Und, was hat das mit dem Thema zu tun?Zitat:
Zitat von Dr Mittendrin
Es gab immer mal heisse Sommer und milde Winter. Der Unterschied zu früher ist die Häufung.
Druckbare Version
Und, was hat das mit dem Thema zu tun?Zitat:
Zitat von Dr Mittendrin
Es gab immer mal heisse Sommer und milde Winter. Der Unterschied zu früher ist die Häufung.
Zitat:
Zitat von Differentialgeometer
Brauchst nicht vertiefen. Warum war es z b 1540 so heiss ?
Simple Logik kennt ihr nicht, kaut nach was Eliten wollen und es ist eine Migrationssteuer.
Die Warmzeit war auch eine Häufung.Zitat:
Zitat von SprecherZwo
Wirst echt zum Spamidiot, hast ja gesagt, wählst Grüne.
Du kennst nicht den Unterschied zwischen Klima und Wetter - macht aber nichts.Zitat:
Zitat von Dr Mittendrin
Natürlich ist in einem chaotischen (weisst Du eigentlich was ‚chaotisch‘ überhaupt heisst - ernstgemeinte Frage) System „keine Prognosen möglich“ - und zwar in dem Sinne, dass man irgendwie ‚linear‘ eine Zahl erhält. Man kann aber das System untersuchen (Fixpunkte, Bifurkationen etc) und gegen numerische Simulationen spricht nun mal nichts, um eine Idee zu entwickeln. Und am Ende sind Näherungen nun mal die Basis jedes physikalischen Modells. Nehmen wir ein Pendel der Länge l. Eigentlich musste man die Bewegung der Luftströmungen um den Faden und das Gewicht durch hydrodynamische Gleichungen beschreiben. De facto ist es aber auch okay, mit Newton eine Schwingungsgleichung aufzuschreiben und erhält dann 2pisqrt(l/g) für die Sxhwingungsdauer.... Man verliert also in diesem Beispiel keine qualitativ relevanten Informationen. Nichts anderes sind Klimamodelle - eine Näherung, mit der man qualitative Aussagen treffen möchte, wie sich unter gewissen Anfangsbedingungen die Temperatur entwickelt.Zitat:
Zitat von kotzfisch
Ah daher weht der Wind. Das ist so geheim, dass es niemand weiss :DZitat:
Zitat von SprecherZwo
Tja, nur haben alle Modelle weder vor noch rückwärts die reale Entwicklung getroffen.Zitat:
Zitat von Differentialgeometer
Sag mir mal eines.
Sischer dat. INM CM5. Das ist nagelnew, zu dem gibt es m.W. Noch keine Prognosen, dafür aber Testrechnungen aus der Vergangenheit. —> https://esd.copernicus.org/preprints...sd-2018-21.pdfZitat:
Zitat von kotzfisch
Zitat:
Climate changes observed in 1850-2014 are modeled and studied on the basis of seven historical runs with the climate model INM-CM5 under the scenario proposed for Coupled Model Intercomparison Project, Phase 6 (CMIP6). In all runs global mean surface temperature rises by 0.8 K at the end of the experiment (2014) in agreement with the observations. Periods of fast warming in 1920-1940 and 1980-2000 as well as its slowdown in 1950-1975 and 2000-2014 are correctly reproduced by the ensemble mean.The notable change here with respect to the CMIP5 results is correct reproduction of the slowdown of global warming in 2000-2014 that we attribute to more accurate description of the Solar constant in CMIP6 protocol. The model is able to reproduce correct behavior of global mean temperature in 1980-2014 despite incorrect phases of the Atlantic Multidecadal Oscillation and Pacific Decadal Oscillation indices in the majority of experiments. The Arctic sea ice lossin recent decades is reasonably close to the observations just in one model run; the model underestimates Arctic sea ice loss by the factor 2.5. Spatial pattern of model mean surface temperature trend during the last 30 years looks close the one for the ERA Interim reanalysis. Model correctly estimates the magnitude of stratospheric cooling.....
