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1.
The interdecadal and interannual variability of the Mediterranean Sea surface temperature (SST), presented by the first and second modes of empirical orthogonal functions (EOF), respectively, is studied using the 1951–2000 data. It is demonstrated that the spatial and temporal structure of the first EOF mode, reflecting interdecadal SST variations, is similar in all seasons, and, thus, is a manifestation of a global signal that is not subject to significant seasonal changes and whose origin is common for all seasons. On the contrary, the second EOF mode, reflecting the interannual variability of the Mediterranean Sea surface temperature and presented by a zonally oriented dipole, demonstrates its well pronounced seasonality. It is found that the character of temporal variability of this mode is specific for each season. The seasonality is also pronounced in significant variability of the mode contribution to the total SST variability. The above-noted seasonal differences are indicative of various mechanisms of formation of the interannual SST variability in the Mediterranean Sea.  相似文献   

2.
A principal component decomposition of monthly sea surface temperature (SST) variability in the tropical Pacific Ocean demonstrates that nearly all of the linear trends during 1950–2010 are found in two leading patterns. The first SST pattern is strongly related to the canonical El Niño-Southern Oscillation (ENSO) pattern. The second pattern shares characteristics with the first pattern and its existence solely depends on the presence of linear trends across the tropical Pacific Ocean. The decomposition also uncovers a third pattern, often referred to as ENSO Modoki, but the linear trend is small and dataset dependent over the full 61-year record and is insignificant within each season. ENSO Modoki is also reflected in the equatorial zonal SST gradient between the Niño-4 region, located in the west-central Pacific, and the Niño-3 region in the eastern Pacific. It is only in this zonal SST gradient that a marginally significant trend arises early in the Northern Hemisphere spring (March–May) during El Niño and La Niña and also in the late summer (July–September) during El Niño. Yet these SST trends in the zonal gradient do not unequivocally represent an ENSO Modoki-like dipole because they are exclusively associated with significant positive SST trends in either the eastern or western Pacific, with no corresponding significant negative trends. Insignificant trends in the zonal SST gradient are evident during the boreal wintertime months when ENSO events typically mature. Given the presence of positive SST trends across much of the equatorial Pacific Ocean, using fixed SST anomaly thresholds to define ENSO events likely needs to be reconsidered.  相似文献   

3.
Climate drift in preindustrial control (PICTL) simulations can lead to spurious climate trends and large uncertainties in historical and future climate simulations in coupled models. This study examined the long-term behaviors and stabilities of the PICTL simulations in the two versions of FGOALS2 (the Flexible Global Ocean-Atmosphere-Land System model Version 2), which have been submitted to the Coupled Model Inter-comparison Project Phase 5 (CMIP5). As verified by examining time series of thermal fields and their linear trends, the PICTL simulations showed stable long-term integration behaviors and no obvious climate drift [the magnitudes of linear trends of SST were both less than 0.04oC (100 yr)-1] over multiple centuries. The changed SSTs in a century (that corresponded to the linear trends) were less than the standard deviations of annual mean values, which implied the internal variability was not affected. These trend values were less than 10% of those of global averaged SST from observations and historical runs during the periods of slow and rapid warming. Such stable long-term integration behaviors reduced the uncertainty of the estimation of global warming rates in the historical and future climate projections in the two versions of FGOALS2. Compared with the trends in the Northern Hemisphere, larger trends existed in the SST and sea ice extents at the middle to high latitudes of the Southern Hemisphere (SH). To estimate the historical and future climate trends in the SH or at some specific regions in FGOALS2, corrections needed to be carried out. The similar long-term behaviors in the two versions of FGOALS2 may be attributed to proper physical processes in the ocean model.  相似文献   

4.
In order to improve seasonal-to-interannual precipitation forecasts and their application by decision makers, there is a clear need to understand when, where, and to what extent seasonal precipitation anomalies are driven by potentially predictable surface–atmosphere interactions versus to chaotic interannual atmospheric dynamics. Using a simple Monte Carlo approach, interannual variability and linear trends in the SST-forced signal and potential predictability of boreal winter precipitation anomalies is examined in an ensemble of twentieth century AGCM simulations. Signal and potential predictability are shown to be non-stationary over more than 80% of the globe, while chaotic noise is shown to be stationary over most of the globe. Correlation analysis with respect to magnitudes of the four leading modes of global SST variability suggests that interannual variability and trends in signal and potential predictability over 35% of the globe is associated with ENSO-related SST variability; signal and potential predictability are not significantly associated with SST modes characterized by a global SST trend, North Atlantic SST variability, and North Pacific SST variability, respectively. Results suggest that mechanisms other than SST variability contribute to the non-stationarity of signal and noise characteristics of hydroclimatic variability over mid- and high-latitude regions.  相似文献   

