The importance of terrestrial weathering for climate system modelling on extended timescales: a study with the UVic ESCM

NASA Astrophysics Data System (ADS)

Brault, Marc-Olivier; Matthews, Damon; Mysak, Lawrence

2016-04-01

The chemical erosion of carbonate and silicate rocks is a key process in the global carbon cycle and, through its coupling with calcium carbonate deposition in the ocean, is the primary sink of carbon on geologic timescales. The dynamic interdependence of terrestrial weathering rates with atmospheric temperature and carbon dioxide concentrations is crucial to the regulation of Earth's climate over multi-millennial timescales. However any attempts to develop a modeling context for terrestrial weathering as part of a dynamic climate system are limited, mostly because of the difficulty in adapting the multi-millennial timescales of the implied negative feedback mechanism with those of the atmosphere and ocean. Much of the earlier work on this topic is therefore based on box-model approaches, abandoning spatial variability for the sake of computational efficiency and the possibility to investigate the impact of weathering on climate change over time frames much longer than those allowed by traditional climate system models. As a result we still have but a rudimentary understanding of the chemical weathering feedback mechanism and its effects on ocean biogeochemistry and atmospheric CO2. Here, we introduce a spatially-explicit, rock weathering model into the University of Victoria Earth System Climate Model (UVic ESCM). We use a land map which takes into account a number of different rock lithologies, changes in sea level, as well as an empirical model of the temperature and NPP dependency of weathering rates for the different rock types. We apply this new model to the last deglacial period (c. 21000BP to 13000BP) as well as a future climate change scenario (c. 1800AD to 6000AD+), comparing the results of our 2-D version of the weathering feedback mechanism to simulations using only the box-model parameterizations of Meissner et al. [2012]. These simulations reveal the importance of two-dimensional factors (i.e., changes in sea level and rock type distribution) in the

Pilot Weather Advisor System

NASA Technical Reports Server (NTRS)

Lindamood, Glenn; Martzaklis, Konstantinos Gus; Hoffler, Keith; Hill, Damon; Mehrotra, Sudhir C.; White, E. Richard; Fisher, Bruce D.; Crabill, Norman L.; Tucholski, Allen D.

2006-01-01

The Pilot Weather Advisor (PWA) system is an automated satellite radio-broadcasting system that provides nearly real-time weather data to pilots of aircraft in flight anywhere in the continental United States. The system was designed to enhance safety in two distinct ways: First, the automated receipt of information would relieve the pilot of the time-consuming and distracting task of obtaining weather information via voice communication with ground stations. Second, the presentation of the information would be centered around a map format, thereby making the spatial and temporal relationships in the surrounding weather situation much easier to understand

A Real-Time Offshore Weather Risk Advisory System

NASA Astrophysics Data System (ADS)

Jolivet, Samuel; Zemskyy, Pavlo; Mynampati, Kalyan; Babovic, Vladan

2015-04-01

Offshore oil and gas operations in South East Asia periodically face extended downtime due to unpredictable weather conditions, including squalls that are accompanied by strong winds, thunder, and heavy rains. This downtime results in financial losses. Hence, a real time weather risk advisory system is developed to provide the offshore Oil and Gas (O&G) industry specific weather warnings in support of safety and environment security. This system provides safe operating windows based on sensitivity of offshore operations to sea state. Information products for safety and security include area of squall occurrence for the next 24 hours, time before squall strike, and heavy sea state warning for the next 3, 6, 12 & 24 hours. These are predicted using radar now-cast, high resolution Numerical Weather Prediction (NWP) and Data Assimilation (DA). Radar based now-casting leverages the radar data to produce short term (up to 3 hours) predictions of severe weather events including squalls/thunderstorms. A sea state approximation is provided through developing a translational model based on these predictions to risk rank the sensitivity of operations. A high resolution Weather Research and Forecasting (WRF, an open source NWP model) is developed for offshore Brunei, Malaysia and the Philippines. This high resolution model is optimized and validated against the adaptation of temperate to tropical met-ocean parameterization. This locally specific parameters are calibrated against federated data to achieve a 24 hour forecast of high resolution Convective Available Potential Energy (CAPE). CAPE is being used as a proxy for the risk of squall occurrence. Spectral decomposition is used to blend the outputs of the now-cast and the forecast in order to assimilate near real time weather observations as an implementation of the integration of data sources. This system uses the now-cast for the first 3 hours and then the forecast prediction horizons of 3, 6, 12 & 24 hours. The output is

Adaptation of Mesoscale Weather Models to Local Forecasting

NASA Technical Reports Server (NTRS)

Manobianco, John T.; Taylor, Gregory E.; Case, Jonathan L.; Dianic, Allan V.; Wheeler, Mark W.; Zack, John W.; Nutter, Paul A.

2003-01-01

Methodologies have been developed for (1) configuring mesoscale numerical weather-prediction models for execution on high-performance computer workstations to make short-range weather forecasts for the vicinity of the Kennedy Space Center (KSC) and the Cape Canaveral Air Force Station (CCAFS) and (2) evaluating the performances of the models as configured. These methodologies have been implemented as part of a continuing effort to improve weather forecasting in support of operations of the U.S. space program. The models, methodologies, and results of the evaluations also have potential value for commercial users who could benefit from tailoring their operations and/or marketing strategies based on accurate predictions of local weather. More specifically, the purpose of developing the methodologies for configuring the models to run on computers at KSC and CCAFS is to provide accurate forecasts of winds, temperature, and such specific thunderstorm-related phenomena as lightning and precipitation. The purpose of developing the evaluation methodologies is to maximize the utility of the models by providing users with assessments of the capabilities and limitations of the models. The models used in this effort thus far include the Mesoscale Atmospheric Simulation System (MASS), the Regional Atmospheric Modeling System (RAMS), and the National Centers for Environmental Prediction Eta Model ( Eta for short). The configuration of the MASS and RAMS is designed to run the models at very high spatial resolution and incorporate local data to resolve fine-scale weather features. Model preprocessors were modified to incorporate surface, ship, buoy, and rawinsonde data as well as data from local wind towers, wind profilers, and conventional or Doppler radars. The overall evaluation of the MASS, Eta, and RAMS was designed to assess the utility of these mesoscale models for satisfying the weather-forecasting needs of the U.S. space program. The evaluation methodology includes

Weather Forecaster Understanding of Climate Models

NASA Astrophysics Data System (ADS)

Bol, A.; Kiehl, J. T.; Abshire, W. E.

2013-12-01

Weather forecasters, particularly those in broadcasting, are the primary conduit to the public for information on climate and climate change. However, many weather forecasters remain skeptical of model-based climate projections. To address this issue, The COMET Program developed an hour-long online lesson of how climate models work, targeting an audience of weather forecasters. The module draws on forecasters' pre-existing knowledge of weather, climate, and numerical weather prediction (NWP) models. In order to measure learning outcomes, quizzes were given before and after the lesson. Preliminary results show large learning gains. For all people that took both pre and post-tests (n=238), scores improved from 48% to 80%. Similar pre/post improvement occurred for National Weather Service employees (51% to 87%, n=22 ) and college faculty (50% to 90%, n=7). We believe these results indicate a fundamental misunderstanding among many weather forecasters of (1) the difference between weather and climate models, (2) how researchers use climate models, and (3) how they interpret model results. The quiz results indicate that efforts to educate the public about climate change need to include weather forecasters, a vital link between the research community and the general public.

Modeling rock weathering in small watersheds

NASA Astrophysics Data System (ADS)

Pacheco, Fernando A. L.; Van der Weijden, Cornelis H.

