Communities across the Southwestern US are increasingly experiencing major disruptions from a changing climate and natural hazards, such as fire, flood, and drought. With this rise in hazardous events, there is a pressing need to support local education and community resilience efforts around climate change impacts. Teaching climate change can be challenging for educators, given the scientific complexity and the need to disentangle political dimensions surrounding the topic. Climate change and environmental hazards are tangible when their impacts are observed close to home. Grounding science learning in personal experiences provides an entry point for learners to the topic and makes learning relevant. In our experience, place-based learning has proven to be a powerful and transformative experience that unites learners through a shared place. Here we present results from three place-based educational programs that serve rural and tribal communities in the Southwestern US and highlight the common findings across these programs around changes in student beliefs and levels of transformation: 1) an after-school program in which students develop a short film about ways in which climate change impacts their community. The storytelling component of film making allows for culturally-sensitive engagement; 2) an in-class instructional unit focused on increasing community resilience in which students learn about local natural hazards through engaging with authentic data, scenario-based role play games and the development of their own community resilience strategy that students present to local community leaders; and 3) a library-based informal science learning program in the southwestern US where communities engage around water as a scarce and valuable resource and share their common stories around the relevance of water. All three programs share a deep grounding in shared place and culture and offer examples of effective engagement with rural communities.

On 10-11 September 2023, Storm Daniel, an exceptionally deep, early-season Mediterranean cyclone triggered an extreme flood in the city of Derna, Libya. The flood destroyed two dams that were built to protect the city, resulting in more than 5,000 casualties, making it one of the deadliest hydrometeorological disasters on record. Here, we aim to unravel (a) whether the catastrophic impact was inevitable, caused by an extremely rare storm, or was it foredoomed because of inadequate dam design, (b) how pivotal were the dam bursts in the tragic outcome, and (c) what insights this event provides for risk management and mitigation strategies elsewhere. Based on atmospheric reanalysis, satellite-based precipitation data, and rainfall-runoff modelling, we estimate the return period of both rainfall and flood to be only a few decades, meaning that the event was not as extreme as could have been implied by its disastrous consequences. Hydraulic simulations of the flood's stream power reveal that the damage caused by the collapse of the dams was approximately 20 times higher than would have been if dams were not built in the Wadi. Our methodological framework, which is based on globally available data, is applicable to risk assessment in other regions 1 as well. It underscores the importance of uncertainty-aware frequency analysis and suggests that distributed flood prevention and warning techniques should be favourable in mitigating flood risks.

Due to the coupled nature of the earth system, precipitation forecast errors at S2S lead times are caused by a combination of errors/biases from the atmosphere, ocean, ice and land across a range of spatial and temporal scales. We show that UFS precipitation errors over the U.S. at Weeks 3-4 can be directly related to biases in simulating tropical dynamics. In particular, the inability of the UFS to realistically simulate the Madden-Julian oscillation (MJO) leads to biases in the teleconnection to North America that produces these errors. When the tropics are nudged to produce an accurate representation of the MJO and other tropical disturbances, U.S. West Coast precipitation biases are substantially reduced. A clustering analysis is used to show that the greatest forecast improvements with nudging occur during warm ENSO events when MJO convection is in the Indian Ocean and about to move into the Maritime Continent. Physical mechanisms that explain the improvement in tropical-extratropical teleconnections during certain MJO and ENSO states will be discussed. We will also present future plans to combine state-of-the-art developments in machine learning with process-based diagnostics of the tropical moisture and moist static energy (MSE) budgets to understand and correct precipitation biases in coupled UFS hindcasts. In particular, we will discuss how model biases and errors in tropical variability (e.g. MJO) and associated teleconnections to midlatitudes lead to errors in U.S. precipitation on S2S timescales, and present methods to reduce these errors via post-processing on a forecast-by-forecast basis.

