Place-based field education is the foundation of Lamont-Doherty Earth Observatory’s Hudson River Field Station. The most effective method of engaging and connecting people with their local environment is through memorable and hands-on field investigations, with the Hudson River itself as the best educational tool. Our ‘Next Generation of Hudson River Educators’ is a six week summer internship program specifically designed to more effectively engage underrepresented minority (URM) students and communities with the Hudson River using a tiered mentoring structure. The high school interns first take a deep dive into the Hudson River to develop a better understanding of the historic to present human connection to the estuary, the dynamism of its biology, physics, chemistry, geology, and topography, and the challenges the Hudson faces, along with potential community solutions. These field investigations build an appreciation for the estuary that they can pass on to their communities. Unfortunately, the coronavirus introduced a unique challenge on place-based education making it impossible to run an in-person program. Through an innovative approach to place-based learning, we decided ‘if we couldn’t bring the students to the river, we would bring the river to the students’. The interns dedicated the first weeks to learning about the Hudson through “Virtual River” videos, games, interactive web activities, and live river demonstrations hosted down by the water. While the content is virtual, it simulates a place-based education that effectively engages students in the geosciences and increases science literacy. The interns then work in teams to create their own communication tools to share Hudson information that is captivating to a multigenerational and diverse audience. In order to offer information that is interesting and relevant to their communities, interns performed interviews to learn directly from their friends, family, and neighbors about their perceptions and existing knowledge of the Hudson. Involving the community in place-based education is crucial because residents provide key information that would be otherwise unknown to a visiting scientist or educator. They then use this information to build their communication outputs that are intended to better connect URM to their local waterways.

Social scientists have a long history of documenting disasters and natural extreme events’ behavioural response through the collection of perishable post-event data (Gruntfest 1977; Quarantelli and Dynes, 1977; Stalling, 1987; Quarantelli, 1997, 2003; Drabeck, 1999). Such empirical and theoretical foundations constitute a strong background to understand crisis responses and advance our knowledge of the drivers of human behavioural responses to fast evolving weather-related events. Outputs from this field of research show that public warning and behavioural response is a social process that takes several phases before a protective action is put in place (Mileti, 1995; Trainor et al., 2008, Parker et al., 2009, Lindell et al., 2004). These authors identified factors related to the characteristics of the hazard, the warning information characteristics, the situational and personal characteristics of the receiver and the socio-cultural context as strong determinants of the public behavioural response. In fast-moving events like flash-floods, the amount of time available to detect the threat and respond to it is so limited that protective actions often consist in dealing with contingent situations triggered by the irruption of dangerous circumstances in the middle of daily life activities and routines (Ruin et al., 2008, 2009; Terti et al., 2015). Understanding how people actually detect potentially dangerous circumstances and manage to timely adapt their routine to cope with the speed of the hazard evolution remains a challenge. Based on insights from post-event interviews, online surveys were used to quantitatively document behavioural responses associated with 3 catastrophic flash flood events that happened in southern France in 2014 and 2015. The coupled analysis of responses to these surveys with hydrometeorological parameters allows to better understand the link between the event magnitude and self-protective behaviours in the context of short-fuse weather events as flash floods. Knowledge gained from such an integrated approach is necessary for drawing lessons for the development of coupled human-natural system modeling and the prediction of the human vulnerability dynamics in short-fuse weather events.

India receives more than 80% of annual rainfall during the summer monsoon season of June – September. Extreme rainfall during summer monsoon season causes severe floods in many parts of India, annually. The floods in Kerala in 2019; Chennai during 2015 and Uttarakhand in 2013 are some of the major floods in recent years. With high population density and weaker infrastructure, even moderate precipitation extremes result in substantial loss to life and property. Thus, understanding and modeling the return levels of extreme precipitation in space and time is crucial for disaster mitigation efforts. To this end, we develop a Bayesian hierarchical model to capture the space-time variability of –summer season 3-day maximum precipitation over India. In this framework, the data layer, the precipitation extreme – i.e., seasonal maximum precipitation, at each station in each year is modeled using a generalized extreme value (GEV) distribution with temporally varying parameters, which are decomposed as linear functions of covariates. The coefficients of the covariates, in the process layer, are spatially modeled with a Gaussian multivariate process which enables capturing the spatial structure of the rainfall extremes and covariates. Suitable priors are used for the spatial model hyperparameters to complete the Bayesian formulation. With the posterior distribution of spatial fields of the GEV parameters for each year, posterior distribution of the nonstationary space–time return levels of the precipitation extremes are obtained. Climate diagnostics will be performed on the 3-day maximum precipitation field to obtain robust covariates. The model is demonstrated by application to extreme summer precipitation at 357 stations from this region. Preliminary model validation indicates that our model captures historical variability at the stations very well. Maps of return levels provide spatial and temporal variability of the risk of extreme precipitation over India that will be of great help in management and mitigation of hazards on natural resources and infrastructure.

