We perform this regridding for data storage management and because we foresee applications of our algorithm for global climate models, which tend to have a resolution closer to 1° × 1°, (b) instead of limiting the integral between 900 hPa and 300 hPa, the flux is taken for the whole column, in order to leverage the integrated variables provided by MERRA-2, and capture the aerosols present below 900 hPa and above 300 hPa identified in Figures 3 and A2. This can have an impact over land near the surface where katabatic winds may affect the flux (Wille et al., 2019). As a result, our criterion variable becomes $vIxT$ as described by Equation 1. This $vIxT$ is a pre-computed quantity provided by MERRA-2 as an integrated meridional flux. (c) As a result of the two previous differences, our threshold is taken as the P97 of $vIxT$ instead of P98, in order to obtain similar climatologies as in Wille et al. (2019) as shown in Figure A11. (d) The climatology is updated and covers the period 1980–2022.

Our methodology for AR detection is slightly different from the Wille et al. (2019) algorithm, both in terms of input data, detection threshold, and implementation. Therefore a validation is carried out, comparing our results in terms of AR climatology and trends with those from the Wille et al. (2019) catalog. The detection catalog from Wille et al. (2019) covers the years 1980–2022 and is available through the ARTMIP database https://doi.org/10.5065/D62R3QFS (Rutz et al., 2019).

Figure A11 summarizes this comparison, with Figure A11a showing that, for the years 1980–2022, both methodologies yield similar magnitudes and spatial patterns in the frequency of AR detection both in the Arctic and the Antarctic, except for slightly stronger gradients in our detection. In the Arctic, maximum frequencies of around 1% are obtained over Greenland, coming from the Northwest Atlantic region, and in the Bering strait region, coming from the North Pacific, with an additional pathway over Western Russia. In the Antarctic, West Antarctica and the peninsula, along with Queen Maud Land feature a 1% maximum frequency detection in both catalogs. Furthermore, the underlying seasonality of ARs, aggregated by pole (50–80°N for the Arctic, 50–80°S for the Antarctic), is the same with both approaches, as described in Figure A11b, with monthly Pearson correlation coefficients of 0.99 and 0.96, for the Arctic and Antarctic, respectively, for the period 1980–2022. This seasonality is stronger in the Arctic with a maximum of detection in winter and a minimum in summer. A weaker seasonality with a maximum in austral winter is observed for the Antarctic.

In terms of trends, Figure A11c shows almost identical spatial patterns between the two catalogs. Both catalogs mainly show increasing trends in the regions where AR detection is climatologically most frequent, suggesting an amplification effect more than a change in physical processes. In the Arctic, the Bering strait region features the largest increasing trend with around 1 more AR day per decade. In the Antarctic, West Antarctica and Queen Maud land are the regions where this increasing trend is the most significant with also 1 more AR day per decade. Finally, Figure A11d describes this trend comparison in terms of regionally aggregated time series, showing very similar annual variations along with identical overall increasing trends over the 1980–2022 period.

In conclusion, despite slight methodological differences, the results given by our adapted polar AR detection scheme are very comparable to (Wille et al., 2019), and our detection leveraging vertically integrated variables provided by MERRA-2 is therefore fit for purpose and can be duplicated to aerosols.

Another parameter than the threshold percentile that could be tuned for p-AARs is the shape criterion imposing a minimum 20° extent in latitude. Aerosol sources, including anthropogenic activities and biomass burning, exist in North America and Siberia around 65°–70°N. Because of the 20°-latitude length criterion, p-AARs originating from these sources will not be accounted for unless they reach the pole. From an aerosol transport perspective this may seem like a limitation. However, we argue that, by design, p-AARs should generally detect extreme, long-range transport of background aerosols from the mid-latitudes, rather than relating to aerosol sources activity. In this respect, we believe it is relevant to keep the 20°-latitude length condition for aerosols as well, despite the implied rejection of high latitude sources that can be important for the Arctic aerosol budget. For the Antarctic, this criterion is not a problem since all aerosol sources (except sea salt) are further away than 20° in latitude.

### A3. Comparison Between p-AARs and AARs

In the atmospheric river community, it has been demonstrated that the use of non-polar specific methods have important limitations for the detection of water vapor transport extremes to the poles (Collow et al., 2022; Shields et al., 2022), which is what motivated the use of a polar-adapted detection method here. Therefore, the detection
method for p-AAR used in this work is different from the approach by Chakraborty et al. (2021, 2022) for AAR.
The main differences are summarized below:

* Chakraborty et al. (2021, 2022) use both zonal and meridional components, whereas our algorithm considers only the meridional component of the integrated transport. This choice is made following the findings from Wille et al. (2019, 2022) that for polar applications, the meridional wind speed component better reflects the dynamical processes that lead to precipitation generation, which is ultimately one of the important applications of this work.

* Chakraborty et al. (2021, 2022) use an aspect ratio criterion, which in our case is only a condition on latitudinal extent.

* Chakraborty et al. (2021, 2022) use a P85 detection threshold which is more permissive than our P97 threshold, which leads to a different event selection.

