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Quantifying the spatial and interconnected structure of regional to continental scale droughts is one of the unsolved global hydrology problems, which is important for understanding the looming risk of mega-scale droughts and the resulting water and food scarcity and their cascading impact on the worldwide economy. Using a Complex Network analysis, this study explores the topological characteristics of global drought events based on the self-calibrated Palmer Drought Severity Index. Event Synchronization is used to measure the strength of association between the onset of droughts at different spatial locations within the time lag of 1-3 months. The network coefficients derived from the synchronization network indicate a highly heterogeneous connectivity structure underlying global drought events. Drought hotspot regions such as Southern Europe, Northeast Brazil, Australia, and Northwest USA behave as drought hubs that synchronize regionally and with other hubs at inter-continental or even inter-hemispheric scale. This observed affinity among drought hubs is equivalent to the ‘rich-club phenomenon’ in Network Theory, where ‘rich’ nodes (here, drought hubs) are tightly interconnected to form a club, implicating the possibility of simultaneous large-scale droughts over multiple continents.

 

The significant impact of flash droughts (FDs) on society can vary based on a combination of FD characteristics (event counts, mean severity, and rate of intensification), which is largely unexplored. We employed root‐zone soil‐moisture for 1980–2018 to calculate the FD characteristics and integrated them to formulate a novel multivariate FD indicator for mapping the global FD hotspot regions. The potential influence of climate characteristics (i.e., anomalies, aridity, and evaporative fractions) and land‐climate feedbacks on the evolution of multivariate FD indicator is investigated. Our results indicate that precipitation is the primary driver of FD evolution, while the effect of temperature, vapor pressure deficit, and land‐climate interaction varies across the climate divisions after the onset of the events. The magnitude of multivariate FD indicator decreases with increased climate aridity, and it is significant in the global humid regimes, underscoring the importance of water and energy supply as limiting factors regulating FD‐risk.

 

Droughts have a dominant three‐dimensional (3‐D) spatiotemporal structure typically spanning hundreds of kilometers and often lasting for months to years. Here, we introduced a novel framework to explore the 3‐D structure of the evolution of droughts based on network theory concepts. The proposed framework is applied to identify critical source regions responsible for large‐scale drought onsets during 1901–2014 for the North American continent using the Standardized Precipitation Evaporation Index (SPEI). We built a spatial network connecting the drought onset timings for the North American continent. Using a spatially weighted network partitioning algorithm, the whole continent is then classified into regional spatial drought networks (RSN), where droughts are more likely to propagate within these regional systems. Finally, a customized network metric was applied to identify locations (source regions) where the drought onsets further propagate to other areas within the regional spatial network. Our results indicated that the West coast, Texas coastal region, and Southeastern Arkansas as major source regions through which atmospheric drought propagates to Western, South Central, and Eastern North America. The formation of drought source regions are due to presence of high pressure ridges and anomalous wind patterns. Furthermore, our results indicate that the drought propagation from these source regions may be due to inadequate moisture transport. The proposed framework can help to develop an early warning detection system for droughts and other spatially extensive extreme events such as heatwaves and floods.

 

Compound drought and heatwaves can cause significant damage to the environment, economy, and society. In this study, we quantify the spatio‐temporal changes in compound drought and heatwave (CDHW) events by integrating weekly self‐calibrated Palmer Drought Severity Index (sc_PDSI) and daily maximum temperatures during the period 1983 to 2016. Multiple data products are used to examine the robustness of sc_PDSI in the compound event analysis. The results consistently suggest significant increases in drought‐related heatwaves and affected global land area in recent (warmer) periods. Several regions across the globe witnessed rise in CDHW frequency (one to three events/year), duration (2–10 days/year), and severity. This increasing pattern is spatially asymmetric, and greater amplification is observed across the Northern hemisphere due to recent warming. Furthermore, the background aridity influences the spatiotemporal evolution of CDHW events. The results can be applied to minimize the impacts of extreme CDHWs in critical geographical regions.

 

Globally, heat stress (HS) is nearly certain to increase rapidly over the coming decades, characterized by increased frequency, severity, and spatiotemporal extent of extreme temperature and humidity. While these characteristics have been investigated independently, a holistic analysis integrating them is potentially more informative. Using observations, climate projections from the CMIP5 model ensemble, and historical and future population estimates, we apply the IPCC risk framework to examine present and projected future potential impact (PI) of summer heat stress for the contiguous United States (CONUS) as a function of non‐stationary HS characteristics and population exposure. We find that the PI of short‐to‐medium duration (1–7 days) HS events is likely to increase more than three‐fold across densely populated regions of the U.S. including the Northeast, Southeast Piedmont, Midwest, and parts of the Desert Southwest by late this century (2060–2099) under the highest emissions scenario. The contribution from climate change alone more than doubles the impact in the coastal Pacific Northwest, central California, and the Great Lakes region, implying a substantial increase in HS risk without aggressive mitigation efforts.

