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1.
Seasonal to interannual variations of the Equatorial Undercurrent (EUC) in the central Atlantic at 23°W are studied using shipboard observation taken during the period 1999–2011 as well as moored velocity time series covering the period May 2005–June 2011. The seasonal variations are dominated by an annual harmonic of the EUC transport and the EUC core depth (both at maximum during September), and a semiannual harmonic of the EUC core velocity (maximum during April and September). Substantial interannual variability during the period of moored observation included anomalous cold/warm equatorial Atlantic cold tongue events during 2005/2008. The easterly winds in the western equatorial Atlantic during boreal spring that represent the preconditioning of cold/warm events were strong/weak during 2005/2008 and associated with strong/weak boreal summer EUC transport. The anomalous year 2009 was instead associated with weak preconditioning and smallest EUC transport on record from January to July, but during August coldest SST anomalies in the eastern equatorial Atlantic were observed. The interannual variations of the EUC are discussed with respect to recently described variability of the tropical Atlantic Ocean.  相似文献   

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Warm sea-surface temperature (SST) biases in the southeastern tropical Atlantic (SETA), which is defined by a region from 5°E to the west coast of southern Africa and from 10°S to 30°S, are a common problem in many current and previous generation climate models. The Coupled Model Intercomparison Project Phase 5 (CMIP5) ensemble provides a useful framework to tackle the complex issues concerning causes of the SST bias. In this study, we tested a number of previously proposed mechanisms responsible for the SETA SST bias and found the following results. First, the multi-model ensemble mean shows a positive shortwave radiation bias of ~20 W m?2, consistent with models’ deficiency in simulating low-level clouds. This shortwave radiation error, however, is overwhelmed by larger errors in the simulated surface turbulent heat and longwave radiation fluxes, resulting in excessive heat loss from the ocean. The result holds for atmosphere-only model simulations from the same multi-model ensemble, where the effect of SST biases on surface heat fluxes is removed, and is not sensitive to whether the analysis region is chosen to coincide with the maximum warm SST bias along the coast or with the main SETA stratocumulus deck away from the coast. This combined with the fact that there is no statistically significant relationship between simulated SST biases and surface heat flux biases among CMIP5 models suggests that the shortwave radiation bias caused by poorly simulated low-level clouds is not the leading cause of the warm SST bias. Second, the majority of CMIP5 models underestimate upwelling strength along the Benguela coast, which is linked to the unrealistically weak alongshore wind stress simulated by the models. However, a correlation analysis between the model simulated vertical velocities and SST biases does not reveal a statistically significant relationship between the two, suggesting that the deficient coastal upwelling in the models is not simply related to the warm SST bias via vertical heat advection. Third, SETA SST biases in CMIP5 models are correlated with surface and subsurface ocean temperature biases in the equatorial region, suggesting that the equatorial temperature bias remotely contributes to the SETA SST bias. Finally, we found that all CMIP5 models simulate a southward displaced Angola–Benguela front (ABF), which in many models is more than 10° south of its observed location. Furthermore, SETA SST biases are most significantly correlated with ABF latitude, which suggests that the inability of CMIP5 models to accurately simulate the ABF is a leading cause of the SETA SST bias. This is supported by simulations with the oceanic component of one of the CMIP5 models, which is forced with observationally derived surface fluxes. The results show that even with the observationally derived surface atmospheric forcing, the ocean model generates a significant warm SST bias near the ABF, underlining the important role of ocean dynamics in SETA SST bias problem. Further model simulations were conducted to address the impact of the SETA SST biases. The results indicate a significant remote influence of the SETA SST bias on global model simulations of tropical climate, underscoring the importance and urgency to reduce the SETA SST bias in global climate models.  相似文献   

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Richter  Ingo  Tokinaga  Hiroki 《Climate Dynamics》2020,55(9-10):2579-2601

General circulation models of the Coupled Model Intercomparison Project Phase 6 (CMIP6) are examined with respect to their ability to simulate the mean state and variability of the tropical Atlantic and its linkage to the tropical Pacific. While, on average, mean state biases have improved little, relative to the previous intercomparison (CMIP5), there are now a few models with very small biases. In particular the equatorial Atlantic warm SST and westerly wind biases are mostly eliminated in these models. Furthermore, interannual variability in the equatorial and subtropical Atlantic is quite realistic in a number of CMIP6 models, which suggests that they should be useful tools for understanding and predicting variability patterns. The evolution of equatorial Atlantic biases follows the same pattern as in previous model generations, with westerly wind biases during boreal spring preceding warm sea-surface temperature (SST) biases in the east during boreal summer. A substantial portion of the westerly wind bias exists already in atmosphere-only simulations forced with observed SST, suggesting an atmospheric origin. While variability is relatively realistic in many models, SSTs seem less responsive to wind forcing than observed, both on the equator and in the subtropics, possibly due to an excessively deep mixed layer originating in the oceanic component. Thus models with realistic SST amplitude tend to have excessive wind amplitude. The models with the smallest mean state biases all have relatively high resolution but there are also a few low-resolution models that perform similarly well, indicating that resolution is not the only way toward reducing tropical Atlantic biases. The results also show a relatively weak link between mean state biases and the quality of the simulated variability. The linkage to the tropical Pacific shows a wide range of behaviors across models, indicating the need for further model improvement.

