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At least 1,279 records · Page 71

Coordinating AgMIP Data and Models Across Global and Regional Scales for 1.5°C and 2.0°C Assessments

The Agricultural Model Intercomparison and Improvement Project (AgMIP) has developed novel methods for Coordinated Global and Regional Assessments (CGRA) of agriculture and food security in a changing world. The present study aims to perform a proof of concept of the CGRA to demonstrate advantages and challenges of the proposed framework. This effort responds to the request by the UN Framework Convention on Climate Change (UNFCCC) for the implications of limiting global temperature increases to 1.5°C and 2.0°C above pre-industrial conditions. The protocols for the 1.5°C/2.0°C assessment establish explicit and testable linkages across disciplines and scales, connecting outputs and inputs from the Shared Socio-economic Pathways (SSPs), Representative Agricultural Pathways (RAPs), Half a degree Additional warming, Prognosis and Projected Impacts (HAPPI) and Coupled Model Intercomparison Project Phase 5 (CMIP5) ensemble scenarios, global gridded crop models, global agricultural economics models, site-based crop models and within-country regional economics models. The CGRA consistently links disciplines, models and scales in order to track the complex chain of climate impacts and identify key vulnerabilities, feedbacks and uncertainties in managing future risk. CGRA proof-of-concept results show that, at the global scale, there are mixed areas of positive and negative simulated wheat and maize yield changes, with declines in some bread basket regions, at both 1.5°C and 2.0°C. Declines are especially evident in simulations that do not take into account direct CO2 effects on crops. These projected global yield changes mostly resulted in increases in prices and areas of wheat and maize in two global economics models. Regional simulations for 1.5°C and 2.0°C using site-based crop models had mixed results depending on the region and the crop. In conjunction with price changes from the global economics models, productivity declines in the Punjab, Pakistan, resulted in an increase in vulnerable households and the poverty rate. This article is part of the theme issue ‘The Paris Agreement: understanding the physical and social challenges for a warming world of 1.5°C above pre-industrial levels’.

interdisciplinary↗

Lunar Instrument Data Integration Into the Virtual Reality Mission Simulation System for Decision Communication and Situational Awareness

In situ resource utilization (ISRU) technologies are a key advancement required to make human habitation on the Moon and Mars viable. The upcoming Volatiles Investigating Polar Exploration Rover (VIPER) mission will provide crucial correlations between volatiles and lunar geology to understand the water content available for ISRU on the moon. The mission will require the coordination of multi-disciplinary teams across the country making real time decisions based on rover instrument data. The virtual reality Mission Simulation System (vMSS) is a virtual reality platform designed at MIT by the Resource Exploration and Science of our Cosmic Environment (RESOURCE) team to provide teams with a collaboration interface for planetary missions like VIPER. Herein we determine the integration pathway for analog based datasets that are examples of VIPER's two main instruments, the near-infrared volatile spectrometer subsystem (NIRVSS) and the neutron spectrometer subsystem (NSS), into vMSS to provide the most valuable visualization tools. Focusing on improving situational awareness, decision making, reducing task load and incorporating comments from scientists working previous analogs and on the current VIPER mission, we recommend critical elements to implement into vMSS and the best approaches for data visualization. We present a review of relevant analogs and state of the art mission software. We have developed a design concept and path to flight of analysed instrument data integrated with data maps that allow for virtual manipulation and annotation between non-co-located team members. We focus on pre-mission mapping of a priori data for improved situational awareness, layering of analysed instrument data, correlative mapping and interactive capabilities for in-mission decision making, as well as archiving and annotation tools for post-mission analysis. Finally, we lay out the roadmap for the future development of immersive sample site visualization capabilities and the use of integrated instrument data in vMSS with automated temporal and geospatial planning.

