Variability and Predictability of West African Droughts: A Review on the Role of Sea Surface Temperature Anomalies
ABSTRACT
The Sahel experienced a severe drought during the 1970s and 1980s after wet periods in the 1950s and 1960s. Although rainfall partially recovered since the 1990s, the drought had devastating impacts on society. Most studies agree that this dry period resulted primarily from remote effects of sea surface temperature (SST) anomalies amplified by local land surface-atmosphere interactions. This paper reviews advances made during the last decade to better understand the impact of global SST variability on West African rainfall at interannual to decadal time scales. At interannual time scales, a warming of the equatorial
1. Introduction
The number of scientific papers motivated by different aspects of Sahel rainfall has increased exponentially since the 1950s (see Fig. 2), from around 150 to more than 5000 entries in the period from January to
The rainy season in the Sahel has large interannual and decadal variations. A substantial part of this variability is due to the influence of slowly varying climate subcomponents, such as sea surface temperatures (SSTs) and land surface conditions. The importance of oceanic influences at interannual and decadal time scales has been supported by the results of several studies (Folland et al. 1986; Palmer 1986; Rowell et al. 1992;
The existence of significant impacts on WAM rainfall of slowly varying climate subcomponents indicates the potential for useful long-range forecasts (Vellinga et al. 2013; Gaetani and Mohino 2013; García-Serrano et al. 2013). To realize this potential with climate models, these must successfully reproduce the important characteristics of the WAM precipitation and circulation. Despite continuous model improvements in the models, a skillful simulation and prediction of the WAM, including its variability at different time and spatial scales and its association with external forcings, remains a daunting task.
The present paper surveys the literature on drought in
The text is organized as follows. We start in section 2 and 3 by surveying the state-of-the-art knowledge of the SST influence on Sahel rainfall at interannual to decadal time scales, at which the variability of the ocean is the main driver of that in the atmosphere. Next, we summarize the progress in seasonal (section 5) to decadal predictability (section 6) and its skill in
2. SST influence at interannual time scales
This section is dedicated to review recent findings on the influence of SST anomalies in different ocean basins (the Atlantic, Pacific, and Indian Oceans and the
a. Influence of the tropical
Since the early papers by Hastenrath and Lamb (1977), Lamb (1978),andHastenrath (1984), many others have documented the tropical Atlantic influence on West African rainfall. This influence unfolds at different time scales: the variability in the equatorial and southern sectors affects that in interannual time scales, while that in the northern sector affects that in decadal time scales (Hastenrath and Polzin 2011).
At interannual time scales, the leading mode of tropical Atlantic variability is the Atlantic Niño, also known as the equatorial mode or zonal mode (Zebiak 1993; Carton et al. 1996). This coupled atmosphere- ocean mode is characterized by a warming (cooling) of the equatorial Atlantic during the boreal spring-summer in association with a relaxation (strengthening) of the trades and a deepening (shallowing) of the eastern equatorial thermocline. Several works using different methodologies have concluded that events of positive SST anomalies (Atlantic Niños) originate a dipole pattern of precipitation anomalies consisting of positive values along the coast of
Most current state-of-the-art atmospheric GCMs (AGCMs) are able to capture the links between SST anomalies and anomalous precipitation over
Complementary to works examining the impacts of SST anomalies in the tropical Atlantic, Nnamchi and Li (2011) highlighted the importance of anomalies in the subtropical South Atlantic together with temperature anomalies with the opposite sign at the equator forming a
b. Influence of the
The finding of relationships between Mediterranean climate variability and WAM dynamics motivated a new line of research in the last decade. Rowell (2003) showed that positive SST anomalies in the
More recently, a number of empirical and numerical studies have provided further support to the links between anomalies in Mediterranean SSTs and WAM precipitation (Jung et al. 2006; Fontaine et al. 2011b; Polo et al. 2011). Peyrillé et al. (2007) and Peyrillé and Lafore (2007) described the local circulations and mechanisms favoring the northward migration of the monsoon rainbelt. Fontaine et al. (2010) provided evidence that warm events over the
c. Influence of the
At interannual time scales, a warming in the tropical Pacific tends to be associated with increased precipitation over the Gulf of
In the framework of AMMA, experiments on the sensitivity of WAM rainfall to SST anomalies in the Pacific were performed for the period 1979-2002. In general, the results showed that positive SST anomalies in the Pacific SST have negative effects on Sahel rainfall (Mohino et al. 2011c). Figure 5 shows composites of rainfall differences between years with both warmer and colder than average SSTs in the
It has been shown using observational data that links between anomalies in WAM rainfall and Pacific SSTs occur during the developing phase of an El Niño- Southern Oscillation (ENSO) event. That is, the anomaly in WAM appears in boreal summer before the peak of ENSO in autumn-winter. CGCMs have difficulties in capturing the temporal aspects of these connections, as shown by Joly and Voldoire (2009) for CMIP3 models. These model difficulties were attributed to shortcomings in the simulation of ENSO locking to the seasonal cycle and the associated atmospheric teleconnections.
