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Since 1982, extreme daily rainfall in the western Sahel has increased persistently, owing to a warmer Sahara which has led to increased wind shear and an increase in intense storms. More storms as desert warms A warming climate is expected to increase the frequency of extreme rainfall events because warmer air can support higher humidity, but other mechanisms may also be at work. Christopher Taylor et al . show that increases in extreme rainfall in the western Sahel region of Africa since 1982 are driven by a larger gradient in temperature across the region caused by a warmer Sahara desert to the north. In turn, the sharper gradient increases wind shear and seems to have led to the frequency of mesoscale convective systems—which are exactly the kind of weather systems likely to generate extreme rainfall—tripling since 1982. The spatial patterns of global warming are likely to further increase the temperature gradient and intensify mesoscale convective systems, leading to more extreme rainfall events. The hydrological cycle is expected to intensify under global warming 1 , with studies reporting more frequent extreme rain events in many regions of the world 2 , 3 , 4 , and predicting increases in future flood frequency 5 . Such early, predominantly mid-latitude observations are essential because of shortcomings within climate models in their depiction of convective rainfall 6 , 7 . A globally important group of intense storms—mesoscale convective systems (MCSs) 8 —poses a particular challenge, because they organize dynamically on spatial scales that cannot be resolved by conventional climate models. Here, we use 35 years of satellite observations from the West African Sahel to reveal a persistent increase in the frequency of the most intense MCSs. Sahelian storms are some of the most powerful on the planet 9 , and rain gauges in this region have recorded a rise in ‘extreme’ 17 daily rainfall totals. We find that intense MCS frequency is only weakly related to the multidecadal recovery of Sahel annual rainfall, but is highly correlated with global land temperatures. Analysis of trends across Africa reveals that MCS intensification is limited to a narrow band south of the Sahara desert. During this period, wet-season Sahelian temperatures have not risen, ruling out the possibility that rainfall has intensified in response to locally warmer conditions. On the other hand, the meridional temperature gradient spanning the Sahel has increased in recent decades, consistent with anthropogenic forcing driving enhanced Saharan warming 10 . We argue that Saharan warming intensifies convection within Sahelian MCSs through increased wind shear and changes to the Saharan air layer. The meridional gradient is projected to strengthen throughout the twenty-first century, suggesting that the Sahel will experience particularly marked increases in extreme rain. The remarkably rapid intensification of Sahelian MCSs since the 1980s sheds new light on the response of organized tropical convection to global warming, and challenges conventional projections made by general circulation models.

Analysis of observations on six continents reveals a global preference for afternoon rain to fall on locally drier soils—contrary to the predictions of large-scale climate models, and suggesting that such models may exaggerate the occurrence of droughts. Rain in the afternoon Soil moisture is known to influence precipitation across a range of scales in time and space, and most models suggest that wetter soils promote higher atmospheric moisture content and favour the local development of storms. But this analysis of global precipitation data from a combination of weather satellites shows that — especially in semi-arid regions — afternoon precipitation is more likely over dry soil than over wet soil. The findings suggest that current climate models may be missing fundamental processes regulating convection and land–atmosphere interactions. Land surface properties, such as vegetation cover and soil moisture, influence the partitioning of radiative energy between latent and sensible heat fluxes in daytime hours. During dry periods, soil-water deficit can limit evapotranspiration, leading to warmer and drier conditions in the lower atmosphere 1 , 2 . Soil moisture can influence the development of convective storms through such modifications of low-level atmospheric temperature and humidity 1 , 3 , which in turn feeds back on soil moisture. Yet there is considerable uncertainty in how soil moisture affects convective storms across the world, owing to a lack of observational evidence and uncertainty in large-scale models 4 . Here we present a global-scale observational analysis of the coupling between soil moisture and precipitation. We show that across all six continents studied, afternoon rain falls preferentially over soils that are relatively dry compared to the surrounding area. The signal emerges most clearly in the observations over semi-arid regions, where surface fluxes are sensitive to soil moisture, and convective events are frequent. Mechanistically, our results are consistent with enhanced afternoon moist convection driven by increased sensible heat flux over drier soils, and/or mesoscale variability in soil moisture. We find no evidence in our analysis of a positive feedback—that is, a preference for rain over wetter soils—at the spatial scale (50–100 kilometres) studied. In contrast, we find that a positive feedback of soil moisture on simulated precipitation does dominate in six state-of-the-art global weather and climate models—a difference that may contribute to excessive simulated droughts in large-scale models.

