An improved understanding of the mechanisms and factors affecting glacial flow is crucial to better predict sea level rise. Glacial ice often contains impurities such as the presence of small insoluble particles. Mixtures of ice and dust can be found in many places throughout the world, specifically in areas of high latitude and altitude (Moore, 2014). This study aims to understand the effect of entrained insoluble debris on processes of glacial motion. Glaciers move through a combination of internal ice deformation and basal sliding. Internal ice deformation, the flow of individual ice grains, has been found to be grain-size dependent in both field and laboratory studies (Goldsby and Kohlstedt, 2001). In an attempt to better understand ice grain size, this study considers the effect of debris on grain growth. Samples of pure ice and ice with debris were fabricated with a standard protocol and maintained at -5°C for controlled annealing. Microstructural characterization was preformed using a light microscope to image the samples, and calculating the average grain sizes using a linear-intercept method. The ice with debris was found to have smaller grain sizes, thought to be associated with grain-boundary pinning. Extrapolated values were used with a flow law, projecting that ice with debris will have lower viscosity, thus flow faster. To address basal sliding, the other form of glacial movement, we conducted a second phase of study. Basal sliding, the process of a glacier sliding over the bedrock, is influenced by the presence of meltwater at the base of the glacier (Hoffman et al., 2011). Frictional heating, from ice-on-rock friction, was studied as a factor affecting meltwater production. We conducted a simple 1D computer model using laboratory friction measurements of ice with entrained debris (Zoet et al., 2013). We find that debris content and frictional heating are directly proportional. Trials run at faster glacial velocities also show larger amounts of frictional heating. As frictional heating may increase meltwater, glaciers with debris may slide faster over bedrock. Overall, by better understanding the motion of debris-rich glaciers, we can focus our attention to areas around the world at risk, and better predict/prepare for sea level rise.

We are investigating terrain deformations of long range and persistence that take place on continental scale over the stable shield of continental South America. The crustal deformation is being investigated by correlating with velocities and directions obtained from time series of approximately 60 GNSS stations deployed in Brazil and neighboring countries that take part of the Continuous network of the Geocentric Reference System for the Americas (SIRGAS-C). We attempt to estimate velocities and mid-plate strain rates using the best GNSS stations located in the stable South America mid-plate. The velocities have been estimated by Least Square Estimation (LSE) using SIRGAS weekly time series with a stochastic model composed of white noise plus flicker or random walk noises. Variance Component Estimation (VCE; Amiri-Simkooei et al., 2007) has been applied to classify the type of noise and compose the time series stochastic model. In addition, the time series breaks and offsets are taken into account in the LSE. The noises were classified as white plus flicker noise in approximately 70% of the horizontal component and most of random walk appears for stations located in the Amazon and Pantanal basins or near the coastal zones. The estimated formal precision reach about 0.10 mm/year with RMS of residual near 1.5 and 4.5 mm respectively for horizontal and vertical velocities. The estimated velocities by LSE were also computed by using the MIDAs code (Blewit et al 2015) and the results show an agreement of the order of 0.30 mm/y. The computed strain rates in the central part of Brazil indicate shortening, consistent with the predominance of reverse faulting mechanisms. When a station pair includes one station near the coast, the linear strain rates indicate extension. However, strain rates do not clearly indicate a preferred principal direction and do not seem compatible with the stress patterns derived from the focal mechanisms. In addition, the rate of seismic moment release indicates strain rates from earthquake occurrence two to three orders of magnitude lower than the observed strain rates from the geodetic network. Assessment of South America linear strain rates computed through estimated GNSS velocities will be discussed.

Solar-induced chlorophyll fluorescence (SIF) offers a promising method to remotely monitor photosynthesis at the canopy and regional scale. However, in order to interpret satellite SIF measurements in a biological context, there needs to be a better understanding of the diurnal dynamics of SIF and photosynthesis under variable stress conditions. Photons absorbed by a leaf can enter photochemistry, be actively dissipated via non-photochemical quenching (NPQ), or be re-emitted as chlorophyll fluorescence. Therefore, having better understanding of NPQ should improve interpretation of SIF. At the canopy scale, we captured diurnal dynamics of SIF and GPP. We then coupled leaf-level measurements of chlorophyll fluorescence, NPQ and photosynthesis and plant water status with canopy-level SIF and GPP to explore the mechanisms controlling diurnal dynamics of fluorescence vs. photosynthesis in a rain-fed maize field situated in upstate New York.