As a result of these methodological differences, the frequency of AAR detection is very different between our catalog and the one created by Chakraborty et al. (2021, 2022). Because they use a lower detection threshold (P85), and because both the meridional and zonal components are considered in their work, they detect more frequent AAR compared to our catalog. We have maximum frequencies of up to 8 BC and DU p-AAR days per year in the North Atlantic and North Pacific, where they obtain up to more than 40 BC or DU AAR days per year in these regions (Figure A12). Similarly, in the Antarctic 5 days per year is our maximum of detection frequency whereas they find up to 40 days per year of BC or DU AAR. In addition to different frequencies, the spatial patterns are also different.

Regarding two of the case studies presented in Section 3.2, the two approaches also result in different conclusions. The 2002 AP case does not appear as a DU AAR in Chakraborty et al. (2022), although a DU AAR is similarly detected between Australia and Antarctica (Figure A13). On the other hand, the 2013 Asia case shows many AARs (BC, DU and SS) detected on the day of the event in the Chakraborty et al. (2022) catalog, while our method shows one clear single event. The fact that these two events studied here, which had already been described as major transport events, were clearly detected as p-AARs and not so clearly as AARs proves that our classification makes sense and can be used for more systematic impact studies in polar regions.

### Acknowledgments

This project has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No 101003826 via project CRiceS (Climate Relevant interactions and feedbacks: the key role of sea ice and Snow in the polar and global climate system). VF and JW acknowledge support from the Agence Nationale de la Recherche project ANR-20CE01-0013 (ARCA). AE and PZ acknowledge the EU H2020 FORCeS project, contract No 821205. We acknowledge J. Schmale at École Polytechnique Fédérale de Lausanne and her team/collaborators who conducted the aerosol measurements during the international Multidisciplinary drifting Observatory for the Study of the Arctic Climate (MOSAiC). These data sets, already published in Dada et al. (2022), were used in this work for the validation of our methodology. We are grateful for their commitment to open data sharing, which advances scientific knowledge. RL, JT, JA and PZ acknowledge the course on "eScience Tools in Climate Science: Linking Observations with Modelling," which was held from 31 October to 11 November 2022 at Tjärnö Marine Laboratory, Sweden, and organized by Michael Schulz (MetNo, Norway) and Paul Zieger (SU, Sweden), for its inspiring atmosphere that contributed to some ideas of this work.

### Data Availability Statement

The detection catalogs for AR and p-AAR, based on MERRA-2 vertically integrated fluxes at 1° × 1° spatial resolution and covering the period 1980–2022, along with the processing and detection codes, are available at https://doi.org/10.5281/zenodo.8082768 (Lapere, 2023).

### References

* Abbatt, J. P. D., Leaitch, W. R., Aliabadi, A. A., Bertram, A. K., Blanchet, J.-P., Boivin-Rioux, A., et al. (2019). Overview paper: New insights into aerosol and climate in the Arctic. *Atmospheric Chemistry and Physics*, 19(4), 2527–2560. https://doi.org/10.5194/acp-19-2527-2019

* Acosta Navarro, J. C., Varma, V., Riipinen, I., Seland, Ø., Kirkevåg, A., Struthers, H., et al. (2016). Amplification of arctic warming by past air pollution reductions in Europe. *Nature Geoscience*, 9(4), 277–281. https://doi.org/10.1038/ngeo2673

* Adusumilli, S., Fish, M. A., Fricker, H. A., & Medley, B. (2021). Atmospheric river precipitation contributed to rapid increases in surface height of the west Antarctic ice sheet in 2019. *Geophysical Research Letters*, 48(5), e2020GL091076. https://doi.org/10.1029/2020GL091076

* AMAP. (2021). *AMAP assessment 2021: Impacts of short-lived climate forcers on arctic climate, air quality, and human health (Tech. Rep.).* Arctic Monitoring and Assessment Programme (AMAP).

* Amino, T., Iizuka, Y., Matoba, S., Shimada, R., Oshima, N., Suzuki, T., et al. (2021). Increasing dust emission from ice free terrain in southeastern Greenland since 2000. *Polar Science*, 27, 100599. https://doi.org/10.1016/j.polar.2020.100599

* Backman, J., Schmeisser, L., & Asmi, E. (2021). Asian emissions explain much of the arctic black carbon events. *Geophysical Research Letters*, 48(5), e2020GL091913. https://doi.org/10.1029/2020GL091913

* Barrie, L. A. (1986). Arctic air pollution: An overview of current knowledge. *Atmospheric Environment*, 20(4), 643–663. https://doi.org/10.1016/0004-6981(86)90180-0

* Bintanja, R., van der Wiel, K., van der Linden, E. C., Reusen, J., Bogerd, L., Krikken, F., & Selten, F. M. (2020). Strong future increases in Arctic precipitation variability linked to poleward moisture transport. *Science Advances*, 6(7), eaax6869. https://doi.org/10.1126/sciadv.aax6869

