The Clouds and the Earth’s Radiant Energy System (CERES) project monitors Earth’s long-term energy balance and produces data products which have improved our understanding of the role clouds and aerosols play in that balance. Cloud property retrievals from the Moderate Resolution Imaging Spectroradiometer (MODIS) and the Visible Infrared Imaging Radiometer Suite (VIIRS) are a major component of many of these data products. It is important for cloud property retrievals to be consistent over the course of the record so that artificial discontinuities are not introduced into the Earth radiation budget record. In practice, the MODIS and VIIRS instruments have different characteristics and different sets of spectral bands so deriving completely consistent cloud properties from the two instruments is a complex task. This paper investigates differences in the cloud properties retrieved from MODIS and VIIRS using the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) instrument as an independent validation source. Particular consideration is given to CALIOP’s sensitivity to optically thin clouds and the effect these clouds have on the retrieved cloud properties, especially cloud thermodynamic phase. Differences in cloud phase and cloud optical depth from MODIS and VIIRS are characterized by different cloud types including multi-layer scenarios. Characterizing these retrieval differences will help understand and mitigate artifacts in the long-term record.

The year 2020 will mark the onset of Paris Agreement, whose main aim is to limit global warming to 2° C. This has set a limit on the amount of Greenhouse gases the world can still emit in order to be safe. Now, different principles (like inertia, equity, blended) for allocating a justified share of carbon emissions to the countries are being actively discussed in research communities. Current study determines the global carbon share of India using these principles. Future cumulative emission quota of India starting from the year 2015 and from 2020 to meet the warming limits of 2°C and 3°C associated with a 66% and 50% probability has been calculated. Methods proposed in previous studies are referred. Results show that the share for India based on the principle of inertia and equity are 9.58% and 16.03% respectively. While the principle that accounts historical accountability (called inclusive sharing) is the most promising one; ranging from 17.98 to 22.46%. The results with inclusive sharing are more than double that of inertia sharing and significantly higher than equity sharing. With these results, we advocate that neither the principle of inertia nor equity alone can be ascertained as fully justified criteria for countries like India in determining the future emissions. On the other hand, ‘inclusive sharing’ that accounts for historical accountability of the country is suggested as a more justified principle for carbon sharing. Additionally, this outcome also questions the general assumption that per capita based emission allocation method is most advantageous for a highly populated country. In the end, we conclude by defending the factor of historical accountability for rationalizing the emission rights of countries that represent high share of world population and significantly low per capita emissions. This study finds importance in climate science research in determining how rational are the different sharing principles and how they can affect the development of different countries in the world.

The warm rain process is an important part of shallow cumulus convection and can influence both cloud microphysics and cloud radiative effects. Model studies suggest that as shallow cumulus grow in size, the likelihood of warm rain increases due to a decreasing impact of entrainment on cloud updrafts. This implies a reduction in evaporative effects near cloud center that may result in more efficient conversion from cloud water to precipitation as cloud size increases. While these findings have been illustrated with cloud resolving models, the likelihood of precipitation and the sensitivity of precipitation efficiency to cloud size has not yet been tested by global observations. A-Train satellite observations, with sensors sensitive to both cloud and precipitation water, can be used to examine shallow cumulus behavior with cloud size. We combine CloudSat and MODIS observations to create a warm cloud climatology by identifying warm oceanic contiguous cloud objects with top heights below the freezing level from August 2006 - December 2010. The characteristics of each cloud object, including cloud top height, along-track extent (size), vertical reflectivity gradients, integrated cloud and precipitation water, and column water vapor (CWV) environment, are calculated. As a proxy for warm rain efficiency, the ratio of precipitation to cloud water is also analyzed for varying cloud object sizes. For a fixed top height, our results show rain likelihood increases with cloud size. Our initial results support the hypothesis that as shallow cumulus size increases and/or environmental moisture increases, shallow cumulus updrafts are able to support larger droplets that are more likely to fall out as rain. Planned analysis will determine how our proxy for warm rain efficiency changes with cloud size.

