Precipitation and temperature space–time variability and extremes in the Mediterranean region: evaluation of dynamical and statistical downscaling methods

This study evaluates how statistical and dynamical downscaling models as well as combined approach perform in retrieving the space–time variability of near-surface temperature and rainfall, as well as their extremes, over the whole Mediterranean region. The dynamical downscaling model used in this study is the Weather Research and Forecasting (WRF) model with varying land-surface models and resolutions (20 and 50 km) and the statistical tool is the Cumulative Distribution Function-transform (CDF-t). To achieve a spatially resolved downscaling over the Mediterranean basin, the European Climate Assessment and Dataset (ECA&D) gridded dataset is used for calibration and evaluation of the downscaling models. In the frame of HyMeX and MED-CORDEX international programs, the downscaling is performed on ERA-I reanalysis over the 1989–2008 period. The results show that despite local calibration, CDF-t produces more accurate spatial variability of near-surface temperature and rainfall with respect to ECA&D than WRF which solves the three-dimensional equation of conservation. This first suggests that at 20–50 km resolutions, these three-dimensional processes only weakly contribute to the local value of temperature and precipitation with respect to local one-dimensional processes. Calibration of CDF-t at each individual grid point is thus sufficient to reproduce accurately the spatial pattern. A second explanation is the use of gridded data such as ECA&D which smoothes in part the horizontal variability after data interpolation and damps the added value of dynamical downscaling. This explains partly the absence of added-value of the 2-stage downscaling approach which combines statistical and dynamical downscaling models. The temporal variability of statistically downscaled temperature and rainfall is finally strongly driven by the temporal variability of its forcing (here ERA-Interim or WRF simulations). CDF-t is thus efficient as a bias correction tool but does not show any added-value regarding the time variability of the downscaled field. Finally, the quality of the reference observation dataset is a key issue. Comparison of CDF-t calibrated with ECA&D dataset and WRF simulations to local measurements from weather stations not assimilated in ECA&D, shows that the temporal variability of the downscaled data with respect to the local observations is closer to the local measurements than to ECA&D data. This highlights the strong added-value of dynamical downscaling which improves the temporal variability of the atmospheric dynamics with regard to the driving model. This article highlights the benefits and inconveniences emerging from the use of both downscaling techniques for climate research. Our goal is to contribute to the discussion on the use of downscaling tools to assess the impact of climate change on regional scales.     

Possible influence of western North Pacific monsoon on TC activity in mid-latitudes of East Asia

The interannual variation of East Asia summer monsoon (EASM) rainfall exhibits considerable differences between early summer [May–June (MJ)] and peak summer [July–August (JA)]. The present study focuses on peak summer. During JA, the mean ridge line of the western Pacific subtropical High (WPSH) divides EASM domain into two sub-domains: the tropical EA (5°N–26.5°N) and subtropical-extratropical EA (26.5°N–50°N). Since the major variability patterns in the two sub-domains and their origins are substantially different, the Part I of this study concentrates on the tropical EA or Southeast Asia (SEA). We apply the predictable mode analysis approach to explore the predictability and prediction of the SEA peak summer rainfall. Four principal modes of interannual rainfall variability during 1979–2013 are identified by EOF analysis: (1) the WPSH-dipole sea surface temperature (SST) feedback mode in the Northern Indo-western Pacific warm pool associated with the decay of eastern Pacific El Niño/Southern Oscillation (ENSO), (2) the central Pacific-ENSO mode, (3) the Maritime continent SST-Australian High coupled mode, which is sustained by a positive feedback between anomalous Australian high and sea surface temperature anomalies (SSTA) over Indian Ocean, and (4) the ENSO developing mode. Based on understanding of the sources of the predictability for each mode, a set of physics-based empirical (P-E) models is established for prediction of the first four leading principal components (PCs). All predictors are selected from either persistent atmospheric lower boundary anomalies from March to June or the tendency from spring to early summer. We show that these four modes can be predicted reasonably well by the P-E models, thus they are identified as the predictable modes. Using the predicted PCs and the corresponding observed spatial patterns, we have made a 35-year cross-validated hindcast, setting up a bench mark for dynamic models’ predictions. The P-E hindcast prediction skill represented by domain-averaged temporal correlation coefficient is 0.44, which is twice higher than the skill of the current dynamical hindcast, suggesting that the dynamical models have large rooms to improve. The maximum potential attainable prediction skills for the peak summer SEA rainfall is also estimated and discussed by using the PMA. High predictability regions are found over several climatological rainfall centers like Indo-China peninsula, southern coast of China, southeastern SCS, and Philippine Sea.     

