地球科学最新文献

Catastrophic landslides are often preceded by slow, progressive, accelerating deformation that differs from the persistent motion of slow-moving landslides. Here, we investigate the motion of a landslide that damaged 12 homes in Rolling Hills Estates (RHE), Los Angeles, California on 8 July 2023, using satellite-based synthetic aperture radar interferometry (InSAR) and pixel tracking of satellite-based optical images. To better understand the precursory motion of the RHE landslide, we compared its behavior with local precipitation and with several slow-moving landslides nearby. Unlike the slow-moving landslides, we found that RHE was a first-time progressive failure that failed after one of the wettest years on record. We then applied a progressive failure model to interpret the failure mechanisms and further predict the failure time from the pre-failure movement of RHE. Our work highlights the importance of monitoring incipient slow motion of landslides, particularly where no discernible historical displacement has been observed.

Climate contrasts across drainage divides, such as orographic precipitation, are ubiquitous in mountain ranges, and as a result, mountain topography is often asymmetric. During glacial periods, these climate gradients can generate asymmetric glaciation, which may modify topographic asymmetry and drive divide migration during glacial-interglacial cycles. Here we quantify topographic asymmetry caused by asymmetric glaciation and its sensitivity to different climate scenarios. Using an analytical model of a steady-state glacial profile, we find that the degree of topographic asymmetry is primarily controlled by differences in the equilibrium line altitude across the divide. Our results show that glacial erosion can respond to the same climate asymmetry differently than fluvial erosion. When there are precipitation differences across the divide, glacial erosion produces greater topographic asymmetry than fluvial erosion, all else equal. These findings suggest that glaciations may promote drainage reorganization and landscape transience in intermittently glaciated mountain ranges.

Artificial intelligence (AI) and machine learning (ML) pose a challenge for achieving science that is both reproducible and replicable. The challenge is compounded in supervised models that depend on manually labeled training data, as they introduce additional decision-making and processes that require thorough documentation and reporting. We address these limitations by providing an approach to hand labeling training data for supervised ML that integrates quantitative content analysis (QCA)—a method from social science research. The QCA approach provides a rigorous and well-documented hand labeling procedure to improve the replicability and reproducibility of supervised ML applications in Earth systems science (ESS), as well as the ability to evaluate them. Specifically, the approach requires (a) the articulation and documentation of the exact decision-making process used for assigning hand labels in a “codebook” and (b) an empirical evaluation of the reliability” of the hand labelers. In this paper, we outline the contributions of QCA to the field, along with an overview of the general approach. We then provide a case study to further demonstrate how this framework has and can be applied when developing supervised ML models for applications in ESS. With this approach, we provide an actionable path forward for addressing ethical considerations and goals outlined by recent AGU work on ML ethics in ESS.

Jupiter's moon Europa contains a subsurface ocean whose presence is inferred from magnetic field measurements, the interpretation of which depends on knowledge of Europa's local plasma environment. A recent Juno spacecraft flyby returned new observations of plasma electrons with unprecedented resolution. Specifically, powerful magnetic field-aligned electron beams were discovered near Europa. These beams, with energies from ∼30 to ∼300 eV, locally enhance electron-impact-excited emissions and ionization in Europa's atmosphere by more than a factor three over the local space environment, and are associated with large jumps of the magnetic fields. The beams therefore play an essential role in shaping Europa's plasma and magnetic field environment and thus need to be accounted for electromagnetic sounding of Europa's ocean and plume detection by future missions such as JUICE and Europa Clipper.

This study analyzes the molecular composition of dissolved organic matter (DOM) in Prydz Bay by Fourier Transform Ion Cyclotron Resonance mass spectrometry to probe the carbon sequestration capacity in the continental shelf system. Concentrations of particulate organic carbon (POC), particulate nitrogen and dissolved organic carbon (DOC) with water depth show that POC could be mainly decomposed into DOC and/or microbially degraded. Highly labile DOC is further degraded and remineralized by microorganisms within the upper 200 m, as evidenced by a downward enrichment of ¹³C_POC and increases in the average molecular weight, oxygen atom number (O) and double bond equivalents of DOM molecules, indicating that biodegradation is the main driver for particulate organic matter and DOM evolution with water depth. Semi-quantitative calculation demonstrates that ∼83% of POC was transformed to DOC as well as dissolved inorganic carbon (DIC), and ∼30% of DOC further to DIC via microbial degradation within the upper 200 m in summer, resulting in a relatively low total organic carbon content in sediments of Prydz Bay. The newly transformed DIC and residue DOC can be preserved in the deep layer due to the formation of well stratified and stable water body in summer of Prydz Bay, ultimately entering the regional circulation system instead of being released back into the atmosphere. This could be one of the most important processes determining the atmosphere CO₂ uptake in the continental shelf system of Southern Ocean.

