Differences

This shows you the differences between two versions of the page.

--- user:heikekalesse [2023/01/24 13:09] – Heike Kalesse-Los
+++ user:heikekalesse [2023/01/24 13:33] – [Publications] Heike Kalesse-Los
@@ Line 45: / Line 45: @@
 Please note that some articles were published under the maiden name Heike Eichler. \\
 orcID: [[ https://orcid.org/0000-0001-6699-7040]] \\
+**2023**
+  *  Linke, O. and Quaas, J. and Baumer, F. and Becker, S. and Chylik, J. and Dahlke, S. and Ehrlich, A. and Handorf, D. and Jacobi, C. and **Kalesse-Los, H.** and Lelli, L. and Mehrdad, S. and Neggers, R. A. J. and Riebold, J. and Saavedra Garfias, P. and Schnierstein, N. and Shupe, M. D. and Smith, C. and Spreen, G. and Verneuil, B. and Vinjamuri, K. S. and Vountas, M. and Wendisch, M.: Constraints on simulated past Arctic amplification and lapse-rate feedback from observations, Atmos. Chem. Phys. Discuss. [preprint], https://doi.org/10.5194/acp-2022-836, in review, 2023.
 **2022**
+  *  **Kalesse-Los, H.** and Kötsche, A. and Röttenbacher, J. and Vogl, T. and Witthuhn, J.: "The Virga-Sniffer – a new tool to identify precipitation evaporation using ground-based remote-sensing observations", Atmos. Meas. Tech. Discuss. [preprint], https://doi.org/10.5194/amt-2022-252, in review, 2022.
+  *  Mahecha, M.D. and Bastos, A. and Bohn, F.J. and Eisenhauer, N. and Feilhauer, H. and Hartmann, H. and Hickler, T. and **Kalesse-Los, H.** and Migliavacca, M. and Otto, F.E.L. and Peng, J. and  Quaas, J. and Tegen, I. and Weigelt, A. and Wendisch, M. and Wirth, C.: Biodiversity loss and climate extremes — study the feedbacks, Nature Comments, doi: https://doi.org/10.1038/d41586-022-04152-y, 2022.
   * Schimmel, W.  and **Kalesse-Los, H.** and Maahn, M. and Vogl, T. and Foth, A. and Saavedra Garfias, P. A. and Seifert, P.: Identifying cloud droplets beyond lidar attenuation from vertically-pointing cloud radar observations using artificial neural networks, Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2022-149, 2022.
   * Vogl, T. and Maahn, M. and Kneifel, S. and Schimmel, W. and Moisseev, D., and, **Kalesse-Los, H.**: Using artificial neural networks to predict riming from Doppler cloud radar observations, Atmos. Meas. Tech., https://doi.org/10.5194/amt-15-365-2022, 2022.