Search for: All records

Abstract Compound events (CEs) are attracting increased attention due to their significant societal and ecological impacts. However, their inherent complexity can pose challenges for climate scientists and practitioners, highlighting the need for a more approachable and intuitive framework for detecting and visualising CEs. Here, we introduce the Compound Events Toolbox and Dataset (CETD), which provides the first integrated, interactive, and extensible platform for CE detection and visualisation. Employing observations, reanalysis, and model simulations, CETD can quantify the frequency, duration, and severity of multiple CE types: multivariate, sequential, and concurrent events. It can analyse CEs often linked to severe impacts on human health, wildfires, and air pollution, such as hot-dry, wet-windy, and hot-dry-stagnation events. To validate the performance of CETD, we conduct statistical analyses for several high-impact events, such as the 2019 Australian wildfires and the 2022 European heatwaves. The accessibility and extensibility of CETD will benefit the broader community by enabling them to better understand and prepare for the risks and challenges posed by CEs in a warming world. 

Abstract Individually, extreme humid heat and extreme precipitation events can trigger widespread socioeconomic impacts which disproportionately affect vulnerable populations. These impacts might become greater when both events occur in close temporal proximity, for example if emergency responses to heat stress casualties are hindered by flooded roads. Improved understanding of the probabilities and physical mechanisms associated with these events’ temporal compounding might uncover causal interrelationships offering avenues for improving early warning systems and projecting changes in a warmer climate. We explore sequential humid heat and rainfall relationships during the local summer season, identifying two classes of temporal relationships. We find that high wet bulb temperature (WBT) anomalies in most mid- to high-latitude and tropical regions are preceded by anomalously low precipitation. In contrast, hot and dry subtropical regions generally experience elevated WBTs during and, to a somewhat lesser extent, before extreme precipitation events. High WBT events are followed by positive precipitation anomalies in many land regions. 

Abstract A sequence of torrential rainstorms pounded Pakistan in the summer of 2022, shattering records by massive margins (7 sigma). The severe socioeconomic damages underscore the urgency of identifying its dynamic drivers and relationship with human-induced climate change. Here, we find that the downpours were primarily initiated by the synoptic low-pressure systems, whose intensity and longevity far exceeded their counterparts in history as fueled by a historically-high cross-equatorial moisture transport over the Arabian Sea. The moisture transport has been trending upward since the 1960s and, in 2022, along with the anomalous easterly moisture influx caused by the combination of La Niña and negative Indian Ocean Dipole events, created a corridor of heavy rainfall extending from central India toward southern Pakistan. While it is not yet established whether the observed trend of the cross-equatorial moisture transport has exceeded natural variability, model-based analysis confirms that it is consistent with the fingerprint of anthropogenic climate warming and will raise the likelihood of such rare events substantially in the coming decades. 

Abstract Anthropogenic climate change has already affected drought severity and risk across many regions, and climate models project additional increases in drought risk with future warming. Historically, droughts are typically caused by periods of below‐normal precipitation and terminated by average or above‐normal precipitation. In many regions, however, soil moisture is projected to decrease primarily through warming‐driven increases in evaporative demand, potentially affecting the ability of negative precipitation anomalies to cause drought and positive precipitation anomalies to terminate drought. Here, we use climate model simulations from Phase Six of the Coupled Model Intercomparison Project (CMIP6) to investigate how different levels of warming (1, 2, and 3°C) affect the influence of precipitation on soil moisture drought in the Mediterranean and Western North America regions. We demonstrate that the same monthly precipitation deficits (25th percentile relative to a preindustrial baseline) at a global warming level of 2°C increase the probability of both surface and rootzone soil moisture drought by 29% in the Mediterranean and 32% and 6% in Western North America compared to the preindustrial baseline. Furthermore, the probability of a dry (25th percentile relative to a preindustrial baseline) surface soil moisture month given a high (75th percentile relative to a preindustrial baseline) precipitation month is 6 (Mediterranean) and 3 (Western North America) times more likely in a 2°C world compared to the preindustrial baseline. For these regions, warming will likely increase the risk of soil moisture drought during low precipitation periods while simultaneously reducing the efficacy of high precipitation periods to terminate droughts. 

