Transoral robotic surgery (TORS) has evolved into a common surgical modality used to treat primarily oropharyngeal malignant and benign pathologies. The single port Intuitive Surgical da Vinci surgical robotics system facilitates access to the hypopharynx and cervical esophagus. We aim to describe our approach and advantages of the technique.

In this letter, an ultra-low-power power-on-reset circuit with reconfigurable trip-voltages is proposed. In order to reduce area and power consumption overhead, an all-MOS sub-threshold architecture based on threshold difference voltage references and current comparator is designed. By configuring the reference current and the different threshold transistors, the different trig voltages are generated to detect multi-supply voltages. Simulation results based on 55 nm CMOS process show that the proposed power-on-reset circuit generates trip voltages of 385.5 mV and 775.4 mV, consuming only 8.5 nA and 92.6 nA at the supply voltage of 0.5 V and 1 V, respectively. And the area of the proposed power-on-reset circuit is as low as 240 μm2.

AbstractThis paper analytically analyzes the use and limitations of ranking systems for highly cited researchers compiled by Stanford University’s ranking of the world’s top 2% most influential scientists. This list is commonly used to identify influential and respected members of a particular field. However, it is important to critically evaluate the list and its methodology and  no such analysis to this date. From a critical analysis of the September 2022 version of this world’s top 2% of scientists list, this research finds that the database of the list is flawed, including inaccurately listing researchers as first publishing in the 19th century and continuing to publish until 2022, listing authors with low publication numbers and career lengths, mixing news articles and editorials with research papers, listing institutes as authors rather than individuals, and listing authors with a high percentage of self-citations. The study suggests that the promotion and use of such “standardized” citation rankings should be discouraged.

Seismic stratigraphic and structural interpretation is often hampered by seismic resolution and, sometimes, human's inability to identify a subtle feature on the seismic. These factors have frequently led to the poor seismic interpretation of geologic features. Thus, an integral approach to studying the structural patterns and hydrocarbon bearing zones using seismic attributes were carried out on the Tomboy field using 3D seismic data covering approximately 56 km 2 of the western belt of the Niger Delta. The seismic volume underwent post-stack processing, which enhanced seismic discontinuities. A deep steering volume was first created, and several dip filters were applied to enhance faults in the study area. After that, curvature and similarity attributes were calculated on the dip-steered and fault-enhanced volume. These calculations show detailed geometry of the faults and zones of subtle lineaments. Six faults (F1, F2, F3, F4, F5, and F6) were identified and mapped. These faults range from antithetic to crestal growth faults. Two major growth faults (F5 and F6) were revealed to dip in the NE-SW directions. A near-extensive crestal fault (F4) appeared beneath the major faults. Although several minor fractures were displayed in the southern and central portion of the seismic data, the SW dipping crestal fault (F4) and growth fault F6 are responsible for holding the hydrocarbon found within the identified closures. Using attributes on the seismic data increased confidence in the mapping and interpreting structural features. Furthermore, Energy attributes were used as Direct Hydrocarbon Indicator (DHI) to visualize viable areas within the study and permits a more robust interpretation. Time slices were taken at regions of flat and bright spots. Spectral decomposition attribute was run on these slices to display areas of high amplitude reflection typical of hydrocarbon-bearing regions, which are trapped mainly by regional to sub-regional growth faults. The surface attribute calculated on the generated surface shows that the field is dominantly controlled by faults serving as traps for hydrocarbon.

Viral vectors for gene therapy, such as recombinant Adeno-Associated Viruses (rAAV), are produced in Human Embryonic Kidney (HEK) 293 cells. However, the presence of the SV40 T-antigen-encoding CDS SV40GP6 and SV40GP7 in the HEK293T genome raises safety issues when these cells are used in manufacturing for clinical purposes. We developed a new T-antigen-negative HEK cell line from ExcellGene’s proprietary HEKExpress®, using the CRISPR-Cas9 strategy. We obtained a high number of clonally-derived cell populations and all of them were demonstrated T-antigen negative. Stability study and AAV production evaluation showed that the deletion of the T-antigen-encoding locus did not impact neither cell growth nor viability nor productivity. The resulting CMC-compliant cell line, named HEKzeroT®, is able to produce high AAV titers, from small to large scale.

