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Liu, L., Cheng, Y., Wang, S., Wei, C., Pöhlker, M., Pöhlker, C., Artaxo, P., Shrivastava, M., Andreae, M. O., Pöschl, U. und Su, H.: Impact of biomass burning aerosols on radiation, clouds, and precipitation over the Amazon during the dry season: dependence of aerosol-cloud and aerosol-radiation interactions on aerosol loading, Atmospheric Chemistry and Physics Discussions, 20, doi:10.5194/acp-2020-191, 2020.

Brockmann, D., Dreier, H., Feld, L., Fiedler, K., Friedrich, B., Fuest, C., Gumbsch, P., Hasselhorn, M., Haug, G. H., Kocka, J., Köller, O., Krieg, T., Kroemer, H., Lengauer, T., Margraf, J., Markschies, C., Marquardt, W., Mayer, K. U., Merkel, R., Mettenleiter, T., Nassehi, A., Prenzel, M., Renn, J., Rösler, F., Schlögl, R. und Wiesemann, C.: Coronavirus-Pandemie — Die Krise nachhaltig überwinden, [online] Available from: http://hdl.handle.net/21.11116/0000-0009-50C9-A, 2020.

Pinardi, G., Van Roozendael, M., Hendrick, F., Theys, N., Abuhassan, N., Bais, A., Boersma, F., Cede, A., Chong, J., Donner, S., Drosoglou, T., Frieß, U., Granville, J., Herman, J. R., Eskes, H., Holla, R., Hovila, J., Irie, H., Kanaya, Y., Karagkiozidis, D., Kouremeti, N., Lambert, J.-C., Ma, J., Peters, E., Piters, A., Postylyakov, O., Richter, A., Remmers, J., Takashima, H., Tiefengraber , M., Valks, P., Vlemmix, T., Wagner, T. und Wittrock , F.: Validation of tropospheric NO₂ column measurements of GOME-2A and OMI using MAX-DOAS and direct sun network observations, Atmospheric Measurement Techniques Discussions, 13, doi:10.5194/amt-2020-76, 2020.

Singh, J., Singh, N., Ojha, N., Sharma, A., Pozzer, A., Kumar, N. K., Rajeev, K., Gunthe, S. S. und Kotamarthi, V. R.: Effects of spatial resolution on WRF v3.8.1 simulated meteorology over the central Himalaya, Geoscientific Model Development Discussions, 13, doi:10.5194/gmd-2020-12, 2020.

Flores-Livas, J. A., Wang, T., Nomoto, T., Koretsune, T., Ma, Y., Arita, R. und Eremets, M.: Reaching room temperature superconductivity by optimizing doping in LaH₁₀?, [online] Available from: https://arxiv.org/pdf/2010.06446, 2020.

Klingmüller, K. und Lelieveld, J.: Climate model-informed deep learning of global soil moisture distribution, Geoscientific Model Development Discussions, 14, doi:10.5194/gmd-2020-434, 2020.