Assessing potential future carbon loss from tropical forests is important for evaluating the efficacy of programmes for reducing emissions from deforestation and degradation (REDD). An exploration of results from 22 climate models in conjunction with a land surface scheme suggests that in the Americas, Africa and Asia, the resilience of tropical forests to climate change is higher than expected, although uncertainties are large. How tropical forest carbon stocks might alter in response to changes in climate and atmospheric composition is uncertain. However, assessing potential future carbon loss from tropical forests is important for evaluating the efficacy of programmes for reducing emissions from deforestation and degradation. Uncertainties are associated with different carbon stock responses in models with different representations of vegetation processes on the one hand 1 , 2 , 3 , and differences in projected changes in temperature and precipitation patterns on the other hand 4 , 5 . Here we present a systematic exploration of these sources of uncertainty, along with uncertainty arising from different emissions scenarios for all three main tropical forest regions: the Americas (that is, Amazonia and Central America), Africa and Asia. Using simulations with 22 climate models and the MOSES–TRIFFID land surface scheme, we find that only in one 5 of the simulations are tropical forests projected to lose biomass by the end of the twenty-first century—and then only for the Americas. When comparing with alternative models of plant physiological processes 1 , 2 , we find that the largest uncertainties are associated with plant physiological responses, and then with future emissions scenarios. Uncertainties from differences in the climate projections are significantly smaller. Despite the considerable uncertainties, we conclude that there is evidence of forest resilience for all three regions.

Evapotranspiration of soil moisture can affect rainfall and the development of convective storms. Satellite observations of cloud and land-surface temperatures over the Sahel suggest that convective storms are more likely to form over strong mesoscale gradients in soil moisture. Evapotranspiration of soil moisture can affect temperature and humidity in the lower atmosphere, and thereby the development of convective rain storms. Climate models have illustrated the importance of soil-moisture–precipitation feedbacks for weekly rainfall totals in semi-arid regions, such as the Sahel 1 . However, large variations exist between model feedbacks, and the mechanisms governing the strength and sign of the feedback are uncertain. Here, we use satellite observations of land surface temperatures and convective cloud cover over West Africa—collected during the wet seasons between 2006 and 2010—to determine the impact of soil moisture on rainfall in the Sahel. We show that variations in soil moisture on length scales of approximately 10–40 km exert a strong control on storm initiation—as evidenced by the appearance of convective cloud. The probability of convective initiation is doubled over strong soil-moisture gradients compared with that over uniform soil-moisture conditions. We find that 37% of all storm initiations analysed occurred over the steepest 25% of soil-moisture gradients. We conclude that heterogeneities in soil moisture on scales of tens of kilometres have a pronounced impact on rainfall in the Sahel, and suggest that similar processes may be important throughout the semi-arid tropics.