With the mass adoption of data analysis in several scientific fields such as climatology, medicine, astronomy and astrophysics, the availability of an appropriate analytics infrastructure has become a necessity increasingly recognized by the scientific community. However, appropriate tools and applications are required to process the large volume of data collected and generated by researchers. One of the biggest challenges lies in the fact that these tools need to be gathered to be applied in specific domains. The area of bioclimatic data is a scientific field that still has much to improve in this matter. It is a field of study that lacks great efforts in the direction to provide methodologies and tools to facilitate the understanding of the complex phenomena involved in the influence that environmental variables have on biodiversity on the planet. Thus, the purpose of this work is to propose a big data analytics architecture that presents an ecosystem that systematizes and facilitates the task of the scientists to deal with the complexity in the bioclimatic data analysis, providing tools for storage, management, analysis using machine learning algorithms and data mining, and visualization tools. The methodological approach of this work was to make a thorough bibliographical study to verify the most used tools and the suitability of each one to the purpose of the work. In addition, the literature provided indications of software ecosystem implementations methodologies that served as a guide in the architecture design. Within the architecture, we attempted to gather a set of bioclimatic data based on a subset of data obtained from the Atmospheric Radiation Measurement (ARM) data repository for climatic data, and the Brazilian Biodiversity Portal for biodiversity data. As a result, we were able to gather a series of tools to access data such as Cassandra, distribution of processing such as Spark, programming interface represented by Jupyter Notebook, system modules for data format conversion, machine learning algorithms libraries and software for data visualization. This research discuss the importance of a domain purpose design of a data analysis architecture for bioclimatic data. We concluded that this type of ecosystem is imperative to facilitate the research process and increase the quality of the results.

Modeling future glacier changes on regional or global scales is challenging due to a scarcity of data for calibrating model parameters. This makes it difficult to derive accurate model parameters and also to convey the model uncertainty associated with those parameters. Previous global-scale models have typically optimized a single glacier or region specific set of model parameters to project global-scale glacier mass changes. As part of the development of a new open source global-scale glacier evolution model this research implements a Markov Chain Monte Carlo method to address this problem. We use geodetic mass-balance observations to determine probability distributions of a set of model parameters at each glacier. We then form an ensemble of model simulations by sampling parameters from these distributions. Using an ensemble allows us to create a range of mass balance changes for each glacier and quantify the model uncertainty. Applying this calibration technique, we use temperature and precipitation projections of one global climate model to model the mass changes until year 2100 of thousands of glaciers in High Mountain Asia. By using climate projections forced by multiple emission scenarios, we compare the uncertainties in changing climate caused by possible emission scenarios with the uncertainties in the glacier evolution model, and evaluate the results of different climate scenarios on glacier evolution.

In response to a growing number of natural and anthropogenic threats, the long-term sustainability of coastal river deltas and wetlands has come into question worldwide. Tools such as remote sensing and numerical modeling have been implemented in an effort to monitor and predict the hydro-geomorphological evolution of our coasts. Hydrological connectivity is known to play an important role in deltaic evolution by delivering flow, sediment, and nutrients to the interior of deltaic islands/wetlands. However, estimating connectivity typically requires detailed field work or numerical modeling, which is difficult to implement over broad spatial and temporal scales. In the present work, we investigate the potential of using remote sensing to estimate hydrological connectivity in the Wax Lake Delta (WLD) and Atchafalaya Delta region of the Louisiana coast. During a three-hour window, five difference maps of water level in the WLD and surrounding wetlands were collected using UAVSAR L-band radar in repeat-pass interferometric mode. We then modeled the WLD subsection of the domain using a 2D shallow-water hydrodynamic model configured to run on the same discharge, tide, and wind conditions as recorded at nearby monitoring stations during the observational window, with vegetation parameterized as a source of additional drag in the deltaic islands. Modeling allowed us to determine the relative influence of tides, vegetation, and wind on WLD water levels, which could then be extrapolated to infer the behavior throughout the rest of the domain. Over the observational window, UAVSAR measured a cumulative loss of over 22 megatons of water from non-channelized wetlands as tides fell. We find that the model tends to under-predict the observed water level draw-down, as well as the degree of hydrological activity in proximal islands that we observe in the UAVSAR data. Models that neglect the influence of wind underestimate the volume of water leaving the islands by up to two-thirds, suggesting the importance of wind on deltaic hydrodynamics during the observational window. With the information gained from the numerical modeling, as well as the computation of information theory statistics, we extend the WLD results to analyze and quantify the water level behavior in the surrounding wetlands and Atchafalaya delta.