d. Influence of the Indian Ocean
e. Modulation of the interannual variability by lower-frequency variations
Studies performed in the last decades have argued that the impact of SST anomalies in some basins appear to be different depending on the decades considered. We will refer to this property as ''nonstationarity.''
The links between SST anomalies in the equatorial Atlantic and rainfall over the Gulf of
A similar tendency to nonstationarity appears in the impact of SST anomalies in the
Broadly, two explanations have been offered for the nonstationarity of impacts. First, nonstationarity might be simply an artifact of sampling errors because some variation in the correlation between two variables can be expected by chance even during a stationary period of climate. Rowell (2013) addressed this hypothesis by applying a bootstrap resampling technique to SST connections to rainfall. He found no reason to reject the hypothesis that nonstationarity and multidecadal variability in the strength of these teleconnections might arise only from sampling variability, at least for the specific SST and rainfall in the regions considered. Internal atmospheric variability could also be relevant even at these longer time scales. For instance, Traore (2011) showed that running a AGCM over one to several centuries with fixed SST patterns (either the 1955- 65 ''moist'' SST pattern or 1975-85 ''dry'' pattern) can provide decadal-scale rainfall anomalies up to 20% of the difference between the ''moist'' and ''wet'' long-term rainfall averages. Second, nonstationary teleconnections could be due to the slowly varying oceans and their multidecadal modes, as will be discussed later. These can alter the mean state of the atmosphere and/or the magnitude of SST variability in a way that during some decades the Atlantic influence interferes with that from the Pacific, whereas in other decades the Atlantic influence acts in isolation from the rest of the tropical basins (Mohino et al. 2011b).
3. Variability at decadal time scales
The first hypothesis on the prolonged Sahelian drought was that a decrease in vegetation cover led to increased albedo and, consequently, to enhanced subsidence in the region (Charney 1975). Later studies, however, identified the crucial role of SSTs over the world ocean in driving decadal Sahelian rainfall variability at decadal time scales. Using observed SSTs as boundary conditions, most AGCMs are able to reproduce the twentieth-century drying trend in
a. Role of SST anomalies
Decreased Sahel rainfall at decadal time scales has been associated with the warming of the tropical SSTs (Giannini et al. 2003, 2013; Lu and Delworth 2005; Mohino et al. 2011a). Hagos and Cook (2008) suggested that the combination of the SST anomalies over the tropical Indian and Atlantic Ocean basins was responsible for the 1980s Sahel drought and subsequent recovery in the 1990s. Caminade and Terray (2010) highlighted the role of the warming of the Pacific basin in reducing Sahel rainfall, while other works suggested that the drought was driven by the warming trend of the Indian Ocean basin during the late twentieth century (Bader and Latif 2003; Giannini et al. 2003; Tippett and Giannini 2006; Lu 2009). This warming of the tropical Indian Ocean and/or Pacific basin would induce enhanced convection locally and the propagation of Kelvin and Rossby waves that would communicate the tropospheric warming to
Alternatively, Sahel drought at decadal time scales has been related to the impacts of an interhemispheric dipole pattern of SST anomalies that is global, but most pronounced in the Atlantic basin (Folland et al. 1986; Palmer 1986). The differential heating of the Northern and Southern Hemisphere leads to a meridional shift of the ITCZ (Zhang and Delworth 2006; Kang et al. 2009; Hwang et al. 2013) and anomalous rainfall in the Sahel (Hoerling et al. 2006; Knight et al. 2006; Ting et al. 2009, 2011; Mohino et al. 2011a). Mechanistically, the movement of the rainbelt in the Sahel might occur through changes in the moisture content of the monsoon flow (Giannini et al. 2013) or circulation changes linked to a strengthening of the Saharan heat low (Martin and Thorncroft 2014a).
