Constructing Perceptions of Climate Change: a case study of regional political decision makers

NASA Astrophysics Data System (ADS)

Bray, D.

2012-12-01

This case study of climate change communications assesses the salient means of communication and the message adopted by regional political decision makers on the German Baltic coast. Realizing that cultural factors and local values (and not simply knowledge) are significant influences in explaining attitudes towards climate change, this analysis draws from the records of regional weather, from scientists with a specific focus on the region, from the political decision makers for that region, and the media message reaching the decision makers, ensuring all elements of the analysis are drawn from the same socioeconomic, geophysical, political and cultural context. This is important as the social dynamics surrounding the trust in science is of critical importance and, as such, all elements of the case study are specifically contained within a common context. If the utility of climate change knowledge is to prompt well conceived adaptation/mitigation strategies then the political decision process, or at least the perceptions shaping it, can best be understood by locating it within the world view of the decision makers involved in the production process. Using the results of two survey questionnaires, one of regional climate scientists and one of regional political decision makers, ten years of local weather records, and a summary of the message from mass media circulation, the discord in perceptions of regional climate change are quantitatively explored. The conclusions drawn from the analysis include, compared to the scientific assessment: The decision makers' perceptions of recent past differ from actual observations. The decision makers' perceptions of the future differ from scientific assessments. The decision makers tend to over estimate the magnitude of regional climate change and its impacts. The decision makers tend to over estimate the sense of immediacy for adaptation measures. The conclusions drawn suggest that in the regional political realm, it is often a social construction of climate change, not scientific claims, that are shaping decisions. While certainty is the common demand of those charged with making decisions concerning climate change, certainty is the quality that seems to be given least value in taking action. Weather records are all but ignored. The direct voice of scientists was heeded but not fully accepted. In the transition, the truth-to-power model appears to be somewhat modified, whereby power states that the future will be different, but the difference is determined by other sources; shaping images of risk and danger. One could not deny that climate and sea level have always been forces shaping patterns of human settlement. And one could not deny that perhaps the time is nigh to reassess the human relationship with nature. However, any measure considered should be done so with a rational sense of objectivity. To do otherwise, there is the risk of misallocating scare resources.

Groups Call for Better Protection From Climate Change and Severe Weather

NASA Astrophysics Data System (ADS)

Fellows, Jack

2008-11-01

With a newly elected U.S. president taking office in January, eight leading professional organizations in the field of weather and climate have called on the next administration and Congress to better protect the United States from severe weather and climate change. The groups' ``transition document,'' which was provided to John McCain and Barack Obama, includes five recommendations to reverse declining budgets and provide tools and information that local and regional decision makers need in trying to prepare for weather- and climate-related impacts. The organizations also have been collecting from the community names that the next president should consider for key weather- and climate-related leadership positions in his administration.

Developing a robust methodology for assessing the value of weather/climate services

NASA Astrophysics Data System (ADS)

Krijnen, Justin; Golding, Nicola; Buontempo, Carlo

2016-04-01

Increasingly, scientists involved in providing weather and climate services are expected to demonstrate the value of their work for end users in order to justify the costs of developing and delivering these services. This talk will outline different approaches that can be used to assess the socio-economic benefits of weather and climate services, including, among others, willingness to pay and avoided costs. The advantages and limitations of these methods will be discussed and relevant case-studies will be used to illustrate each approach. The choice of valuation method may be influenced by different factors, such as resource and time constraints and the end purposes of the study. In addition, there are important methodological differences which will affect the value assessed. For instance the ultimate value of a weather/climate forecast to a decision-maker will not only depend on forecast accuracy but also on other factors, such as how the forecast is communicated to and consequently interpreted by the end-user. Thus, excluding these additional factors may result in inaccurate socio-economic value estimates. In order to reduce the inaccuracies in this valuation process we propose an approach that assesses how the initial weather/climate forecast information can be incorporated within the value chain of a given sector, taking into account value gains and losses at each stage of the delivery process. By this we aim to more accurately depict the socio-economic benefits of a weather/climate forecast to decision-makers.

Community Coordinated Modeling Center: Paving the Way for Progress in Space Science Research to Operational Space Weather Forecasting

NASA Astrophysics Data System (ADS)

Kuznetsova, M. M.; Maddox, M. M.; Mays, M. L.; Mullinix, R.; MacNeice, P. J.; Pulkkinen, A. A.; Rastaetter, L.; Shim, J.; Taktakishvili, A.; Zheng, Y.; Wiegand, C.

2013-12-01

Community Coordinated Modeling Center (CCMC) was established at the dawn of the millennium as an essential element on the National Space Weather Program. One of the CCMC goals was to pave the way for progress in space science research to operational space weather forecasting. Over the years the CCMC acquired the unique experience in preparing complex models and model chains for operational environment, in developing and maintaining powerful web-based tools and systems ready to be used by space weather service providers and decision makers as well as in space weather prediction capabilities assessments. The presentation will showcase latest innovative solutions for space weather research, analysis, forecasting and validation and review on-going community-wide initiatives enabled by CCMC applications.

Developing future precipitation events from historic events: An Amsterdam case study.

NASA Astrophysics Data System (ADS)

Manola, Iris; van den Hurk, Bart; de Moel, Hans; Aerts, Jeroen

2016-04-01

Due to climate change, the frequency and intensity of extreme precipitation events is expected to increase. It is therefore of high importance to develop climate change scenarios tailored towards the local and regional needs of policy makers in order to develop efficient adaptation strategies to reduce the risks from extreme weather events. Current approaches to tailor climate scenarios are often not well adopted in hazard management, since average changes in climate are not a main concern to policy makers, and tailoring climate scenarios to simulate future extremes can be complex. Therefore, a new concept has been introduced recently that uses known historic extreme events as a basis, and modifies the observed data for these events so that the outcome shows how the same event would occur in a warmer climate. This concept is introduced as 'Future Weather', and appeals to the experience of stakeholders and users. This research presents a novel method of projecting a future extreme precipitation event, based on a historic event. The selected precipitation event took place over the broader area of Amsterdam, the Netherlands in the summer of 2014, which resulted in blocked highways, disruption of air transportation, flooded buildings and public facilities. An analysis of rain monitoring stations showed that an event of such intensity has a 5 to 15 years return period. The method of projecting a future event follows a non-linear delta transformation that is applied directly on the observed event assuming a warmer climate to produce an "up-scaled" future precipitation event. The delta transformation is based on the observed behaviour of the precipitation intensity as a function of the dew point temperature during summers. The outcome is then compared to a benchmark method using the HARMONIE numerical weather prediction model, where the boundary conditions of the event from the Ensemble Prediction System of ECMWF (ENS) are perturbed to indicate a warmer climate. The two methodologies are statistically compared and evaluated. The comparison between the historic event generated by the model and the observed event will give information on the realism of the model for this event. The comparison between the delta transformation method and the future simulation will provide information on how the dynamics would affect the precipitation field, as compared to the statistical method.

Irrigation water policy analysis using a business simulation game

NASA Astrophysics Data System (ADS)

Buchholz, M.; Holst, G.; Musshoff, O.

2016-10-01

Despite numerous studies on farmers' responses to changing irrigation water policies, uncertainties remain about the potential of water pricing schemes and water quotas to reduce irrigation. Thus far, policy impact analysis is predominantly based upon rational choice models that assume behavioral assumptions, such as a perfectly rational profit-maximizing decision maker. Also, econometric techniques are applied which could lack internal validity due to uncontrolled field data. Furthermore, such techniques are not capable of identifying ill-designed policies prior to their implementation. With this in mind, we apply a business simulation game for ex ante policy impact analysis of irrigation water policies at the farm level. Our approach has the potential to reveal the policy-induced behavioral change of the participants in a controlled environment. To do so, we investigate how real farmers from Germany, in an economic experiment, respond to a water pricing scheme and a water quota intending to reduce irrigation. In the business simulation game, the participants manage a "virtual" cash-crop farm for which they make crop allocation and irrigation decisions during several production periods, while facing uncertain product prices and weather conditions. The results reveal that a water quota is able to reduce mean irrigation applications, while a water pricing scheme does not have an impact, even though both policies exhibit equal income effects for the farmers. However, both policies appear to increase the variation of irrigation applications. Compared to a perfectly rational profit-maximizing decision maker, the participants apply less irrigation on average, both when irrigation is not restricted and when a water pricing scheme applies. Moreover, the participants' risk attitude affects the irrigation decisions.

When Astronomy Gets Closer to Home: Why space weather outreach is important and how to give it impact

NASA Astrophysics Data System (ADS)

Ferreira, B.

2014-12-01

When the public think about natural hazards, space weather is not the first thing to come to mind. Yet, though uncommon, extreme space weather events can have an economic impact similar to that of large floods or earthquakes. Although there have been efforts across various sectors of society to communicate this topic, many people are still quite confused about it, having only a limited understanding of the relevance of space weather in their daily lives. As such, it is crucial to properly communicate this topic to a variety of audiences. This article explores why we should communicate space weather research, how it can be framed for different audiences and how researchers, science communicators, policy makers and the public can raise awareness of the topic.

Metric optimisation for analogue forecasting by simulated annealing

NASA Astrophysics Data System (ADS)

Bliefernicht, J.; Bárdossy, A.

2009-04-01

It is well known that weather patterns tend to recur from time to time. This property of the atmosphere is used by analogue forecasting techniques. They have a long history in weather forecasting and there are many applications predicting hydrological variables at the local scale for different lead times. The basic idea of the technique is to identify past weather situations which are similar (analogue) to the predicted one and to take the local conditions of the analogues as forecast. But the forecast performance of the analogue method depends on user-defined criteria like the choice of the distance function and the size of the predictor domain. In this study we propose a new methodology of optimising both criteria by minimising the forecast error with simulated annealing. The performance of the methodology is demonstrated for the probability forecast of daily areal precipitation. It is compared with a traditional analogue forecasting algorithm, which is used operational as an element of a hydrological forecasting system. The study is performed for several meso-scale catchments located in the Rhine basin in Germany. The methodology is validated by a jack-knife method in a perfect prognosis framework for a period of 48 years (1958-2005). The predictor variables are derived from the NCEP/NCAR reanalysis data set. The Brier skill score and the economic value are determined to evaluate the forecast skill and value of the technique. In this presentation we will present the concept of the optimisation algorithm and the outcome of the comparison. It will be also demonstrated how a decision maker should apply a probability forecast to maximise the economic benefit from it.

Creating a Realistic Weather Environment for Motion-Based Piloted Flight Simulation

NASA Technical Reports Server (NTRS)

Daniels, Taumi S.; Schaffner, Philip R.; Evans, Emory T.; Neece, Robert T.; Young, Steve D.

2012-01-01

A flight simulation environment is being enhanced to facilitate experiments that evaluate research prototypes of advanced onboard weather radar, hazard/integrity monitoring (HIM), and integrated alerting and notification (IAN) concepts in adverse weather conditions. The simulation environment uses weather data based on real weather events to support operational scenarios in a terminal area. A simulated atmospheric environment was realized by using numerical weather data sets. These were produced from the High-Resolution Rapid Refresh (HRRR) model hosted and run by the National Oceanic and Atmospheric Administration (NOAA). To align with the planned flight simulation experiment requirements, several HRRR data sets were acquired courtesy of NOAA. These data sets coincided with severe weather events at the Memphis International Airport (MEM) in Memphis, TN. In addition, representative flight tracks for approaches and departures at MEM were generated and used to develop and test simulations of (1) what onboard sensors such as the weather radar would observe; (2) what datalinks of weather information would provide; and (3) what atmospheric conditions the aircraft would experience (e.g. turbulence, winds, and icing). The simulation includes a weather radar display that provides weather and turbulence modes, derived from the modeled weather along the flight track. The radar capabilities and the pilots controls simulate current-generation commercial weather radar systems. Appropriate data-linked weather advisories (e.g., SIGMET) were derived from the HRRR weather models and provided to the pilot consistent with NextGen concepts of use for Aeronautical Information Service (AIS) and Meteorological (MET) data link products. The net result of this simulation development was the creation of an environment that supports investigations of new flight deck information systems, methods for incorporation of better weather information, and pilot interface and operational improvements for better aviation safety. This research is part of a larger effort at NASA to study the impact of the growing complexity of operations, information, and systems on crew decision-making and response effectiveness; and then to recommend methods for improving future designs.

Insulation Material

NASA Technical Reports Server (NTRS)

1987-01-01

Apex Mills Corporation's superinsulators are used by makers of cold weather apparel, parkas, jackets, boots and outdoor gear such as sleeping bags. Their attraction in such applications is that radiant barrier insulation offers excellent warmth retention at minimal weight and bulk.

Integration of Weather Avoidance and Traffic Separation

NASA Technical Reports Server (NTRS)

Consiglio, Maria C.; Chamberlain, James P.; Wilson, Sara R.

2011-01-01

This paper describes a dynamic convective weather avoidance concept that compensates for weather motion uncertainties; the integration of this weather avoidance concept into a prototype 4-D trajectory-based Airborne Separation Assurance System (ASAS) application; and test results from a batch (non-piloted) simulation of the integrated application with high traffic densities and a dynamic convective weather model. The weather model can simulate a number of pseudo-random hazardous weather patterns, such as slow- or fast-moving cells and opening or closing weather gaps, and also allows for modeling of onboard weather radar limitations in range and azimuth. The weather avoidance concept employs nested "core" and "avoid" polygons around convective weather cells, and the simulations assess the effectiveness of various avoid polygon sizes in the presence of different weather patterns, using traffic scenarios representing approximately two times the current traffic density in en-route airspace. Results from the simulation experiment show that the weather avoidance concept is effective over a wide range of weather patterns and cell speeds. Avoid polygons that are only 2-3 miles larger than their core polygons are sufficient to account for weather uncertainties in almost all cases, and traffic separation performance does not appear to degrade with the addition of weather polygon avoidance. Additional "lessons learned" from the batch simulation study are discussed in the paper, along with insights for improving the weather avoidance concept. Introduction

The Future of Climate Science (Invited)

NASA Astrophysics Data System (ADS)

Bishop, R.

2010-12-01

High Performance Computing is currently deployed in several centers for climate research, but not at the levels needed to achieve substantial success on a global basis, given the complexity of the problem. A quantum leap in capabilities will be necessary to handle next-generation climate models that integrate newly emerging sciences, high-resolution grids, and voluminous observational data from satellites and sophisticated ground devices. Dr. Bishop will discuss efforts to build an International Centre for Earth Simulation (ICES) based in Switzerland that takes an holistic systems approach, and that has the competence and resources to achieve new insights in this new decade, and is capable to globally influence public policy with respect to weather, climate, environment, disaster risk reduction and socio-economic development. On this progressively crowded and fragile planet, such a capability will be invaluable, Bishop believes, if not imperative, for our long-term survival. ICES could serve as a test-bed for large scale public and private development planning. Decision makers could ask ‘what if’ questions for major construction projects (such as China’s Three Gorges Dam), and then interactively evaluate alternative scenarios. Likewise, ICES could help uncover the possible unintended consequences of climate remediation and adaptation strategies, geo-engineering ideas, CO2 sequestration, deep sea drilling, etc. ICES would be a resource for building more resilient societies in an era of rapid climate change and frequent natural disasters (such as flooding, extreme weather events and volcanic ash clouds), and therefore of great consequence to our future well-being. It would ultimately play a major role in the education and training of policy-makers, the public, and future Earth Scientists - in conjunction with the current national and regional centers.

Benefit from NASA

NASA Image and Video Library

1987-01-01

Radiation insulation technology from Apollo and subsequent spacecraft was used to develop superinsulators, used by makers of cold weather apparel, to make parkas, jackets, boots and outdoor gear such as sleeping bags. The radiant barrier technology offers warmth retention at minimal weight and bulk.

Radiation Insulation

NASA Technical Reports Server (NTRS)

1987-01-01

Radiation insulation technology from Apollo and subsequent spacecraft was used to develop superinsulators, used by makers of cold weather apparel, to make parkas, jackets, boots and outdoor gear such as sleeping bags. The radiant barrier technology offers warmth retention at minimal weight and bulk.

The Climate Disruption Challenge for Water Security in a Growing World

NASA Astrophysics Data System (ADS)

Paxton, L. J.; Nix, M.; Ihde, A.; MacDonald, L. H.; Parker, C.; Schaefer, R. K.; Weiss, M.; Babin, S. M.; Swartz, W. H.; Schloman, J.

2012-12-01

Climate disruption, the increasingly large and erratic departures of weather and climate from the benign conditions of the last one hundred years, is the greatest challenge to the long-term stability of world governments. Population growth, food and water security, energy supplies, and economic factors are, to some degree, within the control of governance and policy and all of these are impacted by climate disruption. Climate disruption, on the other hand, is not amenable to direct modification on the short timescales that commonly dictate governmental policy and human response. Global average temperatures will continue to increase even if there were immediate, profound changes in emission scenarios. Policy makers are faced with the very practical and immediate problem of determining what can one reasonably do to ameliorate the impact of climate disruption. The issue from a policy viewpoint is: how does one make effective policy when faced with a situation in which there are varied viewpoints in competition. How does one establish a consensus for action? What information "speaks" to policy makers? Water security is one such issue and provides an important, immediate, and tangible device to use when we examine how one can determine what policies can be effectively pursued. The Global Assimilation of Information for Action (GAIA) project creates a support environment to address the impact of climate disruption on global, national, regional, and/or local interests. The basic research community is concerned with the scientific aspects of predicting climate change in terms of environmental parameters such as rainfall, temperature and humidity while decision makers must deal with planning for a world that may be very different from the one we have grown accustomed to. Decision makers must deal with the long-term impacts on public health, agriculture, economic productivity, security, extreme weather, etc in an environment that has come to focus on short-term issues. To complicate matters, the information available from the climate studies community is couched in terms of model projections with "uncertainties" and a choice of emission scenarios that are often expressed in terms of the results of computer simulations and model output. GAIA develops actionable information and explores the interactions of policy and practice. Part of this framework is the development of "games". These realistic games include the elements of both agent-based and role simulation games in which subject matter experts interact in a realistic scenario to explore courses of action and their outcomes based on realistic, projected environments. We will present examples of some of the past work done at APL and examples of collaborative or competitive games that could be used to explore climate disruption in terms of social, political, and economic impacts. These games provide immediate, "tactile" experience of the implications of a choice of policy. In this talk we will suggest how this tool can be applied to problems like the Colorado River Basin or the Brahmaputra.

An Urban Resilience to Extreme Weather Events Framework for Development of Post Event Learning and Transformative Adaptation in Cities

NASA Astrophysics Data System (ADS)

Solecki, W. D.; Friedman, E. S.; Breitzer, R.

2016-12-01

Increasingly frequent extreme weather events are becoming an immediate priority for urban coastal practitioners and stakeholders, adding complexity to decisions concerning risk management for short-term action and long-term needs of city climate stakeholders. The conflict between the prioritization of short versus long-term events by decision-makers creates disconnect between climate science and its applications. The Consortium for Climate Risk in the Urban Northeast (CCRUN), a NOAA RISA team, is developing a set of mechanisms to help bridge this gap. The mechanisms are designed to promote the application of climate science on extreme weather events and their aftermath. It is in the post event policy window where significant opportunities for science-policy linkages exist. In particular, CCRUN is interested in producing actionable and useful information for city managers to use in decision-making processes surrounding extreme weather events and climate change. These processes include a sector specific needs assessment survey instrument and two tools for urban coastal practitioners and stakeholders. The tools focus on post event learning and connections between resilience and transformative adaptation. Elements of the two tools are presented. Post extreme event learning supports urban coastal practitioners and decision-makers concerned about maximizing opportunities for knowledge transfer and assimilation, and policy initiation and development following an extreme weather event. For the urban U.S. Northeast, post event learning helps coastal stakeholders build the capacity to adapt to extreme weather events, and inform and develop their planning capacity through analysis of past actions and steps taken in response to Hurricane Sandy. Connecting resilience with transformative adaptation is intended to promote resilience in urban Northeast coastal settings to the long-term negative consequences of extreme weather events. This is done through a knowledge co-production engagement process that links innovative and flexible adaptation pathways that can address requirements for short-term action and long-term needs.

Using Mesoscale Weather Model Output as Boundary Conditions for Atmospheric Large-Eddy Simulations and Wind-Plant Aerodynamic Simulations (Presentation)

DOE Office of Scientific and Technical Information (OSTI.GOV)

Churchfield, M. J.; Michalakes, J.; Vanderwende, B.

Wind plant aerodynamics are directly affected by the microscale weather, which is directly influenced by the mesoscale weather. Microscale weather refers to processes that occur within the atmospheric boundary layer with the largest scales being a few hundred meters to a few kilometers depending on the atmospheric stability of the boundary layer. Mesoscale weather refers to large weather patterns, such as weather fronts, with the largest scales being hundreds of kilometers wide. Sometimes microscale simulations that capture mesoscale-driven variations (changes in wind speed and direction over time or across the spatial extent of a wind plant) are important in windmore » plant analysis. In this paper, we present our preliminary work in coupling a mesoscale weather model with a microscale atmospheric large-eddy simulation model. The coupling is one-way beginning with the weather model and ending with a computational fluid dynamics solver using the weather model in coarse large-eddy simulation mode as an intermediary. We simulate one hour of daytime moderately convective microscale development driven by the mesoscale data, which are applied as initial and boundary conditions to the microscale domain, at a site in Iowa. We analyze the time and distance necessary for the smallest resolvable microscales to develop.« less

Field Scale Optimization for Long-Term Sustainability of Best Management Practices in Watersheds

NASA Astrophysics Data System (ADS)

Samuels, A.; Babbar-Sebens, M.

2012-12-01

Agricultural and urban land use changes have led to disruption of natural hydrologic processes and impairment of streams and rivers. Multiple previous studies have evaluated Best Management Practices (BMPs) as means for restoring existing hydrologic conditions and reducing impairment of water resources. However, planning of these practices have relied on watershed scale hydrologic models for identifying locations and types of practices at scales much coarser than the actual field scale, where landowners have to plan, design and implement the practices. Field scale hydrologic modeling provides means for identifying relationships between BMP type, spatial location, and the interaction between BMPs at a finer farm/field scale that is usually more relevant to the decision maker (i.e. the landowner). This study focuses on development of a simulation-optimization approach for field-scale planning of BMPs in the School Branch stream system of Eagle Creek Watershed, Indiana, USA. The Agricultural Policy Environmental Extender (APEX) tool is used as the field scale hydrologic model, and a multi-objective optimization algorithm is used to search for optimal alternatives. Multiple climate scenarios downscaled to the watershed-scale are used to test the long term performance of these alternatives and under extreme weather conditions. The effectiveness of these BMPs under multiple weather conditions are included within the simulation-optimization approach as a criteria/goal to assist landowners in identifying sustainable design of practices. The results from these scenarios will further enable efficient BMP planning for current and future usage.

Analysis of Surface Heterogeneity Effects with Mesoscale Terrestrial Modeling Platforms

NASA Astrophysics Data System (ADS)

Simmer, C.

2015-12-01

An improved understanding of the full variability in the weather and climate system is crucial for reducing the uncertainty in weather forecasting and climate prediction, and to aid policy makers to develop adaptation and mitigation strategies. A yet unknown part of uncertainty in the predictions from the numerical models is caused by the negligence of non-resolved land surface heterogeneity and the sub-surface dynamics and their potential impact on the state of the atmosphere. At the same time, mesoscale numerical models using finer horizontal grid resolution [O(1)km] can suffer from inconsistencies and neglected scale-dependencies in ABL parameterizations and non-resolved effects of integrated surface-subsurface lateral flow at this scale. Our present knowledge suggests large-eddy-simulation (LES) as an eventual solution to overcome the inadequacy of the physical parameterizations in the atmosphere in this transition scale, yet we are constrained by the computational resources, memory management, big-data, when using LES for regional domains. For the present, there is a need for scale-aware parameterizations not only in the atmosphere but also in the land surface and subsurface model components. In this study, we use the recently developed Terrestrial Systems Modeling Platform (TerrSysMP) as a numerical tool to analyze the uncertainty in the simulation of surface exchange fluxes and boundary layer circulations at grid resolutions of the order of 1km, and explore the sensitivity of the atmospheric boundary layer evolution and convective rainfall processes on land surface heterogeneity.

Mesoscale weather forecasting : technological and institutional challenges July 16, 1996 summary of proceedings

DOT National Transportation Integrated Search

1996-08-31

On October 26-27, 1995, over two hundred transportation leaders and decision-makers from around the nation convened in Cambridge, Massachusetts to participate in a two day symposium on "Challenges and Opportunities for Global Transportation in the 21...

Satellite Delivery of Aviation Weather Data

NASA Technical Reports Server (NTRS)

Kerczewski, Robert J.; Haendel, Richard

2001-01-01

With aviation traffic continuing to increase worldwide, reducing the aviation accident rate and aviation schedule delays is of critical importance. In the United States, the National Aeronautics and Space Administration (NASA) has established the Aviation Safety Program and the Aviation System Capacity Program to develop and test new technologies to increase aviation safety and system capacity. Weather is a significant contributor to aviation accidents and schedule delays. The timely dissemination of weather information to decision makers in the aviation system, particularly to pilots, is essential in reducing system delays and weather related aviation accidents. The NASA Glenn Research Center is investigating improved methods of weather information dissemination through satellite broadcasting directly to aircraft. This paper describes an on-going cooperative research program with NASA, Rockwell Collins, WorldSpace, Jeppesen and American Airlines to evaluate the use of satellite digital audio radio service (SDARS) for low cost broadcast of aviation weather information, called Satellite Weather Information Service (SWIS). The description and results of the completed SWIS Phase 1 are presented, and the description of the on-going SWIS Phase 2 is given.

The Analysis, Numerical Simulation, and Diagnosis of Extratropical Weather Systems

DTIC Science & Technology

2003-09-30

The Analysis, Numerical Simulation, and Diagnosis of Extratropical Weather Systems Dr. Melvyn A. Shapiro NOAA/Office of Weather and Air Quality...predictability of extratropical cyclones. APPROACH My approach toward achieving the above objectives has been to foster national and...TITLE AND SUBTITLE The Analysis, Numerical Simulation, and Diagnosis of Extratropical Weather Systems 5a. CONTRACT NUMBER 5b. GRANT NUMBER 5c. PROGRAM

Tool Integration and Environment Architectures

DTIC Science & Technology

1991-05-01

include the Interactive Development Environment (IDE) Software Through Pictures (STP), Sabre-C and FrameMaker coalition, and the Verdix Ada Development...System (VADS) APSE, which includes the VADS compiler and choices of CADRE Teamwork or STP and FrameMaker or Interleaf. The key characteristic of...remote procedure execution to achieve a simulation of a homoge- neous repository (i.e., a simulation that the data in a FrameMaker document resides in one

Towards more accurate wind and solar power prediction by improving NWP model physics

NASA Astrophysics Data System (ADS)

Steiner, Andrea; Köhler, Carmen; von Schumann, Jonas; Ritter, Bodo

2014-05-01

The growing importance and successive expansion of renewable energies raise new challenges for decision makers, economists, transmission system operators, scientists and many more. In this interdisciplinary field, the role of Numerical Weather Prediction (NWP) is to reduce the errors and provide an a priori estimate of remaining uncertainties associated with the large share of weather-dependent power sources. For this purpose it is essential to optimize NWP model forecasts with respect to those prognostic variables which are relevant for wind and solar power plants. An improved weather forecast serves as the basis for a sophisticated power forecasts. Consequently, a well-timed energy trading on the stock market, and electrical grid stability can be maintained. The German Weather Service (DWD) currently is involved with two projects concerning research in the field of renewable energy, namely ORKA*) and EWeLiNE**). Whereas the latter is in collaboration with the Fraunhofer Institute (IWES), the project ORKA is led by energy & meteo systems (emsys). Both cooperate with German transmission system operators. The goal of the projects is to improve wind and photovoltaic (PV) power forecasts by combining optimized NWP and enhanced power forecast models. In this context, the German Weather Service aims to improve its model system, including the ensemble forecasting system, by working on data assimilation, model physics and statistical post processing. This presentation is focused on the identification of critical weather situations and the associated errors in the German regional NWP model COSMO-DE. First steps leading to improved physical parameterization schemes within the NWP-model are presented. Wind mast measurements reaching up to 200 m height above ground are used for the estimation of the (NWP) wind forecast error at heights relevant for wind energy plants. One particular problem is the daily cycle in wind speed. The transition from stable stratification during nighttime to well mixed conditions during the day presents a big challenge to NWP models. Fast decrease and successive increase in hub-height wind speed after sunrise, and the formation of nocturnal low level jets will be discussed. For PV, the life cycle of low stratus clouds and fog is crucial. Capturing these processes correctly depends on the accurate simulation of diffusion or vertical momentum transport and the interaction with other atmospheric and soil processes within the numerical weather model. Results from Single Column Model simulations and 3d case studies will be presented. Emphasis is placed on wind forecasts; however, some references to highlights concerning the PV-developments will also be given. *) ORKA: Optimierung von Ensembleprognosen regenerativer Einspeisung für den Kürzestfristbereich am Anwendungsbeispiel der Netzsicherheitsrechnungen **) EWeLiNE: Erstellung innovativer Wetter- und Leistungsprognosemodelle für die Netzintegration wetterabhängiger Energieträger, www.projekt-eweline.de

Impact of derived global weather data on simulated crop yields

PubMed Central

van Wart, Justin; Grassini, Patricio; Cassman, Kenneth G

2013-01-01

Crop simulation models can be used to estimate impact of current and future climates on crop yields and food security, but require long-term historical daily weather data to obtain robust simulations. In many regions where crops are grown, daily weather data are not available. Alternatively, gridded weather databases (GWD) with complete terrestrial coverage are available, typically derived from: (i) global circulation computer models; (ii) interpolated weather station data; or (iii) remotely sensed surface data from satellites. The present study's objective is to evaluate capacity of GWDs to simulate crop yield potential (Yp) or water-limited yield potential (Yw), which can serve as benchmarks to assess impact of climate change scenarios on crop productivity and land use change. Three GWDs (CRU, NCEP/DOE, and NASA POWER data) were evaluated for their ability to simulate Yp and Yw of rice in China, USA maize, and wheat in Germany. Simulations of Yp and Yw based on recorded daily data from well-maintained weather stations were taken as the control weather data (CWD). Agreement between simulations of Yp or Yw based on CWD and those based on GWD was poor with the latter having strong bias and large root mean square errors (RMSEs) that were 26–72% of absolute mean yield across locations and years. In contrast, simulated Yp or Yw using observed daily weather data from stations in the NOAA database combined with solar radiation from the NASA-POWER database were in much better agreement with Yp and Yw simulated with CWD (i.e. little bias and an RMSE of 12–19% of the absolute mean). We conclude that results from studies that rely on GWD to simulate agricultural productivity in current and future climates are highly uncertain. An alternative approach would impose a climate scenario on location-specific observed daily weather databases combined with an appropriate upscaling method. PMID:23801639

Impact of derived global weather data on simulated crop yields.

PubMed

van Wart, Justin; Grassini, Patricio; Cassman, Kenneth G

2013-12-01

Crop simulation models can be used to estimate impact of current and future climates on crop yields and food security, but require long-term historical daily weather data to obtain robust simulations. In many regions where crops are grown, daily weather data are not available. Alternatively, gridded weather databases (GWD) with complete terrestrial coverage are available, typically derived from: (i) global circulation computer models; (ii) interpolated weather station data; or (iii) remotely sensed surface data from satellites. The present study's objective is to evaluate capacity of GWDs to simulate crop yield potential (Yp) or water-limited yield potential (Yw), which can serve as benchmarks to assess impact of climate change scenarios on crop productivity and land use change. Three GWDs (CRU, NCEP/DOE, and NASA POWER data) were evaluated for their ability to simulate Yp and Yw of rice in China, USA maize, and wheat in Germany. Simulations of Yp and Yw based on recorded daily data from well-maintained weather stations were taken as the control weather data (CWD). Agreement between simulations of Yp or Yw based on CWD and those based on GWD was poor with the latter having strong bias and large root mean square errors (RMSEs) that were 26-72% of absolute mean yield across locations and years. In contrast, simulated Yp or Yw using observed daily weather data from stations in the NOAA database combined with solar radiation from the NASA-POWER database were in much better agreement with Yp and Yw simulated with CWD (i.e. little bias and an RMSE of 12-19% of the absolute mean). We conclude that results from studies that rely on GWD to simulate agricultural productivity in current and future climates are highly uncertain. An alternative approach would impose a climate scenario on location-specific observed daily weather databases combined with an appropriate upscaling method. © 2013 John Wiley & Sons Ltd.

Modeling the influence of preferential flow on the spatial variability and time-dependence of mineral weathering rates

DOE PAGES

Pandey, Sachin; Rajaram, Harihar

2016-12-05

Inferences of weathering rates from laboratory and field observations suggest significant scale and time-dependence. Preferential flow induced by heterogeneity (manifest as permeability variations or discrete fractures) has been suggested as one potential mechanism causing scale/time-dependence. In this paper, we present a quantitative evaluation of the influence of preferential flow on weathering rates using reactive transport modeling. Simulations were performed in discrete fracture networks (DFNs) and correlated random permeability fields (CRPFs), and compared to simulations in homogeneous permeability fields. The simulations reveal spatial variability in the weathering rate, multidimensional distribution of reactions zones, and the formation of rough weathering interfaces andmore » corestones due to preferential flow. In the homogeneous fields and CRPFs, the domain-averaged weathering rate is initially constant as long as the weathering front is contained within the domain, reflecting equilibrium-controlled behavior. The behavior in the CRPFs was influenced by macrodispersion, with more spread-out weathering profiles, an earlier departure from the initial constant rate and longer persistence of weathering. DFN simulations exhibited a sustained time-dependence resulting from the formation of diffusion-controlled weathering fronts in matrix blocks, which is consistent with the shrinking core mechanism. A significant decrease in the domain-averaged weathering rate is evident despite high remaining mineral volume fractions, but the decline does not follow a math formula dependence, characteristic of diffusion, due to network scale effects and advection-controlled behavior near the inflow boundary. Finally, the DFN simulations also reveal relatively constant horizontally averaged weathering rates over a significant depth range, challenging the very notion of a weathering front.« less

Modeling the influence of preferential flow on the spatial variability and time-dependence of mineral weathering rates

DOE Office of Scientific and Technical Information (OSTI.GOV)

Pandey, Sachin; Rajaram, Harihar

Inferences of weathering rates from laboratory and field observations suggest significant scale and time-dependence. Preferential flow induced by heterogeneity (manifest as permeability variations or discrete fractures) has been suggested as one potential mechanism causing scale/time-dependence. In this paper, we present a quantitative evaluation of the influence of preferential flow on weathering rates using reactive transport modeling. Simulations were performed in discrete fracture networks (DFNs) and correlated random permeability fields (CRPFs), and compared to simulations in homogeneous permeability fields. The simulations reveal spatial variability in the weathering rate, multidimensional distribution of reactions zones, and the formation of rough weathering interfaces andmore » corestones due to preferential flow. In the homogeneous fields and CRPFs, the domain-averaged weathering rate is initially constant as long as the weathering front is contained within the domain, reflecting equilibrium-controlled behavior. The behavior in the CRPFs was influenced by macrodispersion, with more spread-out weathering profiles, an earlier departure from the initial constant rate and longer persistence of weathering. DFN simulations exhibited a sustained time-dependence resulting from the formation of diffusion-controlled weathering fronts in matrix blocks, which is consistent with the shrinking core mechanism. A significant decrease in the domain-averaged weathering rate is evident despite high remaining mineral volume fractions, but the decline does not follow a math formula dependence, characteristic of diffusion, due to network scale effects and advection-controlled behavior near the inflow boundary. Finally, the DFN simulations also reveal relatively constant horizontally averaged weathering rates over a significant depth range, challenging the very notion of a weathering front.« less

Simulation of a weather radar display for over-water airborne radar approaches

NASA Technical Reports Server (NTRS)

Clary, G. R.

1983-01-01

Airborne radar approach (ARA) concepts are being investigated as a part of NASA's Rotorcraft All-Weather Operations Research Program on advanced guidance and navigation methods. This research is being conducted using both piloted simulations and flight test evaluations. For the piloted simulations, a mathematical model of the airborne radar was developed for over-water ARAs to offshore platforms. This simulated flight scenario requires radar simulation of point targets, such as oil rigs and ships, distributed sea clutter, and transponder beacon replies. Radar theory, weather radar characteristics, and empirical data derived from in-flight radar photographs are combined to model a civil weather/mapping radar typical of those used in offshore rotorcraft operations. The resulting radar simulation is realistic and provides the needed simulation capability for ongoing ARA research.

Computational data sciences for assessment and prediction of climate extremes

NASA Astrophysics Data System (ADS)

Ganguly, A. R.

2011-12-01

Climate extremes may be defined inclusively as severe weather events or large shifts in global or regional weather patterns which may be caused or exacerbated by natural climate variability or climate change. This area of research arguably represents one of the largest knowledge-gaps in climate science which is relevant for informing resource managers and policy makers. While physics-based climate models are essential in view of non-stationary and nonlinear dynamical processes, their current pace of uncertainty reduction may not be adequate for urgent stakeholder needs. The structure of the models may in some cases preclude reduction of uncertainty for critical processes at scales or for the extremes of interest. On the other hand, methods based on complex networks, extreme value statistics, machine learning, and space-time data mining, have demonstrated significant promise to improve scientific understanding and generate enhanced predictions. When combined with conceptual process understanding at multiple spatiotemporal scales and designed to handle massive data, interdisciplinary data science methods and algorithms may complement or supplement physics-based models. Specific examples from the prior literature and our ongoing work suggests how data-guided improvements may be possible, for example, in the context of ocean meteorology, climate oscillators, teleconnections, and atmospheric process understanding, which in turn can improve projections of regional climate, precipitation extremes and tropical cyclones in an useful and interpretable fashion. A community-wide effort is motivated to develop and adapt computational data science tools for translating climate model simulations to information relevant for adaptation and policy, as well as for improving our scientific understanding of climate extremes from both observed and model-simulated data.

Directable weathering of concave rock using curvature estimation.

PubMed

Jones, Michael D; Farley, McKay; Butler, Joseph; Beardall, Matthew

2010-01-01

We address the problem of directable weathering of exposed concave rock for use in computer-generated animation or games. Previous weathering models that admit concave surfaces are computationally inefficient and difficult to control. In nature, the spheroidal and cavernous weathering rates depend on the surface curvature. Spheroidal weathering is fastest in areas with large positive mean curvature and cavernous weathering is fastest in areas with large negative mean curvature. We simulate both processes using an approximation of mean curvature on a voxel grid. Both weathering rates are also influenced by rock durability. The user controls rock durability by editing a durability graph before and during weathering simulation. Simulations of rockfall and colluvium deposition further improve realism. The profile of the final weathered rock matches the shape of the durability graph up to the effects of weathering and colluvium deposition. We demonstrate the top-down directability and visual plausibility of the resulting model through a series of screenshots and rendered images. The results include the weathering of a cube into a sphere and of a sheltered inside corner into a cavern as predicted by the underlying geomorphological models.

Simulated building energy demand biases resulting from the use of representative weather stations

DOE PAGES

Burleyson, Casey D.; Voisin, Nathalie; Taylor, Z. Todd; ...

2017-11-06

Numerical building models are typically forced with weather data from a limited number of “representative cities” or weather stations representing different climate regions. The use of representative weather stations reduces computational costs, but often fails to capture spatial heterogeneity in weather that may be important for simulations aimed at understanding how building stocks respond to a changing climate. Here, we quantify the potential reduction in temperature and load biases from using an increasing number of weather stations over the western U.S. Our novel approach is based on deriving temperature and load time series using incrementally more weather stations, ranging frommore » 8 to roughly 150, to evaluate the ability to capture weather patterns across different seasons. Using 8 stations across the western U.S., one from each IECC climate zone, results in an average absolute summertime temperature bias of ~4.0 °C with respect to a high-resolution gridded dataset. The mean absolute bias drops to ~1.5 °C using all available weather stations. Temperature biases of this magnitude could translate to absolute summertime mean simulated load biases as high as 13.5%. Increasing the size of the domain over which biases are calculated reduces their magnitude as positive and negative biases may cancel out. Using 8 representative weather stations can lead to a 20–40% bias of peak building loads during both summer and winter, a significant error for capacity expansion planners who may use these types of simulations. Using weather stations close to population centers reduces both mean and peak load biases. Our approach could be used by others designing aggregate building simulations to understand the sensitivity to their choice of weather stations used to drive the models.« less

Simulated building energy demand biases resulting from the use of representative weather stations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Burleyson, Casey D.; Voisin, Nathalie; Taylor, Z. Todd

Numerical building models are typically forced with weather data from a limited number of “representative cities” or weather stations representing different climate regions. The use of representative weather stations reduces computational costs, but often fails to capture spatial heterogeneity in weather that may be important for simulations aimed at understanding how building stocks respond to a changing climate. Here, we quantify the potential reduction in temperature and load biases from using an increasing number of weather stations over the western U.S. Our novel approach is based on deriving temperature and load time series using incrementally more weather stations, ranging frommore » 8 to roughly 150, to evaluate the ability to capture weather patterns across different seasons. Using 8 stations across the western U.S., one from each IECC climate zone, results in an average absolute summertime temperature bias of ~4.0 °C with respect to a high-resolution gridded dataset. The mean absolute bias drops to ~1.5 °C using all available weather stations. Temperature biases of this magnitude could translate to absolute summertime mean simulated load biases as high as 13.5%. Increasing the size of the domain over which biases are calculated reduces their magnitude as positive and negative biases may cancel out. Using 8 representative weather stations can lead to a 20–40% bias of peak building loads during both summer and winter, a significant error for capacity expansion planners who may use these types of simulations. Using weather stations close to population centers reduces both mean and peak load biases. Our approach could be used by others designing aggregate building simulations to understand the sensitivity to their choice of weather stations used to drive the models.« less

Simulated building energy demand biases resulting from the use of representative weather stations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Burleyson, Casey D.; Voisin, Nathalie; Taylor, Z. Todd

Numerical building models are typically forced with weather data from a limited number of “representative cities” or weather stations representing different climate regions. The use of representative weather stations reduces computational costs, but often fails to capture spatial heterogeneity in weather that may be important for simulations aimed at understanding how building stocks respond to a changing climate. We quantify the potential reduction in bias from using an increasing number of weather stations over the western U.S. The approach is based on deriving temperature and load time series using incrementally more weather stations, ranging from 8 to roughly 150, tomore » capture weather across different seasons. Using 8 stations, one from each climate zone, across the western U.S. results in an average absolute summertime temperature bias of 7.2°F with respect to a spatially-resolved gridded dataset. The mean absolute bias drops to 2.8°F using all available weather stations. Temperature biases of this magnitude could translate to absolute summertime mean simulated load biases as high as 13.8%, a significant error for capacity expansion planners who may use these types of simulations. Increasing the size of the domain over which biases are calculated reduces their magnitude as positive and negative biases may cancel out. Using 8 representative weather stations can lead to a 20-40% overestimation of peak building loads during both summer and winter. Using weather stations close to population centers reduces both mean and peak load biases. This approach could be used by others designing aggregate building simulations to understand the sensitivity to their choice of weather stations used to drive the models.« less

A Fresh Look at Weather Impact on Peak Electricity Demand and Energy Use of Buildings Using 30-Year Actual Weather Data

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hong, Tianzhen; Chang, Wen-Kuei; Lin, Hung-Wen

Buildings consume more than one third of the world?s total primary energy. Weather plays a unique and significant role as it directly affects the thermal loads and thus energy performance of buildings. The traditional simulated energy performance using Typical Meteorological Year (TMY) weather data represents the building performance for a typical year, but not necessarily the average or typical long-term performance as buildings with different energy systems and designs respond differently to weather changes. Furthermore, the single-year TMY simulations do not provide a range of results that capture yearly variations due to changing weather, which is important for building energymore » management, and for performing risk assessments of energy efficiency investments. This paper employs large-scale building simulation (a total of 3162 runs) to study the weather impact on peak electricity demand and energy use with the 30-year (1980 to 2009) Actual Meteorological Year (AMY) weather data for three types of office buildings at two design efficiency levels, across all 17 ASHRAE climate zones. The simulated results using the AMY data are compared to those from the TMY3 data to determine and analyze the differences. Besides further demonstration, as done by other studies, that actual weather has a significant impact on both the peak electricity demand and energy use of buildings, the main findings from the current study include: 1) annual weather variation has a greater impact on the peak electricity demand than it does on energy use in buildings; 2) the simulated energy use using the TMY3 weather data is not necessarily representative of the average energy use over a long period, and the TMY3 results can be significantly higher or lower than those from the AMY data; 3) the weather impact is greater for buildings in colder climates than warmer climates; 4) the weather impact on the medium-sized office building was the greatest, followed by the large office and then the small office; and 5) simulated energy savings and peak demand reduction by energy conservation measures using the TMY3 weather data can be significantly underestimated or overestimated. It is crucial to run multi-decade simulations with AMY weather data to fully assess the impact of weather on the long-term performance of buildings, and to evaluate the energy savings potential of energy conservation measures for new and existing buildings from a life cycle perspective.« less

Climate change and natural disasters: integrating science and practice to protect health.

PubMed

Sauerborn, Rainer; Ebi, Kristie

2012-12-17

Hydro-meteorological disasters are the focus of this paper. The authors examine, to which extent climate change increases their frequency and intensity. Review of IPCC-projections of climate-change related extreme weather events and related literature on health effects. Projections show that climate change is likely to increase the frequency, intensity, duration, and spatial distribution of a range of extreme weather events over coming decades. There is a need for strengthened collaboration between climate scientists, the health researchers and policy-makers as well as the disaster community to jointly develop adaptation strategies to protect human.

Hazardous Convective Weather in the Central United States: Present and Future

NASA Astrophysics Data System (ADS)

Liu, C.; Ikeda, K.; Rasmussen, R.

2017-12-01

Two sets of 13-year continental-scale convection-permitting simulations were performed using the 4-km-resolution WRF model. They consist of a retrospective simulation, which downscales the ERA-Interim reanalysis during the period October 2000 - September 2013, and a future climate sensitivity simulation for the same period based on the perturbed reanalysis-derived boundary conditions with the CMIP5 ensemble-mean high-end emission scenario climate change. The evaluation of the retrospective simulation indicates that the model is able to realistically reproduce the main characteristics of deep precipitating convection observed in the current climate such as the spectra of convective population and propagating mesoscale convective systems (MCSs). It is also shown that severe convection and associated MCS will increase in frequency and intensity, implying a potential increase in high impact convective weather in a future warmer climate. In this study, the warm-season hazardous convective weather (i.e., tonadoes, hails and damaging gusty wind) in the central United states is examined using these 4-km downscaling simulations. First, a model-based proxy for hazardous convective weather is derived on the basis of a set of characteristic meteorological variables such as the model composite radar reflectivity, updraft helicity, vertical wind shear, and low-level wind. Second, the developed proxy is applied to the retrospective simulation for estimate of the model hazardous weather events during the historical period. Third, the simulated hazardous weather statistics are evaluated against the NOAA severe weather reports. Lastly, the proxy is applied to the future climate simulation for the projected change of hazardous convective weather in response to global warming. Preliminary results will be reported at the 2017 AGU session "High Resolution Climate Modeling".

Environmental Education, Drought and the Rural Man: Implications for Policy-Makers and Farmers in Sub-Saharan Africa.

ERIC Educational Resources Information Center

Ladele, Ademola A.

2001-01-01

Examines issues related to the nexus of some factors affecting the environment, specifically drought. Suggests that because small farmers are usually at the mercy of unpredictable weather, even simple tips on resource management, when properly packaged, could make tremendous change. (Contains 27 references.) (Author/YDS)

System Advisor Model, SAM 2014.1.14: General Description

DOE Office of Scientific and Technical Information (OSTI.GOV)

Blair, Nate; Dobos, Aron P.; Freeman, Janine

2014-02-01

This document describes the capabilities of the U.S. Department of Energy and National Renewable Energy Laboratory's System Advisor Model (SAM), Version 2013.9.20, released on September 9, 2013. SAM is a computer model that calculates performance and financial metrics of renewable energy systems. Project developers, policy makers, equipment manufacturers, and researchers use graphs and tables of SAM results in the process of evaluating financial, technology, and incentive options for renewable energy projects. SAM simulates the performance of photovoltaic, concentrating solar power, solar water heating, wind, geothermal, biomass, and conventional power systems. The financial model can represent financial structures for projects thatmore » either buy and sell electricity at retail rates (residential and commercial) or sell electricity at a price determined in a power purchase agreement (utility). SAM's advanced simulation options facilitate parametric and sensitivity analyses, and statistical analysis capabilities are available for Monte Carlo simulation and weather variability (P50/P90) studies. SAM can also read input variables from Microsoft Excel worksheets. For software developers, the SAM software development kit (SDK) makes it possible to use SAM simulation modules in their applications written in C/C++, C#, Java, Python, and MATLAB. NREL provides both SAM and the SDK as free downloads at http://sam.nrel.gov. Technical support and more information about the software are available on the website.« less

The impact of traffic emissions on air quality in the Berlin-Brandenburg region - a case study on cycling scenarios

NASA Astrophysics Data System (ADS)

Kuik, F.; Lauer, A.; von Schneidemesser, E.; Butler, T. M.

2016-12-01

Many European cities continue to struggle with exceedances of NO2 limit values at measurement sites near roads, of which a large contribution is attributed to emissions from traffic. In this study, we explore how urban air quality can be improved with different traffic measures using the example of the Berlin-Brandenburg region. In order to simulate urban background air quality we use the Weather Research and Forecasting model with chemistry (WRF-Chem) at a horizontal resolution of 1km. We use emission input data at a horizontal resolution of 1km obtained by downscaling TNO-MACC III emissions based on local proxy data including population and traffic densities. In addition we use a statistical approach combining the simulated urban background concentrations with information on traffic densities to estimate NO2 at street level. This helps assessing whether the emission scenarios studied here can lead to significant reductions in NO2 concentrations at street level. The emission scenarios in this study represent a range of scenarios in which car traffic is replaced with bicycle traffic. Part of this study was an initial discussion phase with stakeholders, including policy makers and NGOs. The discussions have shown that the different stakeholders are interested in a scientific assessment of the impact of replacing car traffic with bicycle traffic in the Berlin-Brandenburg urban area. Local policy makers responsible for city planning and implementing traffic measures can make best use of scientific modeling results if input data and scenarios are as realistic as possible. For these reasons, the scenarios cover very idealized optimistic ("all passenger cars are replaced by bicycles") and pessimistic ("all cyclists are replaced by cars") scenarios to explore the sensitivity of simulated urban background air quality to these changes, as well as additional scenarios based on city-specific data to analyze more realistic situations. Of particular interest is how these impact street level NO2 concentrations.

The Analysis, Numerical Simulation, and Diagnosis of Extratropical Weather Systems

DTIC Science & Technology

1999-09-30

The Analysis, Numerical Simulation, and Diagnosis of Extratropical Weather Systems Dr. Melvyn A. Shapiro NOAA/Environmental Technology Laboratory...formulation, and numerical prediction of the life cycles of synoptic-scale and mesoscale extratropical weather systems, including the influence of planetary...scale inter-annual and intra-seasonal variability on their evolution. These weather systems include: extratropical oceanic and land-falling cyclones

Alexander Hegedus Lightning Talk: Integrating Measurements to Optimize Space Weather Strategies

NASA Astrophysics Data System (ADS)

Hegedus, A. M.

2017-12-01

Alexander Hegedus is a PhD Candidate at the University of Michigan, and won an Outstanding Student Paper Award at the AGU 2016 Fall Meeting for his poster "Simulating 3D Spacecraft Constellations for Low Frequency Radio Imaging." In this short talk, Alex outlines his current research of analyzing data from both real and simulated instruments to answer Heliophysical questions. He then sketches out future plans to simulate science pipelines in a real-time data assimilation model that uses a Bayesian framework to integrate information from different instruments to determine the efficacy of future Space Weather Alert systems. MHD simulations made with Michigan's own Space Weather Model Framework will provide input to simulated instruments, acting as an Observing System Simulation Experiment to verify that a certain set of measurements can accurately predict different classes of Space Weather events.

Confronting data requirements and data provision in Space Weather: The Contribution of Long Term Archives. Part 1.

NASA Astrophysics Data System (ADS)

Heynderickx, Daniel; Glover, Alexi

Operational space weather services rely heavily on reliable data streams from spacecraft and ground-based facilities, as well as from services providing processed data products. This event focuses on an unusual solar maximum viewed from several different perspectives, and as such highlights the important contribution of long term archives in supporting space weather studies and services. We invite the space weather community to contribute to a discussion on the key topics listed below, with the aim of formulating recommendations and guidelines for policy makers, stakeholders, data and service providers: - facilitating access to and awareness of existing data resources - establishing clear guidelines for space weather data archives including data quality, interoperability and metadata standards - ensuring data ownership and terms of (re)use are clearly identified such that this information can be taken into account when (potentially commercial) services are developed based on data provided without charge for scientific purposes only All participants are invited to submit input for the discussion to the authors ahead of the Assembly. The outcome of the session will be formulated as a set of proposed panel recommendations.

Confronting data requirements and data provision in Space Weather: The Contribution of Long Term Archives. Part 2.

NASA Astrophysics Data System (ADS)

Glover, Alexi; Heynderickx, Daniel

Operational space weather services rely heavily on reliable data streams from spacecraft and ground-based facilities, as well as from services providing processed data products. This event focuses on an unusual solar maximum viewed from several different perspectives, and as such highlights the important contribution of long term archives in supporting space weather studies and services. We invite the space weather community to contribute to a discussion on the key topics listed below, with the aim of formulating recommendations and guidelines for policy makers, stakeholders, data and service providers: - facilitating access to and awareness of existing data resources - establishing clear guidelines for space weather data archives including data quality, interoperability and metadata standards - ensuring data ownership and terms of (re)use are clearly identified such that this information can be taken into account when (potentially commercial) services are developed based on data provided without charge for scientific purposes only All participants are invited to submit input for the discussion to the authors ahead of the Assembly. The outcome of the session will be formulated as a set of proposed panel recommendations.

Constrained optimization via simulation models for new product innovation

NASA Astrophysics Data System (ADS)

Pujowidianto, Nugroho A.

2017-11-01

We consider the problem of constrained optimization where the decision makers aim to optimize the primary performance measure while constraining the secondary performance measures. This paper provides a brief overview of stochastically constrained optimization via discrete event simulation. Most review papers tend to be methodology-based. This review attempts to be problem-based as decision makers may have already decided on the problem formulation. We consider constrained optimization models as there are usually constraints on secondary performance measures as trade-off in new product development. It starts by laying out different possible methods and the reasons using constrained optimization via simulation models. It is then followed by the review of different simulation optimization approach to address constrained optimization depending on the number of decision variables, the type of constraints, and the risk preferences of the decision makers in handling uncertainties.

National Space Weather Program Releases Strategy for the New Decade

NASA Astrophysics Data System (ADS)

Williamson, Samuel P.; Babcock, Michael R.; Bonadonna, Michael F.

2010-12-01

The National Space Weather Program (NSWP; http://www.nswp.gov) is a U.S. federal government interagency program established by the Office of the Federal Coordinator for Meteorology (OFCM) in 1995 to coordinate, collaborate, and leverage capabilities across stakeholder agencies, including space weather researchers, service providers, users, policy makers, and funding agencies, to improve the performance of the space weather enterprise for the United States and its international partners. Two important documents released in recent months have established a framework and the vision, goals, and strategy to move the enterprise forward in the next decade. The U.S. federal agency members of the NSWP include the departments of Commerce, Defense, Energy, Interior, State, and Transportation, plus NASA, the National Science Foundation, and observers from the White House Office of Science and Technology Policy (OSTP) and the Office of Management and Budget (OMB). The OFCM is also working with the Department of Homeland Security's Federal Emergency Management Agency to formally join the program.

Seven Experiment Designs Addressing Problems of Safety and Capacity on Two-Lane Rural Highways : Volume 2. Experimental Design to Develop and Evaluate Dynamic Aids for Narrow Bridges

DOT National Transportation Integrated Search

2000-01-24

The Federal Highway Administration (FHWA) of the U.S. Department of Transportation (USDOT) has a responsibility to coordinate and promote projects that will bring the best information on weather to decision makers, in order to improve performance of ...

Evaluating the accuracy of VEMAP daily weather data for application in crop simulations on a regional scale

USDA-ARS?s Scientific Manuscript database

Weather plays a critical role in eco-environmental and agricultural systems. Limited availability of meteorological records often constrains the applications of simulation models and related decision support tools. The Vegetation/Ecosystem Modeling and Analysis Project (VEMAP) provides daily weather...

Impact of number of realizations on the suitability of simulated weather data for hydrologic and environmental applications

USDA-ARS?s Scientific Manuscript database

Stochastic weather generators are widely used in hydrological, environmental, and agricultural applications to simulate and forecast weather time series. However, such stochastic processes usually produce random outputs hence the question on how representative the generated data are if obtained fro...

A mathematical analysis of the Janus combat simulation weather effects models and sensitivity analysis of sky-to-ground brightness ratio on target detection

NASA Astrophysics Data System (ADS)

Shorts, Vincient F.

1994-09-01

The Janus combat simulation offers the user a wide variety of weather effects options to employ during the execution of any simulation run, which can directly influence detection of opposing forces. Realistic weather effects are required if the simulation is to accurately reproduce 'real world' results. This thesis examines the mathematics of the Janus weather effects models. A weather effect option in Janus is the sky-to-ground brightness ratio (SGR). SGR affects an optical sensor's ability to detect targets. It is a measure of the sun angle in relation to the horizon. A review of the derivation of SGR is performed and an analysis of SGR's affect on the number of optical detections and detection ranges is performed using an unmanned aerial vehicle (UAV) search scenario. For comparison, the UAV's are equipped with a combination of optical and thermal sensors.

The Context Is the Message?! Learning about the Israeli-Palestinian Conflict through Computerized Simulations in Different National Contexts

ERIC Educational Resources Information Center

Kampf, Ronit

2016-01-01

Two cross-national experimental studies examined the effects of PeaceMaker and Global Conflicts on knowledge acquisition and attitude change regarding the Israeli-Palestinian conflict. PeaceMaker and Global Conflicts are role-playing computerized simulations of this conflict. 248 undergraduate students from Turkey, Israel, Palestine and the US…

Climate change and natural disasters – integrating science and practice to protect health

PubMed Central

Sauerborn, Rainer; Ebi, Kristie

2012-01-01

Background Hydro-meteorological disasters are the focus of this paper. The authors examine, to which extent climate change increases their frequency and intensity. Methods Review of IPCC-projections of climate-change related extreme weather events and related literature on health effects. Results Projections show that climate change is likely to increase the frequency, intensity, duration, and spatial distribution of a range of extreme weather events over coming decades. Conclusions There is a need for strengthened collaboration between climate scientists, the health researchers and policy-makers as well as the disaster community to jointly develop adaptation strategies to protect human. PMID:23273248

Games and Simulations for Climate, Weather and Earth Science Education

NASA Astrophysics Data System (ADS)

Russell, R. M.

2014-12-01

We will demonstrate several interactive, computer-based simulations, games, and other interactive multimedia. These resources were developed for weather, climate, atmospheric science, and related Earth system science education. The materials were created by the UCAR Center for Science Education. These materials have been disseminated via our web site (SciEd.ucar.edu), webinars, online courses, teacher workshops, and large touchscreen displays in weather and Sun-Earth connections exhibits in NCAR's Mesa Lab facility in Boulder, Colorado. Our group has also assembled a web-based list of similar resources, especially simulations and games, from other sources that touch upon weather, climate, and atmospheric science topics. We'll briefly demonstrate this directory. More info available at: scied.ucar.edu/events/agu-2014-games-simulations-sessions

Urban weather data and building models for the inclusion of the urban heat island effect in building performance simulation.

PubMed

Palme, M; Inostroza, L; Villacreses, G; Lobato, A; Carrasco, C

2017-10-01

This data article presents files supporting calculation for urban heat island (UHI) inclusion in building performance simulation (BPS). Methodology is used in the research article "From urban climate to energy consumption. Enhancing building performance simulation by including the urban heat island effect" (Palme et al., 2017) [1]. In this research, a Geographical Information System (GIS) study is done in order to statistically represent the most important urban scenarios of four South-American cities (Guayaquil, Lima, Antofagasta and Valparaíso). Then, a Principal Component Analysis (PCA) is done to obtain reference Urban Tissues Categories (UTC) to be used in urban weather simulation. The urban weather files are generated by using the Urban Weather Generator (UWG) software (version 4.1 beta). Finally, BPS is run out with the Transient System Simulation (TRNSYS) software (version 17). In this data paper, four sets of data are presented: 1) PCA data (excel) to explain how to group different urban samples in representative UTC; 2) UWG data (text) to reproduce the Urban Weather Generation for the UTC used in the four cities (4 UTC in Lima, Guayaquil, Antofagasta and 5 UTC in Valparaíso); 3) weather data (text) with the resulting rural and urban weather; 4) BPS models (text) data containing the TRNSYS models (four building models).

Design, Development, and Testing of a Network Frequency Selection Service (NFSS)

DTIC Science & Technology

1994-02-14

mercial simulation software (Sim++), word processor ( FrameMaker ), editor (Gnu Emacs), software ver- sion control (Revision Control System (RCS)), system...of FrameMaker ".mif" files. When viewed using FrameMaker or a PostScript reader, each page of results appears as two columns by four rows of graphics

Evaluating climate models: Should we use weather or climate observations?

DOE Office of Scientific and Technical Information (OSTI.GOV)

Oglesby, Robert J; Erickson III, David J

2009-12-01

Calling the numerical models that we use for simulations of climate change 'climate models' is a bit of a misnomer. These 'general circulation models' (GCMs, AKA global climate models) and their cousins the 'regional climate models' (RCMs) are actually physically-based weather simulators. That is, these models simulate, either globally or locally, daily weather patterns in response to some change in forcing or boundary condition. These simulated weather patterns are then aggregated into climate statistics, very much as we aggregate observations into 'real climate statistics'. Traditionally, the output of GCMs has been evaluated using climate statistics, as opposed to their abilitymore » to simulate realistic daily weather observations. At the coarse global scale this may be a reasonable approach, however, as RCM's downscale to increasingly higher resolutions, the conjunction between weather and climate becomes more problematic. We present results from a series of present-day climate simulations using the WRF ARW for domains that cover North America, much of Latin America, and South Asia. The basic domains are at a 12 km resolution, but several inner domains at 4 km have also been simulated. These include regions of complex topography in Mexico, Colombia, Peru, and Sri Lanka, as well as a region of low topography and fairly homogeneous land surface type (the U.S. Great Plains). Model evaluations are performed using standard climate analyses (e.g., reanalyses; NCDC data) but also using time series of daily station observations. Preliminary results suggest little difference in the assessment of long-term mean quantities, but the variability on seasonal and interannual timescales is better described. Furthermore, the value-added by using daily weather observations as an evaluation tool increases with the model resolution.« less

Student Workshops for Severe Weather Warning Decision Making using AWIPS-2 at the University of Oklahoma

NASA Astrophysics Data System (ADS)

Zwink, A. B.; Morris, D.; Ware, P. J.; Ernst, S.; Holcomb, B.; Riley, S.; Hardy, J.; Mullens, S.; Bowlan, M.; Payne, C.; Bates, A.; Williams, B.

2016-12-01

For several years, employees at the Cooperative Institute of Mesoscale Meteorological Studies at the University of Oklahoma (OU) that are affiliated with Warning Decision Training Division (WDTD) of the National Weather Service (NWS) provided training simulations to students from OU's School of Meteorology (SoM). These simulations focused on warning decision making using Dual-Pol radar data products in an AWIPS-1 environment. Building on these previous experiences, CIMMS/WDTD recently continued the collaboration with the SoM Oklahoma Weather Lab (OWL) by holding a warning decision workshop simulating a NWS Weather Forecast Office (WFO) experience. The workshop took place in the WDTD AWIPS-2 computer laboratory with 25 AWIPS-2 workstations and the WES-2 Bridge (Weather Event Simulator) software which replayed AWIPS-2 data. Using the WES-2 Bridge and the WESSL-2 (WES Scripting Language) event display, this computer lab has the state-of-the-art ability to simulate severe weather events and recreate WFO warning operations. OWL Student forecasters attending the workshop worked in teams in a multi-player simulation of the Hastings, Nebraska WFO on May 6th, 2015, where thunderstorms across the service area produced large hail, damaging winds, and multiple tornadoes. This paper will discuss the design and goals of the WDTD/OWL workshop, as well as plans for holding similar workshops in the future.

Entity Modeling and Immersive Decision Environments

DTIC Science & Technology

2011-09-01

Simulation Technologies (REST) Lerman, D. J. (2010). Correct Weather Modeling of non-Standard Days (10F- SIW -004). In Proceedings of 2010 Fall Simulation...Interoperability Workshop (Fall SIW ) SISO. Orlando, FL: SISO. Most flight simulators compute and fly in a weather environment that matches a

Risk Assessment in Relation to the Effect of Climate Change on Water Shortage in the Taichung Area

NASA Astrophysics Data System (ADS)

Hsiao, J.; Chang, L.; Ho, C.; Niu, M.

2010-12-01

Rapid economic development has stimulated a worldwide greenhouse effect and induced global climate change. Global climate change has increased the range of variation in the quantity of regional river flows between wet and dry seasons, which effects the management of regional water resources. Consequently, the influence of climate change has become an important issue in the management of regional water resources. In this study, the Monte Carlo simulation method was applied to risk analysis of shortage of water supply in the Taichung area. This study proposed a simulation model that integrated three models: weather generator model, surface runoff model, and water distribution model. The proposed model was used to evaluate the efficiency of the current water supply system and the potential effectiveness of two additional plans for water supply: the “artificial lakes” plan and the “cross-basin water transport” plan. A first-order Markov Chain method and two probability distribution models, exponential distribution and normal distribution, were used in the weather generator model. In the surface runoff model, researchers selected the Generalized Watershed Loading Function model (GWLF) to simulate the relationship between quantity of rainfall and basin outflow. A system dynamics model (SD) was applied to the water distribution model. Results of the simulation indicated that climate change could increase the annual quantity of river flow in the Dachia River and Daan River basins. However, climate change could also increase the difference in the quantity of river flow between wet and dry seasons. Simulation results showed that in current system case or in the additional plan cases, shortage status of water for both public and agricultural uses with conditions of climate change will be mostly worse than that without conditions of climate change except for the shortage status for the public use in the current system case. With or without considering the effect of climate change, the additional plans, especially the “cross-basin water transport” plan, for water supply could significantly increase the supply of water for public use. The proposed simulation model and results of analysis in this study could provide valuable reference for decision-makers in regards to risk analysis of regional water supply.

Appropriate Simulants are a Requirement for Mars Surface Systems Technology Development

NASA Technical Reports Server (NTRS)

Edmunson, Jennifer E.; McLemore, Carole A.; Rickman, Douglas L.

2012-01-01

To date, there are two simulants for martian regolith: JSC Mars-1A, produced from palagonitic (weathered) basaltic tephra mined from the Pu'u Nene cinder cone in Hawaii [1] by commercial company Orbitec, and Mojave Mars Simulant (MMS), produced from Saddleback Basalt in the western Mojave desert by the Jet Propulsion Laboratory [2]. Until numerous recent orbiters, rovers, and landers were sent to Mars, weathered basalt was surmised to cover every inch of the martian landscape. All missions since Viking have disproven that the entire martian surface is weathered basalt. In fact, the outcrops, features, and surfaces that are significantly different from weathered basalt are too numerous to realistically count. There are gullies, evaporites, sand dunes, lake deposits, hydrothermal deposits, alluvium, etc. that indicate sedimentary and chemical processes. There is no one size fits all simulant. Each unique area requires its own simulant in order to test technologies and hardware, thereby reducing risk.

Wildland fire probabilities estimated from weather model-deduced monthly mean fire danger indices

Treesearch

Haiganoush K. Preisler; Shyh-Chin Chen; Francis Fujioka; John W. Benoit; Anthony L. Westerling

2008-01-01

The National Fire Danger Rating System indices deduced from a regional simulation weather model were used to estimate probabilities and numbers of large fire events on monthly and 1-degree grid scales. The weather model simulations and forecasts are ongoing experimental products from the Experimental Climate Prediction Center at the Scripps Institution of Oceanography...

Simulating spatial and temporally related fire weather

Treesearch

Isaac C. Grenfell; Mark Finney; Matt Jolly

2010-01-01

Use of fire behavior models has assumed an increasingly important role for managers of wildfire incidents to make strategic decisions. For fire risk assessments and danger rating at very large spatial scales, these models depend on fire weather variables or fire danger indices. Here, we describe a method to simulate fire weather at a national scale that captures the...

Interactive Development of Regional Climate Web Pages for the Western United States

NASA Astrophysics Data System (ADS)

Oakley, N.; Redmond, K. T.

2013-12-01

Weather and climate have a pervasive and significant influence on the western United States, driving a demand for information that is ongoing and constantly increasing. In communications with stakeholders, policy makers, researchers, educators, and the public through formal and informal encounters, three standout challenges face users of weather and climate information in the West. First, the needed information is scattered about the web making it difficult or tedious to access. Second, information is too complex or requires too much background knowledge to be immediately applicable. Third, due to complex terrain, there is high spatial variability in weather, climate, and their associated impacts in the West, warranting information outlets with a region-specific focus. Two web sites, TahoeClim and the Great Basin Weather and Climate Dashboard were developed to overcome these challenges to meeting regional weather and climate information needs. TahoeClim focuses on the Lake Tahoe Basin, a region of critical environmental concern spanning the border of Nevada and California. TahoeClim arose out of the need for researchers, policy makers, and environmental organizations to have access to all available weather and climate information in one place. Additionally, TahoeClim developed tools to both interpret and visualize data for the Tahoe Basin with supporting instructional material. The Great Basin Weather and Climate Dashboard arose from discussions at an informal meeting about Nevada drought organized by the USDA Farm Service Agency. Stakeholders at this meeting expressed a need to take a 'quick glance' at various climate indicators to support their decision making process. Both sites were designed to provide 'one-stop shopping' for weather and climate information in their respective regions and to be intuitive and usable by a diverse audience. An interactive, 'co-development' approach was taken with sites to ensure needs of potential users were met. The sites were presented in meetings of target user groups at several stages of development. Feedback was collected by observing people as they used the sites to complete a task as well as through surveys and informal discussion. The resultant web products meet the needs of the target audience and give them a sense of ownership, making them more inclined to utilize the sites. Even with Western Regional Climate Center's considerable experience in the provision of climate services, this proved to be a very fruitful exercise in how to better serve our clientele and revealed opportunities for improving our products. The lessons learned from this 'co-development' process about how people search for, use, and perceive weather and climate data in the West provide valuable insight for others wishing to create an online tool to supply this type of information.

Uncertainty estimation of long-range ensemble forecasts of snowmelt flood characteristics

NASA Astrophysics Data System (ADS)

Kuchment, L.

2012-04-01

Long-range forecasts of snowmelt flood characteristics with the lead time of 2-3 months have important significance for regulation of flood runoff and mitigation of flood damages at almost all large Russian rivers At the same time, the application of current forecasting techniques based on regression relationships between the runoff volume and the indexes of river basin conditions can lead to serious errors in forecasting resulted in large economic losses caused by wrong flood regulation. The forecast errors can be caused by complicated processes of soil freezing and soil moisture redistribution, too high rate of snow melt, large liquid precipitation before snow melt. or by large difference of meteorological conditions during the lead-time periods from climatologic ones. Analysis of economic losses had shown that the largest damages could, to a significant extent, be avoided if the decision makers had an opportunity to take into account predictive uncertainty and could use more cautious strategies in runoff regulation. Development of methodology of long-range ensemble forecasting of spring/summer floods which is based on distributed physically-based runoff generation models has created, in principle, a new basis for improving hydrological predictions as well as for estimating their uncertainty. This approach is illustrated by forecasting of the spring-summer floods at the Vyatka River and the Seim River basins. The application of the physically - based models of snowmelt runoff generation give a essential improving of statistical estimates of the deterministic forecasts of the flood volume in comparison with the forecasts obtained from the regression relationships. These models had been used also for the probabilistic forecasts assigning meteorological inputs during lead time periods from the available historical daily series, and from the series simulated by using a weather generator and the Monte Carlo procedure. The weather generator consists of the stochastic models of daily temperature and precipitation. The performance of the probabilistic forecasts were estimated by the ranked probability skill scores. The application of Monte Carlo simulations using weather generator has given better results then using the historical meteorological series.

Simulation and Data Analytics for Mobile Road Weather Sensors

NASA Astrophysics Data System (ADS)

Chettri, S. R.; Evans, J. D.; Tislin, D.

2016-12-01

Numerous algorithmic and theoretical considerations arise in simulating a vehicle-based weather observation network known as the Mobile Platform Environmental Data (MoPED). MoPED integrates sensor data from a fleet of commercial vehicles (about 600 at last count, with thousands more to come) as they travel interstate, state and local routes and metropolitan areas throughout the conterminous United States. The MoPED simulator models a fleet of anywhere between 1000-10,000 vehicles that travel a highway network encoded in a geospatial database, starting and finishing at random times and moving at randomly-varying speeds. Virtual instruments aboard these vehicles interpolate surface weather parameters (such as temperature and pressure) from the High-Resolution Rapid Refresh (HRRR) data series, an hourly, coast-to-coast 3km grid of weather parameters modeled by the National Centers for Environmental Prediction. Whereas real MoPED sensors have noise characteristics that lead to drop-outs, drift, or physically unrealizable values, our simulation introduces a variety of noise distributions into the parameter values inferred from HRRR (Fig. 1). Finally, the simulator collects weather readings from the National Weather Service's Automated Surface Observation System (ASOS, comprised of over 800 airports around the country) for comparison, validation, and analytical experiments. The simulator's MoPED-like weather data stream enables studies like the following: Experimenting with data analysis and calibration methods - e.g., by comparing noisy vehicle data with ASOS "ground truth" in close spatial and temporal proximity (e.g., 10km, 10 min) (Fig. 2). Inter-calibrating different vehicles' sensors when they pass near each other. Detecting spatial structure in the surface weather - such as dry lines, sudden changes in humidity that accompany severe weather - and estimating how many vehicles are needed to reliably map these structures and their motion. Detecting bottlenecks in the MoPED data infrastructure to ensure real-time data filtering and dissemination as number of vehicles scales up; or tuning the data structures needed to keep track of individual sensor calibrations. Expanding the analytical and data management approach to other mobile weather sensors such as smartphones.

The effects of clutter-rejection filtering on estimating weather spectrum parameters

NASA Technical Reports Server (NTRS)

Davis, W. T.

1989-01-01

The effects of clutter-rejection filtering on estimating the weather parameters from pulse Doppler radar measurement data are investigated. The pulse pair method of estimating the spectrum mean and spectrum width of the weather is emphasized. The loss of sensitivity, a measure of the signal power lost due to filtering, is also considered. A flexible software tool developed to investigate these effects is described. It allows for simulated weather radar data, in which the user specifies an underlying truncated Gaussian spectrum, as well as for externally generated data which may be real or simulated. The filter may be implemented in either the time or the frequency domain. The software tool is validated by comparing unfiltered spectrum mean and width estimates to their true values, and by reproducing previously published results. The effects on the weather parameter estimates using simulated weather-only data are evaluated for five filters: an ideal filter, two infinite impulse response filters, and two finite impulse response filters. Results considering external data, consisting of weather and clutter data, are evaluated on a range cell by range cell basis. Finally, it is shown theoretically and by computer simulation that a linear phase response is not required for a clutter rejection filter preceeding pulse-pair parameter estimation.

Wildfire risk in the wildland-urban interface: A simulation study in northwestern Wisconsin

USGS Publications Warehouse

Massada, Avi Bar; Radeloff, Volker C.; Stewart, Susan I.; Hawbaker, Todd J.

2009-01-01

The rapid growth of housing in and near the wildland–urban interface (WUI) increases wildfirerisk to lives and structures. To reduce fire risk, it is necessary to identify WUI housing areas that are more susceptible to wildfire. This is challenging, because wildfire patterns depend on fire behavior and spread, which in turn depend on ignition locations, weather conditions, the spatial arrangement of fuels, and topography. The goal of our study was to assess wildfirerisk to a 60,000 ha WUI area in northwesternWisconsin while accounting for all of these factors. We conducted 6000 simulations with two dynamic fire models: Fire Area Simulator (FARSITE) and Minimum Travel Time (MTT) in order to map the spatial pattern of burn probabilities. Simulations were run under normal and extreme weather conditions to assess the effect of weather on fire spread, burn probability, and risk to structures. The resulting burn probability maps were intersected with maps of structure locations and land cover types. The simulations revealed clear hotspots of wildfire activity and a large range of wildfirerisk to structures in the study area. As expected, the extreme weather conditions yielded higher burn probabilities over the entire landscape, as well as to different land cover classes and individual structures. Moreover, the spatial pattern of risk was significantly different between extreme and normal weather conditions. The results highlight the fact that extreme weather conditions not only produce higher fire risk than normal weather conditions, but also change the fine-scale locations of high risk areas in the landscape, which is of great importance for fire management in WUI areas. In addition, the choice of weather data may limit the potential for comparisons of risk maps for different areas and for extrapolating risk maps to future scenarios where weather conditions are unknown. Our approach to modeling wildfirerisk to structures can aid fire risk reduction management activities by identifying areas with elevated wildfirerisk and those most vulnerable under extreme weather conditions.