The Sumatran fault is an arc-parallel dextral strike-slip fault that accommodates much of the right-lateral component of oblique subduction of the Indian-Australian plate beneath the Sunda plate. The 1900-km-long fault is divided into multiple segments, some of which ruptured the surface during the moderate to large historical earthquakes. The northern Sumatran fault in Aceh Province has not ruptured in the past 120 years and is considered a seismic gap. Since 2012, we have mapped the northern Sumatran fault based on the ALOS (Advanced Land Observing Satellite) PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) satellite images. We also conducted several campaigns of geologic fieldworks. The Sumatran fault in the study area is composed of the Aceh and Seulimeum segments. Both segments exhibit conspicuous tectonic landforms, including fault scarps, aligned saddles, offset streams, and linear valleys. The Aceh segment does not show clear geomorphic evidence of late Quaternary movement north of 5°27’N, and the Seulimeum segment appears to accommodate much of the right-lateral motion. We conducted a trenching survey of the Seulimeum segment at Lamtamot, where the fault offsets fluvial terraces. We identified geologic evidence of four surface-rupturing events that occurred after AD1265-1365 and before AD1892. The average recurrence interval of the surface-rupturing earthquake is calculated at 130-210 years. At least 120 years, close to the shortest estimated average recurrence interval, have passed since the last faulting event. We estimate that the probability of a massive earthquake on the northernmost Sumatran fault is high.

Unlike the radiative forcing linked to CO2 and its cumulative storage in oceans since the start of the industrial era around two centuries ago, the Sun has heated the Earth for billions of years without accumulation and dramatic temperature drift. To overcome this obviously illogical difference in evolution, we first analyze several reasons showing that the current universally adopted relationship between carbon dioxide and global warming does not respect the fundamentals of Chemistry, Physics, and Thermodynamics. A recently proposed alternative mechanism, based on these hard sciences, is briefly recalled. In this new mechanism, heat on Earth is managed by water and its solid-liquid and liquid-vapor interphases equilibria before radiative elimination in space. Today, anthropogenic heat is increasingly seen as a complement to the solar heating although it is neglected in the universally adopted consensus. Anthropogenic heat releases are generally estimated from global energy consumption. A broader list of sources is established that includes the capture of solar thermal infrared radiations by artificial installations, including those acting as greenhouses. Three qualitative scenarios are proposed in which climate change depends on whether the ratio of anthropogenic heat releases relative to solar thermal contributions remains negligible, is acceptable or becomes so large that it could shorten the time until the next ice age. Currently, global temperature and ocean level are still very low compared to those in distant past. On the other hand, ice disappearance is indisputable, particularly at the levels of glaciers, floating ice, and permafrost. These features fit the scenario in which temperature continued to fluctuate as it did during the last 8,000 years of the current Holocene interglacial plateau while local rains, winds, floodings, droughts, etc., worsen in magnitude and frequency to help ice melt and evaporation manage excess heat. Policymakers should not wait to discover that decreasing atmospheric carbon dioxide has little effect on the worsening of climate events to begin mitigating of anthropogenic heat with the help of hard sciences scientists to work on quantification. Key points • Carbon dioxide-based radiative forcing as source of global warming does not resist to critical analysis based on fundamentals of chemistry, physics and thermodynamics • Thermal properties of water, water interphase exchanges, formation of clouds and radiative elimination to space control heat supplies and climate changes since water is present on Earth • Anthropogenic heat releases should not affect much temperature and ocean levels provided they remain negligible relative to solar heat supplies, but heat-dispersing local climatic vents should increase in strength and frequency

High-resolution viscous-plastic (VP) sea ice models reproduce the narrow deformations lines observed in the Arctic sea ice, called the Linear Kinematic Features (LKFs). Recent studies showed that standard VP models overestimate the intersection angles between the LKFs when compared to observations. We investigate fracture angles in a uniaxial compression test and two different VP rheology. The first one uses an elliptical yield curve and a normal flow rule. In contrast, the second rheology uses a different elliptical plastic potential that creates a non-normal flow rule. Results show that the non-normality of the flow rule changes the angles of fracture. This new rheology can create fracture angles as low as 22º when the rheology with normal flow rule is limited to angles above 30º. A newly adapted theory – based on one developed from granular material observations – predicts the modeled fracture angles accurately. Using a non-normal flow rule takes longer to solve numerically, but allow reductions of the fracture angle to values within the range of satellite observations and decouples the angle of fracture from the shape of the yield curve.