2014-05-01

Many mountainous watersheds are conceived as aquifer media where multiple groundwater flow systems have developed (Tóth, 1963), and as bimodal landscapes where differential weathering of bare and soil-mantled rock has occurred (Wahrhaftig, 1965). The results of a weathering algorithm (Pacheco and Van der Weijden, 2012a, 2014), which integrates topographic, hydrologic, rock structure and chemical data to calculate weathering rates at the watershed scale, validated the conceptual models in the River Sordo basin, a small watershed located in the Marão cordillera (North of Portugal). The coupling of weathering, groundwater flow and landscape evolution analyses, as accomplished in this study, is innovative and represents a remarkable achievement towards regionalization of rock weathering at the watershed scale. The River Sordo basin occupies an area of approximately 51.2 km2 and was shaped on granite and metassediment terrains between the altitudes 185-1300 m. The groundwater flow system is composed of recharge areas located at elevations >700 m, identified on the basis of δ18O data. Discharge cells comprehend terminations of local, intermediate and regional flow systems, identified on the basis of spring density patterns, infiltration depth estimates based on 87Sr/86Sr data, and spatial distributions of groundwater pH and natural mineralization. Intermediate and regional flow systems, defined where infiltration depths >125 m, develop solely along the contact zone between granites and metassediments, because fractures in this region are profound and their density is very large. Weathering is accelerated where rocks are covered by thick soils, being five times faster relative to sectors of the basin where rocks are covered by thin soils. Differential weathering of bare and soil-mantled rock is also revealed by the spatial distribution of calculated aquifer hydraulic diffusivities and groundwater travel times.

Large-Scale, Extratropical Weather Systems within Mars' Atmosphere

NASA Astrophysics Data System (ADS)

Hollingsworth, Jeffery L.

2013-04-01

During late autumn through early spring, extratropical regions on Mars exhibit profound mean zonal equator-to-pole thermal contrasts. The imposition of this strong meridional temperature variation supports intense eastward-traveling, synoptic weather systems (i.e., transient baroclinic/barotropic waves) within Mars' extratropical atmosphere. Such disturbances grow, mature and decay within the east-west varying seasonal-mean midlatitude jet stream (i.e., the polar vortex) on the planet. Near the surface, the weather disturbances indicated large-scale spiraling "comma"-shaped dust cloud structures and scimitar-shaped dust fronts, indicative of processes associated with cyclo-/fronto-genesis. The weather systems occur during specific seasons on Mars, and in both hemispheres. The northern hemisphere (NH) disturbances are significantly more intense than their counterparts in the southern hemisphere (SH). Further, the NH weather systems and accompanying frontal waves appear to have significant impacts on the transport of tracer fields (e.g., particularly dust and to some extent water species (vapor/ice) as well). And regarding dust, frontal waves appear to be key agents in the lifting, lofting, organization and transport of this particular atmospheric aerosol. In this paper, a brief background and supporting observations of Mars' extratropical weather systems is presented. This is followed by a short review of the theory and various modeling studies (i.e., ranging from highly simplified, mechanistic and full global circulation modeling investigations) which have been pursued. Finally, a discussion of outstanding issues and questions regarding the character and nature of Mars' extratropical traveling weather systems is offered.

Large-Scale Extratropical Weather Systems in Mars' Atmosphere

NASA Technical Reports Server (NTRS)

Hollingsworth, Jeffery L.

2013-01-01

During late autumn through early spring, extratropical regions on Mars exhibit profound mean zonal equator-to-pole thermal contrasts. The imposition of this strong meridional temperature variation supports intense eastward-traveling, synoptic weather systems (i.e., transient baroclinic/barotropic waves) within Mars' extratropical atmosphere. Such disturbances grow, mature and decay within the east-west varying seasonal-mean midlatitude jet stream (i.e., the polar vortex) on the planet. Near the surface, the weather disturbances indicated large-scale spiraling "comma"-shaped dust cloud structures and scimitar-shaped dust fronts, indicative of processes associated with cyclo-/fronto-genesis. The weather systems occur during specific seasons on Mars, and in both hemispheres. The northern hemisphere (NH) disturbances are significantly more intense than their counterparts in the southern hemisphere (SH). Further, the NH weather systems and accompanying frontal waves appear to have significant impacts on the transport of tracer fields (e.g., particularly dust and to some extent water species (vapor/ice) as well). And regarding dust, frontal waves appear to be key agents in the lifting, lofting, organization and transport of this particular atmospheric aerosol. In this paper, a brief background and supporting observations of Mars' extratropical weather systems is presented. This is followed by a short review of the theory and various modeling studies (i.e., ranging from highly simplified, mechanistic and full global circulation modeling investigations) which have been pursued. Finally, a discussion of outstanding issues and questions regarding the character and nature of Mars' extratropical traveling weather systems is offered.

Evaluation of Software Simulation of Road Weather Information System.

DOT National Transportation Integrated Search

2016-09-01

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

Numerical weather prediction model tuning via ensemble prediction system

NASA Astrophysics Data System (ADS)

Jarvinen, H.; Laine, M.; Ollinaho, P.; Solonen, A.; Haario, H.

2011-12-01

This paper discusses a novel approach to tune predictive skill of numerical weather prediction (NWP) models. NWP models contain tunable parameters which appear in parameterizations schemes of sub-grid scale physical processes. Currently, numerical values of these parameters are specified manually. In a recent dual manuscript (QJRMS, revised) we developed a new concept and method for on-line estimation of the NWP model parameters. The EPPES ("Ensemble prediction and parameter estimation system") method requires only minimal changes to the existing operational ensemble prediction infra-structure and it seems very cost-effective because practically no new computations are introduced. The approach provides an algorithmic decision making tool for model parameter optimization in operational NWP. In EPPES, statistical inference about the NWP model tunable parameters is made by (i) generating each member of the ensemble of predictions using different model parameter values, drawn from a proposal distribution, and (ii) feeding-back the relative merits of the parameter values to the proposal distribution, based on evaluation of a suitable likelihood function against verifying observations. In the presentation, the method is first illustrated in low-order numerical tests using a stochastic version of the Lorenz-95 model which effectively emulates the principal features of ensemble prediction systems. The EPPES method correctly detects the unknown and wrongly specified parameters values, and leads to an improved forecast skill. Second, results with an atmospheric general circulation model based ensemble prediction system show that the NWP model tuning capacity of EPPES scales up to realistic models and ensemble prediction systems. Finally, a global top-end NWP model tuning exercise with preliminary results is published.

Climate, weather, space weather: model development in an operational context

NASA Astrophysics Data System (ADS)

Folini, Doris

2018-05-01

Aspects of operational modeling for climate, weather, and space weather forecasts are contrasted, with a particular focus on the somewhat conflicting demands of "operational stability" versus "dynamic development" of the involved models. Some common key elements are identified, indicating potential for fruitful exchange across communities. Operational model development is compelling, driven by factors that broadly fall into four categories: model skill, basic physics, advances in computer architecture, and new aspects to be covered, from costumer needs over physics to observational data. Evaluation of model skill as part of the operational chain goes beyond an automated skill score. Permanent interaction between "pure research" and "operational forecast" people is beneficial to both sides. This includes joint model development projects, although ultimate responsibility for the operational code remains with the forecast provider. The pace of model development reflects operational lead times. The points are illustrated with selected examples, many of which reflect the author's background and personal contacts, notably with the Swiss Weather Service and the Max Planck Institute for Meteorology, Hamburg, Germany. In view of current and future challenges, large collaborations covering a range of expertise are a must - within and across climate, weather, and space weather. To profit from and cope with the rapid progress of computer architectures, supercompute centers must form part of the team.