Observational data of GMST for 1850-2014 used for verification of model results were produced by HadCRUT4 (Morice et al 2012). Monthly mean sea surface temperature (SST) data ERSSTv4 (Huang et al 2015) are used for comparison of the AMO and PDO indices with that of the model. Data of Arctic sea ice extent for 1979-2014 derived from satellite observations are taken from Comiso and Nishio (2008). Stratospheric temperature trend and geographical distribution of near surface air temperature trend for 1979-2014 are calculated from ERA Interim reanalysis data (Dee et al 2011).
Keeping in mind the arguments that the GMST slowdown in the beginning of 21st 6 century could be due to the internal variability of the climate system let us look at the behavior of the AMO and PDO climate indices. Here we calculated the AMO index in the usual way, as the SST anomaly in Atlantic at latitudinal band 0N-60N minus anomaly of the GMST. Model and observed 5 year mean AMO index time series are presented in Fig.3. The well known oscillation with a period of 60-70 years can be clearly seen in the observations. Among the model runs, only one (dashed purple line) shows oscillation with a period of about 70 years, but without significant maximum near year 2000. In other model runs there is no distinct oscillation with a period of 60-70 years but period of 20-40 years prevails. As a result none of seven model trajectories reproduces behavior of observed AMO index after year 1950 (including its warm phase at the turn of the 20th and 21st centuries). One can conclude that anthropogenic forcing is unable to produce any significant impact on the AMO dynamicsas its index averaged over 7 realization stays around zero within one sigma interval (0.08). Consequently, the AMO dynamics is controlled by internal variability of the climate systemand cannot be predicted in historic experiments. On the other hand the model can correctly predict GMST changes in 1980-2014 having wrong phase of the AMO(blue, yellow, orange lines on Fig.1 and 3).
Conclusions
Seven historical runs for 1850-2014 with the climate model INM-CM5 were analyzed. It is shown that magnitude of the GMST rise in model runs agrees with the estimate based on the observations. All model runs reproduce stabilization of GMST in 1950-1970, fast warming in 1980-2000 and a second GMST stabilization in 2000-2014 suggesting that the major factor for predicting GMST evolution is the external forcing rather than system internal variability. Numerical experiments with the previous model version (INMCM4) for CMIP5 showed unrealistic gradual warming in 1950-2014. The difference between the two model results could be explained by more accurate modeling of stratospheric volcanic and tropospheric anthropogenic aerosol radiation effect (stabilization in 1950-1970) due to the new aerosol block in INM-CM5 and more accurate prescription of Solar constant scenario (stabilization in 2000-2014) in CMIP6 protocol. Four of seven INM-CM5 model runs simulate acceleration of warming in 1920-1940 in a correct way, other three produce it earlier or later than in reality. This indicates that for the year warming of 1920-1940 the climate system natural variability plays significant role. No model trajectory reproduces correct time behavior of AMO and PDO indices. Taking into account our results on the GMST modeling one can conclude that anthropogenic forcing does not produce any significant impact on the dynamics of AMO and PDO indices, at least for the INM-CM5 model. In turns, correct prediction of the GMST changes in the 1980-2014 does not require correct phases of the AMO and PDO as all model runs have correct values of the GMST while in at least three model experiments the phases of the AMO and PDO are opposite to the observed ones in that time. The North Atlantic SST time series produced by the model correlates better with the observations in 1980-2014. Three out of seven trajectories have strongly positive North Atlantic SST anomaly as the observations (in the other four cases we see near-to-zero changes for this quantity). The INMCM5 has the same skill for prediction of the Arctic sea ice extent in 2000-2014 as CMIP5 models including INMCM4. It underestimates the rate of sea ice loss by a factor between the two and three. In one extreme case the magnitude of this decrease is as large as in the observations while in the other the sea ice extent does not change compared to the preindustrial ages. In part this could be explained by the strong internal variability of the Arctic sea ice but obviously the new version of INMCM model and new CMIP6 forcing protocol does not improve prediction of the Arctic sea ice extent response to anthropogenic forcing.
Glückwunsch.
Die Vergangenheit korrekt abgebildet.
Ich bin beeindruckt.
Es gibt einen Fachausdruck für solchen Unsinn.Hilfst Du mir drauf?