The ocean has absorbed about 25% of the carbon emitted by humans to date. To better predict how much climate will change, it is critical to understand how this ocean carbon sink will respond to future emissions. Here, we examine the ocean carbon sink response to low emission (SSP1-1.9, SSP1-2.6), intermediate emission (SSP2-4.5, SSP5-3.4-OS), and high emission (SSP5-8.5) scenarios in CMIP6 Earth System Models and in MAGICC7, a reduced-complexity climate carbon system model. From 2020-2100, the trajectory of the global-mean sink approximately parallels the trajectory of anthropogenic emissions. Until emission growth becomes negative, the cumulative ocean carbon sink absorbs 20-30% of cumulative emissions since 2015. In scenarios where emissions decline and become negative, the ocean remains a sink and absorbs more carbon than emitted (up to 120% of cumulative emissions since 2015). Despite similar responses in all models, there remains substantial quantitative spread in estimates of the cumulative sink through 2100 within each scenario, up to 50 PgC in CMIP6 and 120 PgC in the MAGICC7 ensemble. We demonstrate that for all but SSP1-2.6, approximately half of this future spread can be eliminated if models are brought into agreement with modern best-estimates. Considering the spatial distribution of air-sea CO 2 fluxes in CMIP6, we find significant zonal-mean divergence from newly-available observation-based constraints. We conclude that a significant portion of future ocean carbon sink uncertainty is attributable to modern-day errors in the mean state of air-sea CO 2 fluxes, which in turn are associated with model representations of ocean physics and biogeochemistry. Bringing models into agreement with modern observation-based estimates at regional to global scales can substantially reduce uncertainty in future role of the ocean in absorbing anthropogenic CO 2 from the atmosphere and mitigating climate change.

Objective: To identify postoperative vaginal morphology and position factors associated with prolapse recurrence following vaginal surgery. Design: Secondary analysis of MRIs of the Defining Mechanisms of Anterior Vaginal Wall Descent cross-sectional study. Setting: Eight clinical sites in the US Pelvic Floor Disorders Network. Population: Women who underwent vaginal mesh hysteropexy (hysteropexy) with sacrospinous fixation or vaginal hysterectomy with uterosacral ligament suspension (hysterectomy) for symptomatic uterovaginal prolapse between April 2013 and February 2015. Methods: MRIs (rest, strain) obtained 30-42 months after surgery, or earlier for participants with recurrence who desired reoperation prior to 30 months, were analyzed. Prolapse recurrence was defined as prolapse beyond the hymen at strain on MRI. Vaginal segmentations (at rest) were used to create 3D models placed in a morphometry algorithm to quantify and compare vaginal morphology (angulation, dimensions) and position between groups. Main Outcome Measures: Vaginal angulation (upper, lower, and upper-lower vaginal angles in the sagittal and coronal plane), dimensions (length, maximum transverse width, surface area, volume), and position (apex, mid-vagina) at rest. Results: Of the 82 women analyzed, 12/41 (29%) in the hysteropexy group and 22/41 (54%) in the hysterectomy group had prolapse recurrence. After hysteropexy, recurrences had a more laterally deviated upper vagina (p=0.02) at rest than successes. After hysterectomy, recurrences had a more inferiorly (lower) positioned vaginal apex (p=0.01) and mid-vagina (p=0.01) at rest than successes. Conclusions: Vaginal angulation and position were associated with prolapse recurrence and indicative of vaginal support mechanisms related to surgical technique and unaddressed anatomical defects. Future prospective studies in women before and after prolapse surgery may distinguish these two factors. Funding: Eunice Kennedy Shriver National Institute of Child Health and Human Development-sponsored Pelvic Floor Disorders Network (Grant/Award Number: U10 HD054214, U10 HD041267, U10 HD041261, U10 HD069013, U10 HD069025, U10 HD069010, U10 HD069006, U10 HD054215, U01 HD069031); National Institutes of Health Office of Research on Women’s Health; Boston Scientific Corporation; National Academies of Sciences, Engineering, and Medicine’s Ford Foundation Predoctoral Fellowship Program

