An Enhanced Convective Forecast (ECF) for the New York TRACON Area

NASA Technical Reports Server (NTRS)

Wheeler, Mark; Stobie, James; Gillen, Robert; Jedlovec, Gary; Sims, Danny

2008-01-01

In an effort to relieve summer-time congestion in the NY Terminal Radar Approach Control (TRACON) area, the FAA is testing an enhanced convective forecast (ECF) product. The test began in June 2008 and is scheduled to run through early September. The ECF is updated every two hours, right before the Air Traffic Control System Command Center (ATCSCC) national planning telcon. It is intended to be used by traffic managers throughout the National Airspace System (NAS) and airlines dispatchers to supplement information from the Collaborative Convective Forecast Product (CCFP) and the Corridor Integrated Weather System (CIWS). The ECF begins where the current CIWS forecast ends at 2 hours and extends out to 12 hours. Unlike the CCFP it is a detailed deterministic forecast with no aerial coverage limits. It is created by an ENSCO forecaster using a variety of guidance products including, the Weather Research and Forecast (WRF) model. This is the same version of the WRF that ENSCO runs over the Florida peninsula in support of launch operations at the Kennedy Space Center. For this project, the WRF model domain has been shifted to the Northeastern US. Several products from the NASA SPoRT group are also used by the ENSCO forecaster. In this paper we will provide examples of the ECF products and discuss individual cases of traffic management actions using ECF guidance.

Establishing NWP capabilities in African Small Island States (SIDs)

NASA Astrophysics Data System (ADS)

Rögnvaldsson, Ólafur

2017-04-01

Íslenskar orkurannsóknir (ÍSOR), in collaboration with Belgingur Ltd. and the United Nations Economic Commission for Africa (UNECA) signed a Letter of Agreement in 2015 regarding collaboration in the "Establishing Operational Capacity for Building, Deploying and Using Numerical Weather and Seasonal Prediction Systems in Small Island States in Africa (SIDs)" project. The specific objectives of the collaboration were the following: - Build capacity of National Meteorological and Hydrology Services (NMHS) staff on the use of the WRF atmospheric model for weather and seasonal forecasting, interpretation of model results, and the use of observations to verify and improve model simulations. - Establish a platform for integrating short to medium range weather forecasts, as well as seasonal forecasts, into already existing infrastructure at NMHS and Regional Climate Centres. - Improve understanding of existing model results and forecast verification, for improving decision-making on the time scale of days to weeks. To meet these challenges the operational Weather On Demand (WOD) forecasting system, developed by Belgingur, is being installed in a number of SIDs countries (Cabo Verde, Guinea-Bissau, and Seychelles), as well as being deployed for the Pan-Africa region, with forecasts being disseminated to collaborating NMHSs.

IEA Wind Task 36 Forecasting

NASA Astrophysics Data System (ADS)

Giebel, Gregor; Cline, Joel; Frank, Helmut; Shaw, Will; Pinson, Pierre; Hodge, Bri-Mathias; Kariniotakis, Georges; Sempreviva, Anna Maria; Draxl, Caroline

2017-04-01

Wind power forecasts have been used operatively for over 20 years. Despite this fact, there are still several possibilities to improve the forecasts, both from the weather prediction side and from the usage of the forecasts. The new International Energy Agency (IEA) Task on Wind Power Forecasting tries to organise international collaboration, among national weather centres with an interest and/or large projects on wind forecast improvements (NOAA, DWD, UK MetOffice, …) and operational forecaster and forecast users. The Task is divided in three work packages: Firstly, a collaboration on the improvement of the scientific basis for the wind predictions themselves. This includes numerical weather prediction model physics, but also widely distributed information on accessible datasets for verification. Secondly, we will be aiming at an international pre-standard (an IEA Recommended Practice) on benchmarking and comparing wind power forecasts, including probabilistic forecasts aiming at industry and forecasters alike. This WP will also organise benchmarks, in cooperation with the IEA Task WakeBench. Thirdly, we will be engaging end users aiming at dissemination of the best practice in the usage of wind power predictions, especially probabilistic ones. The Operating Agent is Gregor Giebel of DTU, Co-Operating Agent is Joel Cline of the US Department of Energy. Collaboration in the task is solicited from everyone interested in the forecasting business. We will collaborate with IEA Task 31 Wakebench, which developed the Windbench benchmarking platform, which this task will use for forecasting benchmarks. The task runs for three years, 2016-2018. Main deliverables are an up-to-date list of current projects and main project results, including datasets which can be used by researchers around the world to improve their own models, an IEA Recommended Practice on performance evaluation of probabilistic forecasts, a position paper regarding the use of probabilistic forecasts, and one or more benchmark studies implemented on the Windbench platform hosted at CENER. Additionally, spreading of relevant information in both the forecasters and the users community is paramount. The poster also shows the work done in the first half of the Task, e.g. the collection of available datasets and the learnings from a public workshop on 9 June in Barcelona on Experiences with the Use of Forecasts and Gaps in Research. Participation is open for all interested parties in member states of the IEA Annex on Wind Power, see ieawind.org for the up-to-date list. For collaboration, please contact the author grgi@dtu.dk).

Weather-centric rangeland revegetation planning

USGS Publications Warehouse

Hardegree, Stuart P.; Abatzoglou, John T.; Brunson, Mark W.; Germino, Matthew; Hegewisch, Katherine C.; Moffet, Corey A.; Pilliod, David S.; Roundy, Bruce A.; Boehm, Alex R.; Meredith, Gwendwr R.

2018-01-01

Invasive annual weeds negatively impact ecosystem services and pose a major conservation threat on semiarid rangelands throughout the western United States. Rehabilitation of these rangelands is challenging due to interannual climate and subseasonal weather variability that impacts seed germination, seedling survival and establishment, annual weed dynamics, wildfire frequency, and soil stability. Rehabilitation and restoration outcomes could be improved by adopting a weather-centric approach that uses the full spectrum of available site-specific weather information from historical observations, seasonal climate forecasts, and climate-change projections. Climate data can be used retrospectively to interpret success or failure of past seedings by describing seasonal and longer-term patterns of environmental variability subsequent to planting. A more detailed evaluation of weather impacts on site conditions may yield more flexible adaptive-management strategies for rangeland restoration and rehabilitation, as well as provide estimates of transition probabilities between desirable and undesirable vegetation states. Skillful seasonal climate forecasts could greatly improve the cost efficiency of management treatments by limiting revegetation activities to time periods where forecasts suggest higher probabilities of successful seedling establishment. Climate-change projections are key to the application of current environmental models for development of mitigation and adaptation strategies and for management practices that require a multidecadal planning horizon. Adoption of new weather technology will require collaboration between land managers and revegetation specialists and modifications to the way we currently plan and conduct rangeland rehabilitation and restoration in the Intermountain West.

Verification of Space Weather Forecasts using Terrestrial Weather Approaches

NASA Astrophysics Data System (ADS)

Henley, E.; Murray, S.; Pope, E.; Stephenson, D.; Sharpe, M.; Bingham, S.; Jackson, D.

2015-12-01

The Met Office Space Weather Operations Centre (MOSWOC) provides a range of 24/7 operational space weather forecasts, alerts, and warnings, which provide valuable information on space weather that can degrade electricity grids, radio communications, and satellite electronics. Forecasts issued include arrival times of coronal mass ejections (CMEs), and probabilistic forecasts for flares, geomagnetic storm indices, and energetic particle fluxes and fluences. These forecasts are produced twice daily using a combination of output from models such as Enlil, near-real-time observations, and forecaster experience. Verification of forecasts is crucial for users, researchers, and forecasters to understand the strengths and limitations of forecasters, and to assess forecaster added value. To this end, the Met Office (in collaboration with Exeter University) has been adapting verification techniques from terrestrial weather, and has been working closely with the International Space Environment Service (ISES) to standardise verification procedures. We will present the results of part of this work, analysing forecast and observed CME arrival times, assessing skill using 2x2 contingency tables. These MOSWOC forecasts can be objectively compared to those produced by the NASA Community Coordinated Modelling Center - a useful benchmark. This approach cannot be taken for the other forecasts, as they are probabilistic and categorical (e.g., geomagnetic storm forecasts give probabilities of exceeding levels from minor to extreme). We will present appropriate verification techniques being developed to address these forecasts, such as rank probability skill score, and comparing forecasts against climatology and persistence benchmarks. As part of this, we will outline the use of discrete time Markov chains to assess and improve the performance of our geomagnetic storm forecasts. We will also discuss work to adapt a terrestrial verification visualisation system to space weather, to help MOSWOC forecasters view verification results in near real-time; plans to objectively assess flare forecasts under the EU Horizon 2020 FLARECAST project; and summarise ISES efforts to achieve consensus on verification.

Navigating the "Research-to-Operations" Bridge of Death: Collaborative Transition of Remotely-Sensed Snow Data from Research into Operational Water Resources Forecasting

NASA Astrophysics Data System (ADS)

Miller, W. P.; Bender, S.; Painter, T. H.; Bernard, B.

2016-12-01

Water and resource management agencies can benefit from hydrologic forecasts during both flood and drought conditions. Improved predictions of seasonal snowmelt-driven runoff volume and timing can assist operational water managers with decision support and efficient resource management within the spring runoff season. Using operational models and forecasting systems, NOAA's Colorado Basin River Forecast Center (CBRFC) produces hydrologic forecasts for stakeholders and water management groups in the western United States. Collaborative incorporation of research-oriented remote sensing data into CBRFC operational models and systems is one route by which CBRFC forecasts can be improved, ultimately for the benefit of water managers. Successful navigation of research-oriented remote sensing products across the "research-to-operations"/R2O gap (also known as the "valley of death") to operational destinations requires dedicated personnel on both the research and operations sides, working in a highly collaborative environment. Since 2012, the operational CBRFC has collaborated with the research-oriented Jet Propulsion Laboratory (JPL) under funding from NASA to transition remotely-sensed snow data into CBRFC's operational models and forecasting systems. Two specific datasets from JPL, the MODIS Dust Radiative Forcing in Snow (MODDRFS) and the MODIS Snow Covered-Area and Grain size (MODSCAG) products, are used in CBRFC operations as of 2016. Over the past several years, JPL and CBRFC have worked together to analyze patterns in JPL's remote sensing snow datasets from the operational perspective of the CBRFC and to develop techniques to bridge the R2O gap. Retrospective and real-time analyses have yielded valuable insight into the remotely-sensed snow datasets themselves, CBRFC's operational systems, and the collaborative R2O process. Examples of research-oriented JPL snow data, as used in CBRFC operations, are described. A timeline of the collaboration, challenges encountered during the journey across the R2O gap, or "valley of death", and solutions to those challenges are also illustrated.

Why preferring parametric forecasting to nonparametric methods?

PubMed

Jabot, Franck

2015-05-07

A recent series of papers by Charles T. Perretti and collaborators have shown that nonparametric forecasting methods can outperform parametric methods in noisy nonlinear systems. Such a situation can arise because of two main reasons: the instability of parametric inference procedures in chaotic systems which can lead to biased parameter estimates, and the discrepancy between the real system dynamics and the modeled one, a problem that Perretti and collaborators call "the true model myth". Should ecologists go on using the demanding parametric machinery when trying to forecast the dynamics of complex ecosystems? Or should they rely on the elegant nonparametric approach that appears so promising? It will be here argued that ecological forecasting based on parametric models presents two key comparative advantages over nonparametric approaches. First, the likelihood of parametric forecasting failure can be diagnosed thanks to simple Bayesian model checking procedures. Second, when parametric forecasting is diagnosed to be reliable, forecasting uncertainty can be estimated on virtual data generated with the fitted to data parametric model. In contrast, nonparametric techniques provide forecasts with unknown reliability. This argumentation is illustrated with the simple theta-logistic model that was previously used by Perretti and collaborators to make their point. It should convince ecologists to stick to standard parametric approaches, until methods have been developed to assess the reliability of nonparametric forecasting. Copyright © 2015 Elsevier Ltd. All rights reserved.

7 CFR 1710.209 - Approval requirements for load forecast work plans.

Code of Federal Regulations, 2010 CFR

2010-01-01

... cooperate in the preparation of and submittal of the load forecast work plan of their power supply borrower. (b) An approved load forecast work plan establishes the process for the preparation and maintenance... approved load forecast work plan must outline the coordination and preparation requirements for both the...

Data: Big and Small.

PubMed

Jones-Schenk, Jan

2017-02-01

Big data is a big topic in all leadership circles. Leaders in professional development must develop an understanding of what data are available across the organization that can inform effective planning for forecasting. Collaborating with others to integrate data sets can increase the power of prediction. Big data alone is insufficient to make big decisions. Leaders must find ways to access small data and triangulate multiple types of data to ensure the best decision making. J Contin Educ Nurs. 2017;48(2):60-61. Copyright 2017, SLACK Incorporated.

Developing the Capacity of Farmers to Understand and Apply Seasonal Climate Forecasts through Collaborative Learning Processes

ERIC Educational Resources Information Center

Cliffe, Neil; Stone, Roger; Coutts, Jeff; Reardon-Smith, Kathryn; Mushtaq, Shahbaz

2016-01-01

Purpose: This paper documents and evaluates collaborative learning processes aimed at developing farmer's knowledge, skills and aspirations to use seasonal climate forecasting (SCF). Methodology: Thirteen workshops conducted in 2012 engaged over 200 stakeholders across Australian sugar production regions. Workshop design promoted participant…

Better Forecasting for Better Planning: A Systems Approach.

ERIC Educational Resources Information Center

Austin, W. Burnet

Predictions and forecasts are the most critical features of rational planning as well as the most vulnerable to inaccuracy. Because plans are only as good as their forecasts, current planning procedures could be improved by greater forecasting accuracy. Economic factors explain and predict more than any other set of factors, making economic…

How rolling forecasting facilitates dynamic, agile planning.

PubMed

Miller, Debra; Allen, Michael; Schnittger, Stephanie; Hackman, Theresa

2013-11-01

Rolling forecasting may be used to replace or supplement the annual budget process. The rolling forecast typically builds on the organization's strategic financial plan, focusing on the first three years of plan projections and comparing the strategic financial plan assumptions with the organization's expected trajectory. Leaders can then identify and respond to gaps between the rolling forecast and the strategic financial plan on an ongoing basis.

Collaborative Initiative toward Developing River Forecasting in South America

NASA Astrophysics Data System (ADS)

Cabrera, R.

2015-12-01

In the United States, river floods have been discussed as early as 1884. Following a disastrous flooding in 1903, Congress passed legislation and river and flood services became a separate division within the U.S. Weather Bureau. The first River Forecast Center started in 1946 and today the whole country is served by thirteen River Forecast Centers. News from Latin American and Caribbean Countries often report of devastating flooding. However, river forecast services are not fully developed yet. This presentation suggests the utilization of a multinational collaborative approach toward the development of river forecasts in order to mitigate flooding in South America. The benefit of an international strategy resides in the strength created by a team of professionals with different capabilities and expertise.

Improvements in approaches to forecasting and evaluation techniques

NASA Astrophysics Data System (ADS)

Weatherhead, Elizabeth

2014-05-01

The US is embarking on an experiment to make significant and sustained improvements in weather forecasting. The effort stems from a series of community conversations that recognized the rapid advancements in observations, modeling and computing techniques in the academic, governmental and private sectors. The new directions and initial efforts will be summarized, including information on possibilities for international collaboration. Most new projects are scheduled to start in the last half of 2014. Several advancements include ensemble forecasting with global models, and new sharing of computing resources. Newly developed techniques for evaluating weather forecast models will be presented in detail. The approaches use statistical techniques that incorporate pair-wise comparisons of forecasts with observations and account for daily auto-correlation to assess appropriate uncertainty in forecast changes. Some of the new projects allow for international collaboration, particularly on the research components of the projects.

Using Web-Based Collaborative Forecasting to Enhance Information Literacy and Disciplinary Knowledge

ERIC Educational Resources Information Center

Buckley, Patrick; Doyle, Elaine

2016-01-01

This paper outlines how an existing collaborative forecasting tool called a prediction market (PM) can be integrated into an educational context to enhance information literacy skills and cognitive disciplinary knowledge. The paper makes a number of original contributions. First, it describes how this tool can be packaged as a pedagogical…

Collaboration Portals for NASA's Airborne Field Campaigns

NASA Astrophysics Data System (ADS)

Conover, H.; Kulkarni, A.; Garrett, M.; Goodman, M.; Petersen, W. A.; Drewry, M.; Hardin, D. M.; He, M.

2011-12-01

The University of Alabama in Huntsville (UAH), in collaboration with the Global Hydrology Resource Center, a NASA Earth Science Data Center, has provided information management for a number of NASA Airborne Field campaigns, both hurricane science investigations and satellite instrument validation. Effective field campaign management requires communication and coordination tools, including utilities for personnel to upload and share flight plans, weather forecasts, a variety of mission reports, preliminary science data, and personal photos. Beginning with the Genesis and Rapid Intensification Processes (GRIP) hurricane field campaign in 2010, we have provided these capabilities via a Drupal-based collaboration portal. This portal was reused and modified for the Midlatitude Continental Convective Clouds Experiment (MC3E), part of the Global Precipitation Measurement mission ground validation program. An end goal of these development efforts is the creation of a Drupal profile for field campaign management. This presentation will discuss experiences with Drupal in developing and using these collaboration portals. Topics will include Drupal modules used, advantages and disadvantages of working with Drupal in this context, and how the science teams used the portals in comparison with other communication and collaboration tools.

Collaboration Portals for NASA's Airborne Field Campaigns

NASA Technical Reports Server (NTRS)

Conover, Helen; Kulkami, Ajinkya; Garrett, Michele; Goodman, Michael; Peterson, Walter Arthur; Drewry, Marilyn; Hardin, Danny M.; He, Matt

2011-01-01

The University of Alabama in Huntsville (UAH), in collaboration with the Global Hydrology Resource Center, a NASA Earth Science Data Center, has provided information management for a number of NASA Airborne Field campaigns, both hurricane science investigations and satellite instrument validation. Effective field campaign management requires communication and coordination tools, including utilities for personnel to upload and share flight plans, weather forecasts, a variety of mission reports, preliminary science data, and personal photos. Beginning with the Genesis and Rapid Intensification Processes (GRIP) hurricane field campaign in 2010, we have provided these capabilities via a Drupal-based collaboration portal. This portal was reused and modified for the Midlatitude Continental Convective Clouds Experiment (MC3E), part of the Global Precipitation Measurement mission ground validation program. An end goal of these development efforts is the creation of a Drupal profile for field campaign management. This presentation will discuss experiences with Drupal in developing and using these collaboration portals. Topics will include Drupal modules used, advantages and disadvantages of working with Drupal in this context, and how the science teams used the portals in comparison with other communication and collaboration tools.

Information Technology Resources Assessment

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

Not Available

1993-04-01

The Information Technology Resources Assessment (ITRA) is being published as a companion document to the Department of Energy (DOE) FY 1994--FY 1998 Information Resources Management Long-Range Plan. This document represents a collaborative effort between the Office of Information Resources Management and the Office of Energy Research that was undertaken to achieve, in part, the Technology Strategic Objective of IRM Vision 21. An integral part of this objective, technology forecasting provides an understanding of the information technology horizon and presents a perspective and focus on technologies of particular interest to DOE program activities. Specifically, this document provides site planners with anmore » overview of the status and use of new information technology for their planning consideration.« less

Flooding During Drought: Learning from Stakeholder Engagement & Partner Coordination in the California-Nevada Drought Early Warning System (DEWS)

NASA Astrophysics Data System (ADS)

Sheffield, A. M.

2017-12-01

After more than 5 years of drought, extreme precipitation brought drought relief in California and Nevada and presents an opportunity to reflect upon lessons learned while planning for the future. NOAA's National Integrated Drought Information System (NIDIS) California-Nevada Drought Early Warning System (DEWS) in June 2017 convened a regional coordination workshop to provide a forum to discuss and build upon past drought efforts in the region and increase coordination, collaboration and information sharing across the region as a whole. Participants included federal, tribal, state, academic, and local partners who provided a post-mortem on the recent drought and impacts as well as recent innovations in drought monitoring, forecasts, and decision support tools in response to the historic drought. This presentation will highlight lessons learned from stakeholder outreach and engagement around flooding during drought, and pathways for moving forward coordination and collaboration in the region. Additional focus will be on the potential opportunities from examining California decision making calendars from this drought. Identified gaps and challenges will also be shared, such as the need to connect observations with social impacts, capacity building around available tools and resources, and future drought monitoring needs. Drought will continue to impact California and Nevada, and the CA-NV DEWS works to make climate and drought science readily available, easily understandable and usable for decision makers; and to improve the capacity of stakeholders to better monitor, forecast, plan for and cope with the impacts of drought.

Arctic Forecasts Available from Polar Bear Exhibit as an Example of Formal/Informal Collaboration

NASA Astrophysics Data System (ADS)

Landis, C. E.; Cervenec, J.

2012-12-01

A subset of the general population enjoys and frequents informal education venues, offering an opportunity for lifelong learning that also enhances and supports formal education efforts. The Byrd Polar Research Center (BPRC) at The Ohio State University collaborated with the Columbus Zoo & Aquarium (CZA) in the development of their Polar Frontier exhibit, from its initial planning to the Grand Opening of the exhibit, through the present. Of course, the addition to the Zoo of polar bears and Arctic fox in the Polar Frontier has been very popular, with almost a 7% increase in visitors in 2010 when the exhibit opened. The CZA and BPRC are now investigating ways to increase the climate literacy impact of the exhibit, and to increase engagement with the topics through follow-on activities. For example, individuals or classes anywhere in the world can check forecasts from the Polar Weather and Research Forecasting model and compare them to observed conditions-- allowing deep investigation into changes in the Arctic. In addition, opportunities exist to adapt the Zoo School experience (affecting several Central Ohio school districts) and/or to enable regular participation through social media such as Facebook, Twitter, and other forms of digital communication. BPRC's sustained engagement with the CZA is an example of a trusted and meaningful partnership where open dialogue exists about providing the best learning experience for visitors. This presentation will share some of the lessons learned from this unique partnership, and strategies that are adopted to move it forward.

AN OPERATIONAL EVALUATION OF THE ETA-CMAQ AIR QUALITY FORECAST MODEL

EPA Science Inventory

The National Oceanic and Atmospheric Administration (NOAA), in collaboration with the Environmental Protection Agency (EPA), are developing an Air Quality Forecasting Program that will eventually result in an operational Nationwide Air Quality Forecasting System. The initial pha...

Strengthening Connections between Dendrohydrology and Water Management in the Mediterranean Basin

NASA Astrophysics Data System (ADS)

Touchan, R.; Freitas, R. J.

2017-12-01

Dendrochronology can provide the knowledge upon which to base sound decisions for water resources. In general, water managers are limited to using short continuous instrumental records for forecasting streamflows and reservoir levels. Longer hydrological records are required. Proxy data such as annual tree-ring growth provide us with knowledge of the past frequency and severity of climatic anomalies, such as drought and wet periods, and can be used to improve probability calculations of future events. By improving probability input to these plans, water managers can use this information for water allocations, water conservation measures, and water efficiency methods. Accurate planning is critical in water deficit regions with histories of conflict over land and limited water. Here, we link the science of dendrohydrology with water management, and identify appropriate forums for scientists, policy decision makers, and water managers to collaborate in translating science into effective actions anticipating extreme events, such drought or floods. We will present examples of several dendrohydrological reconstructions from the eastern Mediterranean and North Africa as input for water management plans. Different disciplines are needed to work together, and we identify possible mechanisms to collaborate in order to reach this crucial necessity to use scarce water wisely.

Diagnosis of North American Multi-Model Ensemble (NMME) skill for predicting floods and droughts over the continental USA

NASA Astrophysics Data System (ADS)

Slater, L. J.; Villarini, G.; Bradley, A.

2015-12-01

Model predictions of precipitation and temperature are crucial to mitigate the impacts of major flood and drought events through informed planning and response. However, the potential value and applicability of these predictions is inescapably linked to their forecast quality. The North-American Multi-Model Ensemble (NMME) is a multi-agency supported forecasting system for intraseasonal to interannual (ISI) climate predictions. Retrospective forecasts and real-time information are provided by each agency free of charge to facilitate collaborative research efforts for predicting future climate conditions as well as extreme weather events such as floods and droughts. Using the PRISM climate mapping system as the reference data, we examine the skill of five General Circulation Models (GCMs) from the NMME project to forecast monthly and seasonal precipitation and temperature over seven sub-regions of the continental United States. For each model, we quantify the seasonal accuracy of the forecast relative to observed precipitation using the mean square error skill score. This score is decomposed to assess the accuracy of the forecast in the absence of biases (potential skill), and in the presence of conditional (slope reliability) and unconditional (standardized mean error) biases. The quantification of these biases allows us to diagnose each model's skill over a full range temporal and spatial scales. Finally, we test each model's forecasting skill by evaluating its ability to predict extended periods of extreme temperature and precipitation that were conducive to 'billion-dollar' historical flood and drought events in different regions of the continental USA. The forecasting skill of the individual climate models is summarized and presented along with a discussion of different multi-model averaging techniques for predicting such events.

Louisiana Airport System Plan aviation activity forecasts 1990-2010.

DOT National Transportation Integrated Search

1991-07-01

This report documents the methodology used to develop the aviation activity forecasts prepared as a part of the update to the Louisiana Airport System Plan and provides Louisiana aviation forecasts for the years 1990 to 2010. In general, the forecast...

Moving Toward a Globally Harmonized Volcanic Ash Forecast System: Anchorage and Tokyo VAAC Best Practices on Collaboration

NASA Astrophysics Data System (ADS)

Osiensky, J. M.; Moore, D.; Igarashi, Y.

2014-12-01

Since the eruption of Eyjafjallajökull in 2010, there has been an increased awareness on the need for better collaboration between the Volcanic Ash Advisory Centers (VAACs). Work through the International Civil Aviation Organization (ICAO) International Airways Volcano Watch Operations Group (IAVWOPSG) and International Airways Volcano Task Force (IAVTF) brought increased awareness and focus to this challenge. A VAAC Best Practices group was formed out of these larger meetings and focused on VAAC specific issues of importance. Collaboration was one of the topics under consideration. Some ideas and procedures for an effective, yet easy, method for the VAACs to collaborate have been discussed. Implementation has been mainly on a VAAC to VAAC basis, however a more consolidated process needs to be developed and agreed upon between all VAACs in order to successfully move toward harmonization. Collaboration procedures and tools are being considered. The National Weather Service (NWS) Alaska Region has been looking at collaborative software to help the VAACs identify the presence of ash and forecast the plume both in the horizontal and vertical. Having an interactive graphical interface within the forecast operation may help to ensure consistency across VAAC boundaries. Existing chat software within NWS is being investigated to allow Tokyo and Anchorage VAAC to "chat" about forecast issues in real time. This capability is being tested through scenarios. The Anchorage and Tokyo VAACs participated in a series of meetings in Tokyo in March 2014. Collaboration was a major topic of discussion. This paper will outline some of the efforts being undertaken between the Anchorage and Tokyo VAACs as a result of these meetings and subsequent dialogue.

Baseline and Target Values for PV Forecasts: Toward Improved Solar Power Forecasting: Preprint

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

Zhang, Jie; Hodge, Bri-Mathias; Lu, Siyuan

2015-08-05

Accurate solar power forecasting allows utilities to get the most out of the solar resources on their systems. To truly measure the improvements that any new solar forecasting methods can provide, it is important to first develop (or determine) baseline and target solar forecasting at different spatial and temporal scales. This paper aims to develop baseline and target values for solar forecasting metrics. These were informed by close collaboration with utility and independent system operator partners. The baseline values are established based on state-of-the-art numerical weather prediction models and persistence models. The target values are determined based on the reductionmore » in the amount of reserves that must be held to accommodate the uncertainty of solar power output. forecasting metrics. These were informed by close collaboration with utility and independent system operator partners. The baseline values are established based on state-of-the-art numerical weather prediction models and persistence models. The target values are determined based on the reduction in the amount of reserves that must be held to accommodate the uncertainty of solar power output.« less

Integrated Wind Power Planning Tool

NASA Astrophysics Data System (ADS)

Rosgaard, M. H.; Giebel, G.; Nielsen, T. S.; Hahmann, A.; Sørensen, P.; Madsen, H.

2012-04-01

This poster presents the current state of the public service obligation (PSO) funded project PSO 10464, with the working title "Integrated Wind Power Planning Tool". The project commenced October 1, 2011, and the goal is to integrate a numerical weather prediction (NWP) model with purely statistical tools in order to assess wind power fluctuations, with focus on long term power system planning for future wind farms as well as short term forecasting for existing wind farms. Currently, wind power fluctuation models are either purely statistical or integrated with NWP models of limited resolution. With regard to the latter, one such simulation tool has been developed at the Wind Energy Division, Risø DTU, intended for long term power system planning. As part of the PSO project the inferior NWP model used at present will be replaced by the state-of-the-art Weather Research & Forecasting (WRF) model. Furthermore, the integrated simulation tool will be improved so it can handle simultaneously 10-50 times more turbines than the present ~ 300, as well as additional atmospheric parameters will be included in the model. The WRF data will also be input for a statistical short term prediction model to be developed in collaboration with ENFOR A/S; a danish company that specialises in forecasting and optimisation for the energy sector. This integrated prediction model will allow for the description of the expected variability in wind power production in the coming hours to days, accounting for its spatio-temporal dependencies, and depending on the prevailing weather conditions defined by the WRF output. The output from the integrated prediction tool constitute scenario forecasts for the coming period, which can then be fed into any type of system model or decision making problem to be solved. The high resolution of the WRF results loaded into the integrated prediction model will ensure a high accuracy data basis is available for use in the decision making process of the Danish transmission system operator, and the need for high accuracy predictions will only increase over the next decade as Denmark approaches the goal of 50% wind power based electricity in 2020, from the current 20%.

Some Initiatives in a Business Forecasting Course

ERIC Educational Resources Information Center

Chu, Singfat

2007-01-01

The paper reports some initiatives to freshen up the typical undergraduate business forecasting course. These include (1) students doing research and presentations on contemporary tools and industry practices such as neural networks and collaborative forecasting (2) insertion of Logistic Regression in the curriculum (3) productive use of applets…

The International Lunar Decade: A Giant Leap Forward in Understanding the Moon and Opportunities for its Development

NASA Astrophysics Data System (ADS)

Beldavs, Vid; Atvars, Aigars; Ubelis, Arnolds; Salmins, Kalvis; Crisafulli, Jim; Dunlop, David; Foing, Bernard

2015-04-01

In 1957 at the dawn of the space age the United Nations launched the International Geophysical Year which had a profound impact on collaboration among scientists around the globe. Its legacy includes several major scientific organizations as well as the beginnings of collaboration among nations that see themselves as competitors on Earth. The Soviet Union and the United States made many attempts at collaboration in space while building weapons systems to destroy each other. Space technologies have become the infrastructure for the ubiquitous smart phone with global telecommunications, navigation, weather forecasting, environmental monitoring, and hundreds of other applications. In 2015, the International Year of Light, several conferences will be held exploring the idea of an International Lunar Decade1 An informal group, the International Lunar Decade Working Group (ILDWG) has been formed to plan the launch of the International Lunar Decade in 2017, the 60th Anniversary of the International Geophysical Year. This report will cover the progress of the ILDWG covering conferences planned, international organizations involved and key publications. The activities of the ILDWG can be followed at http://2014giantleap.aerospacehawaii.info/. References [1] V. Beldavs, 2014 'The International Lunar Decade', The Space Review, http://www.thespacereview.com/article/2431/1

Operational tools to help stakeholders to protect and alert municipalities facing uncertainties and changes in karst flash floods

NASA Astrophysics Data System (ADS)

Borrell Estupina, V.; Raynaud, F.; Bourgeois, N.; Kong-A-Siou, L.; Collet, L.; Haziza, E.; Servat, E.

2015-06-01

Flash floods are often responsible for many deaths and involve many material damages. Regarding Mediterranean karst aquifers, the complexity of connections, between surface and groundwater, as well as weather non-stationarity patterns, increase difficulties in understanding the basins behaviour and thus warning and protecting people. Furthermore, given the recent changes in land use and extreme rainfall events, knowledge of the past floods is no longer sufficient to manage flood risks. Therefore the worst realistic flood that could occur should be considered. Physical and processes-based hydrological models are considered among the best ways to forecast floods under diverse conditions. However, they rarely match with the stakeholders' needs. In fact, the forecasting services, the municipalities, and the civil security have difficulties in running and interpreting data-consuming models in real-time, above all if data are uncertain or non-existent. To face these social and technical difficulties and help stakeholders, this study develops two operational tools derived from these models. These tools aim at planning real-time decisions given little, changing, and uncertain information available, which are: (i) a hydrological graphical tool (abacus) to estimate flood peak discharge from the karst past state and the forecasted but uncertain intense rainfall; (ii) a GIS-based method (MARE) to estimate the potential flooded pathways and areas, accounting for runoff and karst contributions and considering land use changes. Then, outputs of these tools are confronted to past and recent floods and municipalities observations, and the impacts of uncertainties and changes on planning decisions are discussed. The use of these tools on the recent 2014 events demonstrated their reliability and interest for stakeholders. This study was realized on French Mediterranean basins, in close collaboration with the Flood Forecasting Services (SPC Med-Ouest, SCHAPI, municipalities).

Load Forecasting in Electric Utility Integrated Resource Planning

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

Carvallo, Juan Pablo; Larsen, Peter H.; Sanstad, Alan H

Integrated resource planning (IRP) is a process used by many vertically-integrated U.S. electric utilities to determine least-cost/risk supply and demand-side resources that meet government policy objectives and future obligations to customers and, in many cases, shareholders. Forecasts of energy and peak demand are a critical component of the IRP process. There have been few, if any, quantitative studies of IRP long-run (planning horizons of two decades) load forecast performance and its relationship to resource planning and actual procurement decisions. In this paper, we evaluate load forecasting methods, assumptions, and outcomes for 12 Western U.S. utilities by examining and comparing plansmore » filed in the early 2000s against recent plans, up to year 2014. We find a convergence in the methods and data sources used. We also find that forecasts in more recent IRPs generally took account of new information, but that there continued to be a systematic over-estimation of load growth rates during the period studied. We compare planned and procured resource expansion against customer load and year-to-year load growth rates, but do not find a direct relationship. Load sensitivities performed in resource plans do not appear to be related to later procurement strategies even in the presence of large forecast errors. These findings suggest that resource procurement decisions may be driven by other factors than customer load growth. Our results have important implications for the integrated resource planning process, namely that load forecast accuracy may not be as important for resource procurement as is generally believed, that load forecast sensitivities could be used to improve the procurement process, and that management of load uncertainty should be prioritized over more complex forecasting techniques.« less

OHD/HL: Presentations

Science.gov Websites

enter or select the go button to submit request City, St Go Science Research and Collaboration Hydrology River Forecasts, January 2002 AMS Short Course on Quantitative Precipitation Estimation and Forecasting

Adaptive Regulation of the Northern California Reservoir System for Water, Energy, and Environmental Management

NASA Astrophysics Data System (ADS)

Georgakakos, A. P.; Kistenmacher, M.; Yao, H.; Georgakakos, K. P.

2014-12-01

The 2014 National Climate Assessment of the US Global Change Research Program emphasizes that water resources managers and planners in most US regions will have to cope with new risks, vulnerabilities, and opportunities, and recommends the development of adaptive capacity to effectively respond to the new water resources planning and management challenges. In the face of these challenges, adaptive reservoir regulation is becoming all the more ncessary. Water resources management in Northern California relies on the coordinated operation of several multi-objective reservoirs on the Trinity, Sacramento, American, Feather, and San Joaquin Rivers. To be effective, reservoir regulation must be able to (a) account for forecast uncertainty; (b) assess changing tradeoffs among water uses and regions; and (c) adjust management policies as conditions change; and (d) evaluate the socio-economic and environmental benefits and risks of forecasts and policies for each region and for the system as a whole. The Integrated Forecast and Reservoir Management (INFORM) prototype demonstration project operated in Northern California through the collaboration of several forecast and management agencies has shown that decision support systems (DSS) with these attributes add value to stakeholder decision processes compared to current, less flexible management practices. Key features of the INFORM DSS include: (a) dynamically downscaled operational forecasts and climate projections that maintain the spatio-temporal coherence of the downscaled land surface forcing fields within synoptic scales; (b) use of ensemble forecast methodologies for reservoir inflows; (c) assessment of relevant tradeoffs among water uses on regional and local scales; (d) development and evaluation of dynamic reservoir policies with explicit consideration of hydro-climatic forecast uncertainties; and (e) focus on stakeholder information needs.This article discusses the INFORM integrated design concept, underlying methodologies, and selected applications with the California water resources system.

Identifying needs for streamflow forecasting in the Incomati basin, Southern Africa

NASA Astrophysics Data System (ADS)

Sunday, Robert; Werner, Micha; Masih, Ilyas; van der Zaag, Pieter

2013-04-01

Despite being widely recognised as an efficient tool in the operational management of water resources, rainfall and streamflow forecasts are currently not utilised in water management practice in the Incomati Basin in Southern Africa. Although, there have been initiatives for forecasting streamflow in the Sabie and Crocodile sub-basins, the outputs of these have found little use because of scepticism on the accuracy and reliability of the information, or the relevance of the information provided to the needs of the water managers. The process of improving these forecasts is underway, but as yet the actual needs of the forecasts are unclear and scope of the ongoing initiatives remains very limited. In this study questionnaires and focused group interviews were used to establish the need, potential use, benefit and required accuracy of rainfall and streamflow forecasts in the Incomati Basin. Thirty five interviews were conducted with professionals engaged in water sector and detailed discussions were held with water institutions, including the Inkomati Catchment Management Agency (ICMA), Komati Basin Water Authority (KOBWA), South African Weather Service (SAWS), water managers, dam operators, water experts, farmers and other water users in the Basin. Survey results show that about 97% of the respondents receive weather forecasts. In contrast to expectations, only 5% have access to the streamflow forecast. In the weather forecast, the most important variables were considered to be rainfall and temperature at daily and weekly time scales. Moreover, forecasts of global climatic indices such as El Niño or La Niña were neither received nor demanded. There was limited demand and/or awareness of flood and drought forecasts including the information on their linkages with global climatic indices. While the majority of respondents indicate the need and indeed use the weather forecast, the provision, communication and interpretation were in general found to be with too little detail and clarity. In some cases this was attributed to the short time and space allotted in media such as television and newspapers respectively. Major uses of the weather forecast were made in personal planning i.e., travelling (29%) and dressing (23%). The usefulness in water sector was reported for water allocation (23%), farming (11%) and flood monitoring (9%), but was considered as a factor having minor influence on the actual decision making in operational water management mainly due to uncertainty of the weather forecast, difference in the time scale and institutional arrangements. In the incidences where streamflow forecasts were received (5% of the cases), its application in decision making was not carried out due to high uncertainty. Moreover, dam operators indicated weekly streamflow forecast as very important in releasing water for agriculture but this was not the format in which forecasts were available to them. Generally, users affirmed the accuracy and benefits of weather forecasts and had no major concerns on the impacts of wrong forecasts. However, respondents indicated the need to improve the accuracy and accessibility of the forecast. Likewise, water managers expressed the need for both rainfall and flow forecasts but indicated that they face hindrances due to financial and human resource constraints. This shows that there is a need to strengthen water related forecasts and the consequent uses in the basin. This can be done through collaboration among forecasting and water organisations such as the SAWS, Research Institutions and users like ICMA, KOBWA and farmers. Collaboration between the meteorology and water resources sectors is important to establish consistent forecast information. The forecasts themselves should be detailed and user specific to ensure these are indeed used and can answer to the needs of the users.

Improving global flood risk awareness through collaborative research: Id-Lab

NASA Astrophysics Data System (ADS)

Weerts, A.; Zijderveld, A.; Cumiskey, L.; Buckman, L.; Verlaan, M.; Baart, F.

2015-12-01

Scientific and end-user collaboration on operational flood risk modelling and forecasting requires an environment where scientists and end-users can physically work together and demonstrate, enhance and learn about new tools, methods and models for forecasting and warning purposes. Therefore, Deltares has built a real-time demonstration, training and research infrastructure ('operational' room and ICT backend). This research infrastructure supports various functions like (1) Real time response and disaster management, (2) Training, (3) Collaborative Research, (4) Demonstration. The research infrastructure will be used for a mixture of these functions on a regular basis by Deltares and a multitude of both scientists as well as end users such as universities, research institutes, consultants, governments and aid agencies. This infrastructure facilitates emergency advice and support during international and national disasters caused by rainfall, tropical cyclones or tsunamis. It hosts research flood and storm surge forecasting systems for global/continental/regional scale. It facilitates training for emergency & disaster management (along with hosting forecasting system user trainings in for instance the forecasting platform Delft-FEWS) both internally and externally. The facility is expected to inspire and initiate creative innovations by bringing together different experts from various organizations. The room hosts interactive modelling developments, participatory workshops and stakeholder meetings. State of the art tools, models and software, being applied across the globe are available and on display within the facility. We will present the Id-Lab in detail and we will put particular focus on the global operational forecasting systems GLOFFIS (Global Flood Forecasting Information System) and GLOSSIS (Global Storm Surge Information System).

Forecasting aviation activity by airport

DOT National Transportation Integrated Search

2001-07-01

The Federal Aviation Administration (FAA) has a responsibility to review aviation forecasts that are submitted to the agency in conjunction with airport planning, including airport master plans and environmental studies. FAA reviews such forecasts wi...

Improvement of Operational Streamflow Prediction with MODIS-derived Fractional Snow Covered Area Observations

NASA Astrophysics Data System (ADS)

Bender, S.; Burgess, A.; Goodale, C. E.; Mattmann, C. A.; Miller, W. P.; Painter, T. H.; Rittger, K. E.; Stokes, M.; Werner, K.

2013-12-01

Water managers in the western United States depend heavily on the timing and magnitude of snowmelt-driven runoff for municipal supply, irrigation, maintenance of environmental flows, and power generation. The Colorado Basin River Forecast Center (CBRFC) of the National Weather Service issues operational forecasts of snowmelt-driven streamflow for watersheds within the Colorado River Basin (CRB) and eastern Great Basin (EGB), across a wide variety of scales. Therefore, the CBRFC and its stakeholders consider snowpack observations to be highly valuable. Observations of fractional snow covered area (fSCA) from satellite-borne instrumentation can better inform both forecasters and water users with respect to subsequent snowmelt runoff, particularly when combined with observations from ground-based station networks and/or airborne platforms. As part of a multi-year collaborative effort, CBRFC has partnered with the Jet Propulsion Laboratory (JPL) under funding from NASA to incorporate observations of fSCA from NASA's Moderate Resolution Imaging Spectroradiometer (MODIS) into the operational CBRFC hydrologic forecasting and modeling process. In the first year of the collaboration, CBRFC and NASA/JPL integrated snow products into the forecasting and decision making processes of the CBRFC and showed preliminary improvement in operational streamflow forecasts. In late 2012, CBRFC and NASA/JPL began retrospective analysis of relationships between the MODIS Snow Covered Area and Grain size (MODSCAG) fSCA and streamflow patterns for several watersheds within the CRB and the EGB. During the 2013 snowmelt runoff season, CBRFC forecasters used MODIS-derived fSCA semi-quantitatively as a binary indicator of the presence or lack of snow. Indication of the presence or lack of snow by MODIS assisted CBRFC forecasters in determining the cause of divergence between modeled and recently observed streamflow. Several examples of improved forecasts from across the CRB and EGB, informed by MODIS-derived fSCA, are described. Our analysis shows the value of MODIS fSCA to CBRFC and to users of CBRFC's streamflow forecasts. The relationships between the MODIS fSCA and the melt season streamflow vary with the magnitude of runoff, which is important to resource managers. The analysis also emphasizes the importance of the invaluable collaboration between an operational forecasting agency (CBRFC) and a research-oriented agency (NASA/JPL) specializing in remote sensing science. The collaboration is expected to continue over the next several years as CBRFC and JPL work to further improve modeling of snowmelt and prediction of snowmelt-driven streamflow in the CRB and EGB.

Development of a High Resolution Weather Forecast Model for Mesoamerica Using the NASA Ames Code I Private Cloud Computing Environment

NASA Technical Reports Server (NTRS)

Molthan, Andrew; Case, Jonathan; Venner, Jason; Moreno-Madrinan, Max J.; Delgado, Francisco

2012-01-01

Two projects at NASA Marshall Space Flight Center have collaborated to develop a high resolution weather forecast model for Mesoamerica: The NASA Short-term Prediction Research and Transition (SPoRT) Center, which integrates unique NASA satellite and weather forecast modeling capabilities into the operational weather forecasting community. NASA's SERVIR Program, which integrates satellite observations, ground-based data, and forecast models to improve disaster response in Central America, the Caribbean, Africa, and the Himalayas.

Operational planning using Climatological Observations for Maritime Prediction and Analysis Support Service (COMPASS)

NASA Astrophysics Data System (ADS)

O'Connor, Alison; Kirtman, Benjamin; Harrison, Scott; Gorman, Joe

2016-05-01

The US Navy faces several limitations when planning operations in regard to forecasting environmental conditions. Currently, mission analysis and planning tools rely heavily on short-term (less than a week) forecasts or long-term statistical climate products. However, newly available data in the form of weather forecast ensembles provides dynamical and statistical extended-range predictions that can produce more accurate predictions if ensemble members can be combined correctly. Charles River Analytics is designing the Climatological Observations for Maritime Prediction and Analysis Support Service (COMPASS), which performs data fusion over extended-range multi-model ensembles, such as the North American Multi-Model Ensemble (NMME), to produce a unified forecast for several weeks to several seasons in the future. We evaluated thirty years of forecasts using machine learning to select predictions for an all-encompassing and superior forecast that can be used to inform the Navy's decision planning process.

Climate Change and Water Working Group - User Needs to Manage Hydrclimatic Risk from Days to Decades

NASA Astrophysics Data System (ADS)

Raff, D. A.; Brekke, L. D.; Werner, K.; Wood, A.; White, K. D.

2012-12-01

The Federal Climate Change Water Working Group (CCAWWG) provides engineering and scientific collaborations in support of water management. CCAWWG objectives include building working relationships across federal science and water management agencies, provide a forum to share expertise and leverage resources, develop education and training forums, to work with water managers to understand scientific needs and to foster collaborative efforts across the Federal and non-Federal water management and science communities to address those needs. Identifying and addressing water management needs has been categorized across two major time scales: days to a decade and multi-decadal, respectively. These two time periods are termed "Short-Term" and "Long-Term" in terms of the types of water management decisions they support where Short-Term roughly correlates to water management operations and Long-Term roughly correlates to planning activities. This presentation will focus on portraying the identified water management user needs across these two time periods. User Needs for Long-Term planning were identified in the 2011 Reclamation and USACE "Addressing Climate Change in Long-Term Water Resources Planning and Management: User Needs for Improving Tools and Information." User needs for Long-Term planning are identified across eight major categories: Summarize Relevant Literature, Obtain Climate Change Information, Make Decisions About How to Use the Climate Change Information, Assess Natural Systems Response, Assess Socioeconomic and Institutional Response, Assess System Risks and Evaluate Alternatives, Assess and Characterize Uncertainties, and Communicating Results and Uncertainties to Decisionmakers. User Needs for Short-Term operations are focused on needs relative to available or desired monitoring and forecast products from the hydroclimatic community. These needs are presenting in the 2012 USACE, Reclamation, and NOAA - NWS "Short-Term Water Management Decisions: User Needs for Improved Climate, Weather, and Hydrologic Information." Identified needs are presented in four categories: Monitoring, Forecasting, Understanding on Product Relationships and Utilization in Water Management, and Information Services Enterprise. These needs represent everything from continuation and enhancement of in situ monitoring products such as USGS water gages and precipitation networks to supporting product maintenance and evolution to accommodate newly developed technologies.

VERIFICATION OF SURFACE LAYER OZONE FORECASTS IN THE NOAA/EPA AIR QUALITY FORECAST SYSTEM IN DIFFERENT REGIONS UNDER DIFFERENT SYNOPTIC SCENARIOS

EPA Science Inventory

An air quality forecast (AQF) system has been established at NOAA/NCEP since 2003 as a collaborative effort of NOAA and EPA. The system is based on NCEP's Eta mesoscale meteorological model and EPA's CMAQ air quality model (Davidson et al, 2004). The vision behind this system is ...

The Primi Project: August-September 2009 Validation Cruise On Oil Spill Detection And Fate

NASA Astrophysics Data System (ADS)

Santoleri, R.; Bignami, F.; Bohm, E.; Nichio, F.; De Dominicis, M.; Ruggieri, G.; Marulllo, S.; Trivero, P.; Zambianchi, E.; Archetti, R.; Adamo, M.; Biamino, W.; Borasi, M.; Buongiorno Nardelli, B.; Cavagnero, M.; Colao, F.; Colella, S.; Coppini, G.; Debettio, V.; De Carolis, G.; Forneris, V.; Griffa, A.; Iacono, R.; Lombardi, E.; Manzella, G.; Mercantini, A.; Napolitano, E.; Pinardi, N.; Pandiscia, G.; Pisano, A.; Rupolo, V.; Reseghetti, F.; Sabia, L.; Sorgente, R.; Sprovieri, M.; Terranova, G.; Trani, M.; Volpe, G.

2010-04-01

In the framework of the ASI PRIMI Project, CNR- ISAC, in collaboration with the PRIMI partners, organized a validation cruise for the PRIMI oil spill monitoring and forecasting system on board the CNR R/V Urania. The cruise (Aug. 6 - Sept. 7 2009) took place in the Sicily Strait, an area affected by large oil tanker traffic. The cruise plan was organized in order to have the ship within the selected SAR image frames at acquisition time so that the ship could move toward the oil slick and verify it via visual and instrumental inspection. During the cruise, several oil spills, presumably being the result of illegal tank washing, were detected by the PRIMI system and were verified in situ. Preliminary results indicate that SAR and optical satellites are able to detect heavy and thin film oil spills, the maturity of oil spill forecasting models and that further work combining satellite, model and in situ data is necessary to assess the spill severity from the signature in satellite imagery.

Study on Battery Capacity for Grid-connection Power Planning with Forecasts in Clustered Photovoltaic Systems

NASA Astrophysics Data System (ADS)

Shimada, Takae; Kawasaki, Norihiro; Ueda, Yuzuru; Sugihara, Hiroyuki; Kurokawa, Kosuke

This paper aims to clarify the battery capacity required by a residential area with densely grid-connected photovoltaic (PV) systems. This paper proposes a planning method of tomorrow's grid-connection power from/to the external electric power system by using demand power forecasting and insolation forecasting for PV power predictions, and defines a operation method of the electricity storage device to control the grid-connection power as planned. A residential area consisting of 389 houses consuming 2390 MWh/year of electricity with 2390kW PV systems is simulated based on measured data and actual forecasts. The simulation results show that 8.3MWh of battery capacity is required in the conditions of half-hour planning and 1% or less of planning error ratio and PV output limiting loss ratio. The results also show that existing technologies of forecasting reduce required battery capacity to 49%, and increase the allowable installing PV amount to 210%.

GRIP Collaboration Portal: Information Management for a Hurricane Field Campaign

NASA Astrophysics Data System (ADS)

Conover, H.; Kulkarni, A.; Garrett, M.; Smith, T.; Goodman, H. M.

2010-12-01

NASA’s Genesis and Rapid Intensification Processes (GRIP) experiment, carried out in August and September of 2010, was a complex operation, involving three aircraft and their crews based at different airports, a dozen instrument teams, mission scientists, weather forecasters, project coordinators and a variety of other participants. In addition, GRIP was coordinated with concurrent airborne missions: NOAA’s IFEX and then NSF-funded PREDICT. The GRIP Collaboration Portal was developed to facilitate communication within and between the different teams and serve as an information repository for the field campaign, providing a single access point for project documents, plans, weather forecasts, flight reports and quicklook data. The portal was developed using the Drupal open source content management framework. This presentation will cover both technology and participation issues. Specific examples include: Drupal’s large and diverse open source developer community is an advantage in that we were able to reuse many modules rather than develop capabilities from scratch, but integrating multiple modules developed by many people adds to the overall complexity of the site. Many of the communication capabilities provided by the site, such as discussion forums and blogs, were not used. Participants were diligent about posting necessary documents, but the favored communication method remained email. Drupal's developer-friendly nature allowed for quick development of the customized functionality needed to accommodate the rapidly changing requirements of GRIP experiment. DC-8 Overflight of Hurricane Earl during GRIP Mission

National Centers for Environmental Prediction

Science.gov Websites

/ VISION | About EMC EMC > NAM > Home NAM Operational Products HIRESW Operational Products Operational Forecast Graphics Experimental Forecast Graphics Verification and Diagnostics Model Configuration Collaborators Documentation and Code FAQ Operational Change Log Parallel Experiment Change Log Contacts

Experiments with Tropical Cyclone Wave and Intensity Forecasts

DTIC Science & Technology

2008-09-30

algorithm In collaboration with Paul Wittmann (Fleet Numerical Metorology and Oceanography Center) and Hendrik Tolman (National Centers for...Wittmann, P.A., C Sampson and H. Tolman: 2006: Wave Analysis Guidance for Tropical Cyclone Forecast Advisories. 9th International Workshop on Wave

Comparative analysis of operational forecasts versus actual weather conditions in airline flight planning, volume 4

NASA Technical Reports Server (NTRS)

Keitz, J. F.

1982-01-01

The impact of more timely and accurate weather data on airline flight planning with the emphasis on fuel savings is studied. This volume of the report discusses the results of Task 4 of the four major tasks included in the study. Task 4 uses flight plan segment wind and temperature differences as indicators of dates and geographic areas for which significant forecast errors may have occurred. An in-depth analysis is then conducted for the days identified. The analysis show that significant errors occur in the operational forecast on 15 of the 33 arbitrarily selected days included in the study. Wind speeds in an area of maximum winds are underestimated by at least 20 to 25 kts. on 14 of these days. The analysis also show that there is a tendency to repeat the same forecast errors from prog to prog. Also, some perceived forecast errors from the flight plan comparisons could not be verified by visual inspection of the corresponding National Meteorological Center forecast and analyses charts, and it is likely that they are the result of weather data interpolation techniques or some other data processing procedure in the airlines' flight planning systems.

Comparative analysis of operational forecasts versus actual weather conditions in airline flight planning, volume 3

NASA Technical Reports Server (NTRS)

Keitz, J. F.

1982-01-01

The impact of more timely and accurate weather data on airline flight planning with the emphasis on fuel savings is studied. This volume of the report discusses the results of Task 3 of the four major tasks included in the study. Task 3 compares flight plans developed on the Suitland forecast with actual data observed by the aircraft (and averaged over 10 degree segments). The results show that the average difference between the forecast and observed wind speed is 9 kts. without considering direction, and the average difference in the component of the forecast wind parallel to the direction of the observed wind is 13 kts. - both indicating that the Suitland forecast underestimates the wind speeds. The Root Mean Square (RMS) vector error is 30.1 kts. The average absolute difference in direction between the forecast and observed wind is 26 degrees and the temperature difference is 3 degree Centigrade. These results indicate that the forecast model as well as the verifying analysis used to develop comparison flight plans in Tasks 1 and 2 is a limiting factor and that the average potential fuel savings or penalty are up to 3.6 percent depending on the direction of flight.

AIR QUALITY FORECAST DATABASE AND ANALYSIS

EPA Science Inventory

In 2003, NOAA and EPA signed a Memorandum of Agreement to collaborate on the design and implementation of a capability to produce daily air quality modeling forecast information for the U.S. NOAA's ETA meteorological model and EPA's Community Multiscale Air Quality (CMAQ) model ...

Short Term Load Forecasting with Fuzzy Logic Systems for power system planning and reliability-A Review

NASA Astrophysics Data System (ADS)

Holmukhe, R. M.; Dhumale, Mrs. Sunita; Chaudhari, Mr. P. S.; Kulkarni, Mr. P. P.

2010-10-01

Load forecasting is very essential to the operation of Electricity companies. It enhances the energy efficient and reliable operation of power system. Forecasting of load demand data forms an important component in planning generation schedules in a power system. The purpose of this paper is to identify issues and better method for load foecasting. In this paper we focus on fuzzy logic system based short term load forecasting. It serves as overview of the state of the art in the intelligent techniques employed for load forecasting in power system planning and reliability. Literature review has been conducted and fuzzy logic method has been summarized to highlight advantages and disadvantages of this technique. The proposed technique for implementing fuzzy logic based forecasting is by Identification of the specific day and by using maximum and minimum temperature for that day and finally listing the maximum temperature and peak load for that day. The results show that Load forecasting where there are considerable changes in temperature parameter is better dealt with Fuzzy Logic system method as compared to other short term forecasting techniques.

42 CFR 417.572 - Budget and enrollment forecast and interim reports.

Code of Federal Regulations, 2010 CFR

2010-10-01

... 42 Public Health 3 2010-10-01 2010-10-01 false Budget and enrollment forecast and interim reports... PLANS, AND HEALTH CARE PREPAYMENT PLANS Medicare Payment: Cost Basis § 417.572 Budget and enrollment forecast and interim reports. (a) Annual submittal. The HMO or CMP must submit an annual operating budget...

Developing Environmental Scanning/Forecasting Systems To Augment Community College Planning.

ERIC Educational Resources Information Center

Morrison, James L.; Held, William G.

A description is provided of a conference session that was conducted to explore the structure and function of an environmental scanning/forecasting system that could be used in a community college to facilitate planning. Introductory comments argue that a college that establishes an environmental scanning and forecasting system is able to identify…

A Performance Evaluation of the National Air Quality Forecast Capability for the Summer of 2007

EPA Science Inventory

This paper provides a performance evaluation of the real-time, CONUS-scale National Air Quality Forecast Capability (NAQFC), developed collaboratively by the National Oceanic and Atmospheric Administration (NOAA) and Environmental Protection Agency (EPA), that supported, in part,...

7 CFR 1710.209 - Approval requirements for load forecast work plans.

Code of Federal Regulations, 2011 CFR

2011-01-01

...) In addition to the approved load forecast required under §§ 1710.202 and 1710.203, any power supply... that are members of a power supply borrower with a total utility plant of $500 million or more must cooperate in the preparation of and submittal of the load forecast work plan of their power supply borrower...

Integrating predictive information into an agro-economic model to guide agricultural planning

NASA Astrophysics Data System (ADS)

Block, Paul; Zhang, Ying; You, Liangzhi

2017-04-01

Seasonal climate forecasts can inform long-range planning, including water resources utilization and allocation, however quantifying the value of this information on the economy is often challenging. For rain-fed farmers, skillful season-ahead predictions may lead to superior planning, as compared to business as usual strategies, resulting in additional benefits or reduced losses. In this study, regional-level probabilistic precipitation forecasts of the major rainy season in Ethiopia are fed into an agro-economic model, adapted from the International Food Policy Research Institute, to evaluate economic outcomes (GDP, poverty rates, etc.) as compared with a no-forecast approach. Based on forecasted conditions, farmers can select various actions: adjusting crop area and crop type, purchasing drought resistant seed, or applying additional fertilizer. Preliminary results favor the forecast-based approach, particularly through crop area reallocation.

7 CFR 1710.205 - Minimum approval requirements for all load forecasts.

Code of Federal Regulations, 2013 CFR

2013-01-01

... electronically to RUS computer software applications. RUS will evaluate borrower load forecasts for readability...'s engineering planning documents, such as the construction work plan, incorporate consumer and usage...

7 CFR 1710.205 - Minimum approval requirements for all load forecasts.

Code of Federal Regulations, 2011 CFR

2011-01-01

... electronically to RUS computer software applications. RUS will evaluate borrower load forecasts for readability...'s engineering planning documents, such as the construction work plan, incorporate consumer and usage...

7 CFR 1710.205 - Minimum approval requirements for all load forecasts.

Code of Federal Regulations, 2012 CFR

2012-01-01

... electronically to RUS computer software applications. RUS will evaluate borrower load forecasts for readability...'s engineering planning documents, such as the construction work plan, incorporate consumer and usage...

Supporting Energy-Related Societal Applications Using NASA's Satellite and Modeling Data

NASA Technical Reports Server (NTRS)

Stackhouse, Paul W., Jr.; Whitlock, C. H.; Chandler, W. S.; Hoell, J. M.; Zhang, T.; Mikovitz, J. C.; Leng, G. S.; Lilienthal, P.

2006-01-01

Improvements to NASA Surface Meteorology and Solar Energy (SSE) web site are now being made through the Prediction of Worldwide Energy Resource (POWER) project under NASA Science Mission Directorate Applied Science Energy Management Program. The purpose of this project is to tailor NASA Science Mission results for energy sector applications and decision support systems. The current status of SSE and research towards upgrading estimates of total, direct and diffuse solar irradiance from NASA satellite measurements and analysis are discussed. Part of this work involves collaborating with partners such as the National Renewable Energy Laboratory (NREL) and the Natural Resources Canada (NRCan). Energy Management and POWER plans including historic, near-term and forecast datasets are also overviewed.

New Activities of the U.S. National Tsunami Hazard Mitigation Program, Mapping and Modeling Subcommittee

NASA Astrophysics Data System (ADS)

Wilson, R. I.; Eble, M. C.

2013-12-01

The U.S. National Tsunami Hazard Mitigation Program (NTHMP) is comprised of representatives from coastal states and federal agencies who, under the guidance of NOAA, work together to develop protocols and products to help communities prepare for and mitigate tsunami hazards. Within the NTHMP are several subcommittees responsible for complimentary aspects of tsunami assessment, mitigation, education, warning, and response. The Mapping and Modeling Subcommittee (MMS) is comprised of state and federal scientists who specialize in tsunami source characterization, numerical tsunami modeling, inundation map production, and warning forecasting. Until September 2012, much of the work of the MMS was authorized through the Tsunami Warning and Education Act, an Act that has since expired but the spirit of which is being adhered to in parallel with reauthorization efforts. Over the past several years, the MMS has developed guidance and best practices for states and territories to produce accurate and consistent tsunami inundation maps for community level evacuation planning, and has conducted benchmarking of numerical inundation models. Recent tsunami events have highlighted the need for other types of tsunami hazard analyses and products for improving evacuation planning, vertical evacuation, maritime planning, land-use planning, building construction, and warning forecasts. As the program responsible for producing accurate and consistent tsunami products nationally, the NTHMP-MMS is initiating a multi-year plan to accomplish the following: 1) Create and build on existing demonstration projects that explore new tsunami hazard analysis techniques and products, such as maps identifying areas of strong currents and potential damage within harbors as well as probabilistic tsunami hazard analysis for land-use planning. 2) Develop benchmarks for validating new numerical modeling techniques related to current velocities and landslide sources. 3) Generate guidance and protocols for the production and use of new tsunami hazard analysis products. 4) Identify multistate collaborations and funding partners interested in these new products. Application of these new products will improve the overall safety and resilience of coastal communities exposed to tsunami hazards.