The relative importance of SST anomalies in different basins on Sahel rainfall has been greatly debated (e.g., Hoerling et al. 2006; Giannini et al. 2003; Bader and Latif 2003), partly because the sensitivity to each basin appears to be highly model dependent (Scaife et al. 2009; Biasutti et al. 2008) and partly because the details of the warming pattern matter greatly (Hagos and Cook 2008). Yet, recent work by Giannini et al. (2013) suggests that these differences might be reconciled by assuming that Sahel rainfall responds to relative changes between SST anomalies in the northern Atlantic and the entire tropics.
The broad agreement of the scientific community on SST anomalies being crucial drivers of Sahel rainfall decadal variability during the twentieth century has spurred a lively debate on whether this variability might be due to external forcings (anthropogenic and natural emissions) or to internal climate processes (natural variability modes) or, more likely, to a combination of the two. Recently, Mohino et al. (2011a) interpreted the pattern of SST variations linked to SST rainfall changes as a combination of three different modes of SST decadal variability: the response to the global warming trend, the positive phase of the interdecadal Pacific oscillation (Zhang et al. 1997), also known as the Pacific decadal oscillation (Mantua et al. 1997), and the negative phase of the Atlantic multidecadal oscillation (AMO; Knight et al. 2005), with all three leading to reductions in Sahel precipitation. Some works suggests that the observed AMO is an internal mode of variability not explained by external forcings (Knight et al. 2005; Knight 2009; Ting et al. 2009; 2011), while others point to the role of anthropogenic aerosols in cooling the North Atlantic more than the South Atlantic (Rotstayn and Lohmann 2002; Biasutti and Giannini 2006; Kawase et al. 2010; Ackerley et al. 2011; Biasutti 2011). Recently, Booth et al. (2012) showed that their CGCM experiments could simulate most of the observed twentieth-century SST variability in the North Atlantic, and that this variability was highly dependent on the indirect effect of aerosols. However, Zhang et al. (2013) call into question these results as there are multiple inconsistencies between the previous experiments and key aspects of observed variability within and without the North Atlantic.
Hoerling et al. (2006) and Lau et al. (2006) analyzed historical simulations of CGCMs participating in the CMIP3. Overall, the models failed to simulate the midtwentieth-century Sahel drought and recent recovery (Hoerling et al. 2010) with the correct magnitude and timing, suggesting that anthropogenic forcings played little or no role in driving the drought. On the other hand, Held et al. (2005) showed that the GFDL CM2.0 and CM2.1 coupled models could very well reproduce the observed drying trend during the second half of the twentieth century. Ackerley et al. (2011) suggested that although the aerosols contributed to the intense decline in the rainfall over the Sahel in the 1950-80 period, a fraction of this drying could be related to either the effect of an internal mode (AMO) or climate model deficiencies. Biasutti and Giannini (2006) estimated from historical CMIP3 simulations that anthropogenic forcing, especially by aerosols, may have contributed a third of the long-term twentieth-century drying, and that estimate has been confirmed by CMIP5 models (Biasutti 2013). Recently, Hwang et al. (2013) posited that both the drought and subsequent recovery in the Sahel are greatly influenced by the increase and subsequent reduction of sulfate emissions in
Analyses of simulations by recent generations of CGCMs have provided additional insight on the WAM and its variability (Fig. 7). Control runs, historical simulations, future projections, and seasonal-to-decadal predictions have been analyzed. Rowell (2013) has recently assessed the capability of Sahel models to represent WAM teleconnections. His work suggests that some teleconnections tend to be poorly reproduced (e.g., those with the equatorial Atlantic SSTs and the Pacific ENSO), while others seem to be captured by most models (e.g., the link between the Mediterranean SSTs and Sahel rainfall).