Aims: The present study examined whether people higher in psychopathy experienced less self-reported and psychophysiological pain than people lower in psychopathy. We also examined via self-reports and psychophysiological measures whether psychopathy affects empathy for others’ pain. Method: Three hundred and sixty-nine students (18-78 years; M = 26, SD = 9.34) were screened for psychopathic traits, and stratified sampling was used to recruit 49 adults residing in the highest (n = 23) and lowest (n = 26) 20% of the psychopathy spectrum. Using skin conductance response (SCR) and self-report measures, participants responded to directly experienced pressure pain and observing others’ pain images. Results: People higher in psychopathy self-reported feeling less physical pain compared to people lower in psychopathy, however, we did not find any differences in SCR to physical pain. High psychopathy group displayed lower SCR to viewing other people’s pain compared to low psychopathy. Additionally, high psychopathy group self-reported less empathy to other people’s pain compared to low psychopathy group. Discussion: Our results suggest that psychopathic traits relate to problems with empathising with others’ pain as well as rating pain as feeling less intense. Additionally, a lack of awareness to ones’ body sensations may underlie emotional impairments in psychopathy. We suggest psychopathy interventions for empathy should focus on recognising and empathising with pain.

Binary Solvent Extraction of Microplastics from a Complex Environmental Matrix.Oluniyi O. Fadare1, Leisha Martin2, Nigel Lascelles1, Jessica T. Myers1, Karl Kaiser3, Wei Xu2, and Jeremy L. Conkle11Department of Physical & Environmental Sciences, Texas A&M University-Corpus Christi, 6300 Ocean Drive, Unit 5892, Corpus Christi, Texas 78412, United States.2Department of Life Sciences, Texas A&M University-Corpus Christi, 6300 Ocean Drive, Unit 5892, Corpus Christi, Texas 78412, United States3Department of Marine and Coastal Environmental Science, Texas A&M University at Galveston, Galveston, TX 77553, United StatesAddress correspondence to Jeremy L. Conkle - Department of Physical and Environmental Sciences, Texas A&M University, Corpus Christi, 6300 Ocean Drive, 78412, Texas, United States. Tel: +1 361.825.2862; Email: jeremy.conkle@tamucc.edu

Background and Purpose: Information on tigecycline-induced pancreatitis (TIP) is lacking in real-world settings. We aim to analyze the clinical characteristics and risk factors for TIP and evaluate the safety and efficiency of tigecycline use in non-TIP. Experimental Approach: A retrospective case-control study was conducted on adult and juvenile patients administered tigecycline for >3 days. Adults were classified as TIP, non-TIP (pancreatitis with other causes), and non-pancreatitis. Univariate analyses were performed to compare TIP and non-pancreatitis, multivariate analysis was used to identify risk factors for TIP. The clinical characteristics of TIP and the safety and efficiency of tigecycline use in non-TIP were evaluated. Key results: A total of 3910 patients (3823 adults and 87 juveniles) were enrolled. The adults comprised 21 TIP, 82 non-TIP, and 3720 non-pancreatitis. TIP prevalences were 0.56% in adults and 1.15% in juveniles. The mean time from tigecycline use to symptom onset was 7.2 days (were mild pancreatitis). The mean time from tigecycline withdrawal to symptom relief was 3.6 days. Comorbid renal insufficiency was an independent risk factor for TIP (OR = 3.032). Among the 82 non-TIP patients, 81.7% had severe pancreatitis and 47.6% had necrotizing pancreatitis. The modified computed tomography severity score after tigecycline use was similar to that before use, but the pancreatic enzymes and infection indices were significantly decreased. Conclusions and Implications: The prevalence of TIP was low. Comorbid renal insufficiency was as an independent risk factor for TIP. Tigecycline is safe and efficient for treatment of pancreatitis, especially necrotizing pancreatitis, with intra-abdominal infection.

Einstein-Poincare synchronization and deformation of space-time by gravity are sufficient for obtaining Lorentz transformation starting from Galileo transformation.