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We assess the ability of Global Climate Models participating in phases 3 and 5 of the Coupled Model Intercomparison Project (CMIP3 and CMIP5) to simulate observed annual precipitation cycles over the Caribbean. Compared to weather station records and gridded observations, we find that both CMIP3 and CMIP5 models can be grouped into three categories: (1) models that correctly simulate a bimodal distribution with two rainfall maxima in May–June and September–October, punctuated by a mid-summer drought (MSD) in July–August; (2) models that reproduce the MSD and the second precipitation maxima only; and (3) models that simulate only one precipitation maxima, beginning in early summer. These categories appear related to model simulation of the North Atlantic Subtropical High (NASH) and sea surface temperature (SST) in the Caribbean Sea and Gulf of Mexico. Specifically, models in category 2 tend to anticipate the westward expansion of the NASH into the Caribbean in early summer. Early onset of NASH results in strong moisture divergence and MSD-like conditions at the time of the May–June observed precipitation maxima. Models in category 3 tend to have cooler SST across the region, particularly over the central Caribbean and the Gulf of Mexico, as well as a weaker Caribbean low-level jet accompanying a weaker NASH. In these models, observed June-like patterns of moisture convergence in the central Caribbean and the Central America and divergence in the east Caribbean and the Gulf of Mexico persist through September. This analysis suggests systematic biases in model structure may be responsible for biases in observed precipitation variability over the Caribbean and more confidence may be placed in the precipitation simulated by the GCMs that are able to correctly simulate seasonal cycles of SST and NASH.  相似文献   

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Observations indicate that since the 1970s Equatorial Atlantic sea surface temperature (SST) variations in boreal summer tend to modulate El Niño in the following seasons, indicating that the Atlantic Ocean can have importance for predicting the El Niño–Southern Oscillation (ENSO). The cause of the change in the recent decades remains unknown. Here we show that in the Bergen Climate Model (BCM), a freshwater forced weakening of the Atlantic meridional overturning circulation (AMOC) results in a strengthening of the relation between the Atlantic and the Pacific similar to that observed since the 1970s. During the weakening AMOC phase, SST and precipitation increase in the central Equatorial Atlantic, while the mean state of the Pacific does not change significantly. In the Equatorial Atlantic the SST variability has also increased, with a peak in variability in boreal summer. In addition, the characteristic timescales of ENSO variability is shifted towards higher frequencies. The BCM version used here is flux-adjusted, and hence Atlantic variability is realistic in contrast to in many other models. These results indicate that in the BCM a weakening AMOC can change the mean background state of the Tropical Atlantic surface conditions, enhancing Equatorial Atlantic variability, and resulting in a stronger relationship between the Tropical Atlantic and Pacific Oceans. This in turn alters the variability in the Pacific.  相似文献   

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Climate Dynamics - Precipitation over the tropical Atlantic in 24 atmospheric models is analyzed using an object-based approach, which clusters rainy areas in the models as precipitation objects...  相似文献   