Atmospheric Corrosion Behavior and Mechanism of a Ni-Advanced Weathering Steel in Simulated Tropical Marine Environment

NASA Astrophysics Data System (ADS)

Wu, Wei; Zeng, Zhongping; Cheng, Xuequn; Li, Xiaogang; Liu, Bo

2017-12-01

Corrosion behavior of Ni-advanced weathering steel, as well as carbon steel and conventional weathering steel, in a simulated tropical marine atmosphere was studied by field exposure and indoor simulation tests. Meanwhile, morphology and composition of corrosion products formed on the exposed steels were surveyed through scanning electron microscopy, energy-dispersive x-ray spectroscopy and x-ray diffraction. Results indicated that the additive Ni in weathering steel played an important role during the corrosion process, which took part in the formation of corrosion products, enriched in the inner rust layer and promoted the transformation from loose γ-FeOOH to dense α-FeOOH. As a result, the main aggressive ion, i.e., Cl-, was effectively separated in the outer rust layer which leads to the lowest corrosion rate among these tested steels. Thus, the resistance of Ni-advanced weathering steel to atmospheric corrosion was significantly improved in a simulated tropical marine environment.

Nowcasting system MeteoExpert at Irkutsk airport

NASA Astrophysics Data System (ADS)

Bazlova, Tatiana; Bocharnikov, Nikolai; Solonin, Alexander

2016-04-01

Airport operations are significantly impacted by low visibility concerned with fog. Generation of accurate and timely nowcast products is a basis of early warning automated system providing information about significant weather conditions for decision-makers. Nowcasting system MeteoExpert has been developed that provides aviation forecasters with 0-6 hour nowcasts of the weather conditions including fog and low visibility. The system has been put into operation at the airport Irkutsk since August 2014. Aim is to increase an accuracy of fog forecasts, contributing to the airport safety, efficiency and capacity improvement. Designed for operational use numerical model of atmospheric boundary layer runs with a 10-minute update cycle. An important component of the system is the use of AWOS at the airdrome and three additional automatic weather stations at fogging sites in the vicinity of the airdrome. Nowcasts are visualized on a screen of forecaster's workstation and dedicated website. Nowcasts have been verified against actual observations.

Retrospective Analog Year Analyses Using NASA Satellite Data to Improve USDA's World Agricultural Supply and Demand Estimates

NASA Technical Reports Server (NTRS)

Teng, William; Shannon, Harlan

2011-01-01

The USDA World Agricultural Outlook Board (WAOB) is responsible for monitoring weather and climate impacts on domestic and foreign crop development. One of WAOB's primary goals is to determine the net cumulative effect of weather and climate anomalies on final crop yields. To this end, a broad array of information is consulted, including maps, charts, and time series of recent weather, climate, and crop observations; numerical output from weather and crop models; and reports from the press, USDA attach s, and foreign governments. The resulting agricultural weather assessments are published in the Weekly Weather and Crop Bulletin, to keep farmers, policy makers, and commercial agricultural interests informed of weather and climate impacts on agriculture. Because both the amount and timing of precipitation significantly affect crop yields, WAOB often uses precipitation time series to identify growing seasons with similar weather patterns and help estimate crop yields for the current growing season, based on observed yields in analog years. Historically, these analog years are visually identified; however, the qualitative nature of this method sometimes precludes the definitive identification of the best analog year. Thus, one goal of this study is to derive a more rigorous, statistical approach for identifying analog years, based on a modified coefficient of determination, termed the analog index (AI). A second goal is to compare the performance of AI for time series derived from surface-based observations vs. satellite-based measurements (NASA TRMM and other data).

Games and Simulations for Climate, Weather and Earth Science Education

NASA Astrophysics Data System (ADS)

Russell, R. M.

2013-12-01

We will demonstrate several interactive, computer-based simulations, games, and other interactive multimedia. These resources were developed for weather, climate, atmospheric science, and related Earth system science education. The materials were created by education groups at NCAR/UCAR in Boulder, primarily Spark and the COMET Program. These materials have been disseminated via Spark's web site (spark.ucar.edu), webinars, online courses, teacher workshops, and large touchscreen displays in weather and Sun-Earth connections exhibits in NCAR's Mesa Lab facility. Spark has also assembled a web-based list of similar resources, especially simulations and games, from other sources that touch upon weather, climate, and atmospheric science topics. We'll briefly demonstrate this directory.

Games and Simulations for Climate, Weather and Earth Science Education

NASA Astrophysics Data System (ADS)

Russell, R. M.; Clark, S.

2015-12-01

We will demonstrate several interactive, computer-based simulations, games, and other interactive multimedia. These resources were developed for weather, climate, atmospheric science, and related Earth system science education. The materials were created by the UCAR Center for Science Education. These materials have been disseminated via our web site (SciEd.ucar.edu), webinars, online courses, teacher workshops, and large touchscreen displays in weather and Sun-Earth connections exhibits in NCAR's Mesa Lab facility in Boulder, Colorado. Our group has also assembled a web-based list of similar resources, especially simulations and games, from other sources that touch upon weather, climate, and atmospheric science topics. We'll briefly demonstrate this directory.

Generation of Multivariate Surface Weather Series with Use of the Stochastic Weather Generator Linked to Regional Climate Model

NASA Astrophysics Data System (ADS)

Dubrovsky, M.; Farda, A.; Huth, R.

2012-12-01

The regional-scale simulations of weather-sensitive processes (e.g. hydrology, agriculture and forestry) for the present and/or future climate often require high resolution meteorological inputs in terms of the time series of selected surface weather characteristics (typically temperature, precipitation, solar radiation, humidity, wind) for a set of stations or on a regular grid. As even the latest Global and Regional Climate Models (GCMs and RCMs) do not provide realistic representation of statistical structure of the surface weather, the model outputs must be postprocessed (downscaled) to achieve the desired statistical structure of the weather data before being used as an input to the follow-up simulation models. One of the downscaling approaches, which is employed also here, is based on a weather generator (WG), which is calibrated using the observed weather series and then modified (in case of simulations for the future climate) according to the GCM- or RCM-based climate change scenarios. The present contribution uses the parametric daily weather generator M&Rfi to follow two aims: (1) Validation of the new simulations of the present climate (1961-1990) made by the ALADIN-Climate/CZ (v.2) Regional Climate Model at 25 km resolution. The WG parameters will be derived from the RCM-simulated surface weather series and compared to those derived from observational data in the Czech meteorological stations. The set of WG parameters will include selected statistics of the surface temperature and precipitation (characteristics of the mean, variability, interdiurnal variability and extremes). (2) Testing a potential of RCM output for calibration of the WG for the ungauged locations. The methodology being examined will consist in using the WG, whose parameters are interpolated from the surrounding stations and then corrected based on a RCM-simulated spatial variability. The quality of the weather series produced by the WG calibrated in this way will be assessed in terms of selected climatic characteristics focusing on extreme precipitation and temperature characteristics (including characteristics of dry/wet/hot/cold spells). Acknowledgements: The present experiment is made within the frame of projects ALARO (project P209/11/2405 sponsored by the Czech Science Foundation), WG4VALUE (project LD12029 sponsored by the Ministry of Education, Youth and Sports) and VALUE (COST ES 1102 action).

Reproducibility of Carbon and Water Cycle by an Ecosystem Process Based Model Using a Weather Generator and Effect of Temporal Concentration of Precipitation on Model Outputs

NASA Astrophysics Data System (ADS)

Miyauchi, T.; Machimura, T.

2014-12-01

GCM is generally used to produce input weather data for the simulation of carbon and water cycle by ecosystem process based models under climate change however its temporal resolution is sometimes incompatible to requirement. A weather generator (WG) is used for temporal downscaling of input weather data for models, where the effect of WG algorithms on reproducibility of ecosystem model outputs must be assessed. In this study simulated carbon and water cycle by Biome-BGC model using weather data measured and generated by CLIMGEN weather generator were compared. The measured weather data (daily precipitation, maximum, minimum air temperature) at a few sites for 30 years was collected from NNDC Online weather data. The generated weather data was produced by CLIMGEN parameterized using the measured weather data. NPP, heterotrophic respiration (HR), NEE and water outflow were simulated by Biome-BGC using measured and generated weather data. In the case of deciduous broad leaf forest in Lushi, Henan Province, China, 30 years average monthly NPP by WG was 10% larger than that by measured weather in the growing season. HR by WG was larger than that by measured weather in all months by 15% in average. NEE by WG was more negative in winter and was close to that by measured weather in summer. These differences in carbon cycle were because the soil water content by WG was larger than that by measured weather. The difference between monthly water outflow by WG and by measured weather was large and variable, and annual outflow by WG was 50% of that by measured weather. The inconsistency in carbon and water cycle by WG and measured weather was suggested be affected by the difference in temporal concentration of precipitation, which was assessed.

Assessment of different gridded weather data for soybean yield simulations in Brazil

NASA Astrophysics Data System (ADS)

Battisti, R.; Bender, F. D.; Sentelhas, P. C.

2018-01-01

A high-density, well-distributed, and consistent historical weather data series is of major importance for agricultural planning and climatic risk evaluation. A possible option for regions where weather station network is irregular is the use of gridded weather data (GWD), which can be downloaded online from different sources. Based on that, the aim of this study was to assess the suitability of two GWD, AgMERRA and XAVIER, by comparing them with measured weather data (MWD) for estimating soybean yield in Brazil. The GWD and MWD were obtained for 24 locations across Brazil, considering the period between 1980 and 2010. These data were used to estimate soybean yield with DSSAT-CROPGRO-Soybean model. The comparison of MWD with GWD resulted in a good agreement between climate variables, except for solar radiation. The crop simulations with GWD and MWD resulted in a good agreement for vegetative and reproductive phases. Soybean potential yield (Yp) simulated with AgMERRA and XAVIER had a high correlation (r > 0.88) when compared to the estimates with MWD, with the RMSE of about 400 kg ha-1. For attainable yield (Ya), estimates with XAVIER resulted in a RMSE of 700 kg ha-1 against 864 kg ha-1 from AgMERRA, both compared to the simulations using MWD. Even with these differences in Ya simulations, both GWD can be considered suitable for simulating soybean growth, development, and yield in Brazil; however, with XAVIER GWD presenting a better performance for weather and crop variables assessed.

SYNTOR: A synthetic daily weather generator version 3.4 user manual

USDA-ARS?s Scientific Manuscript database

Existing records of weather observations are often too short to conduct long duration hydrologic and environmental computer simulations. A computer program can be used to generate synthetic weather data to increase the length of existing weather records. SYNTOR, which stands for SYNthetic weather g...

Projecting Future Changes in Extreme Weather During the North American Monsoon in the Southwest with High Resolution, Convective-Permitting Regional Atmospheric Modeling

NASA Astrophysics Data System (ADS)

Chang, H. I.; Castro, C. L.; Luong, T. M.; Lahmers, T.; Jares, M.; Carrillo, C. M.

2014-12-01

Most severe weather during the North American monsoon in the Southwest U.S. occurs in association with organized convection, including microbursts, dust storms, flash flooding and lightning. Our objective is to project how monsoon severe weather is changing due to anthropogenic global warming. We first consider a dynamically downscaled reanalysis (35 km grid spacing), generated with the Weather Research and Forecasting (WRF) model during the period 1948-2010. Individual severe weather events, identified by favorable thermodynamic conditions of instability and precipitable water, are then simulated for short-term, numerical weather prediction-type simulations of 24h at a convective-permitting scale (2 km grid spacing). Changes in the character of severe weather events within this period likely reflect long-term climate change driven by anthropogenic forcing. Next, we apply the identical model simulation and analysis procedures to several dynamically downscaled CMIP3 and CMIP5 models for the period 1950-2100, to assess how monsoon severe weather may change in the future and if these changes correspond with what is already occurring per the downscaled renalaysis and available observational data. The CMIP5 models we are downscaling (HadGEM and MPI-ECHAM6) will be included as part of North American CORDEX. The regional model experimental design for severe weather event projection reasonably accounts for the known operational forecast prerequisites for severe monsoon weather. The convective-permitting simulations show that monsoon convection appears to be reasonably well captured with the use of the dynamically downscaled reanalysis, in comparison to Stage IV precipitation data. The regional model tends to initiate convection too early, though correctly simulates the diurnal maximum in convection in the afternoon and subsequent westward propagation of thunderstorms. Projected changes in extreme event precipitation will be described in relation to the long-term changes in thermodynamic and dynamic forcing mechanisms for severe weather. Results from this project will be used for climate change impacts assessment for U.S. military installations in the region.

Modeling extreme (Carrington-type) space weather events using three-dimensional MHD code simulations

NASA Astrophysics Data System (ADS)

Ngwira, C. M.; Pulkkinen, A. A.; Kuznetsova, M. M.; Glocer, A.

2013-12-01

There is growing concern over possible severe societal consequences related to adverse space weather impacts on man-made technological infrastructure and systems. In the last two decades, significant progress has been made towards the modeling of space weather events. Three-dimensional (3-D) global magnetohydrodynamics (MHD) models have been at the forefront of this transition, and have played a critical role in advancing our understanding of space weather. However, the modeling of extreme space weather events is still a major challenge even for existing global MHD models. In this study, we introduce a specially adapted University of Michigan 3-D global MHD model for simulating extreme space weather events that have a ground footprint comparable (or larger) to the Carrington superstorm. Results are presented for an initial simulation run with ``very extreme'' constructed/idealized solar wind boundary conditions driving the magnetosphere. In particular, we describe the reaction of the magnetosphere-ionosphere system and the associated ground induced geoelectric field to such extreme driving conditions. We also discuss the results and what they might mean for the accuracy of the simulations. The model is further tested using input data for an observed space weather event to verify the MHD model consistence and to draw guidance for future work. This extreme space weather MHD model is designed specifically for practical application to the modeling of extreme geomagnetically induced electric fields, which can drive large currents in earth conductors such as power transmission grids.

Fantasy and Reality in the History of Weather and Climate Control

NASA Astrophysics Data System (ADS)

Fleming, J. R.

2005-12-01

This presentation examines the history of large-scale weather and climate engineering since 1840, with special reference to imaginative and speculative literature and with special relevance to ethical and policy issues. Ultimate control of the weather and climate embodies both our wildest fantasies and our greatest fears. Fantasy often informs reality (and vice-versa). NASA managers know this well, as do Trekkies. The best science fiction authors typically build from the current state of a field to construct futuristic scenarios that reveal and explore the human condition. Scientists as well often venture into flights of fancy. Though not widely documented, the fantasy-reality axis is also a prominent aspect of the history of the geosciences. James Espy's proposal in the 1840s to enhance precipitation by lighting huge fires, thus stimulating convective updrafts, preceded the widespread charlatanism of the rain-makers, or so-called "pluviculturalists," in the western U.S. One hundred years later, promising discoveries in "cloud seeding" by Irving Langmuir and his associates at the General Electric Corporation rapidly devolved into unsupportable proposals and questionable practices by military and commercial rain-makers seeking to control the weather. During the Cold War, Soviet engineers also promoted a chilling vision (to Westerners) of global climate control. Recently, rather immodest proposals to "fix" a climate system perceived to be out of control have received wide circulation. In 2003 the U.S. Pentagon released a report recommending that the government should "explore geo-engineering options that control the climate." In 2004 a symposium in Cambridge, England set out to "identify, debate, and evaluate" possible, but highly controversial options for the design and construction of engineering projects for the management and mitigation of global climate change. This talk will locate the history of weather and climate modification within a long tradition of imaginative and speculative literature involving "control" of nature. The goal is the articulation of a perspective fully informed by history and the initiation of a dialogue, stimulated by this approach, that uncovers otherwise hidden values, ethical implications, social tensions, and public apprehensions.

Towards a More Accurate Solar Power Forecast By Improving NWP Model Physics

NASA Astrophysics Data System (ADS)

Köhler, C.; Lee, D.; Steiner, A.; Ritter, B.

2014-12-01

The growing importance and successive expansion of renewable energies raise new challenges for decision makers, transmission system operators, scientists and many more. In this interdisciplinary field, the role of Numerical Weather Prediction (NWP) is to reduce the uncertainties associated with the large share of weather-dependent power sources. Precise power forecast, well-timed energy trading on the stock market, and electrical grid stability can be maintained. The research project EWeLiNE is a collaboration of the German Weather Service (DWD), the Fraunhofer Institute (IWES) and three German transmission system operators (TSOs). Together, wind and photovoltaic (PV) power forecasts shall be improved by combining optimized NWP and enhanced power forecast models. The conducted work focuses on the identification of critical weather situations and the associated errors in the German regional NWP model COSMO-DE. Not only the representation of the model cloud characteristics, but also special events like Sahara dust over Germany and the solar eclipse in 2015 are treated and their effect on solar power accounted for. An overview of the EWeLiNE project and results of the ongoing research will be presented.

Fire Makers, Barnyards, and Prickly Forests: A Preschool Stroll around the Block

ERIC Educational Resources Information Center

Bentley, Dana Frantz

2012-01-01

The daily trips outside can be challenging, and living in Manhattan makes them even more complex. It seems there is no such thing as a simple stroll, or a quick trip outside; and the winter weather makes such excursions that much more complex. Yet, it is always worth it. In the author's nine years of teaching, she has discovered that a "quick…

Convective Weather Avoidance with Uncertain Weather Forecasts

NASA Technical Reports Server (NTRS)

Karahan, Sinan; Windhorst, Robert D.

2009-01-01

Convective weather events have a disruptive impact on air traffic both in terminal area and in en-route airspaces. In order to make sure that the national air transportation system is safe and efficient, it is essential to respond to convective weather events effectively. Traffic flow control initiatives in response to convective weather include ground delay, airborne delay, miles-in-trail restrictions as well as tactical and strategic rerouting. The rerouting initiatives can potentially increase traffic density and complexity in regions neighboring the convective weather activity. There is a need to perform rerouting in an intelligent and efficient way such that the disruptive effects of rerouting are minimized. An important area of research is to study the interaction of in-flight rerouting with traffic congestion or complexity and developing methods that quantitatively measure this interaction. Furthermore, it is necessary to find rerouting solutions that account for uncertainties in weather forecasts. These are important steps toward managing complexity during rerouting operations, and the paper is motivated by these research questions. An automated system is developed for rerouting air traffic in order to avoid convective weather regions during the 20- minute - 2-hour time horizon. Such a system is envisioned to work in concert with separation assurance (0 - 20-minute time horizon), and longer term air traffic management (2-hours and beyond) to provide a more comprehensive solution to complexity and safety management. In this study, weather is dynamic and uncertain; it is represented as regions of airspace that pilots are likely to avoid. Algorithms are implemented in an air traffic simulation environment to support the research study. The algorithms used are deterministic but periodically revise reroutes to account for weather forecast updates. In contrast to previous studies, in this study convective weather is represented as regions of airspace that pilots are likely to avoid. The automated system periodically updates forecasts and reassesses rerouting decisions in order to account for changing weather predictions. The main objectives are to reroute flights to avoid convective weather regions and determine the resulting complexity due to rerouting. The eventual goal is to control and reduce complexity while rerouting flights during the 20 minute - 2 hour planning period. A three-hour simulation is conducted using 4800 flights in the national airspace. The study compares several metrics against a baseline scenario using the same traffic and weather but with rerouting disabled. The results show that rerouting can have a negative impact on congestion in some sectors, as expected. The rerouting system provides accurate measurements of the resulting complexity in the congested sectors. Furthermore, although rerouting is performed only in the 20-minute - 2-hour range, it results in a 30% reduction in encounters with nowcast weather polygons (100% being the ideal for perfectly predictable and accurate weather). In the simulations, rerouting was performed for the 20-minute - 2-hour flight time horizon, and for the en-route segment of air traffic. The implementation uses CWAM, a set of polygons that represent probabilities of pilot deviation around weather. The algorithms were implemented in a software-based air traffic simulation system. Initial results of the system's performance and effectiveness were encouraging. Simulation results showed that when flights were rerouted in the 20-minute - 2-hour flight time horizon of air traffic, there were fewer weather encounters in the first 20 minutes than for flights that were not rerouted. Some preliminary results were also obtained that showed that rerouting will also increase complexity. More simulations will be conducted in order to report conclusive results on the effects of rerouting on complexity. Thus, the use of the 20-minute - 2-hour flight time horizon weather avoidance teniques performed in the simulation is expected to provide benefits for short-term weather avoidance.

Coupling a Mesoscale Numerical Weather Prediction Model with Large-Eddy Simulation for Realistic Wind Plant Aerodynamics Simulations (Poster)

DOE Office of Scientific and Technical Information (OSTI.GOV)

Draxl, C.; Churchfield, M.; Mirocha, J.

Wind plant aerodynamics are influenced by a combination of microscale and mesoscale phenomena. Incorporating mesoscale atmospheric forcing (e.g., diurnal cycles and frontal passages) into wind plant simulations can lead to a more accurate representation of microscale flows, aerodynamics, and wind turbine/plant performance. Our goal is to couple a numerical weather prediction model that can represent mesoscale flow [specifically the Weather Research and Forecasting model] with a microscale LES model (OpenFOAM) that can predict microscale turbulence and wake losses.

Modeling the weather impact on aviation in a global air traffic model

NASA Astrophysics Data System (ADS)

Himmelsbach, S.; Hauf, T.; Rokitansky, C. H.

2009-09-01

Weather has a strong impact on aviation safety and efficiency. For a better understanding of that impact, especially of thunderstorms and similar other severe hazards, we pursued a modeling approach. We used the detailed simulation software (NAVSIM) of worldwide air traffic, developed by Rokitansky [Eurocontrol, 2005] and implemented a specific weather module. NAVSIM models each aircraft with its specific performance characteristics separately along preplanned and prescribed routes. The specific weather module in its current version simulates a thunderstorm as an impenetrable 3D object, which forces an aircraft to circumvent the latter. We refer to that object in general terms as a weather object. The Cb-weather object, as a specific weather object, is a heuristic model of a real thunderstorm, with its characteristics based on actually observed satellite and precipitation radar data. It is comprised of an upper volume, mostly the anvil, and a bottom volume, the up- and downdrafts and the lower outflow area [Tafferner and Forster, 2009; Kober and Tafferner 2009; Zinner et al, 2008]. The Cb-weather object is already implemented in NAVSIM, other weather objects like icing and turbulence will follow. This combination of NAVSIM with a weather object allows a detailed investigation of situations where conflicts exist between planned flight routes and adverse weather. The first objective is to simulate the observed circum-navigation in NAVSIM. Real occurring routes will be compared with simulated ones. Once this has successfully completed, NAVSIM offers a platform to assess existing rules and develop more efficient strategies to cope with adverse weather. An overview will be given over the implementation status of weather objects within NAVSIM and first results will be presented. Cb-object data provision by A. Tafferner, C. Forster, T. Zinner, K. Kober, M. Hagen (DLR Oberpfaffenhofen) is greatly acknowledged. References: Eurocontrol, VDL Mode 2 Capacity Analysis through Simulations: WP3.B - NAVSIM Overview and Validation Results, Edition 1.2, 2005 Kober K. and A. Tafferner. Tracking and nowcasting of convective cells using remote sensing data from radar and satellite, Meteorologische Zeitschrift, 1 (No. 18), 75-84, 2009 Tafferner A. and C. Forster, Improvement of thunderstorm hazard information for pilots through a ground based weather information and management system, Eighth USA/Europe Air Traffic Management Research and Development Seminar (submitted), 2009 Zinner, T., H. Mannstein, A. Tafferner. Cb-TRAM: Tracking and monitoring severe convection from onset over rapid development to mature phase using multi-channel Meteosat-8 SEVIRI data, Meteorol. Atmos. Phys., 101, 191-210, 2008

Mixture and method for simulating soiling and weathering of surfaces

DOEpatents

Sleiman, Mohamad; Kirchstetter, Thomas; Destaillats, Hugo; Levinson, Ronnen; Berdahl, Paul; Akbari, Hashem

2018-01-02

This disclosure provides systems, methods, and apparatus related to simulated soiling and weathering of materials. In one aspect, a soiling mixture may include an aqueous suspension of various amounts of salt, soot, dust, and humic acid. In another aspect, a method may include weathering a sample of material in a first exposure of the sample to ultraviolet light, water vapor, and elevated temperatures, depositing a soiling mixture on the sample, and weathering the sample in a second exposure of the sample to ultraviolet light, water vapor, and elevated temperatures.

High potential for weathering and climate effects of non-vascular vegetation in the Late Ordovician

NASA Astrophysics Data System (ADS)

Porada, Philipp; Lenton, Tim; Pohl, Alexandre; Weber, Bettina; Mander, Luke; Donnadieu, Yannick; Beer, Christian; Pöschl, Ulrich; Kleidon, Axel

2017-04-01

Early non-vascular vegetation in the Late Ordovician may have strongly increased chemical weathering rates of surface rocks at the global scale. This could have led to a drawdown of atmospheric CO2 and, consequently, a decrease in global temperature and an interval of glaciations. Under current climatic conditions, usually field or laboratory experiments are used to quantify enhancement of chemical weathering rates by non-vascular vegetation. However, these experiments are constrained to a small spatial scale and a limited number of species. This complicates the extrapolation to the global scale, even more so for the geological past, where physiological properties of non-vascular vegetation may have differed from current species. Here we present a spatially explicit modelling approach to simulate large-scale chemical weathering by non-vascular vegetation in the Late Ordovician. For this purpose, we use a process-based model of lichens and bryophytes, since these organisms are probably the closest living analogue to Late Ordovician vegetation. The model explicitly represents multiple physiological strategies, which enables the simulated vegetation to adapt to Ordovician climatic conditions. We estimate productivity of Ordovician vegetation with the model, and relate it to chemical weathering by assuming that the organisms dissolve rocks to extract phosphorus for the production of new biomass. Thereby we account for limits on weathering due to reduced supply of unweathered rock material in shallow regions, as well as decreased transport capacity of runoff for dissolved weathered material in dry areas. We simulate a potential global weathering flux of 2.8 km3 (rock) per year, which we define as volume of primary minerals affected by chemical transformation. Our estimate is around 3 times larger than today's global chemical weathering flux. Furthermore, chemical weathering rates simulated by our model are highly sensitive to atmospheric CO2 concentration, which implies a strong negative feedback between weathering by non-vascular vegetation and Ordovician climate.

General Aviation Cockpit Weather Information System Simulation Studies

NASA Technical Reports Server (NTRS)

McAdaragh, Ray; Novacek, Paul

2003-01-01

This viewgraph presentation provides information on two experiments on the effectiveness of a cockpit weather information system on a simulated general aviation flight. The presentation covers the simulation hardware configuration, the display device screen layout, a mission scenario, conclusions, and recommendations. The second experiment, with its own scenario and conclusions, is a follow-on experiment.

Laboratory Hydrothermal Alteration of Basaltic Tephra by Acid Sulfate Solutions: An Analog Process for Martian Weathering

NASA Technical Reports Server (NTRS)

Golden, D. C.; Ming, D. W.; Morris, R. V.

2003-01-01

The objective of this study is to conduct simulated Mars-like weathering experiments in the laboratory to determine the weathering products that might form during oxidative, acidic weathering of Mars analog materials.

Software Reviews.

ERIC Educational Resources Information Center

McGrath, Diane, Ed.

1989-01-01

Reviewed are two computer software programs for Apple II computers on weather for upper elementary and middle school grades. "Weather" introduces the major factors (temperature, humidity, wind, and air pressure) affecting weather. "How Weather Works" uses simulation and auto-tutorial formats on sun, wind, fronts, clouds, and…

Employing Numerical Weather Models to Enhance Fire Weather and Fire Behavior Predictions

Treesearch

Joseph J. Charney; Lesley A. Fusina

2006-01-01

This paper presents an assessment of fire weather and fire behavior predictions produced by a numerical weather prediction model similar to those used by operational weather forecasters when preparing their forecasts. The PSU/NCAR MM5 model is used to simulate the weather conditions associated with three fire episodes in June 2005. Extreme fire behavior was reported...

Optical Properties of Thermal Control Coatings After Weathering, Simulated Ascent Heating, and Simulated Space Radiation Exposure

NASA Technical Reports Server (NTRS)

Jaworske, Donald A.; Tuan, George C.; Westheimer, David T.; Peters, Wanda C.; Kauder, Lonny R.

2008-01-01

Spacecraft radiators reject heat to their surroundings and coatings play an important role in this heat rejection. The coatings provide the combined optical properties of low solar absorptance and high infrared emittance. The coatings are applied to the radiator panel in a number of ways, including conventional spraying, plasma spraying, or as an applique. Not designed for a terrestrial weathering environment, the durability of spacecraft paints, coatings, and appliques upon exposure to weathering and subsequent exposure to ascent heating, solar wind, and ultraviolet radiation was studied. In addition to traditional aluminum panels, new isocyanate ester composite panels were exposed for a total of 90 days at the Atmospheric Exposure Site of Kennedy Space Center's (KSC) Beach Corrosion Facility for the purpose of identifying their durability to weathering. Selected panel coupons were subsequently exposed to simulated ascent heating, solar wind, and vacuum ultraviolet (UV) radiation to identify the effect of a simulated space environment on as-weathered surfaces. Optical properties and adhesion testing were used to document the durability of the paints, coatings, and appliques.

NASA Weather Support 2017

NASA Technical Reports Server (NTRS)

Carroll, Matt

2017-01-01

In the mid to late 1980's, as NASA was studying ways to improve weather forecasting capabilities to reduce excessive weather launch delays and to reduce excessive weather Launch Commit Criteria (LCC) waivers, the Challenger Accident occurred and the AC-67 Mishap occurred.[1] NASA and USAF weather personnel had advance knowledge of extremely high levels of weather hazards that ultimately caused or contributed to both of these accidents. In both cases, key knowledge of the risks posed by violations of weather LCC was not in the possession of final decision makers on the launch teams. In addition to convening the mishap boards for these two lost missions, NASA convened expert meteorological boards focusing on weather support. These meteorological boards recommended the development of a dedicated organization with the highest levels of weather expertise and influence to support all of American spaceflight. NASA immediately established the Weather Support Office (WSO) in the Office of Space Flight (OSF), and in coordination with the United Stated Air Force (USAF), initiated an overhaul of the organization and an improvement in technology used for weather support as recommended. Soon after, the USAF established a senior civilian Launch Weather Officer (LWO) position to provide meteorological support and continuity of weather expertise and knowledge over time. The Applied Meteorology Unit (AMU) was established by NASA, USAF, and the National Weather Service to support initiatives to place new tools and methods into an operational status. At the end of the Shuttle Program, after several weather office reorganizations, the WSO function had been assigned to a weather branch at Kennedy Space Center (KSC). This branch was dismantled in steps due to further reorganization, loss of key personnel, and loss of budget line authority. NASA is facing the loss of sufficient expertise and leadership required to provide current levels of weather support. The recommendation proposed herein is to re-establish the WSO under a high level office, with funding set at about the same levels as today, with a revitalized charter and focus to allow for the WSO to operate as originally intended.

Wildfire risk in the wildland-urban interface: A simulation study in northwestern Wisconsin

USGS Publications Warehouse

Bar-Massada, A.; Radeloff, V.C.; Stewart, S.I.; Hawbaker, T.J.

2009-01-01

The rapid growth of housing in and near the wildland-urban interface (WUI) increases wildfire risk to lives and structures. To reduce fire risk, it is necessary to identify WUI housing areas that are more susceptible to wildfire. This is challenging, because wildfire patterns depend on fire behavior and spread, which in turn depend on ignition locations, weather conditions, the spatial arrangement of fuels, and topography. The goal of our study was to assess wildfire risk to a 60,000 ha WUI area in northwestern Wisconsin while accounting for all of these factors. We conducted 6000 simulations with two dynamic fire models: Fire Area Simulator (FARSITE) and Minimum Travel Time (MTT) in order to map the spatial pattern of burn probabilities. Simulations were run under normal and extreme weather conditions to assess the effect of weather on fire spread, burn probability, and risk to structures. The resulting burn probability maps were intersected with maps of structure locations and land cover types. The simulations revealed clear hotspots of wildfire activity and a large range of wildfire risk to structures in the study area. As expected, the extreme weather conditions yielded higher burn probabilities over the entire landscape, as well as to different land cover classes and individual structures. Moreover, the spatial pattern of risk was significantly different between extreme and normal weather conditions. The results highlight the fact that extreme weather conditions not only produce higher fire risk than normal weather conditions, but also change the fine-scale locations of high risk areas in the landscape, which is of great importance for fire management in WUI areas. In addition, the choice of weather data may limit the potential for comparisons of risk maps for different areas and for extrapolating risk maps to future scenarios where weather conditions are unknown. Our approach to modeling wildfire risk to structures can aid fire risk reduction management activities by identifying areas with elevated wildfire risk and those most vulnerable under extreme weather conditions. ?? 2009 Elsevier B.V.

Sources and Uses of Weather Information for Agricultural Decision Makers.

NASA Astrophysics Data System (ADS)

McNew, Kevin P.; Mapp, Harry P.; Duchon, Claude E.; Merritt, Earl S.

1991-04-01

Numerous studies have examined the importance of weather information to farmers and ranchers across the U.S. This study is focused on the kinds of weather information received by farmers and ranchers, the sources of that information, and its use in production and marketing decisions. Our results are based on a survey of 292 producers from the principal agricultural areas of Oklahoma. Producers were classified into five categories related to their source of income from crop and livestock sales.Among temperature, precipitation, relative humility, and wind speed, temperature information was most widely received. Forecast lengths of highest interest were 24-h and 5-day forecasts. Precipitation information was used by many respondents for planting and harvesting decisions. Weather data and forecasts seem to be of greater value to diversified crop and livestock operators than specialized crop and livestock, perhaps due to more frequent timing decisions. Relative humility and wind information appear to be important especially during specific times of the growing season, for example, at harvest time and time of pesticide application. Television is the primary source of weather information for more than 60% of the producers.It appears that there may be a role for both public and private entities in transforming weather data and forecasts into recommendations to crop and livestock producers. Further research is needed to determine the potential value of weather information for alternative production, marketing and livestock decisions, different categories of producers, and different geographic regions.

CHEMFLO: ONE-DIMENSIONAL WATER AND CHEMICAL MOVEMENT IN UNSATURATED SOILS

EPA Science Inventory

An interactive software system was developed to enable decision-makers, regulators, policy-makers, scientists, consultants, and students to simulate the movement of waterand chemicals in unsaturated soils. Water movement is modeled using Richards (1931) - equation. Chemical trans...

Novel Methods to Explore Building Energy Sensitivity to Climate and Heat Waves Using PNNL's BEND Model

NASA Astrophysics Data System (ADS)

Burleyson, C. D.; Voisin, N.; Taylor, T.; Xie, Y.; Kraucunas, I.

2017-12-01

The DOE's Pacific Northwest National Laboratory (PNNL) has been developing the Building ENergy Demand (BEND) model to simulate energy usage in residential and commercial buildings responding to changes in weather, climate, population, and building technologies. At its core, BEND is a mechanism to aggregate EnergyPlus simulations of a large number of individual buildings with a diversity of characteristics over large spatial scales. We have completed a series of experiments to explore methods to calibrate the BEND model, measure its ability to capture interannual variability in energy demand due to weather using simulations of two distinct weather years, and understand the sensitivity to the number and location of weather stations used to force the model. The use of weather from "representative cities" reduces computational costs, but often fails to capture spatial heterogeneity that may be important for simulations aimed at understanding how building stocks respond to a changing climate (Fig. 1). We quantify the potential reduction in temperature and load biases from using an increasing number of weather stations across the western U.S., ranging from 8 to roughly 150. Using 8 stations results in an average absolute summertime temperature bias of 4.0°C. The mean absolute bias drops to 1.5°C using all available stations. Temperature biases of this magnitude translate to absolute summertime mean simulated load biases as high as 13.8%. Additionally, using only 8 representative weather stations can lead to a 20-40% bias of peak building loads under heat wave or cold snap conditions, a significant error for capacity expansion planners who may rely on these types of simulations. This analysis suggests that using 4 stations per climate zone may be sufficient for most purposes. Our novel approach, which requires no new EnergyPlus simulations, could be useful to other researchers designing or calibrating aggregate building model simulations - particularly those looking at the impact of future climate scenarios. Fig. 1. An example of temperature bias that results from using 8 representative weather stations: (a) surface temperature from NLDAS on 5-July 2008 at 2000 UTC; (b) temperature from 8 representative stations at the same time mapped to all counties within a given IECC climate zone; (c) the difference between (a) and (b).

High potential for weathering and climate effects of non-vascular vegetation in the Late Ordovician

PubMed Central

Porada, P.; Lenton, T. M.; Pohl, A.; Weber, B.; Mander, L.; Donnadieu, Y.; Beer, C.; Pöschl, U.; Kleidon, A.

2016-01-01

It has been hypothesized that predecessors of today's bryophytes significantly increased global chemical weathering in the Late Ordovician, thus reducing atmospheric CO2 concentration and contributing to climate cooling and an interval of glaciations. Studies that try to quantify the enhancement of weathering by non-vascular vegetation, however, are usually limited to small areas and low numbers of species, which hampers extrapolating to the global scale and to past climatic conditions. Here we present a spatially explicit modelling approach to simulate global weathering by non-vascular vegetation in the Late Ordovician. We estimate a potential global weathering flux of 2.8 (km3 rock) yr−1, defined here as volume of primary minerals affected by chemical transformation. This is around three times larger than today's global chemical weathering flux. Moreover, we find that simulated weathering is highly sensitive to atmospheric CO2 concentration. This implies a strong negative feedback between weathering by non-vascular vegetation and Ordovician climate. PMID:27385026

A graphical weather system design for the NASA transport systems research vehicle B-737

NASA Technical Reports Server (NTRS)

Scanlon, Charles H.

1992-01-01

A graphical weather system was designed for testing in the NASA Transport Systems Research Vehicle B-737 airplane and simulator. The purpose of these tests was to measure the impact of graphical weather products on aircrew decision processes, weather situation awareness, reroute clearances, workload, and weather monitoring. The flight crew graphical weather interface is described along with integration of the weather system with the flight navigation system, and data link transmission methods for sending weather data to the airplane.

Linking the Weather Generator with Regional Climate Model: Effect of Higher Resolution

NASA Astrophysics Data System (ADS)

Dubrovsky, Martin; Huth, Radan; Farda, Ales; Skalak, Petr

2014-05-01

This contribution builds on our last year EGU contribution, which followed two aims: (i) validation of the simulations of the present climate made by the ALADIN-Climate Regional Climate Model (RCM) at 25 km resolution, and (ii) presenting a methodology for linking the parametric weather generator (WG) with RCM output (aiming to calibrate a gridded WG capable of producing realistic synthetic multivariate weather series for weather-ungauged locations). Now we have available new higher-resolution (6.25 km) simulations with the same RCM. The main topic of this contribution is an anser to a following question: What is an effect of using a higher spatial resolution on a quality of simulating the surface weather characteristics? In the first part, the high resolution RCM simulation of the present climate will be validated in terms of selected WG parameters, which are derived from the RCM-simulated surface weather series and compared to those derived from weather series observed in 125 Czech meteorological stations. The set of WG parameters will include statistics of the surface temperature and precipitation series. When comparing the WG parameters from the two sources (RCM vs observations), we interpolate the RCM-based parameters into the station locations while accounting for the effect of altitude. In the second part, we will discuss an effect of using the higher resolution: the results of the validation tests will be compared with those obtained with the lower-resolution RCM. Acknowledgements: The present experiment is made within the frame of projects ALARO-Climate (project P209/11/2405 sponsored by the Czech Science Foundation), WG4VALUE (project LD12029 sponsored by the Ministry of Education, Youth and Sports of CR) and VALUE (COST ES 1102 action).

Evaluation of Software Simulation of Road Weather Information System.

DOT National Transportation Integrated Search

2016-09-01

A road weather information system (RWIS) is a combination of technologies that collects, transmits, models, and disseminates weather and road condition information. Sensors measure a range of weatherrelated conditions, including pavement temperatur...

Presenting Critical Space Weather Information to Customers and Stakeholders (Invited)

NASA Astrophysics Data System (ADS)

Viereck, R. A.; Singer, H. J.; Murtagh, W. J.; Rutledge, B.

2013-12-01

Space weather involves changes in the near-Earth space environment that impact technological systems such as electric power, radio communication, satellite navigation (GPS), and satellite opeartions. As with terrestrial weather, there are several different kinds of space weather and each presents unique challenges to the impacted technologies and industries. But unlike terrestrial weather, many customers are not fully aware of space weather or how it impacts their systems. This issue is further complicated by the fact that the largest space weather events occur very infrequently with years going by without severe storms. Recent reports have estimated very large potential costs to the economy and to society if a geomagnetic storm were to cause major damage to the electric power transmission system. This issue has come to the attention of emergency managers and federal agencies including the office of the president. However, when considering space weather impacts, it is essential to also consider uncertainties in the frequency of events and the predicted impacts. The unique nature of space weather storms, the specialized technologies that are impacted by them, and the disparate groups and agencies that respond to space weather forecasts and alerts create many challenges to the task of communicating space weather information to the public. Many customers that receive forecasts and alerts are highly technical and knowledgeable about the subtleties of the space environment. Others know very little and require ongoing education and explanation about how a space weather storm will affect their systems. In addition, the current knowledge and understanding of the space environment that goes into forecasting storms is quite immature. It has only been within the last five years that physics-based models of the space environment have played important roles in predictions. Thus, the uncertainties in the forecasts are quite large. There is much that we don't know about space weather and this influences our forecasts. In this presentation, I will discuss the unique challenges that space weather forecasters face when explaining what we know and what we don't know about space weather events to customers and policy makers.

Use of medium-range weather forecasts for drought mitigation and adaptation under a Mediterranean area

NASA Astrophysics Data System (ADS)

Lahlou, Ouiam; Imani, Yasmina; Bennasser Alaoui, Si; Dutra, Emanuel; DiGiuseppe, Francesca; Pappenberger, Florian; Wetterhall, Fredrik

2014-05-01

Use of medium-range weather forecasts for drought mitigation and adaptation under a Mediterranean area Authors: Ouiam Lahlou1, Yasmina Imani1, Si Bennasser Alaoui1, Emmanuel Dutra 2, Francesca Di Guiseppe2, Florian Pappenberger2, Fredrik Wetterhall2 1: Institut Agronomique et Vétérinaire Hassan II (IAV Hassan II) 2: European Center for Medium-Range Weather Forecasts (ECMWF) The main pillar of economic development in Morocco is the agricultural sector employing 40% of the active workforce. Agriculture is still mainly dominated by rainfed agriculture which is vulnerable to an increasing frequency and severity of drought events. In rainfed agriculture, there are few interventions possible once crops are planted. Medium to long range weather forecasts could therefore provide valid information for crop selection and sowing time at the onset of the yield season and later to plan mitigation measures during dry-spell episodes. More than 600 daily forecasts from the European Centre for Medium-Range Weather Forecasts (ECMWF) ensemble forecasting system were analyzed in terms of probabilistic skills scores. Results show that, while daily and weekly accumulated precipitation are poorly predicted there is good skill in the forecast of occurrence and extent of dry periods. The availability of this information to decision makers in the agricultural sector would mean moving from a reactive drought management plan to a proactive one. This is very important, especially for the remote areas where often the needed help comes late. A simulation case-study involving farmers who were made aware of the availability of forecasts for the next seasons, show that medium-range forecasts will allow i) governments and relief agencies to position themselves for more effective and cost-efficient drought interventions, ii) producers to be more aware of their production options and insure their payment rate, iii) Herders, to cope with higher food costs for their cattle iv) farmers to better plan the pre-season agronomic corrections, to schedule the most appropriate timing for the unique complementary irrigation that they can provide to cereals, and to better schedule the harvesting date. Since failing on these mitigation actions due to a lack of forecast availability would be highly priced for the rural Marocco economy, we stress that forecasting drought onset, especially under the high variability of the Mediterranean climate, is of a paramount importance.

Using the Large Fire Simulator System to map wildland fire potential for the conterminous United States

Treesearch

LaWen Hollingsworth; James Menakis

2010-01-01

This project mapped wildland fire potential (WFP) for the conterminous United States by using the large fire simulation system developed for Fire Program Analysis (FPA) System. The large fire simulation system, referred to here as LFSim, consists of modules for weather generation, fire occurrence, fire suppression, and fire growth modeling. Weather was generated with...

The CAULDRON game: Helping decision makers understand extreme weather event attribution

NASA Astrophysics Data System (ADS)

Walton, P.; Otto, F. E. L.

2014-12-01

There is a recognition from academics and stakeholders that climate science has a fundamental role to play in the decision making process, but too frequently there is still uncertainty about what, when, how and why to use it. Stakeholders suggest that it is because the science is presented in an inaccessible manner, while academics suggest it is because the stakeholders do not have the scientific knowledge to understand and apply the science appropriately. What is apparent is that stakeholders need support, and that there is an onus on academia to provide it. This support is even more important with recent developments in climate science, such as extreme weather event attribution. We are already seeing the impacts of extreme weather events around the world causing lost of life and damage to property and infrastructure with current research suggesting that these events could become more frequent and more intense. If this is to be the case then a better understanding of the science will be vital in developing robust adaptation and business planning. The use of games, role playing and simulations to aid learning has long been understood in education but less so as a tool to support stakeholder understanding of climate science. Providing a 'safe' space where participants can actively engage with concepts, ideas and often emotions, can lead to deep understanding that is not possible through more passive mechanisms such as papers and web sites. This paper reports on a game that was developed through a collaboration led by the Red Cross/Red Crescent, University of Oxford and University of Reading to help stakeholders understand the role of weather event attribution in the decision making process. The game has already been played successfully at a number of high profile events including COP 19 and the African Climate Conference. It has also been used with students as part of a postgraduate environmental management course. As well as describing the design principles of the game, the paper also evaluates the success of the game as well as future developments.

New weather depiction technology for night vision goggle (NVG) training: 3D virtual/augmented reality scene-weather-atmosphere-target simulation

NASA Astrophysics Data System (ADS)

Folaron, Michelle; Deacutis, Martin; Hegarty, Jennifer; Vollmerhausen, Richard; Schroeder, John; Colby, Frank P.

2007-04-01

US Navy and Marine Corps pilots receive Night Vision Goggle (NVG) training as part of their overall training to maintain the superiority of our forces. This training must incorporate realistic targets; backgrounds; and representative atmospheric and weather effects they may encounter under operational conditions. An approach for pilot NVG training is to use the Night Imaging and Threat Evaluation Laboratory (NITE Lab) concept. The NITE Labs utilize a 10' by 10' static terrain model equipped with both natural and cultural lighting that are used to demonstrate various illumination conditions, and visual phenomena which might be experienced when utilizing night vision goggles. With this technology, the military can safely, systematically, and reliably expose pilots to the large number of potentially dangerous environmental conditions that will be experienced in their NVG training flights. A previous SPIE presentation described our work for NAVAIR to add realistic atmospheric and weather effects to the NVG NITE Lab training facility using the NVG - WDT(Weather Depiction Technology) system (Colby, et al.). NVG -WDT consist of a high end multiprocessor server with weather simulation software, and several fixed and goggle mounted Heads Up Displays (HUDs). Atmospheric and weather effects are simulated using state-of-the-art computer codes such as the WRF (Weather Research μ Forecasting) model; and the US Air Force Research Laboratory MODTRAN radiative transport model. Imagery for a variety of natural and man-made obscurations (e.g. rain, clouds, snow, dust, smoke, chemical releases) are being calculated and injected into the scene observed through the NVG via the fixed and goggle mounted HUDs. This paper expands on the work described in the previous presentation and will describe the 3D Virtual/Augmented Reality Scene - Weather - Atmosphere - Target Simulation part of the NVG - WDT. The 3D virtual reality software is a complete simulation system to generate realistic target - background scenes and display the results in a DirectX environment. This paper will describe our approach and show a brief demonstration of the software capabilities. The work is supported by the SBIR program under contract N61339-06-C-0113.

NASA Center for Climate Simulation (NCCS) Presentation

NASA Technical Reports Server (NTRS)

Webster, William P.

2012-01-01

The NASA Center for Climate Simulation (NCCS) offers integrated supercomputing, visualization, and data interaction technologies to enhance NASA's weather and climate prediction capabilities. It serves hundreds of users at NASA Goddard Space Flight Center, as well as other NASA centers, laboratories, and universities across the US. Over the past year, NCCS has continued expanding its data-centric computing environment to meet the increasingly data-intensive challenges of climate science. We doubled our Discover supercomputer's peak performance to more than 800 teraflops by adding 7,680 Intel Xeon Sandy Bridge processor-cores and most recently 240 Intel Xeon Phi Many Integrated Core (MIG) co-processors. A supercomputing-class analysis system named Dali gives users rapid access to their data on Discover and high-performance software including the Ultra-scale Visualization Climate Data Analysis Tools (UV-CDAT), with interfaces from user desktops and a 17- by 6-foot visualization wall. NCCS also is exploring highly efficient climate data services and management with a new MapReduce/Hadoop cluster while augmenting its data distribution to the science community. Using NCCS resources, NASA completed its modeling contributions to the Intergovernmental Panel on Climate Change (IPCG) Fifth Assessment Report this summer as part of the ongoing Coupled Modellntercomparison Project Phase 5 (CMIP5). Ensembles of simulations run on Discover reached back to the year 1000 to test model accuracy and projected climate change through the year 2300 based on four different scenarios of greenhouse gases, aerosols, and land use. The data resulting from several thousand IPCC/CMIP5 simulations, as well as a variety of other simulation, reanalysis, and observationdatasets, are available to scientists and decision makers through an enhanced NCCS Earth System Grid Federation Gateway. Worldwide downloads have totaled over 110 terabytes of data.

Application of an integrated Weather Research and Forecasting (WRF)/CALPUFF modeling tool for source apportionment of atmospheric pollutants for air quality management: A case study in the urban area of Benxi, China.

PubMed

Wu, Hao; Zhang, Yan; Yu, Qi; Ma, Weichun

2018-04-01

In this study, the authors endeavored to develop an effective framework for improving local urban air quality on meso-micro scales in cities in China that are experiencing rapid urbanization. Within this framework, the integrated Weather Research and Forecasting (WRF)/CALPUFF modeling system was applied to simulate the concentration distributions of typical pollutants (particulate matter with an aerodynamic diameter <10 μm [PM 10 ], sulfur dioxide [SO 2 ], and nitrogen oxides [NO x ]) in the urban area of Benxi. Statistical analyses were performed to verify the credibility of this simulation, including the meteorological fields and concentration fields. The sources were then categorized using two different classification methods (the district-based and type-based methods), and the contributions to the pollutant concentrations from each source category were computed to provide a basis for appropriate control measures. The statistical indexes showed that CALMET had sufficient ability to predict the meteorological conditions, such as the wind fields and temperatures, which provided meteorological data for the subsequent CALPUFF run. The simulated concentrations from CALPUFF showed considerable agreement with the observed values but were generally underestimated. The spatial-temporal concentration pattern revealed that the maximum concentrations tended to appear in the urban centers and during the winter. In terms of their contributions to pollutant concentrations, the districts of Xihu, Pingshan, and Mingshan all affected the urban air quality to different degrees. According to the type-based classification, which categorized the pollution sources as belonging to the Bengang Group, large point sources, small point sources, and area sources, the source apportionment showed that the Bengang Group, the large point sources, and the area sources had considerable impacts on urban air quality. Finally, combined with the industrial characteristics, detailed control measures were proposed with which local policy makers could improve the urban air quality in Benxi. In summary, the results of this study showed that this framework has credibility for effectively improving urban air quality, based on the source apportionment of atmospheric pollutants. The authors endeavored to build up an effective framework based on the integrated WRF/CALPUFF to improve the air quality in many cities on meso-micro scales in China. Via this framework, the integrated modeling tool is accurately used to study the characteristics of meteorological fields, concentration fields, and source apportionments of pollutants in target area. The impacts of classified sources on air quality together with the industrial characteristics can provide more effective control measures for improving air quality. Through the case study, the technical framework developed in this study, particularly the source apportionment, could provide important data and technical support for policy makers to assess air pollution on the scale of a city in China or even the world.

Realistic natural atmospheric phenomena and weather effects for interactive virtual environments

NASA Astrophysics Data System (ADS)

McLoughlin, Leigh

Clouds and the weather are important aspects of any natural outdoor scene, but existing dynamic techniques within computer graphics only offer the simplest of cloud representations. The problem that this work looks to address is how to provide a means of simulating clouds and weather features such as precipitation, that are suitable for virtual environments. Techniques for cloud simulation are available within the area of meteorology, but numerical weather prediction systems are computationally expensive, give more numerical accuracy than we require for graphics and are restricted to the laws of physics. Within computer graphics, we often need to direct and adjust physical features or to bend reality to meet artistic goals, which is a key difference between the subjects of computer graphics and physical science. Pure physically-based simulations, however, evolve their solutions according to pre-set rules and are notoriously difficult to control. The challenge then is for the solution to be computationally lightweight and able to be directed in some measure while at the same time producing believable results. This work presents a lightweight physically-based cloud simulation scheme that simulates the dynamic properties of cloud formation and weather effects. The system simulates water vapour, cloud water, cloud ice, rain, snow and hail. The water model incorporates control parameters and the cloud model uses an arbitrary vertical temperature profile, with a tool described to allow the user to define this. The result of this work is that clouds can now be simulated in near real-time complete with precipitation. The temperature profile and tool then provide a means of directing the resulting formation..

Simulation of precipitation by weather pattern and frontal analysis

NASA Astrophysics Data System (ADS)

Wilby, Robert

1995-12-01

Daily rainfall from two sites in central and southern England was stratified according to the presence or absence of weather fronts and then cross-tabulated with the prevailing Lamb Weather Type (LWT). A semi-Markov chain model was developed for simulating daily sequences of LWTs from matrices of transition probabilities between weather types for the British Isles 1970-1990. Daily and annual rainfall distributions were then simulated from the prevailing LWTs using historic conditional probabilities for precipitation occurrence and frontal frequencies. When compared with a conventional rainfall generator the frontal model produced improved estimates of the overall size distribution of daily rainfall amounts and in particular the incidence of low-frequency high-magnitude totals. Further research is required to establish the contribution of individual frontal sub-classes to daily rainfall totals and of long-term fluctuations in frontal frequencies to conditional probabilities.

A new technique for observationally derived boundary conditions for space weather

NASA Astrophysics Data System (ADS)

Pagano, Paolo; Mackay, Duncan Hendry; Yeates, Anthony Robinson

2018-04-01

Context. In recent years, space weather research has focused on developing modelling techniques to predict the arrival time and properties of coronal mass ejections (CMEs) at the Earth. The aim of this paper is to propose a new modelling technique suitable for the next generation of Space Weather predictive tools that is both efficient and accurate. The aim of the new approach is to provide interplanetary space weather forecasting models with accurate time dependent boundary conditions of erupting magnetic flux ropes in the upper solar corona. Methods: To produce boundary conditions, we couple two different modelling techniques, MHD simulations and a quasi-static non-potential evolution model. Both are applied on a spatial domain that covers the entire solar surface, although they extend over a different radial distance. The non-potential model uses a time series of observed synoptic magnetograms to drive the non-potential quasi-static evolution of the coronal magnetic field. This allows us to follow the formation and loss of equilibrium of magnetic flux ropes. Following this a MHD simulation captures the dynamic evolution of the erupting flux rope, when it is ejected into interplanetary space. Results.The present paper focuses on the MHD simulations that follow the ejection of magnetic flux ropes to 4 R⊙. We first propose a technique for specifying the pre-eruptive plasma properties in the corona. Next, time dependent MHD simulations describe the ejection of two magnetic flux ropes, that produce time dependent boundary conditions for the magnetic field and plasma at 4 R⊙ that in future may be applied to interplanetary space weather prediction models. Conclusions: In the present paper, we show that the dual use of quasi-static non-potential magnetic field simulations and full time dependent MHD simulations can produce realistic inhomogeneous boundary conditions for space weather forecasting tools. Before a fully operational model can be produced there are a number of technical and scientific challenges that still need to be addressed. Nevertheless, we illustrate that coupling quasi-static and MHD simulations in this way can significantly reduce the computational time required to produce realistic space weather boundary conditions.

Feedbacks between Air Pollution and Weather, Part 1: Effects on Weather

EPA Science Inventory

The meteorological predictions of fully coupled air-quality models running in “feedback” versus “nofeedback” simulations were compared against each other as part of Phase 2 of the Air Quality Model Evaluation International Initiative. The model simulations included a “no-feedback...

Can we expect to predict climate if we cannot shadow weather?

NASA Astrophysics Data System (ADS)

Smith, Leonard

2010-05-01

What limits our ability to predict (or project) useful statistics of future climate? And how might we quantify those limits? In the early 1960s, Ed Lorenz illustrated one constraint on point forecasts of the weather (chaos) while noting another (model imperfections). In the mid-sixties he went on to discuss climate prediction, noting that chaos, per se, need not limit accurate forecasts of averages and the distributions that define climate. In short, chaos might place draconian limits on what we can say about a particular summer day in 2010 (or 2040), but it need not limit our ability to make accurate and informative statements about the weather over this summer as a whole, or climate distributions of the 2040's. If not chaos, what limits our ability to produce decision relevant probability distribution functions (PDFs)? Is this just a question of technology (raw computer power) and uncertain boundary conditions (emission scenarios)? Arguably, current model simulations of the Earth's climate are limited by model inadequacy: not that the initial or boundary conditions are unknown but that state-of-the-art models would not yield decision-relevant probability distributions even if they were known. Or to place this statement in an empirically falsifiable format: that in 2100 when the boundary conditions are known and computer power is (hopefully) sufficient to allow exhaustive exploration of today's state-of-the-art models: we will find today's models do not admit a trajectory consistent with our knowledge of the state of the earth in 2009 which would prove of decision support relevance for, say, 25 km, hourly resolution. In short: today's models cannot shadow the weather of this century even after the fact. Restating this conjecture in a more positive frame: a 2100 historian of science will be able to determine the highest space and time scales on which 2009 models could have (i) produced trajectories plausibly consistent with the (by then) observed twenty-first century and (ii) produced probability distributions useful as such for decision support. As it will be some time until such conjectures can be refuted, how might we best advise decision makers of the detail (specifically, space and time resolution of a quantity of interest as a function of lead-time) that it is rational to interpret model-based PDFs as decision-relevant probability distributions? Given the nonlinearities already incorporated in our models, how far into the future can one expect a simulation to get the temperature "right" given the simulation has precipitation badly "wrong"? When can biases in local temperature which melt model-ice no longer be dismissed, and neglected by presenting model-anomalies? At what lead times will feedbacks due to model inadequacies cause the 2007 model simulations to drift away from what today's basic science (and 2100 computer power) would suggest? How might one justify quantitative claims regarding "extreme events" (or NUMB weather)? Models are unlikely to forecast things they cannot shadow, or at least track. There is no constraint on rational scientists to take model distributions as their subjective probabilities, unless they believe the model is empirically adequate. How then are we to use today's simulations to inform today's decisions? Two approaches are considered. The first augments the model-based PDF with an explicit subjective-probability of a "Big Surprise". The second is to look not for a PDF but, following Solvency II, consider the risk from any event that cannot be ruled out at, say, the one in 200 level. The fact that neither approach provides the simplicity and apparent confidence of interpreting model-based PDFs as if they were objective probabilities does not contradict the claim that either might lead to better decision-making.

HF-START: A Regional Radio Propagation Simulator

NASA Astrophysics Data System (ADS)

Hozumi, K.; Maruyama, T.; Saito, S.; Nakata, H.; Rougerie, S.; Yokoyama, T.; Jin, H.; Tsugawa, T.; Ishii, M.

2017-12-01

HF-START (HF Simulator Targeting for All-users' Regional Telecommunications) is a user-friendly simulator developed to meet the needs of space weather users. Prediction of communications failure due to space weather disturbances is of high priority. Space weather users from various backgrounds with high economic impact, i.e. airlines, telecommunication companies, GPS-related companies, insurance companies, international amateur radio union, etc., recently increase. Space weather information provided by Space Weather Information Center of NICT is, however, too professional to be understood and effectively used by the users. To overcome this issue, I try to translate the research level data to the user level data based on users' needs and provide an immediate usable data. HF-START is positioned to be a space weather product out of laboratory based truly on users' needs. It is originally for radio waves in HF band (3-30 MHz) but higher frequencies up to L band are planned to be covered. Regional ionospheric data in Japan and southeast Asia are employed as a reflector of skywave mode propagation. GAIA (Ground-to-topside model of Atmosphere and Ionosphere for Aeronomy) model will be used as ionospheric input for global simulation. To evaluate HF-START, an evaluation campaign for Japan region will be launched in coming months. If the campaign successes, it will be expanded to southeast Asia region as well. The final goal of HF-START is to provide the near-realtime necessary radio parameters as well as the warning message of radio communications failure to the radio and space weather users.

SERVIR: The Regional Visualization and Monitoring System

NASA Technical Reports Server (NTRS)

Irwin, Daniel E.

2010-01-01

This slide presentation reviews the SERVIR program. SERVIR is a partnership between NASA and USAID and three international nodes: Central America, Africa, and the Himalaya region. SERVIR,using satellite observations and ground based observations, is used by decision makers to allow for improved monitoring of air quality, extreme weather, biodiversity, and changes in land cove and has also been used to respond to environmental threats, such as wildfires, floods, landslides, harmful algal blooms, and earthquakes.

Colluvial deposits as a possible weathering reservoir in uplifting mountains

NASA Astrophysics Data System (ADS)

Carretier, Sébastien; Goddéris, Yves; Martinez, Javier; Reich, Martin; Martinod, Pierre

2018-03-01

The role of mountain uplift in the evolution of the global climate over geological times is controversial. At the heart of this debate is the capacity of rapid denudation to drive silicate weathering, which consumes CO2. Here we present the results of a 3-D model that couples erosion and weathering during mountain uplift, in which, for the first time, the weathered material is traced during its stochastic transport from the hillslopes to the mountain outlet. To explore the response of weathering fluxes to progressively cooler and drier climatic conditions, we run model simulations accounting for a decrease in temperature with or without modifications in the rainfall pattern based on a simple orographic model. At this stage, the model does not simulate the deep water circulation, the precipitation of secondary minerals, variations in the pH, below-ground pCO2, and the chemical affinity of the water in contact with minerals. Consequently, the predicted silicate weathering fluxes probably represent a maximum, although the predicted silicate weathering rates are within the range of silicate and total weathering rates estimated from field data. In all cases, the erosion rate increases during mountain uplift, which thins the regolith and produces a hump in the weathering rate evolution. This model thus predicts that the weathering outflux reaches a peak and then falls, consistent with predictions of previous 1-D models. By tracking the pathways of particles, the model can also consider how lateral river erosion drives mass wasting and the temporary storage of colluvial deposits on the valley sides. This reservoir is comprised of fresh material that has a residence time ranging from several years up to several thousand years. During this period, the weathering of colluvium appears to sustain the mountain weathering flux. The relative weathering contribution of colluvium depends on the area covered by regolith on the hillslopes. For mountains sparsely covered by regolith during cold periods, colluvium produces most of the simulated weathering flux for a large range of erosion parameters and precipitation rate patterns. In addition to other reservoirs such as deep fractured bedrock, colluvial deposits may help to maintain a substantial and constant weathering flux in rapidly uplifting mountains during cooling periods.

GFDL's unified regional-global weather-climate modeling system with variable resolution capability for severe weather predictions and regional climate simulations

NASA Astrophysics Data System (ADS)

Lin, S. J.

2015-12-01

The NOAA/Geophysical Fluid Dynamics Laboratory has been developing a unified regional-global modeling system with variable resolution capabilities that can be used for severe weather predictions (e.g., tornado outbreak events and cat-5 hurricanes) and ultra-high-resolution (1-km) regional climate simulations within a consistent global modeling framework. The fundation of this flexible regional-global modeling system is the non-hydrostatic extension of the vertically Lagrangian dynamical core (Lin 2004, Monthly Weather Review) known in the community as FV3 (finite-volume on the cubed-sphere). Because of its flexability and computational efficiency, the FV3 is one of the final candidates of NOAA's Next Generation Global Prediction System (NGGPS). We have built into the modeling system a stretched (single) grid capability, a two-way (regional-global) multiple nested grid capability, and the combination of the stretched and two-way nests, so as to make convection-resolving regional climate simulation within a consistent global modeling system feasible using today's High Performance Computing System. One of our main scientific goals is to enable simulations of high impact weather phenomena (such as tornadoes, thunderstorms, category-5 hurricanes) within an IPCC-class climate modeling system previously regarded as impossible. In this presentation I will demonstrate that it is computationally feasible to simulate not only super-cell thunderstorms, but also the subsequent genesis of tornadoes using a global model that was originally designed for century long climate simulations. As a unified weather-climate modeling system, we evaluated the performance of the model with horizontal resolution ranging from 1 km to as low as 200 km. In particular, for downscaling studies, we have developed various tests to ensure that the large-scale circulation within the global varaible resolution system is well simulated while at the same time the small-scale can be accurately captured within the targeted high resolution region.

Realtime Space Weather Forecasts Via Android Phone App

NASA Astrophysics Data System (ADS)

Crowley, G.; Haacke, B.; Reynolds, A.

2010-12-01

For the past several years, ASTRA has run a first-principles global 3-D fully coupled thermosphere-ionosphere model in real-time for space weather applications. The model is the Thermosphere-Ionosphere Mesosphere Electrodynamics General Circulation Model (TIMEGCM). ASTRA also runs the Assimilative Mapping of Ionospheric Electrodynamics (AMIE) in real-time. Using AMIE to drive the high latitude inputs to the TIMEGCM produces high fidelity simulations of the global thermosphere and ionosphere. These simulations can be viewed on the Android Phone App developed by ASTRA. The SpaceWeather app for the Android operating system is free and can be downloaded from the Google Marketplace. We present the current status of realtime thermosphere-ionosphere space-weather forcasting and discuss the way forward. We explore some of the issues in maintaining real-time simulations with assimilative data feeds in a quasi-operational setting. We also discuss some of the challenges of presenting large amounts of data on a smartphone. The ASTRA SpaceWeather app includes the broadest and most unique range of space weather data yet to be found on a single smartphone app. This is a one-stop-shop for space weather and the only app where you can get access to ASTRA’s real-time predictions of the global thermosphere and ionosphere, high latitude convection and geomagnetic activity. Because of the phone's GPS capability, users can obtain location specific vertical profiles of electron density, temperature, and time-histories of various parameters from the models. The SpaceWeather app has over 9000 downloads, 30 reviews, and a following of active users. It is clear that real-time space weather on smartphones is here to stay, and must be included in planning for any transition to operational space-weather use.

Impact of Tactical and Strategic Weather Avoidance on Separation Assurance

NASA Technical Reports Server (NTRS)

Refai, Mohamad S.; Windhorst, Robert

2011-01-01

The ability to keep flights away from weather hazards while maintaining aircraft-to-aircraft separation is critically important. The Advanced Airspace Concept is an automation concept that implements a ground-based strategic conflict resolution algorithm for management of aircraft separation. The impact of dynamic and uncertain weather avoidance on this concept is investigated. A strategic weather rerouting system is integrated with the Advanced Airspace Concept, which also provides a tactical weather avoidance algorithm, in a fast time simulation of the Air Transportation System. Strategic weather rerouting is used to plan routes around weather in the 20 minute to two-hour time horizon. To address forecast uncertainty, flight routes are revised at 15 minute intervals. Tactical weather avoidance is used for short term trajectory adjustments (30 minute planning horizon) that are updated every minute to address any weather conflicts (instances where aircraft are predicted to pass through weather cells) that are left unresolved by strategic weather rerouting. The fast time simulation is used to assess the impact of tactical weather avoidance on the performance of automated conflict resolution as well as the impact of strategic weather rerouting on both conflict resolution and tactical weather avoidance. The results demonstrate that both tactical weather avoidance and strategic weather rerouting increase the algorithm complexity required to find aircraft conflict resolutions. Results also demonstrate that tactical weather avoidance is prone to higher airborne delay than strategic weather rerouting. Adding strategic weather rerouting to tactical weather avoidance reduces total airborne delays for the reported scenario by 18% and reduces the number of remaining weather violations by 13%. Finally, two features are identified that have proven important for strategic weather rerouting to realize these benefits; namely, the ability to revise reroutes and the use of maneuvers that start far ahead of encountering a weather cell when rerouting around weather.

A Coupled Surface Nudging Scheme for use in Retrospective Weather and Climate Simulations for Environmental Applications

EPA Science Inventory

A surface analysis nudging scheme coupling atmospheric and land surface thermodynamic parameters has been implemented into WRF v3.8 (latest version) for use with retrospective weather and climate simulations, as well as for applications in air quality, hydrology, and ecosystem mo...

Incorporating Medium-Range Weather Forecasts in Seasonal Crop Scenarios over the Greater Horn of Africa to Support National/Regional/Local Decision Makers

NASA Astrophysics Data System (ADS)

Shukla, S.; Husak, G. J.; Funk, C. C.; Verdin, J. P.

2015-12-01

The USAID's Famine Early Warning Systems Network (FEWS NET) provides seasonal assessments of crop conditions over the Greater Horn of Africa (GHA) and other food insecure regions. These assessments and current livelihood, nutrition, market conditions and conflicts are used to generate food security scenarios that help national, regional and local decision makers target their resources and mitigate socio-economic losses. Among the various tools that FEWS NET uses is the FAO's Water Requirement Satisfaction Index (WRSI). The WRSI is a simple yet powerful crop assessment model that incorporates current moisture conditions (at the time of the issuance of forecast), precipitation scenarios, potential evapotranspiration and crop parameters to categorize crop conditions into different classes ranging from "failure" to "very good". The WRSI tool has been shown to have a good agreement with local crop yields in the GHA region. At present, the precipitation scenarios used to drive the WRSI are based on either a climatological forecast (that assigns equal chances of occurrence to all possible scenarios and has no skill over the forecast period) or a sea-surface temperature anomaly based scenario (which at best have skill at the seasonal scale). In both cases, the scenarios fail to capture the skill that can be attained by initial atmospheric conditions (i.e., medium-range weather forecasts). During the middle of a cropping season, when a week or two of poor rains can have a devastating effect, two weeks worth of skillful precipitation forecasts could improve the skill of the crop scenarios. With this working hypothesis, we examine the value of incorporating medium-range weather forecasts in improving the skill of crop scenarios in the GHA region. We use the NCEP's Global Ensemble Forecast system (GEFS) weather forecasts and examine the skill of crop scenarios generated using the GEFS weather forecasts with respect to the scenarios based solely on the climatological forecast. The period of analysis is from 1985-2010 (over which the reforecasts of GEFS is available) and the focus season is October-November-December. We examine the improvement (if any) in long-term skill, and present results for several recent drought events in the region.

Development of an interactive interface to raise awareness of public, policy makers, and practitioners about natural hazards.

NASA Astrophysics Data System (ADS)

Gordova, Yulia; Gordov, Evgeny; Okladnikov, Igor; Titov, Alexander

2017-04-01

Due to a global climate change the following consequences are predicted: rise in sea level due to melting glaciers and polar ice, changes in precipitation, changes in the hydrological regime, impact on ecosystems, agriculture and forestry. In Russia's vast territory these effects will be most dramatic. According to Hydrometeorological Center of Russian Federation report there is an increase in the magnitude and frequency of extreme weather events, as well as in their damage to ecosystems and infrastructure. In the framework of adaptation to climate change and mitigation of its consequences it is necessary to promote and support activities aimed at reducing possible risks. Adaptation methods include among others improving seasonal weather forecasts, systems of early warning and systems of management of risks. But there is a problem of insufficient awareness among decision-makers, as well a lack of scientific background. Those responsible for making decisions, stakeholders and the public do not have the skills and knowledge to work with the accumulated climate data to development an adaptation and sustainable development strategy. The goal is to provide these groups with tools, skills, thematic information for understanding climate processes occurring in the region. We believe that the preparation of both the persons responsible for decision-making, and the future specialist in environmental sciences shouldn't be realized artificial learning environment, but on the basis of actual operating computational and information systems used in climate research. Such kind of a system was developed by a team of the Institute of Monitoring of Climatic and Ecological Systems SB RAS. The information-computational Web GIS "Climate" (http://climate.climate.scert.ru) provides opportunities to study regional climate change and its consequences providing access to climate and weather models, a large set of geophysical data and means of processing and visualization. Also, the system is used for undergraduate and graduate students training. In addition, the system capabilities allow creating information resources to raise public awareness about climate change, its causes and consequences, which is a necessary step for the subsequent adaptation to these changes. "Climate" allows climatologists, specialists in related fields, decision-makers, stakeholders and the public use a variety of geographically distributed spatially-referenced data, resources and processing services via a web-browser. Currently, an interactive System User Manual for decision-makers is developed. It contains not only the information needed to use the system and perform practical tasks, but also the basic concepts explained in detail. The knowledge necessary for understanding the causes and possible consequences of the processes is given. The results of implementation of practical tasks are available not only in the form of color surface maps, but also on the Internet and in the form of layers for most GIS. Thus these layers can be used in usual desktop GIS which is a common software for most of decision-makers. Thus, this manual helps to prepare qualified users, which in the future will be able to determine the policy of the region to adapt to climate change impacts and hazards. The work is supported by Russian Science Foundation grant № 16-19-10257.

Simulating soybean canopy temperature as affected by weather variables and soil water potential

NASA Technical Reports Server (NTRS)

Choudhury, B. J.

1982-01-01

Hourly weather data for several clear sky days during summer at Phoenix and Baltimore which covered a wide range of variables were used with a plant atmosphere model to simulate soybean (Glycine max L.) leaf water potential, stomatal resistance and canopy temperature at various soil water potentials. The air and dew point temperatures were found to be the significant weather variables affecting the canopy temperatures. Under identical weather conditions, the model gives a lower canopy temperature for a soybean crop with a higher rooting density. A knowledge of crop rooting density, in addition to air and dew point temperatures is needed in interpreting infrared radiometric observations for soil water status. The observed dependence of stomatal resistance on the vapor pressure deficit and soil water potential is fairly well represented. Analysis of the simulated leaf water potentials indicates overestimation, possibly due to differences in the cultivars.

Use of a Data-Linked Weather Information Display and Effects on Pilot Navigation Decision Making in a Piloted Simulation Study

NASA Technical Reports Server (NTRS)

Yuchnovicz, Daniel E.; Novacek, Paul F.; Burgess, Malcolm A.; Heck, Michael L.; Stokes, Alan F.

2001-01-01

This study provides recommendations to the FAA and to prospective manufacturers based on an exploration of the effects of data link weather displays upon pilot decision performance. An experiment was conducted with twenty-four current instrument rated pilots who were divided into two equal groups and presented with a challenging but realistic flight scenario involving weather containing significant embedded convective activity. All flights were flown in a full-mission simulation facility within instrument meteorological conditions. The inflight weather display depicted NexRad images, graphical METARs and textual METARs. The objective was to investigate the potential for misuse of a weather display, and incorporate recommendations for the design and use of these displays. The primary conclusion of the study found that the inflight weather display did not improve weather avoidance decision making. Some of the reasons to support this finding include: the pilot's inability to easily perceive their proximity to the storms, increased workload and difficulty in deciphering METAR textual data. The compelling nature of a graphical weather display caused many pilots to reduce their reliance on corroborating weather information from other sources. Minor changes to the weather display could improve the ability of a pilot to make better decisions on hazard avoidance.

Multi-time scale Climate Informed Stochastic Hybrid Simulation-Optimization Model (McISH model) for Multi-Purpose Reservoir System

NASA Astrophysics Data System (ADS)

Lu, M.; Lall, U.