Realistic model representation of ocean phytoplankton is important for simulating nutrient cycles and the biological carbon pump, which affects atmospheric carbon dioxide (pCO2) concentrations and, thus, climate. Until recently, most models assumed constant ratios (or stoichiometry) of phosphorous (P), nitrogen (N), silicon (Si), and carbon (C) in phytoplankton, despite observations indicating systematic variations. Here, we investigate the effects of variable stoichiometry on simulated nutrient distributions, plankton community compositions, and the C cycle in the preindustrial (PI) and glacial oceans. Using a biogeochemical model, a linearly increasing P:N relation to increasing PO4 is implemented for ordinary phytoplankton (PO), and a nonlinearly decreasing Si:N relation to increasing Fe is applied to diatoms (PDiat). C:N remains fixed. Variable P:N affects modeled community composition through enhanced PO4 availability, which increases N-fixers in the oligotrophic ocean, consistent with previous research. This increases the NO3 fertilization of PO, the NO3 inventory, and the total plankton biomass. Surface nutrients are not significantly altered. Conversely, variable Si:N shifts south the Southern Ocean’s meridional surface silicate gradient, which aligns better with observations, but depresses PDiat growth globally. In Last Glacial Maximum simulations, PO respond to more oligotrophic conditions by increasing their C:P. This strengthens the biologically mediated C storage such that dissolved organic (inorganic) C inventories increase by 34-40 (38-50) Pg C and 0.7-1.2 Pg yr-1 more particulate C is exported into the interior ocean. Thus, an additional 13-14 ppm of pCO2 difference from PI levels results, improving model agreement with glacial observations.

The Distributed Hydrology Soil Vegetation Model (DHSVM) code was parallelized for distributed memory computers using the Global Arrays (GA) programming model. To analyze parallel performance, DHSVM was used to simulate the hydrology in two river basins of significant size located in the northwest continental United States and southwest Canada at 90~m resolution: the (1) Clearwater (25,000~km) and (2) Columbia (668,000~km) River basins. Meteorological forcing applied to both basins was dynamically down-scaled from a regional reanalysis using the Weather Research and Forecasting (WRF) model and read into DHSVM as 2D maps for each time step. Parallel code speedup was significant. Run times for 1-year simulations were reduced by an order of magnitude for both test basins. A maximum parallel speedup of 105 was attained with 480 processors while simulating the Columbia River basin. Speedup was limited by input-dominated tasks, particularly the input of meteorological forcing data.

The relationship between aerosol concentration and lightning is complex. Aerosols can act as cloud condensation nuclei, contributing to the formation of cloud droplets, cloud electrification and lightning, while high concentrations of aerosols can contribute to a decrease in lightning due to radiative effects. Meteorology plays a dominant role in lightning activity, distorting the effect of aerosols. More measurements, as presented here, are needed to establish the complex relationship between aerosols and lightning. The Po Valley, a heavily industrialized region, was highly affected by the COVID-19 lockdown. The reduction of non-essential activities and mobility coincided with a significant drop in pollutant concentrations and lightning. We investigate the relationship between lightning, meteorology and aerosols. We find that the variation in lightning during the lockdown cannot be fully attributed to meteorology. $\sim$60\% of the observed decrease can be attributed to meteorology, and $\sim$40\% to the reduction in aerosol emissions.

We show that forward simulations of global CO2 using an atmospheric transport model (ATM) at 0.5°×0.625° and 4°×5° resolutions differ significantly in vertical and meridional distribution. Comparing two observing simulation system experiments at 4°×5° resolution that assimilate pseudo observations sampled from the two forward simulations, we isolated the impact of coarse-resolution ATM error on regional flux estimates that a significant amount of annual carbon uptake from the ocean and tropics is improperly redistributed to the land and extratropics, respectively. In addition, this error leads to an underestimated seasonal amplitude in the northern extratropical land and a reversed seasonal phase in the northern extratropical ocean. The reversed seasonal phase has also been shown in a real data assimilation experiment and state-of-the-art inversions, suggesting that ocean glint retrieval error may not be as significant as previously thought and reasonable ocean flux estimates depend strongly on the accuracy of ATM.