Creating Weather System Ensembles Through Synergistic Process Modeling and Machine Learning

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

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

Treesearch

Joseph J. Charney; Lesley A. Fusina

2006-01-01

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

Large-Scale, Synoptic-Period Weather Systems in Mars' Atmosphere

NASA Astrophysics Data System (ADS)

Hollingsworth, Jeffery L.; Kahre, M.

2013-10-01

During late autumn through early spring, extratropical regions on Mars exhibit profound mean zonal equator-to-pole thermal contrasts associated with its waxing and waning seasonal polar ice caps. The imposition of this strong meridional temperature gradient supports intense eastward-traveling, synoptic-period weather systems (i.e., transient baroclinic/barotropic waves) within Mars' extratropical atmosphere. These disturbances grow, mature and decay within the east-west varying seasonal-mean middle and high-latitude westerly jet stream (i.e., the polar vortex) on the planet. Near the surface, such weather disturbances indicated distinctive, spiraling "comma"-shaped dust cloud structures of large scale, and scimitar-shaped dust fronts, indicative of processes associated with cyclo- and fronto-genesis. The weather systems are most intense during specific seasons on Mars, and in both hemispheres. The northern hemisphere (NH) disturbances appear to be significantly more vigorous than their counterparts in the southern hemisphere (SH). Further, the NH weather systems and accompanying frontal waves appear to have significant impacts on the transport of tracer fields (e.g., particularly dust and to some extent water species (vapor/ice) as well). Regarding dust, frontal waves appear to be key agents in the lifting, lofting, organization and transport of this atmospheric aerosol. A brief background and supporting observations of Mars' extratropical weather systems is presented. This is followed by various modeling studies (i.e., ranging from highly simplified, mechanistic and fully complex global circulation modeling investigations) that we are pursuing. In particular, transport of scalar quantities (e.g., tracers and high-order dynamically revealing diagnostic fields) are investigated. A discussion of outstanding issues and future modeling pursuits is offered related to Mars' extratropical traveling weather systems.

Space weather forecasting with a Multimodel Ensemble Prediction System (MEPS)

NASA Astrophysics Data System (ADS)

Schunk, R. W.; Scherliess, L.; Eccles, V.; Gardner, L. C.; Sojka, J. J.; Zhu, L.; Pi, X.; Mannucci, A. J.; Butala, M.; Wilson, B. D.; Komjathy, A.; Wang, C.; Rosen, G.

2016-07-01

The goal of the Multimodel Ensemble Prediction System (MEPS) program is to improve space weather specification and forecasting with ensemble modeling. Space weather can have detrimental effects on a variety of civilian and military systems and operations, and many of the applications pertain to the ionosphere and upper atmosphere. Space weather can affect over-the-horizon radars, HF communications, surveying and navigation systems, surveillance, spacecraft charging, power grids, pipelines, and the Federal Aviation Administration (FAA's) Wide Area Augmentation System (WAAS). Because of its importance, numerous space weather forecasting approaches are being pursued, including those involving empirical, physics-based, and data assimilation models. Clearly, if there are sufficient data, the data assimilation modeling approach is expected to be the most reliable, but different data assimilation models can produce different results. Therefore, like the meteorology community, we created a Multimodel Ensemble Prediction System (MEPS) for the Ionosphere-Thermosphere-Electrodynamics (ITE) system that is based on different data assimilation models. The MEPS ensemble is composed of seven physics-based data assimilation models for the ionosphere, ionosphere-plasmasphere, thermosphere, high-latitude ionosphere-electrodynamics, and middle to low latitude ionosphere-electrodynamics. Hence, multiple data assimilation models can be used to describe each region. A selected storm event that was reconstructed with four different data assimilation models covering the middle and low latitude ionosphere is presented and discussed. In addition, the effect of different data types on the reconstructions is shown.

WRF-Fire: coupled weather-wildland fire modeling with the weather research and forecasting model

Treesearch

Janice L. Coen; Marques Cameron; John Michalakes; Edward G. Patton; Philip J. Riggan; Kara M. Yedinak

2012-01-01

A wildland fire behavior module (WRF-Fire) was integrated into the Weather Research and Forecasting (WRF) public domain numerical weather prediction model. The fire module is a surface fire behavior model that is two-way coupled with the atmospheric model. Near-surface winds from the atmospheric model are interpolated to a finer fire grid and used, with fuel properties...

The Future of Planetary Climate Modeling and Weather Prediction

NASA Technical Reports Server (NTRS)

Del Genio, A. D.; Domagal-Goldman, S. D.; Kiang, N. Y.; Kopparapu, R. K.; Schmidt, G. A.; Sohl, L. E.

2017-01-01

Modeling of planetary climate and weather has followed the development of tools for studying Earth, with lags of a few years. Early Earth climate studies were performed with 1-dimensionalradiative-convective models, which were soon fol-lowed by similar models for the climates of Mars and Venus and eventually by similar models for exoplan-ets. 3-dimensional general circulation models (GCMs) became common in Earth science soon after and within several years were applied to the meteorology of Mars, but it was several decades before a GCM was used to simulate extrasolar planets. Recent trends in Earth weather and and climate modeling serve as a useful guide to how modeling of Solar System and exoplanet weather and climate will evolve in the coming decade.

Enhanced Weather Radar (EWxR) System

NASA Technical Reports Server (NTRS)

Kronfeld, Kevin M. (Technical Monitor)

2003-01-01

An airborne weather radar system, the Enhanced Weather Radar (EWxR), with enhanced on-board weather radar data processing was developed and tested. The system features additional weather data that is uplinked from ground-based sources, specialized data processing, and limited automatic radar control to search for hazardous weather. National Weather Service (NWS) ground-based Next Generation Radar (NEXRAD) information is used by the EWxR system to augment the on-board weather radar information. The system will simultaneously display NEXRAD and on-board weather radar information in a split-view format. The on-board weather radar includes an automated or hands-free storm-finding feature that optimizes the radar returns by automatically adjusting the tilt and range settings for the current altitude above the terrain and searches for storm cells near the atmospheric 0-degree isotherm. A rule-based decision aid was developed to automatically characterize cells as hazardous, possibly-hazardous, or non-hazardous based upon attributes of that cell. Cell attributes are determined based on data from the on-board radar and from ground-based radars. A flight path impact prediction algorithm was developed to help pilots to avoid hazardous weather along their flight plan and their mission. During development the system was tested on the NASA B757 aircraft and final tests were conducted on the Rockwell Collins Sabreliner.

Models and applications for space weather forecasting and analysis at the Community Coordinated Modeling Center.

NASA Astrophysics Data System (ADS)

Kuznetsova, Maria

The Community Coordinated Modeling Center (CCMC, http://ccmc.gsfc.nasa.gov) was established at the dawn of the new millennium as a long-term flexible solution to the problem of transition of progress in space environment modeling to operational space weather forecasting. CCMC hosts an expanding collection of state-of-the-art space weather models developed by the international space science community. Over the years the CCMC acquired the unique experience in preparing complex models and model chains for operational environment and developing and maintaining custom displays and powerful web-based systems and tools ready to be used by researchers, space weather service providers and decision makers. In support of space weather needs of NASA users CCMC is developing highly-tailored applications and services that target specific orbits or locations in space and partnering with NASA mission specialists on linking CCMC space environment modeling with impacts on biological and technological systems in space. Confidence assessment of model predictions is an essential element of space environment modeling. CCMC facilitates interaction between model owners and users in defining physical parameters and metrics formats relevant to specific applications and leads community efforts to quantify models ability to simulate and predict space environment events. Interactive on-line model validation systems developed at CCMC make validation a seamless part of model development circle. The talk will showcase innovative solutions for space weather research, validation, anomaly analysis and forecasting and review on-going community-wide model validation initiatives enabled by CCMC applications.