2013-12-01

In order to mitigate the impacts of climate change, proactive management strategies to operate reservoirs and dams are needed. A multi-time scale climate informed stochastic model is developed to optimize the operations for a multi-purpose single reservoir by simulating decadal, interannual, seasonal and sub-seasonal variability. We apply the model to a setting motivated by the largest multi-purpose dam in N. India, the Bhakhra reservoir on the Sutlej River, a tributary of the Indus. This leads to a focus on timing and amplitude of the flows for the monsoon and snowmelt periods. The flow simulations are constrained by multiple sources of historical data and GCM future projections, that are being developed through a NSF funded project titled 'Decadal Prediction and Stochastic Simulation of Hydroclimate Over Monsoon Asia'. The model presented is a multilevel, nonlinear programming model that aims to optimize the reservoir operating policy on a decadal horizon and the operation strategy on an updated annual basis. The model is hierarchical, in terms of having a structure that two optimization models designated for different time scales are nested as a matryoshka doll. The two optimization models have similar mathematical formulations with some modifications to meet the constraints within that time frame. The first level of the model is designated to provide optimization solution for policy makers to determine contracted annual releases to different uses with a prescribed reliability; the second level is a within-the-period (e.g., year) operation optimization scheme that allocates the contracted annual releases on a subperiod (e.g. monthly) basis, with additional benefit for extra release and penalty for failure. The model maximizes the net benefit of irrigation, hydropower generation and flood control in each of the periods. The model design thus facilitates the consistent application of weather and climate forecasts to improve operations of reservoir systems. The decadal flow simulations are re-initialized every year with updated climate projections to improve the reliability of the operation rules for the next year, within which the seasonal operation strategies are nested. The multi-level structure can be repeated for monthly operation with weekly subperiods to take advantage of evolving weather forecasts and seasonal climate forecasts. As a result of the hierarchical structure, sub-seasonal even weather time scale updates and adjustment can be achieved. Given an ensemble of these scenarios, the McISH reservoir simulation-optimization model is able to derive the desired reservoir storage levels, including minimum and maximum, as a function of calendar date, and the associated release patterns. The multi-time scale approach allows adaptive management of water supplies acknowledging the changing risks, meeting both the objectives over the decade in expected value and controlling the near term and planning period risk through probabilistic reliability constraints. For the applications presented, the target season is the monsoon season from June to September. The model also includes a monthly flood volume forecast model, based on a Copula density fit to the monthly flow and the flood volume flow. This is used to guide dynamic allocation of the flood control volume given the forecasts.

Comparison of simulated and actual wind shear radar data products

NASA Technical Reports Server (NTRS)

Britt, Charles L.; Crittenden, Lucille H.

1992-01-01

Prior to the development of the NASA experimental wind shear radar system, extensive computer simulations were conducted to determine the performance of the radar in combined weather and ground clutter environments. The simulation of the radar used analytical microburst models to determine weather returns and synthetic aperture radar (SAR) maps to determine ground clutter returns. These simulations were used to guide the development of hazard detection algorithms and to predict their performance. The structure of the radar simulation is reviewed. Actual flight data results from the Orlando and Denver tests are compared with simulated results. Areas of agreement and disagreement of actual and simulated results are shown.

A Study into the Impact of Physical Structures on the Runway Velocity Field at the Atlantic City International Airport

NASA Astrophysics Data System (ADS)

King, David, Jr.; Manson, Russell; Trout, Joseph; Decicco, Nicholas; Rios, Manny

2015-04-01

Wake vortices are generated by airplanes in flight. These vortices decay slowly and may persist for several minutes after their creation. These vortices and associated smaller scale turbulent structures present a hazard to incoming flights. It is for this reason that incoming flights are timed to arrive after these vortices have dissipated. Local weather conditions, mainly prevailing winds, can affect the transport and evolution of these vortices; therefore, there is a need to fully understand localized wind patterns at the airport-sized mircoscale. Here we have undertaken a computational investigation into the impacts of localized wind flows and physical structures on the velocity field at Atlantic City International Airport. The simulations are undertaken in OpenFOAM, an open source computational fluid dynamics software package, using an optimized geometric mesh of the airport. Initial conditions for the simulations are based on historical data with the option to run simulations based on projected weather conditions imported from the Weather Research & Forcasting (WRF) Model. Sub-grid scale turbulence is modeled using a Large Eddy Simulation (LES) approach. The initial results gathered from the WRF Model simulations and historical weather data analysis are presented elsewhere.

An analytical framework to assist decision makers in the use of forest ecosystem model predictions

USDA-ARS?s Scientific Manuscript database

The predictions of most terrestrial ecosystem models originate from deterministic simulations. Relatively few uncertainty evaluation exercises in model outputs are performed by either model developers or users. This issue has important consequences for decision makers who rely on models to develop n...

Improving safety and efficiency of signalized intersections during inclement weather : project summary.

DOT National Transportation Integrated Search

2017-01-01

Using a combination of simulation and field studies, the research team found that agencies can achieve slight improvements by adjusting their traffic signal timing plans during adverse weather conditions. Agencies can detect when adverse weather cond...

ESiWACE: A Center of Excellence for HPC applications to support cloud resolving earth system modelling

NASA Astrophysics Data System (ADS)

Biercamp, Joachim; Adamidis, Panagiotis; Neumann, Philipp

2017-04-01

With the exa-scale era approaching, length and time scales used for climate research on one hand and numerical weather prediction on the other hand blend into each other. The Centre of Excellence in Simulation of Weather and Climate in Europe (ESiWACE) represents a European consortium comprising partners from climate, weather and HPC in their effort to address key scientific challenges that both communities have in common. A particular challenge is to reach global models with spatial resolutions that allow simulating convective clouds and small-scale ocean eddies. These simulations would produce better predictions of trends and provide much more fidelity in the representation of high-impact regional events. However, running such models in operational mode, i.e with sufficient throughput in ensemble mode clearly will require exa-scale computing and data handling capability. We will discuss the ESiWACE initiative and relate it to work-in-progress on high-resolution simulations in Europe. We present recent strong scalability measurements from ESiWACE to demonstrate current computability in weather and climate simulation. A special focus in this particular talk is on the Icosahedal Nonhydrostatic (ICON) model used for a comparison of high resolution regional and global simulations with high quality observation data. We demonstrate that close-to-optimal parallel efficiency can be achieved in strong scaling global resolution experiments on Mistral/DKRZ, e.g. 94% for 5km resolution simulations using 36k cores on Mistral/DKRZ. Based on our scalability and high-resolution experiments, we deduce and extrapolate future capabilities for ICON that are expected for weather and climate research at exascale.

A conditional stochastic weather generator for seasonal to multi-decadal simulations

NASA Astrophysics Data System (ADS)

Verdin, Andrew; Rajagopalan, Balaji; Kleiber, William; Podestá, Guillermo; Bert, Federico

2018-01-01

We present the application of a parametric stochastic weather generator within a nonstationary context, enabling simulations of weather sequences conditioned on interannual and multi-decadal trends. The generalized linear model framework of the weather generator allows any number of covariates to be included, such as large-scale climate indices, local climate information, seasonal precipitation and temperature, among others. Here we focus on the Salado A basin of the Argentine Pampas as a case study, but the methodology is portable to any region. We include domain-averaged (e.g., areal) seasonal total precipitation and mean maximum and minimum temperatures as covariates for conditional simulation. Areal covariates are motivated by a principal component analysis that indicates the seasonal spatial average is the dominant mode of variability across the domain. We find this modification to be effective in capturing the nonstationarity prevalent in interseasonal precipitation and temperature data. We further illustrate the ability of this weather generator to act as a spatiotemporal downscaler of seasonal forecasts and multidecadal projections, both of which are generally of coarse resolution.

Description of the GMAO OSSE for Weather Analysis Software Package: Version 3

NASA Technical Reports Server (NTRS)

Koster, Randal D. (Editor); Errico, Ronald M.; Prive, Nikki C.; Carvalho, David; Sienkiewicz, Meta; El Akkraoui, Amal; Guo, Jing; Todling, Ricardo; McCarty, Will; Putman, William M.;

The Altitude Wind Tunnel (AWT): A unique facility for propulsion system and adverse weather testing

NASA Technical Reports Server (NTRS)

Chamberlin, R.

1985-01-01

A need has arisen for a new wind tunnel facility with unique capabilities for testing propulsion systems and for conducting research in adverse weather conditions. New propulsion system concepts, new aircraft configurations with an unprecedented degree of propulsion system/aircraft integration, and requirements for aircraft operation in adverse weather dictate the need for a new test facility. Required capabilities include simulation of both altitude pressure and temperature, large size, full subsonic speed range, propulsion system operation, and weather simulation (i.e., icing, heavy rain). A cost effective rehabilitation of the NASA Lewis Research Center's Altitude Wind Tunnel (AWT) will provide a facility with all these capabilities.

Evaluation of the HadGEM3-A simulations in view of detection and attribution of human influence on extreme events in Europe

NASA Astrophysics Data System (ADS)

Vautard, Robert; Christidis, Nikolaos; Ciavarella, Andrew; Alvarez-Castro, Carmen; Bellprat, Omar; Christiansen, Bo; Colfescu, Ioana; Cowan, Tim; Doblas-Reyes, Francisco; Eden, Jonathan; Hauser, Mathias; Hegerl, Gabriele; Hempelmann, Nils; Klehmet, Katharina; Lott, Fraser; Nangini, Cathy; Orth, René; Radanovics, Sabine; Seneviratne, Sonia I.; van Oldenborgh, Geert Jan; Stott, Peter; Tett, Simon; Wilcox, Laura; Yiou, Pascal

2018-04-01

A detailed analysis is carried out to assess the HadGEM3-A global atmospheric model skill in simulating extreme temperatures, precipitation and storm surges in Europe in the view of their attribution to human influence. The analysis is performed based on an ensemble of 15 atmospheric simulations forced with observed sea surface temperature of the 54 year period 1960-2013. These simulations, together with dual simulations without human influence in the forcing, are intended to be used in weather and climate event attribution. The analysis investigates the main processes leading to extreme events, including atmospheric circulation patterns, their links with temperature extremes, land-atmosphere and troposphere-stratosphere interactions. It also compares observed and simulated variability, trends and generalized extreme value theory parameters for temperature and precipitation. One of the most striking findings is the ability of the model to capture North-Atlantic atmospheric weather regimes as obtained from a cluster analysis of sea level pressure fields. The model also reproduces the main observed weather patterns responsible for temperature and precipitation extreme events. However, biases are found in many physical processes. Slightly excessive drying may be the cause of an overestimated summer interannual variability and too intense heat waves, especially in central/northern Europe. However, this does not seem to hinder proper simulation of summer temperature trends. Cold extremes appear well simulated, as well as the underlying blocking frequency and stratosphere-troposphere interactions. Extreme precipitation amounts are overestimated and too variable. The atmospheric conditions leading to storm surges were also examined in the Baltics region. There, simulated weather conditions appear not to be leading to strong enough storm surges, but winds were found in very good agreement with reanalyses. The performance in reproducing atmospheric weather patterns indicates that biases mainly originate from local and regional physical processes. This makes local bias adjustment meaningful for climate change attribution.

Towards a unified Global Weather-Climate Prediction System

NASA Astrophysics Data System (ADS)

Lin, S. J.

2016-12-01

The Geophysical Fluid Dynamics Laboratory has been developing a unified regional-global modeling system with variable resolution capabilities that can be used for severe weather predictions and kilometer scale regional climate simulations within a unified global modeling system. The foundation of this flexible modeling system is the nonhydrostatic Finite-Volume Dynamical Core on the Cubed-Sphere (FV3). A unique aspect of FV3 is that it is "vertically Lagrangian" (Lin 2004), essentially reducing the equation sets to two dimensions, and is the single most important reason why FV3 outperforms other non-hydrostatic cores. Owning to its accuracy, adaptability, and computational efficiency, the FV3 has been selected as the "engine" for NOAA's Next Generation Global Prediction System (NGGPS). We have built into the modeling system a stretched grid, a two-way regional-global nested grid, and an optimal combination of the stretched and two-way nests capability, making kilometer-scale regional simulations within a global modeling system feasible. Our main scientific goal is to enable simulations of high impact weather phenomena (such as tornadoes, thunderstorms, category-5 hurricanes) within an IPCC-class climate modeling system previously regarded as impossible. In this presentation I will demonstrate that, with the FV3, it is computationally feasible to simulate not only super-cell thunderstorms, but also the subsequent genesis of tornado-like vortices using a global model that was originally designed for climate simulations. The development and tuning strategy between traditional weather and climate models are fundamentally different due to different metrics. We were able to adapt and use traditional "climate" metrics or standards, such as angular momentum conservation, energy conservation, and flux balance at top of the atmosphere, and gain insight into problems of traditional weather prediction model for medium-range weather prediction, and vice versa. Therefore, the unification in weather and climate models can happen not just at the algorithm or parameterization level, but also in the metric and tuning strategy used for both applications, and ultimately, with benefits to both weather and climate applications.

Mapping Water Stress Incidence and Intensity, Optimal Plant Populations, and Cultivar Duration for African Groundnut Productivity Enhancement.

PubMed

Vadez, Vincent; Halilou, Oumarou; Hissene, Halime M; Sibiry-Traore, Pierre; Sinclair, Thomas R; Soltani, Afshin

2017-01-01

Groundnut production is limited in Sub-Saharan Africa and water deficit or "drought," is often considered as the main yield-limiting factor. However, no comprehensive study has assessed the extent and intensity of "drought"-related yield decreases, nor has it explored avenues to enhance productivity. Hence, crop simulation modeling with SSM (Simple Simulation Modeling) was used to address these issues. To palliate the lack of reliable weather data as input to the model, the validity of weather data generated by Marksim, a weather generator, was tested. Marksim provided good weather representation across a large gradient of rainfall, representative of the region, and although rainfall generated by Marksim was above observations, run-off from Marksim data was also higher, and consequently simulations using observed or Marksim weather agreed closely across this gradient of weather conditions (root mean square of error = 99 g m -2 ; R 2 = 0.81 for pod yield). More importantly, simulation of yield changes upon agronomic or genetic alterations in the model were equally predicted with Marksim weather. A 1° × 1° grid of weather data was generated. "Drought"-related yield reduction were limited to latitudes above 12-13° North in West Central Africa (WCA) and to the Eastern fringes of Tanzania and Mozambique in East South Africa (ESA). Simulation and experimental trials also showed that doubling the sowing density of Spanish cultivars from 20 to 40 plants m -2 would increase yield dramatically in both WCA and ESA. However, increasing density would require growers to invest in more seeds and likely additional labor. If these trade-offs cannot be alleviated, genetic improvement would then need to re-focus on a plant type that is adapted to the current low sowing density, like a runner rather than a bush plant type, which currently receives most of the genetic attention. Genetic improvement targeting "drought" adaptation should also be restricted to areas where water is indeed an issue, i.e., above 12-13°N latitude in WCA and the Eastern fringes of Tanzania and Mozambique.

A method for ensemble wildland fire simulation

Treesearch

Mark A. Finney; Isaac C. Grenfell; Charles W. McHugh; Robert C. Seli; Diane Trethewey; Richard D. Stratton; Stuart Brittain

2011-01-01

An ensemble simulation system that accounts for uncertainty in long-range weather conditions and two-dimensional wildland fire spread is described. Fuel moisture is expressed based on the energy release component, a US fire danger rating index, and its variation throughout the fire season is modeled using time series analysis of historical weather data. This analysis...

More reliable forecasts with less precise computations: a fast-track route to cloud-resolved weather and climate simulators?

PubMed Central

Palmer, T. N.

2014-01-01

This paper sets out a new methodological approach to solving the equations for simulating and predicting weather and climate. In this approach, the conventionally hard boundary between the dynamical core and the sub-grid parametrizations is blurred. This approach is motivated by the relatively shallow power-law spectrum for atmospheric energy on scales of hundreds of kilometres and less. It is first argued that, because of this, the closure schemes for weather and climate simulators should be based on stochastic–dynamic systems rather than deterministic formulae. Second, as high-wavenumber elements of the dynamical core will necessarily inherit this stochasticity during time integration, it is argued that the dynamical core will be significantly over-engineered if all computations, regardless of scale, are performed completely deterministically and if all variables are represented with maximum numerical precision (in practice using double-precision floating-point numbers). As the era of exascale computing is approached, an energy- and computationally efficient approach to cloud-resolved weather and climate simulation is described where determinism and numerical precision are focused on the largest scales only. PMID:24842038

More reliable forecasts with less precise computations: a fast-track route to cloud-resolved weather and climate simulators?

PubMed

Palmer, T N

2014-06-28

This paper sets out a new methodological approach to solving the equations for simulating and predicting weather and climate. In this approach, the conventionally hard boundary between the dynamical core and the sub-grid parametrizations is blurred. This approach is motivated by the relatively shallow power-law spectrum for atmospheric energy on scales of hundreds of kilometres and less. It is first argued that, because of this, the closure schemes for weather and climate simulators should be based on stochastic-dynamic systems rather than deterministic formulae. Second, as high-wavenumber elements of the dynamical core will necessarily inherit this stochasticity during time integration, it is argued that the dynamical core will be significantly over-engineered if all computations, regardless of scale, are performed completely deterministically and if all variables are represented with maximum numerical precision (in practice using double-precision floating-point numbers). As the era of exascale computing is approached, an energy- and computationally efficient approach to cloud-resolved weather and climate simulation is described where determinism and numerical precision are focused on the largest scales only.

Examining Projected Changes in Weather & Air Quality Extremes Between 2000 & 2030 using Dynamical Downscaling

EPA Science Inventory

Climate change may alter regional weather extremes resulting in a range of environmental impacts including changes in air quality, water quality and availability, energy demands, agriculture, and ecology. Dynamical downscaling simulations were conducted with the Weather Research...

Approaches to evaluating weathering effects on release of ...

EPA Pesticide Factsheets

Increased production and use of engineered nanomaterials (ENMs) over the past decade has increased the potential for the transport and release of these materials into the environment. Here we present results of two separate studies designed to simulate the effects of weathering on the potential release of multiwalled carbon nanotubes (MWCNTs) from polyamide or epoxy composites, and nanosilica from composites with low-density polyethylene (LOPE) with added pro-oxidant. With these weathering-resistant ENMs, the release was primarily driven by degradation of the polymer matrix. The MWCNT-polymer composites were investigated in a pilot inter-laboratory study to simulate the effects of weathering on the potential release of multiwalled carbon nanotubes (MWCNTs) from their composites with two polymers. Wafers of MWCNTs in epoxy and polyamide nanocomposi tes were exposed in four laboratories in the US and Europe under carefully controlled conditions to cycles of simulated sunlight and rainfall over a 2000-hour period. Particles released upon submersion of the weathered wafers in the leaching fluid described in EPA Method 1311 were analyzed by Transmission Electron Microscopy (TEM), Inductively Coupled Plasma- Mass Spectrometry (ICP-MS), and Ultraviolet-Visible Spectroscopy (UV-Vis). Rates ofrelease of MWCNTS determined by ICP-MS (Co associatedwith MWCNTS) and UY-Vis agreed within a factor of two. Other weathering studies of nanosilica-LDPE composites were conducted usi

Onset and ending of the late Palaeozoic ice age triggered by tectonically paced rock weathering

NASA Astrophysics Data System (ADS)

Goddéris, Yves; Donnadieu, Yannick; Carretier, Sébastien; Aretz, Markus; Dera, Guillaume; Macouin, Mélina; Regard, Vincent

2017-04-01

The onset of the late Palaeozoic ice age about 340 million years ago has been attributed to a decrease in atmospheric CO2 concentrations associated with expansion of land plants, as plants both enhance silicate rock weathering--which consumes CO2--and increase the storage of organic carbon on land. However, plant expansion and carbon uptake substantially predate glaciation. Here we use climate and carbon cycle simulations to investigate the potential effects of the uplift of the equatorial Hercynian mountains and the assembly of Pangaea on the late Palaeozoic carbon cycle. In our simulations, mountain uplift during the Late Carboniferous caused an increase in physical weathering that removed the thick soil cover that had inhibited silicate weathering. The resulting increase in chemical weathering was sufficient to cause atmospheric CO2 concentrations to fall below the levels required to initiate glaciation. During the Permian, the lowering of the mountains led to a re-establishment of thick soils, whilst the assembly of Pangaea promoted arid conditions in continental interiors that were unfavourable for silicate weathering. These changes allowed CO2 concentrations to rise to levels sufficient to terminate the glacial event. Based on our simulations, we suggest that tectonically influenced carbon cycle changes during the late Palaeozoic were sufficient to initiate and terminate the late Palaeozoic ice age.

Analyzing the Chemical and Spectral Effects of Pulsed Laser Irradiation to Simulate Space Weathering of a Carbonaceous Chondrite

NASA Technical Reports Server (NTRS)

Thompson, M. S.; Keller, L. P.; Christoffersen, R.; Loeffler, M. J.; Morris, R. V.; Graff, T. G.; Rahman, Z.

2017-01-01

Space weathering processes alter the chemical composition, microstructure, and spectral characteristics of material on the surfaces of airless bodies. The mechanisms driving space weathering include solar wind irradiation and the melting, vaporization and recondensation effects associated with micrometeorite impacts e.g., [1]. While much work has been done to understand space weathering of lunar and ordinary chondritic materials, the effects of these processes on hydrated carbonaceous chondrites is poorly understood. Analysis of space weathering of carbonaceous materials will be critical for understanding the nature of samples returned by upcoming missions targeting primitive, organic-rich bodies (e.g., OSIRIS-REx and Hayabusa 2). Recent experiments have shown the spectral properties of carbonaceous materials and associated minerals are altered by simulated weathering events e.g., [2-5]. However, the resulting type of alteration i.e., reddening vs. bluing of the reflectance spectrum, is not consistent across all experiments [2-5]. In addition, the microstructural and crystal chemical effects of many of these experiments have not been well characterized, making it difficult to attribute spectral changes to specific mineralogical or chemical changes in the samples. Here we report results of a pulsed laser irradiation experiment on a chip of the Murchison CM2 carbonaceous chondrite to simulate micrometeorite impact processing.

Scenario-neutral Food Security Risk Assessment: A livestock Heat Stress Case Study

NASA Astrophysics Data System (ADS)

Broman, D.; Rajagopalan, B.; Hopson, T. M.

2015-12-01

Food security risk assessments can provide decision-makers with actionable information to identify critical system limitations, and alternatives to mitigate the impacts of future conditions. The majority of current risk assessments have been scenario-led and results are limited by the scenarios - selected future states of the world's climate system and socioeconomic factors. A generic scenario-neutral framework for food security risk assessments is presented here that uses plausible states of the world without initially assigning likelihoods. Measures of system vulnerabilities are identified and system risk is assessed for these states. This framework has benefited greatly by research in the water and natural resource fields to adapt their planning to provide better risk assessments. To illustrate the utility of this framework we develop a case study using livestock heat stress risk within the pastoral system of West Africa. Heat stress can have a major impact not only on livestock owners, but on the greater food production system, decreasing livestock growth, milk production, and reproduction, and in severe cases, death. A heat stress index calculated from daily weather is used as a vulnerability measure and is computed from historic daily weather data at several locations in the study region. To generate plausible states, a stochastic weather generator is developed to generate synthetic weather sequences at each location, consistent with the seasonal climate. A spatial model of monthly and seasonal heat stress provide projections of current and future livestock heat stress measures across the study region, and can incorporate in seasonal climate and other external covariates. These models, when linked with empirical thresholds of heat stress risk for specific breeds offer decision-makers with actionable information for use in near-term warning systems as well as for future planning. Future assessment can indicate under which states livestock are at greatest risk of heat stress; when coupled with assessments of additional measures (e.g. water and fodder availability) can inform on alternatives that provide satisfactory performance under a wide range of states (e.g. optimal cattle breed, supplemental feed, increased water access).

Numerical Model Simulation of Atmosphere above A.C. Airport

NASA Astrophysics Data System (ADS)

Lutes, Tiffany; Trout, Joseph

2014-03-01

In this research project, the Weather Research & Forecasting (WRF) model from the National Center for Atmospheric Research (NCAR) is used to investigate past and present weather conditions. The Atlantic City Airport area in southern New Jersey is the area of interest. Long-term hourly data is analyzed and model simulations are created. By inputting high resolution surface data, a more accurate picture of the effects of different weather conditions will be portrayed. Currently, the impact of gridded model runs is being tested, and the impact of surface characteristics is being investigated.

Dynamically Evolving Sectors for Convective Weather Impact

NASA Technical Reports Server (NTRS)

Drew, Michael C.

2010-01-01

A new strategy for altering existing sector boundaries in response to blocking convective weather is presented. This method seeks to improve the reduced capacity of sectors directly affected by weather by moving boundaries in a direction that offers the greatest capacity improvement. The boundary deformations are shared by neighboring sectors within the region in a manner that preserves their shapes and sizes as much as possible. This reduces the controller workload involved with learning new sector designs. The algorithm that produces the altered sectors is based on a force-deflection mesh model that needs only nominal traffic patterns and the shape of the blocking weather for input. It does not require weather-affected traffic patterns that would have to be predicted by simulation. When compared to an existing optimal sector design method, the sectors produced by the new algorithm are more similar to the original sector shapes, resulting in sectors that may be more suitable for operational use because the change is not as drastic. Also, preliminary results show that this method produces sectors that can equitably distribute the workload of rerouted weather-affected traffic throughout the region where inclement weather is present. This is demonstrated by sector aircraft count distributions of simulated traffic in weather-affected regions.

Designing Crop Simulation Web Service with Service Oriented Architecture Principle

NASA Astrophysics Data System (ADS)

Chinnachodteeranun, R.; Hung, N. D.; Honda, K.

2015-12-01

Crop simulation models are efficient tools for simulating crop growth processes and yield. Running crop models requires data from various sources as well as time-consuming data processing, such as data quality checking and data formatting, before those data can be inputted to the model. It makes the use of crop modeling limited only to crop modelers. We aim to make running crop models convenient for various users so that the utilization of crop models will be expanded, which will directly improve agricultural applications. As the first step, we had developed a prototype that runs DSSAT on Web called as Tomorrow's Rice (v. 1). It predicts rice yields based on a planting date, rice's variety and soil characteristics using DSSAT crop model. A user only needs to select a planting location on the Web GUI then the system queried historical weather data from available sources and expected yield is returned. Currently, we are working on weather data connection via Sensor Observation Service (SOS) interface defined by Open Geospatial Consortium (OGC). Weather data can be automatically connected to a weather generator for generating weather scenarios for running the crop model. In order to expand these services further, we are designing a web service framework consisting of layers of web services to support compositions and executions for running crop simulations. This framework allows a third party application to call and cascade each service as it needs for data preparation and running DSSAT model using a dynamic web service mechanism. The framework has a module to manage data format conversion, which means users do not need to spend their time curating the data inputs. Dynamic linking of data sources and services are implemented using the Service Component Architecture (SCA). This agriculture web service platform demonstrates interoperability of weather data using SOS interface, convenient connections between weather data sources and weather generator, and connecting various services for running crop models for decision support.

Freeze-Thaw Cycle Test on Basalt, Diorite and Tuff Specimens with the Simulated Ground Temperature of Antarctica

NASA Astrophysics Data System (ADS)

Park, J.; Hyun, C.; Cho, H.; Park, H.

2010-12-01

Physical weathering caused by freeze-thaw action in cold regions was simulated with artificial weathering simulator in laboratory. Physical weathering of rock in cold regions usually depends on the temperature, rock type and moisture content. Then these three variables were considered in this study. The laboratory freeze-thaw tests were conducted on the three types of rocks, e.g. diorite, basalt and tuff, which are the major rock types around Sejong Station, King George Island, Antarctica. Nine core samples composed of three samples from each rock type were prepared in NX core, and 50 cycles of freeze-thaw test was carried out under dried and saturated water conditions. In this study, the physical weathering of rocks was investigated after each 10 cycles by measuring P-wave velocity, bulk density, effective porosity, Schmidt hardness and uniaxial compression strength(UCS). The experimental result of the diorite and the tuff specimens showed that P-wave velocity, bulk density, effective porosity, Schmidt hardness and UCS were gradually decreased as weathering progresses, but the result of the basalt specimens did not show typical trends due to the characteristics of irregular pore distribution and various pore sizes. Scanning electron microscopy(SEM) photographs of diorite, basalt and tuff specimens weathered in dried and saturated conditions were also acquired to investigate the role of water during physical weathering processes. The number and size of microcracks were increased as weathering progresses. This work was supported by the National Research Foundation of Korea(NRF) Grant(NRF-2010-0027753).

Validating the Airspace Concept Evaluation System for Different Weather Days

NASA Technical Reports Server (NTRS)

Zelinski, Shannon; Meyn, Larry

2006-01-01

This paper extends the process for validating the Airspace Concept Evaluation System using real-world historical flight operational data. System inputs such as flight plans and airport en-route capacities, are generated and processed to create a realistic reproduction of a single day's operations within the National Airspace System. System outputs such as airport throughput, delays, and en-route sector loads are then compared to real world operational metrics and delay statistics for the reproduced day. The process is repeated for 4 historical days with high and low traffic volume and delay attributed to weather. These 4 days are simulated using default en-route capacities and variable en-route capacities used to emulate weather. The validation results show that default enroute capacity simulations are closer to real-world data for low weather days than high weather days. The use of reduced variable enroute capacities adds a large delay bias to ACES but delay trends between weather days are better represented.

User Oriented Techniques to Support Interaction and Decision Making with Large Educational Databases

ERIC Educational Resources Information Center

Hartley, Roger; Almuhaidib, Saud M. Y.

2007-01-01

Information Technology is developing rapidly and providing policy/decision makers with large amounts of information that require processing and analysis. Decision support systems (DSS) aim to provide tools that not only help such analyses, but enable the decision maker to experiment and simulate the effects of different policies and selection…

Reported Influence of Evaluation Data on Decision Makers' Actions: An Empirical Examination

ERIC Educational Resources Information Center

Christie, Christina A.

2007-01-01

Using a set of scenarios derived from actual evaluation studies, this simulation study examines the reported influence of evaluation information on decision makers' potential actions. Each scenario described a context where one of three types of evaluation information (large-scale study data, case study data, or anecdotal accounts) is presented…

System Advisor Model (SAM) General Description (Version 2017.9.5)

DOE Office of Scientific and Technical Information (OSTI.GOV)

Freeman, Janine M; DiOrio, Nicholas A; Blair, Nathan J

This document describes the capabilities of the System Advisor Model (SAM) developed and distributed by the U.S. Department of Energy's National Renewable Energy Laboratory. The document is for potential users and others wanting to learn about the model's capabilities. SAM is a techno-economic computer model that calculates performance and financial metrics of renewable energy projects. Project developers, policy makers, equipment manufacturers, and researchers use graphs and tables of SAM results in the process of evaluating financial, technology, and incentive options for renewable energy projects. SAM simulates the performance of photovoltaic, concentrating solar power, solar water heating, wind, geothermal, biomass, andmore » conventional power systems. The financial models are for projects that either buy and sell electricity at retail rates (residential and commercial) or sell electricity at a price determined in a power purchase agreement (PPA). SAM's simulation tools facilitate parametric and sensitivity analyses, Monte Carlo simulation and weather variability (P50/P90) studies. SAM can also read input variables from Microsoft Excel worksheets. For software developers, the SAM software development kit (SDK) makes it possible to use SAM simulation modules in their applications written in C/C plus plus, C sharp, Java, Python, MATLAB, and other languages. NREL provides both SAM and the SDK as free downloads at https://sam.nrel.gov. SAM is an open source project, so its source code is available to the public. Researchers can study the code to understand the model algorithms, and software programmers can contribute their own models and enhancements to the project. Technical support and more information about the software are available on the website.« less

How wild is your model fire? Constraining WRF-Chem wildfire smoke simulations with satellite observations

NASA Astrophysics Data System (ADS)

Fischer, E. V.; Ford, B.; Lassman, W.; Pierce, J. R.; Pfister, G.; Volckens, J.; Magzamen, S.; Gan, R.

2015-12-01

Exposure to high concentrations of particulate matter (PM) present during acute pollution events is associated with adverse health effects. While many anthropogenic pollution sources are regulated in the United States, emissions from wildfires are difficult to characterize and control. With wildfire frequency and intensity in the western U.S. projected to increase, it is important to more precisely determine the effect that wildfire emissions have on human health, and whether improved forecasts of these air pollution events can mitigate the health risks associated with wildfires. One of the challenges associated with determining health risks associated with wildfire emissions is that the low spatial resolution of surface monitors means that surface measurements may not be representative of a population's exposure, due to steep concentration gradients. To obtain better estimates of ambient exposure levels for health studies, a chemical transport model (CTM) can be used to simulate the evolution of a wildfire plume as it travels over populated regions downwind. Improving the performance of a CTM would allow the development of a new forecasting framework that could better help decision makers estimate and potentially mitigate future health impacts. We use the Weather Research and Forecasting model with online chemistry (WRF-Chem) to simulate wildfire plume evolution. By varying the model resolution, meteorology reanalysis initial conditions, and biomass burning inventories, we are able to explore the sensitivity of model simulations to these various parameters. Satellite observations are used first to evaluate model skill, and then to constrain the model results. These data are then used to estimate population-level exposure, with the aim of better characterizing the effects that wildfire emissions have on human health.

Impact of Probabilistic Weather on Flight Routing Decisions

NASA Technical Reports Server (NTRS)

Sheth, Kapil; Sridhar, Banavar; Mulfinger, Daniel

2006-01-01

Flight delays in the United States have been found to increase year after year, along with the increase in air traffic. During the four-month period from May through August of 2005, weather related delays accounted for roughly 70% of all reported delays, The current weather prediction in tactical (within 2 hours) timeframe is at manageable levels, however, the state of forecasting weather for strategic (2-6 hours) timeframe is still not dependable for long-term planning. In the absence of reliable severe weather forecasts, the decision-making for flights longer than two hours is challenging. This paper deals with an approach of using probabilistic weather prediction for Traffic Flow Management use, and a general method using this prediction for estimating expected values of flight length and delays in the National Airspace System (NAS). The current state-of-the-art convective weather forecasting is employed to aid the decision makers in arriving at decisions for traffic flow and flight planing. The six-agency effort working on the Next Generation Air Transportation System (NGATS) have considered weather-assimilated decision-making as one of the principal foci out of a list of eight. The weather Integrated Product Team has considered integrated weather information and improved aviation weather forecasts as two of the main efforts (Ref. 1, 2). Recently, research has focused on the concept of operations for strategic traffic flow management (Ref. 3) and how weather data can be integrated for improved decision-making for efficient traffic management initiatives (Ref. 4, 5). An overview of the weather data needs and benefits of various participants in the air traffic system along with available products can be found in Ref. 6. Previous work related to use of weather data in identifying and categorizing pilot intrusions into severe weather regions (Ref. 7, 8) has demonstrated a need for better forecasting in the strategic planning timeframes and moving towards a probabilistic description of weather (Ref. 9). This paper focuses on. specified probability in a local region for flight intrusion/deviation decision-making. The process uses a probabilistic weather description, implements that in a air traffic assessment system to study trajectories of aircraft crossing a cut-off probability contour. This value would be useful for meteorologists in creating optimum distribution profiles for severe weather, Once available, the expected values of flight path and aggregate delays are calculated for efficient operations. The current research, however, does not deal with the issue of multiple cell encounters, as well as echo tops, and will be a topic of future work.

Evaluation of weather-based rice yield models in India.

PubMed

Sudharsan, D; Adinarayana, J; Reddy, D Raji; Sreenivas, G; Ninomiya, S; Hirafuji, M; Kiura, T; Tanaka, K; Desai, U B; Merchant, S N

2013-01-01

The objective of this study was to compare two different rice simulation models--standalone (Decision Support System for Agrotechnology Transfer [DSSAT]) and web based (SImulation Model for RIce-Weather relations [SIMRIW])--with agrometeorological data and agronomic parameters for estimation of rice crop production in southern semi-arid tropics of India. Studies were carried out on the BPT5204 rice variety to evaluate two crop simulation models. Long-term experiments were conducted in a research farm of Acharya N G Ranga Agricultural University (ANGRAU), Hyderabad, India. Initially, the results were obtained using 4 years (1994-1997) of data with weather parameters from a local weather station to evaluate DSSAT simulated results with observed values. Linear regression models used for the purpose showed a close relationship between DSSAT and observed yield. Subsequently, yield comparisons were also carried out with SIMRIW and DSSAT, and validated with actual observed values. Realizing the correlation coefficient values of SIMRIW simulation values in acceptable limits, further rice experiments in monsoon (Kharif) and post-monsoon (Rabi) agricultural seasons (2009, 2010 and 2011) were carried out with a location-specific distributed sensor network system. These proximal systems help to simulate dry weight, leaf area index and potential yield by the Java based SIMRIW on a daily/weekly/monthly/seasonal basis. These dynamic parameters are useful to the farming community for necessary decision making in a ubiquitous manner. However, SIMRIW requires fine tuning for better results/decision making.

Use of observational and model-derived fields and regime model output statistics in mesoscale forecasting

NASA Technical Reports Server (NTRS)

Forbes, G. S.; Pielke, R. A.

1985-01-01

Various empirical and statistical weather-forecasting studies which utilize stratification by weather regime are described. Objective classification was used to determine weather regime in some studies. In other cases the weather pattern was determined on the basis of a parameter representing the physical and dynamical processes relevant to the anticipated mesoscale phenomena, such as low level moisture convergence and convective precipitation, or the Froude number and the occurrence of cold-air damming. For mesoscale phenomena already in existence, new forecasting techniques were developed. The use of cloud models in operational forecasting is discussed. Models to calculate the spatial scales of forcings and resultant response for mesoscale systems are presented. The use of these models to represent the climatologically most prevalent systems, and to perform case-by-case simulations is reviewed. Operational implementation of mesoscale data into weather forecasts, using both actual simulation output and method-output statistics is discussed.

Reactions of Air Transport Flight Crews to Displays of Weather During Simulated Flight

NASA Technical Reports Server (NTRS)

Bliss, James P.; Fallon, Corey; Bustamante, Ernesto; Bailey, William R., III; Anderson, Brittany

2005-01-01

Display of information in the cockpit has long been a challenge for aircraft designers. Given the limited space in which to present information, designers have had to be extremely selective about the types and amount of flight related information to present to pilots. The general goal of cockpit display design and implementation is to ensure that displays present information that is timely, useful, and helpful. This suggests that displays should facilitate the management of perceived workload, and should allow maximal situation awareness. The formatting of current and projected weather displays represents a unique challenge. As technologies have been developed to increase the variety and capabilities of weather information available to flight crews, factors such as conflicting weather representations and increased decision importance have increased the likelihood for errors. However, if formatted optimally, it is possible that next generation weather displays could allow for clearer indications of weather trends such as developing or decaying weather patterns. Important issues to address include the integration of weather information sources, flight crew trust of displayed weather information, and the teamed reactivity of flight crews to displays of weather. Past studies of weather display reactivity and formatting have not adequately addressed these issues; in part because experimental stimuli have not approximated the complexity of modern weather displays, and in part because they have not used realistic experimental tasks or participants. The goal of the research reported here was to investigate the influence of onboard and NEXRAD agreement, range to the simulated potential weather event, and the pilot flying on flight crew deviation decisions, perceived workload, and perceived situation awareness. Fifteen pilot-copilot teams were required to fly a simulated route while reacting to weather events presented in two graphical formats on a separate visual display. Measures of flight crew reactions included performance-based measures such as deviation decision accuracy, and judgment-based measures such as perceived decision confidence, workload, situation awareness, and display trust. Results demonstrated that pilots adopted a conservative reaction strategy, often choosing to deviate from weather rather than ride through it. When onboard and NEXRAD displays did not agree, flight crews reacted in a complex manner, trusting the onboard system more but using the NEXRAD system to augment their situation awareness. Distance to weather reduced situation awareness and heightened workload levels. Overall, flight crews tended to adopt a participative leadership style marked by open communication. These results suggest that future weather displays should exploit the existing benefits of NEXRAD presentation for situation awareness while retaining the display structure and logic inherent in the onboard system.

Historic halo displays as weather indicator: Criteria and examples

NASA Astrophysics Data System (ADS)

Neuhäuser, Dagmar L.; Neuhäuser, Ralph

2016-04-01

There are numerous celestial signs reported in historic records, many of them refer to atmospheric ("sub-lunar") phenomena, such as ice halos and aurorae. In an interdisciplinary collaboration between astrophysics and cultural astronomy, we noticed that celestial observations including meteorological phenomena are often misinterpreted, mostly due to missing genuine criteria: especially ice crystal halos were recorded frequently in past centuries for religious reasons, but are mistaken nowadays often for other phenomena like aurorae. Ice halo displays yield clear information on humidity and temperature in certain atmospheric layers, and thereby indicate certain weather patterns. Ancient so-called rain makers used halo observations for weather forecast; e.g., a connection between certain halo displays and rain a few day later is statistically significant. Ice halos exist around sun and moon and are reported for both (they can stay for several days): many near, middle, and far eastern records from day- and night-time include such observations with high frequency. (Partly based on publications on halos by D.L. Neuhäuser & R. Neuhäuser, available at http://www.astro.uni-jena.de/index.php/terra-astronomy.html)

Workshop Builds Strategies to Address Global Positioning System Vulnerabilities

NASA Astrophysics Data System (ADS)

Fisher, Genene

2011-01-01

When we examine the impacts of space weather on society, do we really understand the risks? Can past experiences reliably predict what will happen in the future? As the complexity of technology increases, there is the potential for it to become more fragile, allowing for a single point of failure to bring down the entire system. Take the Global Positioning System (GPS) as an example. GPS positioning, navigation, and timing have become an integral part of daily life, supporting transportation and communications systems vital to the aviation, merchant marine, cargo, cellular phone, surveying, and oil exploration industries. Everyday activities such as banking, mobile phone operations, and even the control of power grids are facilitated by the accurate timing provided by GPS. Understanding the risks of space weather to GPS and the many economic sectors reliant upon it, as well as how to build resilience, was the focus of a policy workshop organized by the American Meteorological Society (AMS) and held on 13-14 October 2010 in Washington, D. C. The workshop brought together a select group of policy makers, space weather scientists, and GPS experts and users.

Linking the Weather Generator with Regional Climate Model

NASA Astrophysics Data System (ADS)

Dubrovsky, Martin; Farda, Ales; Skalak, Petr; Huth, Radan

2013-04-01

One of the downscaling approaches, which transform the raw outputs from the climate models (GCMs or RCMs) into data with more realistic structure, is based on linking the stochastic weather generator with the climate model output. The present contribution, in which the parametric daily surface weather generator (WG) M&Rfi is linked to the RCM output, follows two aims: (1) Validation of the new simulations of the present climate (1961-1990) made by the ALADIN-Climate Regional Climate Model at 25 km resolution. The WG parameters are derived from the RCM-simulated surface weather series and compared to those derived from weather series observed in 125 Czech meteorological stations. The set of WG parameters will include statistics of the surface temperature and precipitation series (including probability of wet day occurrence). (2) Presenting a methodology for linking the WG with RCM output. This methodology, which is based on merging information from observations and RCM, may be interpreted as a downscaling procedure, whose product is a gridded WG capable of producing realistic synthetic multivariate weather series for weather-ungauged locations. In this procedure, WG is calibrated with RCM-simulated multi-variate weather series in the first step, and the grid specific WG parameters are then de-biased by spatially interpolated correction factors based on comparison of WG parameters calibrated with gridded RCM weather series and spatially scarcer observations. The quality of the weather series produced by the resultant gridded WG will be assessed in terms of selected climatic characteristics (focusing on characteristics related to variability and extremes of surface temperature and precipitation). Acknowledgements: The present experiment is made within the frame of projects ALARO-Climate (project P209/11/2405 sponsored by the Czech Science Foundation), WG4VALUE (project LD12029 sponsored by the Ministry of Education, Youth and Sports of CR) and VALUE (COST ES 1102 action).

Simulation-based coefficients for adjusting climate impact on energy consumption of commercial buildings

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wang, Na; Makhmalbaf, Atefe; Srivastava, Viraj

This paper presents a new technique for and the results of normalizing building energy consumption to enable a fair comparison among various types of buildings located near different weather stations across the U.S. The method was developed for the U.S. Building Energy Asset Score, a whole-building energy efficiency rating system focusing on building envelope, mechanical systems, and lighting systems. The Asset Score is calculated based on simulated energy use under standard operating conditions. Existing weather normalization methods such as those based on heating and cooling degrees days are not robust enough to adjust all climatic factors such as humidity andmore » solar radiation. In this work, over 1000 sets of climate coefficients were developed to separately adjust building heating, cooling, and fan energy use at each weather station in the United States. This paper also presents a robust, standardized weather station mapping based on climate similarity rather than choosing the closest weather station. This proposed simulated-based climate adjustment was validated through testing on several hundreds of thousands of modeled buildings. Results indicated the developed climate coefficients can isolate and adjust for the impacts of local climate for asset rating.« less

Comparisons of Historical versus Synthetic Weather Inputs to Watershed Models and their Effect on Pollutant Loads

USDA-ARS?s Scientific Manuscript database

Synthetic weather generators are important for continuous-simulation of agricultural watersheds for risk analyses of downstream water quality. Many watersheds are sparsely or totally ungauged and daily weather must either be transposed or augmented. Since water quality models must recognize runoff...

Construction of Gridded Daily Weather Data and its Use in Central-European Agroclimatic Study

NASA Astrophysics Data System (ADS)

Dubrovsky, M.; Trnka, M.; Skalak, P.

2013-12-01

The regional-scale simulations of weather-sensitive processes (e.g. hydrology, agriculture and forestry) for the present and/or future climate often require high resolution meteorological inputs in terms of the time series of selected surface weather characteristics (typically temperature, precipitation, solar radiation, humidity, wind) for a set of stations or on a regular grid. As even the latest Global and Regional Climate Models (GCMs and RCMs) do not provide realistic representation of statistical structure of the surface weather, the model outputs must be postprocessed (downscaled) to achieve the desired statistical structure of the weather data before being used as an input to the follow-up simulation models. One of the downscaling approaches, which is employed also here, is based on a weather generator (WG), which is calibrated using the observed weather series, interpolated, and then modified according to the GCM- or RCM-based climate change scenarios. The present contribution, in which the parametric daily weather generator M&Rfi is linked to the high-resolution RCM output (ALADIN-Climate/CZ model) and GCM-based climate change scenarios, consists of two parts: The first part focuses on a methodology. Firstly, the gridded WG representing the baseline climate is created by merging information from observations and high resolution RCM outputs. In this procedure, WG is calibrated with RCM-simulated multi-variate weather series, and the grid specific WG parameters are then de-biased by spatially interpolated correction factors based on comparison of WG parameters calibrated with RCM-simulated weather series vs. spatially scarcer observations. To represent the future climate, the WG parameters are modified according to the 'WG-friendly' climate change scenarios. These scenarios are defined in terms of changes in WG parameters and include - apart from changes in the means - changes in WG parameters, which represent the additional characteristics of the weather series (e.g. probability of wet day occurrence and lag-1 autocorrelation of daily mean temperature). The WG-friendly scenarios for the present experiment are based on comparison of future vs baseline surface weather series simulated by GCMs from a CMIP3 database. The second part will present results of climate change impact study based on an above methodology applied to Central Europe. The changes in selected climatic (focusing on the extreme precipitation and temperature characteristics) and agroclimatic (including number of days during vegetation season with heat and drought stresses) characteristics will be analysed. In discussing the results, the emphasis will be put on 'added value' of various aspects of above methodology (e.g. inclusion of changes in 'advanced' WG parameters into the climate change scenarios). Acknowledgements: The present experiment is made within the frame of projects WG4VALUE (project LD12029 sponsored by the Ministry of Education, Youth and Sports of CR), ALARO-Climate (project P209/11/2405 sponsored by the Czech Science Foundation), and VALUE (COST ES 1102 action).

TRMM (Tropical Rainfall Measuring Mission): A satellite mission to measure tropical rainfall

NASA Technical Reports Server (NTRS)

Simpson, Joanne (Editor)

1988-01-01

The Tropical Rainfall Measuring Mission (TRMM) is presented. TRMM is a satellite program being studied jointly by the United States and Japan which would carry out the systematic study of tropical rainfall required for major strides in weather and climate research. The scientific justification for TRMM is discussed. The implementation process for the scientific community, NASA management, and the other decision-makers and advisory personnel who are expected to evaluate the priority of the project is outlined.

Processing of next generation weather radar-multisensor precipitation estimates and quantitative precipitation forecast data for the DuPage County streamflow simulation system

USGS Publications Warehouse

Bera, Maitreyee; Ortel, Terry W.

2018-01-12

The U.S. Geological Survey, in cooperation with DuPage County Stormwater Management Department, is testing a near real-time streamflow simulation system that assists in the management and operation of reservoirs and other flood-control structures in the Salt Creek and West Branch DuPage River drainage basins in DuPage County, Illinois. As part of this effort, the U.S. Geological Survey maintains a database of hourly meteorological and hydrologic data for use in this near real-time streamflow simulation system. Among these data are next generation weather radar-multisensor precipitation estimates and quantitative precipitation forecast data, which are retrieved from the North Central River Forecasting Center of the National Weather Service. The DuPage County streamflow simulation system uses these quantitative precipitation forecast data to create streamflow predictions for the two simulated drainage basins. This report discusses in detail how these data are processed for inclusion in the Watershed Data Management files used in the streamflow simulation system for the Salt Creek and West Branch DuPage River drainage basins.

Case Studies Comparing System Advisor Model (SAM) Results to Real Performance Data: Preprint

DOE Office of Scientific and Technical Information (OSTI.GOV)

Blair, N.; Dobos, A.; Sather, N.

2012-06-01

NREL has completed a series of detailed case studies comparing the simulations of the System Advisor Model (SAM) and measured performance data or published performance expectations. These case studies compare PV measured performance data with simulated performance data using appropriate weather data. The measured data sets were primarily taken from NREL onsite PV systems and weather monitoring stations.

Resolving the Multi-scale Behavior of Geochemical Weathering in the Critical Zone Using High Resolution Hydro-geochemical Models

NASA Astrophysics Data System (ADS)

Pandey, S.; Rajaram, H.

2015-12-01

This work investigates hydrologic and geochemical interactions in the Critical Zone (CZ) using high-resolution reactive transport modeling. Reactive transport models can be used to predict the response of geochemical weathering and solute fluxes in the CZ to changes in a dynamic environment, such as those pertaining to human activities and climate change in recent years. The scales of hydrology and geochemistry in the CZ range from days to eons in time and centimeters to kilometers in space. Here, we present results of a multi-dimensional, multi-scale hydro-geochemical model to investigate the role of subsurface heterogeneity on the formation of mineral weathering fronts in the CZ, which requires consideration of many of these spatio-temporal scales. The model is implemented using the reactive transport code PFLOTRAN, an open source subsurface flow and reactive transport code that utilizes parallelization over multiple processing nodes and provides a strong framework for simulating weathering in the CZ. The model is set up to simulate weathering dynamics in the mountainous catchments representative of the Colorado Front Range. Model parameters were constrained based on hydrologic, geochemical, and geophysical observations from the Boulder Creek Critical Zone Observatory (BcCZO). Simulations were performed in fractured rock systems and compared with systems of heterogeneous and homogeneous permeability fields. Tracer simulations revealed that the mean residence time of solutes was drastically accelerated as fracture density increased. In simulations that include mineral reactions, distinct signatures of transport limitations on weathering arose when discrete flow paths were included. This transport limitation was related to both advective and diffusive processes in the highly heterogeneous systems (i.e. fractured media and correlated random permeability fields with σlnk > 3). The well-known time-dependence of mineral weathering rates was found to be the most pronounced in the fractured systems, with a departure from the maximum system-averaged dissolution rate occurring after ~100 kyr followed by a gradual decrease in the reaction rate with time that persists beyond 104 kyr.

Weather-Related Flood and Landslide Damage: A Risk Index for Italian Regions

PubMed Central

Messeri, Alessandro; Morabito, Marco; Messeri, Gianni; Brandani, Giada; Petralli, Martina; Natali, Francesca; Grifoni, Daniele; Crisci, Alfonso; Gensini, Gianfranco; Orlandini, Simone

2015-01-01

The frequency of natural hazards has been increasing in the last decades in Europe and specifically in Mediterranean regions due to climate change. For example heavy precipitation events can lead to disasters through the interaction with exposed and vulnerable people and natural systems. It is therefore necessary a prevention planning to preserve human health and to reduce economic losses. Prevention should mainly be carried out with more adequate land management, also supported by the development of an appropriate risk prediction tool based on weather forecasts. The main aim of this study is to investigate the relationship between weather types (WTs) and the frequency of floods and landslides that have caused damage to properties, personal injuries, or deaths in the Italian regions over recent decades. In particular, a specific risk index (WT-FLARI) for each WT was developed at national and regional scale. This study has identified a specific risk index associated with each weather type, calibrated for each Italian region and applicable to both annual and seasonal levels. The risk index represents the seasonal and annual vulnerability of each Italian region and indicates that additional preventive actions are necessary for some regions. The results of this study represent a good starting point towards the development of a tool to support policy-makers, local authorities and health agencies in planning actions, mainly in the medium to long term, aimed at the weather damage reduction that represents an important issue of the World Meteorological Organization mission. PMID:26714309

Weather-Related Flood and Landslide Damage: A Risk Index for Italian Regions.

PubMed

Messeri, Alessandro; Morabito, Marco; Messeri, Gianni; Brandani, Giada; Petralli, Martina; Natali, Francesca; Grifoni, Daniele; Crisci, Alfonso; Gensini, Gianfranco; Orlandini, Simone

2015-01-01

The frequency of natural hazards has been increasing in the last decades in Europe and specifically in Mediterranean regions due to climate change. For example heavy precipitation events can lead to disasters through the interaction with exposed and vulnerable people and natural systems. It is therefore necessary a prevention planning to preserve human health and to reduce economic losses. Prevention should mainly be carried out with more adequate land management, also supported by the development of an appropriate risk prediction tool based on weather forecasts. The main aim of this study is to investigate the relationship between weather types (WTs) and the frequency of floods and landslides that have caused damage to properties, personal injuries, or deaths in the Italian regions over recent decades. In particular, a specific risk index (WT-FLARI) for each WT was developed at national and regional scale. This study has identified a specific risk index associated with each weather type, calibrated for each Italian region and applicable to both annual and seasonal levels. The risk index represents the seasonal and annual vulnerability of each Italian region and indicates that additional preventive actions are necessary for some regions. The results of this study represent a good starting point towards the development of a tool to support policy-makers, local authorities and health agencies in planning actions, mainly in the medium to long term, aimed at the weather damage reduction that represents an important issue of the World Meteorological Organization mission.

Investigation of powered 2-wheeler accident involvement in urban arterials by considering real-time traffic and weather data.

PubMed

Theofilatos, Athanasios; Yannis, George

2017-04-03

Understanding the various factors that affect accident risk is of particular concern to decision makers and researchers. The incorporation of real-time traffic and weather data constitutes a fruitful approach when analyzing accident risk. However, the vast majority of relevant research has no specific focus on vulnerable road users such as powered 2-wheelers (PTWs). Moreover, studies using data from urban roads and arterials are scarce. This study aims to add to the current knowledge by considering real-time traffic and weather data from 2 major urban arterials in the city of Athens, Greece, in order to estimate the effect of traffic, weather, and other characteristics on PTW accident involvement. Because of the high number of candidate variables, a random forest model was applied to reveal the most important variables. Then, the potentially significant variables were used as input to a Bayesian logistic regression model in order to reveal the magnitude of their effect on PTW accident involvement. The results of the analysis suggest that PTWs are more likely to be involved in multivehicle accidents than in single-vehicle accidents. It was also indicated that increased traffic flow and variations in speed have a significant influence on PTW accident involvement. On the other hand, weather characteristics were found to have no effect. The findings of this study can contribute to the understanding of accident mechanisms of PTWs and reduce PTW accident risk in urban arterials.

Climate Central World Weather Attribution (WWA) project: Real-time extreme weather event attribution analysis

NASA Astrophysics Data System (ADS)

Haustein, Karsten; Otto, Friederike; Uhe, Peter; Allen, Myles; Cullen, Heidi

2015-04-01

Extreme weather detection and attribution analysis has emerged as a core theme in climate science over the last decade or so. By using a combination of observational data and climate models it is possible to identify the role of climate change in certain types of extreme weather events such as sea level rise and its contribution to storm surges, extreme heat events and droughts or heavy rainfall and flood events. These analyses are usually carried out after an extreme event has occurred when reanalysis and observational data become available. The Climate Central WWA project will exploit the increasing forecast skill of seasonal forecast prediction systems such as the UK MetOffice GloSea5 (Global seasonal forecasting system) ensemble forecasting method. This way, the current weather can be fed into climate models to simulate large ensembles of possible weather scenarios before an event has fully emerged yet. This effort runs along parallel and intersecting tracks of science and communications that involve research, message development and testing, staged socialization of attribution science with key audiences, and dissemination. The method we employ uses a very large ensemble of simulations of regional climate models to run two different analyses: one to represent the current climate as it was observed, and one to represent the same events in the world that might have been without human-induced climate change. For the weather "as observed" experiment, the atmospheric model uses observed sea surface temperature (SST) data from GloSea5 (currently) and present-day atmospheric gas concentrations to simulate weather events that are possible given the observed climate conditions. The weather in the "world that might have been" experiments is obtained by removing the anthropogenic forcing from the observed SSTs, thereby simulating a counterfactual world without human activity. The anthropogenic forcing is obtained by comparing the CMIP5 historical and natural simulations from a variety of CMIP5 model ensembles. Here, we present results for the UK 2013/14 winter floods as proof of concept and we show validation and testing results that demonstrate the robustness of our method. We also revisit the record temperatures over Europe in 2014 and present a detailed analysis of this attribution exercise as it is one of the events to demonstrate that we can make a sensible statement of how the odds for such a year to occur have changed while it still unfolds.

A GEOCLIM simulation of climatic and biogeochemical consequences of Pangea breakup

NASA Astrophysics Data System (ADS)

Donnadieu, Y.; GoddéRis, Y.; Pierrehumbert, R.; Dromart, G.; Fluteau, F.; Jacob, R.

2006-11-01

Large fluctuations in continental configuration occur throughout the Mesozoic. While it has long been recognized that paleogeography may potentially influence atmospheric CO2 via the continental silicate weathering feedback, no numerical simulations have been done, because of the lack of a spatially resolved climate-carbon model. GEOCLIM, a coupled numerical model of the climate and global biogeochemical cycles, is used to investigate the consequences of the Pangea breakup. The climate module of the GEOCLIM model is the FOAM atmospheric general circulation model, allowing the calculation of the consumption of atmospheric CO2 through continental silicate weathering with a spatial resolution of 7.5°long × 4.5°lat. Seven time slices have been simulated. We show that the breakup of the Pangea supercontinent triggers an increase in continental runoff, resulting in enhanced atmospheric CO2 consumption through silicate weathering. As a result, atmospheric CO2 falls from values above 3000 ppmv during the Triassic down to rather low levels during the Cretaceous (around 400 ppmv), resulting in a decrease in global mean annual continental temperatures from about 20°C to 10°C. Silicate weathering feedback and paleogeography both act to force the Earth system toward a dry and hot world reaching its optimum over the last 260 Myr during the Middle-Late Triassic. In the super continent case, given the persistent aridity, the model generates high CO2 values to produce very warm continental temperatures. Conversely, in the fragmented case, the runoff becomes the most important contributor to the silicate weathering rate, hence producing a CO2 drawdown and a fall in continental temperatures. Finally, another unexpected outcome is the pronounced fluctuation in carbonate accumulation simulated by the model in response to the Pangea breakup. These fluctuations are driven by changes in continental carbonate weathering flux. Accounting for the fluctuations in area available for carbonate platforms, the simulated ratio of carbonate deposition between neritic and deep sea environments is in better agreement with available data.

Motivating and Facilitating Advancements in Space Weather Real-Time Data Availability: Factors, Data, and Access Methods

NASA Astrophysics Data System (ADS)

Pankratz, C. K.; Baker, D. N.; Jaynes, A. N.; Elkington, S. R.; Baltzer, T.; Sanchez, F.

2017-12-01

Society's growing reliance on complex and highly interconnected technological systems makes us increasingly vulnerable to the effects of space weather events - maybe more than for any other natural hazard. An extreme solar storm today could conceivably impact hundreds of the more than 1400 operating Earth satellites. Such an extreme storm could cause collapse of the electrical grid on continental scales. The effects on navigation, communication, and remote sensing of our home planet could be devastating to our social functioning. Thus, it is imperative that the scientific community address the question of just how severe events might become. At least as importantly, it is crucial that policy makers and public safety officials be informed by the facts on what might happen during extreme conditions. This requires essentially real-time alerts, warnings, and also forecasts of severe space weather events, which in turn demands measurements, models, and associated data products to be available via the most effective data discovery and access methods possible. Similarly, advancement in the fundamental scientific understanding of space weather processes is also vital, requiring that researchers have convenient and effective access to a wide variety of data sets and models from multiple sources. The space weather research community, as with many scientific communities, must access data from dispersed and often uncoordinated data repositories to acquire the data necessary for the analysis and modeling efforts that advance our understanding of solar influences and space physics on the Earth's environment. The Laboratory for Atmospheric and Space Physics (LASP), as a leading institution in both producing data products and advancing the state of scientific understanding of space weather processes, is well positioned to address many of these issues. In this presentation, we will outline the motivating factors for effective space weather data access, summarize the various data and models that are available, and present methods for meeting the data management and access needs of the disparate communities who require low-latency space weather data and information.

Evaluation of weather-based rice yield models in India

NASA Astrophysics Data System (ADS)

Sudharsan, D.; Adinarayana, J.; Reddy, D. Raji; Sreenivas, G.; Ninomiya, S.; Hirafuji, M.; Kiura, T.; Tanaka, K.; Desai, U. B.; Merchant, S. N.

2013-01-01

The objective of this study was to compare two different rice simulation models—standalone (Decision Support System for Agrotechnology Transfer [DSSAT]) and web based (SImulation Model for RIce-Weather relations [SIMRIW])—with agrometeorological data and agronomic parameters for estimation of rice crop production in southern semi-arid tropics of India. Studies were carried out on the BPT5204 rice variety to evaluate two crop simulation models. Long-term experiments were conducted in a research farm of Acharya N G Ranga Agricultural University (ANGRAU), Hyderabad, India. Initially, the results were obtained using 4 years (1994-1997) of data with weather parameters from a local weather station to evaluate DSSAT simulated results with observed values. Linear regression models used for the purpose showed a close relationship between DSSAT and observed yield. Subsequently, yield comparisons were also carried out with SIMRIW and DSSAT, and validated with actual observed values. Realizing the correlation coefficient values of SIMRIW simulation values in acceptable limits, further rice experiments in monsoon (Kharif) and post-monsoon (Rabi) agricultural seasons (2009, 2010 and 2011) were carried out with a location-specific distributed sensor network system. These proximal systems help to simulate dry weight, leaf area index and potential yield by the Java based SIMRIW on a daily/weekly/monthly/seasonal basis. These dynamic parameters are useful to the farming community for necessary decision making in a ubiquitous manner. However, SIMRIW requires fine tuning for better results/decision making.

Advancing the climate data driven crop-modeling studies in the dry areas of Northern Syria and Lebanon: an important first step for assessing impact of future climate.

PubMed

Dixit, Prakash N; Telleria, Roberto

2015-04-01

Inter-annual and seasonal variability in climatic parameters, most importantly rainfall, have potential to cause climate-induced risk in long-term crop production. Short-term field studies do not capture the full nature of such risk and the extent to which modifications to crop, soil and water management recommendations may be made to mitigate the extent of such risk. Crop modeling studies driven by long-term daily weather data can predict the impact of climate-induced risk on crop growth and yield however, the availability of long-term daily weather data can present serious constraints to the use of crop models. To tackle this constraint, two weather generators namely, LARS-WG and MarkSim, were evaluated in order to assess their capabilities of reproducing frequency distributions, means, variances, dry spell and wet chains of observed daily precipitation, maximum and minimum temperature, and solar radiation for the eight locations across cropping areas of Northern Syria and Lebanon. Further, the application of generated long-term daily weather data, with both weather generators, in simulating barley growth and yield was also evaluated. We found that overall LARS-WG performed better than MarkSim in generating daily weather parameters and in 50 years continuous simulation of barley growth and yield. Our findings suggest that LARS-WG does not necessarily require long-term e.g., >30 years observed weather data for calibration as generated results proved to be satisfactory with >10 years of observed data except in area with higher altitude. Evaluating these weather generators and the ability of generated weather data to perform long-term simulation of crop growth and yield is an important first step to assess the impact of future climate on yields, and to identify promising technologies to make agricultural systems more resilient in the given region. Copyright © 2015 Elsevier B.V. All rights reserved.

Evaluating Weather Research and Forecasting Model Sensitivity to Land and Soil Conditions Representative of Karst Landscapes

NASA Astrophysics Data System (ADS)

Johnson, Christopher M.; Fan, Xingang; Mahmood, Rezaul; Groves, Chris; Polk, Jason S.; Yan, Jun

2018-03-01

Due to their particular physiographic, geomorphic, soil cover, and complex surface-subsurface hydrologic conditions, karst regions produce distinct land-atmosphere interactions. It has been found that floods and droughts over karst regions can be more pronounced than those in non-karst regions following a given rainfall event. Five convective weather events are simulated using the Weather Research and Forecasting model to explore the potential impacts of land-surface conditions on weather simulations over karst regions. Since no existing weather or climate model has the ability to represent karst landscapes, simulation experiments in this exploratory study consist of a control (default land-cover/soil types) and three land-surface conditions, including barren ground, forest, and sandy soils over the karst areas, which mimic certain karst characteristics. Results from sensitivity experiments are compared with the control simulation, as well as with the National Centers for Environmental Prediction multi-sensor precipitation analysis Stage-IV data, and near-surface atmospheric observations. Mesoscale features of surface energy partition, surface water and energy exchange, the resulting surface-air temperature and humidity, and low-level instability and convective energy are analyzed to investigate the potential land-surface impact on weather over karst regions. We conclude that: (1) barren ground used over karst regions has a pronounced effect on the overall simulation of precipitation. Barren ground provides the overall lowest root-mean-square errors and bias scores in precipitation over the peak-rain periods. Contingency table-based equitable threat and frequency bias scores suggest that the barren and forest experiments are more successful in simulating light to moderate rainfall. Variables dependent on local surface conditions show stronger contrasts between karst and non-karst regions than variables dominated by large-scale synoptic systems; (2) significant sensitivity responses are found over the karst regions, including pronounced warming and cooling effects on the near-surface atmosphere from barren and forested land cover, respectively; (3) the barren ground in the karst regions provides conditions favourable for convective development under certain conditions. Therefore, it is suggested that karst and non-karst landscapes should be distinguished, and their physical processes should be considered for future model development.

Informing Education Policy in Afghanistan: Using Design of Experiments and Data Envelopment Analysis to Provide Transparency in Complex Simulation

ERIC Educational Resources Information Center

Marlin, Benjamin

2013-01-01

Education planning provides the policy maker and the decision maker a logical framework in which to develop and implement education policy. At the international level, education planning is often confounded by both internal and external complexities, making the development of education policy difficult. This research presents a discrete event…

Effects of ignition location models on the burn patterns of simulated wildfires

USGS Publications Warehouse

Bar-Massada, A.; Syphard, A.D.; Hawbaker, T.J.; Stewart, S.I.; Radeloff, V.C.

2011-01-01

Fire simulation studies that use models such as FARSITE often assume that ignition locations are distributed randomly, because spatially explicit information about actual ignition locations are difficult to obtain. However, many studies show that the spatial distribution of ignition locations, whether human-caused or natural, is non-random. Thus, predictions from fire simulations based on random ignitions may be unrealistic. However, the extent to which the assumption of ignition location affects the predictions of fire simulation models has never been systematically explored. Our goal was to assess the difference in fire simulations that are based on random versus non-random ignition location patterns. We conducted four sets of 6000 FARSITE simulations for the Santa Monica Mountains in California to quantify the influence of random and non-random ignition locations and normal and extreme weather conditions on fire size distributions and spatial patterns of burn probability. Under extreme weather conditions, fires were significantly larger for non-random ignitions compared to random ignitions (mean area of 344.5 ha and 230.1 ha, respectively), but burn probability maps were highly correlated (r = 0.83). Under normal weather, random ignitions produced significantly larger fires than non-random ignitions (17.5 ha and 13.3 ha, respectively), and the spatial correlations between burn probability maps were not high (r = 0.54), though the difference in the average burn probability was small. The results of the study suggest that the location of ignitions used in fire simulation models may substantially influence the spatial predictions of fire spread patterns. However, the spatial bias introduced by using a random ignition location model may be minimized if the fire simulations are conducted under extreme weather conditions when fire spread is greatest. ?? 2010 Elsevier Ltd.

The Effects of Virtual Weather on Presence

NASA Astrophysics Data System (ADS)

Wissmath, Bartholomäus; Weibel, David; Mast, Fred W.

In modern societies people tend to spend more time in front of computer screens than outdoors. Along with an increasing degree of realism displayed in digital environments, simulated weather appears more and more realistic and more often implemented in digital environments. Research has found that the actual weather influences behavior and mood. In this paper we experimentally examine the effects of virtual weather on the sense of presence. Thereby we found individuals (N=30) to immerse deeper in digital environments displaying fair weather conditions than in environments displaying bad weather. We also investigate whether virtual weather can influence behavior. The possible implications of theses findings for presence theory as well as digital environment designers will be discussed.

Methodology for the preliminary design of high performance schools in hot and humid climates

NASA Astrophysics Data System (ADS)

Im, Piljae

A methodology to develop an easy-to-use toolkit for the preliminary design of high performance schools in hot and humid climates was presented. The toolkit proposed in this research will allow decision makers without simulation knowledge easily to evaluate accurately energy efficient measures for K-5 schools, which would contribute to the accelerated dissemination of energy efficient design. For the development of the toolkit, first, a survey was performed to identify high performance measures available today being implemented in new K-5 school buildings. Then an existing case-study school building in a hot and humid climate was selected and analyzed to understand the energy use pattern in a school building and to be used in developing a calibrated simulation. Based on the information from the previous step, an as-built and calibrated simulation was then developed. To accomplish this, five calibration steps were performed to match the simulation results with the measured energy use. The five steps include: (1) Using an actual 2006 weather file with measured solar radiation, (2) Modifying lighting & equipment schedule using ASHRAE's RP-1093 methods, (3) Using actual equipment performance curves (i.e., scroll chiller), (4) Using the Winkelmann's method for the underground floor heat transfer, and (5) Modifying the HVAC and room setpoint temperature based on the measured field data. Next, the calibrated simulation of the case-study K-5 school was compared to an ASHRAE Standard 90.1-1999 code-compliant school. In the next step, the energy savings potentials from the application of several high performance measures to an equivalent ASHRAE Standard 90.1-1999 code-compliant school. The high performance measures applied included the recommendations from the ASHRAE Advanced Energy Design Guides (AEDG) for K-12 and other high performance measures from the literature review as well as a daylighting strategy and solar PV and thermal systems. The results show that the net energy consumption of the final high performance school with the solar thermal and a solar PV system would be 1,162.1 MMBtu, which corresponds to the 14.9 kBtu/sqft-yr of EUI. The calculated final energy and cost savings over the code compliant school are 68.2% and 69.9%, respectively. As a final step of the research, specifications for a simplified easy-to-use toolkit were then developed, and a prototype screenshot of the toolkit was developed. The toolkit is expected to be used by non-technical decision-maker to select and evaluate high performance measures for a new school building in terms of energy and cost savings in a quick and easy way.

A Weather Radar Simulator for the Evaluation of Polarimetric Phased Array Performance

DOE Office of Scientific and Technical Information (OSTI.GOV)

Byrd, Andrew D.; Ivic, Igor R.; Palmer, Robert D.

A radar simulator capable of generating time series data for a polarimetric phased array weather radar has been designed and implemented. The received signals are composed from a high-resolution numerical prediction weather model. Thousands of scattering centers, each with an independent randomly generated Doppler spectrum, populate the field of view of the radar. The moments of the scattering center spectra are derived from the numerical weather model, and the scattering center positions are updated based on the three-dimensional wind field. In order to accurately emulate the effects of the system-induced cross-polar contamination, the array is modeled using a complete setmore » of dual-polarization radiation patterns. The simulator offers reconfigurable element patterns and positions as well as access to independent time series data for each element, resulting in easy implementation of any beamforming method. It also allows for arbitrary waveform designs and is able to model the effects of quantization on waveform performance. Simultaneous, alternating, quasi-simultaneous, and pulse-to-pulse phase coded modes of polarimetric signal transmission have been implemented. This framework allows for realistic emulation of the effects of cross-polar fields on weather observations, as well as the evaluation of possible techniques for the mitigation of those effects.« less

Investigating the Effects of Grid Resolution of WRF Model for Simulating the Atmosphere for use in the Study of Wake Turbulence

NASA Astrophysics Data System (ADS)

Prince, Alyssa; Trout, Joseph; di Mercurio, Alexis

2017-01-01

The Weather Research and Forecasting (WRF) Model is a nested-grid, mesoscale numerical weather prediction system maintained by the Developmental Testbed Center. The model simulates the atmosphere by integrating partial differential equations, which use the conservation of horizontal momentum, conservation of thermal energy, and conservation of mass along with the ideal gas law. This research investigated the possible use of WRF in investigating the effects of weather on wing tip wake turbulence. This poster shows the results of an investigation into the accuracy of WRF using different grid resolutions. Several atmospheric conditions were modeled using different grid resolutions. In general, the higher the grid resolution, the better the simulation, but the longer the model run time. This research was supported by Dr. Manuel A. Rios, Ph.D. (FAA) and the grant ``A Pilot Project to Investigate Wake Vortex Patterns and Weather Patterns at the Atlantic City Airport by the Richard Stockton College of NJ and the FAA'' (13-G-006). Dr. Manuel A. Rios, Ph.D. (FAA), and the grant ``A Pilot Project to Investigate Wake Vortex Patterns and Weather Patterns at the Atlantic City Airport by the Richard Stockton College of NJ and the FAA''

Space Weather Around the World: An IHY Education Program

NASA Astrophysics Data System (ADS)

Thieman, J. R.; Ng, C.; Hawkins, I.; Lewis, E.; Cline, T.

2007-05-01

Fifty years ago the International Geophysical Year organized a unique and unprecedented program of research that united 60,000 scientists from 66 nations to study global phenomena concerning the Earth and its space environment. In that same spirit, "Space Weather Around the World" is a program to coordinate and facilitate the involvement of NASA heliophysics missions and scientists to inspire and educate a world-wide audience about the International Heliophysical Year (IHY). We will use the popular Sun-Earth Day annual event framework sponsored by the Sun-Earth Connection Education Forum to promote IHY science and the spirit of international collaboration. The theme for the March 2007 Sun-Earth Day: "IHY: Living in the Atmosphere of the Sun" was selected a year ago in anticipation of the IHY celebration. These efforts will be expanded through a series of coordinated programs under the theme "Space Weather Around the World" for Sun-Earth Day 2008. We will produce a live broadcast from China of the total solar eclipse on August 1st 2008 as the central event, highlighting investigations associated with the eclipse by the international heliophysics community. Additional collaborative efforts will include: a Space Weather Media Maker web-tool to allow educators and scientists to create their own multi-media resource to enhance teaching and learning at all levels; Rock-n-Sol, a musical composition by children internationally inspired by space weather and incorporating sonifications of solar data; and Space Weather Action Centers for students to track a solar storm featuring podcasts of multi-cultural perspectives on IHY. The anticipated audience would be millions of people internationally The science and E/PO heliophysics community has an exciting story to tell about IHY, and we look forward to the opportunity to share it globally.

A comparative study of European insurance schemes for extreme weather risks and incentives for risk reduction

NASA Astrophysics Data System (ADS)

de Ruiter, Marleen; Hudson, Paul; de Ruig, Lars; Kuik, Onno; Botzen, Wouter

2017-04-01

This paper provides an analysis of the insurance schemes that cover extreme weather events in twelve different EU countries and the risk reduction incentives offered by these schemes. Economic impacts of extreme weather events in many regions in Europe and elsewhere are on the rise due to climate change and increasing exposure as driven by urban development. In an attempt to manage impacts from extreme weather events, natural disaster insurance schemes can provide incentives for taking measures that limit weather-related risks. Insurance companies can influence public risk management policies and risk-reducing behaviour of policyholders by "rewarding behaviour that reduces risks and potential damages" (Botzen and Van den Bergh, 2008, p. 417). Examples of insurance market systems that directly or indirectly aim to incentivize risk reduction with varying degrees of success are: the U.S. National Flood Insurance Programme; the French Catastrophes Naturelles system; and the U.K. Flood Re program which requires certain levels of protection standards for properties to be insurable. In our analysis, we distinguish between four different disaster types (i.e. coastal and fluvial floods, droughts and storms) and three different sectors (i.e. residential, commercial and agriculture). The selected case studies also provide a wide coverage of different insurance market structures, including public, private and public-private insurance provision, and different methods of coping with extreme loss events, such as re-insurance, governmental aid and catastrophe bonds. The analysis of existing mechanisms for risk reduction incentives provides recommendations about incentivizing adaptive behaviour, in order to assist policy makers and other stakeholders in designing more effective insurance schemes for extreme weather risks.

Impact of weather factors on hand, foot and mouth disease, and its role in short-term incidence trend forecast in Huainan City, Anhui Province.

