Recent weather extremes and impact agricultural production and vector-borne disease patterns

USDA-ARS?s Scientific Manuscript database

We document significant worldwide weather anomalies that affected agriculture and vector-borne disease outbreaks during the 2010-2012 period. We utilized 2000-2012 vegetation index and land surface temperature data from NASA’s satellite-based Moderate Resolution Imaging Spectroradiometer (MODIS) to ...

CCMC: bringing space weather awareness to the next generation

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

High Quality Data for Grid Integration Studies

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

Clifton, Andrew; Draxl, Caroline; Sengupta, Manajit

As variable renewable power penetration levels increase in power systems worldwide, renewable integration studies are crucial to ensure continued economic and reliable operation of the power grid. The existing electric grid infrastructure in the US in particular poses significant limitations on wind power expansion. In this presentation we will shed light on requirements for grid integration studies as far as wind and solar energy are concerned. Because wind and solar plants are strongly impacted by weather, high-resolution and high-quality weather data are required to drive power system simulations. Future data sets will have to push limits of numerical weather predictionmore » to yield these high-resolution data sets, and wind data will have to be time-synchronized with solar data. Current wind and solar integration data sets are presented. The Wind Integration National Dataset (WIND) Toolkit is the largest and most complete grid integration data set publicly available to date. A meteorological data set, wind power production time series, and simulated forecasts created using the Weather Research and Forecasting Model run on a 2-km grid over the continental United States at a 5-min resolution is now publicly available for more than 126,000 land-based and offshore wind power production sites. The National Solar Radiation Database (NSRDB) is a similar high temporal- and spatial resolution database of 18 years of solar resource data for North America and India. The need for high-resolution weather data pushes modeling towards finer scales and closer synchronization. We also present how we anticipate such datasets developing in the future, their benefits, and the challenges with using and disseminating such large amounts of data.« less

Toward Robust Climate Baselining: Objective Assessment of Climate Change Using Widely Distributed Miniaturized Sensors for Accurate World-Wide Geophysical Measurements

DOE R&D Accomplishments Database

Teller, E.; Leith, C.; Canavan, G.; Marion, J.; Wood, L.

2001-11-13

A gap-free, world-wide, ocean-, atmosphere-, and land surface-spanning geophysical data-set of three decades time-duration containing the full set of geophysical parameters characterizing global weather is the scientific perquisite for defining the climate; the generally-accepted definition in the meteorological community is that climate is the 30-year running-average of weather. Until such a tridecadal climate baseline exists, climate change discussions inevitably will have a semi-speculative, vs. a purely scientific, character, as the baseline against which changes are referenced will at least somewhat uncertain.

Community Coordinated Modeling Center: A Powerful Resource in Space Science and Space Weather Education

NASA Astrophysics Data System (ADS)

Chulaki, A.; Kuznetsova, M. M.; Rastaetter, L.; MacNeice, P. J.; Shim, J. S.; Pulkkinen, A. A.; Taktakishvili, A.; Mays, M. L.; Mendoza, A. M. M.; Zheng, Y.; Mullinix, R.; Collado-Vega, Y. M.; Maddox, M. M.; Pembroke, A. D.; Wiegand, C.

2015-12-01

Community Coordinated Modeling Center (CCMC) is a NASA affiliated interagency partnership with the primary goal of aiding the transition of modern space science models into space weather forecasting while supporting space science research. Additionally, over the past ten years it has established itself as a global space science education resource supporting undergraduate and graduate education and research, and spreading space weather awareness worldwide. A unique combination of assets, capabilities and close ties to the scientific and educational communities enable this small group to serve as a hub for raising generations of young space scientists and engineers. CCMC resources are publicly available online, providing unprecedented global access to the largest collection of modern space science models (developed by the international research community). CCMC has revolutionized the way simulations are utilized in classrooms settings, student projects, and scientific labs and serves hundreds of educators, students and researchers every year. Another major CCMC asset is an expert space weather prototyping team primarily serving NASA's interplanetary space weather needs. Capitalizing on its unrivaled capabilities and experiences, the team provides in-depth space weather training to students and professionals worldwide, and offers an amazing opportunity for undergraduates to engage in real-time space weather monitoring, analysis, forecasting and research. In-house development of state-of-the-art space weather tools and applications provides exciting opportunities to students majoring in computer science and computer engineering fields to intern with the software engineers at the CCMC while also learning about the space weather from the NASA scientists.

Worldwide Marine Weather Broadcasts.

ERIC Educational Resources Information Center

Department of the Navy, Washington, DC.

This publication is a source of marine weather broadcast information in all areas of the world where such service is provided. This publication was designed for the use of U.S. naval and merchant ships. Sections 1 through 4 contain details of radio telegraph, radio telephone, radio facsimile, and radio teleprinter transmissions, respectively. The…

Strategies for Near Real Time Estimates of Precipitable Water Vapor from GPS Ground Receivers

NASA Technical Reports Server (NTRS)

Y., Bar-Sever; Runge, T.; Kroger, P.

1995-01-01

GPS-based estimates of precipitable water vapor (PWV) may be useful in numerical weather models to improve short-term weather predictions. To be effective in numerical weather prediction models, GPS PWV estimates must be produced with sufficient accuracy in near real time. Several estimation strategies for the near real time processing of GPS data are investigated.

Using 3-D Numerical Weather Data in Piloted Simulations

NASA Technical Reports Server (NTRS)

Daniels, Taumi S.

2016-01-01

This report describes the process of acquiring and using 3-D numerical model weather data sets in NASA Langley's Research Flight Deck (RFD). A set of software tools implement the process and can be used for other purposes as well. Given time and location information of a weather phenomenon of interest, the user can download associated numerical weather model data. These data are created by the National Oceanic and Atmospheric Administration (NOAA) High Resolution Rapid Refresh (HRRR) model, and are then processed using a set of Mathworks' Matlab(TradeMark) scripts to create the usable 3-D weather data sets. Each data set includes radar re ectivity, water vapor, component winds, temperature, supercooled liquid water, turbulence, pressure, altitude, land elevation, relative humidity, and water phases. An open-source data processing program, wgrib2, is available from NOAA online, and is used along with Matlab scripts. These scripts are described with sucient detail to make future modi cations. These software tools have been used to generate 3-D weather data for various RFD experiments.

Space Weather Forecasting at the Joint Space Operations Center (JSpOC)

NASA Astrophysics Data System (ADS)

Nava, O.

2012-12-01

The Joint Space Operations Center (JSpOC) at Vandenberg Air Force Base is the command and control focal point for the operational employment of worldwide joint space forces. The JSpOC focuses on planning and executing US Strategic Command's Joint Functional Component Command for Space (JFCC SPACE) mission. Through the JSpOC, the Weather Specialty Team (WST) monitors space and terrestrial weather effects, plans and assesses weather impacts on military operations, and provides reach-back support for deployed theater solar and terrestrial needs. This presentation will detail how space weather affects the JSpOC mission set and how the scientific community can enhance the WST's capabilities and effectiveness.

A Comparison of Synoptic Classification Methods for Application to Wind Power Prediction

NASA Astrophysics Data System (ADS)

Fowler, P.; Basu, S.

2008-12-01

Wind energy is a highly variable resource. To make it competitive with other sources of energy for integration on the power grid, at the very least, a day-ahead forecast of power output must be available. In many grid operations worldwide, next-day power output is scheduled in 30 minute intervals and grid management routinely occurs at real time. Maintenance and repairs require costly time to complete and must be scheduled along with normal operations. Revenue is dependent on the reliability of the entire system. In other words, there is financial and managerial benefit to short-term prediction of wind power. One approach to short-term forecasting is to combine a data centric method such as an artificial neural network with a physically based approach like numerical weather prediction (NWP). The key is in associating high-dimensional NWP model output with the most appropriately trained neural network. Because neural networks perform the best in the situations they are designed for, one can hypothesize that if one can identify similar recurring states in historical weather data, this data can be used to train multiple custom designed neural networks to be used when called upon by numerical prediction. Identifying similar recurring states may offer insight to how a neural network forecast can be improved, but amassing the knowledge and utilizing it efficiently in the time required for power prediction would be difficult for a human to master, thus showing the advantage of classification. Classification methods are important tools for short-term forecasting because they can be unsupervised, objective, and computationally quick. They primarily involve categorizing data sets in to dominant weather classes, but there are numerous ways to define a class and a great variety in interpretation of the results. In the present study a collection of classification methods are used on a sampling of atmospheric variables from the North American Regional Reanalysis data set. The results will be discussed in relation to their use for short-term wind power forecasting by neural networks.

Fire weather technology for fire agrometeorology operations

Treesearch

Francis Fujioka

2008-01-01

Even as the magnitude of wildfire problems increases globally, United Nations agencies are acting to mitigate the risk of wildfire disasters to members. Fire management organizations worldwide may vary considerably in operational scope, depending on the number and type of resources an organization manages. In any case, good fire weather information is vital. This paper...

Graphical tools for TV weather presentation

NASA Astrophysics Data System (ADS)

Najman, M.

2010-09-01

Contemporary meteorology and its media presentation faces in my opinion following key tasks: - Delivering the meteorological information to the end user/spectator in understandable and modern fashion, which follows industry standard of video output (HD, 16:9) - Besides weather icons show also the outputs of numerical weather prediction models, climatological data, satellite and radar images, observed weather as actual as possible. - Does not compromise the accuracy of presented data. - Ability to prepare and adjust the weather show according to actual synoptic situtation. - Ability to refocus and completely adjust the weather show to actual extreme weather events. - Ground map resolution weather data presentation need to be at least 20 m/pixel to be able to follow the numerical weather prediction model resolution. - Ability to switch between different numerical weather prediction models each day, each show or even in the middle of one weather show. - The graphical weather software need to be flexible and fast. The graphical changes nee to be implementable and airable within minutes before the show or even live. These tasks are so demanding and the usual original approach of custom graphics could not deal with it. It was not able to change the show every day, the shows were static and identical day after day. To change the content of the weather show daily was costly and most of the time impossible with the usual approach. The development in this area is fast though and there are several different options for weather predicting organisations such as national meteorological offices and private meteorological companies to solve this problem. What are the ways to solve it? What are the limitations and advantages of contemporary graphical tools for meteorologists? All these questions will be answered.

The Worldwide Interplanetary Scintillation (IPS) Stations (WIPSS) Network in support of Space-Weather Science and Forecasting

NASA Astrophysics Data System (ADS)

Bisi, M. M.; Gonzalez-Esparza, A.; Jackson, B. V.; Aguilar-Rodriguez, E.; Tokumaru, M.; Chashei, I. V.; Tyul'bashev, S. A.; Manoharan, P. K.; Fallows, R. A.; Chang, O.; Mejia-Ambriz, J. C.; Yu, H. S.; Fujiki, K.; Shishov, V.

2016-12-01

The phenomenon of space weather - analogous to terrestrial weather which describes the changing low-altitude atmospheric conditions on Earth - is essentially a description of the changes in the plasma environment at and near the Earth. Some key parameters for space-weather purposes driving space weather at the Earth include velocity, density, magnetic field, high-energy particles, and radiation coming into and within the near-Earth space environment. Interplanetary scintillation (IPS) can be used to provide a global measure of velocity and density as well as indications of changes in the plasma and magnetic-field rotations along each observational line of sight. If the observations are formally inverted into a three-dimensional (3-D) tomographic reconstruction (such as using the University of California, San Diego - UCSD - kinematic model and reconstruction technique), then source-surface magnetic fields can also be propagated out to the Earth (and beyond) as well as in-situ data also being incorporated into the reconstruction. Currently, this has been done using IPS data only from the Institute for Space-Earth Environmental (ISEE) and has been scientifically since the 1990s, and in a forecast mode since around 2000. There is now a defined IPS Common Data Format (IPSCDFv1.0) which is being implemented by the majority of the IPS community (this also feeds into the tomography). The Worldwide IPS Stations (WIPSS) Network aims to bring together, using IPSCDFv1.0, the worldwide real-time capable IPS observatories with well-developed and tested analyses techniques being unified across all single-site systems (such as MEXART, Pushchino, and Ooty) and cross-calibrated to the multi-site ISEE system (as well as learning from the scientific-based systems such as EISCAT, LOFAR, and the MWA), into the UCSD 3-D tomography to improve the accuracy, spatial and temporal data coverage, and both the spatial and temporal resolution for improved space-weather science and forecast capabilities.

The Worldwide Interplanetary Scintillation (IPS) Stations (WIPSS) Network in support of Space-Weather Science and Forecasting

NASA Astrophysics Data System (ADS)

Bisi, Mario Mark; Americo Gonzalez-Esparza, J.; Jackson, Bernard; Aguilar-Rodriguez, Ernesto; Tokumaru, Munetoshi; Chashei, Igor; Tyul'bashev, Sergey; Manoharan, Periasamy; Fallows, Richard; Chang, Oyuki; Yu, Hsiu-Shan; Fujiki, Ken'ichi; Shishov, Vladimir; Barnes, David

2017-04-01

The phenomenon of space weather - analogous to terrestrial weather which describes the changing low-altitude atmospheric conditions on Earth - is essentially a description of the changes in the plasma environment at and near the Earth. Some key parameters for space-weather purposes driving space weather at the Earth include velocity, density, magnetic field, high-energy particles, and radiation coming into and within the near-Earth space environment. Interplanetary scintillation (IPS) can be used to provide a global measure of velocity and density as well as indications of changes in the plasma and magnetic-field rotations along each observational line of sight. If the observations are formally inverted into a three-dimensional (3-D) tomographic reconstruction (such as using the University of California, San Diego - UCSD - kinematic model and reconstruction technique), then source-surface magnetic fields can also be propagated out to the Earth (and beyond) as well as in-situ data also being incorporated into the reconstruction. Currently, this has been done using IPS data only from the Institute for Space-Earth Environmental (ISEE) and has been scientifically since the 1990s, and in a forecast mode since around 2000. There is now a defined (and updated) IPS Common Data Format (IPSCDFv1.1) which is being implemented by the majority of the IPS community (this also feeds into the UCSD tomography). The Worldwide IPS Stations (WIPSS) Network aims to bring together, using IPSCDFv1.1, the worldwide real-time capable IPS observatories with well-developed and tested analyses techniques being unified across all single-site systems (such as MEXART, Pushchino, and Ooty) and cross-calibrated to the multi-site ISEE system (as well as learning from the scientific-based systems such as EISCAT, LOFAR, and the MWA), into the UCSD 3-D tomography to improve the accuracy, spatial and temporal data coverage, and both the spatial and temporal resolution for improved space-weather science and forecast capabilities.

Protection and consolidation of stone heritage by self-inoculation with indigenous carbonatogenic bacterial communities.

PubMed

Jroundi, Fadwa; Schiro, Mara; Ruiz-Agudo, Encarnación; Elert, Kerstin; Martín-Sánchez, Inés; González-Muñoz, María Teresa; Rodriguez-Navarro, Carlos

2017-08-17

Enhanced salt weathering resulting from global warming and increasing environmental pollution is endangering the survival of stone monuments and artworks. To mitigate the effects of these deleterious processes, numerous conservation treatments have been applied that, however, show limited efficacy. Here we present a novel, environmentally friendly, bacterial self-inoculation approach for the conservation of stone, based on the isolation of an indigenous community of carbonatogenic bacteria from salt damaged stone, followed by their culture and re-application back onto the same stone. This method results in an effective consolidation and protection due to the formation of an abundant and exceptionally strong hybrid cement consisting of nanostructured bacterial CaCO 3 and bacterially derived organics, and the passivating effect of bacterial exopolymeric substances (EPS) covering the substrate. The fact that the isolated and identified bacterial community is common to many stone artworks may enable worldwide application of this novel conservation methodology.Salt weathering enhanced by global warming and environmental pollution is increasingly threatening stone monuments and artworks. Here, the authors present a bacterial self-inoculation approach with indigenous carbonatogenic bacteria and find that this technique consolidates and protects salt damaged stone.

FireMap: A Web Tool for Dynamic Data-Driven Predictive Wildfire Modeling Powered by the WIFIRE Cyberinfrastructure

NASA Astrophysics Data System (ADS)

Block, J.; Crawl, D.; Artes, T.; Cowart, C.; de Callafon, R.; DeFanti, T.; Graham, J.; Smarr, L.; Srivas, T.; Altintas, I.

2016-12-01

The NSF-funded WIFIRE project has designed a web-based wildfire modeling simulation and visualization tool called FireMap. The tool executes FARSITE to model fire propagation using dynamic weather and fire data, configuration settings provided by the user, and static topography and fuel datasets already built-in. Using GIS capabilities combined with scalable big data integration and processing, FireMap enables simple execution of the model with options for running ensembles by taking the information uncertainty into account. The results are easily viewable, sharable, repeatable, and can be animated as a time series. From these capabilities, users can model real-time fire behavior, analyze what-if scenarios, and keep a history of model runs over time for sharing with collaborators. Firemap runs FARSITE with national and local sensor networks for real-time weather data ingestion and High-Resolution Rapid Refresh (HRRR) weather for forecasted weather. The HRRR is a NOAA/NCEP operational weather prediction system comprised of a numerical forecast model and an analysis/assimilation system to initialize the model. It is run with a horizontal resolution of 3 km, has 50 vertical levels, and has a temporal resolution of 15 minutes. The HRRR requires an Environmental Data Exchange (EDEX) server to receive the feed and generate secondary products out of it for the modeling. UCSD's EDEX server, funded by NSF, makes high-resolution weather data available to researchers worldwide and enables visualization of weather systems and weather events lasting months or even years. The high-speed server aggregates weather data from the University Consortium for Atmospheric Research by way of a subscription service from the Consortium called the Internet Data Distribution system. These features are part of WIFIRE's long term goals to build an end-to-end cyberinfrastructure for real-time and data-driven simulation, prediction and visualization of wildfire behavior. Although Firemap is a research product of WIFIRE, developed in collaboration with a number of fire departments, the tool is operational in pilot form for providing big data-driven predictive fire spread modeling. Most recently, FireMap was used for situational awareness in the July 2016 Sand Fire by LA City and LA County Fire Departments.

(abstract) Application of the GPS Worldwide Network in the Study of Global Ionospheric Storms

NASA Technical Reports Server (NTRS)

Ho, C. M.; Mannucci, A. J.; Lindqwister, U. J.; Pi, X.; Sparks, L. C.; Rao, A. M.; Wilsion, B. D.; Yuan, D. N.; Reyes, M.

1997-01-01

Ionospheric storm dynamics as a response to the geomagnetic storms is a very complicated global process involving many different mechanisms. Studying ionospheric storms will help us to understand the energy coupling process between the Sun and Earth and possibly also to effectively forecast space weather changes. Such a study requires a worldwide monitoring system. The worldwide GPS network, for the first time, makes near real-time global ionospheric TEC measurements a possibility.

Utilization of satellite data and regional scale numerical models in short range weather forecasting

NASA Technical Reports Server (NTRS)

Kreitzberg, C. W.

1985-01-01

Overwhelming evidence was developed in a number of studies of satellite data impact on numerical weather prediction that it is unrealistic to expect satellite temperature soundings to improve detailed regional numerical weather prediction. It is likely that satellite data over the United States would substantially impact mesoscale dynamical predictions if the effort were made to develop a composite moisture analysis system. The horizontal variability of moisture, most clearly depicited in images from satellite water vapor channels, would not be determined from conventional rawinsondes even if that network were increased by a doubling of both the number of sites and the time frequency.

On the potential use of radar-derived information in operational numerical weather prediction

NASA Technical Reports Server (NTRS)

Mcpherson, R. D.

1986-01-01

Estimates of requirements likely to be levied on a new observing system for mesoscale meteonology are given. Potential observing systems for mesoscale numerical weather prediction are discussed. Thermodynamic profiler radiometers, infrared radiometer atmospheric sounders, Doppler radar wind profilers and surveillance radar, and moisture profilers are among the instruments described.

Proposed Use of the NASA Ames Nebula Cloud Computing Platform for Numerical Weather Prediction and the Distribution of High Resolution Satellite Imagery

NASA Technical Reports Server (NTRS)

Limaye, Ashutosh S.; Molthan, Andrew L.; Srikishen, Jayanthi

2010-01-01

The development of the Nebula Cloud Computing Platform at NASA Ames Research Center provides an open-source solution for the deployment of scalable computing and storage capabilities relevant to the execution of real-time weather forecasts and the distribution of high resolution satellite data to the operational weather community. Two projects at Marshall Space Flight Center may benefit from use of the Nebula system. The NASA Short-term Prediction Research and Transition (SPoRT) Center facilitates the use of unique NASA satellite data and research capabilities in the operational weather community by providing datasets relevant to numerical weather prediction, and satellite data sets useful in weather analysis. SERVIR provides satellite data products for decision support, emphasizing environmental threats such as wildfires, floods, landslides, and other hazards, with interests in numerical weather prediction in support of disaster response. The Weather Research and Forecast (WRF) model Environmental Modeling System (WRF-EMS) has been configured for Nebula cloud computing use via the creation of a disk image and deployment of repeated instances. Given the available infrastructure within Nebula and the "infrastructure as a service" concept, the system appears well-suited for the rapid deployment of additional forecast models over different domains, in response to real-time research applications or disaster response. Future investigations into Nebula capabilities will focus on the development of a web mapping server and load balancing configuration to support the distribution of high resolution satellite data sets to users within the National Weather Service and international partners of SERVIR.

Degradation Behavior and Accelerated Weathering of Composite Boards Produced from Waste Tetra Pak® Packaging Materials

Treesearch

Nural Yilgor; Coskun Kose; Evren Terzi; Aysel Kanturk Figen; Rebecca Ibach; S. Nami Kartal; Sabriye Piskin

2014-01-01

Manufacturing panels from Tetra Pak® (TP) packaging material might be an alternative to conventional wood-based panels. This study evaluated some chemical and physical properties as well as biological, weathering, and fire performance of panels with and without zinc borate (ZnB) by using shredded TP packaging cartons. Such packaging material, a worldwide well-known...

Using GPS RO L1 data for calibration of the atmospheric path delay model for data reduction of the satellite altimetery observations.

NASA Astrophysics Data System (ADS)

Petrov, L.

2017-12-01

Processing satellite altimetry data requires the computation of path delayin the neutral atmosphere that is used for correcting ranges. The path delayis computed using numerical weather models and the accuracy of its computationdepends on the accuracy of numerical weather models. Accuracy of numerical modelsof numerical weather models over Antarctica and Greenland where there is a very sparse network of ground stations, is not well known. I used the dataset of GPS RO L1 data, computed predicted path delay for ROobservations using the numerical whether model GEOS-FPIT, formed the differences with observed path delay and used these differences for computationof the corrections to the a priori refractivity profile. These profiles wereused for computing corrections to the a priori zenith path delay. The systematic patter of these corrections are used for de-biasing of the the satellite altimetry results and for characterization of the systematic errorscaused by mismodeling atmosphere.

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

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

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

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

Application of Raytracing Through the High Resolution Numerical Weather Model HIRLAM for the Analysis of European VLBI

NASA Technical Reports Server (NTRS)

Garcia-Espada, Susana; Haas, Rudiger; Colomer, Francisco

2010-01-01

An important limitation for the precision in the results obtained by space geodetic techniques like VLBI and GPS are tropospheric delays caused by the neutral atmosphere, see e.g. [1]. In recent years numerical weather models (NWM) have been applied to improve mapping functions which are used for tropospheric delay modeling in VLBI and GPS data analyses. In this manuscript we use raytracing to calculate slant delays and apply these to the analysis of Europe VLBI data. The raytracing is performed through the limited area numerical weather prediction (NWP) model HIRLAM. The advantages of this model are high spatial (0.2 deg. x 0.2 deg.) and high temporal resolution (in prediction mode three hours).

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

NASA Astrophysics Data System (ADS)

Wu, Yanling

2018-05-01

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

The role of COST Actions in unifying the European ionospheric community in the transition between the two millennia

NASA Astrophysics Data System (ADS)

Zolesi, Bruno; Cander, Ljiljana R.

2018-05-01

This paper consists of a review of the important contributions of four COST (European Co-operation in Science and Technology) Actions in the period 1991-2009 to terrestrial ionospheric research, with applications in modern communication and navigation systems. Within this context, new ionospheric studies were initiated, leading to the development of a number of models, algorithms for prediction, forecasting, and real-time specification, as well as numerical programs. These were successfully implemented in different collaborative projects within EU instruments, promoting co-operation between scientists and researchers across Europe. A further outcome was to bring together more than a hundred researchers from around 40 scientific institutions, agencies, and academia in about 25 countries worldwide. They collaborated with enthusiasm in research, as briefly described in this paper, forming a lively ionospheric community and presenting a strong intellectual response to the rapidly growing contemporary challenge of space weather research.

Real-time Retrieving Atmospheric Parameters from Multi-GNSS Constellations

NASA Astrophysics Data System (ADS)

Li, X.; Zus, F.; Lu, C.; Dick, G.; Ge, M.; Wickert, J.; Schuh, H.

2016-12-01

The multi-constellation GNSS (e.g. GPS, GLONASS, Galileo, and BeiDou) bring great opportunities and challenges for real-time retrieval of atmospheric parameters for supporting numerical weather prediction (NWP) nowcasting or severe weather event monitoring. In this study, the observations from different GNSS are combined together for atmospheric parameter retrieving based on the real-time precise point positioning technique. The atmospheric parameters retrieved from multi-GNSS observations, including zenith total delay (ZTD), integrated water vapor (IWV), horizontal gradient (especially high-resolution gradient estimates) and slant total delay (STD), are carefully analyzed and evaluated by using the VLBI, radiosonde, water vapor radiometer and numerical weather model to independently validate the performance of individual GNSS and also demonstrate the benefits of multi-constellation GNSS for real-time atmospheric monitoring. Numerous results show that the multi-GNSS processing can provide real-time atmospheric products with higher accuracy, stronger reliability and better distribution, which would be beneficial for atmospheric sounding systems, especially for nowcasting of extreme weather.

Investigating Anomalies in the Output Generated by the Weather Research and Forecasting (WRF) Model

NASA Astrophysics Data System (ADS)

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

2015-04-01

The Weather Research and Forecasting (WRF) model is an advanced mesoscale numerical weather prediction (NWP) model comprised of two numerical cores, the Numerical Mesoscale Modeling (NMM) core, and the Advanced Research WRF (ARW) core. An investigation was done to determine the source of erroneous output generated by the NMM core. In particular were the appearance of zero values at regularly spaced grid cells in output fields and the NMM core's evident (mis)use of static geographic information at a resolution lower than the nesting level for which the core is performing computation. A brief discussion of the high-level modular architecture of the model is presented as well as methods utilized to identify the cause of these problems. Presented here are the initial results from a research grant, ``A Pilot Project to Investigate Wake Vortex Patterns and Weather Patterns at the Atlantic City Airport by the Richard Stockton College of NJ and the FAA''.

Session on techniques and resources for storm-scale numerical weather prediction

NASA Technical Reports Server (NTRS)

Droegemeier, Kelvin

1993-01-01

The session on techniques and resources for storm-scale numerical weather prediction are reviewed. The recommendations of this group are broken down into three area: modeling and prediction, data requirements in support of modeling and prediction, and data management. The current status, modeling and technological recommendations, data requirements in support of modeling and prediction, and data management are addressed.

Historical winter weather assessment for snow fence design using a numerical weather model.

DOT National Transportation Integrated Search

2017-03-30

Noriaki Ohara, Ph.D., Assistant Professor (0000-0002-7829-0779) : Snow fence is an effective hazard mitigation measure for the low visibility and low friction of the road surface under : winter weather condition. Prevailing wind directions and snow p...

Comparison of Weather Shows in Eastern Europe

NASA Astrophysics Data System (ADS)

Najman, M.

2009-09-01

Comparison of Weather Shows in Eastern Europe Television weather shows in Eastern Europe have in most cases in the high graphical standard. There is though a wast difference in duration and information content in the weather shows. There are few signs and regularities by which we can see the character of the weather show. The main differences are mainly caused by the income structure of the TV station. Either it is a fully privately funded TV relying on the TV commercials income. Or it is a public service TV station funded mainly by the national budget or fixed fee structure/tax. There are wast differences in duration and even a graphical presentation of the weather. Next important aspect is a supplier of the weather information and /or the processor. Shortly we can say, that when the TV show is produced by the national met office, the TV show consists of more scientific terms, synoptic maps, satellite imagery, etc. If the supplier is the private meteorological company, the weather show is more user-friendly, laical with less scientific terms. We are experiencing a massive shift in public weather knowledge and demand for information. In the past, weather shows consisted only of maps with weather icons. In todaýs world, even the laic weather shows consist partly of numerical weather model outputs - they are of course designed to be understandable and graphically attractive. Outputs of the numerical weather models used to be only a part of daily life of a professional meteorologist, today they are common part of life of regular people. Video samples are a part of this presentation.

Transition of R&D into Operations at Fleet Numerical Meteorology and Oceanography Center

NASA Astrophysics Data System (ADS)

Clancy, R. M.

2006-12-01

The U.S. Navy's Fleet Numerical Meteorology and Oceanography Center (FNMOC) plays a significant role in the National capability for operational weather and ocean prediction through its operation of sophisticated global and regional meteorological and oceanographic models, extending from the top of the atmosphere to the bottom of the ocean. FNMOC uniquely satisfies the military's requirement for a global operational weather prediction capability based on software certified to DoD Information Assurance standards and operated in a secure classified computer environment protected from outside intrusion by DoD certified firewalls. FNMOC operates around-the-clock, 365 days per year and distributes products to military and civilian users around the world, both ashore and afloat, through a variety of means. FNMOC's customers include all branches of the Department of Defense, other government organizations such as the National Weather Service, private companies, a number of colleges and universities, and the general public. FNMOC employs three primary models, the Navy Operational Global Atmospheric Prediction System (NOGAPS), the Coupled Ocean/Atmosphere Mesoscale Prediction System (COAMPS), and the WaveWatch III model (WW3), along with a number of specialized models and related applications. NOGAPS is a global weather model, driving nearly all other FNMOC models and applications in some fashion. COAMPS is a high- resolution regional model that has proved to be particularly valuable for forecasting weather and ocean conditions in highly complex coastal areas. WW3 is a state-of-the-art ocean wave model that is employed both globally and regionally in support of a wide variety of naval operations. Other models support and supplement the main models with predictions of ocean thermal structure, ocean currents, sea-ice characteristics, and other data. Fleet Numerical operates at the leading edge of science and technology, and benefits greatly from collocation with its supporting R&D activity, the Marine Meteorology Division of the Naval Research Laboratory (NRL Code 7500). NRL Code 7500 is a world-class research organization, with focus on weather-related support for the warfighter. Fleet Numerical and NRL Code 7500 share space, data, software and computer systems, and together represent one of the largest concentrations of weather-related intellectual capital in the nation. As documented, for example, by the Board on Atmospheric Sciences and Climate (BASC) of the National Research Council, investment in R&D is crucial for maintaining state-of-the-art operational Numerical Weather Prediction (NWP) capabilities (see BASC, 1998). And collocation and close cooperation between research and operations, such as exists between NRL Code 7500 and Fleet Numerical, is the optimum arrangement for transitioning R&D quickly and cost-effectively into new and improved operational weather prediction capabilities.

Simulating infectious disease risk based on climatic drivers: from numerical weather prediction to long term climate change scenario

NASA Astrophysics Data System (ADS)

Caminade, C.; Ndione, J. A.; Diallo, M.; MacLeod, D.; Faye, O.; Ba, Y.; Dia, I.; Medlock, J. M.; Leach, S.; McIntyre, K. M.; Baylis, M.; Morse, A. P.

2012-04-01

Climate variability is an important component in determining the incidence of a number of diseases with significant health and socioeconomic impacts. In particular, vector born diseases are the most likely to be affected by climate; directly via the development rates and survival of both the pathogen and the vector, and indirectly through changes in the surrounding environmental conditions. Disease risk models of various complexities using different streams of climate forecasts as inputs have been developed within the QWeCI EU and ENHanCE ERA-NET project frameworks. This work will present two application examples, one for Africa and one for Europe. First, we focus on Rift Valley fever over sub-Saharan Africa, a zoonosis that affects domestic animals and humans by causing an acute fever. We show that the Rift Valley fever outbreak that occurred in late 2010 in the northern Sahelian region of Mauritania might have been anticipated ten days in advance using the GFS numerical weather prediction system. Then, an ensemble of regional climate projections is employed to model the climatic suitability of the Asian tiger mosquito for the future over Europe. The Asian tiger mosquito is an invasive species originally from Asia which is able to transmit West Nile and Chikungunya Fever among others. This species has spread worldwide during the last decades, mainly through the shipments of goods from Asia. Different disease models are employed and inter-compared to achieve such a task. Results show that the climatic conditions over southern England, central Western Europe and the Balkans might become more suitable for the mosquito (including the proviso that the mosquito has already been introduced) to establish itself in the future.

The Future of Operational Space Weather Observations

NASA Astrophysics Data System (ADS)

Berger, T. E.

2015-12-01

We review the current state of operational space weather observations, the requirements for new or evolved space weather forecasting capablities, and the relevant sections of the new National strategy for space weather developed by the Space Weather Operations, Research, and Mitigation (SWORM) Task Force chartered by the Office of Science and Technology Policy of the White House. Based on this foundation, we discuss future space missions such as the NOAA space weather mission to the L1 Lagrangian point planned for the 2021 time frame and its synergy with an L5 mission planned for the same period; the space weather capabilities of the upcoming GOES-R mission, as well as GOES-Next possiblities; and the upcoming COSMIC-2 mission for ionospheric observations. We also discuss the needs for ground-based operational networks to supply mission critical and/or backup space weather observations including the NSF GONG solar optical observing network, the USAF SEON solar radio observing network, the USGS real-time magnetometer network, the USCG CORS network of GPS receivers, and the possibility of operationalizing the world-wide network of neutron monitors for real-time alerts of ground-level radiation events.

Community Coordinated Modeling Center (CCMC): Using innovative tools and services to support worldwide space weather scientific communities and networks

NASA Astrophysics Data System (ADS)

Mendoza, A. M.; Bakshi, S.; Berrios, D.; Chulaki, A.; Evans, R. M.; Kuznetsova, M. M.; Lee, H.; MacNeice, P. J.; Maddox, M. M.; Mays, M. L.; Mullinix, R. E.; Ngwira, C. M.; Patel, K.; Pulkkinen, A.; Rastaetter, L.; Shim, J.; Taktakishvili, A.; Zheng, Y.

2012-12-01

Community Coordinated Modeling Center (CCMC) was established to enhance basic solar terrestrial research and to aid in the development of models for specifying and forecasting conditions in the space environment. In achieving this goal, CCMC has developed and provides a set of innovative tools varying from: Integrated Space Weather Analysis (iSWA) web -based dissemination system for space weather information, Runs-On-Request System providing access to unique collection of state-of-the-art solar and space physics models (unmatched anywhere in the world), Advanced Online Visualization and Analysis tools for more accurate interpretation of model results, Standard Data formats for Simulation Data downloads, and recently Mobile apps (iPhone/Android) to view space weather data anywhere to the scientific community. The number of runs requested and the number of resulting scientific publications and presentations from the research community has not only been an indication of the broad scientific usage of the CCMC and effective participation by space scientists and researchers, but also guarantees active collaboration and coordination amongst the space weather research community. Arising from the course of CCMC activities, CCMC also supports community-wide model validation challenges and research focus group projects for a broad range of programs such as the multi-agency National Space Weather Program, NSF's CEDAR (Coupling, Energetics and Dynamics of Atmospheric Regions), GEM (Geospace Environment Modeling) and Shine (Solar Heliospheric and INterplanetary Environment) programs. In addition to performing research and model development, CCMC also supports space science education by hosting summer students through local universities; through the provision of simulations in support of classroom programs such as Heliophysics Summer School (with student research contest) and CCMC Workshops; training next generation of junior scientists in space weather forecasting; and educating the general public about the importance and impacts of space weather effects. Although CCMC is organizationally comprised of United States federal agencies, CCMC services are open to members of the international science community and encourages interagency and international collaboration. In this poster, we provide an overview of using Community Coordinated Modeling Center (CCMC) tools and services to support worldwide space weather scientific communities and networks.;

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...

Weather models as virtual sensors to data-driven rainfall predictions in urban watersheds

NASA Astrophysics Data System (ADS)

Cozzi, Lorenzo; Galelli, Stefano; Pascal, Samuel Jolivet De Marc; Castelletti, Andrea

2013-04-01

Weather and climate predictions are a key element of urban hydrology where they are used to inform water management and assist in flood warning delivering. Indeed, the modelling of the very fast dynamics of urbanized catchments can be substantially improved by the use of weather/rainfall predictions. For example, in Singapore Marina Reservoir catchment runoff processes have a very short time of concentration (roughly one hour) and observational data are thus nearly useless for runoff predictions and weather prediction are required. Unfortunately, radar nowcasting methods do not allow to carrying out long - term weather predictions, whereas numerical models are limited by their coarse spatial scale. Moreover, numerical models are usually poorly reliable because of the fast motion and limited spatial extension of rainfall events. In this study we investigate the combined use of data-driven modelling techniques and weather variables observed/simulated with a numerical model as a way to improve rainfall prediction accuracy and lead time in the Singapore metropolitan area. To explore the feasibility of the approach, we use a Weather Research and Forecast (WRF) model as a virtual sensor network for the input variables (the states of the WRF model) to a machine learning rainfall prediction model. More precisely, we combine an input variable selection method and a non-parametric tree-based model to characterize the empirical relation between the rainfall measured at the catchment level and all possible weather input variables provided by WRF model. We explore different lead time to evaluate the model reliability for different long - term predictions, as well as different time lags to see how past information could improve results. Results show that the proposed approach allow a significant improvement of the prediction accuracy of the WRF model on the Singapore urban area.

Supporting smarter, healthier and greener societies: the dawn of operational environmental information services Some examples from the Copernicus Atmosphere Monitoring Service (CAMS) programme in Europe

NASA Astrophysics Data System (ADS)

Peuch, V. H.