Dry outlook for the Amazon The severe drought of 2005 in the western Amazonian rainforest, apparently associated with unusually high sea-surface temperatures in the North Atlantic ocean, was a dramatic event that prompted speculation that tropical forest dieback was a potential 'tipping point' of the climate system. A new analysis suggests that this event can be better understood with reference to the gradient in sea-surface temperatures across the equatorial Atlantic, of which the northern temperature anomalies are just one factor. When the effects of atmospheric aerosols are incorporated into the model, the observed variations in this temperature gradient over the past century can be reproduced. And projecting these trends to the future, the model suggests that sea-surface conditions conducive to droughts like that seen in 2005 will become much more common. In 2005, there was a pronounced drought in the western Amazonian rainforest, which seems to have been associated with a period of unusually warm sea-surface temperatures in the North Atlantic. This event can be better understood with reference to the gradient in sea-surface temperatures across the equatorial Atlantic, of which the northern temperature anomalies are just a factor. By incorporating the effects of atmospheric aerosols into the model, the observed variations in this temperature gradient over the past century are reproduced, and it is predicted that the sea-surface conditions conductive to the droughts experienced in 2005 will become much more common. The Amazon rainforest plays a crucial role in the climate system, helping to drive atmospheric circulations in the tropics by absorbing energy and recycling about half of the rainfall that falls on it. This region (Amazonia) is also estimated to contain about one-tenth of the total carbon stored in land ecosystems, and to account for one-tenth of global, net primary productivity 1 . The resilience of the forest to the combined pressures of deforestation and global warming is therefore of great concern 2 , especially as some general circulation models (GCMs) predict a severe drying of Amazonia in the twenty-first century 3 , 4 , 5 . Here we analyse these climate projections with reference to the 2005 drought in western Amazonia, which was associated 6 with unusually warm North Atlantic sea surface temperatures (SSTs). We show that reduction of dry-season (July–October) rainfall in western Amazonia correlates well with an index of the north–south SST gradient across the equatorial Atlantic (the ‘Atlantic N–S gradient’). Our climate model is unusual among current GCMs in that it is able to reproduce this relationship and also the observed twentieth-century multidecadal variability in the Atlantic N–S gradient 7 , provided that the effects of aerosols are included in the model 8 . Simulations for the twenty-first century using the same model 3 , 8 show a strong tendency for the SST conditions associated with the 2005 drought to become much more common, owing to continuing reductions in reflective aerosol pollution in the Northern Hemisphere 9 .

The Hadley Centre coupled climate-carbon cycle model (HadCM3LC) predicts loss of the Amazon rainforest in response to future anthropogenic greenhouse gas emissions. In this study, the atmospheric component of HadCM3LC is used to assess the role of simulated changes in mid-twenty-first century sea surface temperature (SST) in Amazon Basin climate change. When the full HadCM3LC SST anomalies (SSTAs) are used, the atmosphere model reproduces the Amazon Basin climate change exhibited by HadCM3LC, including much of the reduction in Amazon Basin rainfall. This rainfall change is shown to be the combined effect of SSTAs in both the tropical Atlantic and the Pacific, with roughly equal contributions from each basin. The greatest rainfall reduction occurs from May to October, outside of the mature South American monsoon (SAM) season. This dry season response is the combined effect of a more rapid warming of the tropical North Atlantic relative to the south, and warm SSTAs in the tropical east Pacific. Conversely, a weak enhancement of mature SAM season rainfall in response to Atlantic SST change is suppressed by the atmospheric response to Pacific SST. This net wet season response is sufficient to prevent dry season soil moisture deficits from being recharged through the SAM season, leading to a perennial soil moisture reduction and an associated 30% reduction in annual Amazon Basin net primary productivity (NPP). A further 23% NPP reduction occurs in response to a 3.5°C warmer air temperature associated with a global mean SST warming.

Simulations with the Hadley Centre general circulation model (HadCM3), including carbon cycle model and forced by a 'business-as-usual' emissions scenario, predict a rapid loss of Amazonian rainforest from the middle of this century onwards. The robustness of this projection to both uncertainty in physical climate drivers and the formulation of the land surface scheme is investigated. We analyse how the modelled vegetation cover in Amazonia responds to (i) uncertainty in the parameters specified in the atmosphere component of HadCM3 and their associated influence on predicted surface climate. We then enhance the land surface description and (ii) implement a multilayer canopy light interception model and compare with the simple 'big-leaf' approach used in the original simulations. Finally, (iii) we investigate the effect of changing the method of simulating vegetation dynamics from an area-based model (TRIFFID) to a more complex size- and age-structured approximation of an individual-based model (ecosystem demography). We find that the loss of Amazonian rainforest is robust across the climate uncertainty explored by perturbed physics simulations covering a wide range of global climate sensitivity. The introduction of the refined light interception model leads to an increase in simulated gross plant carbon uptake for the present day, but, with altered respiration, the net effect is a decrease in net primary productivity. However, this does not significantly affect the carbon loss from vegetation and soil as a consequence of future simulated depletion in soil moisture; the Amazon forest is still lost. The introduction of the more sophisticated dynamic vegetation model reduces but does not halt the rate of forest dieback. The potential for human-induced climate change to trigger the loss of Amazon rainforest appears robust within the context of the uncertainties explored in this paper. Some further uncertainties should be explored, particularly with respect to the representation of rooting depth.