b. Role of land surface processes
Pioneer projects as Hydrological Atmospheric Pilot Experiment (HAPEX) in the Sahel (Goutorbe et al. 1997) made a contribution to understanding the land surface processes in relation to the WAM variability. Since then, several studies have addressed the role of land surface processes in driving Sahel drought. Land surface parameterizations in the atmospheric models used in these studies cover a wide range of complexity (e.g., Laval and Picon 1986; Sud and Molud 1988; Xue et al. 1990; Eltahir and Gong 1996). Nevertheless, the results on sensitivity to land conditions in Sahel were quite consistent across models. Increases in albedo (soil moisture) produce negative (positive) feedbacks on rainfall, even the magnitude of the impacts is within a narrow range (Xue and Fennessy 2002). A proper evaluation of the surface feedback to climate can be obtained only when all relevant components of the surface energy and water balances are taken into account.
The impact of land degradation upon regional climate seasonal variability and drought events over the Sahel has been explored using a GCM coupled to a biophysical model (Xue et al. 2004a). According to the results, the primary effect of degrading savanna and shrub conditions in the Sahel is reduced evaporation. This is partially due to reduced net radiation because of higher albedo, but more importantly to lower leaf area index (LAI) and surface roughness length, and to higher stomatal resistance. The reduction in evaporation results in less convection and lower latent heating rates in the troposphere, in association with a relative subsidence, which in turn weakens the monsoon flow and reduces moisture flux convergence and lowers rainfall.
It has also been found that the Sahel, along with a few other regions that are mostly semiarid, has the largest soil moisture/climate coupling strength in the world. This result was obtained in the Global Land-Atmosphere Coupling Experiment (GLACE;
The impact of the vegetation biophysical processes (VBP; i.e., land surface processes relevant to climate interactions associated with vegetation) on the WAM has also been investigated by Xue et al. (2004b, 2010b), who analyzed the results from two AGCMs coupled to three different land models with varying degrees of physically based complexity in the representation of VBP. The criterion to assess the importance of VBP effects was based on the simulation skill in reproducing the observed global precipitation under the assumption that their inclusion would improve precipitation simulations. Figure 8 shows the reduction in absolute seasonal mean bias of 5-yr mean simulated precipitation (or improved prediction skill) due to VBP processes. Accordingly,
The numerical experiments described so far in this section prescribe land conditions. Other experiments have also been performed allowing for two-way vegetation- climate interactions (i.e., land surface conditions are not specified but predicted). Using a simple dynamic vegetation model coupled with the Quasi-Equilibrium Tropical Circulation Model (QTCM), Zeng et al. (1999) showed that the best reproduction of the observed interannual precipitation variability over the Sahel during the past half century was obtained when interactions among vegetation, soil, and ocean components were all included. Wang et al. (2004) investigated the impact of large-scale oceanic forcing and local vegetation feedback on the variability of Sahel rainfall using a global biosphere-atmosphere model. When vegetation was dynamic, the model realistically reproduced the multidecadal-scale fluctuation of rainfall in the Sahel region. However, when the vegetation was kept static, the rainfall regime was characterized by fluctuations at much shorter time scales. This suggests that vegetation dynamics acts as a mechanism for the persistence of the regional climate. Kucharski et al. (2013) obtained a similar result and showed that about 60% of the observed Sahel drought could be reproduced if vegetation dynamics were included in their AGCM ensemble simulations, whereas only 30% could be reproduced if vegetation feedbacks were static. Furthermore, Kucharski et al. (2013) demonstrated that the dominant positive feedback mechanism for the vegetation impact on the Sahel drought is the albedo feedback, in accordance with early work by Charney (1975).