5.
The regional features oflong-term variability ofsea surface temperature (SST) in the Black Sea are analyzed using the satellite data for 1982-2014. It is demonstrated that the maximum intraannual and interannual variability of SST is registered on the northwestern shelf of the Black Sea. The high level of interannual variability of SST and maximum linear trends are observed in the northeastern part of the sea. The qualitative connection is revealed between the long-term variability of SST and the variations in the intensity of the Black Sea Rim Current in the long-term seasonal cycle. An increase in the level of interannual variability of SST is observed in summer, when the Black Sea Rim Current weakens. The significant negative correlation is revealed between the interannual anomalies of SST and the NAO index. The highest correlation coefficients are obtained for the eastern part of the Black Sea and near the Crimean coast.  相似文献   

6.
Seasonal extreme wave statistics were reproduced by using the 25-km-grid global wave model of WAVEWATCH-III. The results showed that the simulated wave dataset for the present climate (1979-2009) was similar to Climate Forecast System Reanalysis (CFSR) wave data. Statistics such as the root mean squared error (RMSE) and correlation coefficient (CC) over the western North Pacific (WNP) basin were 0.5 m and 0.69 over the analysis domain. The largest trends and standard deviation were around the southern coast of Japan and western edge of the WNP. Linear regression analysis was employed to identify the relationship between the leading principal components (PCs) of significant wave heights (SWHs) in the peak season of July to September and sea surface temperature (SST) anomalies in the equatorial Pacific. The results indicated that the inter-annual variability of SWH can be associated with the El Niño-Southern Oscillation in the peak season. The CC between the first PC of the SWH and anomalies in the Nino 3.4 SST index was also significant at a 99% confidence level. Significant variations in the SWH are affected by tropical cyclones (TCs) caused by increased SST anomalies. The genesis and development of simulated TCs can be important to the variation in SWHs for the WNP in the peak season. Therefore, we can project the variability of SWHs through TC activity based on changes in SST conditions for the equatorial Pacific in the future.  相似文献   

7.
Summary:Diagnosing a coupled system with linear inverse modelling (LIM) can provide insight into the nature and strength of the coupling. This technique is applied to the cold season output of the GFDL GCM, forced by observed tropical Pacific SSTs and including a slab mixed layer ocean model elsewhere. It is found that extratropical SST anomalies act to enhance atmospheric thermal variability and diminish barotropic variability over the east Pacific in these GCM runs, in agreement with other theoretical and modelling studies. North-west Atlantic barotropic variability is also enhanced. However, all these feedbacks are very weak. LIM results also suggest that North Pacific extratropical SST anomalies in this model would rapidly decay without atmospheric forcing induced by tropical SST anomalies.  相似文献   

8.
The determination of specific sea surface temperature (SST) patterns from large-scale gridded SST-fields has widely been done. Often principal component analysis (PCA) is used to condense the SST-data to major patterns of variability. In the present study SST-fields for the period 1950?C2003 from the area 20°S to 60°N are analysed with respect to SST-regimes being defined as large-scale oceanic patterns with a regular and at least seasonal occurrence. This has been done in context of investigations on seasonal predictability of Mediterranean regional climate with large-scale SST-regimes as intended predictors in statistical model relationships. The SST-regimes are derived by means of a particular technique including multiple applications of s-mode PCA. Altogether 17 stationary regimes can be identified, eight for the Pacific Ocean, five for the Atlantic Ocean, two for the Indian Ocean, and two regimes which show a distinct co-variability within different ocean basins. Some regimes exist, with varying strength and spatial extent, throughout the whole year, whereas other regimes are only characteristic for a particular season. Several regimes show dominant variability modes, like the regimes associated with El Ni?o, with the Pacific Decadal Oscillation or with the North Atlantic Tripole, whereas other regimes describe little-known patterns of large-scale SST variability. The determined SST-regimes are subsequently used as predictors for monthly precipitation and temperature in the Mediterranean area. This subject is addressed in Part II of this paper.  相似文献   