Environmental decision- and policy-making must contend with uncertainty about the future that can hinder proactive environmental decisions, forcing environmental managers into reactive postures. To help prevent this, a variety of methods exist for exploring potential environmental futures and associated uncertainties. Producing environmental futures benefit those involved by supporting a systems-level understanding and expanding thinking beyond “business as usual”. We review environmental and non-environmental programs that use indicators to inform environmental futures for decision- and policy-making. Review objectives are to: 1) identify and discuss key environmental futures program attributes, and 2) propose program attributes that support their successful uptake in decision processes. Attributes discussed include purpose and audience, methods, addressing uncertainty and assumptions, relationship to indicator programs, how program values and biases are addressed, the role of goals, and how success is measured and defined. We conclude with recommendations for environmental futures programs that can be successfully integrated into environmental decisions. These include: combining multiple environmental futures methods to provide complementary insights or highlight inconsistencies in assumptions, including a schematic of assumptions and drivers, and defining success criteria, whenever possible. These can help increase the acceptance of environmental futures products in decision-making and increase their short-term and long-term contributions.

Climate change and disruptions to disturbance regimes contribute to uncertainty about the best ways to manage forests and promote individual tree health. Indicators of tree health include annual growth, formation of defensive structures (resin ducts), and ability to produce defensive compounds (resin). Higher growth and resin duct area are associated with a lower chance of mortality from disturbances (Ferrenberg et al. 2014). Past research suggests that prescribed burning and thinning treatments can have positive impacts on growth and resin duct metrics (Kolb et al. 1998; Hood et al. 2016), indicating that management activities have the potential to help increase and restore tree health. However, there is limited research comparing different disturbances and management activities in terms of impacts on tree growth, resin ducts, and resin flow. In this research we explore the questions: 1) What factors most influence resin flow in ponderosa pine (Pinus ponderosa)? 2) What is the impact of fire or timber harvest on tree growth, resin flow, and resin ducts? 3) Are there changes in the relationships between tree growth and resin duct metrics that occur after disturbance, which may indicate shifts in tree resource allocation to growth vs. defenses?

Optical aurora can be classified into two broad categories, i.e., diffuse and discrete auroras. Recent studies based on optical observations obtained on the dayside reveal some important processes occurred in the dayside magnetosphere and are reviewed in this paper. Dayside diffuse auroras (DDAs) are classified into unstructured and structured DDAs. Unstructured DDAs predominantly occur in the morning but structured ones are mainly observed near magnetic local noon (MLN). Because structured diffuse auroras have been suggested to be associated with cold plasma structures in the magnetosphere, distribution and generation of cold plasma structures in the dayside outer magnetosphere are discussed based on the detailed observational properties of DDAs. A particular discrete auroral form, i.e., throat aurora, is defined during study on DDA. Detailed observational properties of throat aurora are presented, which suggest that throat auroras are ground signatures for localized magnetopause indentations that are most likely caused by localized high-speed jets impacting on the magnetopause. Studies on throat aurora reveal that the transient structures locally generated in the magnetosheath can frequently cause indentations on the subsolar magnetopause, trigger reconnection, result in a serial of responses in geospace, and thus will play important role on solar wind-magnetosphere coupling.

We present a three-dimensional numerical model of tectonic plates that self-consistently develop in the convecting mantle. The viscosity depends on stress-history as well as temperature. The lithosphere develops as the upper highly viscous part of the thermal boundary layer along the surface boundary owing to a strong dependence of the viscosity on temperature. When the stress S exceeds a threshold Sp in the lithosphere, however, we assumed that the viscosity drops by orders of magnitude and keeps the low value, even when S is reduced below Sp, provided that S remains higher than the other threshold Sm (< Sp). Sp corresponds to the rupture strength of the tectonic plates, while Sm to that at plate margins. The viscosity is a two-valued function of the stress S in the range of (Sm, Sp), and which of the two values the lithosphere chooses is determined by whether or not S has exceeded Sp in the past. When the model parameters are tuned so that the stress in the lithosphere stays in the range, the lithosphere is rifted into several highly viscous pieces, or tectonic plates, separated by narrow plate margins where the viscosity takes the lower value, and the tectonic plates rigidly and stably move and occasionally rotate for several hundred million years or longer. (See the planform of the plate motion shown in the figure. The arrows show the velocity, while the color shows the relative viscosity on the surface.) Because of the rather stable plate motion, the heat flow decreases with the distance from the spreading centers L in their vicinity as 1/sqrt(L), and the secondary convection occurs beneath the plates in the form of two-dimensional rolls with their axes aligned with the direction of plate motions.