Pilot's Automated Weather Support System (PAWSS) concepts demonstration project. Phase 1: Pilot's weather information requirements and implications for weather data systems design

NASA Technical Reports Server (NTRS)

Crabill, Norman L.; Dash, Ernie R.

1991-01-01

The weather information requirements for pilots and the deficiencies of the current aviation weather support system in meeting these requirements are defined. As the amount of data available to pilots increases significantly in the near future, expert system technology will be needed to assist pilots in assimilating that information. Some other desirable characteristics of an automation-assisted system for weather data acquisition, dissemination, and assimilation are also described.

Adaptive Numerical Algorithms in Space Weather Modeling

NASA Technical Reports Server (NTRS)

Toth, Gabor; vanderHolst, Bart; Sokolov, Igor V.; DeZeeuw, Darren; Gombosi, Tamas I.; Fang, Fang; Manchester, Ward B.; Meng, Xing; Nakib, Dalal; Powell, Kenneth G.;

Global Navigation Satellite Systems and Space Weather: Building upon the International Space Weather Initiative

NASA Astrophysics Data System (ADS)

Gadimova, S. H.; Haubold, H. J.

2014-01-01

Globally there is growing interest in better unders tanding solar-terrestrial interactions, particularly patterns and trends in space weather. This is not only for scientific reasons, but also because the reliable operation of ground-based and space-based assets and infrastructures is increasingly dependent on their robustness against the detrimental effects of space weather. Consequently, in 2009, the United Nations Committee on the Peaceful Uses of Outer Space (COPUOS) proposed the International Space Weather Initiative (ISWI), as a follow-up activity to the International Heliophysical Year 2007 (IHY2007), to be implemented under a three-year workplan from 2010 to 2012 (UNGA Document, A/64/20). All achievements of international cooperation and coordination for ISWI, including instrumentation, data analysis, modelling, education, training and public outreach, are made a vailable through the ISWI Newsletter and the ISWI Website (http://www.iswi-secretariat.org/). Since the last solar maximum in 2000, societal dependence on global navigation satellite system (GNSS) has increased substantially. This situation has brought increasing attention to the subject of space weather and its effects on GNSS systems and users. Results concerning the impact of space weather on GNSS are made available at the Information Portal (www.unoosa.org) of the International Committee on Global Navigati on Satellite Systems (ICG). This paper briefly reviews the curre nt status of ISWI with regard to GNSS.

Weather forecasting expert system study

NASA Technical Reports Server (NTRS)

1985-01-01

Weather forecasting is critical to both the Space Transportation System (STS) ground operations and the launch/landing activities at NASA Kennedy Space Center (KSC). The current launch frequency places significant demands on the USAF weather forecasters at the Cape Canaveral Forecasting Facility (CCFF), who currently provide the weather forecasting for all STS operations. As launch frequency increases, KSC's weather forecasting problems will be great magnified. The single most important problem is the shortage of highly skilled forecasting personnel. The development of forecasting expertise is difficult and requires several years of experience. Frequent personnel changes within the forecasting staff jeopardize the accumulation and retention of experience-based weather forecasting expertise. The primary purpose of this project was to assess the feasibility of using Artificial Intelligence (AI) techniques to ameliorate this shortage of experts by capturing aria incorporating the forecasting knowledge of current expert forecasters into a Weather Forecasting Expert System (WFES) which would then be made available to less experienced duty forecasters.

New Space Weather Systems Under Development and Their Contribution to Space Weather Management

NASA Astrophysics Data System (ADS)

Tobiska, W.; Bouwer, D.; Schunk, R.; Garrett, H.; Mertens, C.; Bowman, B.

2008-12-01

There have been notable successes during the past decade in the development of operational space environment systems. Examples include the Magnetospheric Specification Model (MSM) of the Earth's magnetosphere, 2000; SOLAR2000 (S2K) solar spectral irradiances, 2001; High Accuracy Satellite Drag Model (HASDM) neutral atmosphere densities, 2004; Global Assimilation of Ionospheric Measurements (GAIM) ionosphere specification, 2006; Hakamada-Akasofu-Fry (HAF) solar wind parameters, 2007; Communication Alert and Prediction System (CAPS) ionosphere, high frequency radio, and scintillation S4 index prediction, 2008; and GEO Alert and Prediction System (GAPS) geosynchronous environment satellite charging specification and forecast, 2008. Operational systems that are in active operational implementation include the Jacchia-Bowman 2006/2008 (JB2006/2008) neutral atmosphere, 2009, and the Nowcast of Atmospheric Ionizing Radiation for Aviation Safety (NAIRAS) aviation radiation model using the Radiation Alert and Prediction System (RAPS), 2010. U.S. national agency and commercial assets will soon reach a state where specification and prediction will become ubiquitous and where coordinated management of the space environment and space weather will become a necessity. We describe the status of the CAPS, GAPS, RAPS, and JB2008 operational development. We additionally discuss the conditions that are laying the groundwork for space weather management and estimate the unfilled needs as we move beyond specification and prediction efforts.

Community Coordinated Modeling Center: Addressing Needs of Operational Space Weather Forecasting

NASA Technical Reports Server (NTRS)

Kuznetsova, M.; Maddox, M.; Pulkkinen, A.; Hesse, M.; Rastaetter, L.; Macneice, P.; Taktakishvili, A.; Berrios, D.; Chulaki, A.; Zheng, Y.;

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

NASA Astrophysics Data System (ADS)

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

2013-12-01

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

Weather Augmented Risk Determination (WARD) System

NASA Astrophysics Data System (ADS)

Niknejad, M.; Mazdiyasni, O.; Momtaz, F.; AghaKouchak, A.

2017-12-01

Extreme climatic events have direct and indirect impacts on society, economy and the environment. Based on the United States Bureau of Economic Analysis (BEA) data, over one third of the U.S. GDP can be considered as weather-sensitive involving some degree of weather risk. This expands from a local scale concrete foundation construction to large scale transportation systems. Extreme and unexpected weather conditions have always been considered as one of the probable risks to human health, productivity and activities. The construction industry is a large sector of the economy, and is also greatly influenced by weather-related risks including work stoppage and low labor productivity. Identification and quantification of these risks, and providing mitigation of their effects are always the concerns of construction project managers. In addition to severe weather conditions' destructive effects, seasonal changes in weather conditions can also have negative impacts on human health. Work stoppage and reduced labor productivity can be caused by precipitation, wind, temperature, relative humidity and other weather conditions. Historical and project-specific weather information can improve better project management and mitigation planning, and ultimately reduce the risk of weather-related conditions. This paper proposes new software for project-specific user-defined data analysis that offers (a) probability of work stoppage and the estimated project length considering weather conditions; (b) information on reduced labor productivity and its impacts on project duration; and (c) probabilistic information on the project timeline based on both weather-related work stoppage and labor productivity. The software (WARD System) is designed such that it can be integrated into the already available project management tools. While the system and presented application focuses on the construction industry, the developed software is general and can be used for any application that involves

The Impact of Different Complexity on Numerical Weather Predictions within the Coupled Global Online Modeling System

NASA Astrophysics Data System (ADS)

Zhang, L.; Grell, G. A.; McKeen, S. A.; Ahmadov, R.