Although land use changes might not have been the main driver of the 1980s Sahel drought, their impacts over
4. Seasonal forecasting of drought in
During the last decade seasonal forecasting has matured from a research activity to a fully operational service, with many centers using initialized state-of-theart coupled models. There are currently 12 WMO Global Producing Centers (GPCs) for long-range forecasting that routinely issue operational forecasts for rainy season totals (Graham et al. 2011). The forecasts are freely available for national meteorological services, regional climate centers, and global product centers via www.wmolc.org.
Over the African region, the skill of these long-range forecasting systems to predict seasonal total rainfall is high enough to make them useful for planning purposes. An example of the practical use of long-range forecasts and postprocessing techniques is the Prévisions Saisonnière en Afrique de l'Ouest (PRESAO; Fig. 9, top) forum, which meets annually to produce a consensus forecast for the West African region. To make this forecast, output from GPC dynamical systems and statistical models are combined and a spatial bias correction is made using canonical correlation analysis.
These improvements in forecasting seasonal averages have been achieved thanks to the continuous research completed in the last 10 years. For example, Philippon et al. (2010) found that the correlation between observations and a five-model ensemble mean from the ENSEMBLES Sixth Framework Programme (FP6) project (
Despite these advances, there are still some remaining scientific questions such as large biases in tropical Atlantic SSTs in coupled models. Also, from a user's point of view, even more critical than the total seasonal rainfall is the ability to predict the temporal distribution of rain throughout the season (Salack et al. 2014), which determines the optimal planting and harvesting time (Marteau et al. 2011). This has created a clear demand for information such as the onset of rainy seasons in many parts of
Vellinga et al. (2013) analyzed the links between SST and precipitation over the WAM region using dynamical forecasting systems from the ENSEMBLES project. Confirming the results found by Salack et al. (2014) in observations, Vellinga et al. (2013) showed that the forecast skill in coupled models was related to tropical Atlantic SSTs in June. The ability of models to forecast the timing of the monsoon onset was found to be useful, with relative operating characteristics (ROC) scores of 0.6-0.8 at 3-months lead time.
A crucial point from the user perspective is that useful levels of skill are found even in some models with large mean rainfall biases over the region. This is important because, although there are still major model problems that need to be solved (such as biases in tropical Atlantic SSTs and total precipitation), the forecast systems are starting to be able to provide relevant probabilistic information to a crucial user question: Will the onset of the WAM be earlier or later than average this year? Figure 9 (from Vellinga et al. 2013) shows a major advance toward a meaningful answer to such a question, since only 10 years ago there was no forecasting system able to do it with a direct and relevant application to users.
5. Decadal prediction of the WAM
The new field of decadal climate prediction aims to provide climate information on time scales from a few years to a few decades into the future, which is recognized as a key planning horizon (Goddard et al. 2010; Vera et al. 2010; Smith et al. 2012). Decadal predictions are certainly of increasing scientific interest because they potentially represent a benefit to society through improvements in the development of climate services and adaptation strategies. They are recognized as a major part of the CMIP5 experimental design (Taylor et al. 2012).
Decadal predictions explore the benefits of initializing climate models. The initialization tries to provide the forecast system with contemporaneous information on, for instance, the state of the upper-ocean heat content, to achieve forecast quality beyond that provided by simulations based only on externally forced signals such as the standard CMIP3 and CMIP5 climate change scenario experiments. The objectives of decadal prediction include capturing low-frequency internal variability and correcting the model response to climate change forcings and commitment (Meehl et al. 2009, 2014; Murphy et al. 2010; Goddard et al. 2013; Doblas-Reyes et al. 2013).
As has been indicated in previous sections, WAM variability at decadal time scales results from a combination of internal and externally forced components (Biasutti 2011; Mohino et al. 2011a), including anthropogenic aerosols (e.g., Biasutti and Giannini 2006) and greenhouse gases (e.g., Biasutti et al. 2008). All the evidence points to the WAM as a good test bed for assessing the feasibility of decadal prediction.