The Shenhu hydrate reservoirs of northern South China Sea are speculated to form and accumulate under the free gas-rich environment, and accord with the flow-transportation-reaction process. During this process, the area has also experienced simultaneous alternations of the local geological structures and ambient environmental conditions. First-order reaction kinetics, which controls the hydrate reaction, is coupled with the seafloor sedimentation to quest the dynamic formation and aggregation mechanism of the Shenhu hydrate layers. Firstly, based on the indications from Peclet number, the hydrate reaction shall play more active roles during the natural sedimentation in this process. Secondly, when the average seafloor sedimentation rate and the initial seafloor were 5 cm/ka and 988 m, respectively, three moments (50 ka, 3 Ma, and 5 Ma) are chosen to investigate the evolution process of the hydrate reservoirs and exhibit the change of the local pressures, temperatures, dissolved methane and salt, phase saturations, stratum permeability, and pore capillary pressure. The results show that after 5 Ma the occurrence and distribution of hydrate-bearing sediments proceed to be nearly consistent with the current status. Finally, the effects of five factors, including methane flux, kinetic coefficient, initial fluid position, permeability and seafloor sedimentation rate which simultaneously control the accumulation together in this zone, are quantitatively discussed. It verifies that the reaction-sedimentation mechanism is applicable for researching the Shenhu hydrate system. Under this model it should have a small methane flux and relatively small reaction coefficient here.

River discharges that are large enough to be impacted by Coriolis when they reach the coastal ocean create a buoyancy-driven coastal current in the direction of Kelvin wave propagation. This geostrophically adjusted current is a major circulation feature, controlling the transport of riverine waters and associated materials, such as sediments, nutrients and pollutants. Coastal models in areas of large rivers need to accurately represent this coastal current and its variability under the influence of other factors impacting coastal circulation. Coastal altimetry data are an important source of suitable observations to guide modeling and applications. Use of such data around the Mississippi River Delta will be shown, in tandem with in situ data and a high resolution hydrodynamic model that has been optimized for river plume dynamics. During the 2010 Deepwater Horizon incident, this methodology evaluated a period of strong coastal current, which was found relevant to the transport of hydrocarbons from the historically unprecedented Gulf of Mexico oil spill. During the 2015 Mississippi flood episode, the coastal altimetry data confirmed the weak coastal current due to the offshore removal of riverine waters under the influence of oceanic circulation, namely the Loop Current and associated eddies. This variability was captured by both coastal altimetry data and the model, leading to good agreement with in situ data further offshore, along the branches that carried Mississippi waters toward South Florida.

The laboratory approach brings a significant simplification compared to the actual conditions in situ. Laboratory experiments represent the only chance to control the physical conditions under which the investigated physical phenomena occur. Acoustic emission (AE) is the process accompanying the brittle fracturing of solid body and simultaneously an indispensable tool for its study. Laboratory experiments under controlled loading conditions make it possible to differentiate the effect of important factors like material structure, stress field, crack occurrence, etc. on fracture initiation and development, and allow simulate the nature in situ. Microearthquakes detected during AE can be analyzed by methods developed in earthquake seismology. We apply the shear-tensile crack (STC) to describe the source mechanism of the AE events with the aim to detect the mode of rock fracturing, in particular to distinguish between a shear slip and tensile crack, the latter both in the phase of its opening and closing. The benefit of discerning between shear and tensile fracturing is an insight into changes of the permeability of the rock massif both in space and time. By contrast to natural seismology, tens of thousands AE events occur in laboratory during the experiment. Expecting to process large volumes of data, an urgent demand was to make the non-linear STC search together with the estimate of the errors involved as fast as possible. To assess the reliability of the STC solution, the confidence regions of source model parameters are constructed. The misfit function is converted into the probability density function which is integrated over a trial volume of low misfit until requested probability content is achieved. For individual microearthquakes, we display confidence regions both for the mechanism orientation and its decomposition. Aiming to process a large bulk of AE data, a method of assessing of these zones needs to be proposed, which describes them by estimates of their extreme size. This allows us select for subsequent interpretation from all solutions only those that are stable and reliable. We have applied this approach to the experimental data obtained from a couple of uniaxial loading tests performed on a Westerly Granite and Liberec Granite specimen using a 14 channel AE monitoring system.