Validation and Inter-comparison Against Observations of GODAE Ocean View Ocean Prediction Systems

NASA Astrophysics Data System (ADS)

Xu, J.; Davidson, F. J. M.; Smith, G. C.; Lu, Y.; Hernandez, F.; Regnier, C.; Drevillon, M.; Ryan, A.; Martin, M.; Spindler, T. D.; Brassington, G. B.; Oke, P. R.

2016-02-01

For weather forecasts, validation of forecast performance is done at the end user level as well as by the meteorological forecast centers. In the development of Ocean Prediction Capacity, the same level of care for ocean forecast performance and validation is needed. Herein we present results from a validation against observations of 6 Global Ocean Forecast Systems under the GODAE OceanView International Collaboration Network. These systems include the Global Ocean Ice Forecast System (GIOPS) developed by the Government of Canada, two systems PSY3 and PSY4 from the French Mercator-Ocean Ocean Forecasting Group, the FOAM system from UK met office, HYCOM-RTOFS from NOAA/NCEP/NWA of USA, and the Australian Bluelink-OceanMAPS system from the CSIRO, the Australian Meteorological Bureau and the Australian Navy.The observation data used in the comparison are sea surface temperature, sub-surface temperature, sub-surface salinity, sea level anomaly, and sea ice total concentration data. Results of the inter-comparison demonstrate forecast performance limits, strengths and weaknesses of each of the six systems. This work establishes validation protocols and routines by which all new prediction systems developed under the CONCEPTS Collaborative Network will be benchmarked prior to approval for operations. This includes anticipated delivery of CONCEPTS regional prediction systems over the next two years including a pan Canadian 1/12th degree resolution ice ocean prediction system and limited area 1/36th degree resolution prediction systems. The validation approach of comparing forecasts to observations at the time and location of the observation is called Class 4 metrics. It has been adopted by major international ocean prediction centers, and will be recommended to JCOMM-WMO as routine validation approach for operational oceanography worldwide.

Flood Risk Assessment and Forecasting for the Ganges-Brahmaputra-Meghna River Basins

NASA Astrophysics Data System (ADS)

Hopson, T. M.; Priya, S.; Young, W.; Avasthi, A.; Clayton, T. D.; Brakenridge, G. R.; Birkett, C. M.; Riddle, E. E.; Broman, D.; Boehnert, J.; Sampson, K. M.; Kettner, A.; Singh, D.

2017-12-01

During the 2017 South Asia monsoon, torrential rains and catastrophic floods affected more than 45 million people, including 16 million children, across the Ganges-Brahmaputra-Meghna (GBM) basins. The basin is recognized as one of the world's most disaster-prone regions, with severe floods occurring almost annually causing extreme loss of life and property. In light of this vulnerability, the World Bank and collaborators have contributed toward reducing future flood impacts through recent developments to improve operational preparedness for such events, as well as efforts in more general preparedness and resilience building through planning based on detailed risk assessments. With respect to improved event-specific flood preparedness through operational warnings, we discuss a new forecasting system that provides probability-based flood forecasts developed for more than 85 GBM locations. Forecasts are available online, along with near-real-time data maps of rainfall (predicted and actual) and river levels. The new system uses multiple data sets and multiple models to enhance forecasting skill, and provides improved forecasts up to 16 days in advance of the arrival of high waters. These longer lead times provide the opportunity to save both lives and livelihoods. With sufficient advance notice, for example, farmers can harvest a threatened rice crop or move vulnerable livestock to higher ground. Importantly, the forecasts not only predict future water levels but indicate the level of confidence in each forecast. Knowing whether the probability of a danger-level flood is 10 percent or 90 percent helps people to decide what, if any, action to take. With respect to efforts in general preparedness and resilience building, we also present a recent flood risk assessment, and how it provides, for the first time, a numbers-based view of the impacts of different size floods across the Ganges basin. The findings help identify priority areas for tackling flood risks (for example, relocating levees, improving flood warning systems, or boosting overall economic resilience). The assessment includes the locations and numbers of people at risk, as well as the locations and value of buildings, roads and railways, and crops at risk. An accompanying atlas includes easy-to-use risk maps and tables for the Ganges basins.

Socioeconomic Forecasting Model for the Tri-County Regional Planning Commission

DOT National Transportation Integrated Search

1997-01-01

Socioeconomic data is a critical input to transportation planning and travel demand forecasting. Accurate estimates of existing population, incomes, employment and other socioeconomic characteristics are necessary for meaningful calibration of a trav...

Averaging business cycles vs. myopia: Do we need a long term vision when developing IRP?

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

McDonald, C.; Gupta, P.C.

1995-05-01

Utility demand forecasting is inherently imprecise due to the number of uncertainties resulting from business cycles, policy making, technology breakthroughs, national and international political upheavals and the limitations of the forecasting tools. This implies that revisions based primarily on recent experience could lead to unstable forecasts. Moreover, new planning tools are required that provide an explicit consideration of uncertainty and lead to flexible and robust planning tools are required that provide an explicit consideration of uncertainty and lead to flexible and robust planning decisions.

Extended-Range Forecasts at Climate Prediction Center: Current Status and Future Plans

NASA Astrophysics Data System (ADS)

Kumar, A.

2016-12-01

Motivated by a user need to provide forecast information on extended-range time-scales (i.e., weeks 2-4), in recent years Climate Prediction Center (CPC) has made considerable efforts towards developing and testing the feasibility for developing the required forecasts. The forecasts targeting this particular time-scale face a unique challenge in that while the forecast skill due to atmospheric initial conditions is small (because of rapid decay in the memory associated with the atmospheric initial conditions), short time averages for which forecasts are made do not benefit from skill associated with anomalous boundary conditions either. Despite these challenges, CPC has embarked on providing an experimental outlook for weeks 3-4 average. The talk will summarize the current status of CPC's current suite of extended-range forecast products, and further, will discuss some future plans.

The Influences of Social Collaboration on Web 2.0 Self-Efficacy for Higher Education

ERIC Educational Resources Information Center

Turky, Mohamed Abdullah

2016-01-01

The present study tries to research the relationship between Social Collaboration Activity and Web 2.0 Self-Efficacy for Higher Education student. It additionally looks to decide how Social Collaboration adds to the forecast of their sense Web 2.0 Self-Efficacy. The study reported in this paper was led to inspect the relationship Social…

A scoping review of nursing workforce planning and forecasting research.

PubMed

Squires, Allison; Jylhä, Virpi; Jun, Jin; Ensio, Anneli; Kinnunen, Juha

2017-11-01

This study will critically evaluate forecasting models and their content in workforce planning policies for nursing professionals and to highlight the strengths and the weaknesses of existing approaches. Although macro-level nursing workforce issues may not be the first thing that many nurse managers consider in daily operations, the current and impending nursing shortage in many countries makes nursing specific models for workforce forecasting important. A scoping review was conducted using a directed and summative content analysis approach to capture supply and demand analytic methods of nurse workforce planning and forecasting. The literature on nurse workforce forecasting studies published in peer-reviewed journals as well as in grey literature was included in the scoping review. Thirty six studies met the inclusion criteria, with the majority coming from the USA. Forecasting methods were biased towards service utilization analyses and were not consistent across studies. Current methods for nurse workforce forecasting are inconsistent and have not accounted sufficiently for socioeconomic and political factors that can influence workforce projections. Additional studies examining past trends are needed to improve future modelling. Accurate nursing workforce forecasting can help nurse managers, administrators and policy makers to understand the supply and demand of the workforce to prepare and maintain an adequate and competent current and future workforce. © 2017 John Wiley & Sons Ltd.

Colorado Lightning Mapping Array Collaborations through the GOES-R Visiting Scientist Program

NASA Technical Reports Server (NTRS)

Stano, Geoffrey T.; Szoke, Edward; Rydell, Nezette; Cox, Robert; Mazur, Rebecca

2014-01-01

For the past two years, the GOES-R Proving Ground has solicited proposals for its Visiting Scientist Program. NASA's Short-term Prediction Research and Transition (SPoRT) Center has used this opportunity to support the GOES-R Proving Ground by expanding SPoRT's total lightning collaborations. In 2012, this expanded the evaluation of SPoRT's pseudo-geostationary lightning mapper product to the Aviation Weather Center and Storm Prediction Center. This year, SPoRT has collaborated with the Colorado Lightning Mapping Array (COLMA) and potential end users. In particular, SPoRT is collaborating with the Cooperative Institute for Research in the Atmosphere (CIRA) and Colorado State University (CSU) to obtain these data in real-time. From there, SPoRT is supporting the transition of these data to the local forecast offices in Boulder, Colorado and Cheyenne, Wyoming as well as to Proving Ground projects (e.g., the Hazardous Weather Testbed's Spring Program and Aviation Weather Center's Summer Experiment). This presentation will focus on the results of this particular Visiting Scientist Program trip. In particular, the COLMA data are being provided to both forecast offices for initial familiarization. Additionally, several forecast issues have been highlighted as important uses for COLMA data in the operational environment. These include the utility of these data for fire weather situations, situational awareness for both severe weather and lightning safety, and formal evaluations to take place in the spring of 2014.

Forecast and capacity planning for Nogales' ports of entry : [summary].

DOT National Transportation Integrated Search

2009-12-01

This document provides the final report of the activities performed under the project : Nogales POEs Traffic Study: Forecast and Capacity Planning for Nogales Ports of Entry : sponsored by the Arizona Department of Transportation (ADOT) under Gran...

Baseline and Target Values for PV Forecasts: Toward Improved Solar Power Forecasting

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

Zhang, Jie; Hodge, Bri-Mathias; Lu, Siyuan

2015-10-05

Accurate solar power forecasting allows utilities to get the most out of the solar resources on their systems. To truly measure the improvements that any new solar forecasting methods can provide, it is important to first develop (or determine) baseline and target solar forecasting at different spatial and temporal scales. This paper aims to develop baseline and target values for solar forecasting metrics. These were informed by close collaboration with utility and independent system operator partners. The baseline values are established based on state-of-the-art numerical weather prediction models and persistence models. The target values are determined based on the reductionmore » in the amount of reserves that must be held to accommodate the uncertainty of solar power output.« less

[Medical human resources planning in Europe: A literature review of the forecasting models].

PubMed

Benahmed, N; Deliège, D; De Wever, A; Pirson, M

2018-02-01

Healthcare is a labor-intensive sector in which half of the expenses are dedicated to human resources. Therefore, policy makers, at national and internal levels, attend to the number of practicing professionals and the skill mix. This paper aims to analyze the European forecasting model for supply and demand of physicians. To describe the forecasting tools used for physician planning in Europe, a grey literature search was done in the OECD, WHO, and European Union libraries. Electronic databases such as Pubmed, Medine, Embase and Econlit were also searched. Quantitative methods for forecasting medical supply rely mainly on stock-and-flow simulations and less often on systemic dynamics. Parameters included in forecasting models exhibit wide variability for data availability and quality. The forecasting of physician needs is limited to healthcare consumption and rarely considers overall needs and service targets. Besides quantitative methods, horizon scanning enables an evaluation of the changes in supply and demand in an uncertain future based on qualitative techniques such as semi-structured interviews, Delphi Panels, or focus groups. Finally, supply and demand forecasting models should be regularly updated. Moreover, post-hoc analyze is also needed but too rarely implemented. Medical human resource planning in Europe is inconsistent. Political implementation of the results of forecasting projections is essential to insure efficient planning. However, crucial elements such as mobility data between Member States are poorly understood, impairing medical supply regulation policies. These policies are commonly limited to training regulations, while horizontal and vertical substitution is less frequently taken into consideration. Copyright © 2017 Elsevier Masson SAS. All rights reserved.

Futures Research and the Strategic Planning Process: Implications for Higher Education. ASHE-ERIC Higher Education Research Report No. 9, 1984.

ERIC Educational Resources Information Center

Morrison, James L.; And Others

The use of futures research to improve a college's ability to deal with changes brought about by social, economic, political, and technological developments is discussed, with attention to new planning strategies and forecasting methods. While traditional long-range planning tracks and forecasts the institution's internal development, strategic…

Operational Space Weather Activities in the US

NASA Astrophysics Data System (ADS)

Berger, Thomas; Singer, Howard; Onsager, Terrance; Viereck, Rodney; Murtagh, William; Rutledge, Robert

2016-07-01

We review the current activities in the civil operational space weather forecasting enterprise of the United States. The NOAA/Space Weather Prediction Center is the nation's official source of space weather watches, warnings, and alerts, working with partners in the Air Force as well as international operational forecast services to provide predictions, data, and products on a large variety of space weather phenomena and impacts. In October 2015, the White House Office of Science and Technology Policy released the National Space Weather Strategy (NSWS) and associated Space Weather Action Plan (SWAP) that define how the nation will better forecast, mitigate, and respond to an extreme space weather event. The SWAP defines actions involving multiple federal agencies and mandates coordination and collaboration with academia, the private sector, and international bodies to, among other things, develop and sustain an operational space weather observing system; develop and deploy new models of space weather impacts to critical infrastructure systems; define new mechanisms for the transition of research models to operations and to ensure that the research community is supported for, and has access to, operational model upgrade paths; and to enhance fundamental understanding of space weather through support of research models and observations. The SWAP will guide significant aspects of space weather operational and research activities for the next decade, with opportunities to revisit the strategy in the coming years through the auspices of the National Science and Technology Council.

Assessment of reservoir system variable forecasts

NASA Astrophysics Data System (ADS)

Kistenmacher, Martin; Georgakakos, Aris P.

2015-05-01

Forecast ensembles are a convenient means to model water resources uncertainties and to inform planning and management processes. For multipurpose reservoir systems, forecast types include (i) forecasts of upcoming inflows and (ii) forecasts of system variables and outputs such as reservoir levels, releases, flood damage risks, hydropower production, water supply withdrawals, water quality conditions, navigation opportunities, and environmental flows, among others. Forecasts of system variables and outputs are conditional on forecasted inflows as well as on specific management policies and can provide useful information for decision-making processes. Unlike inflow forecasts (in ensemble or other forms), which have been the subject of many previous studies, reservoir system variable and output forecasts are not formally assessed in water resources management theory or practice. This article addresses this gap and develops methods to rectify potential reservoir system forecast inconsistencies and improve the quality of management-relevant information provided to stakeholders and managers. The overarching conclusion is that system variable and output forecast consistency is critical for robust reservoir management and needs to be routinely assessed for any management model used to inform planning and management processes. The above are demonstrated through an application from the Sacramento-American-San Joaquin reservoir system in northern California.

Load Forecasting of Central Urban Area Power Grid Based on Saturated Load Density Index

NASA Astrophysics Data System (ADS)

Huping, Yang; Chengyi, Tang; Meng, Yu

2018-03-01

In the current society, coordination between urban power grid development and city development has become more and more prominent. Electricity saturated load forecasting plays an important role in the planning and development of power grids. Electricity saturated load forecasting is a new concept put forward by China in recent years in the field of grid planning. Urban saturation load forecast is different from the traditional load forecasting method for specific years, the time span of it often relatively large, and involves a wide range of aspects. This study takes a county in eastern Jiangxi as an example, this paper chooses a variety of load forecasting methods to carry on the recent load forecasting calculation to central urban area. At the same time, this paper uses load density index method to predict the Longterm load forecasting of electric saturation load of central urban area lasted until 2030. And further study shows the general distribution of the urban saturation load in space.

Automated system for smoke dispersion prediction due to wild fires in Alaska

NASA Astrophysics Data System (ADS)

Kulchitsky, A.; Stuefer, M.; Higbie, L.; Newby, G.

2007-12-01

Community climate models have enabled development of specific environmental forecast systems. The University of Alaska (UAF) smoke group was created to adapt a smoke forecast system to the Alaska region. The US Forest Service (USFS) Missoula Fire Science Lab had developed a smoke forecast system based on the Weather Research and Forecasting (WRF) Model including chemistry (WRF/Chem). Following the successful experience of USFS, which runs their model operationally for the contiguous U.S., we develop a similar system for Alaska in collaboration with scientists from the USFS Missoula Fire Science Lab. Wildfires are a significant source of air pollution in Alaska because the climate and vegetation favor annual summer fires that burn huge areas. Extreme cases occurred in 2004, when an area larger than Maryland (more than 25000~km2) burned. Small smoke particles with a diameter less than 10~μm can penetrate deep into lungs causing health problems. Smoke also creates a severe restriction to air transport and has tremendous economical effect. The smoke dispersion and forecast system for Alaska was developed at the Geophysical Institute (GI) and the Arctic Region Supercomputing Center (ARSC), both at University of Alaska Fairbanks (UAF). They will help the public and plan activities a few days in advance to avoid dangerous smoke exposure. The availability of modern high performance supercomputers at ARSC allows us to create and run high-resolution, WRF-based smoke dispersion forecast for the entire State of Alaska. The core of the system is a Python program that manages the independent pieces. Our adapted Alaska system performs the following steps \\begin{itemize} Calculate the medium-resolution weather forecast using WRF/Met. Adapt the near real-time satellite-derived wildfire location and extent data that are received via direct broadcast from UAF's "Geographic Information Network of Alaska" (GINA) Calculate fuel moisture using WRF forecasts and National Fire Danger Rating System (NFDRS) fuel maps Calculate smoke emission components using a first order fire emission model Model the smoke plume rise yielding a vertically distribution that accounts for one-dimensional (vertical) concentrations of smoke constituents in the atmosphere above the fire Run WRF/Chem at high resolution for the forecast Use standard graphical tools to provide accessible smoke dispersion The system run twice each day at ARSC. The results will be freely available from a dedicated wildfire smoke web portal at ARSC.

Application of global weather and climate model output to the design and operation of wind-energy systems

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

Curry, Judith

This project addressed the challenge of providing weather and climate information to support the operation, management and planning for wind-energy systems. The need for forecast information is extending to longer projection windows with increasing penetration of wind power into the grid and also with diminishing reserve margins to meet peak loads during significant weather events. Maintenance planning and natural gas trading is being influenced increasingly by anticipation of wind generation on timescales of weeks to months. Future scenarios on decadal time scales are needed to support assessment of wind farm siting, government planning, long-term wind purchase agreements and the regulatorymore » environment. The challenge of making wind forecasts on these longer time scales is associated with a wide range of uncertainties in general circulation and regional climate models that make them unsuitable for direct use in the design and planning of wind-energy systems. To address this challenge, CFAN has developed a hybrid statistical/dynamical forecasting scheme for delivering probabilistic forecasts on time scales from one day to seven months using what is arguably the best forecasting system in the world (European Centre for Medium Range Weather Forecasting, ECMWF). The project also provided a framework to assess future wind power through developing scenarios of interannual to decadal climate variability and change. The Phase II research has successfully developed an operational wind power forecasting system for the U.S., which is being extended to Europe and possibly Asia.« less

Cloud Computing Applications in Support of Earth Science Activities at Marshall Space Flight Center

NASA Astrophysics Data System (ADS)

Molthan, A.; Limaye, A. S.

2011-12-01

Currently, the NASA Nebula Cloud Computing Platform is available to Agency personnel in a pre-release status as the system undergoes a formal operational readiness review. Over the past year, two projects within the Earth Science Office at NASA Marshall Space Flight Center have been investigating the performance and value of Nebula's "Infrastructure as a Service", or "IaaS" concept and applying cloud computing concepts to advance their respective mission goals. The Short-term Prediction Research and Transition (SPoRT) Center focuses on the transition of unique NASA satellite observations and weather forecasting capabilities for use within the operational forecasting community through partnerships with NOAA's National Weather Service (NWS). SPoRT has evaluated the performance of the Weather Research and Forecasting (WRF) model on virtual machines deployed within Nebula and used Nebula instances to simulate local forecasts in support of regional forecast studies of interest to select NWS forecast offices. In addition to weather forecasting applications, rapidly deployable Nebula virtual machines have supported the processing of high resolution NASA satellite imagery to support disaster assessment following the historic severe weather and tornado outbreak of April 27, 2011. Other modeling and satellite analysis activities are underway in support of NASA's SERVIR program, which integrates satellite observations, ground-based data and forecast models to monitor environmental change and improve disaster response in Central America, the Caribbean, Africa, and the Himalayas. Leveraging SPoRT's experience, SERVIR is working to establish a real-time weather forecasting model for Central America. Other modeling efforts include hydrologic forecasts for Kenya, driven by NASA satellite observations and reanalysis data sets provided by the broader meteorological community. Forecast modeling efforts are supplemented by short-term forecasts of convective initiation, determined by geostationary satellite observations processed on virtual machines powered by Nebula. This presentation will provide an overview of these activities from a scientific and cloud computing applications perspective, identifying the strengths and weaknesses for deploying each project within an IaaS environment, and ways to collaborate with the Nebula or other cloud-user communities to collaborate on projects as they go forward.

OAST planning model for space systems technology

NASA Technical Reports Server (NTRS)

Sadin, S. R.

1978-01-01

The NASA Office of Aeronautics and Space Technology (OAST) planning model for space systems technology is described, and some space technology forecasts of a general nature are reported. Technology forecasts are presented as a span of technology levels; uncertainties in level of commitment to project and in required time are taken into account, with emphasis on differences resulting from high or low commitment. Forecasts are created by combining several types of data, including information on past technology trends, the trends of past predictions, the rate of advancement predicted by experts in the field, and technology forecasts already published.

Toward Improved Land Surface Initialization in Support of Regional WRF Forecasts at the Kenya Meteorological Service (KMS)

NASA Technical Reports Server (NTRS)

Case, Jonathan L.; Mungai, John; Sakwa, Vincent; Kabuchanga, Eric; Zavodsky, Bradley T.; Limaye, Ashutosh S.

2014-01-01

SPoRT/SERVIR/RCMRD/KMS Collaboration: Builds off strengths of each organization. SPoRT: Transition of satellite, modeling and verification capabilities; SERVIR-Africa/RCMRD: International capacity-building expertise; KMS: Operational organization with regional weather forecasting expertise in East Africa. Hypothesis: Improved land-surface initialization over Eastern Africa can lead to better temperature, moisture, and ultimately precipitation forecasts in NWP models. KMS currently initializes Weather Research and Forecasting (WRF) model with NCEP/Global Forecast System (GFS) model 0.5-deg initial / boundary condition data. LIS will provide much higher-resolution land-surface data at a scale more representative to regional WRF configuration. Future implementation of real-time NESDIS/VIIRS vegetation fraction to further improve land surface representativeness.

Norway and Cuba Continue Collaborating to Build Capacity to Improve Weather Forecasting

NASA Astrophysics Data System (ADS)

Antuña, Juan Carlos; Kalnay, Eugenia; Mesquita, Michel D. S.

2014-06-01

The Future of Climate Extremes in the Caribbean Extreme Cuban Climate (XCUBE) project, which is funded by the Norwegian Directorate for Civil Protection as part of an assignment for the Norwegian Ministry of Foreign Affairs to support scientific cooperation between Norway and Cuba, carried out a training workshop on seasonal forecasting, reanalysis data, and weather research and forecasting (WRF). The workshop was a follow-up to the XCUBE workshop conducted in Havana in 2013 and provided Cuban scientists with access to expertise on seasonal forecasting, the WRF model developed by the National Center for Atmospheric Research (NCAR) and the community, data assimilation, and reanalysis.

Environmental Information for the U.S. Next Generation Air Transportation System (NextGen)

NASA Astrophysics Data System (ADS)

Murray, J.; Miner, C.; Pace, D.; Minnis, P.; Mecikalski, J.; Feltz, W.; Johnson, D.; Iskendarian, H.; Haynes, J.

2009-09-01

It is estimated that weather is responsible for approximately 70% of all air traffic delays and cancellations in the United States. Annually, this produces an overall economic loss of nearly 40B. The FAA and NASA have determined that weather impacts and other environmental constraints on the U.S. National Airspace System (NAS) will increase to the point of system unsustainability unless the NAS is radically transformed. A Next Generation Air Transportation System (NextGen) is planned to accommodate the anticipated demand for increased system capacity and the super-density operations that this transformation will entail. The heart of the environmental information component that is being developed for NextGen will be a 4-dimensional data cube which will include a single authoritative source comprising probabilistic weather information for NextGen Air Traffic Management (ATM) systems. Aviation weather constraints and safety hazards typically comprise meso-scale, storm-scale and microscale observables that can significantly impact both terminal and enroute aviation operations. With these operational impacts in mind, functional and performance requirements for the NextGen weather system were established which require significant improvements in observation and forecasting capabilities. This will include satellite observations from geostationary and/or polar-orbiting hyperspectral sounders, multi-spectral imagers, lightning mappers, space weather monitors and other environmental observing systems. It will also require improved in situ and remotely sensed observations from ground-based and airborne systems. These observations will be used to better understand and to develop forecasting applications for convective weather, in-flight icing, turbulence, ceilings and visibility, volcanic ash, space weather and the environmental impacts of aviation. Cutting-edge collaborative research efforts and results from NASA, NOAA and the FAA which address these phenomena are summarized. In 2003, a Joint Planning and Development Office (JPDO) was established by public law to meet the significant challenges that NextGen presents. JPDO partners were chartered which include, but are not limited to, the Federal Aviation Administration (FAA), the National Oceanic and Atmospheric Administration (NOAA), the National Aeronautics and Space Administration (NASA), the Department of Defense (DOD) and broad elements of academia and the aviation industry. This paper provides the aviation meteorology community with useful insight on salient NextGen environmental information requirements that have been developed by the JPDO Weather Working Group's Environmental Information Team. These efforts will help to define observation and forecast systems needed to support NextGen and to develop the operational applications for NextGen aviation weather information. Another major goal of this paper is to inform the international weather community of our research progress and plans for NextGen, to foster research collaboration with our colleagues, and to exchange information to maximize success of NextGen, SESAR and related initiatives world-wide.

Ecological forecasts: An emerging imperative

Treesearch

James S. Clark; Steven R. Carpenter; Mary Barber; Scott Collins; Andy Dobson; Jonathan A. Foley; David M. Lodge; Mercedes Pascual; Roger Pielke; William Pizer; Cathy Pringle; Walter V. Reid; Kenneth A. Rose; Osvaldo Sala; William H. Schlesinger; Diana H. Wall; David Wear

2001-01-01

Planning and decision-making can be improved by access to reliable forecasts of ecosystem state, ecosystem services, and natural capital. Availability of new data sets, together with progress in computation and statistics, will increase our ability to forecast ecosystem change. An agenda that would lead toward a capacity to produce, evaluate, and communicate forecasts...

An Integrated Enrollment Forecast Model. IR Applications, Volume 15, January 18, 2008

ERIC Educational Resources Information Center

Chen, Chau-Kuang

2008-01-01

Enrollment forecasting is the central component of effective budget and program planning. The integrated enrollment forecast model is developed to achieve a better understanding of the variables affecting student enrollment and, ultimately, to perform accurate forecasts. The transfer function model of the autoregressive integrated moving average…

Managing Uncertainty: Environmental Analysis/Forecasting in Academic Planning.

ERIC Educational Resources Information Center

Morrison, James L.; Mecca, Thomas V.

An approach to environmental analysis and forecasting that educational policymakers can employ in dealing with the level of uncertainty in strategic decision making is presented. Traditional planning models are weak in identifying environmental changes and assessing their organizational impact. The proposed approach does not lead decision makers…

Evaluating the Impact of AIRS Observations on Regional Forecasts at the SPoRT Center

NASA Technical Reports Server (NTRS)

Zavodsky, Bradley

2011-01-01

NASA Short-term Prediction Research and Transition (SPoRT) Center collaborates with operational partners of different sizes and operational goals to improve forecasts using targeted projects and data sets. Modeling and DA activities focus on demonstrating utility of NASA data sets and capabilities within operational systems. SPoRT has successfully assimilated the Atmospheric Infrared Sounder (AIRS) radiance and profile data. A collaborative project is underway with the Joint Center for Satellite Data Assimilation (JCSDA) to use AIRS profiles to better understand the impact of AIRS radiances assimilated within Gridpoint Statistical Interpolation (GSI) in hopes of engaging the operational DA community in a reassessment of assimilation methodologies to more effectively assimilate hyperspectral radiances.

Seasonal forecasting and health impact models: challenges and opportunities.

PubMed

Ballester, Joan; Lowe, Rachel; Diggle, Peter J; Rodó, Xavier

2016-10-01

After several decades of intensive research, steady improvements in understanding and modeling the climate system have led to the development of the first generation of operational health early warning systems in the era of climate services. These schemes are based on collaborations across scientific disciplines, bringing together real-time climate and health data collection, state-of-the-art seasonal climate predictions, epidemiological impact models based on historical data, and an understanding of end user and stakeholder needs. In this review, we discuss the challenges and opportunities of this complex, multidisciplinary collaboration, with a focus on the factors limiting seasonal forecasting as a source of predictability for climate impact models. © 2016 New York Academy of Sciences.

Tool for Forecasting Cool-Season Peak Winds Across Kennedy Space Center and Cape Canaveral Air Force Station (CCAFS)

NASA Technical Reports Server (NTRS)

Barrett, Joe H., III; Roeder, William P.

2010-01-01

Peak wind speed is important element in 24-Hour and Weekly Planning Forecasts issued by 45th Weather Squadron (45 WS). Forecasts issued for planning operations at KSC/CCAFS. 45 WS wind advisories issued for wind gusts greater than or equal to 25 kt. 35 kt and 50 kt from surface to 300 ft. AMU developed cool-season (Oct - Apr) tool to help 45 WS forecast: daily peak wind speed, 5-minute average speed at time of peak wind, and probability peak speed greater than or equal to 25 kt, 35 kt, 50 kt. AMU tool also forecasts daily average wind speed from 30 ft to 60 ft. Phase I and II tools delivered as a Microsoft Excel graphical user interface (GUI). Phase II tool also delivered as Meteorological Interactive Data Display System (MIDDS) GUI. Phase I and II forecast methods were compared to climatology, 45 WS wind advisories and North American Mesoscale model (MesoNAM) forecasts in a verification data set.

Adaptive spline autoregression threshold method in forecasting Mitsubishi car sales volume at PT Srikandi Diamond Motors

NASA Astrophysics Data System (ADS)

Susanti, D.; Hartini, E.; Permana, A.

2017-01-01

Sale and purchase of the growing competition between companies in Indonesian, make every company should have a proper planning in order to win the competition with other companies. One of the things that can be done to design the plan is to make car sales forecast for the next few periods, it’s required that the amount of inventory of cars that will be sold in proportion to the number of cars needed. While to get the correct forecasting, on of the methods that can be used is the method of Adaptive Spline Threshold Autoregression (ASTAR). Therefore, this time the discussion will focus on the use of Adaptive Spline Threshold Autoregression (ASTAR) method in forecasting the volume of car sales in PT.Srikandi Diamond Motors using time series data.In the discussion of this research, forecasting using the method of forecasting value Adaptive Spline Threshold Autoregression (ASTAR) produce approximately correct.

Sustainable Water Resources for Communities under Climate Change: Can State-of-the-Art Forecasting Inform Decision-Making in Data Sparse Regions?

NASA Astrophysics Data System (ADS)

Mayer, A.; Vivoni, E.; Halvorsen, K.; Robles-Morua, A.; Dana, K.; Che, D.; Mirchi, A.; Kossak, D.; Casteneda, M.

2013-05-01

In this project, we are studying decision-making for water resources management in anticipation of climate change in the Sonora River Basin, Mexico as a case study for the broader arid and semiarid southwestern North America. The goal of the proposed project is to determine whether water resources systems modeling, developed within a participatory framework, can contribute to the building of management strategies in a context of water scarcity, conflicting water uses and highly variable and changing climate conditions. The participatory modeling approach will be conducted through a series of three workshops, designed to encourage substantive participation from a broad range of actors, including representatives from federal and local government agencies, water use sectors, non-governmental organizations, and academics. Participants will guide the design of supply- and demand-side management strategies and selection of climate change and infrastructure management scenarios using state-of-the-art engineering tools. These tools include a water resources systems framework, a spatially-explicit hydrologic model, the use of forecasted climate scenarios under 21st century climate change, and observations obtained from field and satellite sensors. Through the theory of planned behavior, the participatory modeling process will be evaluated to understand if, and to what extent, the engineering tools are useful in the uncertain and politically-complex setting. Pre- and post-workshop surveys will be used in this evaluation. For this contribution, we present the results of the first collaborative modeling workshop that will be held in March 2013, where we will develop the initial modeling framework in collaboration with workshop participants.

Integrated Modelling in CRUCIAL Science Education

NASA Astrophysics Data System (ADS)

Mahura, Alexander; Nuterman, Roman; Mukhamedzhanova, Elena; Nerobelov, Georgiy; Sedeeva, Margarita; Suhodskiy, Alexander; Mostamandy, Suleiman; Smyshlyaev, Sergey

2017-04-01

The NordForsk CRUCIAL project (2016-2017) "Critical steps in understanding land surface - atmosphere interactions: from improved knowledge to socioeconomic solutions" as a part of the Pan-Eurasian EXperiment (PEEX; https://www.atm.helsinki.fi/peex) programme activities, is looking for a deeper collaboration between Nordic-Russian science communities. In particular, following collaboration between Danish and Russian partners, several topics were selected for joint research and are focused on evaluation of: (1) urbanization processes impact on changes in urban weather and climate on urban-subregional-regional scales and at contribution to assessment studies for population and environment; (2) effects of various feedback mechanisms on aerosol and cloud formation and radiative forcing on urban-regional scales for better predicting extreme weather events and at contribution to early warning systems, (3) environmental contamination from continues emissions and industrial accidents for better assessment and decision making for sustainable social and economic development, and (4) climatology of atmospheric boundary layer in northern latitudes to improve understanding of processes, revising parameterizations, and better weather forecasting. These research topics are realized employing the online integrated Enviro-HIRLAM (Environment - High Resolution Limited Area Model) model within students' research projects: (1) "Online integrated high-resolution modelling of Saint-Petersburg metropolitan area influence on weather and air pollution forecasting"; (2) "Modeling of aerosol impact on regional-urban scales: case study of Saint-Petersburg metropolitan area"; (3) "Regional modeling and GIS evaluation of environmental pollution from Kola Peninsula sources"; and (4) "Climatology of the High-Latitude Planetary Boundary Layer". The students' projects achieved results and planned young scientists research training on online integrated modelling (Jun 2017) will be presented and discussed.

Integrating Unified Gravity Wave Physics into the NOAA Next Generation Global Prediction System

NASA Astrophysics Data System (ADS)

Alpert, J. C.; Yudin, V.; Fuller-Rowell, T. J.; Akmaev, R. A.

2017-12-01

The Unified Gravity Wave Physics (UGWP) project for the Next Generation Global Prediction System (NGGPS) is a NOAA collaborative effort between the National Centers for Environmental Prediction (NCEP), Environemntal Modeling Center (EMC) and the University of Colorado, Cooperative Institute for Research in Environmental Sciences (CU-CIRES) to support upgrades and improvements of GW dynamics (resolved scales) and physics (sub-grid scales) in the NOAA Environmental Modeling System (NEMS)†. As envisioned the global climate, weather and space weather models of NEMS will substantially improve their predictions and forecasts with the resolution-sensitive (scale-aware) formulations planned under the UGWP framework for both orographic and non-stationary waves. In particular, the planned improvements for the Global Forecast System (GFS) model of NEMS are: calibration of model physics for higher vertical and horizontal resolution and an extended vertical range of simulations, upgrades to GW schemes, including the turbulent heating and eddy mixing due to wave dissipation and breaking, and representation of the internally-generated QBO. The main priority of the UGWP project is unified parameterization of orographic and non-orographic GW effects including momentum deposition in the middle atmosphere and turbulent heating and eddies due to wave dissipation and breaking. The latter effects are not currently represented in NOAA atmosphere models. The team has tested and evaluated four candidate GW solvers integrating the selected GW schemes into the NGGPS model. Our current work and planned activity is to implement the UGWP schemes in the first available GFS/FV3 (open FV3) configuration including adapted GFDL modification for sub-grid orography in GFS. Initial global model results will be shown for the operational and research GFS configuration for spectral and FV3 dynamical cores. †http://www.emc.ncep.noaa.gov/index.php?branch=NEMS

Toward Global Real Time Hydrologic Modeling - An "Open" View From the Trenches

NASA Astrophysics Data System (ADS)

Nelson, J.

2015-12-01

Big Data has become a popular term to describe the exponential growth of data and related cyber infrastructure to process it so that better analysis can be performed and lead to improved decision-making. How are we doing in the hydrologic sciences? As part of a significant collaborative effort that brought together scientists from public, private, and academic organizations a new transformative hydrologic forecasting modeling infrastructure has been developed. How was it possible to go from deterministic hydrologic forecasts largely driven through manual interactions at 3600 stations to automated 15-day ensemble forecasts at 2.67 million stations? Earth observations of precipitation, temperature, moisture, and other atmospheric and land surface conditions form the foundation of global hydrologic forecasts, but this project demonstrates a critical component to harness these resources can be summed up in one word: OPEN. Whether it is open data sources, open software solutions with open standards, or just being open to collaborations and building teams across institutions, disciplines, and international boundaries, time and time again through my involvement in the development of a high-resolution real time global hydrologic forecasting model I have discovered that in every aspect the sum has always been greater than the parts. While much has been accomplished, much more remains to be done, but the most important lesson learned has been to the degree that we can remain open and work together, the greater our ability will be to use big data hydrologic modeling resources to solve the world's most vexing water related challenges. This presentation will demonstrate a transformational global real time hydrologic forecasting application based on downscaled ECMWF ensemble forecasts, RAPID routing, and Tethys Platform for cloud computing and visualization with discussions of the human and cyber infrastructure connections that make it successful and needs moving forward.

How can monthly to seasonal forecasts help to better manage power systems? (Invited)

NASA Astrophysics Data System (ADS)

Dubus, L.; Troccoli, A.

2013-12-01

The energy industry increasingly depends on weather and climate, at all space and time scales. This is especially true in countries with volunteer renewable energies development policies. There is no doubt that Energy and Meteorology is a burgeoning inter-sectoral discipline. It is also clear that the catalyst for the stronger interaction between these two sectors is the renewed and fervent interest in renewable energies, especially wind and solar power. Recent progress in meteorology has led to a marked increase in the knowledge of the climate system and in the ability to forecast climate on monthly to seasonal time scales. Several studies have already demonstrated the effectiveness of using these forecasts for energy operations, for instance for hydro-power applications. However, it is also obvious that scientific progress on its own is not sufficient to increase the value of weather forecasts. The process of integration of new meteorological products into operational tools and decision making processes is not straightforward but it is at least as important as the scientific discovery. In turn, such integration requires effective communication between users and providers of these products. We will present some important aspects of energy systems in which monthly to seasonal forecasts can bring useful, if not vital, information, and we will give some examples of encouraging energy/meteorology collaborations. We will also provide some suggestions for a strengthened collaboration into the future.

78 FR 37757 - Revisions to the California State Implementation Plan, South Coast Air Quality Management District

Federal Register 2010, 2011, 2012, 2013, 2014

2013-06-24

... the California State Implementation Plan, South Coast Air Quality Management District AGENCY... the South Coast Air Quality Management District (SCAQMD) portion of the California State... Quality Index rather than on 1-hour ozone forecasted values; (b) forecast criteria for allowing a...

76 FR 66346 - Agency Information Collection Activities; Requests for Comments: Clearance of Renewed Approval of...

Federal Register 2010, 2011, 2012, 2013, 2014

2011-10-26

... others for safety assessment, planning, forecasting, cost/benefit analysis, and to target areas for... assessment, planning, forecasting, cost/benefit analysis, and to target areas for research. Respondents... invites public comments about our intention to request the Office of Management and Budget (OMB) approval...

78 FR 75671 - Agency Information Collection Activities: Requests for Comments; Clearance of Renewed Approval of...

Federal Register 2010, 2011, 2012, 2013, 2014

2013-12-12

... others for safety assessment, planning, forecasting, cost/benefit analysis, and to target areas for... assessment, planning, forecasting, cost/benefit analysis, and to target areas for research. Respondents... invites public comments about our intention to request the Office of Management and Budget (OMB) approval...

Demographic Analysis and Planning for the Future. No. 13.

ERIC Educational Resources Information Center

Efird, Cathy M.

The basic sources and types of demographic data available for future planning for the developmentally disabled are reviewed and a frame work for data organization is suggested. It is explained that future forecasts may be undertaken by the following principles: trend forecasting or extrapolation; scenario construction; models, games, and…

Program Tracks Cost Of Travel

NASA Technical Reports Server (NTRS)

Mauldin, Lemuel E., III

1993-01-01

Travel Forecaster is menu-driven, easy-to-use computer program that plans, forecasts cost, and tracks actual vs. planned cost of business-related travel of division or branch of organization and compiles information into data base to aid travel planner. Ability of program to handle multiple trip entries makes it valuable time-saving device.

Establishing an Environmental Scanning/Forecasting System to Augment College and University Planning.

ERIC Educational Resources Information Center

Morrison, James L.

1987-01-01

The major benefit of an environmental scanning/forecasting system is in providing critical information for strategic planning. Such a system allows the institution to detect social, technological, economic, and political trends and potential events. The environmental scanning database developed by United Way of America is described. (MLW)

Socioeconomic and travel demand forecasts for Virginia and potential policy responses : a report for VTrans2035 : Virginia's statewide multimodal transportation plan.

DOT National Transportation Integrated Search

2009-01-01

VTrans2035, Virginia's statewide multimodal transportation plan, requires 25-year forecasts of socioeconomic and travel activity. Between 2010 and 2035, daily vehicle miles traveled (DVMT) will increase between 35% and 45%, accompanied by increases i...

California motor vehicle stock, travel and fuel forecast.

DOT National Transportation Integrated Search

2009-06-01

This is the twenty-fourth in a series of reports that forecasts Vehicle Miles of Travel (VMT) in California. This report is intended for transportation planning, travel forecasting, air quality modeling, and fuel tax revenue projection. : This report...

Demonstrating the Operational Value of Atmospheric Infrared Sounder (AIRS) Retrieved Profiles in the Pre-Convective Environment

NASA Technical Reports Server (NTRS)

Kozlowski, Danielle M.; Zavodsky, T.; Jedloved, Gary J.

2011-01-01

The Short-term Prediction Research and Transition Center (SPoRT) is a collaborative partnership between NASA and operational forecasting partners, including a number of National Weather Service offices. SPoRT provides real-time NASA products and capabilities to its partners to address specific operational forecast challenges. One operational forecast challenge is forecasting convective weather in data-void regions such as large bodies of water (e.g. Gulf of Mexico). To address this forecast challenge, SPoRT produces a twice-daily three-dimensional analysis that blends a model first-guess from the Advanced Research Weather Research and Forecasting (WRF-ARW) model with retrieved profiles from the Atmospheric Infrared Sounder (AIRS) -- a hyperspectral sounding instrument aboard NASA's Aqua satellite that provides temperature and moisture profiles of the atmosphere. AIRS profiles are unique in that they give a three dimensional view of the atmosphere that is not available through the current rawinsonde network. AIRS has two overpass swaths across North America each day, one valid in the 0700-0900 UTC timeframe and the other in the 1900-2100 UTC timeframe. This is helpful because the rawinsonde network only has data from 0000 UTC and 1200 UTC at specific land-based locations. Comparing the AIRS analysis product with control analyses that include no AIRS data demonstrates the value of the retrieved profiles to situational awareness for the pre-convective (and convective) environment. In an attempt to verify that the AIRS analysis was a good representation of the vertical structure of the atmosphere, both the AIRS and control analyses are compared to a Rapid Update Cycle (RUC) analysis used by operational forecasters. Using guidance from operational forecasters, convective available potential energy (CAPE) was determined to be a vital variable in making convective forecasts and is used herein to demonstrate the utility of the AIRS profiles in changing the vertical thermodynamic structure of the atmosphere in the pre-convective and convective environment. CAPE is an important metric because of it is a quantitative measure of atmospheric stability, which is necessary information when forecasting for convective weather. Case studies from the summer of 2010 were examined, and most impact from the AIRS retrieved profiles occurred over the data-void Gulf of Mexico with fields of convective potential closer to the RUC than the CNTL. Mixed results were found when AIRS retrieved profiles were used over land, so more cases need to be examined to determine whether AIRS would be an effective tool over land. Additional analyses of problematic convective forecasts over the Gulf Coast will be needed to determine the operational impact of AIRS. SPoRT eventually plans to transition the AIRS product to select Weather Forecast Office (WFO) partners, pending the outcome of these additional analyses.

The Implementation of NEMS GFS Aerosol Component (NGAC) Version 1.0 for Global Dust Forecasting at NOAA NCEP

NASA Technical Reports Server (NTRS)

Lu, Cheng-Hsuan; Da Silva, Arlindo M.; Wang, Jun; Moorthi, Shrinivas; Chin, Mian; Colarco, Peter; Tang, Youhua; Bhattacharjee, Partha S.; Chen, Shen-Po; Chuang, Hui-Ya;

Demonstrating the Operational Value of Thermodynamic Hyperspectral Profiles in the Pre-Convective Environment

NASA Technical Reports Server (NTRS)

Kozlowski, Danielle; Zavodsky, Bradley T.; Jedlovec, Gary J.

2011-01-01

The Short-term Prediction Research and Transition Center (SPoRT) is a collaborative partnership between NASA and operational forecasting partners, including a number of National Weather Service (NWS) Weather Forecasting Offices (WFO). As a part of the transition to operations process, SPoRT attempts to identify possible limitations in satellite observations and provide operational forecasters a product that will result in the most impact on their forecasts. One operational forecast challenge that some NWS offices face, is forecasting convection in data-void regions such as large bodies of water. The Atmospheric Infrared Sounder (AIRS) is a sounding instrument aboard NASA's Aqua satellite that provides temperature and moisture profiles of the atmosphere. This paper will demonstrate an approach to assimilate AIRS profile data into a regional configuration of the WRF model using its three-dimensional variational (3DVAR) assimilation component to be used as a proxy for the individual profiles.

Comparative analysis of operational forecasts versus actual weather conditions in airline flight planning, volume 1

NASA Technical Reports Server (NTRS)

Keitz, J. F.

1982-01-01

The impact of more timely and accurate weather data on airline flight planning with the emphasis on fuel savings is studied. This volume of the report discusses the results of Task 1 of the four major tasks included in the study. Task 1 compares flight plans based on forecasts with plans based on the verifying analysis from 33 days during the summer and fall of 1979. The comparisons show that: (1) potential fuel savings conservatively estimated to be between 1.2 and 2.5 percent could result from using more timely and accurate weather data in flight planning and route selection; (2) the Suitland forecast generally underestimates wind speeds; and (3) the track selection methodology of many airlines operating on the North Atlantic may not be optimum resulting in their selecting other than the optimum North Atlantic Organized Track about 50 percent of the time.

Development of S-ARIMA Model for Forecasting Demand in a Beverage Supply Chain

NASA Astrophysics Data System (ADS)

Mircetic, Dejan; Nikolicic, Svetlana; Maslaric, Marinko; Ralevic, Nebojsa; Debelic, Borna

2016-11-01

Demand forecasting is one of the key activities in planning the freight flows in supply chains, and accordingly it is essential for planning and scheduling of logistic activities within observed supply chain. Accurate demand forecasting models directly influence the decrease of logistics costs, since they provide an assessment of customer demand. Customer demand is a key component for planning all logistic processes in supply chain, and therefore determining levels of customer demand is of great interest for supply chain managers. In this paper we deal with exactly this kind of problem, and we develop the seasonal Autoregressive IntegratedMoving Average (SARIMA) model for forecasting demand patterns of a major product of an observed beverage company. The model is easy to understand, flexible to use and appropriate for assisting the expert in decision making process about consumer demand in particular periods.

NCAR's Experimental Real-time Convection-allowing Ensemble Prediction System

NASA Astrophysics Data System (ADS)

Schwartz, C. S.; Romine, G. S.; Sobash, R.; Fossell, K.

2016-12-01

Since April 2015, the National Center for Atmospheric Research's (NCAR's) Mesoscale and Microscale Meteorology (MMM) Laboratory, in collaboration with NCAR's Computational Information Systems Laboratory (CISL), has been producing daily, real-time, 10-member, 48-hr ensemble forecasts with 3-km horizontal grid spacing over the conterminous United States (http://ensemble.ucar.edu). These computationally-intensive, next-generation forecasts are produced on the Yellowstone supercomputer, have been embraced by both amateur and professional weather forecasters, are widely used by NCAR and university researchers, and receive considerable attention on social media. Initial conditions are supplied by NCAR's Data Assimilation Research Testbed (DART) software and the forecast model is NCAR's Weather Research and Forecasting (WRF) model; both WRF and DART are community tools. This presentation will focus on cutting-edge research results leveraging the ensemble dataset, including winter weather predictability, severe weather forecasting, and power outage modeling. Additionally, the unique design of the real-time analysis and forecast system and computational challenges and solutions will be described.

Development of a Decision Support System for Monitoring, Reporting, Forecasting Ecological Conditions of the Appalachian Trail

Treesearch

Y. Wang; R. Nemani; F. Dieffenbach; K. Stolte; G. Holcomb

2010-01-01

This paper introduces a collaborative multi-agency effort to develop an Appalachian Trail (A.T.) MEGA-Transect Decision Support System (DSS) for monitoring, reporting and forecasting ecological conditions of the A.T. and the surrounding lands. The project is to improve decision-making on management of the A.T. by providing a coherent framework for data integration,...

Drug Use Forecasting. 1993 Annual Report on Juvenile Arrestees/Detainees: Drugs and Crime in American Cities. Research in Brief.

ERIC Educational Resources Information Center

Department of Justice, Washington, DC. National Inst. of Justice.

This report offers data on juvenile drug use and crime so as to increase understanding of the dimensions of drug use among youthful offenders. The report includes information from collaborative efforts at both the Federal and the local levels. Data on male juvenile arrestees and detainees were collected in 12 Drug Use Forecasting (DUF) sites…

The role of futures forecasts in recreation: some applications in the third nationwide outdoor recreation plan

Treesearch

Meg Maguire; Dana R. Younger

1980-01-01

This paper provides a quick glimpse into the theoretical applicability and importance of futures forecasting techniques in recreation policy planning. The paper also details contemporary socioeconomic trends affecting recreation, current recreation participation patterns and anticipated social changes which will alter public recreation experiences as developed in the...

Development and Implementation of Dynamic Scripts to Support Local Model Verification at National Weather Service Weather Forecast Offices

NASA Technical Reports Server (NTRS)

Zavordsky, Bradley; Case, Jonathan L.; Gotway, John H.; White, Kristopher; Medlin, Jeffrey; Wood, Lance; Radell, Dave

2014-01-01

Local modeling with a customized configuration is conducted at National Weather Service (NWS) Weather Forecast Offices (WFOs) to produce high-resolution numerical forecasts that can better simulate local weather phenomena and complement larger scale global and regional models. The advent of the Environmental Modeling System (EMS), which provides a pre-compiled version of the Weather Research and Forecasting (WRF) model and wrapper Perl scripts, has enabled forecasters to easily configure and execute the WRF model on local workstations. NWS WFOs often use EMS output to help in forecasting highly localized, mesoscale features such as convective initiation, the timing and inland extent of lake effect snow bands, lake and sea breezes, and topographically-modified winds. However, quantitatively evaluating model performance to determine errors and biases still proves to be one of the challenges in running a local model. Developed at the National Center for Atmospheric Research (NCAR), the Model Evaluation Tools (MET) verification software makes performing these types of quantitative analyses easier, but operational forecasters do not generally have time to familiarize themselves with navigating the sometimes complex configurations associated with the MET tools. To assist forecasters in running a subset of MET programs and capabilities, the Short-term Prediction Research and Transition (SPoRT) Center has developed and transitioned a set of dynamic, easily configurable Perl scripts to collaborating NWS WFOs. The objective of these scripts is to provide SPoRT collaborating partners in the NWS with the ability to evaluate the skill of their local EMS model runs in near real time with little prior knowledge of the MET package. The ultimate goal is to make these verification scripts available to the broader NWS community in a future version of the EMS software. This paper provides an overview of the SPoRT MET scripts, instructions for how the scripts are run, and example use cases.

Travel demand forecasting models: a comparison of EMME/2 and QUR II using a real-world network.

DOT National Transportation Integrated Search

2000-10-01

In order to automate the travel demand forecasting process in urban transportation planning, a number of : commercial computer based travel demand forecasting models have been developed, which have provided : transportation planners with powerful and...

Methods and Techniques of Revenue Forecasting.

ERIC Educational Resources Information Center

Caruthers, J. Kent; Wentworth, Cathi L.

1997-01-01

Revenue forecasting is the critical first step in most college and university budget-planning processes. While it seems a straightforward exercise, effective forecasting requires consideration of a number of interacting internal and external variables, including demographic trends, economic conditions, and broad social priorities. The challenge…

Science-Based Strategies for Sustaining Coral Ecosystems

USGS Publications Warehouse

,

2009-01-01

Coral ecosystems and their natural capital are at risk. Greenhouse gas emissions, overfishing, and harmful land-use practices are damaging our coral reefs. Overwhelming scientific evidence indicates that the threats are serious, and if they are left unchecked, the ecological and social consequences will be significant and widespread. Although the primary stressors to coral ecosystems are known, science-based strategies are needed to more accurately explain natural processes and forecast human-induced change. Collaborations among managers and scientists and enhanced mapping, monitoring, research, and modeling can lead to effective mitigation plans. U.S. Geological Survey scientists and their partners assess coral ecosystem history, ecology, vulnerability, and resiliency and provide study results to decisionmakers who may devise policies to sustain coral resources and the essential goods and services they provide.

The Making of National Seasonal Wildfire Outlooks

NASA Astrophysics Data System (ADS)

Garfin, G. M.; Brown, T. J.

2015-12-01

Bridging the gap between research-based experiments and fully operational products has been likened to crossing the valley of death. In this talk, we document the development of pre-season fire potential outlooks, informed by seasonal climate predictions, through a long-term collaboration between NOAA RISA teams, the Program for Climate, Ecosystem and Fire Applications (Desert Research Institute), the National Interagency Fire Center's Predictive Services program and multiple collaborators. To transition experimental outlooks into a sustained, monthly operational product, we co-developed a temporary institution, the National Seasonal Assessment Workshops, as a platform for cross-disciplinary knowledge exchange, training, and experimentation in consensus forecast processes and product development. In our retrospective evaluation of the process, we identified several factors that supported the transition from research to operations. These include: the development of new institutions; focus on a geographic scale commensurate with the needs of federal and state land management agencies; participatory and deliberative engagements; cooperation by many partners with perspectives on the connections between climate and wildland fire management; and iterative engagement sustained by funding and human resource commitments from the key partners. Through co-production of the outlooks and the institution, we created a cross-disciplinary community of practice, thus, increasing the capacity of fire management practitioners to use climate information in decision making. This experiment in developing a collaborative climate service was not an unqualified success. For example, while practitioners almost always *consult* official probabilistic climate forecasts, based on the output from dynamical and statistical models, they sometimes *act* on information from self-constructed forecasts, based on analysis of analogue years. We recommend research to further examine the distribution and use of the outlooks, further dialogue with practitioners, and research to develop forecast evaluation metrics and practices to improve the use of official forecasts. (The figure shows partnerships, information and communication flows for the development of seasonal fire potential outlooks).

The NASA MERIT program - Developing new concepts for accurate flight planning

NASA Technical Reports Server (NTRS)

Steinberg, R.

1982-01-01

It is noted that the rising cost of aviation fuel has necessitated the development of a new approach to upper air forecasting for flight planning. It is shown that the spatial resolution of the present weather forecast models used in fully automated computer flight planning is an important accuracy-limiting factor, and it is proposed that man be put back into the system, although not in the way he has been used in the past. A new approach is proposed which uses the application of man-computer interactive display techniques to upper air forecasting to retain the fine scale features of the atmosphere inherent in the present data base in order to provide a more accurate and cost effective flight plan. It is pointed out that, as a result of NASA research, the hardware required for this approach already exists.

Time-Series Forecast Modeling on High-Bandwidth Network Measurements

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

Yoo, Wucherl; Sim, Alex

With the increasing number of geographically distributed scientific collaborations and the growing sizes of scientific data, it has become challenging for users to achieve the best possible network performance on a shared network. In this paper, we have developed a model to forecast expected bandwidth utilization on high-bandwidth wide area networks. The forecast model can improve the efficiency of the resource utilization and scheduling of data movements on high-bandwidth networks to accommodate ever increasing data volume for large-scale scientific data applications. A univariate time-series forecast model is developed with the Seasonal decomposition of Time series by Loess (STL) and themore » AutoRegressive Integrated Moving Average (ARIMA) on Simple Network Management Protocol (SNMP) path utilization measurement data. Compared with the traditional approach such as Box-Jenkins methodology to train the ARIMA model, our forecast model reduces computation time up to 92.6 %. It also shows resilience against abrupt network usage changes. Finally, our forecast model conducts the large number of multi-step forecast, and the forecast errors are within the mean absolute deviation (MAD) of the monitored measurements.« less

Time-Series Forecast Modeling on High-Bandwidth Network Measurements

DOE PAGES

Yoo, Wucherl; Sim, Alex

2016-06-24

With the increasing number of geographically distributed scientific collaborations and the growing sizes of scientific data, it has become challenging for users to achieve the best possible network performance on a shared network. In this paper, we have developed a model to forecast expected bandwidth utilization on high-bandwidth wide area networks. The forecast model can improve the efficiency of the resource utilization and scheduling of data movements on high-bandwidth networks to accommodate ever increasing data volume for large-scale scientific data applications. A univariate time-series forecast model is developed with the Seasonal decomposition of Time series by Loess (STL) and themore » AutoRegressive Integrated Moving Average (ARIMA) on Simple Network Management Protocol (SNMP) path utilization measurement data. Compared with the traditional approach such as Box-Jenkins methodology to train the ARIMA model, our forecast model reduces computation time up to 92.6 %. It also shows resilience against abrupt network usage changes. Finally, our forecast model conducts the large number of multi-step forecast, and the forecast errors are within the mean absolute deviation (MAD) of the monitored measurements.« less

The NASA Short-Term Prediction Research and Transition (SPoRT) Center: Opportunities for Collaboration in the Great Lakes Region

NASA Technical Reports Server (NTRS)

Molthan, Andrew L.

2010-01-01

The presentation slides include: The SPoRT Center, History and Future of SPoRT, Great Lakes Applications, Great Lakes Forecasting Issues, Applications to the WRF-EMS, Precipitation Science, Lake Effect Precipitation, Sensitivity to Microphysics, Exploring New Schemes, Opportunities for Collaboration, and SPoRT Research and Development.

The implementation of NEMS GFS Aerosol Component (NGAC) Version 1.0 for global dust forecasting at NOAA/NCEP

PubMed Central

Lu, Cheng-Hsuan; da Silva, Arlindo; Wang, Jun; Moorthi, Shrinivas; Chin, Mian; Colarco, Peter; Tang, Youhua; Bhattacharjee, Partha S.; Chen, Shen-Po; Chuang, Hui-Ya; Juang, Hann-Ming Henry; McQueen, Jeffery; Iredell, Mark

2018-01-01

The NOAA National Centers for Environmental Prediction (NCEP) implemented NEMS GFS Aerosol Component (NGAC) for global dust forecasting in collaboration with NASA Goddard Space Flight Center (GSFC). NGAC Version 1.0 has been providing 5 day dust forecasts at 1°×1° resolution on a global scale, once per day at 00:00 Coordinated Universal Time (UTC), since September 2012. This is the first global system capable of interactive atmosphere aerosol forecasting at NCEP. The implementation of NGAC V1.0 reflects an effective and efficient transitioning of NASA research advances to NCEP operations, paving the way for NCEP to provide global aerosol products serving a wide range of stakeholders as well as to allow the effects of aerosols on weather forecasts and climate prediction to be considered. PMID:29652411

The implementation of NEMS GFS Aerosol Component (NGAC) Version 1.0 for global dust forecasting at NOAA/NCEP.

PubMed

Lu, Cheng-Hsuan; da Silva, Arlindo; Wang, Jun; Moorthi, Shrinivas; Chin, Mian; Colarco, Peter; Tang, Youhua; Bhattacharjee, Partha S; Chen, Shen-Po; Chuang, Hui-Ya; Juang, Hann-Ming Henry; McQueen, Jeffery; Iredell, Mark

2016-01-01

The NOAA National Centers for Environmental Prediction (NCEP) implemented NEMS GFS Aerosol Component (NGAC) for global dust forecasting in collaboration with NASA Goddard Space Flight Center (GSFC). NGAC Version 1.0 has been providing 5 day dust forecasts at 1°×1° resolution on a global scale, once per day at 00:00 Coordinated Universal Time (UTC), since September 2012. This is the first global system capable of interactive atmosphere aerosol forecasting at NCEP. The implementation of NGAC V1.0 reflects an effective and efficient transitioning of NASA research advances to NCEP operations, paving the way for NCEP to provide global aerosol products serving a wide range of stakeholders as well as to allow the effects of aerosols on weather forecasts and climate prediction to be considered.

Long-term US energy outlook

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

Friesen, G.

Chase Econometrics summarizes the assumptions underlying long-term US energy forecasts. To illustrate the uncertainty involved in forecasting for the period to the year 2000, they compare Chase Econometrics forecasts with some recent projections prepared by the DOE Office of Policy, Planning and Analysis for the annual National Energy Policy Plan supplement. Scenario B, the mid-range reference case, is emphasized. The purpose of providing Scenario B as well as Scenarios A and C as alternate cases is to show the sensitivity of oil price projections to small swings in energy demand. 4 tables.