* Bond, T. C., Doherty, S. J., Fahey, D. W., Forster, P. M., Berntsen, T., DeAngelo, B. J., et al. (2013). Bounding the role of black carbon in the climate system: A scientific assessment. *Journal of Geophysical Research: Atmospheres*, 118(11), 5380–5552. https://doi.org/10.1002/jgrd.50171

* Böö, S., Ekman, A. M. L., Svensson, G., & Devasthale, A. (2023). Transport of mineral dust into the arctic in two reanalysis datasets of atmospheric composition. *Tellus B: Chemical and Physical Meteorology*, 75(1), 13–32. https://doi.org/10.16993/tellusb.1866
method for p-AAR used in this work is different from the approach by Chakraborty et al. (2021, 2022) for AAR.
The main differences are summarized below:

* Chakraborty et al. (2021, 2022) use both zonal and meridional components, whereas our algorithm considers only the meridional component of the integrated transport. This choice is made following the findings from Wille et al. (2019, 2022) that for polar applications, the meridional wind speed component better reflects the dynamical processes that lead to precipitation generation, which is ultimately one of the important applications of this work.

* Chakraborty et al. (2021, 2022) use an aspect ratio criterion, which in our case is only a condition on latitudinal extent.

* Chakraborty et al. (2021, 2022) use a P85 detection threshold which is more permissive than our P97 threshold, which leads to a different event selection.

As a result of these methodological differences, the frequency of AAR detection is very different between our catalog and the one created by Chakraborty et al. (2021, 2022). Because they use a lower detection threshold (P85), and because both the meridional and zonal components are considered in their work, they detect more frequent AAR compared to our catalog. We have maximum frequencies of up to 8 BC and DU p-AAR days per year in the North Atlantic and North Pacific, where they obtain up to more than 40 BC or DU AAR days per year in these regions (Figure A12). Similarly, in the Antarctic 5 days per year is our maximum of detection frequency whereas they find up to 40 days per year of BC or DU AAR. In addition to different frequencies, the spatial patterns are also different.

Regarding two of the case studies presented in Section 3.2, the two approaches also result in different conclusions. The 2002 AP case does not appear as a DU AAR in Chakraborty et al. (2022), although a DU AAR is similarly detected between Australia and Antarctica (Figure A13). On the other hand, the 2013 Asia case shows many AARs (BC, DU and SS) detected on the day of the event in the Chakraborty et al. (2022) catalog, while our method shows one clear single event. The fact that these two events studied here, which had already been described as major transport events, were clearly detected as p-AARs and not so clearly as AARs proves that our classification makes sense and can be used for more systematic impact studies in polar regions.

### Acknowledgments

This project has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No 101003826 via project CRiceS (Climate Relevant interactions and feedbacks: the key role of sea ice and Snow in the polar and global climate system). VF and JW acknowledge support from the Agence Nationale de la Recherche project ANR-20CE01-0013 (ARCA). AE and PZ acknowledge the EU H2020 FORCeS project, contract No 821205. We acknowledge J. Schmale at École Polytechnique Fédérale de Lausanne and her team/collaborators who conducted the aerosol measurements during the international Multidisciplinary drifting Observatory for the Study of the Arctic Climate (MOSAiC). These data sets, already published in Dada et al. (2022), were used in this work for the validation of our methodology. We are grateful for their commitment to open data sharing, which advances scientific knowledge. RL, JT, JA and PZ acknowledge the course on "eScience Tools in Climate Science: Linking Observations with Modelling," which was held from 31 October to 11 November 2022 at Tjärnö Marine Laboratory, Sweden, and organized by Michael Schulz (MetNo, Norway) and Paul Zieger (SU, Sweden), for its inspiring atmosphere that contributed to some ideas of this work.

### Data Availability Statement

The detection catalogs for AR and p-AAR, based on MERRA-2 vertically integrated fluxes at 1° × 1° spatial resolution and covering the period 1980–2022, along with the processing and detection codes, are available at https://doi.org/10.5281/zenodo.8082768 (Lapere, 2023).

### References

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* Acosta Navarro, J. C., Varma, V., Riipinen, I., Seland, Ø., Kirkevåg, A., Struthers, H., et al. (2016). Amplification of arctic warming by past air pollution reductions in Europe. *Nature Geoscience*, 9(4), 277–281. https://doi.org/10.1038/ngeo2673

* Adusumilli, S., Fish, M. A., Fricker, H. A., & Medley, B. (2021). Atmospheric river precipitation contributed to rapid increases in surface height of the west Antarctic ice sheet in 2019. *Geophysical Research Letters*, 48(5), e2020GL091076. https://doi.org/10.1029/2020GL091076

* AMAP. (2021). *AMAP assessment 2021: Impacts of short-lived climate forcers on arctic climate, air quality, and human health (Tech. Rep.).* Arctic Monitoring and Assessment Programme (AMAP).

