Comparison of the performance of three types of multiple regression for phenology in Bavaria in a dynamical-statistical model approach

Abstract: Some of the most obvious consequences of anthropogenic climate change are observed changes in the dates of the occurrence of phenological events. Most prominently, observations from the Northern Hemisphere’s extratropics indicate an earlier occurrence of spring events. Recent climate models include land surface schemes that provide representation of the vegetation. However, they are limited in simulating the plants’ response to climate change. In this study we present results of a dynamical-statistical modeling approach for phenology in southeastern Germany, combining climate change simulations provided by a high resolution, state-of-the-art regional climate model (RCM) with three different types of regression methods: ordinary least squares (OLS), least absolute deviation (LAD) and random forest (RFO). We focus on changes in the day of the year (DOY) of Forsythia suspensa flowering, the earliest phenophase of the growing season in Bavaria. Based on roughly 2600 observations, colle.... https://www.erdkunde.uni-bonn.de/article/view/2819

Angaben zum Objekt

• Standort: Deutsche Nationalbibliothek Frankfurt am Main
• Umfang: Online-Ressource
• Sprache: Englisch

Verweise und Beziehungen

• Erschienen in: Comparison of the performance of three types of multiple regression for phenology in Bavaria in a dynamical-statistical model approach ; volume:71 ; number:4 ; year:2017 ; Erdkunde ; 71, Heft 4 (2017)

Beteiligte, Orts- und Zeitangaben

• Urheber: Pollinger, Felix ; Ziegler, Katrin ; Paeth, Heiko

Weitere Informationen

• DOI: 10.3112/erdkunde.2017.04.01
• URN: urn:nbn:de:101:1-2410281746465.962002489903
• Rechteinformation: Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
• Letzte Aktualisierung: 15.08.2025, 07:31 MESZ