2016-12-01

Operational environmental services are a reality today, as exemplified by the Copernicus Atmospheric Monitoring Service in Europe. Air quality forecasts, information on the long-range transport of dust or of fire plumes or on greenhouse gas fluxes have become reliable enough to be considered by decision makers and to be communicated broadly -making our societies more informed about the changing environment and about the direct link between human activities, atmospheric composition, weather and climate. Many aspects of the value-adding information chains that have been built over the years share commonalities with Numerical Weather Prediction: global and regional numerical models, reflecting both the level of understanding of physical and chemical processes in the atmosphere and the contemporary computing capabilities, are used to blend observations from different in situ and, increasingly, Earth Observation sources. Significantly, the World Meteorological Organisation has recently added a new component to the Global Atmospheric Watch programme in the form of a Science Advisory Group on "Applications". The main objectives of this group are to develop a portfolio of products and services related to atmospheric composition and to demonstrate particularly the usefulness of exchanging chemical observational data in Near-Real-Time. Exchanging best practices worldwide and facilitating the set-up of new applications are also among the activities. Having operational applications does not imply that research efforts to improve environmental monitoring and forecasting services have become obsolete. Quite the contrary: feedbacks and increasingly demanding requirements from users are stimulating steady progress. The last part of the talk will support the idea that atmospheric compositions services are not only an application or an extension of weather services but contribute now also to the core of them. Atmospheric composition information has become indeed of high interest for modelling physical processes and assimilation of meteorological information. There are also exciting developments regarding the medium- to extended range prediction skill, with potential sources of predictability yet to be fully understood and harnessed.

Strategy for future space weather observational assets

NASA Astrophysics Data System (ADS)

Davies, Jackie; Bogdanova, Yulia; Harrison, Richard; Bisi, Mario; Hapgood, Mike

2017-04-01

Observations from an ad-hoc suite of mainly aging, scientific, space-borne assets currently underpin space weather forecasting capabilities world-wide. While efforts have begun to replace / supplement these assets - in particular with the recent launch of the DSCOVR spacecraft - it is widely accepted that there is an urgent need to accelerate these endeavours in order to mitigate the risk of losing these critical observations. It is hence opportune to critically review the possible options for the provision of space weather observations, particularly in terms of identifying the optimum vantage point(s) and the instrumentation that will provide the most beneficial measurements to support space weather prediction. Here we present the results of several recent European studies that aim to identify the best solution for space-based space weather monitoring - obviously within realistic financial constraints and bearing in mind the immediacy with which such a mission needs to be realised.

Where fast weathering creates thin regolith and slow weathering creates thick regolith

USGS Publications Warehouse

Bazilevskaya, Ekaterina; Lebedeva, Marina; Pavich, Milan J.; Brantley, Susan L.; Rother, Gernot; Parkinson, Dilworth Y.; Cole, David

2013-01-01

Weathering disaggregates rock into regolith – the fractured or granular earth material that sustains life on the continental land surface. Here, we investigate what controls the depth of regolith formed on ridges of two rock compositions with similar initial porosities in Virginia (USA). A priori, we predicted that the regolith on diabase would be thicker than on granite because the dominant mineral (feldspar) in the diabase weathers faster than its granitic counterpart. However, weathering advanced 20 deeper into the granite than the diabase. The 20 -thicker regolith is attributed mainly to connected micron-sized pores, microfractures formed around oxidizing biotite at 20 m depth, and the lower iron (Fe) content in the felsic rock. Such porosity allows pervasive advection and deep oxidation in the granite. These observations may explain why regolith worldwide is thicker on felsic compared to mafic rock under similar conditions. To understand regolith formation will require better understanding of such deep oxidation reactions and how they impact fluid flow during weathering.

Development, Implementation, and Skill Assessment of the NOAA/NOS Great Lakes Operational Forecast System

DTIC Science & Technology

2011-01-01

USA) 2011 Abstract The NOAA Great Lakes Operational Forecast System ( GLOFS ) uses near-real-time atmospheric observa- tions and numerical weather...Operational Oceanographic Products and Services (CO-OPS) in Silver Spring, MD. GLOFS has been making operational nowcasts and forecasts at CO-OPS... GLOFS ) uses near-real-time atmospheric observations and numerical weather prediction forecast guidance to produce three-dimensional forecasts of water

Medium-range fire weather forecasts

Treesearch

J.O. Roads; K. Ueyoshi; S.C. Chen; J. Alpert; F. Fujioka

1991-01-01

The forecast skill of theNational Meteorological Center's medium range forecast (MRF) numerical forecasts of fire weather variables is assessed for the period June 1,1988 to May 31,1990. Near-surface virtual temperature, relative humidity, wind speed and a derived fire weather index (FWI) are forecast well by the MRF model. However, forecast relative humidity has...

Waterspout Forecasting Method Over the Eastern Adriatic Using a High-Resolution Numerical Weather Model

NASA Astrophysics Data System (ADS)

Renko, Tanja; Ivušić, Sarah; Telišman Prtenjak, Maja; Šoljan, Vinko; Horvat, Igor

2018-03-01

In this study, a synoptic and mesoscale analysis was performed and Szilagyi's waterspout forecasting method was tested on ten waterspout events in the period of 2013-2016. Data regarding waterspout occurrences were collected from weather stations, an online survey at the official website of the National Meteorological and Hydrological Service of Croatia and eyewitness reports from newspapers and the internet. Synoptic weather conditions were analyzed using surface pressure fields, 500 hPa level synoptic charts, SYNOP reports and atmospheric soundings. For all observed waterspout events, a synoptic type was determined using the 500 hPa geopotential height chart. The occurrence of lightning activity was determined from the LINET lightning database, and waterspouts were divided into thunderstorm-related and "fair weather" ones. Mesoscale characteristics (with a focus on thermodynamic instability indices) were determined using the high-resolution (500 m grid length) mesoscale numerical weather model and model results were compared with the available observations. Because thermodynamic instability indices are usually insufficient for forecasting waterspout activity, the performance of the Szilagyi Waterspout Index (SWI) was tested using vertical atmospheric profiles provided by the mesoscale numerical model. The SWI successfully forecasted all waterspout events, even the winter events. This indicates that the Szilagyi's waterspout prognostic method could be used as a valid prognostic tool for the eastern Adriatic.

Verifying Operational and Developmental Air Force Weather Cloud Analysis and Forecast Products Using Lidar Data from Department of Energy Atmospheric Radiation Measurement (ARM) Sites

NASA Astrophysics Data System (ADS)

Hildebrand, E. P.

2017-12-01

Air Force Weather has developed various cloud analysis and forecast products designed to support global Department of Defense (DoD) missions. A World-Wide Merged Cloud Analysis (WWMCA) and short term Advected Cloud (ADVCLD) forecast is generated hourly using data from 16 geostationary and polar-orbiting satellites. Additionally, WWMCA and Numerical Weather Prediction (NWP) data are used in a statistical long-term (out to five days) cloud forecast model known as the Diagnostic Cloud Forecast (DCF). The WWMCA and ADVCLD are generated on the same polar stereographic 24 km grid for each hemisphere, whereas the DCF is generated on the same grid as its parent NWP model. When verifying the cloud forecast models, the goal is to understand not only the ability to detect cloud, but also the ability to assign it to the correct vertical layer. ADVCLD and DCF forecasts traditionally have been verified using WWMCA data as truth, but this might over-inflate the performance of those models because WWMCA also is a primary input dataset for those models. Because of this, in recent years, a WWMCA Reanalysis product has been developed, but this too is not a fully independent dataset. This year, work has been done to incorporate data from external, independent sources to verify not only the cloud forecast products, but the WWMCA data itself. One such dataset that has been useful for examining the 3-D performance of the cloud analysis and forecast models is Atmospheric Radiation Measurement (ARM) data from various sites around the globe. This presentation will focus on the use of the Department of Energy (DoE) ARM data to verify Air Force Weather cloud analysis and forecast products. Results will be presented to show relative strengths and weaknesses of the analyses and forecasts.

Simulation of an ensemble of future climate time series with an hourly weather generator

NASA Astrophysics Data System (ADS)

Caporali, E.; Fatichi, S.; Ivanov, V. Y.; Kim, J.

2010-12-01

There is evidence that climate change is occurring in many regions of the world. The necessity of climate change predictions at the local scale and fine temporal resolution is thus warranted for hydrological, ecological, geomorphological, and agricultural applications that can provide thematic insights into the corresponding impacts. Numerous downscaling techniques have been proposed to bridge the gap between the spatial scales adopted in General Circulation Models (GCM) and regional analyses. Nevertheless, the time and spatial resolutions obtained as well as the type of meteorological variables may not be sufficient for detailed studies of climate change effects at the local scales. In this context, this study presents a stochastic downscaling technique that makes use of an hourly weather generator to simulate time series of predicted future climate. Using a Bayesian approach, the downscaling procedure derives distributions of factors of change for several climate statistics from a multi-model ensemble of GCMs. Factors of change are sampled from their distributions using a Monte Carlo technique to entirely account for the probabilistic information obtained with the Bayesian multi-model ensemble. Factors of change are subsequently applied to the statistics derived from observations to re-evaluate the parameters of the weather generator. The weather generator can reproduce a wide set of climate variables and statistics over a range of temporal scales, from extremes, to the low-frequency inter-annual variability. The final result of such a procedure is the generation of an ensemble of hourly time series of meteorological variables that can be considered as representative of future climate, as inferred from GCMs. The generated ensemble of scenarios also accounts for the uncertainty derived from multiple GCMs used in downscaling. Applications of the procedure in reproducing present and future climates are presented for different locations world-wide: Tucson (AZ), Detroit (MI), and Firenze (Italy). The stochastic downscaling is carried out with eight GCMs from the CMIP3 multi-model dataset (IPCC 4AR, A1B scenario).

High-quality weather data for grid integration studies

NASA Astrophysics Data System (ADS)

Draxl, C.

2016-12-01

As variable renewable power penetration levels increase in power systems worldwide, renewable integration studies are crucial to ensure continued economic and reliable operation of the power grid. In this talk we will shed light on requirements for grid integration studies as far as wind and solar energy are concerned. Because wind and solar plants are strongly impacted by weather, high-resolution and high-quality weather data are required to drive power system simulations. Future data sets will have to push limits of numerical weather prediction to yield these high-resolution data sets, and wind data will have to be time-synchronized with solar data. Current wind and solar integration data sets will be presented. The Wind Integration National Dataset (WIND) Toolkit is the largest and most complete grid integration data set publicly available to date. A meteorological data set, wind power production time series, and simulated forecasts created using the Weather Research and Forecasting Model run on a 2-km grid over the continental United States at a 5-min resolution is now publicly available for more than 126,000 land-based and offshore wind power production sites. The Solar Integration National Dataset (SIND) is available as time synchronized with the WIND Toolkit, and will allow for combined wind-solar grid integration studies. The National Solar Radiation Database (NSRDB) is a similar high temporal- and spatial resolution database of 18 years of solar resource data for North America and India. Grid integration studies are also carried out in various countries, which aim at increasing their wind and solar penetration through combined wind and solar integration data sets. We will present a multi-year effort to directly support India's 24x7 energy access goal through a suite of activities aimed at enabling large-scale deployment of clean energy and energy efficiency. Another current effort is the North-American-Renewable-Integration-Study, with the aim of providing a seamless data set across borders for a whole continent, to simulate and analyze the impacts of potential future large wind and solar power penetrations on bulk power system operations.

Satellite Delivery of Aviation Weather Data

NASA Technical Reports Server (NTRS)

Kerczewski, Robert J.; Haendel, Richard

2001-01-01

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

Kinetically limited weathering at low denudation rates in semiarid climatic conditions

NASA Astrophysics Data System (ADS)

Schoonejans, Jérôme; Vanacker, Veerle; Opfergelt, Sophie; Ameijeiras-Mariño, Yolanda; Christl, Marcus

2016-02-01

Biogeochemical cycling within the Critical Zone depends on the interactions between minerals and fluids controlling chemical weathering and physical erosion rates. In this study, we explore the role of water availability in controlling soil chemical weathering in semiarid climatic conditions. Weathering rates and intensities were evaluated for nine soil profiles located on convex ridge crests of three mountain ranges in the Spanish Betic Cordillera. We combine a geochemical mass balance with 10Be cosmogenic nuclides to constrain chemical weathering intensities and long-term denudation rates. As such, this study presents new data on chemical weathering and 10Be-derived denudation for understudied semiarid climate systems. In the Betic Cordillera, chemical weathering intensities are relatively low (~5 to 30% of the total denudation of the soil) and negatively correlated with the magnitude of the water deficit in soils. Chemical mass losses are inversely related to denudation rates (14-109 mm/kyr) and positively to soil thickness (14-58 cm); these results are consistent with kinetic limitation of chemical weathering rates. A worldwide compilation of chemical weathering data suggests that soil water balance may regulate the coupling between chemical weathering and physical erosion by modulating soil solute fluxes. Therefore, future landscape evolution models that seek to link chemical weathering and physical erosion should include soil water flux as an essential driver of weathering.

Development of web-based services for an ensemble flood forecasting and risk assessment system

NASA Astrophysics Data System (ADS)

Yaw Manful, Desmond; He, Yi; Cloke, Hannah; Pappenberger, Florian; Li, Zhijia; Wetterhall, Fredrik; Huang, Yingchun; Hu, Yuzhong

2010-05-01

Flooding is a wide spread and devastating natural disaster worldwide. Floods that took place in the last decade in China were ranked the worst amongst recorded floods worldwide in terms of the number of human fatalities and economic losses (Munich Re-Insurance). Rapid economic development and population expansion into low lying flood plains has worsened the situation. Current conventional flood prediction systems in China are neither suited to the perceptible climate variability nor the rapid pace of urbanization sweeping the country. Flood prediction, from short-term (a few hours) to medium-term (a few days), needs to be revisited and adapted to changing socio-economic and hydro-climatic realities. The latest technology requires implementation of multiple numerical weather prediction systems. The availability of twelve global ensemble weather prediction systems through the ‘THORPEX Interactive Grand Global Ensemble' (TIGGE) offers a good opportunity for an effective state-of-the-art early forecasting system. A prototype of a Novel Flood Early Warning System (NEWS) using the TIGGE database is tested in the Huai River basin in east-central China. It is the first early flood warning system in China that uses the massive TIGGE database cascaded with river catchment models, the Xinanjiang hydrologic model and a 1-D hydraulic model, to predict river discharge and flood inundation. The NEWS algorithm is also designed to provide web-based services to a broad spectrum of end-users. The latter presents challenges as both databases and proprietary codes reside in different locations and converge at dissimilar times. NEWS will thus make use of a ready-to-run grid system that makes distributed computing and data resources available in a seamless and secure way. An ability to run or function on different operating systems and provide an interface or front that is accessible to broad spectrum of end-users is additional requirement. The aim is to achieve robust interoperability through strong security and workflow capabilities. A physical network diagram and a work flow scheme of all the models, codes and databases used to achieve the NEWS algorithm are presented. They constitute a first step in the development of a platform for providing real time flood forecasting services on the web to mitigate 21st century weather phenomena.

Satellite Sounder Data Assimilation for Improving Alaska Region Weather Forecast

NASA Technical Reports Server (NTRS)

Zhu, Jiang; Stevens, E.; Zavodsky, B. T.; Zhang, X.; Heinrichs, T.; Broderson, D.

2014-01-01

Data assimilation has been demonstrated very useful in improving both global and regional numerical weather prediction. Alaska has very coarser surface observation sites. On the other hand, it gets much more satellite overpass than lower 48 states. How to utilize satellite data to improve numerical prediction is one of hot topics among weather forecast community in Alaska. The Geographic Information Network of Alaska (GINA) at University of Alaska is conducting study on satellite data assimilation for WRF model. AIRS/CRIS sounder profile data are used to assimilate the initial condition for the customized regional WRF model (GINA-WRF model). Normalized standard deviation, RMSE, and correlation statistic analysis methods are applied to analyze one case of 48 hours forecasts and one month of 24-hour forecasts in order to evaluate the improvement of regional numerical model from Data assimilation. The final goal of the research is to provide improved real-time short-time forecast for Alaska regions.

Local Infrasound Variability Related to In Situ Atmospheric Observation

NASA Astrophysics Data System (ADS)

Kim, Keehoon; Rodgers, Arthur; Seastrand, Douglas

2018-04-01

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

Effects of sounding temperature assimilation on weather forecasting - Model dependence studies

NASA Technical Reports Server (NTRS)

Ghil, M.; Halem, M.; Atlas, R.

1979-01-01

In comparing various methods for the assimilation of remote sounding information into numerical weather prediction (NWP) models, the problem of model dependence for the different results obtained becomes important. The paper investigates two aspects of the model dependence question: (1) the effect of increasing horizontal resolution within a given model on the assimilation of sounding data, and (2) the effect of using two entirely different models with the same assimilation method and sounding data. Tentative conclusions reached are: first, that model improvement as exemplified by increased resolution, can act in the same direction as judicious 4-D assimilation of remote sounding information, to improve 2-3 day numerical weather forecasts. Second, that the time continuous 4-D methods developed at GLAS have similar beneficial effects when used in the assimilation of remote sounding information into NWP models with very different numerical and physical characteristics.

Application of climatic indices to analyse viticultural suitability in Extremadura, south-western Spain

NASA Astrophysics Data System (ADS)

Moral, Francisco J.; Rebollo, Francisco J.; Paniagua, Luis L.; García, Abelardo; de Salazar, Enrique Martínez

2016-01-01

Although climate is recognised as one of the main drivers of viticulture success, its main features have not been sufficiently described in many viticultural regions, including Extremadura, which contains one of the largest grapevine-growing areas in Europe. Using climatic data from 80 weather stations located throughout Extremadura, seven bioclimatic indices were calculated to estimate heat accumulation and potential water balance during the growing season and the thermal regime during the ripening of grapes. Differences in some climatic indices were found, and after a multivariate geographic analysis, four groups were delimited containing weather stations with similar climatic features, with variability between groups explained by heat accumulation and tempearture and thermal amplitude during the ripening season. Suitability for cultivation of grapevines without thermal restriction and temperate nights during the ripening period are the main characteristics of the weather stations studied, but spatial variability found in climatic potential denotes the importance of differentiating locations to properly relate the viticultural climate to grape quality factors and the style of wines produced. The climatic features of the four groups are very similar to those described in other viticultural regions, including those in close proximity to Extremadura and others worldwide, but few studies have used broad and updated temporal climate data for computing bioclimatic indices as in this case study. Finally, trends in climate indices were analysed. Results revealed that all groups have experienced warmer growing seasons, driven mainly by changes in minimum temperatures. This fact has numerous potential impacts, including changes in grapevine phenological timing, disruption of balanced composition in grapes (ultimately affecting wine characteristics), alterations in varieties grown and spatial changes in viable winegrape-growing zones.

Space and ground-based GNSS activities at NOAA

NASA Astrophysics Data System (ADS)

Cucurull, L.

2016-12-01

With the launch of the FORMOSAT-3/COSMIC satellites in April 2006, the availability of Global Navigation Satellite Systems (GNSS) Radio Occultation (RO) observations for operational Numerical Weather Prediction (NWP) applications began. GNSS RO profiles started being assimilated operationally in the major worldwide weather centers soon after. NOAA started assimilating RO data operationally in early 2007. After COSMIC, other missions carrying GNSS RO receivers became available for operational uses. The incorporation of RO observations into the operational assimilation systems was shown to improve global model forecast skill. Since its launch in 2006, the COSMIC constellation has been the mainstay of the global RO system. However, COSMIC is already past the end of its formal lifetime, and only three satellites are still operating. This has motivated NOAA to invest on the COSMIC-2 mission, a 12-satellite constellation, that will replace COSMIC. The first launch, in equatorial orbit, is planned for March 2017. In addition to the space-based component of the GNSS technique, NOAA is assimilating ground-based products into its operational regional models. Although most stations over CONUS provide estimates of Precipitable Water (PW), this is not the case outside the U.S., where the required auxiliary meteorological information is generally not available. Thus, in order to evaluate the impact of ground-based GNSS products on a global weather model, the assimilation of less derived products, such as zenith total delays, rather than PW, is necessary. The talk will include an update on current activities and future plans for the utilization of space and ground-based GNSS products at NOAA. In addition, an update on the COSMIC-2 mission will be discussed.

GIM-TEC adaptive ionospheric weather assessment and forecast system

NASA Astrophysics Data System (ADS)

Gulyaeva, T. L.; Arikan, F.; Hernandez-Pajares, M.; Stanislawska, I.

2013-09-01

The Ionospheric Weather Assessment and Forecast (IWAF) system is a computer software package designed to assess and predict the world-wide representation of 3-D electron density profiles from the Global Ionospheric Maps of Total Electron Content (GIM-TEC). The unique system products include daily-hourly numerical global maps of the F2 layer critical frequency (foF2) and the peak height (hmF2) generated with the International Reference Ionosphere extended to the plasmasphere, IRI-Plas, upgraded by importing the daily-hourly GIM-TEC as a new model driving parameter. Since GIM-TEC maps are provided with 1- or 2-days latency, the global maps forecast for 1 day and 2 days ahead are derived using an harmonic analysis applied to the temporal changes of TEC, foF2 and hmF2 at 5112 grid points of a map encapsulated in IONEX format (-87.5°:2.5°:87.5°N in latitude, -180°:5°:180°E in longitude). The system provides online the ionospheric disturbance warnings in the global W-index map establishing categories of the ionospheric weather from the quiet state (W=±1) to intense storm (W=±4) according to the thresholds set for instant TEC perturbations regarding quiet reference median for the preceding 7 days. The accuracy of IWAF system predictions of TEC, foF2 and hmF2 maps is superior to the standard persistence model with prediction equal to the most recent ‘true’ map. The paper presents outcomes of the new service expressed by the global ionospheric foF2, hmF2 and W-index maps demonstrating the process of origin and propagation of positive and negative ionosphere disturbances in space and time and their forecast under different scenarios.

Prediction skill of rainstorm events over India in the TIGGE weather prediction models

NASA Astrophysics Data System (ADS)

Karuna Sagar, S.; Rajeevan, M.; Vijaya Bhaskara Rao, S.; Mitra, A. K.

2017-12-01

Extreme rainfall events pose a serious threat of leading to severe floods in many countries worldwide. Therefore, advance prediction of its occurrence and spatial distribution is very essential. In this paper, an analysis has been made to assess the skill of numerical weather prediction models in predicting rainstorms over India. Using gridded daily rainfall data set and objective criteria, 15 rainstorms were identified during the monsoon season (June to September). The analysis was made using three TIGGE (THe Observing System Research and Predictability Experiment (THORPEX) Interactive Grand Global Ensemble) models. The models considered are the European Centre for Medium-Range Weather Forecasts (ECMWF), National Centre for Environmental Prediction (NCEP) and the UK Met Office (UKMO). Verification of the TIGGE models for 43 observed rainstorm days from 15 rainstorm events has been made for the period 2007-2015. The comparison reveals that rainstorm events are predictable up to 5 days in advance, however with a bias in spatial distribution and intensity. The statistical parameters like mean error (ME) or Bias, root mean square error (RMSE) and correlation coefficient (CC) have been computed over the rainstorm region using the multi-model ensemble (MME) mean. The study reveals that the spread is large in ECMWF and UKMO followed by the NCEP model. Though the ensemble spread is quite small in NCEP, the ensemble member averages are not well predicted. The rank histograms suggest that the forecasts are under prediction. The modified Contiguous Rain Area (CRA) technique was used to verify the spatial as well as the quantitative skill of the TIGGE models. Overall, the contribution from the displacement and pattern errors to the total RMSE is found to be more in magnitude. The volume error increases from 24 hr forecast to 48 hr forecast in all the three models.

Numerical Weather Prediction Models on Linux Boxes as tools in meteorological education in Hungary

NASA Astrophysics Data System (ADS)

Gyongyosi, A. Z.; Andre, K.; Salavec, P.; Horanyi, A.; Szepszo, G.; Mille, M.; Tasnadi, P.; Weidiger, T.

2012-04-01

Education of Meteorologist in Hungary - according to the Bologna Process - has three stages: BSc, MSc and PhD, and students graduating at each stage get the respective degree (BSc, MSc and PhD). The three year long base BSc course in Meteorology can be chosen by undergraduate students in the fields of Geosciences, Environmental Sciences and Physics. BasicsFundamentals in Mathematics (Calculus), Physics (General and Theoretical) Physics and Informatics are emphasized during their elementary education. The two year long MSc course - in which about 15 to 25 students are admitted each year - can be studied only at our the Eötvös Loránd uUniversity in the our country. Our aim is to give a basic education in all fields of Meteorology. Main topics are: Climatology, Atmospheric Physics, Atmospheric Chemistry, Dynamic and Synoptic Meteorology, Numerical Weather Prediction, modeling Modeling of surfaceSurface-atmosphere Iinteractions and Cclimate change. Education is performed in two branches: Climate Researcher and Forecaster. Education of Meteorologist in Hungary - according to the Bologna Process - has three stages: BSc, MSc and PhD, and students graduating at each stage get the respective degree. The three year long BSc course in Meteorology can be chosen by undergraduate students in the fields of Geosciences, Environmental Sciences and Physics. Fundamentals in Mathematics (Calculus), (General and Theoretical) Physics and Informatics are emphasized during their elementary education. The two year long MSc course - in which about 15 to 25 students are admitted each year - can be studied only at the Eötvös Loránd University in our country. Our aim is to give a basic education in all fields of Meteorology: Climatology, Atmospheric Physics, Atmospheric Chemistry, Dynamic and Synoptic Meteorology, Numerical Weather Prediction, Modeling of Surface-atmosphere Interactions and Climate change. Education is performed in two branches: Climate Researcher and Forecaster. Numerical modeling became a common tool in the daily practice of weather experts forecasters due to the i) increasing user demands for weather data by the costumers, ii) the growth in computer resources, iii) numerical weather prediction systems available for integration on affordable, off the shelf computers and iv) available input data (from ECMWF or NCEP) for model integrations. Beside learning the theoretical basis, since the last year. Students in their MSc or BSc Thesis Research or in Student's Research ProjectsStudent's Research Projects h have the opportunity to run numerical models and to analyze the outputs for different purposes including wind energy estimation, simulation of the dynamics of a polar low, and subtropical cyclones, analysis of the isentropic potential vorticity field, examination of coupled atmospheric dispersion models, etc. A special course in the application of numerical modeling has been held (is being announced for the upcoming semester) (is being announced for the upcoming semester) for our students in order to improve their skills on this field. Several numerical model (NRIPR ETA and WRF) systems have been adapted in the University and integrated WRF have been tested and used for the geographical region of the Carpathian Basin (NRIPR, ETA and WRF). Recently ALADIN/CHAPEAU the academic version of the ARPEGE ALADIN cy33t1 meso-scale numerical weather prediction model system (which is the operational forecasting tool of our National Weather Service) has been installed at our Institute. ALADIN is the operational forecasting model of the Hungarian Meteorological Service and developed in the framework of the international ALADIN co-operation. Our main objectives are i) the analysis of different typical weather situations, ii) fine tuning of parameterization schemes and the iii) comparison of the ALADIN/CHAPEAU and WRF model outputs based on case studies. The necessary hardware and software innovations has have been done. In the presentation the computer resources needed for the integration of both WRF and ALADIN/CHAPEAU models will be briefly described. The software developments performed for the evaluation and comparison of the different modeling systems will be demonstrated. The main objectives of the education program on the practical numerical weather modeling will be introduced, as well as its detailed thematics and the structure of the labs.

78 FR 51267 - Hours of Service of Drivers: National Ready Mixed Concrete Association; Application for Exemption

Federal Register 2010, 2011, 2012, 2013, 2014

2013-08-20

... rule is extremely difficult due to the numerous variables associated with delivery (e.g., weather... 2 hours resulting from weather or unforeseen construction delays. NRMCA claims that these frequent...

Appropriate Simulants are a Requirement for Mars Surface Systems Technology Development

NASA Technical Reports Server (NTRS)

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

2012-01-01

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

Adding Weather to Wargames

DTIC Science & Technology

2007-01-01

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

Predictability of extreme weather events for NE U.S.: improvement of the numerical prediction using a Bayesian regression approach

NASA Astrophysics Data System (ADS)

Yang, J.; Astitha, M.; Anagnostou, E. N.; Hartman, B.; Kallos, G. B.

2015-12-01

Weather prediction accuracy has become very important for the Northeast U.S. given the devastating effects of extreme weather events in the recent years. Weather forecasting systems are used towards building strategies to prevent catastrophic losses for human lives and the environment. Concurrently, weather forecast tools and techniques have evolved with improved forecast skill as numerical prediction techniques are strengthened by increased super-computing resources. In this study, we examine the combination of two state-of-the-science atmospheric models (WRF and RAMS/ICLAMS) by utilizing a Bayesian regression approach to improve the prediction of extreme weather events for NE U.S. The basic concept behind the Bayesian regression approach is to take advantage of the strengths of two atmospheric modeling systems and, similar to the multi-model ensemble approach, limit their weaknesses which are related to systematic and random errors in the numerical prediction of physical processes. The first part of this study is focused on retrospective simulations of seventeen storms that affected the region in the period 2004-2013. Optimal variances are estimated by minimizing the root mean square error and are applied to out-of-sample weather events. The applicability and usefulness of this approach are demonstrated by conducting an error analysis based on in-situ observations from meteorological stations of the National Weather Service (NWS) for wind speed and wind direction, and NCEP Stage IV radar data, mosaicked from the regional multi-sensor for precipitation. The preliminary results indicate a significant improvement in the statistical metrics of the modeled-observed pairs for meteorological variables using various combinations of the sixteen events as predictors of the seventeenth. This presentation will illustrate the implemented methodology and the obtained results for wind speed, wind direction and precipitation, as well as set the research steps that will be followed in the future.

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.

Ensemble Models

EPA Science Inventory

Ensemble forecasting has been used for operational numerical weather prediction in the United States and Europe since the early 1990s. An ensemble of weather or climate forecasts is used to characterize the two main sources of uncertainty in computer models of physical systems: ...

Error discrimination of an operational hydrological forecasting system at a national scale

NASA Astrophysics Data System (ADS)

Jordan, F.; Brauchli, T.

2010-09-01

The use of operational hydrological forecasting systems is recommended for hydropower production as well as flood management. However, the forecast uncertainties can be important and lead to bad decisions such as false alarms and inappropriate reservoir management of hydropower plants. In order to improve the forecasting systems, it is important to discriminate the different sources of uncertainties. To achieve this task, reanalysis of past predictions can be realized and provide information about the structure of the global uncertainty. In order to discriminate between uncertainty due to the weather numerical model and uncertainty due to the rainfall-runoff model, simulations assuming perfect weather forecast must be realized. This contribution presents the spatial analysis of the weather uncertainties and their influence on the river discharge prediction of a few different river basins where an operational forecasting system exists. The forecast is based on the RS 3.0 system [1], [2], which is also running the open Internet platform www.swissrivers.ch [3]. The uncertainty related to the hydrological model is compared to the uncertainty related to the weather prediction. A comparison between numerous weather prediction models [4] at different lead times is also presented. The results highlight an important improving potential of both forecasting components: the hydrological rainfall-runoff model and the numerical weather prediction models. The hydrological processes must be accurately represented during the model calibration procedure, while weather prediction models suffer from a systematic spatial bias. REFERENCES [1] Garcia, J., Jordan, F., Dubois, J. & Boillat, J.-L. 2007. "Routing System II, Modélisation d'écoulements dans des systèmes hydrauliques", Communication LCH n° 32, Ed. Prof. A. Schleiss, Lausanne [2] Jordan, F. 2007. Modèle de prévision et de gestion des crues - optimisation des opérations des aménagements hydroélectriques à accumulation pour la réduction des débits de crue, thèse de doctorat n° 3711, Ecole Polytechnique Fédérale, Lausanne [3] Keller, R. 2009. "Le débit des rivières au peigne fin", Revue Technique Suisse, N°7/8 2009, Swiss engineering RTS, UTS SA, Lausanne, p. 11 [4] Kaufmann, P., Schubiger, F. & Binder, P. 2003. Precipitation forecasting by a mesoscale numerical weather prediction (NWP) model : eight years of experience, Hydrology and Earth System

Hail formation triggers rapid ash aggregation in volcanic plumes

USGS Publications Warehouse

Van Eaton, Alexa R.; Mastin, Larry G.; Herzog, M.; Schwaiger, Hans F.; Schneider, David J.; Wallace, Kristi; Clarke, Amanda B

2015-01-01

During explosive eruptions, airborne particles collide and stick together, accelerating the fallout of volcanic ash and climate-forcing aerosols. This aggregation process remains a major source of uncertainty both in ash dispersal forecasting and interpretation of eruptions from the geological record. Here we illuminate the mechanisms and timescales of particle aggregation from a well-characterized ‘wet’ eruption. The 2009 eruption of Redoubt Volcano in Alaska incorporated water from the surface (in this case, a glacier), which is a common occurrence during explosive volcanism worldwide. Observations from C-band weather radar, fall deposits, and numerical modeling demonstrate that volcanic hail formed rapidly in the eruption plume, leading to mixed-phase aggregation of ~95% of the fine ash and stripping much of the cloud out of the atmosphere within 30 minutes. Based on these findings, we propose a mechanism of hail-like aggregation that contributes to the anomalously rapid fallout of fine ash and the occurrence of concentrically-layered aggregates in volcanic deposits.

Hail formation triggers rapid ash aggregation in volcanic plumes.

PubMed

Van Eaton, Alexa R; Mastin, Larry G; Herzog, Michael; Schwaiger, Hans F; Schneider, David J; Wallace, Kristi L; Clarke, Amanda B

2015-08-03

During explosive eruptions, airborne particles collide and stick together, accelerating the fallout of volcanic ash and climate-forcing aerosols. This aggregation process remains a major source of uncertainty both in ash dispersal forecasting and interpretation of eruptions from the geological record. Here we illuminate the mechanisms and timescales of particle aggregation from a well-characterized 'wet' eruption. The 2009 eruption of Redoubt Volcano, Alaska, incorporated water from the surface (in this case, a glacier), which is a common occurrence during explosive volcanism worldwide. Observations from C-band weather radar, fall deposits and numerical modelling demonstrate that hail-forming processes in the eruption plume triggered aggregation of ∼95% of the fine ash and stripped much of the erupted mass out of the atmosphere within 30 min. Based on these findings, we propose a mechanism of hail-like ash aggregation that contributes to the anomalously rapid fallout of fine ash and occurrence of concentrically layered aggregates in volcanic deposits.

Hail formation triggers rapid ash aggregation in volcanic plumes

PubMed Central

Van Eaton, Alexa R.; Mastin, Larry G.; Herzog, Michael; Schwaiger, Hans F.; Schneider, David J.; Wallace, Kristi L.; Clarke, Amanda B.

2015-01-01

During explosive eruptions, airborne particles collide and stick together, accelerating the fallout of volcanic ash and climate-forcing aerosols. This aggregation process remains a major source of uncertainty both in ash dispersal forecasting and interpretation of eruptions from the geological record. Here we illuminate the mechanisms and timescales of particle aggregation from a well-characterized ‘wet' eruption. The 2009 eruption of Redoubt Volcano, Alaska, incorporated water from the surface (in this case, a glacier), which is a common occurrence during explosive volcanism worldwide. Observations from C-band weather radar, fall deposits and numerical modelling demonstrate that hail-forming processes in the eruption plume triggered aggregation of ∼95% of the fine ash and stripped much of the erupted mass out of the atmosphere within 30 min. Based on these findings, we propose a mechanism of hail-like ash aggregation that contributes to the anomalously rapid fallout of fine ash and occurrence of concentrically layered aggregates in volcanic deposits. PMID:26235052

Improving Wind Predictions in the Marine Atmospheric Boundary Layer through Parameter Estimation in a Single-Column Model

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

Lee, Jared A.; Hacker, Joshua P.; Delle Monache, Luca

2016-12-14

A current barrier to greater deployment of offshore wind turbines is the poor quality of numerical weather prediction model wind and turbulence forecasts over open ocean. The bulk of development for atmospheric boundary layer (ABL) parameterization schemes has focused on land, partly due to a scarcity of observations over ocean. The 100-m FINO1 tower in the North Sea is one of the few sources worldwide of atmospheric profile observations from the sea surface to turbine hub height. These observations are crucial to developing a better understanding and modeling of physical processes in the marine ABL. In this study, we usemore » the WRF single column model (SCM), coupled with an ensemble Kalman filter from the Data Assimilation Research Testbed (DART), to create 100-member ensembles at the FINO1 location. The goal of this study is to determine the extent to which model parameter estimation can improve offshore wind forecasts.« less

Coordination, Data Management and Enhancement of the International Arctic Buoy Programme (IABP) a US Interagency Arctic Buoy Programme \\201USIABP\\202 contribution to the IABP

DTIC Science & Technology

2013-09-30

data from the IABP ); 2.) Forecasting weather and sea ice conditions; 3.) Forcing, assimilation and validation of global weather and climate models ...International Arctic Buoy Programme ( IABP ) A US Interagency Arctic Buoy Programme (USIABP) contribution to the IABP Dr. Ignatius G. Rigor Polar...ice motion. These observations are assimilated into Numerical Weather Prediction (NWP) models that are used to forecast weather on synoptic time

Earth Remote Sensing for Weather Forecasting and Disaster Applications

NASA Technical Reports Server (NTRS)

Molthan, Andrew; Bell, Jordan; Case, Jonathan; Cole, Tony; Elmer, Nicholas; McGrath, Kevin; Schultz, Lori; Zavodsky, Brad

2016-01-01

NASA's constellation of current missions provide several opportunities to apply satellite remote sensing observations to weather forecasting and disaster response applications. Examples include: Using NASA's Terra and Aqua MODIS, and the NASA/NOAA Suomi-NPP VIIRS missions to prepare weather forecasters for capabilities of GOES-R; Incorporating other NASA remote sensing assets for improving aspects of numerical weather prediction; Using NASA, NOAA, and international partner resources (e.g. ESA/Sentinel Series); and commercial platforms (high-res, or UAV) to support disaster mapping.

