Intensification of future subsurface marine heatwaves in an eddy-resolving model.

A shift in depth range enables marine organisms to adapt to marine heatwaves (MHWs). Subsurface MHWs could limit this pathway, yet their response to climate warming remains unclear. Here, using an eddy-resolving Earth system model forced under a high emission scenario, we project a robust global increase in subsurface MHWs driven by rising subsurface mean temperatures and enhanced temperature variability.

An analytic theory for the degree of Arctic Amplification.

Arctic Amplification (AA), the amplified surface warming in the Arctic relative to the globe, is a salient feature of climate change. While the basic physical picture of AA has been depicted, how its degree is determined has not been clearly understood. Here, by deciphering atmospheric heat transport (AHT), we build a two-box energy-balance model of AA and derive that the degree of AA is a simple nonlinear function of the Arctic and global feedbacks, the meridional heterogeneity in radiative forcing, and the partial sensitivities of AHT to global mean and meridional gradient of warming.

Climate change will reduce North American inland wetland areas and disrupt their seasonal regimes.

Climate change can alter wetland extent and function, but such impacts are perplexing. Here, changes in wetland characteristics over North America from 25° to 53° North are projected under two climate scenarios using a state-of-the-science Earth system model. At the continental scale, annual wetland area decreases by ~10% (6%-14%) under the high emission scenario, but spatiotemporal changes vary, reaching up to ±50%.

The role of interdecadal climate oscillations in driving Arctic atmospheric river trends.

Atmospheric rivers (ARs), intrusions of warm and moist air, can effectively drive weather extremes over the Arctic and trigger subsequent impact on sea ice and climate. What controls the observed multi-decadal Arctic AR trends remains unclear. Here, using multiple sources of observations and model experiments, we find that, contrary to the uniform positive trend in climate simulations, the observed Arctic AR frequency increases by twice as much over the Atlantic sector compared to the Pacific sector in 1981-2021.

A North Atlantic synthetic tropical cyclone track, intensity, and rainfall dataset.

Tropical Cyclones (TCs) cause significant socio-economic damages to the US and Caribbean coastal regions annually, making it important to understand TC risk at the local-to-regional scales. However, the short length of the observed record and the substantial computational expense associated with high-resolution climate models make it difficult to assess TC risk using either approach. To overcome these challenges, we developed a database of synthetic TCs using the Risk Analysis Framework for Tropical Cyclones (RAFT).

Aerosols overtake greenhouse gases causing a warmer climate and more weather extremes toward carbon neutrality.

To mitigate climate warming, many countries have committed to achieve carbon neutrality in the mid-21 century. Here, we assess the global impacts of changing greenhouse gases (GHGs), aerosols, and tropospheric ozone (O) following a carbon neutrality pathway on climate and extreme weather events individually using the Community Earth System Model version 1 (CESM1). The results suggest that the future aerosol reductions significantly contribute to climate warming and increase the frequency and intensity of extreme weathers toward carbon neutrality and aerosol impacts far outweigh those of GHGs and tropospheric O.

Southern Hemisphere dominates recent decline in global water availability.

Global land water underpins livelihoods, socioeconomic development, and ecosystems. It remains unclear how water availability has changed in recent decades. Using an ensemble of observations, we quantified global land water availability over the past two decades.

Future precipitation increase constrained by climatological pattern of cloud effect.

The fractional increase in global mean precipitation ([Formula: see text]) is a first-order measure of the hydrological cycle intensification under anthropogenic warming. However, [Formula: see text] varies by a factor of more than three among model projections, hindering credible assessments of the associated climate impacts. The uncertainty in [Formula: see text] stems from uncertainty in both hydrological sensitivity (global mean precipitation increase per unit warming) and climate sensitivity (global mean temperature increase per forcing).

A cleaner snow future mitigates Northern Hemisphere snowpack loss from warming.

Light-absorbing particles (LAP) deposited on seasonal snowpack can result in snow darkening, earlier snowmelt, and regional climate change. However, their future evolution and contributions to snowpack change relative to global warming remain unclear. Here, using Earth System Model simulations, we project significantly reduced black carbon deposition by 2081-2100, which reduces the December-May average LAP-induced radiative forcing in snow over the Northern Hemisphere from 1.

Robust projection of East Asian summer monsoon rainfall based on dynamical modes of variability.

The Asian monsoon provides the freshwater that a large population in Asia depends on, but how anthropogenic climate warming may alter this key water source remains unclear. This is partly due to the prevailing point-wise assessment of climate projections, even though climate change patterns are inherently organized by dynamics intrinsic to the climate system. Here, we assess the future changes in the East Asian summer monsoon precipitation by projecting the precipitation from several large ensemble simulations and CMIP6 simulations onto the two leading dynamical modes of internal variability.