This research aims to identify several decision-making gaps which seem to be existed around Food-Energy-Water Nexus through local case study in the Kyoto city, Japan. Our research methodologies include calculating food self-sufficiency ratio at local level using national statistics, production area proportion of each food categories using local market reports, and conducting impact assessment for Water-Energy Nexus based on several scenarios of food policy. Based on the above calculation and scenario analysis on several food policies, decision-making gaps regarding Food-Energy-Water Nexus is abstracted. During the scenario analysis, decision-making gaps regarding Food-Energy-Water Nexus are found. In other words, while a watershed is decided automatically by natural and geographical conditions, energy-shed usually depend on big electricity companies and food-shed consists of consumers’ preferences, retailers’ procurement policy, farmers’ tendency to change (or not change) their production style and so on.

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.

Over the past 100 years, socioeconomic development has been ceaselessly putting great pressure on our freshwater resources. It has led to overwhelming and undermining nature’s ability to provide key functions and services, i.e. growing water scarcity and deterioration of water-related environment and ecosystems worldwide. The establishment of the 2030 Agenda’s Sustainable Development Goal (SDG) 6, therefore not only articulates the augmented concerns on water sustainability issues in the global political agenda, but also highlights that all countries (stakeholders) committed to translating the global goals and targets to national (own) targets and indicators, along with their individual challenges and corresponding opportunities of accounting for mutual benefit and win-win cooperation. The European Union (EU) (developed) and China (developing), as the second and third largest economies respectively, have been addressing sustainable development as an overarching objective for policy-making on the economic, social, and environmental dimensions, and working accordingly in a balanced and integrated manner. They have been joining forces, as equal partners, for better water through the China Europe Water Platform (CEWP) built in 2012, which provides a unique prospective to insight into how the EU and China have been making unremitting efforts for pursuing water sustainability, as well as the characteristics of action plans on SDG 6 implementation between the EU and China. The principal aim of this study is to comprehend (1) the status quo of the EU and China’s progress on SDG 6 targets, (2) how the EU and China can take forward implementation in partnership to enable and accelerate progress towards achieving SDG 6, and (3) how the EU and China can go beyond SDG 6 to establish linkages across the 2030 Agenda in the context of water-energy-food nexus. The highlights to fill the aforementioned knowledge gaps can be portrayed as follows: (1) the EU and China could develop a national indicator system together regarding SDG 6 targets, (2) the EU and China could establish a national indicator database together, in accordance with the national indicator system, and (3) the EU and China could conduct a lesson learned workshop together, in terms of equitable, participatory, and transparent SDG 6 policy process.

Aim: Ultrafine particles (UFP; <100 nm diameter) are highly variable in space and time and as such can be challenging to model for use in epidemiological studies. Recent studies have shown that airports are contributors to local air pollution, but research is needed to understand the impact from individual aircraft and how to incorporate flight activity into UFP exposure models. Our aim was to characterize UFP transport from aircraft exhaust during landing at Boston Logan International Airport (MA, USA). Methods: Particle number concentration (PNC; a proxy for UFP) was measured continuously on selected weeks at the University of Massachusetts Boston campus from April-September 2017 at 1-sec resolution. The site was positioned 4.8 km southwest of the airport edge and <1 km from a major landing trajectory (runways 4L and 4R). Wind speed and direction were concurrently measured near the UFP monitor at 5-min resolution. For this same monitoring period, flight activity data were acquired from the U.S. Federal Aviation Administration, which included three-dimensional positions of aircraft at approximately 5-sec resolution. All data were merged by timestamp prior to analysis. Results: During times when flights were landing on 4L/R, the 99th percentile of 1-sec PNC during winds from the east (no traffic sources) was 88,000 particles/cm3. The concentration dropped >50% when flights were landing along other trajectories during these same winds. Stratification by wind speed showed that when flights were landing along 4L/R, higher wind speeds resulted in increased median PNC during winds downwind of arrival aircraft, but not from the opposite direction. When flights were landing along other runway trajectories nearly all wind directions observed decreased PNC with increased wind speed. Conclusions: Our results suggest that aircraft can play a role in peak ambient UFP exposures during landing and that downwind transport of UFP from aircraft exhaust needs further investigation.

