227 resultados para COUPLED GCM


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In this study, the authors evaluate the (El Niño–Southern Oscillation) ENSO–Asian monsoon interaction in a version of the Hadley Centre coupled ocean–atmosphere general circulation model (CGCM) known as HadCM3. The main focus is on two evolving anomalous anticyclones: one located over the south Indian Ocean (SIO) and the other over the western North Pacific (WNP). These two anomalous anticyclones are closely related to the developing and decaying phases of the ENSO and play a crucial role in linking the Asian monsoon to ENSO. It is found that the HadCM3 can well simulate the main features of the evolution of both anomalous anticyclones and the related SST dipoles, in association with the different phases of the ENSO cycle. By using the simulated results, the authors examine the relationship between the WNP/SIO anomalous anticyclones and the ENSO cycle, in particular the biennial component of the relationship. It is found that a strong El Niño event tends to be followed by a more rapid decay and is much more likely to become a La Niña event in the subsequent winter. The twin anomalous anticyclones in the western Pacific in the summer of a decaying El Niño are crucial for the transition from an El Niño into a La Niña. The El Niño (La Niña) events, especially the strong ones, strengthen significantly the correspondence between the SIO anticyclonic (cyclonic) anomaly in the preceding autumn and WNP anticyclonic (cyclonic) anomaly in the subsequent spring, and favor the persistence of the WNP anomaly from spring to summer. The present results suggest that both El Niño (La Niña) and the SIO/WNP anticyclonic (cyclonic) anomalies are closely tied with the tropospheric biennial oscillation (TBO). In addition, variability in the East Asian summer monsoon, which is dominated by the internal atmospheric variability, seems to be responsible for the appearance of the WNP anticyclonic anomaly through an upper-tropospheric meridional teleconnection pattern over the western and central Pacific.

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The time-dependent climate response to changing concentrations of greenhouse gases and sulfate aerosols is studied using a coupled general circulation model of the atmosphere and the ocean (ECHAM4/OPYC3). The concentrations of the well-mixed greenhouse gases like CO2, CH4, N2O, and CFCs are prescribed for the past (1860–1990) and projected into the future according to International Panel on Climate Change (IPCC) scenario IS92a. In addition, the space–time distribution of tropospheric ozone is prescribed, and the tropospheric sulfur cycle is calculated within the coupled model using sulfur emissions of the past and projected into the future (IS92a). The radiative impact of the aerosols is considered via both the direct and the indirect (i.e., through cloud albedo) effect. It is shown that the simulated trend in sulfate deposition since the end of the last century is broadly consistent with ice core measurements, and the calculated radiative forcings from preindustrial to present time are within the uncertainty range estimated by IPCC. Three climate perturbation experiments are performed, applying different forcing mechanisms, and the results are compared with those obtained from a 300-yr unforced control experiment. As in previous experiments, the climate response is similar, but weaker, if aerosol effects are included in addition to greenhouse gases. One notable difference to previous experiments is that the strength of the Indian summer monsoon is not fundamentally affected by the inclusion of aerosol effects. Although the monsoon is damped compared to a greenhouse gas only experiment, it is still more vigorous than in the control experiment. This different behavior, compared to previous studies, is the result of the different land–sea distribution of aerosol forcing. Somewhat unexpected, the intensity of the global hydrological cycle becomes weaker in a warmer climate if both direct and indirect aerosol effects are included in addition to the greenhouse gases. This can be related to anomalous net radiative cooling of the earth’s surface through aerosols, which is balanced by reduced turbulent transfer of both sensible and latent heat from the surface to the atmosphere.

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Anomalous heavy snow during winter or spring has long been regarded as a possible precursor of deficient Indian monsoon rainfall during the subsequent summer. However previous work in this field is inconclusive, in terms of the mechanism that communicates snow anomalies to the monsoon summer, and even the region from which snow has the most impact. In this study we explore these issues in coupled and atmosphere-only versions of the Hadley Centre model. A 1050-year control integration of the HadCM3 coupled model, which well represents the seasonal cycle of snow cover over the Eurasian continent, is analysed and shows evidence for weakened monsoons being preceded by strong snow forcing (in the absence of ENSO) over either the Himalaya/Tibetan Plateau or north/west Eurasia regions. However, empirical orthogonal function (EOF) analysis of springtime interannual variability in snow depth shows the leading mode to have opposite signs between these two regions, suggesting that competing mechanisms may be possible. To determine the dominant region, ensemble integrations are carried out using HadAM3, the atmospheric component of HadCM3, and a variety of anomalous snow forcing initial conditions obtained from the control integration of the coupled model. Forcings are applied during spring in separate experiments over the Himalaya/Tibetan Plateau and north/west Eurasia regions, in conjunction with climatological SSTs in order to avoid the direct effects of ENSO. With the aid of idealized forcing conditions in sensitivity tests, we demonstrate that forcing from the Himalaya region is dominant in this model via a Blanford-type mechanism involving reduced surface sensible heat and longwave fluxes, reduced heating of the troposphere over the Tibetan Plateau and consequently a reduced meridional tropospheric temperature gradient which weakens the monsoon during early summer. Snow albedo is shown to be key to the mechanism, explaining around 50% of the perturbation in sensible heating over the Tibetan Plateau, and accounting for the majority of cooling through the troposphere.