Global droughts connected by linkages between drought hubs.

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.

Threat by marine heatwaves to adaptive large marine ecosystems in an eddy-resolving model.

Marine heatwaves (MHWs), episodic periods of abnormally high sea surface temperature (SST), severely affect marine ecosystems. Large Marine Ecosystems (LMEs) cover ~22% of the global ocean but account for 95% of global fisheries catches. Yet how climate change affects MHWs over LMEs remains unknown, because such LMEs are confined to the coast where low-resolution climate models are known to have biases.

Datasets for characterizing extreme events relevant to hydrologic design over the conterminous United States.

Despite the close linkage between extreme floods and snowmelt, particularly through rain-on-snow (ROS), hydrologic infrastructure is mostly designed based on standard precipitation Intensity-Duration-Frequency curves (PREC-IDF) that neglect snow processes in runoff generation. For snow-dominated regions, such simplification could result in substantial errors in estimating extreme events and infrastructure design risk. To address this long-standing problem, we applied the Next Generation IDF (NG-IDF) technique to estimate design basis extreme events for different durations and return periods in the conterminous United States (CONUS) to distinctly represent the contribution of rain, snowmelt, and ROS events to the amount of water reaching the land surface.

Trends in surface equivalent potential temperature: A more comprehensive metric for global warming and weather extremes.

Trends in surface air temperature (SAT) are a common metric for global warming. Using observations and observationally driven models, we show that a more comprehensive metric for global warming and weather extremes is the trend in surface equivalent potential temperature (Thetae_sfc) since it also accounts for the increase in atmospheric humidity and latent energy. From 1980 to 2019, while SAT increased by 0.

Urbanization Impact on Regional Climate and Extreme Weather: Current Understanding, Uncertainties, and Future Research Directions.

Urban environments lie at the confluence of social, cultural, and economic activities and have unique biophysical characteristics due to continued infrastructure development that generally replaces natural landscapes with built-up structures. The vast majority of studies on urban perturbation of local weather and climate have been centered on the urban heat island (UHI) effect, referring to the higher temperature in cities compared to their natural surroundings. Besides the UHI effect and heat waves, urbanization also impacts atmospheric moisture, wind, boundary layer structure, cloud formation, dispersion of air pollutants, precipitation, and storms.

Uncertainty in El Niño-like warming and California precipitation changes linked by the Interdecadal Pacific Oscillation.

Marked uncertainty in California (CA) precipitation projections challenges their use in adaptation planning in the region already experiencing severe water stress. Under global warming, a westerly jet extension in the North Pacific analogous to the El Niño-like teleconnection has been suggested as a key mechanism for CA winter precipitation changes. However, this teleconnection has not been reconciled with the well-known El Niño-like warming response or the controversial role of internal variability in the precipitation uncertainty.

Early warm-season mesoscale convective systems dominate soil moisture-precipitation feedback for summer rainfall in central United States.

Land-atmosphere interactions play an important role in summer rainfall in the central United States, where mesoscale convective systems (MCSs) contribute to 30 to 70% of warm-season precipitation. Previous studies of soil moisture-precipitation feedbacks focused on the total precipitation, confounding the distinct roles of rainfall from different convective storm types. Here, we investigate the soil moisture-precipitation feedbacks associated with MCS and non-MCS rainfall and their surface hydrological footprints using a unique combination of these rainfall events in observations and land surface simulations with numerical tracers to quantify soil moisture sourced from MCS and non-MCS rainfall.

Identifying Key Drivers of Wildfires in the Contiguous US Using Machine Learning and Game Theory Interpretation.

Understanding the complex interrelationships between wildfire and its environmental and anthropogenic controls is crucial for wildfire modeling and management. Although machine learning (ML) models have yielded significant improvements in wildfire predictions, their limited interpretability has been an obstacle for their use in advancing understanding of wildfires. This study builds an ML model incorporating predictors of local meteorology, land-surface characteristics, and socioeconomic variables to predict monthly burned area at grid cells of 0.

Health and economic impacts of air pollution induced by weather extremes over the continental U.S.

Extreme weather events may enhance ozone (O) and fine particulate matter (PM) pollution, causing additional adverse health effects. This work aims to evaluate the health and associated economic impacts of changes in air quality induced by heat wave, stagnation, and compound extremes under the Representative Concentration Pathways (RCP) 4.5 and 8.

A substantial role of soil erosion in the land carbon sink and its future changes.

Realistic representation of land carbon sink in climate models is vital for predicting carbon climate feedbacks in a changing world. Although soil erosion that removes land organic carbon has increased substantially since the onset of agriculture, it is rarely included in the current generation of climate models. Using an Earth system model (ESM) with soil erosion represented, we estimated that on average soil erosion displaces 5% of newly fixed land organic carbon downslope annually in the continental United States.