Implementation of a Web-Based Collaborative Process Planning System

NASA Astrophysics Data System (ADS)

Wang, Huifen; Liu, Tingting; Qiao, Li; Huang, Shuangxi

Under the networked manufacturing environment, all phases of product manufacturing involving design, process planning, machining and assembling may be accomplished collaboratively by different enterprises, even different manufacturing stages of the same part may be finished collaboratively by different enterprises. Based on the self-developed networked manufacturing platform eCWS(e-Cooperative Work System), a multi-agent-based system framework for collaborative process planning is proposed. In accordance with requirements of collaborative process planning, share resources provided by cooperative enterprises in the course of collaboration are classified into seven classes. Then a reconfigurable and extendable resource object model is built. Decision-making strategy is also studied in this paper. Finally a collaborative process planning system e-CAPP is developed and applied. It provides strong support for distributed designers to collaboratively plan and optimize product process though network.

Collaboration as a process and an outcome: Consumer experiences of collaborating with nurses in care planning in an acute inpatient mental health unit.

PubMed

Reid, Rebecca; Escott, Phil; Isobel, Sophie

2018-04-14

This qualitative study explores inpatient mental health consumer perceptions of how collaborative care planning with mental health nurses impacts personal recovery. Semi-structured interviews were conducted with consumers close to discharge from one unit in Sydney, Australia. The unit had been undertaking a collaborative care planning project which encouraged nurses to use care plan documentation to promote person-centred and goal-focussed interactions and the development of meaningful strategies to aid consumer recovery. The interviews explored consumer understandings of the collaborative care planning process, perceptions of the utility of the care plan document and the process of collaborating with the nurses, and their perception of the impact of collaboration on their recovery. Findings are presented under four organizing themes: the process of collaborating, the purpose of collaborating, the nurse as collaborator and the role of collaboration in wider care and recovery. Consumers highlighted the importance of the process of developing their care plan with a nurse as being as helpful for recovery as the goals and strategies themselves. The findings provide insights into consumers' experiences of care planning in an acute inpatient unit, the components of care that support recovery and highlight specific areas for mental health nursing practice improvement in collaboration. © 2018 Australian College of Mental Health Nurses Inc.

Data Assimilation and Predictability Studies on Typhoon Sinlaku (2008) Using the WRF-LETKF System

NASA Astrophysics Data System (ADS)

Miyoshi, T.; Kunii, M.

2011-12-01

Data assimilation and predictability studies on Tropical Cyclones with a particular focus on intensity forecasts are performed with the newly-developed Local Ensemble Transform Kalman Filter (LETKF) system with the WRF model. Taking advantage of intensive observations of the internationally collaborated T-PARC (THORPEX Pacific Asian Regional Campaign) project, we focus on Typhoon Sinlaku (2008) which intensified rapidly before making landfall to Taiwan. This study includes a number of data assimilation experiments, higher-resolution forecasts, and sensitivity analysis which quantifies impacts of observations on forecasts. This presentation includes latest achievements up to the time of the conference.

Long term load forecasting accuracy in electric utility integrated resource planning

DOE PAGES

Carvallo, Juan Pablo; Larsen, Peter H.; Sanstad, Alan H.; ...

2018-05-23

Forecasts of electricity consumption and peak demand over time horizons of one or two decades are a key element in electric utilities’ meeting their core objective and obligation to ensure reliable and affordable electricity supplies for their customers while complying with a range of energy and environmental regulations and policies. These forecasts are an important input to integrated resource planning (IRP) processes involving utilities, regulators, and other stake-holders. Despite their importance, however, there has been little analysis of long term utility load forecasting accuracy. We conduct a retrospective analysis of long term load forecasts on twelve Western U. S. electricmore » utilities in the mid-2000s to find that most overestimated both energy consumption and peak demand growth. A key reason for this was the use of assumptions that led to an overestimation of economic growth. We find that the complexity of forecast methods and the accuracy of these forecasts are mildly correlated. In addition, sensitivity and risk analysis of load growth and its implications for capacity expansion were not well integrated with subsequent implementation. As a result, we review changes in the utilities load forecasting methods over the subsequent decade, and discuss the policy implications of long term load forecast inaccuracy and its underlying causes.« less

Long term load forecasting accuracy in electric utility integrated resource planning

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

Carvallo, Juan Pablo; Larsen, Peter H.; Sanstad, Alan H.

Forecasts of electricity consumption and peak demand over time horizons of one or two decades are a key element in electric utilities’ meeting their core objective and obligation to ensure reliable and affordable electricity supplies for their customers while complying with a range of energy and environmental regulations and policies. These forecasts are an important input to integrated resource planning (IRP) processes involving utilities, regulators, and other stake-holders. Despite their importance, however, there has been little analysis of long term utility load forecasting accuracy. We conduct a retrospective analysis of long term load forecasts on twelve Western U. S. electricmore » utilities in the mid-2000s to find that most overestimated both energy consumption and peak demand growth. A key reason for this was the use of assumptions that led to an overestimation of economic growth. We find that the complexity of forecast methods and the accuracy of these forecasts are mildly correlated. In addition, sensitivity and risk analysis of load growth and its implications for capacity expansion were not well integrated with subsequent implementation. As a result, we review changes in the utilities load forecasting methods over the subsequent decade, and discuss the policy implications of long term load forecast inaccuracy and its underlying causes.« less

Space Weather Modeling Services at the Community Coordinated Modeling Center

NASA Technical Reports Server (NTRS)

Hesse, Michael

2006-01-01

The Community Coordinated Modeling Center (CCMC) is a multi-agency partnership, which aims at the creation of next generation space weather models. The goal of the CCMC is to support the research and developmental work necessary to substantially increase the present-day modeling capability for space weather purposes, and to provide models for transition to the Rapid Prototyping Centers at the space weather forecast centers. This goal requires close collaborations with and substantial involvement of the research community. The physical regions to be addressed by CCMC-related activities range from the solar atmosphere to the Earth's upper atmosphere. The CCMC is an integral part of the National Space Weather Program Implementation Plan, of NASA's Living With a Star (LWS) initiative, and of the Department of Defense Space Weather Transition Plan. CCMC includes a facility at NASA Goddard Space Flight Center. CCMC also provides, to the research community, access to state-of-the-art space research models. In this paper we will provide a description of the current CCMC status, discuss current plans, research and development accomplishments and goals, and describe the model testing and validation process undertaken as part of the CCMC mandate. Special emphasis will be on solar and heliospheric models currently residing at CCMC, and on plans for validation and verification.

Space Weather Modeling at the Community Coordinated Modeling Center

NASA Technical Reports Server (NTRS)

Hesse M.

2005-01-01

The Community Coordinated Modeling Center (CCMC) is a multi-agency partnership, which aims at the creation of next generation space weather models. The goal of the CCMC is to support the research and developmental work necessary to substantially increase the present-day modeling capability for space weather purposes, and to provide models for transition to the rapid prototyping centers at the space weather forecast centers. This goal requires dose collaborations with and substantial involvement of the research community. The physical regions to be addressed by CCMC-related activities range from the solar atmosphere to the Earth's upper atmosphere. The CCMC is an integral part of the National Space Weather Program Implementation Plan, of NASA's Living With a Star (LWS) initiative, and of the Department of Defense Space Weather Transition Plan. CCMC includes a facility at NASA Goddard Space Flight Center, as well as distributed computing facilities provided by the US Air Force. CCMC also provides, to the research community, access to state-of-the-art space research models. In this paper we will provide updates on CCMC status, on current plans, research and development accomplishments and goals, and on the model testing and validation process undertaken as part of the CCMC mandate. Special emphasis will be on solar and heliospheric models currently residing at CCMC, and on plans for validation and verification.

Albuquerque Public Schools Student Enrollment: History & Forecast 1954-1994. 1975 APS Planning Document 1.

ERIC Educational Resources Information Center

Albuquerque Public Schools, NM.

The material in this report was developed primarily as a basis for better planning and allocation of limited resources in a district experiencing a declining enrollment for the foreseeable future. The charts were developed on the basis of historical enrollment information by grade level, and forecasts were based on a standard regression formula…

Space Weather Model Testing And Validation At The Community Coordinated Modeling Center

NASA Astrophysics Data System (ADS)

Hesse, M.; Kuznetsova, M.; Rastaetter, L.; Falasca, A.; Keller, K.; Reitan, P.

The Community Coordinated Modeling Center (CCMC) is a multi-agency partner- ship aimed at the creation of next generation space weather models. The goal of the CCMC is to undertake the research and developmental work necessary to substantially increase the present-day modeling capability for space weather purposes, and to pro- vide models for transition to the rapid prototyping centers at the space weather forecast centers. This goal requires close collaborations with and substantial involvement of the research community. The physical regions to be addressed by CCMC-related activities range from the solar atmosphere to the Earth's upper atmosphere. The CCMC is an integral part of NASA's Living With aStar initiative, of the National Space Weather Program Implementation Plan, and of the Department of Defense Space Weather Tran- sition Plan. CCMC includes a facility at NASA Goddard Space Flight Center, as well as distributed computing facilities provided by the Air Force. CCMC also provides, to the research community, access to state-of-the-art space research models. In this paper we will provide updates on CCMC status, on current plans, research and devel- opment accomplishments and goals, and on the model testing and validation process undertaken as part of the CCMC mandate.

Urban air quality forecasting based on multi-dimensional collaborative Support Vector Regression (SVR): A case study of Beijing-Tianjin-Shijiazhuang

PubMed Central

Liu, Bing-Chun; Binaykia, Arihant; Chang, Pei-Chann; Tiwari, Manoj Kumar; Tsao, Cheng-Chin

2017-01-01

Today, China is facing a very serious issue of Air Pollution due to its dreadful impact on the human health as well as the environment. The urban cities in China are the most affected due to their rapid industrial and economic growth. Therefore, it is of extreme importance to come up with new, better and more reliable forecasting models to accurately predict the air quality. This paper selected Beijing, Tianjin and Shijiazhuang as three cities from the Jingjinji Region for the study to come up with a new model of collaborative forecasting using Support Vector Regression (SVR) for Urban Air Quality Index (AQI) prediction in China. The present study is aimed to improve the forecasting results by minimizing the prediction error of present machine learning algorithms by taking into account multiple city multi-dimensional air quality information and weather conditions as input. The results show that there is a decrease in MAPE in case of multiple city multi-dimensional regression when there is a strong interaction and correlation of the air quality characteristic attributes with AQI. Also, the geographical location is found to play a significant role in Beijing, Tianjin and Shijiazhuang AQI prediction. PMID:28708836

Comparative analysis of operational forecasts versus actual weather conditions in airline flight planning: Summary report

NASA Technical Reports Server (NTRS)

Keitz, J. F.

1982-01-01

The impact of more timely and accurate weather data on airline flight planning with the emphasis on fuel savings is studied. This summary report discusses the results of each of the four major tasks of the study. Task 1 compared airline flight plans based on operational forecasts to plans based on the verifying analyses and found that average fuel savings of 1.2 to 2.5 percent are possible with improved forecasts. Task 2 consisted of similar comparisons but used a model developed for the FAA by SRI International that simulated the impact of ATc diversions on the flight plans. While parts of Task 2 confirm the Task I findings, inconsistency with other data and the known impact of ATC suggests that other Task 2 findings are the result of errors in the model. Task 3 compares segment weather data from operational flight plans with the weather actually observed by the aircraft and finds the average error could result in fuel burn penalties (or savings) of up to 3.6 percent for the average 8747 flight. In Task 4 an in-depth analysis of the weather forecast for the 33 days included in the study finds that significant errors exist on 15 days. Wind speeds in the area of maximum winds are underestimated by 20 to 50 kts., a finding confirmed in the other three tasks.

Aviation Forecasting in ICAO

NASA Technical Reports Server (NTRS)

Mcmahon, J.

1972-01-01

Opinions or plans of qualified experts in the field are used for forecasting future requirements for air navigational facilities and services of international civil aviation. ICAO periodically collects information from Stators and operates on anticipated future operations, consolidates this information, and forecasts the future level of activity at different airports.

46 CFR 45.191 - Pre-departure requirements.

Code of Federal Regulations, 2012 CFR

2012-10-01

..., verification of mooring/docking space availability, and weather forecast checks were performed, and record the... voyage, the towing vessel master must conduct the following: (a) Weather forecast. Determine the marine weather forecast along the planned route, and contact the dock operator at the destination port to get an...

46 CFR 45.191 - Pre-departure requirements.

Code of Federal Regulations, 2014 CFR

2014-10-01

..., verification of mooring/docking space availability, and weather forecast checks were performed, and record the... voyage, the towing vessel master must conduct the following: (a) Weather forecast. Determine the marine weather forecast along the planned route, and contact the dock operator at the destination port to get an...

46 CFR 45.191 - Pre-departure requirements.

Code of Federal Regulations, 2013 CFR

2013-10-01

..., verification of mooring/docking space availability, and weather forecast checks were performed, and record the... voyage, the towing vessel master must conduct the following: (a) Weather forecast. Determine the marine weather forecast along the planned route, and contact the dock operator at the destination port to get an...

46 CFR 45.191 - Pre-departure requirements.

Code of Federal Regulations, 2011 CFR

2011-10-01

..., verification of mooring/docking space availability, and weather forecast checks were performed, and record the... voyage, the towing vessel master must conduct the following: (a) Weather forecast. Determine the marine weather forecast along the planned route, and contact the dock operator at the destination port to get an...

Forecasting residential electricity demand in provincial China.

PubMed

Liao, Hua; Liu, Yanan; Gao, Yixuan; Hao, Yu; Ma, Xiao-Wei; Wang, Kan

2017-03-01

In China, more than 80% electricity comes from coal which dominates the CO2 emissions. Residential electricity demand forecasting plays a significant role in electricity infrastructure planning and energy policy designing, but it is challenging to make an accurate forecast for developing countries. This paper forecasts the provincial residential electricity consumption of China in the 13th Five-Year-Plan (2016-2020) period using panel data. To overcome the limitations of widely used predication models with unreliably prior knowledge on function forms, a robust piecewise linear model in reduced form is utilized to capture the non-deterministic relationship between income and residential electricity consumption. The forecast results suggest that the growth rates of developed provinces will slow down, while the less developed will be still in fast growing. The national residential electricity demand will increase at 6.6% annually during 2016-2020, and populous provinces such as Guangdong will be the main contributors to the increments.

Forecasts of county-level land uses under three future scenarios: a technical document supporting the Forest Service 2010 RPA Assessment

Treesearch

David N. Wear

2011-01-01

Accurately forecasting future forest conditions and the implications for ecosystem services depends on understanding land use dynamics. In support of the 2010 Renewable Resources Planning Act (RPA) Assessment, we forecast changes in land uses for the coterminous United States in response to three scenarios. Our land use models forecast urbanization in response to the...

Short-term forecasting of emergency inpatient flow.

PubMed

Abraham, Gad; Byrnes, Graham B; Bain, Christopher A

2009-05-01

Hospital managers have to manage resources effectively, while maintaining a high quality of care. For hospitals where admissions from the emergency department to the wards represent a large proportion of admissions, the ability to forecast these admissions and the resultant ward occupancy is especially useful for resource planning purposes. Since emergency admissions often compete with planned elective admissions, modeling emergency demand may result in improved elective planning as well. We compare several models for forecasting daily emergency inpatient admissions and occupancy. The models are applied to three years of daily data. By measuring their mean square error in a cross-validation framework, we find that emergency admissions are largely random, and hence, unpredictable, whereas emergency occupancy can be forecasted using a model combining regression and autoregressive integrated moving average (ARIMA) model, or a seasonal ARIMA model, for up to one week ahead. Faced with variable admissions and occupancy, hospitals must prepare a reserve capacity of beds and staff. Our approach allows estimation of the required reserve capacity.

A prospective earthquake forecast experiment for Japan

NASA Astrophysics Data System (ADS)

Yokoi, Sayoko; Nanjo, Kazuyoshi; Tsuruoka, Hiroshi; Hirata, Naoshi

2013-04-01

One major focus of the current Japanese earthquake prediction research program (2009-2013) is to move toward creating testable earthquake forecast models. For this purpose we started an experiment of forecasting earthquake activity in Japan under the framework of the Collaboratory for the Study of Earthquake Predictability (CSEP) through an international collaboration. We established the CSEP Testing Centre, an infrastructure to encourage researchers to develop testable models for Japan, and to conduct verifiable prospective tests of their model performance. On 1 November in 2009, we started the 1st earthquake forecast testing experiment for the Japan area. We use the unified JMA catalogue compiled by the Japan Meteorological Agency as authorized catalogue. The experiment consists of 12 categories, with 4 testing classes with different time spans (1 day, 3 months, 1 year, and 3 years) and 3 testing regions called All Japan, Mainland, and Kanto. A total of 91 models were submitted to CSEP-Japan, and are evaluated with the CSEP official suite of tests about forecast performance. In this presentation, we show the results of the experiment of the 3-month testing class for 5 rounds. HIST-ETAS7pa, MARFS and RI10K models corresponding to the All Japan, Mainland and Kanto regions showed the best score based on the total log-likelihood. It is also clarified that time dependency of model parameters is no effective factor to pass the CSEP consistency tests for the 3-month testing class in all regions. Especially, spatial distribution in the All Japan region was too difficult to pass consistency test due to multiple events at a bin. Number of target events for a round in the Mainland region tended to be smaller than model's expectation during all rounds, which resulted in rejections of consistency test because of overestimation. In the Kanto region, pass ratios of consistency tests in each model showed more than 80%, which was associated with good balanced forecasting of event number and spatial distribution. Due to the multiple rounds of the experiment, we are now understanding the stability of models, robustness of model selection and earthquake predictability in each region beyond stochastic fluctuations of seismicity. We plan to use the results for design of 3 dimensional earthquake forecasting model in Kanto region, which is supported by the special project for reducing vulnerability for urban mega earthquake disasters from Ministy of Education, Culture, Sports and Technology of Japan.

PRESTIGRIS: an operational system for water resources and droughts management on Tuscany, Central Italy

NASA Astrophysics Data System (ADS)

Campo, Lorenzo; Caparrini, Francesca; Castelli, Fabio

2013-04-01

In the last years the problems of water management faced by local administration due to the growing demand of the territory and to the changes in terms of availability became more and more important. Also in view of problems issued by the Climate Change, it is necessary to have the availability of information about the present and the future state of the water resources on the territory, both in terms of stress of the water bodies and of trends in the near-future. In this respect, an adequate management and planning of the water resources can make use of meteorological seasonal forecasts (one-three month) for the assessment of the primary sources of fresh water in a given region. The PRESTIGRIS project (PREvisioni STagionali Idrologiche per la Gestione della Risorsa Idrica e della Siccità - hydrologic seasonal forecasts for water resources and droughts management), implemented at the University of Florence in collaboration with Eumechanos Environmental Engineering and LaMMa (Laboratorio di Monitoraggio e Modellistica ambientale, Laboratory for Environmental Monitoring and Modeling), is aimed to provide hydrological seasonal forecasts on the territory of the Tuscany Region, Central Italy, basing on the seasonal meteorological forecasts available at different Weather Services (NOAA, IRI, etc.). The PRESTIGRIS system is based on a stochastic disaggregation of the monthly seasonal forecasts of minimum and maximum air temperature at the ground and of the total rainfall height. Through an analysis based on Principal Component Analysis (PCA) techniques, the forecasts are disaggregated in daily maps at a spatial resolution (500 m) compatible with a complete hydrological balance simulation, performed on the entire Tuscany region (about 22000 km2) by the distributed hydrological model MOBIDIC (MOdello di BIlancio Distribuito e Continuo), developed at the Department of Civil and Environmental Engineering of the University of Florence. Given a single seasonal forecast, the system performs an ensemble of 50 hydrological simulations. Basing on the results of the simulations, significant quantiles of the main variables of interest (soil saturation, discharge flows in the stream network, evapotranspiration) are mapped on the territory. The results of the simulations for the year 2003, in particular during the severe drought occurred during the summer, are shown as an example of the capabilities of the system.

Forecasting the response of Earth's surface to future climatic and land use changes: A review of methods and research needs

DOE PAGES

Pelletier, Jon D.; Murray, A. Brad; Pierce, Jennifer L.; ...

2015-07-14

In the future, Earth will be warmer, precipitation events will be more extreme, global mean sea level will rise, and many arid and semiarid regions will be drier. Human modifications of landscapes will also occur at an accelerated rate as developed areas increase in size and population density. We now have gridded global forecasts, being continually improved, of the climatic and land use changes (C&LUC) that are likely to occur in the coming decades. However, besides a few exceptions, consensus forecasts do not exist for how these C&LUC will likely impact Earth-surface processes and hazards. In some cases, we havemore » the tools to forecast the geomorphic responses to likely future C&LUC. Fully exploiting these models and utilizing these tools will require close collaboration among Earth-surface scientists and Earth-system modelers. This paper assesses the state-of-the-art tools and data that are being used or could be used to forecast changes in the state of Earth's surface as a result of likely future C&LUC. We also propose strategies for filling key knowledge gaps, emphasizing where additional basic research and/or collaboration across disciplines are necessary. The main body of the paper addresses cross-cutting issues, including the importance of nonlinear/threshold-dominated interactions among topography, vegetation, and sediment transport, as well as the importance of alternate stable states and extreme, rare events for understanding and forecasting Earth-surface response to C&LUC. Five supplements delve into different scales or process zones (global-scale assessments and fluvial, aeolian, glacial/periglacial, and coastal process zones) in detail.« less

Advances in Monitoring, Modelling and Forecasting Volcanic Ash Plumes over the Past 5 Years and the Impact on Preparedness from the London VAAC Perspective

NASA Astrophysics Data System (ADS)

Lee, D. S.; Lisk, I.

2015-12-01

Hosted and run by the Met Office, the London VAAC (Volcanic Ash Advisory Centre) is responsible for issuing advisories on the location and likely dispersion of ash clouds originating from volcanoes in the North East Atlantic, primarily from Iceland. These advisories and additional guidance products are used by the civil aviation community to make decisions on airspace flight management. London VAAC has specialist forecasters who use a combination of volcano source data, satellite-based, ground-based and aircraft observations, weather forecast models and dispersion models. Since the eruption of the Icelandic volcano Eyjafjallajökull in 2010, which resulted in the decision by many northern European countries to impose significant restrictions on the use of their airspace, London VAAC has been active in further developing its volcanic ash monitoring, modelling and forecasting capabilities, collaborating with research organisations, industry, other VAACs, Meteorological Services and the Volcano Observatory in Iceland. It has been necessary to advance operational capabilities to address evolving requirements, including for more quantitative assessments of volcanic ash in the atmosphere. Here we summarise advances in monitoring, modelling and forecasting of volcanic ash plumes over the past 5 years from the London VAAC perspective, and the realization of science into operations. We also highlight the importance of collaborative activities, such as the 'VAAC Best Practice' Workshop, where information is exchanged between all nine VAACs worldwide on the operational practices in monitoring and forecasting volcanic ash, with the aim of working toward a more harmonized service for decision makers in the aviation community. We conclude on an evaluation of how better we are prepared for the next significant ash-rich Icelandic eruption, and the challenges still remaining.

Toward a US National Air Quality Forecast Capability: Current and Planned Capabilities

EPA Science Inventory

As mandated by Congress, NOAA is establishing a US national air quality forecast capability. This capability is being built with EPA, to provide air quality forecast information with enough accuracy and lead-time so that people can take actions to limit harmful effects of poor a...

Frost Monitoring and Forecasting Using MODIS Land Surface Temperature Data and a Numerical Weather Prediction Model Forecasts for Eastern Africa

NASA Technical Reports Server (NTRS)

Kabuchanga, Eric; Flores, Africa; Malaso, Susan; Mungai, John; Sakwa, Vincent; Shaka, Ayub; Limaye, Ashutosh

2014-01-01

Frost is a major challenge across Eastern Africa, severely impacting agricultural farms. Frost damages have wide ranging economic implications on tea and coffee farms, which represent a major economic sector. Early monitoring and forecasting will enable farmers to take preventive actions to minimize the losses. Although clearly important, timely information on when to protect crops from freezing is relatively limited. MODIS Land Surface Temperature (LST) data, derived from NASA's Terra and Aqua satellites, and 72-hr weather forecasts from the Kenya Meteorological Service's operational Weather Research Forecast model are enabling the Regional Center for Mapping of Resources for Development (RCMRD) and the Tea Research Foundation of Kenya to provide timely information to farmers in the region. This presentation will highlight an ongoing collaboration among the Kenya Meteorological Service, RCMRD, and the Tea Research Foundation of Kenya to identify frost events and provide farmers with potential frost forecasts in Eastern Africa.

Impact of AIRS Thermodynamic Profiles on Precipitation Forecasts for Atmospheric River Cases Affecting the Western United States

NASA Technical Reports Server (NTRS)

Zavodsky, Bradley T.; Jedlovec, Gary J.; Blakenship, Clay B.; Wick, Gary A.; Neiman, Paul J.

2013-01-01

This project is a collaborative activity between the NASA Short-term Prediction Research and Transition (SPoRT) Center and the NOAA Hydrometeorology Testbed (HMT) to evaluate a SPoRT Advanced Infrared Sounding Radiometer (AIRS: Aumann et al. 2003) enhanced moisture analysis product. We test the impact of assimilating AIRS temperature and humidity profiles above clouds and in partly cloudy regions, using the three-dimensional variational Gridpoint Statistical Interpolation (GSI) data assimilation (DA) system (Developmental Testbed Center 2012) to produce a new analysis. Forecasts of the Weather Research and Forecasting (WRF) model initialized from the new analysis are compared to control forecasts without the additional AIRS data. We focus on some cases where atmospheric rivers caused heavy precipitation on the US West Coast. We verify the forecasts by comparison with dropsondes and the Cooperative Institute for Research in the Atmosphere (CIRA) Blended Total Precipitable Water product.

Network bandwidth utilization forecast model on high bandwidth networks

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

Yoo, Wuchert; Sim, Alex

With the increasing number of geographically distributed scientific collaborations and the scale of the data size growth, it has become more challenging for users to achieve the best possible network performance on a shared network. We have developed a forecast model to predict expected bandwidth utilization for high-bandwidth wide area network. The forecast model can improve the efficiency of resource utilization and scheduling data movements on high-bandwidth network to accommodate ever increasing data volume for large-scale scientific data applications. Univariate model is developed with STL and ARIMA on SNMP path utilization data. Compared with traditional approach such as Box-Jenkins methodology,more » our forecast model reduces computation time by 83.2%. It also shows resilience against abrupt network usage change. The accuracy of the forecast model is within the standard deviation of the monitored measurements.« less

Network Bandwidth Utilization Forecast Model on High Bandwidth Network

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

Yoo, Wucherl; Sim, Alex

With the increasing number of geographically distributed scientific collaborations and the scale of the data size growth, it has become more challenging for users to achieve the best possible network performance on a shared network. We have developed a forecast model to predict expected bandwidth utilization for high-bandwidth wide area network. The forecast model can improve the efficiency of resource utilization and scheduling data movements on high-bandwidth network to accommodate ever increasing data volume for large-scale scientific data applications. Univariate model is developed with STL and ARIMA on SNMP path utilization data. Compared with traditional approach such as Box-Jenkins methodology,more » our forecast model reduces computation time by 83.2percent. It also shows resilience against abrupt network usage change. The accuracy of the forecast model is within the standard deviation of the monitored measurements.« less

OAST system technology planning

NASA Technical Reports Server (NTRS)

Sadin, S. R.

1978-01-01

The NASA Office of Aeronautics and Space Technology developed a planning model for space technology consisting of a space systems technology model, technology forecasts and technology surveys. The technology model describes candidate space missions through the year 2000 and identifies their technology requirements. The technology surveys and technology forecasts provide, respectively, data on the current status and estimates of the projected status of relevant technologies. These tools are used to further the understanding of the activities and resources required to ensure the timely development of technological capabilities. Technology forecasting in the areas of information systems, spacecraft systems, transportation systems, and power systems are discussed.

Economic analysis for transmission operation and planning

NASA Astrophysics Data System (ADS)

Zhou, Qun

2011-12-01

Restructuring of the electric power industry has caused dramatic changes in the use of transmission system. The increasing congestion conditions as well as the necessity of integrating renewable energy introduce new challenges and uncertainties to transmission operation and planning. Accurate short-term congestion forecasting facilitates market traders in bidding and trading activities. Cost sharing and recovery issue is a major impediment for long-term transmission investment to integrate renewable energy. In this research, a new short-term forecasting algorithm is proposed for predicting congestion, LMPs, and other power system variables based on the concept of system patterns. The advantage of this algorithm relative to standard statistical forecasting methods is that structural aspects underlying power market operations are exploited to reduce the forecasting error. The advantage relative to previously proposed structural forecasting methods is that data requirements are substantially reduced. Forecasting results based on a NYISO case study demonstrate the feasibility and accuracy of the proposed algorithm. Moreover, a negotiation methodology is developed to guide transmission investment for integrating renewable energy. Built on Nash Bargaining theory, the negotiation of investment plans and payment rate can proceed between renewable generation and transmission companies for cost sharing and recovery. The proposed approach is applied to Garver's six bus system. The numerical results demonstrate fairness and efficiency of the approach, and hence can be used as guidelines for renewable energy investors. The results also shed light on policy-making of renewable energy subsidies.

Projecting technology change to improve space technology planning and systems management

NASA Astrophysics Data System (ADS)

Walk, Steven Robert

2011-04-01

Projecting technology performance evolution has been improving over the years. Reliable quantitative forecasting methods have been developed that project the growth, diffusion, and performance of technology in time, including projecting technology substitutions, saturation levels, and performance improvements. These forecasts can be applied at the early stages of space technology planning to better predict available future technology performance, assure the successful selection of technology, and improve technology systems management strategy. Often what is published as a technology forecast is simply scenario planning, usually made by extrapolating current trends into the future, with perhaps some subjective insight added. Typically, the accuracy of such predictions falls rapidly with distance in time. Quantitative technology forecasting (QTF), on the other hand, includes the study of historic data to identify one of or a combination of several recognized universal technology diffusion or substitution patterns. In the same manner that quantitative models of physical phenomena provide excellent predictions of system behavior, so do QTF models provide reliable technological performance trajectories. In practice, a quantitative technology forecast is completed to ascertain with confidence when the projected performance of a technology or system of technologies will occur. Such projections provide reliable time-referenced information when considering cost and performance trade-offs in maintaining, replacing, or migrating a technology, component, or system. This paper introduces various quantitative technology forecasting techniques and illustrates their practical application in space technology and technology systems management.

Transitioning a Chesapeake Bay Ecological Prediction System to Operations

NASA Astrophysics Data System (ADS)

Brown, C.; Green, D. S.; Eco Forecasters

2011-12-01

Ecological prediction of the impacts of physical, chemical, biological, and human-induced change on ecosystems and their components, encompass a wide range of space and time scales, and subject matter. They vary from predicting the occurrence and/or transport of certain species, such harmful algal blooms, or biogeochemical constituents, such as dissolved oxygen concentrations, to large-scale ecosystem responses and higher trophic levels. The timescales of ecological prediction, including guidance and forecasts, range from nowcasts and short-term forecasts (days), to intraseasonal and interannual outlooks (weeks to months), to decadal and century projections in climate change scenarios. The spatial scales range from small coastal inlets to basin and global scale biogeochemical and ecological forecasts. The types of models that have been used include conceptual, empirical, mechanistic, and hybrid approaches. This presentation will identify the challenges and progress toward transitioning experimental model-based ecological prediction into operational guidance and forecasting. Recent efforts are targeting integration of regional ocean, hydrodynamic and hydrological models and leveraging weather and water service infrastructure to enable the prototyping of an operational ecological forecast capability for the Chesapeake Bay and its tidal tributaries. A path finder demonstration predicts the probability of encountering sea nettles (Chrysaora quinquecirrha), a stinging jellyfish. These jellyfish can negatively impact safety and economic activities in the bay and an impact-based forecast that predicts where and when this biotic nuisance occurs may help management effects. The issuance of bay-wide nowcasts and three-day forecasts of sea nettle probability are generated daily by forcing an empirical habitat model (that predicts the probability of sea nettles) with real-time and 3-day forecasts of sea-surface temperature (SST) and salinity (SSS). In the first demonstration phase, the sea surface temperature (SST) and sea surface salinity (SSS) fields are generated by the Chesapeake Bay Operational Forecast System (CBOFS2), a 3-dimensional hydrodynamic model developed and operated by NOAA's National Ocean Service and run operationally at the National Weather Service National Centers for Environmental Prediction (NCEP). Importantly, this system is readily modified to predict the probability of other important target organisms, such as harmful algal blooms, biogeochemical constituents, such as dissolved oxygen concentration, and water-borne pathogens. Extending this initial effort includes advancement of a regional coastal ocean modeling testbed and proving ground. Such formal collaboration is intended to accelerate transition to operations and increase confidence and use of forecast guidance. The outcome will be improved decision making by emergency and resource managers, scientific researchers and the general public. The presentation will describe partnership plans for this testbed as well as the potential implications for the services and research community.

Forecasted masses for 7000 Kepler Objects of Interest

NASA Astrophysics Data System (ADS)

Chen, Jingjing; Kipping, David M.

2018-01-01

Recent transit surveys have discovered thousands of planetary candidates with directly measured radii, but only a small fraction have measured masses. Planetary mass is crucial in assessing the feasibility of numerous observational signatures, such as radial velocities (RVs), atmospheres, moons and rings. In the absence of a direct measurement, a data-driven, probabilistic forecast enables observational planning, and so here we compute posterior distributions for the forecasted mass of ∼7000 Kepler Objects of Interest (KOIs). Our forecasts reveal that the predicted RV amplitudes of Neptunian planets are relatively consistent, as a result of transit survey detection bias, hovering around a few m s-1 level. We find that mass forecasts are unlikely to improve through more precise planetary radii, with the error budget presently dominated by the intrinsic model uncertainty. Our forecasts identify a couple of dozen KOIs near the Terran-Neptunian divide with particularly large RV semi-amplitudes, which could be promising targets to follow up, particularly in the near-infrared. With several more transit surveys planned in the near-future, the need to quickly forecast observational signatures is likely to grow, and the work here provides a template example of such calculations.

Objective Lightning Forecasting at Kennedy Space Center and Cape Canaveral Air Force Station using Cloud-to-Ground Lightning Surveillance System Data

NASA Technical Reports Server (NTRS)

Lambert, Winfred; Wheeler, Mark; Roeder, William

2005-01-01

The 45th Weather Squadron (45 WS) at Cape Canaveral Air-Force Station (CCAFS)ln Florida issues a probability of lightning occurrence in their daily 24-hour and weekly planning forecasts. This information is used for general planning of operations at CCAFS and Kennedy Space Center (KSC). These facilities are located in east-central Florida at the east end of a corridor known as 'Lightning Alley', an indication that lightning has a large impact on space-lift operations. Much of the current lightning probability forecast is based on a subjective analysis of model and observational data and an objective forecast tool developed over 30 years ago. The 45 WS requested that a new lightning probability forecast tool based on statistical analysis of more recent historical warm season (May-September) data be developed in order to increase the objectivity of the daily thunderstorm probability forecast. The resulting tool is a set of statistical lightning forecast equations, one for each month of the warm season, that provide a lightning occurrence probability for the day by 1100 UTC (0700 EDT) during the warm season.

Results from the second year of a collaborative effort to forecast influenza seasons in the United States.

PubMed

Biggerstaff, Matthew; Johansson, Michael; Alper, David; Brooks, Logan C; Chakraborty, Prithwish; Farrow, David C; Hyun, Sangwon; Kandula, Sasikiran; McGowan, Craig; Ramakrishnan, Naren; Rosenfeld, Roni; Shaman, Jeffrey; Tibshirani, Rob; Tibshirani, Ryan J; Vespignani, Alessandro; Yang, Wan; Zhang, Qian; Reed, Carrie

2018-02-24

Accurate forecasts could enable more informed public health decisions. Since 2013, CDC has worked with external researchers to improve influenza forecasts by coordinating seasonal challenges for the United States and the 10 Health and Human Service Regions. Forecasted targets for the 2014-15 challenge were the onset week, peak week, and peak intensity of the season and the weekly percent of outpatient visits due to influenza-like illness (ILI) 1-4 weeks in advance. We used a logarithmic scoring rule to score the weekly forecasts, averaged the scores over an evaluation period, and then exponentiated the resulting logarithmic score. Poor forecasts had a score near 0, and perfect forecasts a score of 1. Five teams submitted forecasts from seven different models. At the national level, the team scores for onset week ranged from <0.01 to 0.41, peak week ranged from 0.08 to 0.49, and peak intensity ranged from <0.01 to 0.17. The scores for predictions of ILI 1-4 weeks in advance ranged from 0.02-0.38 and was highest 1 week ahead. Forecast skill varied by HHS region. Forecasts can predict epidemic characteristics that inform public health actions. CDC, state and local health officials, and researchers are working together to improve forecasts. Published by Elsevier B.V.

Linking Science of Flood Forecasts to Humanitarian Actions for Improved Preparedness and Effective Response

NASA Astrophysics Data System (ADS)

Uprety, M.; Dugar, S.; Gautam, D.; Kanel, D.; Kshetri, M.; Kharbuja, R. G.; Acharya, S. H.

2017-12-01

Advances in flood forecasting have provided opportunities for humanitarian responders to employ a range of preparedness activities at different forecast time horizons. Yet, the science of prediction is less understood and realized across the humanitarian landscape, and often preparedness plans are based upon average level of flood risk. Working under the remit of Forecast Based Financing (FbF), we present a pilot from Nepal on how available flood and weather forecast products are informing specific pre-emptive actions in the local preparedness and response plans, thereby supporting government stakeholders and humanitarian agencies to take early actions before an impending flood event. In Nepal, forecasting capabilities are limited but in a state of positive flux. Whilst local flood forecasts based upon rainfall-runoff models are yet to be operationalized, streamflow predictions from Global Flood Awareness System (GLoFAS) can be utilized to plan and implement preparedness activities several days in advance. Likewise, 3-day rainfall forecasts from Nepal Department of Hydrology and Meteorology (DHM) can further inform specific set of early actions for potential flash floods due to heavy precipitation. Existing community based early warning systems in the major river basins of Nepal are utilizing real time monitoring of water levels and rainfall together with localised probabilistic flood forecasts which has increased warning lead time from 2-3 hours to 7-8 hours. Based on these available forecast products, thresholds and trigger levels have been determined for different flood scenarios. Matching these trigger levels and assigning responsibilities to relevant actors for early actions, a set of standard operating procedures (SOPs) are being developed, broadly covering general preparedness activities and science informed anticipatory actions for different forecast lead times followed by the immediate response activities. These SOPs are currently being rolled out and tested by the Ministry of Home Affairs (MoHA) through its district emergency operation centres in West Nepal. Potential scale up and successful implementation of this science based approach would be instrumental to take forward global commitments on disaster risk reduction, climate change adaptation and sustainable goals in Nepal.

7 CFR 1710.206 - Approval requirements for load forecasts prepared pursuant to approved load forecast work plans.

Code of Federal Regulations, 2010 CFR

2010-01-01

... narrative shall address the overall approach, time periods, and expected internal and external uses of the forecast. Examples of internal uses include providing information for developing or monitoring demand side... suppliers. Examples of external uses include meeting state and Federal regulatory requirements, obtaining...

Studies of air traffic forecasts, airspace load and the effect of ADS-B via satellites on flight times

NASA Astrophysics Data System (ADS)

Zhong, Z. W.; Ridhwan Salleh, Saiful; Chow, W. X.; Ong, Z. M.

2016-10-01

Air traffic forecasting is important as it helps stakeholders to plan their budgets and facilities. Thus, three most commonly used forecasting models were compared to see which model suited the air passenger traffic the best. General forecasting equations were also created to forecast the passenger traffic. The equations could forecast around 6.0% growth from 2015 onwards. Another study sought to provide an initial work for determining a theoretical airspace load with relevant calculations. The air traffic was simulated to investigate the current airspace load. Logical and reasonable results were obtained from the modelling and simulations. The current utilization percentages for airspace load per hour and the static airspace load in the interested airspace were found to be 6.64% and 11.21% respectively. Our research also studied how ADS-B would affect the time taken for aircraft to travel. 6000 flights departing from and landing at the airport were studied. New flight plans were simulated with improved flight paths due to the implementation of ADS-B, and flight times of all studied flights could be improved.

Short-term forecasts gain in accuracy. [Regression technique using ''Box-Jenkins'' analysis

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

Not Available

Box-Jenkins time-series models offer accuracy for short-term forecasts that compare with large-scale macroeconomic forecasts. Utilities need to be able to forecast peak demand in order to plan their generating, transmitting, and distribution systems. This new method differs from conventional models by not assuming specific data patterns, but by fitting available data into a tentative pattern on the basis of auto-correlations. Three types of models (autoregressive, moving average, or mixed autoregressive/moving average) can be used according to which provides the most appropriate combination of autocorrelations and related derivatives. Major steps in choosing a model are identifying potential models, estimating the parametersmore » of the problem, and running a diagnostic check to see if the model fits the parameters. The Box-Jenkins technique is well suited for seasonal patterns, which makes it possible to have as short as hourly forecasts of load demand. With accuracy up to two years, the method will allow electricity price-elasticity forecasting that can be applied to facility planning and rate design. (DCK)« less

Generating short-term probabilistic wind power scenarios via nonparametric forecast error density estimators: Generating short-term probabilistic wind power scenarios via nonparametric forecast error density estimators

DOE PAGES

Staid, Andrea; Watson, Jean -Paul; Wets, Roger J. -B.; ...

2017-07-11

Forecasts of available wind power are critical in key electric power systems operations planning problems, including economic dispatch and unit commitment. Such forecasts are necessarily uncertain, limiting the reliability and cost effectiveness of operations planning models based on a single deterministic or “point” forecast. A common approach to address this limitation involves the use of a number of probabilistic scenarios, each specifying a possible trajectory of wind power production, with associated probability. We present and analyze a novel method for generating probabilistic wind power scenarios, leveraging available historical information in the form of forecasted and corresponding observed wind power timemore » series. We estimate non-parametric forecast error densities, specifically using epi-spline basis functions, allowing us to capture the skewed and non-parametric nature of error densities observed in real-world data. We then describe a method to generate probabilistic scenarios from these basis functions that allows users to control for the degree to which extreme errors are captured.We compare the performance of our approach to the current state-of-the-art considering publicly available data associated with the Bonneville Power Administration, analyzing aggregate production of a number of wind farms over a large geographic region. Finally, we discuss the advantages of our approach in the context of specific power systems operations planning problems: stochastic unit commitment and economic dispatch. Here, our methodology is embodied in the joint Sandia – University of California Davis Prescient software package for assessing and analyzing stochastic operations strategies.« less

Generating short-term probabilistic wind power scenarios via nonparametric forecast error density estimators: Generating short-term probabilistic wind power scenarios via nonparametric forecast error density estimators

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

Staid, Andrea; Watson, Jean -Paul; Wets, Roger J. -B.

Forecasts of available wind power are critical in key electric power systems operations planning problems, including economic dispatch and unit commitment. Such forecasts are necessarily uncertain, limiting the reliability and cost effectiveness of operations planning models based on a single deterministic or “point” forecast. A common approach to address this limitation involves the use of a number of probabilistic scenarios, each specifying a possible trajectory of wind power production, with associated probability. We present and analyze a novel method for generating probabilistic wind power scenarios, leveraging available historical information in the form of forecasted and corresponding observed wind power timemore » series. We estimate non-parametric forecast error densities, specifically using epi-spline basis functions, allowing us to capture the skewed and non-parametric nature of error densities observed in real-world data. We then describe a method to generate probabilistic scenarios from these basis functions that allows users to control for the degree to which extreme errors are captured.We compare the performance of our approach to the current state-of-the-art considering publicly available data associated with the Bonneville Power Administration, analyzing aggregate production of a number of wind farms over a large geographic region. Finally, we discuss the advantages of our approach in the context of specific power systems operations planning problems: stochastic unit commitment and economic dispatch. Here, our methodology is embodied in the joint Sandia – University of California Davis Prescient software package for assessing and analyzing stochastic operations strategies.« less

Selection of a Planning Horizon for a Hybrid Microgrid Using Simulated Wind Forecasts

DTIC Science & Technology

2014-12-01

microgrid robustness and efficiency and may provide operators with real-time guidance and control policies for microgrid operation. ACKNOWLEDGMENTS The...A PLANNING HORIZON FOR A HYBRID MICROGRID USING SIMULATED WIND FORECASTS Mumtaz Karatas Turkish Naval Academy Tuzla, Istanbul, 34942, TURKEY Emily M...Craparo Dashi I. Singham Naval Postgraduate School 1411 Cunningham Road Monterey, CA, 93943 USA ABSTRACT Hybrid microgrids containing renewable energy

Stochastic Forcing for Ocean Uncertainty Prediction

DTIC Science & Technology

2013-09-30

using the desired dynamics and the fitting of that velocity field to the bathymetry, coasts and discretization for the desired simulation. New algorithms...numerical bias is removed. Pdfs of the forecast errors are shown to capture and evolve non- Gaussian statistics. Comparing the Kullback - Leibler ...advances in collaborative sea exercises of opportunity vi) Strengthen existing and initiate new collaborations with NRL, using and leveraging the MIT

International Collaboration in the field of GNSS-Meteorology and Climate Monitoring

NASA Astrophysics Data System (ADS)

Jones, J.; Guerova, G.; Dousa, J.; Bock, O.; Elgered, G.; Vedel, H.; Pottiaux, E.; de Haan, S.; Pacione, R.; Dick, G.; Wang, J.; Gutman, S. I.; Wickert, J.; Rannat, K.; Liu, G.; Braun, J. J.; Shoji, Y.

2012-12-01

International collaboration in the field of GNSS-meteorology and climate monitoring is essential, as severe weather and climate change have no respect for national boundaries. The use of Global Navigation Satellite Systems (GNSS) for meteorological purposes is an established atmospheric observing technique, which can accurately sense water vapour, the most abundant greenhouse gas, accounting for 60-70% of atmospheric warming. Severe weather forecasting is challenging, in part due to the high temporal and spatial variation of atmospheric water vapour. Water vapour is currently under-sampled and obtaining and exploiting more high-quality humidity observations is essential to severe weather forecasting and climate monitoring. A proposed EU COST Action (http://www.cost.eu) will address new and improved capabilities from concurrent developments in both GNSS and atmospheric communities to improve (short-range) weather forecasts and climate projections. For the first time, the synergy of the three GNSS systems, GPS, GLONASS and Galileo, will be used to develop new, advanced tropospheric products, stimulating the full potential exploitation of multi-GNSS water vapour estimates on a wide range of temporal and spatial scales, from real-time severe weather monitoring and forecasting to climate research. The Action will work in close collaboration with the Global Climate Observing System (GCOS) Reference Upper Air Network (GRUAN), GNSS Precipitable Water Task Team (TT). GRUAN is a global reference observing network, designed to meet climate requirements and to fill a major void in the current global observing system. GRUAN observations will provide long-term, high-quality data to determine climatic trends and to constrain and validate data from space-based remote sensors. Ground-based GNSS PW was identified as a Priority 1 measurement for GRUAN, and the GNSS-PW TT's goal is to develop explicit guidance on hardware, software and data management practices to obtain GNSS PW measurements of consistent quality at all GRUAN sites. The GRUAN GNSS-PW TT and the proposed COST Action will look to expand the international framework already in place with the European E-GVAP programme to facilitate global collaboration to facilitate knowledge and data exchange.

Strategies to strengthen public health inputs to water policy in response to climate change: an Australian perspective.

PubMed

Goater, Sarah; Cook, Angus; Hogan, Anthony; Mengersen, Kerrie; Hieatt, Arron; Weinstein, Philip

2011-03-01

Under current climate change projections, the capacity to provide safe drinking water to Australian communities will be challenged. Part of this challenge is the lack of an adaptive governance strategy that transcends jurisdictional boundaries to support integrated policy making, regulation, or infrastructural adaptation. Consequently, some water-related health hazards may not be adequately captured or forecast under existing water resource management policies to ensure safe water supplies. Given the high degree of spatial and temporal variability in climate conditions experienced by Australian communities, new strategies for national health planning and prioritization for safe water supplies are warranted. The challenges facing public health in Australia will be to develop flexible and robust governance strategies that strengthen public health input to existing water policy, regulation, and surveillance infrastructure through proactive risk planning, adopting new technologies, and intersectoral collaborations. The proposed approach could assist policy makers avert or minimize risk to communities arising from changes in climate and water provisions both in Australia and in the wider Asia Pacific region.

Baseline and target values for regional and point PV power forecasts: Toward improved solar forecasting

DOE PAGES

Zhang, Jie; Hodge, Bri -Mathias; Lu, Siyuan; ...

2015-11-10

Accurate solar photovoltaic (PV) power forecasting allows utilities to reliably utilize solar resources on their systems. However, to truly measure the improvements that any new solar forecasting methods provide, it is important to develop a methodology for determining baseline and target values for the accuracy of solar forecasting at different spatial and temporal scales. This paper aims at developing a framework to derive baseline and target values for a suite of generally applicable, value-based, and custom-designed solar forecasting metrics. The work was informed by close collaboration with utility and independent system operator partners. The baseline values are established based onmore » state-of-the-art numerical weather prediction models and persistence models in combination with a radiative transfer model. The target values are determined based on the reduction in the amount of reserves that must be held to accommodate the uncertainty of PV power output. The proposed reserve-based methodology is a reasonable and practical approach that can be used to assess the economic benefits gained from improvements in accuracy of solar forecasting. Lastly, the financial baseline and targets can be translated back to forecasting accuracy metrics and requirements, which will guide research on solar forecasting improvements toward the areas that are most beneficial to power systems operations.« less

Short Term Weather Forecasting and Long Term Climate Predictions in Mesoamerica

NASA Astrophysics Data System (ADS)

Hardin, D. M.; Daniel, I.; Mecikalski, J.; Graves, S.

2008-05-01

The SERVIR project utilizes several predictive models to support regional monitoring and decision support in Mesoamerica. Short term forecasts ranging from a few hours to several days produce more than 30 data products that are used daily by decision makers, as well as news organizations in the region. The forecast products can be visualized in both two and three dimensional viewers such as Google Maps and Google Earth. Other viewers developed specifically for the Mesoamerican region by the University of Alabama in Huntsville and the Institute for the Application of Geospatial Technologies in Auburn New York can also be employed. In collaboration with the NASA Short Term Prediction Research and Transition (SpoRT) Center SERVIR utilizes the Weather Research and Forecast (WRF) model to produce short-term (24 hr) regional weather forecasts twice a day. Temperature, precipitation, wind, and other variables are forecast in 10km and 30km grids over the Mesoamerica region. Using the PSU/NCAR Mesoscale Model, known as MM5, SERVIR produces 48 hour- forecasts of soil temperature, two meter surface temperature, three hour accumulated precipitation, winds at different heights, and other variables. These are forecast hourly in 9km grids. Working in collaboration with the Atmospheric Science Department of the University of Alabama in Huntsville produces a suite of short-term (0-6 hour) weather prediction products are generated. These "convective initiation" products predict the onset of thunderstorm rainfall and lightning within a 1-hour timeframe. Models are also employed for long term predictions. The SERVIR project, under USAID funding, has developed comprehensive regional climate change scenarios of Mesoamerica for future years: 2010, 2015, 2025, 2050, and 2099. These scenarios were created using the Pennsylvania State University/National Center for Atmospheric Research (MM5) model and processed on the Oak Ridge National Laboratory Cheetah supercomputer. The goal of these Mesoamerican climate change scenarios is to better understand the regional climate, the major controls, and how it might be expected to change in the future. This presentation will present a summary of the model results and show the application of these data in preparation for and response to recent tropical storms.

Collaborative Strategic Planning: Myth or Reality?

ERIC Educational Resources Information Center

Mbugua, Flora; Rarieya, Jane F. A.

2014-01-01

The concept and practice of strategic planning, while entrenched in educational institutions in the West, is just catching on in Kenya. While literature emphasizes the importance of collaborative strategic planning, it does not indicate the challenges presented by collaboratively engaging in strategic planning. This article reports on findings of…

Space weather activities in Australia

NASA Astrophysics Data System (ADS)

Cole, D.

Space Weather Plan Australia has a draft space weather plan to drive and focus appropriate research into services that meet future industry and social needs. The Plan has three main platforms, space weather monitoring and service delivery, support for priority research, and outreach to the community. The details of monitoring, service, research and outreach activities are summarised. A ground-based network of 14 monitoring stations from Antarctica to Papua New Guinea is operated by IPS, a government agency. These sites monitor ionospheric and geomagnetic characteristics, while two of them also monitor the sun at radio and optical wavelengths. Services provided through the Australian Space Forecast Centre (ASFC) include real-time information on the solar, space, ionospheric and geomagnetic environments. Data are gathered automatically from monitoring sites and integrated with data exchanged internationally to create snapshots of current space weather conditions and forecasts of conditions up to several days ahead. IPS also hosts the WDC for Solar-Terrestrial Science and specialises in ground-based solar, ionospheric, and geomagnetic data sets, although recent in-situ magnetospheric measurements are also included. Space weather activities A research consortium operates the Tasman International Geospace Environment Radar (TIGER), an HF southward pointing auroral radar operating from Hobart (Tasmania). A second cooperative radar (Unwin radar) is being constructed in the South Island of New Zealand. This will intersect with TIGER over the auroral zone and enhance the ability of the radar to image the surge of currents that herald space environment changes entering the Polar Regions. Launched in November 2002, the micro satellite FEDSAT, operated by the Cooperative Research Centre for Satellite Systems, has led to successful space science programs and data streams. FEDSAT is making measurements of the magnetic field over Australia and higher latitudes. It also carries a GPS receiver measuring total electron content data for magnetospheric and ionospheric studies. Understanding cosmic ray phenomena requires observations from a range of locations. The Mawson observatory, comprising low and high energy surface and high energy underground instruments, is the largest and most sophisticated observatory of its type in the Southern Hemisphere, and the only one at polar latitudes. The Australian Antarctic Division operates similar detectors at other sites. Australia has proved to be a successful site for ground-based studies and satellite downlink facilities for international collaborative projects, such as ILWS, which are monitoring Sun-Earth activity and exploring techniques for space weather forecasting.

Weather forecasting with open source software

NASA Astrophysics Data System (ADS)

Rautenhaus, Marc; Dörnbrack, Andreas

2013-04-01

To forecast the weather situation during aircraft-based atmospheric field campaigns, we employ a tool chain of existing and self-developed open source software tools and open standards. Of particular value are the Python programming language with its extension libraries NumPy, SciPy, PyQt4, Matplotlib and the basemap toolkit, the NetCDF standard with the Climate and Forecast (CF) Metadata conventions, and the Open Geospatial Consortium Web Map Service standard. These open source libraries and open standards helped to implement the "Mission Support System", a Web Map Service based tool to support weather forecasting and flight planning during field campaigns. The tool has been implemented in Python and has also been released as open source (Rautenhaus et al., Geosci. Model Dev., 5, 55-71, 2012). In this presentation we discuss the usage of free and open source software for weather forecasting in the context of research flight planning, and highlight how the field campaign work benefits from using open source tools and open standards.

A Capacity Forecast Model for Volatile Data in Maintenance Logistics

NASA Astrophysics Data System (ADS)

Berkholz, Daniel

2009-05-01

Maintenance, repair and overhaul processes (MRO processes) are elaborate and complex. Rising demands on these after sales services require reliable production planning and control methods particularly for maintaining valuable capital goods. Downtimes lead to high costs and an inability to meet delivery due dates results in severe contract penalties. Predicting the required capacities for maintenance orders in advance is often difficult due to unknown part conditions unless the goods are actually inspected. This planning uncertainty results in extensive capital tie-up by rising stock levels within the whole MRO network. The article outlines an approach to planning capacities when maintenance data forecasting is volatile. It focuses on the development of prerequisites for a reliable capacity planning model. This enables a quick response to maintenance orders by employing appropriate measures. The information gained through the model is then systematically applied to forecast both personnel capacities and the demand for spare parts. The improved planning reliability can support MRO service providers in shortening delivery times and reducing stock levels in order to enhance the performance of their maintenance logistics.

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.

Predicting Next Year's Resources--Short-Term Enrollment Forecasting for Accurate Budget Planning. AIR Forum Paper 1978.

ERIC Educational Resources Information Center

Salley, Charles D.

Accurate enrollment forecasts are a prerequisite for reliable budget projections. This is because tuition payments make up a significant portion of a university's revenue, and anticipated revenue is the immediate constraint on current operating expenditures. Accurate forecasts are even more critical to revenue projections when a university's…

Generational forecasting in academic medicine: a unique method of planning for success in the next two decades.

PubMed

Howell, Lydia Pleotis; Joad, Jesse P; Callahan, Edward; Servis, Gregg; Bonham, Ann C

2009-08-01

Multigenerational teams are essential to the missions of academic health centers (AHCs). Generational forecasting using Strauss and Howe's predictive model, "the generational diagonal," can be useful for anticipating and addressing issues so that each generation is effective. Forecasts are based on the observation that cyclical historical events are experienced by all generations, but the response of each generation differs according to its phase of life and previous defining experiences. This article relates Strauss and Howe's generational forecasts to AHCs. Predicted issues such as work-life balance, indebtedness, and succession planning have existed previously, but they now have different causes or consequences because of the unique experiences and life stages of current generations. Efforts to address these issues at the authors' AHC include a work-life balance workgroup, expanded leave, and intramural grants.

Scale and modeling issues in water resources planning

USGS Publications Warehouse

Lins, H.F.; Wolock, D.M.; McCabe, G.J.

1997-01-01

Resource planners and managers interested in utilizing climate model output as part of their operational activities immediately confront the dilemma of scale discordance. Their functional responsibilities cover relatively small geographical areas and necessarily require data of relatively high spatial resolution. Climate models cover a large geographical, i.e. global, domain and produce data at comparatively low spatial resolution. Although the scale differences between model output and planning input are large, several techniques have been developed for disaggregating climate model output to a scale appropriate for use in water resource planning and management applications. With techniques in hand to reduce the limitations imposed by scale discordance, water resource professionals must now confront a more fundamental constraint on the use of climate models-the inability to produce accurate representations and forecasts of regional climate. Given the current capabilities of climate models, and the likelihood that the uncertainty associated with long-term climate model forecasts will remain high for some years to come, the water resources planning community may find it impractical to utilize such forecasts operationally.

Short-Term Forecasting of Loads and Wind Power for Latvian Power System: Accuracy and Capacity of the Developed Tools

NASA Astrophysics Data System (ADS)

Radziukynas, V.; Klementavičius, A.

2016-04-01

The paper analyses the performance results of the recently developed short-term forecasting suit for the Latvian power system. The system load and wind power are forecasted using ANN and ARIMA models, respectively, and the forecasting accuracy is evaluated in terms of errors, mean absolute errors and mean absolute percentage errors. The investigation of influence of additional input variables on load forecasting errors is performed. The interplay of hourly loads and wind power forecasting errors is also evaluated for the Latvian power system with historical loads (the year 2011) and planned wind power capacities (the year 2023).

An Overview of NASA SPoRT GOES-R JPSS Proving Ground Testbed Activities

NASA Technical Reports Server (NTRS)

Berndt, Emily; Stano, Geoffrey; Fuell, Kevin; Leroy, Anita; Mcgrath, Kevin; Molthan, Andrew; Schultz, Lori; Smith, Matthew; White, Kris; Schultz, Christopher;

Approaches in Health Human Resource Forecasting: A Roadmap for Improvement.

PubMed

Rafiei, Sima; Mohebbifar, Rafat; Hashemi, Fariba; Ezzatabadi, Mohammad Ranjbar; Farzianpour, Fereshteh

2016-09-01

Forecasting the demand and supply of health manpower in an accurate manner makes appropriate planning possible. The aim of this paper was to review approaches and methods for health manpower forecasting and consequently propose the features that improve the effectiveness of this important process of health manpower planning. A literature review was conducted for studies published in English from 1990-2014 using Pub Med, Science Direct, Pro Quest, and Google Scholar databases. Review articles, qualitative studies, retrospective and prospective studies describing or applying various types of forecasting approaches and methods in health manpower forecasting were included in the review. The authors designed an extraction data sheet based on study questions to collect data on studies' references, designs, and types of forecasting approaches, whether discussed or applied, with their strengths and weaknesses. Forty studies were included in the review. As a result, two main categories of approaches (conceptual and analytical) for health manpower forecasting were identified. Each approach had several strengths and weaknesses. As a whole, most of them were faced with some challenges, such as being static and unable to capture dynamic variables in manpower forecasting and causal relationships. They also lacked the capacity to benefit from scenario making to assist policy makers in effective decision making. An effective forecasting approach is supposed to resolve all the deficits that exist in current approaches and meet the key features found in the literature in order to develop an open system and a dynamic and comprehensive method necessary for today complex health care systems.

Short-term forecasting of electric loads using nonlinear autoregressive artificial neural networks with exogenous vector inputs

DOE PAGES

Buitrago, Jaime; Asfour, Shihab

2017-01-01

Short-term load forecasting is crucial for the operations planning of an electrical grid. Forecasting the next 24 h of electrical load in a grid allows operators to plan and optimize their resources. The purpose of this study is to develop a more accurate short-term load forecasting method utilizing non-linear autoregressive artificial neural networks (ANN) with exogenous multi-variable input (NARX). The proposed implementation of the network is new: the neural network is trained in open-loop using actual load and weather data, and then, the network is placed in closed-loop to generate a forecast using the predicted load as the feedback input.more » Unlike the existing short-term load forecasting methods using ANNs, the proposed method uses its own output as the input in order to improve the accuracy, thus effectively implementing a feedback loop for the load, making it less dependent on external data. Using the proposed framework, mean absolute percent errors in the forecast in the order of 1% have been achieved, which is a 30% improvement on the average error using feedforward ANNs, ARMAX and state space methods, which can result in large savings by avoiding commissioning of unnecessary power plants. Finally, the New England electrical load data are used to train and validate the forecast prediction.« less

Short-term forecasting of electric loads using nonlinear autoregressive artificial neural networks with exogenous vector inputs

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

Buitrago, Jaime; Asfour, Shihab

Short-term load forecasting is crucial for the operations planning of an electrical grid. Forecasting the next 24 h of electrical load in a grid allows operators to plan and optimize their resources. The purpose of this study is to develop a more accurate short-term load forecasting method utilizing non-linear autoregressive artificial neural networks (ANN) with exogenous multi-variable input (NARX). The proposed implementation of the network is new: the neural network is trained in open-loop using actual load and weather data, and then, the network is placed in closed-loop to generate a forecast using the predicted load as the feedback input.more » Unlike the existing short-term load forecasting methods using ANNs, the proposed method uses its own output as the input in order to improve the accuracy, thus effectively implementing a feedback loop for the load, making it less dependent on external data. Using the proposed framework, mean absolute percent errors in the forecast in the order of 1% have been achieved, which is a 30% improvement on the average error using feedforward ANNs, ARMAX and state space methods, which can result in large savings by avoiding commissioning of unnecessary power plants. Finally, the New England electrical load data are used to train and validate the forecast prediction.« less

Accuracy analysis of TDRSS demand forecasts

NASA Technical Reports Server (NTRS)

Stern, Daniel C.; Levine, Allen J.; Pitt, Karl J.

