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Estimation of climate sensitivity is fundamental to assessing how global climate will warm as atmospheric CO2 ${\mathrm{C}\mathrm{O}}_{2}$ concentration increases. Geological archives of environmental change provide insights into Earth's past climate, but the incomplete nature of paleoclimate reconstructions and their inherent uncertainties make estimation of climate sensitivity challenging. Thus, quantifying climate sensitivity and assessing how it changed through geological time requires statistical frameworks that can handle data uncertainties in a principled fashion. Here we demonstrate some of the hurdles to estimating climate sensitivity, with a focus on current statistical techniques that may underestimate both climate sensitivity and its associated uncertainty. To solve these issues, we present a Bayesian error‐in‐variables regression model, which can yield estimates of climate sensitivity without bias. The regression model is flexible and can account for data point uncertainties with a known parametric form. The utility of this approach is demonstrated by estimating specific climate sensitivity with uncertainty for the Eocene. Plain Language Summary: As atmospheric CO2 ${\mathrm{C}\mathrm{O}}_{2}$ increases due to human activities, the Earth will warm. But how much warming can be expected? Climate sensitivity describes how much global average surface temperature will warm with a given increase in atmospheric CO2 ${\mathrm{C}\mathrm{O}}_{2}$. While this is a simple definition, estimating climate sensitivity is difficult because Earth's climate system is complex with a number of poorly understood interacting parts. One approach to estimating climate sensitivity is to quantify how Earth's climate changed as a result of variations in atmospheric CO2 ${\mathrm{C}\mathrm{O}}_{2}$ through geological time. This information is invaluable, but it is patchy and has large uncertainties that make estimating climate sensitivity challenging. In particular, existing statistical techniques may underestimate climate sensitivity and, thus, underestimate future warming. In this paper we present an alternative approach to determining climate sensitivity that overcomes the underestimation problem and demonstrate its performance using geological data from the Eocene epoch. Key Points: We demonstrate that regression‐based estimates of specific climate sensitivity may be biased toward zero because of data uncertaintiesA Bayesian error‐in‐variables approach is developed that accounts for data uncertainties in regression‐based climate sensitivity estimatesEocene specific climate sensitivity is estimated to demonstrate the utility of Bayesian error‐in‐variables regression [ABSTRACT FROM AUTHOR]

This paper addresses one of the critical questions of scientific inquiry: How do we know when a given data set is representative of the phenomenon being examined? For paleomagnetists, the question is often whether a particular data set sufficiently averaged paleosecular variation (PSV). To this aim, we updated an existing PSV data set that now comprises 2,441 site mean directions from 94 individual studies (PSV10‐24). Minimal filtering for data quality resulted in 1,619 sites from 90 publications. Fitting PSV10‐24 with two newly defined parameters as well as two existing ones form the basis of a Giant Gaussian Process field model (THG24) consistent with the data. Drawing directions from THG24 yields directional distributions predicted for a given latitude allowing a comparison between empirical distributions and the cumulative distribution function generated by the model. This tests whether the observed data adequately averaged out PSV according to THG24. We applied these tests to five data sets from Large Igneous Provinces from the last billion years and find that they are consistent with the THG24 model as well. Sedimentary data sets that may have experienced inclination shallowing can be corrected using an (un)flattening factor that yields directions satisfying THG24 in a newly‐defined, four‐parameter space. This approach builds on the Elongation‐Inclination (E/I) method of Tauxe and Kent (2004), https://doi.org/10.1029/145gm08, so the approach introduced here is called SVEI. We show examples of the use of SVEI and explain how to use this newly developed Python code that is publicly available in the PmagPy GitHub repository. Plain Language Summary: Paleomagnetic vectors recorded by rocks and archeological materials yield information on the structure of the magnetic field through Earth's history. The geomagnetic field mostly resembles a geocentric dipole aligned with the spin axis, but the directions at any given time and place generally deviate from this simple model. Data sets produced over several decades help define global magnetic field behavior. Here, we updated a compilation of paleomagnetic data and used it to establish a new field model representative of the last 10 million years. Prior or emerging data sets can be tested against the model to see whether the two agree in terms of field structure and variability. We tested data sets as old as 1.1 billion years and found them compatible with the model. Moreover, this model can also assess, and potentially correct data from sedimentary rocks that may have suffered from inclination shallowing. Although other correction methods exist, our approach employs a more complete description of the geometry of directional data, thereby allowing a more quantitative comparison of empirical and predicted distributions. Corrected inclinations and their uncertainties define paleolatitudes more accurately, key for plate tectonic and paleoclimatic reconstructions. Key Points: Update of the paleosecular variation database from lava flows (PSV10‐24) for the last 10 MaDefinition of a new Giant Gaussian Process (GGP) model (THG24), compatible with PSV10‐24 matching VGP scatter including data sets as old as 1.1 GaDescription of the SVEI method (an update of E/I) to assess secular variation records and to correct for inclination shallowing in sediments [ABSTRACT FROM AUTHOR]

