Articles | Volume 14, issue 3
Geosci. Model Dev., 14, 1821–1839, 2021
https://doi.org/10.5194/gmd-14-1821-2021
Geosci. Model Dev., 14, 1821–1839, 2021
https://doi.org/10.5194/gmd-14-1821-2021

Development and technical paper 01 Apr 2021

Development and technical paper | 01 Apr 2021

Novel estimation of aerosol processes with particle size distribution measurements: a case study with the TOMAS algorithm v1.0.0

Dana L. McGuffin et al.

Data sets

Finland - Hyytiälä (FI0050R) - dmps - particle_number_size_distribution - aerosol P. Aalto and M. Kulmala http://ebas.nilu.no/DataSets.aspx?stations=FI0050R&InstrumentTypes=dmps&components=particle_number_size_distribution&fromDate=1970-01-01&toDate=2021-12-31

Germany - Melpitz (DE0044R) - dmps - particle_number_size_distribution - aerosol A. Sonntag, T. Tuch, B. Wehner, and A. Wiedensohler http://ebas.nilu.no/DataSets.aspx?stations=DE0044R&InstrumentTypes=dmps&components=particle_number_size_distribution&fromDate=2006-01-01&toDate=2007-12-31

MERRA-2 tavg1_2d_slv_Nx: 2d,1-Hourly,Time-Averaged,Single-Level,Assimilation,Single-Level Diagnostics V5.12.4 (M2T1NXSLV) Global Modeling and Assimilation Office (GMAO) https://doi.org/10.5067/VJAFPLI1CSIV

MERRA-2 tavg3_3d_asm_Nv: 3d,3-Hourly,Time-Averaged,Model-Level,Assimilation,Assimilated Meteorological Fields V5.12.4 (M2T3NVASM) Global Modeling and Assimilation Office (GMAO) https://doi.org/10.5067/SUOQESM06LPK

Executable research compendia (ERC)

TOMAS-InverseModel: First release used in GMD paper D. L. McGuffin https://doi.org/10.5281/ZENODO.4010877

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Short summary
Atmospheric particle formation, emissions, and growth process rates are significant sources of uncertainty in predicting climate change. We aim to reduce that uncertainty by using measurements from several ground-based sites across Europe. We developed an estimation technique to adapt the governing process rates so model–measurement bias decays. The estimation framework developed has potential to improve model predictions while providing insight into the underlying atmospheric particle physics.