Time-domain analyses of seismic waveforms have revealed diverse source complexity in large earthquakes (Mw>7). However, source characteristics of small earthquakes have been studied by assuming a simple rupture pattern in the frequency domain. This study utilized high-quality seismic network data from Japan to systematically address the source complexities and radiated energies of Mw 3–7 earthquakes in the time domain. We first determined the apparent moment-rate functions (AMRFs) of the earthquakes using the empirical Green’s functions. Some of the AMRFs showed multiple peaks, suggesting complex ruptures at multiple patches. We then estimated the radiated energies (𝐸𝑅) of 1736 events having more than ten reliable AMRFs. The scaled energy (𝑒𝑅=𝐸𝑅/𝑀0) did not strongly depend on the seismic moment (𝑀0), focal mechanisms, or depth. The median value of 𝑒𝑅 was 3.7×10-5, which is comparable to those of previous studies; however, 𝑒𝑅 varied by approximately one order of magnitude among earthquakes. Additionally, we measured the source complexity based on the radiated energy enhancement factor (𝑅𝐸𝐸𝐹). The values of 𝑅𝐸𝐸𝐹 differed among earthquakes, implying diverse source complexity. The values of 𝑅𝐸𝐸𝐹 did not show strong scale dependence for Mw 3–7 earthquakes, suggesting that the source diversity of smaller earthquakes is similar to that of larger earthquakes at their representative spatial scales. Applying a simple spectral model (e.g., the ω2-source model) to complex ruptures may produce substantial estimation errors of source parameters.

Sorghum is an important cereal crop grown across the globe for its grain and biomass value. It can also efficiently use resources such as nitrogen, and multiple varieties that are nitrogen-use and light-capture efficient are constantly being developed. This study focuses on using the spectral signature of sorghum varieties to predict flowering days, which could be used as a proxy for plants’ growth/productivity and development trends, thus helping breeders make quick decisions about what varieties to move to the next stage. Multiple sorghum varieties from the sorghum association panel were planted in a replicate-design field experiment with the variable supply of nitrogen. The flowering days were monitored and recorded. The hyperspectral reflectance data were collected and used to build a sorghum flowering days predictive model. Although regression models such as partial least square have been used to predict plants’ phenotypes, the non-parametric ensemble machine learning model turned out to perform better on flowering days with an accurate model up to 5 days.

One plate to find Them How a unique surviving photograph confirmed the Hochstetter Paradigm and located the White Terrace — Eighth Wonder of the WorldA Rex Bunn“All photographs are accurate. None of them is the truth.”Richard Avedon

The Zagros orogen in the Iranian Plateau is a natural laboratory in which to investigate the tectonic evolution of the transition from oceanic subduction to continental collision. However, where slab detachment occurred and how slab detachment affects shallower continental subduction remain poorly understood. The formation mechanism of the post-collision magmatism is also unclear. Here, we construct a high-resolution Pn-wave attenuation model for the uppermost mantle beneath the Iranian Plateau and surrounding areas using a newly compiled dataset. Weak Pn attenuation delineates the Arabian Plate front near the Moho discontinuity, extending further toward the subduction direction in the northwestern and southeastern parts, possibly due to the up-bending and underplating of the Arabian lithosphere after the loss of slab pull. The correlations among the surface Miocene-Quaternary volcanism and strong Pn attenuation in the uppermost mantle suggest that asthenospheric materials escaped from slab windows and further feed the post-collision volcanoes.

The spatial scales of whistler-mode waves, determined by their generation process, propagation, and damping, are important for assessing the scaling and efficiency of wave-particle interactions affecting the dynamics of the radiation belts. We use multi-point wave measurements by two Van Allen Probes in 2013-2019 covering all MLTs at L=2-6 to investigate the spatial extent of active regions of chorus and hiss waves, their wave amplitude distribution in the source/generation region, and the scales of chorus wave packets, employing a time-domain correlation technique to the spacecraft approaches closer than 1000 km, which happened every 70 days in 2012-2018 and every 35 days in 2018-2019. The correlation of chorus wave power dynamics using is found to remain significant up to inter-spacecraft separations of 400 km to 750 km transverse to the background magnetic field direction, consistent with previous estimates of the chorus wave packet extent. Our results further suggest that the chorus source region can be slightly asymmetrical, more elongated in either the azimuthal or radial direction, which could also explain the aforementioned two different scales. An analysis of average chorus and hiss wave amplitudes at separate locations similarly shows the reveals different radial and azimuthal extents of the corresponding wave active regions, complementing previous results based on THEMIS spacecraft statistics mainly at larger L>6. Both the chorus source region scale and the chorus active region size appear smaller inside the outer radiation belt (at L< 6) than at higher L-shells.