2017-12-01

The global Flow-following finite-volume Icosahedra Model (FIM), which was developed in the Global Systems Division of NOAA/ESRL and the Finite-volume cubed-sphere dynamical core (FV3) developed by GFDL, have been coupled online with aerosol and gas-phase chemistry schemes (FIM-Chem and FV3-Chem). Within the aerosol and chemistry modules, the models handle wet and dry deposition, chemical reactions, aerosol direct and semi-direct effect, anthropogenic emissions, biogenic emissions, biomass burning, dust and sea-salt emissions. They are able to provide chemical weather predictions at various spatial resolutions and with different levels of complexity. FIM-Chem is also able to quantify the impact of aerosol on numerical weather predictions (NWP). Currently, three different chemical schemes have been coupled with the FIM model. The simplest aerosol modules are from the GOCART model with its simplified parameterization of sulfur/sulfate chemistry. The photochemical gas-phase mechanism RACM was included to determine the impact of additional complexity on the aerosol and gas simulations. We have also implemented a more sophisticated aerosol scheme that includes secondary organic aerosols (SOA) based on the VBS approach. The model performance has been evaluated by comparing with the ATom-1 observations. FIM-Chem is able to reproduce many observed aerosol and gas features very well. A five-day NWP on 120 km horizontal resolution using FIM-Chem has been done for the end of July, 2016 to quantify the impact of the three different chemical schemes on weather forecasts. Compared to a meteorological run that excludes the model chemical schemes, and is driven only by background AODs from the GFS model, the 5-day forecast results shows significant impact on weather predictions when including the prognostic aerosol schemes. This includes convective precipitation, surface temperature, and 700 hPa air temperature. We also use FIM-Chem to investigate the 2012 South American Biomass

Toward a Concept of Operations for Aviation Weather Information Implementation in the Evolving National Airspace System

NASA Technical Reports Server (NTRS)

McAdaragh, Raymon M.

2002-01-01

The capacity of the National Airspace System is being stressed due to the limits of current technologies. Because of this, the FAA and NASA are working to develop new technologies to increase the system's capacity which enhancing safety. Adverse weather has been determined to be a major factor in aircraft accidents and fatalities and the FAA and NASA have developed programs to improve aviation weather information technologies and communications for system users The Aviation Weather Information Element of the Weather Accident Prevention Project of NASA's Aviation Safety Program is currently working to develop these technologies in coordination with the FAA and industry. This paper sets forth a theoretical approach to implement these new technologies while addressing the National Airspace System (NAS) as an evolving system with Weather Information as one of its subSystems. With this approach in place, system users will be able to acquire the type of weather information that is needed based upon the type of decision-making situation and condition that is encountered. The theoretical approach addressed in this paper takes the form of a model for weather information implementation. This model addresses the use of weather information in three decision-making situations, based upon the system user's operational perspective. The model also addresses two decision-making conditions, which are based upon the need for collaboration due to the level of support offered by the weather information provided by each new product or technology. The model is proposed for use in weather information implementation in order to provide a systems approach to the NAS. Enhancements to the NAS collaborative decision-making capabilities are also suggested.

Investigation and Modeling of Cranberry Weather Stress.

NASA Astrophysics Data System (ADS)

Croft, Paul Joseph

Cranberry bog weather conditions and weather-related stress were investigated for development of crop yield prediction models and models to predict daily weather conditions in the bog. Field investigations and data gathering were completed at the Rutgers University Blueberry/Cranberry Research Center experimental bogs in Chatsworth, New Jersey. Study indicated that although cranberries generally exhibit little or no stomatal response to changing atmospheric conditions, the evaluation of weather-related stress could be accomplished via use of micrometeorological data. Definition of weather -related stress was made by establishing critical thresholds of the frequencies of occurrence, and magnitudes of, temperature and precipitation in the bog based on values determined by a review of the literature and a grower questionnaire. Stress frequencies were correlated with cranberry yield to develop predictive models based on the previous season's yield, prior season data, prior and current season data, current season data; and prior and current season data through July 31 of the current season. The predictive ability of the prior season models was best and could be used in crop planning and production. Further examination of bog micrometeorological data permitted the isolation of those weather conditions conducive to cranberry scald and allowed for the institution of a pilot scald advisory program during the 1991 season. The micrometeorological data from the bog was also used to develop models to predict daily canopy temperature and precipitation, based on upper air data, for grower use. Models were developed for each month for maximum and minimum temperatures and for precipitation and generally performed well. The modeling of bog weather conditions is an important first step toward daily prediction of cranberry weather-related stress.

Analysis of errors introduced by geographic coordinate systems on weather numeric prediction modeling

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

Cao, Yanni; Cervone, Guido; Barkley, Zachary

Most atmospheric models, including the Weather Research and Forecasting (WRF) model, use a spherical geographic coordinate system to internally represent input data and perform computations. However, most geographic information system (GIS) input data used by the models are based on a spheroid datum because it better represents the actual geometry of the earth. WRF and other atmospheric models use these GIS input layers as if they were in a spherical coordinate system without accounting for the difference in datum. When GIS layers are not properly reprojected, latitudinal errors of up to 21 km in the midlatitudes are introduced. Recent studiesmore » have suggested that for very high-resolution applications, the difference in datum in the GIS input data (e.g., terrain land use, orography) should be taken into account. However, the magnitude of errors introduced by the difference in coordinate systems remains unclear. This research quantifies the effect of using a spherical vs. a spheroid datum for the input GIS layers used by WRF to study greenhouse gas transport and dispersion in northeast Pennsylvania.« less

Analysis of errors introduced by geographic coordinate systems on weather numeric prediction modeling

DOE PAGES

Cao, Yanni; Cervone, Guido; Barkley, Zachary; ...

2017-09-19

Most atmospheric models, including the Weather Research and Forecasting (WRF) model, use a spherical geographic coordinate system to internally represent input data and perform computations. However, most geographic information system (GIS) input data used by the models are based on a spheroid datum because it better represents the actual geometry of the earth. WRF and other atmospheric models use these GIS input layers as if they were in a spherical coordinate system without accounting for the difference in datum. When GIS layers are not properly reprojected, latitudinal errors of up to 21 km in the midlatitudes are introduced. Recent studiesmore » have suggested that for very high-resolution applications, the difference in datum in the GIS input data (e.g., terrain land use, orography) should be taken into account. However, the magnitude of errors introduced by the difference in coordinate systems remains unclear. This research quantifies the effect of using a spherical vs. a spheroid datum for the input GIS layers used by WRF to study greenhouse gas transport and dispersion in northeast Pennsylvania.« less

Analysis of errors introduced by geographic coordinate systems on weather numeric prediction modeling

NASA Astrophysics Data System (ADS)

Cao, Yanni; Cervone, Guido; Barkley, Zachary; Lauvaux, Thomas; Deng, Aijun; Taylor, Alan

2017-09-01

Most atmospheric models, including the Weather Research and Forecasting (WRF) model, use a spherical geographic coordinate system to internally represent input data and perform computations. However, most geographic information system (GIS) input data used by the models are based on a spheroid datum because it better represents the actual geometry of the earth. WRF and other atmospheric models use these GIS input layers as if they were in a spherical coordinate system without accounting for the difference in datum. When GIS layers are not properly reprojected, latitudinal errors of up to 21 km in the midlatitudes are introduced. Recent studies have suggested that for very high-resolution applications, the difference in datum in the GIS input data (e.g., terrain land use, orography) should be taken into account. However, the magnitude of errors introduced by the difference in coordinate systems remains unclear. This research quantifies the effect of using a spherical vs. a spheroid datum for the input GIS layers used by WRF to study greenhouse gas transport and dispersion in northeast Pennsylvania.

Improving aerosol interaction with clouds and precipitation in a regional chemical weather modeling system

NASA Astrophysics Data System (ADS)

Zhou, C.; Zhang, X.; Gong, S.; Wang, Y.; Xue, M.

