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At least 127 records · Page 7

Observed Impacts

Agricultural applications of El Nino forecasts are already underway in some countries and need to be evaluated or re-evaluated. For example, in Peru, El Nino forecasts have been incorporated into national planning for the agricultural sector, and areas planted with rice and cotton (cotton being the more drought-tolerant crop) are adjusted accordingly. How well are this and other such programs working? Such evaluations will contribute to the governmental and intergovernmental institutions, including the Inter-American Institute for Global Change Research and the US National Ocean and Atmospheric Agency that are fostering programs to aid the effective use of forecasts. This research involves expanding, deepening, and applying the understanding of physical climate to the fields of agronomy and social science; and the reciprocal understanding of crop growth and farm economics to climatology. Delivery of a regional climate forecast with no information about how the climate forecast was derived limits its effectiveness. Explanation of a region's major climate driving forces helps to place a seasonal forecast in context. Then, a useful approach is to show historical responses to previous El Nino events, and projections, with uncertainty intervals, of crop response from dynamic process crop growth models. Regional forecasts should be updated with real-time weather conditions. Since every El Nino event is different, it is important to track, report and advise on each new event as it unfolds.

Rosenzweig, Cynthia↗

Section on Observed Impacts on El Nino

Agricultural applications of El Nino forecasts are already underway in some countries and need to be evaluated or re-evaluated. For example, in Peru, El Nino forecasts have been incorporated into national planning for the agricultural sector, and areas planted with rice and cotton (cotton being the more drought-tolerant crop) are adjusted accordingly. How well are this and other such programs working? Such evaluations will contribute to the governmental and intergovernmental institutions, including the Inter-American Institute for Global Change Research and the US National Ocean and Atmospheric Agency that are fostering programs to aid the effective use of forecasts. As El Nino climate forecasting grows out of the research mode into operational mode, the research focus shifts to include the design of appropriate modes of utilization. Awareness of and sensitivity to the costs of prediction errors also grow. For example, one major forecasting model failed to predict the very large El Nino event of 1997, when Pacific sea-surface temperatures were the highest on record. Although simple correlations between El Nino events and crop yields may be suggestive, more sophisticated work is needed to understand the subtleties of the interplay among the global climate system, regional climate patterns, and local agricultural systems. Honesty about the limitations of an forecast is essential, especially when human livelihoods are at stake. An end-to-end analysis links tools and expertise from the full sequence of ENSO cause-and-effect processes. Representatives from many disciplines are needed to achieve insights, e.g, oceanographers and atmospheric scientists who predict El Nino events, climatologists who drive global climate models with sea-surface temperature predictions, agronomists who translate regional climate connections in to crop yield forecasts, and economists who analyze market adjustments to the vagaries of climate and determine the value of climate forecasts. Methods include historical studies to understand past patterns and to test hindcasts of the prediction tools, crop modeling, spatial analysis and remote sensing. This research involves expanding, deepening, and applying the understanding of physical climate to the fields of agronomy and social science; and the reciprocal understanding of crop growth and farm economics to climatology. Delivery of a regional climate forecast with no information about how the climate forecast was derived limits its effectiveness. Explanation of a region's major climate driving forces helps to place a seasonal forecast in context. Then, a useful approach is to show historical responses to previous El Nino events, and projections, with uncertainty intervals, of crop response from dynamic process crop growth models. Regional ID forecasts should be updated with real-time weather conditions. Since every El Nino event is different, it is important to track, report and advise on each new event as it unfolds. The stability of human enterprises depends on understanding both the potentialities and the limits of predictability. Farmers rely on past experience to anticipate and respond to fluctuations in the biophysical systems on which their livelihoods depend. Now scientists are improving their ability to predict some major elements of climate variability. The improvements in the reliability of El Nino forecasts are encouraging, but seasonal forecasts for agriculture are not, and will probably never be completely infallible, due to the chaotic nature of the climate system. Uncertainties proliferate as we extend beyond Pacific sea-surface temperatures to climate teleconnections and agricultural outcomes. The goal of this research is to shed as a clear light as possible on these inherent uncertainties and thus to contribute to the development of appropriate responses to El Nino and other seasonal forecasts for a range of stakeholders, which, ultimately, includes food consumers everywhere.

Rosenzweig, Cynthia↗

Organizations, Paradigms, and People: The Challenge of KM Interventions

This paper presents viewgraphs on Knowledge Management (KM) and how these interventions are put into practice by organizations and society. The topics include: 1) The Multiple Paradigm Tool; 2) Four Paradigms: tool for the Analyzing Organizations; 3) Assumptions About the Nature of Social Science; 4) Assumptions About the Nature of Society; 5) Schools of Sociological and Organizational Theory; 6) Meaning and Metaphors in the Four Paradigms; and 7) Possibilities and Conclusions.

