We have carried out a statistical study of neutral atmospheric parameters in the mesosphere lower thermosphere (MLT) region, by utilizing simultaneous measurements from the EISCAT VHF radar and sodium LIDAR collocated at  Tromsø , Norway. This study focuses on the incoherent scatter (IS) spectral width, which is a function of the ion-neutral collision frequency, ion temperature, (equal to neutral temperatures in the D-region), and ion mass. Using the neutral temperatures obtained from LIDAR, and ion mass estimated using a chemistry model, we have measured the ion-neutral collision frequency in the 80-100 km altitudes by fitting the spectral width. The study shows that the current widely used formulae underestimate the ion-neutral collision frequency on average by 1.53\(\pm\)0.24 in comparison to the measurements. Also, the measured collision frequencies showed large temporal variations due to neutral density fluctuations, indicating the presence of atmospheric waves. The amplitudes of these waves are found to be as large as 50% of the background densities. This suggests that individual spectral width measurements are likely influenced by these random neutral density fluctuations, which can have a significant impact on the IS temperature fits. In addition, for altitudes below 85 km, the ion mass increases drastically indicating the presence of heavy cluster ions. The dominance of heavy ions makes it further challenging to extract the temperature values from the spectral width at these altitudes. In light of these observations, the inherent limitations of inferring temperatures from IS spectral width in the MLT altitudes are studied.

The energy cycle of a convectively-organized system, as realized by a convective-scale idealized simulation, is analyzed in wavelet space. In the equilibrium state, most of the available potential energy that is generated by convective heating is immediately converted into kinetic energy by means of buoyancy forcing, consistent with the free-ride principle. In turn, most of the generated convective kinetic energy is manifest as gravity waves propagating away from convective centers. The kinetic energy of these small-scale gravity waves is transferred upscale by their own advective nonlinearities. Finally, a large-scale circulation generated by this "inverse cascade' drives the formation of an organized structure in the precipitation field.

Mesoscale warm-core rings, known as Loop Current rings (LCRs) reshape the Gulf of Mexico water masses by redistributing large amounts of heat and salt laterally. LCRs also transform water masses via diapycnal mixing, but the mechanisms by which this occurs are poorly measured. Here, we present glider-MicroPod turbulence observations that reveal enhanced mixing below the mixed layer, along the eddy edges, driving the LCR’s heat, salt, and oxygen exchanges. Submesoscale stirring at the LCR’s edge yields interleavings of adjacent water masses, which facilitates double-diffusive mixing that transforms Subtropical Underwater into Gulf Common Water. Our findings highlight the need for ocean models to parameterize double-diffusive mixing processes directly resulting from submesoscale tracer stirring, which may be important at basin scale in the presence of LCRs in the Gulf of Mexico.

Representing glacial-interglacial changes in ocean carbon sequestration remains a major challenge for Earth system models (ESMs). Uncertainties in ocean circulation and biological carbon export are essential causes for model-proxy data mismatch. We quantify the impact of these factors by calibrating the Max Planck Institute-ESM. A shallower and weaker glacial Atlantic meridional overturning circulation (AMOC) than the present day, achieved by decreasing background vertical diffusivity, enables capturing the main features in observed δ13C, 14C and CO32-. Additionally, a new prognostic computation of marine aggregate sinking speeds enhances organic matter export efficiency in high latitudes. Together, the shallower AMOC and a comprehensive sinking scheme substantially improve the model-data comparison and carbon storage in the glacial Atlantic, but not in the Pacific and Indian oceans owing to low organic matter remineralisation. Our results yield that representing the glacial-interglacial ocean carbon storage in ESMs requires both constraining ocean circulation and improved biogeochemical processes.

A document by Jingwei ZHANG. Click on the document to view its contents.

A document by Tyler Waterman. Click on the document to view its contents.

• Recent regulations on the sulphur content of ship emissions has accelerated global warming by approximately 2-3 years. • Reduced ship emissions induce responses in cloud properties, top-of-atmosphere radiation, and surface temperatures. • The regulations contribute to the exceptional warming observed in 2023, yet other factors are needed to fully account for it.