9.
A standard principal component analysis has been performed over the Mediterranean and over the larger European region on monthly precipitation anomalies for the winters between 1979 and 1995. The main centres of action of the associated EOFs are very similar for the two regions and the two sets of PCs are highly correlated with each other. Focusing on the Mediterranean region, the same analysis has been performed using 500?hPa geopotential height monthly anomalies taken from the operational NCEP analysis. Comparing the two sets of PCs associated with upper-air and surface data, a strong correlation has been found suggesting the presence of a two-way link between regional precipitation patterns and large-scale circulation anomalies. For both fields, the largest fraction of variance is explained by the North Atlantic Oscillation, while smaller but still substantial fractions are explained by other known patterns of large-scale variability such as the Eastern Atlantic pattern and the Euro-Atlantic blocking. No detectable connection has been found between Mediterranean precipitation patterns and El Niño SST anomalies during winter. With respect to temporal variability, significant trends have been found over most European areas during the winters considered. The associated pattern is characterised by a substantial increase of precipitation over western Scandinavia and a general decrease over southern Europe. This result is confirmed by analysing data from stations located in northern Italy.  相似文献   

10.
A study has been made, using the National Centers for Environmental Prediction and National Center for Atmospheric Research re-analysis 500 hPa geopotential height data, to determine how intraseasonal variability influences, or can generate, coherent patterns of interannual variability in the extratropical summer and winter Southern Hemisphere atmospheric circulation. In addition, by separating this intraseasonal component of interannual variability, we also consider how slowly varying external forcings and slowly varying (interannual and longer) internal dynamics might influence the interannual variability of the Southern Hemisphere circulation. This slow component of interannual variation is more likely to be potentially predictable. How sea surface temperatures are related to the slow components is also considered. The four dominant intraseasonal modes of interannual variability have horizontal structures similar to those seen in both well-known intraseasonal dynamical modes and statistical modes of intraseasonal variability. In particular, they reflect intraseasonal variability in the high latitudes associated with the Southern Annular Mode, and wavenumber 4 (summer) and wavenumber 3 (winter) patterns associated with south Pacific regions of persistent anomalies and blocking, and possibly variability related to the Madden-Julian Oscillation (MJO). The four dominant slow components of interannual variability, in both seasons, are related to high latitude variability associated with the Southern Annular Mode, El Nino Southern Oscillation (ENSO) variability, and South Pacific Wave variability associated with Indian Ocean SSTs. In both seasons, there are strong linear trends in the first slow mode of high latitude variability and these are shown to be related to similar trends in the Indian Ocean. Once these are taken into account there is no significant sea surface temperature forcing of these high latitude modes. The second and third ENSO related slow modes, in each season, have high correlations with tropical sea surface temperature variability in the Pacific and Indian Oceans, both contemporaneously and at one season lag. The fourth slow mode has a characteristic South Pacific wave structure of either a wavenumber 4 (summer) or wavenumber 3 (winter) pattern, with strongest loadings in the South Pacific sector, and an association simultaneously with a dipole SST temperature gradient in the subtropical Indian Ocean.  相似文献   

11.
Since the Mediterranean Sea is halfway between subtropical and middle latitudes, and it represents a marginal oceanic region, research has tended to focus on how large-scale modes of atmospheric variability modulate its surface temperature. Conversely, the present study examines the potential influence of the Mediterranean Sea surface temperature (SST) anomalies on the Northern Hemisphere atmospheric circulation. In particular, this work explores the large-scale changes in the global circulation forced/influenced by the eastern Mediterranean summer-autumn SST pattern. To isolate the atmospheric response, AGCM sensitivity experiments with prescribed SST over the Mediterranean Sea and climatology elsewhere are analysed. Observational diagnostics upon the period used to define the boundary conditions (1979–2002) are also interpreted. Our results support the hypothesis of an atmospheric pattern initiated in the Mediterranean basin, pointing out both a local baroclinic response and a barotropic circumglobal anomaly. This atmospheric teleconnection pattern projects onto a hemispheric wave-like structure, reflecting the waveguide effect of the westerly jets. Results suggest, thereby, that the recurrent summer-autumn circumglobal teleconnection pattern can be excited locally by changes in the atmosphere over the Mediterranean region. A linear behaviour is found upon a regional impact over northeastern Africa. The remote impacts present however a nonlinear signature: anomalous warm conditions influencing on northern Europe and Euro–Asia, whereas anomalous cold conditions impacting more on the North Pacific basin. Limitations in our model setup are also discussed.  相似文献   