AFFECTS - Advanced Forecast For Ensuring Communications Through Space

NASA Astrophysics Data System (ADS)

Bothmer, Volker

2013-04-01

Through the AFFECTS project funded by the European Union's 7th Framework Programme, European and US scientists develop an advanced proto-type space weather warning system to safeguard the operation of telecommunication and navigation systems on Earth to the threat of solar storms. The project is led by the University of Göttingen's Institute for Astrophysics and comprises worldwide leading research and academic institutions and industrial enterprises from Germany, Belgium, Ukraine, Norway and the United States. The key objectives of the AFFECTS project are: State-of-the-art analysis and modelling of the Sun-Earth chain of effects on the Earth's ionosphere and their subsequent impacts on communication systems based on multipoint space observations and complementary ground-based data. Development of a prototype space weather early warning system and reliable space weather forecasts, with specific emphasis on ionospheric applications. Dissemination of new space weather products and services to end users, the scientific community and general public. The presentation summarizes the project highlights, with special emphasis on the developed space weather forecast tools.

Decay of sandstone monuments in Petra (Jordan): Gravity-induced stress as a stabilizing factor

NASA Astrophysics Data System (ADS)

Řihošek, Jaroslav; Bruthans, Jiří; Mašín, David; Filippi, Michal; Schweigstillova, Jana

2016-04-01

As demonstrated by physical experiments and numerical modeling the gravity-induced stress (stress in further text) in sandstone massive reduces weathering and erosion rate (Bruthans et al. 2014). This finding is in contrast to common view that stress threatens stability of man-made monuments carved to sandstone. Certain low- levels of gravity-induced stress can in fact stabilize and protect these forms against weathering and disintegration. The purpose of this investigation is to evaluate the effect of the stress on weathering of sandstone monuments at the Petra World Heritage Site in Jordan via field observations, salt weathering experiments, and physical and numerical modeling. Previous studies on weathering of Petra monuments have neglected the impact of stress, but the ubiquitous presence of stress-controlled landforms in Petra suggests that it has a substantial effect on weathering and erosion processes on man-made monuments and natural surfaces. Laboratory salt weathering experiments with cubes of Umm Ishrin sandstone from Petra demonstrated the inverse relationship between stress magnitude and decay rate. Physical modeling with Strelec locked sand from the Czech Republic was used to simulate weathering and decay of Petra monuments. Sharp forms subjected to water erosion decayed to rounded shapes strikingly similar to tombs in Petra subjected to more than 2000 years of weathering and erosion. The physical modeling results enabled visualization of the recession of monument surfaces in high spatial and temporal resolution and indicate that the recession rate of Petra monuments is far from constant both in space and time. Numerical modeling of stress fields confirms the physical modeling results. This novel approach to investigate weathering clearly demonstrates that increased stress decreases the decay rate of Petra monuments. To properly delineate the endangered zones of monuments, the potential damage caused by weathering agents should be combined with stress modeling and verified by documentation of real damage. This research was funded by Grant Agency of Charles University (no. 386815) Bruthans J., Soukup J., Vaculíková J., Filippi M., Schweigstillova J., Mayo A.L., Mašín D., Kletetschka G.,Řihošek J. (2014): Sandstone landforms shaped by negative feedback between stress and erosion. Nature Geoscience 7(8): 597-601.

Monitoring Intense Thunderstorms in the Hindu-Kush Himalayan Region

NASA Technical Reports Server (NTRS)

Gatlin, Patrick; Cecil, Daniel; Case, Jonathan; Bell, Jordan; Petersen, Walter; Adhikary, Bhupesh

2016-01-01

Some of the most intense thunderstorms on the planet routinely occur in the Hindu-Kush Himalaya region(HKH) region where many government organizations lack the capacity needed to predict, observe and effectively respond to the threats and hazards associated with high impact convective weather. This project combines innovative numerical weather prediction, satellite-based precipitation and land imagery techniques into a high impact weather assessment toolkit (HIWAT) that will build the capabilities of national meteorological departments and other weather sensitive agencies in the HKH region to assess the potential threats and impacts of high impact convective weather.

Satellite Broadcast of Graphical Weather Data Flight Tested

NASA Technical Reports Server (NTRS)

Mallasch, Paul G.

2000-01-01

NASA Glenn Research Center at Lewis Field's aviation Weather Information Communications (WINCOMM) and NASA Langley Research Center's Aviation Weather Information (AWIN) programs collaborated in a flight test and evaluation of a worldwide weather data-link capability using satellites. This successful flight testing moves NASA closer to its goal of developing advanced communications and information technologies to enable high-quality and timely dissemination of aviation weather information to all relevant users on the aviation information network. Recognized as a major contributing factor in aviation accidents and incidents, weather contributes directly or indirectly to nearly 80 percent of fatal general aviation (small private aircraft) accidents. In 1997, the Aeronautics Safety Investment Strategy Team s weather team produced a prioritized list of investment areas under weather accident prevention. Weather data dissemination is the most critical and highest ranked priority on the list. NASA's Aviation Safety Program founded the Aviation Weather Information initiative to focus efforts on significantly reducing the number of weather-related aviation fatalities. Access to accurate and timely weather data could contribute to a major reduction of weather-related incidents and accidents. However, a cost-effective solution has eluded most general aviation pilots because of the high cost of onboard weather radar equipment. Rockwell Collins, through a contract with NASA and in cooperation with WorldSpace Corporation, successfully completed ground and flight testing of a receiver and antenna in Johannesburg, South Africa. This NASA/Rockwell Collins project is an evaluation of worldwide weather data-link capability using transmissions from the Satellite Digital Audio Radio Services (S DARS) AfriStar satellite. Owned and operated by WorldSpace, AfriStar is a geostationary satellite that broadcasts commercial digital audio services to stationary and mobile platforms. S DARS satellites are the most powerful communications satellites produced to date, allowing users to receive signals using simple, low-cost patch antennas instead of more expensive, beam-steered antenna arrays. Engineers connected an inexpensive, commercially available radio receiver to a laptop computer and an antenna designed and built by Rockwell Collins, enabling them to receive WorldSpace signals from the AfriStar satellite during flight tests. WorldSpace broadcast their composite color graphical weather data files, which were multiplexed with normal audio streams, to the flat patch antenna mounted on a single-engine aircraft. The aircraft was equipped with a modified commercial S-DARS receiver, a Global Positioning Satellite (GPS) receiver, and a laptop computer with color display. Continuous data reception occurred during normal aircraft maneuvers performed throughout takeoff, cruise, and landing operations. In addition, engineers monitored receiver power levels during steep turns and banks. In most instances, the receiver was able to maintain acceptable power levels during all phases of flight and to obtain weather data with little or with the successful completion of ground and flight testing of a receiver and antenna in Johannesburg, South Africa, the team has started to prepare for experiments using highspeed aircraft in areas of the world with limited access to timely weather data. NASA plans to provide a more advanced antenna design and consultation support. This successful test of real-time aviation-related weather data is a positive step toward solving communications-specific issues associated with the dissemination of weather data directly to the cockpit.

Monitoring Marine Weather Systems Using Quikscat and TRMM Data

NASA Technical Reports Server (NTRS)

Liu, W.; Tang, W.; Datta, A.; Hsu, C.

1999-01-01

We do not understand nor are able to predict marine storms, particularly tropical cyclones, sufficiently well because ground-based measurements are sparse and operational numerical weather prediction models do not have sufficient spatial resolution nor accurate parameterization of the physics.

The solar atmosphere and the structure of active regions. [aircraft accidents, weather

NASA Technical Reports Server (NTRS)

Sturrock, P. A.

1975-01-01

Numerical analyses of solar activities are presented. The effect of these activities on aircraft and weather conditions was studied. Topics considered are: (1) solar flares; (2) solar X-rays; and (3) solar magnetic fields (charts are shown).

Space Weather Monitoring with GOES-16: Instruments and Data Products

NASA Astrophysics Data System (ADS)

Loto'aniu, Paul; Rodriguez, Juan; Redmon, Robert; Machol, Janet; Kress, Brian; Seaton, Daniel; Darnel, Jonathan; Rowland, William; Tilton, Margaret; Denig, William; Boudouridis, Athanasios; Codrescu, Stefan; Claycomb, Abram

2017-04-01

Since their inception in the 1970s, the NOAA GOES satellites have monitored the sources of space weather on the sun and the effects of space weather at Earth. The GOES-16 spacecraft, the first of four satellites as part of the GOES-R spacecraft series mission, was launched in November 2016. The space weather instruments on GOES-16 have significantly improved capabilities over older GOES instruments. They will image the sun's atmosphere in extreme-ultraviolet and monitor solar irradiance in X-rays and UV, solar energetic particles, magnetospheric energetic particles, galactic cosmic rays, and the Earth's magnetic field. These measurements are important for providing alerts and warnings to many worldwide customers, including the NOAA National Weather Service, satellite operators, the power utilities, and NASA's human activities in space. This presentation reviews the capabilities of the GOES-16 space weather instruments and presents initial post launch data along with a discussion of calibration activities and the current status of the instruments. We also describe the space weather Level 2+ products that are being developed for the GOES-R series including solar thematic maps, automated magnetopause crossing detection and spacecraft charging estimates. These new and continuing data products will be an integral part of NOAA space weather operations in the GOES-R era.

Effects of climate on chemical weathering in watersheds

USGS Publications Warehouse

White, A.F.; Blum, A.E.

1995-01-01

Climatic effects on chemical weathering are evaluated by correlating variations in solute concentrations and fluxes with temperature, precipitation, runoff, and evapotranspiration (ET) for a worldwide distribution of sixty-eight watersheds underlain by granitoid rock types. Stream solute concentrations are strongly correlated with proportional ET loss, and evaporative concentration makes stream solute concentrations an inapprorpiate surrogate for chemical weathering. Chemical fluxes are unaffected by ET, and SiO2 and Na weathering fluxes exhibit systematic increases with precipitation, runoff, and temperature. However, warm and wet watersheds produce anomalously rapid weathering rates. A proposed model that provides an improved prediction of weathering rates over climatic extremes is the product of linear precipitation and Arrhenius temperature functions. The resulting apparent activation energies based on SiO2 and Na fluxes are 59.4 and 62.5 kJ.mol-1, respectively. The coupling between temperature and precipitation emphasizes the importance of tropical regions in global silicate weathering fluxes, and suggests it is not representative to use continental averages for temperature and precipitation in the weathering rate functions of global carbon cycling and climatic change models. Fluxes of K, Ca, and Mg exhibit no climatic correlation, implying that other processes, such as ion exchange, nutrient cycling, and variations in lithology, obscure any climatic signal. -from Authors

Climate Change Impact on Sugarcane Production in Developing Countries

USDA-ARS?s Scientific Manuscript database

A combination of long-term change in the weather patterns worldwide (Global climate change), caused by natural processes and anthropogenic factors, may result in major environmental issues that have affected and will continuously affect agriculture. Increases in atmospheric carbon dioxide concentrat...

Climate change, soil health, and ecosystem goods and services

USDA-ARS?s Scientific Manuscript database

Worldwide, climate change is predicted to alter precipitation regimes, annual temperatures, and occurrence of severe weather events. These changes have important implications for soil health-- defined as the capacity of a soil to contribute to ecosystem function and sustain producers and consumers--...

Space and ground segment performance of the FORMOSAT-3/COSMIC mission: four years in orbit

NASA Astrophysics Data System (ADS)

Fong, C.-J.; Whiteley, D.; Yang, E.; Cook, K.; Chu, V.; Schreiner, B.; Ector, D.; Wilczynski, P.; Liu, T.-Y.; Yen, N.

2011-01-01

The FORMOSAT-3/COSMIC (Constellation Observing System for Meteorology, Ionosphere, and Climate) mission consisting of six Low-Earth-Orbit (LEO) satellites is the world's first demonstration constellation using radio occultation signals from Global Positioning System (GPS) satellites. The radio occultation signals are retrieved in near real-time for global weather/climate monitoring, numerical weather prediction, and space weather research. The mission has processed on average 1400 to 1800 high-quality atmospheric sounding profiles per day. The atmospheric radio occultation soundings data are assimilated into operational numerical weather prediction models for global weather prediction, including typhoon/hurricane/cyclone forecasts. The radio occultation data has shown a positive impact on weather predictions at many national weather forecast centers. A proposed follow-on mission transitions the program from the current experimental research system to a significantly improved real-time operational system, which will reliably provide 8000 radio occultation soundings per day. The follow-on mission as planned will consist of 12 satellites with a data latency of 45 min, which will provide greatly enhanced opportunities for operational forecasts and scientific research. This paper will address the FORMOSAT-3/COSMIC system and mission overview, the spacecraft and ground system performance after four years in orbit, the lessons learned from the encountered technical challenges and observations, and the expected design improvements for the new spacecraft and ground system.

Numerical Methods in Atmospheric and Oceanic Modelling: The Andre J. Robert Memorial Volume

NASA Astrophysics Data System (ADS)

Rosmond, Tom

Most people, even including some in the scientific community, do not realize how much the weather forecasts they use to guide the activities of their daily lives depend on very complex mathematics and numerical methods that are the basis of modern numerical weather prediction (NWP). André Robert (1929-1993), to whom Numerical Methods in Atmospheric and Oceanic Modelling is dedicated, had a career that contributed greatly to the growth of NWP and the role that the atmospheric computer models of NWP play in our society. There are probably no NWP models running anywhere in the world today that do not use numerical methods introduced by Robert, and those of us who work with and use these models everyday are indebted to him.The first two chapters of the volume are chronicles of Robert's life and career. The first is a 1987 interview by Harold Ritchie, one of Robert's many proteges and colleagues at the Canadian Atmospheric Environment Service. The interview traces Robert's life from his birth in New York to French Canadian parents, to his emigration to Quebec at an early age, his education and early employment, and his rise in stature as one of the preeminent research meteorologists of our time. An amusing anecdote he relates is his impression of weather forecasts while he was considering his first job as a meteorologist in the early 1950s. A newspaper of the time placed the weather forecast and daily horoscope side by side, and Robert regarded each to have a similar scientific basis. Thankfully he soon realized there was a difference between the two, and his subsequent career certainly confirmed the distinction.

Turbulence sources in mountain terrain: results from MATERHORN program

NASA Astrophysics Data System (ADS)

Di Sabatino, Silvana; Leo, Laura S.; Fernando, Harindra J. S.; Pardyjak, Eric R.; Hocut, Chris M.

2016-04-01

Improving high-resolution numerical weather prediction in complex terrain is essential for the many applications involving mountain weather. It is commonly recognized that high intensity weather phenomena near mountains are a safety hazard to aircrafts and unmanned aerial vehicles, but the prediction of highly variable weather is often unsatisfactory due to inadequacy of resolution or lack of the correct dynamics in the model. Improving mountain weather forecasts has been the goal of the interdisciplinary Mountain Terrain Atmospheric Modeling and Observations (MATERHORN) program (2011-2016). In this paper, we will report some of the findings focusing on several mechanisms of generating turbulence in near surface flows in the vicinity of an isolated mountain. Specifically, we will discuss nocturnal flows under low synoptic forcing. It has been demonstrated that such calm conditions are hard to predict in typical weather predictions models where forcing is dominated by local features that are poorly included in numerical models. It is found that downslope flows in calm and clear nights develop rapidly after sunset and usually persists for few hours. Owing to multiscale flow interactions, slope flows appear to be intermittent and disturbed, with a tendency to decay through the night yet periodically and unexpectedly generated. One of the interesting feature herein is the presence of oscillations that can be associated to different types of waves (e.g. internal and trapping waves) which may break to produce extra mixing. Pulsations of katabatic flow at critical internal-wave frequency, flow intrusions arriving from different topographies and shear layers of flow fanning out from the gaps all contribute to the weakly or intermittently turbulent state. Understanding of low frequency contributions to the total kinetic energy represent a step forward into modelling sub-grid effects in numerical models used for aviation applications.

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.

Space Weather Forecasting and Supporting Research in the USA

NASA Astrophysics Data System (ADS)

Pevtsov, A. A.

2017-12-01

In the United State, scientific research in space weather is funded by several Government Agencies including the National Science Foundation (NSF) and the National Aeronautics and Space Agency (NASA). For civilian and commercial purposes, space weather forecast is done by the Space Weather Prediction Center (SWPC) of the National Oceanic and Atmospheric Administration (NOAA). Observational data for modeling come from the network of groundbased observatories funded via various sources, as well as from the instruments on spacecraft. Numerical models used in forecast are developed in framework of individual research projects. The article provides a brief review of current state of space weather-related research and forecasting in the USA.

Characterization of genetic diversity of high temperature tolerance in sorghum

USDA-ARS?s Scientific Manuscript database

As global warming becomes inevitable, the sustainability of agricultural production in US and worldwide faces serious threat from extreme weather conditions, such as drought and elevated extreme temperatures (heat waves). Among cereal crops, sorghum is considered a versatile crop for semiarid area a...

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.

Preservation of large titanosaur sauropods in overbank fluvial facies: A case study in the Cretaceous of Argentina

NASA Astrophysics Data System (ADS)

González Riga, Bernardo J.; Astini, Ricardo A.

2007-04-01

Patagonia exhibits a particularly abundant record of Cretaceous dinosaurs with worldwide relevance. Although paleontological studies are relatively numerous, few include taphonomic information about these faunas. This contribution provides the first detailed sedimentological and taphonomical analyses of a dinosaur bone quarry from northern Neuquén Basin. At Arroyo Seco (Mendoza Province, Argentina), a large parautochthonous/autochthonous accumulation of articulated and disarticulated bones that represent several sauropod individuals has been discovered. The fossil remains, assigned to Mendozasaurus neguyelap González Riga, correspond to a large (18-27-m long) sauropod titanosaur collected in the strata of the Río Neuquén Subgroup (late Turoronian-late Coniacian). A taphonomic viewpoint recognizes a two-fold division into biostratinomic and fossil-diagenetic processes. Biostratinomic processes include (1) subaerial biodegradation of sauropod carcasses on well-drained floodplains, (2) partial or total skeletal disarticulation, (3) reorientation of bones by sporadic overbank flows, and (4) subaerial weathering. Fossil-diagenetic processes include (1) plastic deformation of bones, (2) initial permineralization with hematite, (3) fracturing and brittle deformation due to lithostatic pressure; (4) secondary permineralization with calcite in vascular canals and fractures, and (5) postfossilization bone weathering. This type of bone concentration, also present in Rincón de los Sauces (northern Patagonia), suggests that overbank facies tended to accumulate large titanosaur bones. This taphonomic mode, referred to as "overbank bone assemblages", outlines the potential of crevasse splay facies as important sources of paleontological data in Cretaceous meandering fluvial systems.

Science of Nowcasting Olympic Weather for Vancouver 2010 (SNOW-V10): a World Weather Research Programme Project

NASA Astrophysics Data System (ADS)

Isaac, G. A.; Joe, P. I.; Mailhot, J.; Bailey, M.; Bélair, S.; Boudala, F. S.; Brugman, M.; Campos, E.; Carpenter, R. L.; Crawford, R. W.; Cober, S. G.; Denis, B.; Doyle, C.; Reeves, H. D.; Gultepe, I.; Haiden, T.; Heckman, I.; Huang, L. X.; Milbrandt, J. A.; Mo, R.; Rasmussen, R. M.; Smith, T.; Stewart, R. E.; Wang, D.; Wilson, L. J.

2014-01-01

A World Weather Research Programme (WWRP) project entitled the Science of Nowcasting Olympic Weather for Vancouver 2010 (SNOW-V10) was developed to be associated with the Vancouver 2010 Olympic and Paralympic Winter Games conducted between 12 February and 21 March 2010. The SNOW-V10 international team augmented the instrumentation associated with the Winter Games and several new numerical weather forecasting and nowcasting models were added. Both the additional observational and model data were available to the forecasters in real time. This was an excellent opportunity to demonstrate existing capability in nowcasting and to develop better techniques for short term (0-6 h) nowcasts of winter weather in complex terrain. Better techniques to forecast visibility, low cloud, wind gusts, precipitation rate and type were evaluated. The weather during the games was exceptionally variable with many periods of low visibility, low ceilings and precipitation in the form of both snow and rain. The data collected should improve our understanding of many physical phenomena such as the diabatic effects due to melting snow, wind flow around and over terrain, diurnal flow reversal in valleys associated with daytime heating, and precipitation reductions and increases due to local terrain. Many studies related to these phenomena are described in the Special Issue on SNOW-V10 for which this paper was written. Numerical weather prediction and nowcast models have been evaluated against the unique observational data set now available. It is anticipated that the data set and the knowledge learned as a result of SNOW-V10 will become a resource for other World Meteorological Organization member states who are interested in improving forecasts of winter weather.

Seafloor weathering buffering climate: numerical experiments

NASA Astrophysics Data System (ADS)

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

2013-12-01

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

Evolution of porosity and diffusivity associated with chemical weathering of a basalt clast

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

Navarre-Sitchler, A.; Steefel, C.I.; Yang, L.

Weathering of rocks as a result of exposure to water and the atmosphere can cause significant changes in their chemistry and porosity. In low-porosity rocks, such as basalts, changes in porosity, resulting from chemical weathering, are likely to modify the rock's effective diffusivity and permeability, affecting the rate of solute transport and thus potentially the rate of overall weathering to the extent that transport is the rate limiting step. Changes in total porosity as a result of mineral dissolution and precipitation have typically been used to calculate effective diffusion coefficients through Archie's law for reactive transport simulations of chemical weathering,more » but this approach fails to account for unconnected porosity that does not contribute to transport. In this study, we combine synchrotron X-ray microcomputed tomography ({mu}CT) and laboratory and numerical diffusion experiments to examine changes in both total and effective porosity and effective diffusion coefficients across a weathering interface in a weathered basalt clast from Costa Rica. The {mu}CT data indicate that below a critical value of {approx}9%, the porosity is largely unconnected in the basalt clast. The {mu}CT data were further used to construct a numerical pore network model to determine upscaled, effective diffusivities as a function of total porosity (ranging from 3 to 30%) for comparison with diffusivities determined in laboratory tracer experiments. By using effective porosity as the scaling parameter and accounting for critical porosity, a model is developed that accurately predicts continuum-scale effective diffusivities across the weathering interface of the basalt clast.« less

Impact of climate variability on vector-borne disease transmission

USDA-ARS?s Scientific Manuscript database

We will discuss the impact of climate variability on vector borne diseases and demonstrate that global climate teleconnections can be used to anticipate and forecast, in the case of Rift Valley fever, epidemics and epizootics. In this context we will examine significant worldwide weather anomalies t...

Aluminum tolerance in sorghum and maize

USDA-ARS?s Scientific Manuscript database

The soils of the tropics and subtropics are highly weathered, leading to poor soil fertility and low soil pH. Root growth and function on these acid soils is impaired by aluminium (Al) toxicity, leading to yield instability that jeopardizes food security worldwide. A wealth of physiological evidence...

Be a Citizen Scientist!: Celebrate Earth Science Week 2006

ERIC Educational Resources Information Center

Benbow, Ann E.; Camphire, Geoff

2006-01-01

During Earth Science Week (October 8-14, 2006), millions of citizen scientists worldwide will be sampling groundwater, monitoring weather, touring quarries, exploring caves, preparing competition projects, and visiting museums and science centers to learn about Earth science. The American Geological Institute organizes this annual event to…

Tailored high-resolution numerical weather forecasts for energy efficient predictive building control

NASA Astrophysics Data System (ADS)

Stauch, V. J.; Gwerder, M.; Gyalistras, D.; Oldewurtel, F.; Schubiger, F.; Steiner, P.

2010-09-01

The high proportion of the total primary energy consumption by buildings has increased the public interest in the optimisation of buildings' operation and is also driving the development of novel control approaches for the indoor climate. In this context, the use of weather forecasts presents an interesting and - thanks to advances in information and predictive control technologies and the continuous improvement of numerical weather prediction (NWP) models - an increasingly attractive option for improved building control. Within the research project OptiControl (www.opticontrol.ethz.ch) predictive control strategies for a wide range of buildings, heating, ventilation and air conditioning (HVAC) systems, and representative locations in Europe are being investigated with the aid of newly developed modelling and simulation tools. Grid point predictions for radiation, temperature and humidity of the high-resolution limited area NWP model COSMO-7 (see www.cosmo-model.org) and local measurements are used as disturbances and inputs into the building system. The control task considered consists in minimizing energy consumption whilst maintaining occupant comfort. In this presentation, we use the simulation-based OptiControl methodology to investigate the impact of COSMO-7 forecasts on the performance of predictive building control and the resulting energy savings. For this, we have selected building cases that were shown to benefit from a prediction horizon of up to 3 days and therefore, are particularly suitable for the use of numerical weather forecasts. We show that the controller performance is sensitive to the quality of the weather predictions, most importantly of the incident radiation on differently oriented façades. However, radiation is characterised by a high temporal and spatial variability in part caused by small scale and fast changing cloud formation and dissolution processes being only partially represented in the COSMO-7 grid point predictions. On the other hand, buildings are affected by particularly local weather conditions at the building site. To overcome this discrepancy, we make use of local measurements to statistically adapt the COSMO-7 model output to the meteorological conditions at the building. For this, we have developed a general correction algorithm that exploits systematic properties of the COSMO-7 prediction error and explicitly estimates the degree of temporal autocorrelation using online recursive estimation. The resulting corrected predictions are improved especially for the first few hours being the most crucial for the predictive controller and, ultimately for the reduction of primary energy consumption using predictive control. The use of numerical weather forecasts in predictive building automation is one example in a wide field of weather dependent advanced energy saving technologies. Our work particularly highlights the need for the development of specifically tailored weather forecast products by (statistical) postprocessing in order to meet the requirements of specific applications.

Global Space Weather Observational Network: Challenges and China's Contribution

NASA Astrophysics Data System (ADS)

Wang, C.

2017-12-01

To understand space weather physical processes and predict space weather accurately, global space-borne and ground-based space weather observational network, making simultaneous observations from the Sun to geo-space (magnetosphere, ionosphere and atmosphere), plays an essential role. In this talk, we will present the advances of the Chinese space weather science missions, including the ASO-S (Advanced Space-borne Solar Observatory), MIT (Magnetosphere - Ionosphere- Thermosphere Coupling Exploration), and the ESA-China joint space weather science mission SMILE (Solar wind - Magnetosphere - Ionosphere Link Explore), a new mission to image the magnetosphere. Compared to satellites, ground-based monitors are cheap, convenient, and provide continuous real-time data. We will also introduce the Chinese Meridian Project (CMP), a ground-based program fully utilizing the geographic location of the Chinese landmass to monitor the geo-space environment. CMP is just one arm of a larger program that Chinese scientists are proposing to the international community. The International Meridian Circle Program (IMCP) for space weather hopes to connect chains of ground-based monitors at the longitudinal meridians 120 deg E and 60 deg W. IMCP takes advantage of the fact that these meridians already have the most monitors of any on Earth, with monitors in Russia, Australia, Brazil, the United States, Canada, and other countries. This data will greatly enhance the ability of scientists to monitor and predict the space weather worldwide.

Recent Weather Extremes and Impacts on Agricultural Production and Vector-Borne Disease Outbreak Patterns

NASA Technical Reports Server (NTRS)

Anyamba, Assaf; Small, Jennifer L.; Britch, Seth C.; Tucker, Compton J.; Pak, Edwin W.; Reynolds, Curt A.; Crutchfield, James; Linthicum, Kenneth J.

2014-01-01

We document significant worldwide weather anomalies that affected agriculture and vector-borne disease outbreaks during the 2010-2012 period. We utilized 2000-2012 vegetation index and land surface temperature data from NASA's satellite-based Moderate Resolution Imaging Spectroradiometer (MODIS) to map the magnitude and extent of these anomalies for diverse regions including the continental United States, Russia, East Africa, Southern Africa, and Australia. We demonstrate that shifts in temperature and/or precipitation have significant impacts on vegetation patterns with attendant consequences for agriculture and public health. Weather extremes resulted in excessive rainfall and flooding as well as severe drought, which caused,10 to 80% variation in major agricultural commodity production (including wheat, corn, cotton, sorghum) and created exceptional conditions for extensive mosquito-borne disease outbreaks of dengue, Rift Valley fever, Murray Valley encephalitis, and West Nile virus disease. Analysis of MODIS data provided a standardized method for quantifying the extreme weather anomalies observed during this period. Assessments of land surface conditions from satellite-based systems such as MODIS can be a valuable tool in national, regional, and global weather impact determinations.

Recent weather extremes and impacts on agricultural production and vector-borne disease outbreak patterns.

PubMed

Anyamba, Assaf; Small, Jennifer L; Britch, Seth C; Tucker, Compton J; Pak, Edwin W; Reynolds, Curt A; Crutchfield, James; Linthicum, Kenneth J

2014-01-01

We document significant worldwide weather anomalies that affected agriculture and vector-borne disease outbreaks during the 2010-2012 period. We utilized 2000-2012 vegetation index and land surface temperature data from NASA's satellite-based Moderate Resolution Imaging Spectroradiometer (MODIS) to map the magnitude and extent of these anomalies for diverse regions including the continental United States, Russia, East Africa, Southern Africa, and Australia. We demonstrate that shifts in temperature and/or precipitation have significant impacts on vegetation patterns with attendant consequences for agriculture and public health. Weather extremes resulted in excessive rainfall and flooding as well as severe drought, which caused ∼10 to 80% variation in major agricultural commodity production (including wheat, corn, cotton, sorghum) and created exceptional conditions for extensive mosquito-borne disease outbreaks of dengue, Rift Valley fever, Murray Valley encephalitis, and West Nile virus disease. Analysis of MODIS data provided a standardized method for quantifying the extreme weather anomalies observed during this period. Assessments of land surface conditions from satellite-based systems such as MODIS can be a valuable tool in national, regional, and global weather impact determinations.

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

NASA Technical Reports Server (NTRS)

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

1987-01-01

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

Atmospheric Diabatic Heating in Different Weather States and the General Circulation

NASA Technical Reports Server (NTRS)

Rossow, William B.; Zhang, Yuanchong; Tselioudis, George

2016-01-01

Analysis of multiple global satellite products identifies distinctive weather states of the atmosphere from the mesoscale pattern of cloud properties and quantifies the associated diabatic heating/cooling by radiative flux divergence, precipitation, and surface sensible heat flux. The results show that the forcing for the atmospheric general circulation is a very dynamic process, varying strongly at weather space-time scales, comprising relatively infrequent, strong heating events by ''stormy'' weather and more nearly continuous, weak cooling by ''fair'' weather. Such behavior undercuts the value of analyses of time-averaged energy exchanges in observations or numerical models. It is proposed that an analysis of the joint time-related variations of the global weather states and the general circulation on weather space-time scales might be used to establish useful ''feedback like'' relationships between cloud processes and the large-scale circulation.

Walker Branch Throughfall Displacement Experiment Data Report: Site Characterization, System Performance, Weather, Species Composition, and Growth (NDP-078 and 078A)

DOE Data Explorer

Cushman, Robert M. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States), Carbon Dioxide Information Analysis Center, Environmental Sciences Division; Hanson, Paul J. [Oak Ridge National Laboratory, Oak Ridge, TN (USA), Environmental Sciences Division; Todd, Donald E. [Oak Ridge National Laboratory, Oak Ridge, TN (USA), Environmental Sciences Division; Riggs, Jeffery S. [Oak Ridge National Laboratory, Oak Ridge, TN (USA), Instrumentation and Controls Division; Wolfe, Mark E. [Tennessee Valley Authority, Norris, TN (USA); O'Neill, Elizabeth G. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States), Environmental Sciences Division

2001-07-01

This numeric data package provides data sets, and accompanying documentation, on site characterization, system performance, weather, species composition, and growth for the Throughfall Displacement Experiment, which was established in the Walker Branch Watershed of East Tennessee to provide data on the responses of forests to altered precipitation regimes. The specific data sets include soil water content and potential, coarse fraction of the soil profile, litter layer temperature, soil temperature, monthly weather, daily weather, hourly weather, species composition of trees and saplings, mature tree and sapling annual growth, and relative leaf area index. Fortran and SAS(TM) access codes are provided to read the ASCII data files.

Observing System Forecast Experiments at the DAO

NASA Technical Reports Server (NTRS)

Atlas, Robert

2001-01-01

Since the advent of meteorological satellites in the 1960's, numerous experiments have been conducted in order to evaluate the impact of these and other data on atmospheric analysis and prediction. Such studies have included both OSE'S and OSSE's. The OSE's were conducted to evaluate the impact of specific observations or classes of observations on analyses and forecasts. Such experiments have been performed for selected types of conventional data and for various satellite data sets as they became available. (See for example the 1989 ECMWF/EUMETSAT workshop proceedings on "The use of satellite data in operational numerical weather prediction" and the references contained therein.) The ODYSSEY were conducted to evaluate the potential for future observing systems to improve Numerical Weather Prediction NWP and to plan for the Global Weather Experiment and more recently for EVANS (Atlas et al., 1985a; Arnold and Day, 1986; Hoffman et al., 1990). In addition, OSSE's have been run to evaluate trade-offs in the design of observing systems and observing networks (Atlas and Emmitt, 1991; Rohaly and Krishnamurti, 1993), and to test new methodology for data assimilation (Atlas and Bloom, 1989).

Atmospheric Electrical Activity and the Prospects for Improving Short-Term, Weather Forcasting

NASA Technical Reports Server (NTRS)

Goodman, Steven J.

2003-01-01

How might lightning measurements be used to improve short-term (0-24 hr) weather forecasting? We examine this question under two different prediction strategies. These include integration of lightning data into short-term forecasts (nowcasts) of convective (including severe) weather hazards and the assimilation of lightning data into cloud-resolving numerical weather prediction models. In each strategy we define specific metrics of forecast improvement and a progress assessment. We also address the conventional observing system deficiencies and potential gap-filling information that can be addressed through the use of the lightning measurement.

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

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

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

Molenkamp, C.R.; Grossman, A.

1999-12-20

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

Global Climate Teleconnections to Forecast Increased Risk of Vector-Borne Animal and Human Disease Transmission

USDA-ARS?s Scientific Manuscript database

We willexamine how climate teleconnect ions and variability impact vector biology and vector borne disease ecology, and demonstrate that global climate monitoring can be used to anticipate and forecast epidemics and epizootics. In this context we willexamine significant worldwide weather anomalies t...

Soil erosion on upland areas by rainfall and overland flow

USDA-ARS?s Scientific Manuscript database

Soil erosion in agricultural watersheds is a systemic problem that has plagued mankind ever since the practice of agriculture began some 9,000 years ago. It is a worldwide problem, the severity of which varies from location to location depending on weather, soil type, topography, cropping practices,...

Exploring Geology on the World-Wide Web--Volcanoes and Volcanism.

ERIC Educational Resources Information Center

Schimmrich, Steven Henry; Gore, Pamela J. W.

1996-01-01

Focuses on sites on the World Wide Web that offer information about volcanoes. Web sites are classified into areas of Global Volcano Information, Volcanoes in Hawaii, Volcanoes in Alaska, Volcanoes in the Cascades, European and Icelandic Volcanoes, Extraterrestrial Volcanism, Volcanic Ash and Weather, and Volcano Resource Directories. Suggestions…

Getting into ENSO

ERIC Educational Resources Information Center

Lee, Hyonyong; Jax, Dan

2004-01-01

To develop scientific literacy in today's global era, however, it is important that students learn about interactions within the Earth's systems worldwide. A unit exploring El Nino and La Nina-phenomena that can result in extreme weather events in locations all around the world-can help bridge this gap and broaden students awareness of global…

A threshold-based weather model for predicting stripe rust infection in winter wheat

USDA-ARS?s Scientific Manuscript database

Wheat stripe rust (WSR) (caused by Puccinia striiformis sp. tritici) is a major threat in most wheat growing regions worldwide, with potential to inflict regular yield losses when environmental conditions are favorable. We propose a threshold-based disease-forecasting model using a stepwise modeling...

Recent examples of mesoscale numerical forecasts of severe weather events along the east coast

NASA Technical Reports Server (NTRS)

Kocin, P. J.; Uccellini, L. W.; Zack, J. W.; Kaplan, M. L.

1984-01-01

Mesoscale numerical forecasts utilizing the Mesoscale Atmospheric Simulation System (MASS) are documented for two East Coast severe weather events. The two events are the thunderstorm and heavy snow bursts in the Washington, D.C. - Baltimore, MD region on 8 March 1984 and the devastating tornado outbreak across North and South Carolina on 28 March 1984. The forecasts are presented to demonstrate the ability of the model to simulate dynamical interactions and diabatic processes and to note some of the problems encountered when using mesoscale models for day-to-day forecasting.

How accurate are the weather forecasts for Bierun (southern Poland)?

NASA Astrophysics Data System (ADS)

Gawor, J.

2012-04-01

Weather forecast accuracy has increased in recent times mainly thanks to significant development of numerical weather prediction models. Despite the improvements, the forecasts should be verified to control their quality. The evaluation of forecast accuracy can also be an interesting learning activity for students. It joins natural curiosity about everyday weather and scientific process skills: problem solving, database technologies, graph construction and graphical analysis. The examination of the weather forecasts has been taken by a group of 14-year-old students from Bierun (southern Poland). They participate in the GLOBE program to develop inquiry-based investigations of the local environment. For the atmospheric research the automatic weather station is used. The observed data were compared with corresponding forecasts produced by two numerical weather prediction models, i.e. COAMPS (Coupled Ocean/Atmosphere Mesoscale Prediction System) developed by Naval Research Laboratory Monterey, USA; it runs operationally at the Interdisciplinary Centre for Mathematical and Computational Modelling in Warsaw, Poland and COSMO (The Consortium for Small-scale Modelling) used by the Polish Institute of Meteorology and Water Management. The analysed data included air temperature, precipitation, wind speed, wind chill and sea level pressure. The prediction periods from 0 to 24 hours (Day 1) and from 24 to 48 hours (Day 2) were considered. The verification statistics that are commonly used in meteorology have been applied: mean error, also known as bias, for continuous data and a 2x2 contingency table to get the hit rate and false alarm ratio for a few precipitation thresholds. The results of the aforementioned activity became an interesting basis for discussion. The most important topics are: 1) to what extent can we rely on the weather forecasts? 2) How accurate are the forecasts for two considered time ranges? 3) Which precipitation threshold is the most predictable? 4) Why are some weather elements easier to verify than others? 5) What factors may contribute to the quality of the weather forecast?