Cody Alison Paige↗

Global peak water limit of future groundwater withdrawals

Over the past 50 years, humans have extracted the Earth’s groundwater stocks at a steep rate, largely to fuel global agro-economic development. Given society’s growing reliance on groundwater, we explore ‘peak water limits’ to investigate whether, when and where humanity might reach peak groundwater extraction. Using an integrated global model of the coupled human–Earth system, we simulate groundwater withdrawals across 235 water basins under 900 future scenarios of global change over the twenty-first century. Here we find that global non-renewable groundwater withdrawals exhibit a distinct peak-and-decline signature, comparable to historical observations of other depletable resources (for example, minerals), in nearly all (98%) scenarios, peaking on average at 625 km 3 yr -1 around mid-century, followed by a decline through 2100. The peak and decline occur in about one-third (82) of basins, including 21 that may have already peaked, exposing about half (44%) of the global population to groundwater stress. Most of these basins are in countries with the highest current extraction rates, including the United States, Mexico, Pakistan, India, China, Saudi Arabia and Iran. Furthermore, these groundwater-dependent basins will probably face increasing costs of groundwater and food production, suggesting important implications for global agricultural trade and a diminished role for groundwater in meeting global water demands during the twenty-first century.

58 GEOSCIENCES↗

Nuclear Trade Atlas 2016-2020

Building on prior work developing a Strategic Trade Atlas promoting understanding of global trade flows of strategic goods, a Nuclear Trade Atlas was developed based on publicly available trade data. The Nuclear Trade Atlas examines trade patterns and trends for seventeen commodities based on a two-step assessment of the trade’s nuclear relevance: first estimating the probability that trade classified under a given Harmonized System (HS) code represents a specific commodity included in the export control lists of the Nuclear Suppliers Group, and second estimating the probability that the listed, often dual-use, commodity would be indicative of nuclear use. These estimates combine to provide a measure of the likelihood trade classified under a given HS code may be nuclear relevant. By exclusively focusing on the HS codes most highly ranked by this measure, the resulting data visualizations comprising the Nuclear Trade Atlas provide those responsible for regulating or monitoring nuclear trade greater understanding of relevant global trading patterns and trends. The Atlas includes both commodity- and country-based views of nuclear trade. It is published as a book and as an interactive tool. Besides trade data, the interactive Atlas also includes data about countries’ non-proliferation commitments, allowing users to take this information into consideration while analyzing specific trade flows.

strategic trade, world customs organization, trade↗

Establishing nationwide power system vulnerability index across US counties using interpretable machine learning

Power outages have become increasingly frequent, intense, and prolonged in the US due to climate change, aging electrical grids, and rising energy demand. However, largely due to the absence of granular spatiotemporal outage data, we lack data-driven evidence and analytics-based metrics to quantify power system vulnerability. This limitation has hindered the ability to effectively evaluate and address vulnerability to power outages in US communities. Here, in this work, we collected ∼179 million power outage records at 15-min intervals across 3022 US contiguous counties (96.15 % of the area) from 2014 to 2023. We developed a power system vulnerability assessment framework based on three dimensions (intensity, frequency, and duration) and applied interpretable machine learning models (XGBoost and SHAP) to compute Power System Vulnerability Index (PSVI) at the county level. Our analysis reveals a consistent increase in power system vulnerability across the US counties over the past decade. We identified 318 counties across 45 states as hotspots for high power system vulnerability, particularly in the West Coast (California and Washington), the East Coast (Florida and the Northeast area), the Great Lakes megalopolis (Chicago-Detroit metropolitan areas), and the Gulf of Mexico (Texas). Our heterogeneity analysis indicates that urban counties and those located along regional transmission boundaries tend to exhibit significantly higher vulnerability. Our results highlight the significance of the proposed PSVI for evaluating the vulnerability of communities to power outages. The findings underscore the widespread and pervasive impact of power outages across the country and offer crucial insights to support infrastructure operators, policymakers, and emergency managers in formulating policies and programs aimed at enhancing the resilience of the US power infrastructure.

24 POWER TRANSMISSION AND DISTRIBUTION↗

National and subnational short-term forecasting of COVID-19 in Germany and Poland during early 2021