2016-01-01

A comprehensive aerosol-cloud-precipitation interaction (ACI) scheme has been developed under a China Meteorological Administration (CMA) chemical weather modeling system, GRAPES/CUACE (Global/Regional Assimilation and PrEdiction System, CMA Unified Atmospheric Chemistry Environment). Calculated by a sectional aerosol activation scheme based on the information of size and mass from CUACE and the thermal-dynamic and humid states from the weather model GRAPES at each time step, the cloud condensation nuclei (CCN) are interactively fed online into a two-moment cloud scheme (WRF Double-Moment 6-class scheme - WDM6) and a convective parameterization to drive cloud physics and precipitation formation processes. The modeling system has been applied to study the ACI for January 2013 when several persistent haze-fog events and eight precipitation events occurred.

The results show that aerosols that interact with the WDM6 in GRAPES/CUACE obviously increase the total cloud water, liquid water content, and cloud droplet number concentrations, while decreasing the mean diameters of cloud droplets with varying magnitudes of the changes in each case and region. These interactive microphysical properties of clouds improve the calculation of their collection growth rates in some regions and hence the precipitation rate and distributions in the model, showing 24 to 48 % enhancements of threat score for 6 h precipitation in almost all regions. The aerosols that interact with the WDM6 also reduce the regional mean bias of temperature by 3 °C during certain precipitation events, but the monthly means bias is only reduced by about 0.3 °C.

Traffic analysis toolbox volume XI : weather and traffic analysis, modeling and simulation.

DOT National Transportation Integrated Search

2010-12-01

This document presents a weather module for the traffic analysis tools program. It provides traffic engineers, transportation modelers and decisions makers with a guide that can incorporate weather impacts into transportation system analysis and mode...

Modelling Wind Turbine Failures based on Weather Conditions

NASA Astrophysics Data System (ADS)

Reder, Maik; Melero, Julio J.

2017-11-01

A large proportion of the overall costs of a wind farm is directly related to operation and maintenance (O&M) tasks. By applying predictive O&M strategies rather than corrective approaches these costs can be decreased significantly. Here, especially wind turbine (WT) failure models can help to understand the components’ degradation processes and enable the operators to anticipate upcoming failures. Usually, these models are based on the age of the systems or components. However, latest research shows that the on-site weather conditions also affect the turbine failure behaviour significantly. This study presents a novel approach to model WT failures based on the environmental conditions to which they are exposed to. The results focus on general WT failures, as well as on four main components: gearbox, generator, pitch and yaw system. A penalised likelihood estimation is used in order to avoid problems due to for example highly correlated input covariates. The relative importance of the model covariates is assessed in order to analyse the effect of each weather parameter on the model output.

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.

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.

Weather Forecasting Systems and Methods

NASA Technical Reports Server (NTRS)

Mecikalski, John (Inventor); MacKenzie, Wayne M., Jr. (Inventor); Walker, John Robert (Inventor)

2014-01-01

A weather forecasting system has weather forecasting logic that receives raw image data from a satellite. The raw image data has values indicative of light and radiance data from the Earth as measured by the satellite, and the weather forecasting logic processes such data to identify cumulus clouds within the satellite images. For each identified cumulus cloud, the weather forecasting logic applies interest field tests to determine a score indicating the likelihood of the cumulus cloud forming precipitation and/or lightning in the future within a certain time period. Based on such scores, the weather forecasting logic predicts in which geographic regions the identified cumulus clouds will produce precipitation and/or lighting within during the time period. Such predictions may then be used to provide a weather map thereby providing users with a graphical illustration of the areas predicted to be affected by precipitation within the time period.

Space Weather Products at the Community Coordinated Modeling Center

NASA Technical Reports Server (NTRS)

Hesse, Michael; Kuznetsova, M.; Pulkkinen, A.; Maddox, M.; Rastaetter, L.; Berrios, D.; MacNeice, P.

2010-01-01

The Community Coordinated Modeling Center (CCMC) is a US inter-agency activity aiming at research in support of the generation of advanced space weather models. As one of its main functions, the CCMC provides to researchers the use of space science models, even if they are not model owners themselves. The second CCMC activity is to support Space Weather forecasting at national Space Weather Forecasting Centers. This second activity involves model evaluations, model transitions to operations, and the development of space weather forecasting tools. Owing to the pace of development in the science community, new model capabilities emerge frequently. Consequently, space weather products and tools involve not only increased validity, but often entirely new capabilities. This presentation will review the present state of space weather tools as well as point out emerging future capabilities.

Improving aerosol interaction with clouds and precipitation in a regional chemical weather modeling system

NASA Astrophysics Data System (ADS)

Zhou, C.; Zhang, X.; Gong, S.

2015-12-01

A comprehensive aerosol-cloud-precipitation interaction (ACI) scheme has been developed under CMA chemical weather modeling system GRAPES/CUACE. Calculated by a sectional aerosol activation scheme based on the information of size and mass from CUACE and the thermal-dynamic and humid states from the weather model GRAPES at each time step, the cloud condensation nuclei (CCN) is fed online interactively into a two-moment cloud scheme (WDM6) and a convective parameterization to drive the cloud physics and precipitation formation processes. The modeling system has been applied to study the ACI for January 2013 when several persistent haze-fog events and eight precipitation events occurred. The results show that interactive aerosols with the WDM6 in GRAPES/CUACE obviously increase the total cloud water, liquid water content and cloud droplet number concentrations while decrease the mean diameter of cloud droplets with varying magnitudes of the changes in each case and region. These interactive micro-physical properties of clouds improve the calculation of their collection growth rates in some regions and hence the precipitation rate and distributions in the model, showing 24% to 48% enhancements of TS scoring for 6-h precipitation in almost all regions. The interactive aerosols with the WDM6 also reduce the regional mean bias of temperature by 3 °C during certain precipitation events, but the monthly means bias is only reduced by about 0.3°C.

An approach to secure weather and climate models against hardware faults

NASA Astrophysics Data System (ADS)

Düben, Peter D.; Dawson, Andrew

2017-03-01

Enabling Earth System models to run efficiently on future supercomputers is a serious challenge for model development. Many publications study efficient parallelization to allow better scaling of performance on an increasing number of computing cores. However, one of the most alarming threats for weather and climate predictions on future high performance computing architectures is widely ignored: the presence of hardware faults that will frequently hit large applications as we approach exascale supercomputing. Changes in the structure of weather and climate models that would allow them to be resilient against hardware faults are hardly discussed in the model development community. In this paper, we present an approach to secure the dynamical core of weather and climate models against hardware faults using a backup system that stores coarse resolution copies of prognostic variables. Frequent checks of the model fields on the backup grid allow the detection of severe hardware faults, and prognostic variables that are changed by hardware faults on the model grid can be restored from the backup grid to continue model simulations with no significant delay. To justify the approach, we perform model simulations with a C-grid shallow water model in the presence of frequent hardware faults. As long as the backup system is used, simulations do not crash and a high level of model quality can be maintained. The overhead due to the backup system is reasonable and additional storage requirements are small. Runtime is increased by only 13 % for the shallow water model.