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

Ensemble flare forecasting: using numerical weather prediction techniques to improve space weather operations

NASA Astrophysics Data System (ADS)

Murray, S.; Guerra, J. A.

2017-12-01

One essential component of operational space weather forecasting is the prediction of solar flares. Early flare forecasting work focused on statistical methods based on historical flaring rates, but more complex machine learning methods have been developed in recent years. A multitude of flare forecasting methods are now available, however it is still unclear which of these methods performs best, and none are substantially better than climatological forecasts. Current operational space weather centres cannot rely on automated methods, and generally use statistical forecasts with a little human intervention. Space weather researchers are increasingly looking towards methods used in terrestrial weather to improve current forecasting techniques. Ensemble forecasting has been used in numerical weather prediction for many years as a way to combine different predictions in order to obtain a more accurate result. It has proved useful in areas such as magnetospheric modelling and coronal mass ejection arrival analysis, however has not yet been implemented in operational flare forecasting. Here we construct ensemble forecasts for major solar flares by linearly combining the full-disk probabilistic forecasts from a group of operational forecasting methods (ASSA, ASAP, MAG4, MOSWOC, NOAA, and Solar Monitor). Forecasts from each method are weighted by a factor that accounts for the method's ability to predict previous events, and several performance metrics (both probabilistic and categorical) are considered. The results provide space weather forecasters with a set of parameters (combination weights, thresholds) that allow them to select the most appropriate values for constructing the 'best' ensemble forecast probability value, according to the performance metric of their choice. In this way different forecasts can be made to fit different end-user needs.

Uncertainty Forecasts Improve Weather-Related Decisions and Attenuate the Effects of Forecast Error

ERIC Educational Resources Information Center

Joslyn, Susan L.; LeClerc, Jared E.

2012-01-01

Although uncertainty is inherent in weather forecasts, explicit numeric uncertainty estimates are rarely included in public forecasts for fear that they will be misunderstood. Of particular concern are situations in which precautionary action is required at low probabilities, often the case with severe events. At present, a categorical weather…

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

PubMed Central

Palmer, T. N.

2014-01-01

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

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

PubMed

Palmer, T N

2014-06-28

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

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

NASA Image and Video Library

2014-09-05

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

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

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

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

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

Physical and mechanical properties of PLA, and their functions in widespread applications - A comprehensive review.

PubMed

Farah, Shady; Anderson, Daniel G; Langer, Robert

2016-12-15

Poly(lactic acid) (PLA), so far, is the most extensively researched and utilized biodegradable aliphatic polyester in human history. Due to its merits, PLA is a leading biomaterial for numerous applications in medicine as well as in industry replacing conventional petrochemical-based polymers. The main purpose of this review is to elaborate the mechanical and physical properties that affect its stability, processability, degradation, PLA-other polymers immiscibility, aging and recyclability, and therefore its potential suitability to fulfill specific application requirements. This review also summarizes variations in these properties during PLA processing (i.e. thermal degradation and recyclability), biodegradation, packaging and sterilization, and aging (i.e. weathering and hygrothermal). In addition, we discuss up-to-date strategies for PLA properties improvements including components and plasticizer blending, nucleation agent addition, and PLA modifications and nanoformulations. Incorporating better understanding of the role of these properties with available improvement strategies is the key for successful utilization of PLA and its copolymers/composites/blends to maximize their fit with worldwide application needs. Copyright © 2016 Elsevier B.V. All rights reserved.

Rainfall thresholds as a landslide indicator for engineered slopes on the Irish Rail network

NASA Astrophysics Data System (ADS)

Martinović, Karlo; Gavin, Kenneth; Reale, Cormac; Mangan, Cathal

2018-04-01

Rainfall thresholds express the minimum levels of rainfall that need to be reached or exceeded in order for landslides to occur in a particular area. They are a common tool in expressing the temporal portion of landslide hazard analysis. Numerous rainfall thresholds have been developed for different areas worldwide, however none of these are focused on landslides occurring on the engineered slopes on transport infrastructure networks. This paper uses empirical method to develop the rainfall thresholds for landslides on the Irish Rail network earthworks. For comparison, rainfall thresholds are also developed for natural terrain in Ireland. The results show that particular thresholds involving relatively low rainfall intensities are applicable for Ireland, owing to the specific climate. Furthermore, the comparison shows that rainfall thresholds for engineered slopes are lower than those for landslides occurring on the natural terrain. This has severe implications as it indicates that there is a significant risk involved when using generic weather alerts (developed largely for natural terrain) for infrastructure management, and showcases the need for developing railway and road specific rainfall thresholds for landslides.

Are atmospheric updrafts a key to unlocking climate forcing and sensitivity?

DOE PAGES

Donner, Leo J.; O'Brien, Travis A.; Rieger, Daniel; ...

2016-10-20

Both climate forcing and climate sensitivity persist as stubborn uncertainties limiting the extent to which climate models can provide actionable scientific scenarios for climate change. A key, explicit control on cloud–aerosol interactions, the largest uncertainty in climate forcing, is the vertical velocity of cloud-scale updrafts. Model-based studies of climate sensitivity indicate that convective entrainment, which is closely related to updraft speeds, is an important control on climate sensitivity. Updraft vertical velocities also drive many physical processes essential to numerical weather prediction. Vertical velocities and their role in atmospheric physical processes have been given very limited attention in models for climatemore » and numerical weather prediction. The relevant physical scales range down to tens of meters and are thus frequently sub-grid and require parameterization. Many state-of-science convection parameterizations provide mass fluxes without specifying Vertical velocities and their role in atmospheric physical processes have been given very limited attention in models for climate and numerical weather prediction. The relevant physical scales range down to tens of meters and are thus frequently sub-grid and require parameterization. Many state-of-science convection parameterizations provide mass fluxes without specifying vs in climate models may capture this behavior, but it has not been accounted for when parameterizing cloud and precipitation processes in current models. New observations of convective vertical velocities offer a potentially promising path toward developing process-level cloud models and parameterizations for climate and numerical weather prediction. Taking account of the scale dependence of resolved vertical velocities offers a path to matching cloud-scale physical processes and their driving dynamics more realistically, with a prospect of reduced uncertainty in both climate forcing and sensitivity.« less

An Overview of Numerical Weather Prediction on Various Scales

NASA Astrophysics Data System (ADS)

Bao, J.-W.

2009-04-01

The increasing public need for detailed weather forecasts, along with the advances in computer technology, has motivated many research institutes and national weather forecasting centers to develop and run global as well as regional numerical weather prediction (NWP) models at high resolutions (i.e., with horizontal resolutions of ~10 km or higher for global models and 1 km or higher for regional models, and with ~60 vertical levels or higher). The need for running NWP models at high horizontal and vertical resolutions requires the implementation of non-hydrostatic dynamic core with a choice of horizontal grid configurations and vertical coordinates that are appropriate for high resolutions. Development of advanced numerics will also be needed for high resolution global and regional models, in particular, when the models are applied to transport problems and air quality applications. In addition to the challenges in numerics, the NWP community is also facing the challenges of developing physics parameterizations that are well suited for high-resolution NWP models. For example, when NWP models are run at resolutions of ~5 km or higher, the use of much more detailed microphysics parameterizations than those currently used in NWP model will become important. Another example is that regional NWP models at ~1 km or higher only partially resolve convective energy containing eddies in the lower troposphere. Parameterizations to account for the subgrid diffusion associated with unresolved turbulence still need to be developed. Further, physically sound parameterizations for air-sea interaction will be a critical component for tropical NWP models, particularly for hurricane predictions models. In this review presentation, the above issues will be elaborated on and the approaches to address them will be discussed.

Are atmospheric updrafts a key to unlocking climate forcing and sensitivity?

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

Donner, Leo J.; O'Brien, Travis A.; Rieger, Daniel

Both climate forcing and climate sensitivity persist as stubborn uncertainties limiting the extent to which climate models can provide actionable scientific scenarios for climate change. A key, explicit control on cloud–aerosol interactions, the largest uncertainty in climate forcing, is the vertical velocity of cloud-scale updrafts. Model-based studies of climate sensitivity indicate that convective entrainment, which is closely related to updraft speeds, is an important control on climate sensitivity. Updraft vertical velocities also drive many physical processes essential to numerical weather prediction. Vertical velocities and their role in atmospheric physical processes have been given very limited attention in models for climatemore » and numerical weather prediction. The relevant physical scales range down to tens of meters and are thus frequently sub-grid and require parameterization. Many state-of-science convection parameterizations provide mass fluxes without specifying Vertical velocities and their role in atmospheric physical processes have been given very limited attention in models for climate and numerical weather prediction. The relevant physical scales range down to tens of meters and are thus frequently sub-grid and require parameterization. Many state-of-science convection parameterizations provide mass fluxes without specifying vs in climate models may capture this behavior, but it has not been accounted for when parameterizing cloud and precipitation processes in current models. New observations of convective vertical velocities offer a potentially promising path toward developing process-level cloud models and parameterizations for climate and numerical weather prediction. Taking account of the scale dependence of resolved vertical velocities offers a path to matching cloud-scale physical processes and their driving dynamics more realistically, with a prospect of reduced uncertainty in both climate forcing and sensitivity.« less

Impact of the 4 April 2014 Saharan dust outbreak on the photovoltaic power generation in Germany

NASA Astrophysics Data System (ADS)

Rieger, Daniel; Steiner, Andrea; Bachmann, Vanessa; Gasch, Philipp; Förstner, Jochen; Deetz, Konrad; Vogel, Bernhard; Vogel, Heike

2017-11-01

The importance for reliable forecasts of incoming solar radiation is growing rapidly, especially for those countries with an increasing share in photovoltaic (PV) power production. The reliability of solar radiation forecasts depends mainly on the representation of clouds and aerosol particles absorbing and scattering radiation. Especially under extreme aerosol conditions, numerical weather prediction has a systematic bias in the solar radiation forecast. This is caused by the design of numerical weather prediction models, which typically account for the direct impact of aerosol particles on radiation using climatological mean values and the impact on cloud formation assuming spatially and temporally homogeneous aerosol concentrations. These model deficiencies in turn can lead to significant economic losses under extreme aerosol conditions. For Germany, Saharan dust outbreaks occurring 5 to 15 times per year for several days each are prominent examples for conditions, under which numerical weather prediction struggles to forecast solar radiation adequately. We investigate the impact of mineral dust on the PV-power generation during a Saharan dust outbreak over Germany on 4 April 2014 using ICON-ART, which is the current German numerical weather prediction model extended by modules accounting for trace substances and related feedback processes. We find an overall improvement of the PV-power forecast for 65 % of the pyranometer stations in Germany. Of the nine stations with very high differences between forecast and measurement, eight stations show an improvement. Furthermore, we quantify the direct radiative effects and indirect radiative effects of mineral dust. For our study, direct effects account for 64 %, indirect effects for 20 % and synergistic interaction effects for 16 % of the differences between the forecast including mineral dust radiative effects and the forecast neglecting mineral dust.

Operational early warning platform for extreme meteorological events

NASA Astrophysics Data System (ADS)

Mühr, Bernhard; Kunz, Michael

2015-04-01

Operational early warning platform for extreme meteorological events Most natural disasters are related to extreme weather events (e.g. typhoons); weather conditions, however, are also highly relevant for humanitarian and disaster relief operations during and after other natural disaster like earthquakes. The internet service "Wettergefahren-Frühwarnung" (WF) provides various information on extreme weather events, especially when these events are associated with a high potential for large damage. The main focus of the platform is on Central Europe, but major events are also monitored worldwide on a daily routine. WF provides high-resolution forecast maps for many weather parameters which allow detailed and reliable predictions about weather conditions during the next days in the affected areas. The WF service became operational in February 2004 and is part of the Center for Disaster Management and Risk Reduction Technology (CEDIM) since 2007. At the end of 2011, CEDIM embarked a new type of interdisciplinary disaster research termed as forensic disaster analysis (FDA) in near real time. In case of an imminent extreme weather event WF plays an important role in CEDIM's FDA group. It provides early and precise information which are always available and updated several times during a day and gives advice and assists with articles and reports on extreme events.

A Data Assimilation System For Operational Weather Forecast In Galicia Region (nw Spain)

NASA Astrophysics Data System (ADS)

Balseiro, C. F.; Souto, M. J.; Pérez-Muñuzuri, V.; Brewster, K.; Xue, M.

Regional weather forecast models, such as the Advanced Regional Prediction System (ARPS), over complex environments with varying local influences require an accurate meteorological analysis that should include all local meteorological measurements available. In this work, the ARPS Data Analysis System (ADAS) (Xue et al. 2001) is applied as a three-dimensional weather analysis tool to include surface station and rawinsonde data with the NCEP AVN forecasts as the analysis background. Currently in ADAS, a set of five meteorological variables are considered during the analysis: horizontal grid-relative wind components, pressure, potential temperature and spe- cific humidity. The analysis is used for high resolution numerical weather prediction for the Galicia region. The analysis method used in ADAS is based on the successive corrective scheme of Bratseth (1986), which asymptotically approaches the result of a statistical (optimal) interpolation, but at lower computational cost. As in the optimal interpolation scheme, the Bratseth interpolation method can take into account the rel- ative error between background and observational data, therefore they are relatively insensitive to large variations in data density and can integrate data of mixed accuracy. This method can be applied economically in an operational setting, providing signifi- cant improvement over the background model forecast as well as any analysis without high-resolution local observations. A one-way nesting is applied for weather forecast in Galicia region, and the use of this assimilation system in both domains shows better results not only in initial conditions but also in all forecast periods. Bratseth, A.M. (1986): "Statistical interpolation by means of successive corrections." Tellus, 38A, 439-447. Souto, M. J., Balseiro, C. F., Pérez-Muñuzuri, V., Xue, M. Brewster, K., (2001): "Im- pact of cloud analysis on numerical weather prediction in the galician region of Spain". Submitted to Journal of Applied Meteorology. Xue, M., Wang. D., Gao, J., Brewster, K, Droegemeier, K. K., (2001): "The Advanced Regional Prediction System (ARPS), storm-scale numerical weather prediction and data assimilation". Meteor. Atmos Physics. Accepted

New, Improved Bulk-microphysical Schemes for Studying Precipitation Processes in WRF. Part 1; Comparisons with Other Schemes

NASA Technical Reports Server (NTRS)

Tao, W.-K.; Shi, J.; Chen, S. S> ; Lang, S.; Hong, S.-Y.; Thompson, G.; Peters-Lidard, C.; Hou, A.; Braun, S.;

Wintertime component of the THORPEX Pacific-Asian Regional Campaign (T-PARC)

NASA Astrophysics Data System (ADS)

Song, Y.; Toth, Z.; Asuma, Y.; Reynolds, C.; Lngland, R.; Szunyogh, I.; Colle, B.; Chang, E.; Doyle, C.; Kats, A.

2009-04-01

The winter component of the T-PARC is an international field project that aims at improving high impact weather event forecasts for North America. The main objective is to understand how perturbations from the tropics, Eurasia and polar fronts travel through waveguide and turn into high impact weather events. Through adaptive observations by using manned aircrafts (NOAA G-IV and US Air force C-130s) and Russian rawinsonde network over data sparse regions, it is expected that accurate initial conditions will improve the numerical weather forecasts. Non-adaptive aircraft measurements over the Pacific Rim and part of India are also deployed through E-AMDAR program, which is expected to improve the background field over Asia where perturbations are initiated. The campaign is led by NOAA and joined by agencies and universities from US, Canada, Mexico, Japan, ECWMF, and Russia. While most observational data will be assimilated by operational centers to improve real time numerical weather predictions, post field studies will focus on aspects such as: data impact on forecast and analysis, dry and moist processes that affect the formation and propagation of perturbations, meso-scale storm structure, error growth, forecast "busts" under certain atmospheric regimes, and socio-economic applications such as costs and benefits of improved forecasts and their use by the public for high impact weather events. In particular, a Winter Olympics demonstration project (February 12 - February 28) is expected to be a test bed during winter T-PARC for real user outreach and application purposes. Effectiveness of existing targeting methods as well as new targeting methods in the 3-5 day lead time range will be pursued and other aspects related to data assimilation and numerical forecasts (both deterministic and ensemble forecasts) will be investigated within this project as well.

Toward understanding molecular mechanisms of durable and non-durable resistance to stripe rust in wheat

USDA-ARS?s Scientific Manuscript database

Stripe rust of wheat, caused by Puccinia striiformis f. sp. tritici, continues causing severe damage worldwide. Durable resistance is a key for sustainable control of the disease. High-temperature adult-plant (HTAP) resistance, which expresses when weather becomes warm and plants grow old, has bee...

Ensemble forecasting of short-term system scale irrigation demands using real-time flow data and numerical weather predictions

NASA Astrophysics Data System (ADS)

Perera, Kushan C.; Western, Andrew W.; Robertson, David E.; George, Biju; Nawarathna, Bandara

2016-06-01

Irrigation demands fluctuate in response to weather variations and a range of irrigation management decisions, which creates challenges for water supply system operators. This paper develops a method for real-time ensemble forecasting of irrigation demand and applies it to irrigation command areas of various sizes for lead times of 1 to 5 days. The ensemble forecasts are based on a deterministic time series model coupled with ensemble representations of the various inputs to that model. Forecast inputs include past flow, precipitation, and potential evapotranspiration. These inputs are variously derived from flow observations from a modernized irrigation delivery system; short-term weather forecasts derived from numerical weather prediction models and observed weather data available from automatic weather stations. The predictive performance for the ensemble spread of irrigation demand was quantified using rank histograms, the mean continuous rank probability score (CRPS), the mean CRPS reliability and the temporal mean of the ensemble root mean squared error (MRMSE). The mean forecast was evaluated using root mean squared error (RMSE), Nash-Sutcliffe model efficiency (NSE) and bias. The NSE values for evaluation periods ranged between 0.96 (1 day lead time, whole study area) and 0.42 (5 days lead time, smallest command area). Rank histograms and comparison of MRMSE, mean CRPS, mean CRPS reliability and RMSE indicated that the ensemble spread is generally a reliable representation of the forecast uncertainty for short lead times but underestimates the uncertainty for long lead times.

Climate change and health in Israel: adaptation policies for extreme weather events.

PubMed

Green, Manfred S; Pri-Or, Noemie Groag; Capeluto, Guedi; Epstein, Yoram; Paz, Shlomit

2013-06-27

Climatic changes have increased the world-wide frequency of extreme weather events such as heat waves, cold spells, floods, storms and droughts. These extreme events potentially affect the health status of millions of people, increasing disease and death. Since mitigation of climate change is a long and complex process, emphasis has recently been placed on the measures required for adaptation. Although the principles underlying these measures are universal, preparedness plans and policies need to be tailored to local conditions. In this paper, we conducted a review of the literature on the possible health consequences of extreme weather events in Israel, where the conditions are characteristic of the Mediterranean region. Strong evidence indicates that the frequency and duration of several types of extreme weather events are increasing in the Mediterranean Basin, including Israel. We examined the public health policy implications for adaptation to climate change in the region, and proposed public health adaptation policy options. Preparedness for the public health impact of increased extreme weather events is still relatively limited and clear public health policies are urgently needed. These include improved early warning and monitoring systems, preparedness of the health system, educational programs and the living environment. Regional collaboration should be a priority.

Recent Weather Extremes and Impacts on Agricultural Production and Vector-Borne Disease Outbreak Patterns

PubMed Central

Anyamba, Assaf; Small, Jennifer L.; Britch, Seth C.; Tucker, Compton J.; Pak, Edwin W.; Reynolds, Curt A.; Crutchfield, James; Linthicum, Kenneth J.

2014-01-01

We document significant worldwide weather anomalies that affected agriculture and vector-borne disease outbreaks during the 2010–2012 period. We utilized 2000–2012 vegetation index and land surface temperature data from NASA's satellite-based Moderate Resolution Imaging Spectroradiometer (MODIS) to map the magnitude and extent of these anomalies for diverse regions including the continental United States, Russia, East Africa, Southern Africa, and Australia. We demonstrate that shifts in temperature and/or precipitation have significant impacts on vegetation patterns with attendant consequences for agriculture and public health. Weather extremes resulted in excessive rainfall and flooding as well as severe drought, which caused ∼10 to 80% variation in major agricultural commodity production (including wheat, corn, cotton, sorghum) and created exceptional conditions for extensive mosquito-borne disease outbreaks of dengue, Rift Valley fever, Murray Valley encephalitis, and West Nile virus disease. Analysis of MODIS data provided a standardized method for quantifying the extreme weather anomalies observed during this period. Assessments of land surface conditions from satellite-based systems such as MODIS can be a valuable tool in national, regional, and global weather impact determinations. PMID:24658301

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

NASA Astrophysics Data System (ADS)

Pu, Z.; Yu, Y.

2016-12-01

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

Memory efficient solution of the primitive equations for numerical weather prediction on the CYBER 205

NASA Technical Reports Server (NTRS)

Tuccillo, J. J.

1984-01-01

Numerical Weather Prediction (NWP), for both operational and research purposes, requires only fast computational speed but also large memory. A technique for solving the Primitive Equations for atmospheric motion on the CYBER 205, as implemented in the Mesoscale Atmospheric Simulation System, which is fully vectorized and requires substantially less memory than other techniques such as the Leapfrog or Adams-Bashforth Schemes is discussed. The technique presented uses the Euler-Backard time marching scheme. Also discussed are several techniques for reducing computational time of the model by replacing slow intrinsic routines by faster algorithms which use only hardware vector instructions.

Operational numerical weather prediction on the CYBER 205 at the National Meteorological Center

NASA Technical Reports Server (NTRS)

Deaven, D.

1984-01-01

The Development Division of the National Meteorological Center (NMC), having the responsibility of maintaining and developing the numerical weather forecasting systems of the center, is discussed. Because of the mission of NMC data products must be produced reliably and on time twice daily free of surprises for forecasters. Personnel of Development Division are in a rather unique situation. They must develop new advanced techniques for numerical analysis and prediction utilizing current state-of-the-art techniques, and implement them in an operational fashion without damaging the operations of the center. With the computational speeds and resources now available from the CYBER 205, Development Division Personnel will be able to introduce advanced analysis and prediction techniques into the operational job suite without disrupting the daily schedule. The capabilities of the CYBER 205 are discussed.

Predicting the magnetospheric plasma of weather

NASA Technical Reports Server (NTRS)

Dawson, John M.

1986-01-01

The prediction of the plasma environment in time, the plasma weather, is discussed. It is important to be able to predict when large magnetic storms will produce auroras, which will affect the space station operating in low orbit, and what precautions to take both for personnel and sensitive control (computer) equipment onboard. It is also important to start to establish a set of plasma weather records and a record of the ability to predict this weather. A successful forecasting system requires a set of satellite weather stations to provide data from which predictions can be made and a set of plasma weather codes capable of accurately forecasting the status of the Earth's magnetosphere. A numerical magnetohydrodynamic fluid model which is used to model the flow in the magnetosphere, the currents flowing into and out of the auroral regions, the magnetopause, the bow shock location and the magnetotail of the Earth is discussed.

Mining key elements for severe convection prediction based on CNN

NASA Astrophysics Data System (ADS)

Liu, Ming; Pan, Ning; Zhang, Changan; Sha, Hongzhou; Zhang, Bolei; Liu, Liang; Zhang, Meng

2017-04-01

Severe convective weather is a kind of weather disasters accompanied by heavy rainfall, gust wind, hail, etc. Along with recent developments on remote sensing and numerical modeling, there are high-volume and long-term observational and modeling data accumulated to capture massive severe convective events over particular areas and time periods. With those high-volume and high-variety weather data, most of the existing studies and methods carry out the dynamical laws, cause analysis, potential rule study, and prediction enhancement by utilizing the governing equations from fluid dynamics and thermodynamics. In this study, a key-element mining method is proposed for severe convection prediction based on convolution neural network (CNN). It aims to identify the key areas and key elements from huge amounts of historical weather data including conventional measurements, weather radar, satellite, so as numerical modeling and/or reanalysis data. Under this manner, the machine-learning based method could help the human forecasters on their decision-making on operational weather forecasts on severe convective weathers by extracting key information from the real-time and historical weather big data. In this paper, it first utilizes computer vision technology to complete the data preprocessing work of the meteorological variables. Then, it utilizes the information such as radar map and expert knowledge to annotate all images automatically. And finally, by using CNN model, it cloud analyze and evaluate each weather elements (e.g., particular variables, patterns, features, etc.), and identify key areas of those critical weather elements, then help forecasters quickly screen out the key elements from huge amounts of observation data by current weather conditions. Based on the rich weather measurement and model data (up to 10 years) over Fujian province in China, where the severe convective weathers are very active during the summer months, experimental tests are conducted with the new machine-learning method via CNN models. Based on the analysis of those experimental results and case studies, the proposed new method have below benefits for the severe convection prediction: (1) helping forecasters to narrow down the scope of analysis and saves lead-time for those high-impact severe convection; (2) performing huge amount of weather big data by machine learning methods rather relying on traditional theory and knowledge, which provide new method to explore and quantify the severe convective weathers; (3) providing machine learning based end-to-end analysis and processing ability with considerable scalability on data volumes, and accomplishing the analysis work without human intervention.

Space Weather: What is it, and Why Should a Meteorologist Care?

NASA Technical Reports Server (NTRS)

SaintCyr, Chris; Murtagh, Bill

2008-01-01

"Space weather" is a term coined almost 15 years ago to describe environmental conditions ABOVE Earth's atmosphere that affect satellites and astronauts. As society has become more dependent on technology, we nave found that space weather conditions increasingly affect numerous commercial and infrastructure sectors: airline operations, the precision positioning industry, and the electric power grid, to name a few. Similar to meteorology where "weather" often refers to severe conditions, "space weather" includes geomagnetic storms, radiation storms, and radio blackouts. But almost all space weather conditions begin at the Sun--our middle-age, magnetically-variable star. At NASA, the science behind space weather takes place in the Heliophysics Division. The Space Weather Prediction Center in Boulder, Colorado, is manned jointly by NCAA and US Air Force personnel, and it provides space weather alerts and warnings for disturbances that can affect people and equipment working in space and on Earth. Organizationally, it resides in NOAA's National Weather Service as one of the National Centers for Environmental Prediction. In this seminar we hope to give the audience a brief introduction to the causes of space weather, discuss some of the effects, and describe the state of the art in forecasting. Our goal is to highlight that meteorologists are increasingly becoming the "first responders" to questions about space weather causes and effects.

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.

Numerical Model Simulation of Atmosphere above A.C. Airport

NASA Astrophysics Data System (ADS)

Lutes, Tiffany; Trout, Joseph

2014-03-01

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

Training the next generation of scientists in Weather Forecasting: new approaches with real models

NASA Astrophysics Data System (ADS)

Carver, Glenn; Váňa, Filip; Siemen, Stephan; Kertesz, Sandor; Keeley, Sarah

2014-05-01

The European Centre for Medium Range Weather Forecasts operationally produce medium range forecasts using what is internationally acknowledged as the world leading global weather forecast model. Future development of this scientifically advanced model relies on a continued availability of experts in the field of meteorological science and with high-level software skills. ECMWF therefore has a vested interest in young scientists and University graduates developing the necessary skills in numerical weather prediction including both scientific and technical aspects. The OpenIFS project at ECMWF maintains a portable version of the ECMWF forecast model (known as IFS) for use in education and research at Universities, National Meteorological Services and other research and education organisations. OpenIFS models can be run on desktop or high performance computers to produce weather forecasts in a similar way to the operational forecasts at ECMWF. ECMWF also provide the Metview desktop application, a modern, graphical, and easy to use tool for analysing and visualising forecasts that is routinely used by scientists and forecasters at ECMWF and other institutions. The combination of Metview with the OpenIFS models has the potential to deliver classroom-friendly tools allowing students to apply their theoretical knowledge to real-world examples using a world-leading weather forecasting model. In this paper we will describe how the OpenIFS model has been used for teaching. We describe the use of Linux based 'virtual machines' pre-packaged on USB sticks that support a technically easy and safe way of providing 'classroom-on-a-stick' learning environments for advanced training in numerical weather prediction. We welcome discussions with interested parties.

A model for predicting onset of stagonospora nodorum blotch in winter wheat based on pre-planting and weather factors

USDA-ARS?s Scientific Manuscript database

Stagonospora nodorum blotch (SNB) is a serious disease of wheat worldwide, and it is prevalent on winter wheat in many eastern states. Management relies mainly on fungicide application after flag leaf emergence. The disease can occur prior to flag leaf emergence, however, the impact of the time of ...

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

None

Many storms around the world have roots in the Indian Ocean, where they are churned up by the atmospheric process called the Madden-Julian Oscillation (MJO). PNNL is working to unlock the secrets of the MJO, particularly how it initiates in the Indian Ocean every 30-60 days. Better prediction of the MJO will help resource managers, weather forecasters and people worldwide better prepare for its effects.

Climatic variability of a fire-weather index based on turbulent kinetic energy and the Haines Index

Treesearch

Warren E. Heilman; Xindi Bian

2010-01-01

Combining the Haines Index (HI) with near-surface turbulent kinetic energy (TKEs) through a product of the two values (HITKEs) has shown promise as an indicator of the atmospheric potential for extreme and erratic fire behavior in the U.S. Numerical simulations of fire-weather evolution during past wildland fire episodes in...

Severe storms and local weather research

NASA Technical Reports Server (NTRS)

1981-01-01

Developments in the use of space related techniques to understand storms and local weather are summarized. The observation of lightning, storm development, cloud development, mesoscale phenomena, and ageostrophic circulation are discussed. Data acquisition, analysis, and the development of improved sensor and computer systems capability are described. Signal processing and analysis and application of Doppler lidar data are discussed. Progress in numerous experiments is summarized.

Middle Atmosphere Program. Handbook for MAP, volume 20

NASA Technical Reports Server (NTRS)

Bowhill, S. A. (Editor); Edwards, B. (Editor)

1986-01-01

Various topics related to investigations of the middle atmosphere are discussed. Numerical weather prediction, performance characteristics of weather profiling radars, determination of gravity wave and turbulence parameters, case studies of gravity-wave propagation, turbulence and diffusion due to gravity waves, the climatology of gravity waves, mesosphere-stratosphere-troposphere radar, antenna arrays, and data management techniques are among the topics discussed.

Large-Scale Aerosol Modeling and Analysis

DTIC Science & Technology

2008-09-30

novel method of simultaneous real- time measurements of ice-nucleating particle concentrations and size- resolved chemical composition of individual...is to develop a practical predictive capability for visibility and weather effects of aerosol particles for the entire globe for timely use in...prediction follows that used in numerical weather prediction, namely real- time assessment for initialization of first-principles models. The Naval

Cloud-Based Numerical Weather Prediction for Near Real-Time Forecasting and Disaster Response

NASA Technical Reports Server (NTRS)

Molthan, Andrew; Case, Jonathan; Venners, Jason; Schroeder, Richard; Checchi, Milton; Zavodsky, Bradley; Limaye, Ashutosh; O'Brien, Raymond

2015-01-01

The use of cloud computing resources continues to grow within the public and private sector components of the weather enterprise as users become more familiar with cloud-computing concepts, and competition among service providers continues to reduce costs and other barriers to entry. Cloud resources can also provide capabilities similar to high-performance computing environments, supporting multi-node systems required for near real-time, regional weather predictions. Referred to as "Infrastructure as a Service", or IaaS, the use of cloud-based computing hardware in an on-demand payment system allows for rapid deployment of a modeling system in environments lacking access to a large, supercomputing infrastructure. Use of IaaS capabilities to support regional weather prediction may be of particular interest to developing countries that have not yet established large supercomputing resources, but would otherwise benefit from a regional weather forecasting capability. Recently, collaborators from NASA Marshall Space Flight Center and Ames Research Center have developed a scripted, on-demand capability for launching the NOAA/NWS Science and Training Resource Center (STRC) Environmental Modeling System (EMS), which includes pre-compiled binaries of the latest version of the Weather Research and Forecasting (WRF) model. The WRF-EMS provides scripting for downloading appropriate initial and boundary conditions from global models, along with higher-resolution vegetation, land surface, and sea surface temperature data sets provided by the NASA Short-term Prediction Research and Transition (SPoRT) Center. This presentation will provide an overview of the modeling system capabilities and benchmarks performed on the Amazon Elastic Compute Cloud (EC2) environment. In addition, the presentation will discuss future opportunities to deploy the system in support of weather prediction in developing countries supported by NASA's SERVIR Project, which provides capacity building activities in environmental monitoring and prediction across a growing number of regional hubs throughout the world. Capacity-building applications that extend numerical weather prediction to developing countries are intended to provide near real-time applications to benefit public health, safety, and economic interests, but may have a greater impact during disaster events by providing a source for local predictions of weather-related hazards, or impacts that local weather events may have during the recovery phase.

Numerical methods for comparing fresh and weathered oils by their FTIR spectra.

PubMed

Li, Jianfeng; Hibbert, D Brynn; Fuller, Stephen

2007-08-01

Four comparison statistics ('similarity indices') for the identification of the source of a petroleum oil spill based on the ASTM standard test method D3414 were investigated. Namely, (1) first difference correlation coefficient squared and (2) correlation coefficient squared, (3) first difference Euclidean cosine squared and (4) Euclidean cosine squared. For numerical comparison, an FTIR spectrum is divided into three regions, described as: fingerprint (900-700 cm(-1)), generic (1350-900 cm(-1)) and supplementary (1770-1685 cm(-1)), which are the same as the three major regions recommended by the ASTM standard. For fresh oil samples, each similarity index was able to distinguish between replicate independent spectra of the same sample and between different samples. In general, the two first difference-based indices worked better than their parent indices. To provide samples to reveal relationships between weathered and fresh oils, a simple artificial weathering procedure was carried out. Euclidean cosine and correlation coefficients both worked well to maintain identification of a match in the fingerprint region and the two first difference indices were better in the generic region. Receiver operating characteristic curves (true positive rate versus false positive rate) for decisions on matching using the fingerprint region showed two samples could be matched when the difference in weathering time was up to 7 days. Beyond this time the true positive rate falls and samples cannot be reliably matched. However, artificial weathering of a fresh source sample can aid the matching of a weathered sample to its real source from a pool of very similar candidates.

New efficient optimizing techniques for Kalman filters and numerical weather prediction models

NASA Astrophysics Data System (ADS)

Famelis, Ioannis; Galanis, George; Liakatas, Aristotelis

2016-06-01

The need for accurate local environmental predictions and simulations beyond the classical meteorological forecasts are increasing the last years due to the great number of applications that are directly or not affected: renewable energy resource assessment, natural hazards early warning systems, global warming and questions on the climate change can be listed among them. Within this framework the utilization of numerical weather and wave prediction systems in conjunction with advanced statistical techniques that support the elimination of the model bias and the reduction of the error variability may successfully address the above issues. In the present work, new optimization methods are studied and tested in selected areas of Greece where the use of renewable energy sources is of critical. The added value of the proposed work is due to the solid mathematical background adopted making use of Information Geometry and Statistical techniques, new versions of Kalman filters and state of the art numerical analysis tools.

The potential impact of scatterometry on oceanography - A wave forecasting case

NASA Technical Reports Server (NTRS)

Cane, M. A.; Cardone, V. J.

1981-01-01

A series of observing system simulation experiments have been performed in order to assess the potential impact of marine surface wind data on numerical weather prediction. In addition to conventional data, the experiments simulated the time-continuous assimilation of remotely sensed marine surface wind or temperature sounding data. The wind data were fabricated directly for model grid points intercepted by a Seasat-1 scatterometer swath and were assimilated into the lowest active level (945 mb) of the model using a localized successive correction method. It is shown that Seasat wind data can greatly improve numerical weather forecasts due to better definition of specific features. The case of the QE II storm is examined.

Contrail Tracking and ARM Data Product Development

NASA Technical Reports Server (NTRS)

Duda, David P.; Russell, James, III

2005-01-01

A contrail tracking system was developed to help in the assessment of the effect of commercial jet contrails on the Earth's radiative budget. The tracking system was built by combining meteorological data from the Rapid Update Cycle (RUC) numerical weather prediction model with commercial air traffic flight track data and satellite imagery. A statistical contrail-forecasting model was created a combination of surface-based contrail observations and numerical weather analyses and forecasts. This model allows predictions of widespread contrail occurrences for contrail research on either a real-time basis or for long-term time scales. Satellite-derived cirrus cloud properties in polluted and unpolluted regions were compared to determine the impact of air traffic on cirrus.

State of Art in space weather observational activities and data management in Europe

NASA Astrophysics Data System (ADS)

Stanislawska, Iwona

One of the primary scientific and technical goals of space weather is to produce data in order to investigate the Sun impact on the Earth and its environment. Studies based on data mining philosophy yield increase the knowledge of space weather physical properties, modelling capabilities and gain applications of various procedures in space weather monitoring and forecasting. Exchanging tailored individually and/or jointly data between different entities, storing of the databases and making data accessible for the users is the most important task undertaken by investigators. National activities spread over Europe is currently consolidated pursuant to the terms of effectiveness and individual contributions embedded in joint integrated efforts. The role of COST 724 Action in animation of such a movement is essential. The paper focuses on the analysis of the European availability in the Internet near-real time and historical collections of the European ground based and satellite observations, operational indices and parameters. A detailed description of data delivered is included. The structure of the content is supplied according to the following selection: (1) observations, raw and/or corrected, updated data, (2) resolution, availability of real-time and historical data, (3) products, as the results of models and theory including (a) maps, forecasts and alerts, (b) resolution, availability of real-time and historical data, (4) platforms to deliver data. Characterization of the networking of stations, observatories and space related monitoring systems of data collections is integrated part of the paper. According to these provisions operational systems developed for these purposes is presented and analysed. It concerns measurements, observations and parameters from the theory and models referred to local, regional collections, European and worldwide networks. Techniques used by these organizations to generate the digital content are identified. As the reference pan-European and some national data centres and bases are described and compared with currently available data information provided worldwide and by relevant entities outside Europe. Current, follow up and expected future European space weather observational activities and data management perspectives in respect to European main lines of policy is the subject of the conclusions.