Correctly representing the response of vegetation productivity to water availability in Earth system models (ESMs) is essential for accurately modelling the terrestrial carbon cycle and the evolution of the climate system. Previous studies evaluating gross primary productivity (GPP) in ESMs have focused on annual mean GPP and interannual variability, but physical processes at shorter timescales are important for determining vegetation–climate coupling. We evaluate GPP responses at the intraseasonal timescale in five CMIP6 ESMs by analysing changes in GPP after intraseasonal rainfall events with a timescale of approximately 25 d. We compare these responses to those found in a range of observation-based products. When composited around all intraseasonal rainfall events globally, both the amplitude and the timing of the GPP response show large inter-model differences, demonstrating discrepancies between models in their representation of water–carbon coupling processes. However, the responses calculated from the observational datasets also vary considerably, making it challenging to assess the realism of the modelled GPP responses. The models correctly capture the fact that larger increases in GPP at the regional scale are associated with larger increases in surface soil moisture and larger decreases in atmospheric vapour pressure deficit. However, the sensitivity of the GPP response to these drivers varies between models. The GPP in NorESM is insufficiently sensitive to vapour pressure deficit perturbations when compared all to other models and six out of seven observational GPP products tested. Most models produce a faster GPP response where the surface soil moisture perturbation is larger, but the observational evidence for this relationship is weak. This work demonstrates the need for a better understanding of the uncertainties in the representation of water–vegetation relationships in ESMs and highlights a requirement for future daily-resolution observations of GPP to provide a tighter constraint on global water–carbon coupling processes.

Soil moisture availability exerts control over the land surface energy partition in parts of Europe. However, determining the strength and variability of this control is impeded by the lack of reliable evaporation observations at the continental scale. This makes it difficult to refine the broad range of soil moisture–evaporation behaviors across global climate models (GCMs). Previous studies show that satellite observations of land surface temperature (LST) during rain-free dry spells can be used to diagnose evaporation regimes at the GCM gridbox scale. This relative warming rate (RWR) diagnostic quantifies the increase in dry spell LST relative to air temperature and is used here to evaluate a land surface model (JULES) both offline and coupled to a GCM (HadGEM3-A). It is shown that RWR can be calculated using outputs from an atmospheric GCM provided the satellite clear-sky sampling bias is incorporated. Both offline JULES and HadGEM3-A reproduce the observed seasonal and regional RWR variations, but with weak springtime RWRs in central Europe. This coincides with sustained bare soil evaporation (Ebs) during dry spells, reflecting previous site-level JULES studies in Europe. To assess whether RWR can discriminate between surface descriptions, the bare soil surface conductance and the vegetation root profile are revised to limit Ebs. This increases RWR by increasing the occurrence of soil moisture–limited dry spells, yielding more realistic springtime RWRs as a function of antecedent precipitation but poorer relationships in summer. This study demonstrates the potential for using satellite LST to assess evaporation regimes in climate models.

Soil moisture plays a fundamental role in regulating the summertime surface energy balance across Europe. Understanding the spatial and temporal behavior in soil moisture and its control on evapotranspiration (ET) is critically important and influences heat wave events. Global climate models (GCMs) exhibit a broad range of land responses to soil moisture in regions that lie between wet and dry soil regimes. In situ observations of soil moisture and evaporation are limited in space, and given the spatial heterogeneity of the landscape, are unrepresentative of the GCM gridbox scale. On the other hand, satelliteborne observations of land surface temperature (LST) can provide important information at the larger scale. As a key component of the surface energy balance, LST is used to provide an indirect measure of surface drying across the landscape. To isolate soil moisture constraints on evaporation, time series of clear-sky LST are analyzed during dry spells lasting at least 10 days from March to October. Averaged over thousands of dry spell events across Europe, and accounting for atmospheric temperature variations, regional surface warming of between 0.5 and 0.8K is observed over the first 10 days of a dry spell. Land surface temperatures are found to be sensitive to antecedent rainfall; stronger dry spell warming rates are observed following relatively wet months, indicative of soil moisture memory effects on the monthly time scale. Furthermore, clear differences in surface warming rate are found between cropland and forest, consistent with contrasting hydrological and aerodynamic properties.