* Amino, T., Iizuka, Y., Matoba, S., Shimada, R., Oshima, N., Suzuki, T., et al. (2021). Increasing dust emission from ice free terrain in southeastern Greenland since 2000. *Polar Science*, 27, 100599. https://doi.org/10.1016/j.polar.2020.100599

* Backman, J., Schmeisser, L., & Asmi, E. (2021). Asian emissions explain much of the arctic black carbon events. *Geophysical Research Letters*, 48(5), e2020GL091913. https://doi.org/10.1029/2020GL091913

* Barrie, L. A. (1986). Arctic air pollution: An overview of current knowledge. *Atmospheric Environment*, 20(4), 643–663. https://doi.org/10.1016/0004-6981(86)90180-0

* Bintanja, R., van der Wiel, K., van der Linden, E. C., Reusen, J., Bogerd, L., Krikken, F., & Selten, F. M. (2020). Strong future increases in Arctic precipitation variability linked to poleward moisture transport. *Science Advances*, 6(7), eaax6869. https://doi.org/10.1126/sciadv.aax6869

* Bond, T. C., Doherty, S. J., Fahey, D. W., Forster, P. M., Berntsen, T., DeAngelo, B. J., et al. (2013). Bounding the role of black carbon in the climate system: A scientific assessment. *Journal of Geophysical Research: Atmospheres*, 118(11), 5380–5552. https://doi.org/10.1002/jgrd.50171

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Boyer, M., Aliaga, D., Pernov, J. B., Angot, H., Quéléver, L. L. J., Dada, L., et al. (2023). A full year of aerosol size distribution data from the central Arctic under an extreme positive Arctic Oscillation: Insights from the Multidisciplinary Drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition. *Atmospheric Chemistry and Physics*, 23(1), 389–415. https://doi.org/10.5194/acp-23-389-2023

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Bullard, J. E., Baddock, M., Bradwell, T., Crusius, J., Darlington, E., Gaiero, D., et al. (2016). High-latitude dust in the Earth system. *Reviews of Geophysics*, 54(2), 447–485. https://doi.org/10.1002/2016RG000518

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Jumelet, J., Klekociuk, A. R., Alexander, S. P., Bekki, S., Hauchecorne, A., Vernier, J. P., et al. (2020). Detection of aerosols in Antarctica from long-range transport of the 2009 Australian wildfires. *Journal of Geophysical Research: Atmospheres*, 125(23), e2020JD032542. https://doi.org/10.1029/2020JD032542

Kawai, K., Matsui, H., & Tobo, Y. (2023). Dominant role of arctic dust with high ice nucleating ability in the arctic lower troposphere. *Geophysical Research Letters*, 50(8), e2022GL102470. https://doi.org/10.1029/2022GL102470

Kirpes, R. M., Bonanno, D., May, N. W., Fraund, M., Barget, A. J., Moffet, R. C., et al. (2019). Wintertime Arctic sea spray aerosol composition controlled by sea ice lead microbiology. *ACS Central Science*, 5(11), 1760–1767. https://doi.org/10.1021/acscentsci.9b00541

Kluyver, T., Ragan-Kelley, B., Pérez, F., Granger, B., Bussonnier, M., Frederic, J., et al. (2016). Jupyter notebooks – A publishing format for reproducible computational workflows. In F. Loizides & B. Schmidt (Eds.), *Positioning and power in academic publishing: Players, agents and agendas* (pp. 87–90).

Komatsu, K. K., Alexeev, V. A., Repina, I. A., & Tachibana, Y. (2018). Poleward upgliding Siberian atmospheric rivers over sea ice heat up Arctic upper air. *Scientific Reports*, 8(1), 2872. https://doi.org/10.1038/s41598-018-21159-6

Krinner, G., & Genthon, C. (2003). Tropospheric transport of continental tracers towards Antarctica under varying climatic conditions. *Tellus B: Chemical and Physical Meteorology*, 55(1), 54–70. https://doi.org/10.1034/j.1600-0889.2003.00004.x

Krinner, G., & Werner, M. (2003). Impact of precipitation seasonality changes on isotopic signals in polar ice cores: A multi-model analysis. *Earth and Planetary Science Letters*, 216(4), 525–538. https://doi.org/10.1016/S0012-821X(03)00550-8

Lachlan-Cope, T. (2010). Antarctic clouds. *Polar Research*, 29(2), 150–158. https://doi.org/10.3402/polar.v29i2.6065

Lapere, R. (2023). Polar atmospheric and aerosol river detection catalogs [Dataset/Software]. Zenodo. https://doi.org/10.5281/zenodo.8082768

Lapere, R., Thomas, J. L., Marelle, L., Ekman, A. M. L., Frey, M. M., Lund, M. T., et al. (2023). The representation of sea salt aerosols and their role in polar climate within CMIP6. *Journal of Geophysical Research: Atmospheres*, 128(6), e2022JD038235. https://doi.org/10.1029/2022JD038235

Lavers, D. A., Villarini, G., Allan, R. P., Wood, E. F., & Wade, A. J. (2012). The detection of atmospheric rivers in atmospheric reanalyses and their links to British winter floods and the large-scale climatic circulation. *Journal of Geophysical Research*, 117, D20. https://doi.org/10.1029/2012JD018027

