Loess tablelands, plateau-like landforms built of wind-blown dust, store large volumes of sediment on its path from bedrock sources to sedimentary basins. Long-term storage of organic carbon also occurs in buried soils beneath loess tableland summits. The evolution of loess tablelands can be conceptualized as a process of relief generation through loess accumulation, raising tableland summits above local base level, followed by stream dissection driven by the increased local relief. We investigated how these landforms of highly erodible material have persisted over 10,000-100,000 yr timescales in the central Great Plains, USA, using stratigraphic data, field measurements of soil strength, geospatial analysis, and numerical modeling. Where subsurface data is adequate, it appears that loess tablelands developed on pre-existing bedrock tablelands. The presence of many closed depressions on tableland summits is the key factor limiting the rate of tableland dissection, rather than an erosion-resistant cap as in bedrock tablelands. These depressions capture most runoff on tableland summits, limiting the drainage area of channels eroding the steep tableland margins. Numerical modeling of loess tableland evolution with the Landlab toolkit produces tablelands similar to those of our study area; tableland summits with many closed depressions persisted substantially longer than those without depressions. Modeling also indicates that depression-breaching by gullies is an important process in tableland dissection and there is clear evidence of this process in tablelands of our study area.

This paper introduces the basics of asymmetrical spectral band fitting and discusses the resolution of overlapping Gaussian shapes. We study how to fit overlapping bands with asymmetric Gaussian shapes. First, we derive an equation for an Asymmetric Gaussian shape. We then use this equation to derive a resolvability basis for the resolution of two nearby Gaussian bands. The so called Master Equation is then used to fit these two overlapping bands. We identify regions of the fitting space where the Asymmetric Gaussian fit is likely to be Optimal, Sub Optimal and Not Optimal. We then demonstrate the use of the Asymmetric Gaussian to fit four overlapping bands, and show how this is relevant to the olivine spectral complex at 1 μm. The limitations of the asymmetric band fitting method and a critical assessment of three commonly used numerical minimization and fitting methods are also provided.

Air pollution is estimated to result in approximately 6.7 million premature mortalities annually, more than 74000 of which may be attributable to aviation emissions. Recent studies of aviation’s environmental impacts have solely focused on the climate impacts of aviation NOx, suggesting they are small and uncertain relative to those of aviation CO2. These analyses have neglected the air quality (AQ) impacts of NOx, which previous studies have found to be substantial, and for which the monetized damages may be of a similar order of magnitude to aviation’s net climate impacts. The AQ impacts are due to surface population exposure to ozone and PM2.5 due to local and transported emissions. To analyze this, prior studies have evaluated global average values of the sensitivity of changes in these parameters to emissions. However, a limitation of this approach is that it does not allow for a spatial differentiation of the impacts at high resolutions.This work addresses this limitation by using a finite difference approach to determine the sensitivity of AQ impacts in regions of interest to aviation emissions at different regions. Simulations with a 0.5° x 0.5° resolution of the region of interest will enable analyzing the effect of the prevailing background conditions of that region on AQ, for which effects on climate have been explored. The GEOSChem High Performance global chemistry transport model with stretched-grid simulation capability will be used, which can model regions of interest at high resolution efficiently without significant increases in computational time. For our analysis, flights in South Asia and East Asia & Pacific, which are aviation hotspots, are chosen for aircraft and engines which have the largest share of impact. This analysis will help shape aviation policies to minimize the environmental damages of aviation by understanding the impact of technology improvements on different types of aircraft. Furthermore, this high-resolution regional data will provide a foundation for analyzing the distributional inequities in aviation AQ impacts. Future work following this study will involve evaluating the total monetized impacts of aviation for damages due to both AQ and climate for different regions.