A planetary surface’s thermal infrared (TIR) emissions provide insight into the surface’s composition. Different minerals can be identified by their characteristic TIR spectral signatures. Therefore one can retrieve surface mineral composition by comparing TIR observations of a planetary surface against a library of known mineral TIR spectra measured on Earth. However for airless bodies such as the Moon, creating such a spectral library poses a challenge: minerals exhibit different TIR characteristics when measured in typical terrestrial conditions versus in lunar surface-like environments. We work to overcome this challenge by measuring TIR emission spectra of mineral samples in a chamber that simulates the lunar environment. The Simulated Airless Body Emission Laboratory (SABEL) chamber heats particulate samples under vacuum to generate a thermal gradient akin to that found in the upper regolith (i.e. epiregolith) of airless bodies. The presence of this thermal gradient—modeled to be as steep as ~60K/100 μm for the Moon—is due to airless bodies lacking the convective heat transfer provided by an atmosphere. This thermal gradient is responsible for the altered TIR spectral emission characteristics of the lunar surface, so simulating it in SABEL allows us to measure TIR spectra that are directly comparable to remotely sensed TIR observations from the Diviner Lunar Radiometer (Diviner) instrument aboard the Lunar Reconnaissance Orbiter (LRO). The work presented here focuses on one particular application of SABEL: characterizing the TIR emission spectra of silicate mineral mixtures with the endmembers plagioclase, pyroxene, and olivine. These endmembers bound the typical mineral compositions of the lunar surface. By understanding the TIR characteristics of these endmembers’ mixtures, and in particular how the wavelength position of the Christiansen feature—an emissivity maximum sensed by Diviner—changes for different mixtures, we can better interpret TIR data and their implications for surface composition.

Cornell University aspires to fully heat and cool its main campus with renewable energy. Cornell is a 30,000-person community, in >14 million ft2 of buildings, that annually consumes ~240,000 MWth-hrs of heat. Successful geothermal district heating at Cornell would provide a model for other communities in the cold-climate Northeast U.S.. A geothermal Play Fairway Analysis (GPFA) of the sedimentary aquifer geothermal potential of the Appalachian Basin (https://bit.ly/2JHOiVH) for NY, PA, and WV demonstrated that Cornell’s campus is located in a favorable sub-region of the basin. The GPFA found that, for Cornell, the expected rock temperature at 3 km depth was 70–85°C, with suitable natural permeability in sedimentary units most likely near 2.4 km depth; indirect indicators of the propensity for induced seismicity revealed no unusual risk. In 2017-2018 we have used geological and geophysical data sets to more robustly analyze the nature of the geological resources, their potential fit to the heating needs, and risks. Data for deep wells in Tompkins County and six abutting counties, archived in New York’s Empire State Organized Geologic Information System, improve the thermal resource estimate. Within 20 km distance, one well log, assumed equilibrated, lists 118 °C rock at 3369 m depth, and another borehole lists a non-equilibrated 93 °C at 3600 m. These underpin revised Cornell temperature-at-depth estimates. Sedimentary reservoir data for units from the Ordovician Trenton Formation to the top of metamorphic basement are under evaluation based on gamma, neutron, sonic and density logs. The estimated depth to the basement is 2865 +/- 200 m. We are evaluating potential reservoirs within basement rocks for heat extraction using Enhanced Geothermal System techniques. Direct basement data are limited to petrology of cuttings from 5 wells. For pre-drill analysis, those data are supplemented by analogous metamorphic rocks in the Adirondack Mountains; we assume a mixture of granitic gneiss, marble, amphibolite and/or anorthosite. Fracture aperture, spacing, and orientation dispersion are estimated based on observations in the southern Adirondacks, to which fracture analysis based on high resolution DEMs is being added. Seismic, gravity and magnetic field studies of potential well field sites are in progress.

