1. School of Engineering, Computing and Mathematics, University of Exeter, Exeter EX4 4QF, UK
2. Met Office Hadley Centre, Exeter EX1 3PB, UK
3. Centre for Ecology and Hydrology, Wallingford OX10 8BB, UK
4. Brazilian Centre for Weather Forecasting and Climate Studies, CPTEC/INPE, Sao Paulo, Brazil

Correspondence to: Peter M. Cox^1,2 Correspondence and requests for materials should be addressed to P.M.C. (Email: p.m.cox@exeter.ac.uk).

In 2005 large areas of the Amazon river basin experienced one of the most intense drought episodes of the last 100 years⁶. The drought most directly affected western Amazonia, and especially the catchments of the Solimões and the Madeiras rivers. Navigation along these major tributaries had to be suspended because the water levels were so low. Unlike during the El Niño-related droughts in 1926, 1983 and 1997, central and eastern Amazonia were not directly affected, although river levels on the Rio Negro in central Amazonia did reach unusually low levels in October 2005, owing to reduced inflow from the tributaries to the west.

Rainfall in Amazonia is sensitive to seasonal, interannual and decadal variations in SSTs^{7, 10, 11}. The warming of the tropical East Pacific during El Niño events suppresses wet-season rainfall through modification of the (east–west) Walker circulation and via the Northern Hemisphere extratropics¹². El Niño-like climate change¹³ has similarly been shown to influence the annual mean rainfall over South America in GCM climate-change projections^{4, 5}.

However, variations in Amazonian precipitation are also known to be linked to SSTs in the tropical Atlantic¹¹. A warming of the tropical Atlantic in the north relative to the south leads to a northwestwards shift in the intertropical convergence zone and compensating atmospheric descent over Amazonia¹⁰. For northeast Brazil the relationship between the north–south Atlantic SST gradient and rainfall is sufficiently strong to form the basis for a seasonal forecasting system¹⁴. Here we show that Atlantic SSTs exert a large influence on dry-season rainfall in western Amazonia by delaying onset of the South American monsoon^{15, 16}.

July to October 2005 was associated with a persistent warm anomaly in the North Atlantic¹⁷ centred on latitudes 10–15° N, and a weaker cold anomaly in the South Atlantic at around latitude 15° S (Fig. 1). The absence of a warming in the tropical East Pacific implies that El Niño was in a near-neutral state and therefore did not contribute to the 2005 drought. The black box over land in Fig. 1 denotes the western Amazonian area chosen for the purposes of this study (75° W–60° W, 12° S–0°). The black boxes over ocean show the northern (15° N–35° N, 75° W–30° W) and southern (25° S–5° S, 40° W–5° E) regions used to calculate an index of the Atlantic N–S gradient (ANSG). These areas were chosen for comparability with the GCM climate projections that we present below, but are also near-optimal on the basis of a statistical analysis using observations alone¹⁸.

Figure 1: Anomalies in SSTs for July–October 2005, relative to the July–October mean values over the standard climatological period 1961–1990.

The black boxes show the regions used in this study.

High resolution image and legend (154K)

We analyse results from the HadCM3LC coupled climate–carbon-cycle model⁴, which is based upon the Met Office Hadley Centre's third-generation ocean–atmosphere GCM, HadCM3¹⁹. This is one of only three current, global climate models that fit within the observational limits on the July–October western Amazonian rainfall and the ANSG (see Supplementary Information). The HadCM3 model has also performed well in GCM intercomparison exercises and was recently recognized to be one of two GCMs that simulate the Amazonian climate with reasonable accuracy⁵. HadCM3LC in addition includes dynamic vegetation and an interactive carbon cycle, meaning that atmospheric CO₂ concentrations can be updated on the basis of anthropogenic emissions, taking into account the effects of climate change on ocean and land CO₂ uptake.

We consider two separate simulations using HadCM3LC for the period from 1860 to 2100 (refs 4, 8). In both cases the model is driven with CO₂ emissions consistent with the IS92a scenario, which is approximately in the centre of the spread of future emissions represented by the results of the more recent Special Report on Emissions Scenarios²⁰. Both model experiments also include prescribed time-varying concentrations of trace greenhouse gases (CH₄, N₂O) based on the IS92a scenario. The second run additionally includes changes in tropospheric and stratospheric ozone, solar variability and, most notably, forcing due to sulphate and volcanic aerosols. This model experiment was able to reproduce the observed warming and CO₂ increase over the twentieth century to good accuracy, especially when we used a revised estimate of the net CO₂ flux from land-use change (run 'ALL70' from ref. 8).