12.
An Atlantic influence on Amazon rainfall   总被引：2，自引：2，他引：0  
Rainfall variability over the Amazon basin has often been linked to variations in Pacific sea surface temperature (SST), and in particular, to the El Niño/Southern Oscillation (ENSO). However, only a fraction of Amazon rainfall variability can be explained by ENSO. Building upon the recent work of Zeng (Environ Res Lett 3:014002, 2008), here we provide further evidence for an influence on Amazon rainfall from the tropical Atlantic Ocean. The strength of the North Atlantic influence is found to be comparable to the better-known Pacific ENSO connection. The tropical South Atlantic Ocean also shows some influence during the wet-to-dry season transition period. The Atlantic influence is through changes in the north-south divergent circulation and the movement of the ITCZ following warm SST. Therefore, it is strongest in the southern part of the Amazon basin during the Amazon’s dry season (July–October). In contrast, the ENSO related teleconnection is through anomalous east-west Walker circulation with largely concentrated in the eastern (lower) Amazon. This ENSO connection is seasonally locked to boreal winter. A complication due to the influence of ENSO on Atlantic SST causes an apparent North Atlantic SST lag of Amazon rainfall. Removing ENSO from North Atlantic SST via linear regression resolves this causality problem in that the residual Atlantic variability correlates well and is in phase with the Amazon rainfall. A strong Atlantic influence during boreal summer and autumn is particularly significant in terms of the impact on the hydro-ecosystem which is most vulnerable during the dry season, as highlighted by the severe 2005 Amazon drought. Such findings have implications for both seasonal-interannual climate prediction and understanding the longer-term changes of the Amazon rainforest.  相似文献   

13.
We analyze decadal climate variability in the Mediterranean region using observational datasets over the period 1850–2009 and a regional climate model simulation for the period 1960–2000, focusing in particular on the winter (DJF) and summer (JJA) seasons. Our results show that decadal variability associated with the winter and summer manifestations of the North Atlantic Oscillation (NAO and SNAO respectively) and the Atlantic Multidecadal Oscillation (AMO) significantly contribute to decadal climate anomalies over the Mediterranean region during these seasons. Over 30% of decadal variance in DJF and JJA precipitation in parts of the Mediterranean region can be explained by NAO and SNAO variability respectively. During JJA, the AMO explains over 30% of regional surface air temperature anomalies and Mediterranean Sea surface temperature anomalies, with significant influence also in the transition seasons. In DJF, only Mediterranean SST still significantly correlates with the AMO while regional surface air temperature does not. Also, there is no significant NAO influence on decadal Mediterranean surface air temperature anomalies during this season. A simulation with the PROTHEUS regional ocean–atmosphere coupled model is utilized to investigate processes determining regional decadal changes during the 1960–2000 period, specifically the wetter and cooler 1971–1985 conditions versus the drier and warmer 1986–2000 conditions. The simulation successfully captures the essence of observed decadal changes. Model set-up suggests that AMO variability is transmitted to the Mediterranean/European region and the Mediterranean Sea via atmospheric processes. Regional feedbacks involving cloud cover and soil moisture changes also appear to contribute to observed changes. If confirmed, the linkage between Mediterranean temperatures and the AMO may imply a certain degree of regional decadal climate predictability. The AMO and other decadal influences outlined here should be considered along with those from long-term increases in greenhouse gas forcings when making regional climate out-looks for the Mediterranean 10–20?years out.  相似文献   