Simulated ENSO-tropical rainfall teleconnections in present-day and under enhanced greenhouse gases conditions

El-Niño/Southern Oscillation (ENSO) variability and its relationship with precipitation in the tropics and subtropics are analysed using the ARPEGE-OPA ocean-atmosphere coupled model. Three 150-year simulations are considered, differing by greenhouse gases (GHG) and aerosols concentrations. The first one has constant (1950 level) concentrations, and the two others follow observed values till 1999, then the SRES B2 scenario until 2099. The model is able to reproduce most present-day features characteristic of ENSO in the Pacific. It also displays ENSO as the leading mode of sea-surface temperature (SST) variability, with spatial patterns and explained variance both quite similar to the observation. A detailed analysis of its teleconnections with rainfall variability is carried out on a seasonal basis. Patterns for the last part of the twentieth century compare favourably with the observation, with the notable exception of parts of the Atlantic sector. The overall strong rainfall response arises from the strong interannual variability of simulated ENSO, and also suggests an ability to simulate atmospheric dynamics in a realistic way. In the future climate, the model does not exhibit major changes in the ENSO/rainfall teleconnections. However, on a regional basis, there is some evidence of strengthening (e.g., in parts of Southern Africa) and weakening (e.g., East Africa) in the course of the twenty-first century. In most cases, decadal swings in the correlations suggest that these alterations may partly reflect natural changes in the teleconnections with ENSO, long-term correlation trends (possibly GHG-induced) being comparatively weaker.     

African monsoon teleconnections with tropical SSTs: validation and evolution in a set of IPCC4 simulations

A set of 12 state-of-the-art coupled ocean-atmosphere general circulation models (OAGCMs) is explored to assess their ability to simulate the main teleconnections between the West African monsoon (WAM) and the tropical sea surface temperatures (SSTs) at the interannual to multi-decadal time scales. Such teleconnections are indeed responsible for the main modes of precipitation variability observed over West Africa and represent an interesting benchmark for the models that have contributed to the fourth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC4). The evaluation is based on a maximum covariance analysis (MCA) applied on tropical SSTs and WAM rainfall. To distinguish between interannual and multi-decadal variability, all datasets are partitioned into low-frequency (LF) and high-frequency (HF) components prior to analysis. First applied to HF observations, the MCA reveals two major teleconnections. The first mode highlights the strong influence of the El Niño Southern Oscillation (ENSO). The second mode reveals a relationship between the SST in the Gulf of Guinea and the northward migration of the monsoon rainbelt over the West African continent. When applied to HF outputs of the twentieth century IPCC4 simulations, the MCA provides heterogeneous results. Most simulations show a single dominant Pacific teleconnection, which is, however, of the wrong sign for half of the models. Only one model shows a significant second mode, emphasizing the OAGCMs’ difficulty in simulating the response of the African rainbelt to Atlantic SST anomalies that are not synchronous with Pacific anomalies. The LF modulation of these HF teleconnections is then explored through running correlations between expansion coefficients (ECs) for SSTs and precipitation. The observed time series indicate that both Pacific and Atlantic teleconnections get stronger during the twentieth century. The IPCC4 simulations of the twentieth and twenty-first centuries do not show any significant change in the pattern of the teleconnections, but the dominant ENSO teleconnection also exhibits a significant strengthening, thereby suggesting that the observed trend could be partly a response to the anthropogenic forcing. Finally, the MCA is also applied to the LF data. The first observed mode reveals a well-known inter-hemispheric SST pattern that is strongly related to the multi-decadal variability of the WAM rainfall dominated by the severe drying trend from the 1950s to the 1980s. Whereas recent studies suggest that this drying could be partly caused by anthropogenic forcings, only 5 among the 12 IPCC4 models capture some features of this LF coupled mode. This result suggests the need for a more detailed validation of the WAM variability, including a dynamical interpretation of the SST–rainfall relationships.     