Across the last decades, various space missions have measured thetotal solar irradiance (TSI) such as the Variability of Irradiance andGravity Oscillations (VIRGO) experiment on the Solar and HeliosphericObservatory (SOHO) starting in 1996. Since the beginning of itsrecording time, one challenge is to correct the measurements from thedegradation of the TSI sensors in space. Various groupshave proposed different methodologies to produce a continuous TSI timeseries (TSI composite) which is essential to monitor the sun activityand its influence on the Earth’s climate. However, the benchmark to test all those solutions is source of adebate in the community. Moreover, the input data for the TSI compositeare the degradation-corrected measurements provided by each individualinstrument team. Here, we propose a different approach using amachine learning and data fusion algorithm to produce automatically thedegradation-corrected TSI time series based on a small number of genericassumptions. The algorithm is applied to the VIRGO/PMO6, VIRGO/DIARADand PREMOS/PMO6 data. The time series agree between each other in termsof mean value with a difference of ~ 0.14 W/m2 (PREMOS), ~ 0.23 W/m2(VIRGO) and ~ -0.18 W/m2 (DIARAD). Finally, taking a conservative valueof 0.3 W/m2 between our different TSI products, induces a variation ofthe global mean surface temperature of ~ 0.02 K based on global climatesimulations, which is within the uncertainties of simulated global meansurface temperatures, hence not impacting significantly any climateforcing scenarios.

Evaluation of the approximate magnitude of the gross discrepancy between the volume of sediment produced on the hinterland and the volume deposited in the basin, over long time and length scales, is required to make source-to-sink sediment mass-balance calculations more accurate so that multiple sources for a single widespread stratigraphic unit, or bypass of the unit, might be more easily detected. This paper outlines a method to characterize the sources of sediments, or provenance lithotypes, according to their relative ability to produce dissolved ions, clay minerals, and unaltered residue at different levels of weathering. Estimating the relative proportion of the hinterland that is dissolved supports mass-balance analysis comparing hinterland denudation with basinal deposition, whereas estimating the relative proportion of clay (both original clay, eroded from mudstone, for example, as well as newly created clay produced by weathering of feldspar) supports potential identification of multiple sediment sources. The method is illustrated with a practical example from the Bohemian Massif and documented with an Excel workbook. This is a mineralogical approach based on mineral inventories of weathering profiles. Even if the prediction is necessarily uncertain because the mineralogical representation of the PLs are gross abstractions, the modelled transformation processes are crude cartoons, and the extent of transformation under different environmental conditions is wild speculation based on sparse examples, quantitative provenance analysis will be more accurate and more precise than it would be if dissolution and alteration were not explicitly accounted. There is ample opportunity for the community to improve the procedure!

Slow earthquakes are mainly distributed in the vicinity of seismogenic zones of megathrust earthquakes and relationships between both types of earthquakes are expected. We examined the activity of very low frequency earthquakes (VLFEs), classified as one type of slow earthquake, around Japan because they have the potential to clarify detailed spatiotemporal slip behaviors at the plate boundaries. The distribution of the shallow VLFE activity rate is heterogeneous along trench axes and exhibits an anticorrelation relationship with the spatial distribution of the interplate coupling ratio, whereas deep VLFEs are distributed only in weakly coupled areas and the spatial variation of the activity rate is small. Furthermore, VLFEs are mainly hosted by low seismic velocity anomalies. Thus, slow earthquakes can be triggered by decreased effective stress due to the high pore fluid pressure within regions with weak interplate coupling and their activity can be an indicator of interplate slip behavior.