Semeru (Indonesia) is a persistent eruptive volcano, but its volcanic activity remains poorly constrained. Here we used a combination of different remote sensing data to improve the understanding of Semeru. By differencing high resolution (2m) Digital Elevation Models (DEM) derived from optical data (EarthDEMs), we estimated a bulk volume of ~43.5x106 m3 of lavas erupted from 2014 to 2020. Thermal data from MIROVA show multiple peaks in the volcanic radiative power and in the cumulative radiant energy (VRE) related with lava flow extrusions. Time series of deformation, obtained with Synthetic Aperture Radar Interferometry (InSAR) from Sentinel-1 data, show on both orbits negative line-of-sight displacements of the SE flank from 2014 to 2023. We modelled this deformation with a Boundary Element Method, showing that displacements are related to a limited (≤1x106 m3) deflation of a shallow (<2 km) reservoir. We used the volume estimated by EarthDEMs to calibrate the VRE and to calculate the erupted volume of lava from VRE for periods not covered by EarthDEM, allowing in the future the near-real-time estimation of volumes from MIROVA data. Erupted volumes of lava over the time reveal a steady state activity. The large discrepancy between the erupted and the modelled volume suggests that the shallow reservoir is a hydrothermal reservoir or an ephemeral gas-rich magma reservoir, with the persistent volcanic activity fed by deeper reservoir(s). This study highlights the importance of using different remote sensing data to monitor, quantify, and interpret the volcanic activity in poorly monitored and studied volcanoes.

Providing a dynamic method to monitor water storage in the Yellow River Basin and obtaining spatial and temporal conclusions on real-time water storage changes is of great significance to the ecological protection and social development of the basin. In this study, we adopted GRACE/GRACE-FO satellite data and meteorological station data from 2003 to 2023 in the Yellow River basin, reconstructed the missing data through multi-layer perceptual neural network. We analysed the characteristics of the Tibetan Plateau region, the Loess Plateau region, and the downstream region by combining the differences in water resources recharge, and human activities under different climatic environments. We further united the basin as a whole, and obtained the sub-districts and basin overall temporal and spatial patterns of change of terrestrial water reserves and temporal patterns of change of climate elements, and then analysed the influencing factors. Finally, we compared and analysed data on climate and terrestrial water storage changes in the Loop and the Beijing-Tianjin-Hebei region to explore the effects of inter-basin water transfers (South-to-North Water Diversion Project) on the restoration of terrestrial water storage. The results showed as follows: 1)The overall land water reserves in the Yellow River Basin showed a downward trend, while the Qinghai-Tibet Plateau showed an upward trend, and the driving forces of regional water reserves were different. 2)There is a seasonal variation of land water reserves in different regions. There is a lag of 2~3 months between peak annual precipitation and peak annual water storage in the Loess Plateau region and downstream region, but not in the Tibetan Plateau region. 3)The cross-basin water transfer project can significantly restore regional land water reserves, which is an important reference for the management of the Yellow River Basin. In order to improve the accuracy of time-space scale estimation of terrestrial water storage changes, it is necessary to further focus on the fusion of multi-source geophysical data to explore the data downscaling method.

Understanding the interaction between Mars and the solar wind is crucial for comprehending the atmospheric evolution and climate change on Mars. To gain a comprehensive understanding of the Martian plasma environment, global numerical simulations are essential in addition to spacecraft observations. However, there are still discrepancies among different simulation models. This study investigates how these discrepancies stem from the considered physical processes and numerical implementations. We compare two global multispecies MHD models: the “Sun model” based on the BATS-R-US code and the “Sakata model” based on a newly developed multifluid model MAESTRO. By employing the same typical upstream conditions and the same neutral atmosphere for current Mars, along with similar numerical implementations such as inner boundary conditions, we obtain simulation results that exhibit unprecedented agreement between the two models. The dayside results are nearly identical, especially along the subsolar line, indicating the reliability of MHD models to predict dayside interaction under given upstream conditions and ionosphere assumptions. The escape rates of planetary ions are also in good agreement. However, discrepancies remain in the terminator and nightside regions. Detailed numerical implementations, including inner boundary conditions, magnetic field divergence control methods, and radial resolutions, are shown to influence certain aspects of the results greatly, such as magnetotail configuration and ion diffusion.

