Modeling impacts of dust mineralogy on fast climate response

Song, Qianqian; Ginoux, Paul; Gonçalves Ageitos, María; Miller, Ron L.; Obiso, Vincenzo; Pérez García-Pando, Carlos

doi:https://doi.org/10.5194/acp-24-7421-2024

Articles | Volume 24, issue 12

https://doi.org/10.5194/acp-24-7421-2024

© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.

https://doi.org/10.5194/acp-24-7421-2024

© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 24, issue 12

Research article

|

28 Jun 2024

Research article |

| 28 Jun 2024

Modeling impacts of dust mineralogy on fast climate response

Qianqian Song, Paul Ginoux, María Gonçalves Ageitos, Ron L. Miller, Vincenzo Obiso, and Carlos Pérez García-Pando

Supplement

https://doi.org/10.5194/acp-24-7421-2024-supplement

Data sets

Version 4 of the CRU TS monthly high-resolution gridded multivariate climate dataset (https://crudata.uea.ac.uk/cru/data/hrg/cru_ts_4.07/observation.v4.07/) I. Harris et al. https://doi.org/10.1038/s41597-020-0453-3

Model code and software

The GFDL Global Atmosphere and Land Model AM4.0/LM4.0: 1. Simulation Characteristics With Prescribed SSTs (https://github.com/NOAA-GFDL/AM4) M. Zhao et al. https://doi.org/10.1002/2017MS001208

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Short summary

We implement and simulate the distribution of eight dust minerals in the GFDL AM4.0 model. We found that resolving the eight minerals reduces dust absorption compared to the homogeneous dust used in the standard GFDL AM4.0 model that assumes a globally uniform hematite content of 2.7 % by volume. Resolving dust mineralogy results in significant impacts on radiation, land surface temperature, surface winds, and precipitation over North Africa in summer.