We compared the results of these simulations with observations of the ANSG index¹⁷ and rainfall in western Amazonia²¹ for the twentieth century, using 20-yr running means in each case (Fig. 2). The 2005 ANSG index value of 4.92 K was exceeded regularly during the 1930s, 1940s and 1950s, but has not reached such a high value since 1960. There is significant variability in the 20-yr-mean ANSG index (which is much larger than the standard deviation of the annual-mean values), with values declining from around 1960 to the mid-1980s before increasing in the past two decades. This variation is mirrored by the 20-yr mean western Amazonian rainfall measurements, which decreased from the 1920s to 1960 and then increased until the mid-1980s before decreasing again to the values observed today.

Figure 2: Comparison of observed and modelled climate variables relevant to the Amazonian drought of 2005.

Evolution of July–October mean values of a, the ANSG index; b, rainfall in western Amazonia. Observations are shown in black^{17, 20}, with the thin lines corresponding to annual values and the thick lines showing 20-yr running means. The other lines show 20-yr running means from the HadCM3LC GCM. The red line corresponds to a simulation of climate change driven by greenhouse gas increases only³, whereas the green line additionally includes changes in aerosols, stratospheric and tropospheric ozone, and revised fluxes of CO₂ from land-use change⁸. The large cross in a and the bar in b show the estimated values for July–October 2005.

High resolution image and legend (119K)

Both HadCM3LC simulations capture the observed inverse relationship between the ANSG index and July–October precipitation in the western Amazon. However, the simulation with greenhouse gases only (Fig. 2, red lines) fails to reproduce the observed decadal variability in the ANSG index (the correlation coefficient between the 20-yr running means of observed and modelled ANSGs is -0.75), and instead predicts a near-monotonic increase in the ANSG index and a corresponding near-monotonic decrease in western Amazonian rainfall from the mid-twentieth century onwards. On the other hand, the HadCM3LC run with aerosols (Fig. 2, green lines) produces a good fit to the multi-decadal variation in the ANSG index (the correlation coefficient between the 20-yr running means is in this case +0.82), and reproduces the observed decrease in 20-yr mean western Amazonian rainfall from the 1920s to 1960.

This suggests that longer-term variations in the ANSG, and associated effects on Amazonian rainfall, are as much a consequence of forced variability as they are of internal variability. Furthermore, the two model runs taken together indicate that non-greenhouse-gas forcing, primarily from anthropogenic and volcanic aerosols, has acted to suppress the development of a stronger ANSG, and thereby delayed the suppression of dry-season rainfall in the western Amazon. It seems that reflective sulphate aerosol pollution produced in the Northern Hemisphere may have helped to maintain rainfall in South America, just as it may have contributed to the Sahelian droughts of the 1970s and 1980s²².

The HadCM3LC model also produces a realistic correlation between interannual variations in the western Amazonian rainfall and the ANSG index (Fig. 3). The best-fit straight lines linking these variables for the model and the observations are very nearly parallel, having respective gradients of -0.650.29 and -0.580.46 mm d^-1 K^-1 (throughout the paper we quote error bars as 2 s.d. giving approximately 95% confidence limits). The HadCM3LC model validates best among current GCMs in this respect (see Supplementary Information). For the twenty-first century, the model predicts a strengthening of the relationship between the (decreasing) western Amazonian rainfall for the July–October period and the (increasing) ANSG index, as indicated by the quadratic best-fit shown in Fig. 3.

Figure 3: Relationship between the July–October mean values of western Amazonian rainfall and the ANSG index.

Observations for the period 1901–2002 are plotted with black crosses^{17, 20}. Model output from the HadCM3LC GCM run with aerosols⁸ is plotted with black diamonds for the historical period (1901–2002) and with green diamonds for the simulation of the twenty-first century (2003–2100). The black lines are the best-fit straight lines to the observations (1950–1999; solid) and the twentieth-century simulation (1900–1999; dashed). The green line is the best quadratic fit to the entire GCM simulation (1860–2099). The large black cross shows the mean and standard deviation of the observations, and the red bar shows the range of estimated values for the 2005 Amazon drought.