 

Complex network (CN) is a graph theory‐based depiction of relation shared by various elements of a complex dynamical system such as the atmosphere. Here we apply the concept of CN to understand the directionality and topological structure of summer extreme precipitation events (SEPEs) over the conterminous United States (CONUS). The SEPEs are calculated based on the 95th percentile daily rainfall at 0.5° × 0.5° spatial resolution for CONUS to investigate the multidimensional characteristics of precipitation extremes. The derived CN coefficients (e.g., betweenness centrality, clustering coefficient, orientation, and network divergence) reveal important structural and dynamical information about the topology of the SEPEs and improve understanding of the dominant meteorological patterns. The initiation and propagation of SEPEs from the source zones to the sink zones are identified. The SEPEs are influenced by topography, dominant wind patterns, and moisture sources in terms of their topological structure and spatial dynamics.

 

Water security is tightly connected with the food security, ecological health, and economic prosperity of a region. In this study, a comprehensive water security assessment based on water footprint concepts from 1995 to 2015 was performed for the counties located in the Contiguous States of the Unites States. The availability of blue water (e.g., surface water) is comparatively less in the western river basins, and most of the rainfed agricultural lands in the eastern United States were characterized by the lower levels of green water (e.g., root zone soil moisture) storage. This integrated assessment of the water security indicators can directly map the critical regions and reveal the dependence between human water consumption, crop water requirements and environmental flow. This analysis can be further extended to incorporate climate change and extreme drought events to inform specific locations (e.g., counties and watersheds) at which problems of water conflict are more likely to occur.

 

Compound drought and heatwave (CDHW) events have garnered much attention in recent studies. However, thus far, the identification of such events is oversimplified, and their association with natural climate variability is not fully explored. Here, we derive anomalies in the weekly self‐calibrated Palmer Drought Severity Index (sc_PDSI) and daily maximum temperatures to identify CDHW events from 1982 to 2016 over 26 climate regions across the globe. Using a Poisson Generalized Linear Model (GLM), we analyze yearly occurrences of seasonal CDHW events and their association with the warm and cold phases of El Nino Southern Oscillation (ENSO), Pacific Decadal Oscillation (PDO), and North Atlantic Oscillation (NAO). ENSO exhibits robust association with CDHW events over the Southern Hemisphere during the austral summer and fall, while PDO influences their occurrences over the Western North America in the Northern Hemisphere during the boreal summer, which is supported by the composites of anomalies in the atmospheric circulations and surface energy budget. However, NAO association with CDHW events is relatively weak. The CDHW occurrence over other regions is driven by a combination of these large‐scale natural forcing. Our analyses also highlight that the cooccurrence of weekly to submonthly scale anomalies in the observed temperature and precipitation may not be always aligned between the observations and the reanalysis. Therefore, caution must be exercised while explaining such observed anomalies on the basis of reanalysis‐based circulations and surface energy budget. Overall, our analyses provide a new insight towards concurrent extremes and should help foster research efforts in this area.

 

Abstract Climate change amplifies dry and hot extremes, yet the mechanism, extent, scope, and temporal scale of causal linkages between dry and hot extremes remain underexplored. Here using the concept of system dynamics, we investigate cross-scale interactions within dry-to-hot and hot-to-dry extreme event networks and quantify the magnitude, temporal-scale, and physical drivers of cascading effects (CEs) of drying-on-heating and vice-versa, across the globe. We find that locations exhibiting exceptionally strong CE (hotspots) for dry-to-hot and hot-to-dry extremes generally coincide. However, the CEs differ strongly in their timescale of interaction, hydroclimatic drivers, and sensitivity to changes in the soil-plant-atmosphere continuum and background aridity. The CE of drying-on-heating in the hotspot locations reaches its peak immediately driven by the compounding influence of vapor pressure deficit, potential evapotranspiration, and precipitation. In contrast, the CE of heating-on-drying peaks gradually dominated by concurrent changes in potential evapotranspiration, precipitation, and net-radiation with the effect of vapor pressure deficit being strongly controlled by ecosystem isohydricity and background aridity. Our results help improve our understanding of the causal linkages and the predictability of compound extremes and related impacts.