PubMed

Zhao, Desheng; Wang, Lulu; Cheng, Jian; Xu, Jun; Xu, Zhiwei; Xie, Mingyu; Yang, Huihui; Li, Kesheng; Wen, Lingying; Wang, Xu; Zhang, Heng; Wang, Shusi; Su, Hong

2017-03-01

Hand, foot, and mouth disease (HFMD) is one of the most common communicable diseases in China, and current climate change had been recognized as a significant contributor. Nevertheless, no reliable models have been put forward to predict the dynamics of HFMD cases based on short-term weather variations. The present study aimed to examine the association between weather factors and HFMD, and to explore the accuracy of seasonal auto-regressive integrated moving average (SARIMA) model with local weather conditions in forecasting HFMD. Weather and HFMD data from 2009 to 2014 in Huainan, China, were used. Poisson regression model combined with a distributed lag non-linear model (DLNM) was applied to examine the relationship between weather factors and HFMD. The forecasting model for HFMD was performed by using the SARIMA model. The results showed that temperature rise was significantly associated with an elevated risk of HFMD. Yet, no correlations between relative humidity, barometric pressure and rainfall, and HFMD were observed. SARIMA models with temperature variable fitted HFMD data better than the model without it (sR 2 increased, while the BIC decreased), and the SARIMA (0, 1, 1)(0, 1, 0) 52 offered the best fit for HFMD data. In addition, compared with females and nursery children, males and scattered children may be more suitable for using SARIMA model to predict the number of HFMD cases and it has high precision. In conclusion, high temperature could increase the risk of contracting HFMD. SARIMA model with temperature variable can effectively improve its forecast accuracy, which can provide valuable information for the policy makers and public health to construct a best-fitting model and optimize HFMD prevention.

Impact of weather factors on hand, foot and mouth disease, and its role in short-term incidence trend forecast in Huainan City, Anhui Province

NASA Astrophysics Data System (ADS)

Zhao, Desheng; Wang, Lulu; Cheng, Jian; Xu, Jun; Xu, Zhiwei; Xie, Mingyu; Yang, Huihui; Li, Kesheng; Wen, Lingying; Wang, Xu; Zhang, Heng; Wang, Shusi; Su, Hong

2017-03-01

Hand, foot, and mouth disease (HFMD) is one of the most common communicable diseases in China, and current climate change had been recognized as a significant contributor. Nevertheless, no reliable models have been put forward to predict the dynamics of HFMD cases based on short-term weather variations. The present study aimed to examine the association between weather factors and HFMD, and to explore the accuracy of seasonal auto-regressive integrated moving average (SARIMA) model with local weather conditions in forecasting HFMD. Weather and HFMD data from 2009 to 2014 in Huainan, China, were used. Poisson regression model combined with a distributed lag non-linear model (DLNM) was applied to examine the relationship between weather factors and HFMD. The forecasting model for HFMD was performed by using the SARIMA model. The results showed that temperature rise was significantly associated with an elevated risk of HFMD. Yet, no correlations between relative humidity, barometric pressure and rainfall, and HFMD were observed. SARIMA models with temperature variable fitted HFMD data better than the model without it (s R 2 increased, while the BIC decreased), and the SARIMA (0, 1, 1)(0, 1, 0)52 offered the best fit for HFMD data. In addition, compared with females and nursery children, males and scattered children may be more suitable for using SARIMA model to predict the number of HFMD cases and it has high precision. In conclusion, high temperature could increase the risk of contracting HFMD. SARIMA model with temperature variable can effectively improve its forecast accuracy, which can provide valuable information for the policy makers and public health to construct a best-fitting model and optimize HFMD prevention.

Atmospheric Test Models and Numerical Experiments for the Simulation of the Global Distributions of Weather Data Transponders III. Horizontal Distributions

DOE Office of Scientific and Technical Information (OSTI.GOV)

Molenkamp, C.R.; Grossman, A.

1999-12-20

A network of small balloon-borne transponders which gather very high resolution wind and temperature data for use by modern numerical weather predication models has been proposed to improve the reliability of long-range weather forecasts. The global distribution of an array of such transponders is simulated using LLNL's atmospheric parcel transport model (GRANTOUR) with winds supplied by two different general circulation models. An initial study used winds from CCM3 with a horizontal resolution of about 3 degrees in latitude and longitude, and a second study used winds from NOGAPS with a 0.75 degree horizontal resolution. Results from both simulations show thatmore » reasonable global coverage can be attained by releasing balloons from an appropriate set of launch sites.« less

Pulsed-Laser Irradiation Space Weathering of a Carbonaceous Chondrite

NASA Astrophysics Data System (ADS)

Thompson, M. S.; Keller, L. P.; Christoffersen, R.; Loeffler, M. J.; Morris, R. V.; Graff, T. G.; Rahman, Z.

2017-07-01

We used pulsed laser irradiation of the Murchison meteorite to simulate space weathering processes in the laboratory. We analyzed changes in the spectral, chemical, and microstructural characteristics of the material after irradiation.

Impact of grain size and rock composition on simulated rock weathering

NASA Astrophysics Data System (ADS)

Israeli, Yoni; Emmanuel, Simon

2018-05-01

Both chemical and mechanical processes act together to control the weathering rate of rocks. In rocks with micrometer size grains, enhanced dissolution at grain boundaries has been observed to cause the mechanical detachment of particles. However, it remains unclear how important this effect is in rocks with larger grains, and how the overall weathering rate is influenced by the proportion of high- and low-reactivity mineral phases. Here, we use a numerical model to assess the effect of grain size on chemical weathering and chemo-mechanical grain detachment. Our model shows that as grain size increases, the weathering rate initially decreases; however, beyond a critical size no significant decrease in the rate is observed. This transition occurs when the density of reactive boundaries is less than ˜ 20 % of the entire domain. In addition, we examined the weathering rates of rocks containing different proportions of high- and low-reactivity minerals. We found that as the proportion of low-reactivity minerals increases, the weathering rate decreases nonlinearly. These simulations indicate that for all compositions, grain detachment contributes more than 36 % to the overall weathering rate, with a maximum of ˜ 50 % when high- and low-reactivity minerals are equally abundant in the rock. This occurs because selective dissolution of the high-reactivity minerals creates large clusters of low-reactivity minerals, which then become detached. Our results demonstrate that the balance between chemical and mechanical processes can create complex and nonlinear relationships between the weathering rate and lithology.

Hourly test reference weather data in the changing climate of Finland for building energy simulations.

PubMed

Jylhä, Kirsti; Ruosteenoja, Kimmo; Jokisalo, Juha; Pilli-Sihvola, Karoliina; Kalamees, Targo; Mäkelä, Hanna; Hyvönen, Reijo; Drebs, Achim

2015-09-01

Dynamic building energy simulations need hourly weather data as input. The same high temporal resolution is required for assessments of future heating and cooling energy demand. The data presented in this article concern current typical values and estimated future changes in outdoor air temperature, wind speed, relative humidity and global, diffuse and normal solar radiation components. Simulated annual and seasonal delivered energy consumptions for heating of spaces, heating of ventilation supply air and cooling of spaces in the current and future climatic conditions are also presented for an example house, with district heating and a mechanical space cooling system. We provide details on how the synthetic future weather files were created and utilised as input data for dynamic building energy simulations by the IDA Indoor Climate and Energy program and also for calculations of heating and cooling degree-day sums. The information supplied here is related to the research article titled "Energy demand for the heating and cooling of residential houses in Finland in a changing climate" [1].

Simulated Job Samples: A Student-Centered Approach to Vocational Exploration and Evaluation.

ERIC Educational Resources Information Center

Richter-Stein, Caryn; Stodden, Robert A.

1981-01-01

Incorporating simulated job samples into the junior high school curriculum can provide vocational exploration opportunities as well as assessment data on special needs students. Students can participate as active learners and decision makers. (CL)

Sensitivity of DIVWAG to Variations in Weather Parameters

DTIC Science & Technology

1976-04-01

1 18. SUPPLEMENTARY NOTES 1 19. KEY WORDS (Continue on reverse aide if necessary and Identify by block number) DIVWAG WAR GAME SIMULATION...simulation of a Division Level War Game , to determine the signif- icance of varying battlefield parameters; i.e., artillery parameters, troop and...The only Red artillery weapons doing better in bad weather are the 130MM guns , but this statistic is tempered by the few casualties occuring in

Simulation of a Real-Time Local Data Integration System over East-Central Florida

NASA Technical Reports Server (NTRS)

Case, Jonathan

1999-01-01

The Applied Meteorology Unit (AMU) simulated a real-time configuration of a Local Data Integration System (LDIS) using data from 15-28 February 1999. The objectives were to assess the utility of a simulated real-time LDIS, evaluate and extrapolate system performance to identify the hardware necessary to run a real-time LDIS, and determine the sensitivities of LDIS. The ultimate goal for running LDIS is to generate analysis products that enhance short-range (less than 6 h) weather forecasts issued in support of the 45th Weather Squadron, Spaceflight Meteorology Group, and Melbourne National Weather Service operational requirements. The simulation used the Advanced Regional Prediction System (ARPS) Data Analysis System (ADAS) software on an IBM RS/6000 workstation with a 67-MHz processor. This configuration ran in real-time, but not sufficiently fast for operational requirements. Thus, the AMU recommends a workstation with a 200-MHz processor and 512 megabytes of memory to run the AMU's configuration of LDIS in real-time. This report presents results from two case studies and several data sensitivity experiments. ADAS demonstrates utility through its ability to depict high-resolution cloud and wind features in a variety of weather situations. The sensitivity experiments illustrate the influence of disparate data on the resulting ADAS analyses.

Spatial Sampling of Weather Data for Regional Crop Yield Simulations

NASA Technical Reports Server (NTRS)

Van Bussel, Lenny G. J.; Ewert, Frank; Zhao, Gang; Hoffmann, Holger; Enders, Andreas; Wallach, Daniel; Asseng, Senthold; Baigorria, Guillermo A.; Basso, Bruno; Biernath, Christian;

Weather Observation Systems and Efficiency of Fighting Forest Fires

NASA Astrophysics Data System (ADS)

Khabarov, N.; Moltchanova, E.; Obersteiner, M.

2007-12-01

Weather observation is an essential component of modern forest fire management systems. Satellite and in-situ based weather observation systems might help to reduce forest loss, human casualties and destruction of economic capital. In this paper, we develop and apply a methodology to assess the benefits of various weather observation systems on reductions of burned area due to early fire detection. In particular, we consider a model where the air patrolling schedule is determined by a fire hazard index. The index is computed from gridded daily weather data for the area covering parts Spain and Portugal. We conduct a number of simulation experiments. First, the resolution of the original data set is artificially reduced. The reduction of the total forest burned area associated with air patrolling based on a finer weather grid indicates the benefit of using higher spatially resolved weather observations. Second, we consider a stochastic model to simulate forest fires and explore the sensitivity of the model with respect to the quality of input data. The analysis of combination of satellite and ground monitoring reveals potential cost saving due to a "system of systems effect" and substantial reduction in burned area. Finally, we estimate the marginal improvement schedule for loss of life and economic capital as a function of the improved fire observing system.

Hydrologic data and groundwater flow simulations in the vicinity of Long Lake, Indiana Dunes National Lakeshore, near Gary, Indiana

USGS Publications Warehouse

Lampe, David C.; Bayless, E. Randall

2013-01-01

The U.S. Geological Survey (USGS) collected data and simulated groundwater flow to increase understanding of the hydrology and the effects of drainage alterations to the water table in the vicinity of Long Lake, near Gary, Indiana. East Long Lake and West Long Lake (collectively known as Long Lake) make up one of the largest interdunal lakes within the Indiana Dunes National Lakeshore. The National Park Service is tasked with preservation and restoration of wetlands in the Indiana Dunes National Lakeshore along the southern shoreline of Lake Michigan. Urban development and engineering have modified drainage and caused changes in the distribution of open water, streams and ditches, and groundwater abundance and flow paths. A better understanding of the effects these modifications have on the hydrologic system in the area will help the National Park Service, the Gary Sanitary District (GSD), and local stakeholders manage and protect the resources within the study area.This study used hydrologic data and steady-state groundwater simulations to estimate directions of groundwater flow and the effects of various engineering controls and climatic conditions on the hydrology near Long Lake. Periods of relatively high and low groundwater levels were examined and simulated by using MODFLOW and companion software. Simulated hydrologic modifications examined the effects of (1) removing the beaver dams in US-12 ditch, (2) discontinuing seepage of water from the filtration pond east of East Long Lake, (3) discontinuing discharge from US-12 ditch to the GSD sewer system, (4) decreasing discharge from US-12 ditch to the GSD sewer system, (5) connecting East Long Lake and West Long Lake, (6) deepening County Line Road ditch, and (7) raising and lowering the water level of Lake Michigan.Results from collected hydrologic data indicate that East Long Lake functioned as an area of groundwater recharge during October 2002 and a “flow-through” lake during March 2011, with the groundwater divide south of US-12. Wetlands to the south of West Long Lake act as points of recharge to the surficial aquifer in both dry- and wet-weather conditions.Among the noteworthy results from a dry-weather groundwater flow model simulation are (1) US-12 ditch does not receive water from East Long Lake or West Long Lake, (2) the filtration pond at the east end of East Long Lake, when active, contributed approximately 10 percent of the total water entering East Long Lake, and (3) County Line Road ditch has little effect on simulated water level.Among the noteworthy results from a wet-weather groundwater flow simulation are (1) US-12 ditch does not receive water from East Long Lake or West Long Lake, (2) when the seepage from the filtration pond to the surficial aquifer is not active, sources of inflow to East Long Lake are restricted to only precipitation (46 percent of total) and inflow from the surficial aquifer (54 percent of total), and (3) County Line Road ditch bisects the groundwater divide and creates two water-table mounds south of US-12.The results from a series of model scenarios simulating certain engineering controls and changes in Lake Michigan levels include the following: (1) The simulated removal of beaver dams in US-12 ditch during a wet-weather simulation increased discharge from the ditch to the Gary Sanitary system by 13 percent. (2) Discontinuation of seepage from the filtration pond east of East Long Lake decreased discharge from US-12 ditch to the Gary Sanitary system by 2.3 percent. (3) Simulated discontinuation of discharge from the US-12 ditch to the GSD sewer system increased the area where the water table was estimated to be above the land surface beyond the inundated area in the initial wet-weather simulation. (4) Simulated modifications to the control structure at the discharge point of US-12 ditch to the GSD sewer system can decrease discharge by as much as 61 percent while increasing the simulated inundated area during dry weather and decrease discharge as much as 6 percent while increasing the simulated inundated area during wet weather. (5) Deepening of County Line Road ditch can decrease the discharge from US-12 ditch by 26 percent during dry weather and 24 percent during wet weather, as well as decrease the extent of flooded areas south and east of the filtration pond near Ogden Dunes. (7) The increase of the Lake Michigan water level to match the historical maximum can increase the discharge from US-12 ditch by 14 percent during dry weather and by 9.6 percent during wet weather. (8) The decrease of the Lake Michigan water level to match the historical minimum can decrease the discharge from US-12 ditch by 7.4 percent during dry weather and by 3.1 percent during wet weather.The results of this study can be used by water-resource managers to understand how surrounding ditches affect water levels in East and West Long Lake and in the surrounding wetlands and residential areas. The groundwater model developed in this study can be applied in the future to answer questions about how alterations to the drainage system in the area will affect water levels in East and West Long Lake and surrounding areas. The modeling methods developed in this study provide a template for other studies of groundwater flow and groundwater/surface-water interactions within the shallow surficial aquifer in northern Indiana, and in similar hydrologic settings that include surficial sand aquifers in coastal settings.

CCMC: bringing space weather awareness to the next generation

NASA Astrophysics Data System (ADS)

Chulaki, A.; Muglach, K.; Zheng, Y.; Mays, M. L.; Kuznetsova, M. M.; Taktakishvili, A.; Collado-Vega, Y. M.; Rastaetter, L.; Mendoza, A. M. M.; Thompson, B. J.; Pulkkinen, A. A.; Pembroke, A. D.

2017-12-01

Making space weather an element of core education is critical for the future of the young field of space weather. Community Coordinated Modeling Center (CCMC) is an interagency partnership established to aid the transition of modern space science models into space weather forecasting while supporting space science research. Additionally, over the past ten years it has established itself as a global space science education resource supporting undergraduate and graduate education and research, and spreading space weather awareness worldwide. A unique combination of assets, capabilities and close ties to the scientific and educational communities enable our small group to serve as a hub for rising generations of young space scientists and engineers. CCMC offers a variety of educational tools and resources publicly available online and providing access to the largest collection of modern space science models developed by the international research community. CCMC has revolutionized the way these simulations are utilized in classrooms settings, student projects, and scientific labs. Every year, this online system serves hundreds of students, educators and researchers worldwide. Another major CCMC asset is an expert space weather prototyping team primarily serving NASA's interplanetary space weather needs. Capitalizing on its unique capabilities and experiences, the team also provides in-depth space weather training to hundreds of students and professionals. One training module offers undergraduates an opportunity to actively engage in real-time space weather monitoring, analysis, forecasting, tools development and research, eventually serving remotely as NASA space weather forecasters. In yet another project, CCMC is collaborating with Hayden Planetarium and Linkoping University on creating a visualization platform for planetariums (and classrooms) to provide simulations of dynamic processes in the large domain stretching from the solar corona to the Earth's upper atmosphere, for near real-time and historical space weather events.

The Variability and Intermittency of Wind and Solar Power Can Be Overcome Without Storage By Using the National Energy With Weather System (NEWS) Simulator To Design A National US Electric (and Energy) Sector

NASA Astrophysics Data System (ADS)

Clack, C.; MacDonald, A. E.; Wilczak, J. M.; Alexander, A.; Dunbar, A. D.; Xie, Y.; Picciano, P.; Paine, J.; Terry, L.; Marquis, M.

2015-12-01

The importance of weather-driven renewable energies for the United States energy portfolio is growing. The main perceived problems with weather-driven renewable energies are their intermittent nature, low power density, and high costs. The Cooperative Institute for the Research in Environmental Sciences at the University of Colorado collaborated with the Earth Systems Research Laboratory of the National Oceanic and Atmospheric Administration to construct a mathematical optimization of a reduced form of the US electric sector. Care was taken to retain salient features of the electric sector, while allowing for detailed weather and power data to be incorporated for wind and solar energies. The National Energy with Weather System (NEWS) simulator was created. With the NEWS simulator tests can be performed that are unique and insightful. The simulator can maintain the status quo and build out a system following costs or imposed targets for carbon dioxide emission reductions. It can find the least cost electric sector for each state, or find a national power system that incorporates vast amounts of variable generation. In the current presentation, we will focus on one of the most unique aspects of the NEWS simulator; the ability to specify a specific amount of wind and/or solar each hour for a three-year historical period for the least total cost. The simulator can find where to place wind and solar to reduce variability (ramping requirements for back-up generators). The amount of variable generation each hour is very different to an RPS type standard because the generators need to work in concert for long periods of time. The results indicate that for very similar costs the amount of back-up generation (natural gas or storage) can be reduced significantly.

A Portable Regional Weather and Climate Downscaling System Using GEOS-5, LIS-6, WRF, and the NASA Workflow Tool

NASA Astrophysics Data System (ADS)

Kemp, E. M.; Putman, W. M.; Gurganus, J.; Burns, R. W.; Damon, M. R.; McConaughy, G. R.; Seablom, M. S.; Wojcik, G. S.

2009-12-01

We present a regional downscaling system (RDS) suitable for high-resolution weather and climate simulations in multiple supercomputing environments. The RDS is built on the NASA Workflow Tool, a software framework for configuring, running, and managing computer models on multiple platforms with a graphical user interface. The Workflow Tool is used to run the NASA Goddard Earth Observing System Model Version 5 (GEOS-5), a global atmospheric-ocean model for weather and climate simulations down to 1/4 degree resolution; the NASA Land Information System Version 6 (LIS-6), a land surface modeling system that can simulate soil temperature and moisture profiles; and the Weather Research and Forecasting (WRF) community model, a limited-area atmospheric model for weather and climate simulations down to 1-km resolution. The Workflow Tool allows users to customize model settings to user needs; saves and organizes simulation experiments; distributes model runs across different computer clusters (e.g., the DISCOVER cluster at Goddard Space Flight Center, the Cray CX-1 Desktop Supercomputer, etc.); and handles all file transfers and network communications (e.g., scp connections). Together, the RDS is intended to aid researchers by making simulations as easy as possible to generate on the computer resources available. Initial conditions for LIS-6 and GEOS-5 are provided by Modern Era Retrospective-Analysis for Research and Applications (MERRA) reanalysis data stored on DISCOVER. The LIS-6 is first run for 2-4 years forced by MERRA atmospheric analyses, generating initial conditions for the WRF soil physics. GEOS-5 is then initialized from MERRA data and run for the period of interest. Large-scale atmospheric data, sea-surface temperatures, and sea ice coverage from GEOS-5 are used as boundary conditions for WRF, which is run for the same period of interest. Multiply nested grids are used for both LIS-6 and WRF, with the innermost grid run at a resolution sufficient for typical local weather features (terrain, convection, etc.) All model runs, restarts, and file transfers are coordinated by the Workflow Tool. Two use cases are being pursued. First, the RDS generates regional climate simulations down to 4-km for the Chesapeake Bay region, with WRF output provided as input to more specialized models (e.g., ocean/lake, hydrological, marine biology, and air pollution). This will allow assessment of climate impact on local interests (e.g., changes in Bay water levels and temperatures, innundation, fish kills, etc.) Second, the RDS generates high-resolution hurricane simulations in the tropical North Atlantic. This use case will support Observing System Simulation Experiments (OSSEs) of dynamically-targeted lidar observations as part of the NASA Sensor Web Simulator project. Sample results will be presented at the AGU Fall Meeting.

The more extreme nature of North American monsoon precipitation in the Southwestern United States

NASA Astrophysics Data System (ADS)

Chang, H. I.; Luong, T. M.; Castro, C. L.; Lahmers, T. M.; Adams, D. K.; Ochoa-Moya, C.

2017-12-01

Most severe weather in the Southwestern United States occurs during the North American monsoon. This research examines how monsoon extreme weather events will change with respect to occurrence and intensity. A new technique to severe weather event projection has been developed, using convective perimitting regional atmospheric modeling of days with highest instabilty and atmospheric moisture. The guiding principle is to use a weather forecast based approach to climate change project, with a modeling paradigm in which organized convective structures and their behavior are explicitly physically represented in the simulation design. Of particular interest is the simulation of severe weather events caused by mesoscale convective systems (MCSs), which account for a greater proportion of monsoon rainfall downwind of the Mogollon Rim in Arizona, in the central and southwestern portions of the state. The convective-permitting model simulations are performed for identified severe weather event days for both historical and future climate projections, similar to an operational weather forecast. There have been significant long-term changes in atmospheric thermodynamic and dynamic conditions that have occurred over the past sixty years. Monsoon thunderstorms are tending to be more 'thermodynamically dominated' with less tendency to organize and propagate. Though there are tending to be a fewer number of strong, organized MCS-type convective events during the monsoon, when they do occur their associated precipitation is now tending to be more intense. The area of central and southwestern Arizona, corresponding to the area of the state most impacted by MCSs during the monsoon, appears to be a local hot spot where precipitation and downdraft winds are becoming more intense. These types of changes are very consistent with the historical observed precipitation data and model projections of historical and future climate, from dynamically downscaled CMIP3 and CMIP5 models.

Does the market maker stabilize the market?

NASA Astrophysics Data System (ADS)

Zhu, Mei; Chiarella, Carl; He, Xue-Zhong; Wang, Duo

2009-08-01

The market maker plays an important role in price formation, but his/her behavior and stabilizing impact on the market are relatively unclear, in particular in speculative markets. This paper develops a financial market model that examines the impact on market stability of the market maker, who acts as both a liquidity provider and an active investor in a market consisting of two types of boundedly rational speculative investors-the fundamentalists and trend followers. We show that the market maker does not necessarily stabilize the market when he/she actively manages the inventory to maximize profits, and that rather the market maker’s impact depends on the behavior of the speculators. Numerical simulations show that the model is able to generate outcomes for asset returns and market inventories that are consistent with empirical findings.

Evaluation of Factors Influencing the Groundwater Chemistry in a Small Tropical Island of Malaysia

PubMed Central

Kura, Nura Umar; Ramli, Mohammad Firuz; Sulaiman, Wan Nur Azmin; Ibrahim, Shaharin; Aris, Ahmad Zaharin; Mustapha, Adamu

2013-01-01

Groun in a very complex way. In this work, multivariate statistical analysis was used to evaluate the factors controlling the groundwater chemistry of Kapas Island (Malaysia). Principal component analysis (P dwater chemistry of small tropical islands is influenced by many factors, such as recharge, weathering and seawater intrusion, among others, which interact with each other CA) was applied to 17 hydrochemical parameters from 108 groundwater samples obtained from 18 sampling sites. PCA extracted four PCs, namely seawater intrusion, redox reaction, anthropogenic pollution and weather factors, which collectively were responsible for more than 87% of the total variance of the island’s hydrochemistry. The cluster analysis indicated that three factors (weather, redox reaction and seawater intrusion) controlled the hydrochemistry of the area, and the variables were allocated to three groups based on similarity. A Piper diagram classified the island’s water types into Ca-HCO3 water type, Na-HCO3 water type, Na-SO4-Cl water type and Na-Cl water type, indicating recharge, mixed, weathering and leached from sewage and seawater intrusion, respectively. This work will provide policy makers and land managers with knowledge of the precise water quality problems affecting the island and can also serve as a guide for hydrochemistry assessments of other islands that share similar characteristics with the island in question. PMID:23648442

User Guidelines and Best Practices for CASL VUQ Analysis Using Dakota.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Adams, Brian M.; Coleman, Kayla; Hooper, Russell

2016-11-01

Sandia's Dakota software (available at http://dakota.sandia.gov) supports science and engineering transformation through advanced exploration of simulations. Specifically it manages and analyzes ensembles of simulations to provide broader and deeper perspective for analysts and decision makers. This enables them to enhance understanding of risk, improve products, and assess simulation credibility.

Salt weathering in Egyptian limestone after laboratory simulations with continuous flow of salt solutions at different temperatures

NASA Astrophysics Data System (ADS)

Aly, Nevin; Gomez-Heras, Miguel; Hamed, Ayman; Alvarez de Buergo, Monica

2013-04-01

weathering in Egyptian limestone after laboratory simulations with continuous flow of salt solutions at different temperatures Nevin Aly Mohamed (1), Miguel Gomez - Heras(2), Ayman Hamed Ahmed (1), and Monica Alvarez de Buergo(2). (1) Faculty of Pet. & Min. Engineering- Suez Canal University, Suez, Egypt, (2) Instituto de Geociencias (CSIC-UCM) Madrid. Spain. Limestone is one of the most frequent building stones in Egypt and is used since the time of ancient Egyptians and salt weathering is one of the main threats to its conservation. Most of the limestone used in historical monuments in Cairo is a biomicrite extracted from the Mid-Eocene Mokattam Group. During this work, cylindrical samples (2.4 cm diameter and approx. 4.8 cm length) were subjected, in a purpose-made simulation chamber, to simulated laboratory weathering tests with fixed salt concentration (10% weight NaCl solution), at different temperatures, which were kept constant throughout each test (10, 20, 30, 40 oC). During each test, salt solutions flowed continuously imbibing samples by capilarity. Humidity within the simulation chamber was reduced using silica gel to keep it low and constant to increase evaporation rate. Temperature, humidity inside the simulation chamber and samples weight were digitally monitored during each test. Results show the advantages of the proposed experimental methodology using a continuous flow of salt solutions and shed light on the effect of temperature on the dynamics of salt crystallization on and within samples. Research funded by mission sector of high education ministry, Egypt and Geomateriales S2009/MAT-1629.

Adding Weather to Wargames

DTIC Science & Technology

2007-01-01

Aid (IWEDA) we developed techniques that allowed significant improvement in weather effects and impacts for wargames. TAWS was run for numerous and...found that the wargame realism was increased without impacting the run time. While these techniques are applicable to wargames in general, we tested...them by incorporation into the Advanced Warfighting Simulation (AWARS) model. AWARS was modified to incorporate weather impacts upon sensor

Weather Observers: A Manipulative Augmented Reality System for Weather Simulations at Home, in the Classroom, and at a Museum

ERIC Educational Resources Information Center

Hsiao, Hsien-Sheng; Chang, Cheng-Sian; Lin, Chien-Yu; Wang, Yau-Zng

2016-01-01

This study focused on how to enhance the interactivity and usefulness of augmented reality (AR) by integrating manipulative interactive tools with a real-world environment. A manipulative AR (MAR) system, which included 3D interactive models and manipulative aids, was designed and developed to teach the unit "Understanding Weather" in a…

Arsenopyrite weathering under conditions of simulated calcareous soil.

PubMed

Lara, René H; Velázquez, Leticia J; Vazquez-Arenas, Jorge; Mallet, Martine; Dossot, Manuel; Labastida, Israel; Sosa-Rodríguez, Fabiola S; Espinosa-Cristóbal, León F; Escobedo-Bretado, Miguel A; Cruz, Roel

2016-02-01

Mining activities release arsenopyrite into calcareous soils where it undergoes weathering generating toxic compounds. The research evaluates the environmental impacts of these processes under semi-alkaline carbonated conditions. Electrochemical (cyclic voltammetry, chronoamperometry, EIS), spectroscopic (Raman, XPS), and microscopic (SEM, AFM, TEM) techniques are combined along with chemical analyses of leachates collected from simulated arsenopyrite weathering to comprehensively examine the interfacial mechanisms. Early oxidation stages enhance mineral reactivity through the formation of surface sulfur phases (e.g., S n (2-)/S(0)) with semiconductor properties, leading to oscillatory mineral reactivity. Subsequent steps entail the generation of intermediate siderite (FeCO3)-like, followed by the formation of low-compact mass sub-micro ferric oxyhydroxides (α, γ-FeOOH) with adsorbed arsenic (mainly As(III), and lower amounts of As(V)). In addition, weathering reactions can be influenced by accessible arsenic resulting in the formation of a symplesite (Fe3(AsO4)3)-like compound which is dependent on the amount of accessible arsenic in the system. It is proposed that arsenic release occurs via diffusion across secondary α, γ-FeOOH structures during arsenopyrite weathering. We suggest weathering mechanisms of arsenopyrite in calcareous soil and environmental implications based on experimental data.

Comparison of pore space textural characteristics of natural stone exposed to real weathering environment and/or subjected to accelerated weathering tests: implications for durability assessment

NASA Astrophysics Data System (ADS)

Prikryl, Richard; Weishauptová, Zuzana

2017-04-01

One of the key questions in the debate on durability of natural stone is related to the relevance of accelerated weathering tests for durability assessments, specifically whether similar material responses can be achieved? In the recent study, specimens of opuka stone (extremely fine-grained clayey-calcareous silicite) was subjected to accelerated weathering tests in a climatic chamber (sulphur dioxide atmosphere, freezing/thawing). After completion of certain number of cycles, pore space textural characteristics by means of mercury porosimetry were studied. These data were compared with porosimetric data obtained from a piece of stone, sampled from a carved stone altar located in the interior of the St. Vitus Cathedral (Prague, Czech Republic) which was affected by 150-years lasting indoor decay processes (cyclic themohygric stresses due to variable indoor atmospheric conditions). Interestingly, the pore space textural characteristics of these two sets of specimens are closely related and show some distinct features different from fresh, non-weathered material. Our observation therefore supports relevance of some accelerated weathering simulations; however, conditions of these simulations must be based on parameters of real environment.

Space Weathering: Laboratory Analyses and In-Situ Instrumentation

NASA Technical Reports Server (NTRS)

Bentley, M. S.; Ball, A. J.; Dyar, M. D.; Pieters, C. M.; Wright, I. P.; Zarnecki, J. C.

2005-01-01

Space weathering is now understood to be a key modifier of visible and near infrared reflectance spectra of airless bodies. Believed to be caused by vapour recondensation after either ion sputtering or impact vaporization, space weathering has been successfully simulated in the laboratory over the past few years. The optical changes caused by space weathering have been attributed to the accumulation of sub-microscopic iron on regolith grain surfaces. Such fine-grained metallic iron has distinctive magnetic properties that can be used to study it.

Proactive pavement asset management with climate change aspects

NASA Astrophysics Data System (ADS)

Zofka, Adam

2018-05-01

Pavement Asset Management System is a systematic and objective tool to manage pavement network based on the rational, engineering and economic principles. Once implemented and mature Pavement Asset Management System serves the entire range of users starting with the maintenance engineers and ending with the decision-makers. Such a system is necessary to coordinate agency management strategy including proactive maintenance. Basic inputs in the majority of existing Pavement Asset Management System approaches comprise the actual pavement inventory with associated construction history and condition, traffic information as well as various economical parameters. Some Pavement Management System approaches include also weather aspects which is of particular importance considering ongoing climate changes. This paper presents challenges in implementing the Pavement Asset Management System for those National Road Administrations that manage their pavement assets using more traditional strategies, e.g. worse-first approach. Special considerations are given to weather-related inputs and associated analysis to demonstrate the effects of climate change in a short- and long-term range. Based on the presented examples this paper concludes that National Road Administrations should account for the weather-related factors in their Pavement Management Systems as this has a significant impact on the system outcomes from the safety and economical perspective.

Incorporating GIS data into an agent-based model to support planning policy making for the development of creative industries

NASA Astrophysics Data System (ADS)

Liu, Helin; Silva, Elisabete A.; Wang, Qian

2016-07-01

This paper presents an extension to the agent-based model "Creative Industries Development-Urban Spatial Structure Transformation" by incorporating GIS data. Three agent classes, creative firms, creative workers and urban government, are considered in the model, and the spatial environment represents a set of GIS data layers (i.e. road network, key housing areas, land use). With the goal to facilitate urban policy makers to draw up policies locally and optimise the land use assignment in order to support the development of creative industries, the improved model exhibited its capacity to assist the policy makers conducting experiments and simulating different policy scenarios to see the corresponding dynamics of the spatial distributions of creative firms and creative workers across time within a city/district. The spatiotemporal graphs and maps record the simulation results and can be used as a reference by the policy makers to adjust land use plans adaptively at different stages of the creative industries' development process.

Nutrient inputs via rock weathering point to enhanced CO2 uptake capacity of the terrestrial biosphere

NASA Astrophysics Data System (ADS)

Dass, P.; Houlton, B. Z.; Wang, Y.; Pak, B. C.; Morford, S.

2016-12-01

Empirical evidence of widespread scarcity of nitrogen (N) and phosphorus (P) availability in natural land ecosystems constrains the carbon dioxide (CO2) uptake capacity of the global biosphere. Recent studies have pointed to the importance of rock weathering in supplying both N and P to terrestrial soils and vegetation; however, the potential for N and P to rapidly weather from different rocks and thereby alter the global carbon (C) cycle remains an open question, particularly at the global scale. Here, we combine empirical measurements and a new global simulation model to quantify the flux of N and P released from rocks to the terrestrial biosphere. Our model considers the role of tectonic uplift and physical and chemical weathering on rock nutrient cycling by using a probabilistic approach that is anchored in watershed-scale 10Be and Na data from the world's rivers. We use USGS DEM data for relief, monthly averaged MODIS evapotranspiration data and global precipitation datasets. Based on simulations using mean climate data for the past 10 years, we estimate annual values of 11 Tg of N and 6 Tg of P to weather from rocks to the terrestrial biosphere. The rate of N weathering rivals that of atmospheric N deposition in natural ecosystems, and the P weathering flux is approximately 6 times higher than prior estimates based on a modeling approach where the chemical weathering is dependant on lithology and runoff with further factors correcting for soil shielding and temperature. The increase in nutrient inputs we simulate reveals an important role for rock weathering to support new production in terrestrial ecosystems, and thereby allow for additional CO2 uptake in sectors of the biosphere where weathering rates are substantial. Given that current generation of models are yet to consider how short-term weathering of rocks can affect nutrient limited C storage, these results will help to advance the geochemical aspects of carbon-climate feedback this century. Moreover, we will present results for CO2 uptake capacity based on the future climate scenario involving the least mitigation storyline, i.e. RCP 8.5 as well as historic uptake from the beginning of the retreat if the glaciers, i.e. the Last Glacial Maximum.

Climate Information Needs for Financial Decision Making

DOE Office of Scientific and Technical Information (OSTI.GOV)

Higgins, Paul

Climate Information Needs for Financial Decision Making (Final Report) This Department of Energy workshop award (grant #DE-SC0008480) provided primary support for the American Meteorological Society’s study on climate information needs for financial decision making. The goal of this study was to help advance societal decision making by examining the implications of climate variability and change on near-term financial investments. We explored four key topics: 1) the conditions and criteria that influence returns on investment of major financial decisions, 2) the climate sensitivity of financial decisions, 3) climate information needs of financial decision makers, and 4) potential new mechanisms to promotemore » collaboration between scientists and financial decision makers. Better understanding of these four topics will help scientists provide the most useful information and enable financial decision makers to use scientific information most effectively. As a result, this study will enable leaders in business and government to make well-informed choices that help maximize long-term economic success and social wellbeing in the United States The outcomes of the study include a workshop, which brought together leaders from the scientific and financial decision making communities, a publication of the study report, and a public briefing of the results to the policy community. In addition, we will present the results to the scientific community at the AMS Annual Meeting in February, 2014. The study results were covered well by the media including Bloomberg News and E&E News. Upon request, we also briefed the Office of Science Technology Policy (OSTP) and the Council on Environmental Quality (CEQ) on the outcomes. We presented the results to the policy community through a public briefing in December on Capitol Hill. The full report is publicly available at www.ametsoc.org/cin. Summary of Key Findings The United States invests roughly $1.5 trillion U.S. dollars (USD) in capital assets each year across the public and private sectors (Orszag 2008; United States Census Bureau 2013). Extreme weather events create and exacerbate risks to these financial investments by contributing to: • Direct physical impacts on the investments themselves • Degradation of critical supporting infrastructure • Changes in the availability of key natural resources • Changes to workforce availability or capacity • Changes in the customer base • Supply chain disruptions • Legal liability • Shifts in the regulatory environment • Reductions in credit ratings Even small changes in weather can impact operations in critical economic sectors. As a result, maximizing returns on financial investments depends on accurately understanding and effectively accounting for these risks. Climate variability and change can either exacerbate existing risks or cause new sources of risk to emerge. Managing these risks most effectively will depend on scientific advances and increases in the capacity of financial decision makers to use the scientific knowledge that results. Barriers to using climate information must also be overcome. This study proposes three predefined levels of certainty for communicating about weather and climate risks: 1) possible (i.e., unknown likelihood or less than 50% chance of occurrence), 2) probable (greater than 50% chance of occurrence), and 3) effectively certain (at least 95% chance of occurrence). For example, it is effectively certain that a change in climate will alter weather patterns. It is probable that climate warming will cause increases in the intensity of some extreme events. It is possible that climate change will cause major and widespread disruptions to key planetary life-support services. Key recommendations of this study: 1) Identify climate-related risks and opportunities for financial decision making. 2) Create a framework to translate scientific information in clear and actionable terms for financial decision makers. 3) Analyze existing climate assessments and translate projected impacts into possible, probable, and effectively certain impacts. 4) Improve climate projections with respect to precipitation (timing, amount, and intensity), extreme events, and tails of probability distributions (i.e., low-probability but high-consequence events). 5) Increase spatial resolution of climate projections in order to provide climate information at the scale most relevant to financial investments. 6) Improve projections of the societal consequences of climate impacts through integrated assessments of physical, natural, and social sciences. 7) Create a user-friendly information repository and portal that provides easy access to information relevant to financial decision making. 8) Create and maintain opportunities to bring together financial decision makers, scientists, and service providers. Near-term financial decisions have long-term implications for the United States’ social and economic well-being that depend, in part, on climate variability and change. Investments will be most successful, and will advance the interests of society most effectively, if they are grounded in the best available knowledge & understanding.« less

Numerical simulation and analysis of the April 2013 Chicago floods

DOE PAGES

Campos, Edwin; Wang, Jiali

2015-09-08

The weather event associated to record Chicago floods on April 2013 is investigated by using the Weather Research and Forecasting (WRF) model. Observations at Argonne National Laboratory and multi-sensor (weather radar and rain gauge) precipitation data from the National Weather Service were employed to evaluate the model’s performance. The WRF model captured the synoptic-scale atmospheric features well, but the simulated 24-h accumulated precipitation and short-period temporal evolution of precipitation over the heavy-rain region were less successful. To investigate the potential reasons for the model bias, four supplementary sensitivity experiments using various microphysics schemes and cumulus parameterizations were designed. Of themore » five tested parameterizations, the WRF Single-Moment 6-class (WSM6) graupel scheme and Kain-Fritsch (KF) cumulus parameterization outperformed the others, such as Grell-Dévényi (GD) cumulus parameterization, which underestimated the precipitation by 30–50% on a regional-average scale. Morrison microphysics and KF outperformed the others for the spatial patterns of 24-h accumulated precipitation. The spatial correlation between observation and Morrison-KF was 0.45, higher than those for other simulations. All of the simulations underestimated the precipitation over northeastern Illinois (especially at Argonne) during 0400–0800 UTC 18 April because of weak ascending motion or small moisture. In conclusion, all of the simulations except WSM6-GD also underestimated the precipitation during 1200–1600 UTC 18 April because of weak southerly flow.« less

Application of the Fractions Skill Score for Tracking the Effectiveness of Improvements Made to Weather Research and Forecasting Model Simulations

DTIC Science & Technology

2017-11-22

Weather Research and Forecasting Model Simulations by John W Raby and Huaqing Cai Computational and Information Sciences Directorate, ARL...burden for this collection of information is estimated to average 1 hour per response, including the time for reviewing instructions, searching...existing data sources, gathering and maintaining the data needed, and completing and reviewing the collection information . Send comments regarding this

Local Infrasound Variability Related to In Situ Atmospheric Observation

NASA Astrophysics Data System (ADS)

Kim, Keehoon; Rodgers, Arthur; Seastrand, Douglas

2018-04-01

Local infrasound is widely used to constrain source parameters of near-surface events (e.g., chemical explosions and volcanic eruptions). While atmospheric conditions are critical to infrasound propagation and source parameter inversion, local atmospheric variability is often ignored by assuming homogeneous atmospheres, and their impact on the source inversion uncertainty has never been accounted for due to the lack of quantitative understanding of infrasound variability. We investigate atmospheric impacts on local infrasound propagation by repeated explosion experiments with a dense acoustic network and in situ atmospheric measurement. We perform full 3-D waveform simulations with local atmospheric data and numerical weather forecast model to quantify atmosphere-dependent infrasound variability and address the advantage and restriction of local weather data/numerical weather model for sound propagation simulation. Numerical simulations with stochastic atmosphere models also showed nonnegligible influence of atmospheric heterogeneity on infrasound amplitude, suggesting an important role of local turbulence.

Cockpit weather radar display demonstrator and ground-to-air sferics telemetry system

NASA Technical Reports Server (NTRS)

Nickum, J. D.; Mccall, D. L.

1982-01-01

The results of two methods of obtaining timely and accurate severe weather presentations in the cockpit are detailed. The first method described is a course up display of uplinked weather radar data. This involves the construction of a demonstrator that will show the feasibility of producing a course up display in the cockpit of the NASA simulator at Langley. A set of software algorithms was designed that could easily be implemented, along with data tapes generated to provide the cockpit simulation. The second method described involves the uplinking of sferic data from a ground based 3M-Ryan Stormscope. The technique involves transfer of the data on the CRT of the Stormscope to a remote CRT. This sferic uplink and display could also be included in an implementation on the NASA cockpit simulator, allowing evaluation of pilot responses based on real Stormscope data.

A Sensitivity-Based Approach to Quantifying the Costs of Weather and Climate Impacts: A Case Study of the Southern Pennsylvania Transportation Authority Adaptation Pilot Project

NASA Astrophysics Data System (ADS)

Casola, J.; Johanson, E.; Groth, P.; Snow, C.; Choate, A.

2012-12-01

Southeastern Pennsylvania Transportation Authority (SEPTA), with support from the Federal Transit Administration, has been investigating its agency's vulnerability to weather-related disruption and damages as a way to inform an overall adaptation strategy for climate variability and change. Exploiting daily rail service records maintained by SEPTA and observations from nearby weather stations, we have developed a methodology for quantifying the sensitivity of SEPTA's Manayunk/Norristown rail line to various weather events (e.g., snow storms, heat waves, heavy rainfall and flooding, tropical storms). For each type of event, sensitivity is equated to the frequency and extent of service disruptions associated with the event, and includes the identification of thresholds beyond which impacts are observed. In addition, we have estimated the monetary costs associated with repair and replacement of infrastructure following these events. Our results have facilitated discussions with SEPTA operational staff, who have outlined the institutional aspects of their preparation and response processes for these weather events. We envision the methodology as being useful for resource and infrastructure managers across the public and private sector, and potentially scalable to smaller or larger operations. There are several advantageous aspects of the method: 1) the quantification of sensitivity, and the coupling of that sensitivity to cost information, provides credible input to SEPTA decision-makers as they establish the priorities and level of investment associated with their adaptation actions for addressing extreme weather; 2) the method provides a conceptual foundation for estimating the magnitude, frequency, and costs of potential future impacts at a local scale, especially with regard to heat waves; 3) the sensitivity information serves as an excellent discussion tool, enabling further research and information gathering about institutional relationships and procedures. These relationships and procedures are critical to the effectiveness of preparation for and responses to extreme weather events, but are often not explicitly documented.

A framework to assess the impacts of Climate Change for different hazards at local and regional scale through probabilistic multi-model approaches

NASA Astrophysics Data System (ADS)

Mercogliano, P.; Reder, A.; Rianna, G.

2017-12-01

Extreme weather events (EWEs) are projected to be more frequent and severe across the globe because of global warming. This poses challenging problems for critical infrastructures (CIs) which can be dramatically affected by EWEs needing adaptation countermeasures againts changing climate conditions. In this work, we present the main results achieved in the framework of the FP7-European project INTACT aimed at analyzing the resilience of CIs against shocks and stresses due to the climate changes. To identify variations in the hazard induced by climate change, appropriate Extreme Weather Indicators (EWIs) are defined for several case studies and different approaches are analyzed to obtain local climate projections. The different approaches, with increasing refinement depending on local information available and methodologies selected, are investigated considering raw versus bias corrected data and weighted or equiprobable ensemble mean projections given by the regional climate models within the Euro-CORDEX program. Specifically, this work focuses on two case studies selected from the five proposed within the INTACT project and for which local station data are available: • rainfall-induced landslide affecting Campania region (Southern Italy) with a special view on the Nocera municipality; • storms and heavy rainfall/winds in port of Rotterdam (Netherlands). In general, our results show a small sensitivity to the weighting approach and a large sensitivity to bias-correction in the future projections. For landslides in Campania region, the Euro-CORDEX simulations projected a generalized worsening of the safety conditions depending on the scenario (RCP4.5/8.5) and period (2011-2040/2041-2070/2071-2100) considered. For the port of Rotterdam, the Euro-CORDEX simulations projected an increment in the intense events of daily and weekly precipitation, also in this case depending on the scenario and period considered. Considering framework, methodologies and results, the activities developed within the INTACT project, also through an intense effort of knowledge co-production between researchers and stakeholders, posed a theoretical-based starting point for CI owners, operators and protection policy makers for the setup of protection systems against present and future climatic hazard features.

Approach to Integrate Global-Sun Models of Magnetic Flux Emergence and Transport for Space Weather Studies

NASA Technical Reports Server (NTRS)

Mansour, Nagi N.; Wray, Alan A.; Mehrotra, Piyush; Henney, Carl; Arge, Nick; Godinez, H.; Manchester, Ward; Koller, J.; Kosovichev, A.; Scherrer, P.;

Noah-MP-Crop: Enhancing cropland representation in the community land surface modeling system

NASA Astrophysics Data System (ADS)

Liu, X.; Chen, F.; Barlage, M. J.; Zhou, G.; Niyogi, D.

2015-12-01

Croplands are important in land-atmosphere interactions and in modifying local and regional weather and climate. Despite their importance, croplands are poorly represented in the current version of the coupled Weather Research and Forecasting (WRF)/ Noah land-surface modeling system, resulting in significant surface temperature and humidity biases across agriculture- dominated regions of the United States. This study aims to improve the WRF weather forecasting and regional climate simulations during the crop growing season by enhancing the representation of cropland in the Noah-MP land model. We introduced dynamic crop growth parameterization into Noah-MP and evaluated the enhanced model (Noah-MP-Crop) at both the field and regional scales with multiple crop biomass datasets, surface fluxes and soil moisture/temperature observations. We also integrated a detailed cropland cover map into WRF, enabling the model to simulate corn and soybean field across the U.S. Great Plains. Results show marked improvement in the Noah-MP-Crop performance in simulating leaf area index (LAI), crop biomass, soil temperature, and surface fluxes. Enhanced cropland representation is not only crucial for improving weather forecasting but can also help assess potential impacts of weather variability on regional hydrometeorology and crop yields. In addition to its applications to WRF, Noah-MP-Crop can be applied in high-spatial-resolution regional crop yield modeling and drought assessments

Evaluation of High Density Air Traffic Operations with Automation for Separation Assurance, Weather Avoidance and Schedule Conformance

NASA Technical Reports Server (NTRS)

Prevot, Thomas; Mercer, Joey S.; Martin, Lynne Hazel; Homola, Jeffrey R.; Cabrall, Christopher D.; Brasil, Connie L.

2011-01-01

In this paper we discuss the development and evaluation of our prototype technologies and procedures for far-term air traffic control operations with automation for separation assurance, weather avoidance and schedule conformance. Controller-in-the-loop simulations in the Airspace Operations Laboratory at the NASA Ames Research Center in 2010 have shown very promising results. We found the operations to provide high airspace throughput, excellent efficiency and schedule conformance. The simulation also highlighted areas for improvements: Short-term conflict situations sometimes resulted in separation violations, particularly for transitioning aircraft in complex traffic flows. The combination of heavy metering and growing weather resulted in an increased number of aircraft penetrating convective weather cells. To address these shortcomings technologies and procedures have been improved and the operations are being re-evaluated with the same scenarios. In this paper we will first describe the concept and technologies for automating separation assurance, weather avoidance, and schedule conformance. Second, the results from the 2010 simulation will be reviewed. We report human-systems integration aspects, safety and efficiency results as well as airspace throughput, workload, and operational acceptability. Next, improvements will be discussed that were made to address identified shortcomings. We conclude that, with further refinements, air traffic control operations with ground-based automated separation assurance can routinely provide currently unachievable levels of traffic throughput in the en route airspace.

Future ATM Concepts Evaluation Tool (FACET) Interface Control Document

NASA Technical Reports Server (NTRS)

Grabbe, Shon R.

2017-01-01

This Interface Control Document (ICD) documents the airspace adaptation and air traffic inputs of NASA's Future ATM Concepts and Evaluation Tool (FACET). Its intended audience is the project manager, project team, development team, and stakeholders interested in interfacing with the system. FACET equips Air Traffic Management (ATM) researchers and service providers with a way to explore, develop and evaluate advanced air transportation concepts before they are field-tested and eventually deployed. FACET is a flexible software tool that is capable of quickly generating and analyzing thousands of aircraft trajectories. It provides researchers with a simulation environment for preliminary testing of advanced ATM concepts. Using aircraft performance profiles, airspace models, weather data, and flight schedules, the tool models trajectories for the climb, cruise, and descent phases of flight for each type of aircraft. An advanced graphical interface displays traffic patterns in two and three dimensions, under various current and projected conditions for specific airspace regions or over the entire continental United States. The system is able to simulate a full day's dynamic national airspace system (NAS) operations, model system uncertainty, measure the impact of different decision-makers in the NAS, and provide analysis of the results in graphical form, including sector, airport, fix, and airway usage statistics. NASA researchers test and analyze the system-wide impact of new traffic flow management algorithms under anticipated air traffic growth projections on the nation's air traffic system. In addition to modeling the airspace system for NASA research, FACET has also successfully transitioned into a valuable tool for operational use. Federal Aviation Administration (FAA) traffic flow managers and commercial airline dispatchers have used FACET technology for real-time operations planning. FACET integrates live air traffic data from FAA radar systems and weather data from the National Weather Service to summarize NAS performance. This information allows system operators to reroute flights around congested airspace and severe weather to maintain safety and minimize delay. FACET also supports the planning and post-operational evaluation of reroute strategies at the national level to maximize system efficiency. For the commercial airline passenger, strategic planning with FACET can result in fewer flight delays and cancellations. The performance capabilities of FACET are largely due to its architecture, which strikes a balance between flexibility and fidelity. FACET is capable of modeling the airspace operations for the continental United States, processing thousands of aircraft on a single computer. FACET was written in Java and C, enabling the portability of its software to a variety of operating systems. In addition, FACET was designed with a modular software architecture to facilitate rapid prototyping of diverse ATM concepts. Several advanced ATM concepts have already been implemented in FACET, including aircraft self-separation, prediction of aircraft demand and sector congestion, system-wide impact assessment of traffic flow management constraints, and wind-optimal routing.

The NASA Altitude Wind Tunnel (AWT): Its role in advanced icing research and development

NASA Technical Reports Server (NTRS)

Blaha, B. J.; Shaw, R. J.

1985-01-01

Currently experimental aircraft icing research is severely hampered by limitations of ground icing simulation facilities. Existing icing facilities do not have the size, speed, altitude, and icing environment simulation capabilities to allow accurate studies to be made of icing problems occurring for high speed fixed wing aircraft and rotorcraft. Use of the currently dormant NASA Lewis Altitude Wind Tunnel (AWT), as a proposed high speed propulsion and adverse weather facility, would allow many such problems to be studied. The characteristics of the AWT related to adverse weather simulation and in particular to icing simulation are discussed, and potential icing research programs using the AWT are also included.

Modeling and Simulation of Shuttle Launch and Range Operations

NASA Technical Reports Server (NTRS)

Bardina, Jorge; Thirumalainambi, Rajkumar

2004-01-01

The simulation and modeling test bed is based on a mockup of a space flight operations control suitable to experiment physical, procedural, software, hardware and psychological aspects of space flight operations. The test bed consists of a weather expert system to advise on the effect of weather to the launch operations. It also simulates toxic gas dispersion model, impact of human health risk, debris dispersion model in 3D visualization. Since all modeling and simulation is based on the internet, it could reduce the cost of operations of launch and range safety by conducting extensive research before a particular launch. Each model has an independent decision making module to derive the best decision for launch.

Creating Weather System Ensembles Through Synergistic Process Modeling and Machine Learning

NASA Astrophysics Data System (ADS)

Chen, B.; Posselt, D. J.; Nguyen, H.; Wu, L.; Su, H.; Braverman, A. J.

2017-12-01

Earth's weather and climate are sensitive to a variety of control factors (e.g., initial state, forcing functions, etc). Characterizing the response of the atmosphere to a change in initial conditions or model forcing is critical for weather forecasting (ensemble prediction) and climate change assessment. Input - response relationships can be quantified by generating an ensemble of multiple (100s to 1000s) realistic realizations of weather and climate states. Atmospheric numerical models generate simulated data through discretized numerical approximation of the partial differential equations (PDEs) governing the underlying physics. However, the computational expense of running high resolution atmospheric state models makes generation of more than a few simulations infeasible. Here, we discuss an experiment wherein we approximate the numerical PDE solver within the Weather Research and Forecasting (WRF) Model using neural networks trained on a subset of model run outputs. Once trained, these neural nets can produce large number of realization of weather states from a small number of deterministic simulations with speeds that are orders of magnitude faster than the underlying PDE solver. Our neural network architecture is inspired by the governing partial differential equations. These equations are location-invariant, and consist of first and second derivations. As such, we use a 3x3 lon-lat grid of atmospheric profiles as the predictor in the neural net to provide the network the information necessary to compute the first and second moments. Results indicate that the neural network algorithm can approximate the PDE outputs with high degree of accuracy (less than 1% error), and that this error increases as a function of the prediction time lag.

A GEOCLIM Simulation Of Climatic And Biogeochemical Consequences Of Pangea Break Up

NASA Astrophysics Data System (ADS)

Donnadieu, Y.; Godderis, Y.; Pierrehumbert, R.; Dromart, G.; Jacob, R.

2006-12-01

Large fluctuations in continental configuration occur all along the Mesozoic times. While it has long been recognized that paleogeography may potentially influence atmospheric CO2 via the continental silicate weathering feedback, no numerical simulation have been done given the lack of a spatially resolved climate- carbon model. GEOCLIM, a coupled numerical model of the climate and global biogeochemical cycles, is used to investigate the consequences of the Pangea break up. The climate module of the GEOCLIM model is the FOAM atmospheric general circulation model, allowing the calculation of the consumption of atmospheric CO2 through continental silicate weathering with a spatial resolution of 7.5°long 4.5°lat. Seven time slices have been simulated. We show that the break up of the Pangea supercontinent triggers an increase in continental runoff, resulting in enhanced atmospheric CO2 consumption through silicate weathering. As a result, atmospheric CO2 falls from values above 3000 ppmv during the Triassic, down to rather low levels during the Cretaceous (around 400 ppmv), resulting in a decrease in continental temperatures from about 20°C to 10°C. Silicate weathering feedback and paleogeography both act to force the Earth system toward a dry and hot world reaching its optimum over the last 260 Ma during the Middle-Late Triassic. In the super continent case, given the relative aridity that cannot be climatically overwhelmed, the model generates high CO2 values to produce very warm continental temperatures compensating for the lack of continental humidity. Conversely, in the fragmented case, the runoff becomes the most important contributor to the silicate weathering rate, hence, producing a CO2 drawdown and a fall in continental temperatures. Finally, an other unexpected outcome is the pronounced fluctuations in carbonate accumulation simulated by the model in response to the Pangea break up. These fluctuations are driven by changes in continental carbonate weathering flux. Accounting for the fluctuations in area available for carbonate platforms, the simulated ratio of carbonate deposition between neritic and deep sea environments is in better agreement with available data.

An analytical framework to assist decision makers in the use of forest ecosystem model predictions

USGS Publications Warehouse

Larocque, Guy R.; Bhatti, Jagtar S.; Ascough, J.C.; Liu, J.; Luckai, N.; Mailly, D.; Archambault, L.; Gordon, Andrew M.

2011-01-01

The predictions from most forest ecosystem models originate from deterministic simulations. However, few evaluation exercises for model outputs are performed by either model developers or users. This issue has important consequences for decision makers using these models to develop natural resource management policies, as they cannot evaluate the extent to which predictions stemming from the simulation of alternative management scenarios may result in significant environmental or economic differences. Various numerical methods, such as sensitivity/uncertainty analyses, or bootstrap methods, may be used to evaluate models and the errors associated with their outputs. However, the application of each of these methods carries unique challenges which decision makers do not necessarily understand; guidance is required when interpreting the output generated from each model. This paper proposes a decision flow chart in the form of an analytical framework to help decision makers apply, in an orderly fashion, different steps involved in examining the model outputs. The analytical framework is discussed with regard to the definition of problems and objectives and includes the following topics: model selection, identification of alternatives, modelling tasks and selecting alternatives for developing policy or implementing management scenarios. Its application is illustrated using an on-going exercise in developing silvicultural guidelines for a forest management enterprise in Ontario, Canada.

SIMULATION-BASED WEATHER NORMALIZATION APPROACH TO STUDY THE IMPACT OF WEATHER ON ENERGY USE OF BUILDINGS IN THE U.S.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Makhmalbaf, Atefe; Srivastava, Viraj; Wang, Na

Weather normalization is a crucial task in several applications related to building energy conservation such as retrofit measurements and energy rating. This paper documents preliminary results found from an effort to determine a set of weather adjustment coefficients that can be used to smooth out impacts of weather on energy use of buildings in 1020 weather location sites available in the U.S. The U.S. Department of Energy (DOE) commercial reference building models are adopted as hypothetical models with standard operations to deliver consistency in modeling. The correlation between building envelop design, HVAC system design and properties for different building typesmore » and the change in heating and cooling energy consumption caused by variations in weather is examined.« less

Evaluating Changes in Extreme Weather During the North American Monsoon in the Southwest U.S. Using High Resolution, Convective-Permitting Regional Atmospheric Modeling

NASA Astrophysics Data System (ADS)

Castro, C. L.; Chang, H. I.; Luong, T. M.; Lahmers, T.; Jares, M.; Mazon, J.; Carrillo, C. M.; Adams, D. K.

2015-12-01

The North American monsoon (NAM) is the principal driver of summer severe weather in the Southwest U.S. Monsoon convection typically initiates during daytime over the mountains and may organize into mesoscale convective systems (MCSs). Most monsoon-related severe weather occurs in association with organized convection, including microbursts, dust storms, flash flooding and lightning. A convective resolving grid spacing (on the kilometer scale) model is required to explicitly represent the physical characteristics of organized convection, for example the presence of leading convective lines and trailing stratiform precipitation regions. Our objective is to analyze how monsoon severe weather is changing in relation to anthropogenic climate change. We first consider a dynamically downscaled reanalysis during a historical period 1948-2010. Individual severe weather event days, identified by favorable thermodynamic conditions, are then simulated for short-term, numerical weather prediction-type simulations of 30h at a convective-permitting scale. Changes in modeled severe weather events indicate increases in precipitation intensity in association with long-term increases in atmospheric instability and moisture, particularly with organized convection downwind of mountain ranges. However, because the frequency of synoptic transients is decreasing during the monsoon, organized convection is less frequent and convective precipitation tends to be more phased locked to terrain. These types of modeled changes also similarly appear in observed CPC precipitation, when the severe weather event days are selected using historical radiosonde data. Next, we apply the identical model simulation and analysis procedures to several dynamically downscaled CMIP3 and CMIP5 models for the period 1950-2100, to assess how monsoon severe weather may change in the future with respect to occurrence and intensity and if these changes correspond with what is already occurring in the historical record. The CMIP5 models we are downscaling (HadGEM2-ES and MPI-ESM-LR) will be included as part of North American COordinated Regional climate Downscaling EXperiment (CORDEX). Results from this project will be used for climate change impacts assessment for U.S. military installations in the region.

Simulating carbon capture by enhanced weathering with croplands: an overview of key processes highlighting areas of future model development

PubMed Central

Quegan, Shaun; Banwart, Steven A.

2017-01-01

Enhanced weathering (EW) aims to amplify a natural sink for CO2 by incorporating powdered silicate rock with high reactive surface area into agricultural soils. The goal is to achieve rapid dissolution of minerals and release of alkalinity with accompanying dissolution of CO2 into soils and drainage waters. EW could counteract phosphorus limitation and greenhouse gas (GHG) emissions in tropical soils, and soil acidification, a common agricultural problem studied with numerical process models over several decades. Here, we review the processes leading to soil acidification in croplands and how the soil weathering CO2 sink is represented in models. Mathematical models capturing the dominant processes and human interventions governing cropland soil chemistry and GHG emissions neglect weathering, while most weathering models neglect agricultural processes. We discuss current approaches to modelling EW and highlight several classes of model having the potential to simulate EW in croplands. Finally, we argue for further integration of process knowledge in mathematical models to capture feedbacks affecting both longer-term CO2 consumption and crop growth and yields. PMID:28381633

Pilot Study: Impact of Computer Simulation on Students' Economic Policy Performance. Pilot Study.

ERIC Educational Resources Information Center

Domazlicky, Bruce; France, Judith

Fiscal and monetary policies taught in macroeconomic principles courses are concepts that might require both lecture and simulation methods. The simulation models, which apply the principles gleened from comparative statistics to a dynamic world, may give students an appreciation for the problems facing policy makers. This paper is a report of a…

Improving Seasonal Crop Monitoring and Forecasting for Soybean and Corn in Iowa

NASA Astrophysics Data System (ADS)

Togliatti, K.; Archontoulis, S.; Dietzel, R.; VanLoocke, A.

2016-12-01

Accurately forecasting crop yield in advance of harvest could greatly benefit farmers, however few evaluations have been conducted to determine the effectiveness of forecasting methods. We tested one such method that used a combination of short-term weather forecasting from the Weather Research and Forecasting Model (WRF) to predict in season weather variables, such as, maximum and minimum temperature, precipitation and radiation at 4 different forecast lengths (2 weeks, 1 week, 3 days, and 0 days). This forecasted weather data along with the current and historic (previous 35 years) data from the Iowa Environmental Mesonet was combined to drive Agricultural Production Systems sIMulator (APSIM) simulations to forecast soybean and corn yields in 2015 and 2016. The goal of this study is to find the forecast length that reduces the variability of simulated yield predictions while also increasing the accuracy of those predictions. APSIM simulations of crop variables were evaluated against bi-weekly field measurements of phenology, biomass, and leaf area index from early and late planted soybean plots located at the Agricultural Engineering and Agronomy Research Farm in central Iowa as well as the Northwest Research Farm in northwestern Iowa. WRF model predictions were evaluated against observed weather data collected at the experimental fields. Maximum temperature was the most accurately predicted variable, followed by minimum temperature and radiation, and precipitation was least accurate according to RMSE values and the number of days that were forecasted within a 20% error of the observed weather. Our analysis indicated that for the majority of months in the growing season the 3 day forecast performed the best. The 1 week forecast came in second and the 2 week forecast was the least accurate for the majority of months. Preliminary results for yield indicate that the 2 week forecast is the least variable of the forecast lengths, however it also is the least accurate. The 3 day and 1 week forecast have a better accuracy, with an increase in variability.

Efficient Simulation of Tropical Cyclone Pathways with Stochastic Perturbations

NASA Astrophysics Data System (ADS)

Webber, R.; Plotkin, D. A.; Abbot, D. S.; Weare, J.

2017-12-01

Global Climate Models (GCMs) are known to statistically underpredict intense tropical cyclones (TCs) because they fail to capture the rapid intensification and high wind speeds characteristic of the most destructive TCs. Stochastic parametrization schemes have the potential to improve the accuracy of GCMs. However, current analysis of these schemes through direct sampling is limited by the computational expense of simulating a rare weather event at fine spatial gridding. The present work introduces a stochastically perturbed parametrization tendency (SPPT) scheme to increase simulated intensity of TCs. We adapt the Weighted Ensemble algorithm to simulate the distribution of TCs at a fraction of the computational effort required in direct sampling. We illustrate the efficiency of the SPPT scheme by comparing simulations at different spatial resolutions and stochastic parameter regimes. Stochastic parametrization and rare event sampling strategies have great potential to improve TC prediction and aid understanding of tropical cyclogenesis. Since rising sea surface temperatures are postulated to increase the intensity of TCs, these strategies can also improve predictions about climate change-related weather patterns. The rare event sampling strategies used in the current work are not only a novel tool for studying TCs, but they may also be applied to sampling any range of extreme weather events.

Urban Flow and Pollutant Dispersion Simulation with Multi-scale coupling of Meteorological Model with Computational Fluid Dynamic Analysis

NASA Astrophysics Data System (ADS)

Liu, Yushi; Poh, Hee Joo

2014-11-01

The Computational Fluid Dynamics analysis has become increasingly important in modern urban planning in order to create highly livable city. This paper presents a multi-scale modeling methodology which couples Weather Research and Forecasting (WRF) Model with open source CFD simulation tool, OpenFOAM. This coupling enables the simulation of the wind flow and pollutant dispersion in urban built-up area with high resolution mesh. In this methodology meso-scale model WRF provides the boundary condition for the micro-scale CFD model OpenFOAM. The advantage is that the realistic weather condition is taken into account in the CFD simulation and complexity of building layout can be handled with ease by meshing utility of OpenFOAM. The result is validated against the Joint Urban 2003 Tracer Field Tests in Oklahoma City and there is reasonably good agreement between the CFD simulation and field observation. The coupling of WRF- OpenFOAM provide urban planners with reliable environmental modeling tool in actual urban built-up area; and it can be further extended with consideration of future weather conditions for the scenario studies on climate change impact.

Evaluation of snowmelt simulation in the Weather Research and Forecasting model

NASA Astrophysics Data System (ADS)

Jin, Jiming; Wen, Lijuan

2012-05-01

The objective of this study is to better understand and improve snowmelt simulations in the advanced Weather Research and Forecasting (WRF) model by coupling it with the Community Land Model (CLM) Version 3.5. Both WRF and CLM are developed by the National Center for Atmospheric Research. The automated Snow Telemetry (SNOTEL) station data over the Columbia River Basin in the northwestern United States are used to evaluate snowmelt simulations generated with the coupled WRF-CLM model. These SNOTEL data include snow water equivalent (SWE), precipitation, and temperature. The simulations cover the period of March through June 2002 and focus mostly on the snowmelt season. Initial results show that when compared to observations, WRF-CLM significantly improves the simulations of SWE, which is underestimated when the release version of WRF is coupled with the Noah and Rapid Update Cycle (RUC) land surface schemes, in which snow physics is oversimplified. Further analysis shows that more realistic snow surface energy allocation in CLM is an important process that results in improved snowmelt simulations when compared to that in Noah and RUC. Additional simulations with WRF-CLM at different horizontal spatial resolutions indicate that accurate description of topography is also vital to SWE simulations. WRF-CLM at 10 km resolution produces the most realistic SWE simulations when compared to those produced with coarser spatial resolutions in which SWE is remarkably underestimated. The coupled WRF-CLM provides an important tool for research and forecasts in weather, climate, and water resources at regional scales.

Application of the NASA A-Train to Evaluate Clouds Simulated by the Weather Research and Forecast Model

NASA Technical Reports Server (NTRS)

Molthan, Andrew L.; Jedlovec, Gary J.; Lapenta, William M.

2008-01-01

The CloudSat Mission, part of the NASA A-Train, is providing the first global survey of cloud profiles and cloud physical properties, observing seasonal and geographical variations that are pertinent to evaluating the way clouds are parameterized in weather and climate forecast models. CloudSat measures the vertical structure of clouds and precipitation from space through the Cloud Profiling Radar (CPR), a 94 GHz nadir-looking radar measuring the power backscattered by clouds as a function of distance from the radar. One of the goals of the CloudSat mission is to evaluate the representation of clouds in forecast models, thereby contributing to improved predictions of weather, climate and the cloud-climate feedback problem. This paper highlights potential limitations in cloud microphysical schemes currently employed in the Weather Research and Forecast (WRF) modeling system. The horizontal and vertical structure of explicitly simulated cloud fields produced by the WRF model at 4-km resolution are being evaluated using CloudSat observations in concert with products derived from MODIS and AIRS. A radiative transfer model is used to produce simulated profiles of radar reflectivity given WRF input profiles of hydrometeor mixing ratios and ambient atmospheric conditions. The preliminary results presented in the paper will compare simulated and observed reflectivity fields corresponding to horizontal and vertical cloud structures associated with midlatitude cyclone events.

Development and Application of Advanced Weather Prediction Technologies for the Wind Energy Industry (Invited)

NASA Astrophysics Data System (ADS)

Mahoney, W. P.; Wiener, G.; Liu, Y.; Myers, W.; Johnson, D.

2010-12-01

Wind energy decision makers are required to make critical judgments on a daily basis with regard to energy generation, distribution, demand, storage, and integration. Accurate knowledge of the present and future state of the atmosphere is vital in making these decisions. As wind energy portfolios expand, this forecast problem is taking on new urgency because wind forecast inaccuracies frequently lead to substantial economic losses and constrain the national expansion of renewable energy. Improved weather prediction and precise spatial analysis of small-scale weather events are crucial for renewable energy management. In early 2009, the National Center for Atmospheric Research (NCAR) began a collaborative project with Xcel Energy Services, Inc. to perform research and develop technologies to improve Xcel Energy's ability to increase the amount of wind energy in their generation portfolio. The agreement and scope of work was designed to provide highly detailed, localized wind energy forecasts to enable Xcel Energy to more efficiently integrate electricity generated from wind into the power grid. The wind prediction technologies are designed to help Xcel Energy operators make critical decisions about powering down traditional coal and natural gas-powered plants when sufficient wind energy is predicted. The wind prediction technologies have been designed to cover Xcel Energy wind resources spanning a region from Wisconsin to New Mexico. The goal of the project is not only to improve Xcel Energy’s wind energy prediction capabilities, but also to make technological advancements in wind and wind energy prediction, expand our knowledge of boundary layer meteorology, and share the results across the renewable energy industry. To generate wind energy forecasts, NCAR is incorporating observations of current atmospheric conditions from a variety of sources including satellites, aircraft, weather radars, ground-based weather stations, wind profilers, and even wind sensors on individual wind turbines. The information is utilized by several technologies including: a) the Weather Research and Forecasting (WRF) model, which generates finely detailed simulations of future atmospheric conditions, b) the Real-Time Four-Dimensional Data Assimilation System (RTFDDA), which performs continuous data assimilation providing the WRF model with continuous updates of the initial atmospheric state, 3) the Dynamic Integrated Forecast System (DICast®), which statistically optimizes the forecasts using all predictors, and 4) a suite of wind-to-power algorithms that convert wind speed to power for a wide range of wind farms with varying real-time data availability capabilities. In addition to these core wind energy prediction capabilities, NCAR implemented a high-resolution (10 km grid increment) 30-member ensemble RTFDDA prediction system that provides information on the expected range of wind power over a 72-hour forecast period covering Xcel Energy’s service areas. This talk will include descriptions of these capabilities and report on several topics including initial results of next-day forecasts and nowcasts of wind energy ramp events, influence of local observations on forecast skill, and overall lessons learned to date.

Data and Tools | Hydrogen and Fuel Cells | NREL

Science.gov Websites

researchers, developers, investors, and others interested in the viability, analysis, and development of , energy use, and emissions. Alternative Fuels Data Center Tools Collection of tools-calculators -makers reduce petroleum use. FASTSim: Future Automotive Systems Technology Simulator Simulation tool that

One-Dimensional Coupled Ecosystem-Carbon Flux Model for the Simulation of Biogeochemical Parameters at Ocean Weather Station P

NASA Technical Reports Server (NTRS)

Signorini, S.; McClain, C.; Christian, J.; Wong, C. S.

2000-01-01

In this Technical Publication, we describe the model functionality and analyze its application to the seasonal and interannual variations of phytoplankton, nutrients, pCO2 and CO2 concentrations in the eastern subarctic Pacific at Ocean Weather Station P (OWSP, 50 deg. N 145 deg. W). We use a verified one-dimensional ecosystem model, coupled with newly incorporated carbon flux and carbon chemistry components, to simulate 22 years (1958-1980) of pCO2 and CO2 variability at Ocean Weather Station P (OWS P). This relatively long period of simulation verifies and extends the findings of previous studies using an explicit approach for the biological component and realistic coupling with the carbon flux dynamics. The slow currents and the horizontally homogeneous ocean in the subarctic Pacific make OWS P one of the best available candidates for modeling the chemistry of the upper ocean in one dimension. The chlorophyll and ocean currents composite for 1998 illustrates this premise. The chlorophyll concentration map was derived from SeaWiFS data and the currents are from an OGCM simulation (from R. Murtugudde).

A weather-driven model of malaria transmission.

PubMed

Hoshen, Moshe B; Morse, Andrew P

2004-09-06

Climate is a major driving force behind malaria transmission and climate data are often used to account for the spatial, seasonal and interannual variation in malaria transmission. This paper describes a mathematical-biological model of the parasite dynamics, comprising both the weather-dependent within-vector stages and the weather-independent within-host stages. Numerical evaluations of the model in both time and space show that it qualitatively reconstructs the prevalence of infection. A process-based modelling structure has been developed that may be suitable for the simulation of malaria forecasts based on seasonal weather forecasts.

The Regional Healthcare Ecosystem Analyst (RHEA): a simulation modeling tool to assist infectious disease control in a health system.

PubMed

Lee, Bruce Y; Wong, Kim F; Bartsch, Sarah M; Yilmaz, S Levent; Avery, Taliser R; Brown, Shawn T; Song, Yeohan; Singh, Ashima; Kim, Diane S; Huang, Susan S

2013-06-01

As healthcare systems continue to expand and interconnect with each other through patient sharing, administrators, policy makers, infection control specialists, and other decision makers may have to take account of the entire healthcare 'ecosystem' in infection control. We developed a software tool, the Regional Healthcare Ecosystem Analyst (RHEA), that can accept user-inputted data to rapidly create a detailed agent-based simulation model (ABM) of the healthcare ecosystem (ie, all healthcare facilities, their adjoining community, and patient flow among the facilities) of any region to better understand the spread and control of infectious diseases. To demonstrate RHEA's capabilities, we fed extensive data from Orange County, California, USA, into RHEA to create an ABM of a healthcare ecosystem and simulate the spread and control of methicillin-resistant Staphylococcus aureus. Various experiments explored the effects of changing different parameters (eg, degree of transmission, length of stay, and bed capacity). Our model emphasizes how individual healthcare facilities are components of integrated and dynamic networks connected via patient movement and how occurrences in one healthcare facility may affect many other healthcare facilities. A decision maker can utilize RHEA to generate a detailed ABM of any healthcare system of interest, which in turn can serve as a virtual laboratory to test different policies and interventions.

Coupled hydro-meteorological modelling on a HPC platform for high-resolution extreme weather impact study

NASA Astrophysics Data System (ADS)

Zhu, Dehua; Echendu, Shirley; Xuan, Yunqing; Webster, Mike; Cluckie, Ian

2016-11-01

Impact-focused studies of extreme weather require coupling of accurate simulations of weather and climate systems and impact-measuring hydrological models which themselves demand larger computer resources. In this paper, we present a preliminary analysis of a high-performance computing (HPC)-based hydrological modelling approach, which is aimed at utilizing and maximizing HPC power resources, to support the study on extreme weather impact due to climate change. Here, four case studies are presented through implementation on the HPC Wales platform of the UK mesoscale meteorological Unified Model (UM) with high-resolution simulation suite UKV, alongside a Linux-based hydrological model, Hydrological Predictions for the Environment (HYPE). The results of this study suggest that the coupled hydro-meteorological model was still able to capture the major flood peaks, compared with the conventional gauge- or radar-driving forecast, but with the added value of much extended forecast lead time. The high-resolution rainfall estimation produced by the UKV performs similarly to that of radar rainfall products in the first 2-3 days of tested flood events, but the uncertainties particularly increased as the forecast horizon goes beyond 3 days. This study takes a step forward to identify how the online mode approach can be used, where both numerical weather prediction and the hydrological model are executed, either simultaneously or on the same hardware infrastructures, so that more effective interaction and communication can be achieved and maintained between the models. But the concluding comments are that running the entire system on a reasonably powerful HPC platform does not yet allow for real-time simulations, even without the most complex and demanding data simulation part.