Sapropels are dark, organic‐rich layers found in Mediterranean sediments that formed during periods of bottom water anoxia. While various mechanisms have been proposed to have caused anoxic conditions, a primary factor is considered to be water column stratification induced by freshwater runoff related to intensified North African monsoon precipitation during precession minima. Monsoon intensification also induced Green Sahara Periods that may have impacted North African hominin dispersal. In this study, we present a novel regression‐based deconvolution of a high‐resolution planktonic foraminiferal oxygen isotope record to estimate the combination of freshwater runoff reaching the eastern Mediterranean and associated surface warming of the water column over the past 5 million years. Sapropels are known to occur in clusters associated with periods of high orbital eccentricity. Our analysis reveals a consistent influence of orbital eccentricity in modulating the North African monsoon, and a possible shift in runoff source area induced by the initiation of Northern Hemisphere ice sheets. Our findings provide important insights into the role of the North African monsoon in shaping Mediterranean environmental changes over the past 5 million years. Plain Language Summary: We investigate long‐term changes in monsoon rains over North Africa, which annually result in freshwater flowing into the Mediterranean Sea. Over geological time, Earth's orbital variations have played a significant role in shaping the monsoon and, consequently, the quantity of freshwater entering the Mediterranean. Foraminifera, small marine organisms, record the oxygen isotope composition of their environment in their shells. Notably, the oxygen isotope balance in North African monsoon rains and the Mediterranean Sea differ, but eventually mix upon the freshwater entering into the Mediterranean. Our research combines a statistical analysis of oxygen isotope data preserved in foraminifera shells with a numerical model of the Mediterranean Sea, enabling us to estimate changes in monsoon freshwater input into the Mediterranean over the past 5 million years. This information not only enhances our understanding of monsoon evolution but also provides insights into the potential for hominin migrations in a more lush North African landscape characterized by higher rainfall than today. Key Points: We present quantitative estimates of Plio‐Pleistocene North African monsoon activity based on deconvolution of planktonic foraminiferal δ18OThrough the past 5 million years estimated monsoon activity is consistent with the expected pattern of orbital eccentricity modulationApparent monsoon strengthening at ∼2.6 Ma may be due to shifting runoff sources induced by Northern Hemisphere ice sheet initiation [ABSTRACT FROM AUTHOR]

