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Quantifying uncertainties of climate signals in chemistry climate models related to the 11-year solar cycle – Part 1: Annual mean response in heating rates, temperature, and ozone

Kunze, Markus; Kruschke, Tim; Langematz, Ulrike; Sinnhuber, Miriam; Reddmann, Thomas; Matthes, Katja

Abstract (englisch):
Variations in the solar spectral irradiance (SSI) with the 11-year sunspot cycle have been shown to have a significant impact on temperatures and the mixing ratios of atmospheric constituents in the stratosphere and mesosphere. Uncertainties in modelling the effects of SSI variations arise from uncertainties in the empirical models reconstructing the prescribed SSI data set as well as from uncertainties in the chemistry–climate model (CCM) formulation. In this study CCM simulations with the ECHAM/MESSy Atmospheric Chemistry (EMAC) model and the Community Earth System Model 1 (CESM1)–Whole Atmosphere Chemistry Climate Model (WACCM) have been performed to quantify the uncertainties of the solar responses in chemistry and dynamics that are due to the usage of five different SSI data sets or the two CCMs. We apply a two-way analysis of variance (ANOVA) to separate the influence of the SSI data sets and the CCMs on the variability of the solar response in shortwave heating rates, temperature, and ozone. The solar response is derived from climatological differences of time slice simulations prescribing SSI for the solar maximum in 1989 and near the solar minimum in 1994. ... mehr

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Verlagsausgabe §
DOI: 10.5445/IR/1000120179
Veröffentlicht am 16.06.2020
DOI: 10.5194/acp-20-6991-2020
Cover der Publikation
Zugehörige Institution(en) am KIT Institut für Meteorologie und Klimaforschung - Atmosphärische Spurenstoffe und Fernerkundung (IMK-ASF)
Publikationstyp Zeitschriftenaufsatz
Publikationsjahr 2020
Sprache Englisch
Identifikator ISSN: 1680-7324
KITopen-ID: 1000120179
HGF-Programm 12.04.03 (POF III, LK 01)
Stratospheric Ozone and Climate Change
Erschienen in Atmospheric chemistry and physics
Band 20
Heft 11
Seiten 6991–7019
Vorab online veröffentlicht am 12.06.2020
Schlagwörter Solar variability, climate, composition-climate models
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