1994-01-01

This paper reviews Space Network (SN) demand forecasting experience over the past 16 years and describes methods used in the forecasts. The paper focuses on the Single Access (SA) service, the most sought-after resource in the Space Network. Of the ten years of actual demand data available, only the last five years (1989 to 1993) were considered predictive due to the extensive impact of the Challenger accident of 1986. NASA's Space Network provides tracking and communications services to user spacecraft such as the Shuttle and the Hubble Space Telescope. Forecasting the customer requirements is essential to planning network resources and to establishing service commitments to future customers. The lead time to procure Tracking and Data Relay Satellites (TDRS's) requires demand forecasts ten years in the future a planning horizon beyond the funding commitments for missions to be supported. The long range forecasts are shown to have had a bias toward underestimation in the 1991 -1992 period. The trend of underestimation can be expected to be replaced by overestimation for a number of years starting with 1998. At that time demand from new missions slated for launch will be larger than the demand from ongoing missions, making the potential for delay the dominant factor. If the new missions appear as scheduled, the forecasts are likely to be moderately underestimated. The SN commitment to meet the negotiated customer's requirements calls for conservatism in the forecasting. Modification of the forecasting procedure to account for a delay bias is, therefore, not advised. Fine tuning the mission model to more accurately reflect the current actual demand is recommended as it may marginally improve the first year forecasting.

Municipal water consumption forecast accuracy

NASA Astrophysics Data System (ADS)

Fullerton, Thomas M.; Molina, Angel L.

2010-06-01

Municipal water consumption planning is an active area of research because of infrastructure construction and maintenance costs, supply constraints, and water quality assurance. In spite of that, relatively few water forecast accuracy assessments have been completed to date, although some internal documentation may exist as part of the proprietary "grey literature." This study utilizes a data set of previously published municipal consumption forecasts to partially fill that gap in the empirical water economics literature. Previously published municipal water econometric forecasts for three public utilities are examined for predictive accuracy against two random walk benchmarks commonly used in regional analyses. Descriptive metrics used to quantify forecast accuracy include root-mean-square error and Theil inequality statistics. Formal statistical assessments are completed using four-pronged error differential regression F tests. Similar to studies for other metropolitan econometric forecasts in areas with similar demographic and labor market characteristics, model predictive performances for the municipal water aggregates in this effort are mixed for each of the municipalities included in the sample. Given the competitiveness of the benchmarks, analysts should employ care when utilizing econometric forecasts of municipal water consumption for planning purposes, comparing them to recent historical observations and trends to insure reliability. Comparative results using data from other markets, including regions facing differing labor and demographic conditions, would also be helpful.

Integrated Forecast-Decision Systems For River Basin Planning and Management

NASA Astrophysics Data System (ADS)

Georgakakos, A. P.

2005-12-01

A central application of climatology, meteorology, and hydrology is the generation of reliable forecasts for water resources management. In principle, effective use of forecasts could improve water resources management by providing extra protection against floods, mitigating the adverse effects of droughts, generating more hydropower, facilitating recreational activities, and minimizing the impacts of extreme events on the environment and the ecosystems. In practice, however, realization of these benefits depends on three requisite elements. First is the skill and reliability of forecasts. Second is the existence of decision support methods/systems with the ability to properly utilize forecast information. And third is the capacity of the institutional infrastructure to incorporate the information provided by the decision support systems into the decision making processes. This presentation discusses several decision support systems (DSS) using ensemble forecasting that have been developed by the Georgia Water Resources Institute for river basin management. These DSS are currently operational in Africa, Europe, and the US and address integrated water resources and energy planning and management in river basins with multiple water uses, multiple relevant temporal and spatial scales, and multiple decision makers. The article discusses the methods used and advocates that the design, development, and implementation of effective forecast-decision support systems must bring together disciplines, people, and institutions necessary to address today's complex water resources challenges.

A hybrid spatiotemporal drought forecasting model for operational use

NASA Astrophysics Data System (ADS)

Vasiliades, L.; Loukas, A.

2010-09-01

Drought forecasting plays an important role in the planning and management of natural resources and water resource systems in a river basin. Early and timelines forecasting of a drought event can help to take proactive measures and set out drought mitigation strategies to alleviate the impacts of drought. Spatiotemporal data mining is the extraction of unknown and implicit knowledge, structures, spatiotemporal relationships, or patterns not explicitly stored in spatiotemporal databases. As one of data mining techniques, forecasting is widely used to predict the unknown future based upon the patterns hidden in the current and past data. This study develops a hybrid spatiotemporal scheme for integrated spatial and temporal forecasting. Temporal forecasting is achieved using feed-forward neural networks and the temporal forecasts are extended to the spatial dimension using a spatial recurrent neural network model. The methodology is demonstrated for an operational meteorological drought index the Standardized Precipitation Index (SPI) calculated at multiple timescales. 48 precipitation stations and 18 independent precipitation stations, located at Pinios river basin in Thessaly region, Greece, were used for the development and spatiotemporal validation of the hybrid spatiotemporal scheme. Several quantitative temporal and spatial statistical indices were considered for the performance evaluation of the models. Furthermore, qualitative statistical criteria based on contingency tables between observed and forecasted drought episodes were calculated. The results show that the lead time of forecasting for operational use depends on the SPI timescale. The hybrid spatiotemporal drought forecasting model could be operationally used for forecasting up to three months ahead for SPI short timescales (e.g. 3-6 months) up to six months ahead for large SPI timescales (e.g. 24 months). The above findings could be useful in developing a drought preparedness plan in the region.

Evaluation of a collaborative model: a case study analysis of watershed planning in the intermountain west

Treesearch

Gary Bentrup

2001-01-01

Collaborative planning processes have become increasingly popular for addressing environmental planning issues, resulting in a number of conceptual models for collaboration. A model proposed by Selin and Chavez suggests that collaboration emerges from a series of antecedents and then proceeds sequentially through problem-setting, direction-setting, implementation, and...

Achieving the NOAA Arctic Action Plan: The Missing Permafrost Element - Permafrost Forecasting Listening Session Results

NASA Astrophysics Data System (ADS)

Buxbaum, T. M.; Thoman, R.; Romanovsky, V. E.

2015-12-01

Permafrost is ground at or below freezing for at least two consecutive years. It currently occupies 80% of Alaska. Permafrost temperature and active layer thickness (ALT) are key climatic variables for monitoring permafrost conditions. Active layer thickness is the depth that the top layer of ground above the permafrost thaws each summer season and permafrost temperature is the temperature of the frozen permafrost under this active layer. Knowing permafrost conditions is key for those individuals working and living in Alaska and the Arctic. The results of climate models predict vast changes and potential permafrost degradation across Alaska and the Arctic. NOAA is working to implement its 2014 Arctic Action Plan and permafrost forecasting is a missing piece of this plan. The Alaska Center for Climate Assessment and Policy (ACCAP), using our webinar software and our diverse network of statewide stakeholder contacts, hosted a listening session to bring together a select group of key stakeholders. During this listening session the National Weather Service (NWS) and key permafrost researchers explained what is possible in the realm of permafrost forecasting and participants had the opportunity to discuss and share with the group (NWS, researchers, other stakeholders) what is needed for usable permafrost forecasting. This listening session aimed to answer the questions: Is permafrost forecasting needed? If so, what spatial scale is needed by stakeholders? What temporal scales do stakeholders need/want? Are there key times (winter, fall freeze-up, etc.) or locations (North Slope, key oil development areas, etc.) where forecasting would be most applicable and useful? Are there other considerations or priority needs we haven't thought of regarding permafrost forecasting? This presentation will present the results of that listening session.

Development of a High Resolution Weather Forecast Model for Mesoamerica Using the NASA Nebula Cloud Computing Environment

NASA Technical Reports Server (NTRS)

Molthan, Andrew L.; Case, Jonathan L.; Venner, Jason; Moreno-Madrinan, Max. J.; Delgado, Francisco

2012-01-01

Over the past two years, scientists in the Earth Science Office at NASA fs Marshall Space Flight Center (MSFC) have explored opportunities to apply cloud computing concepts to support near real ]time weather forecast modeling via the Weather Research and Forecasting (WRF) model. Collaborators at NASA fs Short ]term Prediction Research and Transition (SPoRT) Center and the SERVIR project at Marshall Space Flight Center have established a framework that provides high resolution, daily weather forecasts over Mesoamerica through use of the NASA Nebula Cloud Computing Platform at Ames Research Center. Supported by experts at Ames, staff at SPoRT and SERVIR have established daily forecasts complete with web graphics and a user interface that allows SERVIR partners access to high resolution depictions of weather in the next 48 hours, useful for monitoring and mitigating meteorological hazards such as thunderstorms, heavy precipitation, and tropical weather that can lead to other disasters such as flooding and landslides. This presentation will describe the framework for establishing and providing WRF forecasts, example applications of output provided via the SERVIR web portal, and early results of forecast model verification against available surface ] and satellite ]based observations.

Transition of Suomi National Polar-Orbiting Partnership (S-NPP) Data Products for Operational Weather Forecasting Applications

NASA Technical Reports Server (NTRS)

Smith, Matthew R.; Molthan, Andrew L.; Fuell, Kevin K.; Jedlovec, Gary J.

2012-01-01

SPoRT is a team of NASA/NOAA scientists focused on demonstrating the utility of NASA and future NOAA data and derived products on improving short-term weather forecasts. Work collaboratively with a suite of unique products and selected WFOs in an end-to-end transition activity. Stable funding from NASA and NOAA. Recognized by the science community as the "go to" place for transitioning experimental and research data to the operational weather community. Endorsed by NWS ESSD/SSD chiefs. Proven paradigm for transitioning satellite observations and modeling capabilities to operations (R2O). SPoRT s transition of NASA satellite instruments provides unique or higher resolution data products to complement the baseline suite of geostationary data available to forecasters. SPoRT s partnership with NWS WFOs provides them with unique imagery to support disaster response and local forecast challenges. SPoRT has years of proven experience in developing and transitioning research products to the operational weather community. SPoRT has begun work with CONUS and OCONUS WFOs to determine the best products for maximum benefit to forecasters. VIIRS has already proven to be another extremely powerful tool, enhancing forecasters ability to handle difficult forecasting situations.

Development of a High Resolution Weather Forecast Model for Mesoamerica Using the NASA Nebula Cloud Computing Environment

NASA Astrophysics Data System (ADS)

Molthan, A.; Case, J.; Venner, J.; Moreno-Madriñán, M. J.; Delgado, F.

2012-12-01

Over the past two years, scientists in the Earth Science Office at NASA's Marshall Space Flight Center (MSFC) have explored opportunities to apply cloud computing concepts to support near real-time weather forecast modeling via the Weather Research and Forecasting (WRF) model. Collaborators at NASA's Short-term Prediction Research and Transition (SPoRT) Center and the SERVIR project at Marshall Space Flight Center have established a framework that provides high resolution, daily weather forecasts over Mesoamerica through use of the NASA Nebula Cloud Computing Platform at Ames Research Center. Supported by experts at Ames, staff at SPoRT and SERVIR have established daily forecasts complete with web graphics and a user interface that allows SERVIR partners access to high resolution depictions of weather in the next 48 hours, useful for monitoring and mitigating meteorological hazards such as thunderstorms, heavy precipitation, and tropical weather that can lead to other disasters such as flooding and landslides. This presentation will describe the framework for establishing and providing WRF forecasts, example applications of output provided via the SERVIR web portal, and early results of forecast model verification against available surface- and satellite-based observations.

The Importance of Human Resource Planning in Industrial Enterprises

NASA Astrophysics Data System (ADS)

Koltnerová, Kristína; Chlpeková, Andrea; Samáková, Jana

2012-12-01

Human resource planning in the business practice should represent generally used and key activity for human resource management because human resource planning helps to make optimum utilisation of the human resources in the enterprise and it helps to avoid wastage of human resources. Human resource planning allows to forecast the future manpower requirements and also to forecast the number and type of employees who will be required by the enterprise in a near future. In the long term period, success of any enterprise depends on whether the right people are in the right places at the right time, which is the nature of human resource planning. The aim of this contribution is to explain the importance of human resource planning and to outline results of questionnaire survey which it was realized in industrial enterprises.

Improving socioeconomic land use forecasting for medium-sized metropolitan organizations in Virginia.

DOT National Transportation Integrated Search

2008-01-01

Socioeconomic forecasts are the foundation for long range travel demand modeling, projecting variables such as population, households, employment, and vehicle ownership. In Virginia, metropolitan planning organizations (MPOs) develop socioeconomic fo...

Collaboration as School Reform: Are There Patterns in the Chaos of Planning with Teachers?

ERIC Educational Resources Information Center

Kimmel, Sue C.

2012-01-01

Emphasis on collaboration is a significant thrust in both current school reform and school librarianship. Planning for instruction is generally included in various definitions and models of collaboration. Some research exists about individual planning done in isolation (Warren 2000), but little is known about teachers' planning with other…

Operationally Merged Satellite Visible/IR and Passive Microwave Sea Ice Information for Improved Sea Ice Forecasts and Ship Routing

DTIC Science & Technology

2015-09-30

microwave sea ice information for improved sea ice forecasts and ship routing W. Meier NASA Goddard Space Flight Center, Cryospheric Sciences Laboratory...updating the initial ice concentration analysis fields along the ice edge. In the past year, NASA Goddard and NRL have generated a merged 4 km AMSR-E...collaborations of three groups: NASA Goddard Space Flight Center ( NASA /GSFC) in Greenbelt, MD, NRL/Oceanography Division located at Stennis Space Center (SSC

Aviation Turbulence: Dynamics, Forecasting, and Response to Climate Change

NASA Astrophysics Data System (ADS)

Storer, Luke N.; Williams, Paul D.; Gill, Philip G.

2018-03-01

Atmospheric turbulence is a major hazard in the aviation industry and can cause injuries to passengers and crew. Understanding the physical and dynamical generation mechanisms of turbulence aids with the development of new forecasting algorithms and, therefore, reduces the impact that it has on the aviation industry. The scope of this paper is to review the dynamics of aviation turbulence, its response to climate change, and current forecasting methods at the cruising altitude of aircraft. Aviation-affecting turbulence comes from three main sources: vertical wind shear instabilities, convection, and mountain waves. Understanding these features helps researchers to develop better turbulence diagnostics. Recent research suggests that turbulence will increase in frequency and strength with climate change, and therefore, turbulence forecasting may become more important in the future. The current methods of forecasting are unable to predict every turbulence event, and research is ongoing to find the best solution to this problem by combining turbulence predictors and using ensemble forecasts to increase skill. The skill of operational turbulence forecasts has increased steadily over recent decades, mirroring improvements in our understanding. However, more work is needed—ideally in collaboration with the aviation industry—to improve observations and increase forecast skill, to help maintain and enhance aviation safety standards in the future.

The Differential Effects of Collaborative vs. Individual Prewriting Planning on Computer-Mediated L2 Writing: Transferability of Task-Based Linguistic Skills in Focus

ERIC Educational Resources Information Center

Amiryousefi, Mohammad

2017-01-01

The current study aimed at investigating the effects of three types of prewriting planning conditions, namely teacher-monitored collaborative planning (TMCP), student-led collaborative planning (SLCP), and individual planning (IP) on EFL learners' computer-mediated L2 written production and learning transfer from a pedagogic task to a new task of…

Co-Teaching in Least Restrictive Environments: A Case Study of the Quality of Common Planning Time and Its Impact on Collaboration

ERIC Educational Resources Information Center

Haywood, Paula

2017-01-01

Collaborating teachers need common planning time to plan instruction to teach students with diverse needs in their classroom. Teachers usually have limited common planning time or no time. It therefore became incumbent upon collaborating teachers to be mindful of how productively they use the limited planning time. This qualitative case study…

Post LANDSAT D Advanced Concept Evaluation (PLACE). [with emphasis on mission planning, technological forecasting, and user requirements

NASA Technical Reports Server (NTRS)

1977-01-01

An outline is given of the mission objectives and requirements, system elements, system concepts, technology requirements and forecasting, and priority analysis for LANDSAT D. User requirements and mission analysis and technological forecasting are emphasized. Mission areas considered include agriculture, range management, forestry, geology, land use, water resources, environmental quality, and disaster assessment.

Deciding the Future: A Forecast of Responsibilities of Secondary Teachers of English, 1970-2000 AD.

ERIC Educational Resources Information Center

Farrell, Edmund J.

This document is a slightly revised version of author's Ph.D. Dissertation, "A Forecast of Responsibilities of Secondary Teachers of English 1970-2000 A.D., with Implications for Teacher Education" (ED 049 253). A study in two parts, Part I presents the need for future planning in education; discusses briefly methodologies for forecasting the…

7 CFR 1710.202 - Requirement to prepare a load forecast-power supply borrowers.

Code of Federal Regulations, 2011 CFR

2011-01-01

... 7 Agriculture 11 2011-01-01 2011-01-01 false Requirement to prepare a load forecast-power supply...—power supply borrowers. (a) A power supply borrower with a total utility plant of $500 million or more... be prepared pursuant to the approved load forecast work plan. (b) A power supply borrower that is a...

Near real-time forecasting for cholera decision making in Haiti after Hurricane Matthew

PubMed Central

Camacho, Anton; Grandesso, Francesco; Cohuet, Sandra; Lemaitre, Joseph C.; Rinaldo, Andrea

2018-01-01

Computational models of cholera transmission can provide objective insights into the course of an ongoing epidemic and aid decision making on allocation of health care resources. However, models are typically designed, calibrated and interpreted post-hoc. Here, we report the efforts of a team from academia, field research and humanitarian organizations to model in near real-time the Haitian cholera outbreak after Hurricane Matthew in October 2016, to assess risk and to quantitatively estimate the efficacy of a then ongoing vaccination campaign. A rainfall-driven, spatially-explicit meta-community model of cholera transmission was coupled to a data assimilation scheme for computing short-term projections of the epidemic in near real-time. The model was used to forecast cholera incidence for the months after the passage of the hurricane (October-December 2016) and to predict the impact of a planned oral cholera vaccination campaign. Our first projection, from October 29 to December 31, predicted the highest incidence in the departments of Grande Anse and Sud, accounting for about 45% of the total cases in Haiti. The projection included a second peak in cholera incidence in early December largely driven by heavy rainfall forecasts, confirming the urgency for rapid intervention. A second projection (from November 12 to December 31) used updated rainfall forecasts to estimate that 835 cases would be averted by vaccinations in Grande Anse (90% Prediction Interval [PI] 476-1284) and 995 in Sud (90% PI 508-2043). The experience gained by this modeling effort shows that state-of-the-art computational modeling and data-assimilation methods can produce informative near real-time projections of cholera incidence. Collaboration among modelers and field epidemiologists is indispensable to gain fast access to field data and to translate model results into operational recommendations for emergency management during an outbreak. Future efforts should thus draw together multi-disciplinary teams to ensure model outputs are appropriately based, interpreted and communicated. PMID:29768401

Near real-time forecasting for cholera decision making in Haiti after Hurricane Matthew.

PubMed

Pasetto, Damiano; Finger, Flavio; Camacho, Anton; Grandesso, Francesco; Cohuet, Sandra; Lemaitre, Joseph C; Azman, Andrew S; Luquero, Francisco J; Bertuzzo, Enrico; Rinaldo, Andrea

2018-05-01

Computational models of cholera transmission can provide objective insights into the course of an ongoing epidemic and aid decision making on allocation of health care resources. However, models are typically designed, calibrated and interpreted post-hoc. Here, we report the efforts of a team from academia, field research and humanitarian organizations to model in near real-time the Haitian cholera outbreak after Hurricane Matthew in October 2016, to assess risk and to quantitatively estimate the efficacy of a then ongoing vaccination campaign. A rainfall-driven, spatially-explicit meta-community model of cholera transmission was coupled to a data assimilation scheme for computing short-term projections of the epidemic in near real-time. The model was used to forecast cholera incidence for the months after the passage of the hurricane (October-December 2016) and to predict the impact of a planned oral cholera vaccination campaign. Our first projection, from October 29 to December 31, predicted the highest incidence in the departments of Grande Anse and Sud, accounting for about 45% of the total cases in Haiti. The projection included a second peak in cholera incidence in early December largely driven by heavy rainfall forecasts, confirming the urgency for rapid intervention. A second projection (from November 12 to December 31) used updated rainfall forecasts to estimate that 835 cases would be averted by vaccinations in Grande Anse (90% Prediction Interval [PI] 476-1284) and 995 in Sud (90% PI 508-2043). The experience gained by this modeling effort shows that state-of-the-art computational modeling and data-assimilation methods can produce informative near real-time projections of cholera incidence. Collaboration among modelers and field epidemiologists is indispensable to gain fast access to field data and to translate model results into operational recommendations for emergency management during an outbreak. Future efforts should thus draw together multi-disciplinary teams to ensure model outputs are appropriately based, interpreted and communicated.

Demand forecasting for automotive sector in Malaysia by system dynamics approach

NASA Astrophysics Data System (ADS)

Zulkepli, Jafri; Fong, Chan Hwa; Abidin, Norhaslinda Zainal

2015-12-01

In general, Proton as an automotive company needs to forecast future demand of the car to assist in decision making related to capacity expansion planning. One of the forecasting approaches that based on judgemental or subjective factors is normally used to forecast the demand. As a result, demand could be overstock that eventually will increase the operation cost; or the company will face understock, which resulted losing their customers. Due to automotive industry is very challenging process because of high level of complexity and uncertainty involved in the system, an accurate tool to forecast the future of automotive demand from the modelling perspective is required. Hence, the main objective of this paper is to forecast the demand of automotive Proton car industry in Malaysia using system dynamics approach. Two types of intervention namely optimistic and pessimistic experiments scenarios have been tested to determine the capacity expansion that can prevent the company from overstocking. Finding from this study highlighted that the management needs to expand their production for optimistic scenario, whilst pessimistic give results that would otherwise. Finally, this study could help Proton Edar Sdn. Bhd (PESB) to manage the long-term capacity planning in order to meet the future demand of the Proton cars.

Daily rainfall forecasting for one year in a single run using Singular Spectrum Analysis

NASA Astrophysics Data System (ADS)

Unnikrishnan, Poornima; Jothiprakash, V.

2018-06-01

Effective modelling and prediction of smaller time step rainfall is reported to be very difficult owing to its highly erratic nature. Accurate forecast of daily rainfall for longer duration (multi time step) may be exceptionally helpful in the efficient planning and management of water resources systems. Identification of inherent patterns in a rainfall time series is also important for an effective water resources planning and management system. In the present study, Singular Spectrum Analysis (SSA) is utilized to forecast the daily rainfall time series pertaining to Koyna watershed in Maharashtra, India, for 365 days after extracting various components of the rainfall time series such as trend, periodic component, noise and cyclic component. In order to forecast the time series for longer time step (365 days-one window length), the signal and noise components of the time series are forecasted separately and then added together. The results of the study show that the method of SSA could extract the various components of the time series effectively and could also forecast the daily rainfall time series for longer duration such as one year in a single run with reasonable accuracy.

Collaborative Cyber-infrastructures for the Management of the UNESCO-IGCP Research Project "Forecast of tephra fallout"

NASA Astrophysics Data System (ADS)

Folch, A.; Costa, A.; Cordoba, G.

2009-04-01

Tephra fallout following explosive volcanic eruptions produces several hazardous effects on inhabitants, infrastructure, and property and represents a serious threat for communities located around active volcanoes. In order to mitigate the effects on the surrounding areas, scientists and civil decision-making authorities need reliable short-term forecasts during episodes of eruptive crisis and long-term probabilistic maps to plan territorial policies and land use. Modelling, together with field studies and volcano monitoring, constitutes an indispensable tool to achieve these objectives. The UNESCO-IGCP research project proposal "Forecast of tephra fallout" has the aim to produce a series of tools capable to elaborate both short-term forecasts and long-term hazard assessments using the cutting-edge models for tephra transport and sedimentation. A special project website will be designed to supply a set of models, procedures and expertise to several Latino-American Institutes based in countries seriously threatened by this geo-hazard (Argentina, Chile, Colombia, Ecuador, Mexico, and Nicaragua). This will proportionate to the final users a tool to elaborate short-term forecasts of tephra deposition on the ground, and determine airborne ash concentrations (a quantity of special relevance for aerial navigation safety) during eruptions and emergencies. The project web-site will have a public section and a password-protected area to exchange information and data among participants and, eventually, to allow remote execution of high-resolution mesoscale meteorological forecasts at the BSC facilities. The public website section will be updated periodically and will include sections describing the project objectives and achievements as well as the hazard maps for the investigated volcanoes, and will be linked to other relevant websites such as IAVCEI, IGCP, IUGS and UNESCO homepages. A part of the public section of the website will be devoted to disseminate achieved scientific results, provide general advice, and display hazard maps to a larger public beyond the scientific community. The website private section will include a software and documentation download section as well as a gateway to run the WRF mesoscale meteorological model and the parallel version of the FALL3D model at the BSC facilities. It will be invaluable during an eventual emergency if the affected institution does not yet have an agreement with its national weather service.

The Future Impact of Vietnam Era Veterans on Inpatient Acute Care and Mental Health Product Lines at a Veterans Affairs Medical Center

DTIC Science & Technology

2000-06-20

smoothing and regression which includes curve fitting are two principle forecasting model types utilized in the vast majority of forecasting applications ... model were compared against the VA Office of Policy and Planning forecasting study commissioned with the actuarial firm of Milliman & Robertson (M & R... Application to the Veterans Healthcare System The development of a model to forecast future VEV needs, utilization, and cost of the Acute Care and

Joint Seasonal ARMA Approach for Modeling of Load Forecast Errors in Planning Studies

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

Hafen, Ryan P.; Samaan, Nader A.; Makarov, Yuri V.

2014-04-14

To make informed and robust decisions in the probabilistic power system operation and planning process, it is critical to conduct multiple simulations of the generated combinations of wind and load parameters and their forecast errors to handle the variability and uncertainty of these time series. In order for the simulation results to be trustworthy, the simulated series must preserve the salient statistical characteristics of the real series. In this paper, we analyze day-ahead load forecast error data from multiple balancing authority locations and characterize statistical properties such as mean, standard deviation, autocorrelation, correlation between series, time-of-day bias, and time-of-day autocorrelation.more » We then construct and validate a seasonal autoregressive moving average (ARMA) model to model these characteristics, and use the model to jointly simulate day-ahead load forecast error series for all BAs.« less

Promoting Post-School Success for All: The Role of Collaboration in Person-Centered Transition Planning

ERIC Educational Resources Information Center

Michaels, Craig A.; Ferrara, Denise L.

2006-01-01

Successful collaboration and problem solving are the foundational processes on which meaningful transition plans are constructed. This article discusses the process of planning for the transition from school to adult life for students with disabilities and suggests that person-centered planning is an ideal vehicle for promoting collaboration and…

Using a Software Tool in Forecasting: a Case Study of Sales Forecasting Taking into Account Data Uncertainty

NASA Astrophysics Data System (ADS)

Fabianová, Jana; Kačmáry, Peter; Molnár, Vieroslav; Michalik, Peter

2016-10-01

Forecasting is one of the logistics activities and a sales forecast is the starting point for the elaboration of business plans. Forecast accuracy affects the business outcomes and ultimately may significantly affect the economic stability of the company. The accuracy of the prediction depends on the suitability of the use of forecasting methods, experience, quality of input data, time period and other factors. The input data are usually not deterministic but they are often of random nature. They are affected by uncertainties of the market environment, and many other factors. Taking into account the input data uncertainty, the forecast error can by reduced. This article deals with the use of the software tool for incorporating data uncertainty into forecasting. Proposals are presented of a forecasting approach and simulation of the impact of uncertain input parameters to the target forecasted value by this case study model. The statistical analysis and risk analysis of the forecast results is carried out including sensitivity analysis and variables impact analysis.

The method of planning the energy consumption for electricity market

NASA Astrophysics Data System (ADS)

Russkov, O. V.; Saradgishvili, S. E.

2017-10-01

The limitations of existing forecast models are defined. The offered method is based on game theory, probabilities theory and forecasting the energy prices relations. New method is the basis for planning the uneven energy consumption of industrial enterprise. Ecological side of the offered method is disclosed. The program module performed the algorithm of the method is described. Positive method tests at the industrial enterprise are shown. The offered method allows optimizing the difference between planned and factual consumption of energy every hour of a day. The conclusion about applicability of the method for addressing economic and ecological challenges is made.

The Role of the Manufacturer in Air Transportation Planning

NASA Technical Reports Server (NTRS)

Mackenzie, J.

1972-01-01

The role of the aircraft manufacturer in the airline industry is considered. The process is illustrated by using a fictitious airline as an example--that is, a case study approach with Mid-Coast Airways serving as the example. Both in slide form and with supporting papers, a brief history of the airline, a description of its route structure and a forecast based on econometric analysis are presented. Once the forecast rationale is explained, information outlines the requirements for additional aircraft and the application of new aircraft across the system using alternative fleet plan options. The fleet plan is translated into financial summaries which indicate the relative merit of alternative aircraft types or operating plans.

ARCO Chairman forecasts end of oil dominance

NASA Astrophysics Data System (ADS)

Showstack, Randy

The head of one of the world's biggest oil companies said in February that the era of oil dominating the global energy market is creaking to a close. Future energy needs will be met by a mix of fuels that are less harmful to the environment, he said, and he called for the energy and automobile industries to collaborate on solutions to reduce emissions.“We've embarked on the beginning of the last days of the age of oil,” ARCO Chairman Mike Bowlin said at a Cambridge Energy Research Associates conference in Houston, Texas, where he also described how ARCO is moving toward a new energy model. “Our challenge is not merely to survive today's low prices, but to plan for a future in which hydrocarbons are just one of a wide variety of clean fuels that will build the global economy of the 21st century”.

Approaches in Health Human Resource Forecasting: A Roadmap for Improvement

PubMed Central

Rafiei, Sima; Mohebbifar, Rafat; Hashemi, Fariba; Ezzatabadi, Mohammad Ranjbar; Farzianpour, Fereshteh

2016-01-01

Introduction Forecasting the demand and supply of health manpower in an accurate manner makes appropriate planning possible. The aim of this paper was to review approaches and methods for health manpower forecasting and consequently propose the features that improve the effectiveness of this important process of health manpower planning. Methods A literature review was conducted for studies published in English from 1990–2014 using Pub Med, Science Direct, Pro Quest, and Google Scholar databases. Review articles, qualitative studies, retrospective and prospective studies describing or applying various types of forecasting approaches and methods in health manpower forecasting were included in the review. The authors designed an extraction data sheet based on study questions to collect data on studies’ references, designs, and types of forecasting approaches, whether discussed or applied, with their strengths and weaknesses Results Forty studies were included in the review. As a result, two main categories of approaches (conceptual and analytical) for health manpower forecasting were identified. Each approach had several strengths and weaknesses. As a whole, most of them were faced with some challenges, such as being static and unable to capture dynamic variables in manpower forecasting and causal relationships. They also lacked the capacity to benefit from scenario making to assist policy makers in effective decision making. Conclusions An effective forecasting approach is supposed to resolve all the deficits that exist in current approaches and meet the key features found in the literature in order to develop an open system and a dynamic and comprehensive method necessary for today complex health care systems. PMID:27790343

OHD/HL - National Weather Hydrology Laboratory

Science.gov Websites

Organization Search NWS All NOAA Go Local forecast by "City, St" Search by city or zip code. Press enter or select the go button to submit request City, St Go Science Research and Collaboration Hydrology

THE NOAA - EPA NATIONAL AIR QUALITY FORECASTING SYSTEM

EPA Science Inventory

Building upon decades of collaboration in air pollution meteorology research, in 2003 the National Oceanic and Atmospheric Administration (NOAA) and the United States Environmental Protection Agency (EPA) signed formal partnership agreements to develop and implement an operationa...

TRAVEL FORECASTER

NASA Technical Reports Server (NTRS)

Mauldin, L. E.

1994-01-01

Business travel planning within an organization is often a time-consuming task. Travel Forecaster is a menu-driven, easy-to-use program which plans, forecasts cost, and tracks actual vs. planned cost for business-related travel of a division or branch of an organization and compiles this information into a database to aid the travel planner. The program's ability to handle multiple trip entries makes it a valuable time-saving device. Travel Forecaster takes full advantage of relational data base properties so that information that remains constant, such as per diem rates and airline fares (which are unique for each city), needs entering only once. A typical entry would include selection with the mouse of the traveler's name and destination city from pop-up lists, and typed entries for number of travel days and purpose of the trip. Multiple persons can be selected from the pop-up lists and multiple trips are accommodated by entering the number of days by each appropriate month on the entry form. An estimated travel cost is not required of the user as it is calculated by a Fourth Dimension formula. With this information, the program can produce output of trips by month with subtotal and total cost for either organization or sub-entity of an organization; or produce outputs of trips by month with subtotal and total cost for international-only travel. It will also provide monthly and cumulative formats of planned vs. actual outputs in data or graph form. Travel Forecaster users can do custom queries to search and sort information in the database, and it can create custom reports with the user-friendly report generator. Travel Forecaster 1.1 is a database program for use with Fourth Dimension Runtime 2.1.1. It requires a Macintosh Plus running System 6.0.3 or later, 2Mb of RAM and a hard disk. The standard distribution medium for this package is one 3.5 inch 800K Macintosh format diskette. Travel Forecaster was developed in 1991. Macintosh is a registered trademark of Apple Computer, Inc. Fourth Dimension is a registered trademark of Acius, Inc.

Using a safety forecast model to calculate future safety metrics.

DOT National Transportation Integrated Search

2017-05-01

This research sought to identify a process to improve long-range planning prioritization by using forecasted : safety metrics in place of the existing Utah Department of Transportation Safety Indexa metric based on historical : crash data. The res...

Speed and Delay Prediction Models for Planning Applications

DOT National Transportation Integrated Search

1999-01-01

Estimation of vehicle speed and delay is fundamental to many forms of : transportation planning analyses including air quality, long-range travel : forecasting, major investment studies, and congestion management systems. : However, existing planning...

Wind Energy Forecasting: A Collaboration of the National Center for Atmospheric Research (NCAR) and Xcel Energy

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

Parks, K.; Wan, Y. H.; Wiener, G.

2011-10-01

The focus of this report is the wind forecasting system developed during this contract period with results of performance through the end of 2010. The report is intentionally high-level, with technical details disseminated at various conferences and academic papers. At the end of 2010, Xcel Energy managed the output of 3372 megawatts of installed wind energy. The wind plants span three operating companies1, serving customers in eight states2, and three market structures3. The great majority of the wind energy is contracted through power purchase agreements (PPAs). The remainder is utility owned, Qualifying Facilities (QF), distributed resources (i.e., 'behind the meter'),more » or merchant entities within Xcel Energy's Balancing Authority footprints. Regardless of the contractual or ownership arrangements, the output of the wind energy is balanced by Xcel Energy's generation resources that include fossil, nuclear, and hydro based facilities that are owned or contracted via PPAs. These facilities are committed and dispatched or bid into day-ahead and real-time markets by Xcel Energy's Commercial Operations department. Wind energy complicates the short and long-term planning goals of least-cost, reliable operations. Due to the uncertainty of wind energy production, inherent suboptimal commitment and dispatch associated with imperfect wind forecasts drives up costs. For example, a gas combined cycle unit may be turned on, or committed, in anticipation of low winds. The reality is winds stayed high, forcing this unit and others to run, or be dispatched, to sub-optimal loading positions. In addition, commitment decisions are frequently irreversible due to minimum up and down time constraints. That is, a dispatcher lives with inefficient decisions made in prior periods. In general, uncertainty contributes to conservative operations - committing more units and keeping them on longer than may have been necessary for purposes of maintaining reliability. The downside is costs are higher. In organized electricity markets, units that are committed for reliability reasons are paid their offer price even when prevailing market prices are lower. Often, these uplift charges are allocated to market participants that caused the inefficient dispatch in the first place. Thus, wind energy facilities are burdened with their share of costs proportional to their forecast errors. For Xcel Energy, wind energy uncertainty costs manifest depending on specific market structures. In the Public Service of Colorado (PSCo), inefficient commitment and dispatch caused by wind uncertainty increases fuel costs. Wind resources participating in the Midwest Independent System Operator (MISO) footprint make substantial payments in the real-time markets to true-up their day-ahead positions and are additionally burdened with deviation charges called a Revenue Sufficiency Guarantee (RSG) to cover out of market costs associated with operations. Southwest Public Service (SPS) wind plants cause both commitment inefficiencies and are charged Southwest Power Pool (SPP) imbalance payments due to wind uncertainty and variability. Wind energy forecasting helps mitigate these costs. Wind integration studies for the PSCo and Northern States Power (NSP) operating companies have projected increasing costs as more wind is installed on the system due to forecast error. It follows that reducing forecast error would reduce these costs. This is echoed by large scale studies in neighboring regions and states that have recommended adoption of state-of-the-art wind forecasting tools in day-ahead and real-time planning and operations. Further, Xcel Energy concluded reduction of the normalized mean absolute error by one percent would have reduced costs in 2008 by over $1 million annually in PSCo alone. The value of reducing forecast error prompted Xcel Energy to make substantial investments in wind energy forecasting research and development.« less

Collaborative Strategic Planning in Higher Education

ERIC Educational Resources Information Center

Sanaghan, Patrick

2009-01-01

This book outlines a simple, five-phase collaborative approach to strategic planning that has worked effectively on many campuses. Specifically, Collaborative Strategic Planning (CSP) refers to the disciplined and thoughtful process of meaningfully engaging relevant stakeholders in creating a shared future vision and goals for their institution.…

Results from the centers for disease control and prevention's predict the 2013-2014 Influenza Season Challenge.

PubMed

Biggerstaff, Matthew; Alper, David; Dredze, Mark; Fox, Spencer; Fung, Isaac Chun-Hai; Hickmann, Kyle S; Lewis, Bryan; Rosenfeld, Roni; Shaman, Jeffrey; Tsou, Ming-Hsiang; Velardi, Paola; Vespignani, Alessandro; Finelli, Lyn

2016-07-22

Early insights into the timing of the start, peak, and intensity of the influenza season could be useful in planning influenza prevention and control activities. To encourage development and innovation in influenza forecasting, the Centers for Disease Control and Prevention (CDC) organized a challenge to predict the 2013-14 Unites States influenza season. Challenge contestants were asked to forecast the start, peak, and intensity of the 2013-2014 influenza season at the national level and at any or all Health and Human Services (HHS) region level(s). The challenge ran from December 1, 2013-March 27, 2014; contestants were required to submit 9 biweekly forecasts at the national level to be eligible. The selection of the winner was based on expert evaluation of the methodology used to make the prediction and the accuracy of the prediction as judged against the U.S. Outpatient Influenza-like Illness Surveillance Network (ILINet). Nine teams submitted 13 forecasts for all required milestones. The first forecast was due on December 2, 2013; 3/13 forecasts received correctly predicted the start of the influenza season within one week, 1/13 predicted the peak within 1 week, 3/13 predicted the peak ILINet percentage within 1 %, and 4/13 predicted the season duration within 1 week. For the prediction due on December 19, 2013, the number of forecasts that correctly forecasted the peak week increased to 2/13, the peak percentage to 6/13, and the duration of the season to 6/13. As the season progressed, the forecasts became more stable and were closer to the season milestones. Forecasting has become technically feasible, but further efforts are needed to improve forecast accuracy so that policy makers can reliably use these predictions. CDC and challenge contestants plan to build upon the methods developed during this contest to improve the accuracy of influenza forecasts.

Real-time demonstration and evaluation of over-the-loop short to medium-range ensemble streamflow forecasting

NASA Astrophysics Data System (ADS)

Wood, A. W.; Clark, E.; Newman, A. J.; Nijssen, B.; Clark, M. P.; Gangopadhyay, S.; Arnold, J. R.

2015-12-01

The US National Weather Service River Forecasting Centers are beginning to operationalize short range to medium range ensemble predictions that have been in development for several years. This practice contrasts with the traditional single-value forecast practice at these lead times not only because the ensemble forecasts offer a basis for quantifying forecast uncertainty, but also because the use of ensembles requires a greater degree of automation in the forecast workflow than is currently used. For instance, individual ensemble member forcings cannot (practically) be manually adjusted, a step not uncommon with the current single-value paradigm, thus the forecaster is required to adopt a more 'over-the-loop' role than before. The relative lack of experience among operational forecasters and forecast users (eg, water managers) in the US with over-the-loop approaches motivates the creation of a real-time demonstration and evaluation platform for exploring the potential of over-the-loop workflows to produce usable ensemble short-to-medium range forecasts, as well as long range predictions. We describe the development and early results of such an effort by a collaboration between NCAR and the two water agencies, the US Army Corps of Engineers and the US Bureau of Reclamation. Focusing on small to medium sized headwater basins around the US, and using multi-decade series of ensemble streamflow hindcasts, we also describe early results, assessing the skill of daily-updating, over-the-loop forecasts driven by a set of ensemble atmospheric outputs from the NCEP GEFS for lead times from 1-15 days.

Progress and challenges with Warn-on-Forecast

NASA Astrophysics Data System (ADS)

Stensrud, David J.; Wicker, Louis J.; Xue, Ming; Dawson, Daniel T.; Yussouf, Nusrat; Wheatley, Dustan M.; Thompson, Therese E.; Snook, Nathan A.; Smith, Travis M.; Schenkman, Alexander D.; Potvin, Corey K.; Mansell, Edward R.; Lei, Ting; Kuhlman, Kristin M.; Jung, Youngsun; Jones, Thomas A.; Gao, Jidong; Coniglio, Michael C.; Brooks, Harold E.; Brewster, Keith A.

2013-04-01

The current status and challenges associated with two aspects of Warn-on-Forecast-a National Oceanic and Atmospheric Administration research project exploring the use of a convective-scale ensemble analysis and forecast system to support hazardous weather warning operations-are outlined. These two project aspects are the production of a rapidly-updating assimilation system to incorporate data from multiple radars into a single analysis, and the ability of short-range ensemble forecasts of hazardous convective weather events to provide guidance that could be used to extend warning lead times for tornadoes, hailstorms, damaging windstorms and flash floods. Results indicate that a three-dimensional variational assimilation system, that blends observations from multiple radars into a single analysis, shows utility when evaluated by forecasters in the Hazardous Weather Testbed and may help increase confidence in a warning decision. The ability of short-range convective-scale ensemble forecasts to provide guidance that could be used in warning operations is explored for five events: two tornadic supercell thunderstorms, a macroburst, a damaging windstorm and a flash flood. Results show that the ensemble forecasts of the three individual severe thunderstorm events are very good, while the forecasts from the damaging windstorm and flash flood events, associated with mesoscale convective systems, are mixed. Important interactions between mesoscale and convective-scale features occur for the mesoscale convective system events that strongly influence the quality of the convective-scale forecasts. The development of a successful Warn-on-Forecast system will take many years and require the collaborative efforts of researchers and operational forecasters to succeed.

How seasonal forecast could help a decision maker: an example of climate service for water resource management

NASA Astrophysics Data System (ADS)

Viel, Christian; Beaulant, Anne-Lise; Soubeyroux, Jean-Michel; Céron, Jean-Pierre

2016-04-01

The FP7 project EUPORIAS was a great opportunity for the climate community to co-design with stakeholders some original and innovative climate services at seasonal time scales. In this framework, Météo-France proposed a prototype that aimed to provide to water resource managers some tailored information to better anticipate the coming season. It is based on a forecasting system, built on a refined hydrological suite, forced by a coupled seasonal forecast model. It particularly delivers probabilistic river flow prediction on river basins all over the French territory. This paper presents the work we have done with "EPTB Seine Grands Lacs" (EPTB SGL), an institutional stakeholder in charge of the management of 4 great reservoirs on the upper Seine Basin. First, we present the co-design phase, which means the translation of classical climate outputs into several indices, relevant to influence the stakeholder's decision making process (DMP). And second, we detail the evaluation of the impact of the forecast on the DMP. This evaluation is based on an experiment realised in collaboration with the stakeholder. Concretely EPTB SGL has replayed some past decisions, in three different contexts: without any forecast, with a forecast A and with a forecast B. One of forecast A and B really contained seasonal forecast, the other only contained random forecasts taken from past climate. This placebo experiment, realised in a blind test, allowed us to calculate promising skill scores of the DMP based on seasonal forecast in comparison to a classical approach based on climatology, and to EPTG SGL current practice.

NASA Products to Enhance Energy Utility Load Forecasting

NASA Technical Reports Server (NTRS)

Lough, G.; Zell, E.; Engel-Cox, J.; Fungard, Y.; Jedlovec, G.; Stackhouse, P.; Homer, R.; Biley, S.

2012-01-01

Existing energy load forecasting tools rely upon historical load and forecasted weather to predict load within energy company service areas. The shortcomings of load forecasts are often the result of weather forecasts that are not at a fine enough spatial or temporal resolution to capture local-scale weather events. This project aims to improve the performance of load forecasting tools through the integration of high-resolution, weather-related NASA Earth Science Data, such as temperature, relative humidity, and wind speed. Three companies are participating in operational testing one natural gas company, and two electric providers. Operational results comparing load forecasts with and without NASA weather forecasts have been generated since March 2010. We have worked with end users at the three companies to refine selection of weather forecast information and optimize load forecast model performance. The project will conclude in 2012 with transitioning documented improvements from the inclusion of NASA forecasts for sustained use by energy utilities nationwide in a variety of load forecasting tools. In addition, Battelle has consulted with energy companies nationwide to document their information needs for long-term planning, in light of climate change and regulatory impacts.

Techniques for water demand analysis and forecasting: Puerto Rico, a case study

USGS Publications Warehouse

Attanasi, E.D.; Close, E.R.; Lopez, M.A.

1975-01-01

The rapid economic growth of the Commonwealth-of Puerto Rico since 1947 has brought public pressure on Government agencies for rapid development of public water supply and waste treatment facilities. Since 1945 the Puerto Rico Aqueduct and Sewer Authority has had the responsibility for planning, developing and operating water supply and waste treatment facilities on a municipal basis. The purpose of this study was to develop operational techniques whereby a planning agency, such as the Puerto Rico Aqueduct and Sewer Authority, could project the temporal and spatial distribution of .future water demands. This report is part of a 2-year cooperative study between the U.S. Geological Survey and the Environmental Quality Board of the Commonwealth of Puerto Rico, for the development of systems analysis techniques for use in water resources planning. While the Commonwealth was assisted in the development of techniques to facilitate ongoing planning, the U.S. Geological Survey attempted to gain insights in order to better interface its data collection efforts with the planning process. The report reviews the institutional structure associated with water resources planning for the Commonwealth. A brief description of alternative water demand forecasting procedures is presented and specific techniques and analyses of Puerto Rico demand data are discussed. Water demand models for a specific area of Puerto Rico are then developed. These models provide a framework for making several sets of water demand forecasts based on alternative economic and demographic assumptions. In the second part of this report, the historical impact of water resources investment on regional economic development is analyzed and related to water demand .forecasting. Conclusions and future data needs are in the last section.

How Many Will Choose? School Choice and Student Enrollment Planning.

ERIC Educational Resources Information Center

Chan, Tak C.

1993-01-01

Enrollment planning is the basis of all school system planning. Focuses on assessing the impact of a choice plan on student enrollment planning. Issues involved include home schooling, school employees' choice, and private kindergarten programs. Administrators are advised to evaluate existing forecasting methodologies. (MLF)

Global Drought Services: Collaborations Toward an Information System for Early Warning

NASA Astrophysics Data System (ADS)

Hayes, M. J.; Pulwarty, R. S.; Svoboda, M.

2014-12-01

Drought is a hazard that lends itself well to diligent, sustained monitoring and early warning. However, unlike most hazards, the fact that droughts typically evolve slowly, can last for months or years and cover vast areas spanning multiple political boundaries/jurisdictions and economic sectors can make it a daunting task to monitor, develop plans for, and identify appropriate, proactive mitigation strategies. The National Drought Mitigation Center (NDMC) and National Integrated Drought Information System (NIDIS) have been working together to reduce societal vulnerability to drought by helping decision makers at all levels to: 1) implement drought early warning/forecasting and decision support systems; 2) support and advocate for better collection of, and understanding of drought impacts; and 3) increase long-term resilience to drought through proactive planning. The NDMC and NIDIS risk management approach has been the basis from which many partners around the world are developing a collaboration and coordination nexus with an ultimate goal of building comprehensive global drought early warning information systems (GDEWIS). The core emphasis of this model is on developing and applying useful and usable information that can be integrated and transferred freely to other regions around the globe. The High-Level Ministerial Declaration on Drought, the Integrated Drought Management Programme (IDMP) co-led by the WMO and the Global Water Partnership (GWP), and the Global Framework for Climate Services are drawing extensively from the integrated NDMC-NIDIS risk management framework. This presentation will describe, in detail, the various drought resources, tools, services, and collaborations already being provided and undertaken at the national and regional scales by the NDMC, NIDIS, and their partners. The presentation will be forward-looking, identifying improvements in existing and proposed mechanisms to help strengthen national and international drought early warning information systems to support preparedness and adaptation decisions in a changing climate.

Collaborative Planning: Cooking up an Inclusive Service-Learning Project

ERIC Educational Resources Information Center

Bonati, Michelle L.

2018-01-01

Collaborative planning between special education teachers and general education teachers that focuses on curriculum, instruction, and assessment can improve learning outcomes for students with and without disabilities. Service-learning is a teaching practice that can provide a flexible approach for teachers to collaboratively plan to meet the…

[Demography perspectives and forecasts of the demand for electricity].

PubMed

Roy, L; Guimond, E

1995-01-01

"Demographic perspectives form an integral part in the development of electric load forecasts. These forecasts in turn are used to justify the addition and repair of generating facilities that will supply power in the coming decades. The goal of this article is to present how demographic perspectives are incorporated into the electric load forecasting in Quebec. The first part presents the methods, hypotheses and results of population and household projections used by Hydro-Quebec in updating its latest development plan. The second section demonstrates applications of such demographic projections for forecasting the electric load, with a focus on the residential sector." (SUMMARY IN ENG AND SPA) excerpt

Application of SeaWinds Scatterometer and TMI-SSM/I Rain Rates to Hurricane Analysis and Forecasting

NASA Technical Reports Server (NTRS)

Atlas, Robert; Hou, Arthur; Reale, Oreste

2004-01-01

Results provided by two different assimilation methodologies involving data from passive and active space-borne microwave instruments are presented. The impact of the precipitation estimates produced by the TRMM Microwave Imager (TMI) and Special Sensor Microwave/Imager (SSM/I) in a previously developed 1D variational continuous assimilation algorithm for assimilating tropical rainfall is shown on two hurricane cases. Results on the impact of the SeaWinds scatterometer on the intensity and track forecast of a mid-Atlantic hurricane are also presented. This work is the outcome of a collaborative effort between NASA and NOAA and indicates the substantial improvement in tropical cyclone forecasting that can result from the assimilation of space-based data in global atmospheric models.

Florida Model Information eXchange System (MIXS).

DOT National Transportation Integrated Search

2013-08-01

Transportation planning largely relies on travel demand forecasting, which estimates the number and type of vehicles that will use a roadway at some point in the future. Forecasting estimates are made by computer models that use a wide variety of dat...

Updating the transportation plans in Virginia's small urban areas.

DOT National Transportation Integrated Search

1987-01-01

The Transportation Planning Division (TPD) of the Virginia Department of Transportation is responsible for developing transportation plans for areas in the state having a population greater than 3,500. Although transportation forecasting procedures f...

High-Resolution Hydrological Sub-Seasonal Forecasting for Water Resources Management Over Europe

NASA Astrophysics Data System (ADS)

Wood, E. F.; Wanders, N.; Pan, M.; Sheffield, J.; Samaniego, L. E.; Thober, S.; Kumar, R.; Prudhomme, C.; Houghton-Carr, H.

2017-12-01

For decision-making at the sub-seasonal and seasonal time scale, hydrological forecasts with a high temporal and spatial resolution are required by water managers. So far such forecasts have been unavailable due to 1) lack of availability of meteorological seasonal forecasts, 2) coarse temporal resolution of meteorological seasonal forecasts, requiring temporal downscaling, 3) lack of consistency between observations and seasonal forecasts, requiring bias-correction. The EDgE (End-to-end Demonstrator for improved decision making in the water sector in Europe) project commissioned by the ECMWF (C3S) created a unique dataset of hydrological seasonal forecasts derived from four global climate models (CanCM4, FLOR-B01, ECMF, LFPW) in combination with four global hydrological models (PCR-GLOBWB, VIC, mHM, Noah-MP), resulting in 208 forecasts for any given day. The forecasts provide a daily temporal and 5-km spatial resolution, and are bias corrected against E-OBS meteorological observations. The forecasts are communicated to stakeholders via Sectoral Climate Impact Indicators (SCIIs), created in collaboration with the end-user community of the EDgE project (e.g. the percentage of ensemble realizations above the 10th percentile of monthly river flow, or below the 90th). Results show skillful forecasts for discharge from 3 months to 6 months (latter for N Europe due to snow); for soil moisture up to three months due precipitation forecast skill and short initial condition memory; and for groundwater greater than 6 months (lowest skill in western Europe.) The SCIIs are effective in communicating both forecast skill and uncertainty. Overall the new system provides an unprecedented ensemble for seasonal forecasts with significant skill over Europe to support water management. The consistency in both the GCM forecasts and the LSM parameterization ensures a stable and reliable forecast framework and methodology, even if additional GCMs or LSMs are added in the future.

Historic and forecasted population and land-cover change in eastern North Carolina, 1992-2030

USGS Publications Warehouse

Claggett, Peter; Hearn,, Paul P.; Donato, David I.

2015-01-01

The Southeast Regional Partnership for Planning and Sustainability (SERPPAS) was formed in 2005 as a partnership between the Department of Defense (DOD) and State and Federal agencies to promote better collaboration in making resource-use decisions. In support of this goal, the U.S. Geological Survey (USGS) conducted a study to evaluate historic population growth and land-cover change, and to model future change, for the 13-county SERPPAS study area in southeastern North Carolina (fig. 1). Improved understanding of trends in land-cover change and the ability to forecast land-cover change that is consistent with these trends will be a key component of efforts to accommodate local military-mission imperatives while also promoting sustainable economic growth throughout the 13-county study area. The study had three principal objectives:    1.  Evaluate historic changes in population and land cover for the period 1992–2006 using both previously existing as well as newly generated land-cover data.    2.  Develop models to forecast future change in land cover using the data gathered in objective 1 in conjunction with ancillary data on the suitability of the various sub-areas within the study area for low- and high-intensity urban development.    3.  Deliver these results—including an executive-level briefing and a USGS technical report—to DOD, other project cooperators, and local counties in hard-copy and digital formats and via the Web through a map-based data viewer. This report provides a general overview of the study and is intended for general distribution to non-technical audiences.

Snowpack Estimates Improve Water Resources Climate-Change Adaptation Strategies

NASA Astrophysics Data System (ADS)

Lestak, L.; Molotch, N. P.; Guan, B.; Granger, S. L.; Nemeth, S.; Rizzardo, D.; Gehrke, F.; Franz, K. J.; Karsten, L. R.; Margulis, S. A.; Case, K.; Anderson, M.; Painter, T. H.; Dozier, J.

2010-12-01

Observed climate trends over the past 50 years indicate a reduction in snowpack water storage across the Western U.S. As the primary water source for the region, the loss in snowpack water storage presents significant challenges for managing water deliveries to meet agricultural, municipal, and hydropower demands. Improved snowpack information via remote sensing shows promise for improving seasonal water supply forecasts and for informing decadal scale infrastructure planning. An ongoing project in the California Sierra Nevada and examples from the Rocky Mountains indicate the tractability of estimating snowpack water storage on daily time steps using a distributed snowpack reconstruction model. Fractional snow covered area (FSCA) derived from Moderate Resolution Imaging Spectroradiometer (MODIS) satellite data were used with modeled snowmelt from the snowpack model to estimate snow water equivalent (SWE) in the Sierra Nevada (64,515 km2). Spatially distributed daily SWE estimates were calculated for 10 years, 2000-2009, with detailed analysis for two anamolous years, 2006, a wet year and 2009, an over-forecasted year. Sierra-wide mean SWE was 0.8 cm for 01 April 2006 versus 0.4 cm for 01 April 2009, comparing favorably with known outflow. Modeled SWE was compared to in-situ (observed) SWE for 01 April 2006 for the Feather (northern Sierra, lower-elevation) and Merced (central Sierra, higher-elevation) basins, with mean modeled SWE 80% of observed SWE. Integration of spatial SWE estimates into forecasting operations will allow for better visualization and analysis of high-altitude late-season snow missed by in-situ snow sensors and inter-annual anomalies associated with extreme precipitation events/atmospheric rivers. Collaborations with state and local entities establish protocols on how to meet current and future information needs and improve climate-change adaptation strategies.

Supplier Short Term Load Forecasting Using Support Vector Regression and Exogenous Input

NASA Astrophysics Data System (ADS)

Matijaš, Marin; Vukićcević, Milan; Krajcar, Slavko

2011-09-01

In power systems, task of load forecasting is important for keeping equilibrium between production and consumption. With liberalization of electricity markets, task of load forecasting changed because each market participant has to forecast their own load. Consumption of end-consumers is stochastic in nature. Due to competition, suppliers are not in a position to transfer their costs to end-consumers; therefore it is essential to keep forecasting error as low as possible. Numerous papers are investigating load forecasting from the perspective of the grid or production planning. We research forecasting models from the perspective of a supplier. In this paper, we investigate different combinations of exogenous input on the simulated supplier loads and show that using points of delivery as a feature for Support Vector Regression leads to lower forecasting error, while adding customer number in different datasets does the opposite.

Combination of synoptical-analogous and dynamical methods to increase skill score of monthly air temperature forecasts over Northern Eurasia

NASA Astrophysics Data System (ADS)

Khan, Valentina; Tscepelev, Valery; Vilfand, Roman; Kulikova, Irina; Kruglova, Ekaterina; Tischenko, Vladimir

2016-04-01

Long-range forecasts at monthly-seasonal time scale are in great demand of socio-economic sectors for exploiting climate-related risks and opportunities. At the same time, the quality of long-range forecasts is not fully responding to user application necessities. Different approaches, including combination of different prognostic models, are used in forecast centers to increase the prediction skill for specific regions and globally. In the present study, two forecasting methods are considered which are exploited in operational practice of Hydrometeorological Center of Russia. One of them is synoptical-analogous method of forecasting of surface air temperature at monthly scale. Another one is dynamical system based on the global semi-Lagrangian model SL-AV, developed in collaboration of Institute of Numerical Mathematics and Hydrometeorological Centre of Russia. The seasonal version of this model has been used to issue global and regional forecasts at monthly-seasonal time scales. This study presents results of the evaluation of surface air temperature forecasts generated with using above mentioned synoptical-statistical and dynamical models, and their combination to potentially increase skill score over Northern Eurasia. The test sample of operational forecasts is encompassing period from 2010 through 2015. The seasonal and interannual variability of skill scores of these methods has been discussed. It was noticed that the quality of all forecasts is highly dependent on the inertia of macro-circulation processes. The skill scores of forecasts are decreasing during significant alterations of synoptical fields for both dynamical and empirical schemes. Procedure of combination of forecasts from different methods, in some cases, has demonstrated its effectiveness. For this study the support has been provided by Grant of Russian Science Foundation (№14-37-00053).

Assessment of a new seasonal to inter-annual operational Great Lakes water supply, water levels, and connecting channel flow forecasting system

NASA Astrophysics Data System (ADS)

Gronewold, A.; Fry, L. M.; Hunter, T.; Pei, L.; Smith, J.; Lucier, H.; Mueller, R.

2017-12-01

The U.S. Army Corps of Engineers (USACE) has recently operationalized a suite of ensemble forecasts of Net Basin Supply (NBS), water levels, and connecting channel flows that was developed through a collaboration among USACE, NOAA's Great Lakes Environmental Research Laboratory, Ontario Power Generation (OPG), New York Power Authority (NYPA), and the Niagara River Control Center (NRCC). These forecasts are meant to provide reliable projections of potential extremes in daily discharge in the Niagara and St. Lawrence Rivers over a long time horizon (5 years). The suite of forecasts includes eight configurations that vary by (a) NBS model configuration, (b) meteorological forcings, and (c) incorporation of seasonal climate projections through the use of weighting. Forecasts are updated on a weekly basis, and represent the first operational forecasts of Great Lakes water levels and flows that span daily to inter-annual horizons and employ realistic regulation logic and lake-to-lake routing. We will present results from a hindcast assessment conducted during the transition from research to operation, as well as early indications of success rates determined through operational verification of forecasts. Assessment will include an exploration of the relative skill of various forecast configurations at different time horizons and the potential for application to hydropower decision making and Great Lakes water management.

Lagrangian Transport Model Forecasts as Useful Support of the Flight Planning During the Intercontinental Transport and Chemical Transformation 2002 (ITCT 2k2) Measurement Campaign

NASA Astrophysics Data System (ADS)

Forster, C.; Cooper, O.; Stohl, A.; Eckhardt, S.; James, P.; Dunlea, E.; Nicks, D. K.; Holloway, J. S.; Hübler, G.; Parrish, D. D.; Ryerson, T. B.; Trainer, M.