Meandering channels display complex planform configurations with upstream- and downstream- skewed bends. Bend orientation is linked to near-field hydrodynamics, bed morphodynamic regime, bank characteristics, riparian vegetation, and geological environment, which are the modulating factors that act specially in high-amplitude and high-sinuosity conditions. Based on the interaction between hydrodynamics and morphodynamics, previous studies have suggested that sub- (β < βR) and super-resonant (β > βR) morphodynamic regimes (where β is the half width-to-depth ratio of the channel, and βR is the resonance condition) may trigger a particular bend orientation (upstream- and downstream-skewed, respectively). However, natural rivers exhibit both US-skewed and DS-skewed bend patterns along the same reach, independently of the morphodynamic regime. Little is known about the hydrogeomorphology (forced and free morphodynamic patterns) under these bend orientations. Herein, using the asymmetric Kinoshita laboratory channel, experiments under sub- and super-resonant conditions (with presence or absence of free bars) for upstream-and downstream-skewed conditions are performed. Additional, detailed field measurements at US-skewed and DS-skewed bends of different skewness along the Tigre River in Peru are presented. Conditions at field scale at high-sinuosity and high-amplitude bends filter out the influence of the morphodynamic regime, where nonlinear processes (e.g. width variation) directly the development of the three-dimensional flow structure, then to the erosional and depositional patterns, and then to the lateral migration patterns.

The urban morphology determined by urban canopy parameters (UCPs) plays an important role in simulating the interaction of urban land surface and atmosphere. The impact of urbanization on a typical summer rainfall event in Hangzhou, China, is investigated using the integrated WRF/urban modelling system. Three groups of numerical experiments are designed to assess the uncertainty in parameterization schemes, the sensitivity of urban canopy parameters (UCPs), and the individual and combined impacts of thermal and dynamical effects of urbanization, respectively. The results suggest that the microphysics scheme has the highest level of uncertainty in simulating precipitation, followed by the planetary boundary layer scheme, whereas the land surface and urban physics schemes have minimal impacts. The choices of the physical parameterization schemes for simulating precipitation are much more sensitive than those for simulating temperature, mixing ratio, and wind speed. Of the eight selected UCPs, changes in heat capacity, thermal conductivity, surface albedo, and roughness length have a greater impact on temperature, mixing ratio, and precipitation, while changes in building height, roof width, and road width affect the wind speed more. The total urban impact could lead to higher temperature, less mixing ratio, lower wind speed, and more precipitation in and around the urban area. Comparing the thermal and dynamical effects of urbanization separately, both of them contribute to an increase in temperature and precipitation and the thermal effect plays a major role. However, their impacts are opposite in changes of mixing ratio and wind speed, and each play a major role respectively.

The El Niño-Southern Oscillation (ENSO) influences climate variability across the globe. ENSO is highly predictable on seasonal timescales and therefore its teleconnections are a source of extratropical forecast skill. To fully harness this predictability, teleconnections must be represented accurately in seasonal forecasts. We find that a multimodel ensemble from five seasonal forecast systems can successfully capture the spatial structure of the late winter (JFM) El Niño teleconnection to the North Atlantic via North America, but the simulated amplitude is half of that observed. We find that weak amplitude teleconnections exist in all five models and throughout the troposphere, and that the La Niña teleconnection is also weak. We find evidence that the tropical forcing of the teleconnection is not underestimated and instead, deficiencies are likely to emerge in the extratropics. We investigate the impact of underestimated teleconnection strength on North Atlantic winter predictability, including its relevance to the signal-to-noise paradox.