Using the first coordinated experiment to explore the feasibility of decadal prediction (ENSEMBLES; Doblas-Reyes et al. 2010), van Oldenborgh et al. (2012) and MacLeod et al. (2012) found no significant skill in point-wise precipitation predictions over
From the most recent generation of climate models (i.e., CMIP5), Goddard et al. (2013), Gaetani and Mohino (2013), and Doblas-Reyes et al. (2013) found positive pointwise precipitation correlation over
The good performance of the ENSEMBLES (GarcíaSerrano et al. 2013) and CMIP5 (Gaetani and Mohino 2013) decadal forecast systems in reproducing the relationship between the Sahel precipitation and its associated SST patterns encourages the promotion of improved decadal prediction systems in the future where the problems of SST biases are properly dealt with. This is only achievable in a context of a model development strategy across all communities that use climate models, as suggested by the WCRP.
6. Future projections
Following the IPCC AR4, several studies were published on twenty-first-century rainfall scenarios over
Projections of summertime Sahel rainfall at the end of the twenty-first century by the CGCMs in CMIP3 and CMIP5 of the IPCC are shown in Figs. 11a and 11b for the emission scenarios SRES A1B and RCP4.5, respectively. Although the spread in rainfall projections is large at the end of the twenty-first century over the Sahel within both multimodel ensembles, there is evidence for a general tendency for slightly wetter conditions over central Sahel and drier conditions over
Another recent study of Roehrig et al. (2013) analyzes CMIP5 simulations along a range of time scales from interannual to decadal and future projections. CMIP5 climate change projections in surface air temperature and precipitation are found to be very similar to those obtained in CMIP3. Their results highlight a robust warming trend over the Sahel and an increase in rainfall in the eastern and a decrease in the western Sahel. However, there is a spread between models because of the deficiencies in simulating the Atlantic variability. In most of the models there is a systematic southward shift of the ITCZ.
The CMIP5 simulations reaffirm and strengthen the CMIP3 projections for changes in the seasonal cycle of Sahel rainfall (see, e.g., Biasutti and Sobel 2009; Biasutti 2013). A delay is projected on the start of the rainy season in the future throughout the Sahel, and especially over
Greenhouse gas (GHG) increases affect Sahel rainfall not only via the warming of global SST (slow response), but also via its direct effect on the temperature and energy fluxes of the land-atmosphere system (fast response; Patricola and Cook 2011; Giannini 2010). Using idealized CMIP5 simulations, Biasutti (2013) found that throughout the rainy season the slow response leads to less rain across the Sahel while the fast response forces wet anomalies that span the entire Sahel, although they are stronger in the east. Nevertheless, the fully coupled response, especially the change in seasonality, cannot be explained in terms of a simple linear superposition of the individual fast and slow responses. Biasutti (2013) speculates that the different phasing of the annual cycle over land and ocean interact to determine the projected delay of the Sahel rains in the coupled response.
Another proxy for drought in climate projections can be obtained by counting the annual number of dry days, which are defined as those when daily rainfall is less than 1mm(Frich et al. 2002; Vizy and Cook 2012). Vizy et al. (2013) indicate that current models underestimate the number of dry days along the Guinean coast and over the Congo basin, but conclude, on the basis of intermodel agreement and consistency across time periods, that there is a strong likelihood for fewer dry days over the Sahel of eastern
7. Summary, remaining questions, and future directions
The Sahel experienced starting in the 1970s one of the most dramatic droughts in the historical record, with consequences that have affected large areas and populations. The present paper reviewed studies on Sahel rainfall variability at time scales from interannual to decadal. The emphasis has been on the role of the oceanic anomalies, because according to the consensus view these are the most important contributors to rainfall variability in
a. Summary
1) INTERANNUAL VARIABILITY
In interannual time scales, a warming of the equatorial
A dependence on time (nonstationarity) of these relationships has been found by recent studies (Joly and Voldoire 2009; Rodríguez-Fonseca et al. 2011; Mohino et al. 2011b; Losada et al. 2012). Before the 1970s positive SST anomalies over the Gulf of
Current AGCMs generally capture these features. It has been argued that this time dependence is due to the changing configuration of tropical SST anomalies in different adjacent tropical oceans, which can interact either constructively or destructively according to time (Losada et al. 2012). Figure 12 shows that the periods for which the Atlantic and Pacific may both strongly influence Sahelian rainfall present a multidecadal anomalous SST pattern resembling the positive and negative phases of the Atlantic multidecadal oscillation (AMO), respectively. Thus, a warmer or cooler climatological SSTs in the equatorial and tropical South Atlantic could play an active role.