As the planet continues to warm, precipitation amounts and timing are changing. Predicted increases in frequency and severity of drought in some regions will increase the frequency of dust storms and wildfires, contributing to increased exposure to poor air quality. Poor air quality causes health impacts including respiratory diseases, cardiovascular diseases, stress and mental health outcomes, worsening of pre-existing health conditions, and death. However, relatively few studies exploring future drought-related impacts on health have been conducted in the Canadian context. This study examined self-reported health impacts and coping strategies of members in two First Nation communities in Saskatchewan during poor air quality events. Studying marginalized communities, such as First Nation communities, is essential because these communities face specific exposures due to their ties to the land and are likely to experience significant structural barriers and limits to their adaptation given the impacts of colonization. It is important to work with First Nations communities to understand place-based impacts and culturally appropriate adaptation strategies to effectively inform policy and practice. Elders and Knowledge Holders, Key Informants, and general community members were interviewed to better understand how individuals in First Nation communities in Saskatchewan have experienced and been impacted by drought-induced poor air quality. Common themes emerging include concern for health and wellbeing of youth and Elders in the community, concerns around community preparedness during adverse air quality events, and feelings of community cohesion amongst members for support during these events. Ultimately, the intent of this project is to prioritize Indigenous-specific impacts and actions during poor air quality events in order to enhance evidence-informed policies, education, and awareness.

Among the zoo of Jovian auroral radio emissions, the broadband kilometric (bKOM) component has been the least studied. Taking advantage of Juno in situ measurements within the auroral regions, we surveyed the Juno/Waves radio observations over the 60 first orbits to identify 7 bKOM source candidates. These were mostly detected during dawn storm auroral episodes (4/7) and three were found to be colocated with auroral cavities. By applying a growth rate analysis based on JADE-E electron measurements, we show that the observed waves are driven by the Cyclotron Maser Instability from two free energy sources. The main emission, produced slightly above the electron gyrofrequency (f$_{ce}$), is amplified by conics-type electron distribution functions (EDF) with 2 to 30~keV electron characteristic energies. Sporadic bursts, produced slightly below f$_{ce}$, is driven by shell-type EDF of 0.1 to 10~keV. These results are analyzed comparatively to those obtained previously for Jovian hectometric and decametric emissions.

The sequential Suspended Sediment Concentration (SSC) maps were generated using IRS-P4 OCM data for selected tide dominated, wave dominated and deltaic coasts around the Indian subcontinent. Patterns of SSC were studied to understand the sediment dynamics, circulation patterns, fronts and consequent impact on coastal processes. Hitherto unknown sediment plumes extending for large distance into deep offshore areas could be identified from the major deltaic regions. The high temporal capability of OCM data was extremely useful to understand sediment dynamics in tide dominated regions of the Gulf of Khambhat, Gulf of Kachchh and the Hoogli estuary. SSC maps in conjunction with corresponding tide and bathymetry data could be sequenced as per flooding and ebb cycles. Development, formation shifting nature of shoals and sediment curls during a tide cycle could be studied. It is observed that during the NE monsoon suspended sediment influx of the Ganga-Brahmaputra system influences the coastal processes along the continental margins of Orissa and Northern Andhra Pradesh along east coast of India. The occurrence of cyclone aids in entrapment of fluvial discharge into the coastal waters, leading to a reduced offshore influx into deeper regions of the Bay of Bengal and high sedimentation near to the coast. Seasonal changes along wave-dominated west coast showed net sediment transport from north to south in the pre-monsoon season and south to north in post-monsoon season. Significant onshore-offshore transport along west coast was also observed. The impact of the regional sediment dynamics on the site specific local coastal environment was studied by integrating observations derived from OCM and IRS-1C/1D data.

The Indian coast of around 7,500 km requires vulnerability assessment and mapping in view of enormous number of lives, property and coastal ecosystem worth billions of Rupees at stake. Several natural and human-induced coastal hazards affect the Indian coast, modify the coastal processes operating in the region and needs to be monitored continuously. Remote sensing and geo-information techniques for the Indian coast have proven to be extremely useful to unders tand coastal processes and mitigate coastal zone hazards. The present paper highlights the approach adopted for coastal vulnerability mapping and initial results. Initially six areas have been identified. This work is being followed for entire coast of Gujarat, Kerala, Tamil Nadu, Andhra Pradesh and ultimately all the Maritime States and Union Territories of India. Initial results from SRTM DEM derived relief map and inundation model for 1 m projected SLR around the Indian coast show that large areas covering the Rann of Kachchh, north eastern parts of the Gulf of Kachchh, Sunderban delta, Mahanadi delta, Chilika lagoon, Kolleru region, Kaveri delta, parts of Kerala coast around Cochin, Lakshadweep islands, parts of Maharashtra coast around Mumbai face serious threat due to projected SLR. Work carried out for the Paradip region along east coast of India show that vulnerability of the coast to coastal erosion is segmented as some parts as highly vulnerable, whereas some parts are less vulnerable. It has not been possible to integrate the flood line and hazard line to demarcate setback line as the flood line is exceeding at all places inland.