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Previous studies using the Hadley Centre coupled model (HadCM3) have shown that the islands of the Maritime Continent act as an unrealistic block to the eastward propagation of the Madden-Julian Oscillation (MJO). This blocking effect is investigated using a simplified, aqua-planet version of this GCM, with various idealized configurations of the Maritime Continent islands placed on the equator, and an MJO-like convective signal forced by a propagating sea-surface temperature anomaly dipole. Results suggest that it is the orography of the islands, rather than the presence of the islands themselves, which results in the blocking of the MJO. Although the peak elevation of the orography in the GCM is very much lower than in reality, it appears to act as effective block to the eastward propagation of the low-level Kelvin wave signal which accompanies the MJO. In particular, the representation of Sumatra in the GCM, as a north-south oriented ridge straddling the equator, seems to be particularly effective at blocking the Kelvin wave signal, which in a full GCM would result in the weakening or complete extinction of the MJO signal to the east of the Maritime Continent.

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This study uses a Granger causality time series modeling approach to quantitatively diagnose the feedback of daily sea surface temperatures (SSTs) on daily values of the North Atlantic Oscillation (NAO) as simulated by a realistic coupled general circulation model (GCM). Bivariate vector autoregressive time series models are carefully fitted to daily wintertime SST and NAO time series produced by a 50-yr simulation of the Third Hadley Centre Coupled Ocean-Atmosphere GCM (HadCM3). The approach demonstrates that there is a small yet statistically significant feedback of SSTs oil the NAO. The SST tripole index is found to provide additional predictive information for the NAO than that available by using only past values of NAO-the SST tripole is Granger causal for the NAO. Careful examination of local SSTs reveals that much of this effect is due to the effect of SSTs in the region of the Gulf Steam, especially south of Cape Hatteras. The effect of SSTs on NAO is responsible for the slower-than-exponential decay in lag-autocorrelations of NAO notable at lags longer than 10 days. The persistence induced in daily NAO by SSTs causes long-term means of NAO to have more variance than expected from averaging NAO noise if there is no feedback of the ocean on the atmosphere. There are greater long-term trends in NAO than can be expected from aggregating just short-term atmospheric noise, and NAO is potentially predictable provided that future SSTs are known. For example, there is about 10%-30% more variance in seasonal wintertime means of NAO and almost 70% more variance in annual means of NAO due to SST effects than one would expect if NAO were a purely atmospheric process.

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The climatology of the OPA/ARPEGE-T21 coupled general circulation model (GCM) is presented. The atmosphere GCM has a T21 spectral truncation and the ocean GCM has a 2°×1.5° average resolution. A 50-year climatic simulation is performed using the OASIS coupler, without flux correction techniques. The mean state and seasonal cycle for the last 10 years of the experiment are described and compared to the corresponding uncoupled experiments and to climatology when available. The model reasonably simulates most of the basic features of the observed climate. Energy budgets and transports in the coupled system, of importance for climate studies, are assessed and prove to be within available estimates. After an adjustment phase of a few years, the model stabilizes around a mean state where the tropics are warm and resemble a permanent ENSO, the Southern Ocean warms and almost no sea-ice is left in the Southern Hemisphere. The atmospheric circulation becomes more zonal and symmetric with respect to the equator. Once those systematic errors are established, the model shows little secular drift, the small remaining trends being mainly associated to horizontal physics in the ocean GCM. The stability of the model is shown to be related to qualities already present in the uncoupled GCMs used, namely a balanced radiation budget at the top-of-the-atmosphere and a tight ocean thermocline.

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It is well established that crop production is inherently vulnerable to variations in the weather and climate. More recently the influence of vegetation on the state of the atmosphere has been recognized. The seasonal growth of crops can influence the atmosphere and have local impacts on the weather, which in turn affects the rate of seasonal crop growth and development. Considering the coupled nature of the crop-climate system, and the fact that a significant proportion of land is devoted to the cultivation of crops, important interactions may be missed when studying crops and the climate system in isolation, particularly in the context of land use and climate change. To represent the two-way interactions between seasonal crop growth and atmospheric variability, we integrate a crop model developed specifically to operate at large spatial scales (General Large Area Model for annual crops) into the land surface component of a global climate model (GCM; HadAM3). In the new coupled crop-climate model, the simulated environment (atmosphere and soil states) influences growth and development of the crop, while simultaneously the temporal variations in crop leaf area and height across its growing season alter the characteristics of the land surface that are important determinants of surface fluxes of heat and moisture, as well as other aspects of the land-surface hydrological cycle. The coupled model realistically simulates the seasonal growth of a summer annual crop in response to the GCM's simulated weather and climate. The model also reproduces the observed relationship between seasonal rainfall and crop yield. The integration of a large-scale single crop model into a GCM, as described here, represents a first step towards the development of fully coupled crop and climate models. Future development priorities and challenges related to coupling crop and climate models are discussed.