After the recent large earthquake disasters, Japan now emphasizes the role of universities in disaster prevention. Universities with expert knowledge of disasters and prevention are possibly able to play the role of linking the administration and citizens and supporting the collaboration of the many related agencies. Based on this recognition, since 2016, Nagoya University has actively built a framework for collaborating with the National University of Mongolia (MUIS) and the National Emergency Agency of Mongolia (NEMA). Nagoya University and the Open University of Japan intend to share Japan’s experience on “how to raise citizen’s disaster resilience” from the perspective of these universities. After the 1995 Kobe Earthquake, Japan has implemented many earthquake disaster prevention initiatives; however, in 2011, the Great East Japan Earthquake again caused substantial destructive damage. Although adequate measures had been taken, there is still a limit to governmental measures to deal with huge earthquakes with low occurring frequency. In countries where large earthquakes are possible, it is essential for each citizen to strengthen their own buildings or to endeavor to live in a place with good ground conditions and to ensure that this becomes the normal way of life. However, interest in disaster prevention often dissipates, and we are liable to repeat the same mistakes. How can we enhance citizens’ disaster resilience? As emphasized in the Sendai framework, one of the most important factors is “cooperation” and universities could become the focal point of this cooperation. Since 2002, Nagoya University, together with the administration and citizens, has begun to conduct various disaster prevention education projects in Japan. We introduce here the three projects based on Geography, Cultural Anthropology and Environmental Sciences, which were conducted within the period between 2014 and 2018. 1) Establishment of a Cooperative Center for Resilience Research (CCRR) between the National University of Mongolia and Nagoya University. 2) Organizing a public symposium for earthquake prevention by the Mongolian Government and CCRR. 3) Initiating the Grass-roots Joint Project: “Disaster Awareness Enlightenment Project for Large-scale Natural Disasters Caused by Global Environmental Change in Khovd Province, Mongolia” supported by Japan International Cooperation Agency (JICA). Through these projects, we want to determine disaster prevention methods suitable for Mongolia rather than just utilize Japanese methods of disaster prevention.

Team collaboration theories or the role that organizational design plays in promoting long-term research success are often secondary considerations within ambitious community-wide research initiatives. However, for research project managers or community managers called in to consult on the formation of new projects, research proposals, or collaborative partnerships, understanding and applying this body of knowledge in the early initiating or planning phases of new research can strongly promote innovative, collegial, and productive outcomes. In 2018, the Arctic Research Consortium of the U.S. undertook a strategic planning initiative to identify the strategic goals and objectives that will guide our research community support efforts over the next five years. As part of this effort, we determined ARCUS would be doing more to directly evaluate and understand the Arctic research community and its support needs. We also confirmed that we will be taking part in efforts to build out and new initiatives such as the Arctic System Science Collaboratory and UArctic Analytics Institute. As a first step toward achieving both of these objectives, ARCUS staff undertook an internal study to identify the common organizational design structures of current Arctic research programs and what recommendations we could make to improve on these designs within the new and emerging programs we support. Using document analysis and key informant interviews, we created a typology of the collaborative research program structures supported by ARCUS as well as other Arctic research programs funded through the National Science Foundation. The pros and cons of these support structures were then explored and evaluated through the lens of team collaboration and organizational design theories. Our findings highlight the important role that research project and community managers play in promoting collaborative institutional structures and cultures and that without intentional and without ongoing efforts to build and improve them, the productivity and longevity of research communities is likely to decline.

A document by Abhinav A. Click on the document to view its contents.

Science centers and museums are increasingly exploring a range of approaches for encouraging their visitors and communities to not only learn about climate solutions, but to discover their own pathways to sustained, meaningful participation in action. These place-based institutions have unique opportunities to cultivate a culture of hope and action thanks to their local expertise, diverse programming (e.g., field trips, special events, and community science projects), and wide reach (including both in-person and online interactions). These assets enable science centers and museums to communicate about climate solutions in ways that are visible, relatable, and accessible, all attributes that make them more likely to be taken up. One approach that several museums and other groups have piloted is the use of a GIS-based tool to invite members of their community to share the climate actions they’re undertaking and explore those of others. The tool produces open-access climate action maps that showcase real actions taking place in a particular community and provide an opportunity to leverage several evidence-based practices for communicating about climate solutions. By featuring everyday people who live in one’s community, doing actions that are broadly accessible, the maps build a sense of agency, provide inspiration, convey action-oriented norms, and build a sense of belonging in climate solutions. We will describe the ways that this flexible tool and resulting map can be embedded in a range of museum contexts and will discuss the ways that contributing to and exploring the map benefits museums, their visitors, and communities. We will also discuss opportunities for increasing impact through connections with local media, decision-makers, and K-12 school systems. This work demonstrates the role that science museums can play as hubs for collecting and coordinating climate stories and actionable resource centers for increasing community-led participation in climate action.