An approach to secure weather and climate models against hardware faults

NASA Astrophysics Data System (ADS)

Düben, Peter; Dawson, Andrew

2017-04-01

Enabling Earth System models to run efficiently on future supercomputers is a serious challenge for model development. Many publications study efficient parallelisation to allow better scaling of performance on an increasing number of computing cores. However, one of the most alarming threats for weather and climate predictions on future high performance computing architectures is widely ignored: the presence of hardware faults that will frequently hit large applications as we approach exascale supercomputing. Changes in the structure of weather and climate models that would allow them to be resilient against hardware faults are hardly discussed in the model development community. We present an approach to secure the dynamical core of weather and climate models against hardware faults using a backup system that stores coarse resolution copies of prognostic variables. Frequent checks of the model fields on the backup grid allow the detection of severe hardware faults, and prognostic variables that are changed by hardware faults on the model grid can be restored from the backup grid to continue model simulations with no significant delay. To justify the approach, we perform simulations with a C-grid shallow water model in the presence of frequent hardware faults. As long as the backup system is used, simulations do not crash and a high level of model quality can be maintained. The overhead due to the backup system is reasonable and additional storage requirements are small. Runtime is increased by only 13% for the shallow water model.

An introduction to Space Weather Integrated Modeling

NASA Astrophysics Data System (ADS)

Zhong, D.; Feng, X.

2012-12-01

The need for a software toolkit that integrates space weather models and data is one of many challenges we are facing with when applying the models to space weather forecasting. To meet this challenge, we have developed Space Weather Integrated Modeling (SWIM) that is capable of analysis and visualizations of the results from a diverse set of space weather models. SWIM has a modular design and is written in Python, by using NumPy, matplotlib, and the Visualization ToolKit (VTK). SWIM provides data management module to read a variety of spacecraft data products and a specific data format of Solar-Interplanetary Conservation Element/Solution Element MHD model (SIP-CESE MHD model) for the study of solar-terrestrial phenomena. Data analysis, visualization and graphic user interface modules are also presented in a user-friendly way to run the integrated models and visualize the 2-D and 3-D data sets interactively. With these tools we can locally or remotely analysis the model result rapidly, such as extraction of data on specific location in time-sequence data sets, plotting interplanetary magnetic field lines, multi-slicing of solar wind speed, volume rendering of solar wind density, animation of time-sequence data sets, comparing between model result and observational data. To speed-up the analysis, an in-situ visualization interface is used to support visualizing the data 'on-the-fly'. We also modified some critical time-consuming analysis and visualization methods with the aid of GPU and multi-core CPU. We have used this tool to visualize the data of SIP-CESE MHD model in real time, and integrated the Database Model of shock arrival, Shock Propagation Model, Dst forecasting model and SIP-CESE MHD model developed by SIGMA Weather Group at State Key Laboratory of Space Weather/CAS.

NOAA SWPC / NASA CCMC Space Weather Modeling Assessment Project: Toward the Validation of Advancements in Heliospheric Space Weather Prediction Within WSA-Enlil

NASA Astrophysics Data System (ADS)

Adamson, E. T.; Pizzo, V. J.; Biesecker, D. A.; Mays, M. L.; MacNeice, P. J.; Taktakishvili, A.; Viereck, R. A.

2017-12-01

In 2011, NOAA's Space Weather Prediction Center (SWPC) transitioned the world's first operational space weather model into use at the National Weather Service's Weather and Climate Operational Supercomputing System (WCOSS). This operational forecasting tool is comprised of the Wang-Sheeley-Arge (WSA) solar wind model coupled with the Enlil heliospheric MHD model. Relying on daily-updated photospheric magnetograms produced by the National Solar Observatory's Global Oscillation Network Group (GONG), this tool provides critical predictive knowledge of heliospheric dynamics such as high speed streams and coronal mass ejections. With the goal of advancing this predictive model and quantifying progress, SWPC and NASA's Community Coordinated Modeling Center (CCMC) have initiated a collaborative effort to assess improvements in space weather forecasts at Earth by moving from a single daily-updated magnetogram to a sequence of time-dependent magnetograms to drive the ambient inputs for the WSA-Enlil model as well as incorporating the newly developed Air Force Data Assimilative Photospheric Flux Transport (ADAPT) model. We will provide a detailed overview of the scope of this effort and discuss preliminary results from the first phase focusing on the impact of time-dependent magnetogram inputs to the WSA-Enlil model.

Space Weather Models and Their Validation and Verification at the CCMC

NASA Technical Reports Server (NTRS)

Hesse, Michael

2010-01-01

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

Evaluation of weather-based rice yield models in India.

PubMed

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

2013-01-01

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

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.

Geodetic Space Weather Monitoring by means of Ionosphere Modelling

NASA Astrophysics Data System (ADS)

Schmidt, Michael

2017-04-01

The term space weather indicates physical processes and phenomena in space caused by radiation of energy mainly from the Sun. Manifestations of space weather are (1) variations of the Earth's magnetic field, (2) the polar lights in the northern and southern hemisphere, (3) variations within the ionosphere as part of the upper atmosphere characterized by the existence of free electrons and ions, (4) the solar wind, i.e. the permanent emission of electrons and photons, (5) the interplanetary magnetic field, and (6) electric currents, e.g. the van Allen radiation belt. It can be stated that ionosphere disturbances are often caused by so-called solar storms. A solar storm comprises solar events such as solar flares and coronal mass ejections (CMEs) which have different effects on the Earth. Solar flares may cause disturbances in positioning, navigation and communication. CMEs can effect severe disturbances and in extreme cases damages or even destructions of modern infrastructure. Examples are interruptions to satellite services including the global navigation satellite systems (GNSS), communication systems, Earth observation and imaging systems or a potential failure of power networks. Currently the measurements of solar satellite missions such as STEREO and SOHO are used to forecast solar events. Besides these measurements the Earth's ionosphere plays another key role in monitoring the space weather, because it responses to solar storms with an increase of the electron density. Space-geodetic observation techniques, such as terrestrial GNSS, satellite altimetry, space-borne GPS (radio occultation), DORIS and VLBI provide valuable global information about the state of the ionosphere. Additionally geodesy has a long history and large experience in developing and using sophisticated analysis and combination techniques as well as empirical and physical modelling approaches. Consequently, geodesy is predestinated for strongly supporting space weather monitoring via

A weather-driven model of malaria transmission.

PubMed

Hoshen, Moshe B; Morse, Andrew P

2004-09-06

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

Highlights of Space Weather Services/Capabilities at NASA/GSFC Space Weather Center

NASA Technical Reports Server (NTRS)

Fok, Mei-Ching; Zheng, Yihua; Hesse, Michael; Kuznetsova, Maria; Pulkkinen, Antti; Taktakishvili, Aleksandre; Mays, Leila; Chulaki, Anna; Lee, Hyesook

2012-01-01

The importance of space weather has been recognized world-wide. Our society depends increasingly on technological infrastructure, including the power grid as well as satellites used for communication and navigation. Such technologies, however, are vulnerable to space weather effects caused by the Sun's variability. NASA GSFC's Space Weather Center (SWC) (http://science.gsfc.nasa.gov//674/swx services/swx services.html) has developed space weather products/capabilities/services that not only respond to NASA's needs but also address broader interests by leveraging the latest scientific research results and state-of-the-art models hosted at the Community Coordinated Modeling Center (CCMC: http://ccmc.gsfc.nasa.gov). By combining forefront space weather science and models, employing an innovative and configurable dissemination system (iSWA.gsfc.nasa.gov), taking advantage of scientific expertise both in-house and from the broader community as well as fostering and actively participating in multilateral collaborations both nationally and internationally, NASA/GSFC space weather Center, as a sibling organization to CCMC, is poised to address NASA's space weather needs (and needs of various partners) and to help enhancing space weather forecasting capabilities collaboratively. With a large number of state-of-the-art physics-based models running in real-time covering the whole space weather domain, it offers predictive capabilities and a comprehensive view of space weather events throughout the solar system. In this paper, we will provide some highlights of our service products/capabilities. In particular, we will take the 23 January and the 27 January space weather events as examples to illustrate how we can use the iSWA system to track them in the interplanetary space and forecast their impacts.