The Indian summer monsoon drought of 2002 and its linkage with tropical convective activity over northwest Pacific

The Indian subcontinent witnessed a severe monsoon drought in 2002, which largely resulted from a major rainfall deficiency in the month of July. While moderate El Nino conditions prevailed during this period, the atmospheric convective activity was anomalously enhanced over northwest and north-central Pacific in the 10–20°N latitude belt; and heavy rainfall occurred over this region in association with a series of northward moving tropical cyclones. Similar out-of-phase rainfall variations over the Indian region and the northwest (NW) Pacific have been observed during other instances of El Nino/Southern Oscillation (ENSO). The dynamical linkage corresponding to this out-of-phase rainfall variability is explored in this study by conducting a set of numerical experiments using an atmospheric general circulation model. The results from the model simulations lend credence to the role of the tropical Pacific sea surface temperature anomalies in forcing the out-of-phase precipitation variability over the NW Pacific and the Indian monsoon region. It is seen that the ENSO induced circulation response reveals an anomalous pattern comprising of alternating highs and lows which extend meridionally from the equatorial region into the sub-tropic and mid-latitude regions of west-central Pacific. This meridional pattern is associated with an anomalous cyclonic circulation over NW Pacific, which is found to favor enhanced tropical cyclonic activity and intensified convection over the region. In turn, the intensified convection over NW Pacific induces subsidence and rainfall deficiency over the Indian landmass through anomalous east-west circulation in the 10–20°N latitude belt. Based on the present findings, it is suggested that the convective activity over NW Pacific is an important component in mediating the ENSO-monsoon teleconnection dynamics.     

Interannual variability and predictability of African easterly waves in a GCM

The interannual variability of African Easterly Waves (AEWs) is assessed with the help of spatio-temporal spectral analysis (STSA) and complex empirical orthogonal functions methods applied to the results of ten-member multiyear ensemble simulations. Two sets of experiments were conducted with the Météo-France ARPEGE-Climat GCM, one with interactive soil moisture (control), and the other with soil moisture relaxed towards climatological monthly means calculated from the control. Composites of Soudano–Sahelian AEWs were constructed and associated physical processes and dynamics were studied in the frame of the waves. It is shown that the model is able to simulate realistically some interannual variability in the AEWs, and that this dynamical aspect of the West African climate is potentially predictable (i.e. signal can be extracted from boundary conditions relatively to internal error of the GCM), especially along the moist Guinean coast. Compared with ECMWF 15-year reanalysis (ERA15), the maximum activity of AEWs is located too far to the South and is somewhat too zonal, but the main characteristics of the waves are well represented. The major impact of soil moisture relaxation in the GCM experiments is to reduce the seasonal potential predictability of AEWs over land by enhancing their internal variability.     

Seasonality and time scales in the relationship between global SST and African rainfall

The main goal of this study is to determine the oceanic regions corresponding to variability in African rainfall and seasonal differences in the atmospheric teleconnections. Canonical correlation analysis (CCA) has been applied in order to extract the dominant patterns of linear covariability. An ensemble of six simulations with the global atmospheric general circulation model ECHAM4, forced with observed sea surface temperatures (SSTs) and sea ice boundary variability, is used in order to focus on the SST-related part of African rainfall variability. Our main finding is that the boreal summer rainfall (June–September mean) over Africa is more affected by SST changes than in boreal winter (December–March mean). In winter, there is a highly significant link between tropical African rainfall and Indian Ocean and eastern tropical Pacific SST anomalies, which is closely related to El Niño-Southern Oscillation (ENSO). However, long-term changes are found to be associated with SST changes in the Indian and tropical Atlantic Oceans, thus, showing that the tropical Atlantic plays a critical role in determining the position of the intertropical convergence zone (ITCZ). Since ENSO is less in summer, the tropical Pacific and the Indian Oceans are less important for African rainfall. The African summer monsoon is strongly influenced by SST variations in the Gulf of Guinea, with a response of opposite sign over the Sahelian zone and the Guinean coast region. SST changes in the subtropical and extratropical oceans mostly take place on decadal time scales and are responsible for low-frequency rainfall fluctuations over West Africa. The modelled teleconnections are highly consistent with the observations. The agreement for most of the teleconnection patterns is remarkable and suggests that the modelled rainfall anomalies serve as suitable predictors for the observed changes.     