In addition to SST variability, volcanic eruptions may influence the WAM rainfall some years (Haywood et al. 2013),
2) INTERDECADAL VARIABILITY
SST variability at decadal time scales provides the most important influence leading to drought over the Sahel. It has been shown that the global warming trend, positive phase of the interdecadal Pacific oscillation, and negative phase of the AMO lead to reductions in Sahel precipitation. State-of-the art CGCMs are able to reproduce the observed drying trend over the Sahel. However, models fail in obtaining the observed amplitude and neither generation of CMIP climate models reproduces the magnitude of the observed rainfall variability at decadal to multidecadal time scales over the twentieth century.
Observational evidence also indicates a strong decadal climate component in the Sahel and surrounding areas from the 1950s to the 2000s in vegetation cover and land use/land cover (LULC) change, as well as in aerosol types and spatial distributions (e.g., Rowell 2003; Xue et al. 2004a,b; Lau and Kim 2007; Hastenrath and Polzin 2011). Vegetation dynamics, in particular, may contribute to the persistence of anomalies of the regional climate.
3) MECHANISMS FOR SST IMPACT
The mechanisms for SST impact operating at different climate scales, from interannual to decadal, are conceptually similar: the Atlantic interhemispheric gradients are related to changes in the position of the ITCZ and the warming of the Pacific tropical SSTs is related to anomalous equatorial atmospheric Rossby waves enhancing the subsidence over the Sahel.
A cooling in the equatorial Atlantic influences the large-scale dynamics, enhancing the meridional gradient in sea level pressure and strengthening the monsoon, while warming of the southern tropical Atlantic enhances the anomalous divergence over the Gulf of
4) FUTURE PROJECTIONS
The agreement among future projections has improved from CMIP3 to CMIP5. Although rainfall projections for the Sahel have a large spread at the end of the twenty-first century, model projections exhibit a general tendency for slightly wetter conditions over central part and drier conditions over the western part. A meridional dipole pattern of rainfall anomalies is also obtained over the tropical Atlantic consisting of drier conditions over the Gulf of
5) FORECASTING
The skill of numerical forecasts has improved during the last decades. The increased attention to dynamical vegetation schemes has contributed to improvement. Prediction systems have evolved from seasonal to decadal forecasting. Current forecast systems show skill in their seasonal predictions of total rainfall amounts over
b. Numerical modeling issues
Significant shortcomings remain in the ability of numerical models to simulate some outstanding aspects of the tropical Atlantic climate and its variability.
* Most contemporary coupled atmosphere-ocean (CGCMs) have important rainfall, wind, and SST biases in the tropical Atlantic. The simulations show too weak trade winds, a spurious ITCZ south of the equator, and too warm eastern tropical SSTs, compromising the successful representation of WAM and its response to tropical Atlantic variability.
* CGCMs have difficulties in capturing the relationships among Pacific SSTs and WAM rainfall anomalies during the developing phase of an El Niño (La Niña) event.
* There are large differences among models in the intensity and variance of simulated precipitation and the majority of CGCMs fail to produce proper intensities of the African easterly jet and the tropical easterly jet.
* RCMs capture the northward jump of the precipitation band that represents the monsoon onset over Sahelian Africa, which GCMs fail to simulate. However, the jump in the RCMs occurs earlier than observed, suggesting serious model limitations for predicting the timing of monsoon onset.