A synthesis of new and existing data allows Heinrich Stadial 11 (HS11), a prominent Northern Hemisphere cold event, to be linked to the timing of peak sea-level rise during glacial termination T-II, whereas rapid sea-level rise in T-I is shown to clearly post-date Heinrich Stadial 1, so fundamentally different mechanisms seem to be at work during glacial terminations. Anatomy of a glacial termination A central goal of palaeoclimate research is that of deciphering the mechanisms responsible for major state shifts in the Earth system, such as between glacial and interglacial conditions. This has proven difficult enough even for the last glacial termination (T-I), much less termination II (T-II), which ended glacial conditions about 130,000 years ago. Gianluca Marino et al. use new and existing data to demonstrate a link, within uncertainties, between Heinrich Stadial 11 (HS11) -- a prominent Northern Hemisphere cold event -- and the timing of peak sea level rise during T-II. A strong Southern Hemisphere warming also occurred during HS11, consistent with the idea of a bipolar seesaw that would probably have promoted Antarctic ice sheet melting. In contrast, rapid sea level rise in T-1 clearly postdated Heinrich Stadial 1. Possibly in response to differing CO.sub.2 and insolation conditions during T-I and T-II, fundamentally different mechanisms seem to be at work in triggering glacial terminations. Our current understanding of ocean-atmosphere-cryosphere interactions at ice-age terminations relies largely on assessments of the most recent (last) glacial-interglacial transition.sup.1,2,3, Termination I (T-I). But the extent to which T-I is representative of previous terminations remains unclear. Testing the consistency of termination processes requires comparison of time series of critical climate parameters with detailed absolute and relative age control. However, such age control has been lacking for even the penultimate glacial termination (T-II), which culminated in a sea-level highstand during the last interglacial period that was several metres above present.sup.4. Here we show that Heinrich Stadial 11 (HS11), a prominent North Atlantic cold episode.sup.5,6, occurred between 135 [plus or minus] 1 and 130 [plus or minus] 2 thousand years ago and was linked with rapid sea-level rise during T-II. Our conclusions are based on new and existing.sup.6,7,8,9 data for T-II and the last interglacial that we collate onto a single, radiometrically constrained chronology. The HS11 cold episode.sup.5,6 punctuated T-II and coincided directly with a major deglacial meltwater pulse, which predominantly entered the North Atlantic Ocean and accounted for about 70 per cent of the glacial-interglacial sea-level rise.sup.8,9. We conclude that, possibly in response to stronger insolation and CO.sub.2 forcing earlier in T-II, the relationship between climate and ice-volume changes differed fundamentally from that of T-I. In T-I, the major sea-level rise clearly post-dates.sup.3,10,11 Heinrich Stadial 1. We also find that HS11 coincided with sustained Antarctic warming, probably through a bipolar seesaw temperature response.sup.12, and propose that this heat gain at high southern latitudes promoted Antarctic ice-sheet melting that fuelled the last interglacial sea-level peak., Author(s): G. Marino [sup.1] , E. J. Rohling [sup.1] [sup.2] , L. Rodríguez-Sanz [sup.1] , K. M. Grant [sup.1] , D. Heslop [sup.1] , A. P. Roberts [sup.1] , J. [...]

Voxels have been used in various application domains successfully for the last several decades. Their main advantage is the underlying discrete data structure allowing to reliably work with surrounding voxels all the time. In this paper, capabilities of the Unity game engine for voxels management and geometry voxelisation are assessed, where 4 native solutions and 7 open-source projects written for Unity are investigated. Although many voxel-based options exist in Unity, they only deal with one part related to voxels. Therefore, the available capabilities to voxelise, visualise, structure and export voxels are combined and extended with the goal of successfully processing large 3D models and geometries. Many voxel visualisation techniques are investigated including mesh, VFX, point clouds and SVO, which have distinctive benefits in various aspects. Possibilities to structure voxels for effective management in simulations and other tasks are shown. Also, it is enabled to export voxels as point clouds and to the Postgres database for further processing, spatial analysis and distribution. One of the main conclusions is the lack of support for state-of-the-art voxel data structures, where the presented platform can easily be extended to support any. This platform can be used by people who deal with 3D discrete data, require voxelising 3D data, visualise voxels in different ways and technologies, as well as manage more efficiently sparsely occupied voxels. [ABSTRACT FROM AUTHOR]