Recent studies show that climate change signals in the long-term trend of the tropical ecosystems have emerged earlier than projected by climate models. However, it remains unclear whether tropical ocean surface chlorophyll (SChl) shows a robust trend in the available satellite data era, and what possible physical mechanisms can be responsible for this trend. Here, using combined data from observations, hindcast biogeochemical simulations, and climate model outputs, we document consistently decreasing trends of SChl in the three ocean basins (Indian Ocean, Pacific Ocean, and Atlantic Ocean) with varying magnitude from −1.6% to −10.0% per decade during 1998–2020, with tropical ocean SChl showing a decreasing trend of −7.1% per decade. In the Indo-Pacific Ocean, mechanisms for the two hotspots with significantly decreasing SChl trends are identified. (a) In the northern tropical Pacific, under the anthropogenic forcing, enhanced stratification associated with frequent interannual surface warming overwhelms the Ekman pumping effect due to positive wind stress curl, leading to a decrease in SChl. (b) In the southern tropical Indian Ocean, the downwelling process dominates the decreasing SChl trend due to the Ekman pumping associated with the negative wind stress curl prevailing in the Indian Ocean, while the contribution from the stratification change is negligible. This study identifies two hotspots with consistently decreasing SChl trends in the tropical ocean which are influenced by the complex physical processes under a warmer climate and calls for more comprehensive understanding of the interactions between physical processes and biogeochemical cycles in the tropical ocean ecosystems.

Understanding the impact of climate warming on crop yield and its associated mechanisms is paramount for ensuring food security. Here, we conduct a thorough analysis of the impact of vapor pressure deficit (VPD) on maize yield, leveraging a rich dataset comprising temporal and spatial observations spanning 40 years across 31 maize-growing locations in Northeast and North China. Our investigation extends to the influencing meteorological factors that drive changes in VPD during the maize growing phase. Regression analysis reveals a linear negative relationship between VPD and maize yield, demonstrating diverse spatiotemporal characteristics. Spatially, maize yield exhibits higher sensitivity to VPD in Northeast China (NEC), despite the higher VPD levels in North China Plain (NCP). The opposite patterns reveal that high VPD not invariably lead to detrimental yield impacts. Temporal analysis sheds light on an upward trend in VPD, with values of 0.05 and 0.02 kPa/10yr, accompanied by significant abrupt changes around 1996 in NEC and 2006 in NCP, respectively. These temporal shifts contribute to the heightened sensitivity of maize yield in both regions. Importantly, we emphasize the need to pay closer attention to the substantial the impact of actual vapor pressure on abrupt VPD changes during the maize growing phase, particularly in the context of ongoing climate warming.

A novel sub-sampling method has been used to isolate the dynamic effects of the response of the North Atlantic Oscillation (NAO) and the Siberian High (SH) from the total response to projected Arctic sea-ice loss under 2°C global warming above preindustrial levels in very large initial-condition ensemble climate simulations. Thermodynamic effects of Arctic warming are more prominent in Europe while dynamic effects are more prominent in Asia/East Asia. This explains less-severe cold extremes in Europe but more-severe cold extremes in Asia/East Asia. For Northern Eurasia, dynamic effects overwhelm the effect of increased moisture from a warming Arctic, leading to an overall decrease in precipitation. We show that the response scales linearly with the dynamic response. However, caution is needed when interpreting inter-model differences in the response because of internal variability, which can largely explain the inter-model spread in the NAO and SH response in the Polar Amplification Model Intercomparison Project.

Aerosol increases over the 20th century delayed the rate at which Earth warmed as a result of increases in greenhouse gases (GHGs). Aggressive aerosol mitigation policies arrested aerosol radiative forcing from ∼1980 to ∼2010. Recent evidence supports decreases in forcing magnitude since then. Using the approximate partial radiative perturbation (APRP) method, future shortwave aerosol effective radiative forcing changes are isolated from other shortwave changes in an 18-member ensemble of ScenarioMIP projections from phase 6 of the Coupled Model Intercomparison Project (CMIP6). APRP-derived near-term (2020–2050) aerosol forcing trends are correlated with published model emulation values but are 30%–50% weaker. Differences are likely explained by location shifts of aerosol-impacting emissions and their resultant influences on susceptible clouds. Despite weaker changes, implementation of aggressive aerosol cleanup policies will have a major impact on global warming rates over 2020–2050. APRP-derived aerosol radiative forcings are used together with a forcing and impulse response model to estimate global temperature trends. Strong mitigation of GHGs, as in SSP1-2.6, likely prevents warming exceeding 2C since preindustrial but the strong aerosol cleanup in this scenario increases the probability of exceeding 2C by 2050 from near zero without aerosol changes to 6% with cleanup. When the same aerosol forcing is applied to a more likely GHG forcing scenario (i.e., SSP2-4.5), aggressive aerosol cleanup more than doubles the probability of reaching 2C by 2050 from 30% to 80%. It is thus critical to quantify and simulate the impacts of changes in aerosol radiative forcing over the next few decades.