During the COVID-19 pandemic there has been a strong interest in forecasts of the short-term development of epidemiological indicators to inform decision makers. In this study we evaluate probabilistic real-time predictions of confirmed cases and deaths from COVID-19 in Germany and Poland for the period from January through April 2021. We evaluate probabilistic real-time predictions of confirmed cases and deaths from COVID-19 in Germany and Poland. These were issued by 15 different forecasting models, run by independent research teams. Moreover, we study the performance of combined ensemble forecasts. Evaluation of probabilistic forecasts is based on proper scoring rules, along with interval coverage proportions to assess calibration. The presented work is part of a pre-registered evaluation study. We find that many, though not all, models outperform a simple baseline model up to four weeks ahead for the considered targets. Ensemble methods show very good relative performance. The addressed time period is characterized by rather stable non-pharmaceutical interventions in both countries, making short-term predictions more straightforward than in previous periods. However, major trend changes in reported cases, like the rebound in cases due to the rise of the B.1.1.7 (Alpha) variant in March 2021, prove challenging to predict. Multi-model approaches can help to improve the performance of epidemiological forecasts. However, while death numbers can be predicted with some success based on current case and hospitalization data, predictability of case numbers remains low beyond quite short time horizons. Additional data sources including sequencing and mobility data, which were not extensively used in the present study, may help to improve performance.

60 APPLIED LIFE SCIENCES↗

Iterative self-organizing SCEne-LEvel sampling (ISOSCELES) for large-scale building extraction

Convolutional neural networks (CNN) provide state-of-the-art performance in many computer vision tasks, including those related to remote-sensing image analysis. Successfully training a CNN to generalize well to unseen data, however, requires training on samples that represent the full distribution of variation of both the target classes and their surrounding contexts. With remote sensing data, acquiring a sufficiently representative training set is a challenge due to both the inherent multi-modal variability of satellite or aerial imagery and the general high cost of labeling data. To address this challenge, we have developed ISOSCELES, an Iterative Self-Organizing SCEne LEvel Sampling method for hierarchical sampling of large image sets. Using affinity propagation, ISOSCELES automates the selection of highly representative training images. Compared to random sampling or using available reference data, the distribution of the training is principally data driven, reducing the chance of oversampling uninformative areas or undersampling informative ones. In comparison to manual sample selection by an analyst, ISOSCELES exploits descriptive features, spectral and/or textural, and eliminates human bias in sample selection. Using a hierarchical sampling approach, ISOSCELES can obtain a training set that reflects both between-scene variability, such as in viewing angle and time of day, and within-scene variability at the level of individual training samples. We verify the method by demonstrating its superiority to stratified random sampling in the challenging task of adapting a pre-trained model to a new image and spatial domain for country-scale building extraction. Using a pair of hand-labeled training sets comprising 1,987 sample image chips, a total of 496,000,000 individually labeled pixels, we show, across three distinct model architectures, an increase in accuracy, as measured by F1-score, of 2.2–4.2%.

42 ENGINEERING↗

Flat band driven itinerant magnetism in the Co-pnictides CaCo 2⁢ As 2 and LaCo 2 ⁢P 2

Flat bands can induce strong electron correlation effects that help stabilize both magnetic and superconducting states. Here, in this study, we carry out angle-resolved photoemission spectroscopy and density functional theory calculations to study the electronic structure of the Co-pnictides CaCo 2 ⁢As 2 and LaCo 2 ⁢P 2 . We find that the 𝑘 𝑧 Fermi topology of ferromagnetic LaCo 2 ⁢P 2 is markedly two-dimensional, while the antiferromagnetic CaCo 2 ⁢As 2 develops a 3D Fermi surface described by a zigzaglike band dispersion perpendicular to the Co-As plane. Furthermore, the magnetism is driven by the electronic correlations of the flat bands with 𝑑 𝑥⁢𝑦 and 𝑑 𝑧 2 orbital character at the Fermi level. Our results link the electronic dimensionality and the magnetic order and emphasize the critical role of the As-As and P-P bond strength along the 𝑐 direction to understand the electronic band structure and the rich phase diagram of transition metal pnictides.

36 MATERIALS SCIENCE↗

Washington, D.C. & Maryland Energy: Estimating Solar Potential Using NASA POWER Data to Inform Renewable Energy Policy for Washington, D.C.