Space Weather Forecasting Operational Needs: A view from NOAA/SWPC

NASA Astrophysics Data System (ADS)

Biesecker, D. A.; Onsager, T. G.; Rutledge, R.

2017-12-01

The gaps in space weather forecasting are many. From long lead time forecasts, to accurate warnings with lead time to take action, there is plenty of room for improvement. Significant numbers of new observations would improve this picture, but it's also important to recognize the value of numerical modeling. The obvious interplanetary mission concepts that would be ideal would be 1) to measure the in-situ solar wind along the entire Sun-Earth line from as near to the Sun as possible all the way to Earth 2) a string of spacecraft in 1 AU heliocentric orbits making in-situ measurements as well as remote-sensing observations of the Sun, corona, and heliosphere. Even partially achieving these ideals would benefit space weather services, improving lead time and providing greater accuracy further into the future. The observations alone would improve forecasting. However, integrating these data into numerical models, as boundary conditions or via data assimilation, would provide the greatest improvements.

Visualizing Uncertainty for Probabilistic Weather Forecasting based on Reforecast Analogs

NASA Astrophysics Data System (ADS)

Pelorosso, Leandro; Diehl, Alexandra; Matković, Krešimir; Delrieux, Claudio; Ruiz, Juan; Gröeller, M. Eduard; Bruckner, Stefan

2016-04-01

Numerical weather forecasts are prone to uncertainty coming from inaccuracies in the initial and boundary conditions and lack of precision in numerical models. Ensemble of forecasts partially addresses these problems by considering several runs of the numerical model. Each forecast is generated with different initial and boundary conditions and different model configurations [GR05]. The ensembles can be expressed as probabilistic forecasts, which have proven to be very effective in the decision-making processes [DE06]. The ensemble of forecasts represents only some of the possible future atmospheric states, usually underestimating the degree of uncertainty in the predictions [KAL03, PH06]. Hamill and Whitaker [HW06] introduced the "Reforecast Analog Regression" (RAR) technique to overcome the limitations of ensemble forecasting. This technique produces probabilistic predictions based on the analysis of historical forecasts and observations. Visual analytics provides tools for processing, visualizing, and exploring data to get new insights and discover hidden information patterns in an interactive exchange between the user and the application [KMS08]. In this work, we introduce Albero, a visual analytics solution for probabilistic weather forecasting based on the RAR technique. Albero targets at least two different type of users: "forecasters", who are meteorologists working in operational weather forecasting and "researchers", who work in the construction of numerical prediction models. Albero is an efficient tool for analyzing precipitation forecasts, allowing forecasters to make and communicate quick decisions. Our solution facilitates the analysis of a set of probabilistic forecasts, associated statistical data, observations and uncertainty. A dashboard with small-multiples of probabilistic forecasts allows the forecasters to analyze at a glance the distribution of probabilities as a function of time, space, and magnitude. It provides the user with a more accurate measure of forecast uncertainty that could result in better decision-making. It offers different level of abstractions to help with the recalibration of the RAR method. It also has an inspection tool that displays the selected analogs, their observations and statistical data. It gives the users access to inner parts of the method, unveiling hidden information. References [GR05] GNEITING T., RAFTERY A. E.: Weather forecasting with ensemble methods. Science 310, 5746, 248-249, 2005. [KAL03] KALNAY E.: Atmospheric modeling, data assimilation and predictability. Cambridge University Press, 2003. [PH06] PALMER T., HAGEDORN R.: Predictability of weather and climate. Cambridge University Press, 2006. [HW06] HAMILL T. M., WHITAKER J. S.: Probabilistic quantitative precipitation forecasts based on reforecast analogs: Theory and application. Monthly Weather Review 134, 11, 3209-3229, 2006. [DE06] DEITRICK S., EDSALL R.: The influence of uncertainty visualization on decision making: An empirical evaluation. Springer, 2006. [KMS08] KEIM D. A., MANSMANN F., SCHNEIDEWIND J., THOMAS J., ZIEGLER H.: Visual analytics: Scope and challenges. Springer, 2008.

Improving Weather Forecasts Through Reduced Precision Data Assimilation

NASA Astrophysics Data System (ADS)

Hatfield, Samuel; Düben, Peter; Palmer, Tim

2017-04-01

We present a new approach for improving the efficiency of data assimilation, by trading numerical precision for computational speed. Future supercomputers will allow a greater choice of precision, so that models can use a level of precision that is commensurate with the model uncertainty. Previous studies have already indicated that the quality of climate and weather forecasts is not significantly degraded when using a precision less than double precision [1,2], but so far these studies have not considered data assimilation. Data assimilation is inherently uncertain due to the use of relatively long assimilation windows, noisy observations and imperfect models. Thus, the larger rounding errors incurred from reducing precision may be within the tolerance of the system. Lower precision arithmetic is cheaper, and so by reducing precision in ensemble data assimilation, we can redistribute computational resources towards, for example, a larger ensemble size. Because larger ensembles provide a better estimate of the underlying distribution and are less reliant on covariance inflation and localisation, lowering precision could actually allow us to improve the accuracy of weather forecasts. We will present results on how lowering numerical precision affects the performance of an ensemble data assimilation system, consisting of the Lorenz '96 toy atmospheric model and the ensemble square root filter. We run the system at half precision (using an emulation tool), and compare the results with simulations at single and double precision. We estimate that half precision assimilation with a larger ensemble can reduce assimilation error by 30%, with respect to double precision assimilation with a smaller ensemble, for no extra computational cost. This results in around half a day extra of skillful weather forecasts, if the error-doubling characteristics of the Lorenz '96 model are mapped to those of the real atmosphere. Additionally, we investigate the sensitivity of these results to observational error and assimilation window length. Half precision hardware will become available very shortly, with the introduction of Nvidia's Pascal GPU architecture and the Intel Knights Mill coprocessor. We hope that the results presented here will encourage the uptake of this hardware. References [1] Peter D. Düben and T. N. Palmer, 2014: Benchmark Tests for Numerical Weather Forecasts on Inexact Hardware, Mon. Weather Rev., 142, 3809-3829 [2] Peter D. Düben, Hugh McNamara and T. N. Palmer, 2014: The use of imprecise processing to improve accuracy in weather & climate prediction, J. Comput. Phys., 271, 2-18

Increasing horizontal resolution in numerical weather prediction and climate simulations: illusion or panacea?

PubMed

Wedi, Nils P

2014-06-28

The steady path of doubling the global horizontal resolution approximately every 8 years in numerical weather prediction (NWP) at the European Centre for Medium Range Weather Forecasts may be substantially altered with emerging novel computing architectures. It coincides with the need to appropriately address and determine forecast uncertainty with increasing resolution, in particular, when convective-scale motions start to be resolved. Blunt increases in the model resolution will quickly become unaffordable and may not lead to improved NWP forecasts. Consequently, there is a need to accordingly adjust proven numerical techniques. An informed decision on the modelling strategy for harnessing exascale, massively parallel computing power thus also requires a deeper understanding of the sensitivity to uncertainty--for each part of the model--and ultimately a deeper understanding of multi-scale interactions in the atmosphere and their numerical realization in ultra-high-resolution NWP and climate simulations. This paper explores opportunities for substantial increases in the forecast efficiency by judicious adjustment of the formal accuracy or relative resolution in the spectral and physical space. One path is to reduce the formal accuracy by which the spectral transforms are computed. The other pathway explores the importance of the ratio used for the horizontal resolution in gridpoint space versus wavenumbers in spectral space. This is relevant for both high-resolution simulations as well as ensemble-based uncertainty estimation. © 2014 The Author(s) Published by the Royal Society. All rights reserved.

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 Burning Analysis (SAMBBA) campaign period to determine whether more complex chemistry provides benefits for global numerical weather prediction.

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.;

Climate change and health in Israel: adaptation policies for extreme weather events

PubMed Central

2013-01-01

Climatic changes have increased the world-wide frequency of extreme weather events such as heat waves, cold spells, floods, storms and droughts. These extreme events potentially affect the health status of millions of people, increasing disease and death. Since mitigation of climate change is a long and complex process, emphasis has recently been placed on the measures required for adaptation. Although the principles underlying these measures are universal, preparedness plans and policies need to be tailored to local conditions. In this paper, we conducted a review of the literature on the possible health consequences of extreme weather events in Israel, where the conditions are characteristic of the Mediterranean region. Strong evidence indicates that the frequency and duration of several types of extreme weather events are increasing in the Mediterranean Basin, including Israel. We examined the public health policy implications for adaptation to climate change in the region, and proposed public health adaptation policy options. Preparedness for the public health impact of increased extreme weather events is still relatively limited and clear public health policies are urgently needed. These include improved early warning and monitoring systems, preparedness of the health system, educational programs and the living environment. Regional collaboration should be a priority. PMID:23805950

Worldwide Weather Radar Imagery May Allow Substantial Increase in Meteorite Fall Recovery

NASA Technical Reports Server (NTRS)

Fries, Marc; Matson, Robert; Schaefer, Jacob; Fries, Jeffery; Hankey, Mike; Anderson, Lindsay

2014-01-01

Weather radar imagery is a valuable new technique for the rapid recovery of meteorite falls, to include falls which would not otherwise be recovered (e.g. Battle Mountain). Weather radar imagery reveals about one new meteorite fall per year (18 falls since 1998), using weather radars in the United States alone. However, an additional 75 other nations operate weather radar networks according to the UN World Meteorological Organization (WMO). If the imagery of those radars were analyzed, the current rate of meteorite falls could be improved considerably, to as much as 3.6 times the current recovery rate based on comparison of total radar areal coverage. Recently, the addition of weather radar imagery, seismometry and internet-based aggregation of eyewitness reports has improved the speed and accuracy of fresh meteorite fall recovery [e.g. 1,2]. This was demonstrated recently with the radar-enabled recovery of the Sutter's Mill fall [3]. Arguably, the meteorites recovered via these methods are of special scientific value as they are relatively unweathered, fresh falls. To illustrate this, a recent SAO/NASA ADS search using the keyword "meteorite" shows that all 50 of the top search results included at least one named meteorite recovered from a meteorite fall. This is true even though only 1260 named meteorite falls are recorded among the >49,000 individual falls recorded in the Meteoritical Society online database. The US NEXRAD system used thus far to locate meteorite falls covers most of the United States' surface area. Using a WMO map of the world's weather radars, we estimate that the total coverage of the other 75 national weather radar networks equals about 3.6x NEXRAD's coverage area. There are two findings to draw from this calculation: 1) For the past 16 years during which 18 falls are seen in US radar data, there should be an additional 65 meteorite falls recorded in worldwide radar imagery. Also: 2) if all of the world's radar data could be analyzed, the rate of recovery of fresh meteorite falls can increase by as much as 3.6x the current rate. The authors' experience to date indicates that the most effective course of action would be to have local meteorite research groups (outside of the US) form research consortia and develop a working relationship with their nation's weather bureau for access to data. These research consortia could utilize the same, proven methods used for US NEXRAD imagery, internet eyewitness report aggregation, seismometry analysis, etc. to locate meteorite falls. The consortia could then recover and analyze meteorite falls and enrich their own research efforts. It would be beneficial to conduct a global program to coordinate the development of methods and data tools, as well as to coordinate meteorite sample sharing and research. Perhaps an institution such as the Meteoritical Society could lead such an effort.

Toward Robust Climate Baselining: Objective Assessment of Climate Change Using Widely Distributed Miniaturized Sensors for Accurate World-Wide Geophysical Measurements

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

Teller, E; Leith, C; Canavan, G

A gap-free, world-wide, ocean-, atmosphere-, and land surface-spanning geophysical data-set of three decades time-duration containing the full set of geophysical parameters characterizing global weather is the scientific perquisite for defining the climate; the generally-accepted definition in the meteorological community is that climate is the 30-year running-average of weather. Until such a tridecadal climate base line exists, climate change discussions inevitably will have a semi-speculative, vs. a purely scientific, character, as the baseline against which changes are referenced will be at least somewhat uncertain. The contemporary technology base provides ways-and-means for commencing the development of such a meteorological measurement-intensive climate baseline, moreover with a program budget far less than the {approx}more » $2.5 B/year which the US. currently spends on ''global change'' studies. In particular, the recent advent of satellite-based global telephony enables real-time control of, and data-return from, instrument packages of very modest scale, and Silicon Revolution-based sensor, data-processing and -storage advances permit 'intelligent' data-gathering payloads to be created with 10 gram-scale mass budgets. A geophysical measurement system implemented in such modern technology is a populous constellation 03 long-lived, highly-miniaturized robotic weather stations deployed throughout the weather-generating portions of the Earths atmosphere, throughout its oceans and across its land surfaces. Leveraging the technological advances of the OS, the filly-developed atmospheric weather station of this system has a projected weight of the order of 1 ounce, and contains a satellite telephone, a GPS receiver, a full set of atmospheric sensing instruments and a control computer - and has an operational life of the order of 1 year and a mass-production cost of the order of $$20. Such stations are effectively ''intra-atmospheric satellites'' but likely have serial-production unit costs only about twenty-billionths that of a contemporary NASA global change satellite, whose entirely-remote sensing capabilities they complement with entirely-local sensing. It's thus feasible to deploy millions of them, and thereby to intensively monitor all aspects of the Earths weather. Analogs of these atmospheric weather stations will be employed to provide comparable-quality reporting of oceanic and land-surface geophysical parameters affecting weather. This definitive climate baselining system could be in initial-prototype operation on a one-year time-scale, and in intermediate-scale, proof-of-principle operation within three years, at a total cost of {approx}$$95M. Steady-state operating costs are estimated to be {approx} $$75M/year, or {approx}3% of the current US. ''global change'' program-cost. Its data-return would be of great value very quickly as simply the best weather information, and within a few years as the definitive climatic variability-reporting system. It would become the generator of a definitive climate baseline at a total present-value cost of {approx}$$0.9 B.« less

Chart links solar, geophysical events with impacts on space technologies

NASA Astrophysics Data System (ADS)

Davenport, George R.

While developing a Space Weather Training Program for Air Force Space Command and the 50th Weather Squadron, both based in Colorado, ARINC Incorporated produced a flowchart that correlates solar and geophysical events with their impacts on Air Force systems.Personnel from both organizations collaborated in the development of the flowchart and provided many comments and suggestions. The model became the centerpiece of the Space Environment Impacts Reference Pamphlet, as well as the formal Space Weather Training Program. Although it is not a numerical or computer model, the flowchart became known as the “Space Environmental Impacts Model.”

Meteorological and Environmental Inputs to Aviation Systems

NASA Technical Reports Server (NTRS)

Camp, Dennis W. (Editor); Frost, Walter (Editor)

1988-01-01

Reports on aviation meteorology, most of them informal, are presented by representatives of the National Weather Service, the Bracknell (England) Meteorological Office, the NOAA Wave Propagation Lab., the Fleet Numerical Oceanography Center, and the Aircraft Owners and Pilots Association. Additional presentations are included on aircraft/lidar turbulence comparison, lightning detection and locating systems, objective detection and forecasting of clear air turbulence, comparative verification between the Generalized Exponential Markov (GEM) Model and official aviation terminal forecasts, the evaluation of the Prototype Regional Observation and Forecast System (PROFS) mesoscale weather products, and the FAA/MIT Lincoln Lab. Doppler Weather Radar Program.

Species selection in hardwoods research: variations in baseline physiological responses of select temperate hardwood tree species

Treesearch

Shaneka S. Lawson; Paula M. Pijut; Charles H. Michler

2013-01-01

Drought periods are becoming more extreme worldwide and the ability of plants to contribute towards atmospheric flux is being compromised. Properly functioning stomata provide an exit for water that has been absorbed by the roots, funneled into various cell parts, and eventually released into the atmosphere via transpiration. By observing the effects that weather...

Fuzzy logic-based analogue forecasting and hybrid modelling of horizontal visibility

NASA Astrophysics Data System (ADS)

Tuba, Zoltán; Bottyán, Zsolt

2018-04-01

Forecasting visibility is one of the greatest challenges in aviation meteorology. At the same time, high accuracy visibility forecasts can significantly reduce or make avoidable weather-related risk in aviation as well. To improve forecasting visibility, this research links fuzzy logic-based analogue forecasting and post-processed numerical weather prediction model outputs in hybrid forecast. Performance of analogue forecasting model was improved by the application of Analytic Hierarchy Process. Then, linear combination of the mentioned outputs was applied to create ultra-short term hybrid visibility prediction which gradually shifts the focus from statistical to numerical products taking their advantages during the forecast period. It gives the opportunity to bring closer the numerical visibility forecast to the observations even it is wrong initially. Complete verification of categorical forecasts was carried out; results are available for persistence and terminal aerodrome forecasts (TAF) as well in order to compare. The average value of Heidke Skill Score (HSS) of examined airports of analogue and hybrid forecasts shows very similar results even at the end of forecast period where the rate of analogue prediction in the final hybrid output is 0.1-0.2 only. However, in case of poor visibility (1000-2500 m), hybrid (0.65) and analogue forecasts (0.64) have similar average of HSS in the first 6 h of forecast period, and have better performance than persistence (0.60) or TAF (0.56). Important achievement that hybrid model takes into consideration physics and dynamics of the atmosphere due to the increasing part of the numerical weather prediction. In spite of this, its performance is similar to the most effective visibility forecasting methods and does not follow the poor verification results of clearly numerical outputs.

Enviro-HIRLAM/ HARMONIE Studies in ECMWF HPC EnviroAerosols Project

NASA Astrophysics Data System (ADS)

Hansen Sass, Bent; Mahura, Alexander; Nuterman, Roman; Baklanov, Alexander; Palamarchuk, Julia; Ivanov, Serguei; Pagh Nielsen, Kristian; Penenko, Alexey; Edvardsson, Nellie; Stysiak, Aleksander Andrzej; Bostanbekov, Kairat; Amstrup, Bjarne; Yang, Xiaohua; Ruban, Igor; Bergen Jensen, Marina; Penenko, Vladimir; Nurseitov, Daniyar; Zakarin, Edige

2017-04-01

The EnviroAerosols on ECMWF HPC project (2015-2017) "Enviro-HIRLAM/ HARMONIE model research and development for online integrated meteorology-chemistry-aerosols feedbacks and interactions in weather and atmospheric composition forecasting" is aimed at analysis of importance of the meteorology-chemistry/aerosols interactions and to provide a way for development of efficient techniques for on-line coupling of numerical weather prediction and atmospheric chemical transport via process-oriented parameterizations and feedback algorithms, which will improve both the numerical weather prediction and atmospheric composition forecasts. Two main application areas of the on-line integrated modelling are considered: (i) improved numerical weather prediction with short-term feedbacks of aerosols and chemistry on formation and development of meteorological variables, and (ii) improved atmospheric composition forecasting with on-line integrated meteorological forecast and two-way feedbacks between aerosols/chemistry and meteorology. During 2015-2016 several research projects were realized. At first, the study on "On-line Meteorology-Chemistry/Aerosols Modelling and Integration for Risk Assessment: Case Studies" focused on assessment of scenarios with accidental and continuous emissions of sulphur dioxide for case studies for Atyrau (Kazakhstan) near the northern part of the Caspian Sea and metallurgical enterprises on the Kola Peninsula (Russia), with GIS integration of modelling results into the RANDOM (Risk Assessment of Nature Detriment due to Oil spill Migration) system. At second, the studies on "The sensitivity of precipitation simulations to the soot aerosol presence" & "The precipitation forecast sensitivity to data assimilation on a very high resolution domain" focused on sensitivity and changes in precipitation life-cycle under black carbon polluted conditions over Scandinavia. At third, studies on "Aerosol effects over China investigated with a high resolution convection permitting weather model" & "Meteorological and chemical urban scale modelling for Shanghai metropolitan area" with focus on aerosol effects and influence of urban areas in China at regional-subregional-urban scales. At fourth, study on "Direct variational data assimilation algorithm for atmospheric chemistry data with transport and transformation model" with focus on testing chemical data assimilation algorithm of in situ concentration measurements on real data scenario. At firth, study on "Aerosol influence on High Resolution NWP HARMONIE Operational Forecasts" with focus on impact of sea salt aerosols on numerical weather prediction during low precipitation events. And finally, study on "Impact of regional afforestation on climatic conditions in metropolitan areas: case study of Copenhagen" with focus on impact of forest and land-cover change on formation and development of temperature regimes in the Copenhagen metropolitan area of Denmark. Selected results and findings will be presented and discussed.

rpe v5: an emulator for reduced floating-point precision in large numerical simulations

NASA Astrophysics Data System (ADS)

Dawson, Andrew; Düben, Peter D.

2017-06-01

This paper describes the rpe (reduced-precision emulator) library which has the capability to emulate the use of arbitrary reduced floating-point precision within large numerical models written in Fortran. The rpe software allows model developers to test how reduced floating-point precision affects the result of their simulations without having to make extensive code changes or port the model onto specialized hardware. The software can be used to identify parts of a program that are problematic for numerical precision and to guide changes to the program to allow a stronger reduction in precision.The development of rpe was motivated by the strong demand for more computing power. If numerical precision can be reduced for an application under consideration while still achieving results of acceptable quality, computational cost can be reduced, since a reduction in numerical precision may allow an increase in performance or a reduction in power consumption. For simulations with weather and climate models, savings due to a reduction in precision could be reinvested to allow model simulations at higher spatial resolution or complexity, or to increase the number of ensemble members to improve predictions. rpe was developed with a particular focus on the community of weather and climate modelling, but the software could be used with numerical simulations from other domains.

A stochastic ensemble-based model to predict crop water requirements from numerical weather forecasts and VIS-NIR high resolution satellite images in Southern Italy

NASA Astrophysics Data System (ADS)

Pelosi, Anna; Falanga Bolognesi, Salvatore; De Michele, Carlo; Medina Gonzalez, Hanoi; Villani, Paolo; D'Urso, Guido; Battista Chirico, Giovanni

2015-04-01

Irrigation agriculture is one the biggest consumer of water in Europe, especially in southern regions, where it accounts for up to 70% of the total water consumption. The EU Common Agricultural Policy, combined with the Water Framework Directive, imposes to farmers and irrigation managers a substantial increase of the efficiency in the use of water in agriculture for the next decade. Ensemble numerical weather predictions can be valuable data for developing operational advisory irrigation services. We propose a stochastic ensemble-based model providing spatial and temporal estimates of crop water requirements, implemented within an advisory service offering detailed maps of irrigation water requirements and crop water consumption estimates, to be used by water irrigation managers and farmers. The stochastic model combines estimates of crop potential evapotranspiration retrieved from ensemble numerical weather forecasts (COSMO-LEPS, 16 members, 7 km resolution) and canopy parameters (LAI, albedo, fractional vegetation cover) derived from high resolution satellite images in the visible and near infrared wavelengths. The service provides users with daily estimates of crop water requirements for lead times up to five days. The temporal evolution of the crop potential evapotranspiration is simulated with autoregressive models. An ensemble Kalman filter is employed for updating model states by assimilating both ground based meteorological variables (where available) and numerical weather forecasts. The model has been applied in Campania region (Southern Italy), where a satellite assisted irrigation advisory service has been operating since 2006. This work presents the results of the system performance for one year of experimental service. The results suggest that the proposed model can be an effective support for a sustainable use and management of irrigation water, under conditions of water scarcity and drought. Since the evapotranspiration term represents a staple component in the water balance of a catchment, as outstanding future development, the model could also offer an advanced support for water resources management decisions at catchment scale.

Light scattering and absorption by space weathered planetary bodies: Novel numerical solution

NASA Astrophysics Data System (ADS)

Markkanen, Johannes; Väisänen, Timo; Penttilä, Antti; Muinonen, Karri

2017-10-01

Airless planetary bodies are exposed to space weathering, i.e., energetic electromagnetic and particle radiation, implantation and sputtering from solar wind particles, and micrometeorite bombardment.Space weathering is known to alter the physical and chemical composition of the surface of an airless body (C. Pieters et al., J. Geophys. Res. Planets, 121, 2016). From the light scattering perspective, one of the key effects is the production of nanophase iron (npFe0) near the exposed surfaces (B. Hapke, J. Geophys. Res., 106, E5, 2001). At visible and ultraviolet wavelengths these particles have a strong electromagnetic response which has a major impact on scattering and absorption features. Thus, to interpret the spectroscopic observations of space-weathered asteroids, the model should treat the contributions of the npFe0 particles rigorously.Our numerical approach is based on the hierarchical geometric optics (GO) and radiative transfer (RT). The modelled asteroid is assumed to consist of densely packed silicate grains with npFe0 inclusions. We employ our recently developed RT method for dense random media (K. Muinonen, et al., Radio Science, submitted, 2017) to compute the contributions of the npFe0 particles embedded in silicate grains. The dense media RT method requires computing interactions of the npFe0 particles in the volume element for which we use the exact fast superposition T-matrix method (J. Markkanen, and A.J. Yuffa, JQSRT 189, 2017). Reflections and refractions on the grain surface and propagation in the grain are addressed by the GO. Finally, the standard RT is applied to compute scattering by the entire asteroid.Our numerical method allows for a quantitative interpretation of the spectroscopic observations of space-weathered asteroids. In addition, it may be an important step towards more rigorous a thermophysical model of asteroids when coupled with the radiative and conductive heat transfer techniques.Acknowledgments. Research supported by European Research Council with Advanced Grant No. 320773 SAEMPL. Computational resources provided by CSC- IT Centre for Science Ltd, Finland.

Rice industrial processing worldwide and impact on macro- and micronutrient content, stability, and retention

USDA-ARS?s Scientific Manuscript database

Various processing methods are used in the food industry worldwide to produce numerous rice products with desirable sensory qualities based on cultural and cooking preferences and nutritional considerations. The processes result in variable degrees of macro- and micronutrient content, stability, and...

Statistical Analysis of Atmospheric Forecast Model Accuracy - A Focus on Multiple Atmospheric Variables and Location-Based Analysis

DTIC Science & Technology

2014-04-01

WRF ) model is a numerical weather prediction system designed for operational forecasting and atmospheric research. This report examined WRF model... WRF , weather research and forecasting, atmospheric effects 16. SECURITY CLASSIFICATION OF: 17. LIMITATION OF ABSTRACT SAR 18. NUMBER OF...and Forecasting ( WRF ) model. The authors would also like to thank Ms. Sherry Larson, STS Systems Integration, LLC, ARL Technical Publishing Branch

Atlas : A library for numerical weather prediction and climate modelling

NASA Astrophysics Data System (ADS)

Deconinck, Willem; Bauer, Peter; Diamantakis, Michail; Hamrud, Mats; Kühnlein, Christian; Maciel, Pedro; Mengaldo, Gianmarco; Quintino, Tiago; Raoult, Baudouin; Smolarkiewicz, Piotr K.; Wedi, Nils P.

2017-11-01

The algorithms underlying numerical weather prediction (NWP) and climate models that have been developed in the past few decades face an increasing challenge caused by the paradigm shift imposed by hardware vendors towards more energy-efficient devices. In order to provide a sustainable path to exascale High Performance Computing (HPC), applications become increasingly restricted by energy consumption. As a result, the emerging diverse and complex hardware solutions have a large impact on the programming models traditionally used in NWP software, triggering a rethink of design choices for future massively parallel software frameworks. In this paper, we present Atlas, a new software library that is currently being developed at the European Centre for Medium-Range Weather Forecasts (ECMWF), with the scope of handling data structures required for NWP applications in a flexible and massively parallel way. Atlas provides a versatile framework for the future development of efficient NWP and climate applications on emerging HPC architectures. The applications range from full Earth system models, to specific tools required for post-processing weather forecast products. The Atlas library thus constitutes a step towards affordable exascale high-performance simulations by providing the necessary abstractions that facilitate the application in heterogeneous HPC environments by promoting the co-design of NWP algorithms with the underlying hardware.

Forecasting Winter Storms in the Sierra: A Social Science Perspective in Keeping the Public Safe without Negatively Impacting the Local Tourism Industry

NASA Astrophysics Data System (ADS)

Milne, R.; Wallmann, J.; Myrick, D. T.

2010-12-01

The National Weather Service Office in Reno is responsible for issuing Blizzard Warnings, Winter Storm Warnings, and Winter Weather Advisories for the Sierra, including the Lake Tahoe Basin and heavily traveled routes such as Interstate 80, Highway 395 and Highway 50. These forecast products prepare motorists for harsh travel conditions as well as those venturing into the backcountry, which are essential to the NWS mission of saving lives and property. During the winter season, millions of people from around the world visit the numerous world class ski resorts in the Sierra and the Lake Tahoe Basin, which is vital to the local economy. This situation creates a challenging decision for the forecasters to provide appropriate wording in winter statements to keep the public safe, without significantly impacting the local tourism-based economy. Numerous text and graphical products, including online weather briefings, are utilized by NWS Reno to highlight hazards in ensuring the public, businesses, and other government agencies are prepared for winter storms and take appropriate safety measures. The effectiveness of these product types will be explored, with past snowstorms used as examples to show how forecasters determine which type of text or graphical product is most appropriate to convey the hazardous weather threats.

Characterizing severe weather potential in synoptically weakly forced thunderstorm environments

NASA Astrophysics Data System (ADS)

Miller, Paul W.; Mote, Thomas L.

2018-04-01

Weakly forced thunderstorms (WFTs), short-lived convection forming in synoptically quiescent regimes, are a contemporary forecasting challenge. The convective environments that support severe WFTs are often similar to those that yield only non-severe WFTs and, additionally, only a small proportion of individual WFTs will ultimately produce severe weather. The purpose of this study is to better characterize the relative severe weather potential in these settings as a function of the convective environment. Thirty-one near-storm convective parameters for > 200 000 WFTs in the Southeastern United States are calculated from a high-resolution numerical forecasting model, the Rapid Refresh (RAP). For each parameter, the relative odds of WFT days with at least one severe weather event is assessed along a moving threshold. Parameters (and the values of them) that reliably separate severe-weather-supporting from non-severe WFT days are highlighted.Only two convective parameters, vertical totals (VTs) and total totals (TTs), appreciably differentiate severe-wind-supporting and severe-hail-supporting days from non-severe WFT days. When VTs exceeded values between 24.6 and 25.1 °C or TTs between 46.5 and 47.3 °C, odds of severe-wind days were roughly 5 × greater. Meanwhile, odds of severe-hail days became roughly 10 × greater when VTs exceeded 24.4-26.0 °C or TTs exceeded 46.3-49.2 °C. The stronger performance of VT and TT is partly attributed to the more accurate representation of these parameters in the numerical model. Under-reporting of severe weather and model error are posited to exacerbate the forecasting challenge by obscuring the subtle convective environmental differences enhancing storm severity.

Mycotoxin potential in high-risk American Vitis vinifera vineyards and wines

USDA-ARS?s Scientific Manuscript database

Mycotoxins pose a serious worldwide threat to the safety of numerous food commodities. Red wine made from Vitis vinifera grapes is particularly prone to contamination from ochratoxin A, produced by black-spored Aspergillus spp. worldwide, and it was recently discovered that these species can also p...

Sharka epidemiology and worldwide management strategies: learning lessons to optimize disease control in perennial plants

USDA-ARS?s Scientific Manuscript database

Many plant epidemics that cause major economic losses cannot be controlled with pesticides. Among them, sharka epidemics severely affect prunus trees worldwide. Its causal agent, Plum pox virus (PPV;, genus Potyvirus), has been classified as a quarantine pathogen in numerous countries. As a result, ...

ESA Earth Observation missions at the service of geoscience

NASA Astrophysics Data System (ADS)

Aschbacher, Josef

2017-04-01

The intervention will present ESA's Earth Observation programmes and their relevance to geoscience. ESA's Earth observation missions are mainly grouped into three categories: The Sentinel satellites in the context of the European Copernicus Programme, the scientific Earth Explorers and the meteorological missions. Developments, applications and scientific results for the different mission types will be addressed, along with overall trends and boundary conditions. The Earth Explorers, who form the science and research element of ESA's Living Planet Programme, focus on the atmosphere, biosphere, hydrosphere, cryosphere and Earth's interior. The Earth Explorers also aim at learning more about the interactions between these components and the impact that human activity is having on natural Earth processes. The Sentinel missions provide accurate, timely, long term and uninterrupted data to provide key information services, improving the way the environment is managed, and helping to mitigate the effects of climate change. The operational Sentinel satellites can also be exploited for scientific endeavours. Meteorological satellites help to predict the weather and feature the most mature application of Earth observation. Over the last four decades satellites have been radically improving the accuracy of weather forecasts by providing unique and indispensable input data to numerical computation models. In addition, Essential Climate Variables (ECV) are constantly monitored within ESA's Climate Change Initiative in order to create a long-term record of key geophysical parameters. All of these activities can only be carried out in international cooperation. Accordingly, ESA maintains long-standing partnerships with other space agencies and relevant institutions worldwide. In running its Earth observation programmes, ESA responds to societal needs and challenges as well as to requirements resulting from political priorities, such as the United Nations' Sustainable Development Goals.

Application of Humidity Data for Predictions of Influenza Outbreaks.

NASA Astrophysics Data System (ADS)

Teixeira, J.; Thrastarson, H. T.; Yeo, E.

2016-12-01

Seasonal influenza outbreaks infect millions of people, cause hundreds of thousands of deaths worldwide, and leave an immense economic footprint. Potential forecasting of the timing and intensity of these outbreaks can help mitigation and response efforts (e.g., the management and organization of vaccines, drugs and other resources). Absolute (or specific) humidity has been identified as an important driver of the seasonal behavior of influenza outbreaks in temperate regions. Building upon this result, we incorporate humidity data from both NASA's AIRS (Atmospheric Infra-Red Sounder) instrument and ERA-Interim re-analysis into a SIRS (Susceptible-Infectious-Recovered-Susceptible) type numerical epidemiological model, comprising a prediction system for influenza outbreaks. Data for influenza activity is obtained from sources such as Google Flu Trends and the CDC (Center for Disease Control) and used for comparison and assimilation. The accuracy and limitations of the prediction system are tested with hindcasts of outbreaks in the United States for the years 2005-2015. Our results give support to the hypothesis that local weather conditions drive the seasonality of influenza in temperate regions. The implementation of influenza forecasts that make use of NCEP humidity forecasts is also discussed.

Rock-weathering rates as functions of time

USGS Publications Warehouse

Colman, Steven M.

1981-01-01

The scarcity of documented numerical relations between rock weathering and time has led to a common assumption that rates of weathering are linear. This assumption has been strengthened by studies that have calculated long-term average rates. However, little theoretical or empirical evidence exists to support linear rates for most chemical-weathering processes, with the exception of congruent dissolution processes. The few previous studies of rock-weathering rates that contain quantitative documentation of the relation between chemical weathering and time suggest that the rates of most weathering processes decrease with time. Recent studies of weathering rinds on basaltic and andesitic stones in glacial deposits in the western United States also clearly demonstrate that rock-weathering processes slow with time. Some weathering processes appear to conform to exponential functions of time, such as the square-root time function for hydration of volcanic glass, which conforms to the theoretical predictions of diffusion kinetics. However, weathering of mineralogically heterogeneous rocks involves complex physical and chemical processes that generally can be expressed only empirically, commonly by way of logarithmic time functions. Incongruent dissolution and other weathering processes produce residues, which are commonly used as measures of weathering. These residues appear to slow movement of water to unaltered material and impede chemical transport away from it. If weathering residues impede weathering processes then rates of weathering and rates of residue production are inversely proportional to some function of the residue thickness. This results in simple mathematical analogs for weathering that imply nonlinear time functions. The rate of weathering becomes constant only when an equilibrium thickness of the residue is reached. Because weathering residues are relatively stable chemically, and because physical removal of residues below the ground surface is slight, many weathering features require considerable time to reach constant rates of change. For weathering rinds on volcanic stones in the western United States, this time is at least 0.5 my. ?? 1981.

Demonstrating new technologies to improve atmospheric sounding science using the CubeSat Infrared Atmospheric Sounder (CIRAS).

NASA Astrophysics Data System (ADS)

Pagano, T. S.

2017-12-01

Hyperspectral infrared sounding of the atmosphere has become a vital element in the observational system for weather forecast prediction at National Weather Prediction (NWP) centers worldwide. The NASA Atmospheric Infrared Sounder (AIRS) instrument was the pathfinder for the hyperspectral infrared observations and was designed to provide accurate atmospheric temperature and water vapor profile information in support of weather prediction, climate processes and weather related applications. AIRS was launched in 2002 and continues to operate well. JPL NASA is offering an alternate hyperspectral IR sounder architecture for the future involving CubeSats under the Earth Science Technology Office (ESTO) In-flight Validation of Earth Science Technologies (InVEST) program. The latest technology in large format focal plane assemblies, wide field optics and active cryocoolers enables a reduction in size, mass and cost of the legacy sounders and offer new orbit configurations. The CubeSat Infrared Atmospheric Sounder (CIRAS) employs an MWIR spectrometer operating from 4.08-5.13 µm with 625 channels and spectral resolution of 1.2-2.0 cm-1 to achieve lower tropospheric temperature and water vapor profiles. The CIRAS is packaged in a 6U CubeSat and uses less than 14 W. CIRAS is under development at NASA JPL and scheduled for launch in 2019. This presentation will discuss the CIRAS measurement approach, development status and the plan to demonstrate, in-orbit, higher spatial resolution IR sounding to support new science involving regional weather prediction, applications and weather process studies.

