Internal variability versus multi‐physics uncertainty in a regional climate model

Autor: Stergios Kartsios, Kirsten Warrach-Sagi, Stefan Sobolowski, Josipa Milovac, Torge Lorenz, Rita M. Cardoso, Eleni Katragkou, Lluis Fita, José M. Gutiérrez, Klaus Goergen, Alvaro Lavin-Gullon, Jesús Fernández, Theodore M. Giannaros, Pedro M. M. Soares, Sophie Bastin
Přispěvatelé: Ministerio de Economía y Competitividad (España), European Commission, Grupo de Meteorología de Santander, Universidad de Cantabria [Santander]-Spanish National Research Council (CSIC), SPACE - LATMOS, Laboratoire Atmosphères, Milieux, Observations Spatiales (LATMOS), Sorbonne Université (SU)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS)-Sorbonne Université (SU)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS), Instituto Dom Luiz, Universidade de Lisboa (ULISBOA), Centro de Investigaciones del Mar y la Atmósfera (CIMA), Facultad de Ciencias Exactas y Naturales [Buenos Aires] (FCEyN), Universidad de Buenos Aires [Buenos Aires] (UBA)-Universidad de Buenos Aires [Buenos Aires] (UBA)-Consejo Nacional de Investigaciones Científicas y Técnicas [Buenos Aires] (CONICET), National Observatory of Athens (NOA), Institute of Bio- and Geosciences [Jülich] (IBG), Forschungszentrum Jülich GmbH | Centre de recherche de Juliers, Helmholtz-Gemeinschaft = Helmholtz Association-Helmholtz-Gemeinschaft = Helmholtz Association, Department of Meteorology and Climatology [Thessaloniki], Aristotle University of Thessaloniki, Bjerknes Centre for Climate Research (BCCR), Department of Biological Sciences [Bergen] (BIO / UiB), University of Bergen (UiB)-University of Bergen (UiB), Institute of Physics and Meteorology [Stuttgart] (IPM), University of Hohenheim, Universidad de Cantabria
Jazyk: angličtina
Rok vydání: 2020
Předmět:
Zdroj: International Journal of Climatology
International Journal of Climatology, Wiley, 2021, 41 (S1), pp.E656-E671. ⟨10.1002/joc.6717⟩
Int. J Climatol. 2021; 41 (Suppl. 1): E656-E671
UCrea Repositorio Abierto de la Universidad de Cantabria
Universidad de Cantabria (UC)
International journal of climatology 41(S1), E656-E671 (2021). doi:10.1002/joc.6717
Digital.CSIC. Repositorio Institucional del CSIC
instname
ISSN: 0899-8418
1097-0088
Popis: In a recent study, Coppola et al. assessed the ability of an ensemble of convection‐permitting models (CPM) to simulate deep convection using three case studies. The ensemble exhibited strong discrepancies between models, which were attributed to various factors. In order to shed some light on the issue, we quantify in this article the uncertainty associated to different physical parameterizations from that of using different initial conditions, often referred to as the internal variability. For this purpose, we establish a framework to quantify both signals and we compare them for upper atmospheric circulation and near‐surface variables. The analysis is carried out in the context of the CORDEX Flagship Pilot Study on Convective phenomena at high resolution over Europe and the Mediterranean, in which the intermediate RCM WRF simulations that serve to drive the CPM are run several times with different parameterizations. For atmospheric circulation (geopotential height), the sensitivity induced by multi‐physics and the internal variability show comparable magnitudes and a similar spatial distribution pattern. For 2‐m temperature and 10‐m wind, the simulations with different parameterizations show larger differences than those launched with different initial conditions. The systematic effect over 1 year shows distinct patterns for the multi‐physics and the internal variability. Therefore, the general lesson of this study is that internal variability should be analysed in order to properly distinguish the impact of other sources of uncertainty, especially for short‐term sensitivity simulations.
This work is partially funded by the Spanish government through grant BES‐2016‐078158 and MINECO/FEDER co‐funded projects INSIGNIA (CGL2016‐79210‐R) and MULTI‐SDM (CGL2015‐66583‐R). UNINETT Sigma2. Grant Numbers: NS9001K, NN9280K European Union. Grant Number: 776613
Databáze: OpenAIRE
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