The Europlanet H2020 program started on 1/9/2015 for 4 years. It includes an activity to adapt Virtual Observatory (VO) techniques to Planetary Science data called VESPA. The objective is to facilitate searches in big archives as well as sparse databases, to provide simple data access and on-line visualization, and to allow small data providers to make their data available in an interoperable environment with minimum effort. The VESPA system has been hugely improved during the first three years of Europlanet H2020: the infrastructure has been upgraded to describe data in many fields more accurately; the main user search interface (http://vespa.obspm.fr) has been redesigned to provide more flexibility; alternative ways to access Planetary Science data services from VO tools have been implemented; VO tools are being improved to handle specificities of Solar System data, e.g. measurements in reflected light, coordinate systems, etc. Current steps include the development of a connection between the VO world and GIS tools, and integration of Heliophysics, planetary plasmas, and mineral spectroscopy data to support of the analysis of observations. Existing data services have been updated, and new ones have been designed. The global objective is already overstepped, with 42 services open (including ESA’s PSA) and ~15 more being finalized. A procedure to install data services has been documented, and hands-on sessions are organized twice a year at EGU and EPSC; this is intended to favour the installation of services by individual research teams, e.g. to distribute derived data related to a published study. In complement, regular discussions are held with big data providers, starting with space agencies (IPDA). Common projects with PDS have been engaged, with the goal to connect PDS4 and EPN-TAP based on a local data dictionary. In parallel, a Solar System Interest Group has been established in IVOA; the goal is here to adapt existing astronomy standards to Planetary Science. The Europlanet 2020 Research Infrastructure project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 654208. [1] Erard et al 2014, Astronomy & Computing 7-8, 71-80. http://arxiv.org/abs/1407.4886

Advancing climate change research requires accurate and traceable measurement of the atmospheric longwave irradiance. Current measurement capabilities are limited to an estimated uncertainty of larger than ± 6 W/ m2 using the interim World Infrared Standard Group (WISG). Two independently designed and calibrated absolute radiometers measuring downwelling longwave irradiance were compared during five outdoor comparisons in 2013, 2015, and 2017 at the Physikalisch Meteorologisches Observatorium Davos/World Radiation Center (PMOD/WRC) and the USA-DOE Atmospheric Radiation Measurement program (ARM) in the Southern Great Planes (SGP). Two Absolute Cavity Pyrgeometers (ACPs) developed by the National Renewable Energy Laboratory (NREL) and four Integrating Sphere Infrared Radiometers (IRISs) developed by PMOD/WRC took part in these intercomparisons. From the five comparisons, the difference between the irradiance measured by the ACPs and IRISs varied from 0.2 W/ m2 to 2.5 W/ m2 based on the atmospheric conditions, which is within the combined stated uncertainties of ±3 W/ m2. The irradiance measured by the WISG is lower than the average irradiance measured by ACPs and IRISs, magnitude of the difference varied from 0.2 W/m2 to 6.6 W/ m2 depending on the integrated water vapor. A concerted effort at the World Meteorological Organization (WMO) Commission for Instruments and Methods of Observation Commission (CIMO) Task Team on Radiation References (TT) started during a meeting from November 15 to 17, 2017 in the National Physical Laboratory (NPL), Teddington, United Kingdom to establish a world reference for measuring the atmospheric longwave irradiance with lower uncertainty and with traceability to SI units by using the ACPs and IRISs as the reference.

