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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.

 

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.

Understanding 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.

 

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

 

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.

 

The US Southwest is in a drought crisis that has been developing over the past two decades, contributing to marked increases in burned forest areas and unprecedented efforts to reduce water consumption. Climate change has contributed to this ongoing decadal drought via warming that has increased evaporative demand and reduced snowpack and streamflows. However, on the supply side, precipitation has been low during the 21st century. Here, using simulations with an atmosphere model forced by imposed sea surface temperatures, we show that the 21st century shift to cooler tropical Pacific sea surface temperatures forced a decline in cool season precipitation that in turn drove a decline in spring to summer soil moisture in the southwest. We then project the near-term future out to 2040, accounting for plausible and realistic natural decadal variability of the Pacific and Atlantic Oceans and radiatively-forced change. The future evolution of decadal variability in the Pacific and Atlantic will strongly influence how wet or dry the southwest is in coming decades as a result of the influence on cool season precipitation. The worst-case scenario involves a continued cold state of the tropical Pacific and the development of a warm state of the Atlantic while the best case scenario would be a transition to a warm state of the tropical Pacific and the development of a cold state of the Atlantic. Radiatively-forced cool season precipitation reduction is strongest if future forced SST change continues the observed pattern of no warming in the equatorial Pacific cold tongue. Although this is a weaker influence on summer soil moisture than natural decadal variability, no combination of natural decadal variability and forced change ensures a return to winter precipitation or summer soil moisture levels as high as those in the final two decades of the 20th century.

 

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. 

Cold winters over Eurasia often coincide with warm winters in the Arctic, which has become known as the “warm Arctic–cold Eurasia” pattern. The extent to which this observed correlation is indicative of a causal response to sea ice loss is debated. Here, using large multimodel ensembles of coordinated experiments, we find that the Eurasian temperature response to Arctic sea ice loss is weak compared to internal variability and is not robust across climate models. We show that Eurasian cooling is driven by tropospheric and stratospheric circulation changes in response to sea ice loss but is counteracted by tropospheric thermodynamical warming, as the local warming induced by sea ice loss spreads into the midlatitudes by eddy advection. Although opposing effects of thermodynamical warming and dynamical cooling are found robustly across different models or different sea ice perturbations, their net effect varies in sign and magnitude across the models, resulting in diverse model temperature responses over Eurasia. The contributions from both tropospheric dynamics and thermodynamics show substantial intermodel spread. Although some of this spread in the Eurasian winter temperature response to sea ice loss may stem from model uncertainty, even with several hundred ensemble members, it is challenging to isolate model differences in the forced response from internal variability.