In line with the Sustainable D.C. 2.0 plan to combat climate change, Washington D.C. aims to decrease its greenhouse gas emissions by 100% by 2050. As solar energy is a clean, renewable energy form, its integration into the region’s power grids lowers energy costs and incentivizes sustainable development. We partnered with the Washington D.C. Department of Energy & Environment (DOEE) to determine how urban areas surrounding D.C. can better be incorporated into decisions regarding renewable energy policy. The team used NASA’s Prediction of Worldwide Energy Resources (POWER) solar data and a Light Detection and Ranging (LiDAR) derived digital surface model, to estimate and visualize rooftop solar potential for Maryland’s Prince George’s and Montgomery counties. POWER provided solar irradiance data adjusted for tilt angle while the digital surface model contributed aspect and slope data. This methodology factored out areas that were unsuitable for solar panel installation while displaying areas that possess a high potential for energy return. The team found the total rooftop solar potential for the study area to be almost 32 million kW, which is equivalent to roughly 660 kW per building. The methodology used to generate the solar potential maps can be applied to other regions of the country seeking to efficiently utilize solar energy. The end users at the DOEE can use our resulting solar potential map and data table to effectively target buildings that have the highest potential to generate solar energy.

Edward Cronin↗

Systemic Risk From the Perspective of Climate, Environmental and Disaster Risk Science and Practice

Understanding and managing systemic risk is more important than ever due to our immense global connectivity (e.g., between sectors, such as food-health-water-energy, countries and continents, down to individuals). Despite the fact that the notion of systemic risk is several decades old, the term is used in diverse ways across different disciplines (e.g., financial systems, medicine, earth system sciences, disaster risk research and climate science). Triggered by the repercussions of the global financial crisis of the late 2000s, and more recently the COVID-19 pandemic, which are clear realization of systemic risk, the perception of systemic risk has often been focused on global and catastrophic or even existential risks. Systemic risk, however, can be seen as a feature of systems at all possible scales (e.g., global, national, regional, local) with system boundaries varying depending on the context. Addressing current societal challenges, such as climate change, in terms of systemic risk requires integrating different systems perspectives and fostering system thinking, while implementing key intergovernmental agendas, such as the Paris Agreement, the Sendai Framework for Disaster Risk Reduction and the Sustainable Development Goals. Based on insights gained and knowledge collected from an expert workshop, literature review and expert elicitation, we give an integrated perspective of climate, environmental and disaster risk science and practice on systemic risk as summarized in a Briefing Note to the International Science Council. We provide an overview of concepts of systemic risk that have evolved over time and identify commonalities across terminologies and perspectives associated with systemic risk used in different contexts. Key attributes of systemic risk are outlined without prescribing a single definition, and information and data requirements are discussed that are essential for a better and more actionable understanding of the systemic nature of risk. Finally, the opportunities to connect research and policy for addressing systemic risk are highlighted.

systemic risk↗

Fusion energy for space: Feasibility demonstration. A proposal to NASA

This proposed program is to initiate a space flight research and development program to develop fusion energy for the space applications of direct space propulsion and direct space power, that is, a Space Fusion Energy (SFE) program. 'Direct propulsion' refers to the use of plasma energy directly for thrust without requiring other energy conversion systems. Further, to provide space missions with large electrical power, 'direct space power' is proposed whereby the direct conversion of charged particles into electricity is used, thereby avoiding thermal conversion system losses. The energy release from nuclear fusion reactions makes these highly efficient, high power space systems possible. The program as presented conducts in an orderly, hierarchical manner the necessary planning, analyses, and testing to demonstrate the practical use of fusion energy for space. There is nothing discussed that is known to be theoretically impossible. Validation of the engineering principles is sought in this program which uses a cost-benefit approach. Upon successful program completion, space will become more accessible and space missions more safely conducted. The country will have taken a giant step toward the commercialization of space. The mission enabling capability provided by fusion energy is well beyond mission planners' current dreams.

Schulze, Norman R.↗

Train Like an Astronaut Educational Outreach

In an effort to reduce the incidence of childhood obesity, the National Aeronautics and Space Administration (NASA), capitalizing on the theme of human spaceflight developed two educational outreach programs for children ages 8-12. To motivate young "fit explorers," the Train Like an Astronaut National (TLA) program and the Mission X: Train Like an Astronaut International Fitness Challenge (MX) were created. Based on the astronauts' physical training, these programs consist of activities developed by educators and experts in the areas of space life sciences and fitness. These Activities address components of physical fitness. The educational content hopes to promote students to pursue careers in science, technology, engineering, and math (STEM) fields. At the national level, in partnership with First Lady Michelle Obama's Let?s Move! Initiative, the TLA program consists of 10 physical and 2 educational activities. The program encourages families, schools, and communities to work collaboratively in order to reinforce in children and their families the importance of healthy lifestyle habits In contrast, the MX challenge is a cooperative outreach program involving numerous space agencies and other international partner institutions. During the six-week period, teams of students from around the world are challenged to improve their physical fitness and collectively accumulate points by completing 18 core activities. During the 2011 pilot year, a t otal of 137 teams and more than 4,000 students from 12 countries participated in the event. MX will be implemented within 24 countries during the 2012 challenge. It is projected that 7,000 children will "train like an astronaut".