The United Nations Agenda 2030 and Sendai Framework, as well as African Union's Agenda 2063, are targeted at human peace and prosperity amidst environmental and economic sustainability. These frameworks contain goals for the earth's protection and human poverty/disaster risk reduction. The foremost priority of the Sendai Framework for Disaster Risk Reduction is the increased understanding of disaster risk and strengthening its governance and management. Three overarching questions warrant this study: what are the important predictors of disaster risk in the vulnerable continent of Africa? How does disaster risk relate to climate change literacy and people's beliefs in Africa? Do national action plans respond appropriately to key factors reflecting Africa's disaster risk? This study uses the climate change literacy and belief data from the Afrobarometer and disaster risk data from the Index for Risk Management (INFORM) of the European Commission. Using disaster risk index as the dependent variable and 30 independent variables, the important predictors contributing to disaster risk in all African countries were identified using random forest machine learning models. Essential variables in the model include projected conflict risk, current highly violent conflict intensity, uprooted people, other vulnerable groups, governance, physical infrastructure and access to health care, among others. Also, The higher the percentage of African countries' population that is climate literate, the lower the disaster risk. Conversely, the higher the climate change literacy of the population, the higher the percentage of people who believe that people can do little about climate change. Furthermore, 25 policies of countries with very high disaster risk were analysed. Within these selected policies, concepts related to violent conflicts were the least included, while those about vulnerability factors were the most included. Policies explored included more vulnerability concepts and much fewer hazard (violent conflict) concepts indicating the least responsiveness to hazards. The study provides a deeper understanding of disaster risk in Africa by showing essential factors and offers insight into disaster risk governance in line with the Sendai Framework.

The timely understanding of flood extent is critical information for emergency managers during disaster response. Search and rescue operations require a boundary to reduce fruitless efforts and to prioritize critical or limited resources. However, high-resolution aerial imagery is often unavailable or lacks the necessary geographic extent, making it difficult to obtain real-time information about where flooding is occurring. Volunteered geographic information (VGI) is a subset of crowdsourcing and can be used to disseminate spatially relevant information or request help. In this study, we present a novel approach to map the extent of urban flooding in Harris County, TX during Hurricane Harvey (August 25-31, 2017) and identify where people were most likely to need immediate emergency assistance based on a subset of crowdsourced SOS requests. Using the machine learning software Maximum Entropy (MaxEnt), we predict the spatial extent of flooding based on several physical and socio-economic characteristics. We compare the results against two alternative flood datasets available after Hurricane Harvey (i.e., Copernicus satellite imagery and fluvial flood depths estimated by FEMA), and we validate the performance of the model using a 15% subset of the rescue requests and Houston 311 flood calls. We find that the model predicts a much larger area of flooding than was shown by either Copernicus or FEMA when compared against the locations of rescue requests, and that it performs well using both a subset of rescue requests (AUC 0.917) and 311 calls (AUC 0.929).

The Hellenic arc, where the African (Nubian) slab subducts beneath the Aegean and Anatolian microplates, has emerged as a type-locality for understanding subduction dynamics, including slab tear, slab fragments, drips, and transfer zones. Based on field evidence and geophysical, tectonics, and geochemical studies, it has been recognized that the subducting African slab is a primary driver for extension in the Aegean and Anatolian microplates and plays a significant role in accommodating present-day westward extrusion of the Anatolian microplate. Thus, understanding the Hellenic arc subduction zone initiation (SZI) age is critical in deciphering ancient mantle flow, how plate tectonics is maintained, and the mechanisms involved in triggering the onset of subduction. The SZI for the Hellenic arc has two disparate ages based on different lines of evidence. A Late Cenozoic (Eocene-Pliocene) SZI is proposed using the analysis of topography combined with estimates of slab age and depth, paleomagnetism, the timing of metamorphism, and volcanic activity, and timing of sedimentation within its accretionary wedge, the Mediterranean Ridge. This age follows an induced-transference SZI model, where a new subduction zone initiates following the jamming of an older subduction zone by buoyant crust due to regional compression, uplift, and underthrusting. A Late Cretaceous-Jurassic SZI age has also been proposed using reconstructions of images of subducted slabs seen using tomography and timing of obducted ophiolite fragments thought to be related to the system. In this case, the induced-transference SZI model fails, and a single subduction zone persists. As a result, continental lithospheric fragments and the ancient oceans between them become incorporated into the overall system without creating a new subduction zone. The presence of a long-lived subduction zone has implications for understanding Earth’s mantle dynamics and how plate tectonics operates. This paper describes and summarizes the evidence for both models in the Aegean-Western Anatolia region.

