Deutsch
 
Hilfe Datenschutzhinweis Impressum
  DetailsucheBrowse

Datensatz

DATENSATZ AKTIONENEXPORT
Zur Ablage hinzufügen
 Lokale TagsFreigabegeschichteDetailsÜbersicht
  Monte Carlo climate change forecasts with a global coupled ocean-atmosphere model

Cubasch, U., Santer, B. D., Hellbach, A., Hegerl, G., Höck, H., Maier-Reimer, E., et al. (1994). Monte Carlo climate change forecasts with a global coupled ocean-atmosphere model. Climate Dynamics, 10, 1-19. doi:10.1007/BF00210333.

Item is

 

einblenden: alle ausblenden: alle

Basisdaten

einblenden: ausblenden:
Datensatz-Permalink: https://hdl.handle.net/21.11116/0000-0001-8803-2 Versions-Permalink: https://hdl.handle.net/21.11116/0000-0001-8808-D
Genre: Zeitschriftenartikel

Dateien

einblenden: Dateien
ausblenden: Dateien
:
CD-1994-Hegerl.pdf (Verlagsversion), 15MB
 
Datei-Permalink:
-
Name:
CD-1994-Hegerl.pdf
Beschreibung:
Verlagsversion
OA-Status:
Sichtbarkeit:
Eingeschränkt (Max Planck Institute for Meteorology, MHMT; )
MIME-Typ / Prüfsumme:
application/pdf
Technische Metadaten:
Copyright Datum:
-
Copyright Info:
-
Lizenz:
-
:
097-Report.pdf (Preprint), 4MB
Öffnen   Speichern
Datei-Permalink:
https://hdl.handle.net/21.11116/0000-0001-8806-F
Name:
097-Report.pdf
Beschreibung:
Reportversion / Pre-Print / Retrodigitalisiert
OA-Status:
Sichtbarkeit:
Öffentlich
MIME-Typ / Prüfsumme:
application/pdf / [MD5]
Technische Metadaten:
Öffnen
Copyright Datum:
-
Copyright Info:
-
Lizenz:
-

Externe Referenzen

einblenden:

Urheber

einblenden:
ausblenden:
 Urheber:
Cubasch, U.1, Autor
Santer, B. D.2, Autor
Hellbach, A.1, Autor
Hegerl, G.3, Autor
Höck, H.3, Autor
Maier-Reimer, E.3, Autor
Mikolajewicz, U.3, Autor
Stössel, A.3, Autor
Voss, R.4, Autor
Affiliations:
1Deutsches Klimarechenzentrum (DKRZ), Bundesstraße 55, D-2000 Hamburg 13, GER, ou_persistent22              
2Program for Climate Model Diagnosis and Intercomparison, Lawrence Livermore National Laboratory, Livermore, California 94550, USA, ou_persistent22              
3MPI for Meteorology, Max Planck Society, Bundesstraße 53, 20146 Hamburg, DE, ou_913545              
4Universität Hamburg, Meteorologisches Institut, Bundesstraße 55 D-2000 Hamburg 13, GER, ou_persistent22              

Inhalt

einblenden:
ausblenden:
Schlagwörter: -
 Zusammenfassung: Four time-dependent greenhouse warming experiments were performed with the same global coupled atmosphere-ocean model, but with each simulation using initial conditions from different ''snapshots'' of the control run climate. The radiative forcing - the increase in equivalent CO2 concentrations from 19852035 specified in the Intergovernmental Panel on Climate Change (IPCC) scenario A - was identical in all four 50-year integrations. This approach to climate change experiments is called the Monte Carlo technique and is analogous to a similar experimental set-up used in the field of extended range weather forecasting. Despite the limitation of a very small sample size, this approach enables the estimation of both a mean response and the ''between-experiment'' variability, information which is not available from a single integration. The use of multiple realizations provides insights into the stability of the response, both spatially, seasonally and in terms of different climate variables. The results indicate that the time evolution of the global mean warming signal is strongly dependent on the initial state of the climate system. While the individual members of the ensemble show considerable variation in the pattern and amplitude of near-surface temperature change after 50 years, the ensemble mean climate change pattern closely resembles that obtained in a 100-year integration performed with the same model. In global mean terms, the climate change signals for near surface temperature, the hydrological. cycle and sea level significantly exceed the variability among the members of the ensemble. Due to the high internal variability of the modelled climate system, the estimated detection time of the global mean temperature change signal is uncertain by at least one decade. While the ensemble mean surface temperature and sea level fields show regionally significant responses to greenhouse-gas forcing, it is not possible to identify a significant response in the precipitation and soil moisture fields, variables which are spatially noisy and characterized by large variability between the individual integrations.

Details

einblenden:
ausblenden:
Sprache(n): eng - English
 Datum: 1994
 Publikationsstatus: Erschienen
 Seiten: -
 Ort, Verlag, Ausgabe: -
 Inhaltsverzeichnis: -
 Art der Begutachtung: Expertenbegutachtung
 Identifikatoren: ISI: A1994NX68800001
DOI: 10.1007/BF00210333
 Art des Abschluß: -

Veranstaltung

einblenden:

Entscheidung

einblenden:

Projektinformation

einblenden:

Quelle 1

einblenden:
ausblenden:
Titel: Climate Dynamics
  Andere : Clim. Dyn.
Genre der Quelle: Zeitschrift
 Urheber:
Affiliations:
Ort, Verlag, Ausgabe: Heidelberg : Springer-International
Seiten: - Band / Heft: 10 Artikelnummer: - Start- / Endseite: 1 - 19 Identifikator: ISSN: 0930-7575
CoNE: https://pure.mpg.de/cone/journals/resource/954925568800

Quelle 2

einblenden:
ausblenden:
Titel: Report / Max-Planck-Institut für Meteorologie
  Andere : MPI Report
Genre der Quelle: Reihe
 Urheber:
Affiliations:
Ort, Verlag, Ausgabe: Hamburg : Max-Planck-Institut für Meteorologie
Seiten: - Band / Heft: 097 Artikelnummer: - Start- / Endseite: - Identifikator: Anderer: 0937-1060
CoNE: https://pure.mpg.de/cone/journals/resource/0937-1060