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Based on 15 Coupled Model Intercomparison Project (CMIP) phase 3 (CMIP3) and 32 CMIP phase 5 (CMIP5) models, a detailed diagnosis was carried out to understand what compose the biases in simulation of the Indian Ocean basin mode (IOBM) and its capacitor effect. Cloud-radiation-SST (CRS) feedback and wind-evaporation-SST (WES) feedback are the two major atmospheric processes for SST changes. Most CMIP models simulate a stronger CRS feedback and a weaker WES feedback. During boreal fall of the El Niño/Southern Oscillation developing year and the following spring, there are weak biases of suppressed rainfall anomalies over the Maritime Continent and anomalous anticyclone over South Indian Ocean. Most CMIP models simulate reasonable short wave radiation (SWR) and weaker latent heat flux (LHF) anomalies. This leads to a weak bias of atmospheric processes. During winter, however, the rainfall anomalies are stronger due to west bias, and the anomalous anticyclone is comparable to observations. As such, most models simulate stronger SWR and reasonable LHF anomalies, leading to a strong bias of atmospheric processes. The thermocline feedback is stronger in most models. Though there is a deep bias of climatology thermocline, most models capture reasonable sea surface height-induced SST anomalies. Therefore, the effect of oceanic processes offset the weak bias of atmospheric processes in spring, and the tropical Indian Ocean warming persists into summer. However, anomalous northwest Pacific (NWP) anticyclone is weaker due to weak and west bias of the capacitor effect. The unrealistic western Pacific SST anomalies in models favor the westward extension of Rossby wave from the Pacific, weakening the effect of Kelvin wave from the Indian Ocean. Moreover, the western Pacific warming forces the NWP anticyclone move farther north than observations, suggesting a major forcing from the Pacific. Compared to CMIP3, CMIP5 models simulate the feedbacks more realistically and display less diversity. Thus, the overall performance of CMIP5 models is better than that of CMIP3 models.  相似文献   

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Most coupled general circulation models (GCMs) perform poorly in the tropical Atlantic in terms of climatological seasonal cycle and interannual variability. The reasons for this poor performance are investigated in a suite of sensitivity experiments with the Geophysical Fluid Dynamics Laboratory (GFDL) coupled GCM. The experiments show that a significant portion of the equatorial SST biases in the model is due to weaker than observed equatorial easterlies during boreal spring. Due to these weak easterlies, the tilt of the equatorial thermocline is reduced, with shoaling in the west and deepening in the east. The erroneously deep thermocline in the east prevents cold tongue formation in the following season despite vigorous upwelling, thus inhibiting the Bjerknes feedback. It is further shown that the surface wind errors are due, in part, to deficient precipitation over equatorial South America and excessive precipitation over equatorial Africa, which already exist in the uncoupled atmospheric GCM. Additional tests indicate that the precipitation biases are highly sensitive to land surface conditions such as albedo and soil moisture. This suggests that improving the representation of land surface processes in GCMs offers a way of improving their performance in the tropical Atlantic. The weaker than observed equatorial easterlies also contribute remotely, via equatorial and coastal Kelvin waves, to the severe warm SST biases along the southwest African coast. However, the strength of the subtropical anticyclone and along-shore winds also play an important role.  相似文献   

13.
European temperatures and their projected changes under the 8.5 W/m2 Representative Concentration Pathway scenario are evaluated in an ensemble of 33 global climate models participating in the fifth phase of the Coupled Model Intercomparison Project (CMIP5). Respective contributions of large-scale dynamics and local processes to both biases and changes in temperatures, and to the inter-model spread, are then investigated from a recently proposed methodology based on weather regimes. On average, CMIP5 models exhibit a cold bias in winter, especially in Northern Europe. They overestimate summer temperatures in Central Europe, in association with a greater diurnal range than observed. The projected temperature increase is stronger in summer than in winter, with the highest summer warming occurring over Mediterranean regions. Links between biases and sensitivities are evidenced in winter, suggesting a potential influence of snow cover biases on the projected surface warming. A brief analysis of daily temperature extremes suggests that the intra-seasonal variability is projected to decrease (slightly increase) in winter (summer). Then, in order to understand model discrepancies in both present-day and future climates, we disentangle effects of large-scale atmospheric dynamics and regional physical processes. In particular, in winter, CMIP5 models simulate a stronger North-Atlantic jet stream than observed and, in contrast with CMIP3 results, the majority of them suggests an increased frequency of the negative phase of the North-Atlantic Oscillation under future warming. While large-scale circulation only has a minor contribution to ensemble-mean biases or changes, which are primarily dominated by non-dynamical processes, it substantially affects the inter-model spread. Finally, other sources of uncertainties, including the North-Atlantic warming and local radiative feedbacks related to snow cover and clouds, are briefly discussed.  相似文献   