14.
The present study investigates the Caribbean Sea rainfall variability during the early and late rainy seasons and its association with sea surface temperature (SST) and air?Csea interaction based on observational estimates, the NCEP Climate Forecast System (CFS) and Global Forecast System (GFS) simulations, and the CFS retrospective forecasts. Analysis of the observational estimates indicates that air?Csea interaction is important over the Caribbean Sea, whereas the atmospheric forcing of SST dominates over the Gulf of Mexico. The CFS simulation captures the basic elements of this observed air?Csea relationship. The GFS simulation produces spurious SST forcing of the atmosphere over the Gulf of Mexico largely due to prescribing SST. The CFS forecasts capture the air?Csea relationship in the late rainy season (August?COctober), but cannot reproduce the SST forcing of atmosphere over the Caribbean Sea in the early rainy season (May?CJuly). An empirical orthogonal function (EOF) analysis indicates that the leading modes of percent anomalies of the rainy season precipitation have the largest loading in the southern Caribbean Sea in observations. The model simulations and forecasts skillfully reproduce the spatial pattern, but not the temporal evolution. The Caribbean Sea rainfall variability in the early rainy season is mainly due to the tropical North Atlantic (TNA) SST anomalies in observations, is contributed by both the TNA and eastern equatorial Pacific (EEP) SST anomalies in the CFS simulation, and has an overly large impact from the EEP SST anomalies in the GFS simulation and the CFS forecasts. The observed Caribbean Sea rainfall variability in the late rainy season has a leading impact from the EEP SST anomalies, with a secondary contribution from the TNA SST anomalies. In comparison, the model simulations and forecasts overestimate the impacts of the EEP SST anomalies due to an earlier development and longer duration of the El Ni?o-Southern Oscillation in the CFS compared to observations.  相似文献   

15.
Rainfall over West Africa shows strong interannual variability related to changes in Sea Surface Temperature (SST). Nevertheless, this relationship seem to be non-stationary. A particular turning point is the decade of the 1970s, which witnessed a number of changes in the climatic system, including the climate shift of the late 1970s. The first aim of this study is to explore the change in the interannual variability of West African rainfall after this shift. The analysis indicates that the dipolar features of the rainfall variability over this region, related to changes in the Atlantic SST, disappear after this period. Also, the Pacific SST variability has a higher correlation with Guinean rainfall in the recent period. The results suggest that the current relationship between the Atlantic and Pacific El Ni?o phenomena is the principal responsible for these changes. A fundamental goal of climate research is the development of models simulating a realistic current climate. For this reason, the second aim of this work is to test the performance of Atmospheric General Circulation models in simulating rainfall variability over West Africa. The models have been run with observed SSTs for the common period 1957?C1998 as part of an intercomparison exercise. The results show that the models are able to reproduce Guinean interannual variability, which is strongly related to SST variability in the Equatorial Atlantic. Nevertheless, problems in the simulation of the Sahelian interannual variability appear: not all models are able to reproduce the observed negative link between rainfall over the Sahel and El Ni?o-like anomalies in the Pacific, neither the positive correlation between Mediterranean SSTs and Sahelian rainfall.  相似文献   

16.
Comprehensive characterization of diversity in global patterns of precipitation variability and change is an important starting point for climate adaptation and resilience assessments. Capturing the nature of precipitation probability distribution functions (PDF) is critical for assessing variability and change. Conventional linear regression-based analyses assume that slope coefficients for the wet and dry tails of the PDF are consonant with the conditional mean trend. This assumption is not always borne out in the analyses of historical records. Given the relationship between sea surface temperature (SST) and precipitation, recent trends in global SST complicate interpretations of precipitation variability and risk. In this study, changes in the PDF of annual precipitation (1951–2011) at the global river basin scale were analyzed using quantile regression (QR). QR is a flexible approach allowing for the assessment of precipitation variability conditioned on the leading empirical orthogonal function (EOF) patterns of global SST that reflect El Niño–Southern Oscillation and Atlantic Multi-decadal Oscillation. To this end, the framework presented (a) offers a characterization of the entire PDF and its sensitivity to the leading modes of SST variability, (b) captures a range of responses in the PDF including asymmetries, (c) highlights regions likely to experience higher risks of precipitation excesses and deficits and inter-annual variability, and (d) offers an approach for quantifying risk across specified quantiles. Results show asymmetric responses in the PDF in all regions of the world, either in single or both tails. In one instance, QR detects a differential response to the leading patterns of SST in the Tana basin in eastern Africa, highlighting changes in variability as well as risk.  相似文献   

