Abstract The Initial Spread Index (ISI), a component of the Canadian Forest Fire Danger Rating System, quantifies the expected rate of fire spread and is used operationally across Alaska. Despite its importance, ISI's historical behavior, variability, and environmental sensitivity have not been systematically characterized for Alaska. This study presents the first Alaska-wide climatology, trend analysis, and extremes assessment of ISI using gridded reanalysis data spanning 1991–2024, organized by Predictive Service Areas (PSAs) and fire season sub-seasons. ISI climatology peaks during the wind-driven and duff sub-seasons, with the highest values at low elevations in interior Alaska. Decadal trends show increasing early-season ISI statewide, with the strongest, most statistically significant increases in the Upper Yukon Valley (≥0.5 per decade), consistent with an earlier onset of fire activity. ISI variability has increased across all PSA groups, with a statistically significant rise in the East Boreal, and the frequency of days exceeding the 95th percentile of historical ISI has increased in 17 of 18 PSA regions. Sensitivity analysis showed that wind speed increases lead to the greatest ISI variability (+12% to +60%), while the largest impacts on mean ISI occurred when relative humidity was decreased or increased by 30% (+39% to +77% and −27% to −72%, respectively); high ISI values did not occur when precipitation exceeded 2 mm. Case studies from June 2013 and May 2021 show ISI spikes aligned with surges in acres burned, supporting its value as a diagnostic indicator of rapid fire spread. These findings provide a foundation for improved fire season planning and management across Alaska's boreal and tundra regions.
Abstract Global warming is intensifying hydroclimatic extremes across the Indian River Basins (IRBs) under the 1.5°C and 2.0°C global warming levels (GWLs) relative to preindustrial levels. Using multi-model CMIP6 projections under SSP2-4.5 and SSP5-8.5, we evaluate precipitation extremes across the IRBs. The Consecutive Dry Days (CDD) index shows a scenario-dependent response: under SSP2-4.5, dry-spell duration declines by 17–28% (approximately 11-28 fewer days) in the Barak, Indus, Brahmaputra, EFR (Pennar-Kanyakumari), Pennar, and Cauvery basins, while the Sabarmati and Inland Drainage basins increase by 9–11% (approximately 20-23 additional days) at 2.0°C GWL. However, the Consecutive Wet Days (CWD) index also shows a scenario-dependent response: under SSP2-4.5, wet-spell duration increases by up to 20.2% (approximately 5–8 additional days) in the Indus and EFR (Pennar–Kanyakumari) basins, whereas under SSP5-8.5, CWD decreases by 19–21% (approximately 10–12 fewer days) in the EFR (Mahanadi–Pennar) and Krishna basins. Projected maximum 5-day rainfall (Rx5day) shows mixed signals, with the largest increases in the West-Flowing River (Kutch–Saurashtra–Luni) basin (+16%) and the Ganga basin (+5%), and the largest decreases in the basin draining to Myanmar (−22%) and the Inland Drainage basin (−21%). Hotspots of increasing flood risk emerge in the Ganga and West-Flowing River basins, while the Inland Drainage basin shows the largest projected decrease in extreme rainfall. Overall, the additional 0.5°C of warming produces basin-specific and scenario-dependent shifts in drought and flood indices rather than a uniform amplification of both hazards, underscoring the need for basin-specific adaptation.
The global thermohaline circulation, driven by density contrasts in seawater, plays a fundamental role in global climate regulation. Within this system, the Atlantic meridional overturning circulation (AMOC) governs large-scale heat redistribution between hemispheres. However, anthropogenic forcing in the Anthropocene threatens to weaken the AMOC, with profound consequences for regional climates and ecosystems. In this study, we applied a global atmospheric circulation model coupled with a dynamic global vegetation model to evaluate two sea surface temperature scenarios: a control case and an anomaly experiment based on Manabe and Stouffer. The simulations revealed pronounced precipitation anomalies, including substantial reductions in rainfall during several months that typically belong to the wet season and enhanced rainfall during months historically associated with the dry season in parts of the Amazon, linked to a displacement of the intertropical convergence zone (ITCZ). Additional impacts included surface cooling in the Amazon, warming in central Brazil, and weakening of the South Atlantic subtropical high, which enhanced frontal system penetration in southeastern Brazil. Vegetation dynamics indicated an expansion of tropical forests into Caatinga regions, where Caatinga is a semiarid dense shrubland ecosystem in Northeast Brazil, reflecting strong biosphere-climate feedbacks. Moreover, the reorganization of Hadley cell circulation confirmed large-scale atmospheric adjustments. Altogether, these results suggest that AMOC weakening may substantially reshape rainfall regimes, temperature patterns, pressure systems, and vegetation cover across Brazil.