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Decadal variability in the climate system from the Atlantic Multidecadal Oscillation (AMO) is one of the major sources of variability at this temporal scale that climate models must properly incorporate because of its climate impact. The current analysis of historical simulations of the twentieth century climate from models participating in the CMIP3 and CMIP5 projects assesses how these models portray the observed spatiotemporal features of the sea surface temperature (SST) and precipitation anomalies associated with the AMO. A short sample of the models is analyzed in detail by using all ensembles available of the models CCSM3, GFDL-CM2.1, UKMO-HadCM3, and ECHAM5/MPI-OM from the CMIP3 project, and the models CCSM4, GFDL-CM3, UKMO-HadGEM2-ES, and MPI-ESM-LR from the CMIP5 project. The structure and evolution of the SST anomalies of the AMO have not progressed consistently from the CMIP3 to the CMIP5 models. While the characteristic period of the AMO (smoothed with a binomial filter applied fifty times) is underestimated by the three of the models, the e-folding time of the autocorrelations shows that all models underestimate the 44-year value from observations by almost 50 %. Variability of the AMO in the 10–20/70–80 year ranges is overestimated/underestimated in the models and the variability in the 10–20 year range increases in three of the models from the CMIP3 to the CMIP5 versions. Spatial variability and correlation of the AMO regressed precipitation and SST anomalies in summer and fall indicate that models are not up to the task of simulating the AMO impact on the hydroclimate over the neighboring continents. This is in spite of the fact that the spatial variability and correlations in the SST anomalies improve from CMIP3 to CMIP5 versions in two of the models. However, a multi-model mean from a sample of 14 models whose first ensemble was analyzed indicated there were no improvements in the structure of the SST anomalies of the AMO or associated regional precipitation anomalies in summer and fall from CMIP3 to CMIP5 projects.  相似文献   

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Average long-term and average annual values of meridional Ekman heat (mass) transport are estimated using the NCEP/NCAR (for 1948-2014) and 20CR (for 1871-2012) atmospheric reanalyses, and their interdecadal variability is analyzed. It was corroborated that the typical period of interdecadal variability of meridional Ekman transport in the North Atlantic coincides with that of the Atlantic Multidecadal Oscillation (AMO) and is about 60 years. The strengthening of northeastern trade winds and westerlies accompanied by the development of the negative phase of AMO occurred in the 1880s-1920s and in the 1960s-1990s. The opposite trend is observed for the 1930s-1950s and for the period from the 1990s till the beginning of the 21st century.  相似文献   

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利用观测海温资料和CMIP5模式模拟结果分析西北太平洋(120°E~120°W,20~60°N)海表温度的气候态和年代际变化特征。结果表明,所选22个模式可以较好地模拟出西北太平洋海表温度的气候特征及其年际、年代际变化特征;模式模拟的海表温度总体标准偏差在黑潮延伸体区域最大;绝大多数模式能模拟出海表温度的第一EOF模态;西北太平洋海表温度具有较明显的年代际振荡现象,13/22的模式模拟的海表温度存在明显的年代际振荡,同时海表温度气候态的模拟偏差对其周期振荡模拟的影响较大,尤其在黑潮延伸体区域。  相似文献   

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We investigate the multidecadal variability of summer temperature over Romania as measured at 14 meteorological stations with long-term observational records. The dominant pattern of summer temperature variability has a monopolar structure and shows pronounced multidecadal variations. A correlation analysis reveals that these multidecadal variations are related with multidecadal variations in the frequency of four daily atmospheric circulation patterns from the North Atlantic region. It is found that on multidecadal time scales, negative summer mean temperature (TT) anomalies are associated with positive sea level pressure (SLP) anomalies centered over the northern part of the Atlantic Ocean and Scandinavia and negative SLP anomalies centered over the northern part of Africa. It is speculated that a possible cause of multidecadal fluctuations in the frequency of these four patterns are the sea surface temperature (SST) anomalies associated to the Atlantic Multidecadal Oscillation (AMO). These results have implications for predicting the evolution of summer temperature over Romania on multidecadal time scales.  相似文献   

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One of the main sources of uncertainty in estimating climate projections affected by global warming is the choice of the global climate model (GCM). The aim of this study is to evaluate the skill of GCMs from CMIP3 and CMIP5 databases in the north-east Atlantic Ocean region. It is well known that the seasonal and interannual variability of surface inland variables (e.g. precipitation and snow) and ocean variables (e.g. wave height and storm surge) are linked to the atmospheric circulation patterns. Thus, an automatic synoptic classification, based on weather types, has been used to assess whether GCMs are able to reproduce spatial patterns and climate variability. Three important factors have been analyzed: the skill of GCMs to reproduce the synoptic situations, the skill of GCMs to reproduce the historical inter-annual variability and the consistency of GCMs experiments during twenty-first century projections. The results of this analysis indicate that the most skilled GCMs in the study region are UKMO-HadGEM2, ECHAM5/MPI-OM and MIROC3.2(hires) for CMIP3 scenarios and ACCESS1.0, EC-EARTH, HadGEM2-CC, HadGEM2-ES and CMCC-CM for CMIP5 scenarios. These models are therefore recommended for the estimation of future regional multi-model projections of surface variables driven by the atmospheric circulation in the north-east Atlantic Ocean region.  相似文献   

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