIED Pagowski, M. UNSPECIFIED UNSPECIFIED UNSPECIFIED Perez Camano, J. L. UNSPECIFIED UNSPECIFIED UNSPECIFIED Saide, P. E. UNSPECIFIED UNSPECIFIED UNSPECIFIED San Jose, R. UNSPECIFIED UNSPECIFIED UNSPECIFIED Sofiev, M. UNSPECIFIED UNSPECIFIED UNSPECIFIED Vira, J. UNSPECIFIED UNSPECIFIED UNSPECIFIED Baklanov, A. UNSPECIFIED UNSPECIFIED UNSPECIFIED Carnevale, C. UNSPECIFIED UNSPECIFIED UNSPECIFIED Grell, G. UNSPECIFIED UNSPECIFIED UNSPECIFIED Seigneur, C. UNSPECIFIED UNSPECIFIED UNSPECIFIED
URN:	urn:nbn:de:hbz:38-416477
DOI:	10.5194/acp-15-5325-2015
Journal or Publication Title:	Atmos. Chem. Phys.
Volume:	15
Number:	10
Page Range:	S. 5325 - 5359
Date:	2015
Publisher:	COPERNICUS GESELLSCHAFT MBH
Place of Publication:	GOTTINGEN
ISSN:	1680-7324
Language:	English
Faculty:	Unspecified
Divisions:	Unspecified
Subjects:	no entry
Uncontrolled Keywords:	Keywords Language ENSEMBLE KALMAN FILTER; VARIATIONAL DATA ASSIMILATION; AEROSOL OPTICAL DEPTH; CHEMICAL-DATA ASSIMILATION; UNDERGROUND RAILWAY STATION; AIR-QUALITY; PART I; OPTIMAL INTERPOLATION; TRANSPORT MODEL; OPERATIONAL IMPLEMENTATION Multiple languages Environmental Sciences; Meteorology & Atmospheric Sciences Multiple languages
URI:	http://kups.ub.uni-koeln.de/id/eprint/41647