First‐order reversal curve (FORC) distributions are a powerful diagnostic tool for characterizing and quantifying magnetization processes in fine magnetic particle systems. Estimation of FORC distributions requires the computation of the second‐order mixed derivative of noisy magnetic hysteresis data. This operation amplifies measurement noise, and for weakly magnetic systems, it can compromise estimation of a FORC distribution. Previous processing schemes, which are based typically on local polynomial regression, have been developed to smooth FORC data to suppress detrimental noise. Importantly, the smoothed FORC distribution needs to be consistent with the measurement data from which it was estimated. This can be a challenging task even for expert users, who must adjust subjectively parameters that define the form and extent of smoothing until a "satisfactory" FORC distribution is obtained. For nonexpert users, estimation of FORC distributions using inappropriate smoothing parameters can produce distorted results corrupted by processing artifacts, which can lead to spurious inferences concerning the magnetic system under investigation. We have developed a statistical machine learning framework based on a probabilistic model comparison to guide the estimation of FORC distributions. An intuitive approach is presented that reveals regions of a FORC distribution that may have been smoothed inappropriately. An associated metric can also be used to compare data preparation and local regression schemes to assess their suitability for processing a given FORC data set. Ultimately, our approach selects FORC smoothing parameters in a probabilistic fashion, which automates the derivative estimation process regardless of user expertise. Key Points: We develop a probabilistic framework for estimating FORC distributionsUsing Bayesian model selection, we identify underfitting and overfitting of FORC distributionsFORCsensei software can be used to determine smoothing parameters to estimate a FORC distribution [ABSTRACT FROM AUTHOR]

Estimation of paleomagnetic directions plays a crucial role in magnetostratigaphy, paleogeographic reconstruction, and constraining past geomagnetic field behavior. While analysis and aggregation of paleomagnetic directional data are performed in a hierarchical fashion, the standard statistical framework employed by paleomagnetists does not consider uncertainty propagation through each level of the hierarchy. With this limitation, inferences drawn from paleomagnetic data will be affected by underestimated uncertainties. We provide here an approximate directional uncertainty propagation scheme that applies to Fisher distributions and, thus, to a number of paleomagnetic data processing tasks. The scheme is a straightforward addition to the existing paleomagnetic statistical framework and is demonstrated using case studies to show how uncertainties can be propagated through different stages of the paleomagnetic data processing chain. Furthermore, we discuss situations, such as the transformation into virtual geomagnetic poles, where this simple form of uncertainty propagation cannot be employed because the data are not Fisher distributed. Key Points: A scheme for propagation of paleomagnetic directional uncertainties is presentedUncertainty approximation is a simple extension of existing paleomagnetic statisticsThe utility of the approximation is demonstrated for several paleomagnetic data sets [ABSTRACT FROM AUTHOR]

The potential use of 'pharmaceuticals' has been identified by civilian law enforcement agencies, and counter-terrorism responders, as a threat that fills the gap between physical restraint and lethal weapons. This rise in availability of synthetic opiates reassessment of the overall public health threat from pharmaceutical based agents. The large quantities of illicitly synthetized novel opioids create a significant risk of accidental exposures or, potentially, a major deliberate release, and represents a global health security concern. Here we present a health security risk assessment of PBAs and approaches to threat prevention or mitigation, gaps in research, and medical countermeasure considerations. [ABSTRACT FROM AUTHOR]

An ability to compare paleomagnetic poles quantitatively is fundamental to paleogeographic reconstruction. The Fisher distribution provides a statistical framework for both constructing and relating paleomagnetic poles to enable comparison of estimated pole positions in paleomagnetic reconstructions. However, Fisher distribution‐based confidence regions for paleomagnetic poles are often compared using empirical rules of thumb rather than by quantitative analysis of their full structure. Here we demonstrate potential shortcomings of such comparisons and propose continuous metrics for quantitative comparison of paleomagnetic poles. These metrics are simple to apply for Fisher distributions and can be modified readily for a broad range of alternative distributions that may be more appropriate for representing some paleomagnetic data sets. We demonstrate how our proposed metrics provide both quantitative and probabilistic approaches to common tasks in paleomagnetic reconstruction, such as comparing estimated mean pole positions with apparent polar wander paths. Key Points: The similarity between paleomagnetic poles is quantified with information‐theoretic metricsA Bayes error is derived to measure pole similarity in a probabilistic frameworkThis approach enables quantitative comparison of new and published paleomagnetic poles [ABSTRACT FROM AUTHOR]