17.
There is strong evidence that Indian Ocean sea surface temperatures (SSTs) influence the climate variability of Southern Asia and Africa; hence, accurate prediction of these SSTs is a high priority. In this study, we use canonical correlation analysis (CCA) to design empirical models to assess the predictability of tropical Indian Ocean SST from sea level pressure (SLP) and SST themselves with lead-times up to one year. One model uses the first twelve empirical orthogonal functions (EOFs) of SLP over the Indian Ocean using different lead-times to predict SST. A CCA model with EOFs of SST as the predictor at the same lead-times is compared to SLP as a predictor and shows the auto-correlation of the system. A CCA using the first five extended empirical orthogonal functions (EEOFs) of sea level pressure over the Indian Ocean basin for an interval of two years combined with SST EOFs as predictors is found to produce the greatest correlation between forecast and observed SSTs. This model obtains higher skill by explicitly considering the development in time of SLP anomalies in the region. The skill of this model, assessed from retroactive forecasts of an 18 year period, shows improvement relative to other empirical forecasts particularly for the central and eastern Indian Ocean and boreal autumn months preceding the Southern Hemisphere summer rainfall season. This is likely due to the limited domain of this model identifying modes of variability that are more pronounced in these areas during this season. Finally, a nonlinear canonical correlation analysis (NLCCA) derived from a neural network is used to analyze the leading nonlinear modes. These nonlinear modes differ from the linear CCA modes with distinct cold and warm SST phases suggesting a nonlinear relationship between SST and SLP over the tropical Indian Ocean.  相似文献   

18.
The natural sea surface temperature (SST) variability in the global oceans is evaluated in simulations of the Climate Model Intercomparison Project Phase 3 (CMIP3) and CMIP5 models. In this evaluation, we examine how well the spatial structure of the SST variability matches between the observations and simulations on the basis of their leading empirical orthogonal functions-modes. Here we focus on the high-pass filter monthly mean time scales and the longer 5 years running mean time scales. We will compare the models and observations against simple null hypotheses, such as isotropic diffusion (red noise) or a slab ocean model, to illustrate the models skill in simulating realistic patterns of variability. Some models show good skill in simulating the observed spatial structure of the SST variability in the tropical domains and less so in the extra-tropical domains. However, most models show substantial deviations from the observations and from each other in most domains and particularly in the North Atlantic and Southern Ocean on the longer (5 years running mean) time scale. In many cases the simple spatial red noise null hypothesis is closer to the observed structure than most models, despite the fact that the observed SST variability shows significant deviations from this simple spatial red noise null hypothesis. The CMIP models tend to largely overestimate the effective spatial number degrees of freedom and simulate too strongly localized patterns of SST variability at the wrong locations with structures that are different from the observed. However, the CMIP5 ensemble shows some improvement over the CMIP3 ensemble, mostly in the tropical domains. Further, the spatial structure of the SST modes of the CMIP3 and CMIP5 super ensemble is more realistic than any single model, if the relative explained variances of these modes are scaled by the observed eigenvalues.  相似文献   

19.
用偏最小二乘(Partial Least Square,PLS)回归方法分析了 1979～2018年影响亚马逊旱季(6～8月)降水年际变率的热带海面温度模态.第一海面温度模态解释了总方差的64％,主要表现为前期亚马逊雨季(12月至次年2月)至旱季(6～8月)热带东太平洋La Ni?a型海面温度异常演变.12月至次年2月...  相似文献   

20.
The roles of anthropogenic climate change and internal climate variability in causing the Mediterranean region’s late 20th Century extended winter drying trend are examined using 19 coupled models from the Intergovernmental Panel on Climate Change Fourth Assessment Report. The observed drying was influenced by the robust positive trend in the North Atlantic Oscillation (NAO) from the 1960s to the 1990s. Model simulations and observations are used to assess the probable relative roles of radiative forcing, and internal variability in explaining the circulation trend that drove much of the precipitation change. Using the multi-model ensemble we assess how well the models can produce multidecadal trends of realistic magnitude, and apply signal-to-noise maximizing EOF analysis to obtain a best estimate of the models’ (mean) sea-level pressure (SLP) and precipitation responses to changes in radiative forcing. The observed SLP and Mediterranean precipitation fields are regressed onto the timeseries associated with the models’ externally forced pattern and the implied linear trends in both fields between 1960 and 1999 are calculated. It is concluded that the radiatively forced trends are a small fraction of the total observed trends. Instead it is argued that the robust trends in the observed NAO and Mediterranean rainfall during this period were largely due to multidecadal internal variability with a small contribution from the external forcing. Differences between the observed and NAO-associated precipitation trends are consistent with those expected as a response to radiative forcing. The radiatively forced trends in circulation and precipitation are expected to strengthen in the current century and this study highlights the importance of their contribution to future precipitation changes in the region.  相似文献   

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