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The transport of the Antarctic Circumpolar Current (ACC) varies strongly across the coupled GCMs (general circulation models) used for the IPCC AR4. This note shows that a large fraction of this across-model variance can be explained by relating it to the parameterization of eddy-induced transports. In the majority of models this parameterization is based on the study by Gent and McWilliams (1990). The main parameter is the quasi-Stokes diffusivity kappa (often referred to less accurately as ’’thickness diffusion’’). The ACC transport and the meridional density gradient both correlate strongly with kappa across those models where kappa is a prescribed constant. In contrast, there is no correlation with the isopycnal diffusivity jiso across the models. The sensitivity of the ACC transport to kappa is larger than to the zonal wind stress maximum. Experiments with the fast GCM FAMOUS show that changing kappa directly affects the ACC transport by changing the density structure throughout the water column. Our results suggest that this limits the role of the wind stress magnitude in setting the ACC transport in FAMOUS. The sensitivities of the ACC and the meridional density gradient are very similar across the AR4 GCMs (for those models where kappa is a prescribed constant) and among the FAMOUS experiments. The strong sensitivity of the ACC transport to kappa needs careful assessment in climate models.

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A range of possible changes in the frequency and characteristics of European wind storms under future climate conditions was investigated on the basis of a multi-model ensemble of 9 coupled global climate model (GCM) simulations for the 20th and 21st centuries following the IPCC SRES A1B scenario. A multi-model approach allowed an estimation of the (un)certainties of the climate change signals. General changes in large-scale atmospheric flow were analysed, the occurrence of wind storms was quantified, and atmospheric features associated with wind storm events were considered. Identified storm days were investigated according to atmospheric circulation, associated pressure patterns, cyclone tracks and wind speed patterns. Validation against reanalysis data revealed that the GCMs are in general capable of realistically reproducing characteristics of European circulation weather types (CWTs) and wind storms. Results are given with respect to frequency of occurrence, storm-associated flow conditions, cyclone tracks and specific wind speed patterns. Under anthropogenic climate change conditions (SRES A1B scenario), increased frequency of westerly flow during winter is detected over the central European investigation area. In the ensemble mean, the number of detected wind storm days increases between 19 and 33% for 2 different measures of storminess, only 1 GCM revealed less storm days. The increased number of storm days detected in most models is disproportionately high compared to the related CWT changes. The mean intensity of cyclones associated with storm days in the ensemble mean increases by about 10 (±10)% in the Eastern Atlantic, near the British Isles and in the North Sea. Accordingly, wind speeds associated with storm events increase significantly by about 5 (±5)% over large parts of central Europe, mainly on days with westerly flow. The basic conclusions of this work remain valid if different ensemble contructions are considered, leaving out an outlier model or including multiple runs of one particular model.

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Reconstructions of salinity are used to diagnose changes in the hydrological cycle and ocean circulation. A widely used method of determining past salinity uses oxygen isotope (δOw) residuals after the extraction of the global ice volume and temperature components. This method relies on a constant relationship between δOw and salinity throughout time. Here we use the isotope-enabled fully coupled General Circulation Model (GCM) HadCM3 to test the application of spatially and time-independent relationships in the reconstruction of past ocean salinity. Simulations of the Late Holocene (LH), Last Glacial Maximum (LGM), and Last Interglacial (LIG) climates are performed and benchmarked against existing compilations of stable oxygen isotopes in carbonates (δOc), which primarily reflect δOw and temperature. We find that HadCM3 produces an accurate representation of the surface ocean δOc distribution for the LH and LGM. Our simulations show considerable variability in spatial and temporal δOw-salinity relationships. Spatial gradients are generally shallower but within ∼50% of the actual simulated LH to LGM and LH to LIG temporal gradients and temporal gradients calculated from multi-decadal variability are generally shallower than both spatial and actual simulated gradients. The largest sources of uncertainty in salinity reconstructions are found to be caused by changes in regional freshwater budgets, ocean circulation, and sea ice regimes. These can cause errors in salinity estimates exceeding 4 psu. Our results suggest that paleosalinity reconstructions in the South Atlantic, Indian and Tropical Pacific Oceans should be most robust, since these regions exhibit relatively constant δOw-salinity relationships across spatial and temporal scales. Largest uncertainties will affect North Atlantic and high latitude paleosalinity reconstructions. Finally, the results show that it is difficult to generate reliable salinity estimates for regions of dynamic oceanography, such as the North Atlantic, without additional constraints.