\justifying The atmospheric radiative transfer calculations are among the most time-consuming components of the numerical weather prediction (NWP) models. Deep learning (DL) models have recently been increasingly applied to accelerate radiative transfer modeling. Besides, a physical relationship exists between the output variables, including fluxes and heating rate profiles. Integration of such physical laws in DL models is crucial for the consistency and credibility of the DL-based parameterizations. Therefore, we propose a physics-incorporated framework for the radiative transfer DL model, in which the physical relationship between fluxes and heating rates is encoded as a layer of the network so that the energy conservation can be satisfied. It is also found that the prediction accuracy was improved with the physic-incorporated layer. In addition, we trained and compared various types of deep learning model architectures, including fully connected (FC) neural networks (NNs), convolutional-based NNs (CNNs), bidirectional recurrent-based NNs (RNNs), transformer-based NNs, and neural operator networks, respectively. The offline evaluation demonstrates that bidirectional RNNs, transformer-based NNs, and neural operator networks significantly outperform the FC NNs and CNNs due to their capability of global perception. A global perspective of an entire atmospheric column is essential and suitable for radiative transfer modeling as the changes in atmospheric components of one layer/level have both local and global impacts on radiation along the entire vertical column. Furthermore, the bidirectional RNNs achieve the best performance as they can extract information from both upward and downward directions, similar to the radiative transfer processes in the atmosphere.

Anthropogenic litter is omnipresent in terrestrial and freshwater systems, and can have major economic and ecological impacts. Monitoring and modelling of anthropogenic litter comes with large uncertainties due to the wide variety of litter characteristics, including size, mass, and item type. It is unclear as to what the effect of sample set size is on the reliability and representativeness of litter item statistics. Reliable item statistics are needed to (1) improve monitoring strategies, (2) parameterize litter in transport models, and (3) convert litter counts to mass for stock and flux calculations. In this paper we quantify sample set size requirement for riverbank litter characterization, using a database of more than 14,000 macrolitter items (>0.5 cm), sampled for one year at eight riverbank locations along the Dutch Rhine, IJssel and Meuse rivers. We use this database to perform a Monte Carlo based bootstrap analysis on the item statistics, to determine the relation between sample size and variability in the mean and median values. Based on this, we present sample set size requirements, corresponding to selected uncertainty and confidence levels. Optima between sampling effort and information gain is suggested (depending on the acceptable uncertainty level), which is a function of litter type heterogeneity. We found that the heterogeneity of the characteristics of litter items varies between different litter categories, and demonstrate that the minimum required sample set size depends on the heterogeneity of the litter category. More items of heterogeneous litter categories need to be sampled than of heterogeneous item categories to reach the same uncertainty level in item statistics. For example, to describe the mean mass the heterogeneous category soft fragments (>2.5cm) with 90% confidence, 990 items were needed, while only 39 items were needed for the uniform category metal bottle caps. Finally, we use the heterogeneity within litter categories to assess the sample size requirements for each river system. All data collected for this study are freely available, and may form the basis of an open access global database which can be used by scientists, practitioners, and policymakers to improve future monitoring strategies and modelling efforts.

A weather station in Nukuʻalofa (NUKU), Tonga, ~68km away from the epicenter of the 2022 Tonga eruption, recorded exceptional pressure, temperature, and wind data representative of the eruption source hydrodynamics. These high-quality data are available for further source and propagation studies. In contrast to other barometers and infrasound sensors at greater ranges, the NUKU barometer recorded a decrease in pressure during the climactic stage of the eruption. A simple fluid dynamic explanation of the depressurization is provided, with a commentary on near- vs far-field pressure observations of very large eruptions.

The direct acquisition of the permeability of porous media by digital images helps to enhance our understanding of and facilitate research into the problem of subsurface flow. A complex pore space makes the numerical simulation methods used to calculate the permeability quite time-consuming. Deep learning models represented by three-dimensional convolutional neural networks (3D CNNs), as a promising approach to improving efficiency, have made significant advances concerning predicting the permeability of porous media. However, 3D CNNs only have the ability to represent the local information of 3D images, and they cannot consider the spatial correlation between 2D slices, a significant factor in the reconstruction of porous media. This study combines a 2D CNN and a self-attention mechanism to propose a novel CNN-Transformer hybrid neural network that can make full use of the 2D slice sequences of porous media to accurately predict their permeability. In addition, we added physical information to the slice sequences and built a PhyCNN-Transformer model to reflect the impact of physical properties on permeability prediction. In terms of dataset preparation, we used the publicly available DeePore porous media dataset with the labeled permeability calculated by pore network modelling (PNM). We compared the two transformer-based models with a 3D CNN in terms of parameter number, training efficiency, prediction performance, and generalization, and the results showed significant improvement. Combined with the transfer learning method, we demonstrate the superior generalization ability of the transformer-based models to unfamiliar samples with small sample sizes.