Skill, reproducibility and potential predictability of the West African monsoon in coupled GCMs

In the framework of the ENSEMBLES FP6 project, an ensemble prediction system based on five different state-of-the-art European coupled models has been developed. This study evaluates the performance of these models for forecasting the West African monsoon (WAM) at the monthly time scale. From simulations started the 1 May of each year and covering the period 1991–2001, the reproducibility and potential predictability (PP) of key parameters of the WAM—rainfall, zonal and meridional wind at four levels from the surface to 200 hPa, and specific humidity, from July to September—are assessed. The Sahelian rainfall mode of variability is not accurately reproduced contrary to the Guinean rainfall one: the correlation between observations (from CMAP) and the multi-model ensemble mean is 0.17 and 0.55, respectively. For the Sahelian mode, the correlation is consistent with a low PP of about ~6%. The PP of the Guinean mode is higher, ~44% suggesting a stronger forcing of the sea surface temperature on rainfall variability over this region. Parameters relative to the atmospheric dynamics are on average much more skillful and reproducible than rainfall. Among them, the first mode of variability of the zonal wind at 200 hPa that depicts the Tropical Easterly Jet, is correlated at 0.79 with its “observed” counterpart (from the NCEP/DOE2 reanalyses) and has a PP of 39%. Moreover, models reproduce the correlations between all the atmospheric dynamics parameters and the Sahelian rainfall in a satisfactory way. In that context, a statistical adaptation of the atmospheric dynamic forecasts, using a linear regression model with the leading principal components of the atmospheric dynamical parameters studied, leads to moderate receiver operating characteristic area under the curve and correlation skill scores for the Sahelian rainfall. These scores are however much higher than those obtained using the modelled rainfall.     

Interannual variability of rainfall over the Sahel based on multiple regional climate models simulations

We analyse the interannual variability of the averaged summer monsoon rainfall over the Sahel from multiple regional climate models driven by the ERA-interim reanalysis and seek to provide effective information for future modelling work. We find that the majority of the models are able to reproduce the rainfall variability with correlation coefficient exceeding 0.5 compared with observations. This is due to a good representation of the dynamics of the main monsoon features of the West African climate such as the monsoon flux, African Easterly Jet (AEJ) and Tropical Easterly Jet (TEJ). Among the models, only HIRHAM fails to reproduce the rainfall variability exhibiting hence a correlation coefficient of ?0.2. This deficiency originates from the fact that HIRHAM does not properly capture the variability of monsoon flow and the relationship between rainfall and the AEJ dynamic. We conclude that a good performance of a regional climate model in simulating the monsoon dynamical features variability is of primary importance for a better representation of the interannual variability of rainfall over the Sahel.     

Teleconnections and predictive characteristics of Australian seasonal rainfall

A new methodology is proposed that allows patterns of interannual covariability, or teleconnections, between the intraseasonal and slow components of seasonal mean Australian rainfall and the corresponding components in the Southern Hemisphere atmospheric circulation to be estimated. In all seasons, the dominant rainfall–circulation teleconnections in the intraseasonal component are shown to have the characteristic features associated with well-known intraseasonal dynamical and statistical atmospheric modes and their relationship with rainfall. Thus, for example, there are patterns of interannual covariability that reflect rainfall relationships with the intraseasonal Southern Annular Mode, the Madden-Julian Oscillation and wavenumber 3 and 4 intraseasonal modes of variability. The predictive characteristics of the atmospheric circulation–rainfall relationship are shown to reside with the slow components. In all seasons, we find rainfall–circulation teleconnections in the slow components related to the El Niño-Southern Oscillation. Each season also has a coupled mode, with a statistically significant trend in the time series of the atmospheric component that appears to be related to recent observed trends in rainfall. The slow Southern Annular Mode also features in association with southern Australian rainfall, especially during austral winter and spring. There is also evidence of an influence of Indian Ocean sea surface temperature variability on rainfall in southeast Australia during austral winter and spring.     