The investigation of the Ora Ignimbrite (~275 Ma) helps further our understanding of how vast amounts (>1,000 km3) of melt are generated, stored, and erupted from the shallow crust. As the last eruptive product of a slab rollback ignimbrite flareup that lasted for 10 Ma, Ora’s glacially incised outcrops tower over 1,300 m above Bolzano, Italy. Two key outcrops, early-erupted intracaldera vitrophyre and late-erupted outflow vitrophyre, provide well-preserved, glass-bearing juvenile material. Petrographic optical and electronic (back-scattered electron) analysis was used to document the textural features of minerals and glass. Glass and mineral major-element compositions were obtained using Energy-Dispersive X-ray (EDX) analysis on a Scanning Electron Microscope (SEM). Glass with low Na/high K concentrations and A/CNK ratios > 1.1 was deemed altered. Intracaldera vitrophyre contains two distinct fiamma types: very coarse-grained, crystal-rich (VCCR) and fine-grained (FG) fiamme. Glass in VCCR fiamme is homogeneous high-silica rhyolite (76.5-77.5 wt. % SiO2; normalized anhydrous) with low K2O values (3-3.5 wt. %). The FG fiamme have a broader SiO2 range (75-78 wt. % and 72-78 wt. %) and higher K2O values (3-4.5 wt. %). Outflow vitrophyre has medium-grained (MG) and fine-grained, crystal-poor (FGCP) fiamme. The MG fiamme have homogeneous high-silica rhyolite glass (76-78 wt. % SiO2) with lower K2O (2-3 wt. %). Glass in three FGCP fiamma form compositional continua from 68-78 wt. %, 67-79 wt. %, and 72-78 wt. % SiO2, and K2O varies substantially (0.5-3.5 wt. %). These results demonstrate mingling and mixing and suggest that multiple melt-rich zones contributed to the erupting magma. We propose that at least four separate magma bodies contributed to the Ora eruption. Each one evolved independently, leading to variable amounts of magma mingling and mixing. These results illuminate the subsurface architecture of a large silicic system during the final episodes of an ignimbrite flareup.

Volcanism in continental rifts is generally observed to shift over time from the inside of the basin to its flanks and conversely, but the controls on these switches are still unclear. Here we use numerical simulations of dike propagation to test the hypothesis that the spatio-temporal evolution of rift volcanism is controlled by the crustal stresses produced during the development of the rift basin. We find that the progressive deepening of a rift is accompanied by a developing stress barrier under the basin, which deflects ascending dikes, causing an early shift of volcanism from the inside to the flanks. The intensification of the barrier due to further deepening of the basin promotes the formation of lower crustal sill-like structures that can stack under the rift, shallowing the depth of magma injection, eventually causing a late stage of in-rift axial volcanism.

Sangamon watershed is recognized as one of the most worth noting regions for water and environmental supply planning and management purposes according to its intensively management for soybean and corn production. It is also a representative area with limited geological and hydraulic measurement data, in which sustainable ground water and environmental management is essential. To better understand the hydraulic properties of the entire watershed, a multi-fidelity Gaussian Processes (Kriging) model was applied to predict the hydraulic conductivity of the upper Sangamon watershed, using previous multi-sources of field observation data (Electrical Earth Resistivity and pumping test data). The model also provided a quantification of uncertainty of the predicted values, which helps us to make reliable suggestions for the future design of hydraulic observations. The data fidelity effect to the model was discussed by comparing multi-fidelity and single-high-fidelity Kriging results. The model predicted values suggest that the accuracy of multi-fidelity Kriging depends on the locations and the distribution of both the high- and low-fidelity data. When high-fidelity data points are sparse and far away from the low-fidelity data points, the information provided from the low-fidelity data becomes extremely important, which can greatly enhance the model performance and accuracy. This study has paved the way to a more efficient parameter estimation in under-sampled sites by effectively estimating large-scale parameter maps using small-scale measurements and by applying uncertainty quantification method to a real watershed observation case. It will also draw upon and contribute to advances in Bayesian experimental design, and will optimally result in financial savings.