Measurements and models of global geophysical parameters such as potential fields, seismic velocity models and dynamic / residual topography are well represented as 2D coloured / contoured maps. However, as teaching aids and for outreach, they offer little impact. Modern 3D-printing techniques help to visualize these and other concepts that are difficult to grasp, such as the intangible structures in the deep Earth. We developed a simple method for portraying scalar fields by 3D printing modified globes of surface topography, representing the parameter of interest as additional, exaggerated topography. This is particularly effective for long-wavelength (>500 km) fields. The workflow uses only open source and free-to-use software, and the resulting models print easily and effectively on a cheap (<300 GBP, 400USD) desktop 3D-printer. We have printed 3D representations of different scalar fields, including models of the surface topography of rocky planets, which can be used in outreach events. These objects are powerful to explain the importance of plate tectonics in shaping a planet. The workflow was extended to 3D scalar fields by analogy to Russian nesting dolls, where the audience can remove shallower layers to see how structures change with depth. We applied this to global seismic tomography models resulting in prototypes of “seismic matryoshkas” (see Figure). The tactile nature of these objects ensures that anyone, including the visually impaired, can explore the structures present deep within our planet

We present approach based on physically substantiated short-term precursor’s selection to provide the real-time multiparameter monitoring having as a purpose the short-term forecast of earthquakes. Three main principles should be fulfilled: 1. We register natural phenomena for which we have multi-year experience demonstrating their connection with the earthquake preparation process 2. All these phenomena have very high statistical confidence in relation to post-phenomena earthquake occurrence 3. We have the physical explanation of these anomalous phenomena generation and their interrelation within the framework of earthquake preparation process. It is important to note that precursors are registered in different geospheres (lithosphere, atmosphere, ionosphere and magnetosphere) what confirms the fact of geospheres coupling during the earthquake preparation period. For the first time we included in consideration the role of triggers and their relationship with precursors. One of the well confirmed triggers is the Space weather evens changing the global atmospheric circulation. The arising large-scale irregularities of atmospheric pressure may serve as earthquake triggers while their linear borders coincide with the active tectonic fault. Another recently revealed effect is existence of earthquake retarders when earthquake happens later (up to month) in comparison with our procedure of earthquake time determination. Complications created by triggers and retarders in developed procedure of short-term earthquake forecast should be resolved in future development of our research. All these ideas are presented in the book which just published by Institute of Physics (IOP) and has the same title as abstract. This work was supported by RSF (project No 18-12-00441)

High pressures, along with thermal processes and irradiation, have a measurable effect on carbonaceous compounds which are found throughout the solar system. High pressure environments, such as those generated by impacts, occur frequently during the evolution of the solar system, and the effects of pressure on the carbonaceous materials present can influence the subsequent chemistry of the body. In situ high pressure synchrotron source Fourier Transform Infrared (FTIR) spectroscopy coupled with computational models has been used to directly study the effects of pressure on carbonaceous materials. Our work using these techniques investigates the specific case of structural sugars, where ribose and deoxyribose have differing responses to high pressures. These particular carbonaceous materials play a key role in the prebiotic chemistry of the early Earth as constituents of the bioinformational molecules ribonucleic acid (RNA) and deoxyribonucleic acid (DNA) respectively. Ribose is substantially less stable than deoxyribose at pressures exceeding 14 GPa and shows less recovery on decompression. Our results imply that the modest impacts experienced throughout the solar system could substantially alter the carbonaceous payload of many bodies, with consequences for any prebiotic chemistry.

The American Association for the Advancement of Science’s Leshner Leadership Institute for Public Engagement with Science, founded in 2015, empowers scientists and engineers to develop and implement public engagement activities, mentor other scientists in their communities and promote public engagement within their institutions. Each year the AAAS Leshner Leadership Institute brings together 15 mid-career researchers working on a topic at the nexus of science and society for a week of intensive training, public engagement practice, and planning. During the following year at their home institutions, AAAS Leshner Fellows implement their plans, interact via regular virtual meetings and receive additional support from staff and experts in the field of public engagement. One of the goals of the AAAS Leshner Leadership Institute is to catalyze institutional change: building understanding about, capacity for and support of public engagement within the various institutions with which researchers are affiliated. AAAS Leshner Fellows have sought to identify opportunities for institutional change within a variety of settings, including universities, government agencies and professional societies. This presentation will provide examples of institutional change from the first three cohorts of AAAS Leshner Fellows (2016-17, climate change; 2017-18, infectious disease; 2018-19, food and water security), including the ways in which they have worked to integrate public engagement into the purpose of the institutions, build processes to support public engagement, and empower people within the institutions to participate in public engagement. It will also discuss the opportunities and challenges for encouraging institutional change via a distributed network of individuals who are linked by discipline but not (necessarily) by institution.