Intra-seasonal rainfall and piped water revenue variability in rural Africa

Rainfall patterns influence water usage and revenue from user payments in rural Africa. We explore these dynamics by examining monthly rainfall against 4,888 records of rural piped water revenue in Ghana, Rwanda, and Uganda and quantifying revenue changes over 635 transitions between dry and wet seasons.Results show operators experience revenue variability at regional and intra-seasonal scales. Revenues fall by an average of 30 percent during the wettest months of the year in climate regimes with consistent wet season rainfall. However, seasonally stable revenues are observed in areas where consecutive dry days are common during the wet season, potentially reflecting a dependency on reliable services. We also find changes in tariff level, waterpoint connection type, and payment approach do not consistently prevent or increase seasonal revenue variability.Local revenue generation underpins delivery of drinking water services. Where rainfall patterns remain consistent, piped water operators can expect to encounter seasonal revenue reductions regardless of whether services are provided on or off premises and of how services are paid for. Revenue projections that assume consistent volumetric demand year-round may lead to shortfalls that threaten sustainability and undermine the case for future investment. Intra-seasonal rainfall analysis can enhance rural piped water revenue planning by offering localised insight into demand dynamics and revealing where climate variability may increase dependency on reliable services.     

The impacts of the Indian summer rainfall on North China summer rainfall

Previous studies have indicated a connection between interannual variations of the Indian and North China summer rainfall. An atmospheric circulation wave pattern over the mid-latitude Asia plays an important role in the connection. The present study compares the influence of the above-normal and below-normal Indian summer rainfall on the North China summer rainfall variations. Composite analysis shows that the mid-latitude Asian atmospheric circulation and the North China rainfall anomalies during summer tend to be anti-symmetric in above-normal and below-normal Indian rainfall years. Analysis indicates that the Indian-North China summer rainfall relation tends to be stronger when larger Indian rainfall anomaly occurs during a higher mean rainfall period. The observed long-term change in the Indian-North China summer rainfall relationship cannot be explained by the impact of the El Niño-Southern Oscillation (ENSO). The present study evaluates the Indian-North China summer rainfall relationship in climate models. Analysis shows that the Indian-North China summer rainfall relationship differs largely among different climate models and among different simulations of a specific model. The relationship also displays obvious temporal variations in both individual and ensemble mean model simulations. This suggests an important role of the atmospheric internal variability in the change of the Indian-North China summer rainfall relationship.     

Assessment of Indian summer monsoon simulation by Community Atmosphere Model (CAM3)

Seasonal prediction of Indian Summer Monsoon (ISM) has been attempted for the current year 2011 using Community Atmosphere Model (CAM) developed at the National Centre for Atmospheric Research (NCAR). First, 30?years of model climatology starting from 1981 to 2010 has been generated to capture the variability of ISM over the Indian region using 30 seasonal simulations. The simulated model climatology has been validated with different sets of observed climatology, and it was observed that the simulated climatological rainfall is affected by model bias. Subsequently, a bias correction procedure using the Tropical Rainfall Measuring Mission (TRMM) 3B43 rainfall has been proposed. The bias-corrected rainfall climatology shows both spatial and temporal variability of ISM satisfactorily. Further, four sets of 10-member ensemble simulations of ISM 2009 and 2010 have been performed in hindcast mode using observed sea surface temperature (SST) and persistence of April SST anomaly, and it has been found that the bias-corrected model rainfall captures the seasonal variability of ISM reasonably well with some discrepancies in these two contrasting monsoon years. With this positive background, the seasonal prediction of ISM 2011 has been carried out in forecast mode with the assumption of persistence of May SST anomaly from June through September 2011. The model assessment shows an 11% deficiency in All-India Rainfall (AIR) of ISM 2011. In particular, the monthly accumulated rains are predicted to be 101% (17.6?cm), 86% (24.3?cm), 83% (21.0?cm) and 95% (15.5?cm) of normal AIR for the months of June, July, August and September, respectively.     

