TY - JOUR
T1 - Source-receptor matrix calculation for deposited mass with the Lagrangian particle dispersion model FLEXPART v10.2 in backward mode
AU - Eckhardt, Sabine
AU - Cassiani, Massimo
AU - Evangeliou, Nikolaos
AU - Sollum, Espen
AU - Pisso, Ignacio
AU - Stohl, Andreas
N1 - Funding Information:
Acknowledgements. The authors acknowledge S. J. Doherty for providing the database of snow BC observations described in Doherty et al. (2010). We thank Zbigniew Klimont and Chris Heyes at the International Institute for Applied System Analysis – IIASA for providing BC emissions from their GAINS model. ECMWF is acknowledged for meteorological data and Louis Giglio and Guido van der Werf for the GFED data. Computational and storage resources for FLEXPART simulations were provided by NOTUR (NN9419K) and NorStore (NS9419K). Funding was received as part of eSTICC-eScience Tools for Investigating Climate Change in northern high latitudes, which is supported by NordForsk Nordic Centre of Excellence grant 57001. Andreas Stohl and Massimo Cassiani were supported by the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme under grant agreement no. 670462 (COMTESSA).
PY - 2017/12/18
Y1 - 2017/12/18
N2 - Existing Lagrangian particle dispersion models are capable of establishing source-receptor relationships by running either forward or backward in time. For receptor-oriented studies such as interpretation of "point" measurement data, backward simulations can be computationally more efficient by several orders of magnitude. However, to date, the backward modelling capabilities have been limited to atmospheric concentrations or mixing ratios. In this paper, we extend the backward modelling technique to substances deposited at the Earth's surface by wet scavenging and dry deposition. This facilitates efficient calculation of emission sensitivities for deposition quantities at individual sites, which opens new application fields such as the comprehensive analysis of measured deposition quantities, or of deposition recorded in snow samples or ice cores. This could also include inverse modelling of emission sources based on such measurements. We have tested the new scheme as implemented in the Lagrangian particle dispersion model FLEXPART v10.2 by comparing results from forward and backward calculations. We also present an example application for black carbon concentrations recorded in Arctic snow.
AB - Existing Lagrangian particle dispersion models are capable of establishing source-receptor relationships by running either forward or backward in time. For receptor-oriented studies such as interpretation of "point" measurement data, backward simulations can be computationally more efficient by several orders of magnitude. However, to date, the backward modelling capabilities have been limited to atmospheric concentrations or mixing ratios. In this paper, we extend the backward modelling technique to substances deposited at the Earth's surface by wet scavenging and dry deposition. This facilitates efficient calculation of emission sensitivities for deposition quantities at individual sites, which opens new application fields such as the comprehensive analysis of measured deposition quantities, or of deposition recorded in snow samples or ice cores. This could also include inverse modelling of emission sources based on such measurements. We have tested the new scheme as implemented in the Lagrangian particle dispersion model FLEXPART v10.2 by comparing results from forward and backward calculations. We also present an example application for black carbon concentrations recorded in Arctic snow.
UR - https://www.scopus.com/pages/publications/85038821162
U2 - 10.5194/gmd-10-4605-2017
DO - 10.5194/gmd-10-4605-2017
M3 - Article
AN - SCOPUS:85038821162
SN - 1991-959X
VL - 10
SP - 4605
EP - 4618
JO - Geoscientific Model Development
JF - Geoscientific Model Development
IS - 12
ER -