Quantifying the role of variability in future intensification of heat extremes

Decadal-scale variability and warming affect spring timing and forest growth across the western Great Lakes region

The Great Lakes region of North America has warmed by 1-2 °C on average since pre-industrial times, with the most pronounced changes observable during winter and spring. Interannual variability in temperatures remains high, however, due to the influence of ocean-atmosphere circulation patterns that modulate the warming trend across years. Variations in spring temperatures determine growing season length and plant phenology, with implications for whole ecosystem function. Studying how both internal climate variability and the "secular" warming trend interact to produce trends in temperature is necessary to estimate potential ecological responses to future warming scenarios. This study examines how external anthropogenic forcing and decadal-scale variability influence spring temperatures across the western Great Lakes region and estimates the sensitivity of regional forests to temperature using long-term growth records from tree-rings and satellite data. Using a modeling approach designed to test for regime shifts in dynamic time series, this work shows that mid-continent spring climatology was strongly influenced by the 1976/1977 phase change in North Pacific atmospheric circulation, and that regional forests show a strengthening response to spring temperatures during the last half-century.

Enhanced risk of record-breaking regional temperatures during the 2023-24 El Niño

In 2023, the development of El Niño is poised to drive a global upsurge in surface air temperatures (SAT), potentially resulting in unprecedented warming worldwide. Nevertheless, the regional patterns of SAT anomalies remain diverse, obscuring where historical warming records may be surpassed in the forthcoming year. Our study underscores the significant influence of El Niño and the persistence of climate signals on the inter-annual variability of regional SAT, both in amplitude and spatial distribution. The likelihood of global mean SAT exceeding historical records, calculated from July 2023 to June 2024, is estimated at 90%, contingent upon annual-mean sea surface temperature anomalies in the eastern equatorial Pacific exceeding 0.6 °C. Regions particularly susceptible to recording record-high SAT include coastal and adjacent areas in Asia such as the Bay of Bengal and the South China Sea, as well as Alaska, the Caribbean Sea, and the Amazon. This impending warmth heightens the risk of year-round marine heatwaves and escalates the threat of wildfires and other negative consequences in Alaska and the Amazon basin, necessitating strategic mitigation measures to minimize potential worst-case impacts.

Projected climate extremes over agro-climatic zones of Ganga River Basin under 1.5, 2, and 3° global warming levels

Recurring floods, droughts, heatwaves, and other hydro-meteorological extreme events are likely to be increased under the climate change scenarios. The increased risk of these extreme events might have more exposure to the population; thus, it is important to discuss such extreme events and their projected behavior under a changing climate scenario. In the present study, we have computed the extreme precipitation and temperature indices over the 10 agro-climatic zones falling under the Ganga River Basin (GRB)utilizing a high-resolution daily gridded temperature and precipitation multi-model ensembled CMIP6 dataset (0.25° × 0.25°) under global warming levels of 1.5 °C, 2 °C, and 3 °C. We found that the annual daily minimum temperature (TNN) showed a higher rise of about 67% than the maximum temperature (TXX) of 48% in GRB. The basin also experiences a greater increase in the frequency of warm nights (TN90P) of about 67.71% compared to warm days (TX90P) of 29.1% for the 3 °C global warming level. Along with extreme indices, the population exposed due to the impact of the extreme maximum temperature has also been analyzed for progressive warming levels. Population exposure to extreme temperature event (TXX) has been analyzed with 20-year return period using GEV distribution method. The study concludes that the exposed population to extreme temperature event experienced an increase from 46.99 to 52.16% for the whole Ganga Basin. Consecutive dry days (CDD) and consecutive wet days (CWD) both show a significant increasing trend, but CWD has a significant increase in the majority of the zones, while CDD shows a significant decreasing trend for some of the zones for three warming levels periods. Extreme climate indices help to understand the frequency and intensity of extreme weather events such as heavy rainfall, droughts, and heatwaves to develop early warning systems and adaptation strategies to mitigate such events.