Phytoplankton blooms occur annually at the sea-ice edge throughout the Arctic during the spring melt period. Our study considers how these spring blooms may depend on sea-ice meltwater, focusing on the role of horizontal mixing and advection. We extend the classic Fisher reaction-diffusion equation to consider a time- and space-varying death rate that represents the role of meltwater in the system. Our results indicate that blooms peak at a characteristic distance from the ice edge where (i) meltwater is concentrated enough to stratify the upper ocean such that the phytoplankton are confined near the surface and (ii) phytoplankton have been exposed to sufficient sunlight to allow for optimized growth. The results reproduce key characteristics of a large bloom observed in Fram Strait in May 2019. Our findings support the idea that sea-ice meltwater is of central importance in setting the spatial patterns of Arctic phytoplankton blooms.

Monitoring in season crop conditions is critical when assessing the food security situation and prompting action to mitigate adverse outcomes in largely rain-fed agricultural systems. The Group of Earth Observation for Global Agricultural Monitoring (GEOGLAM) has been supporting global assessments for partners in the Agricultural market information system (AMIS) and in countries that are at risk of food insecurity with the Crop Monitor for AMIS and Crop Monitor for Early Warning respectively. Africa, and specifically Kenya is dependent on rain-fed agricultural production and with climate variability and change, timely, relevant and accurate information on crop conditions is necessary to ensure appropriate and sometimes lifesaving responses. By implementation of national crop monitors countries can synthesize and customize information to suit their reporting metrics and provide detailed sub-regional assessments in a standardized format that can inform global and regional assessments. Successful implementation and publication of The Kenya Crop Monitor Bulletin by the Kenyan Ministry of Agriculture and Irrigation is already influencing agricultural decision making. The bulletin is being used to inform internal decision making in the ministry; and through dissemination on the ministry’s website, as an important source of information for food security agencies. The report which combines earth observation data and field reports from county officers, is improving the way food security decisions are being made. Specifically, monitoring the spread of diseases and pests such as the Fall Army Worm, assessing the implications of extreme events such as floods and droughts on production, providing expected trends based on the prevailing conditions and the expected yield outlook at the end of the season. Through the bulletin, the government has also been able to assess the impact of subsidies on production and as an early warning report to prompt for mitigation and other responses.

Elastic properties of rocks in subduction zones are indicators of stress states and play important roles in earthquake nucleation. We measured elastic properties of core samples taken from Susaki area in the Shimanto accretionary complex, SW Japan, which experienced the depth condition of the seismogenic zone. We found that the samples have higher P- and S-wave velocities of 5.4-5.8 km/s and lower porosities of 1-2.5 % than other sedimentary rocks in the Shimanto accretionary complex. This may be caused by tight contacts among grains due to pressure solution processes according to microstructural observations. Comparison with seismological observations in the present Nankai Trough indicated that the samples correspond to the hanging wall rocks of the megasplay fault where now a high velocity body is resolved. We further considered velocity-porosity relation using both the samples in this study and the drilled samples from the Nankai Trough, and proposed a model explaining from low to high porosities that is applicable to shallow to deep depths toward the seismogenic zone. The obtained elastic properties provided a critical nucleation length for an earthquake along the plate boundary fault of ~0.5 m. Material and structural heterogeneities below this length scale have the potential to modulate earthquake nucleation processes and future studies on this length scale will be necessary to bridge between laboratories and natural conditions.

Following the 15 January 2022 Hunga Tonga-Hunga Ha’apai eruption, several trace gases measured by the Aura Microwave Limb Sounder displayed anomalous stratospheric values. Trajectories and radiance simulations confirm that the H2O, SO2, and HCl enhancements were injected by the eruption. In comparison with those from previous eruptions, the SO2 and HCl injections were unexceptional, although they reached higher altitudes. In contrast, the H2O injection was unprecedented in both magnitude (far exceeding any previous values in the 17-year MLS record) and altitude (penetrating into the mesosphere). We estimate the mass of H2O injected into the stratosphere to be 146+-5 Tg - ~10% of the stratospheric burden. It may take several years for the H2O plume to dissipate. This eruption could impact climate not through surface cooling due to sulfate aerosols, but rather through surface warming due to the radiative forcing from the excess stratospheric H2O.