Geophysical Research Letters最新文献

Fracture connectivity is a key parameter controlling fluid flow throughout the Earth's crust. While some theoretical and numerical studies suggest that seismic waves are sensitive to fracture connectivity, an experimental validation of this critically important phenomenon was so far unavailable. In this study, we present a novel methodology for fabricating synthetic analogs of rock samples containing connected and unconnected fluid-saturated fractures with well-constrained geometric characteristics. Using a low-frequency forced-oscillation apparatus, we show that the P-wave velocities are higher in samples with unconnected fractures than in those with connected ones. Complementary numerical simulations corroborate these findings and indicate that the dominant mechanism behind the observed differences is wave-induced fluid pressure diffusion within connected fractures. Our results provide direct experimental evidence that, for otherwise identical fracture networks, the presence of interconnectivity produces a measurable reduction in P-wave velocity at seismic frequencies, which is consistent with that previously predicted by corresponding numerical models. This, in turn, opens new and important perspectives for the seismo-hydraulic characterization of fractured rocks.

Rivers self-organize to convey water and sediment, giving rise to robust downstream scaling between channel geometry and drainage area, underpinning landscape evolution models. However, these relations rely on limited observations per watershed. We quantify downstream changes in channel slope and bankfull width for six gravel rivers. We develop a novel method to automatically extract bankfull width and determine high-resolution (10-m), catchment-specific width-area scaling, revealing new insights on the covariation between slope and width hidden in large data compilations. We identify a threshold slope, below which average width is slope-independent. Notably, slope and width deviations display contrasting patterns depending on the channel's elevation profile. Deviations are anticorrelated when knickpoints are present and correlated when they are absent. High-resolution, catchment-specific scaling laws capture systematic, interpretable deviations reflecting underlying controls on channel adjustment and fluvial erosive power. With growing availability of high-resolution topography, our approach provides new insights into river process and form.

Extreme open-ocean phytoplankton events can influence marine ecosystems, yet their global occurrence, drivers, and consequences remain poorly understood. Most large-scale studies rely on satellite chlorophyll, which provides only a surface view, is affected by physiological variability, and is often missing due to clouds and low sunlight. Here, we use an Earth system model with a satellite chlorophyll simulator to test when and where vertically integrated phytoplankton biomass extremes align with satellite-detected chlorophyll extremes. Globally, about 10% of low and 19% of high phytoplankton biomass extremes are detected. The detection rate is the result of the combined impacts of missing data and extreme misalignment: only 34% of low and 56% of high detected chlorophyll extremes correspond with true biomass extremes, with the largest discrepancies occurring in the subtropical gyres. These findings highlight the need for caution when interpreting satellite chlorophyll as a proxy for phytoplankton biomass extremes.

The probability density function of drops is difficult to model. Current approaches make assumptions that are often problematic, as they allow negative values for the mean of the distribution. While the statistical goodness of fit of those models might be reasonable for precipitation radar estimation, the situation is unsatisfactory if a fully consistent physical modeling of precipitation across scales is desired. This is the case of weather and climate models. This paper discusses a model that satisfies mathematical and physical consistency. The model can be seamlessly integrated into the parameterizations of the microphysics of precipitation and is tested on an extensive disdrometer data set. Comparison with existing models shows that the new method has substantial practical and theoretical advantages. The research has implications in elucidating the role of clouds in the climate sensitivity of climate models.

The response of marine low-cloud mesoscale morphologies to climate change and emission reductions remains poorly understood. Here, we link long-term trends in six cloud morphologies to variations in large-scale meteorology and aerosols. The trends show strong spatial heterogeneity, with closed and disorganized mesoscale cellular convection decreasing in the Northeast Pacific and Southeast Atlantic. We develop a deep learning model (UMorNet) to predict instantaneous cloud morphologies from meteorology and cloud droplet number concentration (N_d), a proxy for aerosols. UMorNet achieves an average test accuracy of 0.55 and captures spatial patterns of climatology and long-term trends. Out-of-sample test with a marine heatwave event further demonstrates the model's performance. Sensitivity experiments identify N_d, marine cold-air outbreak index, sea surface temperature, and inversion strength as key drivers. Different responses of clustered Cu and suppressed Cu to N_d was identified. These findings highlight the potential role of aerosols in shaping cloud morphological changes.

Oxygen in the global oceans has declined since the 1960s, including in the Eastern Equatorial Pacific (EEP). Reconstructions of EEP glacial oxygenation help advance understanding of current and projected ocean deoxygenation. Previous estimates of the glacial oxygen deficient zones (ODZs) in the upper EEP are poorly constrained. Here we include sediment cores that extend shallower into the ODZ and quantitatively reconstruct the glacial oxygen depth profile. We find glacial oxygen levels were similar or slightly lower than modern in the upper-intermediate ocean and much lower in the deep EEP. We estimate ∼95% of the lower glacial oxygen occurred in the deep EEP. This contrasts with modern, where only 67% of oxygen loss is in the deep ocean, and could be due to a smaller role of temperature-dependent oxygen solubility in modulating oxygen on longer timescales and/or a longer ocean response time to record oxygen changes at depths during glacial times.

Northwest China is facing socio-environmental challenges linked to ongoing climatic warming. However, a scarcity of regional paleorecord syntheses limits our understanding of natural long-term climate variability in the region and hinders the contextualization of contemporary warming. Here, we present paleorecord syntheses for both summer and annual temperatures during the Holocene based on a range of lacustrine sediment records from northwest China, with consideration of chronological uncertainties within records. The syntheses show similar summer and annual temperature variations, including peak warmth at ∼9000 years BP, followed by a 2000-year cooling trend, and stable temperatures thereafter. These variations may reflect inter-seasonal impact of summer insolation forcing through climate feedbacks (e.g., Arctic sea-ice cover) that are still not well represented in climate models. The early-Holocene peak warmth was >1.0°C warmer than the 20th century mean warmth, but is expected to be exceeded during the 21st century even under a low emission scenario.

The downward influence of extreme stratospheric events is typically described by the evolution of the Northern Annular Mode (NAM) across atmospheric levels. However, the dynamics and uncertainty in vertical coupling are not fully resolved. By applying the linear inverse model (LIM) to daily, multi-level NAM indices from reanalysis and CMIP6 models, we show that the leading eigenmode of NAM displays a deep structure extending from the stratosphere to the surface, with an e-folding timescale of about 30 days in reanalysis data. This stratospheric mode captures the downward propagation of NAM anomalies during weak polar vortex events, further supported by the LIM simulations forced by white noise. Analysis of inter-model spread suggests that the LIM-based estimates can reduce the uncertainty in the surface response to stratospheric extreme events by more than 50%. These findings provide dynamic insights into stratosphere-troposphere coupling of NAM and its representations in climate models.

Increasing basal meltwater from Antarctic ice shelves may impact the Southern Ocean properties that feed back on the rate of melting. We investigate this feedback in a high-emissions scenario using an Earth-system model with interactive ice-shelf basal melting, an improvement on previous studies that did not have the capability to evolve melt rates and the ocean state self-consistently. We find that when interactive melt increases, it primarily accelerates the evolution of a spatial pattern of continental shelf warming and cooling that is initiated by freshening and sea-ice formation decline due to projected atmospheric warming. The competition between enhanced warming at depth from reduced ventilation and enhanced continental shelf cooling from reduced dense water export leads to net $��\sim �$35% reduction in ice-shelf meltwater input into the Southern Ocean over the 21st century. Omitting this feedback introduces a bias in the timing of projected ocean-melt-driven ice loss from Antarctica.