2002-12-01

In this study, the Lagrangian tracer transport model FLEXPART is shown to be a useful forecasting tool for the flight planning during the ITCT 2k2 (Intercontinental Transport and Chemical Transformation 2002) aircraft measurement campaign. The advantages of this model are that it requires only a short computation time, has a finer spatial resolution and does not suffer numerical diffusion compared to chemistry transport models (CTMs). It is a compromise between simple trajectory calculations and complex CTMs that makes best use of available computer hardware. During the campaign FLEXPART provided three-day forecasts for four different anthropogenic CO tracers: Asian, North American, Japanese, and European. The forecasts were based on data from the Aviation model (AVN) of the National Center for Environmental Prediction (NCEP) and relied on the EDGAR emission inventory for the base year 1990. In two case studies, the forecast abilities of FLEXPART are analysed and discussed by comparing the forecasts with measurement data, results from the post analysis modelling, infrared satellite images, and backward trajectories calculated with two different Lagrangian trajectory models. It is shown that intercontinental transport and dispersion of pollution plumes were qualitatively well predicted, and the aircraft could successfully be directed into the polluted air masses.

Demand forecasting for automotive sector in Malaysia by system dynamics approach

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

Zulkepli, Jafri, E-mail: zhjafri@uum.edu.my; Abidin, Norhaslinda Zainal, E-mail: nhaslinda@uum.edu.my; Fong, Chan Hwa, E-mail: hfchan7623@yahoo.com

In general, Proton as an automotive company needs to forecast future demand of the car to assist in decision making related to capacity expansion planning. One of the forecasting approaches that based on judgemental or subjective factors is normally used to forecast the demand. As a result, demand could be overstock that eventually will increase the operation cost; or the company will face understock, which resulted losing their customers. Due to automotive industry is very challenging process because of high level of complexity and uncertainty involved in the system, an accurate tool to forecast the future of automotive demand frommore » the modelling perspective is required. Hence, the main objective of this paper is to forecast the demand of automotive Proton car industry in Malaysia using system dynamics approach. Two types of intervention namely optimistic and pessimistic experiments scenarios have been tested to determine the capacity expansion that can prevent the company from overstocking. Finding from this study highlighted that the management needs to expand their production for optimistic scenario, whilst pessimistic give results that would otherwise. Finally, this study could help Proton Edar Sdn. Bhd (PESB) to manage the long-term capacity planning in order to meet the future demand of the Proton cars.« less

National plans for aircraft icing and improved aircraft icing forecasts and associated warning services

NASA Technical Reports Server (NTRS)

Pass, Ralph P.

1988-01-01

Recently, the United States has increased its activities related to aircraft icing in numerous fields: ice phobics, revised characterization of icing conditions, instrument development/evaluation, de-ice/anti-ice devices, simulated supercooled clouds, computer simulation and flight tests. The Federal Coordinator for Meteorology is involved in two efforts, one a National Plan on Aircraft Icing and the other a plan for Improved Aircraft Icing Forecasts and Associated Warning Services. These two plans will provide an approved structure for future U.S. activities related to aircraft icing. The recommended activities will significantly improve the position of government agencies to perform mandated activities and to enable U.S. manufacturers to be competitive in the world market.

Rapid weather information dissemination in Florida

NASA Technical Reports Server (NTRS)

Martsolf, J. D.; Heinemann, P. H.; Gerber, J. F.; Crosby, F. L.; Smith, D. L.

1984-01-01

The development of the Florida Agricultural Services and Technology (FAST) plan to provide ports for users to call for weather information is described. FAST is based on the Satellite Frost Forecast System, which makes a broad base of weather data available to its users. The methods used for acquisition and dissemination of data from various networks under the FAST plan are examined. The system provides color coded IR or thermal maps, precipitation maps, and textural forecast information. A diagram of the system is provided.

A Comparision of Heuristic Methods Used in Hierarchical Production Planning.

DTIC Science & Technology

1979-03-01

literature: Equalization— of—Run—Out—Ti mes ( EROT ) (12], Winters ( 18 ] , Hex and Meal (lii, and Knap- sack [1] . Figure 2 displays a flow chart...forecast error mus t be greater than 24% for this difference to be noticed. Hax—Meal outperformed the EROT with forecast error between 18 and 23% by more...planning frame- work: the Equalization—of—Run—Out—Time approach (12], the Winters approach [ 18 ], the Hax—Meal approach [lii, and the Knapsack approach (1

Strategic Science for Coral Ecosystems 2007-2011

USGS Publications Warehouse

,

2010-01-01

Shallow and deep coral ecosystems are being imperiled by a combination of stressors. Climate change, unsustainable fishing practices, and disease are transforming coral communities at regional to global scales. At local levels, excessive amounts of sediments, nutrients, and contaminants are also impacting the many benefits that healthy coral ecosystems provide. This Plan, Strategic Science for Coral Ecosystems, describes the information needs of resource managers and summarizes current research being conducted by U.S. Geological Survey (USGS) scientists and partners. It outlines important research actions that need to be undertaken over the next five years to achieve more accurate forecasting of future conditions and develop more effective decision-support tools to adaptively manage coral ecosystems. The overarching outcome of this Plan, if fully implemented, would be in transferring relevant knowledge to decision-makers, enabling them to better protect and sustain coral ecosystem services. These services include sources of food, essential habitat for fisheries and protected species, protection of coastlines from wave damage and erosion, recreation, and cultural values for indigenous communities. The USGS has a long history of research and monitoring experience in studying ancient and living coral communities and serving many stakeholders. The research actions in this Plan build on the USGS legacy of conducting integrated multidisciplinary science to address complex environmental issues. This Plan is responsive to Federal legislation and authorities and a variety of external and internal drivers that include the President's Ocean Action Plan, the recommendations of the Coral Reef Task Force, the information needs of Bureaus in the Department of Interior, the USGS Bureau Science Strategy (USGS 2007) and the formal plans of several USGS Programs. To achieve this Plan's desired outcomes will require increased funding and more effective coordination and collaboration among USGS managers and scientists within a national and international framework of partnerships in coral ecosystem science.

WIPCast: Probabilistic Forecasting for Aviation Decision Aid Applications

DTIC Science & Technology

2011-06-01

traders, or families planning an outing – manage weather-related risk. By quantifying risk , probabilistic forecasting enables optimization of actions via...confidence interval to the user’s risk tolerance helps drive highly effective and innovative decision support mechanisms for visually quantifying risk for

Making Thinking Visible: Collaborative Planning--Concepts, Processes, and Assignments: A Casebook.

ERIC Educational Resources Information Center

Aston, Jean A., Ed.; And Others

This casebook is part of a set of materials written by the members of the Making Thinking Visible Project. It offers high school, college, and community college teachers' multiple perspectives on the teaching and learning of collaborative planning, and on classroom inquiry and practice. The casebook explains collaborative planning (a writing…

State of the Art Review of Human-Human Collaboration Research: An Integrated, Multidisciplinary Perspective

DTIC Science & Technology

2002-10-31

NJ: Lawrence Erlbaum. Jamal, T. B. & Getz, D. (1995). Collaboration Theory and Community Tourism Planning. Annals of Tourism Planning...Surveys, 31. Jamal, T. B. & Getz, D. (1995). Collaboration Theory and Community Tourism Planning. Annals of Tourism Planning Research, 22 (1...granum/altdocs/dav_alt.htm. Jorn, L. A., Duin, A. H., & Wahlstrom, B. J. (1996). Designing and Managing Virtual Learning ommunities . IEEE

Distributed HUC-based modeling with SUMMA for ensemble streamflow forecasting over large regional domains.

NASA Astrophysics Data System (ADS)

Saharia, M.; Wood, A.; Clark, M. P.; Bennett, A.; Nijssen, B.; Clark, E.; Newman, A. J.

2017-12-01

Most operational streamflow forecasting systems rely on a forecaster-in-the-loop approach in which some parts of the forecast workflow require an experienced human forecaster. But this approach faces challenges surrounding process reproducibility, hindcasting capability, and extension to large domains. The operational hydrologic community is increasingly moving towards `over-the-loop' (completely automated) large-domain simulations yet recent developments indicate a widespread lack of community knowledge about the strengths and weaknesses of such systems for forecasting. A realistic representation of land surface hydrologic processes is a critical element for improving forecasts, but often comes at the substantial cost of forecast system agility and efficiency. While popular grid-based models support the distributed representation of land surface processes, intermediate-scale Hydrologic Unit Code (HUC)-based modeling could provide a more efficient and process-aligned spatial discretization, reducing the need for tradeoffs between model complexity and critical forecasting requirements such as ensemble methods and comprehensive model calibration. The National Center for Atmospheric Research is collaborating with the University of Washington, the Bureau of Reclamation and the USACE to implement, assess, and demonstrate real-time, over-the-loop distributed streamflow forecasting for several large western US river basins and regions. In this presentation, we present early results from short to medium range hydrologic and streamflow forecasts for the Pacific Northwest (PNW). We employ a real-time 1/16th degree daily ensemble model forcings as well as downscaled Global Ensemble Forecasting System (GEFS) meteorological forecasts. These datasets drive an intermediate-scale configuration of the Structure for Unifying Multiple Modeling Alternatives (SUMMA) model, which represents the PNW using over 11,700 HUCs. The system produces not only streamflow forecasts (using the MizuRoute channel routing tool) but also distributed model states such as soil moisture and snow water equivalent. We also describe challenges in distributed model-based forecasting, including the application and early results of real-time hydrologic data assimilation.

VSP - Discussion: The Common Interest on Planning Hulls and Plan for Collaboration Studies between NSWC and KRISO - Washington DC

DTIC Science & Technology

2016-03-07

planning hulls and plan for N62909-15-1-2052 collaboration studies between NSWC and KRISO - Washington DC Sb. GRANT NUMBER N62909-15-1-2052 Sc. PROGRAM...be carried out in MASK’s facilities. We discussed common interests on planing hulls , and made plans for collaboration studies between NSWC and KRISO... hull forms for satisfying the requirements of the project. Model tests and analyses are required to assess the maneuvering and seakeeping performance

Developing guidelines for incorporating managing demand into WSDOT planning and programming: transportation demand management guidance for corridor planning studies.

DOT National Transportation Integrated Search

2016-02-01

The Washington State Department of Transportation (WSDOT) regional planning programs address current and forecasted deficiencies of State highways through the conduct of corridor studies. This Guidance for the conduct of corridor planning studies is ...

Evaluation of an Early-Warning System for Heat Wave-Related Mortality in Europe: Implications for Sub-seasonal to Seasonal Forecasting and Climate Services

PubMed Central

Lowe, Rachel; García-Díez, Markel; Ballester, Joan; Creswick, James; Robine, Jean-Marie; Herrmann, François R.; Rodó, Xavier

2016-01-01

Heat waves have been responsible for more fatalities in Europe over the past decades than any other extreme weather event. However, temperature-related illnesses and deaths are largely preventable. Reliable sub-seasonal-to-seasonal (S2S) climate forecasts of extreme temperatures could allow for better short-to-medium-term resource management within heat-health action plans, to protect vulnerable populations and ensure access to preventive measures well in advance. The objective of this study is to assess the extent to which S2S climate forecasts could be incorporated into heat-health action plans, to support timely public health decision-making ahead of imminent heat wave events in Europe. Forecasts of apparent temperature at different lead times (e.g., 1 day, 4 days, 8 days, up to 3 months) were used in a mortality model to produce probabilistic mortality forecasts up to several months ahead of the 2003 heat wave event in Europe. Results were compared to mortality predictions, inferred using observed apparent temperature data in the mortality model. In general, we found a decreasing transition in skill between excellent predictions when using observed temperature, to predictions with no skill when using forecast temperature with lead times greater than one week. However, even at lead-times up to three months, there were some regions in Spain and the United Kingdom where excess mortality was detected with some certainty. This suggests that in some areas of Europe, there is potential for S2S climate forecasts to be incorporated in localised heat–health action plans. In general, these results show that the performance of this climate service framework is not limited by the mortality model itself, but rather by the predictability of the climate variables, at S2S time scales, over Europe. PMID:26861369

Evaluation of an Early-Warning System for Heat Wave-Related Mortality in Europe: Implications for Sub-seasonal to Seasonal Forecasting and Climate Services.

PubMed

Lowe, Rachel; García-Díez, Markel; Ballester, Joan; Creswick, James; Robine, Jean-Marie; Herrmann, François R; Rodó, Xavier

2016-02-06

Heat waves have been responsible for more fatalities in Europe over the past decades than any other extreme weather event. However, temperature-related illnesses and deaths are largely preventable. Reliable sub-seasonal-to-seasonal (S2S) climate forecasts of extreme temperatures could allow for better short-to-medium-term resource management within heat-health action plans, to protect vulnerable populations and ensure access to preventive measures well in advance. The objective of this study is to assess the extent to which S2S climate forecasts could be incorporated into heat-health action plans, to support timely public health decision-making ahead of imminent heat wave events in Europe. Forecasts of apparent temperature at different lead times (e.g., 1 day, 4 days, 8 days, up to 3 months) were used in a mortality model to produce probabilistic mortality forecasts up to several months ahead of the 2003 heat wave event in Europe. Results were compared to mortality predictions, inferred using observed apparent temperature data in the mortality model. In general, we found a decreasing transition in skill between excellent predictions when using observed temperature, to predictions with no skill when using forecast temperature with lead times greater than one week. However, even at lead-times up to three months, there were some regions in Spain and the United Kingdom where excess mortality was detected with some certainty. This suggests that in some areas of Europe, there is potential for S2S climate forecasts to be incorporated in localised heat-health action plans. In general, these results show that the performance of this climate service framework is not limited by the mortality model itself, but rather by the predictability of the climate variables, at S2S time scales, over Europe.

TEMPO Early Adopters in Air-Quality Forecasting, Planning and Assessment, Pollution Emissions, Health, Agriculture, and Environmental Impacts: Applications and Decision Support

NASA Astrophysics Data System (ADS)

Newchurch, M.; Zavodsky, B.; Chance, K.; Haynes, J.; Lefer, B. L.; Naeger, A.

2016-12-01

The AQ research community has a long legacy of using space-based observations (e.g., Solar Backscatter Ultraviolet Instrument [SBUV], Global Ozone Monitoring Experiment [GOME], Ozone Monitoring Instrument [OMI], and the Ozone Mapping & Profiler Suite [OMPS]) to study atmospheric chemistry. These measurements have been used to observe day-to-day and year-to-year changes in atmospheric constituents. However, they have not been able to capture the diurnal variability of pollution with enough temporal or spatial fidelity and a low enough latency for regular use by operational decision makers. As a result, the operational AQ community has traditionally relied on ground-based (e.g., collection stations, LIDAR) and airborne observing systems to study tropospheric chemistry. In order to maximize its utility for applications and decision support, there is a need to educate the community about the game-changing potential for the geostationary TEMPO mission well ahead of its expected launch date early in the third decade of this millinium. This NASA mission will engage user communities and enable science across the NASA Applied Science Focus Areas of Health and Air Quality, Disasters, Water Resources, and Ecological Forecasting, In addition, topics discussed will provide opportunities for collaborations extending TEMPO applications to future program areas in Agriculture, Weather and Climate (including Numerical Weather Prediction), Energy, and Oceans.

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.

Medium term municipal solid waste generation prediction by autoregressive integrated moving average

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

Younes, Mohammad K.; Nopiah, Z. M.; Basri, Noor Ezlin A.

2014-09-12

Generally, solid waste handling and management are performed by municipality or local authority. In most of developing countries, local authorities suffer from serious solid waste management (SWM) problems and insufficient data and strategic planning. Thus it is important to develop robust solid waste generation forecasting model. It helps to proper manage the generated solid waste and to develop future plan based on relatively accurate figures. In Malaysia, solid waste generation rate increases rapidly due to the population growth and new consumption trends that characterize the modern life style. This paper aims to develop monthly solid waste forecasting model using Autoregressivemore » Integrated Moving Average (ARIMA), such model is applicable even though there is lack of data and will help the municipality properly establish the annual service plan. The results show that ARIMA (6,1,0) model predicts monthly municipal solid waste generation with root mean square error equals to 0.0952 and the model forecast residuals are within accepted 95% confident interval.« less

Medium term municipal solid waste generation prediction by autoregressive integrated moving average

NASA Astrophysics Data System (ADS)

Younes, Mohammad K.; Nopiah, Z. M.; Basri, Noor Ezlin A.; Basri, Hassan

2014-09-01

Generally, solid waste handling and management are performed by municipality or local authority. In most of developing countries, local authorities suffer from serious solid waste management (SWM) problems and insufficient data and strategic planning. Thus it is important to develop robust solid waste generation forecasting model. It helps to proper manage the generated solid waste and to develop future plan based on relatively accurate figures. In Malaysia, solid waste generation rate increases rapidly due to the population growth and new consumption trends that characterize the modern life style. This paper aims to develop monthly solid waste forecasting model using Autoregressive Integrated Moving Average (ARIMA), such model is applicable even though there is lack of data and will help the municipality properly establish the annual service plan. The results show that ARIMA (6,1,0) model predicts monthly municipal solid waste generation with root mean square error equals to 0.0952 and the model forecast residuals are within accepted 95% confident interval.

Applying Ad Hoc Institutional Research Findings to College Strategic Planning

ERIC Educational Resources Information Center

Clagett, Craig A.

2004-01-01

Environmental scanning, enrollment forecasting, budget analyses, and institutional effectiveness assessment are examples of the explicit contributions institutional research offices make to campus strategic planning.

Project 1990: Educational Planning at the Metropolitan Level.

ERIC Educational Resources Information Center

Swanson, Austin D.; Lamitie, Robert E.

This paper describes a project designed to provide educational decisionmakers with projections of and forecasts about future metropolitan conditions and problems, and information about the implications of alternative ways of solving metropolitan problems. Project components included (1) population and economic projections and forecasts, (2)…

Forecast and capacity planning for Nogales' ports of entry.

DOT National Transportation Integrated Search

2009-12-01

This report documents the findings and the activities performed under ADOT grant JPA 08024T. The overall purpose of this study was to forecast the number of border crossings by mode of traffic at the NogalesMariposa and DeConcini Ports of Entry...

An Interim Update to the 2035 Socioeconomic and Travel Demand Forecasts for Virginia

DOT National Transportation Integrated Search

2012-10-01

In support of the update to Virginias 2035 Statewide Multimodal Plan, this report provides an update to select : socioeconomic forecasts initially made in 2009 based on a review of data from national sources and the literature. Mobility : needs ex...

An interim update to the 2035 socioeconomic and travel demand forecasts for Virginia.

DOT National Transportation Integrated Search

2012-09-01

"In support of the update to Virginias 2035 Statewide Multimodal Plan, this report provides an update to select : socioeconomic forecasts initially made in 2009 based on a review of data from national sources and the literature. Mobility : needs e...

An interim update to the 2035 socioeconomic and travel demand forecasts for Virginia.

DOT National Transportation Integrated Search

2012-10-01

In support of the update to Virginias 2035 Statewide Multimodal Plan, this report provides an update to select : socioeconomic forecasts initially made in 2009 based on a review of data from national sources and the literature. Mobility : needs ex...

A Hybrid Approach on Tourism Demand Forecasting

NASA Astrophysics Data System (ADS)

Nor, M. E.; Nurul, A. I. M.; Rusiman, M. S.

2018-04-01

Tourism has become one of the important industries that contributes to the country’s economy. Tourism demand forecasting gives valuable information to policy makers, decision makers and organizations related to tourism industry in order to make crucial decision and planning. However, it is challenging to produce an accurate forecast since economic data such as the tourism data is affected by social, economic and environmental factors. In this study, an equally-weighted hybrid method, which is a combination of Box-Jenkins and Artificial Neural Networks, was applied to forecast Malaysia’s tourism demand. The forecasting performance was assessed by taking the each individual method as a benchmark. The results showed that this hybrid approach outperformed the other two models

Economic benefits of improved meteorological forecasts - The construction industry

NASA Technical Reports Server (NTRS)

Bhattacharyya, R. K.; Greenberg, J. S.

1976-01-01

Estimates are made of the potential economic benefits accruing to particular industries from timely utilization of satellite-derived six-hour weather forecasts, and of economic penalties resulting from failure to utilize such forecasts in day-to-day planning. The cost estimate study is centered on the U.S. construction industry, with results simplified to yes/no 6-hr forecasts on thunderstorm activity and work/no work decisions. Effects of weather elements (thunderstorms, snow and sleet) on various construction operations are indicated. Potential dollar benefits for other industries, including air transportation and other forms of transportation, are diagrammed for comparison. Geosynchronous satellites such as STORMSAT, SEOS, and SMS/GOES are considered as sources of the forecast data.

Assessing the viability of `over-the-loop' real-time short-to-medium range ensemble streamflow forecasts

NASA Astrophysics Data System (ADS)

Wood, A. W.; Clark, E.; Mendoza, P. A.; Nijssen, B.; Newman, A. J.; Clark, M. P.; Arnold, J.; Nowak, K. C.

2016-12-01

Many if not most national operational short-to-medium range streamflow prediction systems rely on a forecaster-in-the-loop approach in which some parts of the forecast workflow are automated, but others require the hands-on-effort of an experienced human forecaster. This approach evolved out of the need to correct for deficiencies in the models and datasets that were available for forecasting, and often leads to skillful predictions despite the use of relatively simple, conceptual models. On the other hand, the process is not reproducible, which limits opportunities to assess and incorporate process variations, and the effort required to make forecasts in this way is an obstacle to expanding forecast services - e.g., though adding new forecast locations or more frequent forecast updates, running more complex models, or producing forecast ensembles and hindcasts that can support verification. In the last decade, the hydrologic forecasting community has begun to develop more centralized, `over-the-loop' systems. The quality of these new forecast products will depend on their ability to leverage research in areas including earth system modeling, parameter estimation, data assimilation, statistical post-processing, weather and climate prediction, verification, and uncertainty estimation through the use of ensembles. Currently, the operational streamflow forecasting and water management communities have little experience with the strengths and weaknesses of over-the-loop approaches, even as the systems are being rolled out in major operational forecasting centers. There is thus a need both to evaluate these forecasting advances and to demonstrate their potential in a public arena, raising awareness in forecast user communities and development programs alike. To address this need, the National Center for Atmospheric Research is collaborating with the University of Washington, the Bureau of Reclamation and the US Army Corps of Engineers, using the NCAR 'System for Hydromet Analysis, Research, and Prediction' (SHARP) to implement, assess and demonstrate real-time over-the-loop forecasts. We present early hindcast and verification results from SHARP for short to medium range streamflow forecasts in a number of US case study watersheds.

Analyzing Effect of System Inertia on Grid Frequency Forecasting Usnig Two Stage Neuro-Fuzzy System

NASA Astrophysics Data System (ADS)

Chourey, Divyansh R.; Gupta, Himanshu; Kumar, Amit; Kumar, Jitesh; Kumar, Anand; Mishra, Anup

2018-04-01

Frequency forecasting is an important aspect of power system operation. The system frequency varies with load-generation imbalance. Frequency variation depends upon various parameters including system inertia. System inertia determines the rate of fall of frequency after the disturbance in the grid. Though, inertia of the system is not considered while forecasting the frequency of power system during planning and operation. This leads to significant errors in forecasting. In this paper, the effect of inertia on frequency forecasting is analysed for a particular grid system. In this paper, a parameter equivalent to system inertia is introduced. This parameter is used to forecast the frequency of a typical power grid for any instant of time. The system gives appreciable result with reduced error.

Short-term Forecasting Tools for Agricultural Nutrient Management.

PubMed

Easton, Zachary M; Kleinman, Peter J A; Buda, Anthony R; Goering, Dustin; Emberston, Nichole; Reed, Seann; Drohan, Patrick J; Walter, M Todd; Guinan, Pat; Lory, John A; Sommerlot, Andrew R; Sharpley, Andrew

2017-11-01

The advent of real-time, short-term farm management tools is motivated by the need to protect water quality above and beyond the general guidance offered by existing nutrient management plans. Advances in high-performance computing and hydrologic or climate modeling have enabled rapid dissemination of real-time information that can assist landowners and conservation personnel with short-term management planning. This paper reviews short-term decision support tools for agriculture that are under various stages of development and implementation in the United States: (i) Wisconsin's Runoff Risk Advisory Forecast (RRAF) System, (ii) New York's Hydrologically Sensitive Area Prediction Tool, (iii) Virginia's Saturated Area Forecast Model, (iv) Pennsylvania's Fertilizer Forecaster, (v) Washington's Application Risk Management (ARM) System, and (vi) Missouri's Design Storm Notification System. Although these decision support tools differ in their underlying model structure, the resolution at which they are applied, and the hydroclimates to which they are relevant, all provide forecasts (range 24-120 h) of runoff risk or soil moisture saturation derived from National Weather Service Forecast models. Although this review highlights the need for further development of robust and well-supported short-term nutrient management tools, their potential for adoption and ultimate utility requires an understanding of the appropriate context of application, the strategic and operational needs of managers, access to weather forecasts, scales of application (e.g., regional vs. field level), data requirements, and outreach communication structure. Copyright © by the American Society of Agronomy, Crop Science Society of America, and Soil Science Society of America, Inc.

Verification of Meteorological and Oceanographic Ensemble Forecasts in the U.S. Navy

NASA Astrophysics Data System (ADS)

Klotz, S.; Hansen, J.; Pauley, P.; Sestak, M.; Wittmann, P.; Skupniewicz, C.; Nelson, G.

2013-12-01

The Navy Ensemble Forecast Verification System (NEFVS) has been promoted recently to operational status at the U.S. Navy's Fleet Numerical Meteorology and Oceanography Center (FNMOC). NEFVS processes FNMOC and National Centers for Environmental Prediction (NCEP) meteorological and ocean wave ensemble forecasts, gridded forecast analyses, and innovation (observational) data output by FNMOC's data assimilation system. The NEFVS framework consists of statistical analysis routines, a variety of pre- and post-processing scripts to manage data and plot verification metrics, and a master script to control application workflow. NEFVS computes metrics that include forecast bias, mean-squared error, conditional error, conditional rank probability score, and Brier score. The system also generates reliability and Receiver Operating Characteristic diagrams. In this presentation we describe the operational framework of NEFVS and show examples of verification products computed from ensemble forecasts, meteorological observations, and forecast analyses. The construction and deployment of NEFVS addresses important operational and scientific requirements within Navy Meteorology and Oceanography. These include computational capabilities for assessing the reliability and accuracy of meteorological and ocean wave forecasts in an operational environment, for quantifying effects of changes and potential improvements to the Navy's forecast models, and for comparing the skill of forecasts from different forecast systems. NEFVS also supports the Navy's collaboration with the U.S. Air Force, NCEP, and Environment Canada in the North American Ensemble Forecast System (NAEFS) project and with the Air Force and the National Oceanic and Atmospheric Administration (NOAA) in the National Unified Operational Prediction Capability (NUOPC) program. This program is tasked with eliminating unnecessary duplication within the three agencies, accelerating the transition of new technology, such as multi-model ensemble forecasting, to U.S. Department of Defense use, and creating a superior U.S. global meteorological and oceanographic prediction capability. Forecast verification is an important component of NAEFS and NUOPC. Distribution Statement A: Approved for Public Release; distribution is unlimited

Verification of Meteorological and Oceanographic Ensemble Forecasts in the U.S. Navy

NASA Astrophysics Data System (ADS)

Klotz, S. P.; Hansen, J.; Pauley, P.; Sestak, M.; Wittmann, P.; Skupniewicz, C.; Nelson, G.

2012-12-01

The Navy Ensemble Forecast Verification System (NEFVS) has been promoted recently to operational status at the U.S. Navy's Fleet Numerical Meteorology and Oceanography Center (FNMOC). NEFVS processes FNMOC and National Centers for Environmental Prediction (NCEP) meteorological and ocean wave ensemble forecasts, gridded forecast analyses, and innovation (observational) data output by FNMOC's data assimilation system. The NEFVS framework consists of statistical analysis routines, a variety of pre- and post-processing scripts to manage data and plot verification metrics, and a master script to control application workflow. NEFVS computes metrics that include forecast bias, mean-squared error, conditional error, conditional rank probability score, and Brier score. The system also generates reliability and Receiver Operating Characteristic diagrams. In this presentation we describe the operational framework of NEFVS and show examples of verification products computed from ensemble forecasts, meteorological observations, and forecast analyses. The construction and deployment of NEFVS addresses important operational and scientific requirements within Navy Meteorology and Oceanography (METOC). These include computational capabilities for assessing the reliability and accuracy of meteorological and ocean wave forecasts in an operational environment, for quantifying effects of changes and potential improvements to the Navy's forecast models, and for comparing the skill of forecasts from different forecast systems. NEFVS also supports the Navy's collaboration with the U.S. Air Force, NCEP, and Environment Canada in the North American Ensemble Forecast System (NAEFS) project and with the Air Force and the National Oceanic and Atmospheric Administration (NOAA) in the National Unified Operational Prediction Capability (NUOPC) program. This program is tasked with eliminating unnecessary duplication within the three agencies, accelerating the transition of new technology, such as multi-model ensemble forecasting, to U.S. Department of Defense use, and creating a superior U.S. global meteorological and oceanographic prediction capability. Forecast verification is an important component of NAEFS and NUOPC.

Probabilistic eruption forecasting at short and long time scales

NASA Astrophysics Data System (ADS)

Marzocchi, Warner; Bebbington, Mark S.

2012-10-01

Any effective volcanic risk mitigation strategy requires a scientific assessment of the future evolution of a volcanic system and its eruptive behavior. Some consider the onus should be on volcanologists to provide simple but emphatic deterministic forecasts. This traditional way of thinking, however, does not deal with the implications of inherent uncertainties, both aleatoric and epistemic, that are inevitably present in observations, monitoring data, and interpretation of any natural system. In contrast to deterministic predictions, probabilistic eruption forecasting attempts to quantify these inherent uncertainties utilizing all available information to the extent that it can be relied upon and is informative. As with many other natural hazards, probabilistic eruption forecasting is becoming established as the primary scientific basis for planning rational risk mitigation actions: at short-term (hours to weeks or months), it allows decision-makers to prioritize actions in a crisis; and at long-term (years to decades), it is the basic component for land use and emergency planning. Probabilistic eruption forecasting consists of estimating the probability of an eruption event and where it sits in a complex multidimensional time-space-magnitude framework. In this review, we discuss the key developments and features of models that have been used to address the problem.

Timetable of an operational flood forecasting system

NASA Astrophysics Data System (ADS)

Liechti, Katharina; Jaun, Simon; Zappa, Massimiliano

2010-05-01

At present a new underground part of Zurich main station is under construction. For this purpose the runoff capacity of river Sihl, which is passing beneath the main station, is reduced by 40%. If a flood is to occur the construction site is evacuated and gates can be opened for full runoff capacity to prevent bigger damages. However, flooding the construction site, even if it is controlled, is coupled with costs and retardation. The evacuation of the construction site at Zurich main station takes about 2 to 4 hours and opening the gates takes another 1 to 2 hours each. In the upper part of the 336 km2 Sihl catchment the Sihl lake, a reservoir lake, is situated. It belongs and is used by the Swiss Railway Company for hydropower production. This lake can act as a retention basin for about 46% of the Sihl catchment. Lowering the lake level to gain retention capacity, and therewith safety, is coupled with direct loss for the Railway Company. To calculate the needed retention volume and the water to be released facing unfavourable weather conditions, forecasts with a minimum lead time of 2 to 3 days are needed. Since the catchment is rather small, this can only be realised by the use of meteorological forecast data. Thus the management of the construction site depends on accurate forecasts to base their decisions on. Therefore an operational hydrological ensemble prediction system (HEPS) was introduced in September 2008 by the Swiss Federal Institute for Forest, Snow and Landscape Research (WSL). It delivers daily discharge forecasts with a time horizon of 5 days. The meteorological forecasts are provided by MeteoSwiss and stem from the operational limited-area COSMO-LEPS which downscales the ECMWF ensemble prediction system to a spatial resolution of 7 km. Additional meteorological data for model calibration and initialisation (air temperature, precipitation, water vapour pressure, global radiation, wind speed and sunshine duration) and radar data are also provided by MeteoSwiss. Additional meteorological and hydrological observations are provided by a hydropower company, the Canton of Zurich and the Federal Office for the Environment (FOEN). The hydrological forecasting is calculated by the semi-distributed hydrological model PREVAH (Precipitation-Runoff-EVapotranspiration-HRU-related Model) and is further processed by the hydraulic model FLORIS. Finally the forecasts and alerts along with additional meteorological and hydrological observations and forecasts from collaborating institution are sent to a webserver accessible for decision makers. We will document the setup of our operational flood forecasting system, evaluate its performance and show how the collaboration and communication between science and practice, including all the different interests, works for this particular example.

The North American Multi-Model Ensemble (NMME): Phase-1 Seasonal to Interannual Prediction, Phase-2 Toward Developing Intra-Seasonal Prediction

NASA Technical Reports Server (NTRS)

Kirtman, Ben P.; Min, Dughong; Infanti, Johnna M.; Kinter, James L., III; Paolino, Daniel A.; Zhang, Qin; vandenDool, Huug; Saha, Suranjana; Mendez, Malaquias Pena; Becker, Emily;

Accounting for fuel price risk: Using forward natural gas prices instead of gas price forecasts to compare renewable to natural gas-fired generation

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

Bolinger, Mark; Wiser, Ryan; Golove, William

2003-08-13

Against the backdrop of increasingly volatile natural gas prices, renewable energy resources, which by their nature are immune to natural gas fuel price risk, provide a real economic benefit. Unlike many contracts for natural gas-fired generation, renewable generation is typically sold under fixed-price contracts. Assuming that electricity consumers value long-term price stability, a utility or other retail electricity supplier that is looking to expand its resource portfolio (or a policymaker interested in evaluating different resource options) should therefore compare the cost of fixed-price renewable generation to the hedged or guaranteed cost of new natural gas-fired generation, rather than to projectedmore » costs based on uncertain gas price forecasts. To do otherwise would be to compare apples to oranges: by their nature, renewable resources carry no natural gas fuel price risk, and if the market values that attribute, then the most appropriate comparison is to the hedged cost of natural gas-fired generation. Nonetheless, utilities and others often compare the costs of renewable to gas-fired generation using as their fuel price input long-term gas price forecasts that are inherently uncertain, rather than long-term natural gas forward prices that can actually be locked in. This practice raises the critical question of how these two price streams compare. If they are similar, then one might conclude that forecast-based modeling and planning exercises are in fact approximating an apples-to-apples comparison, and no further consideration is necessary. If, however, natural gas forward prices systematically differ from price forecasts, then the use of such forecasts in planning and modeling exercises will yield results that are biased in favor of either renewable (if forwards < forecasts) or natural gas-fired generation (if forwards > forecasts). In this report we compare the cost of hedging natural gas price risk through traditional gas-based hedging instruments (e.g., futures, swaps, and fixed-price physical supply contracts) to contemporaneous forecasts of spot natural gas prices, with the purpose of identifying any systematic differences between the two. Although our data set is quite limited, we find that over the past three years, forward gas prices for durations of 2-10 years have been considerably higher than most natural gas spot price forecasts, including the reference case forecasts developed by the Energy Information Administration (EIA). This difference is striking, and implies that resource planning and modeling exercises based on these forecasts over the past three years have yielded results that are biased in favor of gas-fired generation (again, presuming that long-term stability is desirable). As discussed later, these findings have important ramifications for resource planners, energy modelers, and policy-makers.« less

UPDATE ON DEVELOPMENT OF NUDGING FDDA FOR ADVANCED RESEARCH WRF

EPA Science Inventory

A nudging-based four-dimensional data assimilation (FDDA) system is being developed for the Weather Research and Forecasting (WRF) Model. This effort represents a collaboration between The Pennsylvania State University (i.e., Penn State), the National Center for Atmospheric Rese...

7 CFR 1710.300 - General.

Code of Federal Regulations, 2012 CFR

2012-01-01

... forecast. The forecast should be used by the board of directors and the manager to guide the system towards... projected results of future actions planned by the borrower's board of directors; (2) The financial goals... type of large power loads, projections of future borrowings and the associated interest, projected...

7 CFR 1710.300 - General.

Code of Federal Regulations, 2013 CFR

2013-01-01

... forecast. The forecast should be used by the board of directors and the manager to guide the system towards... projected results of future actions planned by the borrower's board of directors; (2) The financial goals... type of large power loads, projections of future borrowings and the associated interest, projected...

Modeling, Simulation, and Forecasting of Subseasonal Variability

NASA Technical Reports Server (NTRS)

Waliser, Duane; Schubert, Siegfried; Kumar, Arun; Weickmann, Klaus; Dole, Randall

2003-01-01

A planning workshop on "Modeling, Simulation and Forecasting of Subseasonal Variability" was held in June 2003. This workshop was the first of a number of meetings planned to follow the NASA-sponsored workshop entitled "Prospects For Improved Forecasts Of Weather And Short-Term Climate Variability On Sub-Seasonal Time Scales" that was held April 2002. The 2002 workshop highlighted a number of key sources of unrealized predictability on subseasonal time scales including tropical heating, soil wetness, the Madden Julian Oscillation (MJO) [a.k.a Intraseasonal Oscillation (ISO)], the Arctic Oscillation (AO) and the Pacific/North American (PNA) pattern. The overarching objective of the 2003 follow-up workshop was to proceed with a number of recommendations made from the 2002 workshop, as well as to set an agenda and collate efforts in the areas of modeling, simulation and forecasting intraseasonal and short-term climate variability. More specifically, the aims of the 2003 workshop were to: 1) develop a baseline of the "state of the art" in subseasonal prediction capabilities, 2) implement a program to carry out experimental subseasonal forecasts, and 3) develop strategies for tapping the above sources of predictability by focusing research, model development, and the development/acquisition of new observations on the subseasonal problem. The workshop was held over two days and was attended by over 80 scientists, modelers, forecasters and agency personnel. The agenda of the workshop focused on issues related to the MJO and tropicalextratropical interactions as they relate to the subseasonal simulation and prediction problem. This included the development of plans for a coordinated set of GCM hindcast experiments to assess current model subseasonal prediction capabilities and shortcomings, an emphasis on developing a strategy to rectify shortcomings associated with tropical intraseasonal variability, namely diabatic processes, and continuing the implementation of an experimental forecast and model development program that focuses on one of the key sources of untapped predictability, namely the MJO. The tangible outcomes of the meeting included: 1) the development of a recommended framework for a set of multi-year ensembles of 45-day hindcasts to be carried out by a number of GCMs so that they can be analyzed in regards to their representations of subseasonal variability, predictability and forecast skill, 2) an assessment of the present status of GCM representations of the MJO and recommendations for future steps to take in order to remedy the remaining shortcomings in these representations, and 3) a final implementation plan for a multi-institute/multi-nation Experimental MJO Prediction Program.

Review of travel data issues in VDOT's Transportation Planning Division.

DOT National Transportation Integrated Search

1991-01-01

The Transportation Planning Division (TPD) of the Virginia Department of Transportation uses an extensive amount of travel data in both its routine planning activities and its provision of data forecasts to other divisions. Travel data consist of suc...

A Global Aerosol Model Forecast for the ACE-Asia Field Experiment

NASA Technical Reports Server (NTRS)

Chin, Mian; Ginoux, Paul; Lucchesi, Robert; Huebert, Barry; Weber, Rodney; Anderson, Tad; Masonis, Sarah; Blomquist, Byron; Bandy, Alan; Thornton, Donald

2003-01-01

We present the results of aerosol forecast during the Aerosol Characterization Experiment (ACE-Asia) field experiment in spring 2001, using the Georgia Tech/Goddard Global Ozone Chemistry Aerosol Radiation and Transport (GOCART) model and the meteorological forecast fields from the Goddard Earth Observing System Data Assimilation System (GEOS DAS). The aerosol model forecast provides direct information on aerosol optical thickness and concentrations, enabling effective flight planning, while feedbacks from measurements constantly evaluate the model, making successful model improvements. We verify the model forecast skill by comparing model predicted total aerosol extinction, dust, sulfate, and SO2 concentrations with those quantities measured by the C-130 aircraft during the ACE-Asia intensive operation period. The GEOS DAS meteorological forecast system shows excellent skills in predicting winds, relative humidity, and temperature for the ACE-Asia experiment area as well as for each individual flight, with skill scores usually above 0.7. The model is also skillful in forecast of pollution aerosols, with most scores above 0.5. The model correctly predicted the dust outbreak events and their trans-Pacific transport, but it constantly missed the high dust concentrations observed in the boundary layer. We attribute this missing dust source to the desertification regions in the Inner Mongolia Province in China, which have developed in recent years but were not included in the model during forecasting. After incorporating the desertification sources, the model is able to reproduce the observed high dust concentrations at low altitudes over the Yellow Sea. Two key elements for a successful aerosol model forecast are correct source locations that determine where the emissions take place, and realistic forecast winds and convection that determine where the aerosols are transported. We demonstrate that our global model can not only account for the large-scale intercontinental transport, but also produce the small-scale spatial and temporal variations that are adequate for aircraft measurements planning.

Space Weather Modeling at the Community Coordinated Modeling Center

NASA Astrophysics Data System (ADS)

Hesse, M.; Falasca, A.; Johnson, J.; Keller, K.; Kuznetsova, M.; Rastaetter, L.

2003-04-01

The Community Coordinated Modeling Center (CCMC) is a multi-agency partnership aimed at the creation of next generation space weather models. The goal of the CCMC is to support the research and developmental work necessary to substantially increase the present-day modeling capability for space weather purposes, and to provide models for transition to the rapid prototyping centers at the space weather forecast centers. This goal requires close collaborations with and substantial involvement of the research community. The physical regions to be addressed by CCMC-related activities range from the solar atmosphere to the Earth's upper atmosphere. The CCMC is an integral part of NASA's Living With a Star (LWS) initiative, of the National Space Weather Program Implementation Plan, and of the Department of Defense Space Weather Transition Plan. CCMC includes a facility at NASA Goddard Space Flight Center, as well as distributed computing facilities provided by the US Air Force. CCMC also provides, to the research community, access to state-of-the-art space research models. In this paper we will provide updates on CCMC status, on current plans, research and development accomplishments and goals, and on the model testing and validation process undertaken as part of the CCMC mandate. We will demonstrate the capabilities of models resident at CCMC via the analysis of a geomagnetic storm, driven by a shock in the solar wind.

The attitudinal and cognitive effects of interdisciplinary collaboration on elementary pre-service teachers development of biological science related lesson plans

NASA Astrophysics Data System (ADS)

Mills, Jada Jamerson

There is a need for STEM (science, technology, engineering, and mathematics) education to be taught effectively in elementary schools. In order to achieve this, teacher preparation programs should graduate confident, content strong teachers to convey knowledge to elementary students. This study used interdisciplinary collaboration between the School of Education and the College of Liberal Arts through a Learning-by-Teaching method (LdL): Lernen durch Lernen in German. Pre-service teacher (PST) achievement levels of understanding science concepts based on pretest and posttest data, quality of lesson plans developed, and enjoyment of the class based on the collaboration with science students. The PSTs enrolled in two treatment sections of EDEL 404: Science in the Elementary Classroom collaborated with science students enrolled in BISC 327: Introductory Neuroscience to enhance their science skills and create case-based lesson plans on neurothology topics: echolocation, electrosensory reception, steroid hormones, and vocal learning. The PSTs enrolled in the single control section of EDEL 404 collaborated with fellow elementary education majors to develop lesson plans also based on the same selected topics. Qualitative interviews of education faculty, science faculty, and PSTs provided depth to the quantitative findings. Upon lesson plan completion, in-service teachers also graded the two best and two worst plans for the treatment and control sections and a science reviewer graded the plans for scientific accuracy. Statistical analyses were conducted for hypotheses, and one significant hypothesis found that PSTs who collaborated with science students had more positive science lesson plan writing attitudes than those who did not. Despite overall insignificant statistical analyses, all PSTs responded as more confident after collaboration. Additionally, interviews provided meaning and understanding to the insignificant statistical results as well as scientific accuracy of the lesson plans.

Uses and Applications of Climate Forecasts for Power Utilities.

NASA Astrophysics Data System (ADS)

Changnon, Stanley A.; Changnon, Joyce M.; Changnon, David

1995-05-01

The uses and potential applications of climate forecasts for electric and gas utilities were assessed 1) to discern needs for improving climate forecasts and guiding future research, and 2) to assist utilities in making wise use of forecasts. In-depth structured interviews were conducted with 56 decision makers in six utilities to assess existing and potential uses of climate forecasts. Only 3 of the 56 use forecasts. Eighty percent of those sampled envisioned applications of climate forecasts, given certain changes and additional information. Primary applications exist in power trading, load forecasting, fuel acquisition, and systems planning, with slight differences in interests between utilities. Utility staff understand probability-based forecasts but desire climatological information related to forecasted outcomes, including analogs similar to the forecasts, and explanations of the forecasts. Desired lead times vary from a week to three months, along with forecasts of up to four seasons ahead. The new NOAA forecasts initiated in 1995 provide the lead times and longer-term forecasts desired. Major hindrances to use of forecasts are hard-to-understand formats, lack of corporate acceptance, and lack of access to expertise. Recent changes in government regulations altered the utility industry, leading to a more competitive world wherein information about future weather conditions assumes much more value. Outreach efforts by government forecast agencies appear valuable to help achieve the appropriate and enhanced use of climate forecasts by the utility industry. An opportunity for service exists also for the private weather sector.

Short-Term Forecasts Using NU-WRF for the Winter Olympics 2018

NASA Technical Reports Server (NTRS)

Srikishen, Jayanthi; Case, Jonathan L.; Petersen, Walter A.; Iguchi, Takamichi; Tao, Wei-Kuo; Zavodsky, Bradley T.; Molthan, Andrew

2017-01-01

The NASA Unified-Weather Research and Forecasting model (NU-WRF) will be included for testing and evaluation in the forecast demonstration project (FDP) of the International Collaborative Experiment -PyeongChang 2018 Olympic and Paralympic (ICE-POP) Winter Games. An international array of radar and supporting ground based observations together with various forecast and now-cast models will be operational during ICE-POP. In conjunction with personnel from NASA's Goddard Space Flight Center, the NASA Short-term Prediction Research and Transition (SPoRT) Center is developing benchmark simulations for a real-time NU-WRF configuration to run during the FDP. ICE-POP observational datasets will be used to validate model simulations and investigate improved model physics and performance for prediction of snow events during the research phase (RDP) of the project The NU-WRF model simulations will also support NASA Global Precipitation Measurement (GPM) Mission ground-validation physical and direct validation activities in relation to verifying, testing and improving satellite-based snowfall retrieval algorithms over complex terrain.

Climate forecasts in disaster management: Red Cross flood operations in West Africa, 2008.

PubMed

Braman, Lisette Martine; van Aalst, Maarten Krispijn; Mason, Simon J; Suarez, Pablo; Ait-Chellouche, Youcef; Tall, Arame

2013-01-01

In 2008, the International Federation of Red Cross and Red Crescent Societies (IFRC) used a seasonal forecast for West Africa for the first time to implement an Early Warning, Early Action strategy for enhanced flood preparedness and response. Interviews with disaster managers suggest that this approach improved their capacity and response. Relief supplies reached flood victims within days, as opposed to weeks in previous years, thereby preventing further loss of life, illness, and setbacks to livelihoods, as well as augmenting the efficiency of resource use. This case demonstrates the potential benefits to be realised from the use of medium-to-long-range forecasts in disaster management, especially in the context of potential increases in extreme weather and climate-related events due to climate variability and change. However, harnessing the full potential of these forecasts will require continued effort and collaboration among disaster managers, climate service providers, and major humanitarian donors. © 2013 The Author(s). Journal compilation © Overseas Development Institute, 2013.

DEVELOPMENT OF NEAR-SHORE HYDRODYNAMIC MODELS FOR BEACH CLOSURE FORECASTING IN THE GREAT LAKES

EPA Science Inventory

Water quality managers and other planning and decision entities are increasingly calling for up-to-the-minute data on present water quality conditions or forecasts of these data that can be used to adjust or respond to quickly developing activities with environmental implications...

Introduction to Agricultural Marketing.

ERIC Educational Resources Information Center

Futrell, Gene; And Others

This marketing unit focuses on the importance of forecasting in order for a farm family to develop marketing plans. It describes sources of information and includes a glossary of marketing terms and exercises using both fundamental and technical methods to predict prices in order to improve forecasting ability. The unit is organized in the…

7 CFR 1710.206 - Approval requirements for load forecasts prepared pursuant to approved load forecast work plans.

Code of Federal Regulations, 2012 CFR

2012-01-01

... effects on electric revenues caused by competition from alternative energy sources or other electric... uncertainty or alternative futures that may determine the borrower's actual loads. Examples of economic... basis. Include alternative futures, as applicable. This summary shall be designed to accommodate the...

7 CFR 1710.206 - Approval requirements for load forecasts prepared pursuant to approved load forecast work plans.

Code of Federal Regulations, 2014 CFR

2014-01-01

... effects on electric revenues caused by competition from alternative energy sources or other electric... uncertainty or alternative futures that may determine the borrower's actual loads. Examples of economic... basis. Include alternative futures, as applicable. This summary shall be designed to accommodate the...

7 CFR 1710.206 - Approval requirements for load forecasts prepared pursuant to approved load forecast work plans.

Code of Federal Regulations, 2011 CFR

2011-01-01

... effects on electric revenues caused by competition from alternative energy sources or other electric... uncertainty or alternative futures that may determine the borrower's actual loads. Examples of economic... basis. Include alternative futures, as applicable. This summary shall be designed to accommodate the...

7 CFR 1710.206 - Approval requirements for load forecasts prepared pursuant to approved load forecast work plans.

Code of Federal Regulations, 2013 CFR

2013-01-01

... effects on electric revenues caused by competition from alternative energy sources or other electric... uncertainty or alternative futures that may determine the borrower's actual loads. Examples of economic... basis. Include alternative futures, as applicable. This summary shall be designed to accommodate the...

Information Manpower Forecasting. Papers Presented at the FID/ET Seminar (Espoo, Finland, August 24-27, 1988).

ERIC Educational Resources Information Center

Dosa, Marta L., Ed.; Froehlich, Thomas J., Ed.

This collection contains 20 papers written by educators, administrators and information scientists who had conducted manpower surveys in the library and information fields: (1) "Background and Evolution of Educational Planning and Forecasting for Information Manpower" (Yves Courrier); (2) "Indicators for the Emerging Information…

Forecast Occupational Supply: A Methodological Handbook.

ERIC Educational Resources Information Center

McKinlay, Bruce; Johnson, Lowell E.

Greater concern with unemployment in recent years has increased the need for accurate forecasting of future labor market requirements, in order to plan for vocational education and other manpower programs. However, past emphasis has been placed on labor demand, rather than supply, even though either side by itself is useless in determining skill…

Socio-Political Forecasting: Who Needs It?

ERIC Educational Resources Information Center

Burnett, D. Jack

1978-01-01

Socio-political forecasting, a new dimension to university planning that can provide universities time to prepare for the impact of social and political changes, is examined. The four elements in the process are scenarios of the future, the probability/diffusion matrix, the profile of significant value-system changes, and integration and…

46 CFR 45.191 - Pre-departure requirements.

Code of Federal Regulations, 2010 CFR

2010-10-01

... voyage, the towing vessel master must conduct the following: (a) Weather forecast. Determine the marine weather forecast along the planned route, and contact the dock operator at the destination port to get an update on local weather conditions. (b) Inspection. Inspect each barge of the tow to ensure that they...

Social science to improve fuels management: a synthesis of research on collaboration.

Treesearch

Victoria Sturtevant; Margaret Ann Moote; Pamela Jakes; Anthony S. Cheng

2005-01-01

A series of syntheses were commissioned by the USDA Forest Service to aid in fuels mitigation project planning. This synthesis focuses on collaboration research, and offers knowledge and tools to improve collaboration in the planning and implementation of wildland fire and fuels management projects. It covers a variety of topics including benefits of collaboration,...

Distributed collaborative environments for virtual capability-based planning

NASA Astrophysics Data System (ADS)

McQuay, William K.

2003-09-01

Distributed collaboration is an emerging technology that will significantly change how decisions are made in the 21st century. Collaboration involves two or more geographically dispersed individuals working together to share and exchange data, information, knowledge, and actions. The marriage of information, collaboration, and simulation technologies provides the decision maker with a collaborative virtual environment for planning and decision support. This paper reviews research that is focusing on the applying open standards agent-based framework with integrated modeling and simulation to a new Air Force initiative in capability-based planning and the ability to implement it in a distributed virtual environment. Virtual Capability Planning effort will provide decision-quality knowledge for Air Force resource allocation and investment planning including examining proposed capabilities and cost of alternative approaches, the impact of technologies, identification of primary risk drivers, and creation of executable acquisition strategies. The transformed Air Force business processes are enabled by iterative use of constructive and virtual modeling, simulation, and analysis together with information technology. These tools are applied collaboratively via a technical framework by all the affected stakeholders - warfighter, laboratory, product center, logistics center, test center, and primary contractor.

Performance of time-series methods in forecasting the demand for red blood cell transfusion.

PubMed

Pereira, Arturo

2004-05-01

Planning the future blood collection efforts must be based on adequate forecasts of transfusion demand. In this study, univariate time-series methods were investigated for their performance in forecasting the monthly demand for RBCs at one tertiary-care, university hospital. Three time-series methods were investigated: autoregressive integrated moving average (ARIMA), the Holt-Winters family of exponential smoothing models, and one neural-network-based method. The time series consisted of the monthly demand for RBCs from January 1988 to December 2002 and was divided into two segments: the older one was used to fit or train the models, and the younger to test for the accuracy of predictions. Performance was compared across forecasting methods by calculating goodness-of-fit statistics, the percentage of months in which forecast-based supply would have met the RBC demand (coverage rate), and the outdate rate. The RBC transfusion series was best fitted by a seasonal ARIMA(0,1,1)(0,1,1)(12) model. Over 1-year time horizons, forecasts generated by ARIMA or exponential smoothing laid within the +/- 10 percent interval of the real RBC demand in 79 percent of months (62% in the case of neural networks). The coverage rate for the three methods was 89, 91, and 86 percent, respectively. Over 2-year time horizons, exponential smoothing largely outperformed the other methods. Predictions by exponential smoothing laid within the +/- 10 percent interval of real values in 75 percent of the 24 forecasted months, and the coverage rate was 87 percent. Over 1-year time horizons, predictions of RBC demand generated by ARIMA or exponential smoothing are accurate enough to be of help in the planning of blood collection efforts. For longer time horizons, exponential smoothing outperforms the other forecasting methods.

Forecasting Cool Season Daily Peak Winds at Kennedy Space Center and Cape Canaveral Air Force Station

NASA Technical Reports Server (NTRS)

Barrett, Joe, III; Short, David; Roeder, William

2008-01-01

The expected peak wind speed for the day is an important element in the daily 24-Hour and Weekly Planning Forecasts issued by the 45th Weather Squadron (45 WS) for planning operations at Kennedy Space Center (KSC) and Cape Canaveral Air Force Station (CCAFS). The morning outlook for peak speeds also begins the warning decision process for gusts ^ 35 kt, ^ 50 kt, and ^ 60 kt from the surface to 300 ft. The 45 WS forecasters have indicated that peak wind speeds are a challenging parameter to forecast during the cool season (October-April). The 45 WS requested that the Applied Meteorology Unit (AMU) develop a tool to help them forecast the speed and timing of the daily peak and average wind, from the surface to 300 ft on KSC/CCAFS during the cool season. The tool must only use data available by 1200 UTC to support the issue time of the Planning Forecasts. Based on observations from the KSC/CCAFS wind tower network, surface observations from the Shuttle Landing Facility (SLF), and CCAFS upper-air soundings from the cool season months of October 2002 to February 2007, the AMU created multiple linear regression equations to predict the timing and speed of the daily peak wind speed, as well as the background average wind speed. Several possible predictors were evaluated, including persistence, the temperature inversion depth, strength, and wind speed at the top of the inversion, wind gust factor (ratio of peak wind speed to average wind speed), synoptic weather pattern, occurrence of precipitation at the SLF, and strongest wind in the lowest 3000 ft, 4000 ft, or 5000 ft. Six synoptic patterns were identified: 1) surface high near or over FL, 2) surface high north or east of FL, 3) surface high south or west of FL, 4) surface front approaching FL, 5) surface front across central FL, and 6) surface front across south FL. The following six predictors were selected: 1) inversion depth, 2) inversion strength, 3) wind gust factor, 4) synoptic weather pattern, 5) occurrence of precipitation at the SLF, and 6) strongest wind in the lowest 3000 ft. The forecast tool was developed as a graphical user interface with Microsoft Excel to help the forecaster enter the variables, and run the appropriate regression equations. Based on the forecaster's input and regression equations, a forecast of the day's peak and average wind is generated and displayed. The application also outputs the probability that the peak wind speed will be ^ 35 kt, 50 kt, and 60 kt.

From Forecasters to the General Public: A Communication Tool to Understand Decision-making Challenges in Weather-related Early Warning Systems

NASA Astrophysics Data System (ADS)

Terti, G.; Ruin, I.; Kalas, M.; Lorini, V.; Sabbatini, T.; i Alonso, A. C.

2017-12-01

New technologies are currently adopted worldwide to improve weather forecasts and communication of the corresponding warnings to the end-users. "EnhANcing emergency management and response to extreme WeatHER and climate Events" (ANYWHERE) project is an innovating action that aims at developing and implementing a European decision-support platform for weather-related risks integrating cutting-edge forecasting technology. The initiative is built in a collaborative manner where researchers, developers, potential users and other stakeholders meet frequently to define needs, capabilities and challenges. In this study, we propose a role-playing game to test the added value of the ANYWHERE platform on i) the decision-making process and the choice of warning levels under uncertainty, ii) the management of the official emergency response and iii) the crisis communication and triggering of protective actions at different levels of the warning system (from hazard detection to citizen response). The designed game serves as an interactive communication tool. Here, flood and flash flood focused simulations seek to enhance participant's understanding of the complexities and challenges embedded in various levels of the decision-making process under the threat of weather disasters (e.g., forecasting/warnings, official emergency actions, self-protection). Also, we facilitate collaboration and coordination between the participants who belong to different national or local agencies/authorities across Europe. The game is first applied and tested in ANYWHERE's workshop in Helsinki (September, 2017) where about 30-50 people, including researchers, forecasters, civil protection and representatives of related companies, are anticipated to play the simulation. The main idea is to provide to the players a virtual case study that well represents realistic uncertainties and dilemmas embedded in the real-time forecasting-warning processes. At the final debriefing step the participants are encouraged to exchange knowledge, thoughts and insights on their capability or difficulty to decide and communicate their action based on the available information and given constrains. Such feedback will be analyzed and presented and future potentialities for the application of the game will be discussed.

National Centers for Environmental Prediction

Science.gov Websites

/ VISION | About EMC EMC > GEFS > COLLABORATORS Home Operational Products Experimental Data ENSEMBLE FORECAST SYSTEM MSC NAEFS Products CPC NAEFS Experimental 8 to 14 Day Temperature Guidance CPC NAEFS Experimental 8 to 14 Day Precip Guidance NOAA / National Weather Service National Centers for

Forecast-Informed Reservoir Operations: Lessons Learned from a Multi-Agency Collaborative Research and Operations Effort to improve Flood Risk Management, Water Supply and Environmental Benefits

NASA Astrophysics Data System (ADS)

Talbot, C. A.; Ralph, M.; Jasperse, J.; Forbis, J.

2017-12-01

Lessons learned from the multi-agency Forecast-Informed Reservoir Operations (FIRO) effort demonstrate how research and observations can inform operations and policy decisions at Federal, State and Local water management agencies with the collaborative engagement and support of researchers, engineers, operators and stakeholders. The FIRO steering committee consists of scientists, engineers and operators from research and operational elements of the National Oceanographic and Atmospheric Administration and the US Army Corps of Engineers, researchers from the US Geological Survey and the US Bureau of Reclamation, the state climatologist from the California Department of Water Resources, the chief engineer from the Sonoma County Water Agency, and the director of the Scripps Institution of Oceanography's Center for Western Weather and Water Extremes at the University of California-San Diego. The FIRO framework also provides a means of testing and demonstrating the benefits of next-generation water cycle observations, understanding and models in water resources operations.

Advancing Data Assimilation in Operational Hydrologic Forecasting: Progresses, Challenges, and Emerging Opportunities

NASA Technical Reports Server (NTRS)

Liu, Yuqiong; Weerts, A.; Clark, M.; Hendricks Franssen, H.-J; Kumar, S.; Moradkhani, H.; Seo, D.-J.; Schwanenberg, D.; Smith, P.; van Dijk, A. I. J. M.;

Suggestions for Formulating Collaborative Remote Sensing Emergency Plan Based on Case Studies

NASA Astrophysics Data System (ADS)

Liu, B.; Wang, F.; Zheng, X.; Qi, M.

2017-09-01

With the rapid development of the Remote Sensing (RS) technology, Remote Sensing Services for Emergency Monitoring (RSSEM) are playing a more and more important role in the field of emergency management, where the collaborative RS approaches (including such as Space-Air-Ground platforms) can provide the decision-makers a quick access to the detailed, real-time information about the emergencies. However, there are still some problems in the current mechanism of RSSEM, for example, the inappropriate choices of the collaborative RS approaches, the miscellaneous procedures and so on. It is urgent to formulate a collaborative RS emergency plan for regulating the applications of the RS monitoring approaches in order to be well prepared for the emergency management. In our studies, creating a good collaborative RS emergency plan is the main research objective. This paper is divided into four parts. The Part Ⅰ gives a brief introduction about the research background. The Part Ⅱ investigates four case studies to analyze the applications of the RS technologies under the guidance of the available RS related emergency plans, and then points out the existing problems in the mechanism of the RSSEM. The Part Ⅲ proposes our suggestions for formulating the collaborative RS emergency plan to explore the countermeasures of the problems pointed out in the Part Ⅱ. The last part concludes this paper and discusses the future work of the collaborative RS emergency plan.

Using Seasonal Forecasting Data for Vessel Routing

NASA Astrophysics Data System (ADS)

Bell, Ray; Kirtman, Ben

2017-04-01

We present an assessment of seasonal forecasting of surface wind speed, significant wave height and ocean surface current speed in the North Pacific for potential use of vessel routing from Singapore to San Diego. WaveWatchIII is forced with surface winds and ocean surface currents from the Community Climate System Model 4 (CCSM4) retrospective forecasts for the period of 1982-2015. Several lead time forecasts are used from zero months to six months resulting in 2,720 model years, ensuring the findings from this study are robust. July surface wind speed and significant wave height can be skillfully forecast with a one month lead time, with the western North Pacific being the most predictable region. Beyond May initial conditions (lead time of two months) the El Niño Southern Oscillation (ENSO) Spring predictability barrier limits skill of significant wave height but there is skill for surface wind speed with January initial conditions (lead time of six months). In a separate study of vessel routing between Norfolk, Virginia and Gibraltar we demonstrate the benefit of a multimodel approach using the North American Multimodel Ensemble (NMME). In collaboration with Charles River Analytics an all-encompassing forecast is presented by using machine learning on the various ensembles which can be using used for industry applications.

