Soil drought can mitigate deadly heat stress thanks to a reduction of air humidity.

Climate models indicate that dry extremes will be exacerbated in many regions of the world^1,2. However, confidence in the magnitude and timing of these projected changes remains low^3,4, leaving societies largely unprepared^5,6. Here we show that constraining model projections with observations using a newly proposed emergent constraint (EC) reduces the uncertainty in predictions of a core drought indicator, the longest annual dry spell (LAD), by 10–26% globally. Our EC-corrected projections reveal that the increase in LAD will be 42–44% greater, on average, than ‘mid-range’ or ‘high-end’ future forcing scenarios currently indicate. These results imply that by the end of this century, the global mean land-only LAD could be 10 days longer than currently expected. Using two generations of climate models, we further uncover global regions for which historical LAD biases affect the magnitude of projected LAD increases, and we explore the role of land–atmosphere feedbacks therein. Our findings reveal regions with potentially higher- and earlier-than-expected drought risks for societies and ecosystems, and they point to possible mechanisms underlying the biases in the current generation of climate models.

The coupling between soil, vegetation and atmosphere is thought to be crucial in the development and intensification of weather extremes, especially meteorological droughts, heat waves and severe storms. Therefore, understanding the evolution of the atmospheric boundary layer (ABL) and the role of land–atmosphere feedbacks is necessary for earlier warnings, better climate projection and timely societal adaptation. However, this understanding is hampered by the difficulties of attributing cause–effect relationships from complex coupled models and the irregular space–time distribution of in situ observations of the land–atmosphere system. As such, there is a need for simple deterministic appraisals that systematically discriminate land–atmosphere interactions from observed weather phenomena over large domains and climatological time spans. Here, we present a new interactive data platform to study the behavior of the ABL and land–atmosphere interactions based on worldwide weather balloon soundings and an ABL model. This software tool – referred to as CLASS4GL (http://class4gl.eu, last access: 27 May 2018) – is developed with the objectives of (a) mining appropriate global observational data from ∼15 million weather balloon soundings since 1981 and combining them with satellite and reanalysis data and (b) constraining and initializing a numerical model of the daytime evolution of the ABL that serves as a tool to interpret these observations mechanistically and deterministically. As a result, it fully automizes extensive global model experiments to assess the effects of land and atmospheric conditions on the ABL evolution as observed in different climate regions around the world. The suitability of the set of observations, model formulations and global parameters employed by CLASS4GL is extensively validated. In most cases, the framework is able to realistically reproduce the observed daytime response of the mixed-layer height, potential temperature and specific humidity from the balloon soundings. In this extensive global validation exercise, a bias of 10.1 m h⁻¹, −0.036 K h⁻¹ and 0.06 g kg⁻¹ h⁻¹ is found for the morning-to-afternoon evolution of the mixed-layer height, potential temperature and specific humidity. The virtual tool is in continuous development and aims to foster a better process understanding of the drivers of the ABL evolution and their global distribution, particularly during the onset and amplification of weather extremes. Finally, it can also be used to scrutinize the representation of land–atmosphere feedbacks and ABL dynamics in Earth system models, numerical weather prediction models, atmospheric reanalysis and satellite retrievals, with the ultimate goal of improving local climate projections, providing earlier warning of extreme weather and fostering a more effective development of climate adaptation strategies. The tool can be easily downloaded via http://class4gl.eu (last access: 27 May 2018) and is open source.

The magnitude and sign of soil moisture–precipitation coupling (SMPC) is investigated using a probability-based approach and 10 years of daily microwave satellite data across North Africa at a 1∘ horizontal scale. Specifically, the co-existence and co-variability of spatial (i.e. using soil moisture gradients) and temporal (i.e. using soil moisture anomaly) soil moisture effects on afternoon rainfall is explored. The analysis shows that in the semi-arid environment of the Sahel, the negative spatial and the negative temporal coupling relationships do not only co-exist, but are also dependent on one another. Hence, if afternoon rain falls over temporally drier soils, it is likely to be surrounded by a wetter environment. Two regions are identified as SMPC “hot spots”. These are the south-western part of the domain (7–15∘ N, 10∘ W–7∘ E), with the most robust negative SMPC signal, and the South Sudanese region (5–13∘ N, 24–34∘ E). The sign and significance of the coupling in the latter region is found to be largely modulated by the presence of wetlands and is susceptible to the number of long-lived propagating convective systems. The presence of wetlands and an irrigated land area is found to account for about 30 % of strong and significant spatial SMPC in the North African domain. This study provides the first insight into regional variability of SMPC in North Africa, and supports the potential relevance of mechanisms associated with enhanced sensible heat flux and mesoscale variability in surface soil moisture for deep convection development.

Recent observational studies have demonstrated the relevance of soil moisture heterogeneity and the associated thermally-induced circulation on deep convection and rainfall triggering. However, whether this dynamical mechanism further influences rainfall properties—such as rain volume or timing—has yet to be confirmed by observational data. Here, we analyze 10 years of satellite-based sub-daily soil moisture and precipitation records and explore the potential of strong spatial gradients in morning soil moisture to influence the properties of afternoon rainfall in the North African region, at the 100-km scale. We find that the convective rain systems that form over locally drier soils and anomalously strong soil moisture gradients have a tendency to initiate earlier in the afternoon; they also yield lower volumes of rain, weaker intensity and lower spatial variability. The strongest sensitivity to antecedent soil conditions is identified for the timing of the rain onset; it is found to be correlated with the magnitude of the soil moisture gradient. Further analysis shows that the early initiation of rainfall over dry soils and strong surface gradients yet requires the presence of a very moist boundary layer on that day. Our findings agree well with the expected effects of thermally-induced circulation on rainfall properties suggested by theoretical studies and point to the potential of locally drier and heterogeneous soils to influence convective rainfall development. The systematic nature of the identified effect of soil moisture state on the onset time of rainstorms in the region is of particular relevance and may help foster research on rainfall predictability.

The magnitude and sign of soil moisture - precipitation coupling (SMPC) is investigated using a probability-based approach and 10 years of daily microwave satellite data across North Africa at 1° horizontal resolution. Specifically, the co-existence and co-variability of spatial (i.e. using soil moisture gradients) and temporal (i.e. using soil moisture anomaly) soil moisture effects on afternoon rainfall is studied at 100 km scale. The analysis shows that in the semi-arid environment of the Sahel, the negative spatial and the negative temporal coupling relationships do not only co-exist, but are also dependent of one another. Hence, if afternoon rain falls over temporally drier soils, it is likely to be surrounded by a wetter environment. Two regions are identified as SMPC "hot spots". These are the south-western part of the domain (7–15° N, 10° W–7° E) with the most robust negative SMPC signal, and the South Sudanian region (5–13° N, 24–34° E). The sign and significance of the coupling in the latter region is found to be largely modulated by the presence of wetlands and is susceptible to the amount of long-lived propagating convective systems. The presence of wetlands and irrigated land areas is found to account for about 30 % of strong and significant spatial SMPC in North African domain. This study provides the first insight into regional variability of SMPC in North Africa, and supports potential relevance of mechanisms associated with enhanced sensible heat flux and meso-scale variability in surface soil moisture for deep convection development.