Atmospheric surface pressure provides valuable information on the vertical dynamical structure of the atmosphere. Previous studies have reported that among the waves observed in surface pressure, semi-diurnal tides (SDTs) are significantly affected by the stratospheric quasi-biennial oscillation (QBO). Using historical surface-pressure observations and the Earth-system model MRI-ESM2.0, this study confirms that SDTs and the QBO are synchronized, such that SDT amplitude respectively increases or decreases at a rate of ~1 Pa per 20 ms−1 during westerly or easterly phases of the QBO at 30 hPa. Our numerical simulations and a linear analytical model support the QBO–SDT relationship being dynamically forced by background zonal winds rather than by anomalous ozone radiative heating. We also find that the QBO–SDT relationship was notably disturbed by the volcanic eruptions of Mount Agung in 1963 and Mount Pinatubo in 1991, during which increased shortwave radiative absorption caused by stratospheric aerosol enhanced the SDT amplitude. Short-lived El Nino events also occurred, moistening the upper troposphere to provide extra solar heating when volcanic aerosol was transported to higher latitudes. The influence of volcanic eruptions and El Nino events overlap with the QBO frequency band, jointly working as ‘noise’ in QBO–SDT synchronization.

To explore the hypothesis of a common source of variability in two time series, observers may estimate the magnitude-squared coherence (MSC), which is a frequency-domain view of the cross correlation. For time series that do not have uniform observing cadence, MSC can be estimated using Welch’s overlapping segment averaging. However, multitaper has superior statistical properties to Welch’s method in terms of the tradeoff between bias, variance, and bandwidth. The classical multitaper technique has recently been extended to accommodate time series with underlying uniform observing cadence from which some observations are missing. This situation is common for solar and geomagnetic datasets, which may have gaps due to breaks in satellite coverage, instrument downtime, or poor observing conditions. We demonstrate the scientific use of missing-data multitaper magnitude-squared coherence by detecting known solar mid-term oscillations in simultaneous, missing-data time series of solar Lyman-α flux and geomagnetic Disturbance Storm Time index. Due to their superior statistical properties, we recommend that multitaper methods be used for all heliospheric time series with underlying uniform observing cadence.

This work identifies and characterizes magnetic structures, especially in terms of small-scale magnetic flux ropes (SFRs), in the solar wind and magnetosheath across the Earth’s bow shock. We investigate the differences between the properties of SFR structures in these regions immediately upstream and downstream of the bow shock by employing two data analysis methods: one based on wavelet transforms and the other based on the Grad-Shafranov (GS) detection and reconstruction techniques. In situ magnetic field and plasma data from the Magnetospheric Multiscale (MMS) and Time History of Events and Macroscale Interactions during Substorms (THEMIS) missions are used to identify these coherent structures through the two approaches. We identify thousands of SFR event intervals with a range of variable duration over a total time period of $\lesssim$1000 hours in each region. We report parameters associated with the SFRs such as scale size, duration, magnetic flux content, and magnetic helicity density, derived from primarily the GS-based analysis results. These parameters are summarized through statistical analysis, and their changes across the bow shock are shown based on comparisons of their respective distributions. We find that in general, the distributions of various parameters follow power laws. The SFR structures seem to be compressed in the magnetosheath, as compared with their counterparts in the solar wind. A significant rotation in the $z$-axis defining the orientation of the structures is also seen across the bow shock. We also discuss the implications for the elongation of the SFRs in the magnetosheath along one spatial dimension.

On 12 February 2020, a ground blizzard impacted North Dakota, driven by a strong Arctic cold front that swept southward through the eastern Dakotas and western Minnesota. This event brought frontal snow, strong winds, and sub-zero temperatures, leading to significant blowing snow (BLSN) conditions in the Red River Valley and causing widespread disruption. This research provides a detailed analysis of the meteorological phenomena on 12 February, with a focus on BLSN dynamics. We employed a BLSN algorithm based on the PIEKTUK-D model, coupled with the Polar Weather Research and Forecasting (PWRF) model. Simulations were conducted using lateral boundary conditions from the 0.25° Global Forecast System analysis data. We evaluated basic meteorological parameters, such as temperature, wind, and relative humidity, alongside specialized parameters like snow depth. Analysis revealed that the BLSN transport rate and number concentration from the simulations showed strong agreement with observations from the GOES-16. The most significant impact of incorporating the BLSN algorithm in PWRF is observed in the vertical distribution of relative humidity. A notable outcome of this research is the successful implementation of the BLSN code to calculate visibility, which can prove to be particularly useful during blizzard conditions.