Soil microbial nitrous acid (HONO) production has been identified as a significant emission source to the atmosphere and, thus, considerably affects atmospheric oxidizing capacity and formation of secondary air pollutants. Soil HONO emissions are controlled by soil water content, soil temperature, and nitrogen content, which are affected by climatic conditions and fertilizer application rates. However, long-term global soil HONO emissions driven by climate change and increasing fertilizer use have not yet been quantified, hindering the assessment and prediction of the global impact of soil emissions on air quality and vegetation. Here, we derive the first global soil HONO emissions from natural and fertilized lands over the past four decades and evaluate the variation of their impacts on global ozone (O3) and vegetation exposure. Our results show that climate change and the enhanced fertilizer use have increased global soil HONO emissions from 11.0 Tg N in 1980 to 13.4 Tg N in 2016. The rise in fertilizer consumption has substantially intensified soil emissions in the three major grain-producing regions, India, China, and North America with growth rates of 14.9, 9.5, and 0.9 kt N yr-1 , respectively; climate change has predominantly increased soil emissions in Africa and South America with growth rates of 22.3 and 10.9 kt N yr-1 , respectively. Incorporating soil HONO emissions in a global chemistry-climate model improves the model performance in simulating global Page 2 of 22 atmospheric HONO. Simulations with the updated model showed that soil HONO emissions increased global surface O3 concentrations by 2.9% (up to 29%) and the subsequent risk of vegetation exposure to O3, especially in crop-production regions. The enhancement effect of soil HONO emissions on O3 is increased from 1980s to 2016 in regions with low anthropogenic emissions. Therefore, we speculate that with future decreases in anthropogenic emissions, the relative impact of soil HONO emissions on air quality and vegetation is expected to increase. Thus, we recommend the consideration of soil HONO emissions in strategies for mitigating global air pollution.

The scientific publishing landscape is evolving rapidly. This evolution is driven by a confluence of internal and external forces, including the growth of metrics-based evaluation of scientists; an increasing volume of manuscripts combined with expectations for rapid review and publication; an increasing number of journals, including for-profit Open Access publications; and the adoption of preprint servers across a growing range of disciplines. Many of these forces are contributing to personal anxiety and fatigue for authors, reviewers, and editors. Collectively, they are placing substantial stress on scientific publishing, which is a foundational pillar of the scientific enterprise. As editors of American Geophysical Union journals and books, we remain confident in the fundamental foundations of scientific publishing, but we are concerned about the impact of these increasing stressors. By affirming and investing in editorial values, respecting scientific integrity and credibility, and committing to accessibility, transparency, and accountability, we can fortify the foundations of the scientific enterprise during a time of rapid change.

Climate models struggle to produce sea surface temperature (SST) gradient trends in the tropical Pacific comparable to those seen recently in nature. Here, we investigate whether models systematically underestimate internally-generated SST trends by underestimating cloud feedbacks on SST gradients. A heat-budget analysis reveals coupling between cloud-radiative effects, circulation, and SST gradients in driving multi-decadal variability in the Eastern Pacific and suggests that biases in cloud feedbacks may be causing models to underestimate internal SST variability. We find that the magnitude of the cloud-SST feedback in the subtropical Southeast Pacific is correlated across models with the magnitude of Eastern Pacific multi-decadal SST variability. Using this relationship and observed feedback estimates, we estimate that internal Eastern Pacific SST variability is under-predicted in most models. Adjusting for model bias increases the likelihood of generating a cooling trend at least as large as observations in preindustrial control simulations by between ~10% and ~58%.

We estimate depth-dependent azimuthal anisotropy and shear wave velocity structure beneath the Alaska subduction zone by the inversion of a new Rayleigh wave dispersion dataset from 8-85 s period. We present a layered azimuthal anisotropy model from the forearc region offshore to the subduction zone onshore. In the forearc crust, we find a trench-parallel pattern in the Semidi and Kodiak segments, while a trench-oblique pattern is observed in the Shumagin segment. These fast directions agree well with the orientations of local faults. Within the subducted slab, a dichotomous pattern of anisotropy fast axes is observed along the trench, which is consistent with the orientation of fossil anisotropy generated at the mid-ocean ridges of the Pacific-Vancouver and Kula-Pacific plates that is preserved during subduction. Beneath the subducted slab, a trench-parallel pattern is observed near the trench, which may indicate the direction of mantle flow.

AbstractAmong the photosynthetic powerhouses of aquatic ecosystems, microalgae are now the most promising source of sustainable and bioactive compounds with massive potential in the functional food category. Unicellular cell plants differing the synthesis of various substances, including proteins, lipids, carbohydrates and pigmented substances, which are important to their living and contribute to the workout of human health. Carotenoids and polyunsaturated fatty acids (PUFAs) present in a wealth of compounds have been the most attractive compounds due to their antioxidative and anti-inflammatory properties, which may be beneficial in alleviating oxidative stress and chronic inflammation. Spirulina and chlorella are two of the most consumable microalgae. They have been developed commercially as nutraceuticals because they offer a useful nutrient profile that includes essential amino acids, vitamins, and minerals needed to maintain human health. Because of its diverse bioactivity, microalgae can be used to create functional foods that target particular health issues like metabolic disorders and cardiovascular diseases. Because microalgae can be grown on non-arable land with little freshwater requirements, they do not compete with traditional agriculture, which further justifies their integration into the food industry. Furthermore, the heterotrophic cultivation of microalgae techniques that depend on sources of organic carbon for growth offers a chance to raise the yield of bioactive compounds and possibly lower production costs. This strategy aligns with the biorefinery concept, which maximizes resource utilization and economic viability by using microalgae as a biotechnological platform to produce high-value nutraceuticals and biofuels simultaneously. Only a few microalgal compounds have been successfully commercialized, and most studies on them are still preclinical. However, continued research and technological developments in the processing and cultivation of microalgae are opening the door to a broader range of uses in functional foods.