Research to Operations of Ionospheric Scintillation Detection and Forecasting

NASA Astrophysics Data System (ADS)

Jones, J.; Scro, K.; Payne, D.; Ruhge, R.; Erickson, B.; Andorka, S.; Ludwig, C.; Karmann, J.; Ebelhar, D.

Ionospheric Scintillation refers to random fluctuations in phase and amplitude of electromagnetic waves caused by a rapidly varying refractive index due to turbulent features in the ionosphere. Scintillation of transionospheric UHF and L-Band radio frequency signals is particularly troublesome since this phenomenon can lead to degradation of signal strength and integrity that can negatively impact satellite communications and navigation, radar, or radio signals from other systems that traverse or interact with the ionosphere. Although ionospheric scintillation occurs in both the equatorial and polar regions of the Earth, the focus of this modeling effort is on equatorial scintillation. The ionospheric scintillation model is data-driven in a sense that scintillation observations are used to perform detection and characterization of scintillation structures. These structures are then propagated to future times using drift and decay models to represent the natural evolution of ionospheric scintillation. The impact on radio signals is also determined by the model and represented in graphical format to the user. A frequency scaling algorithm allows for impact analysis on frequencies other than the observation frequencies. The project began with lab-grade software and through a tailored Agile development process, deployed operational-grade code to a DoD operational center. The Agile development process promotes adaptive promote adaptive planning, evolutionary development, early delivery, continuous improvement, regular collaboration with the customer, and encourage rapid and flexible response to customer-driven changes. The Agile philosophy values individuals and interactions over processes and tools, working software over comprehensive documentation, customer collaboration over contract negotiation, and responding to change over following a rigid plan. The end result was an operational capability that met customer expectations. Details of the model and the process of operational integration are discussed as well as lessons learned to improve performance on future projects.

Towards a framework for geospatial tangible user interfaces in collaborative urban planning

NASA Astrophysics Data System (ADS)

Maquil, Valérie; Leopold, Ulrich; De Sousa, Luís Moreira; Schwartz, Lou; Tobias, Eric

2018-04-01

The increasing complexity of urban planning projects today requires new approaches to better integrate stakeholders with different professional backgrounds throughout a city. Traditional tools used in urban planning are designed for experts and offer little opportunity for participation and collaborative design. This paper introduces the concept of geospatial tangible user interfaces (GTUI) and reports on the design and implementation as well as the usability of such a GTUI to support stakeholder participation in collaborative urban planning. The proposed system uses physical objects to interact with large digital maps and geospatial data projected onto a tabletop. It is implemented using a PostGIS database, a web map server providing OGC web services, the computer vision framework reacTIVision, a Java-based TUIO client, and GeoTools. We describe how a GTUI has be instantiated and evaluated within the scope of two case studies related to real world collaborative urban planning scenarios. Our results confirm the feasibility of our proposed GTUI solutions to (a) instantiate different urban planning scenarios, (b) support collaboration, and (c) ensure an acceptable usability.

Towards a framework for geospatial tangible user interfaces in collaborative urban planning

NASA Astrophysics Data System (ADS)

Maquil, Valérie; Leopold, Ulrich; De Sousa, Luís Moreira; Schwartz, Lou; Tobias, Eric

2018-03-01

The increasing complexity of urban planning projects today requires new approaches to better integrate stakeholders with different professional backgrounds throughout a city. Traditional tools used in urban planning are designed for experts and offer little opportunity for participation and collaborative design. This paper introduces the concept of geospatial tangible user interfaces (GTUI) and reports on the design and implementation as well as the usability of such a GTUI to support stakeholder participation in collaborative urban planning. The proposed system uses physical objects to interact with large digital maps and geospatial data projected onto a tabletop. It is implemented using a PostGIS database, a web map server providing OGC web services, the computer vision framework reacTIVision, a Java-based TUIO client, and GeoTools. We describe how a GTUI has be instantiated and evaluated within the scope of two case studies related to real world collaborative urban planning scenarios. Our results confirm the feasibility of our proposed GTUI solutions to (a) instantiate different urban planning scenarios, (b) support collaboration, and (c) ensure an acceptable usability.

Environmental predictors of stunting among children under-five in Somalia: cross-sectional studies from 2007 to 2010.

PubMed

Kinyoki, Damaris K; Berkley, James A; Moloney, Grainne M; Odundo, Elijah O; Kandala, Ngianga-Bakwin; Noor, Abdisalan M

2016-07-28

Stunting among children under five years old is associated with long-term effects on cognitive development, school achievement, economic productivity in adulthood and maternal reproductive outcomes. Accurate estimation of stunting and tools to forecast risk are key to planning interventions. We estimated the prevalence and distribution of stunting among children under five years in Somalia from 2007 to 2010 and explored the role of environmental covariates in its forecasting. Data from household nutritional surveys in Somalia from 2007 to 2010 with a total of 1,066 clusters covering 73,778 children were included. We developed a Bayesian hierarchical space-time model to forecast stunting by using the relationship between observed stunting and environmental covariates in the preceding years. We then applied the model coefficients to environmental covariates in subsequent years. To determine the accuracy of the forecasting, we compared this model with a model that used data from all the years with the corresponding environmental covariates. Rainfall (OR = 0.994, 95 % Credible interval (CrI): 0.993, 0.995) and vegetation cover (OR = 0.719, 95 % CrI: 0.603, 0.858) were significant in forecasting stunting. The difference in estimates of stunting using the two approaches was less than 3 % in all the regions for all forecast years. Stunting in Somalia is spatially and temporally heterogeneous. Rainfall and vegetation are major drivers of these variations. The use of environmental covariates for forecasting of stunting is a potentially useful and affordable tool for planning interventions to reduce the high burden of malnutrition in Somalia.

A Collaborative, Ongoing University Strategic Planning Framework: Process, Landmines, and Lessons

ERIC Educational Resources Information Center

Hill, Susan E. Kogler; Thomas, Edward G.; Keller, Lawrence F.

2009-01-01

This article examines the strategic planning process at Cleveland State University, a large metropolitan state university in Ohio. A faculty-administrative team used a communicative planning approach to develop a collaborative, ongoing, bottom-up, transparent strategic planning process. This team then spearheaded the process through plan…

Collaborative Planning in Process: An Ethnomethodological Perspective

ERIC Educational Resources Information Center

Lee, Josephine; Burch, Alfred Rue

2017-01-01

Following Ellis's (2005) call for more social and process-oriented planning research, this study explores how learners approach collaborative planning tasks in the classroom as a locally contingent activity in situ. Drawing on ethnomethodology and conversation analysis, the present study focuses on a group planning stage that precedes the final…

Stochastic Simulations of Long-Range Forecasting Models for Less Developed Regions

DTIC Science & Technology

1975-06-01

descriptors—nation national alignment, internal insl; less developed regions of Africa, report describes (1) the regions’ (2) the strategic importance of...imr.T.ARSTFTi?n SPI unty ( I,is*iif it at i 3200.0 (Att ] to End l) Mar 7, 66 *. ( * y. o 1 < n i Forecasting for Planning Strategic Importance...the long range. The forecasts that have been produced so far have been direct inputs into the Joint Long-Range Strategic Study (JLRSS), prepared by

A plan for the economic assessment of the benefits of improved meteorological forecasts

NASA Technical Reports Server (NTRS)

Bhattacharyya, R.; Greenberg, J.

1975-01-01

Benefit-cost relationships for the development of meteorological satellites are outlined. The weather forecast capabilities of the various weather satellites (Tiros, SEOS, Nimbus) are discussed, and the development of additional satellite systems is examined. A rational approach is development that leads to the establishment of the economic benefits which may result from the utilization of meteorological satellite data. The economic and social impacts of improved weather forecasting for industries and resources management are discussed, and significant weather sensitive industries are listed.

Business Planning in the Light of Neuro-fuzzy and Predictive Forecasting

NASA Astrophysics Data System (ADS)

Chakrabarti, Prasun; Basu, Jayanta Kumar; Kim, Tai-Hoon

In this paper we have pointed out gain sensing on forecast based techniques.We have cited an idea of neural based gain forecasting. Testing of sequence of gain pattern is also verifies using statsistical analysis of fuzzy value assignment. The paper also suggests realization of stable gain condition using K-Means clustering of data mining. A new concept of 3D based gain sensing has been pointed out. The paper also reveals what type of trend analysis can be observed for probabilistic gain prediction.

Integrated urban systems model with multiple transportation supply agents.

DOT National Transportation Integrated Search

2012-10-01

This project demonstrates the feasibility of developing quantitative models that can forecast future networks under : current and alternative transportation planning processes. The current transportation planning process is modeled : based on empiric...

GIS and Transportation Planning

DOT National Transportation Integrated Search

1998-09-16

Two main objectives of transportation planning are to simulate the current : traffic volume and to forecast the future traffic volume on a transportation : network. Traffic demand modeling typically consists of the following : tasks (1)defining traff...

Randomized controlled trial of a health plan-level mood disorders psychosocial intervention for solo or small practices.

PubMed

Kilbourne, Amy M; Nord, Kristina M; Kyle, Julia; Van Poppelen, Celeste; Goodrich, David E; Kim, Hyungjin Myra; Eisenberg, Daniel; Un, Hyong; Bauer, Mark S

2014-01-01

Mood disorders represent the most expensive mental disorders for employer-based commercial health plans. Collaborative care models are effective in treating chronic physical and mental illnesses at little to no net healthcare cost, but to date have primarily been implemented by larger healthcare organizations in facility-based models. The majority of practices providing commercially insured care are far too small to implement such models. Health plan-level collaborative care treatment can address this unmet need. The goal of this study is to implement at the national commercial health plan level a collaborative care model to improve outcomes for persons with mood disorders. A randomized controlled trial of a collaborative care model versus usual care will be conducted among beneficiaries of a large national health plan from across the country seen by primary care or behavioral health practices. At discharge 344 patients identified by health plan claims as hospitalized for unipolar depression or bipolar disorder will be randomized to receive collaborative care (patient phone-based self-management support, care management, and guideline dissemination to practices delivered by a plan-level care manager) or usual care from their provider. Primary outcomes are changes in mood symptoms and mental health-related quality of life at 12 months. Secondary outcomes include rehospitalization, receipt of guideline-concordant care, and work productivity. This study will determine whether a collaborative care model for mood disorders delivered at the national health plan level improves outcomes compared to usual care, and will inform a business case for collaborative care models for these settings that can reach patients wherever they receive treatment. ClinicalTrials.gov Identifier: NCT02041962; registered January 3, 2014.

Development of binomial sequential sampling plans for forecasting Listronotus maculicollis (Coleoptera: Curculionidae) larvae based on the relationship to adult counts and turfgrass damage.

PubMed

McGraw, Benjamin A; Koppenhöfer, Albrecht M

2009-06-01

Binomial sequential sampling plans were developed to forecast weevil Listronotus maculicollis Kirby (Coleoptera: Curculionidae), larval damage to golf course turfgrass and aid in the development of integrated pest management programs for the weevil. Populations of emerging overwintered adults were sampled over a 2-yr period to determine the relationship between adult counts, larval density, and turfgrass damage. Larval density and composition of preferred host plants (Poa annua L.) significantly affected the expression of turfgrass damage. Multiple regression indicates that damage may occur in moderately mixed P. annua stands with as few as 10 larvae per 0.09 m2. However, > 150 larvae were required before damage became apparent in pure Agrostis stolonifera L. plots. Adult counts during peaks in emergence as well as cumulative counts across the emergence period were significantly correlated to future densities of larvae. Eight binomial sequential sampling plans based on two tally thresholds for classifying infestation (T = 1 and two adults) and four adult density thresholds (0.5, 0.85, 1.15, and 1.35 per 3.34 m2) were developed to forecast the likelihood of turfgrass damage by using adult counts during peak emergence. Resampling for validation of sample plans software was used to validate sampling plans with field-collected data sets. All sampling plans were found to deliver accurate classifications (correct decisions were made between 84.4 and 96.8%) in a practical timeframe (average sampling cost < 22.7 min).

Building the Sun4Cast System: Improvements in Solar Power Forecasting

DOE PAGES

Haupt, Sue Ellen; Kosovic, Branko; Jensen, Tara; ...

2017-06-16

The Sun4Cast System results from a research-to-operations project built on a value chain approach, and benefiting electric utilities’ customers, society, and the environment by improving state-of-the-science solar power forecasting capabilities. As integration of solar power into the national electric grid rapidly increases, it becomes imperative to improve forecasting of this highly variable renewable resource. Thus, a team of researchers from public, private, and academic sectors partnered to develop and assess a new solar power forecasting system, Sun4Cast. The partnership focused on improving decision-making for utilities and independent system operators, ultimately resulting in improved grid stability and cost savings for consumers.more » The project followed a value chain approach to determine key research and technology needs to reach desired results. Sun4Cast integrates various forecasting technologies across a spectrum of temporal and spatial scales to predict surface solar irradiance. Anchoring the system is WRF-Solar, a version of the Weather Research and Forecasting (WRF) numerical weather prediction (NWP) model optimized for solar irradiance prediction. Forecasts from multiple NWP models are blended via the Dynamic Integrated Forecast (DICast) System, the basis of the system beyond about 6 h. For short-range (0-6 h) forecasts, Sun4Cast leverages several observation-based nowcasting technologies. These technologies are blended via the Nowcasting Expert System Integrator (NESI). The NESI and DICast systems are subsequently blended to produce short to mid-term irradiance forecasts for solar array locations. The irradiance forecasts are translated into power with uncertainties quantified using an analog ensemble approach, and are provided to the industry partners for real-time decision-making. The Sun4Cast system ran operationally throughout 2015 and results were assessed. As a result, this paper analyzes the collaborative design process, discusses the project results, and provides recommendations for best-practice solar forecasting.« less

Building the Sun4Cast System: Improvements in Solar Power Forecasting

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

Haupt, Sue Ellen; Kosovic, Branko; Jensen, Tara

The Sun4Cast System results from a research-to-operations project built on a value chain approach, and benefiting electric utilities’ customers, society, and the environment by improving state-of-the-science solar power forecasting capabilities. As integration of solar power into the national electric grid rapidly increases, it becomes imperative to improve forecasting of this highly variable renewable resource. Thus, a team of researchers from public, private, and academic sectors partnered to develop and assess a new solar power forecasting system, Sun4Cast. The partnership focused on improving decision-making for utilities and independent system operators, ultimately resulting in improved grid stability and cost savings for consumers.more » The project followed a value chain approach to determine key research and technology needs to reach desired results. Sun4Cast integrates various forecasting technologies across a spectrum of temporal and spatial scales to predict surface solar irradiance. Anchoring the system is WRF-Solar, a version of the Weather Research and Forecasting (WRF) numerical weather prediction (NWP) model optimized for solar irradiance prediction. Forecasts from multiple NWP models are blended via the Dynamic Integrated Forecast (DICast) System, the basis of the system beyond about 6 h. For short-range (0-6 h) forecasts, Sun4Cast leverages several observation-based nowcasting technologies. These technologies are blended via the Nowcasting Expert System Integrator (NESI). The NESI and DICast systems are subsequently blended to produce short to mid-term irradiance forecasts for solar array locations. The irradiance forecasts are translated into power with uncertainties quantified using an analog ensemble approach, and are provided to the industry partners for real-time decision-making. The Sun4Cast system ran operationally throughout 2015 and results were assessed. As a result, this paper analyzes the collaborative design process, discusses the project results, and provides recommendations for best-practice solar forecasting.« less

Preparations for Integrating Space-Based Total Lightning Observations into Forecast Operations

NASA Technical Reports Server (NTRS)

Stano, Geoffrey T.; Fuell, Kevin K.; Molthan, Andrew L.

2016-01-01

NASA's Short-term Prediction Research and Transition (SPoRT) Center has been a leader in collaborating with the United States National Weather Service (NWS) offices to integrate ground-based total lightning (intra-cloud and cloud-to-ground) observations into the real-time operational environment. For much of these collaborations, the emphasis has been on training, dissemination of data to the NWS AWIPS system, and focusing on the utility of these data in the warning decision support process. A shift away from this paradigm has occurred more recently for several reasons. For one, SPoRT's collaborations have expanded to new partners, including emergency managers and the aviation community. Additionally, and most importantly, is the impending launch of the GOES-R Geostationary Lightning Mapper (GLM). This has led to collaborative efforts to focus on additional forecast needs, new data displays, develop training for GLM uses based on the lessons learned from ground-based lightning mapping arrays, and ways to better relate total lightning data to other meteorological parameters. This presentation will focus on these efforts to prepare the operational end user community for GLM with an eye towards sharing lessons learned as EUMETSAT prepares for the Meteosat Third Generation Lightning Imager. This will focus on both software and training needs. In particular, SPoRT has worked closely with the Meteorological Development Laboratory to create the total lightning tracking tool. This software allows for NWS forecasters to manually track storms of interest and display a time series trend of observations. This tool also has been expanded to work on any gridded data set allowing for easy visual comparisons of multiple parameters in addition to total lightning. A new web display has been developed for the ground-based observations that can be easily extended to satellite observations. This paves the way for new collaborations outside of the NWS, both domestically and internationally, as the web display will be functional on PCs and mobile devices. Furthermore, SPoRT has helped developed the software plug-in to visualize GLM data. Examples using the official GLM proxy product will be used to provide a glimpse as to what real-time GLM and likely MTG-LI data will be in the near future.

Verification of Ensemble Forecasts for the New York City Operations Support Tool

NASA Astrophysics Data System (ADS)

Day, G.; Schaake, J. C.; Thiemann, M.; Draijer, S.; Wang, L.

2012-12-01

The New York City water supply system operated by the Department of Environmental Protection (DEP) serves nine million people. It covers 2,000 square miles of portions of the Catskill, Delaware, and Croton watersheds, and it includes nineteen reservoirs and three controlled lakes. DEP is developing an Operations Support Tool (OST) to support its water supply operations and planning activities. OST includes historical and real-time data, a model of the water supply system complete with operating rules, and lake water quality models developed to evaluate alternatives for managing turbidity in the New York City Catskill reservoirs. OST will enable DEP to manage turbidity in its unfiltered system while satisfying its primary objective of meeting the City's water supply needs, in addition to considering secondary objectives of maintaining ecological flows, supporting fishery and recreation releases, and mitigating downstream flood peaks. The current version of OST relies on statistical forecasts of flows in the system based on recent observed flows. To improve short-term decision making, plans are being made to transition to National Weather Service (NWS) ensemble forecasts based on hydrologic models that account for short-term weather forecast skill, longer-term climate information, as well as the hydrologic state of the watersheds and recent observed flows. To ensure that the ensemble forecasts are unbiased and that the ensemble spread reflects the actual uncertainty of the forecasts, a statistical model has been developed to post-process the NWS ensemble forecasts to account for hydrologic model error as well as any inherent bias and uncertainty in initial model states, meteorological data and forecasts. The post-processor is designed to produce adjusted ensemble forecasts that are consistent with the DEP historical flow sequences that were used to develop the system operating rules. A set of historical hindcasts that is representative of the real-time ensemble forecasts is needed to verify that the post-processed forecasts are unbiased, statistically reliable, and preserve the skill inherent in the "raw" NWS ensemble forecasts. A verification procedure and set of metrics will be presented that provide an objective assessment of ensemble forecasts. The procedure will be applied to both raw ensemble hindcasts and to post-processed ensemble hindcasts. The verification metrics will be used to validate proper functioning of the post-processor and to provide a benchmark for comparison of different types of forecasts. For example, current NWS ensemble forecasts are based on climatology, using each historical year to generate a forecast trace. The NWS Hydrologic Ensemble Forecast System (HEFS) under development will utilize output from both the National Oceanic Atmospheric Administration (NOAA) Global Ensemble Forecast System (GEFS) and the Climate Forecast System (CFS). Incorporating short-term meteorological forecasts and longer-term climate forecast information should provide sharper, more accurate forecasts. Hindcasts from HEFS will enable New York City to generate verification results to validate the new forecasts and further fine-tune system operating rules. Project verification results will be presented for different watersheds across a range of seasons, lead times, and flow levels to assess the quality of the current ensemble forecasts.

Housing, health and master planning: rules of engagement.

PubMed

Harris, P; Haigh, F; Thornell, M; Molloy, L; Sainsbury, P

2014-04-01

Knowledge about health focussed policy collaboration to date has been either tactical or technical. This article focusses on both technical and tactical issues to describe the experience of cross-sectoral collaboration between health and housing stakeholders across the life of a housing master plan, including but not limited to a health impact assessment (HIA). A single explanatory case study of collaboration on a master plan to regenerate a deprived housing estate in Western Sydney was developed to explain why and how the collaboration worked or did not work. Data collection included stakeholder interviews, document review, and reflections by the health team. Following a realist approach, data was analysed against established public policy theory dimensions. Tactically we did not know what we were doing. Despite our technical knowledge and skills with health focussed processes, particularly HIA, we failed to appreciate complexities inherent in master planning. This limited our ability to provide information at the right points. Eventually however the HIA did provide substantive connections between the master plan and health. We use our analysis to develop technical and tactical rules of engagement for future cross-sectoral collaboration. This case study from the field provides insight for future health focussed policy collaboration. We demonstrate the technical and tactical requirements for future intersectoral policy and planning collaborations, including HIAs, with the housing sector on master planning. The experience also suggested how HIAs can be conducted flexibly alongside policy development rather than at a specific point after a policy is drafted. Copyright © 2014 The Royal Society for Public Health. All rights reserved.

The psychology of intelligence analysis: drivers of prediction accuracy in world politics.

PubMed

Mellers, Barbara; Stone, Eric; Atanasov, Pavel; Rohrbaugh, Nick; Metz, S Emlen; Ungar, Lyle; Bishop, Michael M; Horowitz, Michael; Merkle, Ed; Tetlock, Philip

2015-03-01

This article extends psychological methods and concepts into a domain that is as profoundly consequential as it is poorly understood: intelligence analysis. We report findings from a geopolitical forecasting tournament that assessed the accuracy of more than 150,000 forecasts of 743 participants on 199 events occurring over 2 years. Participants were above average in intelligence and political knowledge relative to the general population. Individual differences in performance emerged, and forecasting skills were surprisingly consistent over time. Key predictors were (a) dispositional variables of cognitive ability, political knowledge, and open-mindedness; (b) situational variables of training in probabilistic reasoning and participation in collaborative teams that shared information and discussed rationales (Mellers, Ungar, et al., 2014); and (c) behavioral variables of deliberation time and frequency of belief updating. We developed a profile of the best forecasters; they were better at inductive reasoning, pattern detection, cognitive flexibility, and open-mindedness. They had greater understanding of geopolitics, training in probabilistic reasoning, and opportunities to succeed in cognitively enriched team environments. Last but not least, they viewed forecasting as a skill that required deliberate practice, sustained effort, and constant monitoring of current affairs. PsycINFO Database Record (c) 2015 APA, all rights reserved.

76 FR 81009 - Agency Information Collection Activities: Requests for Comments; Clearance of Renewed Approval of...

Federal Register 2010, 2011, 2012, 2013, 2014

2011-12-27

... assessment, planning, forecasting, cost/benefit analysis, and to target areas for research. DATES: Written..., forecasting, cost/benefit analysis, and to target areas for research. Respondents: Approximately 83,500 owners... invites public comments about our intention to request the Office of Management and Budget (OMB) approval...

Forecasting trends in outdoor recreation activities on multi-state basis

Treesearch

Vincent A. Scardino; Josef Schwalbe; Marianne Beauregard

1980-01-01

Since a substantial amount of recreation planning takes place on a statewide basis, it is essential to have reliable information and forecasts of recreational needs on a state level. However, most of the recreation research over the last few years have used either national survey data, statewide data or site specific information.

Using External Environmental Scanning and Forecasting to Improve Strategic Planning

ERIC Educational Resources Information Center

Lapin, Joel D.

2004-01-01

The effectiveness of community colleges is increasingly dependent on their understanding of the external environment and their capacity to forecast and respond to the changing external landscape. As a result, they need to establish a system to continuously monitor changes in that environment and to identify and weigh the implications of changes on…

Flood monitoring for ungauged rivers: the power of combining space-based monitoring and global forecasting models

NASA Astrophysics Data System (ADS)

Revilla-Romero, Beatriz; Netgeka, Victor; Raynaud, Damien; Thielen, Jutta

2013-04-01

Flood warning systems typically rely on forecasts from national meteorological services and in-situ observations from hydrological gauging stations. This capacity is not equally developed in flood-prone developing countries. Low-cost satellite monitoring systems and global flood forecasting systems can be an alternative source of information for national flood authorities. The Global Flood Awareness System (GloFAS) has been develop jointly with the European Centre for Medium-Range Weather Forecast (ECMWF) and the Joint Research Centre, and it is running quasi operational now since June 2011. The system couples state-of-the art weather forecasts with a hydrological model driven at a continental scale. The system provides downstream countries with information on upstream river conditions as well as continental and global overviews. In its test phase, this global forecast system provides probabilities for large transnational river flooding at the global scale up to 30 days in advance. It has shown its real-life potential for the first time during the flood in Southeast Asia in 2011, and more recently during the floods in Australia in March 2012, India (Assam, September-October 2012) and Chad Floods (August-October 2012).The Joint Research Centre is working on further research and development, rigorous testing and adaptations of the system to create an operational tool for decision makers, including national and regional water authorities, water resource managers, hydropower companies, civil protection and first line responders, and international humanitarian aid organizations. Currently efforts are being made to link GloFAS to the Global Flood Detection System (GFDS). GFDS is a Space-based river gauging and flood monitoring system using passive microwave remote sensing which was developed by a collaboration between the JRC and Dartmouth Flood Observatory. GFDS provides flood alerts based on daily water surface change measurements from space. Alerts are shown on a world map, with detailed reports for individual gauging sites. A comparison of discharge estimates from the Global Flood Detection System (GFDS) and the Global Flood Awareness System (GloFAS) with observations for representative climatic zones is presented. Both systems have demonstrated strong potential in forecasting and detecting recent catastrophic floods. The usefulness of their combined information on global scale for decision makers at different levels is discussed. Combining space-based monitoring and global forecasting models is an innovative approach and has significant benefits for international river commissions as well as international aid organisations. This is in line with the objectives of the Hyogo and the Post-2015 Framework that aim at the development of systems which involve trans-boundary collaboration, space-based earth observation, flood forecasting and early warning.

Application of Jason-2/3 Altimetry for Virtual Gauging and Flood Forecasting in Mekong Basin

NASA Astrophysics Data System (ADS)

Lee, H.; Hossain, F.; Okeowo, M. A.; Nguyen, L. D.; Bui, D. D.; Chang, C. H.

2016-12-01

Vietnam suffers from both flood and drought during the rainy and dry seasons, respectively, due to its highly varying surface water resources. However, the National Center for Water Resources Planning and Investigation (NAWAPI) states that only 7 surface water monitoring stations have been constructed in Central and Highland Central regions with 100 station planned to be constructed by 2030 throughout Vietnam. For the Mekong Delta (MD), the Mekong River Commission (MRC) provides 7-day river level forecasting, but only at the two gauge stations located near the border between Cambodia and Vietnam (http://ffw.mrcmekong.org/south.htm). In order to help stakeholder agencies monitor upstream processes in the rivers and manage their impacts on the agricultural sector and densely populated delta cities, we, first of all, construct the so-called virtual stations throughout the entire Mekong River using the fully automated river level extraction tool with Jason-2/3 Geophysical Research Record (GDR) data. Then, we discuss the potentials and challenges of river level forecasting using Jason-2/3 Interim GDR (IGDR) data, which has 1 - 2 days of latency, over the Mekong River. Finally, based on our analyses, we propose a forecasting system for the Mekong River by drawing from our experience in operationalizing Jason-2 altimetry for Bangladesh flood forecasting.

Short Range Planning for Educational Management.

ERIC Educational Resources Information Center

Turksen, I. B.; Holzman, A. G.

A planning cycle for any autonomous university entity contains five basic processes: information storage and retrieval forecasting, resource allocation, scheduling, and a term of study with a feedback loop. The resource allocation process is investigated for the development of shortrange planning models. Dynamic models wth linear and quadratic…

The North Alabama Lightning Mapping Array: Recent Results and Future Prospects

NASA Technical Reports Server (NTRS)

Goodman, S. J.; Blakeslee, R.; Christian, H.; Boccippio, D.; Koshak, W.; Bailey, J.; Hall, J.; Bateman, M.; McCaul, E.; Buechler, D.

2002-01-01

The North Alabama Lightning Mapping Array became operational in November 2001 as a principal component of a severe weather test bed to infuse new science and technologies into the short-term forecasting of severe and hazardous weather and the warning decision-making process. The LMA project is a collaboration among NASA scientists, National Weather Service (NWS) weather forecast offices (WFOs), emergency managers, and other partners. The time rate-of-change of storm characteristics and life-cycle trending are accomplished in real-time through the second generation Lightning Imaging Sensor Data Applications Display (LISDAD II) system, initially developed in T997 through a collaboration among NASA/MSFC, MIT/Lincoln Lab and the Melbourne, FL WFO. LISDAD II is now a distributed decision support system with a JAVA-based display application that allows anyone, anywhere to track individual storm histories within the Tennessee Valley region of the southeastern U.S. Since the inauguration of the LMA there has been an abundance of severe weather. During 23-24 November 2001, a major tornado outbreak was monitored by LMA in its first data acquisition effort (36 tornadoes in Alabama). Since that time the LMA has collected a vast amount of data on hailstorms and damaging wind events, non-tornadic supercells, and ordinary non-severe thunderstorms. In this paper we provide an overview of LMA observations and discuss future prospects for improving the short-term forecasting of convective weather.

The development rainfall forecasting using kalman filter

NASA Astrophysics Data System (ADS)

Zulfi, Mohammad; Hasan, Moh.; Dwidja Purnomo, Kosala

2018-04-01

Rainfall forecasting is very interesting for agricultural planing. Rainfall information is useful to make decisions about the plan planting certain commodities. In this studies, the rainfall forecasting by ARIMA and Kalman Filter method. Kalman Filter method is used to declare a time series model of which is shown in the form of linear state space to determine the future forecast. This method used a recursive solution to minimize error. The rainfall data in this research clustered by K-means clustering. Implementation of Kalman Filter method is for modelling and forecasting rainfall in each cluster. We used ARIMA (p,d,q) to construct a state space for KalmanFilter model. So, we have four group of the data and one model in each group. In conclusions, Kalman Filter method is better than ARIMA model for rainfall forecasting in each group. It can be showed from error of Kalman Filter method that smaller than error of ARIMA model.

Earthquake forecasting during the complex Amatrice-Norcia seismic sequence

PubMed Central

Marzocchi, Warner; Taroni, Matteo; Falcone, Giuseppe

2017-01-01

Earthquake forecasting is the ultimate challenge for seismologists, because it condenses the scientific knowledge about the earthquake occurrence process, and it is an essential component of any sound risk mitigation planning. It is commonly assumed that, in the short term, trustworthy earthquake forecasts are possible only for typical aftershock sequences, where the largest shock is followed by many smaller earthquakes that decay with time according to the Omori power law. We show that the current Italian operational earthquake forecasting system issued statistically reliable and skillful space-time-magnitude forecasts of the largest earthquakes during the complex 2016–2017 Amatrice-Norcia sequence, which is characterized by several bursts of seismicity and a significant deviation from the Omori law. This capability to deliver statistically reliable forecasts is an essential component of any program to assist public decision-makers and citizens in the challenging risk management of complex seismic sequences. PMID:28924610

Earthquake forecasting during the complex Amatrice-Norcia seismic sequence.

PubMed

Marzocchi, Warner; Taroni, Matteo; Falcone, Giuseppe

2017-09-01

Earthquake forecasting is the ultimate challenge for seismologists, because it condenses the scientific knowledge about the earthquake occurrence process, and it is an essential component of any sound risk mitigation planning. It is commonly assumed that, in the short term, trustworthy earthquake forecasts are possible only for typical aftershock sequences, where the largest shock is followed by many smaller earthquakes that decay with time according to the Omori power law. We show that the current Italian operational earthquake forecasting system issued statistically reliable and skillful space-time-magnitude forecasts of the largest earthquakes during the complex 2016-2017 Amatrice-Norcia sequence, which is characterized by several bursts of seismicity and a significant deviation from the Omori law. This capability to deliver statistically reliable forecasts is an essential component of any program to assist public decision-makers and citizens in the challenging risk management of complex seismic sequences.

Improving Arctic Sea Ice Observations and Data Access to Support Advances in Sea Ice Forecasting

NASA Astrophysics Data System (ADS)

Farrell, S. L.

2017-12-01

The economic and strategic importance of the Arctic region is becoming apparent. One of the most striking and widely publicized changes underway is the declining sea ice cover. Since sea ice is a key component of the climate system, its ongoing loss has serious, and wide-ranging, socio-economic implications. Increasing year-to-year variability in the geographic location, concentration, and thickness of the Arctic ice cover will pose both challenges and opportunities. The sea ice research community must be engaged in sustained Arctic Observing Network (AON) initiatives so as to deliver fit-for-purpose remote sensing data products to a variety of stakeholders including Arctic communities, the weather forecasting and climate modeling communities, industry, local, regional and national governments, and policy makers. An example of engagement is the work currently underway to improve research collaborations between scientists engaged in obtaining and assessing sea ice observational data and those conducting numerical modeling studies and forecasting ice conditions. As part of the US AON, in collaboration with the Interagency Arctic Research Policy Committee (IARPC), we are developing a strategic framework within which observers and modelers can work towards the common goal of improved sea ice forecasting. Here, we focus on sea ice thickness, a key varaible of the Arctic ice cover. We describe multi-sensor, and blended, sea ice thickness data products under development that can be leveraged to improve model initialization and validation, as well as support data assimilation exercises. We will also present the new PolarWatch initiative (polarwatch.noaa.gov) and discuss efforts to advance access to remote sensing satellite observations and improve communication with Arctic stakeholders, so as to deliver data products that best address societal needs.

Objective Lightning Probability Forecasting for Kennedy Space Center and Cape Canaveral Air Force Station

NASA Technical Reports Server (NTRS)

Lambert, Winifred; Wheeler, Mark

2005-01-01

Five logistic regression equations were created that predict the probability of cloud-to-ground lightning occurrence for the day in the KSC/CCAFS area for each month in the warm season. These equations integrated the results from several studies over recent years to improve thunderstorm forecasting at KSC/CCAFS. All of the equations outperform persistence, which is known to outperform NPTI, the current objective tool used in 45 WS lightning forecasting operations. The equations also performed well in other tests. As a result, the new equations will be added to the current set of tools used by the 45 WS to determine the probability of lightning for their daily planning forecast. The results from these equations are meant to be used as first-guess guidance when developing the lightning probability forecast for the day. They provide an objective base from which forecasters can use other observations, model data, consultation with other forecasters, and their own experience to create the final lightning probability for the 1100 UTC briefing.

Forecasting the short-term passenger flow on high-speed railway with neural networks.

PubMed

Xie, Mei-Quan; Li, Xia-Miao; Zhou, Wen-Liang; Fu, Yan-Bing

2014-01-01

Short-term passenger flow forecasting is an important component of transportation systems. The forecasting result can be applied to support transportation system operation and management such as operation planning and revenue management. In this paper, a divide-and-conquer method based on neural network and origin-destination (OD) matrix estimation is developed to forecast the short-term passenger flow in high-speed railway system. There are three steps in the forecasting method. Firstly, the numbers of passengers who arrive at each station or depart from each station are obtained from historical passenger flow data, which are OD matrices in this paper. Secondly, short-term passenger flow forecasting of the numbers of passengers who arrive at each station or depart from each station based on neural network is realized. At last, the OD matrices in short-term time are obtained with an OD matrix estimation method. The experimental results indicate that the proposed divide-and-conquer method performs well in forecasting the short-term passenger flow on high-speed railway.

Census mapbook for transportation planning.

DOT National Transportation Integrated Search

1994-12-01

Geographic display of Census data in transportation planning and policy decisions are compiled in a report of 49 maps, depicting use of the data in applications such as travel demand model development and model validation, population forecasting, cor...

Verification of National Weather Service spot forecasts using surface observations

NASA Astrophysics Data System (ADS)

Lammers, Matthew Robert

Software has been developed to evaluate National Weather Service spot forecasts issued to support prescribed burns and early-stage wildfires. Fire management officials request spot forecasts from National Weather Service Weather Forecast Offices to provide detailed guidance as to atmospheric conditions in the vicinity of planned prescribed burns as well as wildfires that do not have incident meteorologists on site. This open source software with online display capabilities is used to examine an extensive set of spot forecasts of maximum temperature, minimum relative humidity, and maximum wind speed from April 2009 through November 2013 nationwide. The forecast values are compared to the closest available surface observations at stations installed primarily for fire weather and aviation applications. The accuracy of the spot forecasts is compared to those available from the National Digital Forecast Database (NDFD). Spot forecasts for selected prescribed burns and wildfires are used to illustrate issues associated with the verification procedures. Cumulative statistics for National Weather Service County Warning Areas and for the nation are presented. Basic error and accuracy metrics for all available spot forecasts and the entire nation indicate that the skill of the spot forecasts is higher than that available from the NDFD, with the greatest improvement for maximum temperature and the least improvement for maximum wind speed.

Medium Range Ensembles Flood Forecasts for Community Level Applications

NASA Astrophysics Data System (ADS)

Fakhruddin, S.; Kawasaki, A.; Babel, M. S.; AIT

2013-05-01

Early warning is a key element for disaster risk reduction. In recent decades, there has been a major advancement in medium range and seasonal forecasting. These could provide a great opportunity to improve early warning systems and advisories for early action for strategic and long term planning. This could result in increasing emphasis on proactive rather than reactive management of adverse consequences of flood events. This can be also very helpful for the agricultural sector by providing a diversity of options to farmers (e.g. changing cropping pattern, planting timing, etc.). An experimental medium range (1-10 days) flood forecasting model has been developed for Bangladesh which provides 51 set of discharge ensembles forecasts of one to ten days with significant persistence and high certainty. This could help communities (i.e. farmer) for gain/lost estimation as well as crop savings. This paper describe the application of ensembles probabilistic flood forecast at the community level for differential decision making focused on agriculture. The framework allows users to interactively specify the objectives and criteria that are germane to a particular situation, and obtain the management options that are possible, and the exogenous influences that should be taken into account before planning and decision making. risk and vulnerability assessment was conducted through community consultation. The forecast lead time requirement, users' needs, impact and management options for crops, livestock and fisheries sectors were identified through focus group discussions, informal interviews and questionnaire survey.

Nonmechanistic forecasts of seasonal influenza with iterative one-week-ahead distributions.

PubMed

Brooks, Logan C; Farrow, David C; Hyun, Sangwon; Tibshirani, Ryan J; Rosenfeld, Roni

2018-06-15

Accurate and reliable forecasts of seasonal epidemics of infectious disease can assist in the design of countermeasures and increase public awareness and preparedness. This article describes two main contributions we made recently toward this goal: a novel approach to probabilistic modeling of surveillance time series based on "delta densities", and an optimization scheme for combining output from multiple forecasting methods into an adaptively weighted ensemble. Delta densities describe the probability distribution of the change between one observation and the next, conditioned on available data; chaining together nonparametric estimates of these distributions yields a model for an entire trajectory. Corresponding distributional forecasts cover more observed events than alternatives that treat the whole season as a unit, and improve upon multiple evaluation metrics when extracting key targets of interest to public health officials. Adaptively weighted ensembles integrate the results of multiple forecasting methods, such as delta density, using weights that can change from situation to situation. We treat selection of optimal weightings across forecasting methods as a separate estimation task, and describe an estimation procedure based on optimizing cross-validation performance. We consider some details of the data generation process, including data revisions and holiday effects, both in the construction of these forecasting methods and when performing retrospective evaluation. The delta density method and an adaptively weighted ensemble of other forecasting methods each improve significantly on the next best ensemble component when applied separately, and achieve even better cross-validated performance when used in conjunction. We submitted real-time forecasts based on these contributions as part of CDC's 2015/2016 FluSight Collaborative Comparison. Among the fourteen submissions that season, this system was ranked by CDC as the most accurate.

Collaborative Inquiry for Equity: Discipline and Discomfort

ERIC Educational Resources Information Center

Winkelman, Peg

2012-01-01

In this study the discipline of collaborative inquiry is employed to prepare aspiring administrators to lead for equity. Educational leadership students are required to conduct a site-based collaborative inquiry resulting in an Equity Plan signature assignment. As they develop their Equity Plans, emerging leaders also participate in a…

Forecasting the impacts of shale gas developments on public health and transportation systems on both sides of the Mexico-U.S. border.

DOT National Transportation Integrated Search

2015-08-01

The activities completed for this project includes the literature research on the Eagle Ford formation, the review : of public-health and transportation related variables to shale gas developments, and the definition of the project : collaborative si...

The Keys to the White House: Prediction for 2012

ERIC Educational Resources Information Center

Lichtman, Allan

2012-01-01

Conventional pundits, pollsters, and forecasters are focused on whether the economy will improve sufficiently in 2012 for President Barack Obama to gain reelection. The Keys to the White House, a prediction system that the author developed in collaboration with Vladimir Keilis-Borok, founder of the International Institute of Earthquake Prediction…

Using ensembles in water management: forecasting dry and wet episodes

NASA Astrophysics Data System (ADS)

van het Schip-Haverkamp, Tessa; van den Berg, Wim; van de Beek, Remco

2015-04-01

Extreme weather situations as droughts and extensive precipitation are becoming more frequent, which makes it more important to obtain accurate weather forecasts for the short and long term. Ensembles can provide a solution in terms of scenario forecasts. MeteoGroup uses ensembles in a new forecasting technique which presents a number of weather scenarios for a dynamical water management project, called Water-Rijk, in which water storage and water retention plays a large role. The Water-Rijk is part of Park Lingezegen, which is located between Arnhem and Nijmegen in the Netherlands. In collaboration with the University of Wageningen, Alterra and Eijkelkamp a forecasting system is developed for this area which can provide water boards with a number of weather and hydrology scenarios in order to assist in the decision whether or not water retention or water storage is necessary in the near future. In order to make a forecast for drought and extensive precipitation, the difference 'precipitation- evaporation' is used as a measurement of drought in the weather forecasts. In case of an upcoming drought this difference will take larger negative values. In case of a wet episode, this difference will be positive. The Makkink potential evaporation is used which gives the most accurate potential evaporation values during the summer, when evaporation plays an important role in the availability of surface water. Scenarios are determined by reducing the large number of forecasts in the ensemble to a number of averaged members with each its own likelihood of occurrence. For the Water-Rijk project 5 scenario forecasts are calculated: extreme dry, dry, normal, wet and extreme wet. These scenarios are constructed for two forecasting periods, each using its own ensemble technique: up to 48 hours ahead and up to 15 days ahead. The 48-hour forecast uses an ensemble constructed from forecasts of multiple high-resolution regional models: UKMO's Euro4 model,the ECMWF model, WRF and Hirlam. Using multiple model runs and additional post processing, an ensemble can be created from non-ensemble models. The 15-day forecast uses the ECMWF Ensemble Prediction System forecast from which scenarios can be deduced directly. A combination of the ensembles from the two forecasting periods is used in order to have the highest possible resolution of the forecast for the first 48 hours followed by the lower resolution long term forecast.

Manpower Planning, Rate of Return Analysis, and the University Medical Schools: The Case of Australia

ERIC Educational Resources Information Center

Davis, Denis J.

1977-01-01

Some of the errors in educational planning that arise from manpower forecasts are examined using the Australian doctors manpower plan, 1975-91 as an illustration. The large variation in results that can occur through the substitution of alternatively feasible coefficients is shown. (Editor/LBH)

76 FR 66229 - Transmission Planning Reliability Standards

Federal Register 2010, 2011, 2012, 2013, 2014

2011-10-26

... Transmission Services, at all demand levels over the range of forecast system demands, under the contingency... any planned firm load that is not directly served by the elements that are removed from service as a... to plan for the loss of firm service for a single contingency, the Commission finds that their...

Transition, Training, and Assessment of Multispectral Composite Imagery in Support of the NWS Aviation Forecast Mission

NASA Technical Reports Server (NTRS)

Fuell, Kevin; Jedlovec, Gary; Leroy, Anita; Schultz, Lori

2015-01-01

The NASA/Short-term Prediction, Research, and Transition (SPoRT) Program works closely with NOAA/NWS weather forecasters to transition unique satellite data and capabilities into operations in order to assist with nowcasting and short-term forecasting issues. Several multispectral composite imagery (i.e. RGB) products were introduced to users in the early 2000s to support hydrometeorology and aviation challenges as well as incident support. These activities lead to SPoRT collaboration with the GOES-R Proving Ground efforts where instruments such as MODIS (Aqua, Terra) and S-NPP/VIIRS imagers began to be used as near-realtime proxies to future capabilities of the Advanced Baseline Imager (ABI). One of the composite imagery products introduced to users was the Night-time Microphysics RGB, originally developed by EUMETSAT. SPoRT worked to transition this imagery to NWS users, provide region-specific training, and assess the impact of the imagery to aviation forecast needs. This presentation discusses the method used to interact with users to address specific aviation forecast challenges, including training activities undertaken to prepare for a product assessment. Users who assessed the multispectral imagery ranged from southern U.S. inland and coastal NWS weather forecast offices (WFOs), to those in the Rocky Mountain Front Range region and West Coast, as well as highlatitude forecasters of Alaska. These user-based assessments were documented and shared with the satellite community to support product developers and the broad users of new generation satellite data.

Decadal-Scale Forecasting of Climate Drivers for Marine Applications.

PubMed

Salinger, J; Hobday, A J; Matear, R J; O'Kane, T J; Risbey, J S; Dunstan, P; Eveson, J P; Fulton, E A; Feng, M; Plagányi, É E; Poloczanska, E S; Marshall, A G; Thompson, P A

Climate influences marine ecosystems on a range of time scales, from weather-scale (days) through to climate-scale (hundreds of years). Understanding of interannual to decadal climate variability and impacts on marine industries has received less attention. Predictability up to 10 years ahead may come from large-scale climate modes in the ocean that can persist over these time scales. In Australia the key drivers of climate variability affecting the marine environment are the Southern Annular Mode, the Indian Ocean Dipole, the El Niño/Southern Oscillation, and the Interdecadal Pacific Oscillation, each has phases that are associated with different ocean circulation patterns and regional environmental variables. The roles of these drivers are illustrated with three case studies of extreme events-a marine heatwave in Western Australia, a coral bleaching of the Great Barrier Reef, and flooding in Queensland. Statistical and dynamical approaches are described to generate forecasts of climate drivers that can subsequently be translated to useful information for marine end users making decisions at these time scales. Considerable investment is still needed to support decadal forecasting including improvement of ocean-atmosphere models, enhancement of observing systems on all scales to support initiation of forecasting models, collection of important biological data, and integration of forecasts into decision support tools. Collaboration between forecast developers and marine resource sectors-fisheries, aquaculture, tourism, biodiversity management, infrastructure-is needed to support forecast-based tactical and strategic decisions that reduce environmental risk over annual to decadal time scales. © 2016 Elsevier Ltd. All rights reserved.

Evaluating the Impact of Atmospheric Infrared Sounder (AIRS) Data On Convective Forecasts

NASA Technical Reports Server (NTRS)

Kozlowski, Danielle; Zavodsky, Bradley

2011-01-01

The Short-term Prediction Research and Transition Center (SPoRT) is a collaborative partnership between NASA and operational forecasting partners, including a number of National Weather Service (NWS) offices. SPoRT provides real-time NASA products and capabilities to its partners to address specific operational forecast challenges. The mission of SPoRT is to transition observations and research capabilities into operations to help improve short-term weather forecasts on a regional scale. Two areas of focus are data assimilation and modeling, which can to help accomplish SPoRT's programmatic goals of transitioning NASA data to operational users. Forecasting convective weather is one challenge that faces operational forecasters. Current numerical weather prediction (NWP) models that operational forecasters use struggle to properly forecast location, timing, intensity and/or mode of convection. Given the proper atmospheric conditions, convection can lead to severe weather. SPoRT's partners in the National Oceanic and Atmospheric Administration (NOAA) have a mission to protect the life and property of American citizens. This mission has been tested as recently as this 2011 severe weather season, which has seen more than 300 fatalities and injuries and total damages exceeding $10 billion. In fact, during the three day period from 25-27 April, 1,265 storms reports (362 tornado reports) were collected making this three day period one of most active in American history. To address the forecast challenge of convective weather, SPoRT produces a real-time NWP model called the SPoRT Weather Research and Forecasting (SPoRT-WRF), which incorporates unique NASA data sets. One of the NASA assets used in this unique model configuration is retrieved profiles from the Atmospheric Infrared Sounder (AIRS).The goal of this project is to determine the impact that these AIRS profiles have on the SPoRT-WRF forecasts by comparing to a current operational model and a control SPoRT-WRF model that does not contain AIRS profiles.

Exploring the calibration of a wind forecast ensemble for energy applications

NASA Astrophysics Data System (ADS)

Heppelmann, Tobias; Ben Bouallegue, Zied; Theis, Susanne

2015-04-01

In the German research project EWeLiNE, Deutscher Wetterdienst (DWD) and Fraunhofer Institute for Wind Energy and Energy System Technology (IWES) are collaborating with three German Transmission System Operators (TSO) in order to provide the TSOs with improved probabilistic power forecasts. Probabilistic power forecasts are derived from probabilistic weather forecasts, themselves derived from ensemble prediction systems (EPS). Since the considered raw ensemble wind forecasts suffer from underdispersiveness and bias, calibration methods are developed for the correction of the model bias and the ensemble spread bias. The overall aim is to improve the ensemble forecasts such that the uncertainty of the possible weather deployment is depicted by the ensemble spread from the first forecast hours. Additionally, the ensemble members after calibration should remain physically consistent scenarios. We focus on probabilistic hourly wind forecasts with horizon of 21 h delivered by the convection permitting high-resolution ensemble system COSMO-DE-EPS which has become operational in 2012 at DWD. The ensemble consists of 20 ensemble members driven by four different global models. The model area includes whole Germany and parts of Central Europe with a horizontal resolution of 2.8 km and a vertical resolution of 50 model levels. For verification we use wind mast measurements around 100 m height that corresponds to the hub height of wind energy plants that belong to wind farms within the model area. Calibration of the ensemble forecasts can be performed by different statistical methods applied to the raw ensemble output. Here, we explore local bivariate Ensemble Model Output Statistics at individual sites and quantile regression with different predictors. Applying different methods, we already show an improvement of ensemble wind forecasts from COSMO-DE-EPS for energy applications. In addition, an ensemble copula coupling approach transfers the time-dependencies of the raw ensemble to the calibrated ensemble. The calibrated wind forecasts are evaluated first with univariate probabilistic scores and additionally with diagnostics of wind ramps in order to assess the time-consistency of the calibrated ensemble members.

Modifications to the Objective Lightning Probability Forecast Tool at Kennedy Space Center/Cape Canaveral Air Force Station, Florida

NASA Technical Reports Server (NTRS)

Crawford, Winifred; Roeder, William

2010-01-01

The 45th Weather Squadron (45 WS) at Cape Canaveral Air Force Station (CCAFS) includes the probability of lightning occurrence in their 24-Hour and Weekly Planning Forecasts, briefed at 0700 EDT for daily operations planning on Kennedy Space Center (KSC) and CCAFS. This forecast is based on subjective analyses of model and observational data and output from an objective tool developed by the Applied Meteorology Unit (AMU). This tool was developed over two phases (Lambert and Wheeler 2005, Lambert 2007). It consists of five equations, one for each warm season month (May-Sep), that calculate the probability of lightning occurrence for the day and a graphical user interface (GUI) to display the output. The Phase I and II equations outperformed previous operational tools by a total of 56%. Based on this success, the 45 WS tasked the AMU with Phase III to improve the tool further.

Web-based GIS for collaborative planning and public participation: an application to the strategic planning of wind farm sites.

PubMed

Simão, Ana; Densham, Paul J; Haklay, Mordechai Muki

2009-05-01

Spatial planning typically involves multiple stakeholders. To any specific planning problem, stakeholders often bring different levels of knowledge about the components of the problem and make assumptions, reflecting their individual experiences, that yield conflicting views about desirable planning outcomes. Consequently, stakeholders need to learn about the likely outcomes that result from their stated preferences; this learning can be supported through enhanced access to information, increased public participation in spatial decision-making and support for distributed collaboration amongst planners, stakeholders and the public. This paper presents a conceptual system framework for web-based GIS that supports public participation in collaborative planning. The framework combines an information area, a Multi-Criteria Spatial Decision Support System (MC-SDSS) and an argumentation map to support distributed and asynchronous collaboration in spatial planning. After analysing the novel aspects of this framework, the paper describes its implementation, as a proof of concept, in a system for Web-based Participatory Wind Energy Planning (WePWEP). Details are provided on the specific implementation of each of WePWEP's four tiers, including technical and structural aspects. Throughout the paper, particular emphasis is placed on the need to support user learning throughout the planning process.

Interprofessional collaboration regarding patients' care plans in primary care: a focus group study into influential factors.

PubMed

van Dongen, Jerôme Jean Jacques; Lenzen, Stephanie Anna; van Bokhoven, Marloes Amantia; Daniëls, Ramon; van der Weijden, Trudy; Beurskens, Anna

2016-05-28

The number of people with multiple chronic conditions demanding primary care services is increasing. To deal with the complex health care demands of these people, professionals from different disciplines collaborate. This study aims to explore influential factors regarding interprofessional collaboration related to care plan development in primary care. A qualitative study, including four semi-structured focus group interviews (n = 4). In total, a heterogeneous group of experts (n = 16) and health care professionals (n = 15) participated. Participants discussed viewpoints, barriers, and facilitators regarding interprofessional collaboration related to care plan development. The data were analysed by means of inductive content analysis. The findings show a variety of factors influencing the interprofessional collaboration in developing a care plan. Factors can be divided into 5 key categories: (1) patient-related factors: active role, self-management, goals and wishes, membership of the team; (2) professional-related factors: individual competences, domain thinking, motivation; (3) interpersonal factors: language differences, knowing each other, trust and respect, and motivation; (4) organisational factors: structure, composition, time, shared vision, leadership and administrative support; and (5) external factors: education, culture, hierarchy, domain thinking, law and regulations, finance, technology and ICT. Improving interprofessional collaboration regarding care plan development calls for an integral approach including patient- and professional related factors, interpersonal, organisational, and external factors. Further, the leader of the team seems to play a key role in watching the patient perspective, organising and coordinating interprofessional collaborations, and guiding the team through developments. The results of this study can be used as input for developing tools and interventions targeted at executing and improving interprofessional collaboration related to care plan development.

A Hybrid Neural Network Model for Sales Forecasting Based on ARIMA and Search Popularity of Article Titles.

PubMed

Omar, Hani; Hoang, Van Hai; Liu, Duen-Ren

2016-01-01

Enhancing sales and operations planning through forecasting analysis and business intelligence is demanded in many industries and enterprises. Publishing industries usually pick attractive titles and headlines for their stories to increase sales, since popular article titles and headlines can attract readers to buy magazines. In this paper, information retrieval techniques are adopted to extract words from article titles. The popularity measures of article titles are then analyzed by using the search indexes obtained from Google search engine. Backpropagation Neural Networks (BPNNs) have successfully been used to develop prediction models for sales forecasting. In this study, we propose a novel hybrid neural network model for sales forecasting based on the prediction result of time series forecasting and the popularity of article titles. The proposed model uses the historical sales data, popularity of article titles, and the prediction result of a time series, Autoregressive Integrated Moving Average (ARIMA) forecasting method to learn a BPNN-based forecasting model. Our proposed forecasting model is experimentally evaluated by comparing with conventional sales prediction techniques. The experimental result shows that our proposed forecasting method outperforms conventional techniques which do not consider the popularity of title words.

A Hybrid Neural Network Model for Sales Forecasting Based on ARIMA and Search Popularity of Article Titles

PubMed Central

Omar, Hani; Hoang, Van Hai; Liu, Duen-Ren

2016-01-01

Enhancing sales and operations planning through forecasting analysis and business intelligence is demanded in many industries and enterprises. Publishing industries usually pick attractive titles and headlines for their stories to increase sales, since popular article titles and headlines can attract readers to buy magazines. In this paper, information retrieval techniques are adopted to extract words from article titles. The popularity measures of article titles are then analyzed by using the search indexes obtained from Google search engine. Backpropagation Neural Networks (BPNNs) have successfully been used to develop prediction models for sales forecasting. In this study, we propose a novel hybrid neural network model for sales forecasting based on the prediction result of time series forecasting and the popularity of article titles. The proposed model uses the historical sales data, popularity of article titles, and the prediction result of a time series, Autoregressive Integrated Moving Average (ARIMA) forecasting method to learn a BPNN-based forecasting model. Our proposed forecasting model is experimentally evaluated by comparing with conventional sales prediction techniques. The experimental result shows that our proposed forecasting method outperforms conventional techniques which do not consider the popularity of title words. PMID:27313605

Stationarity test with a direct test for heteroskedasticity in exchange rate forecasting models

NASA Astrophysics Data System (ADS)

Khin, Aye Aye; Chau, Wong Hong; Seong, Lim Chee; Bin, Raymond Ling Leh; Teng, Kevin Low Lock

2017-05-01

Global economic has been decreasing in the recent years, manifested by the greater exchange rates volatility on international commodity market. This study attempts to analyze some prominent exchange rate forecasting models on Malaysian commodity trading: univariate ARIMA, ARCH and GARCH models in conjunction with stationarity test on residual diagnosis direct testing of heteroskedasticity. All forecasting models utilized the monthly data from 1990 to 2015. Given a total of 312 observations, the data used to forecast both short-term and long-term exchange rate. The forecasting power statistics suggested that the forecasting performance of ARIMA (1, 1, 1) model is more efficient than the ARCH (1) and GARCH (1, 1) models. For ex-post forecast, exchange rate was increased from RM 3.50 per USD in January 2015 to RM 4.47 per USD in December 2015 based on the baseline data. For short-term ex-ante forecast, the analysis results indicate a decrease in exchange rate on 2016 June (RM 4.27 per USD) as compared with 2015 December. A more appropriate forecasting method of exchange rate is vital to aid the decision-making process and planning on the sustainable commodities' production in the world economy.

Streamlining Collaborative Planning in Spacecraft Mission Architectures

NASA Technical Reports Server (NTRS)

Misra, Dhariti; Bopf, Michel; Fishman, Mark; Jones, Jeremy; Kerbel, Uri; Pell, Vince

2000-01-01

During the past two decades, the planning and scheduling community has substantially increased the capability and efficiency of individual planning and scheduling systems. Relatively recently, research work to streamline collaboration between planning systems is gaining attention. Spacecraft missions stand to benefit substantially from this work as they require the coordination of multiple planning organizations and planning systems. Up to the present time this coordination has demanded a great deal of human intervention and/or extensive custom software development efforts. This problem will become acute with increased requirements for cross-mission plan coordination and multi -spacecraft mission planning. The Advanced Architectures and Automation Branch of NASA's Goddard Space Flight Center is taking innovative steps to define collaborative planning architectures, and to identify coordinated planning tools for Cross-Mission Campaigns. Prototypes are being developed to validate these architectures and assess the usefulness of the coordination tools by the planning community. This presentation will focus on one such planning coordination too], named Visual Observation Layout Tool (VOLT), which is currently being developed to streamline the coordination between astronomical missions

Sources of information for tsunami forecasting in New Zealand

NASA Astrophysics Data System (ADS)

Barberopoulou, A.; Ristau, J. P.; D'Anastasio, E.; Wang, X.

2013-12-01

Tsunami science has evolved considerably in the last two decades due to technological advancements which also helped push for better numerical modelling of the tsunami phases (generation to inundation). The deployment of DART buoys has also been a considerable milestone in tsunami forecasting. Tsunami forecasting is one of the parts that tsunami modelling feeds into and is related to response, preparedness and planning. Usually tsunami forecasting refers to short-term forecasting that takes place in real-time after a tsunami has or appears to have been generated. In this report we refer to all types of forecasting (short-term or long-term) related to work in advance of a tsunami impacting a coastline that would help in response, planning or preparedness. We look at the standard types of data (seismic, GPS, water level) that are available in New Zealand for tsunami forecasting, how they are currently being used, other ways to use these data and provide recommendations for better utilisation. The main findings are: -Current investigations of the use of seismic parameters quickly obtained after an earthquake, have potential to provide critical information about the tsunamigenic potential of earthquakes. Further analysis of the most promising methods should be undertaken to determine a path to full implementation. -Network communication of the largest part of the GPS network is not currently at a stage that can provide sufficient data early enough for tsunami warning. It is believed that it has potential, but changes including data transmission improvements may have to happen before real-time processing oriented to tsunami early warning is implemented on the data that is currently provided. -Tide gauge data is currently under-utilised for tsunami forecasting. Spectral analysis, modal analysis based on identified modes and arrival times extracted from the records can be useful in forecasting. -The current study is by no means exhaustive of the ways the different types of data can be used. We are only presenting an overview of what can be done. More extensive studies with each one of the types of data collected by GeoNet and other relevant networks will help improve tsunami forecasting in New Zealand.

The Chicago to Iowa City intercity passenger rail route : business plan.

DOT National Transportation Integrated Search

2011-03-21

Business Plan Highlights : -No Iowa General Fund or RIIF appropriations : -State/local partnership : -Funds operation for the first 10 years : -Local cash commitment to passenger rail : -Conservative and practical financial forecasts : -Three compone...

Small city synthesis of transportation planning and economic development : user's guide

DOT National Transportation Integrated Search

1999-10-01

Using Alice, Texas, as a model, a template has been developed to increase the cooperation and communication between transportation planning and economic development groups. The template establishes a foundation for coordinating traffic forecasts with...