Lenaerts, J. T. M., Medley, B., van den Broeke, M. R., & Wouters, B. (2019). Observing and modeling ice sheet surface mass balance. *Reviews of Geophysics*, 57(2), 376–420. https://doi.org/10.1029/2018RG000622

Levine, J. G., Yang, X., Jones, A. E., & Wolff, E. W. (2014). Sea salt as an ice core proxy for past sea ice extent: A process-based model study. *Journal of Geophysical Research: Atmospheres*, 119(9), 5737–5756. https://doi.org/10.1002/2013JD020925

Li, F., Ginoux, P., & Ramaswamy, V. (2008). Distribution, transport, and deposition of mineral dust in the southern ocean and Antarctica: Contribution of major sources. *Journal of Geophysical Research*, 113(D10). https://doi.org/10.1029/2007JD009190

Maclennan, M. L., & Lenaerts, J. T. M. (2021). Large-scale atmospheric drivers of snowfall over Thwaites glacier, Antarctica. *Geophysical Research Letters*, 48(17), e2021GL093644. https://doi.org/10.1029/2021GL093644

Maclennan, M. L., Lenaerts, J. T. M., Shields, C. A., Hoffman, A. O., Wever, N., Thompson-Munson, M., et al. (2023). Climatology and surface impacts of atmospheric rivers on West Antarctica. *The Cryosphere*, 17(2), 865–881. https://doi.org/10.5194/tc-17-865-2023

Marelle, L., Raut, J.-C., Law, K. S., & Duclaux, O. (2018). Current and future arctic aerosols and ozone from remote emissions and emerging local sources—Modeled source contributions and radiative effects. *Journal of Geophysical Research: Atmospheres*, 123(22), 12942–12963. https://doi.org/10.1029/2018JD028863

Mattingly, K. S., Mote, T. L., & Fettweis, X. (2018). Atmospheric river impacts on Greenland ice sheet surface mass balance. *Journal of Geophysical Research: Atmospheres*, 123(16), 8538–8560. https://doi.org/10.1029/2018JD028714

Matus, A. V., & L'Ecuyer, T. S. (2017). The role of cloud phase in Earth's radiation budget. *Journal of Geophysical Research: Atmospheres*, 122(5), 2559–2578. https://doi.org/10.1002/2016JD025951

Mei, L., Xue, Y., de Leeuw, G., von Hoyningen-Huene, W., Kokhanovsky, A. A., Istomina, L., et al. (2013). Aerosol optical depth retrieval in the Arctic region using MODIS data over snow. *Remote Sensing of Environment*, 128, 234–245. https://doi.org/10.1016/j.rse.2012.10.009

Meinander, O., Dagsson-Waldhauserova, P., Amosov, P., Aseyeva, E., Atkins, C., Baklanov, A., et al. (2022). Newly identified climatically and environmentally significant high-latitude dust sources. *Atmospheric Chemistry and Physics*, 22(17), 11889–11930. https://doi.org/10.5194/acp-22-11889-2022

Moseid, K. O., Schulz, M., Eichler, A., Schwikowski, M., McConnell, J. R., Olivié, D., et al. (2022). Using ice cores to evaluate CMIP6 aerosol concentrations over the historical era. *Journal of Geophysical Research: Atmospheres*, 127(18), e2021JD036105. https://doi.org/10.1029/2021JD036105

Murray, B. J., Carslaw, K. S., & Field, P. R. (2021). Opinion: Cloud-phase climate feedback and the importance of ice-nucleating particles. *Atmospheric Chemistry and Physics*, 21(2), 665–679. https://doi.org/10.5194/acp-21-665-2021

Murray, B. J., O'Sullivan, D., Atkinson, J. D., & Webb, M. E. (2012). Ice nucleation by particles immersed in supercooled cloud droplets. *Chemical Society Reviews*, 41(19), 6519–6554. https://doi.org/10.1039/C2CS35200A

Myhre, G., Shindell, D., Bréon, F.-M., Collins, W., Fuglestvedt, J., Huang, J., et al. (2013). In T. F. Stocker, D. Qin, G.-K. Plattner, M. Tignor, S. K. Allen, J. Boschung, et al. (Eds.), *Climate change 2013: The physical science basis. Contribution of working Group I to the fifth assessment report of the intergovernmental panel on climate change, In (chap. Anthropogenic and natural radiative forcing)*. Cambridge University Press.

NASA. (2013). EOSDIS Worldview. Retrieved from https://worldview.earthdata.nasa.gov/

Nash, D., Waliser, D., Guan, B., Ye, H., & Ralph, F. M. (2018). The role of atmospheric rivers in extratropical and polar hydroclimate. *Journal of Geophysical Research: Atmospheres*, 123(13), 6804–6821. https://doi.org/10.1029/2017JD028130

Neff, P. D., & Bertler, N. A. N. (2015). Trajectory modeling of modern dust transport to the southern ocean and Antarctica. *Journal of Geophysical Research: Atmospheres*, 120(18), 9303–9322. https://doi.org/10.1002/2015JD023304