Intraseasonal oscillation of the rainfall variability over Rwanda and evaluation of its subseasonal forecasting skill

非洲中东部地区的经济主要依靠自给农业支撑,该地区农业经济对降水的变化尤为敏感.本文以卢旺达为例,观测分析指出卢旺达的次季节降雨主要集中在10-25天;根据次季节尺度降水变率的单点相关方法,发现卢旺达的次季节降水变率和周围区域变化一致;进一步合成结果显示该地区次季节降水变率与异常西风有关,这可追溯到赤道地区西传的赤道Rossby波.最后,本文评估了当前动力模式ECMWF对 卢旺达地区(即非洲中东部)次季节降水变率的预报能力,发现EC模式在对该区域降水和相关风场指数的预报技巧都在18天左右,且预报技巧表现出一定的年际差异,这可能与热带太平洋的背景海温信号有关.该工作增进了当 前对非洲中东部地区的次季节降水变率和预测水平的认知,并且对该地区国家粮食安全和防灾减灾具有启示性意义.     

Stochastic and deterministic multicloud parameterizations for tropical convection

Despite recent advances in supercomputing, current general circulation models poorly represent the variability associated with organized tropical convection. In a recent study, the authors have shown, in the context of a paradigm two baroclinic mode system, that a stochastic multicloud convective parameterization based on three cloud types (congestus, deep and stratiform) can be used to improve the variability and the dynamical structure of tropical convection. Here, the stochastic multicloud model is modified with a lag type stratiform closure and augmented with an explicit mechanism for congestus detrainment moistening. These modifications improve the representation of intermittent coherent structures such as synoptic and mesoscale convective systems. Moreover, the new stratiform-lag closure allows for increased robustness of the coherent features of the model with respect to the amount of stochastic noise and leading to a multi-scale organization of slowly moving waves envelopes in which short-lived and chaotic convective events persist. Congestus cloud decks dominate the suppressed-dry phase of the wave envelopes. The simulations with the new closure have a higher amount of stochastic noise and result in a Walker type circulation with realistic mean and coherent variability which surpasses results of previous deterministic and stochastic multicloud models in the same parameter regime. Further, deterministic mean field limit equations (DMFLE) for the stochastic multicloud model are considered. Aside from providing a link to the deterministic multicloud parameterization, the DMFLE allow a judicious way of determining the amount of deterministic and stochastic “chaos” in the system. It is shown that with the old stratiform heating closure, the stochastic process accounts for most of the chaotic behavior. The simulations with the new stratiform heating closure exhibit a mixture of stochastic and deterministic chaos. The highly chaotic dynamics in the simulations with congestus detrainment mechanism is due to the strongly nonlinear and numerically stiff deterministic dynamics. In the latter two cases, the DMFLE can be viewed as a “standalone” parameterization, which is capable of capturing some dynamical features of the stochastic parameterization. Furthermore, it is shown that, in spatially extended simulations, the stochastic multicloud model can capture qualitatively two local statistical features of the observations: long and short auto-correlation times of moisture and precipitation, respectively and the approximate power-law in the probability density of precipitation event size for large precipitation events. The latter feature is not reproduced in the column simulations. This fact underscores the importance of gravity waves and large scale moisture convergence.     

Can a 25-year trend in Soudano-Sahelian vegetation dynamics be interpreted in terms of land use change? A remote sensing approach

This study is based on the premise that, in the Sahel/Sudanian belt of Africa, the main determinants of interannual variation in vegetation dynamics are rainfall and land cover type. We analyzed the spatio-temporal sensitivity of the NOAA-AVHRR 8 km-resolution vegetation index (NDVI) to (i) annual rainfall variability (0.5° × 0.5° resolution) acquired over a 25-year period (1982-2006); and (ii) land use changes in the different eco-climatic regions of the Bani catchment in Mali (130 000 km²). During the period 1982-2006, there was no clear trend in rainfall over the catchment, whereas there was a strong positive trend in the NDVI, both when the NDVI values were corrected using annual rainfall variability and when they were not. We divided the catchment into three eco-climatic regions based on the relationship between the annual NDVI and rainfall. In each region, we analyzed the observed greening in relation to changes in land use after correcting for the effect of annual rainfall on the NDVI. Results show that there is a mixed level of agreement between the land cover changes at the grid cell scale and the spatial pattern of the NDVI trend. Increased cropping does not explain the increase in the annual NDVI, except in the Sahelian part of the catchment. We hypothesize that the natural vegetation dynamics related to the non-linear rainfall patterns during the 25-year study period were responsible for these results.     