Worldwide multi-model intercomparison of clear-sky solar irradiance predictions

NASA Astrophysics Data System (ADS)

Ruiz-Arias, Jose A.; Gueymard, Christian A.; Cebecauer, Tomas

2017-06-01

Accurate modeling of solar radiation in the absence of clouds is highly important because solar power production peaks during cloud-free situations. The conventional validation approach of clear-sky solar radiation models relies on the comparison between model predictions and ground observations. Therefore, this approach is limited to locations with availability of high-quality ground observations, which are scarce worldwide. As a consequence, many areas of in-terest for, e.g., solar energy development, still remain sub-validated. Here, a worldwide inter-comparison of the global horizontal irradiance (GHI) and direct normal irradiance (DNI) calculated by a number of appropriate clear-sky solar ra-diation models is proposed, without direct intervention of any weather or solar radiation ground-based observations. The model inputs are all gathered from atmospheric reanalyses covering the globe. The model predictions are compared to each other and only their relative disagreements are quantified. The largest differences between model predictions are found over central and northern Africa, the Middle East, and all over Asia. This coincides with areas of high aerosol optical depth and highly varying aerosol distribution size. Overall, the differences in modeled DNI are found about twice larger than for GHI. It is argued that the prevailing weather regimes (most importantly, aerosol conditions) over regions exhibiting substantial divergences are not adequately parameterized by all models. Further validation and scrutiny using conventional methods based on ground observations should be pursued in priority over those specific regions to correctly evaluate the performance of clear-sky models, and select those that can be recommended for solar concentrating applications in particular.

Space Weather Research in Armenia

NASA Astrophysics Data System (ADS)

Chilingarian, A. A.

DVIN for ASEC (Data Visualization interactive Network for Aragats Space Environmental Center) is product for accessing and analysis the on-line data from Solar Monitors located at high altitude research station on Mt. Aragats in Armenia. Data from ASEC monitors is used worldwide for scientific purposes and for monitoring of severe solar storms in progress. Alert service, based on the automatic analysis of variations of the different species of cosmic ray particles is available for subscribers. DVIN advantages: DVIN is strategically important as a scientific application to help develop space science and to foster global collaboration in forecasting potential hazards of solar storms. It precisely fits with the goals of the new evolving information society to provide long-term monitoring and collection of high quality scientific data, and enables adequate dialogue between scientists, decision makers, and civil society. The system is highly interactive and exceptional information is easily accessible online. Data can be monitored and analyzed for desired time spans in a fast and reliable manner. The ASEC activity is an example of a balance between the scientific independence of fundamental research and the needs of civil society. DVIN is also an example of how scientific institutions can apply the newest powerful methods of information technologies, such as multivariate data analysis, to their data and also how information technologies can provide convenient and reliable access to this data and to new knowledge for the world-wide scientific community. DVIN provides very wide possibilities for sharing data and sending warnings and alerts to scientists and other entities world-wide, which have fundamental and practical interest in knowing the space weather conditions.

Building resilience of the Global Positioning System to space weather

NASA Astrophysics Data System (ADS)

Fisher, Genene; Kunches, Joseph

2011-12-01

Almost every aspect of the global economy now depends on GPS. Worldwide, nations are working to create a robust Global Navigation Satellite System (GNSS), which will provide global positioning, navigation, and timing (PNT) services for applications such as aviation, electric power distribution, financial exchange, maritime navigation, and emergency management. The U.S. government is examining the vulnerabilities of GPS, and it is well known that space weather events, such as geomagnetic storms, contribute to errors in single-frequency GPS and are a significant factor for differential GPS. The GPS industry has lately begun to recognize that total electron content (TEC) signal delays, ionospheric scintillation, and solar radio bursts can also interfere with daily operations and that these threats grow with the approach of the next solar maximum, expected to occur in 2013. The key challenges raised by these circumstances are, first, to better understand the vulnerability of GPS technologies and services to space weather and, second, to develop policies that will build resilience and mitigate risk.

Initiation of the Madden-Julian Oscillation

ScienceCinema

None

2018-01-16

Many storms around the world have roots in the Indian Ocean, where they are churned up by the atmospheric process called the Madden-Julian Oscillation (MJO). PNNL is working to unlock the secrets of the MJO, particularly how it initiates in the Indian Ocean every 30-60 days. Better prediction of the MJO will help resource managers, weather forecasters and people worldwide better prepare for its effects.

Sub-kilometer Numerical Weather Prediction in complex urban areas

NASA Astrophysics Data System (ADS)

Leroyer, S.; Bélair, S.; Husain, S.; Vionnet, V.

2013-12-01

A Sub-kilometer atmospheric modeling system with grid-spacings of 2.5 km, 1 km and 250 m and including urban processes is currently being developed at the Meteorological Service of Canada (MSC) in order to provide more accurate weather forecasts at the city scale. Atmospheric lateral boundary conditions are provided with the 15-km Canadian Regional Deterministic Prediction System (RDPS). Surface physical processes are represented with the Town Energy Balance (TEB) model for the built-up covers and with the Interactions between the Surface, Biosphere, and Atmosphere (ISBA) land surface model for the natural covers. In this study, several research experiments over large metropolitan areas and using observational networks at the urban scale are presented, with a special emphasis on the representation of local atmospheric circulations and their impact on extreme weather forecasting. First, numerical simulations are performed over the Vancouver metropolitan area during a summertime Intense Observing Period (IOP of 14-15 August 2008) of the Environmental Prediction in Canadian Cities (EPiCC) observational network. The influence of the horizontal resolution on the fine-scale representation of the sea-breeze development over the city is highlighted (Leroyer et al., 2013). Then severe storms cases occurring in summertime within the Greater Toronto Area (GTA) are simulated. In view of supporting the 2015 PanAmerican and Para-Pan games to be hold in GTA, a dense observational network has been recently deployed over this region to support model evaluations at the urban and meso scales. In particular, simulations are conducted for the case of 8 July 2013 when exceptional rainfalls were recorded. Leroyer, S., S. Bélair, J. Mailhot, S.Z. Husain, 2013: Sub-kilometer Numerical Weather Prediction in an Urban Coastal Area: A case study over the Vancouver Metropolitan Area, submitted to Journal of Applied Meteorology and Climatology.

Improved Impact of Atmospheric Infrared Sounder (AIRS) Radiance Assimilation in Numerical Weather Prediction

NASA Technical Reports Server (NTRS)

Zavodsky, Bradley; Chou, Shih-Hung; Jedlovec, Gary

2012-01-01

Improvements to global and regional numerical weather prediction (NWP) have been demonstrated through assimilation of data from NASA s Atmospheric Infrared Sounder (AIRS). Current operational data assimilation systems use AIRS radiances, but impact on regional forecasts has been much smaller than for global forecasts. Retrieved profiles from AIRS contain much of the information that is contained in the radiances and may be able to reveal reasons for this reduced impact. Assimilating AIRS retrieved profiles in an identical analysis configuration to the radiances, tracking the quantity and quality of the assimilated data in each technique, and examining analysis increments and forecast impact from each data type can yield clues as to the reasons for the reduced impact. By doing this with regional scale models individual synoptic features (and the impact of AIRS on these features) can be more easily tracked. This project examines the assimilation of hyperspectral sounder data used in operational numerical weather prediction by comparing operational techniques used for AIRS radiances and research techniques used for AIRS retrieved profiles. Parallel versions of a configuration of the Weather Research and Forecasting (WRF) model with Gridpoint Statistical Interpolation (GSI) that mimics the analysis methodology, domain, and observational datasets for the regional North American Mesoscale (NAM) model run at the National Centers for Environmental Prediction (NCEP)/Environmental Modeling Center (EMC) are run to examine the impact of each type of AIRS data set. The first configuration will assimilate the AIRS radiance data along with other conventional and satellite data using techniques implemented within the operational system; the second configuration will assimilate AIRS retrieved profiles instead of AIRS radiances in the same manner. Preliminary results of this study will be presented and focus on the analysis impact of the radiances and profiles for selected cases.

Simulation of a severe convective storm using a numerical model with explicitly incorporated aerosols

NASA Astrophysics Data System (ADS)

Lompar, Miloš; Ćurić, Mladjen; Romanic, Djordje

2017-09-01

Despite an important role the aerosols play in all stages of cloud lifecycle, their representation in numerical weather prediction models is often rather crude. This paper investigates the effects the explicit versus implicit inclusion of aerosols in a microphysics parameterization scheme in Weather Research and Forecasting (WRF) - Advanced Research WRF (WRF-ARW) model has on cloud dynamics and microphysics. The testbed selected for this study is a severe mesoscale convective system with supercells that struck west and central parts of Serbia in the afternoon of July 21, 2014. Numerical products of two model runs, i.e. one with aerosols explicitly (WRF-AE) included and another with aerosols implicitly (WRF-AI) assumed, are compared against precipitation measurements from surface network of rain gauges, as well as against radar and satellite observations. The WRF-AE model accurately captured the transportation of dust from the north Africa over the Mediterranean and to the Balkan region. On smaller scales, both models displaced the locations of clouds situated above west and central Serbia towards southeast and under-predicted the maximum values of composite radar reflectivity. Similar to satellite images, WRF-AE shows the mesoscale convective system as a merged cluster of cumulonimbus clouds. Both models over-predicted the precipitation amounts; WRF-AE over-predictions are particularly pronounced in the zones of light rain, while WRF-AI gave larger outliers. Unlike WRF-AI, the WRF-AE approach enables the modelling of time evolution and influx of aerosols into the cloud which could be of practical importance in weather forecasting and weather modification. Several likely causes for discrepancies between models and observations are discussed and prospects for further research in this field are outlined.

Numerical modeling analysis of the mesoscale environment conducive to two tornado events using the COSMO.Gr model over Greece

NASA Astrophysics Data System (ADS)

Avgoustoglou, E.; Matsangouras, I. T.; Pytharoulis, I.; Kamperakis, N.; Mylonas, M.; Nastos, P. T.; Bluestein, H. W.

2018-08-01

The COnsortium for Small-scale MOdeling (COSMO) was formed in October 1998, and its general goal is to develop, improve and maintain a non-hydrostatic limited-area atmospheric model. The COSMO model has been designed both for operational numerical weather prediction (NWP) as well as various scientific applications on the meso-β and meso-γ scale. Two tornado case studies were selected to investigate the ability of COSMO model to depict the characteristics of severe convective weather, which favoured the development of the associated storms. The first tornado (TR01) occurred, close to Ag. Ilias village, 8 Km north-western of Aitoliko city over western Greece on February 7, 2013, while the second tornado (TR02) was developed close to Palio Katramio village, 8 Km southern from Xanthi city over northern Greece on November 25, 2015. Although both tornadoes had a short lifetime, they caused significant damages. The COSMO.GR atmospheric model was initialized with analysis from the European Centre for Medium-Range Weather Forecasts (ECMWF). The resulting numerical products with spatial resolution of 0.02° (∼ 2 km) over the geographical domain of Greece depicted very well the severe convective conditions close to tornadoes formation. The Energy Helicity Index (EHI) diagnostic variable in both numerical simulations showed a gradual increase of values closing to the location and time of the tornadogenesis. Similar to EHI, the storm relative helicity (SRH) spatio-temporal analysis followed a gradual increase prior to the tornadogenesis events and was reduced after them.

Fabrication and researching of weathering resistant double cladding power delivery fiber

NASA Astrophysics Data System (ADS)

Rong, Liang; Ren, Junjiang; Li, Rundong; Wang, Lianping; Zou, Huan

2016-01-01

A novel well weathering resistant power delivery fiber which is of double cladding and high optical energy transmitting ability is developed via fluoroplastic out sheath extruding process. The fiber has been comprehensively evaluated including optical performance, mechanical performance, environmental suitability and laser transmitting property. It is shown that the fiber has not only low attenuation, high numerical aperture and better mechanical bending performance, but also outstanding weathering resistance and high power laser transmitting performance, which implies the qualification of the fiber for various kinds of applying situations, such as laser ignition, laser induced expanding sound underwater, ship-based and airborne laser weapon.

The representation of low-level clouds during the West African monsoon in weather and climate models

NASA Astrophysics Data System (ADS)

Kniffka, Anke; Hannak, Lisa; Knippertz, Peter; Fink, Andreas

2016-04-01

The West African monsoon is one of the most important large-scale circulation features in the tropics and the associated seasonal rainfalls are crucial to rain-fed agriculture and water resources for hundreds of millions of people. However, numerical weather and climate models still struggle to realistically represent salient features of the monsoon across a wide range of scales. Recently it has been shown that substantial errors in radiation and clouds exist in the southern parts of West Africa (8°W-8°E, 5-10°N) during summer. This area is characterised by strong low-level jets associated with the formation of extensive ultra-low stratus clouds. Often persisting long after sunrise, these clouds have a substantial impact on the radiation budget at the surface and thus the diurnal evolution of the planetary boundary layer (PBL). Here we present some first results from a detailed analysis of the representation of these clouds and the associated PBL features across a range of weather and climate models. Recent climate model simulations for the period 1991-2010 run in the framework of the Year of Tropical Convection (YOTC) offer a great opportunity for this analysis. The models are those used for the latest Assessment Report of the Intergovernmental Panel on Climate Change, but for YOTC the model output has a much better temporal resolution, allowing to resolve the diurnal cycle, and includes diabatic terms, allowing to much better assess physical reasons for errors in low-level temperature, moisture and thus cloudiness. These more statistical climate model analyses are complemented by experiments using ICON (Icosahedral non-hydrostatic general circulation model), the new numerical weather prediction model of the German Weather Service and the Max Planck Institute for Meteorology. ICON allows testing sensitivities to model resolution and numerical schemes. These model simulations are validated against (re-)analysis data, satellite observations (e.g. CM SAF cloud and radiation data) and ground-based eye observations of clouds and radiation measurements from weather stations. Our results show that many of the climate models have great difficulties representing the diurnal cycle of winds and clouds, leading to associated errors in radiation. Typical errors include a substantial underestimation of the lowest clouds accompanied by an overestimation of clouds at the top of the monsoon layer, indicating systematic problems in vertical exchange processes, which are also reflected in large errors in jet speed. Consequently, many models show a too flat diurnal cycle in cloudiness. This contribution is part of the EU-funded DACCIWA (Dynamics-Aerosol-Chemistry-Cloud Interactions in West Africa) project that aims to investigate the impact of the drastic increase in anthropogenic emissions in West Africa on the local weather and climate, for example through cloud-aerosol interactions. The analysis of the capability of state-of-the-art numerical models to represent low-level cloudiness presented here is an important requisite for the planned assessments of the influence of anthropogenic aerosol.

Numerical simulations of island effects on airflow and weather during the summer over the island of Oahu

Treesearch

Hiep Van Nguyen; Yie-Leng Chen; Francis Fujioka

2010-01-01

The high-resolution (1.5 km) nonhydrostatic fifth-generation Pennsylvania StateUniversity–National Center for Atmospheric Research (PSU–NCAR) Mesoscale Model (MM5) and an advanced land surface model (LSM) are used to study the island-induced airflow and weather for the island of Oahu, Hawaii, under summer trade wind conditions. Despite Oahu’s relatively small...

First report on Cretaceous paleoweathering rates in western Panthalassa: Evidence of global enhancement of continental weathering during OAE 2

NASA Astrophysics Data System (ADS)

Ohta, T.

2013-12-01

Mid-Cretaceous is characterized by intensified oceanic anoxia (Oceanic Anoxic Events: OAEs) that raised global deposition of organic black shales. Several models have been proposed to explain the cause of the OAEs in conjunction with Cretaceous global warmth, active volcanism, sea-level changes and others. For example, Weissert et al. (1998) proposed a mechanism called 'weathering hypothesis'. In this model, the cause of the OAEs is explained in a following chain reaction, (1) global warmth and increase in atmospheric CO2 enhanced weathering of continental crust, (2) enhanced land weathering led excessive influx of nutrients from continents to oceans, (3) eutrophication enhanced primary productivity, (4) the excessive primary producers consumed dissolved oceanic oxygen that finally led to the OAEs. Several studies, in fact, revealed a causal relation between enhanced weathering and OAEs in northern Tethys region. However, it is necessary to collect worldwide information to unravel the global response of weathering hypothesis as a cause of OAEs. For such reason, the present contribution conducted measurements of the degree of hinterland paleoweathering during OAEs in northern Japan, for the purpose to provide a first report on the relation between continental weathering and OAEs in open ocean, the western Panthalassa Ocean. Aptian to Campanian forearc basin mudstones (Yezo Group) were analyzed by XRF and the degree of hinterland weathering was evaluated by geochemical weathering index (W index; Ohta and Arai, 2007). The W values obtained for the Yezo Group are 30~50, which is equivalent to the W values of recent soils developed in temperate mid-latitude climate. The W values show a fluctuation pattern that is concordant with the Cretaceous paleotemperature changes. This match indicates that the change in paleotemperature governed the weathering rates of East Asian continental crust. In addition, hinterland weathering rates show instantaneous increase during the OAE intervals. Specifically, a clear positive excursion of W value is recorded in the OAE 2 horizon. High-resolution analysis revealed that increase in weathering rate slightly predates the OAE 2, c.a. 100 to 500 ka before the onset of anoxia. Therefore, our results are consistent with the weathering hypothesis in two aspects. As assumed in weathering hypothesis, enhanced hinterland weathering is linked with the OAEs and hinterland weathering precedes the onset of OAEs. Furthermore, our data suggests that, as well as in Tethys Ocean, enhanced hinterland paleoweathering during OAEs also occurred in the open Panathalassa Ocean. This indicates that enhanced hinterland weathering was a global and pervasive event causing OAEs.

The origins of computer weather prediction and climate modeling

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

Lynch, Peter

2008-03-20

Numerical simulation of an ever-increasing range of geophysical phenomena is adding enormously to our understanding of complex processes in the Earth system. The consequences for mankind of ongoing climate change will be far-reaching. Earth System Models are capable of replicating climate regimes of past millennia and are the best means we have of predicting the future of our climate. The basic ideas of numerical forecasting and climate modeling were developed about a century ago, long before the first electronic computer was constructed. There were several major practical obstacles to be overcome before numerical prediction could be put into practice. Amore » fuller understanding of atmospheric dynamics allowed the development of simplified systems of equations; regular radiosonde observations of the free atmosphere and, later, satellite data, provided the initial conditions; stable finite difference schemes were developed; and powerful electronic computers provided a practical means of carrying out the prodigious calculations required to predict the changes in the weather. Progress in weather forecasting and in climate modeling over the past 50 years has been dramatic. In this presentation, we will trace the history of computer forecasting through the ENIAC integrations to the present day. The useful range of deterministic prediction is increasing by about one day each decade, and our understanding of climate change is growing rapidly as Earth System Models of ever-increasing sophistication are developed.« less

The origins of computer weather prediction and climate modeling

NASA Astrophysics Data System (ADS)

Lynch, Peter

2008-03-01

Numerical simulation of an ever-increasing range of geophysical phenomena is adding enormously to our understanding of complex processes in the Earth system. The consequences for mankind of ongoing climate change will be far-reaching. Earth System Models are capable of replicating climate regimes of past millennia and are the best means we have of predicting the future of our climate. The basic ideas of numerical forecasting and climate modeling were developed about a century ago, long before the first electronic computer was constructed. There were several major practical obstacles to be overcome before numerical prediction could be put into practice. A fuller understanding of atmospheric dynamics allowed the development of simplified systems of equations; regular radiosonde observations of the free atmosphere and, later, satellite data, provided the initial conditions; stable finite difference schemes were developed; and powerful electronic computers provided a practical means of carrying out the prodigious calculations required to predict the changes in the weather. Progress in weather forecasting and in climate modeling over the past 50 years has been dramatic. In this presentation, we will trace the history of computer forecasting through the ENIAC integrations to the present day. The useful range of deterministic prediction is increasing by about one day each decade, and our understanding of climate change is growing rapidly as Earth System Models of ever-increasing sophistication are developed.

Generic magnetohydrodynamic model at the Community Coordinated Modeling Center

NASA Astrophysics Data System (ADS)

Honkonen, I. J.; Rastaetter, L.; Glocer, A.

2016-12-01

The Community Coordinated Modeling Center (CCMC) at NASA Goddard Space Flight Center is a multi-agency partnership to enable, support and perform research and development for next-generation space science and space weather models. CCMC currently hosts nearly 100 numerical models and a cornerstone of this activity is the Runs on Request (RoR) system which allows anyone to request a model run and analyse/visualize the results via a web browser. CCMC is also active in the education community by organizing student research contests, heliophysics summer schools, and space weather forecaster training for students, government and industry representatives. Recently a generic magnetohydrodynamic (MHD) model was added to the CCMC RoR system which allows the study of a variety of fluid and plasma phenomena in one, two and three dimensions using a dynamic point-and-click web interface. For example students can experiment with the physics of fundamental wave modes of hydrodynamic and MHD theory, behavior of discontinuities and shocks as well as instabilities such as Kelvin-Helmholtz.Students can also use the model to experiments with numerical effects of models, i.e. how the process of discretizing a system of equations and solving them on a computer changes the solution. This can provide valuable background understanding e.g. for space weather forecasters on the effects of model resolution, numerical resistivity, etc. on the prediction.

Towards Improved Forecasts of Atmospheric and Oceanic Circulations over the Complex Terrain of the Eastern Mediterranean

NASA Technical Reports Server (NTRS)

Chronis, Themis; Case, Jonathan L.; Papadopoulos, Anastasios; Anagnostou, Emmanouil N.; Mecikalski, John R.; Haines, Stephanie L.

2008-01-01

Forecasting atmospheric and oceanic circulations accurately over the Eastern Mediterranean has proved to be an exceptional challenge. The existence of fine-scale topographic variability (land/sea coverage) and seasonal dynamics variations can create strong spatial gradients in temperature, wind and other state variables, which numerical models may have difficulty capturing. The Hellenic Center for Marine Research (HCMR) is one of the main operational centers for wave forecasting in the eastern Mediterranean. Currently, HCMR's operational numerical weather/ocean prediction model is based on the coupled Eta/Princeton Ocean Model (POM). Since 1999, HCMR has also operated the POSEIDON floating buoys as a means of state-of-the-art, real-time observations of several oceanic and surface atmospheric variables. This study attempts a first assessment at improving both atmospheric and oceanic prediction by initializing a regional Numerical Weather Prediction (NWP) model with high-resolution sea surface temperatures (SST) from remotely sensed platforms in order to capture the small-scale characteristics.

Operational Dust Prediction

NASA Technical Reports Server (NTRS)

Benedetti, Angela; Baldasano, Jose M.; Basart, Sara; Benincasa, Francesco; Boucher, Olivier; Brooks, Malcolm E.; Chen, Jen-Ping; Colarco, Peter R.; Gong, Sunlin; Huneeus, Nicolas;

UMTS Network Stations

NASA Astrophysics Data System (ADS)

Hernandez, C.

2010-09-01

The weakness of small island electrical grids implies a handicap for the electrical generation with renewable energy sources. With the intention of maximizing the installation of photovoltaic generators in the Canary Islands, arises the need to develop a solar forecasting system that allows knowing in advance the amount of PV generated electricity that will be going into the grid, from the installed PV power plants installed in the island. The forecasting tools need to get feedback from real weather data in "real time" from remote weather stations. Nevertheless, the transference of this data to the calculation computer servers is very complicated with the old point to point telecommunication systems that, neither allow the transfer of data from several remote weather stations simultaneously nor high frequency of sampling of weather parameters due to slowness of the connection. This one project has developed a telecommunications infrastructure that allows sensorizadas remote stations, to send data of its sensors, once every minute and simultaneously, to the calculation server running the solar forecasting numerical models. For it, the Canary Islands Institute of Technology has added a sophisticated communications network to its 30 weather stations measuring irradiation at strategic sites, areas with high penetration of photovoltaic generation or that have potential to host in the future photovoltaic power plants connected to the grid. In each one of the stations, irradiance and temperature measurement instruments have been installed, over inclined silicon cell, global radiation on horizontal surface and room temperature. Mobile telephone devices have been installed and programmed in each one of the weather stations, which allow the transfer of their data taking advantage of the UMTS service offered by the local telephone operator. Every minute the computer server running the numerical weather forecasting models receives data inputs from 120 instruments distributed over the 30 radiometric stations. As a the result, currently it exist a stable, flexible, safe and economic infrastructure of radiometric stations and telecommunications that allows, on the one hand, to have data in real time from all 30 remote weather stations, and on the other hand allows to communicate with them in order to reprogram them and to carry out maintenance works.

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

NASA Astrophysics Data System (ADS)

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

2012-12-01

To better understand and communicate the important roles of weather and climate on the coastal environment, a unique publically available tool is being developed to support research, education, and outreach activities. This tool uses virtualization technologies to facilitate an interactive, hands-on environment in which students, researchers, and general public can perform their own numerical modeling experiments. While prior efforts have focused solely on the study of the coastal and estuary environments, this effort incorporates the community supported weather and climate model (WRF-ARW) into the Coastal Science Educational Virtual Appliance (CSEVA), an education tool used to assist in the learning of coastal transport processes; storm surge and inundation; and evacuation modeling. The Weather Research and Forecasting (WRF) Model is a next-generation, community developed and supported, mesoscale numerical weather prediction system designed to be used internationally for research, operations, and teaching. It includes two dynamical solvers (ARW - Advanced Research WRF and NMM - Nonhydrostatic Mesoscale Model) as well as a data assimilation system. WRF-ARW is the ARW dynamics solver combined with other components of the WRF system which was developed primarily at NCAR, community support provided by the Mesoscale and Microscale Meteorology (MMM) division of National Center for Atmospheric Research (NCAR). Included with WRF is the WRF Pre-processing System (WPS) which is a set of programs to prepare input for real-data simulations. The CSEVA is based on the Grid Appliance (GA) framework and is built using virtual machine (VM) and virtual networking technologies. Virtualization supports integration of an operating system, libraries (e.g. Fortran, C, Perl, NetCDF, etc. necessary to build WRF), web server, numerical models/grids/inputs, pre-/post-processing tools (e.g. WPS / RIP4 or UPS), graphical user interfaces, "Cloud"-computing infrastructure and other tools into a single ready-to-use package. Thus, the previous ornery task of setting up and compiling these tools becomes obsolete and the research, educator or student can focus on using the tools to study the interactions between weather, climate and the coastal environment. The incorporation of WRF into the CSEVA has been designed to be synergistic with the extensive online tutorials and biannual tutorials hosted by NCAR. Included are working examples of the idealized test simulations provided with WRF (2D sea breeze and squalls, a large eddy simulation, a Held and Suarez simulation, etc.) To demonstrate the integration of weather, coastal and coastal science education, example applications are being developed to demonstrate how the system can be used to couple a coastal and estuarine circulation, transport and storm surge model with downscale reanalysis weather and future climate predictions. Documentation, tutorials and the enhanced CSEVA itself will be found on the web at: http://cseva.coastal.ufl.edu.

The application of heliospheric imaging to space weather operations: Lessons learned from published studies

NASA Astrophysics Data System (ADS)

Harrison, Richard A.; Davies, Jackie A.; Biesecker, Doug; Gibbs, Mark

2017-08-01

The field of heliospheric imaging has matured significantly over the last 10 years—corresponding, in particular, to the launch of NASA's STEREO mission and the successful operation of the heliospheric imager (HI) instruments thereon. In parallel, this decade has borne witness to a marked increase in concern over the potentially damaging effects of space weather on space and ground-based technological assets, and the corresponding potential threat to human health, such that it is now under serious consideration at governmental level in many countries worldwide. Hence, in a political climate that recognizes the pressing need for enhanced operational space weather monitoring capabilities most appropriately stationed, it is widely accepted, at the Lagrangian L1 and L5 points, it is timely to assess the value of heliospheric imaging observations in the context of space weather operations. To this end, we review a cross section of the scientific analyses that have exploited heliospheric imagery—particularly from STEREO/HI—and discuss their relevance to operational predictions of, in particular, coronal mass ejection (CME) arrival at Earth and elsewhere. We believe that the potential benefit of heliospheric images to the provision of accurate CME arrival predictions on an operational basis, although as yet not fully realized, is significant and we assert that heliospheric imagery is central to any credible space weather mission, particularly one located at a vantage point off the Sun-Earth line.

Ionospheric Scintillation Explorer (ISX)

NASA Astrophysics Data System (ADS)

Iuliano, J.; Bahcivan, H.

2015-12-01

NSF has recently selected Ionospheric Scintillation Explorer (ISX), a 3U Cubesat mission to explore the three-dimensional structure of scintillation-scale ionospheric irregularities associated with Equatorial Spread F (ESF). ISX is a collaborative effort between SRI International and Cal Poly. This project addresses the science question: To what distance along a flux tube does an irregularity of certain transverse-scale extend? It has been difficult to measure the magnetic field-alignment of scintillation-scale turbulent structures because of the difficulty of sampling a flux tube at multiple locations within a short time. This measurement is now possible due to the worldwide transition to DTV, which presents unique signals of opportunity for remote sensing of ionospheric irregularities from numerous vantage points. DTV spectra, in various formats, contain phase-stable, narrowband pilot carrier components that are transmitted simultaneously. A 4-channel radar receiver will simultaneously record up to 4 spatially separated transmissions from the ground. Correlations of amplitude and phase scintillation patterns corresponding to multiple points on the same flux tube will be a measure of the spatial extent of the structures along the magnetic field. A subset of geometries where two or more transmitters are aligned with the orbital path will be used to infer the temporal development of the structures. ISX has the following broad impact. Scintillation of space-based radio signals is a space weather problem that is intensively studied. ISX is a step toward a CubeSat constellation to monitor worldwide TEC variations and radio wave distortions on thousands of ionospheric paths. Furthermore, the rapid sampling along spacecraft orbits provides a unique dataset to deterministically reconstruct ionospheric irregularities at scintillation-scale resolution using diffraction radio tomography, a technique that enables prediction of scintillations at other radio frequencies, and potentially, mitigation of phase distortions.

Evaluation and economic value of winter weather forecasts

NASA Astrophysics Data System (ADS)

Snyder, Derrick W.

State and local highway agencies spend millions of dollars each year to deploy winter operation teams to plow snow and de-ice roadways. Accurate and timely weather forecast information is critical for effective decision making. Students from Purdue University partnered with the Indiana Department of Transportation to create an experimental winter weather forecast service for the 2012-2013 winter season in Indiana to assist in achieving these goals. One forecast product, an hourly timeline of winter weather hazards produced daily, was evaluated for quality and economic value. Verification of the forecasts was performed with data from the Rapid Refresh numerical weather model. Two objective verification criteria were developed to evaluate the performance of the timeline forecasts. Using both criteria, the timeline forecasts had issues with reliability and discrimination, systematically over-forecasting the amount of winter weather that was observed while also missing significant winter weather events. Despite these quality issues, the forecasts still showed significant, but varied, economic value compared to climatology. Economic value of the forecasts was estimated to be 29.5 million or 4.1 million, depending on the verification criteria used. Limitations of this valuation system are discussed and a framework is developed for more thorough studies in the future.

Weathering Patterns of Forensic Biomarker Compounds and PAHs in Coastal Marsh Sediment Samples since the 2010 Deepwater Horizon Oil Spill

NASA Astrophysics Data System (ADS)

Overton, E. B.; Meyer, B.; Miles, S.; Olson, G.; Adhikari, P. L.

2016-02-01

It has been well established that the composition of oil, when spilled into the marine environment, undergoes substantial changes caused by weathering. The general sequence of this compositional change begins with straight chain alkanes (the fastest to degrade), followed by low molecular weight branched and cyclic alkanes and, finally the aromatics. Most resistant to weathering are the higher molecular weight cyclic and branched alkanes (i.e., the "forensic biomarker compounds" such as the hopanes and steranes) and tri-aromatic ringed steroids. The composition of these biomarker compounds is particularly resistant to change because they are not affected by evaporative weathering, are not water soluble, and are not readily degraded by microbial and/or photo-oxidation. However, after extensive time in the environment, being subjected to numerous weathering factors, biomarker compositional patterns are beginning to exhibit significant changes. This presentation will describe the general weathering patterns of petroleum residues in sediment samples collected from marsh areas of coastal Louisiana over a five year period. Particular attention will focus on compositional changes that have been observed in the steranes and diasteranes compounds that traditionally have been considered the most resistant to compositional changes due to weathering.

Mexican Space Weather Service (SCiESMEX)

NASA Astrophysics Data System (ADS)

Gonzalez-Esparza, J. A.; De la Luz, V.; Corona-Romero, P.; Mejia-Ambriz, J. C.; Gonzalez, L. X.; Sergeeva, M. A.; Romero-Hernandez, E.; Aguilar-Rodriguez, E.

2017-01-01

Legislative modifications of the General Civil Protection Law in Mexico in 2014 included specific references to space hazards and space weather phenomena. The legislation is consistent with United Nations promotion of international engagement and cooperation on space weather awareness, studies, and monitoring. These internal and external conditions motivated the creation of a space weather service in Mexico. The Mexican Space Weather Service (SCiESMEX in Spanish) (www.sciesmex.unam.mx) was initiated in October 2014 and is operated by the Institute of Geophysics at the Universidad Nacional Autonoma de Mexico (UNAM). SCiESMEX became a Regional Warning Center of the International Space Environment Services (ISES) in June 2015. We present the characteristics of the service, some products, and the initial actions for developing a space weather strategy in Mexico. The service operates a computing infrastructure including a web application, data repository, and a high-performance computing server to run numerical models. SCiESMEX uses data of the ground-based instrumental network of the National Space Weather Laboratory (LANCE), covering solar radio burst emissions, solar wind and interplanetary disturbances (by interplanetary scintillation observations), geomagnetic measurements, and analysis of the total electron content (TEC) of the ionosphere (by employing data from local networks of GPS receiver stations).

Realistic natural atmospheric phenomena and weather effects for interactive virtual environments

NASA Astrophysics Data System (ADS)

McLoughlin, Leigh

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

Introduction of the Mobile Platform for the Meteorological Observations in Seoul Metropolitan City of Korea

NASA Astrophysics Data System (ADS)

Baek, K. T.; Lee, S.; Kang, M.; Lee, G.

2016-12-01

Traffic accidents due to adverse weather such as fog, heavy rainfall, flooding and road surface freezing have been increasing in Korea. To reduce damages caused by the severe weather on the road, a forecast service of combined real-time road-wise weather and the traffic situation is required. Conventional stationary meteorological observations in sparse location system are limited to observe the detailed road environment. For this reason, a mobile meteorological observation platform has been coupled in Weather Information Service Engine (WISE) which is the prototype of urban-scale high resolution weather prediction system in Seoul metropolitan area of Korea in early August 2016. The instruments onboard are designed to measure 15 meteorological parameters; pressure, temperature, relative humidity, precipitation, up/down net radiation, up/down longwave radiation, up/down shortwave radiation, road surface condition, friction coefficient, water depth, wind direction and speed. The observations from mobile platform show a distinctive advantage of data collection in need for road conditions and inputs for the numerical forecast model. In this study, we introduce and examine the feasibility of mobile observations in urban weather prediction and applications.

Monitoring a local extreme weather event with the scope of hyperspectral sounding

NASA Astrophysics Data System (ADS)

Satapathy, Jyotirmayee; Jangid, Buddhi Prakash

2018-06-01

Operational space-based hyperspectral Infrared sounders retrieve atmospheric temperature and humidity profiles from the measured radiances. These sounders like Atmospheric InfraRed Sounder, Infrared Atmospheric Sounding Interferometer as well as INSAT-3D sounders on geostationary orbit have proved to be very successful in providing these retrievals on global and regional scales, respectively, with good enough spatio-temporal resolutions and are well competent with that of traditional profiles from radiosondes and models fields. The aim of this work is to show how these new generation hyperspectral Infrared sounders can benefit in real-time weather monitoring. We have considered a regional extreme weather event to demonstrate how the profiles retrieved from these operational sounders are consistent with the environmental conditions which have led to this severe weather event. This work has also made use of data products of Moderate Resolution Imaging Spectroradiometer as well as by radiative transfer simulation of clear and cloudy atmospheric conditions using Numerical Weather Prediction profiles in conjunction with INSAT-3D sounder. Our results indicate the potential use of high-quality hyperspectral atmospheric profiles to aid in delineation of real-time weather prediction.

The effort to increase the space weather forecasting accuracy in KSWC

NASA Astrophysics Data System (ADS)

Choi, J. S.

2017-12-01

The Korean Space Weather Center (KSWC) of the National Radio Research Agency (RRA) is a government agency which is the official source of space weather information for Korean Government and the primary action agency of emergency measure to severe space weather condition as the Regional Warning Center of the International Space Environment Service (ISES). KSWC's main role is providing alerts, watches, and forecasts in order to minimize the space weather impacts on both of public and commercial sectors of satellites, aviation, communications, navigations, power grids, and etc. KSWC is also in charge of monitoring the space weather condition and conducting research and development for its main role of space weather operation in Korea. Recently, KSWC are focusing on increasing the accuracy of space weather forecasting results and verifying the model generated results. The forecasting accuracy will be calculated based on the probability statistical estimation so that the results can be compared numerically. Regarding the cosmic radiation does, we are gathering the actual measured data of radiation does using the instrument by cooperation with the domestic airlines. Based on the measurement, we are going to verify the reliability of SAFE system which was developed by KSWC to provide the cosmic radiation does information with the airplane cabin crew and public users.

A numerical circulation model with topography for the Martian Southern Hemisphere

NASA Technical Reports Server (NTRS)

Mass, C.; Sagan, C.

1975-01-01

A quasi-geostrophic numerical model, including friction, radiation, and the observed planetary topography, is applied to the general circulation of the Martian atmosphere in the Southern Hemisphere at latitudes south of about 35 deg. Near equilibrium weather systems developed after about 5 model days. To avoid violating the quasi-geostrophic approximation, only 0.8 of the already smoothed relief was employed. Weather systems and velocity fields are strikingly tied to topography. A 2mb middle latitude jet stream is found of remarkably terrestrial aspect. Highest surface velocities, both horizontal and vertical, are predicted in western Hellas Planitia and eastern Argyre Planitia, which are observed to be preferred sites of origin of major Martian dust storms. Mean horizontal velocities and vertical velocities are found just above the surface velocity boundary layer.