48 CFR 1807.7201 - Definitions.

Code of Federal Regulations, 2011 CFR

2011-10-01

... 48 Federal Acquisition Regulations System 6 2011-10-01 2011-10-01 false Definitions. 1807.7201 Section 1807.7201 Federal Acquisition Regulations System NATIONAL AERONAUTICS AND SPACE ADMINISTRATION COMPETITION AND ACQUISITION PLANNING ACQUISITION PLANNING Acquisition Forecasting 1807.7201 Definitions. Class...

Elementary Teachers' Perceptions of Appropriate Collaborative Planning and Professional Planning Time: A Case Study

ERIC Educational Resources Information Center

Wise, Kristi

2017-01-01

Professional Learning Communities (PLCs) are a best practice that has been around for decades; however, due to organizational structuring in elementary schools, teachers are allowed 30 minutes of planning time. During this time little planning or collaboration with peers is achieved. Previous research has proven that professional learning by way…

Exploration of Urban Spatial Planning Evaluation Based on Humanland Harmony

NASA Astrophysics Data System (ADS)

Hu, X. S.; Ma, Q. R.; Liang, W. Q.; Wang, C. X.; Xiong, X. Q.; Han, X. H.

2017-09-01

This study puts forward a new concept, "population urbanization level forecast - driving factor analysis - urban spatial planning analysis" for achieving efficient and intensive development of urbanization considering human-land harmony. We analyzed big data for national economic and social development, studied the development trends of population urbanization and its influencing factors using the grey system model in Chengmai county of Hainan province, China. In turn, we calculated the population of Chengmai coming years based on the forecasting urbanization rate and the corresponding amount of urban construction land, and evaluated the urban spatial planning with GIS spatial analysis method in the study area. The result shows that the proposed concept is feasible for evaluation of urban spatial planning, and is meaningful for guiding the rational distribution of urban space, controlling the scale of development, improving the quality of urbanization and thus promoting highly-efficient and intensive use of limited land resource.

An Airborne Conflict Resolution Approach Using a Genetic Algorithm

NASA Technical Reports Server (NTRS)

Mondoloni, Stephane; Conway, Sheila

2001-01-01

An airborne conflict resolution approach is presented that is capable of providing flight plans forecast to be conflict-free with both area and traffic hazards. This approach is capable of meeting constraints on the flight plan such as required times of arrival (RTA) at a fix. The conflict resolution algorithm is based upon a genetic algorithm, and can thus seek conflict-free flight plans meeting broader flight planning objectives such as minimum time, fuel or total cost. The method has been applied to conflicts occurring 6 to 25 minutes in the future in climb, cruise and descent phases of flight. The conflict resolution approach separates the detection, trajectory generation and flight rules function from the resolution algorithm. The method is capable of supporting pilot-constructed resolutions, cooperative and non-cooperative maneuvers, and also providing conflict resolution on trajectories forecast by an onboard FMC.

Public Higher Education Enrollment Forecasting in the State of Ohio.

ERIC Educational Resources Information Center

Render, Barry

With the growing concern for the development of good mathematical education planning models, few states have developed the type of enrollment projection systems that they would consider to be ideal. The primary objectives of this research project were to develop, construct, and document an enrollment forecasting system for use by the Ohio Board of…

Identifying, Tracking, and Prioritizing Parts Unavailability

DTIC Science & Technology

2013-03-01

of RFM with MRP Equivalents in Parentheses ................ 13 Figure 2. Flow Chart of Repair Process...by the Air Force is the Reparability Forecast Model (RFM). The RFM operates similar to a Material Requirements Planning ( MRP ) system, where it...Outputs of RFM with MRP Equivalents in Parentheses (Gaudette et al, 2002: 7) The Reparability Forecast Model does not determine stock levels or

Health Sciences Libraries Forecasting Information Service Trends for Researchers: Models Applicable to All Academic Libraries

ERIC Educational Resources Information Center

Cain, Timothy J.; Cheek, Fern M.; Kupsco, Jeremy; Hartel, Lynda J.; Getselman, Anna

2016-01-01

To better understand the value of current information services and to forecast the evolving information and data management needs of researchers, a study was conducted at two research-intensive universities. The methodology and planning framework applied by health science librarians at Emory University and The Ohio State University focused on…

The First Six Months: PDEM Innovations in Forecasting Higher Education, January to July 1972.

ERIC Educational Resources Information Center

Hoffman, Benjamin B.

A Postsecondary Demand Survey was undertaken in 1972 to study the demand for postsecondary education in Manitoba, Canada, and to develop a system for forecasting enrollment at postsecondary institutions. The survey objective was to establish a profile of grade 12 students in 1972 to learn about their aspirations, plans, expectations after…

Modelling Levels of Collaboration Among Health and Social Care Professionals in the Management of a Mental Health Plan.

PubMed

Luzi, Daniela; Pecoraro, Fabrizio; Tamburis, Oscar

2018-01-01

Professional collaboration among health and social care providers is considered an essential pattern to improve the integration of care. This is particularly important considering the planning activities for children with complex conditions. In this paper the level of collaboration among professionals in the development and implementation of the personalized plan in the mental health domain is analysed across 30 EU/EEA countries within the MOCHA project.

Time Series Analysis for Forecasting Hospital Census: Application to the Neonatal Intensive Care Unit

PubMed Central

Hoover, Stephen; Jackson, Eric V.; Paul, David; Locke, Robert

2016-01-01

Summary Background Accurate prediction of future patient census in hospital units is essential for patient safety, health outcomes, and resource planning. Forecasting census in the Neonatal Intensive Care Unit (NICU) is particularly challenging due to limited ability to control the census and clinical trajectories. The fixed average census approach, using average census from previous year, is a forecasting alternative used in clinical practice, but has limitations due to census variations. Objective Our objectives are to: (i) analyze the daily NICU census at a single health care facility and develop census forecasting models, (ii) explore models with and without patient data characteristics obtained at the time of admission, and (iii) evaluate accuracy of the models compared with the fixed average census approach. Methods We used five years of retrospective daily NICU census data for model development (January 2008 – December 2012, N=1827 observations) and one year of data for validation (January – December 2013, N=365 observations). Best-fitting models of ARIMA and linear regression were applied to various 7-day prediction periods and compared using error statistics. Results The census showed a slightly increasing linear trend. Best fitting models included a non-seasonal model, ARIMA(1,0,0), seasonal ARIMA models, ARIMA(1,0,0)x(1,1,2)7 and ARIMA(2,1,4)x(1,1,2)14, as well as a seasonal linear regression model. Proposed forecasting models resulted on average in 36.49% improvement in forecasting accuracy compared with the fixed average census approach. Conclusions Time series models provide higher prediction accuracy under different census conditions compared with the fixed average census approach. Presented methodology is easily applicable in clinical practice, can be generalized to other care settings, support short- and long-term census forecasting, and inform staff resource planning. PMID:27437040

Time Series Analysis for Forecasting Hospital Census: Application to the Neonatal Intensive Care Unit.

PubMed

Capan, Muge; Hoover, Stephen; Jackson, Eric V; Paul, David; Locke, Robert

2016-01-01

Accurate prediction of future patient census in hospital units is essential for patient safety, health outcomes, and resource planning. Forecasting census in the Neonatal Intensive Care Unit (NICU) is particularly challenging due to limited ability to control the census and clinical trajectories. The fixed average census approach, using average census from previous year, is a forecasting alternative used in clinical practice, but has limitations due to census variations. Our objectives are to: (i) analyze the daily NICU census at a single health care facility and develop census forecasting models, (ii) explore models with and without patient data characteristics obtained at the time of admission, and (iii) evaluate accuracy of the models compared with the fixed average census approach. We used five years of retrospective daily NICU census data for model development (January 2008 - December 2012, N=1827 observations) and one year of data for validation (January - December 2013, N=365 observations). Best-fitting models of ARIMA and linear regression were applied to various 7-day prediction periods and compared using error statistics. The census showed a slightly increasing linear trend. Best fitting models included a non-seasonal model, ARIMA(1,0,0), seasonal ARIMA models, ARIMA(1,0,0)x(1,1,2)7 and ARIMA(2,1,4)x(1,1,2)14, as well as a seasonal linear regression model. Proposed forecasting models resulted on average in 36.49% improvement in forecasting accuracy compared with the fixed average census approach. Time series models provide higher prediction accuracy under different census conditions compared with the fixed average census approach. Presented methodology is easily applicable in clinical practice, can be generalized to other care settings, support short- and long-term census forecasting, and inform staff resource planning.

Next Day Price Forecasting in Deregulated Market by Combination of Artificial Neural Network and ARIMA Time Series Models

NASA Astrophysics Data System (ADS)

Areekul, Phatchakorn; Senjyu, Tomonobu; Urasaki, Naomitsu; Yona, Atsushi

Electricity price forecasting is becoming increasingly relevant to power producers and consumers in the new competitive electric power markets, when planning bidding strategies in order to maximize their benefits and utilities, respectively. This paper proposed a method to predict hourly electricity prices for next-day electricity markets by combination methodology of ARIMA and ANN models. The proposed method is examined on the Australian National Electricity Market (NEM), New South Wales regional in year 2006. Comparison of forecasting performance with the proposed ARIMA, ANN and combination (ARIMA-ANN) models are presented. Empirical results indicate that an ARIMA-ANN model can improve the price forecasting accuracy.

USA Nutrient managment forecasting via the "Fertilizer Forecaster": linking surface runnof, nutrient application and ecohydrology.

NASA Astrophysics Data System (ADS)

Drohan, Patrick; Buda, Anthony; Kleinman, Peter; Miller, Douglas; Lin, Henry; Beegle, Douglas; Knight, Paul

2017-04-01

USA and state nutrient management planning offers strategic guidance that strives to educate farmers and those involved in nutrient management to make wise management decisions. A goal of such programs is to manage hotspots of water quality degradation that threaten human and ecosystem health, water and food security. The guidance provided by nutrient management plans does not provide the day-to-day support necessary to make operational decisions, particularly when and where to apply nutrients over the short term. These short-term decisions on when and where to apply nutrients often make the difference between whether the nutrients impact water quality or are efficiently utilized by crops. Infiltrating rainfall events occurring shortly after broadcast nutrient applications are beneficial, given they will wash soluble nutrients into the soil where they are used by crops. Rainfall events that generate runoff shortly after nutrients are broadcast may wash off applied nutrients, and produce substantial nutrient losses from that site. We are developing a model and data based support tool for nutrient management, the Fertilizer Forecaster, which identifies the relative probability of runoff or infiltrating events in Pennsylvania (PA) landscapes in order to improve water quality. This tool will support field specific decisions by farmers and land managers on when and where to apply fertilizers and manures over 24, 48 and 72 hour periods. Our objectives are to: (1) monitor agricultural hillslopes in watersheds representing four of the five Physiographic Provinces of the Chesapeake Bay basin; (2) validate a high resolution mapping model that identifies soils prone to runoff; (3) develop an empirically based approach to relate state-of-the-art weather forecast variables to site-specific rainfall infiltration or runoff occurrence; (4) test the empirical forecasting model against alternative approaches to forecasting runoff occurrence; and (5) recruit farmers from the four watersheds to use web-based forecast maps in daily manure and fertilizer application decisions. Data from on-farm trials is being used to assess farmer fertilizer, manure, and tillage management decisions before and after use of the Fertilizer Forecaster. This data will help us understand not only the effectiveness of the tool, but also characteristics of farmers with the greatest potential to benefit from such a tool. Feedback from on-farm trials will be used to refine a final tool for field deployment. We hope that the Fertilizer Forecaster will serve as the basis for state (USA-PA), regional (Chesapeake Bay), and national changes in nutrient management planning. This Fertilizer Forecaster is an innovative management practice that is designed to enhance the services of aquatic ecosystems by improving water quality and enhance the services of terrestrial ecosystems by increasing the efficiency of nutrient use by targeted crops.

Progress and Challenges in Short to Medium Range Coupled Prediction

NASA Technical Reports Server (NTRS)

Brassington, G. B.; Martin, M. J.; Tolman, H. L.; Akella, Santha; Balmeseda, M.; Chambers, C. R. S.; Cummings, J. A.; Drillet, Y.; Jansen, P. A. E. M.; Laloyaux, P.;

Using Sensor Web Processes and Protocols to Assimilate Satellite Data into a Forecast Model

NASA Technical Reports Server (NTRS)

Goodman, H. Michael; Conover, Helen; Zavodsky, Bradley; Maskey, Manil; Jedlovec, Gary; Regner, Kathryn; Li, Xiang; Lu, Jessica; Botts, Mike; Berthiau, Gregoire

2008-01-01

The goal of the Sensor Management Applied Research Technologies (SMART) On-Demand Modeling project is to develop and demonstrate the readiness of the Open Geospatial Consortium (OGC) Sensor Web Enablement (SWE) capabilities to integrate both space-based Earth observations and forecast model output into new data acquisition and assimilation strategies. The project is developing sensor web-enabled processing plans to assimilate Atmospheric Infrared Sounding (AIRS) satellite temperature and moisture retrievals into a regional Weather Research and Forecast (WRF) model over the southeastern United States.

Study to forecast and determine characteristics of world satellite communications market

NASA Technical Reports Server (NTRS)

Filep, R. T.; Schnapf, A.; Fordyce, S. W.

1983-01-01

The world commercial communications satellite market during the spring and summer of 1983 was examined and characteristics and forecasts of the market extending to the year 2000 were developed. Past, present and planned satellites were documented in relation to frequencies, procurement and launch dates, costs, transponders, and prime contractor. Characteristics of the market are outlined for the periods 1965 - 1985, 1986 - 1989, and 1990 - 2000. Market share forecasts, discussions of potential competitors in various world markets, and profiles of major communication satellite manufacturing and user countries are documented.

Burning through organizational boundaries? Examining inter-organizational communication networks in policy-mandated collaborative bushfire planning groups

Treesearch

Rachel F. Brummel; Kristen C. Nelson; Pamela J. Jakes

2012-01-01

Collaboration can enhance cooperation across geographic and organizational scales, effectively "burning through" those boundaries. Using structured social network analysis (SNA) and qualitative in-depth interviews, this study examined three collaborative bushfire planning groups in New South Wales, Australia and asked: How does participation in policy-...

Daily Peak Load Forecasting of Next Day using Weather Distribution and Comparison Value of Each Nearby Date Data

NASA Astrophysics Data System (ADS)

Ito, Shigenobu; Yukita, Kazuto; Goto, Yasuyuki; Ichiyanagi, Katsuhiro; Nakano, Hiroyuki

By the development of industry, in recent years; dependence to electric energy is growing year by year. Therefore, reliable electric power supply is in need. However, to stock a huge amount of electric energy is very difficult. Also, there is a necessity to keep balance between the demand and supply, which changes hour after hour. Consequently, to supply the high quality and highly dependable electric power supply, economically, and with high efficiency, there is a need to forecast the movement of the electric power demand carefully in advance. And using that forecast as the source, supply and demand management plan should be made. Thus load forecasting is said to be an important job among demand investment of electric power companies. So far, forecasting method using Fuzzy logic, Neural Net Work, Regression model has been suggested for the development of forecasting accuracy. Those forecasting accuracy is in a high level. But to invest electric power in higher accuracy more economically, a new forecasting method with higher accuracy is needed. In this paper, to develop the forecasting accuracy of the former methods, the daily peak load forecasting method using the weather distribution of highest and lowest temperatures, and comparison value of each nearby date data is suggested.

Hydrologic Forecasting in the 21st Century: Challenges and Directions of Research

NASA Astrophysics Data System (ADS)

Restrepo, P.; Schaake, J.

2009-04-01

Traditionally, the role of the Hydrology program of the National Weather Service has been centered around forecasting floods, in order to minimize loss of lives and damage to property as a result of floods as well as water levels for navigable rivers, and water supply in some areas of the country. A number of factors, including shifting population patterns, widespread drought and concerns about climate change have made it imperative to widen the focus to cover forecasting flows ranging from drought to floods and anything in between. Because of these concerns, it is imperative to develop models that rely more on the physical characteristics of the watershed for parameterization and less on historical observations. Furthermore, it is also critical to consider explicitly the sources of uncertainty in the forecasting process, including parameter values, model structure, forcings (both observations and forecasts), initial conditions, and streamflow observations. A consequence of more widespread occurrence of low flows as a result either of the already evident earlier snowmelt in the Western United States, or of the predicted changes in precipitation patterns, is the issue of water quality: lower flows will have higher concentrations of certain pollutants. This paper describes the current projects and future directions of research for hydrologic forecasting in the United States. Ongoing projects on quantitative precipitation and temperature estimates and forecasts, uncertainty modeling by the use of ensembles, data assimilation, verification, distributed conceptual modeling will be reviewed. Broad goals of the research directions are: 1) reliable modeling of the different sources of uncertainty. 2) a more expeditious and cost-effective approach by reducing the effort required in model calibration; 3) improvements in forecast lead-time and accuracy; 4) an approach for rapid adjustment of model parameters to account for changes in the watershed, both rapid as the result from forest fires or levee breaches, and slow, as the result of watershed reforestation, reforestation or urban development; 5) an expanded suite of products, including soil moisture and temperature forecasts, and water quality constituents; and 6) a comprehensive verification system to assess the effectiveness of the other 5 goals. To this end, the research plan places an emphasis on research of models with parameters that can be derived from physical watershed characteristics. Purely physically based models may be unattainable or impractical, and, therefore, models resulting from a combination of physically and conceptually approached processes may be required With respect to the hydrometeorological forcings the research plan emphasizes the development of improved precipitation estimation techniques through the synthesis of radar, rain gauge, satellite, and numerical weather prediction model output, particularly in those areas where ground-based sensors are inadequate to detect spatial variability in precipitation. Better estimation and forecasting of precipitation are most likely to be achieved by statistical merging of remote-sensor observations and forecasts from high-resolution numerical prediction models. Enhancements to the satellite-based precipitation products will include use of TRMM precipitation data in preparation for information to be supplied by the Global Precipitation Mission satellites not yet deployed. Because of a growing need for services in water resources, including low-flow forecasts for water supply customers, we will be directing research into coupled surface-groundwater models that will eventually replace the groundwater component of the existing models, and will be part of the new generation of models. Finally, the research plan covers the directions of research for probabilistic forecasting using ensembles, data assimilation and the verification and validation of both deterministic and probabilistic forecasts.

The Promise of Collaboration

ERIC Educational Resources Information Center

Bauml, Michelle

2016-01-01

Whether a teacher loves it or dreads it, lesson planning is a crucial step in the teaching process. Done effectively, collaborative lesson planning--in which teachers work together to design lessons--leads to increased professional learning, higher job satisfaction for teachers, and better lesson plans. The process poses challenges for both…

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.

Physics-based Space Weather Forecasting in the Project for Solar-Terrestrial Environment Prediction (PSTEP) in Japan

NASA Astrophysics Data System (ADS)

Kusano, K.

2016-12-01

Project for Solar-Terrestrial Environment Prediction (PSTEP) is a Japanese nation-wide research collaboration, which was recently launched. PSTEP aims to develop a synergistic interaction between predictive and scientific studies of the solar-terrestrial environment and to establish the basis for next-generation space weather forecasting using the state-of-the-art observation systems and the physics-based models. For this project, we coordinate the four research groups, which develop (1) the integration of space weather forecast system, (2) the physics-based solar storm prediction, (3) the predictive models of magnetosphere and ionosphere dynamics, and (4) the model of solar cycle activity and its impact on climate, respectively. In this project, we will build the coordinated physics-based model to answer the fundamental questions concerning the onset of solar eruptions and the mechanism for radiation belt dynamics in the Earth's magnetosphere. In this paper, we will show the strategy of PSTEP, and discuss about the role and prospect of the physics-based space weather forecasting system being developed by PSTEP.

FY 1996 solid waste integrated life-cycle forecast characteristics summary. Volumes 1 and 2

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

Templeton, K.J.

1996-05-23

For the past six years, a waste volume forecast has been collected annually from onsite and offsite generators that currently ship or are planning to ship solid waste to the Westinghouse Hanford Company`s Central Waste Complex (CWC). This document provides a description of the physical waste forms, hazardous waste constituents, and radionuclides of the waste expected to be shipped to the CWC from 1996 through the remaining life cycle of the Hanford Site (assumed to extend to 2070). In previous years, forecast data has been reported for a 30-year time period; however, the life-cycle approach was adopted this year tomore » maintain consistency with FY 1996 Multi-Year Program Plans. This document is a companion report to two previous reports: the more detailed report on waste volumes, WHC-EP-0900, FY1996 Solid Waste Integrated Life-Cycle Forecast Volume Summary and the report on expected containers, WHC-EP-0903, FY1996 Solid Waste Integrated Life-Cycle Forecast Container Summary. All three documents are based on data gathered during the FY 1995 data call and verified as of January, 1996. These documents are intended to be used in conjunction with other solid waste planning documents as references for short and long-term planning of the WHC Solid Waste Disposal Division`s treatment, storage, and disposal activities over the next several decades. This document focuses on two main characteristics: the physical waste forms and hazardous waste constituents of low-level mixed waste (LLMW) and transuranic waste (both non-mixed and mixed) (TRU(M)). The major generators for each waste category and waste characteristic are also discussed. The characteristics of low-level waste (LLW) are described in Appendix A. In addition, information on radionuclides present in the waste is provided in Appendix B. The FY 1996 forecast data indicate that about 100,900 cubic meters of LLMW and TRU(M) waste is expected to be received at the CWC over the remaining life cycle of the site. Based on ranges provided by the waste generators, this baseline volume could fluctuate between a minimum of about 59,720 cubic meters and a maximum of about 152,170 cubic meters. The range is primarily due to uncertainties associated with the Tank Waste Remediation System (TWRS) program, including uncertainties regarding retrieval of long-length equipment, scheduling, and tank retrieval technologies.« less

The Continuing Seminar on Organizational Planning and Policy Analysis: Implications for Community College Planning Offices.

ERIC Educational Resources Information Center

Morrison, James L.

At the University of North Carolina at Chapel Hill, a seminar on planning and policy analysis is offered for doctoral students who wish to conduct planning and forecasting studies for their doctoral dissertations or who simply wish to learn such techniques. One of the major projects of the seminar is the development of an environmental scanning…

A real-time evaluation and demonstration of strategies for 'Over-The-Loop' ensemble streamflow forecasting in US watersheds

NASA Astrophysics Data System (ADS)

Wood, Andy; Clark, Elizabeth; Mendoza, Pablo; Nijssen, Bart; Newman, Andy; Clark, Martyn; Nowak, Kenneth; Arnold, Jeffrey

2017-04-01

Many if not most national operational streamflow prediction systems rely on a forecaster-in-the-loop approach that require the hands-on-effort of an experienced human forecaster. This approach evolved from the need to correct for long-standing deficiencies in the models and datasets used in forecasting, and the practice often leads to skillful flow predictions despite the use of relatively simple, conceptual models. Yet the 'in-the-loop' forecast process is not reproducible, which limits opportunities to assess and incorporate new techniques systematically, and the effort required to make forecasts in this way is an obstacle to expanding forecast services - e.g., though adding new forecast locations or more frequent forecast updates, running more complex models, or producing forecast and hindcasts that can support verification. In the last decade, the hydrologic forecasting community has begun develop more centralized, 'over-the-loop' systems. The quality of these new forecast products will depend on their ability to leverage research in areas including earth system modeling, parameter estimation, data assimilation, statistical post-processing, weather and climate prediction, verification, and uncertainty estimation through the use of ensembles. Currently, many national operational streamflow forecasting and water management communities have little experience with the strengths and weaknesses of over-the-loop approaches, even as such systems are beginning to be deployed operationally in centers such as ECMWF. There is thus a need both to evaluate these forecasting advances and to demonstrate their potential in a public arena, raising awareness in forecast user communities and development programs alike. To address this need, the US National Center for Atmospheric Research is collaborating with the University of Washington, the Bureau of Reclamation and the US Army Corps of Engineers, using the NCAR 'System for Hydromet Analysis Research and Prediction Applications' (SHARP) to implement, assess and demonstrate real-time over-the-loop ensemble flow forecasts in a range of US watersheds. The system relies on fully ensemble techniques, including: an 100-member ensemble of meteorological model forcings and an ensemble particle filter data assimilation for initializing watershed states; analog/regression-based downscaling of ensemble weather forecasts from GEFS; and statistical post-processing of ensemble forecast outputs, all of which run in real-time within a workflow managed by ECWMF's ecFlow libraries over large US regional domains. We describe SHARP and present early hindcast and verification results for short to seasonal range streamflow forecasts in a number of US case study watersheds.

Collaborative Science: Human Sensor Networks for Real-time Natural Disaster Prediction

NASA Astrophysics Data System (ADS)

Halem, M.; Yesha, Y.; Aulov, O.; Martineau, J.; Brown, S.; Conte, T.; CenterHybrid Multicore Productivity Research

2010-12-01

We have implemented a ‘Human Sensor Network’ as a real time collaborative science data observing system by collecting and integrating the vast untapped information potential of digital social media data sources occurring during the oil spill situation arising from the Macondo well in the Gulf of Mexico. We collected, and archived blogs, Twitter status updates (aka tweets), photographs posted to Flicker, and videos posted to YouTube related to the Gulf oil spill and processed the meta data, text, and photos to extract quantitative physical data such as locations and estimates of the severity and dispersion of oil being collected on the beaches and marshes, frequencies of observations of tar ball sightings, correlations of sightings from different media, numbers of dead or distressed animals, trends, etc. These data were then introduced into the NOAA operational Gnome oil spill predictive model as time dependent boundary conditions employing a 2-D variational data assimilation scheme. The three participating institutions employed a distributed cloud computing system for the processing and model executions. In this presentation, we conducted preliminary forecast impact tests of the Gnome model with and without the use of social media data using a 2-D variational data assimilation technique. The 2-D VAR is used to adjust the state variables of the model by recursively minimizing the differences between oil spill predictions reaching locations across the entire coastlines of the Gulf of Mexico and the estimated positions of oil derived from analyzed social media data. Ensemble forecasts will be performed to provide estimates of the rates of oil and surface oil distributions emanating from the Deepwater Horizon. We display the derived predictions from the photos and animations from Flicker, YouTube, and extracted content from tweets and blogs in a dynamic representation on very large tiled walls of LCDs at the UCSD Cal IT2 visualization facility. We describe the processing systems used to extract the physical quantifiable data from the “human sensor network” such as natural language tools, the semantic web, image analysis techniques which can be employed to form a collaborative framework for other real time situation analysis undergoing similar natural or human caused disasters. We believe this innovative approach of extracting geophysical data from the social media sources is unprecedented in bridging geosciences with social sciences. In the near future, we plan on expanding the collaboration with researchers from University of Minnesota (U/MN) and Florida International University(FIU). Currently U/MN is working on a project of deploying aquabots (aquatic robots) in the Gulf in order to sample water properties at different depths as well as on the surface and FIU has developed a real time Terrafly processing system incorporating high resolution commercial and gov’t satellites and aircraft data.

Small area population forecasting: some experience with British models.

PubMed

Openshaw, S; Van Der Knaap, G A

1983-01-01

This study is concerned with the evaluation of the various models including time-series forecasts, extrapolation, and projection procedures, that have been developed to prepare population forecasts for planning purposes. These models are evaluated using data for the Netherlands. "As part of a research project at the Erasmus University, space-time population data has been assembled in a geographically consistent way for the period 1950-1979. These population time series are of sufficient length for the first 20 years to be used to build models and then evaluate the performance of the model for the next 10 years. Some 154 different forecasting models for 832 municipalities have been evaluated. It would appear that the best forecasts are likely to be provided by either a Holt-Winters model, or a ratio-correction model, or a low order exponential-smoothing model." excerpt

Evaluation of origin-destination matrix estimation techniques to support aspects of traffic modeling.

DOT National Transportation Integrated Search

2014-05-01

Travel demand forecasting models are used to predict future traffic volumes to evaluate : roadway improvement alternatives. Each of the metropolitan planning organizations (MPO) in : Alabama maintains a travel demand model to support planning efforts...

Virtual Collaboration: Advantages and Disadvantages in the Planning and Execution of Operations in the Information Age

DTIC Science & Technology

2004-02-09

FINAL 3. DATES COVERED (From - To) 4. TITLE AND SUBTITLE VIRTUAL COLLABORATION: 5a. CONTRACT NUMBER ADVANTAGES AND DISADVANTAGES IN THE PLANNING AND...warfare is not one system; it is a system of systems from sensors to information flow. In analyzing the specific advantages and disadvantages of one of...Standard Form 298 (Rev. 8-98) NAVAL WAR COLLEGE Newport, R.I. VIRTUAL COLLABORATION: ADVANTAGES AND DISADVANTAGES IN THE PLANNING AND EXECUTION OF OPERATIONS

Fine‐resolution conservation planning with limited climate‐change information

USGS Publications Warehouse

Shah, Payal; Mallory, Mindy L.; Ando , Amy W.; Guntenspergen, Glenn R.

2017-01-01

Climate‐change induced uncertainties in future spatial patterns of conservation‐related outcomes make it difficult to implement standard conservation‐planning paradigms. A recent study translates Markowitz's risk‐diversification strategy from finance to conservation settings, enabling conservation agents to use this diversification strategy for allocating conservation and restoration investments across space to minimize the risk associated with such uncertainty. However, this method is information intensive and requires a large number of forecasts of ecological outcomes associated with possible climate‐change scenarios for carrying out fine‐resolution conservation planning. We developed a technique for iterative, spatial portfolio analysis that can be used to allocate scarce conservation resources across a desired level of subregions in a planning landscape in the absence of a sufficient number of ecological forecasts. We applied our technique to the Prairie Pothole Region in central North America. A lack of sufficient future climate information prevented attainment of the most efficient risk‐return conservation outcomes in the Prairie Pothole Region. The difference in expected conservation returns between conservation planning with limited climate‐change information and full climate‐change information was as large as 30% for the Prairie Pothole Region even when the most efficient iterative approach was used. However, our iterative approach allowed finer resolution portfolio allocation with limited climate‐change forecasts such that the best possible risk‐return combinations were obtained. With our most efficient iterative approach, the expected loss in conservation outcomes owing to limited climate‐change information could be reduced by 17% relative to other iterative approaches.

Enrollment Planning Using Computer Decision Model: A Case Study at Grambling State University.

ERIC Educational Resources Information Center

Ghosh, Kalyan; Lundy, Harold W.

Achieving enrollment goals continues to be a major administrative concern in higher education. Enrollment management can be assisted through the use of computerized planning and forecast models. Although commercially available Markov transition type curve fitting models have been developed and used, a microcomputer-based decision planning model…

Establishing an Environmental Scanning System to Augment College and University Planning.

ERIC Educational Resources Information Center

Morrison, James L.

A plan to establish an environmental scanning and forecasting system for colleges and universities is discussed as a way to maximize long-range planning. After proposing a program structure, attention is directed to methods of gaining organizational acceptance, developing a comprehensive taxonomy with an electronic filing system, identifying and…

Comparative analysis of operational forecasts versus actual weather conditions in airline flight planning, volume 2

NASA Technical Reports Server (NTRS)

Keitz, J. F.

1982-01-01

The impact of more timely and accurate weather data on airline flight planning with the emphasis on fuel savings is studied. This volume of the report discusses the results of Task 2 of the four major tasks included in the study. Task 2 compares various catagories of flight plans and flight tracking data produced by a simulation system developed for the Federal Aviation Administrations by SRI International. (Flight tracking data simulate actual flight tracks of all aircraft operating at a given time and provide for rerouting of flights as necessary to resolve traffic conflicts.) The comparisons of flight plans on the forecast to flight plans on the verifying analysis confirm Task 1 findings that wind speeds are generally underestimated. Comparisons involving flight tracking data indicate that actual fuel burn is always higher than planned, in either direction, and even when the same weather data set is used. Since the flight tracking model output results in more diversions than is known to be the case, it was concluded that there is an error in the flight tracking algorithm.

Forecasting the Revenues of Local Public Health Departments in the Shadows of the ‘Great Recession’

PubMed Central

Reschovsky, Andrew; Zahner, Susan J.

2015-01-01

Context The ability of local health departments (LHD) to provide core public health services depends on a reliable stream of revenue from federal, state, and local governments. This study investigates the impact of the “Great Recession” on major sources of LHD revenues and develops a fiscal forecasting model to predict revenues to LHDs in one state over the period 2012 to 2014. Economic forecasting offers a new financial planning tool for LHD administrators and local government policy-makers. This study represents a novel research application for these econometric methods. Methods Detailed data on revenues by source for each LHD in Wisconsin were taken from annual surveys conducted by the Wisconsin Department of Health Services over an eight year period (2002-2009). A forecasting strategy appropriate for each revenue source was developed resulting in “base case” estimates. An analysis of the sensitivity of these revenue forecasts to a set of alternative fiscal policies by the federal, state, and local governments was carried out. Findings The model forecasts total LHD revenues in 2012 of $170.5 million (in 2010 dollars). By 2014 inflation-adjusted revenues will decline by $8 million, a reduction of 4.7 percent. Because of population growth, per capita real revenues of LHDs are forecast to decline by 6.6 percent between 2012 and 2014. There is a great deal of uncertainty about the future of federal funding in support of local public health. A doubling of the reductions in federal grants scheduled under current law would result in an additional $4.4 million decline in LHD revenues in 2014. Conclusions The impact of the Great Recession continues to haunt LHDs. Multi-year revenue forecasting offers a new financial tool to help LHDs better plan for an environment of declining resources. New revenue sources are needed if sharp drops in public health service delivery are to be avoided. PMID:23531611

The FASTER Approach: A New Tool for Calculating Real-Time Tsunami Flood Hazards

NASA Astrophysics Data System (ADS)

Wilson, R. I.; Cross, A.; Johnson, L.; Miller, K.; Nicolini, T.; Whitmore, P.

2014-12-01

In the aftermath of the 2010 Chile and 2011 Japan tsunamis that struck the California coastline, emergency managers requested that the state tsunami program provide more detailed information about the flood potential of distant-source tsunamis well ahead of their arrival time. The main issue is that existing tsunami evacuation plans call for evacuation of the predetermined "worst-case" tsunami evacuation zone (typically at a 30- to 50-foot elevation) during any "Warning" level event; the alternative is to not call an evacuation at all. A solution to provide more detailed information for secondary evacuation zones has been the development of tsunami evacuation "playbooks" to plan for tsunami scenarios of various sizes and source locations. To determine a recommended level of evacuation during a distant-source tsunami, an analytical tool has been developed called the "FASTER" approach, an acronym for factors that influence the tsunami flood hazard for a community: Forecast Amplitude, Storm, Tides, Error in forecast, and the Run-up potential. Within the first couple hours after a tsunami is generated, the National Tsunami Warning Center provides tsunami forecast amplitudes and arrival times for approximately 60 coastal locations in California. At the same time, the regional NOAA Weather Forecast Offices in the state calculate the forecasted coastal storm and tidal conditions that will influence tsunami flooding. Providing added conservatism in calculating tsunami flood potential, we include an error factor of 30% for the forecast amplitude, which is based on observed forecast errors during recent events, and a site specific run-up factor which is calculated from the existing state tsunami modeling database. The factors are added together into a cumulative FASTER flood potential value for the first five hours of tsunami activity and used to select the appropriate tsunami phase evacuation "playbook" which is provided to each coastal community shortly after the forecast is provided.

Forecasting the Revenues of Local Public Health Departments in the Shadows of the "Great Recession".

PubMed

Reschovsky, Andrew; Zahner, Susan J

2016-01-01

The ability of local health departments (LHD) to provide core public health services depends on a reliable stream of revenue from federal, state, and local governments. This study investigates the impact of the "Great Recession" on major sources of LHD revenues and develops a fiscal forecasting model to predict revenues to LHDs in one state over the period 2012 to 2014. Economic forecasting offers a new financial planning tool for LHD administrators and local government policy makers. This study represents a novel research application for these econometric methods. Detailed data on revenues by source for each LHD in Wisconsin were taken from annual surveys conducted by the Wisconsin Department of Health Services over an 8-year period (2002-2009). A forecasting strategy appropriate for each revenue source was developed resulting in "base case" estimates. An analysis of the sensitivity of these revenue forecasts to a set of alternative fiscal policies by the federal, state, and local governments was carried out. The model forecasts total LHD revenues in 2012 of $170.5 million (in 2010 dollars). By 2014, inflation-adjusted revenues will decline by $8 million, a reduction of 4.7%. Because of population growth, per capita real revenues of LHDs are forecast to decline by 6.6% between 2012 and 2014. There is a great deal of uncertainty about the future of federal funding in support of local public health. A doubling of the reductions in federal grants scheduled under current law would result in an additional $4.4 million decline in LHD revenues in 2014. The impact of the Great Recession continues to haunt LHDs. Multiyear revenue forecasting offers a new financial tool to help LHDs better plan for an environment of declining resources. New revenue sources are needed if sharp drops in public health service delivery are to be avoided.

Type- and Subtype-Specific Influenza Forecast.

PubMed

Kandula, Sasikiran; Yang, Wan; Shaman, Jeffrey

2017-03-01

Prediction of the growth and decline of infectious disease incidence has advanced considerably in recent years. As these forecasts improve, their public health utility should increase, particularly as interventions are developed that make explicit use of forecast information. It is the task of the research community to increase the content and improve the accuracy of these infectious disease predictions. Presently, operational real-time forecasts of total influenza incidence are produced at the municipal and state level in the United States. These forecasts are generated using ensemble simulations depicting local influenza transmission dynamics, which have been optimized prior to forecast with observations of influenza incidence and data assimilation methods. Here, we explore whether forecasts targeted to predict influenza by type and subtype during 2003-2015 in the United States were more or less accurate than forecasts targeted to predict total influenza incidence. We found that forecasts separated by type/subtype generally produced more accurate predictions and, when summed, produced more accurate predictions of total influenza incidence. These findings indicate that monitoring influenza by type and subtype not only provides more detailed observational content but supports more accurate forecasting. More accurate forecasting can help officials better respond to and plan for current and future influenza activity. © The Author 2017. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Manifestations of Metacognitive Activity during the Collaborative Planning of Chemistry Practical Investigations

ERIC Educational Resources Information Center

Mathabathe, Kgadi Clarrie; Potgieter, Marietjie

2017-01-01

This paper elaborates a process followed to characterise manifestations of cognitive regulation during the collaborative planning of chemistry practical investigations. Metacognitive activity was defined as the demonstration of planning, monitoring, control and evaluation of cognitive activities by students while carrying out the chemistry task.…

Collaborative Lesson Planning as Professional Development for Beginning Primary Teachers

ERIC Educational Resources Information Center

Bauml, Michelle

2014-01-01

This qualitative case study describes how one beginning primary grade teacher benefited from collaborative lesson-planning meetings with her grade-level colleagues. The teacher accumulated knowledge of curriculum, pedagogy, and professional contexts as she participated in planning meetings each week during her first year of teaching. Furthermore,…

Hydrological time series modeling: A comparison between adaptive neuro-fuzzy, neural network and autoregressive techniques

NASA Astrophysics Data System (ADS)

Lohani, A. K.; Kumar, Rakesh; Singh, R. D.

2012-06-01

SummaryTime series modeling is necessary for the planning and management of reservoirs. More recently, the soft computing techniques have been used in hydrological modeling and forecasting. In this study, the potential of artificial neural networks and neuro-fuzzy system in monthly reservoir inflow forecasting are examined by developing and comparing monthly reservoir inflow prediction models, based on autoregressive (AR), artificial neural networks (ANNs) and adaptive neural-based fuzzy inference system (ANFIS). To take care the effect of monthly periodicity in the flow data, cyclic terms are also included in the ANN and ANFIS models. Working with time series flow data of the Sutlej River at Bhakra Dam, India, several ANN and adaptive neuro-fuzzy models are trained with different input vectors. To evaluate the performance of the selected ANN and adaptive neural fuzzy inference system (ANFIS) models, comparison is made with the autoregressive (AR) models. The ANFIS model trained with the input data vector including previous inflows and cyclic terms of monthly periodicity has shown a significant improvement in the forecast accuracy in comparison with the ANFIS models trained with the input vectors considering only previous inflows. In all cases ANFIS gives more accurate forecast than the AR and ANN models. The proposed ANFIS model coupled with the cyclic terms is shown to provide better representation of the monthly inflow forecasting for planning and operation of reservoir.

Systems modeling and analysis for Saudi Arabian electric power requirements

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

Al-Mohawes, N.A.

This thesis addresses the long-range generation planning problem in Saudi Arabia up to the year 2000. The first part presents various models for electric energy consumption in the residential and industrial sectors. These models can be used by the decision makers for the purposes of policy analysis, evaluation, and forecasting. Forecasts of energy in each sector are obtained from two different models for each sector. These models are based on two forecasting techniques: (1) Hybrid econometric/time series model. The idea of adaptive smoothing was utilized to produce forecasts under several scenarios. (2) Box-Jenkins time series technique. Box-Jenkins models and forecastsmore » are developed for the monthly number of electric consumers and the monthly energy consumption per consumer. The results obtained indicate that high energy consumption is expected during the coming two decades which necessitate serious energy assessment and optimization. Optimization of a mix of energy sources was considered using the group multiattribute utility (MAU) function. The results of MAU for three classes of decision makers (managerial, technical, and consumers) are developed through personal interactions. The computer package WASP was also used to develop a tentative optimum plan. According to this plan, four heavy-water nuclear power plants (800 MW) and four light-water nuclear power plants (1200 MW) have to be introduced by the year 2000 in addition to sixteen oil-fired power plants (400 MW) and nine gas turbines (100 MW).« less

Collaborative Multi-Scale 3d City and Infrastructure Modeling and Simulation

NASA Astrophysics Data System (ADS)

Breunig, M.; Borrmann, A.; Rank, E.; Hinz, S.; Kolbe, T.; Schilcher, M.; Mundani, R.-P.; Jubierre, J. R.; Flurl, M.; Thomsen, A.; Donaubauer, A.; Ji, Y.; Urban, S.; Laun, S.; Vilgertshofer, S.; Willenborg, B.; Menninghaus, M.; Steuer, H.; Wursthorn, S.; Leitloff, J.; Al-Doori, M.; Mazroobsemnani, N.

2017-09-01

Computer-aided collaborative and multi-scale 3D planning are challenges for complex railway and subway track infrastructure projects in the built environment. Many legal, economic, environmental, and structural requirements have to be taken into account. The stringent use of 3D models in the different phases of the planning process facilitates communication and collaboration between the stake holders such as civil engineers, geological engineers, and decision makers. This paper presents concepts, developments, and experiences gained by an interdisciplinary research group coming from civil engineering informatics and geo-informatics banding together skills of both, the Building Information Modeling and the 3D GIS world. New approaches including the development of a collaborative platform and 3D multi-scale modelling are proposed for collaborative planning and simulation to improve the digital 3D planning of subway tracks and other infrastructures. Experiences during this research and lessons learned are presented as well as an outlook on future research focusing on Building Information Modeling and 3D GIS applications for cities of the future.

Climate Prediction Center - Expert Assessments: East Pacific Hurricane

Science.gov Websites

influence seasonal eastern Pacific hurricane activity, along with climate model forecasts. The outlook also National Weather Service NWS logo - Click to go to the NWS home page Climate Prediction Center Site Map Administration (NOAA) Climate Prediction Center (CPC), and is produced in collaboration with scientists from the

Concepts and Methodology for Labour Market Forecasts by Occupation and Qualification in the Context of a Flexible Labour Market.

ERIC Educational Resources Information Center

Borghans, Lex; de Grip, Andries; Heijke, Hans

The problem of planning and making labor market forecasts by occupation and qualification in the context of a constantly changing labor market was examined. The examination focused on the following topics: assumptions, benefits, and pitfalls of the labor requirement model of projecting future imbalances between labor supply and demand for certain…

7 CFR 1710.203 - Requirement to prepare a load forecast-distribution borrowers.

Code of Federal Regulations, 2011 CFR

2011-01-01

...—distribution borrowers. (a) A distribution borrower that is a member of a power supply borrower with a total... forecast work plan of its power supply borrower. (b) A distribution borrower that is a member of a power supply borrower which is itself a member of another power supply borrower that has a total utility plant...

A MODIS direct broadcast algorithm for mapping wildfire burned area in the western United States

Treesearch

S. P. Urbanski; J. M. Salmon; B. L. Nordgren; W. M. Hao

2009-01-01

Improved wildland fire emission inventory methods are needed to support air quality forecasting and guide the development of air shed management strategies. Air quality forecasting requires dynamic fire emission estimates that are generated in a timely manner to support real-time operations. In the regulatory and planning realm, emission inventories are essential for...

An Agent-Based Interface to Terrestrial Ecological Forecasting

NASA Technical Reports Server (NTRS)

Golden, Keith; Nemani, Ramakrishna; Pang, Wan-Lin; Votava, Petr; Etzioni, Oren

2004-01-01

This paper describes a flexible agent-based ecological forecasting system that combines multiple distributed data sources and models to provide near-real-time answers to questions about the state of the Earth system We build on novel techniques in automated constraint-based planning and natural language interfaces to automatically generate data products based on descriptions of the desired data products.

Hydrology for urban land planning - A guidebook on the hydrologic effects of urban land use

USGS Publications Warehouse

Leopold, Luna Bergere

1968-01-01

The application of current knowledge of the hydrologic effects of urbanization to the Brandywine should be viewed as a forecast of conditions which may be expected as urbanization proceeds. By making such forecasts in advance of actual urban development, the methods can be tested, data can be extended, and procedures improved as verification becomes possible.

SPoRT's Participation in the GOES-R Proving Ground Activity

NASA Technical Reports Server (NTRS)

Jedlovec, Gary; Fuell, Kevin; Smith, Matthew; Stano, Geoffrey; Molthan, Andrew

2011-01-01

The next generation geostationary satellite, GOES-R, will carry two new instruments with unique atmospheric and surface observing capabilities, the Advanced Baseline Imager (ABI) and the Geostationary Lightning Mapper (GLM), to study short-term weather processes. The ABI will bring enhanced multispectral observing capabilities with frequent refresh rates for regional and full disk coverage to geostationary orbit to address many existing and new forecast challenges. The GLM will, for the first time, provide the continuous monitoring of total lightning flashes over a hemispherical region from space. NOAA established the GOES-R Proving Ground activity several years ago to demonstrate the new capabilities of these instruments and to prepare forecasters for their day one use. Proving Ground partners work closely with algorithm developers and the end user community to develop and transition proxy data sets representing GOES-R observing capabilities. This close collaboration helps to maximize refine algorithms leading to the delivery of a product that effectively address a forecast challenge. The NASA Short-term Prediction Research and Transition (SPoRT) program has been a participant in the NOAA GOES-R Proving Ground activity by developing and disseminating selected GOES-R proxy products to collaborating WFOs and National Centers. Established in 2002 to demonstrate the weather and forecasting application of real-time EOS measurements, the SPoRT program has grown to be an end-to-end research to operations activity focused on the use of advanced NASA modeling and data assimilation approaches, nowcasting techniques, and unique high-resolution multispectral data from EOS satellites to improve short-term weather forecasts on a regional and local scale. Participation in the Proving Ground activities extends SPoRT s activities and taps its experience and expertise in diagnostic weather analysis, short-term weather forecasting, and the transition of research and experimental data to operational decision support systems like NAWIPS, AWIPS, AWIPS2, and Google Earth. Recent SPoRT Proving Ground activities supporting the development and use of a pseudo GLM total lightning product and the transition of the AWG s Convective Initiation (CI) product, both of which were available in AWIPS and AWIPS II environments, by forecasters during the Hazardous Weather Testbed (HWT) Spring Experiment. SPoRT is also providing a suite of SEVIRI and MODIS RGB image products, and a high resolution composite SST product to several National Centers for use in there ongoing demonstration activities. Additionally, SPoRT has involved numerous WFOs in the evaluation of a GOES-MODIS hybrid product which brings ABI-like data sets in front of the forecaster for everyday use. An overview of this activity will be presented at the conference.

SPoRT's Participation in the GOES-R Proving Ground Activity

NASA Astrophysics Data System (ADS)

Jedlovec, G.; Fuell, K.; Smith, M. R.; Stano, G. T.; Molthan, A.

2011-12-01

The next generation geostationary satellite, GOES-R, will carry two new instruments with unique atmospheric and surface observing capabilities, the Advanced Baseline Imager (ABI) and the Geostationary Lightning Mapper (GLM), to study short-term weather processes. The ABI will bring enhanced multispectral observing capabilities with frequent refresh rates for regional and full disk coverage to geostationary orbit to address many existing and new forecast challenges. The GLM will, for the first time, provide the continuous monitoring of total lightning flashes over a hemispherical region from space. NOAA established the GOES-R Proving Ground activity several years ago to demonstrate the new capabilities of these instruments and to prepare forecasters for their day one use. Proving Ground partners work closely with algorithm developers and the end user community to develop and transition proxy data sets representing GOES-R observing capabilities. This close collaboration helps to maximize refine algorithms leading to the delivery of a product that effectively address a forecast challenge. The NASA Short-term Prediction Research and Transition (SPoRT) program has been a participant in the NOAA GOES-R Proving Ground activity by developing and disseminating selected GOES-R proxy products to collaborating WFOs and National Centers. Established in 2002 to demonstrate the weather and forecasting application of real-time EOS measurements, the SPoRT program has grown to be an end-to-end research to operations activity focused on the use of advanced NASA modeling and data assimilation approaches, nowcasting techniques, and unique high-resolution multispectral data from EOS satellites to improve short-term weather forecasts on a regional and local scale. Participation in the Proving Ground activities extends SPoRT's activities and taps its experience and expertise in diagnostic weather analysis, short-term weather forecasting, and the transition of research and experimental data to operational decision support systems like NAWIPS, AWIPS, AWIPS2, and Google Earth. Recent SPoRT Proving Ground activities supporting the development and use of a pseudo GLM total lightning product and the transition of the AWG's Convective Initiation (CI) product, both of which were available in AWIPS and AWIPS II environments, by forecasters during the Hazardous Weather Testbed (HWT) Spring Experiment. SPoRT is also providing a suite of SEVIRI and MODIS RGB image products, and a high resolution composite SST product to several National Centers for use in there ongoing demonstration activities. Additionally, SPoRT has involved numerous WFOs in the evaluation of a GOES-MODIS hybrid product which brings ABI-like data sets in front of the forecaster for everyday use. An overview of this activity will be presented at the conference.

Towards a Global Hub and a Network for Collaborative Advancing of Space Weather Predictive Capabilities.

NASA Astrophysics Data System (ADS)

Kuznetsova, M. M.; Heynderickz, D.; Grande, M.; Opgenoorth, H. J.

2017-12-01

The COSPAR/ILWS roadmap on space weather published in 2015 (Advances in Space Research, 2015: DOI: 10.1016/j.asr.2015.03.023) prioritizes steps to be taken to advance understanding of space environment phenomena and to improve space weather forecasting capabilities. General recommendations include development of a comprehensive space environment specification, assessment of the state of the field on a 5-yr basis, standardization of meta-data and product metrics. To facilitate progress towards roadmap goals there is a need for a global hub for collaborative space weather capabilities assessment and development that brings together research, engineering, operational, educational, and end-user communities. The COSPAR Panel on Space Weather is aiming to build upon past progress and to facilitate coordination of established and new international space weather research and development initiatives. Keys to the success include creating flexible, collaborative, inclusive environment and engaging motivated groups and individuals committed to active participation in international multi-disciplinary teams focused on topics addressing emerging needs and challenges in the rapidly growing field of space weather. Near term focus includes comprehensive assessment of the state of the field and establishing an internationally recognized process to quantify and track progress over time, development of a global network of distributed web-based resources and interconnected interactive services required for space weather research, analysis, forecasting and education.

Economic consequences of improved temperature forecasts: An experiment with the Florida citrus growers (control group results). [weather forecasting

NASA Technical Reports Server (NTRS)

1977-01-01

A demonstration experiment is being planned to show that frost and freeze prediction improvements are possible utilizing timely Synchronous Meteorological Satellite temperature measurements and that this information can affect Florida citrus grower operations and decisions. An economic experiment was carried out which will monitor citrus growers' decisions, actions, costs and losses, and meteorological forecasts and actual weather events and will establish the economic benefits of improved temperature forecasts. A summary is given of the economic experiment, the results obtained to date, and the work which still remains to be done. Specifically, the experiment design is described in detail as are the developed data collection methodology and procedures, sampling plan, data reduction techniques, cost and loss models, establishment of frost severity measures, data obtained from citrus growers, National Weather Service, and Federal Crop Insurance Corp., resulting protection costs and crop losses for the control group sample, extrapolation of results of control group to the Florida citrus industry and the method for normalization of these results to a normal or average frost season so that results may be compared with anticipated similar results from test group measurements.

Fuzzy Multi-Objective Transportation Planning with Modified S-Curve Membership Function

NASA Astrophysics Data System (ADS)

Peidro, D.; Vasant, P.

2009-08-01

In this paper, the S-Curve membership function methodology is used in a transportation planning decision (TPD) problem. An interactive method for solving multi-objective TPD problems with fuzzy goals, available supply and forecast demand is developed. The proposed method attempts simultaneously to minimize the total production and transportation costs and the total delivery time with reference to budget constraints and available supply, machine capacities at each source, as well as forecast demand and warehouse space constraints at each destination. We compare in an industrial case the performance of S-curve membership functions, representing uncertainty goals and constraints in TPD problems, with linear membership functions.

Assessing the continuum of applications and societal benefits of US CLIVAR science

NASA Astrophysics Data System (ADS)

Ray, A. J.; Garfin, G. M.

2015-12-01

The new US CLIVAR strategic plan seeks to address the challenges of communicating the climate knowledge generated through its activities and to collaborate with the research and operational communities that may use this knowledge for managing climate risks. This presentation provides results of an overview in progress of the continuum of potential applications of climate science organized and coordinated through US CLIVAR. We define applications more broadly than simply ready for operations or direct use, and find that there are several stages in a continuum of readiness for communication and collaboration with communities that use climate information. These stages include: 1) advancing scientific understanding to a readiness for the next research steps aimed at predictable signals; 2) application of understanding climate phenomena in collaboration with a boundary organization, such as NOAA RISAs DOI Climate Science Centers, and USDA Climate Hubs, to understand how predictable signals may be translated into useable products; 3) use of knowledge in risk framing for a decision process, or in a science synthesis, such as the National Climate Assessment, and 4) transitioning new science knowledge into operational products (e.g. R2O), such as intraseasonal climate prediction. In addition, US CLIVAR has sponsored efforts to build science-to-decisions capacity, e.g., the Postdocs Applying Climate Expertise (PACE) program, in its 7th cohort, which has embedded climate experts into decision-making institutions. We will spotlight accomplishments of US CLIVAR science that are ripe for application in communities that are managing climate risks -- such as drought outlooks, MJO forecasting, extremes, and ocean conditions -- for agricultural production, water use, and marine ecosystems. We will use these examples to demonstrate the usefulness of an "applications continuum framework" identifying pathways from research to applications.

Extreme Precipitation, Stormwater, and Flooding in King County: Co-producing Research to Support Adaptation

NASA Astrophysics Data System (ADS)

Mauger, G. S.; Lorente-Plazas, R.; Salathe, E. P., Jr.; Mitchell, T. P.; Simmonds, J.; Lee, S. Y.; Hegewisch, K.; Warner, M.; Won, J.

2017-12-01

King County has experienced 12 federally declared flood disasters since 1990, and tens of thousands of county residents commute through, live, and work in floodplains. In addition to flooding, stormwater is a critical management challenge, exacerbated by aging infrastructure, combined sewer and drainage systems, and continued development. Even absent the effects of climate change these are challenging management issues. Recent studies clearly point to an increase in precipitation extremes for the Pacific Northwest (e.g., Warner et al. 2015). Yet very little information is available on the magnitude and spatial distribution of this change. Others clearly show that local-scale changes in extreme precipitation can only be accurately quantified with dynamical downscaling, i.e.: using a regional climate model. This talk will describe a suite of research and adaptation efforts developed in a close collaboration between King County and the UW Climate Impacts Group. Building on past collaborations, research efforts were defined in collaboration with King County managers, addressing three key science questions: (1) How are the mesoscale variations in extreme precipitation modulated by changes in large-scale weather conditions? (2) How will precipitation extremes change? This was assessed via two new high-resolution regional model projections using the Weather Research and Forecasting (WRF) mesoscale model (Skamarock et al. 2005). (3) What are the implications for stormwater and flooding in King County? This was assessed by both exploring the statistics of hourly precipitation extremes in the new projections, as well as new hydrologic modeling to assess the implications for river flooding. The talk will present results from these efforts, review the implications for King County planning and infrastructure, and synthesize lessons learned and opportunities for additional work.

Extending to seasonal scales the current usage of short range weather forecasts and climate projections for water management in Spain

NASA Astrophysics Data System (ADS)

Rodriguez-Camino, Ernesto; Voces, José; Sánchez, Eroteida; Navascues, Beatriz; Pouget, Laurent; Roldan, Tamara; Gómez, Manuel; Cabello, Angels; Comas, Pau; Pastor, Fernando; Concepción García-Gómez, M.°; José Gil, Juan; Gil, Delfina; Galván, Rogelio; Solera, Abel

2016-04-01

This presentation, first, briefly describes the current use of weather forecasts and climate projections delivered by AEMET for water management in Spain. The potential use of seasonal climate predictions for water -in particular dams- management is then discussed more in-depth, using a pilot experience carried out by a multidisciplinary group coordinated by AEMET and DG for Water of Spain. This initiative is being developed in the framework of the national implementation of the GFCS and the European project, EUPORIAS. Among the main components of this experience there are meteorological and hydrological observations, and an empirical seasonal forecasting technique that provides an ensemble of water reservoir inflows. These forecasted inflows feed a prediction model for the dam state that has been adapted for this purpose. The full system is being tested retrospectively, over several decades, for selected water reservoirs located in different Spanish river basins. The assessment includes an objective verification of the probabilistic seasonal forecasts using standard metrics, and the evaluation of the potential social and economic benefits, with special attention to drought and flooding conditions. The methodology of implementation of these seasonal predictions in the decision making process is being developed in close collaboration with final users participating in this pilot experience.

Forecasting the Short-Term Passenger Flow on High-Speed Railway with Neural Networks

PubMed Central

Xie, Mei-Quan; Li, Xia-Miao; Zhou, Wen-Liang; Fu, Yan-Bing

2014-01-01

Short-term passenger flow forecasting is an important component of transportation systems. The forecasting result can be applied to support transportation system operation and management such as operation planning and revenue management. In this paper, a divide-and-conquer method based on neural network and origin-destination (OD) matrix estimation is developed to forecast the short-term passenger flow in high-speed railway system. There are three steps in the forecasting method. Firstly, the numbers of passengers who arrive at each station or depart from each station are obtained from historical passenger flow data, which are OD matrices in this paper. Secondly, short-term passenger flow forecasting of the numbers of passengers who arrive at each station or depart from each station based on neural network is realized. At last, the OD matrices in short-term time are obtained with an OD matrix estimation method. The experimental results indicate that the proposed divide-and-conquer method performs well in forecasting the short-term passenger flow on high-speed railway. PMID:25544838

INTEGRATED PLANNING MODEL - EPA APPLICATIONS

EPA Science Inventory

The Integrated Planning Model (IPM) is a multi-regional, dynamic, deterministic linear programming (LP) model of the electric power sector in the continental lower 48 states and the District of Columbia. It provides forecasts up to year 2050 of least-cost capacity expansion, elec...

Home | Sonoma County Water Agency

Science.gov Websites

Precipitation Information (AQPI) Fluoridation Atmospheric Rivers Urban Water Management Plan Flood Protection Advanced Quantitative Precipitation Information (AQPI) Fluoridation Atmospheric Rivers Urban Water Management Plan Flood Protection Flood Forecast/Emergency Info Stream Maintenance Program Flood Protection

Development of a prototype land use model for statewide transportation planning activities.

DOT National Transportation Integrated Search

2011-11-30

Future land use forecasting is an important input to transportation planning modeling. Traditionally, land use is allocated to individual : traffic analysis zones (TAZ) based on variables such as the amount of vacant land, zoning restriction, land us...

Demographic Planning: An Action Approach

ERIC Educational Resources Information Center

Finch, Harold L.; Smith, Joyce

1974-01-01

Community colleges are in a good position to obtain reliable long-term forecasts of future demand. An approach developed at Johnson County Community College in Overland Park, Kansas, has enabled the college to assist other community institutions in their parallel planning efforts. (Author/MLF)

Travel demand modeling for the small and medium sized MPOs in Illinois.

DOT National Transportation Integrated Search

2011-09-01

Travel demand modeling is an important tool in the transportation planning community. It helps forecast travel : characteristics into the future at various planning levels such as state, region and corridor. Using travel demand : modeling to evaluate...

Next generation air transportation system : issues associated with midterm implementation of capabilities and full system transformation.

DOT National Transportation Integrated Search

2009-03-01

To prepare for forecasted air traffic : growth, the Federal Aviation : Administration (FAA), including its : Joint Planning and Development : Office (JPDO) and Air Traffic : Organization (ATO), is planning for : and implementing the Next : Generation...

Seasonal Climate Forecasts and Adoption by Agriculture

NASA Astrophysics Data System (ADS)

Garbrecht, Jurgen; Meinke, Holger; Sivakumar, Mannava V. K.; Motha, Raymond P.; Salinger, Michael J.

2005-06-01

Recent advances in atmospheric and ocean sciences and a better understanding of the global climate have led to skillful climate forecasts at seasonal to interannual timescales, even in midlatitudes. These scientific advances and forecasting capabilities have opened the door to practical applications that benefit society. The benefits include the reduction of weather/climate related risks and vulnerability, increased economic opportunities, enhanced food security, mitigation of adverse climate impacts, protection of environmental quality, and so forth. Agriculture in particular can benefit substantially from accurate long-lead seasonal climate forecasts. Indeed, agricultural production very much depends on weather, climate, and water availability, and unexpected departures from anticipated climate conditions can thwart the best laid management plans. Timely climate forecasts offer means to reduce losses in drought years, increase profitability in good years, deal more effectively with climate variability, and choose from targeted risk-management strategies. In addition to benefiting farmers, forecasts can also help marketing systems and downstream users prepare for anticipated production outcomes and associated consequences.