Over the past century, groundwater overexploitation has triggered severe land subsidence in coastal megacities like Tianjin, China. However, with policy changes such as enforced extraction restrictions and large-scale water diversion, the downward trend has now been reversed, unexpectedly leading to strange phenomena. Long-term monitoring in Tianjin (2013-23) reveals a complex spatiotemporal pattern where areas of persistent land subsidence coexist with zones of recent uplift, following shifts in groundwater policy. The mechanisms governing this transition, particularly the lagged, nonelastic nature of the uplift, remain poorly quantified. The decade-long leveling data and field experiments were integrated to elucidate the differential hydromechanical response of layered soils. Especially, the field experiments reveal distinct deformation mechanisms: Sand layers exhibit primarily elastoplastic behavior, whereas clay layers are dominated by viscoplastic deformation. These contrasting responses, combined with variations in layer thickness, lead to spatially heterogeneous ground movement. These insights inform the development of a 3D visco-elasto-plastic hydromechanical coupling model, explicitly incorporating state-dependent parameters to capture hysteresis and inelasticity. The validated model not only reproduces the observed decadal deformation field but also enables a quantitative, scenario-based risk assessment for critical infrastructure, projecting differential displacement under various groundwater management futures. SIGNIFICANCE STATEMENT: This study reveals how policies restricting groundwater extraction in coastal cities can unexpectedly cause ground uplift alongside subsidence, creating new risks for infrastructure like railways and tunnels. By analyzing a decade of data from Tianjin, China, we show that rising groundwater levels lead to uneven ground movement some areas lift while others sink due to differing soil properties. Our predictive model helps cities anticipate these shifts, enabling proactive protection of critical infrastructure. This work is vital for urban planners and policymakers seeking to balance water resource management with public safety, especially as global coastal cities face similar challenges from climate adaptation strategies.
The study focuses on the scale dependence of surface energy fluxes in topographically diverse landscapes, where variations in soil moisture and vegetation types significantly influence evapotranspiration processes. Land-atmosphere interaction plays a major role in atmospheric processes in the Qinghai-Tibet Plateau (QTP) region, and the inability of current land-atmosphere models to capture the landscape-scale heterogeneity in the latent heat flux introduces uncertainties in these models. To address this issue, the remote sensing-based fine-scale energy balance modeling [Mapping Evapotranspiration at High Resolution with Internalized Calibration (METRIC)] was combined here with topographical analysis [2D FFT spectral analysis and Landscape Unit Mapping Program (LUMP) hillslope discretization] to identify a representative elementary area (REA) for latent heat flux. A scale dependence analysis within a 1-10-km range is performed, and two flux aggregation methods are proposed: the mechanistic approach to define REA, which identifies optimal aggregation areas for latent heat through window size variations, and the landscape-explicit approach, which upscales latent heat based on hillslope elements of dominant quasi-periodic topographic features. It was established that the representative elementary area for latent heat at QTP is in the 2-4-km range. Moreover, REA is formed by characteristic topographical patterns that can be defined through regularity and repetition, which can be seen in representative hillslopes. Benchmark simulations conducted with the METRIC model indicate that ignoring topographical influences results in the absence of REA. The landscape-explicit approach may offer greater interpretability and predictive capability for future land-atmosphere model development as it considers topographic effects on lateral water redistribution and surface energy transfer.