The Eocene‐Oligocene transition (EOT) marked the initiation of large‐scale Antarctic glaciation. This fundamental change in Cenozoic climate state is recorded in deep‐sea sediments by a rapid benthic foraminiferal δ18O increase and appearance of ice‐rafted debris in the Southern Ocean. However, we know little about the magnitude of cooling associated with the EOT in shallow water environments, particularly at middle to high latitudes. Here we present new stratigraphic records of the C13r/C13n magnetochron boundary and the EOT in the clay‐rich Blanche Point Formation, South Australia. The Blanche Point Formation was deposited in a shallow shelf setting (water depths of <100 m) at a paleolatitude of ~51°S. We present high‐resolution δ18O, δ13C, and Mg/Ca records of environmental change from well‐preserved benthic foraminifera of latest Eocene age at this site. A marked, negative δ13C excursion occurs immediately before EOT Step 1 and may be a globally representative signal. An ~2 °C cooling of shallow shelf seawater is evident from benthic foraminiferal Mg/Ca across Step 1. This cooling signal is both sufficient to account fully for the δ18O increase in our data and is of similar amplitude to that documented in published records for shallow shelf and upper water column open ocean settings, which suggests no obvious polar amplification of this cooling signal. Our results strengthen the evidence base for attributing EOT Step 1 to global cooling with little contribution from ice volume growth and contradict the mechanism suggested to explain the inferred northward migration of the intertropical convergence zone in the contemporaneous equatorial Pacific Ocean. Key Points: We present a detailed stable isotopic and Mg/Ca record for the early Eocene‐Oligocene transition from southern Australia at ~51°SShallow shelf (<100 m deep) seawater temperatures fell 2 °C across this part of the transitionSurface seawater δ18O values were probably closer to positive one than negative one within this embayment in the latest Eocene, indicating that a source of relatively saline water was present at this time [ABSTRACT FROM AUTHOR]

For over 60 years a suite of field tests has provided paleomagnetists with a means to evaluate the timing of magnetic remanence acquisition and subsequent remanence stability. These tests are crucial for detecting potential overprinting by secondary remanences and for assessing the fidelity of the geological information carried by paleomagnetic signals. The reversal test was developed to detect secondary remanent magnetizations that could potentially bias paleomagnetic reconstructions. More recently, the reversal test has been applied to a broader set of problems, which require statistical assessment of common or antipodal paleomagnetic directions. From a statistical standpoint, the reversal test must distinguish whether two sets of paleomagnetic directions originate from populations with a common mean. However, earlier work has demonstrated that the reversal test may be ambiguous for small numbers of observations because insufficient information is available to reject the null hypothesis of a common mean direction. Here we develop a Bayesian framework to estimate directly the probability that two Fisher‐distributed sets of directions originate from populations with a common mean. This framework can be used to consider data sets with common or different precisions and, thus, provides a fully probabilistic version of the parametric reversal test. Additionally, adoption of a Bayesian framework means that ambiguity associated with the lack of information provided by small numbers of observations is incorporated into the final probability estimate in a natural way. Our new Bayesian test is demonstrated with numerical examples and case studies. Key Points: Tests for a common mean paleomagnetic direction are placed into a Bayesian frameworkTest results naturally incorporate uncertainty when only small sets of observations are availableThe Bayesian test for a common mean direction is illustrated with a number of case studies [ABSTRACT FROM AUTHOR]

Abstract: First‐order reversal curve (FORC) diagrams provide information about domain states and magnetostatic interactions that underpin paleomagnetic interpretations. FORC diagrams are a complex representation of remanent, induced, and transient magnetizations that can be assessed individually using additional FORC‐type measurements along with conventional measurements. We provide the first extensive assessment of the information provided by remanent, transient, and induced FORC diagrams for a diverse range of soil, loess/paleosol, and marine sediment samples. These new diagrams provide substantial information in addition to that provided by conventional FORC diagrams that aids comprehensive domain state diagnosis for mixed magnetic particle assemblages. In particular, we demonstrate from transient FORC diagrams that particles occur routinely in the magnetic vortex state. Likewise, remanent FORC diagrams provide information about the remanence‐bearing magnetic particles that are of greatest interest in paleomagnetic studies. [ABSTRACT FROM AUTHOR]