Abstract Southwest North America is projected by models to aridify, defined as declining summer soil moisture, under the influence of rising greenhouse gases. Here, we investigate the driving mechanisms of aridification that connect the oceans, atmosphere, and land surface across seasons. The analysis is based on atmosphere model simulations forced by imposed sea surface temperatures (SSTs). For the historical period, these are the observed ones, and the model is run to 2041 using SSTs that account for realistic and plausible evolutions of Pacific Ocean and Atlantic Ocean interannual to decadal variability imposed on estimates of radiatively forced SST change. The results emphasize the importance of changes in precipitation throughout the year for declines in summer soil moisture. In the worst-case scenario, a cool tropical Pacific and warm North Atlantic lead to reduced cool season precipitation and soil moisture. Drier soils then persist into summer such that evapotranspiration reduces and soil moisture partially recovers. In the best-case scenario, the opposite states of the oceans lead to increased cool season precipitation but higher evapotranspiration prevents this from increasing summer soil moisture. Across the scenarios, atmospheric humidity is primarily controlled by soil moisture: drier soils lead to reduced evapotranspiration, lower air humidity, and higher vapor pressure deficit (VPD). Radiatively forced change reduces fall precipitation via anomalous transient eddy moisture flux divergence. Fall drying causes soils to enter winter dry such that, even in the best-case scenario of cool season precipitation increase, soil moisture remains dry. Radiative forcing reduces summer precipitation aided by reduced evapotranspiration from drier soils. Significance StatementSouthwest North America has long been projected to undergo aridification under rising greenhouse gases. In this model-based paper, we examine how coupling across seasons between the atmosphere and land system moves the region toward reduced summer soil moisture. The results show the dominant control on summer soil moisture by precipitation throughout the year. It also shows that even in best-case scenarios when changes in decadal modes of ocean variability lead to increases in cool season precipitation, rising spring and summer evapotranspiration means this does not translate into increased summer soil moisture. The work places projections of regional aridification on a firmer basis of understanding of the ocean driving of the atmosphere and its coupling to the land system. 

The seasonal rainy phase observed in many places across Earth is shaping the climate and is being changed by global climate trends. 

Abstract Previous findings show that large-scale atmospheric circulation plays an important role in driving Arctic sea ice variability from synoptic to seasonal time scales. While some circulation patterns responsible for Barents–Kara sea ice changes have been identified in previous works, the most important patterns and the role of their persistence remain unclear. Our study uses self-organizing maps to identify nine high-latitude circulation patterns responsible for day-to-day Barents–Kara sea ice changes. Circulation patterns with a high pressure center over the Urals (Scandinavia) and a low pressure center over Iceland (Greenland) are found to be the most important for Barents–Kara sea ice loss. Their opposite-phase counterparts are found to be the most important for sea ice growth. The persistence of these circulation patterns helps explain sea ice variability from synoptic to seasonal time scales. We further use sea ice models forced by observed atmospheric fields (including the surface circulation and temperature) to reproduce observed sea ice variability and diagnose the role of atmosphere-driven thermodynamic and dynamic processes. Results show that thermodynamic and dynamic processes similarly contribute to Barents–Kara sea ice concentration changes on synoptic time scales via circulation. On seasonal time scales, thermodynamic processes seem to play a stronger role than dynamic processes. Overall, our study highlights the importance of large-scale atmospheric circulation, its persistence, and varying physical processes in shaping sea ice variability across multiple time scales, which has implications for seasonal sea ice prediction. Significance StatementUnderstanding what processes lead to Arctic sea ice changes is important due to their significant impacts on the ecosystem, weather, and shipping, and hence our society. A well-known process that causes sea ice changes is atmospheric circulation variability. We further pin down what circulation patterns and underlying mechanisms matter. We identify multiple circulation patterns responsible for sea ice loss and growth to different extents. We find that the circulation can cause sea ice loss by mechanically pushing sea ice northward and bringing warm and moist air to melt sea ice. The two processes are similarly important. Our study advances understanding of the Arctic sea ice variability with important implications for Arctic sea ice prediction. 