Nowcasting in the FROST-2014 Sochi Olympic project

NASA Astrophysics Data System (ADS)

Bica, Benedikt; Wang, Yong; Joe, Paul; Isaac, George; Kiktev, Dmitry; Bocharnikov, Nikolai

2013-04-01

FROST (Forecast and Research: the Olympic Sochi Testbed) 2014 is a WMO WWRP international project aimed at development, implementation, and demonstration of capabilities of short-range numerical weather prediction and nowcasting technologies for mountainous terrain in winter season. Sharp weather contrasts and high spatial and temporal variability are typical for the region of the Sochi-2014 Olympics. Steep mountainous terrain and an intricate mixture of maritime sub-tropical and Alpine environments make weather forecasting in this region extremely challenging. Goals of the FROST-2014 project: • To develop a comprehensive information resource of Alpine winter weather observations; • To improve and exploit: o Nowcasting systems of high impact weather phenomena (precipitation type and intensity, snow levels, visibility, wind speed, direction and gusts) in complex terrain; o High-resolution deterministic and ensemble mesoscale forecasts in winter complex terrain environment; • To improve the understanding of physics of high impact weather phenomena in the region; • To deliver forecasts (Nowcasts) to Olympic weather forecasters and decision makers and assess benefits of forecast improvement. 46 Automatic Meteorological Stations (AMS) were installed in the Olympic region by Roshydromet, by owners of sport venues and by the Megafon corporation, provider of mobile communication services. The time resolution of AMS observations does not exceed 10 minutes. For a subset of the stations it is even equal to 1 min. Data flow from the new dual polarization Doppler weather radar WRM200 in Sochi was organized at the end of 2012. Temperature/humidity and wind profilers and two Micro Rain Radars (MRR) will supplement the network. Nowcasting potential of NWP models participating in the project (COSMO, GEM, WRF, AROME, HARMONIE) is to be assessed for direct and post-processed (e.g. Kalman filter, 1-D model, MOS) model forecasts. Besides the meso-scale models, the specialized nowcasting systems are expected to be used in the project - ABOM, CARDS, INCA, INTW, STEPS, MeteoExpert. FROST-2014 is intended as an 'end-to-end' project. Its products will be used by local forecasters for meteorological support of the Olympics and preceding test sport events. The project is open for new interested participants. Additional information is available at http://frost2014.meteoinfo.ru.

Retrospective Analog Year Analyses Using NASA Satellite Data to Improve USDA's World Agricultural Supply and Demand Estimates

NASA Astrophysics Data System (ADS)

Teng, W. L.; Shannon, H. D.

2011-12-01

The USDA World Agricultural Outlook Board (WAOB) is responsible for monitoring weather and climate impacts on domestic and foreign crop development. One of WAOB's primary goals is to determine the net cumulative effect of weather and climate anomalies on final crop yields. To this end, a broad array of information is consulted, including maps, charts, and time series of recent weather, climate, and crop observations; numerical output from weather and crop models; and reports from the press, USDA attachés, and foreign governments. The resulting agricultural weather assessments are published in the Weekly Weather and Crop Bulletin, to keep farmers, policy makers, and commercial agricultural interests informed of weather and climate impacts on agriculture. Because both the amount and timing of precipitation significantly impact crop yields, WAOB often uses precipitation time series to identify growing seasons with similar weather patterns and help estimate crop yields for the current growing season, based on observed yields in analog years. Although, historically, these analog years are identified through visual inspection, the qualitative nature of this methodology sometimes precludes the definitive identification of the best analog year. One goal of this study is to introduce a more rigorous, statistical approach for identifying analog years. This approach is based on a modified coefficient of determination, termed the analog index (AI). The derivation of AI will be described. Another goal of this study is to compare the performance of AI for time series derived from surface-based observations vs. satellite-based measurements (NASA TRMM and other data). Five study areas and six growing seasons of data were analyzed (2003-2007 as potential analog years and 2008 as the target year). Results thus far show that, for all five areas, crop yield estimates derived from satellite-based precipitation data are closer to measured yields than are estimates derived from surface-based precipitation measurements. Work is continuing to include satellite-based surface soil moisture data and model-assimilated root zone soil moisture. This study is part of a larger effort to improve WAOB estimates by integrating NASA remote sensing observations and research results into WAOB's decision-making environment.

Enhancing USDA's Retrospective Analog Year Analyses Using NASA Satellite Precipitation and Soil Moisture Data

NASA Astrophysics Data System (ADS)

Teng, W. L.; Shannon, H. D.

2013-12-01

The USDA World Agricultural Outlook Board (WAOB) is responsible for monitoring weather and climate impacts on domestic and foreign crop development. One of WAOB's primary goals is to determine the net cumulative effect of weather and climate anomalies on final crop yields. To this end, a broad array of information is consulted, including maps, charts, and time series of recent weather, climate, and crop observations; numerical output from weather and crop models; and reports from the press, USDA attachés, and foreign governments. The resulting agricultural weather assessments are published in the Weekly Weather and Crop Bulletin, to keep farmers, policy makers, and commercial agricultural interests informed of weather and climate impacts on agriculture. Because both the amount and timing of precipitation significantly affect crop yields, WAOB has often, as part of its operational process, used historical time series of surface-based precipitation observations to visually identify growing seasons with similar (analog) weather patterns as, and help estimate crop yields for, the current growing season. As part of a larger effort to improve WAOB estimates by integrating NASA remote sensing observations and research results into WAOB's decision-making environment, a more rigorous, statistical method for identifying analog years was developed. This method, termed the analog index (AI), is based on the Nash-Sutcliffe model efficiency coefficient. The AI was computed for five study areas and six growing seasons of data analyzed (2003-2007 as potential analog years and 2008 as the target year). Previously reported results compared the performance of AI for time series derived from surface-based observations vs. satellite-retrieved precipitation data. Those results showed that, for all five areas, crop yield estimates derived from satellite-retrieved precipitation data are closer to measured yields than are estimates derived from surface-based precipitation observations. Subsequent work has compared the relative performance of AI for time series derived from satellite-retrieved surface soil moisture data and from root zone soil moisture derived from the assimilation of surface soil moisture data into a land surface model. These results, which also showed the potential benefits of satellite data for analog year analyses, will be presented.

Exploring Space Physics Concepts Using Simulation Results

NASA Astrophysics Data System (ADS)

Gross, N. A.

2008-05-01

The Center for Integrated Space Weather Modeling (CISM), a Science and Technology Center (STC) funded by the National Science Foundation, has the goal of developing a suite of integrated physics based computer models of the space environment that can follow the evolution of a space weather event from the Sun to the Earth. In addition to the research goals, CISM is also committed to training the next generation of space weather professionals who are imbued with a system view of space weather. This view should include an understanding of both helio-spheric and geo-space phenomena. To this end, CISM offers a yearly Space Weather Summer School targeted to first year graduate students, although advanced undergraduates and space weather professionals have also attended. This summer school uses a number of innovative pedagogical techniques including devoting each afternoon to a computer lab exercise that use results from research quality simulations and visualization techniques, along with ground based and satellite data to explore concepts introduced during the morning lectures. These labs are suitable for use in wide variety educational settings from formal classroom instruction to outreach programs. The goal of this poster is to outline the goals and content of the lab materials so that instructors may evaluate their potential use in the classroom or other settings.

Bayesian evaluation of budgets for endemic disease control: An example using management changes to reduce milk somatic cell count early in the first lactation of Irish dairy cows.

PubMed

Archer, S C; Mc Coy, F; Wapenaar, W; Green, M J

2014-01-01

The aim of this research was to determine budgets for specific management interventions to control heifer mastitis in Irish dairy herds as an example of evidence synthesis and 1-step Bayesian micro-simulation in a veterinary context. Budgets were determined for different decision makers based on their willingness to pay. Reducing the prevalence of heifers with a high milk somatic cell count (SCC) early in the first lactation could be achieved through herd level management interventions for pre- and peri-partum heifers, however the cost effectiveness of these interventions is unknown. A synthesis of multiple sources of evidence, accounting for variability and uncertainty in the available data is invaluable to inform decision makers around likely economic outcomes of investing in disease control measures. One analytical approach to this is Bayesian micro-simulation, where the trajectory of different individuals undergoing specific interventions is simulated. The classic micro-simulation framework was extended to encompass synthesis of evidence from 2 separate statistical models and previous research, with the outcome for an individual cow or herd assessed in terms of changes in lifetime milk yield, disposal risk, and likely financial returns conditional on the interventions being simultaneously applied. The 3 interventions tested were storage of bedding inside, decreasing transition yard stocking density, and spreading of bedding evenly in the calving area. Budgets for the interventions were determined based on the minimum expected return on investment, and the probability of the desired outcome. Budgets for interventions to control heifer mastitis were highly dependent on the decision maker's willingness to pay, and hence minimum expected return on investment. Understanding the requirements of decision makers and their rational spending limits would be useful for the development of specific interventions for particular farms to control heifer mastitis, and other endemic diseases. Copyright © 2013 The Authors. Published by Elsevier B.V. All rights reserved.

BLAST: Building energy simulation in Hong Kong

NASA Astrophysics Data System (ADS)

Fong, Sai-Keung

1999-11-01

The characteristics of energy use in buildings under local weather conditions were studied and evaluated using the energy simulation program BLAST-3.0. The parameters used in the energy simulation for the study and evaluation include the architectural features, different internal building heat load settings and weather data. In this study, mathematical equations and the associated coefficients useful to the industry were established. A technology for estimating energy use in buildings under local weather conditions was developed by using the results of this study. A weather data file of Typical Meteorological Years (TMY) has been compiled for building energy studies by analyzing and evaluating the weather of Hong Kong from the year 1979 to 1988. The weather data file TMY and the example weather years 1980 and 1988 were used by BLAST-3.0 to evaluate and study the energy use in different buildings. BLAST-3.0 was compared with other building energy simulation and approximation methods: Bin method and Degree Days method. Energy use in rectangular compartments of different volumes varying from 4,000 m3 to 40,000 m3 with different aspect ratios were analyzed. The use of energy in buildings with concrete roofs was compared with those with glass roofs at indoor temperature 21°C, 23°C and 25°C. Correlation relationships among building energy, space volume, monthly mean temperature and solar radiation were derived and investigated. The effects of space volume, monthly mean temperature and solar radiation on building energy were evaluated. The coefficients of the mathematical relationships between space volume and energy use in a building were computed and found satisfactory. The calculated coefficients can be used for quick estimation of energy use in buildings under similar situations. To study energy use in buildings, the cooling load per floor area against room volume was investigated. The case of an air-conditioned single compartment with 5 m ceiling height was evaluated. It was found that the supply of cool air to the lower portion of the compartment provided significant performance of space cooling. The mathematical relationships between different shading patterns and different glass window to wall ratios of single compartments were established to provide a guide for easy approximation of energy use under similar conditions. In addition, the Overall Thermal Transfer Values (OTTV) for the compartments were studied. The monthly and annual energy use of three realistic buildings were investigated. They were a commercial building, an industrial building and a dual-purpose building. The cooling loads per floor area for the buildings were studied and the OTTV were evaluated by two different methods. Sensitivity analysis was carried out to investigate the impact of the parameters of internal heat gains on the energy use of an academic building. It was found that there was major influence of indoor temperature setting on building energy use The performances of using the local weather data file of TMY and example weather years 1980 and 1989 were evaluated. TMY was found to be the most suitable for energy simulation while the weather years 1980 and 1989 yielded good results.

Notional Scoring for Technical Review Weighting As Applied to Simulation Credibility Assessment

NASA Technical Reports Server (NTRS)

Hale, Joseph Peter; Hartway, Bobby; Thomas, Danny

2008-01-01

NASA's Modeling and Simulation Standard requires a credibility assessment for critical engineering data produced by models and simulations. Credibility assessment is thus a "qualifyingfactor" in reporting results from simulation-based analysis. The degree to which assessors should be independent of the simulation developers, users and decision makers is a recurring question. This paper provides alternative "weighting algorithms" for calculating the value-added for independence of the levels of technical review defined for the NASA Modeling and Simulation Standard.

Quantum decision-maker theory and simulation

NASA Astrophysics Data System (ADS)

Zak, Michail; Meyers, Ronald E.; Deacon, Keith S.

2000-07-01

A quantum device simulating the human decision making process is introduced. It consists of quantum recurrent nets generating stochastic processes which represent the motor dynamics, and of classical neural nets describing the evolution of probabilities of these processes which represent the mental dynamics. The autonomy of the decision making process is achieved by a feedback from the mental to motor dynamics which changes the stochastic matrix based upon the probability distribution. This feedback replaces unavailable external information by an internal knowledge- base stored in the mental model in the form of probability distributions. As a result, the coupled motor-mental dynamics is described by a nonlinear version of Markov chains which can decrease entropy without an external source of information. Applications to common sense based decisions as well as to evolutionary games are discussed. An example exhibiting self-organization is computed using quantum computer simulation. Force on force and mutual aircraft engagements using the quantum decision maker dynamics are considered.

Stochastic Hourly Weather Generator HOWGH: Validation and its Use in Pest Modelling under Present and Future Climates

NASA Astrophysics Data System (ADS)

Dubrovsky, M.; Hirschi, M.; Spirig, C.

2014-12-01

To quantify impact of the climate change on a specific pest (or any weather-dependent process) in a specific site, we may use a site-calibrated pest (or other) model and compare its outputs obtained with site-specific weather data representing present vs. perturbed climates. The input weather data may be produced by the stochastic weather generator. Apart from the quality of the pest model, the reliability of the results obtained in such experiment depend on an ability of the generator to represent the statistical structure of the real world weather series, and on the sensitivity of the pest model to possible imperfections of the generator. This contribution deals with the multivariate HOWGH weather generator, which is based on a combination of parametric and non-parametric statistical methods. Here, HOWGH is used to generate synthetic hourly series of three weather variables (solar radiation, temperature and precipitation) required by a dynamic pest model SOPRA to simulate the development of codling moth. The contribution presents results of the direct and indirect validation of HOWGH. In the direct validation, the synthetic series generated by HOWGH (various settings of its underlying model are assumed) are validated in terms of multiple climatic characteristics, focusing on the subdaily wet/dry and hot/cold spells. In the indirect validation, we assess the generator in terms of characteristics derived from the outputs of SOPRA model fed by the observed vs. synthetic series. The weather generator may be used to produce weather series representing present and future climates. In the latter case, the parameters of the generator may be modified by the climate change scenarios based on Global or Regional Climate Models. To demonstrate this feature, the results of codling moth simulations for future climate will be shown. Acknowledgements: The weather generator is developed and validated within the frame of projects WG4VALUE (project LD12029 sponsored by the Ministry of Education, Youth and Sports of CR), and VALUE (COST ES 1102 action).

Development of a standard accelerated weathering test for aggregates using dimethyl sulfoxide (DMSO) : final report.

DOT National Transportation Integrated Search

1986-09-01

A standard accelerated weathering test using Dimethyl Sulfoxide (DMSO) was developed to simulate the chemical degradation of basaltic rocks. After a thorough study of the parameters affecting the current procedure, such as container geometry, aggrega...

Numerical tools to predict the environmental loads for offshore structures under extreme weather conditions

NASA Astrophysics Data System (ADS)

Wu, Yanling

2018-05-01

In this paper, the extreme waves were generated using the open source computational fluid dynamic (CFD) tools — OpenFOAM and Waves2FOAM — using linear and nonlinear NewWave input. They were used to conduct the numerical simulation of the wave impact process. Numerical tools based on first-order (with and without stretching) and second-order NewWave are investigated. The simulation to predict force loading for the offshore platform under the extreme weather condition is implemented and compared.

Ecohydrologic processes and soil thickness feedbacks control limestone-weathering rates in a karst landscape

DOE PAGES

Dong, Xiaoli; Cohen, Matthew J.; Martin, Jonathan B.; ...

2018-05-18

Here, chemical weathering of bedrock plays an essential role in the formation and evolution of Earth's critical zone. Over geologic time, the negative feedback between temperature and chemical weathering rates contributes to the regulation of Earth climate. The challenge of understanding weathering rates and the resulting evolution of critical zone structures lies in complicated interactions and feedbacks among environmental variables, local ecohydrologic processes, and soil thickness, the relative importance of which remains unresolved. We investigate these interactions using a reactive-transport kinetics model, focusing on a low-relief, wetland-dominated karst landscape (Big Cypress National Preserve, South Florida, USA) as a case study.more » Across a broad range of environmental variables, model simulations highlight primary controls of climate and soil biological respiration, where soil thickness both supplies and limits transport of biologically derived acidity. Consequently, the weathering rate maximum occurs at intermediate soil thickness. The value of the maximum weathering rate and the precise soil thickness at which it occurs depend on several environmental variables, including precipitation regime, soil inundation, vegetation characteristics, and rate of groundwater drainage. Simulations for environmental conditions specific to Big Cypress suggest that wetland depressions in this landscape began to form around beginning of the Holocene with gradual dissolution of limestone bedrock and attendant soil development, highlighting large influence of age-varying soil thickness on weathering rates and consequent landscape development. While climatic variables are often considered most important for chemical weathering, our results indicate that soil thickness and biotic activity are equally important. Weathering rates reflect complex interactions among soil thickness, climate, and local hydrologic and biotic processes, which jointly shape the supply and delivery of chemical reactants, and the resulting trajectories of critical zone and karst landscape development.« less

Ecohydrologic processes and soil thickness feedbacks control limestone-weathering rates in a karst landscape

DOE Office of Scientific and Technical Information (OSTI.GOV)

Dong, Xiaoli; Cohen, Matthew J.; Martin, Jonathan B.

Here, chemical weathering of bedrock plays an essential role in the formation and evolution of Earth's critical zone. Over geologic time, the negative feedback between temperature and chemical weathering rates contributes to the regulation of Earth climate. The challenge of understanding weathering rates and the resulting evolution of critical zone structures lies in complicated interactions and feedbacks among environmental variables, local ecohydrologic processes, and soil thickness, the relative importance of which remains unresolved. We investigate these interactions using a reactive-transport kinetics model, focusing on a low-relief, wetland-dominated karst landscape (Big Cypress National Preserve, South Florida, USA) as a case study.more » Across a broad range of environmental variables, model simulations highlight primary controls of climate and soil biological respiration, where soil thickness both supplies and limits transport of biologically derived acidity. Consequently, the weathering rate maximum occurs at intermediate soil thickness. The value of the maximum weathering rate and the precise soil thickness at which it occurs depend on several environmental variables, including precipitation regime, soil inundation, vegetation characteristics, and rate of groundwater drainage. Simulations for environmental conditions specific to Big Cypress suggest that wetland depressions in this landscape began to form around beginning of the Holocene with gradual dissolution of limestone bedrock and attendant soil development, highlighting large influence of age-varying soil thickness on weathering rates and consequent landscape development. While climatic variables are often considered most important for chemical weathering, our results indicate that soil thickness and biotic activity are equally important. Weathering rates reflect complex interactions among soil thickness, climate, and local hydrologic and biotic processes, which jointly shape the supply and delivery of chemical reactants, and the resulting trajectories of critical zone and karst landscape development.« less

Seafloor weathering buffering climate: numerical experiments

NASA Astrophysics Data System (ADS)

Farahat, N. X.; Archer, D. E.; Abbot, D. S.

2013-12-01

Continental silicate weathering is widely held to consume atmospheric CO2 at a rate controlled in part by temperature, resulting in a climate-weathering feedback [Walker et al., 1981]. It has been suggested that weathering of oceanic crust of warm mid-ocean ridge flanks also has a CO2 uptake rate that is controlled by climate [Sleep and Zahnle, 2001; Brady and Gislason, 1997]. Although this effect might not be significant on present-day Earth [Caldeira, 1995], seafloor weathering may be more pronounced during snowball states [Le Hir et al., 2008], during the Archean when seafloor spreading rates were faster [Sleep and Zahnle, 2001], and on waterworld planets [Abbot et al., 2012]. Previous studies of seafloor weathering have made significant contributions using qualitative, generally one-box, models, and the logical next step is to extend this work using a spatially resolved model. For example, experiments demonstrate that seafloor weathering reactions are temperature dependent, but it is not clear whether the deep ocean temperature affects the temperature at which the reactions occur, or if instead this temperature is set only by geothermal processes. Our goal is to develop a 2-D numerical model that can simulate hydrothermal circulation and resulting alteration of oceanic basalts, and can therefore address such questions. A model of diffusive and convective heat transfer in fluid-saturated porous media simulates hydrothermal circulation through porous oceanic basalt. Unsteady natural convection is solved for using a Darcy model of porous media flow that has been extensively benchmarked. Background hydrothermal circulation is coupled to mineral reaction kinetics of basaltic alteration and hydrothermal mineral precipitation. In order to quantify seafloor weathering as a climate-weathering feedback process, this model focuses on hydrothermal reactions that influence carbon uptake as well as ocean alkalinity: silicate rock dissolution, calcium and magnesium leaching reactions, carbonate precipitation, and clay formation.

A Proposal for Modeling Real Hardware, Weather and Marine Conditions for Underwater Sensor Networks

PubMed Central

Climent, Salvador; Capella, Juan Vicente; Blanc, Sara; Perles, Angel; Serrano, Juan José

2013-01-01

Network simulators are useful for researching protocol performance, appraising new hardware capabilities and evaluating real application scenarios. However, these tasks can only be achieved when using accurate models and real parameters that enable the extraction of trustworthy results and conclusions. This paper presents an underwater wireless sensor network ecosystem for the ns-3 simulator. This ecosystem is composed of a new energy-harvesting model and a low-cost, low-power underwater wake-up modem model that, alongside existing models, enables the performance of accurate simulations by providing real weather and marine conditions from the location where the real application is to be deployed. PMID:23748171

Evaluating impacts of different longitudinal driver assistance systems on reducing multi-vehicle rear-end crashes during small-scale inclement weather.

PubMed

Li, Ye; Xing, Lu; Wang, Wei; Wang, Hao; Dong, Changyin; Liu, Shanwen

2017-10-01

Multi-vehicle rear-end (MVRE) crashes during small-scale inclement (SSI) weather cause high fatality rates on freeways, which cannot be solved by traditional speed limit strategies. This study aimed to reduce MVRE crash risks during SSI weather using different longitudinal driver assistance systems (LDAS). The impact factors on MVRE crashes during SSI weather were firstly analyzed. Then, four LDAS, including Forward collision warning (FCW), Autonomous emergency braking (AEB), Adaptive cruise control (ACC) and Cooperative ACC (CACC), were modeled based on a unified platform, the Intelligent Driver Model (IDM). Simulation experiments were designed and a large number of simulations were then conducted to evaluate safety effects of different LDAS. Results indicate that the FCW and ACC system have poor performance on reducing MVRE crashes during SSI weather. The slight improvement of sight distance of FCW and the limitation of perception-reaction time of ACC lead the failure of avoiding MVRE crashes in most scenarios. The AEB system has the better effect due to automatic perception and reaction, as well as performing the full brake when encountering SSI weather. The CACC system has the best performance because wireless communication provides a larger sight distance and a shorter time delay at the sub-second level. Sensitivity analyses also indicated that the larger number of vehicles and speed changes after encountering SSI weather have negative impacts on safety performances. Results of this study provide useful information for accident prevention during SSI weather. Copyright © 2017 Elsevier Ltd. All rights reserved.

Fundamental statistical relationships between monthly and daily meteorological variables: Temporal downscaling of weather based on a global observational dataset

NASA Astrophysics Data System (ADS)

Sommer, Philipp; Kaplan, Jed

2016-04-01

Accurate modelling of large-scale vegetation dynamics, hydrology, and other environmental processes requires meteorological forcing on daily timescales. While meteorological data with high temporal resolution is becoming increasingly available, simulations for the future or distant past are limited by lack of data and poor performance of climate models, e.g., in simulating daily precipitation. To overcome these limitations, we may temporally downscale monthly summary data to a daily time step using a weather generator. Parameterization of such statistical models has traditionally been based on a limited number of observations. Recent developments in the archiving, distribution, and analysis of "big data" datasets provide new opportunities for the parameterization of a temporal downscaling model that is applicable over a wide range of climates. Here we parameterize a WGEN-type weather generator using more than 50 million individual daily meteorological observations, from over 10'000 stations covering all continents, based on the Global Historical Climatology Network (GHCN) and Synoptic Cloud Reports (EECRA) databases. Using the resulting "universal" parameterization and driven by monthly summaries, we downscale mean temperature (minimum and maximum), cloud cover, and total precipitation, to daily estimates. We apply a hybrid gamma-generalized Pareto distribution to calculate daily precipitation amounts, which overcomes much of the inability of earlier weather generators to simulate high amounts of daily precipitation. Our globally parameterized weather generator has numerous applications, including vegetation and crop modelling for paleoenvironmental studies.

Climate Change Boot Camps: Targeting Policy Makers and Outreach Trainers in Arizona to Improve Climate Literacy

NASA Astrophysics Data System (ADS)

Ferguson, D. B.; Guido, Z. S.; Buizer, J.; Roy, M.

2010-12-01

Bringing climate change issues into focus for decision makers is a growing challenge. Decision makers are often confronted with unique informational needs, a lack of useable information, and needs for customized climate change training, among other issues. Despite significant progress in improving climate literacy among certain stakeholders such as water managers, recent reports have highlighted the growing demand for climate-change information in regions and sectors across the US. In recent years many ventures have sprung up to address these gaps and have predominantly focused on K-12 education and resource management agencies such as the National Park Service and National Weather Service. However, two groups that are critical for integrating climate information into actions have received less attention: (1) policy makers and (2) outreach experts, such as Cooperative Extension agents. Climate Change Boot Camps (CCBC) is a joint effort between the Climate Assessment for the Southwest (CLIMAS)—a NOAA Regionally Integrated Sciences and Assessments (RISA) program—and researchers at Arizona State University to diagnose climate literacy and training gaps in Arizona and develop a process that converts these deficiencies into actionable knowledge among the two aforementioned groups. This presentation will highlight the initial phases of the CCBC process, which has as its outcomes the identification of effective strategies for reaching legislators, climate literacy and training needs for both policy makers and trainers, and effective metrics to evaluate the success of these efforts. Specific attention is given to evaluating the process from initial needs assessment to the effectiveness of the workshops. Web curriculum and training models made available on the internet will also be developed, drawing on extensive existing Web resources for other training efforts and converted to meet the needs of these two groups. CCBC will also leverage CLIMAS’ long history of engaging with stakeholders in the Southwest to facilitate to use of climate information in the decision process.

Simulation of three lanes one-way freeway in low visibility weather by possible traffic accidents

NASA Astrophysics Data System (ADS)

Pang, Ming-bao; Zheng, Sha-sha; Cai, Zhang-hui

2015-09-01

The aim of this work is to investigate the traffic impact of low visibility weather on a freeway including the fraction of real vehicle rear-end accidents and road traffic capacity. Based on symmetric two-lane Nagel-Schreckenberg (STNS) model, a cellular automaton model of three-lane freeway mainline with the real occurrence of rear-end accidents in low visibility weather, which considers delayed reaction time and deceleration restriction, was established with access to real-time traffic information of intelligent transportation system (ITS). The characteristics of traffic flow in different visibility weather were discussed via the simulation experiments. The results indicate that incoming flow control (decreasing upstream traffic volume) and inputting variable speed limits (VSL) signal are effective in accident reducing and road actual traffic volume's enhancing. According to different visibility and traffic demand the appropriate control strategies should be adopted in order to not only decrease the probability of vehicle accidents but also avoid congestion.

Making the Case for GeoSTEM Education

NASA Astrophysics Data System (ADS)

Moore, John

2014-05-01

As the national Science-Technology-Engineering-Mathematics (STEM) education policy makers in the United States work through reports, findings, forums, workshops, etc., there emerges an opportunity to present the strong case of why and how the role of the Geosciences community can and should be at the forefront of these discussions. Currently existing within the Geosciences scientific and educational community are policies, frameworks, guidance, innovative technology, and unique interdisciplinary Earth System data sets that will establish a pathway to the role of the Geosciences in the classroom, in the 21st Century workforce, and in society. The question may be raised, "Why GeoSTEM?" But the real question should be … "Why not?" Over the past several years the Geosciences have dominated the news cycle in the United States. As we face future natural and human generated hazards and disasters such as the Gulf Oil Spill, not to mention issues confronting society such as Climate Change, Sustainability and Energy, the Geosciences have a critical role in the public awareness, safety, and national security of our nation. In the past year we have experienced volcanic eruptions, earth¬quakes, tsunamis, hurricanes, tornadoes, wildfires, severe drought and flooding, outbreaks of severe weather. Planet Earth will be monitored, observed, and studied as an Earth System, in real or near real time. Policy-makers, decision-makers, scientists, teachers, students, and citizens will not only participate in the process, but come to use such information and data routinely in their daily lives. 3-D data visualizations, virtual field trips, and interactive imagery from space all will contribute to the doing of real science in real time. Policy-Makers have linked Science, Technology, Engineering, and Mathematics (STEM) Education to United States' future economy and national security. The GeoSTEM community can deliver added value through leveraging current and future Geoscience-related resources that monitor our planet and protect the life and property of our citizens. The integration of a Geoscience and Remote Sensing Laboratory into an existing Earth Science program or a new Earth Systems Science course allows students to acquire the necessary rigorous laboratory skills as required by colleges or universities, while developing and becoming proficient in technological skills using industry standard analysis tools. With the accessibility of real-time or near real time data, students in a GeoSTEM driven course can engage in inquiry-based laboratory experiences focusing on real life applications, both local and global. Developing pathways between geoscientists, researchers, teachers, and students, will create an exchange of information, data, observations, and measurements that will lead to authentic science investigations through the monitoring of weather, water quality, sea surface temperature, coral reefs, marine wildlife, earthquakes, tsunamis, wildfires, air quality, land cover, and much more. Satellite, remote sensing, and geospatial technologies can introduce students and society to data that can inform policy makers and society both now and in the future.

Platinum Alloy Tailored All-Weather Solar Cells for Energy Harvesting from Sun and Rain.

PubMed

Tang, Qunwei; Duan, Yanyan; He, Benlin; Chen, Haiyan

2016-11-07

Solar cells that can harvest energy in all weathers are promising in solving the energy crisis and environmental problems. The power outputs are nearly zero under dark conditions for state-of-the-art solar cells. To address this issue, we present herein a class of platinum alloy (PtM x , M=Ni, Fe, Co, Cu, Mo) tailored all-weather solar cells that can harvest energy from rain and realize photoelectric conversion under sun illumination. By tuning the stoichiometric Pt/M ratio and M species, the optimized solar cell yields a photoelectric conversion efficiency of 10.38 % under simulated sunlight irradiation (AM 1.5, 100 mW cm -2 ) as well as current of 3.90 μA and voltage of 115.52 μV under simulated raindrops. Moreover, the electric signals are highly dependent on the dripping velocity and the concentration of simulated raindrops along with concentrations of cation and anion. © 2016 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

An Overview of NASA's IM&S Verification and Validation Process Plan and Specification for Space Exploration

NASA Technical Reports Server (NTRS)

Gravitz, Robert M.; Hale, Joseph

2006-01-01

NASA's Exploration Systems Mission Directorate (ESMD) is implementing a management approach for modeling and simulation (M&S) that will provide decision-makers information on the model's fidelity, credibility, and quality. This information will allow the decision-maker to understand the risks involved in using a model's results in the decision-making process. This presentation will discuss NASA's approach for verification and validation (V&V) of its models or simulations supporting space exploration. This presentation will describe NASA's V&V process and the associated M&S verification and validation (V&V) activities required to support the decision-making process. The M&S V&V Plan and V&V Report templates for ESMD will also be illustrated.

Evaluation of regional climate simulations for air quality modelling purposes

NASA Astrophysics Data System (ADS)

Menut, Laurent; Tripathi, Om P.; Colette, Augustin; Vautard, Robert; Flaounas, Emmanouil; Bessagnet, Bertrand

2013-05-01

In order to evaluate the future potential benefits of emission regulation on regional air quality, while taking into account the effects of climate change, off-line air quality projection simulations are driven using weather forcing taken from regional climate models. These regional models are themselves driven by simulations carried out using global climate models (GCM) and economical scenarios. Uncertainties and biases in climate models introduce an additional "climate modeling" source of uncertainty that is to be added to all other types of uncertainties in air quality modeling for policy evaluation. In this article we evaluate the changes in air quality-related weather variables induced by replacing reanalyses-forced by GCM-forced regional climate simulations. As an example we use GCM simulations carried out in the framework of the ERA-interim programme and of the CMIP5 project using the Institut Pierre-Simon Laplace climate model (IPSLcm), driving regional simulations performed in the framework of the EURO-CORDEX programme. In summer, we found compensating deficiencies acting on photochemistry: an overestimation by GCM-driven weather due to a positive bias in short-wave radiation, a negative bias in wind speed, too many stagnant episodes, and a negative temperature bias. In winter, air quality is mostly driven by dispersion, and we could not identify significant differences in either wind or planetary boundary layer height statistics between GCM-driven and reanalyses-driven regional simulations. However, precipitation appears largely overestimated in GCM-driven simulations, which could significantly affect the simulation of aerosol concentrations. The identification of these biases will help interpreting results of future air quality simulations using these data. Despite these, we conclude that the identified differences should not lead to major difficulties in using GCM-driven regional climate simulations for air quality projections.

Global Precipitation Measurement mission data released on This Week @NASA - September 5, 2014

NASA Image and Video Library

2014-09-05

Precipitation information from the first six months of the Global Precipitation Measurement Core Observatory mission now is fully available to the public. Launched from Japan in February, the joint NASA and Japan Aerospace Exploration Agency mission works with international partner satellites to produce precise and standardized data sets on worldwide rainfall, snowfall and other precipitation. The data can be used to improve forecasts of extreme weather events like floods and help decision makers worldwide better manage water resources. Also, Earthquake data from the air, Next ISS crew trains, Talking STEM with students and OSIRIS-REx time capsule!

Operational Numerical Weather Prediction at the Met Office and potential ways forward for operational space weather prediction systems

NASA Astrophysics Data System (ADS)

Jackson, David

NICT (National Institute of Information and Communications Technology) has been in charge of space weather forecast service in Japan for more than 20 years. The main target region of the space weather is the geo-space in the vicinity of the Earth where human activities are dominant. In the geo-space, serious damages of satellites, international space stations and astronauts take place caused by energetic particles or electromagnetic disturbances: the origin of the causes is dynamically changing of solar activities. Positioning systems via GPS satellites are also im-portant recently. Since the most significant effect of positioning error comes from disturbances of the ionosphere, it is crucial to estimate time-dependent modulation of the electron density profiles in the ionosphere. NICT is one of the 13 members of the ISES (International Space Environment Service), which is an international assembly of space weather forecast centers under the UNESCO. With help of geo-space environment data exchanging among the member nations, NICT operates daily space weather forecast service every day to provide informa-tion on forecasts of solar flare, geomagnetic disturbances, solar proton event, and radio-wave propagation conditions in the ionosphere. The space weather forecast at NICT is conducted based on the three methodologies: observations, simulations and informatics (OSI model). For real-time or quasi real-time reporting of space weather, we conduct our original observations: Hiraiso solar observatory to monitor the solar activity (solar flare, coronal mass ejection, and so on), domestic ionosonde network, magnetometer HF radar observations in far-east Siberia, and south-east Asia low-latitude ionosonde network (SEALION). Real-time observation data to monitor solar and solar-wind activities are obtained through antennae at NICT from ACE and STEREO satellites. We have a middle-class super-computer (NEC SX-8R) to maintain real-time computer simulations for solar and solar-wind, magnetosphere and ionosphere. The three simulations are directly or indirectly connected each other based on real-time observa-tion data to reproduce a virtual geo-space region on the super-computer. Informatics is a new methodology to make precise forecast of space weather. Based on new information and communication technologies (ICT), it provides more information in both quality and quantity. At NICT, we have been developing a cloud-computing system named "space weather cloud" based on a high-speed network system (JGN2+). Huge-scale distributed storage (1PB), clus-ter computers, visualization systems and other resources are expected to derive new findings and services of space weather forecasting. The final goal of NICT space weather service is to predict near-future space weather conditions and disturbances which will be causes of satellite malfunctions, tele-communication problems, and error of GPS navigations. In the present talk, we introduce our recent activities on the space weather services and discuss how we are going to develop the services from the view points of space science and practical uses.

Earth Observation Data Quality Monitoring and Control: A Case Study of STAR Central Data Repository

NASA Astrophysics Data System (ADS)

Han, W.; Jochum, M.

2017-12-01

Earth observation data quality is very important for researchers and decision makers involved in weather forecasting, severe weather warning, disaster and emergency response, environmental monitoring, etc. Monitoring and control earth observation data quality, especially accuracy, completeness, and timeliness, is very useful in data management and governance to optimize data flow, discover potential transmission issues, and better connect data providers and users. Taking a centralized near real-time satellite data repository, STAR (Center for Satellite Applications and Research of NOAA) Central Data Repository (SCDR), as an example, this paper describes how to develop new mechanism to verify data integrity, check data completeness, and monitor data latency in an operational data management system. Such quality monitoring and control of large volume satellite data help data providers and managers improve data transmission of near real-time satellite data, enhance its acquisition and management, and overcome performance and management issues to better serve research and development activities.

Fate, behaviour and weathering of priority HNS in the marine environment: An online tool.

PubMed

Cunha, Isabel; Oliveira, Helena; Neuparth, Teresa; Torres, Tiago; Santos, Miguel Machado

2016-10-15

Literature data and data obtained with modelling tools were compiled to derive the physicochemical behaviour of 24 priority Hazardous and Noxious Substances (HNS), as a proxy to improve environmental, public health and political issues in relation to HNS spills. Parameters that rule the HNS behaviour in water and those that determine their distribution and persistence in the environment, such as fugacity, physicochemical degradation, biodegradation, bioaccumulation/biotransformation and aquatic toxicity, were selected. Data systematized and produced in the frame of the Arcopol Platform project was made available through a public database (http://www.ciimar.up.pt/hns/substances.php). This tool is expected to assist stakeholders involved in HNS spills preparedness and response, policy makers and legislators, as well as to contribute to a current picture of the scientific knowledge on the fate, behaviour, weathering and toxicity of priority HNS, being essential to support future improvements in maritime safety and coastal pollution response before, during and after spill incidents. Copyright © 2016 Elsevier Ltd. All rights reserved.

Working Toward a Healthy Planet

NASA Technical Reports Server (NTRS)

Maynard, Nancy G.

2003-01-01

Using information from NASA s Earth Science Public Health Applications Program, Dr. Maynard will address how remote sensing data and associated technologies can be used toward a better understanding of the links among human health, the environment and weather/climate - and, how this increased understanding plus improved information sharing can empower local health and environmental decision-makers to better predict climate-related health problems, take preventive measures, and improve response actions. Remotely-sensed data and observations are providing powerful new tools for addressing climate and environment-related human health problems through increased capabilities for monitoring and surveillance of parameters useful to such problems as infectious and vector-borne diseases, air and water quality, harmful algal blooms, UV radiation, contaminant and pathogen transport in air and water, and thermal stress. NASA s multi-disciplinary scientific team is demonstrating how satellites from their unique vantage point in space can serve as sentinels for weather, climate, and health problems through studies on asthma, malaria, Rift Valley Fever, Asian and African dust, and West Nile Virus

Evaluating the effects of terrestrial ecosystems, climate and carbon dioxide on weathering over geological time: a global-scale process-based approach.

PubMed

Taylor, Lyla L; Banwart, Steve A; Valdes, Paul J; Leake, Jonathan R; Beerling, David J

2012-02-19

Global weathering of calcium and magnesium silicate rocks provides the long-term sink for atmospheric carbon dioxide (CO(2)) on a timescale of millions of years by causing precipitation of calcium carbonates on the seafloor. Catchment-scale field studies consistently indicate that vegetation increases silicate rock weathering, but incorporating the effects of trees and fungal symbionts into geochemical carbon cycle models has relied upon simple empirical scaling functions. Here, we describe the development and application of a process-based approach to deriving quantitative estimates of weathering by plant roots, associated symbiotic mycorrhizal fungi and climate. Our approach accounts for the influence of terrestrial primary productivity via nutrient uptake on soil chemistry and mineral weathering, driven by simulations using a dynamic global vegetation model coupled to an ocean-atmosphere general circulation model of the Earth's climate. The strategy is successfully validated against observations of weathering in watersheds around the world, indicating that it may have some utility when extrapolated into the past. When applied to a suite of six global simulations from 215 to 50 Ma, we find significantly larger effects over the past 220 Myr relative to the present day. Vegetation and mycorrhizal fungi enhanced climate-driven weathering by a factor of up to 2. Overall, we demonstrate a more realistic process-based treatment of plant fungal-geosphere interactions at the global scale, which constitutes a first step towards developing 'next-generation' geochemical models.

Evaluating the effects of terrestrial ecosystems, climate and carbon dioxide on weathering over geological time: a global-scale process-based approach

PubMed Central

Taylor, Lyla L.; Banwart, Steve A.; Valdes, Paul J.; Leake, Jonathan R.; Beerling, David J.

2012-01-01

Global weathering of calcium and magnesium silicate rocks provides the long-term sink for atmospheric carbon dioxide (CO2) on a timescale of millions of years by causing precipitation of calcium carbonates on the seafloor. Catchment-scale field studies consistently indicate that vegetation increases silicate rock weathering, but incorporating the effects of trees and fungal symbionts into geochemical carbon cycle models has relied upon simple empirical scaling functions. Here, we describe the development and application of a process-based approach to deriving quantitative estimates of weathering by plant roots, associated symbiotic mycorrhizal fungi and climate. Our approach accounts for the influence of terrestrial primary productivity via nutrient uptake on soil chemistry and mineral weathering, driven by simulations using a dynamic global vegetation model coupled to an ocean–atmosphere general circulation model of the Earth's climate. The strategy is successfully validated against observations of weathering in watersheds around the world, indicating that it may have some utility when extrapolated into the past. When applied to a suite of six global simulations from 215 to 50 Ma, we find significantly larger effects over the past 220 Myr relative to the present day. Vegetation and mycorrhizal fungi enhanced climate-driven weathering by a factor of up to 2. Overall, we demonstrate a more realistic process-based treatment of plant fungal–geosphere interactions at the global scale, which constitutes a first step towards developing ‘next-generation’ geochemical models. PMID:22232768

An experience of knowledge co-production for setting up landslide risk management processes in a critical infrastructure: the case of Campania Region (Southern Italy)

NASA Astrophysics Data System (ADS)

Rianna, Guido; Roca Collell, Marta; Uzielli, Marco; Van Ruiten, Kees; Mercogliano, Paola; Ciervo, Fabio; Reder, Alfredo

2017-04-01

In Campania Region (Southern Italy), expected increases in heavy rainfall events under the effect of climate changes and demographic pressure could entail a growth of occurrence of weather induced landslides and associated damages. Indeed, already in recent years, pyroclastic covers mantling the slopes of a large part of the Region have been affected by numerous events often causing victims and damages to infrastructures serving the urban centers. Due to the strategic relevance of the area, landslide events affecting volcanic layers in Campania Region are one of the five case studies investigated in the FP7 European Project INTACT about the impacts of extreme weather on critical infrastructure. The main aim of INTACT project is to increase the resilience of critical infrastructures (CI) facing extreme weather events improving the awareness of stakeholders and asset managers about such phenomena and their potential variations due to Climate Changes and providing tools to support risk management strategies. A WIKI has been designed as a remote support for all stages of the risk process through brief theoretical explanations (in Wiki style) about tools and methods proposed and reports on the findings and hints returned by case studies investigations. In order to have a product tailored to the needs and background of CI owners, managers and policy makers, an intense effort of knowledge co-production between researchers and stakeholders have been carried out in different case studies through questionnaires, meetings, workshops and/or 1-to-1 interviews. This work presents the different tools and approaches adopted to facilitate the exchange with stakeholders in the Campanian case study such as the "Storytelling approach", aiming to stress the need for a comprehensive and overall approach to the issue between the different disaster management phases (mitigation, preparedness, response and recovery) and actors; the CIRCLE approach developed by Deltares, partner in INTACT consortium, which investigates direct and cascading effects induced by landslide events in pyroclastic cover; pairwise comparisons to identify the more relevant parameters of protection actions against landslide events in pyroclastic soils; and cumulative distribution functions returned by multi model climate simulation ensembles, displaying the occurrence probability of fixed variations in weather-proxy for landslide events, and providing a reliable frame of the current uncertainties in climate projections. The main findings achieved through the application of these tools and methods for the Campanian test case are illustrated and discussed.

A Real-time 3D Visualization of Global MHD Simulation for Space Weather Forecasting

NASA Astrophysics Data System (ADS)

Murata, K.; Matsuoka, D.; Kubo, T.; Shimazu, H.; Tanaka, T.; Fujita, S.; Watari, S.; Miyachi, H.; Yamamoto, K.; Kimura, E.; Ishikura, S.

2006-12-01

Recently, many satellites for communication networks and scientific observation are launched in the vicinity of the Earth (geo-space). The electromagnetic (EM) environments around the spacecraft are always influenced by the solar wind blowing from the Sun and induced electromagnetic fields. They occasionally cause various troubles or damages, such as electrification and interference, to the spacecraft. It is important to forecast the geo-space EM environment as well as the ground weather forecasting. Owing to the recent remarkable progresses of super-computer technologies, numerical simulations have become powerful research methods in the solar-terrestrial physics. For the necessity of space weather forecasting, NICT (National Institute of Information and Communications Technology) has developed a real-time global MHD simulation system of solar wind-magnetosphere-ionosphere couplings, which has been performed on a super-computer SX-6. The real-time solar wind parameters from the ACE spacecraft at every one minute are adopted as boundary conditions for the simulation. Simulation results (2-D plots) are updated every 1 minute on a NICT website. However, 3D visualization of simulation results is indispensable to forecast space weather more accurately. In the present study, we develop a real-time 3D webcite for the global MHD simulations. The 3-D visualization results of simulation results are updated every 20 minutes in the following three formats: (1)Streamlines of magnetic field lines, (2)Isosurface of temperature in the magnetosphere and (3)Isoline of conductivity and orthogonal plane of potential in the ionosphere. For the present study, we developed a 3-D viewer application working on Internet Explorer browser (ActiveX) is implemented, which was developed on the AVS/Express. Numerical data are saved in the HDF5 format data files every 1 minute. Users can easily search, retrieve and plot past simulation results (3D visualization data and numerical data) by using the STARS (Solar-terrestrial data Analysis and Reference System). The STARS is a data analysis system for satellite and ground-based observation data for solar-terrestrial physics.

Application of an interactive water simulation model in urban water management: a case study in Amsterdam.

PubMed

Leskens, J G; Brugnach, M; Hoekstra, A Y

2014-01-01

Water simulation models are available to support decision-makers in urban water management. To use current water simulation models, special expertise is required. Therefore, model information is prepared prior to work sessions, in which decision-makers weigh different solutions. However, this model information quickly becomes outdated when new suggestions for solutions arise and are therefore limited in use. We suggest that new model techniques, i.e. fast and flexible computation algorithms and realistic visualizations, allow this problem to be solved by using simulation models during work sessions. A new Interactive Water Simulation Model was applied for two case study areas in Amsterdam and was used in two workshops. In these workshops, the Interactive Water Simulation Model was positively received. It included non-specialist participants in the process of suggesting and selecting possible solutions and made them part of the accompanying discussions and negotiations. It also provided the opportunity to evaluate and enhance possible solutions more often within the time horizon of a decision-making process. Several preconditions proved to be important for successfully applying the Interactive Water Simulation Model, such as the willingness of the stakeholders to participate and the preparation of different general main solutions that can be used for further iterations during a work session.

Studying the Processes Contributed to the Hairpin Turn of Hurricane Joaquin with WRF numerical simulations and TCI-2015 observations

NASA Astrophysics Data System (ADS)

Pu, Z.; Yu, Y.

2016-12-01

The prediction of Hurricane Joaquin's hairpin clockwise during 1 and 2 October 2015 presents a forecasting challenge during real-time numerical weather prediction, as tracks of several major numerical weather prediction models differ from each other. To investigate the large-scale environment and hurricane inner-core structures related to the hairpin turn of Joaquin, a series of high-resolution mesoscale numerical simulations of Hurricane Joaquin had been performed with an advanced research version of the Weather Research and Forecasting (WRF) model. The outcomes were compared with the observations obtained from the US Office of Naval Research's Tropical Cyclone Intensity (TCI) Experiment during 2015 hurricane season. Specifically, five groups of sensitivity experiments with different cumulus, boundary layer, and microphysical schemes as well as different initial and boundary conditions and initial times in WRF simulations had been performed. It is found that the choice of the cumulus parameterization scheme plays a significant role in reproducing reasonable track forecast during Joaquin's hairpin turn. The mid-level environmental steering flows can be the reason that leads to different tracks in the simulations with different cumulus schemes. In addition, differences in the distribution and amounts of the latent heating over the inner-core region are associated with discrepancies in the simulated intensity among different experiments. Detailed simulation results, comparison with TCI-2015 observations, and comprehensive diagnoses will be presented.

A high-fidelity weather time series generator using the Markov Chain process on a piecewise level

NASA Astrophysics Data System (ADS)

Hersvik, K.; Endrerud, O.-E. V.

2017-12-01

A method is developed for generating a set of unique weather time-series based on an existing weather series. The method allows statistically valid weather variations to take place within repeated simulations of offshore operations. The numerous generated time series need to share the same statistical qualities as the original time series. Statistical qualities here refer mainly to the distribution of weather windows available for work, including durations and frequencies of such weather windows, and seasonal characteristics. The method is based on the Markov chain process. The core new development lies in how the Markov Process is used, specifically by joining small pieces of random length time series together rather than joining individual weather states, each from a single time step, which is a common solution found in the literature. This new Markov model shows favorable characteristics with respect to the requirements set forth and all aspects of the validation performed.

Space Weather Models at the CCMC And Their Capabilities

NASA Technical Reports Server (NTRS)

Hesse, Michael; Rastatter, Lutz; MacNeice, Peter; Kuznetsova, Masha

2007-01-01

The Community Coordinated Modeling Center (CCMC) is a US inter-agency activity aiming at research in support of the generation of advanced space weather models. As one of its main functions, the CCMC provides to researchers the use of space science models, even if they are not model owners themselves. The second focus of CCMC activities is on validation and verification of space weather models, and on the transition of appropriate models to space weather forecast centers. As part of the latter activity, the CCMC develops real-time simulation systems that stress models through routine execution. A by-product of these real-time calculations is the ability to derive model products, which may be useful for space weather operators. In this presentation, we will provide an overview of the community-provided, space weather-relevant, model suite, which resides at CCMC. We will discuss current capabilities, and analyze expected future developments of space weather related modeling.

Modeling the Stability of Volatile Deposits in Lunar Cold Traps

NASA Technical Reports Server (NTRS)

Crider, D. H.; Vondrak, R. R.

2002-01-01

There are several mechanisms acting at the cold traps that can alter the inventory of volatiles there. Primarily, the lunar surface is bombarded by meteoroids which impact, melt, process, and redistribute the regolith. Further, solar wind and magnetospheric ion fluxes are allowed limited access onto the regions in permanent shadow. Also, although cold traps are in the permanent shadow of the Sun, there is a small flux of radiation incident on the regions from interstellar sources. We investigate the effects of these space weathering processes on a deposit of volatiles in a lunar cold trap through simulations. We simulate the development of a column of material near the surface of the Moon resulting from space weathering. This simulation treats a column of material at a lunar cold trap and focuses on the hydrogen content of the column. We model space weathering processes on several time and spatial scales to simulate the constant rain of micrometeoroids as well as sporadic larger impactors occurring near the cold traps to determine the retention efficiency of the cold traps. We perform the Monte Carlo simulation over many columns of material to determine the expectation value for hydrogen content of the top few meters of soil for comparison with Lunar Prospector neutron data.

A weather-driven model of malaria transmission

PubMed Central

Hoshen, Moshe B; Morse, Andrew P

2004-01-01

Background Climate is a major driving force behind malaria transmission and climate data are often used to account for the spatial, seasonal and interannual variation in malaria transmission. Methods This paper describes a mathematical-biological model of the parasite dynamics, comprising both the weather-dependent within-vector stages and the weather-independent within-host stages. Results Numerical evaluations of the model in both time and space show that it qualitatively reconstructs the prevalence of infection. Conclusion A process-based modelling structure has been developed that may be suitable for the simulation of malaria forecasts based on seasonal weather forecasts. PMID:15350206

The quiet revolution of numerical weather prediction.

PubMed

Bauer, Peter; Thorpe, Alan; Brunet, Gilbert

2015-09-03

Advances in numerical weather prediction represent a quiet revolution because they have resulted from a steady accumulation of scientific knowledge and technological advances over many years that, with only a few exceptions, have not been associated with the aura of fundamental physics breakthroughs. Nonetheless, the impact of numerical weather prediction is among the greatest of any area of physical science. As a computational problem, global weather prediction is comparable to the simulation of the human brain and of the evolution of the early Universe, and it is performed every day at major operational centres across the world.

Reducing EnergyPlus Run Time For Code Compliance Tools

DOE Office of Scientific and Technical Information (OSTI.GOV)

Athalye, Rahul A.; Gowri, Krishnan; Schultz, Robert W.

2014-09-12

Integration of the EnergyPlus ™ simulation engine into performance-based code compliance software raises a concern about simulation run time, which impacts timely feedback of compliance results to the user. EnergyPlus annual simulations for proposed and code baseline building models, and mechanical equipment sizing result in simulation run times beyond acceptable limits. This paper presents a study that compares the results of a shortened simulation time period using 4 weeks of hourly weather data (one per quarter), to an annual simulation using full 52 weeks of hourly weather data. Three representative building types based on DOE Prototype Building Models and threemore » climate zones were used for determining the validity of using a shortened simulation run period. Further sensitivity analysis and run time comparisons were made to evaluate the robustness and run time savings of using this approach. The results of this analysis show that the shortened simulation run period provides compliance index calculations within 1% of those predicted using annual simulation results, and typically saves about 75% of simulation run time.« less

Adolescents' perceived risk and personal experience with natural disasters: an evaluation of cognitive heuristics.

PubMed

Greening, L; Dollinger, S J; Pitz, G

1996-02-01

Elevated risk judgments for negative life events have been linked to personal experience with events. We tested the hypothesis that cognitive heuristics are the underlying cognitive mechanism for this relation. The availability (i.e., memory for incidents) and simulation (i.e., imagery) heuristics were evaluated as possible mediators for the relation between personal experience and risk estimates for fatal weather events. Adolescents who had experienced weather disasters estimated their personal risk for weather events. Support was obtained for the simulation heuristic (imagery) as a mediator for the relation. Availability for lightning disaster experience was also found to be a mediator for the relation between personal lightning disaster experience and risk estimate for future events. The implications for risk perception research are discussed.

Thermal Performance of Aged and Weathered Spray-On Foam Insulation (SOFI) Materials Under Cryogenic Vacuum Conditions (Cryostat-4)

NASA Technical Reports Server (NTRS)

2008-01-01

The NASA Cryogenics Test Laboratory at Kennedy Space Center conducted long-term testing of SOFI materials under actual-use cryogenic conditions with Cryostat-4. The materials included in the testing were NCFI 24-124 (acreage foam), BX-265 (close-out foam, including intertank flange and bipod areas), and a potential alternate material, NCFI 27-68, (acreage foam with the flame retardant removed). Specimens of these materials were placed at two locations: a site that simulated aging (the Vehicle Assembly Building [VAB]) and a site that simulated weathering (the Atmospheric Exposure Test Site [beach site]). After aging/weathering intervals of 3, 6, and 12 months, the samples were retrieved and tested for their thermal performance under cryogenic vacuum conditions with test apparatus Cryostat-4.

Contributions of the ARM Program to Radiative Transfer Modeling for Climate and Weather Applications

NASA Technical Reports Server (NTRS)

Mlawer, Eli J.; Iacono, Michael J.; Pincus, Robert; Barker, Howard W.; Oreopoulos, Lazaros; Mitchell, David L.

2016-01-01

Accurate climate and weather simulations must account for all relevant physical processes and their complex interactions. Each of these atmospheric, ocean, and land processes must be considered on an appropriate spatial and temporal scale, which leads these simulations to require a substantial computational burden. One especially critical physical process is the flow of solar and thermal radiant energy through the atmosphere, which controls planetary heating and cooling and drives the large-scale dynamics that moves energy from the tropics toward the poles. Radiation calculations are therefore essential for climate and weather simulations, but are themselves quite complex even without considering the effects of variable and inhomogeneous clouds. Clear-sky radiative transfer calculations have to account for thousands of absorption lines due to water vapor, carbon dioxide, and other gases, which are irregularly distributed across the spectrum and have shapes dependent on pressure and temperature. The line-by-line (LBL) codes that treat these details have a far greater computational cost than can be afforded by global models. Therefore, the crucial requirement for accurate radiation calculations in climate and weather prediction models must be satisfied by fast solar and thermal radiation parameterizations with a high level of accuracy that has been demonstrated through extensive comparisons with LBL codes. See attachment for continuation.

Comparison of Microclimate Simulated weather data to ASHRAE Clear Sky Model and Measured Data

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bhandari, Mahabir S.

In anticipation of emerging global urbanization and its impact on microclimate, a need exists to better understand and quantify microclimate effects on building energy use. Satisfaction of this need will require coordinated research of microclimate impacts on and from “human systems.” The Urban Microclimate and Energy Tool (Urban-MET) project seeks to address this need by quantifying and analyzing the relationships among climatic conditions, urban morphology, land cover, and energy use; and using these relationships to inform energy-efficient urban development and planning. Initial research will focus on analysis of measured and modeled energy efficiency of various building types in selected urbanmore » areas and temporal variations in energy use for different urban morphologies under different microclimatic conditions. In this report, we analyze the differences between microclimate weather data sets for the Oak Ridge National Laboratory campus produced by ENVI-met and Weather Research Forecast (WRF) models, the ASHRAE clear sky which defines the maximum amounts of solar radiation that can be expected, and measured data from a weather station on campus. Errors with climate variables and their impact on building energy consumption will be shown for the microclimate simulations to help prioritize future improvement for use in microclimate simulation impacts to energy use of buildings.« less

Hypothetical scenario exercises to improve planning and readiness for drinking water quality management during extreme weather events.

PubMed

Deere, Daniel; Leusch, Frederic D L; Humpage, Andrew; Cunliffe, David; Khan, Stuart J

2017-03-15

Two hypothetical scenario exercises were designed and conducted to reflect the increasingly extreme weather-related challenges faced by water utilities as the global climate changes. The first event was based on an extreme flood scenario. The second scenario involved a combination of weather events, including a wild forest fire ('bushfire') followed by runoff due to significant rainfall. For each scenario, a panel of diverse personnel from water utilities and relevant agencies (e.g. health departments) formed a hypothetical water utility and associated regulatory body to manage water quality following the simulated extreme weather event. A larger audience participated by asking questions and contributing key insights. Participants were confronted with unanticipated developments as the simulated scenarios unfolded, introduced by a facilitator. Participants were presented with information that may have challenged their conventional experiences regarding operational procedures in order to identify limitations in current procedures, assumptions, and readily available information. The process worked toward the identification of a list of specific key lessons for each event. At the conclusion of each simulation a facilitated discussion was used to establish key lessons of value to water utilities in preparing them for similar future extreme events. Copyright © 2016 Elsevier Ltd. All rights reserved.

Configuring the HYSPLIT Model for National Weather Service Forecast Office and Spaceflight Meteorology Group Applications

NASA Technical Reports Server (NTRS)

Dreher, Joseph; Blottman, Peter F.; Sharp, David W.; Hoeth, Brian; Van Speybroeck, Kurt

2009-01-01

The National Weather Service Forecast Office in Melbourne, FL (NWS MLB) is responsible for providing meteorological support to state and county emergency management agencies across East Central Florida in the event of incidents involving the significant release of harmful chemicals, radiation, and smoke from fires and/or toxic plumes into the atmosphere. NWS MLB uses the National Oceanic and Atmospheric Administration Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model to provide trajectory, concentration, and deposition guidance during such events. Accurate and timely guidance is critical for decision makers charged with protecting the health and well-being of populations at risk. Information that can describe the geographic extent of areas possibly affected by a hazardous release, as well as to indicate locations of primary concern, offer better opportunity for prompt and decisive action. In addition, forecasters at the NWS Spaceflight Meteorology Group (SMG) have expressed interest in using the HYSPLIT model to assist with Weather Flight Rules during Space Shuttle landing operations. In particular, SMG would provide low and mid-level HYSPLIT trajectory forecasts for cumulus clouds associated with smoke plumes, and high-level trajectory forecasts for thunderstorm anvils. Another potential benefit for both NWS MLB and SMG is using the HYSPLIT model concentration and deposition guidance in fog situations.

Integrating NASA Satellite Data Into USDA World Agricultural Outlook Board Decision Making Environment To Improve Agricultural Estimates

NASA Technical Reports Server (NTRS)

Teng, William; Shannon, Harlan; deJeu, Richard; Kempler, Steve

2012-01-01

The USDA World Agricultural Outlook Board (WAOB) is responsible for monitoring weather and climate impacts on domestic and foreign crop development. One of WAOB's primary goals is to determine the net cumulative effect of weather and climate anomalies on final crop yields. To this end, a broad array of information is consulted. The resulting agricultural weather assessments are published in the Weekly Weather and Crop Bulletin, to keep farmers, policy makers, and commercial agricultural interests informed of weather and climate impacts on agriculture. The goal of the current project is to improve WAOB estimates by integrating NASA satellite precipitation and soil moisture observations into WAOB's decision making environment. Precipitation (Level 3 gridded) is from the TRMM Multi-satellite Precipitation Analysis (TMPA). Soil moisture (Level 2 swath and Level 3 gridded) is generated by the Land Parameter Retrieval Model (LPRM) and operationally produced by the NASA Goddard Earth Sciences Data and Information Services Center (GBS DISC). A root zone soil moisture (RZSM) product is also generated, via assimilation of the Level 3 LPRM data by a land surface model (part of a related project). Data services to be available for these products include GeoTIFF, GDS (GrADS Data Server), WMS (Web Map Service), WCS (Web Coverage Service), and NASA Giovanni. Project benchmarking is based on retrospective analyses of WAOB analog year comparisons. The latter are between a given year and historical years with similar weather patterns and estimated crop yields. An analog index (AI) was developed to introduce a more rigorous, statistical approach for identifying analog years. Results thus far show that crop yield estimates derived from TMPA precipitation data are closer to measured yields than are estimates derived from surface-based precipitation measurements. Work is continuing to include LPRM surface soil moisture data and model-assimilated RZSM.

Severe weather investigation using GNSS signals - a new dimension of GNSS meteorology

NASA Astrophysics Data System (ADS)

Rohm, W.; Zhang, K.; Choy, S.; Kuleshov, Y.; Bosy, J.; Kroszczyński, K.

2012-04-01

The Global Navigation Satellite Systems (GNSS) signals transmitted from satellites are subjected to atmospheric delays since the signals have to propagate through different layers of the atmosphere before GNSS receiver receives them. Two major distinctive effects according to the nature of the impact on the signal propagation are the ionosphere which is a dispersive media and the troposphere which is a non-dispersive layer. In this study, our focus of research is concentrated on the troposphere and the severe weather phenomena caused by midlatitude cyclonic storms. GNSS tomography technique is used to investigate both the spatial and temporal structures of a cyclonic storm. New algorithms will be developed based on optimal integrations of various observation techniques, such as ground-based meteorological measurements, radiosonde data, numerical weather prediction (NWP) models, GNSS radio occultation (RO) profiles. Our initial results suggest that the ground-based GNSS CORS stations will play a major role in the integration process. The structure and distribution of the GNSS CORS network and satellite constellations in context of size and resolution of tomography model are investigated along with the a priori information required, observation and estimation time interval and precision and accuracy needs. A number of numerical analyses are carried out using actual measurements in different parts of the world to evaluate the new algorithms developed through international collaboration. It is expected that GNSS tomography with a number of integrated measurements will provide an important insight into the vertical as well as the horizontal structure of different kinds of severe weather phenomena. It is also expected that GNSS tomography will become an important tool for the study of the severe weather processes, such as the development, maturation, and dissipation stages, which is complementary to other meteorological techniques such as weather radars and microwave radiometers. Potential usages of the new technique in real and/or near-real time would provide an exciting opportunity to launch monitoring and warning services that are able to offer vital information for community and decision makers.

Dimensions and dynamics of citizen observatories: The case of online amateur weather networks

NASA Astrophysics Data System (ADS)

Gharesifard, Mohammad; Wehn, Uta; van der Zaag, Pieter

2016-04-01

Crowd-sourced environmental observations are being increasingly considered as having the potential to enhance the spatial and temporal resolution of current data streams from terrestrial and areal sensors. The rapid diffusion of ICTs during the past decades has facilitated the process of data collection and sharing by the general public (so-called citizen science) and has resulted in the formation of various online environmental citizen observatory networks. Online amateur weather networks are a particular example of such ICT-mediated citizen observatories as one of the oldest and most widely practiced citizen science activities. The objective of this paper is to introduce a conceptual framework that enables a systematic review of different dimensions of these mushrooming/expanding networks. These dimensions include the geographic scope and types of network participants; the network's establishment mechanism, revenue stream(s) and existing communication paradigm; efforts required by citizens and support offered by platform providers; and issues such as data accessibility, availability and quality. An in-depth understanding of these dimensions helps to analyze various dynamics such as interactions between different stakeholders, motivations to run these networks, sustainability of the platforms, data ownership and level of transparency of each network. This framework is then utilized to perform a critical and normative review of six existing online amateur weather networks based on publicly available data. The main findings of this analysis suggest that: (1) There are several key stakeholders such as emergency services and local authorities that are not (yet) engaged in these networks. (2) The revenue stream(s) of online amateur weather networks is one of the least discussed but most important dimensions that is crucial for the sustainability of these networks. (3) Although all of the networks included in this study have one or more explicit pattern of two-way communications, there is no sign (yet) of interactive information exchange among the triangle of weather observers, data aggregators and policy makers. KEYWORDS Citizen Science, Citizen Observatories, ICT-enabled citizen participation, online amateur weather networks

Development of a resource modelling tool to support decision makers in pandemic influenza preparedness: The AsiaFluCap Simulator.

PubMed

Stein, Mart Lambertus; Rudge, James W; Coker, Richard; van der Weijden, Charlie; Krumkamp, Ralf; Hanvoravongchai, Piya; Chavez, Irwin; Putthasri, Weerasak; Phommasack, Bounlay; Adisasmito, Wiku; Touch, Sok; Sat, Le Minh; Hsu, Yu-Chen; Kretzschmar, Mirjam; Timen, Aura

2012-10-12

Health care planning for pandemic influenza is a challenging task which requires predictive models by which the impact of different response strategies can be evaluated. However, current preparedness plans and simulations exercises, as well as freely available simulation models previously made for policy makers, do not explicitly address the availability of health care resources or determine the impact of shortages on public health. Nevertheless, the feasibility of health systems to implement response measures or interventions described in plans and trained in exercises depends on the available resource capacity. As part of the AsiaFluCap project, we developed a comprehensive and flexible resource modelling tool to support public health officials in understanding and preparing for surges in resource demand during future pandemics. The AsiaFluCap Simulator is a combination of a resource model containing 28 health care resources and an epidemiological model. The tool was built in MS Excel© and contains a user-friendly interface which allows users to select mild or severe pandemic scenarios, change resource parameters and run simulations for one or multiple regions. Besides epidemiological estimations, the simulator provides indications on resource gaps or surpluses, and the impact of shortages on public health for each selected region. It allows for a comparative analysis of the effects of resource availability and consequences of different strategies of resource use, which can provide guidance on resource prioritising and/or mobilisation. Simulation results are displayed in various tables and graphs, and can also be easily exported to GIS software to create maps for geographical analysis of the distribution of resources. The AsiaFluCap Simulator is freely available software (http://www.cdprg.org) which can be used by policy makers, policy advisors, donors and other stakeholders involved in preparedness for providing evidence based and illustrative information on health care resource capacities during future pandemics. The tool can inform both preparedness plans and simulation exercises and can help increase the general understanding of dynamics in resource capacities during a pandemic. The combination of a mathematical model with multiple resources and the linkage to GIS for creating maps makes the tool unique compared to other available software.

Applying dynamic simulation modeling methods in health care delivery research-the SIMULATE checklist: report of the ISPOR simulation modeling emerging good practices task force.

PubMed

Marshall, Deborah A; Burgos-Liz, Lina; IJzerman, Maarten J; Osgood, Nathaniel D; Padula, William V; Higashi, Mitchell K; Wong, Peter K; Pasupathy, Kalyan S; Crown, William

2015-01-01

Health care delivery systems are inherently complex, consisting of multiple tiers of interdependent subsystems and processes that are adaptive to changes in the environment and behave in a nonlinear fashion. Traditional health technology assessment and modeling methods often neglect the wider health system impacts that can be critical for achieving desired health system goals and are often of limited usefulness when applied to complex health systems. Researchers and health care decision makers can either underestimate or fail to consider the interactions among the people, processes, technology, and facility designs. Health care delivery system interventions need to incorporate the dynamics and complexities of the health care system context in which the intervention is delivered. This report provides an overview of common dynamic simulation modeling methods and examples of health care system interventions in which such methods could be useful. Three dynamic simulation modeling methods are presented to evaluate system interventions for health care delivery: system dynamics, discrete event simulation, and agent-based modeling. In contrast to conventional evaluations, a dynamic systems approach incorporates the complexity of the system and anticipates the upstream and downstream consequences of changes in complex health care delivery systems. This report assists researchers and decision makers in deciding whether these simulation methods are appropriate to address specific health system problems through an eight-point checklist referred to as the SIMULATE (System, Interactions, Multilevel, Understanding, Loops, Agents, Time, Emergence) tool. It is a primer for researchers and decision makers working in health care delivery and implementation sciences who face complex challenges in delivering effective and efficient care that can be addressed with system interventions. On reviewing this report, the readers should be able to identify whether these simulation modeling methods are appropriate to answer the problem they are addressing and to recognize the differences of these methods from other modeling approaches used typically in health technology assessment applications. Copyright © 2015 International Society for Pharmacoeconomics and Outcomes Research (ISPOR). Published by Elsevier Inc. All rights reserved.

Population exposure to hazardous air quality due to the 2015 fires in Equatorial Asia.

PubMed

Crippa, P; Castruccio, S; Archer-Nicholls, S; Lebron, G B; Kuwata, M; Thota, A; Sumin, S; Butt, E; Wiedinmyer, C; Spracklen, D V

2016-11-16

Vegetation and peatland fires cause poor air quality and thousands of premature deaths across densely populated regions in Equatorial Asia. Strong El-Niño and positive Indian Ocean Dipole conditions are associated with an increase in the frequency and intensity of wildfires in Indonesia and Borneo, enhancing population exposure to hazardous concentrations of smoke and air pollutants. Here we investigate the impact on air quality and population exposure of wildfires in Equatorial Asia during Fall 2015, which were the largest over the past two decades. We performed high-resolution simulations using the Weather Research and Forecasting model with Chemistry based on a new fire emission product. The model captures the spatio-temporal variability of extreme pollution episodes relative to space- and ground-based observations and allows for identification of pollution sources and transport over Equatorial Asia. We calculate that high particulate matter concentrations from fires during Fall 2015 were responsible for persistent exposure of 69 million people to unhealthy air quality conditions. Short-term exposure to this pollution may have caused 11,880 (6,153-17,270) excess mortalities. Results from this research provide decision-relevant information to policy makers regarding the impact of land use changes and human driven deforestation on fire frequency and population exposure to degraded air quality.

Population exposure to hazardous air quality due to the 2015 fires in Equatorial Asia

PubMed Central

Crippa, P.; Castruccio, S.; Archer-Nicholls, S.; Lebron, G. B.; Kuwata, M.; Thota, A.; Sumin, S.; Butt, E.; Wiedinmyer, C.; Spracklen, D. V.

2016-01-01

Vegetation and peatland fires cause poor air quality and thousands of premature deaths across densely populated regions in Equatorial Asia. Strong El-Niño and positive Indian Ocean Dipole conditions are associated with an increase in the frequency and intensity of wildfires in Indonesia and Borneo, enhancing population exposure to hazardous concentrations of smoke and air pollutants. Here we investigate the impact on air quality and population exposure of wildfires in Equatorial Asia during Fall 2015, which were the largest over the past two decades. We performed high-resolution simulations using the Weather Research and Forecasting model with Chemistry based on a new fire emission product. The model captures the spatio-temporal variability of extreme pollution episodes relative to space- and ground-based observations and allows for identification of pollution sources and transport over Equatorial Asia. We calculate that high particulate matter concentrations from fires during Fall 2015 were responsible for persistent exposure of 69 million people to unhealthy air quality conditions. Short-term exposure to this pollution may have caused 11,880 (6,153–17,270) excess mortalities. Results from this research provide decision-relevant information to policy makers regarding the impact of land use changes and human driven deforestation on fire frequency and population exposure to degraded air quality. PMID:27848989

A Socio-Hydrological Model of the Voluntary Urban Water Conservation Behavior during Droughts

NASA Astrophysics Data System (ADS)

Sangwan, N.; Eisma, J. A.; Sung, K.; Yu, D. J.

2016-12-01

Several cities across the globe are increasingly struggling to meet the water demands of their population. By 2050, nearly 160 million urban dwellers are likely to face perennial water shortage due to ever rising population numbers and climate change. As observed once again during recent drought in California, voluntary water conservation is a key approach for managing urban water availability during periods of constrained supply. It relies on behavioral adaptation that is critical for long-term reductions in water use and building drought resilient communities. Strong interdependencies between human group behavior and regional hydrology in this context entail that the two components be coupled together in a socio-hydrology model to fully understand the dynamics of urban water systems. This work proposes a conceptual framework for one such model and simulates the dynamics of a voluntary conservation program in Marin Municipal Water District, California using dynamic systems modeling approach. Through this model, we plan to assess the effects of different social factors (such as social concern and conformist tendencies) and climato-hydrological conditions (viz. storage levels and weather forecast) on the trajectory of a voluntary conservation program. Our preliminary results have indicated several `tipping points' which can be capitalized on by policy makers to boost conservation at low social costs.

The Effect of NEXRAD Image Looping and National Convective Weather Forecast Product on Pilot Decision Making in the Use of a Cockpit Weather Information Display

NASA Technical Reports Server (NTRS)

Burgess, Malcolm A.; Thomas, Rickey P.

2004-01-01

This experiment investigated improvements to cockpit weather displays to better support the hazardous weather avoidance decision-making of general aviation pilots. Forty-eight general aviation pilots were divided into three equal groups and presented with a simulated flight scenario involving embedded convective activity. The control group had access to conventional sources of pre-flight and in-flight weather products. The two treatment groups were provided with a weather display that presented NEXRAD mosaic images, graphic depiction of METARs, and text METARs. One treatment group used a NEXRAD image looping feature and the second group used the National Convective Weather Forecast (NCWF) product overlaid on the NEXRAD display. Both of the treatment displays provided a significant increase in situation awareness but, they provided incomplete information required to deal with hazardous convective weather conditions, and would require substantial pilot training to permit their safe and effective use.

Parameter sensitivity analysis for pesticide impacts on honeybee colonies

EPA Science Inventory

We employ Monte Carlo simulation and linear sensitivity analysis techniques to describe the dynamics of a bee exposure model, VarroaPop. Daily simulations are performed that simulate hive population trajectories, taking into account queen strength, foraging success, weather, colo...

Characterization of Minnesota lunar simulant for plant growth

NASA Technical Reports Server (NTRS)

Oglesby, James P.; Lindsay, Willard L.; Sadeh, Willy Z.

1993-01-01

Processing of lunar regolith into a plant growth medium is crucial in the development of a regenerative life support system for a lunar base. Plants, which are the core of such a system, produce food and oxygen for humans and, at the same time, consume carbon dioxide. Because of the scarcity of lunar regolith, simulants must be used to infer its properties and to develop procedures for weathering and chemical analyses. The Minnesota Lunar Simulant (MLS) has been identified to date as the best available simulant for lunar regolith. Results of the dissolution studies reveal that appropriately fertilized MLS can be a suitable medium for plant growth. The techniques used in conducting these studies can be extended to investigate the suitability of actual lunar regolith as a plant growth medium. Dissolution experiments were conducted using the MLS to determine its nutritional and toxicity characteristics for plant growth and to develop weathering and chemical analysis techniques. Two weathering regimes, one with water and one with dilute organic acids simulating the root rhizosphere microenvironment, were investigated. Elemental concentrations were measured using inductively-coupled-plasma (ICP) emission spectrometry and ion chromatography (IC). The geochemical speciation model, MINTEQA2, was used to determine the major solution species and the minerals controlling them. Acidification was found to be a useful method for increasing cation concentrations to meaningful levels. Initial results indicate that MLS weathers to give neutral to slightly basic solutions which contain acceptable amounts of the essential elements required for plant nutrition (i.e., potassium, calcium, magnesium, sulfur, zinc, sodium, silicon, manganese, copper, chlorine, boron, molybdenum, and cobalt). Elements that need to be supplemented include carbon, nitrogen, and perhaps phosphorus and iron. Trace metals in solution were present at nontoxic levels.