A document by Meiyun Lin. Click on the document to view its contents.

High-relief glacial valleys shape the modern topography of the Southern Patagonian Andes, but their formation remains poorly understood. Two Miocene plutonic complexes in the Andean retroarc, the Fitz Roy (49°S) and Torres del Paine (51°S) massifs, were emplaced between 16.9–16.4 Ma and 12.6–12.4 Ma, respectively. Subduction of oceanic ridge segments initiated ca. 16 Ma at 54°S, leading to northward opening of a slab window with associated mantle upwelling. The onset of major glaciations caused drastic topographic changes since ca. 7 Ma. To constrain the respective contributions of tectonic-mantle dynamics and fluvio-glacial erosion to rock exhumation and landscape evolution, we perform inverse thermal modeling of a new dataset of zircon and apatite (U-Th)/He from the two massifs, complemented by apatite 4He/3He data for Torres del Paine. Our results show rapid rock exhumation recorded only in the Fitz Roy massif between 10 and 8 Ma, which we ascribe to local mantle upwelling forcing surface uplift and intensified erosion around 49°S. Both massifs record a pulse of rock exhumation between 7 and 4 Ma, which we interpret as enhanced erosion during the beginning of Patagonian glaciations. After a period of erosional and tectonic quiescence in the Pliocene, increased rock exhumation since 3-2 Ma is interpreted as the result of alpine glacial valley carving promoted by reinforced glacial-interglacial cycles. This study highlights that glacial erosion was the main driver to rock exhumation in the Patagonian retroarc since 7 Ma, but that mantle upwelling might be a driving force to rock exhumation as well.

Pillar et al.

This study tackles the limitations of traditional distance metrics in machine learning, particularly their inadequacy in managing missing data and varying feature importance. We introduce a novel custom distance metric that offers a more nuanced and robust measure of similarity, addressing the complexities and imperfections of real-world data. Our extensive evaluation of the CustomKNN algorithm, leveraging this custom distance metric, reveals exceptional performance and robustness across diverse datasets, consistently outperforming traditional metrics in various classification tasks. The custom distance metric shows superior robustness to missing data and scalability, despite its higher computational complexity and memory requirements. Our findings highlight the versatility and effectiveness of the CustomKNN algorithm, establishing it as a formidable option for classification tasks. This research advances the development of more adaptable and context-aware distance metrics, significantly enhancing the accuracy and reliability of machine learning models in practical applications.

The last glacial cycle provides the opportunity to investigate large changes in the Atlantic Meridional Overturning Circulation (AMOC) beyond the small fluctuations evidenced from modern measurements. Paleotemperature records from Greenland and the North Atlantic show an abrupt variability, called Dansgaard–Oeschger (DO) events, which is associated with abrupt changes of the AMOC. These DO events also have Southern Hemisphere counterparts via the thermal bipolar seesaw, a concept describing the meridional heat transport leading to asynchronous temperature changes between both hemispheres. However, temperature records from the North Atlantic show more pronounced DO cooling events during massive releases of icebergs known as Heinrich (H) events, contrary to ice-core–based temperature records from Greenland. Here, we present two high-resolution temperature records from the southern Iberian Margin, which are derived from two independent paleotemperature proxies (RI-OH′ and UK′37). Both temperature records from the southern Iberian Margin faithfully reflect the contrasting DO cooling amplitudes with and without H events. We show that temperature records from the southern Iberian Margin better support the classical thermal bipolar seesaw model than do ice-core–based temperature records from Greenland. We also introduce an extended thermal bipolar seesaw model that considers the contrasting DO cooling amplitudes with and without H events in the southern Iberian Margin, and a Bipolar Seesaw Index to discriminate DO cooling events with and without H events. Our data-model comparison emphasizes the role of the thermal bipolar seesaw in the abrupt temperature variability of both hemispheres with a clear enhancement during DO cooling events with H events, implying a relationship that is more complex than a simple flip-flop between two climate states linked to a tipping point threshold.

A document by John Robert Potter. Click on the document to view its contents.