Study of the tornado event in Greece on March 25, 2009: Synoptic analysis and numerical modeling using modified topography

NASA Astrophysics Data System (ADS)

Matsangouras, I. T.; Nastos, P. T.; Pytharoulis, I.

2016-03-01

Recent research revealed that western Greece and NW Peloponnese are regions that favor prefrontal tornadic incidence. On March 25, 2009 a tornado developed approximately at 10:30 UTC near Varda village (NW Peloponnese). Tornado intensity was T4-T5 (TORRO scale) and consequently caused an economic impact of 350,000 € over the local society. The goals of this study are: (i) to analyze synoptic and remote sensing features regarding the tornado event over NW Peloponnese and (ii) to investigate the role of topography in tornadogenesis triggered under strong synoptic scale forcing over that area. Synoptic analysis was based on the European Centre for Medium-Range Weather Forecasts (ECMWF) data sets. The analysis of daily anomaly of synoptic conditions with respect to 30 years' climatology (1981-2010), was based on the National Centers for Environmental Prediction-National Center for Atmospheric Research (NCEP-NCAR) reanalysis data sets. In addition, numerous remote sensing data sets were derived by the Hellenic National Meteorological Service (HNMS) weather station network in order to better interpret the examined tornado event. Finally, numerical modeling was performed using the non-hydrostatic Weather Research and Forecasting model (WRF), initialized by ECMWF gridded analyses, with telescoping nested grids that allow the representation of atmospheric circulations ranging from the synoptic scale down to the meso-scale. The two numerical experiments were performed on the basis of: (a) the presence and (b) the absence of topography (landscape), so as to determine whether the occurrence of a tornado - identified by diagnostic instability indices - could be indicated by modifying topography. The energy helicity index (EHI), the bulk Richardson number (BRN) shear, the storm-relative environmental helicity (SRH), and the maximum convective available potential energy (MCAPE, for parcels with maximum θe) were considered as principal diagnostic instability variables and employed in both numerical experiments. Furthermore, model verification was conducted, accompanied by analysis of the absolute vorticity budget. Synoptic analysis revealed that the synoptic weather conditions on March 25, 2009 are in agreement with the composite synoptic climatology for tornado days over western Greece. In addition, maximum daily anomalies at the barometric levels of 500, 700, 850 and 925 hPa were found, compared to the climatology of composite mean anomalies for tornado days over western Greece. Numerical simulations revealed that the topography of NW Peloponnese did not constitute an important factor during the tornado event on March 25, 2009, based on EHI, SRH, BRN, and MCAPE analyses.

Airline flight planning - The weather connection

NASA Technical Reports Server (NTRS)

Steinberg, R.

1981-01-01

The history of airline flight planning is briefly reviewed. Over half a century ago, when scheduled airline services began, weather data were almost nonexistent. By the early 1950's a reliable synoptic network provided upper air reports. The next 15 years saw a rapid growth in commercial aviation, and airlines introduced computer techniques to flight planning. The 1970's saw the development of weather satellites. The current state of flight planning activities is analyzed. It is found that accurate flight planning will require meteorological information on a finer scale than can be provided by a synoptic forecast. Opportunities for a new approach are examined, giving attention to the available options, a mesoscale numerical weather prediction model, limited area fine mesh models, man-computer interactive display systems, the use of interactive techniques with the present upper air data base, and the implementation of interactive techniques.

The NASA Severe Thunderstorm Observations and Regional Modeling (NASA STORM) Project

NASA Technical Reports Server (NTRS)

Schultz, Christopher J.; Gatlin, Patrick N.; Lang, Timothy J.; Srikishen, Jayanthi; Case, Jonathan L.; Molthan, Andrew L.; Zavodsky, Bradley T.; Bailey, Jeffrey; Blakeslee, Richard J.; Jedlovec, Gary J.

2016-01-01

The NASA Severe Storm Thunderstorm Observations and Regional Modeling(NASA STORM) project enhanced NASA’s severe weather research capabilities, building upon existing Earth Science expertise at NASA Marshall Space Flight Center (MSFC). During this project, MSFC extended NASA’s ground-based lightning detection capacity to include a readily deployable lightning mapping array (LMA). NASA STORM also enabled NASA’s Short-term Prediction and Research Transition (SPoRT) to add convection allowing ensemble modeling to its portfolio of regional numerical weather prediction (NWP) capabilities. As a part of NASA STORM, MSFC developed new open-source capabilities for analyzing and displaying weather radar observations integrated from both research and operational networks. These accomplishments enabled by NASA STORM are a step towards enhancing NASA’s capabilities for studying severe weather and positions them for any future NASA related severe storm field campaigns.

Major and Daytime Meteor Showers using Global Radio Meteor Observations covering the period 2001-2016

NASA Astrophysics Data System (ADS)

Ogawa, Hiroshi; Steyaert, Christian

2017-10-01

With radio, it is possible to observe meteor activity even in bad weather and during daytime. The research in this paper succeeded in detecting the important stream features, such as peak time, peak level and FWHM (Full Width Half Maximum) in not only major streams but also daytime meteor showers, using worldwide radio forward scattering data covering the period 2001-2016.

Changing Sea Levels

NASA Astrophysics Data System (ADS)

Pugh, David

2004-04-01

Flooding of coastal communities is one of the major causes of environmental disasters world-wide. This textbook explains how sea levels are affected by astronomical tides, weather effects, ocean circulation and climate trends. Based on courses taught by the author in the U.K. and the U.S., it is aimed at undergraduate students at all levels, with non-basic mathematics being confined to Appendices and a website http://publishing.cambridge.org/resources/0521532183/.

Worldwide Emerging Environmental Issues Affecting the U.S. Military. December 2009 Report

DTIC Science & Technology

2009-12-01

serious loss of ice sheets and associated sea-level rise • Amazon rainforest ––increased weather-altering deforestation after passing a critical...scientists agree on some tipping elements that are extremely sensitive to climate shifts and therefore might have an important impact on the planetary...trigger radical changes Scientists point out that an additional important unknown element is the interaction of these and other known elements

Development of a Graphical User Interface to Visualize Surface Observations

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

Buckley, R.L.

1998-07-13

Thousands of worldwide observing stations provide meteorological information near the earth's surface as often as once each hour. This surface data may be plotted on geographical maps to provide the meteorologist useful information regarding weather patterns for a region of interest. This report describes the components and applications of a graphical user interface which have been developed to visualize surface observations at any global location and time of interest.

Extreme weather caused by concurrent cyclone, front and thunderstorm occurrences

PubMed Central

Dowdy, Andrew J.; Catto, Jennifer L.

2017-01-01

Phenomena such as cyclones, fronts and thunderstorms can cause extreme weather in various regions throughout the world. Although these phenomena have been examined in numerous studies, they have not all been systematically examined in combination with each other, including in relation to extreme precipitation and extreme winds throughout the world. Consequently, the combined influence of these phenomena represents a substantial gap in the current understanding of the causes of extreme weather events. Here we present a systematic analysis of cyclones, fronts and thunderstorms in combination with each other, as represented by seven different types of storm combinations. Our results highlight the storm combinations that most frequently cause extreme weather in various regions of the world. The highest risk of extreme precipitation and extreme wind speeds is found to be associated with a triple storm type characterized by concurrent cyclone, front and thunderstorm occurrences. Our findings reveal new insight on the relationships between cyclones, fronts and thunderstorms and clearly demonstrate the importance of concurrent phenomena in causing extreme weather. PMID:28074909

The Czech Hydrometeorological Institute's severe storm nowcasting system

NASA Astrophysics Data System (ADS)

Novak, Petr

2007-02-01

To satisfy requirements for operational severe weather monitoring and prediction, the Czech Hydrometeorological Institute (CHMI) has developed a severe storm nowcasting system which uses weather radar data as its primary data source. Previous CHMI studies identified two methods of radar echo prediction, which were then implemented during 2003 into the Czech weather radar network operational weather processor. The applications put into operations were the Continuity Tracking Radar Echoes by Correlation (COTREC) algorithm, and an application that predicts future radar fields using the wind field derived from the geopotential at 700 hPa calculated from a local numerical weather prediction model (ALADIN). To ensure timely delivery of the prediction products to the users, the forecasts are implemented into a web-based viewer (JSMeteoView) that has been developed by the CHMI Radar Department. At present, this viewer is used by all CHMI forecast offices for versatile visualization of radar and other meteorological data (Meteosat, lightning detection, NWP LAM output, SYNOP data) in the Internet/Intranet environment, and the viewer has detailed geographical navigation capabilities.

Future frequencies of extreme weather events in the National Wildlife Refuges of the conterminous U.S.

USGS Publications Warehouse

Martinuzzi, Sebastian; Allstadt, Andrew J.; Bateman, Brooke L.; Heglund, Patricia J.; Pidgeon, Anna M.; Thogmartin, Wayne E.; Vavrus, Stephen J.; Radeloff, Volker C.

2016-01-01

Climate change is a major challenge for managers of protected areas world-wide, and managers need information about future climate conditions within protected areas. Prior studies of climate change effects in protected areas have largely focused on average climatic conditions. However, extreme weather may have stronger effects on wildlife populations and habitats than changes in averages. Our goal was to quantify future changes in the frequency of extreme heat, drought, and false springs, during the avian breeding season, in 415 National Wildlife Refuges in the conterminous United States. We analyzed spatially detailed data on extreme weather frequencies during the historical period (1950–2005) and under different scenarios of future climate change by mid- and late-21st century. We found that all wildlife refuges will likely experience substantial changes in the frequencies of extreme weather, but the types of projected changes differed among refuges. Extreme heat is projected to increase dramatically in all wildlife refuges, whereas changes in droughts and false springs are projected to increase or decrease on a regional basis. Half of all wildlife refuges are projected to see increases in frequency (> 20% higher than the current rate) in at least two types of weather extremes by mid-century. Wildlife refuges in the Southwest and Pacific Southwest are projected to exhibit the fastest rates of change, and may deserve extra attention. Climate change adaptation strategies in protected areas, such as the U.S. wildlife refuges, may need to seriously consider future changes in extreme weather, including the considerable spatial variation of these changes.

Calling computers names in Swedish

DOE PAGES

Carlsson, Johan

2017-11-01

I very much enjoyed reading Jim Fleming’s article on Carl-Gustaf Rossby and the seminal contributions Rossby made to meteorology. Furthermore, the otherwise excellent article has two errors. Something must have gotten lost in translation to cause Fleming to claim that “Rossby pursued numerical weather prediction in Sweden in an era in which there was no Swedish word for digital computer.” With applied mathematician Germund Dahlquist, Rossby developed a weather model for the Binär Elektronisk Sekvens Kalkylator (BESK; Binary Electronic Sequence Calculator). Designed and built in Sweden, BESK was the world’s fastest computer when it became operational in 1953. From Septembermore » 1954, BESK weather simulations enabled routine 24-hour national forecasts.« less

Quantitative impact of aerosols on numerical weather prediction. Part II: Impacts to IR radiance assimilation

NASA Astrophysics Data System (ADS)

Marquis, J. W.; Campbell, J. R.; Oyola, M. I.; Ruston, B. C.; Zhang, J.

2017-12-01

This is part II of a two-part series examining the impacts of aerosol particles on weather forecasts. In this study, the aerosol indirect effects on weather forecasts are explored by examining the temperature and moisture analysis associated with assimilating dust contaminated hyperspectral infrared radiances. The dust induced temperature and moisture biases are quantified for different aerosol vertical distribution and loading scenarios. The overall impacts of dust contamination on temperature and moisture forecasts are quantified over the west coast of Africa, with the assistance of aerosol retrievals from AERONET, MPL, and CALIOP. At last, methods for improving hyperspectral infrared data assimilation in dust contaminated regions are proposed.

Calling computers names in Swedish

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

Carlsson, Johan

I very much enjoyed reading Jim Fleming’s article on Carl-Gustaf Rossby and the seminal contributions Rossby made to meteorology. Furthermore, the otherwise excellent article has two errors. Something must have gotten lost in translation to cause Fleming to claim that “Rossby pursued numerical weather prediction in Sweden in an era in which there was no Swedish word for digital computer.” With applied mathematician Germund Dahlquist, Rossby developed a weather model for the Binär Elektronisk Sekvens Kalkylator (BESK; Binary Electronic Sequence Calculator). Designed and built in Sweden, BESK was the world’s fastest computer when it became operational in 1953. From Septembermore » 1954, BESK weather simulations enabled routine 24-hour national forecasts.« less

A Madden-Julian oscillation event realistically simulated by a global cloud-resolving model.

PubMed

Miura, Hiroaki; Satoh, Masaki; Nasuno, Tomoe; Noda, Akira T; Oouchi, Kazuyoshi

2007-12-14

A Madden-Julian Oscillation (MJO) is a massive weather event consisting of deep convection coupled with atmospheric circulation, moving slowly eastward over the Indian and Pacific Oceans. Despite its enormous influence on many weather and climate systems worldwide, it has proven very difficult to simulate an MJO because of assumptions about cumulus clouds in global meteorological models. Using a model that allows direct coupling of the atmospheric circulation and clouds, we successfully simulated the slow eastward migration of an MJO event. Topography, the zonal sea surface temperature gradient, and interplay between eastward- and westward-propagating signals controlled the timing of the eastward transition of the convective center. Our results demonstrate the potential making of month-long MJO predictions when global cloud-resolving models with realistic initial conditions are used.

Modeling the Zeeman effect in high altitude SSMIS channels for numerical weather prediction profiles: comparing a fast model and a line-by-line model

NASA Astrophysics Data System (ADS)

Larsson, R.; Milz, M.; Rayer, P.; Saunders, R.; Bell, W.; Booton, A.; Buehler, S. A.; Eriksson, P.; John, V.

2015-10-01

We present a comparison of a reference and a fast radiative transfer model using numerical weather prediction profiles for the Zeeman-affected high altitude Special Sensor Microwave Imager/Sounder channels 19-22. We find that the models agree well for channels 21 and 22 compared to the channels' system noise temperatures (1.9 and 1.3 K, respectively) and the expected profile errors at the affected altitudes (estimated to be around 5 K). For channel 22 there is a 0.5 K average difference between the models, with a standard deviation of 0.24 K for the full set of atmospheric profiles. Same channel, there is 1.2 K in average between the fast model and the sensor measurement, with 1.4 K standard deviation. For channel 21 there is a 0.9 K average difference between the models, with a standard deviation of 0.56 K. Same channel, there is 1.3 K in average between the fast model and the sensor measurement, with 2.4 K standard deviation. We consider the relatively small model differences as a validation of the fast Zeeman effect scheme for these channels. Both channels 19 and 20 have smaller average differences between the models (at below 0.2 K) and smaller standard deviations (at below 0.4 K) when both models use a two-dimensional magnetic field profile. However, when the reference model is switched to using a full three-dimensional magnetic field profile, the standard deviation to the fast model is increased to almost 2 K due to viewing geometry dependencies causing up to ± 7 K differences near the equator. The average differences between the two models remain small despite changing magnetic field configurations. We are unable to compare channels 19 and 20 to sensor measurements due to limited altitude range of the numerical weather prediction profiles. We recommended that numerical weather prediction software using the fast model takes the available fast Zeeman scheme into account for data assimilation of the affected sensor channels to better constrain the upper atmospheric temperatures.

Modeling the Zeeman effect in high-altitude SSMIS channels for numerical weather prediction profiles: comparing a fast model and a line-by-line model

NASA Astrophysics Data System (ADS)

Larsson, Richard; Milz, Mathias; Rayer, Peter; Saunders, Roger; Bell, William; Booton, Anna; Buehler, Stefan A.; Eriksson, Patrick; John, Viju O.

2016-03-01

We present a comparison of a reference and a fast radiative transfer model using numerical weather prediction profiles for the Zeeman-affected high-altitude Special Sensor Microwave Imager/Sounder channels 19-22. We find that the models agree well for channels 21 and 22 compared to the channels' system noise temperatures (1.9 and 1.3 K, respectively) and the expected profile errors at the affected altitudes (estimated to be around 5 K). For channel 22 there is a 0.5 K average difference between the models, with a standard deviation of 0.24 K for the full set of atmospheric profiles. Concerning the same channel, there is 1.2 K on average between the fast model and the sensor measurement, with 1.4 K standard deviation. For channel 21 there is a 0.9 K average difference between the models, with a standard deviation of 0.56 K. Regarding the same channel, there is 1.3 K on average between the fast model and the sensor measurement, with 2.4 K standard deviation. We consider the relatively small model differences as a validation of the fast Zeeman effect scheme for these channels. Both channels 19 and 20 have smaller average differences between the models (at below 0.2 K) and smaller standard deviations (at below 0.4 K) when both models use a two-dimensional magnetic field profile. However, when the reference model is switched to using a full three-dimensional magnetic field profile, the standard deviation to the fast model is increased to almost 2 K due to viewing geometry dependencies, causing up to ±7 K differences near the equator. The average differences between the two models remain small despite changing magnetic field configurations. We are unable to compare channels 19 and 20 to sensor measurements due to limited altitude range of the numerical weather prediction profiles. We recommended that numerical weather prediction software using the fast model takes the available fast Zeeman scheme into account for data assimilation of the affected sensor channels to better constrain the upper atmospheric temperatures.

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

NASA Technical Reports Server (NTRS)

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

2012-01-01

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

Exploration of Objective Functions for Optimal Placement of Weather Stations

NASA Astrophysics Data System (ADS)

Snyder, A.; Dietterich, T.; Selker, J. S.

2016-12-01

Many regions of Earth lack ground-based sensing of weather variables. For example, most countries in Sub-Saharan Africa do not have reliable weather station networks. This absence of sensor data has many consequences ranging from public safety (poor prediction and detection of severe weather events), to agriculture (lack of crop insurance), to science (reduced quality of world-wide weather forecasts, climate change measurement, etc.). The Trans-African Hydro-Meteorological Observatory (TAHMO.org) project seeks to address these problems by deploying and operating a large network of weather stations throughout Sub-Saharan Africa. To design the TAHMO network, we must determine where to locate each weather station. We can formulate this as the following optimization problem: Determine a set of N sites that jointly optimize the value of an objective function. The purpose of this poster is to propose and assess several objective functions. In addition to standard objectives (e.g., minimizing the summed squared error of interpolated values over the entire region), we consider objectives that minimize the maximum error over the region and objectives that optimize the detection of extreme events. An additional issue is that each station measures more than 10 variables—how should we balance the accuracy of our interpolated maps for each variable? Weather sensors inevitably drift out of calibration or fail altogether. How can we incorporate robustness to failed sensors into our network design? Another important requirement is that the network should make it possible to detect failed sensors by comparing their readings with those of other stations. How can this requirement be met? Finally, we provide an initial assessment of the computational cost of optimizing these various objective functions. We invite everyone to join the discussion at our poster by proposing additional objectives, identifying additional issues to consider, and expanding our bibliography of relevant papers. A prize (derived from grapes grown in Oregon) will be awarded for the most insightful contribution to the discussion!

WWOSC 2014: research needs for better health resilience to weather hazards.

PubMed

Jancloes, Michel; Anderson, Vidya; Gosselin, Pierre; Mee, Carol; Chong, Nicholas J

2015-03-05

The first World Weather Open Science Conference (WWOSC, held from 17-21 August 2014 in Montreal, Québec), provided an open forum where the experience and perspective of a variety of weather information providers and users was combined with the latest application advances in social sciences. A special session devoted to health focused on how best the most recent weather information and communication technologies (ICT) could improve the health emergency responses to disasters resulting from natural hazards. Speakers from a plenary presentation and its corresponding panel shared lessons learnt from different international multidisciplinary initiatives against weather-related epidemics, such as malaria, leptospirosis and meningitis and from public health responses to floods and heat waves such as in Ontario and Quebec, Canada. Participants could bear witness to recent progress made in the use of forecasting tools and in the application of increased spatiotemporal resolutions in the management of weather related health risks through anticipative interventions, early alert and warning and early responses especially by vulnerable groups. There was an agreement that resilience to weather hazards is best developed based on evidence of their health impact and when, at local level, there is a close interaction between health care providers, epidemiologists, climate services, public health authorities and communities. Using near real time health data (such as hospital admission, disease incidence monitoring…) combined with weather information has been recommended to appraise the relevance of decisions and the effectiveness of interventions and to make adjustments when needed. It also helps appraising how people may be more or less vulnerable to a particular hazard depending on the resilience infrastructures and services. This session was mainly attended by climate, environment and social scientists from North American and European countries. Producing a commentary appears to be an effective way to share this session's conclusions to research institutions and public health experts worldwide. It also advocates for better linking operational research and decision making and for appraising the impact of ICT and public health interventions on health.

Tectonic constraints on a deep-seated rock slide in weathered crystalline rocks

NASA Astrophysics Data System (ADS)

Borrelli, Luigi; Gullà, Giovanni

2017-08-01

Deep-seated rock slides (DSRSs), recognised as one of the most important mass wasting processes worldwide, involve large areas and cause several consequences in terms of environmental and economic damage; they result from a complex of controlling features and processes. DSRSs are common in Calabria (southern Italy) where the complex geo-structural setting plays a key role in controlling the geometry of the failure surface and its development. This paper describes an integrated multi-disciplinary approach to investigate a DSRS in Palaeozoic high-grade metamorphic rocks of the Sila Massif; it focuses on the definition of the internal structure and the predisposing factors of the Serra di Buda landslide near the town of Acri, which is a paradigm for numerous landslides in this area. An integrated interdisciplinary study based on geological, structural, and geomorphological investigations-including field observations of weathering grade of rocks, minero-petrographic characterisations, geotechnical investigations and, in particular, fifteen years of displacement monitoring-is presented. Stereoscopic analysis of aerial photographs and field observations indicate that the Serra di Buda landslide consists of two distinct compounded bodies: (i) an older and dormant body ( 7 ha) and (ii) a more recent and active body ( 13 ha) that overlies the previous one. The active landslide shows movement linked to a deep-seated translational rock slide (block slide); the velocity scale ranges from slow (1.6 m/year during paroxysmal stages) to extremely slow (< 16 mm/year during stable creep stages). The geological structures and rock weathering have played a key role in the landslide's initiation and further development. Steep slope angles, rugged topography, river deepening and erosion at the toe of the slope are also responsible for the formation of this landslide. In particular, the landslide shows a strongly tectonic constraint: the flanks are bounded by high-angle faults, and the main basal failure surface developed inside an E-W southward-dipping thrust fault zone. The entire active rock mass (total volume of approximately 6 Mm3) slid at one time on a failure surface that dipped < 27°, and the maximum depth, as determined by inclinometer measurements, was approximately 58 m. Petrographic and mineralogical analyses suggest that the rocks in the thrust zones, where the failure surfaces develop, are highly affected by weathering processes that significantly reduce the rock strength and facilitate the extensive failure of the Serra di Buda landslide. Finally, the landslide's internal structure, according to geotechnical investigations and displacement monitoring, is proposed. The proposed approach and the obtained results can be generalised to typify other deep landslides in similar geological settings.

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

DOE PAGES

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

2017-11-06

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

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

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

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

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

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

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

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

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

Space Weather Storm Responses at Mars: Lessons from A Weakly Magnetized Terrestrial Planet

NASA Astrophysics Data System (ADS)

Luhmann, J. G.; Dong, C. F.; Ma, Y. J.; Curry, S. M.; Li, Yan; Lee, C. O.; Hara, T.; Lillis, R.; Halekas, J.; Connerney, J. E.; Espley, J.; Brain, D. A.; Dong, Y.; Jakosky, B. M.; Thiemann, E.; Eparvier, F.; Leblanc, F.; Withers, P.; Russell, C. T.

2017-10-01

Much can be learned from terrestrial planets that appear to have had the potential to be habitable, but failed to realize that potential. Mars shows evidence of a once hospitable surface environment. The reasons for its current state, and in particular its thin atmosphere and dry surface, are of great interest for what they can tell us about habitable zone planet outcomes. A main goal of the MAVEN mission is to observe Mars' atmosphere responses to solar and space weather influences, and in particular atmosphere escape related to space weather `storms' caused by interplanetary coronal mass ejections (ICMEs). Numerical experiments with a data-validated MHD model suggest how the effects of an observed moderately strong ICME compare to what happens during a more extreme event. The results suggest the kinds of solar and space weather conditions that can have evolutionary importance at a planet like Mars.

Quantitative impact of aerosols on numerical weather prediction. Part I: Direct radiative forcing

NASA Astrophysics Data System (ADS)

Marquis, J. W.; Zhang, J.; Reid, J. S.; Benedetti, A.; Christensen, M.

2017-12-01

While the effects of aerosols on climate have been extensively studied over the past two decades, the impacts of aerosols on operational weather forecasts have not been carefully quantified. Despite this lack of quantification, aerosol plumes can impact weather forecasts directly by reducing surface reaching solar radiation and indirectly through affecting remotely sensed data that are used for weather forecasts. In part I of this study, the direct impact of smoke aerosol plumes on surface temperature forecasts are quantified using a smoke aerosol event affecting the United States Upper-Midwest in 2015. NCEP, ECMWF and UKMO model forecast surface temperature uncertainties are studied with respect to aerosol loading. Smoke aerosol direct cooling efficiencies are derived and the potential of including aerosol particles in operational forecasts is discussed, with the consideration of aerosol trends, especially over regions with heavy aerosol loading.

Weighting Statistical Inputs for Data Used to Support Effective Decision Making During Severe Emergency Weather and Environmental Events

NASA Technical Reports Server (NTRS)

Gardner, Adrian

2010-01-01

National Aeronautical and Space Administration (NASA) weather and atmospheric environmental organizations are insatiable consumers of geophysical, hydrometeorological and solar weather statistics. The expanding array of internet-worked sensors producing targeted physical measurements has generated an almost factorial explosion of near real-time inputs to topical statistical datasets. Normalizing and value-based parsing of such statistical datasets in support of time-constrained weather and environmental alerts and warnings is essential, even with dedicated high-performance computational capabilities. What are the optimal indicators for advanced decision making? How do we recognize the line between sufficient statistical sampling and excessive, mission destructive sampling ? How do we assure that the normalization and parsing process, when interpolated through numerical models, yields accurate and actionable alerts and warnings? This presentation will address the integrated means and methods to achieve desired outputs for NASA and consumers of its data.

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

NASA Astrophysics Data System (ADS)

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

2012-04-01

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

A GEOCLIM simulation of climatic and biogeochemical consequences of Pangea breakup

NASA Astrophysics Data System (ADS)

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

2006-11-01

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

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

NASA Astrophysics Data System (ADS)

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

2009-09-01

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

ECOLES: a Citizen Observers network engaging communities to map climate change at the local level

NASA Astrophysics Data System (ADS)

Thejll, Peter; Walker, Nicholas; Sandholt, Inge; Brown, Ian; Solberg, Rune; Suwala, Jason; Kelly, Richard; Tangen, Helge; Berglund, Robin; Dean, Andy; Engset, Rune; Siewertsen, Bjarne

2016-04-01

Engaging people in environmental studies is an important way to bring across awareness of expected future climate changes, and also a way to measure environmental change in ways that are better or complementary to remote sensing methods. With a hands-on approach, people are more likely to embrace the idea that climate change is occurring, and with modern technologies it is possible to collect quite stunning amounts of relevant data. We suggest several national activities tailored to conditions in each of the participating countries and also to existing national CO-projects. The project focuses on gathering data on biological changes, on weather, and on snow-pack information in Nordic countries as well as Greenland and Canada. Data will be gathered with existing equipment (mobile phones and internet-connected weather stations) and the project provides the means for collation of data into a database for dissemination and quality control. Numerical data collected by small non-professional weather stations or mobile phones with sensors are not directly useful quantitatively for e.g. numerical weather prediction without validation of data quality, but with validation there is a huge untapped potential due to the number of observers. Students are a central part of the project, which also seeks to engage people out and about in nature, and people with their own weather stations or other environmental data-collection activities, as well as passive data collection from mobile phone data sensors in people's bags and pockets. Appropriate software, educational and training materials will be designed with end-users in mind; school-age materials will be produced in the appropriate languages (e.g. Kalaallisut for COs of school age in Greenland).

Evaluation of numerical weather predictions performed in the context of the project DAPHNE

NASA Astrophysics Data System (ADS)

Tegoulias, Ioannis; Pytharoulis, Ioannis; Bampzelis, Dimitris; Karacostas, Theodore

2014-05-01

The region of Thessaly in central Greece is one of the main areas of agricultural production in Greece. Severe weather phenomena affect the agricultural production in this region with adverse effects for farmers and the national economy. For this reason the project DAPHNE aims at tackling the problem of drought by means of weather modification through the development of the necessary tools to support the application of a rainfall enhancement program. In the present study the numerical weather prediction system WRF-ARW is used, in order to assess its ability to represent extreme weather phenomena in the region of Thessaly. WRF is integrated in three domains covering Europe, Eastern Mediterranean and Central-Northern Greece (Thessaly and a large part of Macedonia) using telescoping nesting with grid spacing of 15km, 5km and 1.667km, respectively. The cases examined span throughout the transitional and warm period (April to September) of the years 2008 to 2013, including days with thunderstorm activity. Model results are evaluated against all available surface observations and radar products, taking into account the spatial characteristics and intensity of the storms. Preliminary results indicate a good level of agreement between the simulated and observed fields as far as the standard parameters (such as temperature, humidity and precipitation) are concerned. Moreover, the model generally exhibits a potential to represent the occurrence of the convective activity, but not its exact spatiotemporal characteristics. Acknowledgements This research work has been co-financed by the European Union (European Regional Development Fund) and Greek national funds, through the action "COOPERATION 2011: Partnerships of Production and Research Institutions in Focused Research and Technology Sectors" (contract number 11SYN_8_1088 - DAPHNE) in the framework of the operational programme "Competitiveness and Entrepreneurship" and Regions in Transition (OPC II, NSRF 2007-2013)

Impact of bacterial ice nucleating particles on weather predicted by a numerical weather prediction model

NASA Astrophysics Data System (ADS)

Sahyoun, Maher; Korsholm, Ulrik S.; Sørensen, Jens H.; Šantl-Temkiv, Tina; Finster, Kai; Gosewinkel, Ulrich; Nielsen, Niels W.

2017-12-01

Bacterial ice-nucleating particles (INP) have the ability to facilitate ice nucleation from super-cooled cloud droplets at temperatures just below the melting point. Bacterial INP have been detected in cloud water, precipitation, and dry air, hence they may have an impact on weather and climate. In modeling studies, the potential impact of bacteria on ice nucleation and precipitation formation on global scale is still uncertain due to their small concentration compared to other types of INP, i.e. dust. Those earlier studies did not account for the yet undetected high concentration of nanoscale fragments of bacterial INP, which may be found free or attached to soil dust in the atmosphere. In this study, we investigate the sensitivity of modeled cloud ice, precipitation and global solar radiation in different weather scenarios to changes in the fraction of cloud droplets containing bacterial INP, regardless of their size. For this purpose, a module that calculates the probability of ice nucleation as a function of ice nucleation rate and bacterial INP fraction was developed and implemented in a numerical weather prediction model. The threshold value for the fraction of cloud droplets containing bacterial INP needed to produce a 1% increase in cloud ice was determined at 10-5 to 10-4. We also found that increasing this fraction causes a perturbation in the forecast, leading to significant differences in cloud ice and smaller differences in convective and total precipitation and in net solar radiation reaching the surface. These effects were most pronounced in local convective events. Our results show that bacterial INP can be considered as a trigger factor for precipitation, but not an enhancement factor.

Forecasting of wet snow avalanche activity: Proof of concept and operational implementation

NASA Astrophysics Data System (ADS)

Gobiet, Andreas; Jöbstl, Lisa; Rieder, Hannes; Bellaire, Sascha; Mitterer, Christoph

2017-04-01

State-of-the-art tools for the operational assessment of avalanche danger include field observations, recordings from automatic weather stations, meteorological analyses and forecasts, and recently also indices derived from snowpack models. In particular, an index for identifying the onset of wet-snow avalanche cycles (LWCindex), has been demonstrated to be useful. However, its value for operational avalanche forecasting is currently limited, since detailed, physically based snowpack models are usually driven by meteorological data from automatic weather stations only and have therefore no prognostic ability. Since avalanche risk management heavily relies on timely information and early warnings, many avalanche services in Europe nowadays start issuing forecasts for the following days, instead of the traditional assessment of the current avalanche danger. In this context, the prognostic operation of detailed snowpack models has recently been objective of extensive research. In this study a new, observationally constrained setup for forecasting the onset of wet-snow avalanche cycles with the detailed snow cover model SNOWPACK is presented and evaluated. Based on data from weather stations and different numerical weather prediction models, we demonstrate that forecasts of the LWCindex as indicator for wet-snow avalanche cycles can be useful for operational warning services, but is so far not reliable enough to be used as single warning tool without considering other factors. Therefore, further development currently focuses on the improvement of the forecasts by applying ensemble techniques and suitable post processing approaches to the output of numerical weather prediction models. In parallel, the prognostic meteo-snow model chain is operationally used by two regional avalanche warning services in Austria since winter 2016/2017 for the first time. Experiences from the first operational season and first results from current model developments will be reported.

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.;

Chemical models for martian weathering profiles: Insights into formation of layered phyllosilicate and sulfate deposits

NASA Astrophysics Data System (ADS)

Zolotov, Mikhail Yu.; Mironenko, Mikhail V.

2016-09-01

Numerical chemical models for water-basalt interaction have been used to constrain the formation of stratified mineralogical sequences of Noachian clay-bearing rocks exposed in the Mawrth Vallis region and in other places on cratered martian highlands. The numerical approaches are based on calculations of water-rock type chemical equilibria and models which include rates of mineral dissolution. Results show that the observed clay-bearing sequences could have formed through downward percolation and neutralization of acidic H2SO4-HCl solutions. A formation of weathering profiles by slightly acidic fluids equilibrated with current atmospheric CO2 requires large volumes of water and is inconsistent with observations. Weathering by solutions equilibrated with putative dense CO2 atmospheres leads to consumption of CO2 to abundant carbonates which are not observed in clay stratigraphies. Weathering by H2SO4-HCl solutions leads to formation of amorphous silica, Al-rich clays, ferric oxides/oxyhydroxides, and minor titanium oxide and alunite at the top of weathering profiles. Mg-Fe phyllosilicates, Ca sulfates, zeolites, and minor carbonates precipitate from neutral and alkaline solutions at depth. Acidic weathering causes leaching of Na, Mg, and Ca from upper layers and accumulation of Mg-Na-Ca sulfate-chloride solutions at depth. Neutral MgSO4 type solutions dominate in middle parts of weathering profiles and could occur in deeper layers owing to incomplete alteration of Ca minerals and a limited trapping of Ca to sulfates. Although salts are not abundant in the Noachian geological formations, the results suggest the formation of Noachian salty solutions and their accumulation at depth. A partial freezing and migration of alteration solutions could have separated sulfate-rich compositions from low-temperature chloride brines and contributed to the observed diversity of salt deposits. A Hesperian remobilization and release of subsurface MgSO4 type solutions into newly-formed depressions could account for formation of some massive layered sulfate deposits through freezing or evaporation. This scenario explains the observed deficiency of salts in Noachian formations, a paucity of Hesperian phyllosilicates, and the occurrence of sulfate deposits in Valles Marineris troughs, chaotic terrains, and some craters of the Hesperian age.

Impact of grain size and rock composition on simulated rock weathering

NASA Astrophysics Data System (ADS)

Israeli, Yoni; Emmanuel, Simon

2018-05-01

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

Communicating weather forecast uncertainty: Do individual differences matter?

PubMed

Grounds, Margaret A; Joslyn, Susan L

2018-03-01

Research suggests that people make better weather-related decisions when they are given numeric probabilities for critical outcomes (Joslyn & Leclerc, 2012, 2013). However, it is unclear whether all users can take advantage of probabilistic forecasts to the same extent. The research reported here assessed key cognitive and demographic factors to determine their relationship to the use of probabilistic forecasts to improve decision quality. In two studies, participants decided between spending resources to prevent icy conditions on roadways or risk a larger penalty when freezing temperatures occurred. Several forecast formats were tested, including a control condition with the night-time low temperature alone and experimental conditions that also included the probability of freezing and advice based on expected value. All but those with extremely low numeracy scores made better decisions with probabilistic forecasts. Importantly, no groups made worse decisions when probabilities were included. Moreover, numeracy was the best predictor of decision quality, regardless of forecast format, suggesting that the advantage may extend beyond understanding the forecast to general decision strategy issues. This research adds to a growing body of evidence that numerical uncertainty estimates may be an effective way to communicate weather danger to general public end users. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

Stochastic Parameterization: Toward a New View of Weather and Climate Models

DOE PAGES

Berner, Judith; Achatz, Ulrich; Batté, Lauriane; ...