Uranium adsorption on weathered schist - Intercomparison of modeling approaches

USGS Publications Warehouse

Payne, T.E.; Davis, J.A.; Ochs, M.; Olin, M.; Tweed, C.J.

2004-01-01

Experimental data for uranium adsorption on a complex weathered rock were simulated by twelve modelling teams from eight countries using surface complexation (SC) models. This intercomparison was part of an international project to evaluate the present capabilities and limitations of SC models in representing sorption by geologic materials. The models were assessed in terms of their predictive ability, data requirements, number of optimised parameters, ability to simulate diverse chemical conditions and transferability to other substrates. A particular aim was to compare the generalised composite (GC) and component additivity (CA) approaches for modelling sorption by complex substrates. Both types of SC models showed a promising capability to simulate sorption data obtained across a range of chemical conditions. However, the models incorporated a wide variety of assumptions, particularly in terms of input parameters such as site densities and surface site types. Furthermore, the methods used to extrapolate the model simulations to different weathered rock samples collected at the same field site tended to be unsatisfactory. The outcome of this modelling exercise provides an overview of the present status of adsorption modelling in the context of radionuclide migration as practised in a number of countries worldwide.

Simulating cyber warfare and cyber defenses: information value considerations

NASA Astrophysics Data System (ADS)

Stytz, Martin R.; Banks, Sheila B.

2011-06-01

Simulating cyber warfare is critical to the preparation of decision-makers for the challenges posed by cyber attacks. Simulation is the only means we have to prepare decision-makers for the inevitable cyber attacks upon the information they will need for decision-making and to develop cyber warfare strategies and tactics. Currently, there is no theory regarding the strategies that should be used to achieve objectives in offensive or defensive cyber warfare, and cyber warfare occurs too rarely to use real-world experience to develop effective strategies. To simulate cyber warfare by affecting the information used for decision-making, we modify the information content of the rings that are compromised during in a decision-making context. The number of rings affected and value of the information that is altered (i.e., the closeness of the ring to the center) is determined by the expertise of the decision-maker and the learning outcome(s) for the simulation exercise. We determine which information rings are compromised using the probability that the simulated cyber defenses that protect each ring can be compromised. These probabilities are based upon prior cyber attack activity in the simulation exercise as well as similar real-world cyber attacks. To determine which information in a compromised "ring" to alter, the simulation environment maintains a record of the cyber attacks that have succeeded in the simulation environment as well as the decision-making context. These two pieces of information are used to compute an estimate of the likelihood that the cyber attack can alter, destroy, or falsify each piece of information in a compromised ring. The unpredictability of information alteration in our approach adds greater realism to the cyber event. This paper suggests a new technique that can be used for cyber warfare simulation, the ring approach for modeling context-dependent information value, and our means for considering information value when assigning cyber resources to information protection tasks. The first section of the paper introduces the cyber warfare simulation challenge and the reasons for its importance. The second section contains background information related to our research. The third section contains a discussion of the information ring technique and its use for simulating cyber attacks. The fourth section contains a summary and suggestions for research.

Distributed Web-Based Expert System for Launch Operations

NASA Technical Reports Server (NTRS)

Bardina, Jorge E.; Thirumalainambi, Rajkumar

2005-01-01

The simulation and modeling of launch operations is based on a representation of the organization of the operations suitable to experiment of the physical, procedural, software, hardware and psychological aspects of space flight operations. The virtual test bed consists of a weather expert system to advice on the effect of weather to the launch operations. It also simulates toxic gas dispersion model, and the risk impact on human health. Since all modeling and simulation is based on the internet, it could reduce the cost of operations of launch and range safety by conducting extensive research before a particular launch. Each model has an independent decision making module to derive the best decision for launch.

Nesting large-eddy simulations within mesoscale simulations for wind energy applications

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lundquist, J K; Mirocha, J D; Chow, F K

2008-09-08

With increasing demand for more accurate atmospheric simulations for wind turbine micrositing, for operational wind power forecasting, and for more reliable turbine design, simulations of atmospheric flow with resolution of tens of meters or higher are required. These time-dependent large-eddy simulations (LES), which resolve individual atmospheric eddies on length scales smaller than turbine blades and account for complex terrain, are possible with a range of commercial and open-source software, including the Weather Research and Forecasting (WRF) model. In addition to 'local' sources of turbulence within an LES domain, changing weather conditions outside the domain can also affect flow, suggesting thatmore » a mesoscale model provide boundary conditions to the large-eddy simulations. Nesting a large-eddy simulation within a mesoscale model requires nuanced representations of turbulence. Our group has improved the Weather and Research Forecasting model's (WRF) LES capability by implementing the Nonlinear Backscatter and Anisotropy (NBA) subfilter stress model following Kosovic (1997) and an explicit filtering and reconstruction technique to compute the Resolvable Subfilter-Scale (RSFS) stresses (following Chow et al, 2005). We have also implemented an immersed boundary method (IBM) in WRF to accommodate complex terrain. These new models improve WRF's LES capabilities over complex terrain and in stable atmospheric conditions. We demonstrate approaches to nesting LES within a mesoscale simulation for farms of wind turbines in hilly regions. Results are sensitive to the nesting method, indicating that care must be taken to provide appropriate boundary conditions, and to allow adequate spin-up of turbulence in the LES domain.« less

Approaches to evaluating weathering effects on release of engineered nanomaterials from solid matrices

EPA Science Inventory

Increased production and use of engineered nanomaterials (ENMs) over the past decade has increased the potential for the transport and release of these materials into the environment. Here we present results of two separate studies designed to simulate the effects of weathering o...

Pilot Inter-Laboratory Studies for Evaluating Weathering-Induced Release of Carbon Nanotubes from Solid Matrices

EPA Science Inventory

Nanomaterials are increasingly being used in polymer composites to enhance the properties of these materials. Here we present results of a pilot inter-laboratory study to simulate the effects of weathering on the potential release of multiwalled carbon nanotubes (MWCNT) from thei...

Activities of NICT space weather project

NASA Astrophysics Data System (ADS)

Murata, Ken T.; Nagatsuma, Tsutomu; Watari, Shinichi; Shinagawa, Hiroyuki; Ishii, Mamoru

NICT (National Institute of Information and Communications Technology) has been in charge of space weather forecast service in Japan for more than 20 years. The main target region of the space weather is the geo-space in the vicinity of the Earth where human activities are dominant. In the geo-space, serious damages of satellites, international space stations and astronauts take place caused by energetic particles or electromagnetic disturbances: the origin of the causes is dynamically changing of solar activities. Positioning systems via GPS satellites are also im-portant recently. Since the most significant effect of positioning error comes from disturbances of the ionosphere, it is crucial to estimate time-dependent modulation of the electron density profiles in the ionosphere. NICT is one of the 13 members of the ISES (International Space Environment Service), which is an international assembly of space weather forecast centers under the UNESCO. With help of geo-space environment data exchanging among the member nations, NICT operates daily space weather forecast service every day to provide informa-tion on forecasts of solar flare, geomagnetic disturbances, solar proton event, and radio-wave propagation conditions in the ionosphere. The space weather forecast at NICT is conducted based on the three methodologies: observations, simulations and informatics (OSI model). For real-time or quasi real-time reporting of space weather, we conduct our original observations: Hiraiso solar observatory to monitor the solar activity (solar flare, coronal mass ejection, and so on), domestic ionosonde network, magnetometer HF radar observations in far-east Siberia, and south-east Asia low-latitude ionosonde network (SEALION). Real-time observation data to monitor solar and solar-wind activities are obtained through antennae at NICT from ACE and STEREO satellites. We have a middle-class super-computer (NEC SX-8R) to maintain real-time computer simulations for solar and solar-wind, magnetosphere and ionosphere. The three simulations are directly or indirectly connected each other based on real-time observa-tion data to reproduce a virtual geo-space region on the super-computer. Informatics is a new methodology to make precise forecast of space weather. Based on new information and communication technologies (ICT), it provides more information in both quality and quantity. At NICT, we have been developing a cloud-computing system named "space weather cloud" based on a high-speed network system (JGN2+). Huge-scale distributed storage (1PB), clus-ter computers, visualization systems and other resources are expected to derive new findings and services of space weather forecasting. The final goal of NICT space weather service is to predict near-future space weather conditions and disturbances which will be causes of satellite malfunctions, tele-communication problems, and error of GPS navigations. In the present talk, we introduce our recent activities on the space weather services and discuss how we are going to develop the services from the view points of space science and practical uses.

Simulation tests to assess occupational exposure to airborne asbestos from artificially weathered asphalt-based roofing products.

PubMed

Sheehan, Patrick; Mowat, Fionna; Weidling, Ryan; Floyd, Mark

2010-11-01

Historically, asbestos-containing roof cements and coatings were widely used for patching and repairing leaks. Although fiber releases from these materials when newly applied have been studied, there are virtually no useful data on airborne asbestos fiber concentrations associated with the repair or removal of weathered roof coatings and cements, as most studies involve complete tear-out of old roofs, rather than only limited removal of the roof coating or cement during a repair job. This study was undertaken to estimate potential chrysotile asbestos fiber exposures specific to these types of roofing products following artificially enhanced weathering. Roof panels coated with plastic roof cement and fibered roof coating were subjected to intense solar radiation and daily simulated precipitation events for 1 year and then scraped to remove the weathered materials to assess chrysotile fiber release and potential worker exposures. Analysis of measured fiber concentrations for hand scraping of the weathered products showed 8-h time-weighted average concentrations that were well below the current Occupational Safety and Health Administration permissible exposure limit for asbestos. There was, however, visibly more dust and a few more fibers collected during the hand scraping of weathered products compared to the cured products previously tested. There was a notable difference between fibers released from weathered and cured roofing products. In weathered samples, a large fraction of chrysotile fibers contained low concentrations of or essentially no magnesium and did not meet the spectral, mineralogical, or morphological definitions of chrysotile asbestos. The extent of magnesium leaching from chrysotile fibers is of interest because several researchers have reported that magnesium-depleted chrysotile fibers are less toxic and produce fewer mesothelial tumors in animal studies than normal chrysotile fibers.

Technical evaluation report, AGARD Fluid Dynamics Panel Symposium on Effects of Adverse Weather on Aerodynamics

NASA Technical Reports Server (NTRS)

Reinmann, J. J.

1991-01-01

The purpose of the meeting on Effects of Adverse Weather on Aerodynamics was to provide an update of the stae-of-the-art with respect to the prediction, simulation, and measurement of the effects of icing, anti-icing fluids, and various precipitation on the aerodynamic characteristics of flight vehicles. Sessions were devoted to introductory and survey papers and icing certification issues, to analytical and experimental simulation of ice frost contamination and its effects of aerodynamics, and to the effects of heavy rain and deicing/anti-icing fluids.

Towards Developing a Regional Drought Information System for Lower Mekong

NASA Astrophysics Data System (ADS)

Dutta, R.; Jayasinghe, S.; Basnayake, S. B.; Apirumanekul, C.; Pudashine, J.; Granger, S. L.; Andreadis, K.; Das, N. N.

2016-12-01

With the climate and weather patterns changing over the years, the Lower Mekong Basin have been experiencing frequent and prolonged droughts resulting in severe damage to the agricultural sector affecting food security and livelihoods of the farming community. However, the Regional Drought Information System (RDIS) for Lower Mekong countries would help prepare vulnerable communities from frequent and severe droughts through monitoring, assessing and forecasting of drought conditions and allowing decision makers to take effective decisions in terms of providing early warning, incentives to farmers, and adjustments to cropping calendars and so on. The RDIS is an integrated system that is being designed for drought monitoring, analysis and forecasting based on the need to meet the growing demand of an effective monitoring system for drought by the lower Mekong countries. The RDIS is being built on four major components that includes earth observation component, meteorological data component, database storage and Regional Hydrologic Extreme Assessment System (RHEAS) framework while the outputs from the system will be made open access to the public through a web-based user interface. The system will run on the RHEAS framework that allows both nowcasting and forecasting using hydrological and crop simulation models such as the Variable Infiltration Capacity (VIC) model and the Decision Support System for Agro-Technology Transfer (DSSAT) model respectively. The RHEAS allows for a tightly constrained observation based drought and crop yield information system that can provide customized outputs on drought that includes root zone soil moisture, Standard Precipitation Index (SPI), Standard Runoff Index (SRI), Palmer Drought Severity Index (PDSI) and Crop Yield and can integrate remote sensing products, along with evapotranspiration and soil moisture data. The anticipated outcomes from the RDIS is to improve the operational, technological and institutional capabilities of lower Mekong countries to prepare for and respond towards drought situations and providing policy makers with current and forecast drought indices for decision making on adjusting cropping calendars as well as planning short and long term mitigation measures.

High resolution regional climate simulation of the Hawaiian Islands - Validation of the historical run from 2003 to 2012

NASA Astrophysics Data System (ADS)

Xue, L.; Newman, A. J.; Ikeda, K.; Rasmussen, R.; Clark, M. P.; Monaghan, A. J.

2016-12-01

A high-resolution (a 1.5 km grid spacing domain nested within a 4.5 km grid spacing domain) 10-year regional climate simulation over the entire Hawaiian archipelago is being conducted at the National Center for Atmospheric Research (NCAR) using the Weather Research and Forecasting (WRF) model version 3.7.1. Numerical sensitivity simulations of the Hawaiian Rainband Project (HaRP, a filed experiment from July to August in 1990) showed that the simulated precipitation properties are sensitive to initial and lateral boundary conditions, sea surface temperature (SST), land surface models, vertical resolution and cloud droplet concentration. The validations of model simulated statistics of the trade wind inversion, temperature, wind field, cloud cover, and precipitation over the islands against various observations from soundings, satellites, weather stations and rain gauges during the period from 2003 to 2012 will be presented at the meeting.

Large-eddy simulations of a Salt Lake Valley cold-air pool

NASA Astrophysics Data System (ADS)

Crosman, Erik T.; Horel, John D.

2017-09-01

Persistent cold-air pools are often poorly forecast by mesoscale numerical weather prediction models, in part due to inadequate parameterization of planetary boundary-layer physics in stable atmospheric conditions, and also because of errors in the initialization and treatment of the model surface state. In this study, an improved numerical simulation of the 27-30 January 2011 cold-air pool in Utah's Great Salt Lake Basin is obtained using a large-eddy simulation with more realistic surface state characterization. Compared to a Weather Research and Forecasting model configuration run as a mesoscale model with a planetary boundary-layer scheme where turbulence is highly parameterized, the large-eddy simulation more accurately captured turbulent interactions between the stable boundary-layer and flow aloft. The simulations were also found to be sensitive to variations in the Great Salt Lake temperature and Salt Lake Valley snow cover, illustrating the importance of land surface state in modelling cold-air pools.

All Roads Lead to Computing: Making, Participatory Simulations, and Social Computing as Pathways to Computer Science

ERIC Educational Resources Information Center

Brady, Corey; Orton, Kai; Weintrop, David; Anton, Gabriella; Rodriguez, Sebastian; Wilensky, Uri

2017-01-01

Computer science (CS) is becoming an increasingly diverse domain. This paper reports on an initiative designed to introduce underrepresented populations to computing using an eclectic, multifaceted approach. As part of a yearlong computing course, students engage in Maker activities, participatory simulations, and computing projects that…

A Special Education Systems Simulation Model: Teacher Training Emphasis.

ERIC Educational Resources Information Center

Jones, Wayne; And Others

The authors illustrate the application of a systems approach for educational decision-makers through utilization of a special education systems simulation model with emphasis on teacher training. It is noted that the model provides a procedure to answer "what if" type questions before actually implementing a proposed program. Discussed are the…

Validation of Noah-simulated Soil Temperature in the North American Land Data Assimilation System Phase 2

DOE Office of Scientific and Technical Information (OSTI.GOV)

Xia, Youlong; Ek, Michael; Sheffield, Justin

2013-02-25

Soil temperature can exhibit considerable memory from weather and climate signals and is among the most important initial conditions in numerical weather and climate models. Consequently, a more accurate long-term land surface soil temperature dataset is needed to improve weather and climate simulation and prediction, and is also important for the simulation of agricultural crop yield and ecological processes. The North-American Land Data Assimilation (NLDAS) Phase 2 (NLDAS-2) has generated 31-years (1979-2009) of simulated hourly soil temperature data with a spatial resolution of 1/8o. This dataset has not been comprehensively evaluated to date. Thus, the ultimate purpose of the presentmore » work is to assess Noah-simulated soil temperature for different soil depths and timescales. We used long-term (1979-2001) observed monthly mean soil temperatures from 137 cooperative stations over the United States to evaluate simulated soil temperature for three soil layers (0-10 cm, 10-40 cm, 40-100 cm) for annual and monthly timescales. We used short-term (1997-1999) observed soil temperature from 72 Oklahoma Mesonet stations to validate simulated soil temperatures for three soil layers and for daily and hourly timescales. The results showed that the Noah land surface model (Noah LSM) generally matches observed soil temperature well for different soil layers and timescales. At greater depths, the simulation skill (anomaly correlation) decreased for all time scales. The monthly mean diurnal cycle difference between simulated and observed soil temperature revealed large midnight biases in the cold season due to small downward longwave radiation and issues related to model parameters.« less

Assessing Climate Change Impacts for Military Installations in the Southwest United States During the Warm Season

NASA Astrophysics Data System (ADS)

Castro, C.

2013-05-01

Arid and semi-arid regions are experiencing some of the most adverse impacts of climate change with increased heat waves, droughts, and extreme weather. These events will likely exacerbate socioeconomic and political instabilities in regions where the United States has vital strategic interests and ongoing military operations. The Southwest U.S. is strategically important in that it houses some of the most spatially expansive and important military installations in the country. The majority of severe weather events in the Southwest occur in association with the North American monsoon system (NAMS), and current observational record has shown a 'wet gets wetter and dry gets drier' global monsoon precipitation trend. We seek to evaluate the warm season extreme weather projection in the Southwest U.S., and how the extremes can affect Department of Defense (DoD) military facilities in that region. A baseline methodology is being developed to select extreme warm season weather events based on historical sounding data and moisture surge observations from Gulf of California. Numerical Weather Prediction (NWP)-type high resolution simulations will be performed for the extreme events identified from Weather Research and Forecast (WRF) model simulations initiated from IPCC GCM and NCAR Reanalysis data in both climate control and climate change periods. The magnitude in extreme event changes will be analyzed, and the synoptic forcing patterns of the future severe thunderstorms will provide a guide line to assess if the military installations in the Southwest will become more or less susceptible to severe weather in the future.

Long-term ensemble forecast of snowmelt inflow into the Cheboksary Reservoir under two different weather scenarios

NASA Astrophysics Data System (ADS)

Gelfan, Alexander; Moreydo, Vsevolod; Motovilov, Yury; Solomatine, Dimitri P.

2018-04-01

A long-term forecasting ensemble methodology, applied to water inflows into the Cheboksary Reservoir (Russia), is presented. The methodology is based on a version of the semi-distributed hydrological model ECOMAG (ECOlogical Model for Applied Geophysics) that allows for the calculation of an ensemble of inflow hydrographs using two different sets of weather ensembles for the lead time period: observed weather data, constructed on the basis of the Ensemble Streamflow Prediction methodology (ESP-based forecast), and synthetic weather data, simulated by a multi-site weather generator (WG-based forecast). We have studied the following: (1) whether there is any advantage of the developed ensemble forecasts in comparison with the currently issued operational forecasts of water inflow into the Cheboksary Reservoir, and (2) whether there is any noticeable improvement in probabilistic forecasts when using the WG-simulated ensemble compared to the ESP-based ensemble. We have found that for a 35-year period beginning from the reservoir filling in 1982, both continuous and binary model-based ensemble forecasts (issued in the deterministic form) outperform the operational forecasts of the April-June inflow volume actually used and, additionally, provide acceptable forecasts of additional water regime characteristics besides the inflow volume. We have also demonstrated that the model performance measures (in the verification period) obtained from the WG-based probabilistic forecasts, which are based on a large number of possible weather scenarios, appeared to be more statistically reliable than the corresponding measures calculated from the ESP-based forecasts based on the observed weather scenarios.

Will climate change affect weather types associated with flooding in the Elbe river basin?

NASA Astrophysics Data System (ADS)

Nissen, Katrin M.; Pardowitz, Tobias; Ulbrich, Uwe; Nied, Manuela

2013-04-01

This study investigates the effects of anthropogenic climate change on weather types associated with flooding in the Elbe river basin. The study is based on an ensemble of 3 simulations with the ECHAM5 MPIOM coupled model forced with historical and SRES A1B greenhouse gas concentrations. Relevant weather types, occuring in association with recent flood events, are identified in the ERA40 reanalysis data set. The weather types are classified with the SANDRA cluster algorithm. Distributions of tropospheric humidity content, 500 hPa geopotential height and 500 hPa temperature over Europe are taken as input parameters. 8 (out of 40) weather types are found to be associated with flooding events in the Elbe river basin. The majority of these (6) typically occur during winter, while 2 are warm season patterns. Downscaling reveals characteristic precipitation anomalies associated with the individual patterns. The 8 flood relevant weather types are then identified in the ECHAM5 simulations. The effect of climate change on these patterns is investigated by comparing the last 30 years of the previous century to the last 30 years of the 21st century. According to the model the frequency of most patterns will not change. 5 patterns may experience a statistically significant increase in the mean precipitation over the catchment area and 4 patterns an increase in extreme precipitation. Persistence may slightly decrease for 2 patterns and remain unchanged for the others. Overall, this indicates a moderate increase in the risk for Elbe river flooding, related to changes in the weather patterns, in the coming decades.

Understanding the weather signal in national crop-yield variability

NASA Astrophysics Data System (ADS)

Frieler, Katja; Schauberger, Bernhard; Arneth, Almut; Balkovič, Juraj; Chryssanthacopoulos, James; Deryng, Delphine; Elliott, Joshua; Folberth, Christian; Khabarov, Nikolay; Müller, Christoph; Olin, Stefan; Pugh, Thomas A. M.; Schaphoff, Sibyll; Schewe, Jacob; Schmid, Erwin; Warszawski, Lila; Levermann, Anders

2017-06-01

Year-to-year variations in crop yields can have major impacts on the livelihoods of subsistence farmers and may trigger significant global price fluctuations, with severe consequences for people in developing countries. Fluctuations can be induced by weather conditions, management decisions, weeds, diseases, and pests. Although an explicit quantification and deeper understanding of weather-induced crop-yield variability is essential for adaptation strategies, so far it has only been addressed by empirical models. Here, we provide conservative estimates of the fraction of reported national yield variabilities that can be attributed to weather by state-of-the-art, process-based crop model simulations. We find that observed weather variations can explain more than 50% of the variability in wheat yields in Australia, Canada, Spain, Hungary, and Romania. For maize, weather sensitivities exceed 50% in seven countries, including the United States. The explained variance exceeds 50% for rice in Japan and South Korea and for soy in Argentina. Avoiding water stress by simulating yields assuming full irrigation shows that water limitation is a major driver of the observed variations in most of these countries. Identifying the mechanisms leading to crop-yield fluctuations is not only fundamental for dampening fluctuations, but is also important in the context of the debate on the attribution of loss and damage to climate change. Since process-based crop models not only account for weather influences on crop yields, but also provide options to represent human-management measures, they could become essential tools for differentiating these drivers, and for exploring options to reduce future yield fluctuations.

Study of weather and thermal comfort influence on sport performance: prognostic analysis applied to Rio de Janeiro's city marathon

NASA Astrophysics Data System (ADS)

Pallotta, M.; Herdies, D. L.; Gonçalves, L. G.

2013-05-01

There is nowadays a growing interest in the influence and impacts of weather and climate in human life. The weather conditions analysis shows the utility of this type of tool when applied in sports. These conditions act as a differential in strategy and training, especially for outdoor sports. This study had as aim objective develop weather forecast and thermal comfort evaluation targeted to sports, and hoped that the results can be used to the development of products and weather service in the Olympic Games 2016 in Rio de Janeiro City. The use of weather forecast applied to the sport showed to be efficient for the case of Rio de Janeiro City Marathon, especially due to the high spatial resolution. The WRF simulations for the three marathons studied showed good results for temperature, atmospheric pressure, and relative humidity. On the other hand, the forecast of the wind showed a pattern of overestimation of the real situation in all cases. It was concluded that the WRF model provides, in general, more representative simulations from 36 hours in advance, and with 18 hours of integration they were even better, describing efficiently the synoptic situation that would be found. A review of weather conditions and thermal comfort at specific points of the marathon route showed that there are significant differences between the stages of the marathon, which makes possible to plan the competition strategy under the thermal comfort. It was concluded that a relationship between a situation more thermally comfortable (uncomfortable) and the best (worst) time in Rio de Janeiro City Marathon

Land Use for Marsh Beach. 4-H Marine Science Simulation Game. Member's Guide [and] Agent's Supplement. MSp 5 [and] 6.

ERIC Educational Resources Information Center

Auburn Univ., AL. Cooperative Extension Service.

A six-part marine science simulation game for 4-H members concerning land use in a hypothetical community is provided. The major problem is to decide what are some possible uses of a three-mile (1,250 acre) Marsh Beach which the city recently purchased. Members assume the roles of decision-makers in the simulated environment and compete for…

Incremental laser space weathering of Allende reveals non-lunar like space weathering effects

NASA Astrophysics Data System (ADS)

Gillis-Davis, Jeffrey J.; Lucey, Paul G.; Bradley, John P.; Ishii, Hope A.; Kaluna, Heather M.; Misra, Anumpam; Connolly, Harold C.

2017-04-01

We report findings from a series of laser-simulated space weathering experiments on Allende, a CV3 carbonaceous chondrite. The purpose of these experiments is to understand how spectra of anhydrous C-complex asteroids might vary as a function of micrometeorite bombardment. Four 0.5-gram aliquots of powdered, unpacked Allende meteorite were incrementally laser weathered with 30 mJ pulses while under vacuum. Radiative transfer modeling of the spectra and Scanning Transmission Electron Microscope (STEM) analyses of the samples show lunar-like similarities and differences in response to laser-simulated space weathering. For instance, laser weathered Allende exhibited lunar-like spectral changes. The overall spectra from visible to near infrared (Vis-NIR) redden and darken, and characteristic absorption bands weaken as a function of laser exposure. Unlike lunar weathering, however, the continuum slope between 450-550 nm does not vary monotonically with laser irradiation. Initially, spectra in this region redden with laser irradiation; then, the visible continua become less red and eventually spectrally bluer. STEM analyses of less mature samples confirm submicroscopic iron metal (SMFe) and micron sized sulfides. More mature samples reveal increased dispersal of Fe-Ni sulfides by the laser, which we infer to be the cause for the non-lunar-like changes in spectral behavior. Spectra of laser weathered Allende are a reasonable match to T- or possibly K-type asteroids; though the spectral match with a parent body is not exact. The key take away is, laser weathered Allende looks spectrally different (i.e., darker, and redder or bluer depending on the wavelength region) than its unweathered spectrum. Consequently, connecting meteorites to asteroids using unweathered spectra of meteorites would result in a different parent body than one matched on the basis of weathered spectra. Further, spectra for these laser weathering experiments may provide an explanation for inconsistencies observed in both laboratory (e.g., Hiroi et al., 2003, 2001; Lazzarin et al., 2006; Moroz et al., 2004, 1996; Shingareva et al., 2004) and telescopic data (Lazzarin et al., 2006; Marchi et al., 2006; Nesvorný et al., 2005).

Weather-Driven Variation in Dengue Activity in Australia Examined Using a Process-Based Modeling Approach

PubMed Central

Bannister-Tyrrell, Melanie; Williams, Craig; Ritchie, Scott A.; Rau, Gina; Lindesay, Janette; Mercer, Geoff; Harley, David

2013-01-01

The impact of weather variation on dengue transmission in Cairns, Australia, was determined by applying a process-based dengue simulation model (DENSiM) that incorporated local meteorologic, entomologic, and demographic data. Analysis showed that inter-annual weather variation is one of the significant determinants of dengue outbreak receptivity. Cross-correlation analyses showed that DENSiM simulated epidemics of similar relative magnitude and timing to those historically recorded in reported dengue cases in Cairns during 1991–2009, (r = 0.372, P < 0.01). The DENSiM model can now be used to study the potential impacts of future climate change on dengue transmission. Understanding the impact of climate variation on the geographic range, seasonality, and magnitude of dengue transmission will enhance development of adaptation strategies to minimize future disease burden in Australia. PMID:23166197

A dataset of future daily weather data for crop modelling over Europe derived from climate change scenarios

NASA Astrophysics Data System (ADS)

Duveiller, G.; Donatelli, M.; Fumagalli, D.; Zucchini, A.; Nelson, R.; Baruth, B.

2017-02-01

Coupled atmosphere-ocean general circulation models (GCMs) simulate different realizations of possible future climates at global scale under contrasting scenarios of land-use and greenhouse gas emissions. Such data require several additional processing steps before it can be used to drive impact models. Spatial downscaling, typically by regional climate models (RCM), and bias-correction are two such steps that have already been addressed for Europe. Yet, the errors in resulting daily meteorological variables may be too large for specific model applications. Crop simulation models are particularly sensitive to these inconsistencies and thus require further processing of GCM-RCM outputs. Moreover, crop models are often run in a stochastic manner by using various plausible weather time series (often generated using stochastic weather generators) to represent climate time scale for a period of interest (e.g. 2000 ± 15 years), while GCM simulations typically provide a single time series for a given emission scenario. To inform agricultural policy-making, data on near- and medium-term decadal time scale is mostly requested, e.g. 2020 or 2030. Taking a sample of multiple years from these unique time series to represent time horizons in the near future is particularly problematic because selecting overlapping years may lead to spurious trends, creating artefacts in the results of the impact model simulations. This paper presents a database of consolidated and coherent future daily weather data for Europe that addresses these problems. Input data consist of daily temperature and precipitation from three dynamically downscaled and bias-corrected regional climate simulations of the IPCC A1B emission scenario created within the ENSEMBLES project. Solar radiation is estimated from temperature based on an auto-calibration procedure. Wind speed and relative air humidity are collected from historical series. From these variables, reference evapotranspiration and vapour pressure deficit are estimated ensuring consistency within daily records. The weather generator ClimGen is then used to create 30 synthetic years of all variables to characterize the time horizons of 2000, 2020 and 2030, which can readily be used for crop modelling studies.

Simulated space weathering of Fe- and Mg-rich aqueously altered minerals using pulsed laser irradiation

NASA Astrophysics Data System (ADS)

Kaluna, H. M.; Ishii, H. A.; Bradley, J. P.; Gillis-Davis, J. J.; Lucey, P. G.

2017-08-01

Simulated space weathering experiments on volatile-rich carbonaceous chondrites (CCs) have resulted in contrasting spectral behaviors (e.g. reddening vs bluing). The aim of this work is to investigate the origin of these contrasting trends by simulating space weathering on a subset of minerals found in these meteorites. We use pulsed laser irradiation to simulate micrometeorite impacts on aqueously altered minerals and observe their spectral and physical evolution as a function of irradiation time. Irradiation of the mineral lizardite, a Mg-phyllosilicate, produces a small degree of reddening and darkening, but a pronounced reduction in band depths with increasing irradiation. In comparison, irradiation of an Fe-rich aqueously altered mineral assemblage composed of cronstedtite, pyrite and siderite, produces significant darkening and band depth suppression. The spectral slopes of the Fe-rich assemblage initially redden then become bluer with increasing irradiation time. Post-irradiation analyses of the Fe-rich assemblage using scanning and transmission electron microscopy reveal the presence of micron sized carbon-rich particles that contain notable fractions of nitrogen and oxygen. Radiative transfer modeling of the Fe-rich assemblage suggests that nanometer sized metallic iron (npFe0) particles result in the initial spectral reddening of the samples, but the increasing production of micron sized carbon particles (μpC) results in the subsequent spectral bluing. The presence of npFe0 and the possible catalytic nature of cronstedtite, an Fe-rich phyllosilicate, likely promotes the synthesis of these carbon-rich, organic-like compounds. These experiments indicate that space weathering processes may enable organic synthesis reactions on the surfaces of volatile-rich asteroids. Furthermore, Mg-rich and Fe-rich aqueously altered minerals are dominant at different phases of the aqueous alteration process. Thus, the contrasting spectral slope evolution between the Fe- and Mg-rich samples in these experiments may indicate that space weathering trends of volatile-rich asteroids have a compositional dependency that could be used to determine the aqueous histories of asteroid parent bodies.

Simulated Transmission of the Dengue Virus Across the US-Mexico Border Using Remotely Sensed and Ground Based Weather Data

NASA Technical Reports Server (NTRS)

Morin, Cory; Quattrochi, Dale A.

2015-01-01

Incidence of dengue fever, caused by a mosquito transmitted virus, have increased in the Americas during recent decades. In the US, local transmission has been reported in southern Texas and Florida. However, despite its close proximity to dengue endemic areas in Mexico and the presence of a primary mosquito vector, there are no reports of local transmission in Arizona. Many studies have demonstrated that weather influences dengue virus transmission by regulating vector development rates, vector habitat availability, and the duration of the virus extrinsic incubation period (EIP). The EIP, the period between mosquito infection and the ability for it to retransmit the virus, is especially important given its high sensitivity to temperature and the short lifespan of mosquitoes. Other studies, however, have suggested that human related factors such as socioeconomic status and herd immunity may explain much of the disparity in dengue incidence in the US-Mexico border region. Using a meteorologically driven model of vector population dynamics and virus transmission we compare simulations of dengue fever cases in southern Arizona and northern Mexico. A Monte Carlo approach is employed to select parameter values by evaluating simulations in Hermosillo Mexico with reported dengue fever case data. Simulations that replicate the case data best are retained and rerun using remotely sensed climate data from other Arizona and Mexico locations to determine the relative influence of weather on virus transmission. Although human and environmental factors undoubtedly influence dengue transmission in the US-Mexico border regions, weather is a major facilitator of the transmission process.

The contribution of changes in P release and CO2 consumption by chemical weathering to the historical trend in land carbon uptake

NASA Astrophysics Data System (ADS)

Goodale, C. L.; Fredriksen, G.; McCalley, C. K.; Sparks, J. P.; Thomas, S. A.

2011-12-01

The atmospheric carbon dioxide (CO2) concentration has increased to a level unprecedented in the last 2 million years, and the concentration is projected to increase further with a rate unseen in geological past. The increase in CO2 cause a rise in surface temperatures and changes in the hydrological cycle through the redistribution of rainfall patterns. All of these changes will impact the weathering of rocks, which in turn affect atmospheric CO2 concentrations via two different pathways. On the one hand, CO2 is consumed by the dissolution reaction of the exposed minerals. And on the other hand, biological CO2 fixation is affected due to changes in phosphorus release from minerals, as biological activity is constrained by phosphorus availability at large scales. The traditional view is that both effects are negligible on a centennial time scale, but recent work on catchment scale challenge this view in favor of a potential high sensitivity of weathering to ongoing climate and land use changes. To globally quantify the contribution of CO2 fixation associated with weathering on the historical trend in terrestrial CO2 uptake, we applied a model of chemical weathering and phosphorus release under climate reconstructions from four Earth System Models. The simulations indicate that changes in weathering could have contributed considerably to the trend in terrestrial CO2 uptake since the pre-industrial revolution, with warming being the main driver of change. The increase in biological CO2 fixation is of comparable magnitude as the increase in CO2 consumption by chemical weathering. Our simulations support the previous findings on catchment scale that weathering can change significantly on a centennial time scale. This finding has implications for 21st century climate projections, which ignore changes in weathering, as well as for long-term airborne fraction of CO2 emissions, whose calculation usually neglects changes in phosphorus availability.

The contribution of changes in P release and CO2 consumption by chemical weathering to the historical trend in land carbon uptake

NASA Astrophysics Data System (ADS)

Goll, D. S.; Moosdorf, N.; Brovkin, V.; Hartmann, J.

2013-12-01

The atmospheric carbon dioxide (CO2) concentration has increased to a level unprecedented in the last 2 million years, and the concentration is projected to increase further with a rate unseen in geological past. The increase in CO2 cause a rise in surface temperatures and changes in the hydrological cycle through the redistribution of rainfall patterns. All of these changes will impact the weathering of rocks, which in turn affect atmospheric CO2 concentrations via two different pathways. On the one hand, CO2 is consumed by the dissolution reaction of the exposed minerals. And on the other hand, biological CO2 fixation is affected due to changes in phosphorus release from minerals, as biological activity is constrained by phosphorus availability at large scales. The traditional view is that both effects are negligible on a centennial time scale, but recent work on catchment scale challenge this view in favor of a potential high sensitivity of weathering to ongoing climate and land use changes. To globally quantify the contribution of CO2 fixation associated with weathering on the historical trend in terrestrial CO2 uptake, we applied a model of chemical weathering and phosphorus release under climate reconstructions from four Earth System Models. The simulations indicate that changes in weathering could have contributed considerably to the trend in terrestrial CO2 uptake since the pre-industrial revolution, with warming being the main driver of change. The increase in biological CO2 fixation is of comparable magnitude as the increase in CO2 consumption by chemical weathering. Our simulations support the previous findings on catchment scale that weathering can change significantly on a centennial time scale. This finding has implications for 21st century climate projections, which ignore changes in weathering, as well as for long-term airborne fraction of CO2 emissions, whose calculation usually neglects changes in phosphorus availability.

User's guide to the weather model: a component of the western spruce budworm modeling system.

Treesearch

W. P. Kemp; N. L. Crookston; P. W. Thomas

1989-01-01

A stochastic model useful in simulating daily maximum and minimum temperature and precipitation developed by Bruhn and others has been adapted for use in the western spruce budworm modeling system. This document describes how to use the weather model and illustrates some aspects of its behavior.

Software Tools for Stochastic Simulations of Turbulence

DTIC Science & Technology

2015-08-28

client interface to FTI. Specefic client programs using this interface include the weather forecasting code WRF ; the high energy physics code, FLASH...client programs using this interface include the weather forecasting code WRF ; the high energy physics code, FLASH; and two locally constructed fluid...45 4.4.2.2 FLASH . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 45 4.4.2.3 WRF

Early Benchmarks of Product Generation Capabilities of the GOES-R Ground System for Operational Weather Prediction

NASA Astrophysics Data System (ADS)

Kalluri, S. N.; Haman, B.; Vititoe, D.

2014-12-01

The ground system under development for Geostationary Operational Environmental Satellite-R (GOES-R) series of weather satellite has completed a key milestone in implementing the science algorithms that process raw sensor data to higher level products in preparation for launch. Real time observations from GOES-R are expected to make significant contributions to Earth and space weather prediction, and there are stringent requirements to product weather products at very low latency to meet NOAA's operational needs. Simulated test data from all the six GOES-R sensors are being processed by the system to test and verify performance of the fielded system. Early results show that the system development is on track to meet functional and performance requirements to process science data. Comparison of science products generated by the ground system from simulated data with those generated by the algorithm developers show close agreement among data sets which demonstrates that the algorithms are implemented correctly. Successful delivery of products to AWIPS and the Product Distribution and Access (PDA) system from the core system demonstrate that the external interfaces are working.

Final Results from A Pilot Project to Investigate Wake Vortex Patterns and Weather Patterns at the Atlantic City Airport by the Richard Stockton College of NJ and the FAA

NASA Astrophysics Data System (ADS)

Trout, Joseph; Manson, J. Russell; King, David; Decicco, Nicolas; Prince, Alyssa; di Mercurio, Alexis; Rios, Manual

2017-01-01

Wake Vortex Turbulence is the turbulence generated by an aircraft in flight. This turbulence is created by vortices at the tips of the wing that may decay slowly and persist for several minutes after creation. These vortices and turbulence are hazardous to other aircraft in the vicinity. The strength, formation and lifetime of the turbulence and vortices are effected by many things including the weather. Here we present the final results of the pilot project to investigation of low level wind fields generated by the Weather Research and Forecasting Model and an analysis of historical data. The findings from the historical data and the data simulations were used as inputs for the computational fluid dynamics model (OpenFoam) to show that the vortices could be simulated using OpenFoam. Presented here are the updated results from a research grant, ``A Pilot Project to Investigate Wake Vortex Patterns and Weather Patterns at the Atlantic City Airport by the Stockton University and the FAA''.

A Modeling Study of the Spring 2011 Extreme US Weather Activity

NASA Technical Reports Server (NTRS)

Schubert, S.; Suarez, M.; Chang, Y.

2012-01-01

The spring of 2011 was characterized by record-breaking tornadic activity with substantial loss of life and destruction of property. While a waning La Nina and other atmospheric teleconnections have been implicated in the development of these extreme weather events, a quantitative assessment of their causes is still lacking. This study uses high resolution (1/4 lat/lon) GEOS-5 AGCM experiments to quantify the role of SSTs and soil moisture in the development of the extreme weather activity with a focus on April - the month of peak tornadic activity. The simulations, consisting of 22-member ensembles of three-month long simulations (initialized March 1st) reproduce the main features of the observed large-scale changes including the below-normal temperature and above-normal precipitation in the Central US, and the hot and dry conditions to the south. Various sensitivity experiments are conducted to separate the roles of the SST, soil moisture and the initial atmospheric conditions in the development and predictability of the atmospheric conditions (wind shear, moisture, etc.) favoring the severe weather activity and flooding.

Magnetomineralogy as a tool for determination of the meteorite weathering

NASA Astrophysics Data System (ADS)

Kohout, T.; Kletetschka, G.; Kobr, M.; Pruner, P.; Wasilewski, P. J.

2002-12-01

In early solar system history are several electromagnetic processes expected capable of magnetizing the primitive solid particles condensating from the Solar Nebula. The signature of this magnetic events can be observed in meteorites found on the Earth. It can take a long time from meteorite fall till laboratory study. Some samples are deposited in the desert or Antarctic ice for thousands of years. In this work we used the sample of the LL chondrite found in Libya desert for weathering simulations, magnetic mineralogy and magnetic properties study. The weathering in this sample is related to the desert varnish formation. From high and low temperature magnetic susceptibility measurements we can see, that most important magnetic carriers are iron, magnetite and hematite. The influence on magnetic mineralogy can be seen from weathering simulations done by leaching the samples in different solutions. This change affects the suitability of different samples for primary magnetic record study. Acknowledgements: This work is supported by Charles University Grant Agency, Czech Republic and would not be possible without the help of following people: Jakub Haloda, Petr Jakes, Marcela Bukovanska, Jaroslav Kadlec, Libuse Kohoutova, Vladimir Kohout.

Retrieving Storm Electric Fields From Aircraft Field Mill Data. Part 2; Applications

NASA Technical Reports Server (NTRS)

Koshak, W. J.; Mach, D. M.; Christian, H. J.; Stewart, M. F.; Bateman, M. G.

2005-01-01

The Lagrange multiplier theory and "pitch down method" developed in Part I of this study are applied to complete the calibration of a Citation aircraft that is instrumented with six field mill sensors. When side constraints related to average fields are used, the method performs well in computer simulations. For mill measurement errors of 1 V/m and a 5 V/m error in the mean fair weather field function, the 3-D storm electric field is retrieved to within an error of about 12%. A side constraint that involves estimating the detailed structure of the fair weather field was also tested using computer simulations. For mill measurement errors of 1 V/m, the method retrieves the 3-D storm field to within an error of about 8% if the fair weather field estimate is typically within 1 V/m of the true fair weather field. Using this side constraint and data from fair weather field maneuvers taken on 29 June 2001, the Citation aircraft was calibrated. The resulting calibration matrix was then used to retrieve storm electric fields during a Citation flight on 2 June 2001. The storm field results are encouraging and agree favorably with the results obtained from earlier calibration analyses that were based on iterative techniques.

An advanced stochastic weather generator for simulating 2-D high-resolution climate variables

NASA Astrophysics Data System (ADS)

Peleg, Nadav; Fatichi, Simone; Paschalis, Athanasios; Molnar, Peter; Burlando, Paolo

2017-07-01

A new stochastic weather generator, Advanced WEather GENerator for a two-dimensional grid (AWE-GEN-2d) is presented. The model combines physical and stochastic approaches to simulate key meteorological variables at high spatial and temporal resolution: 2 km × 2 km and 5 min for precipitation and cloud cover and 100 m × 100 m and 1 h for near-surface air temperature, solar radiation, vapor pressure, atmospheric pressure, and near-surface wind. The model requires spatially distributed data for the calibration process, which can nowadays be obtained by remote sensing devices (weather radar and satellites), reanalysis data sets and ground stations. AWE-GEN-2d is parsimonious in terms of computational demand and therefore is particularly suitable for studies where exploring internal climatic variability at multiple spatial and temporal scales is fundamental. Applications of the model include models of environmental systems, such as hydrological and geomorphological models, where high-resolution spatial and temporal meteorological forcing is crucial. The weather generator was calibrated and validated for the Engelberg region, an area with complex topography in the Swiss Alps. Model test shows that the climate variables are generated by AWE-GEN-2d with a level of accuracy that is sufficient for many practical applications.

Fuzzy bilevel programming with multiple non-cooperative followers: model, algorithm and application

NASA Astrophysics Data System (ADS)

Ke, Hua; Huang, Hu; Ralescu, Dan A.; Wang, Lei

2016-04-01

In centralized decision problems, it is not complicated for decision-makers to make modelling technique selections under uncertainty. When a decentralized decision problem is considered, however, choosing appropriate models is no longer easy due to the difficulty in estimating the other decision-makers' inconclusive decision criteria. These decision criteria may vary with different decision-makers because of their special risk tolerances and management requirements. Considering the general differences among the decision-makers in decentralized systems, we propose a general framework of fuzzy bilevel programming including hybrid models (integrated with different modelling methods in different levels). Specially, we discuss two of these models which may have wide applications in many fields. Furthermore, we apply the proposed two models to formulate a pricing decision problem in a decentralized supply chain with fuzzy coefficients. In order to solve these models, a hybrid intelligent algorithm integrating fuzzy simulation, neural network and particle swarm optimization based on penalty function approach is designed. Some suggestions on the applications of these models are also presented.

Space Weather Models and Their Validation and Verification at the CCMC

NASA Technical Reports Server (NTRS)

Hesse, Michael

2010-01-01

The Community Coordinated l\\lodeling Center (CCMC) is a US multi-agency activity with a dual mission. With equal emphasis, CCMC strives to provide science support to the international space research community through the execution of advanced space plasma simulations, and it endeavors to support the space weather needs of the CS and partners. Space weather support involves a broad spectrum, from designing robust forecasting systems and transitioning them to forecasters, to providing space weather updates and forecasts to NASA's robotic mission operators. All of these activities have to rely on validation and verification of models and their products, so users and forecasters have the means to assign confidence levels to the space weather information. In this presentation, we provide an overview of space weather models resident at CCMC, as well as of validation and verification activities undertaken at CCMC or through the use of CCMC services.

Urban Heat Island Effect on the Energy Consumption of Institutional Buildings in Rome

NASA Astrophysics Data System (ADS)

Calice, Claudia; Clemente, Carola; Salvati, Agnese; Palme, Massimo; Inostroza, Luis

2017-10-01

The urban heat island (UHI) effect is constantly increasing the energy consumption of buildings, especially in summer periods. The energy gap between the estimated energy performance - often simulated without considering UHI - and the real operational consumption is especially relevant for institutional buildings, where the cooling needs are in general higher than in other kind of buildings, due to more internal gains (people, appliances) and different architectural design (more transparent façades and light walls). This paper presents a calculation of the energy penalty due to UHI in two institutional buildings in Rome. Urban Weather Generator (UWG) is used to generate a modified weather file, taking into account the UHI phenomenon. Then, two building performance simulations are done for each case: the first simulation uses a standard weather file and the second uses the modified one. Results shows how is it necessary to re-develop mitigation strategies and a new energy retrofit approach, in order to include urbanization ad UHI effect, especially in this kind of buildings, characterized by very poor conditions of comfort during summer, taking into account users and occupant-driven demand.

Identification of sewer pipes to be cleaned for reduction of CSO pollutant load.

PubMed

Nagaiwa, Akihiro; Settsu, Katsushi; Nakajima, Fumiyuki; Furumai, Hiroaki

2007-01-01

To reduce the CSO (Combined Sewer Overflow) pollutant discharge, one of the effective options is cleaning of sewer pipes before rainfall events. To maximize the efficiency, identification of pipes to be cleaned is necessary. In this study, we discussed the location of pipe deposit in dry weather in a combined sewer system using a distributed model and investigated the effect of pipe cleaning to reduce the pollutant load from the CSO. First we simulated the dry weather flow in a combined sewer system. The pipe deposit distribution in the network was estimated after 3 days of dry weather period. Several specific pipes with structural defect and upper end pipes tend to have an accumulation of deposit. Wet weather simulations were conducted with and without pipe cleaning in rainfall events with different patterns. The SS loads in CSO with and without the pipe cleaning were compared. The difference in the estimated loads was interpreted as the contribution of wash-off in the cleaned pipe. The effect of pipe cleaning on reduction of the CSO pollutant load was quantitatively evaluated (e.g. the cleaning of one specific pipe could reduce 22% of total CSO load). The CSO simulations containing pipe cleaning options revealed that identification of pipes with accumulated deposit using the distributed model is very useful and informative to evaluate the applicability of pipe cleaning option for CSO pollutant reduction.

Measuring ignitability for in situ burning of oil spills weathered under Arctic conditions: from laboratory studies to large-scale field experiments.

PubMed

Fritt-Rasmussen, Janne; Brandvik, Per Johan

2011-08-01

This paper compares the ignitability of Troll B crude oil weathered under simulated Arctic conditions (0%, 50% and 90% ice cover). The experiments were performed in different scales at SINTEF's laboratories in Trondheim, field research station on Svalbard and in broken ice (70-90% ice cover) in the Barents Sea. Samples from the weathering experiments were tested for ignitability using the same laboratory burning cell. The measured ignitability from the experiments in these different scales showed a good agreement for samples with similar weathering. The ice conditions clearly affected the weathering process, and 70% ice or more reduces the weathering and allows a longer time window for in situ burning. The results from the Barents Sea revealed that weathering and ignitability can vary within an oil slick. This field use of the burning cell demonstrated that it can be used as an operational tool to monitor the ignitability of oil spills. Copyright © 2011 Elsevier Ltd. All rights reserved.

A Reactive Transport Model for Marcellus Shale Weathering

NASA Astrophysics Data System (ADS)

Li, L.; Heidari, P.; Jin, L.; Williams, J.; Brantley, S.

2017-12-01

Shale formations account for 25% of the land surface globally. One of the most productive shale-gas formations is the Marcellus, a black shale that is rich in organic matter and pyrite. As a first step toward understanding how Marcellus shale interacts with water, we developed a reactive transport model to simulate shale weathering under ambient temperature and pressure conditions, constrained by soil chemistry and water data. The simulation was carried out for 10,000 years, assuming bedrock weathering and soil genesis began right after the last glacial maximum. Results indicate weathering was initiated by pyrite dissolution for the first 1,000 years, leading to low pH and enhanced dissolution of chlorite and precipitation of iron hydroxides. After pyrite depletion, chlorite dissolved slowly, primarily facilitated by the presence of CO2 and organic acids, forming vermiculite as a secondary mineral. A sensitivity analysis indicated that the most important controls on weathering include the presence of reactive gases (CO2 and O2), specific surface area, and flow velocity of infiltrating meteoric water. The soil chemistry and mineralogy data could not be reproduced without including the reactive gases. For example, pyrite remained in the soil even after 10,000 years if O2 was not continuously present in the soil column; likewise, chlorite remained abundant and porosity remained small with the presence of soil CO2. The field observations were only simulated successfully when the specific surface areas of the reactive minerals were 1-3 orders of magnitude smaller than surface area values measured for powdered minerals, reflecting the lack of accessibility of fluids to mineral surfaces and potential surface coating. An increase in the water infiltration rate enhanced weathering by removing dissolution products and maintaining far-from-equilibrium conditions. We conclude that availability of reactive surface area and transport of H2O and gases are the most important factors affecting chemical weathering of the Marcellus shale in the shallow subsurface. This study documents the utility of reactive transport modeling for complex subsurface processes. Such modelling could be extended to understand interactions between injected fluids and Marcellus shale gas reservoirs at higher temperature and pressure.

Use of simulated satellite radiances from a mesoscale numerical model to understand kinematic and dynamic processes

NASA Technical Reports Server (NTRS)

Kalb, Michael; Robertson, Franklin; Jedlovec, Gary; Perkey, Donald

1987-01-01

Techniques by which mesoscale numerical weather prediction model output and radiative transfer codes are combined to simulate the radiance fields that a given passive temperature/moisture satellite sensor would see if viewing the evolving model atmosphere are introduced. The goals are to diagnose the dynamical atmospheric processes responsible for recurring patterns in observed satellite radiance fields, and to develop techniques to anticipate the ability of satellite sensor systems to depict atmospheric structures and provide information useful for numerical weather prediction (NWP). The concept of linking radiative transfer and dynamical NWP codes is demonstrated with time sequences of simulated radiance imagery in the 24 TIROS vertical sounder channels derived from model integrations for March 6, 1982.

A Reward-Maximizing Spiking Neuron as a Bounded Rational Decision Maker.

PubMed

Leibfried, Felix; Braun, Daniel A

2015-08-01

Rate distortion theory describes how to communicate relevant information most efficiently over a channel with limited capacity. One of the many applications of rate distortion theory is bounded rational decision making, where decision makers are modeled as information channels that transform sensory input into motor output under the constraint that their channel capacity is limited. Such a bounded rational decision maker can be thought to optimize an objective function that trades off the decision maker's utility or cumulative reward against the information processing cost measured by the mutual information between sensory input and motor output. In this study, we interpret a spiking neuron as a bounded rational decision maker that aims to maximize its expected reward under the computational constraint that the mutual information between the neuron's input and output is upper bounded. This abstract computational constraint translates into a penalization of the deviation between the neuron's instantaneous and average firing behavior. We derive a synaptic weight update rule for such a rate distortion optimizing neuron and show in simulations that the neuron efficiently extracts reward-relevant information from the input by trading off its synaptic strengths against the collected reward.

Observational Simulation of Icing in Extreme Weather Conditions

NASA Astrophysics Data System (ADS)

Gultepe, Ismail; Heymsfield, Andrew; Agelin-Chaab, Martin; Komar, John; Elfstrom, Garry; Baumgardner, Darrel

2017-04-01

Observations and prediction of icing in extreme weather conditions are important for aviation, transportation, and shipping applications, and icing adversely affects the economy. Icing environments can be studied either in the outdoor atmosphere or in the laboratory. There have been several aircraft based in-situ studies related to weather conditions affecting aviation operations, transportation, and marine shipping that includes icing, wind, and turbulence. However, studying severe weather conditions from aircraft observations are limited due to safety and sampling issues, instrumental uncertainties, and even the possibility of aircraft producing its own physical and dynamical effects. Remote sensing based techniques (e.g. retrieval techniques) for studying severe weather conditions represent usually a volume that cannot characterize the important scales and also represents indirect observations. Therefore, laboratory simulations of atmospheric processes can help us better understand the interactions among microphysical and dynamical processes. The Climatic Wind Tunnel (CWT) in ACE at the University of Ontario Institute of Technology (UOIT) has a large semi-open jet test chamber with flow area 7-13 m2 that can precisely control temperatures down to -40°C, and up to 250 km hr-1 wind speeds, for heavy or dry snow conditions with low visibility, similar to ones observed in the Arctic and cold climate regions, or at high altitude aeronautical conditions. In this study, the ACE CWT employed a spray nozzle array suspended in its settling chamber and fed by pressurized water, creating various particle sizes from a few microns up to mm size range. This array, together with cold temperature and high wind speed, enabled simulation of severe weather conditions, including icing, visibility, strong wind and turbulence, ice fog and frost, freezing fog, heavy snow and blizzard conditions. In this study, the test results will be summarized, and their application to aircraft icing will be provided in detail. Overall, based on these results, scientific challenges related to icing environments will be emphasized for Arctic and cold environments in future projects in the ACE CWT.

Simulations of the Montréal urban heat island

NASA Astrophysics Data System (ADS)

Roberge, François; Sushama, Laxmi; Fanta, Gemechu

2017-04-01

The current population of Montreal is around 3.8 million and this number is projected to go up in the coming years to decades, which will lead to vast expansion of urban areas. It is well known that urban morphology impacts weather and climate, and therefore should be taken into consideration in urban planning. This is particularly important in the context of a changing climate, as the intensity and frequency of temperature extremes such as hot spells are projected to increase in future climate, and Urban Heat Island (UHI) can potentially raise already stressful temperatures during such events, which can have significant effects on human health and energy consumption. High-resolution regional climate model simulations can be utilized to understand better urban-weather/climate interactions in current and future climates, particularly the spatio-temporal characteristics of the Urban Heat Island and its impact on other weather/climate characteristics such as urban flows, precipitation etc. This paper will focus on two high-resolution (250 m) simulations performed with (1) the Canadian Land Surface Scheme (CLASS) and (2) CLASS and TEB (Town Energy Balance) model; TEB is a single layer urban canopy model and is used to model the urban fractions. The two simulations are performed over a domain covering Montreal for the 1960-2015 period, driven by atmospheric forcing data coming from a high-resolution Canadian Regional Climate Model (CRCM5) simulation, driven by ERA-Interim. The two simulations are compared to assess the impact of urban regions on selected surface fields and the simulation with both CLASS and TEB is then used to study the spatio-temporal characteristics of the UHI over the study domain. Some preliminary results from a coupled simulation, i.e. CRCM5+CLASS+TEB, for selected years, including extreme warm years, will also be presented.

Assessing the Role of Seafloor Weathering in Global Geochemical Cycling

NASA Astrophysics Data System (ADS)

Farahat, N. X.; Abbot, D. S.; Archer, D. E.

2015-12-01

Low-temperature alteration of the basaltic upper oceanic crust, known as seafloor weathering, has been proposed as a mechanism for long-term climate regulation similar to the continental climate-weathering negative feedback. Despite this potentially far-reaching impact of seafloor weathering on habitable planet evolution, existing modeling frameworks do not include the full scope of alteration reactions or recent findings of convective flow dynamics. We present a coupled fluid dynamic and geochemical numerical model of low-temperature, off-axis hydrothermal activity. This model is designed to explore the the seafloor weathering flux of carbon to the oceanic crust and its responsiveness to climate fluctuations. The model's ability to reproduce the seafloor weathering environment is evaluated by constructing numerical simulations for comparison with two low-temperature hydrothermal systems: A transect east of the Juan de Fuca Ridge and the southern Costa Rica Rift flank. We explore the sensitivity of carbon uptake by seafloor weathering on climate and geology by varying deep ocean temperature, seawater dissolved inorganic carbon, continental weathering inputs, and basaltic host rock in a suite of numerical experiments.

Cognitive Task Analysis of Business Jet Pilots' Weather Flying Behaviors: Preliminary Results

NASA Technical Reports Server (NTRS)

Latorella, Kara; Pliske, Rebecca; Hutton, Robert; Chrenka, Jason

2001-01-01

This report presents preliminary findings from a cognitive task analysis (CTA) of business aviation piloting. Results describe challenging weather-related aviation decisions and the information and cues used to support these decisions. Further, these results demonstrate the role of expertise in business aviation decision-making in weather flying, and how weather information is acquired and assessed for reliability. The challenging weather scenarios and novice errors identified in the results provide the basis for experimental scenarios and dependent measures to be used in future flight simulation evaluations of candidate aviation weather information systems. Finally, we analyzed these preliminary results to recommend design and training interventions to improve business aviation decision-making with weather information. The primary objective of this report is to present these preliminary findings and to document the extended CTA methodology used to elicit and represent expert business aviator decision-making with weather information. These preliminary findings will be augmented with results from additional subjects using this methodology. A summary of the complete results, absent the detailed treatment of methodology provided in this report, will be documented in a separate publication.

Usability of NASA Satellite Imagery-Based Daily Solar Radiation for Crop Yield Simulation and Management Decisions

NASA Astrophysics Data System (ADS)

Yang, H.; Cassman, K. G.; Stackhouse, P. W.; Hoell, J. M.

2007-12-01

We tested the usability of NASA satellite imagery-based daily solar radiation for farm-specific crop yield simulation and management decisions using the Hybrid-Maize model (www.hybridmaize.unl.edu). Solar radiation is one of the key inputs for crop yield simulation. Farm-specific crop management decisions using simulation models require long-term (i.e., 20 years or longer) daily local weather data including solar radiation for assessing crop yield potential and its variation, optimizing crop planting date, and predicting crop yield in a real time mode. Weather stations that record daily solar radiation have sparse coverage and many of them have record shorter than 15 years. Based on satellite imagery and other remote sensed information, NASA has provided estimates of daily climatic data including solar radiation at a resolution of 1 degree grid over the earth surface from 1983 to 2005. NASA is currently continuing to update the database and has plans to provide near real-time data in the future. This database, which is free to the public at http://power.larc.nasa.gov, is a potential surrogate for ground- measured climatic data for farm-specific crop yield simulation and management decisions. In this report, we quantified (1) the similarities between NASA daily solar radiation and ground-measured data atr 20 US sites and four international sites, and (2) the accuracy and precision of simulated corn yield potential and its variability using NASA solar radiation coupled with other weather data from ground measurements. The 20 US sites are in the western Corn Belt, including Iowa, South Dakota, Nebraska, and Kansas. The four international sites are Los Banos in the Philippines, Beijing in China, Cali in Columbia, and Ibatan in Nigeria. Those sites were selected because of their high quality weather record and long duration (more than 20 years on average). We found that NASA solar radiation was highly significantly correlated (mean r2 =0.88**) with the ground measurements at the 20 US sites, while the correlation was poor (mean r2=0.55**, though significant) at the four international sites. At the 20 US sites, the mean root mean square error (RMSE) between NASA solar radiation and the ground data was 2.7 MJ/m2/d, or 19% of the mean daily ground data. At the four international sites, the mean RMSE was 4.0 MJ/m2/d, or 25% of the mean daily ground value. Large differences between NASA solar radiation and the ground data were likely associated with tropical environment or significant variation in elevation within a short distance. When using NASA solar radiation coupled with other weather data from ground measurements, the simulated corn yields were highly significantly correlated (mean r2=0.85**) with those using complete ground weather data at the 20 US sites, while the correlation (mean r2=0.48**) was poor at the four international sites. The mean RMSE between the simulated corn yields of the two batches was 0.50 Mg/ha, or 3% of the mean absolute value using the ground data. At the four international sites, the RMSE of the simulated yields was 1.5 Mg/ha, or 13% of the mean absolute value using the ground data. We conclude that the NASA satellite imagery-based daily solar radiation is a reasonably reliable surrogate for the ground observations for farm-specific crop yield simulation and management decisions, especially at locations where ground-measured solar radiation is unavailable.

Using Virtualization to Integrate Weather, Climate, and Coastal Science Education

NASA Astrophysics Data System (ADS)

Davis, J. R.; Paramygin, V. A.; Figueiredo, R.; Sheng, Y.

2012-12-01

To better understand and communicate the important roles of weather and climate on the coastal environment, a unique publically available tool is being developed to support research, education, and outreach activities. This tool uses virtualization technologies to facilitate an interactive, hands-on environment in which students, researchers, and general public can perform their own numerical modeling experiments. While prior efforts have focused solely on the study of the coastal and estuary environments, this effort incorporates the community supported weather and climate model (WRF-ARW) into the Coastal Science Educational Virtual Appliance (CSEVA), an education tool used to assist in the learning of coastal transport processes; storm surge and inundation; and evacuation modeling. The Weather Research and Forecasting (WRF) Model is a next-generation, community developed and supported, mesoscale numerical weather prediction system designed to be used internationally for research, operations, and teaching. It includes two dynamical solvers (ARW - Advanced Research WRF and NMM - Nonhydrostatic Mesoscale Model) as well as a data assimilation system. WRF-ARW is the ARW dynamics solver combined with other components of the WRF system which was developed primarily at NCAR, community support provided by the Mesoscale and Microscale Meteorology (MMM) division of National Center for Atmospheric Research (NCAR). Included with WRF is the WRF Pre-processing System (WPS) which is a set of programs to prepare input for real-data simulations. The CSEVA is based on the Grid Appliance (GA) framework and is built using virtual machine (VM) and virtual networking technologies. Virtualization supports integration of an operating system, libraries (e.g. Fortran, C, Perl, NetCDF, etc. necessary to build WRF), web server, numerical models/grids/inputs, pre-/post-processing tools (e.g. WPS / RIP4 or UPS), graphical user interfaces, "Cloud"-computing infrastructure and other tools into a single ready-to-use package. Thus, the previous ornery task of setting up and compiling these tools becomes obsolete and the research, educator or student can focus on using the tools to study the interactions between weather, climate and the coastal environment. The incorporation of WRF into the CSEVA has been designed to be synergistic with the extensive online tutorials and biannual tutorials hosted by NCAR. Included are working examples of the idealized test simulations provided with WRF (2D sea breeze and squalls, a large eddy simulation, a Held and Suarez simulation, etc.) To demonstrate the integration of weather, coastal and coastal science education, example applications are being developed to demonstrate how the system can be used to couple a coastal and estuarine circulation, transport and storm surge model with downscale reanalysis weather and future climate predictions. Documentation, tutorials and the enhanced CSEVA itself will be found on the web at: http://cseva.coastal.ufl.edu.

Recent examples of mesoscale numerical forecasts of severe weather events along the east coast

NASA Technical Reports Server (NTRS)

Kocin, P. J.; Uccellini, L. W.; Zack, J. W.; Kaplan, M. L.

1984-01-01

Mesoscale numerical forecasts utilizing the Mesoscale Atmospheric Simulation System (MASS) are documented for two East Coast severe weather events. The two events are the thunderstorm and heavy snow bursts in the Washington, D.C. - Baltimore, MD region on 8 March 1984 and the devastating tornado outbreak across North and South Carolina on 28 March 1984. The forecasts are presented to demonstrate the ability of the model to simulate dynamical interactions and diabatic processes and to note some of the problems encountered when using mesoscale models for day-to-day forecasting.

Developing of operational hydro-meteorological simulating and displaying system

NASA Astrophysics Data System (ADS)

Wang, Y.; Shih, D.; Chen, C.

2010-12-01

Hydrological hazards, which often occur in conjunction with extreme precipitation events, are the most frequent type of natural disaster in Taiwan. Hence, the researchers at the Taiwan Typhoon and Flood Research Institute (TTFRI) are devoted to analyzing and gaining a better understanding of the causes and effects of natural disasters, and in particular, typhoons and floods. The long-term goal of the TTFRI is to develop a unified weather-hydrological-oceanic model suitable for simulations with local parameterizations in Taiwan. The development of a fully coupled weather-hydrology interaction model is not yet completed but some operational hydro-meteorological simulations are presented as a step in the direction of completing a full model. The predicted rainfall data from Weather Research Forecasting (WRF) are used as our meteorological forcing on watershed modeling. The hydrology and hydraulic modeling are conducted by WASH123D numerical model. And the WRF/WASH123D coupled system is applied to simulate floods during the typhoon landfall periods. The daily operational runs start at 04UTC, 10UTC, 16UTC and 22UTC, about 4 hours after data downloaded from NCEP GFS. This system will execute 72-hr weather forecasts. The simulation of WASH123D will sequentially trigger after receiving WRF rainfall data. This study presents the preliminary framework of establishing this system, and our goal is to build this earlier warning system to alert the public form dangerous. The simulation results are further display by a 3D GIS web service system. This system is established following the Open Geospatial Consortium (OGC) standardization process for GIS web service, such as Web Map Service (WMS) and Web Feature Service (WFS). The traditional 2D GIS data, such as high resolution aerial photomaps and satellite images are integrated into 3D landscape model. The simulated flooding and inundation area can be dynamically mapped on Wed 3D world. The final goal of this system is to real-time forecast flood and the results can be visually displayed on the virtual catchment. The policymaker can easily and real-time gain visual information for decision making at any site through internet.

Simulation of the 23 July 2012 Extreme Space Weather Event: What if This Extremely Rare CME Was Earth Directed?

NASA Technical Reports Server (NTRS)

Ngwira, Chigomezyo M.; Pulkkinen, Antti; Mays, M. Leila; Kuznetsova, Maria M.; Galvin, A. B.; Simunac, Kristin; Baker, Daniel N.; Li, Xinlin; Zheng, Yihua; Glocer, Alex

2013-01-01

Extreme space weather events are known to cause adverse impacts on critical modern day technological infrastructure such as high-voltage electric power transmission grids. On 23 July 2012, NASA's Solar Terrestrial Relations Observatory-Ahead (STEREO-A) spacecraft observed in situ an extremely fast coronal mass ejection (CME) that traveled 0.96 astronomical units (approx. 1 AU) in about 19 h. Here we use the SpaceWeather Modeling Framework (SWMF) to perform a simulation of this rare CME.We consider STEREO-A in situ observations to represent the upstream L1 solar wind boundary conditions. The goal of this study is to examine what would have happened if this Rare-type CME was Earth-bound. Global SWMF-generated ground geomagnetic field perturbations are used to compute the simulated induced geoelectric field at specific ground-based active INTERMAGNET magnetometer sites. Simulation results show that while modeled global SYM-H index, a high-resolution equivalent of the Dst index, was comparable to previously observed severe geomagnetic storms such as the Halloween 2003 storm, the 23 July CME would have produced some of the largest geomagnetically induced electric fields, making it very geoeffective. These results have important practical applications for risk management of electrical power grids.

Explicit simulation of ice particle habits in a Numerical Weather Prediction Model

NASA Astrophysics Data System (ADS)

Hashino, Tempei

2007-05-01

This study developed a scheme for explicit simulation of ice particle habits in Numerical Weather Prediction (NWP) Models. The scheme is called Spectral Ice Habit Prediction System (SHIPS), and the goal is to retain growth history of ice particles in the Eulerian dynamics framework. It diagnoses characteristics of ice particles based on a series of particle property variables (PPVs) that reflect history of microphysieal processes and the transport between mass bins and air parcels in space. Therefore, categorization of ice particles typically used in bulk microphysical parameterization and traditional bin models is not necessary, so that errors that stem from the categorization can be avoided. SHIPS predicts polycrystals as well as hexagonal monocrystals based on empirically derived habit frequency and growth rate, and simulates the habit-dependent aggregation and riming processes by use of the stochastic collection equation with predicted PPVs. Idealized two dimensional simulations were performed with SHIPS in a NWP model. The predicted spatial distribution of ice particle habits and types, and evolution of particle size distributions showed good quantitative agreement with observation This comprehensive model of ice particle properties, distributions, and evolution in clouds can be used to better understand problems facing wide range of research disciplines, including microphysics processes, radiative transfer in a cloudy atmosphere, data assimilation, and weather modification.

Investigation of boundary-layer wind predictions during nocturnal low-level jet events using the Weather Research and Forecasting model

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mirocha, Jeff D.; Simpson, Matthew D.; Fast, Jerome D.

Simulations of two periods featuring three consecutive low level jet (LLJ) events in the US Upper Great Plains during the autumn of 2011 were conducted to explore the impacts of various setup configurations and physical process models on simulated flow parameters within the lowest 200 m above the surface, using the Weather Research and Forecasting (WRF) model. Sensitivities of simulated flow parameters to the horizontal and vertical grid spacing, planetary boundary layer (PBL) and land surface model (LSM) physics options, were assessed. Data from a Light Detection and Ranging (lidar) system, deployed to the Weather Forecast Improvement Project (WFIP; Finleymore » et al. 2013) were used to evaluate the accuracy of simulated wind speed and direction at 80 m above the surface, as well as their vertical distributions between 120 and 40 m, covering the typical span of contemporary tall wind turbines. All of the simulations qualitatively captured the overall diurnal cycle of wind speed and stratification, producing LLJs during each overnight period, however large discrepancies occurred at certain times for each simulation in relation to the observations. 54-member ensembles encompassing changes of the above discussed configuration parameters displayed a wide range of simulated vertical distributions of wind speed and direction, and potential temperature, reflecting highly variable representations of stratification during the weakly stable overnight conditions. Root mean square error (RMSE) statistics show that different ensemble members performed better and worse in various simulated parameters at different times, with no clearly superior configuration . Simulations using a PBL parameterization designed specifically for the stable conditions investigated herein provided superior overall simulations of wind speed at 80 m, demonstrating the efficacy of targeting improvements of physical process models in areas of known deficiencies. However, the considerable magnitudes of the RMSE values of even the best performing simulations indicate ample opportunities for further improvements.« less

How climate and weather affect the erosion risk in the northern Gulf of Mexico

NASA Astrophysics Data System (ADS)

Wahl, T.; Plant, N. G.

2015-12-01

Oceanographic variables such as mean sea level, tides, storm surges, and waves are drivers of erosion, and they act on different time scales ranging from hours (associated with weather) to seasonal and decadal variations and trends (associated with climate). Here we explore how the related sea-state conditions affect the erosion risk in the northern Gulf of Mexico for past and future climate scenarios. From the climate perspective we find that long-term trends in the relevant variables have caused an increase of ~30% in the erosion risk since the 1980s; at least half of this increase was due to changes in the wave climate. In the next decades, sea level rise will likely become the dominating driver and may, in combination with ongoing changes in the wave climate (and depending on the emission scenario), escalate the erosion risk by up to 300% over the next 30 years. We also find significant changes in the seasonal cycles of sea level and significant wave height, which have in combination caused a considerable increase of the erosion risk in summer and decrease in winter (superimposed onto the long-term trends). The influence of weather is assessed with a copula-based multivariate sea storm model in a Monte-Carlo framework; i.e. we simulate hundreds of thousands of artificial but physically consistent sea-state conditions to quantify how different our understanding of the present day erosion risk would be if we had seen more or less extreme combinations of the different sea-state parameters over the last three decades. We find, for example, that total water levels (tide + surge + wave run-up) associated with 100-year return periods may be underestimated by up to 30% and that the average number of impact hours - when total water levels exceeded the height of the dune toe (collision) or dune crest (overwash) - could have been up to 50% higher than what we inferred based on the actually observed oceanographic conditions. Assessing erosion risk in such a probabilistic way while accounting for non-stationarity due to climate variability and change can help decision makers and planners to implement improved monitoring and adaptation strategies for long-term sustainability of the coastline and barrier islands.

Erosion risk in the northern Gulf of Mexico - the effects of climate and weather

NASA Astrophysics Data System (ADS)

Wahl, Thomas; Plant, Nathaniel G.; Long, Joseph W.

2016-04-01

Oceanographic variables such as mean sea level, tides, storm surges, and waves are drivers of erosion, and they act on different time scales ranging from hours (associated with weather) to seasonal and decadal variations and trends (associated with climate). Here we explore how the related sea-state conditions affect the erosion risk in the northern Gulf of Mexico for past and future climate scenarios. From the climate perspective we find that long-term trends in the relevant variables have caused an increase of ~30% in the erosion risk since the 1980s; at least half of this increase was due to changes in the wave climate. In the next decades, sea level rise will likely become the dominating driver and may, in combination with ongoing changes in the wave climate (and depending on the emission scenario), escalate the erosion risk by up to 300% over the next 30 years. We also find significant changes in the seasonal cycles of sea level and significant wave height, which have in combination caused a considerable increase of the erosion risk in summer and decrease in winter (superimposed onto the long-term trends). The influence of weather is assessed with a copula-based multivariate sea storm model in a Monte-Carlo framework; i.e. we simulate hundreds of thousands of artificial but physically consistent sea-state conditions to quantify how different our understanding of the present day erosion risk would be if we had seen more or less extreme combinations of the different sea-state parameters over the last three decades. We find, for example, that total water levels (tide + surge + wave run-up) associated with 100-year return periods may be underestimated by up to 30% and that the average number of impact hours - when total water levels exceeded the height of the dune toe (collision) or dune crest (overwash) - could have been up to 50% higher than what we inferred based on the actually observed oceanographic conditions. Assessing erosion risk in such a probabilistic way while accounting for non-stationarity due to climate variability and change can help decision makers and planners to implement improved monitoring and adaptation strategies for long-term sustainability of the coastline and barrier islands.

NASA GSFC Space Weather Center - Innovative Space Weather Dissemination: Web-Interfaces, Mobile Applications, and More

NASA Technical Reports Server (NTRS)

Maddox, Marlo; Zheng, Yihua; Rastaetter, Lutz; Taktakishvili, A.; Mays, M. L.; Kuznetsova, M.; Lee, Hyesook; Chulaki, Anna; Hesse, Michael; Mullinix, Richard;

Quantitative assessment of current and future risks related rainfall in processing tomato in the Guadiana river basin (SW Spain)

NASA Astrophysics Data System (ADS)

Castañeda-Vera, Alba; Garrido, Alberto; Ruiz-Ramos, Margarita; Sánchez-Sánchez, Enrique; Inés Mínguez, M.