Many regions across the globe broke their surface temperature records in recent years, further sparking concerns about the impending arrival of “tipping points” later in the 21st century. This study analyzes observed global surface temperature trends in three target latitudinal regions: the Arctic Circle, the Tropics, and the Antarctic Circle. We show that global warming is accelerating unevenly across the planet, with the Arctic warming at approximately three times the average rate of our world. We further analyzed the reliability of latitude-dependent surface temperature simulations from a suite of Coupled Model Intercomparison Project Phase 6 models and their multi-model mean. We found that GISS-E2-1-G and FGOALS-g3 were the best-performing models based on their statistical abilities to reproduce observational, latitude-dependent data. Surface temperatures were projected from ensemble simulations of the Shared Socioeconomic Pathway 2-4.5 (SSP2-4.5). We estimate when the climate will warm by 1.5, 2.0, and 2.5 ℃ relative to the preindustrial period, globally and regionally. GISS-E2-1-G projects that global surface temperature anomalies would reach 1.5, 2.0, and 2.5 ℃ in 2024 (±1.34), 2039 (±2.83), and 2057 (±5.03) respectively, while FGOALS-g3 predicts these “tipping points” would arrive in 2024 (±2.50), 2054 (±7.90), and 2087 (±10.55) respectively. Our results reaffirm a dramatic, upward trend in projected climate warming acceleration, with upward concavity in 21st century projections of the Arctic, which could lead to catastrophic consequences across the Earth. Further studies are necessary to determine the most efficient solutions to reduce global warming acceleration and maintain a low SSP, both globally and regionally.

Weighting models according to their performance has been used in constructing multi-model regional climate change scenarios. But the added value of model weighting is not always examined. Here we apply an imperfect model framework to examine the added value of model weighting in projecting summer temperature changes over China. Members of large ensemble initial condition simulations by three climate models of different climate sensitivities under the historical forcing and future scenarios are used as pseudo-observations. Performance of the models participating in the 6th phase of the coupled model intercomparison project (CMIP6) in simulating past climate are evaluated against the pseudo-observations based on climatology, trends in global, regional and local temperatures. The performance along with model’s independence are used to determine the model weights for future projection. The weighted projections are then compared with the pseudo-observations for the future. We find that regional trend as a metric of model performance yields the best skill for future projection while past climatology as performance metric does not improve future projection. Trend at the grid-box scale is also not a good performance indicator as small scale trend is highly uncertain. Projected summer warming based on model weighting is similar to that of unweighted projection, at 2.3°C increase relative to 1995-2014 by the middle of the 21st century under SSP8.5 scenario, but the 5th-95th uncertainty range of the weighted projection is 18% smaller with the reduction mainly in the upper bound, with the largest reduction in the northern Tibetan Plateau.

Warm, salty Circumpolar Deep Water (CDW) is recognized as the primary driver for Antarctic glacial melt, but the mechanism by which it reaches the continental shelves remains highly uncertain from an observational standpoint. With the scarcity of eddy flux estimation in the Antarctic margin, we quantify the isopycnal diffusivity of CDW using hydrographic variability and satellite altimetry under the mixing length framework. For comparison, the spiciness and thickness are used as isopycnal tracers, and the two tracers yield qualitatively similar estimates. Over the Antarctic Circumpolar Current (ACC), spatial variation of mixing length is generally aligned with the jet-induced mixing suppression theory, including its exception in the lee of the topography. In contrast, the mixing length does not depend on the mean flow in the subpolar zone, likely reflecting the relatively quiescent flow regime. The estimated isopycnal diffusivity ranges from 100 to 500 m2 s-1 south of the ACC. The eddy diffusivity tends to be enhanced where the gradient of isopycnal thickness becomes small and CDW intrudes onshore. The cross-slope eddy CDW flux is estimated, and the associated onshore heat flux across is calculated as ~3.6 TW in the eastern Indian sector. The eddy heat flux and coastal solar heating are generally balanced with cryospheric heat sinks including glacial melting and surface freezing, suggesting that the eddy advection is substantial for the onshore CDW flux. The thickness field is essential for determining mixing length and eddy fluxes in the subpolar zone, whereas the situation does not hold for the ACC domain.