Neiman, P. J., Ralph, F. M., Moore, B. J., Hughes, M., Mahoney, K. M., Cordeira, J. M., & Dettinger, M. D. (2013). The landfall and inland penetration of a flood-producing atmospheric river in Arizona. Part I: Observed synoptic-scale, orographic, and hydrometeorological characteristics. *Journal of Hydrometeorology*, 14(2), 460–484. https://doi.org/10.1175/JHM-D-12-0101.1
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O'Brien, T. A., Wehner, M. F., Payne, A. E., Shields, C. A., Rutz, J. J., Leung, L.-R., et al. (2022). Increases in future AR count and size: Overview of the ARTMIP Tier 2 CMIP5/6 experiment. *Journal of Geophysical Research: Atmospheres*, 127(6), e2021JD036013. https://doi.org/10.1029/2021JD036013

Papritz, L., Hauswirth, D., & Hartmuth, K. (2022). Moisture origin, transport pathways, and driving processes of intense wintertime moisture transport into the Arctic. *Weather and Climate Dynamics*, 3, 1–20. https://doi.org/10.5194/wcd-3-1-2022

Pernov, J. B., Beddows, D., Thomas, D. C., Dall'Osto, M., Harrison, R. M., Schmale, J., et al. (2022). Increased aerosol concentrations in the High Arctic attributable to changing atmospheric transport patterns. *npj Climate and Atmospheric Science*, 5(1), 1–13. https://doi.org/10.1038/s41612-022-00286-y

Pithan, F., Svensson, G., Caballero, R., Chechin, D., Cronin, T. W., Ekman, A. M. L., et al. (2018). Role of air-mass transformations in exchange between the Arctic and mid-latitudes. *Nature Geoscience*, 11(11), 805–812. https://doi.org/10.1038/s41561-018-0234-1

Pohl, B., Favier, V., Wille, J., Udy, D. G., Vance, T. R., Pergaud, J., et al. (2021). Relationship between weather regimes and atmospheric Rivers in East Antarctica. *Journal of Geophysical Research: Atmospheres*, 126(24), e2021JD035294. https://doi.org/10.1029/2021JD035294

Quinn, P. K., Shaw, G., Andrews, E., Dutton, E. G., Ruoho-Airola, T., & Gong, S. L. (2007). Arctic haze: Current trends and knowledge gaps. *Tellus B: Chemical and Physical Meteorology*, 59(1), 99–114. https://doi.org/10.1111/j.1600-0889.2006.00238.x

Quinn, P. K., Stohl, A., Arneth, A., Berntsen, T., Burkhart, J. F., Christensen, J., et al. (2011). The impact of black carbon on arctic climate. *Arctic Monitoring and Assessment Programme (AMAP)*.

Ralph, F. M., Rutz, J. J., Cordeira, J. M., Dettinger, M., Anderson, M., Reynolds, D., et al. (2019). A scale to characterize the strength and impacts of atmospheric rivers. *Bulletin of the American Meteorological Society*, 100(2), 269–289. https://doi.org/10.1175/BAMS-D-18-0023.1

Randles, C. A., Da Silva, A. M., Buchard, V., Colarco, P. R., Darmenov, A., Govindaraju, R., et al. (2017). The MERRA-2 aerosol reanalysis, 1980–Onward, Part I: System description and data assimilation evaluation. *Journal of Climate*, 30(17), 6823–6850. https://doi.org/10.1175/JCLI-D-16-0609.1

Rantanen, M., Karpechko, A. Y., Lipponen, A., Nordling, K., Hyvärinen, O., Ruosteenoja, K., et al. (2022). The Arctic has warmed nearly four times faster than the globe since 1979. *Communications Earth & Environment*, 3, 1–10. https://doi.org/10.1038/s43247-022-00498-3

Raut, J.-C., Marelle, L., Fast, J. D., Thomas, J. L., Weinzierl, B., Law, K. S., et al. (2017). Cross-polar transport and scavenging of Siberian aerosols containing black carbon during the 2012 ACCESS summer campaign. *Atmospheric Chemistry and Physics*, 17(18), 10969–10995. https://doi.org/10.5194/acp-17-10969-2017

Rhodes, R. H., Yang, X., & Wolff, E. W. (2018). Sea ice versus storms: What controls sea salt in arctic ice cores? *Geophysical Research Letters*, 45(11), 5572–5580. https://doi.org/10.1029/2018GL077403

Rinke, A., Segger, B., Crewell, S., Maturilli, M., Naakka, T., Nygård, T., et al. (2019). Trends of vertically integrated water vapor over the arctic during 1979–2016: Consistent moistening all over? *Journal of Climate*, 32(18), 6097–6116. https://doi.org/10.1175/JCLI-D-19-0092.1

Roiger, A., Schlager, H., Schäfler, A., Huntrieser, H., Scheibe, M., Aufmhoff, H., et al. (2011). In-situ observation of Asian pollution transported into the Arctic lowermost stratosphere. *Atmospheric Chemistry and Physics*, 11(21), 10975–10994. https://doi.org/10.5194/acp-11-10975-2011

