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Variability in the Atlantic Meridional Overturning Circulation (AMOC) has been analysed using a 600-year pre-industrial control simulation with the Bergen Climate Model. The typical AMOC variability has amplitudes of 1?Sverdrup (1 Sv?=?106?m3?s?1) and time scales of 40–70?years. The model is reproducing the observed dense water formation regions and has very realistic ocean transports and water mass distributions. The dense water produced in the Labrador Sea (1/3) and in the Nordic Seas, including the water entrained into the dense overflows across the Greenland-Scotland Ridge (GSR; 2/3), are the sources of North Atlantic Deep Water (NADW) forming the lower limb of the AMOC’s northern overturning. The variability in the Labrador Sea and the Nordic Seas convection is driven by decadal scale air-sea fluxes in the convective region that can be related to opposite phases of the North Atlantic Oscillation. The Labrador Sea convection is directly linked to the variability in AMOC. Linkages between convection and water mass transformation in the Nordic Seas are more indirect. The Scandinavian Pattern, the third mode of atmospheric variability in the North Atlantic, is a driver of the ocean’s poleward heat transport (PHT), the overall constraint on northern water mass transformation. Increased PHT is both associated with an increased water mass exchange across the GSR, and a stronger AMOC.  相似文献   
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Stolpe  Martin B.  Cowtan  Kevin  Medhaug  Iselin  Knutti  Reto 《Climate Dynamics》2021,56(1-2):613-634

Global mean temperature change simulated by climate models deviates from the observed temperature increase during decadal-scale periods in the past. In particular, warming during the ‘global warming hiatus’ in the early twenty-first century appears overestimated in CMIP5 and CMIP6 multi-model means. We examine the role of equatorial Pacific variability in these divergences since 1950 by comparing 18 studies that quantify the Pacific contribution to the ‘hiatus’ and earlier periods and by investigating the reasons for differing results. During the ‘global warming hiatus’ from 1992 to 2012, the estimated contributions differ by a factor of five, with multiple linear regression approaches generally indicating a smaller contribution of Pacific variability to global temperature than climate model experiments where the simulated tropical Pacific sea surface temperature (SST) or wind stress anomalies are nudged towards observations. These so-called pacemaker experiments suggest that the ‘hiatus’ is fully explained and possibly over-explained by Pacific variability. Most of the spread across the studies can be attributed to two factors: neglecting the forced signal in tropical Pacific SST, which is often the case in multiple regression studies but not in pacemaker experiments, underestimates the Pacific contribution to global temperature change by a factor of two during the ‘hiatus’; the sensitivity with which the global temperature responds to Pacific variability varies by a factor of two between models on a decadal time scale, questioning the robustness of single model pacemaker experiments. Once we have accounted for these factors, the CMIP5 mean warming adjusted for Pacific variability reproduces the observed annual global mean temperature closely, with a correlation coefficient of 0.985 from 1950 to 2018. The CMIP6 ensemble performs less favourably but improves if the models with the highest transient climate response are omitted from the ensemble mean.

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