A further assessment of vegetation feedback on decadal Sahel rainfall variability

The effect of vegetation feedback on decadal-scale Sahel rainfall variability is analyzed using an ensemble of climate model simulations in which the atmospheric general circulation model ICTPAGCM (“SPEEDY”) is coupled to the dynamic vegetation model VEGAS to represent feedbacks from surface albedo change and evapotranspiration, forced externally by observed sea surface temperature (SST) changes. In the control experiment, where the full vegetation feedback is included, the ensemble is consistent with the observed decadal rainfall variability, with a forced component 60 % of the observed variability. In a sensitivity experiment where climatological vegetation cover and albedo are prescribed from the control experiment, the ensemble of simulations is not consistent with the observations because of strongly reduced amplitude of decadal rainfall variability, and the forced component drops to 35 % of the observed variability. The decadal rainfall variability is driven by SST forcing, but significantly enhanced by land-surface feedbacks. Both, local evaporation and moisture flux convergence changes are important for the total rainfall response. Also the internal decadal variability across the ensemble members (not SST-forced) is much stronger in the control experiment compared with the one where vegetation cover and albedo are prescribed. It is further shown that this positive vegetation feedback is physically related to the albedo feedback, supporting the Charney hypothesis.     

Mediterranean wave climate variability and its links with NAO and Indian Monsoon

This study examines the variability of the monthly average significant wave height (SWH) field in the Mediterranean Sea, in the period 1958–2001. The analysed data are provided by simulations carried out using the WAM model (WAMDI group, 1988) forced by the wind fields of the ERA-40 (ECMWF Re-Analysis). Comparison with buoy observations, satellite data, and simulations forced by higher resolution wind fields shows that, though results underestimate the actual SWH, they provide a reliable representation of its real space and time variability. Principal component analysis (PCA) shows that the annual cycle is characterised by two main empirical orthogonal functions (EOF) patterns. Most inter-monthly variability is associated with the first EOF, whose positive/negative phase is due to the action of Mistral/Etesian wind regimes. The second EOF is related to the action of southerly winds (Libeccio and Sirocco). The annual cycle presents two main seasons, winter and summer characterised, the first, by the prevalence of eastwards and southeastwards propagating waves all over the basin, and the second, by high southwards propagating waves in the Aegean Sea and Levantin Basin. Spring and fall are transitional seasons, characterised by northwards and northeastwards propagating waves, associated to an intense meridional atmospheric circulation, and by attenuation and amplification, respectively, of the action of Mistral. These wave field variability patterns are associated with consistent sea level pressure (SLP) and surface wind field structures. The intensity of the SWH field shows large inter-annual and inter-decadal variability and a statistically significant decreasing trend of mean winter values. The winter average SWH is anti-correlated with the winter NAO (North Atlantic Oscillation) index, which shows a correspondingly increasing trend. During summer, a minor component of the wave field inter-annual variability (associated to the second EOF) presents a statistically significant correlation with the Indian Monsoon reflecting its influence on the meridional Mediterranean circulation. However, the SLP patterns associated with the SWH inter-annual variability reveal structures different from NAO and Monsoon circulation. In fact, wave field variability is conditioned by regional storminess in combination with the effect of fetch. The latter is likely to be the most important. Therefore, the inter-annual variability of the mean SWH is associated to SLP patterns, which present their most intense features above or close to Mediterranean region, where they are most effective for wave generation.