Deep learning models have been widely applied in seismological signal processing, including phase picking, signal denoising, polarity determination, and phase association. But when it comes to the tasks to process phase information across a station network, most current workflows rely on either traditional physics informed optimization (e.g., hypocenter and grid search for source locations and focal mechanisms), or machine leaning models pre-trained on fixed station arrays, which limits the generality of the model to specific areas. We propose that by making proper use of transformer encoders (self-attention layers), in which we treat every station’s phase information as a “token vector” and append with the station locations/metadata as “positional encodings”, we can train a model capable of processing phase information from any general set of station networks.To demonstrate this idea, we built a transformer-based focal-mechanism determination model, named FOCONET, which directly solves for the strike, dip, and rake angles of a double couple focal mechanism, based on the locations, first-motion polarities, S/P amplitude ratios, and SNRs from a set of stations. FOCONET is trained on 440,000 noise-added synthetics generated with random source locations, focal mechanisms, and station distributions. We use the Kagan angle - the minimum rotation angle between the predicted and the (known) ground truth mechanism - to evaluate the prediction quality. Tested on the noised synthetics with known focal mechanisms, FOCONET reaches average Kagan angles of 29°, 16° and 12° when using data from 12, 24 or 32 stations. This is well within typical focal mechanism errors (25°–30°), and 3­º–10° lower than the predictions from traditional methods including: FPFIT and HASH (S/P included or excluded). We also tested our FOCONET on 200+ M>2.5 events of the 2016 Amatrice, Italy earthquake sequence with A-class HASH solutions for comparison, and achieved an average Kagan angle of 20º. Given its stronger performance on the synthetic test data, it is plausible that the FOCONET predictions may in fact be closer to the unknown ground truths. The success of FOCONET in focal mechanism determination from a network of stations suggests that similar joint-station seismological task would benefit from transformer-based models.

Many iron meteorites sample the metallic cores of planetesimals, providing a unique opportunity to study early Solar System planetary processes. Modeling the chemical evolution during crystallization of these iron meteorite groups provides evidence that both S and P were present as light elements in planetesimal cores. As fractional crystallization of these cores proceeded, the concentrations of both S and P in the residual metallic liquid in the core increased, and eventually, liquid immiscibility in the Fe-Ni-S-P system would be expected to be encountered in many cases. For example, the IIAB and IIG irons may be related in this way. Considerable previous experimental work has determined element partitioning behaviors between solid metal and liquid metal as a function of the S and P concentrations of the metallic liquid, but few experimental studies have examined trace element partitioning behavior after the onset of liquid immiscibility. In this work, we present new experimental results that determine element partitioning behavior between two coexisting immiscible metallic liquids in the Fe-Ni-S-P system, as may be experienced during the later stages of the evolution of planetesimal cores.

A document by Kevin Raeder. Click on the document to view its contents.

The reliable operation of transformers is critical to power system stability, and early fault detection in transformers can significantly reduce the risk of catastrophic failures. Dissolved gas analysis (DGA) is a commonly used method to assess transformer health, as gas concentrations correlate with fault conditions inside the transformer. Methane (CH4), a gas indicative of thermal faults, serves as a key parameter in detecting early signs of fault. This study proposes a linear epsilon support vector regression (SVR) model fine-tuned with Grid Search for predicting methane concentration based on transformer temperature, oil temperature, winding resistance, load factor, service life, and transformer age using grey relational analysis. By predicting methane concentration in ppm, this model supports proactive fault management, optimizing maintenance schedules, and effectively reducing transformer downtime. Comparative results suggest that the proposed SVR model is an effective baseline for improving dissolved gas analysis accuracy, contributing to enhanced transformer diagnostics and preventive maintenance strategies.