2017-03-31

The last decade has seen the success of stochastic parameterizations in short-term, medium-range, and seasonal forecasts: operational weather centers now routinely use stochastic parameterization schemes to represent model inadequacy better and to improve the quantification of forecast uncertainty. Developed initially for numerical weather prediction, the inclusion of stochastic parameterizations not only provides better estimates of uncertainty, but it is also extremely promising for reducing long-standing climate biases and is relevant for determining the climate response to external forcing. This article highlights recent developments from different research groups that show that the stochastic representation of unresolved processes in the atmosphere, oceans,more » land surface, and cryosphere of comprehensive weather and climate models 1) gives rise to more reliable probabilistic forecasts of weather and climate and 2) reduces systematic model bias. We make a case that the use of mathematically stringent methods for the derivation of stochastic dynamic equations will lead to substantial improvements in our ability to accurately simulate weather and climate at all scales. Recent work in mathematics, statistical mechanics, and turbulence is reviewed; its relevance for the climate problem is demonstrated; and future research directions are outlined« less

Aerosols and their Impact on Radiation, Clouds, Precipitation & Severe Weather Events

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

Li, Zhanqing; Rosenfeld, Daniel; Fan, Jiwen

Aerosols, the tiny particles suspended in the atmosphere, have been in the forefront of environmental and climate change sciences as the primary atmospheric pollutant and external force affecting Earth’s weather and climate. There are two dominant mechanisms by which aerosols affect weather and climate: aerosol-radiation interactions (ARI) and aerosol-cloud interactions (ACI). ARI arises from aerosol scattering and absorption, which alters the radiation budgets of the atmosphere and surface, while ACI is rooted to the fact that aerosols serve as cloud condensation nuclei and ice nuclei. Both ARI and ACI are coupled with atmospheric dynamics to produce a chain of complexmore » interactions with a large range of meteorological variables that influence both weather and climate. Elaborated here are the impacts of aerosols on the radiation budget, clouds (microphysics, structure, and lifetime), precipitation, and severe weather events (lightning, thunderstorms, hail, and tornados). Depending on environmental variables and aerosol properties, the effects can be both positive and negative, posing the largest uncertainties in the external forcing of the climate system. This has considerably hindered our ability in projecting future climate changes and in doing accurate numerical weather predictions.« less

Stochastic Parameterization: Toward a New View of Weather and Climate Models

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

Berner, Judith; Achatz, Ulrich; Batté, Lauriane

The last decade has seen the success of stochastic parameterizations in short-term, medium-range, and seasonal forecasts: operational weather centers now routinely use stochastic parameterization schemes to represent model inadequacy better and to improve the quantification of forecast uncertainty. Developed initially for numerical weather prediction, the inclusion of stochastic parameterizations not only provides better estimates of uncertainty, but it is also extremely promising for reducing long-standing climate biases and is relevant for determining the climate response to external forcing. This article highlights recent developments from different research groups that show that the stochastic representation of unresolved processes in the atmosphere, oceans,more » land surface, and cryosphere of comprehensive weather and climate models 1) gives rise to more reliable probabilistic forecasts of weather and climate and 2) reduces systematic model bias. We make a case that the use of mathematically stringent methods for the derivation of stochastic dynamic equations will lead to substantial improvements in our ability to accurately simulate weather and climate at all scales. Recent work in mathematics, statistical mechanics, and turbulence is reviewed; its relevance for the climate problem is demonstrated; and future research directions are outlined« less

Evaluation of downscaled, gridded climate data for the conterminous United States

USGS Publications Warehouse

Robert J. Behnke,; Stephen J. Vavrus,; Andrew Allstadt,; Thomas P. Albright,; Thogmartin, Wayne E.; Volker C. Radeloff,

2016-01-01

Weather and climate affect many ecological processes, making spatially continuous yet fine-resolution weather data desirable for ecological research and predictions. Numerous downscaled weather data sets exist, but little attempt has been made to evaluate them systematically. Here we address this shortcoming by focusing on four major questions: (1) How accurate are downscaled, gridded climate data sets in terms of temperature and precipitation estimates?, (2) Are there significant regional differences in accuracy among data sets?, (3) How accurate are their mean values compared with extremes?, and (4) Does their accuracy depend on spatial resolution? We compared eight widely used downscaled data sets that provide gridded daily weather data for recent decades across the United States. We found considerable differences among data sets and between downscaled and weather station data. Temperature is represented more accurately than precipitation, and climate averages are more accurate than weather extremes. The data set exhibiting the best agreement with station data varies among ecoregions. Surprisingly, the accuracy of the data sets does not depend on spatial resolution. Although some inherent differences among data sets and weather station data are to be expected, our findings highlight how much different interpolation methods affect downscaled weather data, even for local comparisons with nearby weather stations located inside a grid cell. More broadly, our results highlight the need for careful consideration among different available data sets in terms of which variables they describe best, where they perform best, and their resolution, when selecting a downscaled weather data set for a given ecological application.

Use of MODIS Cloud Top Pressure to Improve Assimilation Yields of AIRS Radiances in GSI

NASA Technical Reports Server (NTRS)

Zavodsky, Bradley; Srikishen, Jayanthi

2014-01-01

Improvements to global and regional numerical weather prediction have been demonstrated through assimilation of data from NASA's Atmospheric Infrared Sounder (AIRS). Current operational data assimilation systems use AIRS radiances, but impact on regional forecasts has been much smaller than for global forecasts. Previously, it has been shown that cloud top designation associated with quality control procedures within the Gridpoint Statistical Interpolation (GSI) system used operationally by a number of Joint Center for Satellite Data Assimilation (JCSDA) partners may not provide the best representation of cloud top pressure (CTP). Because this designated CTP determines which channels are cloud-free and, thus, available for assimilation, ensuring the most accurate representation of this value is imperative to obtaining the greatest impact from satellite radiances. This paper examines the assimilation of hyperspectral sounder data used in operational numerical weather prediction by comparing analysis increments and numerical forecasts generated using operational techniques with a research technique that swaps CTP from the Moderate-resolution Imaging Spectroradiometer (MODIS) for the value of CTP calculated from the radiances within GSI.

Evaluating aerosol impacts on Numerical Weather Prediction in two extreme dust and biomass-burning events

NASA Astrophysics Data System (ADS)

Remy, Samuel; Benedetti, Angela; Jones, Luke; Razinger, Miha; Haiden, Thomas

2014-05-01

The WMO-sponsored Working Group on Numerical Experimentation (WGNE) set up a project aimed at understanding the importance of aerosols for numerical weather prediction (NWP). Three cases are being investigated by several NWP centres with aerosol capabilities: a severe dust case that affected Southern Europe in April 2012, a biomass burning case in South America in September 2012, and an extreme pollution event in Beijing (China) which took place in January 2013. At ECMWF these cases are being studied using the MACC-II system with radiatively interactive aerosols. Some preliminary results related to the dust and the fire event will be presented here. A preliminary verification of the impact of the aerosol-radiation direct interaction on surface meteorological parameters such as 2m Temperature and surface winds over the region of interest will be presented. Aerosol optical depth (AOD) verification using AERONET data will also be discussed. For the biomass burning case, the impact of using injection heights estimated by a Plume Rise Model (PRM) for the biomass burning emissions will be presented.

Urban pluvial flood prediction: a case study evaluating radar rainfall nowcasts and numerical weather prediction models as model inputs.

PubMed

Thorndahl, Søren; Nielsen, Jesper Ellerbæk; Jensen, David Getreuer

2016-12-01

Flooding produced by high-intensive local rainfall and drainage system capacity exceedance can have severe impacts in cities. In order to prepare cities for these types of flood events - especially in the future climate - it is valuable to be able to simulate these events numerically, both historically and in real-time. There is a rather untested potential in real-time prediction of urban floods. In this paper, radar data observations with different spatial and temporal resolution, radar nowcasts of 0-2 h leadtime, and numerical weather models with leadtimes up to 24 h are used as inputs to an integrated flood and drainage systems model in order to investigate the relative difference between different inputs in predicting future floods. The system is tested on the small town of Lystrup in Denmark, which was flooded in 2012 and 2014. Results show it is possible to generate detailed flood maps in real-time with high resolution radar rainfall data, but rather limited forecast performance in predicting floods with leadtimes more than half an hour.

Sharing of Data Products From CPTEC/INPE and New Developments for Data Distribution

NASA Astrophysics Data System (ADS)

Almeida, W. G.; Lima, A. A.; Pessoa, A. S.; Ferreira, A. T.; Mendes, M. V.; Ferreira, N. J.; Silva Dias, M. F.; Yoksas, T.

2006-05-01

The CPTEC is the Center for Weather Forecast and Climatic Analysis, a division of the INPE, the Brazilian National Institute for Space Research. The CPTEC is an operational and research center, that runs the fastest supercomputer and is a pioneer in global and regional numerical weather forecasting in South America. The INPE is a traditional provider of data, softwares and services for researchers, forecasters and decision makers in Brazil and South America. The institution is a reference for space science, satellite imagery, and environmental studies. Several of the INPE's departments and centers, like the CPTEC, have a variety of valuable datasets, many of them freely available. Currently the politics of "free data and software" is being strengthened, as the INPE's administration has stated it as a priority for the following years. The CPTEC/INPE distributes outputs from several numerical models, like the COLA/CPTEC global model, and regional models for South America, among others. The web and FTP servers also are used to disseminate satellite imagery, satellite derived products, and data from INPE's automated reporting network. Products from the GTS data also are available. To improve these services new servers for FTP and internet are being installed. The data-sharing component of the Unidata Internet Data Distribution (IDD) also is being used to disseminate these data to university participants in both the South American IDD-Brazil and North American IDD. The IDD- Brasil is the expansion of the IDD system in Brazil, and now is delivering data to a rapidly increasing community of university users. Some months ago the CPTEC finished the installation of two new LDM/IDD servers for data relaying and dissemination. With this infrastructure the author believe that the LDM/IDD demand in South America must be attended for the next three years. Some projects and developments are under execution to provide external access to broader set of meteorological and hydro-meteorological data from CPTEC's databases. Under the auspices of the PROTIM (Program for Information Technology Applied to Meteorology), a project supported by one Brazilian governmental foundation (FINEP), the CPTEC embarked on several developments to open the internal databases for free external access. We view the data dissemination infrastructure installed in the INPE as the beginnings of a continent-wide network that can act for multi-way sharing of locally held data sets with peers worldwide.

Orogen and long-term carbon cycle, what numerical modelling can tell us about their interactions.

NASA Astrophysics Data System (ADS)

Maffre, P.; Godderis, Y.; Carretier, S.; Ladant, J. B.; Moquet, J. S.; Donnadieu, Y.

2017-12-01

If the uplift of current mountain ranges is often cited as a possible cause for Cenozoic cooling and the onset of the quaternary glaciation, this hypothesis is highly discussed. The main reason is that mountain uplift has a wide range of consequences, turning on or of sources or sinks of CO2. Most of these CO2 fluxes are still poorly constrained. Indeed, high erosion rates of mountain ranges increase silicate weathering by increasing fresh material supply (Goddéris et al. 2017) and enhance organic matter burial throughout intense sediment discharge by rivers (Galy et al. 2007). Yet, the effect of fresh matter supply by erosion is different if it happens on a weathering-limited or a supply-limited place (West 2012), and as eroded clasts are often weathered in pediments or floodplains (Moquet et al 2011, Lupker et al. 2012), it makes the issue more complex. Moreover, mountain ranges dramatically alter local and global climatic pattern by affecting atmospheric and oceanic circulation (Maffre et al. 2017), which must have consequences on weathering efficiency. Finally, it has been shown that the CO2 source due to sulphur oxidation can locally exceed the CO2 sink associated to silicate weathering (Torres et al. 2016) and may be relevant at geological timescale (Torres et al. 2014). Our aim here is to investigate theses processes in a global model in order to quantify their relative importance. We used the spatially resolved numerical model GEOCLIM (geoclimmodel.worpress.com) to test the effect of orography on CO2 fluxes with present-day continent configuration. We designed for that purpose two experiments, with and without orography, everything else kept as present-day state. Preliminary results show antagonist effects of mountain ranges. While erosion acts to enhance weathering efficiency when mountains are built, dryer and cooler conditions triggered by reorganization of ocean-atmosphere circulation act to reduce it. A first quantification using weathering data to constraint the model gives a probable range of 30% less to 100% more weathering with mountains (at constant CO2), depending on the sensitivity to the model to climate pattern or erosion. The uncertainty is primarily due to the lack of data.

Meteorological tools in support to the railway security system on the Calabria region

NASA Astrophysics Data System (ADS)

Laviola, Sante; Gabriele, Salvatore; Iovine, Giulio; Baldini, Luca; Chiravalloti, Francesco; Federico, Stefano; Miglietta, Marcello Mario; Milani, Lisa; Procopio, Antonio; Roberto, Nicoletta; Tiesi, Alessandro; Agostino, Mario; Niccoli, Raffaele; Stassi, Sergio; Rago, Valeria

2017-04-01

RAMSES (RAilway Meteorological SEcurity System) is a pilot project co-funded by the Italian Railway Company - RFI S.p.A. and conceived for the mitigation of the hydrological risk along the Calabria railways. RAMSES aims at improving the forecast of very short life-cycle convection systems, responsible of intense and localized rainfalls affecting small catchment areas, which are often underestimated by the numerical weather models and even non-adequately detected by the network of sparse raingauges. The RAMSES operational design is based on a synergistic and integrated architecture, providing a series of information able to identify the most active convective cells and monitoring their evolution in terms of vertical structure, rain intensity and geo-hydrological effects at ground (debris flow, landslides, collapses of bridges, erosion of the ballast). The RAMSES meteorological component is designed to identify and track the short-term evolution (15-60 min) of convective cells, by means of imaging techniques based on dual-polarization weather radar and Meteosat data. In support of this quasi-real time analysis, the numerical model WRF provides the weather forecast at 3-6 hours range by ingesting, through the assimilation system LAPS, the observational data (rain gauges, ground weather stations, radar, satellites) in order to improve the initial condition. Finally, the hydraulic flow modeling is used to assess the ground effects in terms of landslide susceptibility, rainfall-runoff intensity, debris impact on the drainage network and evaluate of risk along the railway track.

A Case Study of the Impact of AIRS Temperature Retrievals on Numerical Weather Prediction

NASA Technical Reports Server (NTRS)

Reale, O.; Atlas, R.; Jusem, J. C.

2004-01-01

Large errors in numerical weather prediction are often associated with explosive cyclogenesis. Most studes focus on the under-forecasting error, i.e. cases of rapidly developing cyclones which are poorly predicted in numerical models. However, the over-forecasting error (i.e., to predict an explosively developing cyclone which does not occur in reality) is a very common error that severely impacts the forecasting skill of all models and may also present economic costs if associated with operational forecasting. Unnecessary precautions taken by marine activities can result in severe economic loss. Moreover, frequent occurrence of over-forecasting can undermine the reliance on operational weather forecasting. Therefore, it is important to understand and reduce the prdctions of extreme weather associated with explosive cyclones which do not actually develop. In this study we choose a very prominent case of over-forecasting error in the northwestern Pacific. A 960 hPa cyclone develops in less than 24 hour in the 5-day forecast, with a deepening rate of about 30 hPa in one day. The cyclone is not versed in the analyses and is thus a case of severe over-forecasting. By assimilating AIRS data, the error is largely eliminated. By following the propagation of the anomaly that generates the spurious cyclone, it is found that a small mid-tropospheric geopotential height negative anomaly over the northern part of the Indian subcontinent in the initial conditions, propagates westward, is amplified by orography, and generates a very intense jet streak in the subtropical jet stream, with consequent explosive cyclogenesis over the Pacific. The AIRS assimilation eliminates this anomaly that may have been caused by erroneous upper-air data, and represents the jet stream more correctly. The energy associated with the jet is distributed over a much broader area and as a consequence a multiple, but much more moderate cyclogenesis is observed.

Applied environmental fluid mechanics: what's the weather in your backyard?

NASA Astrophysics Data System (ADS)

Chow, F. K.

2011-12-01

The microclimates of the San Francisco Bay Area can lead to 30-40F differences in temperature from the coast to just 30 miles inland. The reasons for this include local topography which affects development of the atmospheric boundary layer. A Bay Area resident's experience of fog, air pollution, and weather events therefore differs greatly depending on exactly where they live. Such local weather phenomena provide a natural topic for introduction to boundary layer processes and are the basis of a new course developed at the University of California, Berkeley. This course complements the PI's research focus on numerical methods applied to atmospheric boundary layer flow over complex terrain. This new outreach and research-based course was created to teach students about the boundary layer and teach them how to use a community weather prediction model, WRF, to simulate conditions in the local area, while at the same time being actively involved in public outreach. The course was offered in the Civil and Environmental Engineering department with the collaboration and support of the Lawrence Hall of Science, Berkeley's public science museum. The students chose topics such as air quality, wind energy, climate change, and plume dispersion, all applied to the local San Francisco Bay Area. The students conducted independent research on their team projects, involving literature reviews, numerical model setup, and analysis of model results through comparison with field observations. The outreach component of the course included website design and culminated in demonstrations at the Lawrence Hall of Science. The seven student teams presented hands-on demos to 300-400 visitors, mostly kids 4-9 years old and their parents. Involving students directly in outreach efforts is hoped to encourage continued integration of research and education in their own careers. Early exposure to numerical modeling also improves student technical skills for future career experiences . Given positive feedback from students, the course will now be offered regularly as a senior design class which will also fulfill engineering graduation requirements.

Weather and seasonal climate prediction for South America using a multi-model superensemble

NASA Astrophysics Data System (ADS)

Chaves, Rosane R.; Ross, Robert S.; Krishnamurti, T. N.

2005-11-01

This work examines the feasibility of weather and seasonal climate predictions for South America using the multi-model synthetic superensemble approach for climate, and the multi-model conventional superensemble approach for numerical weather prediction, both developed at Florida State University (FSU). The effect on seasonal climate forecasts of the number of models used in the synthetic superensemble is investigated. It is shown that the synthetic superensemble approach for climate and the conventional superensemble approach for numerical weather prediction can reduce the errors over South America in seasonal climate prediction and numerical weather prediction.For climate prediction, a suite of 13 models is used. The forecast lead-time is 1 month for the climate forecasts, which consist of precipitation and surface temperature forecasts. The multi-model ensemble is comprised of four versions of the FSU-Coupled Ocean-Atmosphere Model, seven models from the Development of a European Multi-model Ensemble System for Seasonal to Interannual Prediction (DEMETER), a version of the Community Climate Model (CCM3), and a version of the predictive Ocean Atmosphere Model for Australia (POAMA). The results show that conditions over South America are appropriately simulated by the Florida State University Synthetic Superensemble (FSUSSE) in comparison to observations and that the skill of this approach increases with the use of additional models in the ensemble. When compared to observations, the forecasts are generally better than those from both a single climate model and the multi-model ensemble mean, for the variables tested in this study.For numerical weather prediction, the conventional Florida State University Superensemble (FSUSE) is used to predict the mass and motion fields over South America. Predictions of mean sea level pressure, 500 hPa geopotential height, and 850 hPa wind are made with a multi-model superensemble comprised of six global models for the period January, February, and December of 2000. The six global models are from the following forecast centers: FSU, Bureau of Meteorology Research Center (BMRC), Japan Meteorological Agency (JMA), National Centers for Environmental Prediction (NCEP), Naval Research Laboratory (NRL), and Recherche en Prevision Numerique (RPN). Predictions of precipitation are made for the period January, February, and December of 2001 with a multi-analysis-multi-model superensemble where, in addition to the six forecast models just mentioned, five additional versions of the FSU model are used in the ensemble, each with a different initialization (analysis) based on different physical initialization procedures. On the basis of observations, the results show that the FSUSE provides the best forecasts of the mass and motion field variables to forecast day 5, when compared to both the models comprising the ensemble and the multi-model ensemble mean during the wet season of December-February over South America. Individual case studies show that the FSUSE provides excellent predictions of rainfall for particular synoptic events to forecast day 3. Copyright

Space Weather Around the World: An IHY Education Program

NASA Astrophysics Data System (ADS)

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

2007-05-01

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

Projecting future precipitation and temperature at sites with diverse climate through multiple statistical downscaling schemes

NASA Astrophysics Data System (ADS)

Vallam, P.; Qin, X. S.

2017-10-01

Anthropogenic-driven climate change would affect the global ecosystem and is becoming a world-wide concern. Numerous studies have been undertaken to determine the future trends of meteorological variables at different scales. Despite these studies, there remains significant uncertainty in the prediction of future climates. To examine the uncertainty arising from using different schemes to downscale the meteorological variables for the future horizons, projections from different statistical downscaling schemes were examined. These schemes included statistical downscaling method (SDSM), change factor incorporated with LARS-WG, and bias corrected disaggregation (BCD) method. Global circulation models (GCMs) based on CMIP3 (HadCM3) and CMIP5 (CanESM2) were utilized to perturb the changes in the future climate. Five study sites (i.e., Alice Springs, Edmonton, Frankfurt, Miami, and Singapore) with diverse climatic conditions were chosen for examining the spatial variability of applying various statistical downscaling schemes. The study results indicated that the regions experiencing heavy precipitation intensities were most likely to demonstrate the divergence between the predictions from various statistical downscaling methods. Also, the variance computed in projecting the weather extremes indicated the uncertainty derived from selection of downscaling tools and climate models. This study could help gain an improved understanding about the features of different downscaling approaches and the overall downscaling uncertainty.

El Nino winners and losers declared

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

Kerr, R.A.

Last spring human forecasters thought they saw signs of an imminent warming of the tropical Pacific, a classic El Nino, that could wreak havoc with weather around the globe. Researchers running computer models, on the other hand, saw a slight warming but not enough for an El Nino. The modelers were right. The season for El Ninos has ended and nothing happened. Since the models came online about 5 years ago, there have been two contests to predict El Ninos, which occur every 3 to 7 years, and the models have won both. The models are still experimental, but themore » general feeling is that they're indicating the right trends. The prospect of having reliable El Nino prediction models is good news beyond the small coterie of tropical Pacific specialists. Worldwide weather patterns are closely tied to El Nino cycles.« less

Modeled Forecasts of Dengue Fever in San Juan, PR Using NASA Satellite Enhanced Weather Forecasts

NASA Technical Reports Server (NTRS)

Morin, Cory; Quattrochi, Dale; Zavodsky, Bradley; Case, Jonathan

2015-01-01

Dengue virus is transmitted between humans and mosquitoes of the genus Aedes and causes approximately 96 million cases of disease (dengue fever) each year (Bhatet al. 2013). Symptoms of dengue fever include fever, headache, nausea, vomiting, and eye, muscle and joint pain (CDC). More sever manifestations such as abdominal pain, bleeding from nose and gums, vomiting of blood, and clammy skin occur in rare cases of dengue hemorrhagic fever (CDC). Dengue fever occurs throughout tropical and sub-tropical regions worldwide, however, the geographical range and size of epidemics is increasing. Weather and climate are drivers of dengue virus transmission dynamics (Morin et al. 2013) by affecting mosquito proliferation and the virus extrinsic incubation period (i.e. required time for the virus to replicate and disseminate within the mosquito before it can retransmit the virus).

Inertial confinement fusion for energy: overview of the ongoing experimental, theoretical and numerical studies

NASA Astrophysics Data System (ADS)

Jacquemot, S.

2017-10-01

This paper provides an overview of the results presented at the 26th IAEA Fusion Energy Conference in the field of inertial confinement fusion for energy, covering its various experimental, numerical/theoretical and technological facets, as well as the different paths towards ignition that are currently followed worldwide.

Working Group 1 "Advanced GNSS Processing Techniques" of the COST Action GNSS4SWEC: Overview of main achievements

NASA Astrophysics Data System (ADS)

Douša, Jan; Dick, Galina; Kačmařík, Michal; Václavovic, Pavel; Pottiaux, Eric; Zus, Florian; Brenot, Hugues; Moeller, Gregor; Hinterberger, Fabian; Pacione, Rosa; Stuerze, Andrea; Eben, Kryštof; Teferle, Norman; Ding, Wenwu; Morel, Laurent; Kaplon, Jan; Hordyniec, Pavel; Rohm, Witold

2017-04-01

The COST Action ES1206 GNSS4SWEC addresses new exploitations of the synergy between developments in GNSS and meteorological communities. The Working Group 1 (Advanced GNSS processing techniques) deals with implementing and assessing new methods for GNSS tropospheric monitoring and precise positioning exploiting all modern GNSS constellations, signals, products etc. Besides other goals, WG1 coordinates development of advanced tropospheric products in support of weather numerical and non-numerical nowcasting. These are ultra-fast and high-resolution tropospheric products available in real time or in a sub-hourly fashion and parameters in support of monitoring an anisotropy of the troposphere, e.g. horizontal gradients and tropospheric slant path delays. This talk gives an overview of WG1 activities and, particularly, achievements in two activities, Benchmark and Real-time demonstration campaigns. For the Benchmark campaign a complex data set of GNSS observations and various meteorological data were collected for a two-month period in 2013 (May-June) which included severe weather events in central Europe. An initial processing of data sets from GNSS and numerical weather models (NWM) provided independently estimated reference parameters - ZTDs and tropospheric horizontal gradients. The comparison of horizontal tropospheric gradients from GNSS and NWM data demonstrated a very good agreement among independent solutions with negligible biases and an accuracy of about 0.5 mm. Visual comparisons of maps of zenith wet delays and tropospheric horizontal gradients showed very promising results for future exploitations of advanced GNSS tropospheric products in meteorological applications such as severe weather event monitoring and weather nowcasting. The Benchmark data set is also used for an extensive validation of line-of-sight tropospheric Slant Total Delays (STD) from GNSS, NWM-raytracing and Water Vapour Radiometer (WVR) solutions. Seven institutions delivered their STDs estimated based on GNSS observations processed using different software and strategies. STDs from NWM ray-tracing came from three institutions using four different NWM models. Results show generally a very good mutual agreement among all solutions from all techniques. The influence of adding not cleaned GNSS post-fit residuals, i.e. residuals that still contains non-tropospheric systematic effects such as multipath, to estimated STDs will be presented. The Real-time demonstration campaign aims at enhancing and assessing ultra-fast GNSS tropospheric products for severe weather and NWM nowcasting. Results are showed from real-time demonstrations as well as offline production simulating real-time using Benchmark campaign.

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

PubMed Central

Quegan, Shaun; Banwart, Steven A.

2017-01-01

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

Chemical studies of H chondrites. II - Weathering effects in the Victoria Land, Antarctic population and comparison of two Antarctic populations with non-Antarctic falls

NASA Astrophysics Data System (ADS)

Dennison, J. E.; Lipschutz, M. E.

1987-03-01

The authors report RNAA data for 14 siderophile, lithophile and chalcophile volatile/mobile trace elements in interior portions of 45 different H4-6 chondrites (49 samples) from Victoria Land, Antarctica and 5 H5 chondrites from the Yamato Mts., Antarctica. Relative to H5 chondrites of weathering types A and B, all elements are depleted (10 at statistically significant levels) in extensively weathered (types B/C and C) samples. Chondrites of weathering types A and B seem compositionally uncompromised and as useful as contemporary falls for trace-element studies. When data distributions for these 14 trace elements in non-Antarctic H chondrite falls and unpaired samples from Victoria Land and from the Yamato Mts. (Queen Maud Land) are compared statistically, numerous significant differences are apparent. These and other differences give ample cause to doubt that the various sample populations derive from the same parent population. The observed differences do no reflect weathering, chance or other trivial causes: a preterrestrial source must be responsible.

Mexican Space Weather Service (SCIESMEX)

NASA Astrophysics Data System (ADS)

Gonzalez-Esparza, A.; De la Luz, V.; Mejia-Ambriz, J. C.; Aguilar-Rodriguez, E.; Corona-Romero, P.; Gonzalez, L. X.

2015-12-01

Recent modifications of the Civil Protection Law in Mexico include now specific mentions to space hazards and space weather phenomena. During the last few years, the UN has promoted international cooperation on Space Weather awareness, studies and monitoring. Internal and external conditions motivated the creation of a Space Weather Service in Mexico (SCIESMEX). The SCIESMEX (www.sciesmex.unam.mx) is operated by the Geophysics Institute at the National Autonomous University of Mexico (UNAM). The UNAM has the experience of operating several critical national services, including the National Seismological Service (SSN); besides that has a well established scientific group with expertise in space physics and solar- terrestrial phenomena. The SCIESMEX is also related with the recent creation of the Mexican Space Agency (AEM). The project combines a network of different ground instruments covering solar, interplanetary, geomagnetic, and ionospheric observations. The SCIESMEX has already in operation computing infrastructure running the web application, a virtual observatory and a high performance computing server to run numerical models. SCIESMEX participates in the International Space Environment Services (ISES) and in the Inter-progamme Coordination Team on Space Weather (ICTSW) of the Word Meteorological Organization (WMO).

Interactions between tectonics, silicate weathering, and climate explored with carbon cycle modeling

NASA Astrophysics Data System (ADS)

Penman, D. E.; Caves Rugenstein, J. K.; Ibarra, D. E.; Winnick, M.

2017-12-01

Earth's long-term carbon cycle is thought to benefit from a stabilizing negative feedback in the form of CO2 consumption by the chemical weathering of silicate minerals: during periods of elevated atmospheric pCO2, chemical weathering rates increase, thus consuming more atmospheric CO2 and cooling global climate, whereas during periods of low pCO2, weathering rates decrease, allowing buildup of CO2 in the atmosphere and warming. At equilibrium, CO2 consumption by silicate weathering balances volcanic CO2 degassing at a specific atmospheric pCO2 dictated by the relationship between total silicate weathering rate and pCO2: Earth's "weathering curve." We use numerical carbon cycle modeling to demonstrate that the shape and slope of the weathering curve is crucial to understanding proposed tectonic controls on pCO2 and climate. First, the shape of the weathering curve dictates the equilibrium response of the carbon cycle to changes in the rate of background volcanic/solid Earth CO2 degassing, which has been suggested to vary significantly with plate tectonic reorganizations over geologic timescales. Second, we demonstrate that if tectonic events can significantly change the weathering curve, this can act as an effective driver of pCO2 and climate on tectonic timescales by changing the atmospheric pCO2 at which silicate weathering balances a constant volcanic/solid Earth degassing rate. Finally, we review the complex interplay of environmental factors that affect modern weathering rates in the field and highlight how the resulting uncertainty surrounding the shape of Earth's weathering curve significantly hampers our ability to quantitatively predict the response of pCO2 and climate to tectonic forcing, and thus represents a substantial knowledge gap in Earth science. We conclude with strategies for closing this knowledge gap by using precise paleoclimatic reconstructions of intervals with known tectonic forcings.

Historical Time Series of Extreme Convective Weather in Finland

NASA Astrophysics Data System (ADS)

Laurila, T. K.; Mäkelä, A.; Rauhala, J.; Olsson, T.; Jylhä, K.

2016-12-01

Thunderstorms, lightning, tornadoes, downbursts, large hail and heavy precipitation are well-known for their impacts to human life. In the high latitudes as in Finland, these hazardous warm season convective weather events are focused in the summer season, roughly from May to September with peak in the midsummer. The position of Finland between the maritime Atlantic and the continental Asian climate zones makes possible large variability in weather in general which reflects also to the occurrence of severe weather; the hot, moist and extremely unstable air masses sometimes reach Finland and makes possible for the occurrence of extreme and devastating weather events. Compared to lower latitudes, the Finnish climate of severe convection is "moderate" and contains a large year-to-year variation; however, behind the modest annual average is hidden the climate of severe weather events that practically every year cause large economical losses and sometimes even losses of life. Because of the increased vulnerability of our modern society, these episodes have gained recently plenty of interest. During the decades, the Finnish Meteorological Institute (FMI) has collected observations and damage descriptions of severe weather episodes in Finland; thunderstorm days (1887-present), annual number of lightning flashes (1960-present), tornados (1796-present), large hail (1930-present), heavy rainfall (1922-present). The research findings show e.g. that a severe weather event may occur practically anywhere in the country, although in general the probability of occurrence is smaller in the Northern Finland. This study, funded by the Finnish Research Programme on Nuclear Power Plant Safety (SAFIR), combines the individual Finnish severe weather time series' and examines their trends, cross-correlation and correlations with other atmospheric parameters. Furthermore, a numerical weather model (HARMONIE) simulation is performed for a historical severe weather case for analyzing how well the present state-of-the-art models grasp these small-scale weather phenomena. Our results give important background for estimating the Finnish severe weather climate in the future.

An Analysis of Numerical Weather Prediction of the Diabatic Rossby Vortex

DTIC Science & Technology

2014-06-01

Forecast SLP Mean and Spread ...............................................................................................148   2.   DRV02 72 Hour...ECMWF Ensemble Forecast SLP Mean and Spread ...............................................................................................149   3...DRV03 72 Hour ECMWF Ensemble Forecast SLP Mean and Spread

Glossary - NOAA's National Weather Service

Science.gov Websites

Organization Search NWS All NOAA Go Local forecast by "City, St" Search by city. Press enter or Text Bulletins By State By Message Type National Forecast Models Numerical Models Statistical Models

ENVIRONMENTAL TECHNOLOGY VERIFICATION (ETV) PROGRAM: WET-WEATHER FLOW/SOURCE WATER PROTECTION

EPA Science Inventory

This paper presents an overview of the Environmental Protection Agency's (EPA) Environmental Technology Verification (ETV) program which was established to overcome the numerous impediments to commercialization experienced by developers of innovative environmental technologies. ...

Impact of a variational objective analysis scheme on a regional area numerical model: The Italian Air Force Weather Service experience

NASA Astrophysics Data System (ADS)

Bonavita, M.; Torrisi, L.

2005-03-01

A new data assimilation system has been designed and implemented at the National Center for Aeronautic Meteorology and Climatology of the Italian Air Force (CNMCA) in order to improve its operational numerical weather prediction capabilities and provide more accurate guidance to operational forecasters. The system, which is undergoing testing before operational use, is based on an “observation space” version of the 3D-VAR method for the objective analysis component, and on the High Resolution Regional Model (HRM) of the Deutscher Wetterdienst (DWD) for the prognostic component. Notable features of the system include a completely parallel (MPI+OMP) implementation of the solution of analysis equations by a preconditioned conjugate gradient descent method; correlation functions in spherical geometry with thermal wind constraint between mass and wind field; derivation of the objective analysis parameters from a statistical analysis of the innovation increments.

Research on regional numerical weather prediction

NASA Technical Reports Server (NTRS)

Kreitzberg, C. W.

1976-01-01

Extension of the predictive power of dynamic weather forecasting to scales below the conventional synoptic or cyclonic scales in the near future is assessed. Lower costs per computation, more powerful computers, and a 100 km mesh over the North American area (with coarser mesh extending beyond it) are noted at present. Doubling the resolution even locally (to 50 km mesh) would entail a 16-fold increase in costs (including vertical resolution and halving the time interval), and constraints on domain size and length of forecast. Boundary conditions would be provided by the surrounding 100 km mesh, and time-varying lateral boundary conditions can be considered to handle moving phenomena. More physical processes to treat, more efficient numerical techniques, and faster computers (improved software and hardware) backing up satellite and radar data could produce further improvements in forecasting in the 1980s. Boundary layer modeling, initialization techniques, and quantitative precipitation forecasting are singled out among key tasks.

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

NASA Astrophysics Data System (ADS)

Crosman, Erik T.; Horel, John D.

2017-09-01

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

Estimating 1 min rain rate distributions from numerical weather prediction

NASA Astrophysics Data System (ADS)

Paulson, Kevin S.

2017-01-01

Internationally recognized prognostic models of rain fade on terrestrial and Earth-space EHF links rely fundamentally on distributions of 1 min rain rates. Currently, in Rec. ITU-R P.837-6, these distributions are generated using the Salonen-Poiares Baptista method where 1 min rain rate distributions are estimated from long-term average annual accumulations provided by numerical weather prediction (NWP). This paper investigates an alternative to this method based on the distribution of 6 h accumulations available from the same NWPs. Rain rate fields covering the UK, produced by the Nimrod network of radars, are integrated to estimate the accumulations provided by NWP, and these are linked to distributions of fine-scale rain rates. The proposed method makes better use of the available data. It is verified on 15 NWP regions spanning the UK, and the extension to other regions is discussed.

The role of sediments stored in valleys in modulating the Quaternary weathering flux variations

NASA Astrophysics Data System (ADS)

Carretier, Sebastien; Goddéris, Yves; Vigier, Nathalie; Maffre, Pierre

2017-04-01

Silicate weathering is known to be central to the regulation of atmospheric CO2. Yet it is unclear how weathering responds to climatic variations. Data sets based on different proxies in sediment cores suggest either negligible Quaternary silicate weathering variations, or more weathering during wet and hot periods, or even the reverse. For example, a recent study based on d7Li in clay of Himalayan river terraces suggests, counter-intuitively, a less intense weathering during hot and wet periods compared to dry periods for the last 40 ka, with no clear physical explanation. We analyse catchment scale weathering signals using the numerical model Cidre, coupling landscape evolution with chemical weathering. Chemical weathering occurs within a regolith, either produced in situ at a rate depending on regolith thickness, temperature and precipitation, or corresponding to a deposit. The chemical flux is calculated from the dissolution of granitoid clasts, first exhumed on the hillslopes and then transported and potentially stocked in the valleys. This approach accounts for part of the stochastic nature of grain weathering within a catchment. We prescribe an uplift to an initial horizontal surface to reach a dynamic equilibrium under a constant climate. Then, we vary the precipitation rate and the temperature, alternating cold and dry periods with hot and wet periods (10 to 400 ka tested). When these variations are applied to an equilibrium mountain covered by a regolith ("transport-limited"), the weathering outlfux and the erosion flux are larger during wet and hot periods. On the contrary, for less weatherable conditions such that the mountain is not covered by regolith ("kinetically-limited"), the weathering is the highest at the beginning of the dry, cold and low erosive periods. This apparent paradox is explained by the temporary accumulation of sediment in the valleys in response to the drought. The hillslopes being striped, these valley deposits constitute the only weathering reservoir, whose large volume compensates for the unfavourable climatic conditions. Such a behaviour explains out-of-phase weathering signals, and suggests that the dominant weathering reservoir goes back and forth between the hillslopes and the valleys during climatic oscillations.

Data Assimilation of SMAP Observations and the Impact on Weather Forecasts and Heat Stress

NASA Technical Reports Server (NTRS)

Zavodsky, Bradley; Case, Jonathan; Blankenship, Clay; Crosson, William; White, Khristopher

2014-01-01

SPoRT produces real-time LIS soil moisture products for situational awareness and local numerical weather prediction over CONUS, Mesoamerica, and East Africa ?Currently interact/collaborate with operational partners on evaluation of soil moisture products ?Drought/fire ?Extreme heat ?Convective initiation ?Flood and water borne diseases ?Initial efforts to assimilate L2 soil moisture observations from SMOS (as a precursor for SMAP) have been successful ?Active/passive blended product from SMAP will be assimilated similarly and higher spatial resolution should improve on local-scale processes

Hurricane and Monsoon Tracking with Driftsondes

NASA Astrophysics Data System (ADS)

Drobinski, Philippe; Cocquerez, Philippe; Doerenbecher, A.; Hock, Terrence; Lavaysse, C.; