We develop a climatological model for the Northern Hemisphere based on a long-term dataset (2010-2021) of the rate of change of the total electron content (TEC) index (ROTI) maps from the International GNSS Service (IGS). The IGS ROTI maps are daily averaged in magnetic latitude and local time coordinates. To develop a climatological model, the ROTI maps are decomposed into a few base functions and coefficients using the empirical orthogonal function (EOF) method. The EOF method converges very quickly, and the first four EOFs reflect the majority (96%) of the total data variability. Furthermore, different EOF components can reflect different drivers of ionospheric irregularities. The first EOF reflects the averaged ROTI activity and the impact of the solar radiation and geomagnetic activity; the 2nd EOF reflects the impact of the interplanetary magnetic field (IMF) Bz and electric field; the 3rd and 4th EOFs reflect the dawn-dusk asymmetry around the auroral oval and polar cap, and they can be related to the IMF By. To build an empirical model, we fit the EOF coefficients using helio-geophysical indices from four different categories (solar activity; geomagnetic indices; IMF; the solar wind coupling function). The final EOF model is dependent on seven selected indices (F10.7P, Kp, Dst, Bt, By, Bz and Ekl). The statistical data-model comparisons show satisfactory results with a good correlation coefficient. However, the model cannot capture the significant expansion of the dayside ROTI activity during strong geomagnetic storms. Future effort is needed to provide corrections to the model for severe storms.

Evidence for asymmetric plate growth, variable crustal thickness, and non-uniform spreading rates is ubiquitous on the seafloor. However, conventional numerical modeling approaches are often incapable of explaining the non-uniform growth of oceanic lithosphere. Noting that plate-boundary forces can dynamically determine plate speed by finding a balance against the resistance to extension at ridge axes, we introduce plate-boundary tractions instead of kinematics to drive plate motions in numerical models for mid-ocean ridges. We construct such models using FLAC, an open-source finite element code for geodynamic simulations. Our preliminary two-dimensional models for slow-spreading ridges have constant tractions on the boundary far from the ridge. Applying periodic variations in thermal states or magmatic accretion rates at the spreading center, we monitor how plate speed, crustal thickness, faulting styles and fault offset change in time. We also compare the model results to the temporal variations found in the bathymetry and seismic reflection data along a 1500 km-long transect across the slow-spreading South Atlantic seafloor, which were acquired in the 2017 CREST (Crustal Reflectivity Experiment Southern Transect) expedition.

An increased frequency of droughts due to anthropogenic climate change can lead to considerable stress for soil microorganisms and their functioning within northern peatlands. A better understanding of the diversity and abundance of methane producing and reducing taxa, and their functional genes, can help predict the functional potential of peatlands and how the microorganisms respond to disturbances such as drought. In order to address knowledge gaps in the understanding of how functional genetic diversity shifts under drought conditions, we investigated a hemi boreal mire in Southern Sweden. Environmental parameters, including soil and air temperature, precipitation and water table depth, as well as methane flux data were collected during the summer of 2017 under typical growing conditions, and in 2018 during a drought. In addition, the diversity and composition of genes encoding for methane metabolism were determined using the captured metagenomics technique. During drought we observed a substantial increase in air and soil temperature, reduced precipitation, and a lower water table depth. Taxonomic and functional gene composition significantly changed during the drought, while diversity indices, such as alpha and beta diversity, remained similar. These results indicate that methane producing and reducing microbial communities, and their functional genes, displayed a resilience to drought with specific genera having the ability to outcompete others under stress. Furthermore, our results show that although methane emissions are substantially reduced during drought, we can expect to see a shift towards more resilient methanogens and methanotrophs under future climate conditions.

Climate change tends to be addressed by accurate statistics and modelling, but it is generally perceived abstractly, being considered a distant psychological risk in which impacts and effects are spatially and temporally differentiated. In other words, people’s attitude towards climate change is that it will impact other individuals and communities that are geographically, temporally, and even generationally removed from themselves. However, due to the hybrid nature of climate change as both a physical and social phenomenon, individuals are not ‘blank slates’ receiving information and facing climate change. Many have argued that deepening personal experience could be the first step for reducing individual and community psychological distance of climate change while increasing the potential for behavior change. Considering that agriculture affects and is affected by climate change in several ways, farmers can provide first-hand observations of climate change impacts and testing different adaptation options. This contribution provides an overview of the intellectual structure of farmers’ behavior on climate change awareness, perceived risks, and adaptation capacity. A portfolio of 108 survey studies published in the last decade was selected for a comprehensive analysis. Exploratory variables such as farmers’ socio-demographic characteristics, level of climate change awareness, major perceived impacts, and adaptation measures, parameters, and barriers have been reported. In addition to the bibliographic analysis, the first results from a survey conducted in different irrigation systems in northern Italy will be tested to identify(dis)similar trends in farmers’ behavior. The identification of not only farmers’ behavior gaps but also their causing reasons will contribute to focus attention on most concerning issues and provide more accurate bottom-up knowledge to managers and decision-makers.

Traditionally, astronomers have separated giant planets from brown dwarfs based on the object’s mass. Objects more massive than 13 Jupiter masses but less massive than 80 Jupiter masses are considered to be brown dwarfs. However, in detail, the lower mass threshold is 11 to 16 Jupiter masses depending on the metallicity of the object. This betrays how arbitrary a purely mass-based distinction between planets and brown dwarfs is. Instead, we take a critical look at the population of brown dwarfs for which we have the most fundamental information: transiting brown dwarfs. Transiting brown dwarfs provide us their mass, radius, and sometimes age, which makes them useful for directly testing substellar evolutionary models. Through a better understanding of how well these models describe the population of transiting brown dwarfs, we will develop a better definition of what makes a brown dwarf different than a giant planet: its formation mechanism. It is certainly true that in the mass range spanning between giant planets and low-mass stars that the dominant formation mechanism must change in a significant way. If we can determine which mass or distribution of masses that this change occurs at, then we will have a more physical way to distinguish planets from brown dwarfs. This poster provides an overview of the substellar mass-radius diagram and highlights several of the recent discoveries facilitated by the TESS mission.

The field is not always easy for plant phenotyping using conventional phenotyping platforms due to the limited accessibility and regulated aviation area. Smartphone-triggered ground images were collected on wheat field that has a limited access to monitor growth conditions of four wheat varieties, Shinyoung (SY), Joseong (JS), Taewoo (TW), and Cheongwoo (CW). For field mapping during the growing season, six sets of the raw RGB images were acquired by a smartphone camera in an oblique view angle and processed to transform into nadir view images. A series of algorithms were developed to process the skewed tile images to straighten into the nadir images, align the deskewed images, and stitch them into a field image by detecting crop rows using Hough Transformation. Open-source software, iStitch, was developed to automate the algorithms in a batch process. Plot-level metrics were extracted to analyze plant growth of the wheat varieties using a gridding method for vegetation and leaf area indexes. The processed images resulted in the successful transformation and consistency of algorithms on image alignment and stitching. Plot-level analysis indicated that SY variety performed superior to the other varieties in plant quality and quantity and significantly different from TW variety in canopy coverage. The proposed approach of the stitching and gridding was applied on the skewed images acquired by a smartphone camera but can be directly used for other applications of plant phenotyping on images acquired by a camera on a mobile platform or a grid of stationary cameras in greenhouse or outdoor fields.

Fram Strait is the primary pathway for sea ice export from the Arctic Ocean, yet estimates of volume export are constrained by observations of ice thickness and drift. Using a new year-round CryoSat-2 ice thickness product we determine an average annual export of 1,712 ± 452 km^3 from 2011-2022. 15% of the Arctic Oceans sea ice volume is exported annually, while 3.2% of the volume lost during the melt season is exported. Comparing high- and low-resolution ice drift products reveals the latter underestimate export by 30%. Comparing volume export between 82°N and 79°N reveals a high melt rate of 1 cm d-1, reducing export by 53%. September sea ice volume declines by 286 km^3 for every 100 km^3 exported during summer, highlighting how export amplifies the ice-albedo feedback. Our estimates of volume export provide new insight into Fram Straits role as a sea ice sink and freshwater source.

Accurate mapping of urban infrastructure, specifically buildings, and extent is a high priority in addressing environmental and socioeconomic problems. Importantly, such mapping must account for the three-dimensionality (3D) of the urban environment that has traditionally been lacking (e.g., land cover and land use change—LCLUC—analyses often utilize two-dimensional satellite imagery). Undoubtedly, considerable development and change in urban areas takes place in the vertical dimension. Light detection and ranging (lidar) data provide the ability to map in 3D, but systematic data coverage both spatially and temporally is direly insufficient globally. Previous works have successfully implemented spaceborne radar data such as 1-km QuikSCAT data in lieu of lidar data to assess 3D urban build-up. Higher spatial resolution is required, though, to examine urban characteristics in detail. In this study, we test whether Sentinel-1 C-band Synthetic Aperture Radar (SAR) data can monitor 3D urban build-up in high spatial resolution (i.e. 40-m) in Detroit, Michigan, USA, 2015. Findings confirm, through comparison with aggregated 1-m lidar data, the utility of high spatial resolution SAR data for examination of urban built-up volume. Correlation and regression results show a strong linear relationship between SAR backscatter and lidar volume citywide. Moreover, SAR data, unlike coarser resolution radar data, can detect 3D anomalies over time (e.g., new building construction, building demolitions, etc.) further attesting to their utility for comprehensive 3D urban analyses a lower cost and higher repeatability over a much more extensive coverage compared to lidar data.

This study examines how greenhouse gas (GHG) production and organic matter (OM) transformations in coastal wetland soils vary with the availability of oxygen and other terminal electron acceptors. We also evaluated how OM and redox-sensitive species varied across different size fractions: particulates (0.45-1μm), fine colloids (0.1-0.45μm), and nano particulates plus truly soluble (<0.1μm; NP+S) during 21-day aerobic and anaerobic slurry incubations. Soils were collected from the center of a freshwater coastal wetland (FW-C) in Lake Erie, the upland-wetland edge of the same wetland (FW-E), and the center of a saline coastal wetland (SW-C) in Washington state. Anaerobic methane production for FW-E soils were 47 and 27,537 times greater than FW-C and SW-C soils, respectively. High particulate Fe2+ and dissolved sulfate concentrations in FW-C and SW-C soils suggest that iron and/or sulfate reduction inhibited methanogenesis. Aerobic CO2 production was highest for both freshwater soils, which had a higher proportion of OM in the NP+S fraction (64±28% and 70±10% for FW-C and FW-E, respectively) and C:N ratios reflective of microbial detritus (1.7±0.2 and 1.4±0.3 for FW-E and FW-C, respectively) compared to SW-C, which had a higher fraction of particulate (58±9%) and fine colloidal (19±7%) OM and C:N ratios reflective of vegetation detritus (11.2 ± 0.5). The variability in GHG production and shifts in OM size fractionation and composition observed across freshwater and saline soils collected within individual and across different sites reinforce the high spatial variability in the processes controlling OM stability, mobility, and bioavailability in coastal wetland soils.

1. Freshwater phytoplankton communities are currently experiencing multiple global change stressors, including increasing frequency and intensity of storms. An important mechanism by which storms affect lake and reservoir phytoplankton is by altering the water column’s thermal structure (e.g., changes to thermocline depth). However, little is known about the effects of intermittent thermocline deepening on phytoplankton community vertical distribution and composition or the consistency of phytoplankton responses to varying frequency of these disturbances over multiple years. 2. We conducted whole-ecosystem thermocline deepening manipulations in a small reservoir. We used an epilimnetic mixing system to experimentally deepen the thermocline in two summers, simulating potential responses to storms, and did not manipulate thermocline depth in two succeeding summers. We collected weekly depth profiles of water temperature, light, nutrients, and phytoplankton biomass as well as discrete samples to assess phytoplankton community composition. We then used time-series analysis and multivariate ordination to assess the effects of intermittent thermocline deepening due to both our experimental manipulations and naturally-occurring storms on phytoplankton community structure. 3. We observed inter-annual and intra-annual variability in phytoplankton community response to thermocline deepening. We found that peak phytoplankton biomass was significantly deeper in years with a higher frequency of thermocline deepening events (i.e., years with both manipulations and natural storms) due to weaker thermal stratification and deeper depth distributions of soluble reactive phosphorus. Furthermore, we found that the depth of peak phytoplankton biomass was linked to phytoplankton community composition, with certain taxa being associated with deep or shallow biomass peaks, often according to functional traits such as optimal growth temperature, mixotrophy, and low-light tolerance. 4. Our results demonstrate that abrupt thermocline deepening due to water column mixing affects both phytoplankton depth distribution and community structure via alteration of physical and chemical gradients. In addition, our work supports previous research that phytoplankton depth distribution and community composition interact at inter-annual and intra-annual timescales. 5. Variability in the inter-annual and intra-annual responses of phytoplankton to abrupt thermocline deepening indicates that antecedent conditions and the seasonal timing of surface water mixing may mediate these responses. Our findings emphasize that phytoplankton depth distributions are sensitive to global change stressors and effects on depth distributions should be taken into account when predicting phytoplankton responses to increased storms under global change.

In support of the environmental justice (EJ) movement, researchers, activists, and policymakers often use environmental data to document evidence of the unequal distribution of environmental burdens and benefits along lines of race, class, and other socioeconomic characteristics. Numerous limitations, such as spatial or temporal discontinuities, exist with commonly used data measurement techniques, which include ground monitoring and federal screening tools. Satellite data is well poised to address these gaps in EJ measurement and monitoring; however, little is known about how satellite data has advanced findings in EJ or can help to promote EJ through interventions. Thus, this scoping review aims to 1) explore trends in study design, topics, geographic scope, and satellite datasets used to research EJ, 2) synthesize findings from studies that use satellite data to characterize disparities and inequities across socio-demographic groups for various environmental categories, and 3) capture how satellite data are relevant to policy and real-world impact. Following PRISMA extension guidelines for scoping reviews, we retrieved 81 articles that applied satellite data for EJ research in the United States from 2000 to 2022. The majority of the studies leveraged the technical advantages of satellite data to identify socio-demographic disparities in exposure to environmental risk factors, such as air pollution, and access to environmental benefits, such as green space, at wider coverage and with greater precision than previously possible. These disparities in exposure and access are associated with health outcomes such as increased cardiovascular and respiratory diseases, mental illness, and mortality. Research using satellite data to illuminate EJ concerns can contribute to efforts to mitigate environmental inequalities and reduce health disparities. Satellite data for EJ research can therefore support targeted interventions or influence planning and policy changes, but significant work remains to facilitate the application of satellite data for policy and community impact.

Debate abounds regarding the composition of the deep (middle + lower) continental crust. Studies of medium and high grade metamorphic lithologies guide us but encompass mafic (< 52 wt.%) to felsic (> 68 wt.%) compositions. This study presents a global compilation of geochemical data on amphibolite (n = 6500), granulite (n = 4000), and eclogite (n = 200) facies lithologies and quantifies systematic trends, uncertainties, and sources of bias in the deep crust sampling. The continental crust’s Daly Gap is well documented in amphibolite and most granulite facies lithologies, with eclogite facies lithologies and granulite facies xenoliths having mostly mafic compositions. Al2O3, Lu, and Yb vary little from the top to bottom of the crust. In contrast, SiO2 and incompatible elements show a wider range of abundances. Because of oversampling of mafic lithologies, our predictions are a lower bound on middle crustal composition. The distinction between granulite facies terrains (intermediate SiO2, high heat production, high incompatibles) or granulite facies xenoliths (low SiO2, low heat production, low incompatibles) as being the best analogs of the deep crust remains disputable. We incorporated both, along with amphibolite facies lithologies, to define a deep crustal composition that approaches 57.6 wt.% SiO2. This number, however, represents a compositional middle ground, as seismological studies indicate a general increase in density and seismic velocity with increasing depth. Future studies should analyze more closely the depth dependent trends in deep crustal composition so that we may develop compositional models that are not limited to a three-layer crust.

The reproducibility crisis was sparked five years ago by a Nature survey that revealed most researchers have tried and failed to reproduce another scientist’s experiments (Baker, 2016). Although the severity of the crisis is still being debated, it has spurred researchers to include reproducibility and open science practices in their work. To that end, the Python in Heliophysics Community (PyHC) encourages members of the heliophysics community to create “executable papers,” which are interactive pieces of software that combine text, data, and code to enable readers to reproduce every step taken to arrive at a publication’s conclusions. We describe the development of an executable paper—in this case, one centered around magnetopause boundary crossings in satellite data—our coordination efforts between scientists and software developers, and the current technology that makes this possible. We aim to promote this novel paper format and be an example to the heliophysics community of how scientists and software developers can work together to produce research that is transparent and reproducible.

Quantifying the effect of anthropogenic land use change on dust emission is a contentious issue. In this research, 1508 dust point sources were detected in the Southern High Plains and Chihuahuan Desert regions of the United States for 2001-2016, encompassing a period of extreme drought. These points were subjected to quantitative and spatio-temporal analysis. Point pattern analysis showed a significant cluster of these points in West Texas (Nearest Neighbor Ratio = 0.33, р < 0.001) where cultivated lands and grasslands are dominant land cover. Spatial observation suggests that the geographic center of dust points in these regions shifts away from bare soil and shrublands toward grasslands and cultivated lands as drought level increases, while it shifts away from grasslands and cultivated lands towards bare soil and shrublands in cases of no drought. Chi-square test captured a significant association between land use type and drought level on dust emission (χ2 (6) = 47.33, р < 0.001). However, Cramer’s V value (0.13, р < 0.001) indicates that the association captured by the chi-square is weak, suggesting that other factors, perhaps meteorological variables, are at play in the spatial distribution of dust sources in this region. The proportion of dust points differs significantly during severe/exceptional droughts versus no drought or abnormally dry/moderate drought in both cultivated lands and grasslands. The proportion of dust points in bare lands and shrublands, however, did not significantly change between no drought and severe-exceptional drought. These results suggest anthropogenic land use in southwestern U.S. is significantly associated with drought in terms of dust emission. Human activity amplifies of the effects of drought by increasing soil erodibility; thus, adopting land management practices to resist wind erosion is crucial. Further investigations on a global scale should provide more information on this association.