Bailey, Teresa↗

Publication Bias ( The "File-Drawer Problem") in Scientific Inference

Publication bias arises whenever the probability that a study is published depends on the statistical significance of its results. This bias, often called the file-drawer effect since the unpublished results are imagined to be tucked away in researchers' file cabinets, is potentially a severe impediment to combining the statistical results of studies collected from the literature. With almost any reasonable quantitative model for publication bias, only a small number of studies lost in the file-drawer will produce a significant bias. This result contradicts the well known Fail Safe File Drawer (FSFD) method for setting limits on the potential harm of publication bias, widely used in social, medical and psychic research. This method incorrectly treats the file drawer as unbiased, and almost always miss-estimates the seriousness of publication bias. A large body of not only psychic research, but medical and social science studies, has mistakenly relied on this method to validate claimed discoveries. Statistical combination can be trusted only if it is known with certainty that all studies that have been carried out are included. Such certainty is virtually impossible to achieve in literature surveys.

Scargle, Jeffrey D.↗

Severe Space Weather Events--Understanding Societal and Economic Impacts: A Workshop Report - Extended Summary

The effects of space weather on modern technological systems are well documented in both the technical literature and popular accounts. Most often cited perhaps is the collapse within 90 seconds of northeastern Canada's Hydro-Quebec power grid during the great geomagnetic storm of March 1989, which left millions of people without electricity for up to 9 hours. This event exemplifies the dramatic impact that severe space weather can have on a technology upon which modern society critically depends. Nearly two decades have passed since the March 1989 event. During that time, awareness of the risks of severe space weather has increased among the affected industries, mitigation strategies have been developed, new sources of data have become available, new models of the space environment have been created, and a national space weather infrastructure has evolved to provide data, alerts, and forecasts to an increasing number of users. Now, 20 years later and approaching a new interval of increased solar activity, how well equipped are we to manage the effects of space weather? Have recent technological developments made our critical technologies more or less vulnerable? How well do we understand the broader societal and economic impacts of severe space weather events? Are our institutions prepared to cope with the effects of a 'space weather Katrina,' a rare, but according to the historical record, not inconceivable eventuality? On May 22 and 23, 2008, a one-and-a-half-day workshop held in Washington, D.C., under the auspices of the National Research Council's (NRC's) Space Studies Board brought together representatives of industry, the federal government, and the social science community to explore these and related questions. The key themes, ideas, and insights that emerged during the presentations and discussions are summarized in 'Severe Space Weather Events--Understanding Societal and Economic Impacts: A Workshop Report' (The National Academies Press, Washington, D.C., 2008), which was prepared by the Committee on the Societal and Economic Impacts of Severe Space Weather Events: A Workshop. The present document is an expanded summary of that report.

Source record↗

Organizational Influences on Interdisciplinary Interactions during Research and Design of Large-Scale Complex Engineered Systems

The design of large-scale complex engineered systems (LaCES) such as an aircraft is inherently interdisciplinary. Multiple engineering disciplines, drawing from a team of hundreds to thousands of engineers and scientists, are woven together throughout the research, development, and systems engineering processes to realize one system. Though research and development (R&D) is typically focused in single disciplines, the interdependencies involved in LaCES require interdisciplinary R&D efforts. This study investigates the interdisciplinary interactions that take place during the R&D and early conceptual design phases in the design of LaCES. Our theoretical framework is informed by both engineering practices and social science research on complex organizations. This paper provides preliminary perspective on some of the organizational influences on interdisciplinary interactions based on organization theory (specifically sensemaking), data from a survey of LaCES experts, and the authors experience in the research and design. The analysis reveals couplings between the engineered system and the organization that creates it. Survey respondents noted the importance of interdisciplinary interactions and their significant benefit to the engineered system, such as innovation and problem mitigation. Substantial obstacles to interdisciplinarity are uncovered beyond engineering that include communication and organizational challenges. Addressing these challenges may ultimately foster greater efficiencies in the design and development of LaCES and improved system performance by assisting with the collective integration of interdependent knowledge bases early in the R&D effort. This research suggests that organizational and human dynamics heavily influence and even constrain the engineering effort for large-scale complex systems.