Freshwater is limited in the semi-arid Arequipa region in Southern Peru that is home to more than 1.3 million people, agricultural and industrial sectors. To address water demand, eight reservoirs and more than 200 km of water diversion tunnels and canals have been implemented in the Quilca and Camaná river basins, resulting in severely modified hydrology and interconnection of the two basins. The Soil and Water Assessment Tool (SWAT) was used to simulate the current hydrological status and potential alternative management scenarios for the two interconnected basins. Simulation challenges include scarcity of data on soil and land cover to run SWAT, which was addressed by developing publicly available regional soil and land cover databases. A representation of water infrastructure required a complex model structure incorporating point sources to represent water transfers and reservoir outflows and water withdrawals at 17 locations. The developed model is used to provide a comprehensive understanding of water availability in the region under current and alternate scenarios for water regulation. The impact of current water infrastructure on minimum streamflow is explored in the Quilca and Camaná river basins. Results were shared with the local water authorities and the public via an online tool called HidroAQP to support water allocation and related water resource decisions.

Velocity distribution functions (VDFs) measured by the Magnetospheric Multiscale (MMS) mission are complex 3D datasets that can be represented as a superposition of multiple beams (M. V. Goldman et al., 2020). A recent work (Dupuis et al., 2020) proposed the use of the Gaussian Mixture Model (GMM). Here we investigate the approach by considering first synthetic distributions made by artificially creating beams of either Maxwellian distributions or kappa distributions with varying power law index. By varying the inter-beam average difference and the beam standard deviation we evaluate the ability of the GMM in recognizing correctly the beam. We then apply the method systematically to MMS data in the tail and in the dayside. In this case, the data need preparation before being processed by the GMM to account for the specifics of the instrument and in particular the lack of data at low energy and to account for the noise in the counts. The conclusion of the analysis is that the GMM is capable of detecting the presence of multiple beams when their distinction is significant. The GMM can define reliably the complexity of a measured dataset in terms of the number of optimal beams provided by information theory criteria. Visual inspection confirms this automatic definition of complexity.

New information is needed about the potential sources and pathways of trans-Atlantic dust plumes. Such knowledge has important implications for the long-distance transport and survivability of microorganisms. Forward trajectories of trans-Atlantic dust plumes were studied over a 14-year period, between 2008 and 2021 (n =>500,000 trajectories). Two major dust transport patterns emerged from these analyses. First, summer trajectories (June – August) that arrive in the southeastern regions of the United States and the Caribbean basin and travel above the marine boundary layer at an average altitude of 1,600 m. Second, winter trajectories (December – February) that arrive in the Amazon basin and travel within the boundary layer at an average altitude of 660 m. Ambient meteorological conditions such as solar radiation and relative humidity along dust trajectories suggest a more suitable condition for the survivability of microorganisms reaching the Amazon during the winter with a lower mean solar radiation flux of 294 W m-2 and mean relative humidity levels at around 61% as compared to averages of 370 W m-2 solar radiation and 45% relative humidity for summer trajectories intruding the Caribbean basin. Nevertheless, 14% of winter trajectories (4,664 out of 32,352) reaching the Amazon basin face intense precipitation of higher than 30 mm and get potentially removed as compared to 8% of trajectories (2,540 out of 31,826) intruding the Caribbean basin during the summer. Collectively, our results have important implications for the survivability of microorganisms in trans-Atlantic dust plumes and their potential for major incursion events at receptor regions.

Using template matching and GPS data, we investigate the evolution of seismicity and observable deformation in Central Apennines. Seismicity appears more persistent at the base of the seismogenic layer than in the shallower crust. Diffuse activity is reported on segments at depth, alternating along strike with apparent quiescence on segments that experienced one or more Mw6+ earthquakes in 1997, 2009 and 2016. Central Apennines are likely underlain by a sizeable shear zone with areas of diffuse seismicity bounding shallow normal faults where Mw6+ earthquakes occurred. The deformation observed at the surface seems to follow the seismicity variations at the base of seismogenic layer along the Apenninic chain. Principal and independent component analysis of GPS data exhibits a transient when the 2016 foreshock sequence starts. This transient propagated northward from the Campotosto fault up to the Alto Tiberina fault system and has likely loaded the Mw6+ 2016 earthquake sequence.

Purpose: To propose a clean, maintenance-free, free of charge, uninterrupted and permanent energy source solution for mankind. Methods: Based on the all known fact that solar energy is relatively unlimited to create an idea of how to harness such unlimited energy on earth. Results: A possible solution has been found to realize such goal. Conclusion: We can build such solution and benefit all mankind for thousands of years because all the technologies needed are available at present time.