---

Dynamics of the Indian monsoon and ENSO relationships in the SINTEX global coupled model

This paper uses recent gridded climatological data and a coupled general circulation model (GCM) simulation in order to assess the relationships between the interannual variability of the Indian summer monsoon (ISM) and the El Niño-Southern Oscillation (ENSO). The focus is on the dynamics of the ISM-ENSO relationships and the ability of the state-of-the-art coupled GCM to reproduce the complex lead-lag relationships between the ISM and the ENSO. The coupled GCM is successful in reproducing the ISM circulation and rainfall climatology in the Indian areas even though the entire ISM circulation is weaker relative to that observed. In both observations and in the simulation, the ISM rainfall anomalies are significantly associated with fluctuations of the Hadley circulation and the 200 hPa zonal wind anomalies over the Indian Ocean. A quasi-biennial time scale is found to structure the ISM dynamical and rainfall indices in both cases. Moreover, ISM indices have a similar interannual variability in the simulation and observations. The coupled model is less successful in simulating the annual cycle in the tropical Pacific. A major model bias is the eastward displacement of the western North Pacific inter-tropical convergence zone (ITCZ), near the dateline, during northern summer. This introduces a strong semiannual component in Pacific Walker circulation indices and central equatorial Pacific sea surface temperatures. Another weakness of the coupled model is a less-than-adequate simulation of the Southern Oscillation due to an erroneous eastward extension of the Southern Pacific convergence zone (SPCZ) year round. Despite these problems, the coupled model captures some aspects of the interannual variability in the tropical Pacific. ENSO events are phase-locked with the annual cycle as observed, but are of reduced amplitude relative to the observations. Wavelet analysis of the model Niño34 time series shows enhanced power in the 2–4 year band, as compared to the 2–8 year range for observations during the 1950–2000 period. The ISM circulation is weakened during ENSO years in both the simulation and the observations. However, the model fails to reproduce the lead-lag relationship between the ISM and Niño34 sea surface temperatures (SSTs). Furthermore, lag correlations show that the delayed response of the wind stress over the central Pacific to ISM variability is insignificant in the simulation. These features are mainly due to the unrealistic interannual variability simulated by the model in the western North Pacific. The amplitude and even the sign of the simulated surface and upper level wind anomalies in these areas are not consistent with observed patterns during weak/strong ISM years. The ISM and western North Pacific ITCZ fluctuate independently in the observations, while they are negatively and significantly correlated in the simulation. This isolates the Pacific Walker circulation from the ISM forcing. These systematic errors may also contribute to the reduced amplitude of ENSO variability in the coupled simulation. Most of the unrealistic features in simulating the Indo-Pacific interannual variability may be traced back to systematic errors in the base state of the coupled model.     

A statistical�Cdynamical scheme for reconstructing ocean forcing in the Atlantic. Part I: weather regimes as predictors for ocean surface variables

The links between the observed variability of the surface ocean variables estimated from reanalysis and the overlying atmosphere decomposed in classes of large-scale atmospheric circulation via clustering are investigated over the Atlantic from 1958 to 2002. Daily 500?hPa geopotential height and 1,000?hPa wind anomaly maps are classified following a weather-typing approach to describe the North Atlantic and tropical Atlantic atmospheric dynamics, respectively. The algorithm yields patterns that correspond in the extratropics to the well-known North Atlantic-Europe weather regimes (NAE-WR) accounting for the barotropic dynamics, and in the tropics to wind classes (T-WC) representing the alteration of the trades. 10-m wind and 2-m temperature (T2) anomaly composites derived from regime/wind class occurrence are indicative of strong relationships between daily large-scale atmospheric circulation and ocean surface over the entire Atlantic basin. High temporal correlation values are obtained basin-wide at low frequency between the observed fields and their reconstruction by multiple linear regressions with the frequencies of occurrence of both NAE-WR and T-WC used as sole predictors. Additional multiple linear regressions also emphasize the importance of accounting for the strength of the daily anomalous atmospheric circulation estimated by the combined distances to all regimes centroids in order to reproduce the daily to interannual variability of the Atlantic ocean. We show that for most of the North Atlantic basin the occurrence of NAE-WR generally sets the sign of the ocean surface anomaly for a given day, and that the inter-regime distances are valuable predictors for the magnitude of that anomaly. Finally, we provide evidence that a large fraction of the low-frequency trends in the Atlantic observed at the surface over the last 50?years can be traced back, except for T2, to changes in occurrence of tropical and extratropical weather classes. All together, our findings are encouraging for the prospects of basin-scale ocean dynamical downscaling using a weather-typing approach to reconstruct forcing fields for high resolution ocean models (Part II) from coarse resolution climate models.