Pore-pressure depletion in sandstone reservoirs is well known to cause both elastic and inelastic compaction, often resulting in notable surface subsidence and induced seismicity. Recent studies indicate that in such cases inelastic strain, which is often neglected in geomechanical models, represents a significant proportion of the total strain throughout reservoir production. While there has been considerable effort to quantify the proportion of continuous inelastic deformation from the mechanical response of laboratory samples, there has been little focus to date on the associated acoustic response throughout compaction. With this in mind, we employ three coda-wave based processing methods for the active source monitoring of ultrasonic velocity, scattering power, and intrinsic/scattering attenuation during the pore-pressure depletion of core samples from the Slochteren sandstone reservoir in the Groningen gas field (the Netherlands). Our results corroborate previous studies suggesting that initially, inelastic deformation occurs primarily along intergranular boundaries, with intergranular cracking developing towards the end of depletion and particularly for the highest porosity samples. Furthermore, analysis of Biot type intrinsic attenuation indicates that this compaction occurs in several stages of predominately intergranular closure, transitioning into predominantly intergranular slip/cracking, and eventually porosity-dependent intragranular cracking. We demonstrate how this segmentation of pore-pressure driven compaction can be used to characterise differences in sample properties, and monitor the evolution of microstructural inelastic deformation throughout depletion. We further discuss the feasibility of in/cross-borehole monitoring of reservoir compaction, for both improved geo-mechanical modelling and early warning detection of induced seismicity.

From the word go till nowadays, laboratory biologists have been focused mostly on a few practical biological models, which largely determined and narrowed down our modern vision of diverse complex physiological cellular and molecular bioprocesses. The choice of model organism is an important issue in experimental biology, particularly, in space exploration biomedical science. Largely unknown non-classical aquatic model organisms will be advantageous for further developments on the path of humanity into space. Selected perspective hydrobiont models based on old almost-forgotten and new literature data are discussed that could be of future use in the expanding biomedical space science.

The upper-level jet stream impacts surface-level trace gas variability, yet the cause of this relationship remains unclear. We investigate the mechanism(s) responsible for the relationship using idealized tracers with different source regions within a chemical transport model. All tracers’ daily variabilities are correlated with the meridional position of the jet in the mid-latitudes, but tracers emitted south (north) of the jet increase (decrease) in the mid-latitudes when the jet is shifted poleward. The jet stream regulates the near-surface meridional wind, and this coupling together with the meridional tracer gradient robustly predicts where the jet stream and tracers are in and out of phase. Our study elucidates a major driver of trace gas variability and links it to the location of the jet stream and emissions. These results are useful for understanding changes in trace gas variability if the jet stream’s position or major emission source regions change in the future.

We present an O(n) complexity and implicit algorithm for the two-dimensional solution of the Stream Power Incision Model (SPIM) enriched by a discharge threshold term and taking into account variability in rainfall and thus discharge. The algorithm is based on the formulation developed by Deal et al (2018) and the generalization of the FastScape algorithm \cite{BraunWillett2013}where the slope is approximated by first-order accurate finite difference. We consider a variety of discharge thresholds that vary in their dependence on channel slope. The algorithm requires finding the root of a non-linear equation using a Newton-Raphson iterative scheme. We show that the convergence of this scheme is unconditional, except for a narrow range of model parameters where the threshold increases with the slope and for low discharge variability. We also show that the rate of convergence of the iterative scheme is directly proportional to the slope exponent n in the SPIM. We compare the algorithm to analytical solutions and to numerical solutions obtained using a higher-order finite difference scheme. We show that the accuracy of the FastScape algorithm and its generalization presented here is comparable to other schemes for values of n>1. We also confirm that the FastScape algorithm and its generalization to variable discharge+threshold conditions does not need to satisfy the CFL condition and provides an accurate solution for both small and very long time steps. We finally use the new algorithm to quantify how the existence of an erosional threshold strongly affects the length of the post-orogenic decay of mountain belts.