Garcia, Yamil L.↗

Accelerating Low-Income Financing and Transactions (LIFT) for Solar Access Everywhere (Final Technical Report)

The Accelerating Low-Income Financing and Transactions (LIFT) for Solar Access Everywhere project’s goal was to expand Low-to-Moderate Income (LMI) solar access for homeowners and renters. The LIFT project researched and gathered data on 453 LMI community solar project across the country. Following three years of research, the project delivered three groundbreaking research papers in June 2022, focused on 1) customer experience, 2) the growth of community solar programs, and 3) project-level financial best practices for serving LMI communities. These were followed by a user-friendly web-based Toolkit allowing users to interact with project data and key findings in November 2022. The customer experience research examined community solar subscribers’ primary motivations to join and remain satisfied with projects. Our research identified 453 projects across the country that dedicated some portion of the system capacity to LMI households. Seventeen of these projects participated in the LIFT customer experience research, allowing the project team to survey their customers and gain insight into how LMI subscribers feel about community solar and the programs that serve them. Subscribers in our sample indicated that the most critical issue that motivated them to participate in their program, however, was not savings but helping the environment. This was true for both LMI and non-LMI subscribers. Helping the environment was also the most important issue for LMI subscribers to measure how well their program was working for them. LIFT also explored how rapidly community solar has grown since its inception in 2006, publishing results in the Growth of U.S. Community Solar Serving LMI Households report. The results showed that community solar projects serving LMI households are one of the fastest growing segments of the solar industry. The report identifies and recommends ways developers should overcome real or perceived risks to LMI customer acquisition and subscriber management. Through the analysis of community solar project finance research, LIFT showed that most community solar projects serving LMI households are financed in the same ways mainstream community solar projects are financed. The value stacks and financial returns are no different, although LMI inclusion and participation rate varied across programs in our sample, ranging from between 10% and 100%. Based on the findings from the LIFT research, the team built a web-based user-friendly Toolkit, consisting of case studies, project finance best practices, and several tools built around the national dataset of 453 community solar projects that serve LMI households. These allow users to engage with the dataset in multiple ways; to explore the landscape of LMI community solar in the U.S., and to design community solar projects to optimize LMI inclusion, equity, and savings levels. The Toolkit also includes a library of LIFT-generated and LIFT-curated resources for users to learn more about how to best serve LMI communities through community solar. LIFT officially published the Toolkit on October 31, 2022, followed by a launch event (public webinar) on November 17, 2022. The core LIFT partners continue to engage in outreach and dissemination efforts to promote the LIFT Toolkit and research publications. Our driving motivation is to continue enabling solar developers to leverage the findings of this three-year research effort. By implication, the LIFT Toolkit is designed for use by utilities, energy service providers, and financiers or investors as a learning and decision-making tool to rapidly scale project models that optimize LMI inclusion and maximize real household savings.

14 SOLAR ENERGY↗

Analysis of US Industrial Assessment Centers (IACs) implementation

Industrial energy assessments are a fundamental action toward developing a decarbonization strategy at any level. They provide an understanding of where energy efficiency opportunities exist and help to make informed business decisions about the costs and benefits of implementing sustainable policies and practices. This paper examines the effectiveness of the Department of Energy's Industrial Assessment Centers Program at providing useful energy-efficiency audits as well as the barriers faced by the program and plans for future growth and improvement. This paper presents an analysis of the program between 1981 and 2022, covering 20,290 industrial assessments and 151,198 recommendations, with $2.6 billion of recommended savings. The analysis includes a breakdown of the IAC recommendations and implemented projects based on both the industrial subsectors according to the Standard Industrial Classification code, energy type, and systems evaluated. The results include a 47 % implementation rate, a gap analysis to understand the missed opportunities, and a discussion about reasons for recommendation rejection. A comparison of the IAC Program with other country-level energy auditing or assessment programs was conducted, and suggestions for improving implementation rates were mentioned.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Anthropogenic Pathways for Modeling and Managing Future Arctic Fires