* It is very important to emphasize that over
* Since forecasts are sensitive to the quality of the data used to initialize the model, an improvement of the initial conditions used over the equatorial and extratropical Atlantic as well as over land is just as essential to improve the forecast quality as the model improvement is.
c. Remaining questions
* The role of the Indian Ocean in forcing interannual rainfall anomalies over
* The reasons for the nonstationary impact of tropical SST anomalies in different basins are not clear at the present time. There are at two competing hypotheses that require further validation: statistical artifacts due to sampling errors and modulations by changes in the ocean climatology, which introduce nonlinearities in the system and, thus, different impacts.
* Despite the general agreement that the long-term Sahel drought was mainly driven by SST variability and amplified by land surface processes, the details as to which basin or SST pattern lead this drought are still debated. Some works suggest that the warming of the tropical SSTs in the Indian, Pacific, and/or Atlantic Ocean basins were the dominant factors, while others place a more fundamental role on the interhemispheric north-south SST gradient in the Atlantic.
* Another key point still under debate is the attribution of the long-term Sahel drought to anthropogenic factors, as greenhouse gases or anthropogenic aerosols. On the one hand, some works suggest that these factors played little or no role in the twentieth-century Sahel drought. On the other hand, other studies argue they were the main driver of the drought.
* There is still a substantial spread in rainfall projections, which is large at the end of the twenty-first century over the Sahel.
* What are the key model components to be improved for a higher skill of drought prediction over the Sahel? Should radiative impacts of natural aerosols from the continent be considered in reference to the systematic errors of CGCMs over the Atlantic, both in the subtropics and the tropics? The answers to these questions may require the realization of field campaigns in the eastern tropical Atlantic.
* Could land surface processes become the primarily responsible for drought over
d. Future directions
One of the most dramatic and immediate impacts of climate variation is on disease, especially the vectorborne diseases that disproportionally affect the poorest populations in
New European projects are being launched to enhance predictability of this region. For example, the Seasonal-to-Decadal Climate Prediction for the Improvement of European Climate Services (SPECS) EU project (http://www.specs-fp7.eu/), which started in 2012, produces quasi-operational and actionable local climate information at seasonal-to-decadal time scales over the longest possible observational period over land, focusing on
Acknowledgments. Belen Rodríguez-Fonseca,
This work was supported by Spanish projects MINECO CGL2011-13564-E and GL2012-38923-C0201. Support from the
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BELEN RODRÍGUEZ-FONSECA,a ELSA MOHINO,b CARLOS R. MECHOSO,c CYRIL CAMINADE,d MICHELA BIASUTTI,e MARCO GAETANI,f J. GARCIA-SERRANO,g EDWARD K. VIZY,h KERRY COOK,h YONGKANG XUE,c IRENE POLO,i TERESA LOSADA,j LEONARD DRUYAN,k BERNARD FONTAINE,l JUERGEN BADER,m FRANCISCO J. DOBLAS-REYES,n LISA GODDARD,o SERGE JANICOT,p ALBERTO ARRIBAS,q WILLIAM LAU,r ANDREW COLMAN,q M. VELLINGA,q DAVID P. ROWELL,q FRED KUCHARSKI,s AND
a Departamento de Física
CSIC, and Universidad Complutense de
b Departamento de Física
Universidad Complutense de
c
d
e
f
g Institut Catal à de Ciències
h
i NCAS-Climate,
j Instituto de Ciencias Ambientales, Universidad de Castilla-La Mancha,
k
l Centre de Recherches de Climatologie, CNRS/Universit é de Bourgogne, Dijon,
m
n Institut Catal à de Ciències
o
p IRD, LOCEAN/IPSL, UPMC,
q Met Office Hadley Center,
r
s
t Centre National de Recherches Météorologiques/Groupe d'Etude de l'Atmosphère Météorologique, Météo-
(Manuscript received
Corresponding author address: Belén Rodríguez-Fonseca, Departamento de Física
E-mail: [email protected]
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