An integrated weather and sea-state forecasting system for the Arabian Peninsula (WASSF)

NASA Astrophysics Data System (ADS)

Kallos, George; Galanis, George; Spyrou, Christos; Mitsakou, Christina; Solomos, Stavros; Bartsotas, Nikolaos; Kalogrei, Christina; Athanaselis, Ioannis; Sofianos, Sarantis; Vervatis, Vassios; Axaopoulos, Panagiotis; Papapostolou, Alexandros; Qahtani, Jumaan Al; Alaa, Elyas; Alexiou, Ioannis; Beard, Daniel

2013-04-01

Nowadays, large industrial conglomerates such as the Saudi ARAMCO, require a series of weather and sea state forecasting products that cannot be found in state meteorological offices or even commercial data providers. The two major objectives of the system is prevention and mitigation of environmental problems and of course early warning of local conditions associated with extreme weather events. The management and operations part is related to early warning of weather and sea-state events that affect operations of various facilities. The environmental part is related to air quality and especially the desert dust levels in the atmosphere. The components of the integrated system include: (i) a weather and desert dust prediction system with forecasting horizon of 5 days, (ii) a wave analysis and prediction component for Red Sea and Arabian Gulf, (iii) an ocean circulation and tidal analysis and prediction of both Red Sea and Arabian Gulf and (iv) an Aviation part specializing in the vertical structure of the atmosphere and extreme events that affect air transport and other operations. Specialized data sets required for on/offshore operations are provided ate regular basis. State of the art modeling components are integrated to a unique system that distributes the produced analysis and forecasts to each department. The weather and dust prediction system is SKIRON/Dust, the wave analysis and prediction system is based on WAM cycle 4 model from ECMWF, the ocean circulation model is MICOM while the tidal analysis and prediction is a development of the Ocean Physics and Modeling Group of University of Athens, incorporating the Tidal Model Driver. A nowcasting subsystem is included. An interactive system based on Google Maps gives the capability to extract and display the necessary information for any location of the Arabian Peninsula, the Red Sea and Arabian Gulf.

Implementation guidelines for road weather information systems

DOT National Transportation Integrated Search

1997-11-01

The report presents guidelines for implementing road weather information systems (RWIS). These guidelines will assist highway agency personnel with the planning, installation, and maintenance of road weather information systems for either ice or high...

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

NASA Astrophysics Data System (ADS)

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

2009-09-01

Weather has a strong impact on aviation safety and efficiency. For a better understanding of that impact, especially of thunderstorms and similar other severe hazards, we pursued a modeling approach. We used the detailed simulation software (NAVSIM) of worldwide air traffic, developed by Rokitansky [Eurocontrol, 2005] and implemented a specific weather module. NAVSIM models each aircraft with its specific performance characteristics separately along preplanned and prescribed routes. The specific weather module in its current version simulates a thunderstorm as an impenetrable 3D object, which forces an aircraft to circumvent the latter. We refer to that object in general terms as a weather object. The Cb-weather object, as a specific weather object, is a heuristic model of a real thunderstorm, with its characteristics based on actually observed satellite and precipitation radar data. It is comprised of an upper volume, mostly the anvil, and a bottom volume, the up- and downdrafts and the lower outflow area [Tafferner and Forster, 2009; Kober and Tafferner 2009; Zinner et al, 2008]. The Cb-weather object is already implemented in NAVSIM, other weather objects like icing and turbulence will follow. This combination of NAVSIM with a weather object allows a detailed investigation of situations where conflicts exist between planned flight routes and adverse weather. The first objective is to simulate the observed circum-navigation in NAVSIM. Real occurring routes will be compared with simulated ones. Once this has successfully completed, NAVSIM offers a platform to assess existing rules and develop more efficient strategies to cope with adverse weather. An overview will be given over the implementation status of weather objects within NAVSIM and first results will be presented. Cb-object data provision by A. Tafferner, C. Forster, T. Zinner, K. Kober, M. Hagen (DLR Oberpfaffenhofen) is greatly acknowledged. References: Eurocontrol, VDL Mode 2 Capacity Analysis through

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

NASA Technical Reports Server (NTRS)

Scanlon, Charles H.

1992-01-01

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

A weather-driven model of malaria transmission

PubMed Central

Hoshen, Moshe B; Morse, Andrew P

2004-01-01

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

Weather-based prediction of Plasmodium falciparum malaria in epidemic-prone regions of Ethiopia II. Weather-based prediction systems perform comparably to early detection systems in identifying times for interventions.

PubMed

Teklehaimanot, Hailay D; Schwartz, Joel; Teklehaimanot, Awash; Lipsitch, Marc

2004-11-19

Timely and accurate information about the onset of malaria epidemics is essential for effective control activities in epidemic-prone regions. Early warning methods that provide earlier alerts (usually by the use of weather variables) may permit control measures to interrupt transmission earlier in the epidemic, perhaps at the expense of some level of accuracy. Expected case numbers were modeled using a Poisson regression with lagged weather factors in a 4th-degree polynomial distributed lag model. For each week, the numbers of malaria cases were predicted using coefficients obtained using all years except that for which the prediction was being made. The effectiveness of alerts generated by the prediction system was compared against that of alerts based on observed cases. The usefulness of the prediction system was evaluated in cold and hot districts. The system predicts the overall pattern of cases well, yet underestimates the height of the largest peaks. Relative to alerts triggered by observed cases, the alerts triggered by the predicted number of cases performed slightly worse, within 5% of the detection system. The prediction-based alerts were able to prevent 10-25% more cases at a given sensitivity in cold districts than in hot ones. The prediction of malaria cases using lagged weather performed well in identifying periods of increased malaria cases. Weather-derived predictions identified epidemics with reasonable accuracy and better timeliness than early detection systems; therefore, the prediction of malarial epidemics using weather is a plausible alternative to early detection systems.

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

Treesearch

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

2008-01-01

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

INNOVATIVE URBAN WET-WEATHER FLOW MANAGEMENT SYSTEMS

EPA Science Inventory

This report describes innovative methods to improve wet weather flow (WWF) management systems, that provide drainage services at the same time as decreasing stormwater pollutant discharges, for urban developments of the 21st century. Traditionally, wet-weather collection systems...

Ensemble superparameterization versus stochastic parameterization: A comparison of model uncertainty representation in tropical weather prediction

NASA Astrophysics Data System (ADS)

Subramanian, Aneesh C.; Palmer, Tim N.

2017-06-01

Stochastic schemes to represent model uncertainty in the European Centre for Medium-Range Weather Forecasts (ECMWF) ensemble prediction system has helped improve its probabilistic forecast skill over the past decade by both improving its reliability and reducing the ensemble mean error. The largest uncertainties in the model arise from the model physics parameterizations. In the tropics, the parameterization of moist convection presents a major challenge for the accurate prediction of weather and climate. Superparameterization is a promising alternative strategy for including the effects of moist convection through explicit turbulent fluxes calculated from a cloud-resolving model (CRM) embedded within a global climate model (GCM). In this paper, we compare the impact of initial random perturbations in embedded CRMs, within the ECMWF ensemble prediction system, with stochastically perturbed physical tendency (SPPT) scheme as a way to represent model uncertainty in medium-range tropical weather forecasts. We especially focus on forecasts of tropical convection and dynamics during MJO events in October-November 2011. These are well-studied events for MJO dynamics as they were also heavily observed during the DYNAMO field campaign. We show that a multiscale ensemble modeling approach helps improve forecasts of certain aspects of tropical convection during the MJO events, while it also tends to deteriorate certain large-scale dynamic fields with respect to stochastically perturbed physical tendencies approach that is used operationally at ECMWF.