4 resultados para General circulation models

em Universidade Complutense de Madrid


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The Atlantic thermohaline circulation (THC) is an important part of the earth's climate system. Previous research has shown large uncertainties in simulating future changes in this critical system. The simulated THC response to idealized freshwater perturbations and the associated climate changes have been intercompared as an activity of World Climate Research Program (WCRP) Coupled Model Intercomparison Project/Paleo-Modeling Intercomparison Project (CMIP/PMIP) committees. This intercomparison among models ranging from the earth system models of intermediate complexity (EMICs) to the fully coupled atmosphere-ocean general circulation models (AOGCMs) seeks to document and improve understanding of the causes of the wide variations in the modeled THC response. The robustness of particular simulation features has been evaluated across the model results. In response to 0.1-Sv (1 Sv equivalent to 10^6 ms^3 s^-1) freshwater input in the northern North Atlantic, the multimodel ensemble mean THC weakens by 30% after 100 yr. All models simulate sonic weakening of the THC, but no model simulates a complete shutdown of the THC. The multimodel ensemble indicates that the surface air temperature could present a complex anomaly pattern with cooling south of Greenland and warming over the Barents and Nordic Seas. The Atlantic ITCZ tends to shift southward. In response to 1.0-Sv freshwater input, the THC switches off rapidly in all model simulations. A large cooling occurs over the North Atlantic. The annual mean Atlantic ITCZ moves into the Southern Hemisphere. Models disagree in terms of the reversibility of the THC after its shutdown. In general, the EMICs and AOGCMs obtain similar THC responses and climate changes with more pronounced and sharper patterns in the AOGCMs.

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The ECHAM-1 T21/LSG coupled ocean-atmosphere general circulation model (GCM) is used to simulate climatic conditions at the last interglacial maximum (Eemian. 125 kyr BP). The results reflect thc expected surface temperature changes (with respect to the control run) due to the amplification (reduction) of the seasonal cycle of insolation in the Northern (Southern) Hemisphere. A number of simulated features agree with previous results from atmospheric GCM simulations e.g. intensified summer southwest monsoons) except in the Northern Hemisphere poleward of 30 degrees N. where dynamical feedback, in the North Atlantic and North Pacific increase zonal temperatures about 1 degrees C above what would be predicted from simple energy balance considerations. As this is the same area where most of the terrestrial geological data originate, this result suggests that previous estimates of Eemian global average temperature might have been biased by sample distribution. This conclusion is supported by the fact that the estimated global temperature increase of only 0.3 degrees C greater than the control run ha, been previously shown to be consistent a with CLIMAP sea surface temperature estimates. Although the Northern Hemisphere summer monsoon is intensified. globally averaged precipitation over land is within about 1% of the present, contravening some geological inferences bur not the deep-sea delta(13)C estimates of terrestrial carbon storage changes. Winter circulation changes in the northern Arabian Sea. driven by strong cooling on land, are as large as summer circulation changes that are the usual focus of interest, suggesting that interpreting variations in the Arabian Sea. sedimentary record solely in terms of the summer monsoon response could sometimes lead to errors. A small monsoonal response over northern South America suggests that interglacial paleotrends in this region were not just due to El Nino variations.

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Studies addressing climate variability during the last millennium generally focus on variables with a direct influence on climate variability, like the fast thermal response to varying radiative forcing, or the large-scale changes in atmospheric dynamics (e. g. North Atlantic Oscillation). The ocean responds to these variations by slowly integrating in depth the upper heat flux changes, thus producing a delayed influence on ocean heat content (OHC) that can later impact low frequency SST (sea surface temperature) variability through reemergence processes. In this study, both the externally and internally driven variations of the OHC during the last millennium are investigated using a set of fully coupled simulations with the ECHO-G (coupled climate model ECHAMA4 and ocean model HOPE-G) atmosphere-ocean general circulation model (AOGCM). When compared to observations for the last 55 yr, the model tends to overestimate the global trends and underestimate the decadal OHC variability. Extending the analysis back to the last one thousand years, the main impact of the radiative forcing is an OHC increase at high latitudes, explained to some extent by a reduction in cloud cover and the subsequent increase of short-wave radiation at the surface. This OHC response is dominated by the effect of volcanism in the preindustrial era, and by the fast increase of GHGs during the last 150 yr. Likewise, salient impacts from internal climate variability are observed at regional scales. For instance, upper temperature in the equatorial Pacific is controlled by ENSO (El Nino Southern Oscillation) variability from interannual to multidecadal timescales. Also, both the Pacific Decadal Oscillation (PDO) and the Atlantic Multidecadal Oscillation (AMO) modulate intermittently the interdecadal OHC variability in the North Pacific and Mid Atlantic, respectively. The NAO, through its influence on North Atlantic surface heat fluxes and convection, also plays an important role on the OHC at multiple timescales, leading first to a cooling in the Labrador and Irminger seas, and later on to a North Atlantic warming, associated with a delayed impact on the AMO.

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We consider a robust version of the classical Wald test statistics for testing simple and composite null hypotheses for general parametric models. These test statistics are based on the minimum density power divergence estimators instead of the maximum likelihood estimators. An extensive study of their robustness properties is given though the influence functions as well as the chi-square inflation factors. It is theoretically established that the level and power of these robust tests are stable against outliers, whereas the classical Wald test breaks down. Some numerical examples confirm the validity of the theoretical results.