McGowan, Anna-Maria R.↗

Mapping Impervious Surfaces Globally at 30m Resolution Using Global Land Survey Data

Impervious surfaces, mainly artificial structures and roads, cover less than 1% of the world's land surface (1.3% over USA). Regardless of the relatively small coverage, impervious surfaces have a significant impact on the environment. They are the main source of the urban heat island effect, and affect not only the energy balance, but also hydrology and carbon cycling, and both land and aquatic ecosystem services. In the last several decades, the pace of converting natural land surface to impervious surfaces has increased. Quantitatively monitoring the growth of impervious surface expansion and associated urbanization has become a priority topic across both the physical and social sciences. The recent availability of consistent, global scale data sets at 30m resolution such as the Global Land Survey from the Landsat satellites provides an unprecedented opportunity to map global impervious cover and urbanization at this resolution for the first time, with unprecedented detail and accuracy. Moreover, the spatial resolution of Landsat is absolutely essential to accurately resolve urban targets such a buildings, roads and parking lots. With long term GLS data now available for the 1975, 1990, 2000, 2005 and 2010 time periods, the land cover/use changes due to urbanization can now be quantified at this spatial scale as well. In the Global Land Survey - Imperviousness Mapping Project (GLS-IMP), we are producing the first global 30 m spatial resolution impervious cover data set. We have processed the GLS 2010 data set to surface reflectance (8500+ TM and ETM+ scenes) and are using a supervised classification method using a regression tree to produce continental scale impervious cover data sets. A very large set of accurate training samples is the key to the supervised classifications and is being derived through the interpretation of high spatial resolution (approx. 2 m or less) commercial satellite data (Quickbird and Worldview2) available to us through the unclassified archive of the National Geospatial Intelligence Agency (NGA). For each continental area several million training pixels are derived by analysts using image segmentation algorithms and tools and then aggregated to the 30m resolution of Landsat. Here we will discuss the production/testing of this massive data set for Europe, North and South America and Africa, including assessments of the 2010 surface reflectance data. This type of analysis is only possible because of the availability of long term 30m data sets from GLS and shows much promise for integration of Landsat 8 data in the future.

global land survey↗

Characterization of Evidence for Human System Risk Assessment

Understanding the kinds of evidence available and using the best evidence to answer a question is critical to evidenced-based decision-making, and it requires synthesis of evidence from a variety of sources. Categorization of human system risks in spaceflight, in particular, focuses on how well the integration and interpretation of all available evidence informs the risk statement that describes the relationship between spaceflight hazards and an outcome of interest. A mature understanding and categorization of these risks requires: 1) sufficient characterization of risk, 2) sufficient knowledge to determine an acceptable level of risk (i.e., a standard), 3) development of mitigations to meet the acceptable level of risk, and 4) identification of factors affecting generalizability of the evidence to different design reference missions. In the medical research community, evidence is often ranked by increasing confidence in findings gleaned from observational and experimental research (e.g., "levels of evidence"). However, an approach based solely on aspects of experimental design is problematic in assessing human system risks for spaceflight. For spaceflight, the unique challenges and opportunities include: (1) The independent variables in most evidence are the hazards of spaceflight, such as space radiation or low gravity, which cannot be entirely duplicated in terrestrial (Earth-based) analogs, (2) Evidence is drawn from multiple sources including medical and mission operations, Lifetime Surveillance of Astronaut Health (LSAH), spaceflight research (LSDA), and relevant environmental & terrestrial databases, (3) Risk metrics based primarily on LSAH data are typically derived from available prevalence or incidence data, which may limit rigorous interpretation, (4) The timeframe for obtaining adequate spaceflight sample size (n) is very long, given the small population, (5) Randomized controlled trials are unattainable in spaceflight, (6) Collection of personal and environmental data on the astronaut population may create opportunities for advanced analytics and human-environment modeling that goes beyond that achieved in isolated experimental designs; and (7) Translation of relevant research to operations is a complex, transdisciplinary enterprise in which the approach must apply across the physical, biological, behavioral, and social sciences. The approach to synthesizing evidence must address both source and fidelity of data, and reflect the most general attributes of quality of evidence in science and engineering: reliability and validity. The authors are developing a two-factor approach which includes the various kinds of evidence required to understand risks and for the integrated interpretation of all evidence that is essential to develop standards and countermeasures. A unified framework for aggregating and assessing different kinds of evidence provides a consistent, traceable, evidence-based decision-making process to translate research to operations in an environment where engineers, scientists, physicians, and managers all engage in analyzing the trade space of vehicle design, standards, requirements and solutions for spaceflight.