The distance over which planktonic larvae are dispersed and the variability within that dispersal distance are important for understanding gene flow and persistence of species with planktonic larvae in the coastal ocean. The breadth of spatial and temporal scales that can be important to dispersal in shelf seas makes direct observations of larvae, and thus these statistics difficult - instead, we often use numerical simulations of circulation to estimate the statistics of larval dispersal. However, meroplanktonic life histories are most common in coastal regions where drifter-based estimates of circulation are sparsely distributed, making validation of these numerical simulations quite difficult. We use a novel technique to validate climatological mean and standard deviation of dispersal distance at a global scale by drawing on the tens of thousands of sparsely distributed drifter observations on the shelf. Numerical dispersal estimates were made using Lagrangian particle trajectories calculated with circulation fields from a 1/12{degree sign} global physical model and were validated against drifter data from the Global Drifter Program (GDP). The median dispersal distance of a climatological ensemble of numerical drifters released from a single location were found to match GDP drifter estimates quite well (with a mean deviation of 0.2%), while model estimates of dispersal were shown to underestimate the diffusivity of GDP drifters by 30 to 50%. Our results indicate that while global numerical estimates of dispersal statistics provide a close approximation of median dispersal distance in the coastal ocean, these numerical simulations underestimate the overall variation present in the coastal ocean.

A document by Berkay Aydin. Click on the document to view its contents.

This article explores the potential of polycentric governance to strengthen civic virtue for collective action towards social-ecological sustainability, including by helping ‘re-enchant’ human relationships with the more-than-human world (Nature). Much of humanity remains alienated in some degree from Nature under the influence of a ‘disenchanted’ (anthropocentric) worldview rendering her of only instrumental value to us. The consequent loss of human affinity with Nature depleted the civic virtue required for this sustainability. The potential for polycentric governance to strengthen this virtue is explored by drawing from theories of collective action and self-determination, and from scholarship on biophilia, Indigenous knowledge, and non-human behaviour. This potential is affirmed in respect of community-based forms of this governance informed by the subsidiarity principle and Indigenous knowledge systems that Fikret Berkes identified as central to sacred ecology as a re-enchanted tradition of ecological science. The article concludes from an anthropocentric perspective that community-based, versus centralised, sustainability governance is likely to cultivate more civic virtue for sustaining Nature given its greater support for humans’ basic psychological needs. A sacred ecology perspective leads to the conclusion that such governance has potential to generate further such virtue by increasing our exposure to Nature and thereby strengthening fulfilment of these needs. The additional needs fulfilment arising from a re-enchanted worldview can thus lead us to care and act more for Nature – not only from enlightened recognition of the instrumental value of doing so but also from experiencing more of Nature as integral to our senses of self.

Event detection analysis is a data-model comparison technique in which all observational and numerical values are converted into a binary yes-no categorization of being in or out of ”event state.” Common metrics within event detection analysis include several skill scores – specifically those of Heidke, Peirce (true skill statistic), Clayton, and Gilbert (equitable threat score). All of these skill scores use the general skill score formula, comparing a metric score for the new model against that of a reference model. Moreover, all of them use, to some degree, the same ”expected random matrix” as the reference model. This matrix reshuffles the two number sets of observed and modeled events, randomizing when events occur. These skill scores are, therefore, based on the new model results and thus depend on its performance. That is, these are not calculated relative to an independent reference model. It is shown that for a given metric score (holding proportion correct or critical success index constant), these skill scores have a range of possible values. Conversely, identical skill scores could result from a range of original metric scores. It is recommended to stop using these named skill scores and instead use one of the presented alternatives. One reference model option uses the observed events in place of the new modeled events, while the other uses a 50-50 ”coin flip” option (i.e., truly random chance). These new skill score formulas map one-to-one with the underlying metric values and are, therefore, appropriate for inter-model comparison or intra-model assessment.