2013-04-01

An extension of risk coverages in the insurance policies for processing tomato, mainly related to rainfall events, has resulted in an important increase in claims. This suggests that damages related to extreme or ill-timed showers have been underestimated in previous years. An estimation of damages related to rainfall in the last thirty years and the impact of climate change in the risk related to rainfall in processing tomato crops in the Guadiana river basin (SW Spain) were studied through a risk index. First, the risk index was defined with temperature and relative humidity thresholds related to different damage magnitudes. Then, this index was applied to current climate and to future climate scenarios in nine weather stations representative of the studied area to determine the trends in losses related to extreme or inopportune rainfall events. Thresholds of temperature and relative humidity were obtained from cross-checking agricultural insurance records and meteorological data from local weather stations (REDAREX, http://sw-aperos.juntaex.es/redarex). To consider longer time series, the reanalysis database ERA-INTERIM (Dee et al., 2011) was used. Simulated climate was obtained from the European Project ENSEMBLES (http://www.ensembles-eu.org/). Trends in climatic risk were analysed by applying the risk index to three sets of data defining current climate (1980-2010), mid-future climate (2010-2040) and long-term future climate (2040-2070). An algorithm to choose the surrounding cell that minimizes the temperature and precipitation climatic biases and maximizes seasonal correlation when comparing ENSEMBLES regional climate model simulations and observed climate was applied before index calculation. The results show the trends in frequency and magnitude of the risk of suffering damages related to rainfall events. The methodology decreased the uncertainty on risk levels. Results contribute to detect the periods during the growing season with larger risk of damage in order to provide information to assist research on risk management practices and to support insurance policy makers to extend guaranties and to adapt the insurance conditions and costs to real crop risks. This research is being financed by MULCLIVAR project (CGL2012-38923-C02-02), MINECO, Spain Keywords: climate change, risk, rainfall, processing tomato. References Dee, D. P., with 35 co-authors, 2011: The ERA-Interim reanalysis: configuration and performance of the data assimilation system. Quart. J. R. Meteorol. Soc., 137, 553-597.

Trusted Advisors, Decision Models and Other Keys to Communicating Science to Decision Makers

NASA Astrophysics Data System (ADS)

Webb, E.

2006-12-01

Water resource management decisions often involve multiple parties engaged in contentious negotiations that try to navigate through complex combinations of legal, social, hydrologic, financial, and engineering considerations. The standard approach for resolving these issues is some form of multi-party negotiation, a formal court decision, or a combination of the two. In all these cases, the role of the decision maker(s) is to choose and implement the best option that fits the needs and wants of the community. However, each path to a decision carries the risk of technical and/or financial infeasibility as well as the possibility of unintended consequences. To help reduce this risk, decision makers often rely on some type of predictive analysis from which they can evaluate the projected consequences of their decisions. Typically, decision makers are supported in the analysis process by trusted advisors who engage in the analysis as well as the day to day tasks associated with multi-party negotiations. In the case of water resource management, the analysis is frequently a numerical model or set of models that can simulate various management decisions across multiple systems and output results that illustrate the impact on areas of concern. Thus, in order to communicate scientific knowledge to the decision makers, the quality of the communication between the analysts, the trusted advisor, and the decision maker must be clear and direct. To illustrate this concept, a multi-attribute decision analysis matrix will be used to outline the value of computer model-based collaborative negotiation approaches to guide water resources decision making and communication with decision makers. In addition, the critical role of the trusted advisor and other secondary participants in the decision process will be discussed using examples from recent water negotiations.

Weather extremes in very large, high-resolution ensembles: the weatherathome experiment

NASA Astrophysics Data System (ADS)

Allen, M. R.; Rosier, S.; Massey, N.; Rye, C.; Bowery, A.; Miller, J.; Otto, F.; Jones, R.; Wilson, S.; Mote, P.; Stone, D. A.; Yamazaki, Y. H.; Carrington, D.

2011-12-01

Resolution and ensemble size are often seen as alternatives in climate modelling. Models with sufficient resolution to simulate many classes of extreme weather cannot normally be run often enough to assess the statistics of rare events, still less how these statistics may be changing. As a result, assessments of the impact of external forcing on regional climate extremes must be based either on statistical downscaling from relatively coarse-resolution models, or statistical extrapolation from 10-year to 100-year events. Under the weatherathome experiment, part of the climateprediction.net initiative, we have compiled the Met Office Regional Climate Model HadRM3P to run on personal computer volunteered by the general public at 25 and 50km resolution, embedded within the HadAM3P global atmosphere model. With a global network of about 50,000 volunteers, this allows us to run time-slice ensembles of essentially unlimited size, exploring the statistics of extreme weather under a range of scenarios for surface forcing and atmospheric composition, allowing for uncertainty in both boundary conditions and model parameters. Current experiments, developed with the support of Microsoft Research, focus on three regions, the Western USA, Europe and Southern Africa. We initially simulate the period 1959-2010 to establish which variables are realistically simulated by the model and on what scales. Our next experiments are focussing on the Event Attribution problem, exploring how the probability of various types of extreme weather would have been different over the recent past in a world unaffected by human influence, following the design of Pall et al (2011), but extended to a longer period and higher spatial resolution. We will present the first results of the unique, global, participatory experiment and discuss the implications for the attribution of recent weather events to anthropogenic influence on climate.

Preliminary Observing System Simulation Experiments for Doppler Wind Lidars Deployed on the International Space Station

NASA Technical Reports Server (NTRS)

Kemp, E.; Jacob, J.; Rosenberg, R.; Jusem, J. C.; Emmitt, G. D.; Wood, S.; Greco, L. P.; Riishojgaard, L. P.; Masutani, M.; Ma, Z.;

Simulations of Effects of Nanophase Iron Space Weather Products on Lunar Regolith Reflectance Spectra

NASA Astrophysics Data System (ADS)

Escobar-Cerezo, J.; Penttilä, A.; Kohout, T.; Muñoz, O.; Moreno, F.; Muinonen, K.

2018-01-01

Lunar soil spectra differ from pulverized lunar rocks spectra by reddening and darkening effects, and shallower absorption bands. These effects have been described in the past as a consequence of space weathering. In this work, we focus on the effects of nanophase iron (npFe0) inclusions on the experimental reflectance spectra of lunar regolith particles. The reflectance spectra are computed using SIRIS3, a code that combines ray optics with radiative-transfer modeling to simulate light scattering by different types of scatterers. The imaginary part of the refractive index as a function of wavelength of immature lunar soil is derived by comparison with the measured spectra of the corresponding material. Furthermore, the effect of adding nanophase iron inclusions on the reflectance spectra is studied. The computed spectra qualitatively reproduce the observed effects of space weathered lunar regolith.

Dynamic evaluation of two decades of WRF-CMAQ ozone simulations over the contiguous United States

EPA Science Inventory

Dynamic evaluation of the fully coupled Weather Research and Forecasting (WRF)– Community Multi-scale Air Quality (CMAQ) model ozone simulations over the contiguous United States (CONUS) using two decades of simulations covering the period from 1990 to 2010 is conducted to ...

Dynamic evaluation of two decades of WRF-CMAQ ozone simulations over the contiguous United States

EPA Science Inventory

Dynamic evaluation of the fully coupled Weather Research and Forecasting (WRF)– Community Multi-scale Air Quality (CMAQ) model ozone simulations over the contiguous United States (CONUS) using two decades of simulations covering the period from 1990 to 2010 is conducted to assess...

A synoptic climatology for forest fires in the NE US and future implications for GCM simulations

Treesearch

Yan Qing; Ronald Sabo; Yiqiang Wu; J.Y. Zhu

1994-01-01

We studied surface-pressure patterns corresponding to reduced precipitation, high evaporation potential, and enhanced forest-fire danger for West Virginia, which experienced extensive forest-fire damage in November 1987. From five years of daily weather maps we identified eight weather patterns that describe distinctive flow situations throughout the year. Map patterns...

Response of North American ecosystem models to multi-annual periodicities in temperature and precipitation

Treesearch

J. Alan Yeakley; Ron A. Moen; David D. Breshears; Martha K. Nungesser

1994-01-01

Ecosystem models typically use input temperature and precipitation data generated stochastically from weather station means and variances. Although the weather station data are based on measurements taken over a few decades, model simulations are usually on the order of centuries. Consequently, observed periodicities in temperature and precipitation at the continental...

GFDL's Data Portal

Science.gov Websites

Regional Climate Change Assessment Program (NARCCAP) Related Info CM2.1 experiments (6hr data) AM2.1 : oar.gfdl.webmaster-data1@ Spotlight on NOMADS NOMADS is being developed as a Unified Climate and Weather Archive to observed and simulated data to the climate and weather communities. The infrastructure created within GO

Simulating transport of nitrogen and phosphorus in a Cambisol after natural and simulated intense rainfall.

PubMed

Kaufmann, Vander; Pinheiro, Adilson; Castro, Nilza Maria dos Reis

2014-05-01

Intense rainfall adversely affects agricultural areas, causing transport of pollutants. Physically-based hydrological models to simulate flows of water and chemical substances can be used to help decision-makers adopt measures which reduce such problems. The purpose of this paper is to evaluate the performance of SWAP and ANIMO models for simulating transport of water, nitrate and phosphorus nutrients, during intense rainfall events generated by a simulator, and during natural rainfall, on a volumetric drainage lysimeter. The models were calibrated and verified using daily time series and simulated rainfall measured at 10-minute intervals. For daily time-intervals, the Nash-Sutcliffe coefficient was 0.865 for the calibration period and 0.805 for verification. Under simulated rainfall, these coefficients were greater than 0.56. The pattern of both nitrate and phosphate concentrations in daily drainage flow under simulated rainfall was acceptably reproduced by the ANIMO model. In the simulated rainfall, loads of nitrate transported in surface runoff varied between 0.08 and 8.46 kg ha(-1), and in drainage form the lysimeter, between 2.44 and 112.57 kg ha(-1). In the case of phosphate, the loads transported in surface runoff varied between 0.002 and 0.504 kg ha(-1), and in drainage, between 0.005 and 1.107 kg ha(-1). The use of the two models SWAP and ANIMO shows the magnitudes of nitrogen and phosphorus fluxes transported by natural and simulated intense rainfall in an agricultural area with different soil management procedures, as required by decision makers. Copyright © 2014 Elsevier B.V. All rights reserved.

Local health and social care responses to implementing the national cold weather plan.

PubMed

Heffernan, C; Jones, L; Ritchie, B; Erens, B; Chalabi, Zaid; Mays, N

2017-09-18

The Cold Weather Plan (CWP) for England was launched by the Department of Health in 2011 to prevent avoidable harm to health by cold weather by enabling individuals to prepare and respond appropriately. This study sought the views of local decision makers involved in the implementation of the CWP in the winter of 2012/13 to establish the effects of the CWP on local planning. It was part of a multi-component independent evaluation of the CWP. Ten LA areas were purposively sampled which varied in level of deprivation and urbanism. Fifty-two semi-structured interviews were held with health and social care managers involved in local planning between November 2012 and May 2013. Thematic analysis revealed that the CWP was considered a useful framework to formalize working arrangements between agencies though local leadership varied across localities. There were difficulties in engaging general practitioners, differences in defining vulnerable individuals and a lack of performance monitoring mechanisms. The CWP was welcomed by local health and social care managers, and improved proactive winter preparedness. Areas for improvement include better integration with general practice, and targeting resources at socially isolated individuals in cold homes with specific interventions aimed at reducing social isolation and building community resilience. © The Author 2017. Published by Oxford University Press on behalf of Faculty of Public Health. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com

Sun-Burned: Space Weather's Impact on United States National Security

NASA Astrophysics Data System (ADS)

Stebbins, B.

2014-12-01

The heightened media attention surrounding the 2013-14 solar maximum presented an excellent opportunity to examine the ever-increasing vulnerability of US national security and its Department of Defense to space weather. This vulnerability exists for three principal reasons: 1) a massive US space-based infrastructure; 2) an almost exclusive reliance on an aging and stressed continental US power grid; and 3) a direct dependence upon a US economy adapted to the conveniences of space and uninterrupted power. I tailored my research and work for the national security policy maker and military strategists in an endeavor to initiate and inform a substantive dialogue on America's preparation for, and response to, a major solar event that would severely degrade core national security capabilities, such as military operations. Significant risk to the Department of Defense exists from powerful events that could impact its space-based infrastructure and even the terrestrial power grid. Given this ever-present and increasing risk to the United States, my work advocates raising the issue of space weather and its impacts to the level of a national security threat. With the current solar cycle having already peaked and the next projected solar maximum just a decade away, the government has a relatively small window to make policy decisions that prepare the nation and its Defense Department to mitigate impacts from these potentially catastrophic phenomena.

Cockpit display of hazardous weather information

NASA Technical Reports Server (NTRS)

Hansman, R. John, Jr.; Wanke, Craig

1990-01-01

Information transfer and display issues associated with the dissemination of hazardous weather warnings are studied in the context of windshear alerts. Operational and developmental windshear detection systems are briefly reviewed. The July 11, 1988 microburst events observed as part of the Denver Terminal Doppler Weather Radar (TDWR) operational evaluation are analyzed in terms of information transfer and the effectiveness of the microburst alerts. Information transfer, message content and display issues associated with microburst alerts generated from ground based sources are evaluated by means of pilot opinion surveys and part task simulator studies.

[Impact of short weather changes on the population's health risk from ambient air pollution].

PubMed

Novikov, S M; Skvortsova, N S; Kislitsin, V A; Shashina, T A

2007-01-01

The paper considers the negative impact of weather changes in combination with the altered quality of ambient air on the economic and social spheres of society and on the population's health. It describes experience in assessing a possible damage to the health of the Moscow population from exposure to elevated concentrations of ambient air pollutants (suspended matter, nitrogen and sulfur dioxides, carbon oxide). The results of assessment simulation of dissemination of chemicals contained in the emission from the Moscow heat-and-power objects under poor weather conditions are presented.

Development of a resource modelling tool to support decision makers in pandemic influenza preparedness: The AsiaFluCap Simulator

PubMed Central

2012-01-01

Background Health care planning for pandemic influenza is a challenging task which requires predictive models by which the impact of different response strategies can be evaluated. However, current preparedness plans and simulations exercises, as well as freely available simulation models previously made for policy makers, do not explicitly address the availability of health care resources or determine the impact of shortages on public health. Nevertheless, the feasibility of health systems to implement response measures or interventions described in plans and trained in exercises depends on the available resource capacity. As part of the AsiaFluCap project, we developed a comprehensive and flexible resource modelling tool to support public health officials in understanding and preparing for surges in resource demand during future pandemics. Results The AsiaFluCap Simulator is a combination of a resource model containing 28 health care resources and an epidemiological model. The tool was built in MS Excel© and contains a user-friendly interface which allows users to select mild or severe pandemic scenarios, change resource parameters and run simulations for one or multiple regions. Besides epidemiological estimations, the simulator provides indications on resource gaps or surpluses, and the impact of shortages on public health for each selected region. It allows for a comparative analysis of the effects of resource availability and consequences of different strategies of resource use, which can provide guidance on resource prioritising and/or mobilisation. Simulation results are displayed in various tables and graphs, and can also be easily exported to GIS software to create maps for geographical analysis of the distribution of resources. Conclusions The AsiaFluCap Simulator is freely available software (http://www.cdprg.org) which can be used by policy makers, policy advisors, donors and other stakeholders involved in preparedness for providing evidence based and illustrative information on health care resource capacities during future pandemics. The tool can inform both preparedness plans and simulation exercises and can help increase the general understanding of dynamics in resource capacities during a pandemic. The combination of a mathematical model with multiple resources and the linkage to GIS for creating maps makes the tool unique compared to other available software. PMID:23061807

Seamless atmospheric modeling across the hydrostatic-nonhydrostatic scales - preliminary results using an unstructured-Voronoi mesh for weather prediction.

NASA Astrophysics Data System (ADS)

Skamarock, W. C.

2015-12-01

One of the major problems in atmospheric model applications is the representation of deep convection within the models; explicit simulation of deep convection on fine meshes performs much better than sub-grid parameterized deep convection on coarse meshes. Unfortunately, the high cost of explicit convective simulation has meant it has only been used to down-scale global simulations in weather prediction and regional climate applications, typically using traditional one-way interactive nesting technology. We have been performing real-time weather forecast tests using a global non-hydrostatic atmospheric model (the Model for Prediction Across Scales, MPAS) that employs a variable-resolution unstructured Voronoi horizontal mesh (nominally hexagons) to span hydrostatic to nonhydrostatic scales. The smoothly varying Voronoi mesh eliminates many downscaling problems encountered using traditional one- or two-way grid nesting. Our test weather forecasts cover two periods - the 2015 Spring Forecast Experiment conducted at the NOAA Storm Prediction Center during the month of May in which we used a 50-3 km mesh, and the PECAN field program examining nocturnal convection over the US during the months of June and July in which we used a 15-3 km mesh. An important aspect of this modeling system is that the model physics be scale-aware, particularly the deep convection parameterization. These MPAS simulations employ the Grell-Freitas scale-aware convection scheme. Our test forecasts show that the scheme produces a gradual transition in the deep convection, from the deep unstable convection being handled entirely by the convection scheme on the coarse mesh regions (dx > 15 km), to the deep convection being almost entirely explicit on the 3 km NA region of the meshes. We will present results illustrating the performance of critical aspects of the MPAS model in these tests.

Long-term flow-through column experiments and their relevance to natural granitoid weathering rates

USGS Publications Warehouse

White, Arthur F.; Schulz, Marjorie S.; Lawrence, Corey R.; Vivit, Davison V.; Stonestrom, David A.

2017-01-01

Four pairs of fresh and partly-weathered granitoids, obtained from well-characterized watersheds—Merced River, CA, USA; Panola, GA, USA; Loch Vale, CO, USA, and Rio Icacos, Puerto Rico—were reacted in columns under ambient laboratory conditions for 13.8 yrs, the longest running experimental weathering study to date. Low total column mass losses (<1 wt. %), correlated with the absence of pitting or surface roughening of primary silicate grains. BET surface area (SBET) increased, primarily due to Fe-oxyhydroxide precipitation. Surface areas returned to within factors of 2 to 3 of their original values after dithionite extraction. Miscible displacement experiments indicated homogeneous plug flow with negligible immobile water, commonly cited for column experiments. Fresh granitoid effluent solute concentrations initially declined rapidly, followed by much slower decreases over the next decade. Weathered granitoid effluent concentrations increased modestly over the same time period, indicating losses of natural Fe-oxide and/or clay coatings and the increased exposure of primary mineral surfaces. Corresponding (fresh and weathered) elemental effluent concentrations trended toward convergence during the last decade of reaction. NETPATH/PHREEQC code simulations indicated non-stoichiometric dissolution involving Ca release from disseminated calcite and excess K release from interlayer biotite. Effluent 87Sr/85Sr ratios reflected a progressive weathering sequence beginning and ending with 87Sr/85Sr values of plagioclase with an additional calcite input and a radiogenic biotite excursion proportional to the granitoid ages.Effluents became thermodynamically saturated with goethite and gibbsite, slightly under-saturated with kaolinite and strongly under-saturated with plagioclase, consistent with kinetically-limited weathering in which solutes such as Na varied with column flow rates. Effluent Na concentrations showed no clear trend with time during the last decade of reaction (fresh granitoids) or increased slowly with time (weathered granitoids). Analysis of cumulative Na release indicated that plagioclase dissolution achieved steady state in 3 of the 4 fresh granitoids during the last decade of reaction. Surface-area normalized plagioclase dissolution rates exhibited a narrow range (0.95 to 1.26 10-13 moles m-2 s-1), in spite of significant stoichiometric differences (An0.21 to An0.50). Rates were an order of magnitude slower than previously reported in shorter duration experiments but generally 2 to 3 orders of magnitude faster than corresponding natural analogs. CrunchFlow simulations indicated that more than a hundredfold decrease in column flow rates would be required to produce near-saturation reaction affinities that would start to slow plagioclase weathering to real-world levels. Extending simulations to approximate long term weathering in naturally weathered profiles required additional decreases in the intrinsic plagioclase dissolution and kaolinite precipitation rates and relatively large decreases in the fluid flow rate, implying that exposure to reactive mineral surfaces is significantly limited in the natural environment compared to column experiments.

Long-term flow-through column experiments and their relevance to natural granitoid weathering rates

NASA Astrophysics Data System (ADS)

White, Art F.; Schulz, Marjorie S.; Lawrence, Corey R.; Vivit, Davison V.; Stonestrom, David A.

2017-04-01

Four pairs of fresh and partly-weathered granitoids, obtained from well-characterized watersheds-Merced River, CA, USA; Panola, GA, USA; Loch Vale, CO, USA, and Rio Icacos, Puerto Rico-were reacted in columns under ambient laboratory conditions for 13.8 yrs, the longest running experimental weathering study to date. Low total column mass losses (<1 wt.%), correlated with the absence of pitting or surface roughening of primary silicate grains. BET surface area (SBET) increased, primarily due to Fe-oxyhydroxide precipitation. Surface areas returned to within factors of 2-3 of their original values after dithionite extraction. Miscible displacement experiments indicated homogeneous plug flow with negligible immobile water, commonly cited for column experiments. Fresh granitoid effluent solute concentrations initially declined rapidly, followed by much slower decreases over the next decade. Weathered granitoid effluent concentrations increased modestly over the same time period, indicating losses of natural Fe-oxide and/or clay coatings and the increased exposure of primary mineral surfaces. Corresponding (fresh and weathered) elemental effluent concentrations trended toward convergence during the last decade of reaction. NETPATH/PHREEQC code simulations indicated non-stoichiometric dissolution involving Ca release from disseminated calcite and excess K release from interlayer biotite. Effluent 87Sr/85Sr ratios reflected a progressive weathering sequence beginning and ending with 87Sr/85Sr values of plagioclase with an additional calcite input and a radiogenic biotite excursion proportional to the granitoid ages. Effluents became thermodynamically saturated with goethite and gibbsite, slightly under-saturated with kaolinite and strongly under-saturated with plagioclase, consistent with kinetically-limited weathering in which solutes such as Na varied with column flow rates. Effluent Na concentrations showed no clear trend with time during the last decade of reaction (fresh granitoids) or increased slowly with time (weathered granitoids). Analysis of cumulative Na release indicated that plagioclase dissolution achieved steady state in 3 of the 4 fresh granitoids during the last decade of reaction. Surface-area normalized plagioclase dissolution rates exhibited a narrow range (0.95-1.26 10-13 moles m-2 s-1), in spite of significant stoichiometric differences (An0.21 to An0.50). Rates were an order of magnitude slower than previously reported in shorter duration experiments but generally 2-3 orders of magnitude faster than corresponding natural analogs. CrunchFlow simulations indicated that more than a hundredfold decrease in column flow rates would be required to produce near-saturation reaction affinities that would start to slow plagioclase weathering to real-world levels. Extending simulations to approximate long term weathering in naturally weathered profiles required additional decreases in the intrinsic plagioclase dissolution and kaolinite precipitation rates and relatively large decreases in the fluid flow rate, implying that exposure to reactive mineral surfaces is significantly limited in the natural environment compared to column experiments.

Is This Global Warming? Communicating the Intangibles of Climate Change

NASA Astrophysics Data System (ADS)

Warner, L.; Henson, R.

2004-05-01

Unlike weather, which is immediate, tangible, and relevant on a daily basis, climate change is long-term, slow to evolve, and often difficult to relate to the public's daily concerns. By explaining global-change research to wide and diverse audiences through a variety of vehicles, including publications, exhibits, Web sites, and television B-roll, UCAR has gained experience and perspective on the challenges involved. This talk will explore some of the lessons learned and some of the key difficulties that face global-change communicators, including: --The lack of definitive findings on regional effects of global change -- The long time frame in which global change plays out, versus the short attention span of media, the public, and policy makers --The use of weather events as news pegs (they pique interest, but they may not be good exemplars of global change and are difficult to relate directly to changes in greenhouse-gas emissions) --The perils of the traditional journalistic technique of point-counterpoint in discussing climate change --The presence of strong personal/political convictions among various interest groups and how these affect the message(s) conveyed

The NASA Short-term Prediction Research and Transition (SPoRT) Center: A Collaborative Model for Accelerating Research into Operations

NASA Technical Reports Server (NTRS)

Goodman, S. J.; Lapenta, W.; Jedlovec, G.; Dodge, J.; Bradshaw, T.

2003-01-01

The NASA Short-term Prediction Research and Transition (SPoRT) Center in Huntsville, Alabama was created to accelerate the infusion of NASA earth science observations, data assimilation and modeling research into NWS forecast operations and decision-making. The principal focus of experimental products is on the regional scale with an emphasis on forecast improvements on a time scale of 0-24 hours. The SPoRT Center research is aligned with the regional prediction objectives of the US Weather Research Program dealing with 0-1 day forecast issues ranging from convective initiation to 24-hr quantitative precipitation forecasting. The SPoRT Center, together with its other interagency partners, universities, and the NASA/NOAA Joint Center for Satellite Data Assimilation, provides a means and a process to effectively transition NASA Earth Science Enterprise observations and technology to National Weather Service operations and decision makers at both the global/national and regional scales. This paper describes the process for the transition of experimental products into forecast operations, current products undergoing assessment by forecasters, and plans for the future.

A Comparative Analysis of Commercial Off-The-Shelf Naval Simulations and Classic Operations Research Models

DTIC Science & Technology

2009-09-01

69 VI. CONCLUSIONS AND RECOMMENDATIONS ........................73 A. CONCLUSION ........................................73 1. Benefits of Off...simulation software results and similar results produced from the thesis work conducted by Ozdemir (2009). This study directly benefits decision makers...interested in identifying and benefiting from a cost- effective, readily available aggregated learning tool, with the potential to provide tactical

APEX: A Computerized Simulation Game as the Basis for an Undergraduate Interdisciplinary Course.

ERIC Educational Resources Information Center

Tannenbaum, Robert S.

APEX is a computerized gaming simulation; it is also the name of an interdisciplinary course in environmental problems in urban areas introduced at the School of Health Science, Hunter College of the City University of New York. In the course, students assume the roles of decision makers in both the private and public sectors. They receive data…

Communication with U.S. federal decision makers : a primer with notes on the use of computer models as a means of communication.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Webb, Erik Karl; Tidwell, Vincent Carroll

2009-10-01

This document outlines ways to more effectively communicate with U.S. Federal decision makers by outlining the structure, authority, and motivations of various Federal groups, how to find the trusted advisors, and how to structure communication. All three branches of Federal governments have decision makers engaged in resolving major policy issues. The Legislative Branch (Congress) negotiates the authority and the resources that can be used by the Executive Branch. The Executive Branch has some latitude in implementation and prioritizing resources. The Judicial Branch resolves disputes. The goal of all decision makers is to choose and implement the option that best fitsmore » the needs and wants of the community. However, understanding the risk of technical, political and/or financial infeasibility and possible unintended consequences is extremely difficult. Primarily, decision makers are supported in their deliberations by trusted advisors who engage in the analysis of options as well as the day-to-day tasks associated with multi-party negotiations. In the best case, the trusted advisors use many sources of information to inform the process including the opinion of experts and if possible predictive analysis from which they can evaluate the projected consequences of their decisions. The paper covers the following: (1) Understanding Executive and Legislative decision makers - What can these decision makers do? (2) Finding the target audience - Who are the internal and external trusted advisors? (3) Packaging the message - How do we parse and integrate information, and how do we use computer simulation or models in policy communication?« less

Simulation Modeling of Resilience Assessment in Indonesian Fertiliser Industry Supply Networks

NASA Astrophysics Data System (ADS)

Utami, I. D.; Holt, R. J.; McKay, A.

2018-01-01

Supply network resilience is a significant aspect in the performance of the Indonesian fertiliser industry. Decision makers use risk assessment and port management reports to evaluate the availability of infrastructure. An opportunity was identified to incorporate both types of data into an approach for the measurement of resilience. A framework, based on a synthesis of literature and interviews with industry practitioners, covering both social and technical factors is introduced. A simulation model was then built to allow managers to explore implications for resilience and predict levels of risk in different scenarios. Result of interview with respondens from Indonesian fertiliser industry indicated that the simulation model could be valuable in the assessment. This paper provides details of the simulation model for decision makers to explore levels of risk in supply networks. For practitioners, the model could be used by government to assess the current condition of supply networks in Indonesian industries. On the other hand, for academia, the approach provides a new application of agent-based models in research on supply network resilience and presents a real example of how agent-based modeling could be used as to support the assessment approach.

Rain Simulation for the Test of Automotive Surround Sensors

NASA Astrophysics Data System (ADS)

Hasirlioglu, Sinan; Riener, Andreas; Doric, Igor

2017-04-01

The WHO Global Health Observatory data indicates that over 1.25 million people die in traffic accidents annually. To save lives, car manufacturers spend lot of efforts on the development of novel safety systems aiming to avoid or mitigate accidents and provide maximum protection for vehicle occupants as well as vulnerable road users. All the safety features mainly rely on data from surround sensors such as radar, lidar and camera and intelligent vehicles today use these environmental data for instant decision making and vehicle control. As already small errors in sensor data measurements could lead to catastrophes like major injuries or road traffic fatalities, it is of utmost importance to ensure high reliability and accuracy of sensors and safety systems. This work focuses on the influence of environmental factors such as rain conditions, as it is known that rain drops scatter the electromagnetic waves. The result is incorrect measurements with a direct negative impact on environment detection. To identify potential problems of sensors under varying environmental conditions, systems are today tested in real-world settings with two main problems: First, tests are time-consuming and second, environmental conditions are not reproducible. Our approach to test the influence of weather on automotive sensors is to use an indoor rain simulator. Our artificial rain maker, installed at CARISSMA (Center of Automotive Research on Integrated Safety Systems and Measurement Area), is parametrized with rain characteristics measured in the field using a standard disdrometer. System behavior on artificial rain is compared and validated with natural rainfall. With this simulator it is finally possible to test environmental influence at various levels and under reproducible conditions. This saves lot of efforts required for the test process itself and furthermore has a positive impact on the reliability of sensor systems due to the fact that test driven development is enabled.

A Madden-Julian oscillation event realistically simulated by a global cloud-resolving model.

PubMed

Miura, Hiroaki; Satoh, Masaki; Nasuno, Tomoe; Noda, Akira T; Oouchi, Kazuyoshi

2007-12-14

A Madden-Julian Oscillation (MJO) is a massive weather event consisting of deep convection coupled with atmospheric circulation, moving slowly eastward over the Indian and Pacific Oceans. Despite its enormous influence on many weather and climate systems worldwide, it has proven very difficult to simulate an MJO because of assumptions about cumulus clouds in global meteorological models. Using a model that allows direct coupling of the atmospheric circulation and clouds, we successfully simulated the slow eastward migration of an MJO event. Topography, the zonal sea surface temperature gradient, and interplay between eastward- and westward-propagating signals controlled the timing of the eastward transition of the convective center. Our results demonstrate the potential making of month-long MJO predictions when global cloud-resolving models with realistic initial conditions are used.

Numerical simulation of the rapid intensification of Hurricane Katrina (2005): Sensitivity to boundary layer parameterization schemes

NASA Astrophysics Data System (ADS)

Liu, Jianjun; Zhang, Feimin; Pu, Zhaoxia

2017-04-01

Accurate forecasting of the intensity changes of hurricanes is an important yet challenging problem in numerical weather prediction. The rapid intensification of Hurricane Katrina (2005) before its landfall in the southern US is studied with the Advanced Research version of the WRF (Weather Research and Forecasting) model. The sensitivity of numerical simulations to two popular planetary boundary layer (PBL) schemes, the Mellor-Yamada-Janjic (MYJ) and the Yonsei University (YSU) schemes, is investigated. It is found that, compared with the YSU simulation, the simulation with the MYJ scheme produces better track and intensity evolution, better vortex structure, and more accurate landfall time and location. Large discrepancies (e.g., over 10 hPa in simulated minimum sea level pressure) are found between the two simulations during the rapid intensification period. Further diagnosis indicates that stronger surface fluxes and vertical mixing in the PBL from the simulation with the MYJ scheme lead to enhanced air-sea interaction, which helps generate more realistic simulations of the rapid intensification process. Overall, the results from this study suggest that improved representation of surface fluxes and vertical mixing in the PBL is essential for accurate prediction of hurricane intensity changes.

Stress Testing Water Resource Systems at Regional and National Scales with Synthetic Drought Event Sets

NASA Astrophysics Data System (ADS)

Hall, J. W.; Mortazavi-Naeini, M.; Coxon, G.; Guillod, B. P.; Allen, M. R.

2017-12-01

Water resources systems can fail to deliver the services required by water users (and deprive the environment of flow requirements) in many different ways. In an attempt to make systems more resilient, they have also been made more complex, for example through a growing number of large-scale transfers, optimized storages and reuse plants. These systems may be vulnerable to complex variants of hydrological variability in space and time, and behavioural adaptations by water users. In previous research we have used non-parametric stochastic streamflow generators to test the vulnerability of water resource systems. Here we use a very large ensemble of regional climate model outputs from the weather@home crowd-sourced citizen science project, which has generated more than 30,000 years of synthetic weather for present and future climates in the UK and western Europe, using the HadAM3P regional climate model. These simulations have been constructed in order to preserve prolonged drought characteristics, through treatment of long-memory processes in ocean circulations and soil moisture. The weather simulations have been propagated through the newly developed DynaTOP national hydrological for Britain, in order to provide low flow simulations at points of water withdrawal for public water supply, energy and agricultural abstractors. We have used the WATHNET water resource simulation model, set up for the Thames Basin and for all of the large water resource zones in England, to simulate the frequency, severity and duration of water shortages in all of these synthetic weather conditions. In particular, we have sought to explore systemic vulnerabilities associated with inter-basin transfers and the trade-offs between different water users. This analytical capability is providing the basis for (i) implementation of the Duty of Resilience, which has been placed upon the water industry in the 2014 Water Act and (ii) testing reformed abstraction arrangements which the UK government is committed to implementing.

The Portable War Room Research Project

NASA Technical Reports Server (NTRS)

Govers, Francis X., III; Fry, Mark

1997-01-01

The Portable War Room is an internal TASC project to research and develop a visualization and simulation environment to provide for decision makers the power to review the past, understand the present, and peer into the future.

Retrieving Storm Electric Fields from Aircrfaft Field Mill Data: Part II: Applications

NASA Technical Reports Server (NTRS)

Koshak, William; Mach, D. M.; Christian H. J.; Stewart, M. F.; Bateman M. G.

2006-01-01

The Lagrange multiplier theory developed in Part I of this study is applied to complete a relative calibration of a Citation aircraft that is instrumented with six field mill sensors. When side constraints related to average fields are used, the Lagrange multiplier method performs well in computer simulations. For mill measurement errors of 1 V m(sup -1) and a 5 V m(sup -1) error in the mean fair-weather field function, the 3D storm electric field is retrieved to within an error of about 12%. A side constraint that involves estimating the detailed structure of the fair-weather field was also tested using computer simulations. For mill measurement errors of 1 V m(sup -l), the method retrieves the 3D storm field to within an error of about 8% if the fair-weather field estimate is typically within 1 V m(sup -1) of the true fair-weather field. Using this type of side constraint and data from fair-weather field maneuvers taken on 29 June 2001, the Citation aircraft was calibrated. Absolute calibration was completed using the pitch down method developed in Part I, and conventional analyses. The resulting calibration matrices were then used to retrieve storm electric fields during a Citation flight on 2 June 2001. The storm field results are encouraging and agree favorably in many respects with results derived from earlier (iterative) techniques of calibration.

The C20C+ Detection and Attribution Project

NASA Astrophysics Data System (ADS)

Stone, D. A.; Angélil, O. M.; Cholia, S.; Christidis, N.; Dittus, A. J.; Folland, C. K.; King, A.; Kinter, J. L.; Krishnan, H.; Min, S. K.; Shiogama, H.; Wehner, M. F.; Wolski, P.

2015-12-01

Over the past decade there has been a remarkable growth in interest concerning the effects of anthropogenic emissions on extreme weather. However, research has been constrained by the lack of a public climate-model-based data product optimised for investigation of extreme weather in the context of climate change, relying instead on products designed for other purposes or on bespoke simulations designed for the particular study and not generally applicable to other extremes. The international Climate of the 20th Century Plus (C20C+) Detection and Attribution Project is filling this gap by producing the first large ensemble, multi-model, multi-year, and multi-scenario historical climate data product, specifically designed for resolving variations in the occurrence and characteristics of extreme weather from year to year and their differences from what might have been in the absence of anthropogenic emissions. Updates on project status and tens of terabytes of simulation output are available at http://portal.nersc.gov/c20c.Here we describe the experimental design of the first phase of the project, conducted with six atmospheric climate models, and discuss its various strengths and weaknesses with respect to various types of extreme weather. We also present analyses of the relative importance of climate model, estimate of anthropogenic ocean warming, spatial and temporal scale, and aspects of experimental design on estimates of how much emissions have affected extreme weather.

Determining minimum staffing levels during snowstorms using an integrated simulation, regression, and reliability model.

PubMed

Kunkel, Amber; McLay, Laura A

2013-03-01

Emergency medical services (EMS) provide life-saving care and hospital transport to patients with severe trauma or medical conditions. Severe weather events, such as snow events, may lead to adverse patient outcomes by increasing call volumes and service times. Adequate staffing levels during such weather events are critical for ensuring that patients receive timely care. To determine staffing levels that depend on weather, we propose a model that uses a discrete event simulation of a reliability model to identify minimum staffing levels that provide timely patient care, with regression used to provide the input parameters. The system is said to be reliable if there is a high degree of confidence that ambulances can immediately respond to a given proportion of patients (e.g., 99 %). Four weather scenarios capture varying levels of snow falling and snow on the ground. An innovative feature of our approach is that we evaluate the mitigating effects of different extrinsic response policies and intrinsic system adaptation. The models use data from Hanover County, Virginia to quantify how snow reduces EMS system reliability and necessitates increasing staffing levels. The model and its analysis can assist in EMS preparedness by providing a methodology to adjust staffing levels during weather events. A key observation is that when it is snowing, intrinsic system adaptation has similar effects on system reliability as one additional ambulance.

Simulation of all-scale atmospheric dynamics on unstructured meshes

NASA Astrophysics Data System (ADS)

Smolarkiewicz, Piotr K.; Szmelter, Joanna; Xiao, Feng

2016-10-01

The advance of massively parallel computing in the nineteen nineties and beyond encouraged finer grid intervals in numerical weather-prediction models. This has improved resolution of weather systems and enhanced the accuracy of forecasts, while setting the trend for development of unified all-scale atmospheric models. This paper first outlines the historical background to a wide range of numerical methods advanced in the process. Next, the trend is illustrated with a technical review of a versatile nonoscillatory forward-in-time finite-volume (NFTFV) approach, proven effective in simulations of atmospheric flows from small-scale dynamics to global circulations and climate. The outlined approach exploits the synergy of two specific ingredients: the MPDATA methods for the simulation of fluid flows based on the sign-preserving properties of upstream differencing; and the flexible finite-volume median-dual unstructured-mesh discretisation of the spatial differential operators comprising PDEs of atmospheric dynamics. The paper consolidates the concepts leading to a family of generalised nonhydrostatic NFTFV flow solvers that include soundproof PDEs of incompressible Boussinesq, anelastic and pseudo-incompressible systems, common in large-eddy simulation of small- and meso-scale dynamics, as well as all-scale compressible Euler equations. Such a framework naturally extends predictive skills of large-eddy simulation to the global atmosphere, providing a bottom-up alternative to the reverse approach pursued in the weather-prediction models. Theoretical considerations are substantiated by calculations attesting to the versatility and efficacy of the NFTFV approach. Some prospective developments are also discussed.

Communicating Uncertainties in Weather and Climate Information: Results of a National Academies Workshop

NASA Astrophysics Data System (ADS)

Friday, E.; Barron, E. J.; Elfring, C.; Geller, L.

2002-12-01

When a major East Coast snowstorm was forecast during the winter of 2001, people began preparing - both the public and the decision-makers responsible for public services. There was an air of urgency, heightened because just the previous year the region had been hit hard by a storm of unpredicted strength. But this time, the storm never materialized and people were left wondering what went "wrong" with the forecast. Did something go wrong or did forecasters just fail to communicate their information in an effective way? Did they convey a sense of the likelihood of the event and keep people up to date as information changed? In the summer of 2001, the National Academies' Board on Atmospheric Sciences and Climate hosted a workshop designed to explore the communication of uncertainty in weather and climate information. Workshop participants examined five case studies that were chosen to illustrate a range of forecast timescales and certainty levels. The cases were: Red River Flood, Grand Forks, April 1997; East Coast Winter Storm, March 2001; Oklahoma-Kansas Tornado Outbreak, May 3, 1999; El Nino 1997-1998, and Climate Change Science, a report issued in 2001. In each of these cases, participants examined who said what, when, to whom, how, and with what effect. The last two cases specifically address climate-related topics. This paper summarizes the final workshop report (Communicating Uncertainties in Weather and Climate Information: Summary of a Workshop, NRC 2002), including an overview of the five cases and lessons learned about communicating uncertainties in weather and climate forecasts. Among other findings, the report stresses that communication and appropriate dissemination of information, including information about uncertainty in the forecasts and the forecaster's confidence in the product, should be an integral, ongoing part of the forecasting process, not an afterthought. Explaining uncertainty should be an integral part of what weather and climate forecasters do and is essential to delivering accurate and useful information.

Streamflow Impacts of Biofuel Policy-Driven Landscape Change

PubMed Central

Khanal, Sami; Anex, Robert P.; Anderson, Christopher J.; Herzmann, Daryl E.

2014-01-01

Likely changes in precipitation (P) and potential evapotranspiration (PET) resulting from policy-driven expansion of bioenergy crops in the United States are shown to create significant changes in streamflow volumes and increase water stress in the High Plains. Regional climate simulations for current and biofuel cropping system scenarios are evaluated using the same atmospheric forcing data over the period 1979–2004 using the Weather Research Forecast (WRF) model coupled to the NOAH land surface model. PET is projected to increase under the biofuel crop production scenario. The magnitude of the mean annual increase in PET is larger than the inter-annual variability of change in PET, indicating that PET increase is a forced response to the biofuel cropping system land use. Across the conterminous U.S., the change in mean streamflow volume under the biofuel scenario is estimated to range from negative 56% to positive 20% relative to a business-as-usual baseline scenario. In Kansas and Oklahoma, annual streamflow volume is reduced by an average of 20%, and this reduction in streamflow volume is due primarily to increased PET. Predicted increase in mean annual P under the biofuel crop production scenario is lower than its inter-annual variability, indicating that additional simulations would be necessary to determine conclusively whether predicted change in P is a response to biofuel crop production. Although estimated changes in streamflow volume include the influence of P change, sensitivity results show that PET change is the significantly dominant factor causing streamflow change. Higher PET and lower streamflow due to biofuel feedstock production are likely to increase water stress in the High Plains. When pursuing sustainable biofuels policy, decision-makers should consider the impacts of feedstock production on water scarcity. PMID:25289698

Impact of texting on young drivers' behavior and safety on urban and rural roads through a simulation experiment.

PubMed

Yannis, George; Laiou, Alexandra; Papantoniou, Panagiotis; Christoforou, Charalambos

2014-06-01

This research aims to investigate the impact of texting on the behavior and safety of young drivers on urban and rural roads. A driving simulator experiment was carried out in which 34 young participants drove in different driving scenarios; specifically, driving in good weather, in raining conditions, in daylight and in night were examined. Lognormal regression methods were used to investigate the influence of texting as well as various other parameters on the mean speed and mean reaction time. Binary logistic methods were used to investigate the influence of texting use as well as various other parameters in the probability of an accident. It appears that texting leads to statistically significant decrease of the mean speed and increase of the mean reaction time in urban and rural road environment. Simultaneously, it leads to an increased accident probability due to driver distraction and delayed reaction at the moment of the incident. It appeared that drivers using mobile phones with a touch screen present different driving behavior with respect to their speed, however, they had an even higher probability of being involved in an accident. The analysis of the distracted driving performance of drivers who are texting while driving may allow for the identification of measures for the improvement of driving performance (e.g., restrictive measures, training and licensing, information campaigns). The identification of some of the parameters that have an impact on the behavior and safety of young drivers concerning texting and the consequent results can be exploited by policy decision makers in future efforts for the improvement of road safety. Copyright © 2014 Elsevier Ltd. All rights reserved.

Simulated vs. empirical weather responsiveness of crop yields: US evidence and implications for the agricultural impacts of climate change

DOE PAGES

Mistry, Malcolm N.; Wing, Ian Sue; De Cian, Enrica

2017-07-10

Global gridded crop models (GGCMs) are the workhorse of assessments of the agricultural impacts of climate change. Yet the changes in crop yields projected by different models in response to the same meteorological forcing can differ substantially. Through an inter-method comparison, we provide a first glimpse into the origins and implications of this divergence—both among GGCMs and between GGCMs and historical observations. We examine yields of rainfed maize, wheat, and soybeans simulated by six GGCMs as part of the Inter-Sectoral Impact Model Intercomparison Project-Fast Track (ISIMIP-FT) exercise, comparing 1981–2004 hindcast yields over the coterminous United States (US) against US Departmentmore » of Agriculture (USDA) time series for about 1000 counties. Leveraging the empirical climate change impacts literature, we estimate reduced-form econometric models of crop yield responses to temperature and precipitation exposures for both GGCMs and observations. We find that up to 60% of the variance in both simulated and observed yields is attributable to weather variation. A majority of the GGCMs have difficulty reproducing the observed distribution of percentage yield anomalies, and exhibit aggregate responses that show yields to be more weather-sensitive than in the observational record over the predominant range of temperature and precipitation conditions. In conclusion, this disparity is largely attributable to heterogeneity in GGCMs' responses, as opposed to uncertainty in historical weather forcings, and is responsible for widely divergent impacts of climate on future crop yields.« less

Simulated vs. empirical weather responsiveness of crop yields: US evidence and implications for the agricultural impacts of climate change

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mistry, Malcolm N.; Wing, Ian Sue; De Cian, Enrica

Global gridded crop models (GGCMs) are the workhorse of assessments of the agricultural impacts of climate change. Yet the changes in crop yields projected by different models in response to the same meteorological forcing can differ substantially. Through an inter-method comparison, we provide a first glimpse into the origins and implications of this divergence—both among GGCMs and between GGCMs and historical observations. We examine yields of rainfed maize, wheat, and soybeans simulated by six GGCMs as part of the Inter-Sectoral Impact Model Intercomparison Project-Fast Track (ISIMIP-FT) exercise, comparing 1981–2004 hindcast yields over the coterminous United States (US) against US Departmentmore » of Agriculture (USDA) time series for about 1000 counties. Leveraging the empirical climate change impacts literature, we estimate reduced-form econometric models of crop yield responses to temperature and precipitation exposures for both GGCMs and observations. We find that up to 60% of the variance in both simulated and observed yields is attributable to weather variation. A majority of the GGCMs have difficulty reproducing the observed distribution of percentage yield anomalies, and exhibit aggregate responses that show yields to be more weather-sensitive than in the observational record over the predominant range of temperature and precipitation conditions. In conclusion, this disparity is largely attributable to heterogeneity in GGCMs' responses, as opposed to uncertainty in historical weather forcings, and is responsible for widely divergent impacts of climate on future crop yields.« less

An approach to secure weather and climate models against hardware faults

NASA Astrophysics Data System (ADS)

Düben, Peter D.; Dawson, Andrew

2017-03-01

Enabling Earth System models to run efficiently on future supercomputers is a serious challenge for model development. Many publications study efficient parallelization to allow better scaling of performance on an increasing number of computing cores. However, one of the most alarming threats for weather and climate predictions on future high performance computing architectures is widely ignored: the presence of hardware faults that will frequently hit large applications as we approach exascale supercomputing. Changes in the structure of weather and climate models that would allow them to be resilient against hardware faults are hardly discussed in the model development community. In this paper, we present an approach to secure the dynamical core of weather and climate models against hardware faults using a backup system that stores coarse resolution copies of prognostic variables. Frequent checks of the model fields on the backup grid allow the detection of severe hardware faults, and prognostic variables that are changed by hardware faults on the model grid can be restored from the backup grid to continue model simulations with no significant delay. To justify the approach, we perform model simulations with a C-grid shallow water model in the presence of frequent hardware faults. As long as the backup system is used, simulations do not crash and a high level of model quality can be maintained. The overhead due to the backup system is reasonable and additional storage requirements are small. Runtime is increased by only 13 % for the shallow water model.

An approach to secure weather and climate models against hardware faults

NASA Astrophysics Data System (ADS)

Düben, Peter; Dawson, Andrew

2017-04-01

Enabling Earth System models to run efficiently on future supercomputers is a serious challenge for model development. Many publications study efficient parallelisation to allow better scaling of performance on an increasing number of computing cores. However, one of the most alarming threats for weather and climate predictions on future high performance computing architectures is widely ignored: the presence of hardware faults that will frequently hit large applications as we approach exascale supercomputing. Changes in the structure of weather and climate models that would allow them to be resilient against hardware faults are hardly discussed in the model development community. We present an approach to secure the dynamical core of weather and climate models against hardware faults using a backup system that stores coarse resolution copies of prognostic variables. Frequent checks of the model fields on the backup grid allow the detection of severe hardware faults, and prognostic variables that are changed by hardware faults on the model grid can be restored from the backup grid to continue model simulations with no significant delay. To justify the approach, we perform simulations with a C-grid shallow water model in the presence of frequent hardware faults. As long as the backup system is used, simulations do not crash and a high level of model quality can be maintained. The overhead due to the backup system is reasonable and additional storage requirements are small. Runtime is increased by only 13% for the shallow water model.

Evaluating the Impact of Aerosols on Numerical Weather Prediction

NASA Astrophysics Data System (ADS)

Freitas, Saulo; Silva, Arlindo; Benedetti, Angela; Grell, Georg; Members, Wgne; Zarzur, Mauricio

2015-04-01

The Working Group on Numerical Experimentation (WMO, http://www.wmo.int/pages/about/sec/rescrosscut/resdept_wgne.html) has organized an exercise to evaluate the impact of aerosols on NWP. This exercise will involve regional and global models currently used for weather forecast by the operational centers worldwide and aims at addressing the following questions: a) How important are aerosols for predicting the physical system (NWP, seasonal, climate) as distinct from predicting the aerosols themselves? b) How important is atmospheric model quality for air quality forecasting? c) What are the current capabilities of NWP models to simulate aerosol impacts on weather prediction? Toward this goal we have selected 3 strong or persistent events of aerosol pollution worldwide that could be fairly represented in current NWP models and that allowed for an evaluation of the aerosol impact on weather prediction. The selected events includes a strong dust storm that blew off the coast of Libya and over the Mediterranean, an extremely severe episode of air pollution in Beijing and surrounding areas, and an extreme case of biomass burning smoke in Brazil. The experimental design calls for simulations with and without explicitly accounting for aerosol feedbacks in the cloud and radiation parameterizations. In this presentation we will summarize the results of this study focusing on the evaluation of model performance in terms of its ability to faithfully simulate aerosol optical depth, and the assessment of the aerosol impact on the predictions of near surface wind, temperature, humidity, rainfall and the surface energy budget.

Separate and combined sewer systems: a long-term modelling approach.

PubMed

Mannina, Giorgio; Viviani, Gaspare

2009-01-01

Sewer systems convey mostly dry weather flow, coming from domestic and industrial sanitary sewage as well as infiltration flow, and stormwater due to meteoric precipitations. Traditionally, in urban drainage two types of sewer systems are adopted: separate and combined sewers. The former convey dry and wet weather flow separately into two different networks, while the latter convey dry and wet weather flow together. Which is the best solution in terms of cost-benefit analysis still remains a controversial subject. The present study was aimed at comparing the pollution loads discharged to receiving bodies by Wastewater Treatment Plant (WWTP) and Combined Sewer Overflow (CSO) for different kinds of sewer systems (combined and separate). To accomplish this objective, a comparison between the two systems was carried out using results from simulations of catchments characterised by different dimensions, population densities and water supply rate. The analysis was based on a parsimonious mathematical model able to simulate the sewer system as well as the WWTP during both dry and wet weather. The rain series employed for the simulations was six years long. Several pollutants, both dissolved and particulate, were modelled. The results confirmed the uncertainties in the choice of one system versus the other, emphasising the concept that case-by-case solutions have to be undertaken. Further, the compared systems showed different responses in terms of effectiveness in reducing the discharged mass to the RWB in relation to the particular pollutant taken into account.

Simulated vs. empirical weather responsiveness of crop yields: US evidence and implications for the agricultural impacts of climate change

NASA Astrophysics Data System (ADS)

Mistry, Malcolm N.; Wing, Ian Sue; De Cian, Enrica

2017-07-01

Global gridded crop models (GGCMs) are the workhorse of assessments of the agricultural impacts of climate change. Yet the changes in crop yields projected by different models in response to the same meteorological forcing can differ substantially. Through an inter-method comparison, we provide a first glimpse into the origins and implications of this divergence—both among GGCMs and between GGCMs and historical observations. We examine yields of rainfed maize, wheat, and soybeans simulated by six GGCMs as part of the Inter-Sectoral Impact Model Intercomparison Project-Fast Track (ISIMIP-FT) exercise, comparing 1981-2004 hindcast yields over the coterminous United States (US) against US Department of Agriculture (USDA) time series for about 1000 counties. Leveraging the empirical climate change impacts literature, we estimate reduced-form econometric models of crop yield responses to temperature and precipitation exposures for both GGCMs and observations. We find that up to 60% of the variance in both simulated and observed yields is attributable to weather variation. A majority of the GGCMs have difficulty reproducing the observed distribution of percentage yield anomalies, and exhibit aggregate responses that show yields to be more weather-sensitive than in the observational record over the predominant range of temperature and precipitation conditions. This disparity is largely attributable to heterogeneity in GGCMs’ responses, as opposed to uncertainty in historical weather forcings, and is responsible for widely divergent impacts of climate on future crop yields.

Performance simulation of a grid connected photovoltaic power system using TRNSYS 17

NASA Astrophysics Data System (ADS)

Raja Sekhar, Y.; Ganesh, D.; Kumar, A. Suresh; Abraham, Raju; Padmanathan, P.

2017-11-01

Energy plays an important role in a country’s economic growth in the current energy scenario, the major problem is depletion of energy sources (non-renewable) are more than being formed. One of the prominent solutions is minimizing the use of fossil fuels by utilization of renewable energy resources. A photovoltaic system is an efficient option in terms of utilizing the solar energy resource. The electricity output produced by the photovoltaic systems depends upon the incident solar radiation. This paper examines the performance simulation of 200KW photovoltaic power system at VIT University, Vellore. The main objective of this paper is to correlate the results between the predicted simulation data and the experimental data. The simulation tool used here is TRNSYS. Using TRNSYS modelling prediction of electricity produced throughout the year can be calculated with the help of TRNSYS weather station. The deviation of the simulated results with the experimented results varies due to the choice of weather station. Results from the field test and simulation results are to be correlated to attain the maximum performance of the system.

Climate services in the tourism sector - examples and market research

NASA Astrophysics Data System (ADS)

Damm, Andrea; Köberl, Judith; Prettenthaler, Franz; Kortschak, Dominik; Hofer, Marianne; Winkler, Claudia

2017-04-01

Tourism is one of the most weather-sensitive sectors. Hence, dealing with weather and climate risks is an important part of operational risk management. WEDDA® (WEather Driven Demand Analysis), developed by Joanneum Research, represents a comprehensive and flexible toolbox for managing weather and climate risks. Modelling the demand for products or services of a particular economic sector or company and its weather and climate sensitivity usually forms the starting and central point of WEDDA®. Coupling the calibrated demand models to either long-term climate scenarios or short-term weather forecasts enables the use of WEDDA® for the following areas of application: (i) implementing short-term forecasting systems for the prediction of the considered indicator; (ii) quantifying the weather risk of a particular economic sector or company using parameters from finance (e.g. Value-at-Risk); (iii) assessing the potential impacts of changing climatic conditions on a particular economic sector or company. WEDDA® for short-term forecasts on the demand for products or services is currently used by various tourism businesses, such as open-air swimming pools, ski areas, and restaurants. It supports tourism and recreation facilities to better cope with (increasing) weather variability by optimizing the disposability of staff, resources and merchandise according to expected demand. Since coping with increasing weather variability forms one of the challenges with respect to climate change, WEDDA® may become an important component within a whole pool of weather and climate services designed to support tourism and recreation facilities to adapt to climate change. Climate change impact assessments at European scale, as conducted in the EU-FP7 project IMPACT2C, provide basic information of climate change impacts on tourism demand not only for individual tourism businesses, but also for regional and national tourism planners and policy makers interested in benchmarks for the vulnerability of their tourism destination. In this project we analysed the impacts of +2 °C global warming on winter tourism demand in ski tourism related regions in Europe. In order to achieve the climate targets, tailored climate information services - for individual businesses as well as at the regional and national level - play an important role. The current market, however, is still in the early stages. In the ongoing H2020 projects EU-MACS (www.eu-macs.eu) and MARCO (www.marco-h2020.eu) (Nov 2016 - Oct 2018) Joanneum Research explores the climate services market in the tourism sector. The current use of climate services is reviewed in detail and in an interactive process key market barriers and enablers will be identified in close collaboration with stakeholders from the tourism industry. The analysis and co-development of new climate services concepts for the tourism sector aims to reduce the gaps between climate services supply and demand.

Modeling fire behavior on tropical islands with high-resolution weather data

Treesearch

John W. Benoit; Francis M. Fujioka; David R. Weise

2009-01-01

In this study, we consider fire behavior simulation in tropical island scenarios such as Hawaii and Puerto Rico. The development of a system to provide real-time fire behavior prediction in Hawaii is discussed. This involves obtaining fuels and topography information at a fine scale, as well as supplying daily high-resolution weather forecast data for the area of...

Climatic variability of a fire-weather index based on turbulent kinetic energy and the Haines Index

Treesearch

Warren E. Heilman; Xindi Bian

2010-01-01

Combining the Haines Index (HI) with near-surface turbulent kinetic energy (TKEs) through a product of the two values (HITKEs) has shown promise as an indicator of the atmospheric potential for extreme and erratic fire behavior in the U.S. Numerical simulations of fire-weather evolution during past wildland fire episodes in...

Accelerating Climate and Weather Simulations through Hybrid Computing

NASA Technical Reports Server (NTRS)

Zhou, Shujia; Cruz, Carlos; Duffy, Daniel; Tucker, Robert; Purcell, Mark

2011-01-01

Unconventional multi- and many-core processors (e.g. IBM (R) Cell B.E.(TM) and NVIDIA (R) GPU) have emerged as effective accelerators in trial climate and weather simulations. Yet these climate and weather models typically run on parallel computers with conventional processors (e.g. Intel, AMD, and IBM) using Message Passing Interface. To address challenges involved in efficiently and easily connecting accelerators to parallel computers, we investigated using IBM's Dynamic Application Virtualization (TM) (IBM DAV) software in a prototype hybrid computing system with representative climate and weather model components. The hybrid system comprises two Intel blades and two IBM QS22 Cell B.E. blades, connected with both InfiniBand(R) (IB) and 1-Gigabit Ethernet. The system significantly accelerates a solar radiation model component by offloading compute-intensive calculations to the Cell blades. Systematic tests show that IBM DAV can seamlessly offload compute-intensive calculations from Intel blades to Cell B.E. blades in a scalable, load-balanced manner. However, noticeable communication overhead was observed, mainly due to IP over the IB protocol. Full utilization of IB Sockets Direct Protocol and the lower latency production version of IBM DAV will reduce this overhead.

Defining the `negative emission' capacity of global agriculture deployed for enhanced rock weathering

NASA Astrophysics Data System (ADS)

Beerling, D. J.; Taylor, L.; Banwart, S. A.; Kantzas, E. P.; Lomas, M.; Mueller, C.; Ridgwell, A.; Quegan, S.

2016-12-01

Enhanced rock weathering involves application of crushed silicates (e.g. basalt) to the landscape to accelerate their chemical breakdown to release base cations and form bicarbonate that ultimate sequester CO2 in the oceans. Global croplands cover an area of 12 million km2 and might be deployed for long-term removal of anthropogenic CO2 through enhanced rock weathering with a number of co-benefits for food security. This presentation assesses the potential of this strategy to contribute to `negative emissions' as defined by a suite of simulations coupling a detailed model of rock grain weathering by crop root-microbial processes with a managed land dynamic global vegetation model driven by the `business as usual' future climate change scenarios. We calculate potential atmospheric CO2 drawdown over the next century by introducing a strengthened C-sink term into the global carbon cycle model within an intermediate complexity Earth system model. Our simulations indicate agricultural lands deployed in this way constitute a `low tech' biological negative emissions strategy. As part of a wider portfolio of options, this strategy might contribute to limiting future warming to 2oC, subject to economic costs and energy requirements.

Simulating air temperature in an urban street canyon in all weather conditions using measured data at a reference meteorological station

NASA Astrophysics Data System (ADS)

Erell, E.; Williamson, T.

2006-10-01

A model is proposed that adapts data from a standard meteorological station to provide realistic site-specific air temperature in a city street exposed to the same meso-scale environment. In addition to a rudimentary description of the two sites, the canyon air temperature (CAT) model requires only inputs measured at standard weather stations; yet it is capable of accurately predicting the evolution of air temperature in all weather conditions for extended periods. It simulates the effect of urban geometry on radiant exchange; the effect of moisture availability on latent heat flux; energy stored in the ground and in building surfaces; air flow in the street based on wind above roof height; and the sensible heat flux from individual surfaces and from the street canyon as a whole. The CAT model has been tested on field data measured in a monitoring program carried out in Adelaide, Australia, in 2000-2001. After calibrating the model, predicted air temperature correlated well with measured data in all weather conditions over extended periods. The experimental validation provides additional evidence in support of a number of parameterisation schemes incorporated in the model to account for sensible heat and storage flux.

Using 3-D Numerical Weather Data in Piloted Simulations

NASA Technical Reports Server (NTRS)

Daniels, Taumi S.

2016-01-01

This report describes the process of acquiring and using 3-D numerical model weather data sets in NASA Langley's Research Flight Deck (RFD). A set of software tools implement the process and can be used for other purposes as well. Given time and location information of a weather phenomenon of interest, the user can download associated numerical weather model data. These data are created by the National Oceanic and Atmospheric Administration (NOAA) High Resolution Rapid Refresh (HRRR) model, and are then processed using a set of Mathworks' Matlab(TradeMark) scripts to create the usable 3-D weather data sets. Each data set includes radar re ectivity, water vapor, component winds, temperature, supercooled liquid water, turbulence, pressure, altitude, land elevation, relative humidity, and water phases. An open-source data processing program, wgrib2, is available from NOAA online, and is used along with Matlab scripts. These scripts are described with sucient detail to make future modi cations. These software tools have been used to generate 3-D weather data for various RFD experiments.

Indoor test and long-term weathering effects on the thermal performance of the solar energy system (liquid) solar collector. [Marshall Space Flight Center solar test facility and solar simulator

NASA Technical Reports Server (NTRS)

1979-01-01

The procedures used and the results obtained during the evaluation test program on a liquid solar collector are presented. The narrow flat plate collector with reflective concentrating mirrors uses water as the working fluid. The double-covered collector weighs 137 pounds and has overall dimensions of about 35" by 77" by 6.75". The test program was conducted to obtain the following information: thermal performance data under simulated conditions, structural behavior under static load, and the effects of long term exposure to natural weathering.

Mathematical simulation of water and salt transfer in geosystems of solonetzic soils in the Northern Caspian region

NASA Astrophysics Data System (ADS)

Golovanov, A. I.; Sotneva, N. I.

2009-03-01

The Dzhanybek two-dimensional radial-axial mathematical model was developed for water and salt transfer in geosystems of solonetzic complexes of the Northern Caspian region; the model is capable of considering the geochemical links and revealing the features of migration processes between the conjugated elements of the microcatena. The simulation results suggested that the stabilization of salinization-desalinization processes occurs under stable weather conditions within approximately 100 years. When the weather conditions changed (the total moisture pool of the area increased from 1978), the simulation results indicated a tendency toward salinization of dark-colored soils in microdepressions and removal of salts in the upper 1-m thick soil layer on microhighs and microslopes. Predictions for 2040 showed that a deep accumulation of salts in microdepressions and desalinization of soils of microhighs and microslopes will occur under the current weather conditions. Thus, the changes in the halogeochemical capacity of geosystems of solonetzic complexes primarily depend on the climatic conditions, although the capacity value remains almost constant with increasing total water reserves; the changes occur only between the conjugated soils of solonetzic complexes, which is of great importance for predicting the soil-geochemical status of the entire landscape.

Simulation of the trajectory of microwaves during passage of Mesoescale Convective System over Southern Brazil

NASA Astrophysics Data System (ADS)

Diniz, F. L.; Munchow, G. B.; Herdies, D. L.; Foster, P. R.

2010-12-01

When the eletromagnetic wave travels in the atmosphere from one medium to another with different density and/or composition suffers small changes in speed and direction of propagation. These changes are caused by the vertical variation of atmospheric refractive index. This causes different types of trajectory deviations, which can be called: normal refraction, sub-refraction, super-refraction and duct. The condition to create duct is satisfied when there is a especific vertical profile of refraction, in this case an eletromagnectic wave will oscillate in a layer of the atmosphere. Considering that this ducts condition can causes damage in the transmission and reception of microwave system equipment (e.g. telecomunications, global positioning, weather radars and satellites) and that in the Rio Grande do Sul, state of Brazil, there are two weather radars, this study present a simulation of the trajectory that would have an eletromagnetic wave. In this study was used soundings of the atmosphere to infer the vertical profile of refractive index during the passage of a Mesoescale Convective System on September 7, 2009. In the lack of this data a numerical simulation with nested grids using Weather Research & Forecasting Model was performed to infer this.

Estimating risks of heat strain by age and sex: a population-level simulation model.

PubMed

Glass, Kathryn; Tait, Peter W; Hanna, Elizabeth G; Dear, Keith

2015-05-18

Individuals living in hot climates face health risks from hyperthermia due to excessive heat. Heat strain is influenced by weather exposure and by individual characteristics such as age, sex, body size, and occupation. To explore the population-level drivers of heat strain, we developed a simulation model that scales up individual risks of heat storage (estimated using Myrup and Morgan's man model "MANMO") to a large population. Using Australian weather data, we identify high-risk weather conditions together with individual characteristics that increase the risk of heat stress under these conditions. The model identifies elevated risks in children and the elderly, with females aged 75 and older those most likely to experience heat strain. Risk of heat strain in males does not increase as rapidly with age, but is greatest on hot days with high solar radiation. Although cloudy days are less dangerous for the wider population, older women still have an elevated risk of heat strain on hot cloudy days or when indoors during high temperatures. Simulation models provide a valuable method for exploring population level risks of heat strain, and a tool for evaluating public health and other government policy interventions.

Pyrite oxidation under simulated acid rain weathering conditions.

PubMed

Zheng, Kai; Li, Heping; Wang, Luying; Wen, Xiaoying; Liu, Qingyou

2017-09-01

We investigated the electrochemical corrosion behavior of pyrite in simulated acid rain with different acidities and at different temperatures. The cyclic voltammetry, polarization curve, and electrochemical impedance spectroscopy results showed that pyrite has the same electrochemical interaction mechanism under different simulated acid rain conditions, regardless of acidity or environmental temperature. Either stronger acid rain acidity or higher environmental temperature can accelerate pyrite corrosion. Compared with acid rain having a pH of 5.6 at 25 °C, the prompt efficiency of pyrite weathering reached 104.29% as the acid rain pH decreased to 3.6, and it reached 125.31% as environmental temperature increased to 45 °C. Increasing acidity dramatically decreases the charge transfer resistance, and increasing temperature dramatically decreases the passivation film resistance, when other conditions are held constant. Acid rain always causes lower acidity mine drainage, and stronger acidity or high environmental temperatures cause serious acid drainage. The natural parameters of latitude, elevation, and season have considerable influence on pyrite weathering, because temperature is an important influencing factor. These experimental results are of direct significance for the assessment and management of sulfide mineral acid drainage in regions receiving acid rain.

Intra-seasonal risk of agriculturally-relevant weather extremes in West African Sudan Savanna

NASA Astrophysics Data System (ADS)

Boansi, David; Tambo, Justice A.; Müller, Marc

2018-01-01

Using household survey data and historical daily climate data for 29 communities across Upper East Ghana and Southwest Burkina Faso, we document climatic conditions deemed major threat to farming in the West African Sudan Savanna and assess risks posed by such conditions over the period 1997-2014. Based on farmers' perception, it is found that drought, low rainfall, intense precipitation, flooding, erratic rainfall pattern, extremely high temperatures, delayed rains, and early cessation of rains are the major threats farmers face. Using first-order Markov chain model and relevant indices for monitoring weather extremes, it is discovered that climatic risk is a general inherent attribute of the rainy season in the study area. Due to recent changes in onset of rains and length of the rainy season, some farmers have either resorted to early planting of drought-hardy crops, late planting of drought-sensitive crops, or spreading of planting across the first 3 months of the season to moderate harm. Each of these planting decisions however has some risk implications. The months of May, June, and October are found to be more susceptible to relatively longer duration of dry and hot spells, while July, August, and September are found to be more susceptible to intense precipitation and flooding. To moderate harm from anticipated weather extremes, farmers need to adjust their cropping calendar, adopt appropriate crop varieties, and implement soil and water management practices. For policy makers and other stakeholders, we recommend the supply of timely and accurate weather forecasts to guide farmers in their seasonal cropping decisions and investment in/installation of low cost irrigation facilities to enhance the practice of supplemental irrigation.

Investigating the feasibility of Visualising Complex Space Weather Data in a CAVE

NASA Astrophysics Data System (ADS)

Loughlin, S.; Habash Krause, L.

2013-12-01

The purpose of this study was to investigate the feasibility of visualising complex space weather data in a Cave Automatic Virtual Environment (CAVE). Space weather is increasingly causing disruptions on Earth, such as power outages and disrupting communication to satellites. We wanted to display this space weather data within the CAVE since the data from instruments, models and simulations are typically too complex to understand on their own, especially when they are of 7 dimensions. To accomplish this, I created a VTK to NetCDF converter. NetCDF is a science data format, which stores array oriented scientific data. The format is maintained by the University Corporation for Atmospheric Research, and is used extensively by the atmospheric and space communities.

The dependence of magnetosphere-ionosphere system on the Earth's magnetic dipole moment

NASA Astrophysics Data System (ADS)

Ngwira, C. M.; Pulkkinen, A. A.; Sibeck, D. G.; Rastaetter, L.

2017-12-01

Space weather is increasingly recognized as an international problem affecting several different man-made technologies. The ability to understand, monitor and forecast Earth-directed space weather is of paramount importance for our highly technology-dependent society and for the current rapid developments in awareness and exploration within the heliosphere. It is well known that the strength of the Earth's magnetic field changes over long time scales. We use physics-based simulations with the University of Michigan Space Weather Modeling Framework (SWMF) to examine how the magnetosphere, ionosphere, and ground geomagnetic field perturbations respond as the geomagnetic dipole moment changes. We discuss the implication of these results for our community and the end-users of space weather information.

The Future of Planetary Climate Modeling and Weather Prediction

NASA Technical Reports Server (NTRS)

Del Genio, A. D.; Domagal-Goldman, S. D.; Kiang, N. Y.; Kopparapu, R. K.; Schmidt, G. A.; Sohl, L. E.

2017-01-01

Modeling of planetary climate and weather has followed the development of tools for studying Earth, with lags of a few years. Early Earth climate studies were performed with 1-dimensionalradiative-convective models, which were soon fol-lowed by similar models for the climates of Mars and Venus and eventually by similar models for exoplan-ets. 3-dimensional general circulation models (GCMs) became common in Earth science soon after and within several years were applied to the meteorology of Mars, but it was several decades before a GCM was used to simulate extrasolar planets. Recent trends in Earth weather and and climate modeling serve as a useful guide to how modeling of Solar System and exoplanet weather and climate will evolve in the coming decade.

A basis set for exploration of sensitivity to prescribed ocean conditions for estimating human contributions to extreme weather in CAM5.1-1degree

DOE Office of Scientific and Technical Information (OSTI.GOV)

Stone, Dáithí A.; Risser, Mark D.; Angélil, Oliver M.

This paper presents two contributions for research into better understanding the role of anthropogenic warming in extreme weather. The first contribution is the generation of a large number of multi-decadal simulations using a medium-resolution atmospheric climate model, CAM5.1-1degree, under two scenarios of historical climate following the protocols of the C20C+ Detection and Attribution project: the one we have experienced (All-Hist), and one that might have been experienced in the absence of human interference with the climate system (Nat-Hist). These simulations are also specifically designed for understanding extreme weather and atmospheric variability in the context of anthropogenic climate change.The second contributionmore » takes advantage of the duration and size of these simulations in order to identify features of variability in the prescribed ocean conditions that may strongly influence calculated estimates of the role of anthropogenic emissions on extreme weather frequency (event attribution). There is a large amount of uncertainty in how much anthropogenic emissions should warm regional ocean surface temperatures, yet contributions to the C20C+ Detection and Attribution project and similar efforts so far use only one or a limited number of possible estimates of the ocean warming attributable to anthropogenic emissions when generating their Nat-Hist simulations. Thus, the importance of the uncertainty in regional attributable warming estimates to the results of event attribution studies is poorly understood. The identification of features of the anomalous ocean state that seem to strongly influence event attribution estimates should therefore be able to serve as a basis set for effective sampling of other plausible attributable warming patterns. The identification performed in this paper examines monthly temperature and precipitation output from the CAM5.1-1degree simulations averaged over 237 land regions, and compares interannual anomalous variations in the ratio between the frequencies of extremes in the All-Hist and Nat-Hist simulations against variations in ocean temperatures.« less

A basis set for exploration of sensitivity to prescribed ocean conditions for estimating human contributions to extreme weather in CAM5.1-1degree

DOE PAGES

Stone, Dáithí A.; Risser, Mark D.; Angélil, Oliver M.; ...

2018-03-01

This paper presents two contributions for research into better understanding the role of anthropogenic warming in extreme weather. The first contribution is the generation of a large number of multi-decadal simulations using a medium-resolution atmospheric climate model, CAM5.1-1degree, under two scenarios of historical climate following the protocols of the C20C+ Detection and Attribution project: the one we have experienced (All-Hist), and one that might have been experienced in the absence of human interference with the climate system (Nat-Hist). These simulations are also specifically designed for understanding extreme weather and atmospheric variability in the context of anthropogenic climate change.The second contributionmore » takes advantage of the duration and size of these simulations in order to identify features of variability in the prescribed ocean conditions that may strongly influence calculated estimates of the role of anthropogenic emissions on extreme weather frequency (event attribution). There is a large amount of uncertainty in how much anthropogenic emissions should warm regional ocean surface temperatures, yet contributions to the C20C+ Detection and Attribution project and similar efforts so far use only one or a limited number of possible estimates of the ocean warming attributable to anthropogenic emissions when generating their Nat-Hist simulations. Thus, the importance of the uncertainty in regional attributable warming estimates to the results of event attribution studies is poorly understood. The identification of features of the anomalous ocean state that seem to strongly influence event attribution estimates should therefore be able to serve as a basis set for effective sampling of other plausible attributable warming patterns. The identification performed in this paper examines monthly temperature and precipitation output from the CAM5.1-1degree simulations averaged over 237 land regions, and compares interannual anomalous variations in the ratio between the frequencies of extremes in the All-Hist and Nat-Hist simulations against variations in ocean temperatures.« less

Sobol’ sensitivity analysis for stressor impacts on honeybee colonies

EPA Science Inventory

We employ Monte Carlo simulation and nonlinear sensitivity analysis techniques to describe the dynamics of a bee exposure model, VarroaPop. Daily simulations are performed of hive population trajectories, taking into account queen strength, foraging success, mite impacts, weather...

SPAGETTA: a Multi-Purpose Gridded Stochastic Weather Generator

NASA Astrophysics Data System (ADS)

Dubrovsky, M.; Huth, R.; Rotach, M. W.; Dabhi, H.