Wildland fires, including extreme fire events and seasons, are becoming more common in the boreal and Arctic regions due to climate change. Current climate modeling approaches do not include country- or region-specific socioeconomic pathways that specifically address the drivers of and potential mitigation techniques for wildland fires. Forest management, energy extraction, and tourism, together with firefighting capacity and readiness as well as fuels treatment, can have a significant impact on future wildland fire risks and impacts. To assess the impacts of anthropogenic factors and to align with previous work done on shared socioeconomic pathways (SSPs), climate pathways for future wildfires up to 2050 were created for the states that compose the original Arctic Council countries: Canada, the United States, the Kingdom of Denmark, Iceland, Sweden, Norway, and Finland as well as the Russian Federation (with whom the other seven countries withdrew participation from in May 2022 due to the invasion and ongoing war in Ukraine). High and low fire activity and risk pathways for all states comprising the Arctic were made, with expert ‘best guess’ pathways for each state created separately to represent the middle of road. The low activity and low fire risk pathways, named “We Got This”, assume active fire suppression via citizenry participation and official land management, efficient and extensive fuel treatments, and consistent and active wildland firefighting for each new ignition. The high activity and high fire risk pathways, named “Let It Burn”, assume nearly the opposite, due to lack of government and community response and no action on climate change drivers that increase wildland fire risk. The ‘best guess’ pathway, named “The Fire Will Come”, indicates that some countries are currently on the pathway for less fire compared to other Arctic and Boreal states but not a ‘no-fire’ future. For example, in the Nordic countries, human ignition sources from tourism, timber and energy extraction, summer cottages, and expanding wildland-urban intermix due to exurban growth may increase. In North America, these same risks will apply but also may see an expansion of agriculture that increases the likelihood of open burning in croplands. Drier fuel condition and extreme heat events due to climate change create favorable conditions for extreme wildfires from any ignition source. Throughout the Arctic and boreal lightning is expected to increase, increasing the risk of tundra fires in addition to forest fires in hard-to-reach locations that are more difficult to coordinate and execute wildland firefighting. To move the future Arctic fire SSPs forward, several short-term and long-term actions must be completed. Certain data needs are required, like a harmonized pan-Arctic and pan-boreal fuels geospatial product, while also a need to refine and socialize current definitions of fire seasons and fire management – including developing an open-source system to track and share innovation, mitigation, and adaptation strategies across Arctic states.

Arctic↗

SMART Mobility. Urban Science Capstone Report

The U.S. Department of Energy’s Systems and Modeling for Accelerated Research in Transportation (SMART) Mobility Consortium is a multiyear, multi-laboratory collaborative, managed by the Energy Efficient Mobility Systems Program of the Office of Energy Efficiency and Renewable Energy, Vehicle Technologies Office, dedicated to further understanding the energy implications and opportunities of advanced mobility technologies and services. The Urban Science (US) Pillar focuses on maximum-mobility and minimum-energy opportunities associated with emerging transportation and transportation-related technologies specifically within the urban context. Such technologies, often referred to as automated, connected, efficient (or electrified), and shared (ACES), have the potential to greatly improve mobility and related quality of life in urban areas. Although all the SMART Mobility research pillars share some commonalities, Urban Science strives to model, analyze, and gain insights from the perspective of human settlements (the “city”) as a living organism. This is especially critical as the United States is one of the most urbanized countries, and as more and more of the global population migrates to urban areas.1 The urban mobility system consists of a complex network that reaches well beyond roads and vehicles and includes significant investments in public transit, private mobility services (such as taxis and transportation network companies, or TNCs), significant parking reserves, and curb management practices, not to mention the abundance of emerging on-demand micromobility services for the movement of people and goods such as e-bikes and scooters, which make the urban space a dynamic laboratory for mobility. Urban spaces also concentrate employment, markets, services, and attractions, which are the destinations for most trips. The concentration of human activities and ensuing density also creates the need and emphasis for space efficiency in urban environments, which is often less of a constraint in suburban or rural contexts. This mixture of transportation and mobility infrastructure and practice, combined with global urbanization trends, make urban spaces a critical focus of research for developing energy-efficient mobility systems (EEMS).