Roiger, A., Thomas, J.-L., Schlager, H., Law, K. S., Kim, J., Schäfler, A., et al. (2015). Quantifying emerging local anthropogenic emissions in the arctic region: The ACCESS aircraft campaign experiment. *Bulletin of the American Meteorological Society*, 96(3), 441–460. https://doi.org/10.1175/BAMS-D-13-00169.1

Rutz, J. J., Shields, C. A., Lora, J. M., Payne, A. E., Guan, B., Ullrich, P. A., et al. (2019). Artmip tier-1 catalogues [Dataset]. UCAR. https://doi.org/10.5065/D62R3QFS

Schmale, J., Zieger, P., & Ekman, A. M. L. (2021). Aerosols in current and future Arctic climate. *Nature Climate Change*, 11(2), 95–105. https://doi.org/10.1038/s41558-020-00969-5

Servettaz, A. P. M., Orsi, A. J., Curran, M. A. J., Moy, A. D., Landais, A., McConnell, J. R., et al. (2023). A 2000-year temperature reconstruction on the East Antarctic plateau from argon–nitrogen and water stable isotopes in the Aurora Basin North ice core. *Climate of the Past*, 19(6), 1125–1152. https://doi.org/10.5194/cp-19-1125-2023

Shi, Y., Liu, X., Wu, M., Zhao, X., Ke, Z., & Brown, H. (2022). Relative importance of high-latitude local and long-range-transported dust for Arctic ice-nucleating particles and impacts on Arctic mixed-phase clouds. *Atmospheric Chemistry and Physics*, 22(4), 2909–2935. https://doi.org/10.5194/acp-22-2909-2022

Shields, C. A., Payne, A. E., Shearer, E. J., Wehner, M. F., O'Brien, T. A., Rutz, J. J., et al. (2023). Future atmospheric rivers and impacts on precipitation: Overview of the ARTMIP tier 2 high-resolution global warming experiment. *Geophysical Research Letters*, 50(6), e2022GL0102091. https://doi.org/10.1029/2022GL0102091

Shields, C. A., Rosenbloom, N., Bates, S., Hannay, C., Hu, A., Payne, A. E., et al. (2019). Meridional heat transport during atmospheric rivers in high-resolution CESM climate projections. *Geophysical Research Letters*, 46(24), 14702–14712. https://doi.org/10.1029/2019GL085565

Shields, C. A., Rutz, J. J., Leung, L.-Y., Ralph, F. M., Wehner, M., Kawzenuk, B., et al. (2018). Atmospheric river tracking method intercomparison project (ARTMIP): Project goals and experimental design. *Geoscientific Model Development*, 11(6), 2455–2474. https://doi.org/10.5194/gmd-11-2455-2018

Shields, C. A., Wille, J. D., Marquardt Collow, A. B., Maclennan, M., & Gorodetskaya, I. V. (2022). Evaluating uncertainty and modes of variability for Antarctic atmospheric rivers. *Geophysical Research Letters*, 49(16), e2022GL099577. https://doi.org/10.1029/2022GL099577

Shupe, M. D., Rex, M., Blomquist, B., Persson, P. O. G., Schmale, J., Uttal, T., et al., (2022). Overview of the MOSAiC expedition: Atmosphere. *Elementa: Science of the Anthropocene*, 10(1), 00060. https://doi.org/10.1525/elementa.2021.00060

Skiles, S. M., Flanner, M., Cook, J. M., Dumont, M., & Painter, T. H. (2018). Radiative forcing by light-absorbing particles in snow. *Nature Climate Change*, 8(11), 964–971. https://doi.org/10.1038/s41558-018-0296-5

Sodemann, H., Pommier, M., Arnold, S. R., Monks, S. A., Stebel, K., Burkhart, J. F., et al. (2011). Episodes of cross-polar transport in the Arctic troposphere during July 2008 as seen from models, satellite, and aircraft observations. *Atmospheric Chemistry and Physics*, 11(8), 3631–3651. https://doi.org/10.5194/acp-11-3631-2011

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Tan, I., & Storelvmo, T. (2019). Evidence of strong contributions from mixed-phase clouds to arctic climate change. *Geophysical Research Letters*, 46(5), 2894–2902. https://doi.org/10.1029/2018GL081871
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O'Brien, T. A., Wehner, M. F., Payne, A. E., Shields, C. A., Rutz, J. J., Leung, L.-R., et al. (2022). Increases in future AR count and size: Overview of the ARTMIP Tier 2 CMIP5/6 experiment. *Journal of Geophysical Research: Atmospheres*, 127(6), e2021JD036013. https://doi.org/10.1029/2021JD036013

Papritz, L., Hauswirth, D., & Hartmuth, K. (2022). Moisture origin, transport pathways, and driving processes of intense wintertime moisture transport into the Arctic. *Weather and Climate Dynamics*, 3, 1–20. https://doi.org/10.5194/wcd-3-1-2022

Pernov, J. B., Beddows, D., Thomas, D. C., Dall'Osto, M., Harrison, R. M., Schmale, J., et al. (2022). Increased aerosol concentrations in the High Arctic attributable to changing atmospheric transport patterns. *npj Climate and Atmospheric Science*, 5(1), 1–13. https://doi.org/10.1038/s41612-022-00286-y