2017-12-01

SPAGETTA is a new multisite/gridded multivariate parametric stochastic weather generator (WG). Site-specific precipitation occurrence and amount are modelled by Markov chain and Gamma distribution, the non-precipitation variables are modelled by an autoregressive (AR) model conditioned on precipitation occurrence, and the spatial coherence of all variables is modelled following the Wilks' (2009) approach. SPAGETTA may be run in two modes. Mode 1: it is run as a classical WG, which is calibrated using weather series from multiple sites, and only then it may produce arbitrarily long synthetic series mimicking the spatial and temporal structure of the calibration data. To generate the weather series representing the future climate, the WG parameters are modified according to the climate change scenario, typically derived from GCM or RCM simulations. Mode 2: the user provides only basic information (not necessarily to be realistic) on the temporal and spatial auto-correlation structure of the weather variables and their mean annual cycle; the generator itself derives the parameters of the underlying AR model, which produces the multi-site weather series. Optionally, the user may add the spatially varying trend, which is superimposed to the synthetic series. The contribution consists of following parts: (a) Model of the WG. (b) Validation of WG in terms of the spatial temperature and precipitation characteristics, including characteristics of spatial hot/cold/dry/wet spells. (c) Results of the climate change impact experiment, in which the WG parameters representing the spatial and temporal variability are modified using the climate change scenarios and the effect on the above spatial validation indices is analysed. In this experiment, the WG is calibrated using the E-OBS gridded daily weather data for several European regions, and the climate change scenarios are derived from the selected RCM simulations (CORDEX database). (d) The second mode of operation will be demonstrated by results obtained while developing the methodology for assessing collective significance of trends in multi-site weather series. The performance of the proposed test statistics is assessed based on large number of realisations of synthetic series produced by WG assuming a given statistical structure and trend of the weather series.

The importance of terrestrial weathering for climate system modelling on extended timescales: a study with the UVic ESCM

NASA Astrophysics Data System (ADS)

Brault, Marc-Olivier; Matthews, Damon; Mysak, Lawrence

2016-04-01

The chemical erosion of carbonate and silicate rocks is a key process in the global carbon cycle and, through its coupling with calcium carbonate deposition in the ocean, is the primary sink of carbon on geologic timescales. The dynamic interdependence of terrestrial weathering rates with atmospheric temperature and carbon dioxide concentrations is crucial to the regulation of Earth's climate over multi-millennial timescales. However any attempts to develop a modeling context for terrestrial weathering as part of a dynamic climate system are limited, mostly because of the difficulty in adapting the multi-millennial timescales of the implied negative feedback mechanism with those of the atmosphere and ocean. Much of the earlier work on this topic is therefore based on box-model approaches, abandoning spatial variability for the sake of computational efficiency and the possibility to investigate the impact of weathering on climate change over time frames much longer than those allowed by traditional climate system models. As a result we still have but a rudimentary understanding of the chemical weathering feedback mechanism and its effects on ocean biogeochemistry and atmospheric CO2. Here, we introduce a spatially-explicit, rock weathering model into the University of Victoria Earth System Climate Model (UVic ESCM). We use a land map which takes into account a number of different rock lithologies, changes in sea level, as well as an empirical model of the temperature and NPP dependency of weathering rates for the different rock types. We apply this new model to the last deglacial period (c. 21000BP to 13000BP) as well as a future climate change scenario (c. 1800AD to 6000AD+), comparing the results of our 2-D version of the weathering feedback mechanism to simulations using only the box-model parameterizations of Meissner et al. [2012]. These simulations reveal the importance of two-dimensional factors (i.e., changes in sea level and rock type distribution) in the role of the weathering negative feedback mechanism on multi-millennial timescales.

Community Coordinated Modeling Center (CCMC): Using innovative tools and services to support worldwide space weather scientific communities and networks

NASA Astrophysics Data System (ADS)

Mendoza, A. M.; Bakshi, S.; Berrios, D.; Chulaki, A.; Evans, R. M.; Kuznetsova, M. M.; Lee, H.; MacNeice, P. J.; Maddox, M. M.; Mays, M. L.; Mullinix, R. E.; Ngwira, C. M.; Patel, K.; Pulkkinen, A.; Rastaetter, L.; Shim, J.; Taktakishvili, A.; Zheng, Y.

2012-12-01

Community Coordinated Modeling Center (CCMC) was established to enhance basic solar terrestrial research and to aid in the development of models for specifying and forecasting conditions in the space environment. In achieving this goal, CCMC has developed and provides a set of innovative tools varying from: Integrated Space Weather Analysis (iSWA) web -based dissemination system for space weather information, Runs-On-Request System providing access to unique collection of state-of-the-art solar and space physics models (unmatched anywhere in the world), Advanced Online Visualization and Analysis tools for more accurate interpretation of model results, Standard Data formats for Simulation Data downloads, and recently Mobile apps (iPhone/Android) to view space weather data anywhere to the scientific community. The number of runs requested and the number of resulting scientific publications and presentations from the research community has not only been an indication of the broad scientific usage of the CCMC and effective participation by space scientists and researchers, but also guarantees active collaboration and coordination amongst the space weather research community. Arising from the course of CCMC activities, CCMC also supports community-wide model validation challenges and research focus group projects for a broad range of programs such as the multi-agency National Space Weather Program, NSF's CEDAR (Coupling, Energetics and Dynamics of Atmospheric Regions), GEM (Geospace Environment Modeling) and Shine (Solar Heliospheric and INterplanetary Environment) programs. In addition to performing research and model development, CCMC also supports space science education by hosting summer students through local universities; through the provision of simulations in support of classroom programs such as Heliophysics Summer School (with student research contest) and CCMC Workshops; training next generation of junior scientists in space weather forecasting; and educating the general public about the importance and impacts of space weather effects. Although CCMC is organizationally comprised of United States federal agencies, CCMC services are open to members of the international science community and encourages interagency and international collaboration. In this poster, we provide an overview of using Community Coordinated Modeling Center (CCMC) tools and services to support worldwide space weather scientific communities and networks.;

Multi-objective optimisation and decision-making of space station logistics strategies

NASA Astrophysics Data System (ADS)

Zhu, Yue-he; Luo, Ya-zhong

2016-10-01

Space station logistics strategy optimisation is a complex engineering problem with multiple objectives. Finding a decision-maker-preferred compromise solution becomes more significant when solving such a problem. However, the designer-preferred solution is not easy to determine using the traditional method. Thus, a hybrid approach that combines the multi-objective evolutionary algorithm, physical programming, and differential evolution (DE) algorithm is proposed to deal with the optimisation and decision-making of space station logistics strategies. A multi-objective evolutionary algorithm is used to acquire a Pareto frontier and help determine the range parameters of the physical programming. Physical programming is employed to convert the four-objective problem into a single-objective problem, and a DE algorithm is applied to solve the resulting physical programming-based optimisation problem. Five kinds of objective preference are simulated and compared. The simulation results indicate that the proposed approach can produce good compromise solutions corresponding to different decision-makers' preferences.

An Overview of NASA's Program of Future M&S VV&A Outreach and Training Activities

NASA Technical Reports Server (NTRS)

Caine, Lisa; Hale, Joseph P.

2006-01-01

NASA's Exploration Systems Mission Directorate (ESMD) is implementing a management approach for modeling and simulation (M&S) that will provide decision-makers information on the model s fidelity, credibility, and quality. The Integrated Modeling & Simulation Verification, Validation and Accreditation (IM&S W&A) process will allow the decision-maker to understand the risks involved in using a model s results for mission-critical decisions. The W&A Technical Working Group (W&A TWG) has been identified to communicate this process throughout the agency. As the W&A experts, the W&A NVG will be the central resource for support of W&A policy, procedures, training and templates for documentation. This presentation will discuss the W&A Technical Working Group s outreach approach aimed at educating M&S program managers, developers, users and proponents on the W&A process, beginning at MSFC with the CLV program.

Use of the AHP methodology in system dynamics: Modelling and simulation for health technology assessments to determine the correct prosthesis choice for hernia diseases.

PubMed

Improta, Giovanni; Russo, Mario Alessandro; Triassi, Maria; Converso, Giuseppe; Murino, Teresa; Santillo, Liberatina Carmela

2018-05-01

Health technology assessments (HTAs) are often difficult to conduct because of the decisive procedures of the HTA algorithm, which are often complex and not easy to apply. Thus, their use is not always convenient or possible for the assessment of technical requests requiring a multidisciplinary approach. This paper aims to address this issue through a multi-criteria analysis focusing on the analytic hierarchy process (AHP). This methodology allows the decision maker to analyse and evaluate different alternatives and monitor their impact on different actors during the decision-making process. However, the multi-criteria analysis is implemented through a simulation model to overcome the limitations of the AHP methodology. Simulations help decision-makers to make an appropriate decision and avoid unnecessary and costly attempts. Finally, a decision problem regarding the evaluation of two health technologies, namely, the evaluation of two biological prostheses for incisional infected hernias, will be analysed to assess the effectiveness of the model. Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.

Dust Storm Feature Identification and Tracking from 4D Simulation Data

NASA Astrophysics Data System (ADS)

Yu, M.; Yang, C. P.

2016-12-01

Dust storms cause significant damage to health, property and the environment worldwide every year. To help mitigate the damage, dust forecasting models simulate and predict upcoming dust events, providing valuable information to scientists, decision makers, and the public. Normally, the model simulations are conducted in four-dimensions (i.e., latitude, longitude, elevation and time) and represent three-dimensional (3D), spatial heterogeneous features of the storm and its evolution over space and time. This research investigates and proposes an automatic multi-threshold, region-growing based identification algorithm to identify critical dust storm features, and track the evolution process of dust storm events through space and time. In addition, a spatiotemporal data model is proposed, which can support the characterization and representation of dust storm events and their dynamic patterns. Quantitative and qualitative evaluations for the algorithm are conducted to test the sensitivity, and capability of identify and track dust storm events. This study has the potential to assist a better early warning system for decision-makers and the public, thus making hazard mitigation plans more effective.

Marine traffic model based on cellular automaton: Considering the change of the ship's velocity under the influence of the weather and sea

NASA Astrophysics Data System (ADS)

Qi, Le; Zheng, Zhongyi; Gang, Longhui

2017-10-01

It was found that the ships' velocity change, which is impacted by the weather and sea, e.g., wind, sea wave, sea current, tide, etc., is significant and must be considered in the marine traffic model. Therefore, a new marine traffic model based on cellular automaton (CA) was proposed in this paper. The characteristics of the ship's velocity change are taken into account in the model. First, the acceleration of a ship was divided into two components: regular component and random component. Second, the mathematical functions and statistical distribution parameters of the two components were confirmed by spectral analysis, curve fitting and auto-correlation analysis methods. Third, by combining the two components, the acceleration was regenerated in the update rules for ships' movement. To test the performance of the model, the ship traffic flows in the Dover Strait, the Changshan Channel and the Qiongzhou Strait were studied and simulated. The results show that the characteristics of ships' velocities in the simulations are consistent with the measured data by Automatic Identification System (AIS). Although the characteristics of the traffic flow in different areas are different, the velocities of ships can be simulated correctly. It proves that the velocities of ships under the influence of weather and sea can be simulated successfully using the proposed model.

Final Project Report: Release of aged contaminants from weathered sediments: Effects of sorbate speciation on scaling of reactive transport

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jon Chorover, University of Arizona; Peggy O'€™Day, University of California, Merced; Karl Mueller, Penn State University

2012-10-01

Hanford sediments impacted by hyperalkaline high level radioactive waste have undergone incongruent silicate mineral weathering concurrent with contaminant uptake. In this project, we studied the impact of background pore water (BPW) on strontium, cesium and iodine desorption and transport in Hanford sediments that were experimentally weathered by contact with simulated hyperalkaline tank waste leachate (STWL) solutions. Using those lab-weathered Hanford sediments (HS) and model precipitates formed during nucleation from homogeneous STWL solutions (HN), we (i) provided detailed characterization of reaction products over a matrix of field-relevant gradients in contaminant concentration, PCO2, and reaction time; (ii) improved molecular-scale understanding of howmore » sorbate speciation controls contaminant desorption from weathered sediments upon removal of caustic sources; and (iii) developed a mechanistic, predictive model of meso- to field-scale contaminant reactive transport under these conditions.« less

Using Weather Data and Climate Model Output in Economic Analyses of Climate Change

DOE Office of Scientific and Technical Information (OSTI.GOV)

Auffhammer, M.; Hsiang, S. M.; Schlenker, W.

2013-06-28

Economists are increasingly using weather data and climate model output in analyses of the economic impacts of climate change. This article introduces a set of weather data sets and climate models that are frequently used, discusses the most common mistakes economists make in using these products, and identifies ways to avoid these pitfalls. We first provide an introduction to weather data, including a summary of the types of datasets available, and then discuss five common pitfalls that empirical researchers should be aware of when using historical weather data as explanatory variables in econometric applications. We then provide a brief overviewmore » of climate models and discuss two common and significant errors often made by economists when climate model output is used to simulate the future impacts of climate change on an economic outcome of interest.« less

Meteorological Controls on Biomass Burning During Santa Ana Events in Southern California

NASA Technical Reports Server (NTRS)

Veraverbeke, Sander; Capps, Scott; Hook, Simon J.; Randerson, James T.; Jin, Yufang; Hall, Alex

2013-01-01

Fires occurring during Santa Ana (SA) events in southern California are driven by extreme fire weather characterized by high temperatures, low humidities, and high wind speeds. We studied the controls on burned area and carbon emissions during two intensive SA burning periods in 2003 and 2007. We therefore used remote sensing data in parallel with fire weather simulations of the Weather and Regional Forecast model. Total carbon emissions were approximately 1800 gigagrams in 2003 and 900 gigagrams in 2007, based on a daily burned area and a fire emission model that accounted for spatial variability in fuel loads and combustion completeness. On a regional scale, relatively strong positive correlations were found between the daily Fosberg fire weather index and burned area/emissions (probability is less than 0.01). Our analysis provides a quantitative assessment of relationships between fire activity and weather during severe SA fires in southern California.

Ion Irradiation Experiments on the Murchison CM2 Carbonaceous Chondrite: Simulating Space Weathering of Primitive Asteroids

NASA Technical Reports Server (NTRS)

Keller, L. P.; Christoffersen, R.; Dukes, C. A.; Baragiola, R. A.; Rahman, Z.

2015-01-01

Remote sensing observations show that space weathering processes affect all airless bodies in the Solar System to some degree. Sample analyses and lab experiments provide insights into the chemical, spectroscopic and mineralogic effects of space weathering and aid in the interpretation of remote- sensing data. For example, analyses of particles returned from the S-type asteroid Itokawa by the Hayabusa mission revealed that space-weathering on that body was dominated by interactions with the solar wind acting on LL ordinary chondrite-like materials [1, 2]. Understanding and predicting how the surface regoliths of primitive carbonaceous asteroids respond to space weathering processes is important for future sample return missions (Hayabusa 2 and OSIRIS-REx) that are targeting objects of this type. Here, we report the results of our preliminary ion irradiation experiments on a hydrated carbonaceous chondrite with emphasis on microstructural and infrared spectral changes.

Health care planning and education via gaming-simulation: a two-stage experiment.

PubMed

Gagnon, J H; Greenblat, C S

1977-01-01

A two-stage process of gaming-simulation design was conducted: the first stage of design concerned national planning for hemophilia care; the second stage of design was for gaming-simulation concerning the problems of hemophilia patients and health care providers. The planning design was intended to be adaptable to large-scale planning for a variety of health care problems. The educational game was designed using data developed in designing the planning game. A broad range of policy-makers participated in the planning game.

Demonstration of NICT Space Weather Cloud --Integration of Supercomputer into Analysis and Visualization Environment--

NASA Astrophysics Data System (ADS)

Watari, S.; Morikawa, Y.; Yamamoto, K.; Inoue, S.; Tsubouchi, K.; Fukazawa, K.; Kimura, E.; Tatebe, O.; Kato, H.; Shimojo, S.; Murata, K. T.

2010-12-01

In the Solar-Terrestrial Physics (STP) field, spatio-temporal resolution of computer simulations is getting higher and higher because of tremendous advancement of supercomputers. A more advanced technology is Grid Computing that integrates distributed computational resources to provide scalable computing resources. In the simulation research, it is effective that a researcher oneself designs his physical model, performs calculations with a supercomputer, and analyzes and visualizes for consideration by a familiar method. A supercomputer is far from an analysis and visualization environment. In general, a researcher analyzes and visualizes in the workstation (WS) managed at hand because the installation and the operation of software in the WS are easy. Therefore, it is necessary to copy the data from the supercomputer to WS manually. Time necessary for the data transfer through long delay network disturbs high-accuracy simulations actually. In terms of usefulness, integrating a supercomputer and an analysis and visualization environment seamlessly with a researcher's familiar method is important. NICT has been developing a cloud computing environment (NICT Space Weather Cloud). In the NICT Space Weather Cloud, disk servers are located near its supercomputer and WSs for data analysis and visualization. They are connected to JGN2plus that is high-speed network for research and development. Distributed virtual high-capacity storage is also constructed by Grid Datafarm (Gfarm v2). Huge-size data output from the supercomputer is transferred to the virtual storage through JGN2plus. A researcher can concentrate on the research by a familiar method without regard to distance between a supercomputer and an analysis and visualization environment. Now, total 16 disk servers are setup in NICT headquarters (at Koganei, Tokyo), JGN2plus NOC (at Otemachi, Tokyo), Okinawa Subtropical Environment Remote-Sensing Center, and Cybermedia Center, Osaka University. They are connected on JGN2plus, and they constitute 1PB (physical size) virtual storage by Gfarm v2. These disk servers are connected with supercomputers of NICT and Osaka University. A system that data output from the supercomputers are automatically transferred to the virtual storage had been built up. Transfer rate is about 50 GB/hrs by actual measurement. It is estimated that the performance is reasonable for a certain simulation and analysis for reconstruction of coronal magnetic field. This research is assumed an experiment of the system, and the verification of practicality is advanced at the same time. Herein we introduce an overview of the space weather cloud system so far we have developed. We also demonstrate several scientific results using the space weather cloud system. We also introduce several web applications of the cloud as a service of the space weather cloud, which is named as "e-SpaceWeather" (e-SW). The e-SW provides with a variety of space weather online services from many aspects.

Simulation and field monitoring of moisture in alpine rock walls during freeze-thaw events

NASA Astrophysics Data System (ADS)

Rode, Matthias; Sass, Oliver

2013-04-01

Detachment of rock fragments from alpine rockwalls is mainly assigned to frost weathering. However, the actual process of frost weathering as well as the contribution of further weathering processes (e.g. hydration, thermal fatigue) is poorly understood. Rock moisture distribution during freeze-thaw events is key to understanding weathering. For this purpose, different measuring systems were set up in two study areas (Dachstein - permafrost area (2700m a.s.l.) and Gesäuse - non permafrost area (900m a.s.l.), Styria, Austria) within the framework of the research project ROCKING ALPS (FWF-P24244). We installed small-scale 2D-geoelectric survey lines in north and in south facing rockwalls, supplemented by high resolution temperature and moisture sensors. Moisture is determined by means of resistivity measurements which are difficult to calibrate, but provide good time series. Additional novel moisture sensors were developed which use the heat capacity of the surrounding rock as a proxy of water content. These sensors give point readings from a defined depth and are independent from soluble salt contents. Pore water pressure occurring during freeze-thaw events is recorded by means of pressure transducers (piezometers). First results from the Dachstein show that short term latent heat effects during the phase change have crucial influence on the moisture content. These results are cross-checked by simulation calculations. Based on meteorologic and lithologic input values, the simulation routine calculates, in an iterative procedure, the hourly energy and water transport at different depths, the latter in the liquid and in the vapor phase. The calculated profile lines and chronological sequences of rock moisture allow - in combination with temperature data - to detect possible periods of active weathering. First simulations from the Gesäuse show that maximum values of pore saturation occur from May to September. The thresholds of the "classical" frost shattering theory (high number of freeze-thaw cycles and 90% pore saturation) are achieved predominantly in spring and autumn and in north-facing rock walls. The time spent within the effective "frost cracking window" (-3 - -8°C) is also higher for north-facing sites.

Estimating national crop yield potential and the relevance of weather data sources

NASA Astrophysics Data System (ADS)

Van Wart, Justin

2011-12-01

To determine where, when, and how to increase yields, researchers often analyze the yield gap (Yg), the difference between actual current farm yields and crop yield potential. Crop yield potential (Yp) is the yield of a crop cultivar grown under specific management limited only by temperature and solar radiation and also by precipitation for water limited yield potential (Yw). Yp and Yw are critical components of Yg estimations, but are very difficult to quantify, especially at larger scales because management data and especially daily weather data are scarce. A protocol was developed to estimate Yp and Yw at national scales using site-specific weather, soils and management data. Protocol procedures and inputs were evaluated to determine how to improve accuracy of Yp, Yw and Yg estimates. The protocol was also used to evaluate raw, site-specific and gridded weather database sources for use in simulations of Yp or Yw. The protocol was applied to estimate crop Yp in US irrigated maize and Chinese irrigated rice and Yw in US rainfed maize and German rainfed wheat. These crops and countries account for >20% of global cereal production. The results have significant implications for past and future studies of Yp, Yw and Yg. Accuracy of national long-term average Yp and Yw estimates was significantly improved if (i) > 7 years of simulations were performed for irrigated and > 15 years for rainfed sites, (ii) > 40% of nationally harvested area was within 100 km of all simulation sites, (iii) observed weather data coupled with satellite derived solar radiation data were used in simulations, and (iv) planting and harvesting dates were specified within +/- 7 days of farmers actual practices. These are much higher standards than have been applied in national estimates of Yp and Yw and this protocol is a substantial step in making such estimates more transparent, robust, and straightforward. Finally, this protocol may be a useful tool for understanding yield trends and directing research and development efforts aimed at providing for a secure and stable future food supply.

A reactive transport model for Marcellus shale weathering

NASA Astrophysics Data System (ADS)

Heidari, Peyman; Li, Li; Jin, Lixin; Williams, Jennifer Z.; Brantley, Susan L.

2017-11-01

Shale formations account for 25% of the land surface globally and contribute a large proportion of the natural gas used in the United States. One of the most productive shale-gas formations is the Marcellus, a black shale that is rich in organic matter and pyrite. As a first step toward understanding how Marcellus shale interacts with water in the surface or deep subsurface, we developed a reactive transport model to simulate shale weathering under ambient temperature and pressure conditions, constrained by soil and water chemistry data. The simulation was carried out for 10,000 years since deglaciation, assuming bedrock weathering and soil genesis began after the last glacial maximum. Results indicate weathering was initiated by pyrite dissolution for the first 1000 years, leading to low pH and enhanced dissolution of chlorite and precipitation of iron hydroxides. After pyrite depletion, chlorite dissolved slowly, primarily facilitated by the presence of CO2 and organic acids, forming vermiculite as a secondary mineral. A sensitivity analysis indicated that the most important controls on weathering include the presence of reactive gases (CO2 and O2), specific surface area, and flow velocity of infiltrating meteoric water. The soil chemistry and mineralogy data could not be reproduced without including the reactive gases. For example, pyrite remained in the soil even after 10,000 years if O2 was not continuously present in the soil column; likewise, chlorite remained abundant and porosity remained small if CO2 was not present in the soil gas. The field observations were only simulated successfully when the modeled specific surface areas of the reactive minerals were 1-3 orders of magnitude smaller than surface area values measured for powdered minerals. Small surface areas could be consistent with the lack of accessibility of some fluids to mineral surfaces due to surface coatings. In addition, some mineral surface is likely interacting only with equilibrated pore fluids. An increase in the water infiltration rate enhanced weathering by removing dissolution products and maintaining far-from-equilibrium conditions. We conclude from these observations that availability of reactive surface area and transport of H2O and gases are the most important factors affecting rates of Marcellus shale weathering of the in the shallow subsurface. This weathering study documents the utility of reactive transport modeling for complex subsurface processes. Such modelling could be extended to understand interactions between injected fluids and Marcellus shale gas reservoirs at higher temperature, pressure, and salinity conditions.

Cockpit display of hazardous weather information

NASA Technical Reports Server (NTRS)

Hansman, R. John, Jr.; Wanke, Craig

1991-01-01

Information transfer and display issues associated with the dissemination of hazardous weather warnings are studied in the context of wind shear alerts. Operational and developmental wind shear detection systems are briefly reviewed. The July 11, 1988 microburst events observed as part of the Denver Terminal Doppler Weather Radar (TDWR) operational evaluation are analyzed in terms of information transfer and the effectiveness of the microburst alerts. Information transfer, message content and display issues associated with microburst alerts generated from ground based sources (Doppler Radar, Low Level Wind Shear Alert System, and Pilot Reports) are evaluated by means fo pilot opinion surveys and part task simulator studies.

Carbonation-induced weathering effect on cesium retention of cement paste

NASA Astrophysics Data System (ADS)

Park, S. M.; Jang, J. G.

2018-07-01

Carbonation is inevitable for cement and concrete in repositories over an extended period of time. This study investigated the carbonation-induced weathering effect on cesium retention of cement. Cement paste samples were exposed to accelerated carbonation for different durations to simulate the extent of weathering among samples. The extent of carbonation in cement was characterized by XRD, TG and NMR spectroscopy, while the retention capacity for cesium was investigated by zeta potential measurement and batch adsorption tests. Though carbonation led to decalcification from the binder gel, it negatively charged the surface of cement hydrates and enhanced their cesium adsorption capacity.

Weather Indices for Designing Micro-Insurance Products for Small-Holder Farmers in the Tropics

PubMed Central

Díaz Nieto, Jacqueline; Fisher, Myles; Cook, Simon; Läderach, Peter; Lundy, Mark

2012-01-01

Agriculture is inherently risky. Drought is a particularly troublesome hazard that has a documented adverse impact on agricultural development. A long history of decision-support tools have been developed to try and help farmers or policy makers manage risk. We offer site-specific drought insurance methodology as a significant addition to this process. Drought insurance works by encapsulating the best available scientific estimate of drought probability and severity at a site within a single number- the insurance premium, which is offered by insurers to insurable parties in a transparent risk-sharing agreement. The proposed method is demonstrated in a case study for dry beans in Nicaragua. PMID:22737210

AGU:Comments Requested on Natural Hazards Position Statement

NASA Astrophysics Data System (ADS)

2004-11-01

Natural hazards (earthquakes, floods, hurricanes, landslides, meteors, space weather, tornadoes, volcanoes, and other geophysical phenomena) are an integral component of our dynamic planet. These can have disastrous effects on vulnerable communities and ecosystems. By understanding how and where hazards occur, what causes them, and what circumstances increase their severity, we can develop effective strategies to reduce their impact. In practice, mitigating hazards requires addressing issues such as real-time monitoring and prediction, emergency preparedness, public education and awareness, post-disaster recovery, engineering, construction practices, land use, and building codes. Coordinated approaches involving scientists, engineers, policy makers, builders, lenders, insurers, news media, educators, relief organizations, and the public are therefore essential to reducing the adverse effects of natural hazards.

Dynamic simulation modelling of policy responses to reduce alcohol-related harms: rationale and procedure for a participatory approach.

PubMed

Atkinson, Jo-An; O'Donnell, Eloise; Wiggers, John; McDonnell, Geoff; Mitchell, Jo; Freebairn, Louise; Indig, Devon; Rychetnik, Lucie

2017-02-15

Development of effective policy responses to address complex public health problems can be challenged by a lack of clarity about the interaction of risk factors driving the problem, differing views of stakeholders on the most appropriate and effective intervention approaches, a lack of evidence to support commonly implemented and acceptable intervention approaches, and a lack of acceptance of effective interventions. Consequently, political considerations, community advocacy and industry lobbying can contribute to a hotly contested debate about the most appropriate course of action; this can hinder consensus and give rise to policy resistance. The problem of alcohol misuse and its associated harms in New South Wales (NSW), Australia, provides a relevant example of such challenges. Dynamic simulation modelling is increasingly being valued by the health sector as a robust tool to support decision making to address complex problems. It allows policy makers to ask 'what-if' questions and test the potential impacts of different policy scenarios over time, before solutions are implemented in the real world. Participatory approaches to modelling enable researchers, policy makers, program planners, practitioners and consumer representatives to collaborate with expert modellers to ensure that models are transparent, incorporate diverse evidence and perspectives, are better aligned to the decision-support needs of policy makers, and can facilitate consensus building for action. This paper outlines a procedure for embedding stakeholder engagement and consensus building in the development of dynamic simulation models that can guide the development of effective, coordinated and acceptable policy responses to complex public health problems, such as alcohol-related harms in NSW.

Potential Vorticity Analysis of Low Level Thunderstorm Dynamics in an Idealized Supercell Simulation

DTIC Science & Technology

2009-03-01

Severe Weather, Supercell, Weather Research and Forecasting Model , Advanced WRF 16. PRICE CODE 17. SECURITY CLASSIFICATION OF REPORT...27 A. ADVANCED RESEARCH WRF MODEL .................................................27 1. Data, Model Setup, and Methodology...03/11/2006 GFS model run. Top row: 11/12Z initialization. Middle row: 12 hour forecast valid at 12/00Z. Bottom row: 24 hour forecast valid at

Combining turbulent kinetic energy and Haines Index predictions for fire-weather assessments

Treesearch

Warren E. Heilman; Xindi Bian

2007-01-01

The 24- to 72-hour fire-weather predictions for different regions of the United States are now readily available from the regional Fire Consortia for Advanced Modeling of Meteorology and Smoke (FCAMMS) that were established as part of the U.S. National Fire Plan. These predictions are based on daily real-time MM5 model simulations of atmospheric conditions and fire-...

European summer heatwaves and North Atlantic weather regimes in the last Millennium

NASA Astrophysics Data System (ADS)

Alvarez Castro, Maria del Carmen; Trasancos, Romain; Yiou, Pascal

2015-04-01

The European summer heatwaves have been increasing in frequency and magnitude in the past decades. A higher confidence in future changes in such extremes necessitates to have a better knowledge about extremes behavior in the past climate. The last millennium is well documented in terms of climate forcings. Modelling efforts have provided a wealth of climate simulations covering the last millennium. We want to exploit such data in order to assess how models simulate extreme summer heatwaves. The surface temperature and precipitation are closely related to atmospheric patterns. It has been shown that rainy winter/spring seasons reduce the frequency of hot summer days whereas dry seasons can be followed by summers with high or low frequency of hot days. In this poster, we show the relation between winter/spring precipitation with the frequency of hot days in the 10 hottest summers in Europe and Southern Europe during the Medieval Warm Period (MWP 1150-1250), the Little Ice Age (LIA 1650-1750), and the historical-present period (1850-2005). We first focus on a millennium simulations with the IPSL model (IPSL-CM5). We use daily temperature, precipitation, and SLP data from CMIP5 (Coupled Model Intercomparison Project phase 5) and a couple of IPSL simulations with diferents forcings. Summer weather regimes has been computed as well for NCEP sea level pressure data in order to compare observations with the same period (1948-2005) in CMIP5 and IPSL simulations outputs. We discuss and present the results comparing the effects of hydrological deficits in the preceding season, and the occurrence of specific weather regimes, during the hottest summers over Europe and SouthWestern Europe. This analysis compares differents climate forcings simulations.

Numerical simulation of raindrop scattering for C-band dual-polarization Doppler weather radar parameters

NASA Astrophysics Data System (ADS)

Teng, Shiwen; Hu, Hanfeng; Liu, Chao; Hu, Fangchao; Wang, Zhenhui; Yin, Yan

2018-07-01

The dual-polarization Doppler weather radar plays an important role in precipitation estimation and weather monitoring. For radar applications, the retrieval of precipitation microphysical characteristics is of great importance, and requires assumed scattering properties of raindrops. This study numerically investigates the scattering properties of raindrops and considers the capability of numerical models for raindrop scattering simulations. Besides the widely used spherical and oblate spheroid models, a non-spheroidal model based on realistic raindrop geometries with a flattened base and a smoothly rounded top is also considered. To study the effects of scattering simulations on radar applications, the polarization radar parameters are modeled based on the scattering properties calculated by different scattering models (i.e. the extended boundary condition T-matrix (EBCM) method and discretize dipole approximation (DDA)) and given size distributions, and compared with observations of a C-band dual-polarization radar. Note that, when the spatial resolution of the DDA simulation is large enough, the DDA results can be very close to those of the EBCM. Most simulated radar variables, except copolar correlation coefficient, match closely with radar observations, and the results based on different non-spheroidal models considered in this study show little differences. The comparison indicates that, even for the C-band radar, the effects of raindrop shape and canting angle on scattering properties are relatively minor due to relatively small size parameters. However, although more realistic particle geometry model may provide better representation on raindrop shape, considering the relatively time-consuming and complex scattering simulations for those particles, the oblate spheroid model with appropriate axis ratio variation is suggested for polarization radar applications.

A Simple Ensemble Simulation Technique for Assessment of Future Variations in Specific High-Impact Weather Events

NASA Astrophysics Data System (ADS)

Taniguchi, Kenji

2018-04-01

To investigate future variations in high-impact weather events, numerous samples are required. For the detailed assessment in a specific region, a high spatial resolution is also required. A simple ensemble simulation technique is proposed in this paper. In the proposed technique, new ensemble members were generated from one basic state vector and two perturbation vectors, which were obtained by lagged average forecasting simulations. Sensitivity experiments with different numbers of ensemble members, different simulation lengths, and different perturbation magnitudes were performed. Experimental application to a global warming study was also implemented for a typhoon event. Ensemble-mean results and ensemble spreads of total precipitation, atmospheric conditions showed similar characteristics across the sensitivity experiments. The frequencies of the maximum total and hourly precipitation also showed similar distributions. These results indicate the robustness of the proposed technique. On the other hand, considerable ensemble spread was found in each ensemble experiment. In addition, the results of the application to a global warming study showed possible variations in the future. These results indicate that the proposed technique is useful for investigating various meteorological phenomena and the impacts of global warming. The results of the ensemble simulations also enable the stochastic evaluation of differences in high-impact weather events. In addition, the impacts of a spectral nudging technique were also examined. The tracks of a typhoon were quite different between cases with and without spectral nudging; however, the ranges of the tracks among ensemble members were comparable. It indicates that spectral nudging does not necessarily suppress ensemble spread.

Photoenhanced toxicity of weathered oil to Mysidopsis bahia

USGS Publications Warehouse

Cleveland, L.; Little, E.E.; Calfee, R.D.; Barron, M.G.

2000-01-01

The toxicity of a water-accommodated fraction (WAF) prepared from weathered oil was assessed in a 7-day static renewal test with Mysidopsis bahia. Weathered oil was collected from the 5 x monitoring well at the Guadalupe oil field. Solar ultraviolet and visible light intensities were measured in various habitats in the vicinity of the weathered oil sample collection site, and the resultant measurements were used to produce laboratory light treatments that were representative of the on-site quality and intensity of natural solar radiation. Each of five WAF dilutions and a control without WAF was tested under three different simulated solar radiation intensities. During the test, survival and growth of the mysids, irradiance, and total petroleum hydrocarbon (TPH) concentrations in the test treatments were measured. Significant increases (P ??? 0.05) in mortality occurred among mysids exposed to 0.57 and 1.30 mg TPH/l and the effects were potentiated as irradiance increased. Seven-day LC50 (0.92-0.42 mg TPH/l) and LC20 (0.58-0.15 mg TPH/l) values decreased as the simulated solar irradiance increased. Calculated EC20 and EC50 values for mysid growth indicate that surviving mysids exposed to 0.1-1.0 mg TPH/l would incur significant reductions (P ??? 0.05) in productivity (biomass). Results of the present study indicate that effects elicited through the interaction of WAF of weathered oil and solar radiation will substantially increase the toxicity of weathered oil. Further, the photomediated effects of petroleum compounds measured as TPH on mysid survival and growth demonstrate a need to consider the interactions of ultraviolet light and contaminant to avoid under estimating toxicity that might occur in the environment. (C) 2000 Elsevier Science B.V.

Assessment of an extended version of the Jenkinson-Collison classification on CMIP5 models over Europe

NASA Astrophysics Data System (ADS)

Otero, Noelia; Sillmann, Jana; Butler, Tim

2018-03-01

A gridded, geographically extended weather type classification has been developed based on the Jenkinson-Collison (JC) classification system and used to evaluate the representation of weather types over Europe in a suite of climate model simulations. To this aim, a set of models participating in the Coupled Model Intercomparison Project Phase 5 (CMIP5) is compared with the circulation from two reanalysis products. Furthermore, we examine seasonal changes between simulated frequencies of weather types at present and future climate conditions. The models are in reasonably good agreement with the reanalyses, but some discrepancies occur in cyclonic days being overestimated over North, and underestimated over South Europe, while anticyclonic situations were overestimated over South, and underestimated over North Europe. Low flow conditions were generally underestimated, especially in summer over South Europe, and Westerly conditions were generally overestimated. The projected frequencies of weather types in the late twenty-first century suggest an increase of Anticyclonic days over South Europe in all seasons except summer, while Westerly days increase over North and Central Europe, particularly in winter. We find significant changes in the frequency of Low flow conditions and the Easterly type that become more frequent during the warmer seasons over Southeast and Southwest Europe, respectively. Our results indicate that in winter the Westerly type has significant impacts on positive anomalies of maximum and minimum temperature over most of Europe. Except in winter, the warmer temperatures are linked to Easterlies, Anticyclonic and Low Flow conditions, especially over the Mediterranean area. Furthermore, we show that changes in the frequency of weather types represent a minor contribution of the total change of European temperatures, which would be mainly driven by changes in the temperature anomalies associated with the weather types themselves.

Whether the weather drives patterns of endemic amphibian chytridiomycosis: a pathogen proliferation approach.

PubMed

Murray, Kris A; Skerratt, Lee F; Garland, Stephen; Kriticos, Darren; McCallum, Hamish

2013-01-01

The pandemic amphibian disease chytridiomycosis often exhibits strong seasonality in both prevalence and disease-associated mortality once it becomes endemic. One hypothesis that could explain this temporal pattern is that simple weather-driven pathogen proliferation (population growth) is a major driver of chytridiomycosis disease dynamics. Despite various elaborations of this hypothesis in the literature for explaining amphibian declines (e.g., the chytrid thermal-optimum hypothesis) it has not been formally tested on infection patterns in the wild. In this study we developed a simple process-based model to simulate the growth of the pathogen Batrachochytrium dendrobatidis (Bd) under varying weather conditions to provide an a priori test of a weather-linked pathogen proliferation hypothesis for endemic chytridiomycosis. We found strong support for several predictions of the proliferation hypothesis when applied to our model species, Litoria pearsoniana, sampled across multiple sites and years: the weather-driven simulations of pathogen growth potential (represented as a growth index in the 30 days prior to sampling; GI30) were positively related to both the prevalence and intensity of Bd infections, which were themselves strongly and positively correlated. In addition, a machine-learning classifier achieved ~72% success in classifying positive qPCR results when utilising just three informative predictors 1) GI30, 2) frog body size and 3) rain on the day of sampling. Hence, while intrinsic traits of the individuals sampled (species, size, sex) and nuisance sampling variables (rainfall when sampling) influenced infection patterns obtained when sampling via qPCR, our results also strongly suggest that weather-linked pathogen proliferation plays a key role in the infection dynamics of endemic chytridiomycosis in our study system. Predictive applications of the model include surveillance design, outbreak preparedness and response, climate change scenario modelling and the interpretation of historical patterns of amphibian decline.

Hydrological Responses of Weather Conditions and Crop Change of Agricultural Area in the Rincon Valley, New Mexico

NASA Astrophysics Data System (ADS)

Ahn, S.; Sheng, Z.; Abudu, S.

2017-12-01

Hydrologic cycle of agricultural area has been changing due to the impacts of climate and land use changes (crop coverage changes) in an arid region of Rincon Valley, New Mexico. This study is to evaluate the impacts of weather condition and crop coverage change on hydrologic behavior of agricultural area in Rincon Valley (2,466km2) for agricultural watershed management using a watershed-scale hydrologic model, SWAT (Soil and Water Assessment Tool). The SWAT model was developed to incorporate irrigation of different crops using auto irrigation function. For the weather condition and crop coverage change evaluation, three spatial crop coverages including a normal (2008), wet (2009), and dry (2011) years were prepared using USDA crop data layer (CDL) for fourteen different crops. The SWAT model was calibrated for the period of 2001-2003 and validated for the period of 2004-2006 using daily-observed streamflow data. Scenario analysis was performed for wet and dry years based on the unique combinations of crop coverages and releases from Caballo Reservoir. The SWAT model simulated the present vertical water budget and horizontal water transfer considering irrigation practices in the Rincon Valley. Simulation results indicated the temporal and spatial variability for irrigation and non-irrigation seasons of hydrologic cycle in agricultural area in terms of surface runoff, evapotranspiration, infiltration, percolation, baseflow, soil moisture, and groundwater recharge. The water supply of the dry year could not fully cover whole irrigation period due to dry weather conditions, resulting in reduction of crop acreage. For extreme weather conditions, the temporal variation of water budget became robust, which requires careful irrigation management of the agricultural area. The results could provide guidelines for farmers to decide crop patterns in response to different weather conditions and water availability.

STS-114: Discovery L-2 Countdown Status Briefing

NASA Technical Reports Server (NTRS)

2005-01-01

George Diller of NASA Public Affairs hosted this briefing. Pete Nickolenko, NASA Test Director; Scott Higgenbotham, STS-114 Payload-Mission Manager; Cathy Winters, Shuttle Weather Officer were present. Pete reports his team has completed the avionics system check ups, servicing of the cryogenic tanks will take about seven hours that day, and will perform engine system checks and pad close outs come evening. Pete also summarized other standard close out activities: check ups of the Orbiter and ground communications network, rotary service, structure retraction, and external tank load (ETL). Pete reported that the mission will be 12 days with two weather contingency days, and end of mission landing scheduled at Kennedy Space Center (KSC) at approximately 11:00 in the morning, Eastern time on July 25th. Scott briefly reported that all hardware is on board Discovery, closed out, and ready to fly. Cathy reported that hurricane Dennis moved to the North and looking forward to launch. She mentioned of a new hurricane looming and will be named Emily, spotted some crosswinds which will migrate to the west, there is 30% probability weather prohibiting launch. Cathy further gave current weather forecast supported with charts: the Launch Forecast, Tanking Forecast, SRB (Shuttle Solid Rocket Booster) Forecast, CONUS and TAL Launch Sites Forecast, and with 24 hours and 48 hours turn around plan. Launch constraints, weather, crosswinds, cloud cover, ground imagery system, launch countdown, launch crews, mission management simulations, launch team simulations were topics covered with the News Media.

Impact of climate change on European weather extremes

NASA Astrophysics Data System (ADS)

Duchez, Aurelie; Forryan, Alex; Hirschi, Joel; Sinha, Bablu; New, Adrian; Freychet, Nicolas; Scaife, Adam; Graham, Tim

2015-04-01

An emerging science consensus is that global climate change will result in more extreme weather events with concomitant increasing financial losses. Key questions that arise are: Can an upward trend in natural extreme events be recognised and predicted at the European scale? What are the key drivers within the climate system that are changing and making extreme weather events more frequent, more intense, or both? Using state-of-the-art coupled climate simulations from the UK Met Office (HadGEM3-GC2, historical and future scenario runs) as well as reanalysis data, we highlight the potential of the currently most advanced forecasting systems to progress understanding of the causative drivers of European weather extremes, and assess future frequency and intensity of extreme weather under various climate change scenarios. We characterize European extremes in these simulations using a subset of the 27 core indices for temperature and precipitation from The Expert Team on Climate Change Detection and Indices (Tank et al., 2009). We focus on temperature and precipitation extremes (e.g. extremes in daily and monthly precipitation and temperatures) and relate them to the atmospheric modes of variability over Europe in order to establish the large-scale atmospheric circulation patterns that are conducive to the occurrence of extreme precipitation and temperature events. Klein Tank, Albert M.G., and Francis W. Zwiers. Guidelines on Analysis of Extremes in a Changing Climate in Support of Informed Decisions for Adaptation. WMO-TD No. 1500. Climate Data and Monitoring. World Meteorological Organization, 2009.

Use of CMIP3 simulations to estimate the changes of temperature indicators over France and Europe during the 21st century

NASA Astrophysics Data System (ADS)

Leboucher, V.; Couillaux, A.; Parey, S.; Fil, C.

2007-12-01

Projections of changes in temperature are essential to assess the impact of climate change on the energy supply sector as heating and cooling, energy demand highly depends on temperature. A selection of temperature indicators and their changes are examined for several simulations using SRES Emission Scenario A2 from the CMIP3 archive. We compare the present day simulated indicators to those in European Center for Medium-Range Weather Forecasts (ECMWF) ERA40 reanalysis The results are analysed for six areas over Europe and two time periods during the 21st century. We focus our study on changes in number and duration of hot and cold events and on changes in heating degree-days and cooling degree-days, which are commonly used to estimate the weather-related variations in energy consumption. Results are presented for the different models with some comparisons to the regional model simulations from the European PRUDENCE project to evaluate uncertainties.

Assessment of WRF Simulated Precipitation by Meteorological Regimes

NASA Astrophysics Data System (ADS)

Hagenhoff, Brooke Anne

This study evaluated warm-season precipitation events in a multi-year (2007-2014) database of Weather Research and Forecasting (WRF) simulations over the Northern Plains and Southern Great Plains. These WRF simulations were run daily in support of the National Oceanic and Atmospheric Administration (NOAA) Hazardous Weather Testbed (HWT) by the National Severe Storms Laboratory (NSSL) for operational forecasts. Evaluating model skill by synoptic pattern allows for an understanding of how model performance varies with particular atmospheric states and will aid forecasters with pattern recognition. To conduct this analysis, a competitive neural network known as the Self-Organizing Map (SOM) was used. SOMs allow the user to represent atmospheric patterns in an array of nodes that represent a continuum of synoptic categorizations. North American Regional Reanalysis (NARR) data during the warm season (April-September) was used to perform the synoptic typing over the study domains. Simulated precipitation was evaluated against observations provided by the National Centers for Environmental Prediction (NCEP) Stage IV precipitation analysis.

Space Weathering of Ordinary Chondrite Parent Bodies, Its Impact on the Method of Distinguishing H, L, and LL Types and Implications for Itokawa Samples Returned by the Hayabusa Mission

NASA Technical Reports Server (NTRS)

Hiroi, T.; Sasaki, S.; Noble, S. K.; Pieters, C. M.

2011-01-01

As the most abundance meteorites in our collections, ordinary chondrites potentially have very important implications on the origin and formation of our Solar System. In order to map the distribution of ordinary chondrite-like asteroids through remote sensing, the space weathering effects of ordinary chondrite parent bodies must be addressed through experiments and modeling. Of particular importance is the impact on distinguishing different types (H/L/LL) of ordinary chondrites. In addition, samples of asteroid Itokawa returned by the Hayabusa spacecraft may re veal the mechanism of space weathering on an LLchondrite parent body. Results of space weathering simulations on ordinary chondrites and implications for Itokawa samples are presented here.

The potential impact of scatterometry on oceanography - A wave forecasting case

NASA Technical Reports Server (NTRS)

Cane, M. A.; Cardone, V. J.

1981-01-01

A series of observing system simulation experiments have been performed in order to assess the potential impact of marine surface wind data on numerical weather prediction. In addition to conventional data, the experiments simulated the time-continuous assimilation of remotely sensed marine surface wind or temperature sounding data. The wind data were fabricated directly for model grid points intercepted by a Seasat-1 scatterometer swath and were assimilated into the lowest active level (945 mb) of the model using a localized successive correction method. It is shown that Seasat wind data can greatly improve numerical weather forecasts due to better definition of specific features. The case of the QE II storm is examined.

Performance of the NASA Airborne Radar with the Windshear Database for Forward-Looking Systems

NASA Technical Reports Server (NTRS)

Switzer, George F.; Britt, Charles L.

1996-01-01

This document describes the simulation approach used to test the performance of the NASA airborne windshear radar. An explanation of the actual radar hardware and processing algorithms provides an understanding of the parameters used in the simulation program. This report also contains a brief overview of the NASA airborne windshear radar experimental flight test results. A description of the radar simulation program shows the capabilities of the program and the techniques used for certification evaluation. Simulation of the NASA radar is comprised of three steps. First, the choice of the ground clutter data must be made. The ground clutter is the return from objects in or nearby an airport facility. The choice of the ground clutter also dictates the aircraft flight path since ground clutter is gathered while in flight. The second step is the choice of the radar parameters and the running of the simulation program which properly combines the ground clutter data with simulated windshear weather data. The simulated windshear weather data is comprised of a number of Terminal Area Simulation System (TASS) model results. The final step is the comparison of the radar simulation results to the known windshear data base. The final evaluation of the radar simulation is based on the ability to detect hazardous windshear with the aircraft at a safe distance while at the same time not displaying false alerts.

The role of situation assessment and flight experience in pilots' decisions to continue visual flight rules flight into adverse weather.

PubMed

Wiegmann, Douglas A; Goh, Juliana; O'Hare, David

2002-01-01

Visual flight rules (VFR) flight into instrument meteorological conditions (IMC) is a major safety hazard in general aviation. In this study we examined pilots' decisions to continue or divert from a VFR flight into IMC during a dynamic simulation of a cross-country flight. Pilots encountered IMC either early or later into the flight, and the amount of time and distance pilots flew into the adverse weather prior to diverting was recorded. Results revealed that pilots who encountered the deteriorating weather earlier in the flight flew longer into the weather prior to diverting and had more optimistic estimates of weather conditions than did pilots who encountered the deteriorating weather later in the flight. Both the time and distance traveled into the weather prior to diverting were negatively correlated with pilots' previous flight experience. These findings suggest that VFR flight into IMC may be attributable, at least in part, to poor situation assessment and experience rather than to motivational judgment that induces risk-taking behavior as more time and effort are invested in a flight. Actual or potential applications of this research include the design of interventions that focus on improving weather evaluation skills in addition to addressing risk-taking attitudes.

The weather roulette: assessing the economic value of seasonal wind speed predictions

NASA Astrophysics Data System (ADS)

Christel, Isadora; Cortesi, Nicola; Torralba-Fernandez, Veronica; Soret, Albert; Gonzalez-Reviriego, Nube; Doblas-Reyes, Francisco

2016-04-01

Climate prediction is an emerging and highly innovative research area. For the wind energy sector, predicting the future variability of wind resources over the coming weeks or seasons is especially relevant to quantify operation and maintenance logistic costs or to inform energy trading decision with potential cost savings and/or economic benefits. Recent advances in climate predictions have already shown that probabilistic forecasting can improve the current prediction practices, which are based in the use of retrospective climatology and the assumption that what happened in the past is the best estimation of future conditions. Energy decision makers now have this new set of climate services but, are they willing to use them? Our aim is to properly explain the potential economic benefits of adopting probabilistic predictions, compared with the current practice, by using the weather roulette methodology (Hagedorn & Smith, 2009). This methodology is a diagnostic tool created to inform in a more intuitive and relevant way about the skill and usefulness of a forecast in the decision making process, by providing an economic and financial oriented assessment of the benefits of using a particular forecast system. We have selected a region relevant to the energy stakeholders where the predictions of the EUPORIAS climate service prototype for the energy sector (RESILIENCE) are skillful. In this region, we have applied the weather roulette to compare the overall prediction success of RESILIENCE's predictions and climatology illustrating it as an effective interest rate, an economic term that is easier to understand for energy stakeholders.

Diagnosing Geospatial Uncertainty Visualization Challenges in Seasonal Temperature and Precipitation Forecasts

NASA Astrophysics Data System (ADS)

Speciale, A.; Kenney, M. A.; Gerst, M.; Baer, A. E.; DeWitt, D.; Gottschalk, J.; Handel, S.

2017-12-01

The uncertainty of future weather and climate conditions is important for many decisions made in communities and economic sectors. One tool that decision-makers use in gauging this uncertainty is forecasts, especially maps (or visualizations) of probabilistic forecast results. However, visualizing geospatial uncertainty is challenging because including probability introduces an extra variable to represent and probability is often poorly understood by users. Using focus group and survey methods, this study seeks to understand the barriers to using probabilistic temperature and precipitation visualizations for specific decisions in the agriculture, energy, emergency management, and water resource sectors. Preliminary results shown here focus on findings of emergency manager needs. Our experimental design uses National Oceanic and Atmospheric Administration (NOAA's) Climate Prediction Center (CPC) climate outlooks, which produce probabilistic temperature and precipitation forecast visualizations at the 6-10 day, 8-14 day, 3-4 week, and 1 and 3 month timeframes. Users were asked to complete questions related to how they use weather information, how uncertainty is represented, and design elements (e.g., color, contour lines) of the visualizations. Preliminary results from the emergency management sector indicate there is significant confusion on how "normal" weather is defined, boundaries between probability ranges, and meaning of the contour lines. After a complete understandability diagnosis is made using results from all sectors, we will collaborate with CPC to suggest modifications to the climate outlook visualizations. These modifications will then be retested in similar focus groups and web-based surveys to confirm they better meet the needs of users.

IMPACT: a generic tool for modelling and simulating public health policy.

PubMed

Ainsworth, J D; Carruthers, E; Couch, P; Green, N; O'Flaherty, M; Sperrin, M; Williams, R; Asghar, Z; Capewell, S; Buchan, I E

2011-01-01

Populations are under-served by local health policies and management of resources. This partly reflects a lack of realistically complex models to enable appraisal of a wide range of potential options. Rising computing power coupled with advances in machine learning and healthcare information now enables such models to be constructed and executed. However, such models are not generally accessible to public health practitioners who often lack the requisite technical knowledge or skills. To design and develop a system for creating, executing and analysing the results of simulated public health and healthcare policy interventions, in ways that are accessible and usable by modellers and policy-makers. The system requirements were captured and analysed in parallel with the statistical method development for the simulation engine. From the resulting software requirement specification the system architecture was designed, implemented and tested. A model for Coronary Heart Disease (CHD) was created and validated against empirical data. The system was successfully used to create and validate the CHD model. The initial validation results show concordance between the simulation results and the empirical data. We have demonstrated the ability to connect health policy-modellers and policy-makers in a unified system, thereby making population health models easier to share, maintain, reuse and deploy.

An evaluation of soil water outlooks for winter wheat in south-eastern Australia

NASA Astrophysics Data System (ADS)

Western, A. W.; Dassanayake, K. B.; Perera, K. C.; Alves, O.; Young, G.; Argent, R.

2015-12-01

Abstract: Soil moisture is a key limiting resource for rain-fed cropping in Australian broad-acre cropping zones. Seasonal rainfall and temperature outlooks are standard operational services offered by the Australian Bureau of Meteorology and are routinely used to support agricultural decisions. This presentation examines the performance of proposed soil water seasonal outlooks in the context of wheat cropping in south-eastern Australia (autumn planting, late spring harvest). We used weather ensembles simulated by the Predictive Ocean-Atmosphere Model for Australia (POAMA), as input to the Agricultural Production Simulator (APSIM) to construct ensemble soil water "outlooks" at twenty sites. Hindcasts were made over a 33 year period using the 33 POAMA ensemble members. The overall modelling flow involved: 1. Downscaling of the daily weather series (rainfall, minimum and maximum temperature, humidity, radiation) from the ~250km POAMA grid scale to a local weather station using quantile-quantile correction. This was based on a 33 year observation record extracted from the SILO data drill product. 2. Using APSIM to produce soil water ensembles from the downscaled weather ensembles. A warm up period of 5 years of observed weather was followed by a 9 month hindcast period based on each ensemble member. 3. The soil water ensembles were summarized by estimating the proportion of outlook ensembles in each climatological tercile, where the climatology was constructed using APSIM and observed weather from the 33 years of hindcasts at the relevant site. 4. The soil water outlooks were evaluated for different lead times and months using a "truth" run of APSIM based on observed weather. Outlooks generally have useful some forecast skill for lead times of up to two-three months, except late spring; in line with current useful lead times for rainfall outlooks. Better performance was found in summer and autumn when vegetation cover and water use is low.

Avoiding verisimilitude when modelling ecological responses to climate change: the influence of weather conditions on trapping efficiency in European badgers (Meles meles).

PubMed

Noonan, Michael J; Rahman, M Abidur; Newman, Chris; Buesching, Christina D; Macdonald, David W

2015-10-01

The signal for climate change effects can be abstruse; consequently, interpretations of evidence must avoid verisimilitude, or else misattribution of causality could compromise policy decisions. Examining climatic effects on wild animal population dynamics requires ability to trap, observe or photograph and to recapture study individuals consistently. In this regard, we use 19 years of data (1994-2012), detailing the life histories on 1179 individual European badgers over 3288 (re-) trapping events, to test whether trapping efficiency was associated with season, weather variables (both contemporaneous and time lagged), body-condition index (BCI) and trapping efficiency (TE). PCA factor loadings demonstrated that TE was affected significantly by temperature and precipitation, as well as time lags in these variables. From multi-model inference, BCI was the principal driver of TE, where badgers in good condition were less likely to be trapped. Our analyses exposed that this was enacted mechanistically via weather variables driving BCI, affecting TE. Notably, the very conditions that militated for poor trapping success have been associated with actual survival and population abundance benefits in badgers. Using these findings to parameterize simulations, projecting best-/worst-case scenario weather conditions and BCI resulted in 8.6% ± 4.9 SD difference in seasonal TE, leading to a potential 55.0% population abundance under-estimation under the worst-case scenario; 38.6% over-estimation under the best case. Interestingly, simulations revealed that while any single trapping session might prove misrepresentative of the true population abundance, due to weather effects, prolonging capture-mark-recapture studies under sub-optimal conditions decreased the accuracy of population estimates significantly. We also use these projection scenarios to explore how weather could impact government-led trapping of badgers in the UK, in relation to TB management. We conclude that population monitoring must be calibrated against the likelihood that weather conditions could be altering trap success directly, and therefore biasing model design. © 2015 John Wiley & Sons Ltd.

Estimating the Exceedance Probability of the Reservoir Inflow Based on the Long-Term Weather Outlooks

NASA Astrophysics Data System (ADS)

Huang, Q. Z.; Hsu, S. Y.; Li, M. H.

2016-12-01

The long-term streamflow prediction is important not only to estimate water-storage of a reservoir but also to the surface water intakes, which supply people's livelihood, agriculture, and industry. Climatology forecasts of streamflow have been traditionally used for calculating the exceedance probability curve of streamflow and water resource management. In this study, we proposed a stochastic approach to predict the exceedance probability curve of long-term streamflow with the seasonal weather outlook from Central Weather Bureau (CWB), Taiwan. The approach incorporates a statistical downscale weather generator and a catchment-scale hydrological model to convert the monthly outlook into daily rainfall and temperature series and to simulate the streamflow based on the outlook information. Moreover, we applied Bayes' theorem to derive a method for calculating the exceedance probability curve of the reservoir inflow based on the seasonal weather outlook and its imperfection. The results show that our approach can give the exceedance probability curves reflecting the three-month weather outlook and its accuracy. We also show how the improvement of the weather outlook affects the predicted exceedance probability curves of the streamflow. Our approach should be useful for the seasonal planning and management of water resource and their risk assessment.

For how long can we predict the weather? - Insights into atmospheric predictability from global convection-allowing simulations

NASA Astrophysics Data System (ADS)

Judt, Falko

2017-04-01

A tremendous increase in computing power has facilitated the advent of global convection-resolving numerical weather prediction (NWP) models. Although this technological breakthrough allows for the seamless prediction of weather from local to global scales, the predictability of multiscale weather phenomena in these models is not very well known. To address this issue, we conducted a global high-resolution (4-km) predictability experiment using the Model for Prediction Across Scales (MPAS), a state-of-the-art global NWP model developed at the National Center for Atmospheric Research. The goals of this experiment are to investigate error growth from convective to planetary scales and to quantify the intrinsic, scale-dependent predictability limits of atmospheric motions. The globally uniform resolution of 4 km allows for the explicit treatment of organized deep moist convection, alleviating grave limitations of previous predictability studies that either used high-resolution limited-area models or global simulations with coarser grids and cumulus parameterization. Error growth is analyzed within the context of an "identical twin" experiment setup: the error is defined as the difference between a 20-day long "nature run" and a simulation that was perturbed with small-amplitude noise, but is otherwise identical. It is found that in convectively active regions, errors grow by several orders of magnitude within the first 24 h ("super-exponential growth"). The errors then spread to larger scales and begin a phase of exponential growth after 2-3 days when contaminating the baroclinic zones. After 16 days, the globally averaged error saturates—suggesting that the intrinsic limit of atmospheric predictability (in a general sense) is about two weeks, which is in line with earlier estimates. However, error growth rates differ between the tropics and mid-latitudes as well as between the troposphere and stratosphere, highlighting that atmospheric predictability is a complex problem. The comparatively slower error growth in the tropics and in the stratosphere indicates that certain weather phenomena could potentially have longer predictability than currently thought.

Large-Scale Weather Disturbances in Mars’ Southern Extratropics

NASA Astrophysics Data System (ADS)

Hollingsworth, Jeffery L.; Kahre, Melinda A.

2015-11-01

Between late autumn and early spring, Mars’ middle and high latitudes within its atmosphere support strong mean thermal gradients between the tropics and poles. Observations from both the Mars Global Surveyor (MGS) and Mars Reconnaissance Orbiter (MRO) indicate that this strong baroclinicity supports intense, large-scale eastward traveling weather systems (i.e., transient synoptic-period waves). These extratropical weather disturbances are key components of the global circulation. Such wave-like disturbances act as agents in the transport of heat and momentum, and generalized scalar/tracer quantities (e.g., atmospheric dust, water-vapor and ice clouds). The character of large-scale, traveling extratropical synoptic-period disturbances in Mars' southern hemisphere during late winter through early spring is investigated using a moderately high-resolution Mars global climate model (Mars GCM). This Mars GCM imposes interactively lifted and radiatively active dust based on a threshold value of the surface stress. The model exhibits a reasonable "dust cycle" (i.e., globally averaged, a dustier atmosphere during southern spring and summer occurs). Compared to their northern-hemisphere counterparts, southern synoptic-period weather disturbances and accompanying frontal waves have smaller meridional and zonal scales, and are far less intense. Influences of the zonally asymmetric (i.e., east-west varying) topography on southern large-scale weather are examined. Simulations that adapt Mars’ full topography compared to simulations that utilize synthetic topographies emulating key large-scale features of the southern middle latitudes indicate that Mars’ transient barotropic/baroclinic eddies are highly influenced by the great impact basins of this hemisphere (e.g., Argyre and Hellas). The occurrence of a southern storm zone in late winter and early spring appears to be anchored to the western hemisphere via orographic influences from the Tharsis highlands, and the Argyre and Hellas impact basins. Geographically localized transient-wave activity diagnostics are constructed that illuminate dynamical differences amongst the simulations and these are presented.

Structuring modeling and simulation analysis for evacuation planning and operations.

DOT National Transportation Integrated Search

2009-06-01

This document is intended to provide guidance to decision-makers at agencies and jurisdictions considering the role of analytical tools in evacuation planning and operations. It is often unclear what kind of analytical approach may be of most value, ...

Probability for Weather and Climate

NASA Astrophysics Data System (ADS)

Smith, L. A.

2013-12-01

Over the last 60 years, the availability of large-scale electronic computers has stimulated rapid and significant advances both in meteorology and in our understanding of the Earth System as a whole. The speed of these advances was due, in large part, to the sudden ability to explore nonlinear systems of equations. The computer allows the meteorologist to carry a physical argument to its conclusion; the time scales of weather phenomena then allow the refinement of physical theory, numerical approximation or both in light of new observations. Prior to this extension, as Charney noted, the practicing meteorologist could ignore the results of theory with good conscience. Today, neither the practicing meteorologist nor the practicing climatologist can do so, but to what extent, and in what contexts, should they place the insights of theory above quantitative simulation? And in what circumstances can one confidently estimate the probability of events in the world from model-based simulations? Despite solid advances of theory and insight made possible by the computer, the fidelity of our models of climate differs in kind from the fidelity of models of weather. While all prediction is extrapolation in time, weather resembles interpolation in state space, while climate change is fundamentally an extrapolation. The trichotomy of simulation, observation and theory which has proven essential in meteorology will remain incomplete in climate science. Operationally, the roles of probability, indeed the kinds of probability one has access too, are different in operational weather forecasting and climate services. Significant barriers to forming probability forecasts (which can be used rationally as probabilities) are identified. Monte Carlo ensembles can explore sensitivity, diversity, and (sometimes) the likely impact of measurement uncertainty and structural model error. The aims of different ensemble strategies, and fundamental differences in ensemble design to support of decision making versus advance science, are noted. It is argued that, just as no point forecast is complete without an estimate of its accuracy, no model-based probability forecast is complete without an estimate of its own irrelevance. The same nonlinearities that made the electronic computer so valuable links the selection and assimilation of observations, the formation of ensembles, the evolution of models, the casting of model simulations back into observables, and the presentation of this information to those who use it to take action or to advance science. Timescales of interest exceed the lifetime of a climate model and the career of a climate scientist, disarming the trichotomy that lead to swift advances in weather forecasting. Providing credible, informative climate services is a more difficult task. In this context, the value of comparing the forecasts of simulation models not only with each other but also with the performance of simple empirical models, whenever possible, is stressed. The credibility of meteorology is based on its ability to forecast and explain the weather. The credibility of climatology will always be based on flimsier stuff. Solid insights of climate science may be obscured if the severe limits on our ability to see the details of the future even probabilistically are not communicated clearly.

Using Relative Humidity Forecasts to Manage Meningitis in the Sahel

NASA Astrophysics Data System (ADS)

Pandya, R. E.; Adams-Forgor, A.; Akweogno, P.; Awine, T.; Dalaba, M.; Dukic, V.; Dumont, A.; Hayden, M.; Hodgson, A.; Hopson, T. M.; Hugonnet, S.; Yoksas, T. C.

2012-12-01

Meningitis epidemics in the Sahel occur quasi-regularly and with devastating impact. In 2008, for example, eighty-eight thousand people contracted meningitis and over five thousand died. Until very recently, the protection provided by the only available vaccine was so limited and short-lived that the only practical strategy for vaccination was reactive: waiting until an epidemic occurred in the region and then vaccinating in that region to prevent the epidemic's further growth. Even with that strategy, there were still times when demand outpaced available vaccine. While a new vaccine has recently been developed that is effective and inexpensive enough to be used more broadly and proactively, it is only effective against the strain of bacteria that causes the most common kind of bacterial meningitis. As a result, there will likely be continued need for reactive vaccination strategies. It is widely known that meningitis epidemics in the Sahel occur only in the dry season. Our project investigated this relationship, and several independent lines of evidence demonstrate a robust relationship between the onset of the rainy season, as marked by weekly average relative humidity above 40%, and the end of meningitis epidemics. These lines of evidence include statistical analysis of two years of weekly meningitis and weather data across the Sahel, cross-correlation of ten years of meningitis and weather data in the Upper East region of northern Ghana, and high-resolution weather simulations of past meningitis seasons to interpolate available weather data. We also adapted two techniques that have been successfully used in public health studies: generalized additive models, which have been used to relate air quality and health, and a linearized version of the compartmental epidemics model that has been used to understand MRSA. Based on these multiple lines of evidence, average weekly relative humidity forecast two weeks in advance appears consistently and strongly related to the number cases of meningitis in the Sahel. Using currently available forecast models contributed through the WMO Thorpex-Tigge project, and applying quantile regression to enhance their accuracy, we can forecast the average weekly relative humidity to two weeks in advance which allows us to anticipate the end of an epidemic in a region of the Sahel up to four weeks in advance. This would allow public health officials to deploy vaccines to areas in which the epidemics are likely to persist due to continued dryness and avoid vaccinating in areas where the epidemics will end with higher humidity. Our presentation will conclude by introducing the relative humidity decision-information tool developed for use by public-health officials. We will also summarize the results of a weekly meningitis forecast exercise held during the 2011-2012 dry season with public health decision makers from several African countries and the World Health Organization. Finally, we highlight some results of concurrent socio-economic research that suggests other interventions for managing meningitis and helps quantify the economic impact of the disease in Ghana. Overall, while our research has demonstrated an actionable relationship between weather and disease, this relationship is only one factor in a complex and coupled human-natural system which merits continued investigation.

Blizzards to hurricanes: computer modeling of hydrology, weathering, and isotopic fractionation across hydroclimatic regions

Treesearch

Richard MT Webb; David L. Parkhurst

2016-01-01

The U.S. Geological Survey’s (USGS) Water, Energy, and Biogeochemical Model (WEBMOD) was used to simulate hydrology, weathering, and isotopic fractionation in the Andrews Creek watershed in Rocky Mountain National Park, Colorado and the Icacos River watershed in the Luquillo Experimental Forest, Puerto Rico. WEBMOD includes hydrologic modules derived from the USGS...

Estimation of fire danger in Hawai'i using limited weather data and simulation

Treesearch

D.R. Weise; S.L. Stephens; F.M. Fujioka; T.J. Moody; J. Benoit

2010-01-01

The presence of fire in Hawai'i has increased with introduction of nonnative grasses. Fire danger estimation using the National Fire Danger Rating System (NFDRS) typically requires 5 to 10 yr of data to determine percentile weather values and fire activity. The U.S. Army Pōhakuloa Training Area in Hawai‘i is located in the interface zone between windward...

Weather forecast performances for complex orographic areas: Impact of different grid resolutions and of geographic data on heavy rainfall event simulations in Sicily

NASA Astrophysics Data System (ADS)

Caccamo, M. T.; Castorina, G.; Colombo, F.; Insinga, V.; Maiorana, E.; Magazù, S.

2017-12-01

Over the past decades, Sicily has undergone an increasing sequence of extreme weather events that have produced, besides huge damages to both environment and territory, the death of hundreds of people together with the evacuation of thousands of residents, which have permanently lost their properties. In this framework, with this paper we have investigated the impact of different grid spacing and geographic data on the performance of forecasts over complex orographic areas. In order to test the validity of this approach we have analyzed and discussed, as case study, the heavy rainfall occurred in Sicily during the night of October 10, 2015. In just 9 h, a Mediterranean depression, centered on the Tunisian coastline, produced a violent mesoscale storm localized on the Peloritani Mountains with a maximum rain accumulation of about 200 mm. The results of these simulations were obtained using the Weather Research and Forecasting (WRF-ARW) Model, version 3.7.1, at different grid spacing values and the Two Way Nesting procedure with a sub-domain centered on the area of interest. The results highlighted that providing correct and timely forecasts of extreme weather events is a challenge that could have been efficiently and effectively countered using proper employment of high spatial resolution models.

Examining the relative effects of fire weather, suppression and fuel treatment on fire behaviour--a simulation study.

PubMed

Penman, T D; Collins, L; Price, O F; Bradstock, R A; Metcalf, S; Chong, D M O

2013-12-15

Large budgets are spent on both suppression and fuel treatments in order to reduce the risk of wildfires. There is little evidence regarding the relative contribution of fire weather, suppression and fuel treatments in determining the risk posed from wildfires. Here we undertake a simulation study in the Sydney Basin, Australia, to examine this question using a fire behaviour model (Phoenix Rapidfire). Results of the study indicate that fire behaviour is most strongly influenced by fire weather. Suppression has a greater influence on whether a fire reaches 5 ha in size compared to fuel treatments. In contrast, fuel treatments have a stronger effect on the fire size and maximum distance the fire travels. The study suggests that fire management agencies will receive additional benefits from fuel treatment if they are located in areas which suppression resources can respond rapidly and attempt to contain the fires. No combination of treatments contained all fires, and the proportion of uncontained fires increased under more severe fire weather when the greatest number of properties are lost. Our study highlights the importance of alternative management strategies to reduce the risk of property loss. Crown Copyright © 2013. Published by Elsevier Ltd. All rights reserved.

Assessment of marine weather forecasts over the Indian sector of Southern Ocean

NASA Astrophysics Data System (ADS)

Gera, Anitha; Mahapatra, D. K.; Sharma, Kuldeep; Prakash, Satya; Mitra, A. K.; Iyengar, G. R.; Rajagopal, E. N.; Anilkumar, N.

2017-09-01

The Southern Ocean (SO) is one of the important regions where significant processes and feedbacks of the Earth's climate take place. Expeditions to the SO provide useful data for improving global weather/climate simulations and understanding many processes. Some of the uncertainties in these weather/climate models arise during the first few days of simulation/forecast and do not grow much further. NCMRWF issued real-time five day weather forecasts of mean sea level pressure, surface winds, winds at 500 hPa & 850 hPa and rainfall, daily to NCAOR to provide guidance for their expedition to Indian sector of SO during the austral summer of 2014-2015. Evaluation of the skill of these forecasts indicates possible error growth in the atmospheric model at shorter time scales. The error growth is assessed using the model analysis/reanalysis, satellite data and observations made during the expedition. The observed variability of sub-seasonal rainfall associated with mid-latitude systems is seen to exhibit eastward propagations and are well reproduced in the model forecasts. All cyclonic disturbances including the sub-polar lows and tropical cyclones that occurred during this period were well captured in the model forecasts. Overall, this model performs reasonably well over the Indian sector of the SO in medium range time scale.

Monitoring a local extreme weather event with the scope of hyperspectral sounding

NASA Astrophysics Data System (ADS)

Satapathy, Jyotirmayee; Jangid, Buddhi Prakash

2018-06-01

Operational space-based hyperspectral Infrared sounders retrieve atmospheric temperature and humidity profiles from the measured radiances. These sounders like Atmospheric InfraRed Sounder, Infrared Atmospheric Sounding Interferometer as well as INSAT-3D sounders on geostationary orbit have proved to be very successful in providing these retrievals on global and regional scales, respectively, with good enough spatio-temporal resolutions and are well competent with that of traditional profiles from radiosondes and models fields. The aim of this work is to show how these new generation hyperspectral Infrared sounders can benefit in real-time weather monitoring. We have considered a regional extreme weather event to demonstrate how the profiles retrieved from these operational sounders are consistent with the environmental conditions which have led to this severe weather event. This work has also made use of data products of Moderate Resolution Imaging Spectroradiometer as well as by radiative transfer simulation of clear and cloudy atmospheric conditions using Numerical Weather Prediction profiles in conjunction with INSAT-3D sounder. Our results indicate the potential use of high-quality hyperspectral atmospheric profiles to aid in delineation of real-time weather prediction.

The Effect of Ownship Information and NexRad Resolution on Pilot Decision Making in the Use of a Cockpit Weather Information Display

NASA Technical Reports Server (NTRS)

Novacek, Paul F.; Burgess, Malcolm A.; Heck, Michael L.; Stokes, Alan F.; Stough, H. Paul, III (Technical Monitor)

2001-01-01

A two-phase experiment was conducted to explore the effects of data-link weather displays upon pilot decision performance. The experiment was conducted with 49 instrument rated pilots who were divided into four groups and placed in a simulator with a realistic flight scenario involving weather containing convective activity. The inflight weather display depicted NEXRAD images, with graphical and textual METARs over a moving map display. The experiment explored the effect of weather information, ownship position symbology and NEXRAD cell size resolution. The phase-two experiment compared two groups using the data-linked weather display with ownship position symbology. These groups were compared to the phase-one group that did not have ownship position symbology. The phase-two pilots were presented with either large NEXRAD cell size (8 km) or small cell size (4 km). Observations noted that the introduction of ownship symbology did not appear to significantly impact the decision making process, however, the introduction of ownship did reduce workload. Additionally, NEXRAD cell size resolution did appear to influence the tactical decision making process.

Diagnostic Analysis of Ozone Concentrations Simulated by Two Regional-Scale Air Quality Models

EPA Science Inventory

Since the Community Multiscale Air Quality modeling system (CMAQ) and the Weather Research and Forecasting with Chemistry model (WRF/Chem) use different approaches to simulate the interaction of meteorology and chemistry, this study compares the CMAQ and WRF/Chem air quality simu...

Effect of woody and herbaceous plants on chemical weathering of basalt material

NASA Astrophysics Data System (ADS)

Mark, N.; Dontsova, K.; Barron-Gafford, G. A.

2011-12-01

Worldwide, semi-arid landscapes are transitioning from shallow-rooted grasslands to mixed vegetation savannas composed of deeper-rooted shrubs. These contrasting growth forms differentially drive below-ground processes because they occupy different soil horizons, are differentially stressed by periods of drought, and unequally stimulate soil weathering. Our study aims to determine the effect of woody and herbaceous plants on weathering of granular basalt serving as a model for soil. We established pots with velvet mesquite (Prosopis veluntina), sideoats grama (Bouteloua curtipendula), and bare-soil pots within two temperature treatments in University of Arizona Biosphere 2. The Desert biome served as the ambient temperature treatment, while the Savanna biome was maintained 4°C warmer to simulate projected air temperatures if climate change continues unabated. Rhizon water samplers were installed at a depth of one inch from the soil surface to monitor root zone exudates (total dissolved carbon and nitrogen), dissolved inorganic carbon, and lithogenic elements resulting from basalt weathering. Soil leachates were collected through the course of the experiment. The anion content of the leachates was determined using the ICS-5000 Reagent-Free ion chromatography system. Dissolved carbon and nitrogen were analyzed by combustion using the Shimadzu TOC-VCSH with TN module. Metals and metalloids were measured using inductively coupled plasma mass spectrometry. Irrigation of the pots was varied in time to simulate periods of drought and determine the effect of stress on root exudation. Leachates from all treatments displayed higher pH and electrical conductivity than water used for irrigation indicating weathering. On average, leachates from the potted grasses displayed higher pH and electrical conductivity than mesquites. This agreed with higher concentrations of organic carbon, a measure of root exudation, and inorganic carbon, measure of soil respiration. Both organic acids exuded by plants and respired CO2 have been linked to mineral weathering. Increased weathering in grass treatments also resulted in higher concentrations of plant nutrients. No effect of temperature on plant exudation or basalt weathering was observed in the course of the experiment. This work links physiological plant responses to temperature and water stress by two vegetation types with below-ground processes that result in soil evolution.