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Quo Vadis Payload Safety?

As we complete the preparations for the fourth Hubble Space Telescope (HST) servicing mission, we note an anniversary approaching: it was 30 years ago in July that the first HST payload safety review panel meeting was held. This, in turn, was just over a year after the very first payload safety review, a Phase 0 review for the Tracking and Data Relay Satellite and its Inertial Upper Stage, held in June of 1977. In adapting a process that had been used in the review and certification of earlier Skylab payloads, National Aeronautics and Space Administration (NASA) engineers sought to preserve the lessons learned in the development of technical payload safety requirements, while creating a new process that would serve the very different needs of the new space shuttle program. Their success in this undertaking is substantiated by the fact that this process and these requirements have proven to be remarkably robust, flexible, and adaptable. Furthermore, the payload safety process has, to date, served us well in the critical mission of safeguarding our astronauts, cosmonauts, and spaceflight participants. Both the technical requirements and their interpretation, as well as the associated process requirements have grown, evolved, been streamlined, and have been adapted to fit multiple programs, including the International Space Station (ISS) program, the Shuttle/Mir program, and most recently the United States Constellation program. From its earliest days, it was anticipated that the payload safety process would be international in scope, and so it has been. European Space Agency (ESA), Japan Aerospace Exploration Agency (JAXA), German Space Agency (DLR), Canadian Space Agency (CSA), Russian Space Agency (RSA), and many additional countries have flown payloads on both the space shuttle and on the ISS. Our close cooperation and long-term working relationships have culminated in the franchising of the payload safety review process itself to our partners in ESA, which in turn will serve as a roadmap for extending the franchise to other Partners.

Fodroci, Michael P.↗

Quantifying Water Storage Change and Land Subsidence Induced by Reservoir Impoundment Using GRACE, Landsat, and GPS Data

The construction of hydropower dams is a common strategy to support a country's increasing need for electricityand river water management for industry and agriculture. Although the hydrological and geophysical impacts ofwater relocation are usually assessed prior to impoundment, their accuracy is generally limited due to the lack ofin situ observations, especially in a remote area. This study presents a workflow to quantify the terrestrial waterstorage change (TWS) and land subsidence induced by a reservoir's water impoundment using multiple satelliteobservations (GRACE, Landsat), land surface models (CABLE, GLDAS, NCEP, ECMWF), and GPS data. The studysite is the Bakun Dam, located in Sarawak, Malaysia, which is the largest hydropower dam in Southeast Asia.Commencing operation in late 2010, the dam induced a change of water mass and lake surface area that wasclearly observed by GRACE and Landsat observations, respectively. During the 17-month impounding period(from August 2010 to December 2011), GRACE observed a dramatic increase of approximately 200mmequivalent water height, while Landsat detected an increased lake extent of around 600 km2. In this paper, aforward model is developed to determine the increased water surface level corresponding to GRACE observations,estimated to be about 120 m. In contrast to GRACE, the TWS derived from land surface models cannotcapture the increased TWS, due to the lack of reservoir routing algorithms in the models. In addition, the landsubsidence was calculated using the disk load model constructed based on the GRACE-derived lake level andLandsat-derived lake extent; the result is validated with the GPS data from BIN1 station, located at the westerncoast of Borneo. The commencement stage of the Bakun Dam induces the large-scale land subsidence, whichcauses the GPS-BIN1 station to subside by ~9 mm, and move toward the Bakun Lake by ~4 mm. Computation ofthe surface displacements directly from GRACE spherical harmonic coefficient data fails to capture the subsidencefeature, mainly due to the truncation error. Overall, this study demonstrates that evaluating GRACE inconjunction with Landsat, LSMs, and GPS data allows the exploitation of the gravity signal at a much smallerspatial scale than its intrinsic resolution. Benefiting from global coverage, the newly developed satellite-basedalgorithm is a valuable tool for assessing the impacts of reservoir operation on hydrological and geophysicalchanges from local to regional scales.

Tangdamrongsub, Natthachet↗