Steinberg, S. L.↗

Working at the Speed of Innovation: Impedance Mismatch in Rapid and Innovation Projects

In this paper we report on the results of an ethnographic study of a rapid design innovation (RDI) experiment in NASA Aeronautics. This work is based on the study of the Aeronautics Autonomy Testbed Capability (AATC) team in the Convergent Aeronautics Solutions (CAS) project. This paper focuses on and summarizes one of the key over-arching findings from the study: there is a significant mismatch in the organizational culture in the rest of the organization compared with that required for RDI. And, if this organizational cultural mismatch is not addressed, the likelihood of any organization being able to advance a new and different type of work (such as RDI) will be jeopardized. We delineate several aspects of the two different cultures identified in order to enable leaders and practitioners to better understand what contributes to the cultural dissonance and the implications of the differences in the cultures. As well, we identify ways in which those differences can be addressed. Research from organization and other social sciences are incorporated to highlight the differences. The implications of the research suggest that the significant cultural differences trigger a strong and resistive response from the dominant culture that may negate leadership’s strategy to build the new capacity for RDI. While the research results noted the pervasive nature of innovation throughout the workplace, the type of innovation envisioned in RDI is a rare type of innovation that requires significantly new methods, work processes, tools, and skills such that approaches used in the dominate culture cannot be adopted by expediting the existing approaches. Examples include: innovation teaming and leadership; the need for adaptive leadership that changes the relationship of a research leader to the other researchers; and, an interdisciplinary teaming approach which shapes team relationships and activities. Each of these aspects requires new teaming, tools, and skills in order to succeed. Thus, when introducing RDI activities where there is a different dominant culture, teams need to be: well trained; protected; recognized and rewarded. And, team leaders must also be trained in the unique types of teaming and innovation tools used in RDI. Both RDI teaming and team leadership must be sanctioned, supported, and rewarded by leadership. Because of the cultural mismatch, in some organizations looking to add RDI to their existing and established organizations, sep to avoid or mitigate the negative impact of the culture mismatch.

Crain, Cathleen↗

A NASA GISTEMP Observational Uncertainty Ensemble: Regional and Monthly Uncertainty

The historical global temperature record is an essential data product for quantifying the variability and change of the Earth system. In recent years, better characterization of observational uncertainty in global and hemispheric trends has become available, but the methodologies are not necessarily applicable to analyses at smaller regional areas, or monthly means, where station sparsity and other systematic issues contribute to greater uncertainty. This work details a gridded uncertainty ensemble of historical temperature anomalies from the Goddard Institute for Space Studies (GISS) Surface Temperature product (GISTEMP) product. This ensemble characterizes the complex spatial and temporal correlation structure of uncertainty in gridded historical temperature, enabling proper uncertainty propagation for climate and social science at regional and monthly scales. This work details the methodology for generating the uncertainty ensemble, key statistics of the uncertainty evolution over space and time, and provides best practices for using the uncertainty ensemble in future studies. Summary statistics from the uncertainty ensemble are in good agreement with production GISTEMP. Two applications of the uncertainty ensemble are also presented. First, the warmest year on record is shown to most likely be 2016 with a 53.2% chance and 2020 as the second most likely with a 44.4% chance. Second, it is shown that the arctic is warming 2.5 - 5 times faster than the globe, significantly faster than the regularly quoted twice as fast.

GISTEMP↗

Engineering A Bridge Across Cultures: Insights to Support Dialogue with Engineering Professionals on Ethical and Social Design Considerations

In April 2023, the National Aeronautics and Space Administration (NASA) hosted the Artemis and Ethics workshop at NASA headquarters, inviting 55 participants from a wide range of scholarly disciplines to participate in a dialogue on ethical considerations for Artemis and the Moon to Mars initiative. At this event, participants identified a set of challenges in engaging the ethical and social implications of these missions. This paper seeks to further explore those concepts from the workshop report and provide insights on how to discuss the design implications of engineering leadership decisions and to elicit meaningful engagement on these topics. This analysis can inform future research and educational approaches and help ethics and social science researchers to engage engineering and project leaders in constructive dialogue.

Artemis↗

LA100 Equity Strategies

In the Los Angeles 100% Renewable Energy Study (LA100), the National Renewable Energy Laboratory (NREL) found that the City of Los Angeles can achieve its ambitious goal of reliable, 100% carbon-free energy as early as 2035. While all communities will benefit from air quality and health improvements of clean energy, improving equity in participation and outcomes requires intentionally designed equity strategies. To plan for a clean energy future that benefits all Angelenos, the Los Angeles Department of Water and Power (LADWP), NREL, and the University of California Los Angeles (UCLA) partnered on the LA100 Equity Strategies project. In an innovative, community-informed approach, the LA100 Equity Strategies project integrated robust social science research techniques with rigorous data analysis - and incorporated what community members themselves know is needed to achieve a more equitable energy future. The team developed effective strategies for engaging communities, funding equitable technology and infrastructure investments, expanding existing clean energy and energy assistance programs, and designing new programs and policies to enhance equity.

community↗