High resolution image and legend (142K)

Our simulations suggest that the North Atlantic region will warm more rapidly than the South Atlantic in the future, leading to a northwards movement of the intertropical convergence zone and suppression of July–October rainfall in western Amazonia. Aerosol pollution has occurred predominantly in the industrialised north, which tends to suppress the development of this north–south warming gradient. However, as air quality improves, aerosol cooling of the climate is expected to decrease⁹, potentially revealing a larger ANSG. This is evident in the HadCM3LC run with aerosols (Fig. 2, green lines), which predicts a 2 K increase in the ANSG index by the end of the twenty-first century. As a consequence, this GCM projection suggests that the conditions of 2005 will be experienced more and more frequently as atmospheric greenhouse gas concentrations increase and sulphur dioxide emissions decrease in the Northern Hemisphere (see Supplementary Information).

Climate model projections are known to differ markedly with respect to regional rainfall changes over Amazonia, but a comparison of the results from 20 GCMs included in the Fourth Assessment Report of the Intergovernmental Panel on Climate Change reveals two robust features: there is a cross-model relationship between the twenty-first-century trends in western Amazonian rainfall and the twenty-first-century trends in the ANSG index, which is consistent with the observed interannual variability in these variables; and models that include aerosol forcing tend to predict greater increases in the ANSG index in the first few decades of the twenty-first century (see Supplementary Fig. S3). Taken together, these findings support our basic conclusion that aerosol forcing has delayed reductions in Amazonian rainfall but is unlikely to do so for much longer.

We estimated the probability of a '2005-like' year occurring in the HadCM3LC run with aerosols, based on the fraction of years in a centred 20-yr window that exceed the ANSG index for 2005 (Fig. 4). The model suggests that 2005 was an approximately 1-in-20-yr event, but will become a 1-in-2-yr event by 2025 and a 9-in-10-yr event by 2060. These thresholds obviously depend on the rate of increase of CO₂, which is itself dependent on the emissions scenario chosen. Figure 4b shows how the probability of a 2005-like event increases as a function of CO₂ concentration in this HadCM3LC model, with the 50% probability level exceeded at about 450 p.p.m.v. and the 90% probability level exceeded at around 610 p.p.m.v. These results suggest a rapidly increasing risk of 2005-like droughts in Amazonia under conditions of reduced aerosol loading and increased greenhouse gases.

Figure 4: Predicted change in the probability of a 2005-like drought in Amazonia, based on results from the HadCM3LC GCM run with aerosols8.

Probabilities are calculated as the fraction of years that exceed the July–October 2005 anomaly in the ANSG index, using the 20-yr window centred on each year: a, probability versus year; b, probability versus simulated CO₂ concentration. The dotted lines respectively mark the points beyond which the 2005 anomaly is exceeded in 50% of the simulated years (2025, 450 p.p.m.v. of CO₂) and in 90% of the simulated years (2060, 610 p.p.m.v. of CO₂).

High resolution image and legend (103K)

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Supplementary Information

Supplementary information accompanies this paper.

Acknowledgements

The authors acknowledge funding from the NERC CLASSIC programme and Great Western Research (P.M.C. and T.E.J.); the CEH Science Budget (C.H. and P.P.H.); the UK Department for Environment, Food and Rural Affairs and the UK Ministry of Defence (R.A.B, C.D.J. and M.C.); and the Brazilian Research Council and the Global Opportunities Fund from the UK Foreign and Commonwealth Office (C.A.N. and J.A.M.). We also acknowledge the modelling groups the Program for Climate Model Diagnosis and Intercomparison and the WCRP Working Group on Coupled Modelling for their roles in making available the WCRP CMIP3 multimodel data set. Support for this data set is provided by the Office of Science, US Department of Energy.

Author Contributions P.M.C. coordinated the work, identified the role of aerosols in delaying Amazonian drying in HadCM3LC, and drafted the paper; P.P.H. and C.H. defined the SST indices and analysed the relationships between these indices and western Amazonian rainfall, in both the observations and the model runs; C.D.J. and R.A.B. carried out the HadCM3LC runs and provided output data from them; J.A.M. and C.A.N. provided observational data and insights on the nature of the 2005 drought in western Amazonia; M.C. extracted and then intercompared data on predicted changes in Amazonia from the CMIP3 models; C.H. and T.E.J. provided guidance on statistical significance.

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