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Ralph, F. M., Rutz, J. J., Cordeira, J. M., Dettinger, M., Anderson, M., Reynolds, D., et al. (2019). A scale to characterize the strength and impacts of atmospheric rivers. *Bulletin of the American Meteorological Society*, 100(2), 269–289. https://doi.org/10.1175/BAMS-D-18-0023.1

Randles, C. A., Da Silva, A. M., Buchard, V., Colarco, P. R., Darmenov, A., Govindaraju, R., et al. (2017). The MERRA-2 aerosol reanalysis, 1980–Onward, Part I: System description and data assimilation evaluation. *Journal of Climate*, 30(17), 6823–6850. https://doi.org/10.1175/JCLI-D-16-0609.1

Rantanen, M., Karpechko, A. Y., Lipponen, A., Nordling, K., Hyvärinen, O., Ruosteenoja, K., et al. (2022). The Arctic has warmed nearly four times faster than the globe since 1979. *Communications Earth & Environment*, 3, 1–10. https://doi.org/10.1038/s43247-022-00498-3

Raut, J.-C., Marelle, L., Fast, J. D., Thomas, J. L., Weinzierl, B., Law, K. S., et al. (2017). Cross-polar transport and scavenging of Siberian aerosols containing black carbon during the 2012 ACCESS summer campaign. *Atmospheric Chemistry and Physics*, 17(18), 10969–10995. https://doi.org/10.5194/acp-17-10969-2017

Rhodes, R. H., Yang, X., & Wolff, E. W. (2018). Sea ice versus storms: What controls sea salt in arctic ice cores? *Geophysical Research Letters*, 45(11), 5572–5580. https://doi.org/10.1029/2018GL077403

Rinke, A., Segger, B., Crewell, S., Maturilli, M., Naakka, T., Nygård, T., et al. (2019). Trends of vertically integrated water vapor over the arctic during 1979–2016: Consistent moistening all over? *Journal of Climate*, 32(18), 6097–6116. https://doi.org/10.1175/JCLI-D-19-0092.1

Roiger, A., Schlager, H., Schäfler, A., Huntrieser, H., Scheibe, M., Aufmhoff, H., et al. (2011). In-situ observation of Asian pollution transported into the Arctic lowermost stratosphere. *Atmospheric Chemistry and Physics*, 11(21), 10975–10994. https://doi.org/10.5194/acp-11-10975-2011

Roiger, A., Thomas, J.-L., Schlager, H., Law, K. S., Kim, J., Schäfler, A., et al. (2015). Quantifying emerging local anthropogenic emissions in the arctic region: The ACCESS aircraft campaign experiment. *Bulletin of the American Meteorological Society*, 96(3), 441–460. https://doi.org/10.1175/BAMS-D-13-00169.1

Rutz, J. J., Shields, C. A., Lora, J. M., Payne, A. E., Guan, B., Ullrich, P. A., et al. (2019). Artmip tier-1 catalogues [Dataset]. UCAR. https://doi.org/10.5065/D62R3QFS

Schmale, J., Zieger, P., & Ekman, A. M. L. (2021). Aerosols in current and future Arctic climate. *Nature Climate Change*, 11(2), 95–105. https://doi.org/10.1038/s41558-020-00969-5

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Shi, Y., Liu, X., Wu, M., Zhao, X., Ke, Z., & Brown, H. (2022). Relative importance of high-latitude local and long-range-transported dust for Arctic ice-nucleating particles and impacts on Arctic mixed-phase clouds. *Atmospheric Chemistry and Physics*, 22(4), 2909–2935. https://doi.org/10.5194/acp-22-2909-2022

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Shields, C. A., Rosenbloom, N., Bates, S., Hannay, C., Hu, A., Payne, A. E., et al. (2019). Meridional heat transport during atmospheric rivers in high-resolution CESM climate projections. *Geophysical Research Letters*, 46(24), 14702–14712. https://doi.org/10.1029/2019GL085565

Shields, C. A., Rutz, J. J., Leung, L.-Y., Ralph, F. M., Wehner, M., Kawzenuk, B., et al. (2018). Atmospheric river tracking method intercomparison project (ARTMIP): Project goals and experimental design. *Geoscientific Model Development*, 11(6), 2455–2474. https://doi.org/10.5194/gmd-11-2455-2018

Shields, C. A., Wille, J. D., Marquardt Collow, A. B., Maclennan, M., & Gorodetskaya, I. V. (2022). Evaluating uncertainty and modes of variability for Antarctic atmospheric rivers. *Geophysical Research Letters*, 49(16), e2022GL099577. https://doi.org/10.1029/2022GL099577

Shupe, M. D., Rex, M., Blomquist, B., Persson, P. O. G., Schmale, J., Uttal, T., et al., (2022). Overview of the MOSAiC expedition: Atmosphere. *Elementa: Science of the Anthropocene*, 10(1), 00060. https://doi.org/10.1525/elementa.2021.00060

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