Experimental Forecasts of Wildfire Pollution at the Canadian Meteorological Centre

NASA Astrophysics Data System (ADS)

Pavlovic, Radenko; Beaulieu, Paul-Andre; Chen, Jack; Landry, Hugo; Cousineau, Sophie; Moran, Michael

2016-04-01

Environment and Climate Change Canada's Canadian Meteorological Centre Operations division (CMCO) has been running an experimental North American air quality forecast system with near-real-time wildfire emissions since 2014. This system, named FireWork, also takes anthropogenic and other natural emission sources into account. FireWork 48-hour forecasts are provided to CMCO forecasters and external partners in Canada and the U.S. twice daily during the wildfire season. This system has proven to be very useful in capturing short- and long-range smoke transport from wildfires over North America. Several upgrades to the FireWork system have been made since 2014 to accommodate the needs of operational AQ forecasters and to improve system performance. In this talk we will present performance statistics and some case studies for the 2014 and 2015 wildfire seasons. We will also describe current limitations of the FireWork system and ongoing and future work planned for this air quality forecast system.

The SPoRT-WRF: Evaluating the Impact of NASA Datasets on Convective Forecasts

NASA Technical Reports Server (NTRS)

Zavodsky, Bradley; Case, Jonathan; Kozlowski, Danielle; Molthan, Andrew

2012-01-01

The Short-term Prediction Research and Transition Center (SPoRT) is a collaborative partnership between NASA and operational forecasting entities, including a number of National Weather Service offices. SPoRT transitions real-time NASA products and capabilities to its partners to address specific operational forecast challenges. One challenge that forecasters face is applying convection-allowing numerical models to predict mesoscale convective weather. In order to address this specific forecast challenge, SPoRT produces real-time mesoscale model forecasts using the Weather Research and Forecasting (WRF) model that includes unique NASA products and capabilities. Currently, the SPoRT configuration of the WRF model (SPoRT-WRF) incorporates the 4-km Land Information System (LIS) land surface data, 1-km SPoRT sea surface temperature analysis and 1-km Moderate resolution Imaging Spectroradiometer (MODIS) greenness vegetation fraction (GVF) analysis, and retrieved thermodynamic profiles from the Atmospheric Infrared Sounder (AIRS). The LIS, SST, and GVF data are all integrated into the SPoRT-WRF through adjustments to the initial and boundary conditions, and the AIRS data are assimilated into a 9-hour SPoRT WRF forecast each day at 0900 UTC. This study dissects the overall impact of the NASA datasets and the individual surface and atmospheric component datasets on daily mesoscale forecasts. A case study covering the super tornado outbreak across the Ce ntral and Southeastern United States during 25-27 April 2011 is examined. Three different forecasts are analyzed including the SPoRT-WRF (NASA surface and atmospheric data), the SPoRT WRF without AIRS (NASA surface data only), and the operational National Severe Storms Laboratory (NSSL) WRF (control with no NASA data). The forecasts are compared qualitatively by examining simulated versus observed radar reflectivity. Differences between the simulated reflectivity are further investigated using convective parameters along with model soundings to determine the impacts of the various NASA datasets. Additionally, quantitative evaluation of select meteorological parameters is performed using the Meteorological Evaluation Tools model verification package to compare forecasts to in situ surface and upper air observations.

Mapping users' expectations regarding extended-range forecasts

NASA Astrophysics Data System (ADS)

Ervasti, Tiina; Gregow, Hilppa; Vajda, Andrea; Laurila, Terhi K.; Mäkelä, Antti

2018-05-01

An online survey was used to map the needs and preferences of the Finnish general public concerning extended-range forecasts and their presentation. First analyses of the survey were used to guide the co-design process of novel extended-range forecasts to be developed and tested during the project. In addition, the survey was used to engage the respondents from the general public to participate in a one year piloting phase that started in June 2017. The respondents considered that the tailored extended-range forecasts would be beneficial in planning activities, preparing for the weather risks and scheduling the everyday life. The respondents also perceived the information about the impacts of weather conditions more important than advice on how to prepare for the impacts.

Flood risk awareness during the 2011 floods in the central United States: showcasing the importance of hydrologic data and interagency collaboration

USGS Publications Warehouse

Holmes, Robert R.; Schwein, Noreen O.; Shadie, Charles E.

2012-01-01

Floods have long had a major impact on society and the environment, evidenced by the more than 1,500 federal disaster declarations since 1952 that were associated with flooding. Calendar year 2011 was an epic year for floods in the United States, from the flooding on the Red River of the North in late spring to the Ohio, Mississippi, and Missouri River basin floods in the spring and summer to the flooding caused by Hurricane Irene along the eastern seaboard in August. As a society, we continually seek to reduce flood impacts, with these efforts loosely grouped into two categories: mitigation and risk awareness. Mitigation involves such activities as flood assessment, flood control implementation, and regulatory activities such as storm water and floodplain ordinances. Risk awareness ranges from issuance of flood forecasts and warnings to education of lay audiences about the uncertainties inherent in assessing flood probability and risk. This paper concentrates on the issue of flood risk awareness, specifically the importance of hydrologic data and good interagency communication in providing accurate and timely flood forecasts to maximize risk awareness. The 2011 floods in the central United States provide a case study of the importance of hydrologic data and the value of proper, timely, and organized communication and collaboration around the collection and dissemination of that hydrologic data in enhancing the effectiveness of flood forecasting and flood risk awareness.

Networking 2.0: Expanding your collaboration circles through the Interagency Arctic Research Policy Committee (IARPC)

NASA Astrophysics Data System (ADS)

Rohde, J. A.; Bowden, S.; Stephenson, S. N.; Starkweather, S.

2015-12-01

The Interagency Arctic Research Policy Committee (IARPC) envisions a prosperous, sustainable, and healthy Arctic understood through innovative and collaborative research coordinated among Federal agencies and domestic and international partners. IARPC's approach is to harnesses the talent of the scientific and stakeholder community through Federally-run but broadly open collaboration teams, and an innovative website that expands the frontiers of collaborative research. The Obama Administration released the five-year Arctic Research Plan: FY2013-2017 in February 2013. The Plan focuses on advancing knowledge and sustainability of the Arctic by improving collaboration in seven priority research areas: sea ice and marine ecosystems, terrestrial ice and ecosystems, atmospheric studies, observing systems, regional climate models, human health studies, and adaptation tools for communities. From these seven research areas, 12 collaboration teams were formed to respond to the 145 milestones laid out in the Plan. The collaboration teams are charged with enhancing inter-institutional and interdisciplinary implementation of scientific research on local, regional, and circumpolar environmental and societal issues in the Arctic. The collaboration teams are co-chaired by Federal program managers, and, in some cases, external partners and are open to research and stakeholder communities. They meet on a regular basis by web- or teleconference to inform one another about ongoing and planned programs and new research results, as well as to inventory existing programs, identify gaps in knowledge and research, and address and implement the Plan's milestones. In-between meetings, team members communicate via our innovative, user-driven, collaboration website. Members share information about their research activities by posting updates, uploading documents, and including events on our calendar, and entering into dialogue about their research activities. Conversations taking place on the website are open to any other member, enabling new talent to enter into conversations and collaborations to form.

Assessment of the Pseudo Geostationary Lightning Mapper Products at the Spring Program and Summer Experiment

NASA Technical Reports Server (NTRS)

Stano, Geoffrey T.; Calhoun, Kristin K.; Terborg, Amanda M.

2014-01-01

Since 2010, the de facto Geostationary Lightning Mapper (GLM) demonstration product has been the Pseudo-Geostationary Lightning Mapper (PGLM) product suite. Originally prepared for the Hazardous Weather Testbed's Spring Program (specifically the Experimental Warning Program) when only four ground-based lightning mapping arrays were available, the effort now spans collaborations with several institutions and eight collaborative networks. For 2013, NASA's Short-term Prediction Research and Transition (SPoRT) Center and NOAA's National Severe Storms Laboratory have worked to collaborate with each network to obtain data in real-time. This has gone into producing the SPoRT variant of the PGLM that was demonstrated in AWIPS II for the 2013 Spring Program. Alongside the PGLM products, the SPoRT / Meteorological Development Laboratory's total lightning tracking tool also was evaluated to assess not just another visualization of future GLM data but how to best extract more information while in the operational environment. Specifically, this tool addressed the leading request by forecasters during evaluations; provide a time series trend of total lightning in real-time. In addition to the Spring Program, SPoRT is providing the PGLM "mosaic" to the Aviation Weather Center (AWC) and Storm Prediction Center. This is the same as what is used at the Hazardous Weather Testbed, but combines all available networks into one display for use at the national centers. This year, the mosaic was evaluated during the AWC's Summer Experiment. An important distinction between this and the Spring Program is that the Summer Experiment focuses on the national center perspective and not at the local forecast office level. Specifically, the Summer Experiment focuses on aviation needs and concerns and brings together operational forecaster, developers, and FAA representatives. This presentation will focus on the evaluation of SPoRT's pseudo-GLM products in these separate test beds. The emphasis will be on how future GLM observations can support operations at both the local and national scale and how the PGLM was used in combination with other lightning data sets. Evaluations for the PGLM were quite favorable with forecasters appreciating the high temporal resolution, the ability to look for rapid increases in lightning activity ahead of severe weather, as well as situational awareness for where convection is firing and for flight routing.

Uncertainty quantification and reliability assessment in operational oil spill forecast modeling system.

PubMed

Hou, Xianlong; Hodges, Ben R; Feng, Dongyu; Liu, Qixiao

2017-03-15

As oil transport increasing in the Texas bays, greater risks of ship collisions will become a challenge, yielding oil spill accidents as a consequence. To minimize the ecological damage and optimize rapid response, emergency managers need to be informed with how fast and where oil will spread as soon as possible after a spill. The state-of-the-art operational oil spill forecast modeling system improves the oil spill response into a new stage. However uncertainty due to predicted data inputs often elicits compromise on the reliability of the forecast result, leading to misdirection in contingency planning. Thus understanding the forecast uncertainty and reliability become significant. In this paper, Monte Carlo simulation is implemented to provide parameters to generate forecast probability maps. The oil spill forecast uncertainty is thus quantified by comparing the forecast probability map and the associated hindcast simulation. A HyosPy-based simple statistic model is developed to assess the reliability of an oil spill forecast in term of belief degree. The technologies developed in this study create a prototype for uncertainty and reliability analysis in numerical oil spill forecast modeling system, providing emergency managers to improve the capability of real time operational oil spill response and impact assessment. Copyright © 2017 Elsevier Ltd. All rights reserved.

Status of Air Quality in Central California and Needs for Further Study

NASA Astrophysics Data System (ADS)

Tanrikulu, S.; Beaver, S.; Soong, S.; Tran, C.; Jia, Y.; Matsuoka, J.; McNider, R. T.; Biazar, A. P.; Palazoglu, A.; Lee, P.; Wang, J.; Kang, D.; Aneja, V. P.

2012-12-01

Ozone and PM2.5 levels frequently exceed NAAQS in central California (CC). Additional emission reductions are needed to attain and maintain the standards there. Agencies are developing cost-effective emission control strategies along with complementary incentive programs to reduce emissions when exceedances are forecasted. These approaches require accurate modeling and forecasting capabilities. A variety of models have been rigorously applied (MM5, WRF, CMAQ, CAMx) over CC. Despite the vast amount of land-based measurements from special field programs and significant effort, models have historically exhibited marginal performance. Satellite data may improve model performance by: establishing IC/BC over outlying areas of the modeling domain having unknown conditions; enabling FDDA over the Pacific Ocean to characterize important marine inflows and pollutant outflows; and filling in the gaps of the land-based monitoring network. BAAQMD, in collaboration with the NASA AQAST, plans to conduct four studies that include satellite-based data in CC air quality analysis and modeling: The first project enhances and refines weather patterns, especially aloft, impacting summer ozone formation. Surface analyses were unable to characterize the strong attenuating effect of the complex terrain to steer marine winds impinging on the continent. The dense summer clouds and fog over the Pacific Ocean form spatial patterns that can be related to the downstream air flows through polluted areas. The goal of this project is to explore, characterize, and quantify these relationships using cloud cover data. Specifically, cloud agreement statistics will be developed using satellite data and model clouds. Model skin temperature predictions will be compared to both MODIS and GOES skin temperatures. The second project evaluates and improves the initial and simulated fields of meteorological models that provide inputs to air quality models. The study will attempt to determine whether a cloud dynamical adjustment developed by UAHuntsville can improve model performance for maritime stratus and whether a moisture adjustment scheme in the Pleim-Xiu boundary layer scheme can use satellite data in place of coarse surface air temperature measurements. The goal is to improve meteorological model performance that leads to improved air quality model performance. The third project evaluates and improves forecasting skills of the National Air Quality Forecasting Model in CC by using land-based routine measurements as well as satellite data. Local forecasts are mostly based on surface meteorological and air quality measurements and weather charts provided by NWS. The goal is to improve the average accuracy in forecasting exceedances, which is around 60%. The fourth project uses satellite data for monitoring trends in fine particulate matter (PM2.5) in the San Francisco Bay Area. It evaluates the effectiveness of a rule adopted in 2008 that restricts household wood burning on days forecasted to have high PM2.5 levels. The goal is to complement current analyses based on surface data covering the largest sub-regions and population centers. The overall goal is to use satellite data to overcome limitations of land-based measurements. The outcomes will be further conceptual understanding of pollutant formation, improved regulatory model performance, and better optimized forecasting programs.

Surface Current Skill Assessment of Global and Regional forecast models.

NASA Astrophysics Data System (ADS)

Allen, A. A.

2016-02-01

The U.S. Coast Guard has been using SAROPS since January 2007 at all fifty of its operational centers to plan search and rescue missions. SAROPS relies on an Environmental Data Server (EDS) that integrates global, national, and regional ocean and meteorological observation and forecast data. The server manages spatial and temporal aggregation of hindcast, nowcast, and forecast data so the SAROPS controller has the best available data for search planning. The EDS harvests a wide range of global and regional forecasts and data, including NOAA NCEP's global HYCOM model (RTOFS), the U.S. Navy's Global HYCOM model, the 5 NOAA NOS Great Lakes models and a suite of other reginal forecasts from NOS and IOOS Regional Associations. The EDS also integrates surface drifter data as the U.S. Coast Guard regularly deploys Self-Locating Datum Marker Buoys (SLDMBs) during SAR cases and a significant set of drifter data has been collected and the archive continues to grow. This data is critically useful during real-time SAR planning, but also represents a valuable scientific dataset for analyzing surface currents. In 2014, a new initiative was started by the U.S. Coast Guard to evaluate the skill of the various models to support the decision making process during search and rescue planning. This analysis falls into 2 categories: historical analysis of drifter tracks and model predictions to provide skill assessment of models in different regions and real-time analysis of models and drifter tracks during a SAR incident. The EDS, using Liu and Wiesberg's (2014) autonomously determines surface skill measurements of the co-located models' simulated surface trajectories versus the actual drift of the SLDMBs (CODE/Davis style surface drifters GPS positioned at 30min intervals). Surface skill measurements are archived in a database and are user retrieval by lat/long/time cubes. This paper will focus on the comparison of models from in the period from 23 August to 21 September 2015. Surface Skill was determined for the following regions: California Coast, Gulf of Mexico, South and Mid Atlantic Bights. Skill was determined for the two version of the NCEP Global RTOFS, Navy's Global HYCOM model, and where appropriated the local regional models

Oregon's acts, cross-jurisdictional collaboration and improved transportation planning : final report : appendices.

DOT National Transportation Integrated Search

2009-01-01

This appendix summarizes interviews completed as part of an Oregon Department of : Transportation (ODOT) research study titled, Oregons ACTs, Cross-Jurisdictional : Collaboration and Improved Transportation Planning. The research was conduct...

Calibration of decadal ensemble predictions

NASA Astrophysics Data System (ADS)

Pasternack, Alexander; Rust, Henning W.; Bhend, Jonas; Liniger, Mark; Grieger, Jens; Müller, Wolfgang; Ulbrich, Uwe

2017-04-01

Decadal climate predictions are of great socio-economic interest due to the corresponding planning horizons of several political and economic decisions. Due to uncertainties of weather and climate, forecasts (e.g. due to initial condition uncertainty), they are issued in a probabilistic way. One issue frequently observed for probabilistic forecasts is that they tend to be not reliable, i.e. the forecasted probabilities are not consistent with the relative frequency of the associated observed events. Thus, these kind of forecasts need to be re-calibrated. While re-calibration methods for seasonal time scales are available and frequently applied, these methods still have to be adapted for decadal time scales and its characteristic problems like climate trend and lead time dependent bias. Regarding this, we propose a method to re-calibrate decadal ensemble predictions that takes the above mentioned characteristics into account. Finally, this method will be applied and validated to decadal forecasts from the MiKlip system (Germany's initiative for decadal prediction).

Forecasting urban water demand: A meta-regression analysis.

PubMed

Sebri, Maamar

2016-12-01

Water managers and planners require accurate water demand forecasts over the short-, medium- and long-term for many purposes. These range from assessing water supply needs over spatial and temporal patterns to optimizing future investments and planning future allocations across competing sectors. This study surveys the empirical literature on the urban water demand forecasting using the meta-analytical approach. Specifically, using more than 600 estimates, a meta-regression analysis is conducted to identify explanations of cross-studies variation in accuracy of urban water demand forecasting. Our study finds that accuracy depends significantly on study characteristics, including demand periodicity, modeling method, forecasting horizon, model specification and sample size. The meta-regression results remain robust to different estimators employed as well as to a series of sensitivity checks performed. The importance of these findings lies in the conclusions and implications drawn out for regulators and policymakers and for academics alike. Copyright © 2016. Published by Elsevier Ltd.

Social learning in a policy-mandated collaboration: Community wildfire protection planning in the eastern United States

Treesearch

Rachel F. Brummel; Kristen C. Nelson; Pamela J. Jakes; Daniel R. Williams

2010-01-01

Policies such as the US Healthy Forests Restoration Act (HFRA) mandate collaboration in planning to create benefits such as social learning and shared understanding among partners. However, some question the ability of top-down policy to foster successful local collaboration. Through in-depth interviews and document analysis, this paper investigates social learning and...

Preventing Elder Abuse: The Texas Plan for a Coordinated Service Delivery System. Collaborative Elder Abuse Prevention Project.

ERIC Educational Resources Information Center

McDaniel, Garry L.

The Texas Department of Human Services, in collaboration with 13 other public and private organizations, co-sponsored a statewide Collaborative Elder Abuse Prevention project. The goal of this project is to develop a comprehensive, long-range plan for the prevention of elder abuse, a method for achieving a coordinated service delivery system for…

Decomposition of Sources of Errors in Seasonal Streamflow Forecasts in a Rainfall-Runoff Dominated Basin

NASA Astrophysics Data System (ADS)

Sinha, T.; Arumugam, S.

2012-12-01

Seasonal streamflow forecasts contingent on climate forecasts can be effectively utilized in updating water management plans and optimize generation of hydroelectric power. Streamflow in the rainfall-runoff dominated basins critically depend on forecasted precipitation in contrast to snow dominated basins, where initial hydrological conditions (IHCs) are more important. Since precipitation forecasts from Atmosphere-Ocean-General Circulation Models are available at coarse scale (~2.8° by 2.8°), spatial and temporal downscaling of such forecasts are required to implement land surface models, which typically runs on finer spatial and temporal scales. Consequently, multiple sources are introduced at various stages in predicting seasonal streamflow. Therefore, in this study, we addresses the following science questions: 1) How do we attribute the errors in monthly streamflow forecasts to various sources - (i) model errors, (ii) spatio-temporal downscaling, (iii) imprecise initial conditions, iv) no forecasts, and (iv) imprecise forecasts? and 2) How does monthly streamflow forecast errors propagate with different lead time over various seasons? In this study, the Variable Infiltration Capacity (VIC) model is calibrated over Apalachicola River at Chattahoochee, FL in the southeastern US and implemented with observed 1/8° daily forcings to estimate reference streamflow during 1981 to 2010. The VIC model is then forced with different schemes under updated IHCs prior to forecasting period to estimate relative mean square errors due to: a) temporally disaggregation, b) spatial downscaling, c) Reverse Ensemble Streamflow Prediction (imprecise IHCs), d) ESP (no forecasts), and e) ECHAM4.5 precipitation forecasts. Finally, error propagation under different schemes are analyzed with different lead time over different seasons.

Issues and Experiences in Logistics Collaboration

NASA Astrophysics Data System (ADS)

Lehoux, Nadia; Audy, Jean-François; D‘Amours, Sophie; Rönnqvist, Mikael

Collaborative logistics is becoming more important in today’s industry. This is driven by increased environmental concerns, improved efficiency through collaborative planning supporting resources sharing and new business models implementation. This paper explores collaborative logistics and reports on business applications within the forest products industry in Sweden and Canada. It first describes current opportunities in collaborative planning. It then discusses issues related to building the coalition as well as sharing resources and benefits. Three business cases are described and used to support the discussion around these main issues. Finally, different challenges are detailed, opening new paths for researchers in the field.

Integration of Weather Data into Airspace and Traffic Operations Simulation (ATOS) for Trajectory- Based Operations Research

NASA Technical Reports Server (NTRS)

Peters, Mark; Boisvert, Ben; Escala, Diego

2009-01-01

Explicit integration of aviation weather forecasts with the National Airspace System (NAS) structure is needed to improve the development and execution of operationally effective weather impact mitigation plans and has become increasingly important due to NAS congestion and associated increases in delay. This article considers several contemporary weather-air traffic management (ATM) integration applications: the use of probabilistic forecasts of visibility at San Francisco, the Route Availability Planning Tool to facilitate departures from the New York airports during thunderstorms, the estimation of en route capacity in convective weather, and the application of mixed-integer optimization techniques to air traffic management when the en route and terminal capacities are varying with time because of convective weather impacts. Our operational experience at San Francisco and New York coupled with very promising initial results of traffic flow optimizations suggests that weather-ATM integrated systems warrant significant research and development investment. However, they will need to be refined through rapid prototyping at facilities with supportive operational users We have discussed key elements of an emerging aviation weather research area: the explicit integration of aviation weather forecasts with NAS structure to improve the effectiveness and timeliness of weather impact mitigation plans. Our insights are based on operational experiences with Lincoln Laboratory-developed integrated weather sensing and processing systems, and derivative early prototypes of explicit ATM decision support tools such as the RAPT in New York City. The technical components of this effort involve improving meteorological forecast skill, tailoring the forecast outputs to the problem of estimating airspace impacts, developing models to quantify airspace impacts, and prototyping automated tools that assist in the development of objective broad-area ATM strategies, given probabilistic weather forecasts. Lincoln Laboratory studies and prototype demonstrations in this area are helping to define the weather-assimilated decision-making system that is envisioned as a key capability for the multi-agency Next Generation Air Transportation System [1]. The Laboratory's work in this area has involved continuing, operations-based evolution of both weather forecasts and models for weather impacts on the NAS. Our experience has been that the development of usable ATM technologies that address weather impacts must proceed via rapid prototyping at facilities whose users are highly motivated to participate in system evolution.

Application and verification of ECMWF seasonal forecast for wind energy

NASA Astrophysics Data System (ADS)

Žagar, Mark; Marić, Tomislav; Qvist, Martin; Gulstad, Line

2015-04-01

A good understanding of long-term annual energy production (AEP) is crucial when assessing the business case of investing in green energy like wind power. The art of wind-resource assessment has emerged into a scientific discipline on its own, which has advanced at high pace over the last decade. This has resulted in continuous improvement of the AEP accuracy and, therefore, increase in business case certainty. Harvesting the full potential output of a wind farm or a portfolio of wind farms depends heavily on optimizing operation and management strategy. The necessary information for short-term planning (up to 14 days) is provided by standard weather and power forecasting services, and the long-term plans are based on climatology. However, the wind-power industry is lacking quality information on intermediate scales of the expected variability in seasonal and intra-annual variations and their geographical distribution. The seasonal power forecast presented here is designed to bridge this gap. The seasonal power production forecast is based on the ECMWF seasonal weather forecast and the Vestas' high-resolution, mesoscale weather library. The seasonal weather forecast is enriched through a layer of statistical post-processing added to relate large-scale wind speed anomalies to mesoscale climatology. The resulting predicted energy production anomalies, thus, include mesoscale effects not captured by the global forecasting systems. The turbine power output is non-linearly related to the wind speed, which has important implications for the wind power forecast. In theory, the wind power is proportional to the cube of wind speed. However, due to the nature of turbine design, this exponent is close to 3 only at low wind speeds, becomes smaller as the wind speed increases, and above 11-13 m/s the power output remains constant, called the rated power. The non-linear relationship between wind speed and the power output generally increases sensitivity of the forecasted power to the wind speed anomalies. On the other hand, in some cases and areas where turbines operate close to, or above the rated power, the sensitivity of power forecast is reduced. Thus, the seasonal power forecasting system requires good knowledge of the changes in frequency of events with sufficient wind speeds to have acceptable skill. The scientific background for the Vestas seasonal power forecasting system is described and the relationship between predicted monthly wind speed anomalies and observed wind energy production are investigated for a number of operating wind farms in different climate zones. Current challenges will be discussed and some future research and development areas identified.

A national framework for flood forecasting model assessment for use in operations and investment planning over England and Wales

NASA Astrophysics Data System (ADS)

Moore, Robert J.; Wells, Steven C.; Cole, Steven J.

2016-04-01

It has been common for flood forecasting systems to be commissioned at a catchment or regional level in response to local priorities and hydrological conditions, leading to variety in system design and model choice. As systems mature and efficiencies of national management are sought, there can be a drive towards system rationalisation, gaining an overview of model performance and consideration of simplification through model-type convergence. Flood forecasting model assessments, whilst overseen at a national level, may be commissioned and managed at a catchment and regional level, take a variety of forms and be large in number. This presents a challenge when an integrated national assessment is required to guide operational use of flood forecasts and plan future investment in flood forecasting models and supporting hydrometric monitoring. This contribution reports on how a nationally consistent framework for flood forecasting model performance has been developed to embrace many past, ongoing and future assessments for local river systems by engineering consultants across England & Wales. The outcome is a Performance Summary for every site model assessed which, on a single page, contains relevant catchment information for context, a selection of overlain forecast and observed hydrographs and a set of performance statistics with associated displays of novel condensed form. One display provides performance comparison with other models that may exist for the site. The performance statistics include skill scores for forecasting events (flow/level threshold crossings) of differing severity/rarity, indicating their probability and likely timing, which have real value in an operational setting. The local models assessed can be of any type and span rainfall-runoff (conceptual and transfer function) and flow routing (hydrological and hydrodynamic) forms. Also accommodated by the framework is the national G2G (Grid-to-Grid) distributed hydrological model, providing area-wide coverage across the fluvial rivers of England and Wales, which can be assessed at gauged sites. Thus the performance of the national G2G model forecasts can be directly compared with that from the local models. The Performance Summary for each site model is complemented by a national spatial analysis of model performance stratified by model-type, geographical region and forecast lead-time. The map displays provide an extensive evidence-base that can be interrogated, through a Flood Forecasting Model Performance web portal, to reveal fresh insights into comparative performance across locations, lead-times and models. This work was commissioned by the Environment Agency in partnership with Natural Resources Wales and the Flood Forecasting Centre for England and Wales.

Next generation air transportation system : status of transformation and issues associated with midterm implementation of capabilities.

DOT National Transportation Integrated Search

2009-03-01

"To prepare for forecasted air traffic growth, the Federal Aviation Administration (FAA), including its Joint Planning and Development Office (JPDO) and Air Traffic Organization (ATO), is planning for and implementing the Next Generation Air Transpor...

Seasonal drought ensemble predictions based on multiple climate models in the upper Han River Basin, China

NASA Astrophysics Data System (ADS)

Ma, Feng; Ye, Aizhong; Duan, Qingyun

2017-03-01

An experimental seasonal drought forecasting system is developed based on 29-year (1982-2010) seasonal meteorological hindcasts generated by the climate models from the North American Multi-Model Ensemble (NMME) project. This system made use of a bias correction and spatial downscaling method, and a distributed time-variant gain model (DTVGM) hydrologic model. DTVGM was calibrated using observed daily hydrological data and its streamflow simulations achieved Nash-Sutcliffe efficiency values of 0.727 and 0.724 during calibration (1978-1995) and validation (1996-2005) periods, respectively, at the Danjiangkou reservoir station. The experimental seasonal drought forecasting system (known as NMME-DTVGM) is used to generate seasonal drought forecasts. The forecasts were evaluated against the reference forecasts (i.e., persistence forecast and climatological forecast). The NMME-DTVGM drought forecasts have higher detectability and accuracy and lower false alarm rate than the reference forecasts at different lead times (from 1 to 4 months) during the cold-dry season. No apparent advantage is shown in drought predictions during spring and summer seasons because of a long memory of the initial conditions in spring and a lower predictive skill for precipitation in summer. Overall, the NMME-based seasonal drought forecasting system has meaningful skill in predicting drought several months in advance, which can provide critical information for drought preparedness and response planning as well as the sustainable practice of water resource conservation over the basin.

The value of model averaging and dynamical climate model predictions for improving statistical seasonal streamflow forecasts over Australia

NASA Astrophysics Data System (ADS)

Pokhrel, Prafulla; Wang, Q. J.; Robertson, David E.

2013-10-01

Seasonal streamflow forecasts are valuable for planning and allocation of water resources. In Australia, the Bureau of Meteorology employs a statistical method to forecast seasonal streamflows. The method uses predictors that are related to catchment wetness at the start of a forecast period and to climate during the forecast period. For the latter, a predictor is selected among a number of lagged climate indices as candidates to give the "best" model in terms of model performance in cross validation. This study investigates two strategies for further improvement in seasonal streamflow forecasts. The first is to combine, through Bayesian model averaging, multiple candidate models with different lagged climate indices as predictors, to take advantage of different predictive strengths of the multiple models. The second strategy is to introduce additional candidate models, using rainfall and sea surface temperature predictions from a global climate model as predictors. This is to take advantage of the direct simulations of various dynamic processes. The results show that combining forecasts from multiple statistical models generally yields more skillful forecasts than using only the best model and appears to moderate the worst forecast errors. The use of rainfall predictions from the dynamical climate model marginally improves the streamflow forecasts when viewed over all the study catchments and seasons, but the use of sea surface temperature predictions provide little additional benefit.

Application of Neural Network Optimized by Mind Evolutionary Computation in Building Energy Prediction

NASA Astrophysics Data System (ADS)

Song, Chen; Zhong-Cheng, Wu; Hong, Lv

2018-03-01

Building Energy forecasting plays an important role in energy management and plan. Using mind evolutionary algorithm to find the optimal network weights and threshold, to optimize the BP neural network, can overcome the problem of the BP neural network into a local minimum point. The optimized network is used for time series prediction, and the same month forecast, to get two predictive values. Then two kinds of predictive values are put into neural network, to get the final forecast value. The effectiveness of the method was verified by experiment with the energy value of three buildings in Hefei.

An analysis of land use planning and equity issues surrounding hazardous liquid and natural gas transmission pipelines in North Carolina

NASA Astrophysics Data System (ADS)

Osland, Anna Christine

Hazardous liquid and natural gas transmission pipelines have received limited attention by planning scholars even though local development decisions can have broad consequences if a rupture occurs. In this dissertation, I evaluated the implications of land-use planning for reducing risk to transmission pipeline hazards in North Carolina via three investigations. First, using a survey of planning directors in jurisdictions with transmission pipeline hazards, I investigated the land use planning tools used to mitigate pipeline hazards and the factors associated with tool adoption. Planning scholars have documented the difficulty of inducing planning in hazardous areas, yet there remain gaps in knowledge about the factors associated with tool adoption. Despite the risks associated with pipeline ruptures, I found most localities use few mitigation tools, and the adoption of regulatory and informational tools appear to be influenced by divergent factors. Whereas risk perception, commitment, capacity, and community context were associated with total tool and information tool use, only risk perception and capacity factors were associated with regulatory tool use. Second, using interviews of emergency managers and planning directors, I examined the role of agency collaboration for building mitigation capacity. Scholars have highlighted the potential of technical collaboration, yet less research has investigated how inter-agency collaboration shapes mitigation capacity. I identify three categories of technical collaboration, discuss how collaborative spillovers can occur from one planning area to another, and challenge the notion that all technical collaborations result in equal mitigation outcomes. Third, I evaluated characteristics of the population near pipelines to address equity concerns. Surprisingly, I did not find broad support for differences in exposure of vulnerable populations. Nonetheless, my analyses uncovered statistically significant clusters of vulnerable groups within the hazard area. Interestingly, development closer to pipelines was newer than areas farther away, illustrating the failure of land-use planning to reduce development encroachment. Collectively, these results highlight the potential of land-use planning to keep people and development from encroaching on pipeline hazards. While this study indicates that planners in many areas address pipeline hazards, it also illustrates how changes to local practices can further reduce risks to human health, homeland security, and the environment.

Research on water shortage risks and countermeasures in North China

NASA Astrophysics Data System (ADS)

Cheng, Yuxiang; Fang, Wenxuan; Wu, Ziqin

2017-05-01

In the paper, a grey forecasting model and a population growth model are established for forecasting water resources supply and demand situation in the region, and evaluating the scarcity of water resources thereof in order to solve the problem of water shortage in North China. A concrete plan for alleviating water resources pressure is proposed with AHP as basis, thereby discussing the feasibility of the plan. Firstly, water resources supply and demand in the future 15 years are predicted. There are four sources for the demand of water resources mainly: industry, agriculture, ecology and resident living. Main supply sources include surface water and underground water resources. A grey forecasting method is adopted for predicting in the paper aiming at water resources demands since industrial, agricultural and ecological water consumption data have excessive decision factors and the correlation is relatively fuzzy. Since residents' water consumption is determined by per capita water consumption and local population, a logistic growth model is adopted to forecast the population. The grey forecasting method is used for predicting per capita water consumption, and total water demand can be obtained finally. International calculation standards are adopted as reference aiming at water supply. The grey forecasting method is adopted for forecasting surface water quantity and underground water quantity, and water resources supply is obtained finally. Per capita water availability in the region is calculated by comparing the water resources supply and demand. Results show that per capita water availability in the region is only 283 cubic meters this year, people live in serious water shortage region, who will suffer from water shortage state for long time. Then, sensitivity analysis is applied for model test. The test result is excellent, and the prediction results are more accurate. In the paper, the following measures are proposed for improving water resources condition in the region according to prediction results, such as construction of reservoirs, sewage treatment, water diversion project and other measures. A detailed water supply plan is formulated. Water supply weights of all measures are determined according to the AHP model. Solution is sought after original models are improved. Results show that water resources quantity per capita will be up to 2170 cubic meters or so this year, people suffer from moderate water shortage in the region, which can meet people's life needs and economic development needs basically. In addition, water resources quantity per capita is increased year by year, and it can reach mild water shortage level after 2030. In a word, local water resources dilemma can be effectively solved by the plan actually, and thoughts can be provided for decision makers.

Operational Planning of Channel Airlift Missions Using Forecasted Demand

DTIC Science & Technology

2013-03-01

tailored to the specific problem ( Metaheuristics , 2005). As seen in the section Cargo Loading Algorithm , heuristic methods are often iterative...that are equivalent to the forecasted cargo amount. The simulated pallets are then used in a heuristic cargo loading algorithm . The loading... algorithm places cargo onto available aircraft (based on real schedules) given the date and the destination and outputs statistics based on the aircraft ton

Comprehensive Flood Plain Studies Using Spatial Data Management Techniques.

DTIC Science & Technology

1978-06-01

Hydrologic Engineer- ing Center computer programs that forecast urban storm water quality and dynamic in- stream water quality response to waste...determination. Water Quality The water quality analysis planned for the pilot study includes urban storm water quality forecasting and in-streamn...analysis is performed under the direction of Tony Thomas. Chief, Research Branch, by Jess Abbott for storm water quality analysis, R. G. Willey for

Demand Forecasting: An Evaluation of DODs Accuracy Metric and Navys Procedures

DTIC Science & Technology

2016-06-01

inventory management improvement plan, mean of absolute scaled error, lead time adjusted squared error, forecast accuracy, benchmarking, naïve method...Manager JASA Journal of the American Statistical Association LASE Lead-time Adjusted Squared Error LCI Life Cycle Indicator MA Moving Average MAE...Mean Squared Error xvi NAVSUP Naval Supply Systems Command NDAA National Defense Authorization Act NIIN National Individual Identification Number

Solar forecast and real-time monitoring needs of the Study of Energy Release in Flares (SERF)

NASA Technical Reports Server (NTRS)

Rust, D. M.

1979-01-01

Complementary, simultaneous observations of flares from as many observatories, both ground based and orbiting, as possible planned for the Solar Maximum Year are considered. The need for forecasts of solar activity on long term, one week, and two day intervals is described. Real time reporting is not needed, but daily summaries of activity and permanent records are important.

A multiscale forecasting method for power plant fleet management

NASA Astrophysics Data System (ADS)

Chen, Hongmei

In recent years the electric power industry has been challenged by a high level of uncertainty and volatility brought on by deregulation and globalization. A power producer must minimize the life cycle cost while meeting stringent safety and regulatory requirements and fulfilling customer demand for high reliability. Therefore, to achieve true system excellence, a more sophisticated system-level decision-making process with a more accurate forecasting support system to manage diverse and often widely dispersed generation units as a single, easily scaled and deployed fleet system in order to fully utilize the critical assets of a power producer has been created as a response. The process takes into account the time horizon for each of the major decision actions taken in a power plant and develops methods for information sharing between them. These decisions are highly interrelated and no optimal operation can be achieved without sharing information in the overall process. The process includes a forecasting system to provide information for planning for uncertainty. A new forecasting method is proposed, which utilizes a synergy of several modeling techniques properly combined at different time-scales of the forecasting objects. It can not only take advantages of the abundant historical data but also take into account the impact of pertinent driving forces from the external business environment to achieve more accurate forecasting results. Then block bootstrap is utilized to measure the bias in the estimate of the expected life cycle cost which will actually be needed to drive the business for a power plant in the long run. Finally, scenario analysis is used to provide a composite picture of future developments for decision making or strategic planning. The decision-making process is applied to a typical power producer chosen to represent challenging customer demand during high-demand periods. The process enhances system excellence by providing more accurate market information, evaluating the impact of external business environment, and considering cross-scale interactions between decision actions. Along with this process, system operation strategies, maintenance schedules, and capacity expansion plans that guide the operation of the power plant are optimally identified, and the total life cycle costs are estimated.

Forecasted Flood Depth Grids Providing Early Situational Awareness to FEMA during the 2017 Atlantic Hurricane Season

NASA Astrophysics Data System (ADS)

Jones, M.; Longenecker, H. E., III

2017-12-01

The 2017 hurricane season brought the unprecedented landfall of three Category 4 hurricanes (Harvey, Irma and Maria). FEMA is responsible for coordinating the federal response and recovery efforts for large disasters such as these. FEMA depends on timely and accurate depth grids to estimate hazard exposure, model damage assessments, plan flight paths for imagery acquisition, and prioritize response efforts. In order to produce riverine or coastal depth grids based on observed flooding, the methodology requires peak crest water levels at stream gauges, tide gauges, high water marks, and best-available elevation data. Because peak crest data isn't available until the apex of a flooding event and high water marks may take up to several weeks for field teams to collect for a large-scale flooding event, final observed depth grids are not available to FEMA until several days after a flood has begun to subside. Within the last decade NOAA's National Weather Service (NWS) has implemented the Advanced Hydrologic Prediction Service (AHPS), a web-based suite of accurate forecast products that provide hydrograph forecasts at over 3,500 stream gauge locations across the United States. These forecasts have been newly implemented into an automated depth grid script tool, using predicted instead of observed water levels, allowing FEMA access to flood hazard information up to 3 days prior to a flooding event. Water depths are calculated from the AHPS predicted flood stages and are interpolated at 100m spacing along NHD hydrolines within the basin of interest. A water surface elevation raster is generated from these water depths using an Inverse Distance Weighted interpolation. Then, elevation (USGS NED 30m) is subtracted from the water surface elevation raster so that the remaining values represent the depth of predicted flooding above the ground surface. This automated process requires minimal user input and produced forecasted depth grids that were comparable to post-event observed depth grids and remote sensing-derived flood extents for the 2017 hurricane season. These newly available forecasted models were used for pre-event response planning and early estimated hazard exposure counts, allowing FEMA to plan for and stand up operations several days sooner than previously possible.

Modeling and Analysis of Geoelectric Fields: Extended Solar Shield

NASA Astrophysics Data System (ADS)

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

2016-12-01

In the NASA Applied Sciences Program Solar Shield project, an unprecedented first-principles-based system to forecast geomagnetically induced current (GIC) in high-voltage power transmission systems was developed. Rapid progress in the field of numerical physics-based space environment modeling has led to major developments over the past few years. In this study modeling and analysis of induced geoelectric fields is discussed. Specifically, we focus on the successful incorporation of 3-D EM transfer functions in the modeling of E-fields, and on the analysis of near real-time simulation outputs used in the Solar Shield forecast system. The extended Solar Shield is a collaborative project between DHS, NASA, NOAA, CUA and EPRI.

Applications of NASA and NOAA Satellite Observations by NASA's Short-term Prediction Research and Transition (SPoRT) Center in Response to Natural Disasters

NASA Technical Reports Server (NTRS)

Molthan, Andrew L.; Burks, Jason E.; McGrath, Kevin M.; Jedlovec, Gary J.

2012-01-01

NASA s Short-term Prediction Research and Transition (SPoRT) Center supports the transition of unique NASA and NOAA research activities to the operational weather forecasting community. SPoRT emphasizes real-time analysis and prediction out to 48 hours. SPoRT partners with NOAA s National Weather Service (NWS) Weather Forecast Offices (WFOs) and National Centers to improve current products, demonstrate future satellite capabilities and explore new data assimilation techniques. Recently, the SPoRT Center has been involved in several activities related to disaster response, in collaboration with NOAA s National Weather Service, NASA s Applied Sciences Disasters Program, and other partners.

Development of a decision support system for monitoring, reporting and forecasting ecological conditions of the Appalachian Trail

USGS Publications Warehouse

Wang, Yeqiao; Nemani, Ramakrishna; Dieffenbach, Fred; Stolte, Kenneth; Holcomb, Glenn B.; Robinson, Matt; Reese, Casey C.; McNiff, Marcia; Duhaime, Roland; Tierney, Geri; Mitchell, Brian; August, Peter; Paton, Peter; LaBash, Charles

2010-01-01

This paper introduces a collaborative multi-agency effort to develop an Appalachian Trail (A.T.) MEGA-Transect Decision Support System (DSS) for monitoring, reporting and forecasting ecological conditions of the A.T. and the surrounding lands. The project is to improve decisionmaking on management of the A.T. by providing a coherent framework for data integration, status reporting and trend analysis. The A.T. MEGA-Transect DSS is to integrate NASA multi-platform sensor data and modeling through the Terrestrial Observation and Prediction System (TOPS) and in situ measurements from A.T. MEGA-Transect partners to address identified natural resource priorities and improve resource management decisions.

76 FR 17419 - Federal Health IT Strategic Plan: 2011-2015 Open Comment Period

Federal Register 2010, 2011, 2012, 2013, 2014

2011-03-29

... consultation with other appropriate Federal agencies and in collaboration with private and public entities. Work on the five-year Plan began more than a year ago and has included collaboration across federal...

Collaboration process for integrated social and health care strategy implementation.

PubMed

Korpela, Jukka; Elfvengren, Kalle; Kaarna, Tanja; Tepponen, Merja; Tuominen, Markku

2012-01-01

To present a collaboration process for creating a roadmap for the implementation of a strategy for integrated health and social care. The developed collaboration process includes multiple phases and uses electronic group decision support system technology (GDSS). A case study done in the South Karelia District of Social and Health Services in Finland during 2010-2011. An expert panel of 13 participants was used in the planning process of the strategy implementation. The participants were interviewed and observed during the case study. As a practical result, a roadmap for integrated health and social care strategy implementation has been developed. The strategic roadmap includes detailed plans of several projects which are needed for successful integration strategy implementation. As an academic result, a collaboration process to create such a roadmap has been developed. The collaboration process and technology seem to suit the planning process well. The participants of the meetings were satisfied with the collaboration process and the GDSS technology. The strategic roadmap was accepted by the participants, which indicates satisfaction with the developed process.

Financial forecasts accuracy in Brazil's social security system.

PubMed

Silva, Carlos Patrick Alves da; Puty, Claudio Alberto Castelo Branco; Silva, Marcelino Silva da; Carvalho, Solon Venâncio de; Francês, Carlos Renato Lisboa

2017-01-01

Long-term social security statistical forecasts produced and disseminated by the Brazilian government aim to provide accurate results that would serve as background information for optimal policy decisions. These forecasts are being used as support for the government's proposed pension reform that plans to radically change the Brazilian Constitution insofar as Social Security is concerned. However, the reliability of official results is uncertain since no systematic evaluation of these forecasts has ever been published by the Brazilian government or anyone else. This paper aims to present a study of the accuracy and methodology of the instruments used by the Brazilian government to carry out long-term actuarial forecasts. We base our research on an empirical and probabilistic analysis of the official models. Our empirical analysis shows that the long-term Social Security forecasts are systematically biased in the short term and have significant errors that render them meaningless in the long run. Moreover, the low level of transparency in the methods impaired the replication of results published by the Brazilian Government and the use of outdated data compromises forecast results. In the theoretical analysis, based on a mathematical modeling approach, we discuss the complexity and limitations of the macroeconomic forecast through the computation of confidence intervals. We demonstrate the problems related to error measurement inherent to any forecasting process. We then extend this exercise to the computation of confidence intervals for Social Security forecasts. This mathematical exercise raises questions about the degree of reliability of the Social Security forecasts.

Financial forecasts accuracy in Brazil’s social security system

PubMed Central

2017-01-01

Long-term social security statistical forecasts produced and disseminated by the Brazilian government aim to provide accurate results that would serve as background information for optimal policy decisions. These forecasts are being used as support for the government’s proposed pension reform that plans to radically change the Brazilian Constitution insofar as Social Security is concerned. However, the reliability of official results is uncertain since no systematic evaluation of these forecasts has ever been published by the Brazilian government or anyone else. This paper aims to present a study of the accuracy and methodology of the instruments used by the Brazilian government to carry out long-term actuarial forecasts. We base our research on an empirical and probabilistic analysis of the official models. Our empirical analysis shows that the long-term Social Security forecasts are systematically biased in the short term and have significant errors that render them meaningless in the long run. Moreover, the low level of transparency in the methods impaired the replication of results published by the Brazilian Government and the use of outdated data compromises forecast results. In the theoretical analysis, based on a mathematical modeling approach, we discuss the complexity and limitations of the macroeconomic forecast through the computation of confidence intervals. We demonstrate the problems related to error measurement inherent to any forecasting process. We then extend this exercise to the computation of confidence intervals for Social Security forecasts. This mathematical exercise raises questions about the degree of reliability of the Social Security forecasts. PMID:28859172

Collaboration between civilian and military healthcare professionals: a better way for planning, preparing, and responding to all hazard domestic events.

PubMed

Marklund, LeRoy A; Graham, Adrienne M; Morton, Patricia G; Hurst, Charles G; Motola, Ivette; Robinson, Donald W; Kelley, Vivian A; Elenberg, Kimberly J; Russler, Michael F; Boehm, Daniel E; Higgins, Dawn M; McAndrew, Patrick E; Williamson, Hope M; Atwood, Rodney D; Huebner, Kermit D; Brotons, Angel A; Miller, Geoffrey T; Rimpel, Laukton Y; Harris, Larry L; Santiago, Manuel; Cantrell, LeRoy

2010-01-01

Collaboration is used by the US National Security Council as a means to integrate inter-federal government agencies during planning and execution of common goals towards unified, national security. The concept of collaboration has benefits in the healthcare system by building trust, sharing resources, and reducing costs. The current terrorist threats have made collaborative medical training between military and civilian agencies crucial. This review summarizes the long and rich history of collaboration between civilians and the military in various countries and provides support for the continuation and improvement of collaborative efforts. Through collaboration, advances in the treatment of injuries have been realized, deaths have been reduced, and significant strides in the betterment of the Emergency Medical System have been achieved. This review promotes collaborative medical training between military and civilian medical professionals and provides recommendations for the future based on medical collaboration.

Distributed Cognition and Embodiment in Text Planning: A Situated Study of Collaborative Writing in the Workplace

ERIC Educational Resources Information Center

Clayson, Ashley

2018-01-01

Through a study of collaborative writing at a student advocacy nonprofit, this article explores how writers distribute their text planning across tools, artifacts, and gestures, with a particular focus on how embodied representations of texts are present in text planning. Findings indicate that these and other representations generated by the…

Community wildfire protection plans: enhancing collaboration and building scoial capacity

Treesearch

Daniel R. Williams; Pamela J. Jakes; Sam Burns; Antony Cheng

2009-01-01

The Healthy Forest Restoration Act of 2003 (HFRA) was enacted to reduce wildfire risk to communities and other at-risk lands through a collaborative process of planning, prioritizing and implementing hazardous fuel reduction projects. One of the key features of HFRA is the development of community wildfire protection plans (CWPPs). We studied the development of CWPPs...

The Agenda for Strategic Planning in Social Institutions Such as Government, Post-Secondary Education and Corporations: An Element of the Accreditation Self-Study at College of the Mainland.

ERIC Educational Resources Information Center

Vaughan, Jerry L., Sr.

This paper presents a discussion of strategic planning within social institutions and provides a planning agenda that focuses on modern trends, forecasts, and projections. First, the background of the strategic planning process is reviewed, and historical changes in the nature of modern technology are delineated, including a transformation in…

Strategic Planning: An Integrated Academic Information Management System (IAIMS) at Georgetown University Medical Center. Volume 1, Implementation Plan. Volume 2, Planning Accomplishments. Volume 3, Environmental Forecast. Volume 4, Institutional Self Study.

ERIC Educational Resources Information Center

Broering, Naomi C.; And Others

Strategic planning for an Integrated Academic Information Management System (IAIMS) for Georgetown University Medical Center is considered. The goal is to organize and transmit accessible and timely biomedical information where it is needed. Activities are proposed for education, research, patient care, management, sharing information on…

Building successful coalitions for promoting advance care planning.

PubMed

Marchand, Lucille; Fowler, Kathryn J; Kokanovic, Obrad

2006-01-01

Advance care planning (ACP) has had few successful initiatives. This qualitative study explores the challenges and successes of an advance care planning coalition in Wisconsin called Life Planning 2000 using key informant interviews (n = 24) and grounded theory. Major themes included: commitment (the need for leadership, recruitment of key members, and funding); cohesiveness (disparate groups collaborating toward a common purpose), and outcomes (shift in paradigm from signing documents to process of advanced care planning, new-found collaborative relationships, and educational tool development). Coalitions need to define short-, intermediate-, and long-term goals that result in measurable outcomes and an evaluation process. Resources must be commensurate with goals. Strong leadership, paid staff adequate funding, and the collaboration of diverse groups working toward common goals are the basic requirements of a successful coalition.

Forecasting Reading Anxiety for Promoting English-Language Reading Performance Based on Reading Annotation Behavior

ERIC Educational Resources Information Center

Chen, Chih-Ming; Wang, Jung-Ying; Chen, Yong-Ting; Wu, Jhih-Hao

2016-01-01

To reduce effectively the reading anxiety of learners while reading English articles, a C4.5 decision tree, a widely used data mining technique, was used to develop a personalized reading anxiety prediction model (PRAPM) based on individual learners' reading annotation behavior in a collaborative digital reading annotation system (CDRAS). In…

Fine-resolution conservation planning with limited climate-change information.

PubMed

Shah, Payal; Mallory, Mindy L; Ando, Amy W; Guntenspergen, Glenn R

2017-04-01

Climate-change induced uncertainties in future spatial patterns of conservation-related outcomes make it difficult to implement standard conservation-planning paradigms. A recent study translates Markowitz's risk-diversification strategy from finance to conservation settings, enabling conservation agents to use this diversification strategy for allocating conservation and restoration investments across space to minimize the risk associated with such uncertainty. However, this method is information intensive and requires a large number of forecasts of ecological outcomes associated with possible climate-change scenarios for carrying out fine-resolution conservation planning. We developed a technique for iterative, spatial portfolio analysis that can be used to allocate scarce conservation resources across a desired level of subregions in a planning landscape in the absence of a sufficient number of ecological forecasts. We applied our technique to the Prairie Pothole Region in central North America. A lack of sufficient future climate information prevented attainment of the most efficient risk-return conservation outcomes in the Prairie Pothole Region. The difference in expected conservation returns between conservation planning with limited climate-change information and full climate-change information was as large as 30% for the Prairie Pothole Region even when the most efficient iterative approach was used. However, our iterative approach allowed finer resolution portfolio allocation with limited climate-change forecasts such that the best possible risk-return combinations were obtained. With our most efficient iterative approach, the expected loss in conservation outcomes owing to limited climate-change information could be reduced by 17% relative to other iterative approaches. © 2016 Society for Conservation Biology.

Seasonal scale water deficit forecasting in Africa and the Middle East using NASA's Land Information System (LIS)

NASA Astrophysics Data System (ADS)

Peters-Lidard, C. D.; Arsenault, K. R.; Shukla, S.; Getirana, A.; McNally, A.; Koster, R. D.; Zaitchik, B. F.; Badr, H. S.; Roningen, J. M.; Kumar, S.; Funk, C. C.

2017-12-01

A seamless and effective water deficit monitoring and early warning system is critical for assessing food security in Africa and the Middle East. In this presentation, we report on the ongoing development and validation of a seasonal scale water deficit forecasting system based on NASA's Land Information System (LIS) and seasonal climate forecasts. First, our presentation will focus on the implementation and validation of drought and water availability monitoring products in the region. Next, it will focus on evaluating drought and water availability forecasts. Finally, details will be provided of our ongoing collaboration with end-user partners in the region (e.g., USAID's Famine Early Warning Systems Network, FEWS NET), on formulating meaningful early warning indicators, effective communication and seamless dissemination of the products through NASA's web-services. The water deficit forecasting system thus far incorporates NASA GMAO's Catchment and the Noah Multi-Physics (MP) LSMs. In addition, the LSMs' surface and subsurface runoff are routed through the Hydrological Modeling and Analysis Platform (HyMAP) to simulate surface water dynamics. To establish a climatology from 1981-2015, the two LSMs are driven by NASA/GMAO's Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2), and the USGS and UCSB Climate Hazards Group InfraRed Precipitation with Station (CHIRPS) daily rainfall dataset. Comparison of the models' energy and hydrological budgets with independent observations suggests that major droughts are well-reflected in the climatology. The system uses seasonal climate forecasts from NASA's GEOS-5 (the Goddard Earth Observing System Model-5) and NCEP's Climate Forecast System-2, and it produces forecasts of soil moisture, ET and streamflow out to 6 months in the future. Forecasts of those variables are formulated in terms of indicators to provide forecasts of drought and water availability in the region. Current work suggests that for the Blue Nile basin, (1) the combination of GEOS-5 and CFSv2 is equivalent in skill to the full North American Multimodel Ensemble (NMME); and (2) the seasonal water deficit forecasting system skill for both soil moisture and streamflow anomalies is greater than the standard Ensemble Streamflow Prediction (ESP) approach.

Developing a web-based forecasting tool for nutrient management

USDA-ARS?s Scientific Manuscript database

Modern nutrient management planning tools provide strategic guidance that, in the best cases, educates farmers and others involved in nutrient management to make prudent management decisions. The strategic guidance provided by nutrient management plans does not provide the day-to-day support require...

Environmental Scanning Practices for Rural Colleges.

ERIC Educational Resources Information Center

Friedel, Janice Nahra; Lapin, Joel D.

1995-01-01

Discusses the importance of environmental scanning in the planning efforts of rural community colleges. Reviews basic techniques and terminology and suggests sources of data. Argues that environmental scanning allows rural colleges to inexpensively forecast change, identify implications for the organization, and plan preferred responses to shape…

Assessment of Folsom Lake Watershed response to historical and potential future climate scenarios

USGS Publications Warehouse

Carpenter, Theresa M.; Georgakakos, Konstantine P.

2000-01-01

An integrated forecast-control system was designed to allow the profitable use of ensemble forecasts for the operational management of multi-purpose reservoirs. The system ingests large-scale climate model monthly precipitation through the adjustment of the marginal distribution of reservoir-catchment precipitation to reflect occurrence of monthly climate precipitation amounts in the extreme terciles of their distribution. Generation of ensemble reservoir inflow forecasts is then accomplished with due account for atmospheric- forcing and hydrologic- model uncertainties. These ensemble forecasts are ingested by the decision component of the integrated system, which generates non- inferior trade-off surfaces and, given management preferences, estimates of reservoir- management benefits over given periods. In collaboration with the Bureau of Reclamation and the California Nevada River Forecast Center, the integrated system is applied to Folsom Lake in California to evaluate the benefits for flood control, hydroelectric energy production, and low flow augmentation. In addition to retrospective studies involving the historical period 1964-1993, system simulations were performed for the future period 2001-2030, under a control (constant future greenhouse-gas concentrations assumed at the present levels) and a greenhouse-gas- increase (1-% per annum increase assumed) scenario. The present paper presents and validates ensemble 30-day reservoir- inflow forecasts under a variety of situations. Corresponding reservoir management results are presented in Yao and Georgakakos, A., this issue. Principle conclusions of this paper are that the integrated system provides reliable ensemble inflow volume forecasts at the 5-% confidence level for the majority of the deciles of forecast frequency, and that the use of climate model simulations is beneficial mainly during high flow periods. It is also found that, for future periods with potential sharp climatic increases of precipitation amount and to maintain good reliability levels, operational ensemble inflow forecasting should involve atmospheric forcing from appropriate climatic periods.

Practical implementation of a particle filter data assimilation approach to estimate initial hydrologic conditions and initialize medium-range streamflow forecasts

NASA Astrophysics Data System (ADS)

Clark, Elizabeth; Wood, Andy; Nijssen, Bart; Mendoza, Pablo; Newman, Andy; Nowak, Kenneth; Arnold, Jeffrey

2017-04-01

In an automated forecast system, hydrologic data assimilation (DA) performs the valuable function of correcting raw simulated watershed model states to better represent external observations, including measurements of streamflow, snow, soil moisture, and the like. Yet the incorporation of automated DA into operational forecasting systems has been a long-standing challenge due to the complexities of the hydrologic system, which include numerous lags between state and output variations. To help demonstrate that such methods can succeed in operational automated implementations, we present results from the real-time application of an ensemble particle filter (PF) for short-range (7 day lead) ensemble flow forecasts in western US river basins. We use the System for Hydromet Applications, Research and Prediction (SHARP), developed by the National Center for Atmospheric Research (NCAR) in collaboration with the University of Washington, U.S. Army Corps of Engineers, and U.S. Bureau of Reclamation. SHARP is a fully automated platform for short-term to seasonal hydrologic forecasting applications, incorporating uncertainty in initial hydrologic conditions (IHCs) and in hydrometeorological predictions through ensemble methods. In this implementation, IHC uncertainty is estimated by propagating an ensemble of 100 temperature and precipitation time series through conceptual and physically-oriented models. The resulting ensemble of derived IHCs exhibits a broad range of possible soil moisture and snow water equivalent (SWE) states. The PF selects and/or weights and resamples the IHCs that are most consistent with external streamflow observations, and uses the particles to initialize a streamflow forecast ensemble driven by ensemble precipitation and temperature forecasts downscaled from the Global Ensemble Forecast System (GEFS). We apply this method in real-time for several basins in the western US that are important for water resources management, and perform a hindcast experiment to evaluate the utility of PF-based data assimilation on streamflow forecasts skill. This presentation describes findings, including a comparison of sequential and non-sequential particle weighting methods.

A collaborative interaction and visualization multi-modal environment for surgical planning.

PubMed

Foo, Jung Leng; Martinez-Escobar, Marisol; Peloquin, Catherine; Lobe, Thom; Winer, Eliot

2009-01-01

The proliferation of virtual reality visualization and interaction technologies has changed the way medical image data is analyzed and processed. This paper presents a multi-modal environment that combines a virtual reality application with a desktop application for collaborative surgical planning. Both visualization applications can function independently but can also be synced over a network connection for collaborative work. Any changes to either application is immediately synced and updated to the other. This is an efficient collaboration tool that allows multiple teams of doctors with only an internet connection to visualize and interact with the same patient data simultaneously. With this multi-modal environment framework, one team working in the VR environment and another team from a remote location working on a desktop machine can both collaborate in the examination and discussion for procedures such as diagnosis, surgical planning, teaching and tele-mentoring.

Understanding Farmers’ Forecast Use from Their Beliefs, Values, Social Norms, and Perceived Obstacles

NASA Astrophysics Data System (ADS)

Hu, Qi; Pytlik Zillig, Lisa M.; Lynne, Gary D.; Tomkins, Alan J.; Waltman, William J.; Hayes, Michael J.; Hubbard, Kenneth G.; Artikov, Ikrom; Hoffman, Stacey J.; Wilhite, Donald A.

2006-09-01

Although the accuracy of weather and climate forecasts is continuously improving and new information retrieved from climate data is adding to the understanding of climate variation, use of the forecasts and climate information by farmers in farming decisions has changed little. This lack of change may result from knowledge barriers and psychological, social, and economic factors that undermine farmer motivation to use forecasts and climate information. According to the theory of planned behavior (TPB), the motivation to use forecasts may arise from personal attitudes, social norms, and perceived control or ability to use forecasts in specific decisions. These attributes are examined using data from a survey designed around the TPB and conducted among farming communities in the region of eastern Nebraska and the western U.S. Corn Belt. There were three major findings: 1) the utility and value of the forecasts for farming decisions as perceived by farmers are, on average, around 3.0 on a 0 7 scale, indicating much room to improve attitudes toward the forecast value. 2) The use of forecasts by farmers to influence decisions is likely affected by several social groups that can provide “expert viewpoints” on forecast use. 3) A major obstacle, next to forecast accuracy, is the perceived identity and reliability of the forecast makers. Given the rapidly increasing number of forecasts in this growing service business, the ambiguous identity of forecast providers may have left farmers confused and may have prevented them from developing both trust in forecasts and skills to use them. These findings shed light on productive avenues for increasing the influence of forecasts, which may lead to greater farming productivity. In addition, this study establishes a set of reference points that can be used for comparisons with future studies to quantify changes in forecast use and influence.