The determination of buoyancy flux and its contribution to turbulence kinetic energy (TKE) is a fundamental problem in planetary boundary layer (PBL). However, due to the complexity of turbulence, previous studies mainly adopted dimensional analysis and empirical formula to determine TKE budget. This study introduces the endoreversible heat engine model concept to the convective boundary layer (CBL) TKE analysis and establishes a theoretical model based on the first principles. We found that the total contribution of buoyancy to TKE and heat engine efficiency in the boundary layer increase linearly with the boundary layer height. The derived buoyancy flux from our theoretical model is consistent with the results from numerical simulation and dimensional analysis. This heat engine-based theory reveals the physical mechanism of the power of TKE generated by buoyancy. Our theoretical model can replace the empirical value and provide an ideal method for buoyancy flux determination in PBL.

The El Niño-Southern Oscillation (ENSO) in the equatorial Pacific is the dominant mode of global air-sea CO2 flux interannual variability (IAV). Air-sea CO2 fluxes are driven by the difference between atmospheric and surface ocean pCO2, with variability of the latter driving flux variability. Previous studies found that models in Coupled Model Intercomparison Project Phase 5 (CMIP5) failed to reproduce the observed ENSO-related pattern of CO2 fluxes and had weak pCO2 IAV, which were explained by both weak upwelling IAV and weak mean vertical DIC gradients. We assess whether the latest generation of CMIP6 models can reproduce equatorial Pacific pCO2 IAV by validating models against observations-based data products. We decompose pCO2 IAV into thermally and non-thermally driven anomalies to examine the balance between these competing anomalies, which explain the total pCO2 IAV. The majority of CMIP6 models underestimate pCO2 IAV, while they overestimate SST IAV. Thermal and non-thermal pCO2 anomalies are not appropriately balanced in models, such that the resulting pCO2 IAV is too weak. We compare the relative strengths of the vertical transport of temperature and DIC and evaluate their contributions to thermal and non-thermal pCO2 anomalies. Model-to-observations-based product comparisons reveal that modeled mean vertical DIC gradients are biased weak relative to their mean vertical temperature gradients, but upwelling acting on these gradients is insufficient to explain the relative magnitudes of thermal and non-thermal pCO2 anomalies.

Western Indian Ocean basin shows one of the most complex signatures of the ocean floor anomalies by juxtaposition of the rapidly evolving, multiple spreading ridges, subduction systems and microcontinental slivers. This study based on ocean floor magnetic anomalies, gravity gradient map, tomographic profiles and geometrical kinematic models reports a significant westward drift of the Central Indian Ridge (CIR) segments. Documented precisely between the latitudes 17°S and 21°S the drift is coincident with the Deccan volcanism at ~65±2 Ma and we further explain its bearing on the Indian plate kinematics. The progressive stair-step trend of the ridge segments towards NE is marked by anomalous deflection to NW for a brief distance of ~217 km between these latitudes represented by the anomalies C30n-C29n. The observed length of the ridge segments moving NW at 17°S match the calculated NW drift rates of Indian plate (Bhagat et al., 2022). We infer that the NW drift and its restoration towards NE triggered short Plume Induced Subduction Initiation along the Amirante trench. Further a plume induced lithospheric tilt of the Indian plate (Sangode et al 2022) led to restoration of subduction along the Sunda trench at ~65 Ma imparting new slab pull force over the Indian subcontinent besides the NE trend for CIR. This episode resulted into anticlockwise rotation of the Indian plate along with accelerated drift rates due to vector addition of the plume push and the slab pull forces from Eurasian as well as Sunda subduction systems after 65 Ma. The Deccan eruption thus resulted in major geodynamic reorganization that altered the kinematics of Indian plate; and the signatures of which are well preserved over the ocean floor.