Abstract June 2023 witnessed the hottest, largest, and longest‐lasting heatwave across Mexico and Texas between 1940 and 2023. We apply constructed analogs with multiple linear regression models to quantify the contribution of different drivers to daily temperature anomalies during this heatwave. On the hottest day (20 June), circulation, soil moisture, and their interaction explained 3.82°C (90% CI: 2.72–4.91°C) of the 5.42°C observed anomaly with most of the residual attributed to the thermodynamic effects of long‐term warming. Using CESM2‐LENS2, we find that June 2023‐like patterns are not projected to increase in frequency but will become 1.9°C hotter by the mid‐21st century under SSP3‐7.0. The hottest simulated day with these patterns could produce temperatures >50°C (122°F) across south Texas, representing a low‐likelihood yet physically plausible worst‐case scenario that could inform disaster preparedness and adaptation planning. 

Abstract Increases in population exposure to humid heat extremes in agriculturally-dependent areas of the world highlights the importance of understanding how the location and timing of humid heat extremes intersects with labor-intensive agricultural activities. Agricultural workers are acutely vulnerable to heat-related health and productivity impacts as a result of the outdoor and physical nature of their work and by compounding socio-economic factors. Here, we identify the regions, crops, and seasons when agricultural workers experience the highest hazard from extreme humid heat. Using daily maximum wet-bulb temperature data, and region-specific agricultural calendars and cropland area for 12 crops, we quantify the number of extreme humid heat days during the planting and harvesting seasons for each crop between 1979–2019. We find that rice, an extremely labor-intensive crop, and maize croplands experienced the greatest exposure to dangerous humid heat (integrating cropland area exposed to >27 °C wet-bulb temperatures), with 2001–2019 mean rice and maize cropland exposure increasing 1.8 and 1.9 times the 1979–2000 mean exposure, respectively. Crops in socio-economically vulnerable regions, including Southeast Asia, equatorial South America, the Indo-Gangetic Basin, coastal Mexico, and the northern coast of the Gulf of Guinea, experience the most frequent exposure to these extremes, in certain areas exceeding 60 extreme humid heat days per year when crops are being cultivated. They also experience higher trends relative to other world regions, with certain areas exceeding a 15 day per decade increase in extreme humid heat days. Our crop and location-specific analysis of extreme humid heat hazards during labor-intensive agricultural seasons can inform the design of policies and efforts to reduce the adverse health and productivity impacts on this vulnerable population that is crucial to the global food system. 

Abstract The interannual variability of summertime subtropical stationary waves, the forcing mechanisms, and their connections to regional tropical cyclone (TC) variability are investigated in this study. Two indices are identified to characterize the interannual variability of subtropical stationary waves: the longitudinal displacement of the zonal wavenumber-1 component (WN1) and the intensity change of the zonal wavenumber-2 component (WN2). These two indices are strongly anticorrelated and offer simple metrics to depict the interannual variability of subtropical stationary waves. Furthermore, the longitudinal displacement of the WN1 is significantly correlated with the variability of TC activity over the North Pacific and North Atlantic, and its influences on regional TC activity can be explained by variations in vertical wind shear, tropospheric humidity, and the frequency of Rossby wave breaking. The subtropical stationary waves are strongly related to precipitation anomalies over different oceanic regions, implying the possible impacts of low-frequency climate modes. Semi-idealized experiments using the Community Earth System Model version 2 (CESM2) show that the longitude of the WN1 is strongly modulated by ENSO, as well as SST anomalies over the Atlantic main development region and the central North Pacific. Further diagnosis using a baroclinic stationary wave model demonstrates the dominant role of diabatic heating in driving the interannual variability of stationary waves and confirms the impacts of different air–sea coupled modes on subtropical stationary waves. Overall, subtropical stationary waves provide a unified framework to understand the impacts of various forcing agents, such as ENSO, the Atlantic meridional mode, and extratropical Rossby wave breaking, on TC activity over the North Atlantic and North Pacific.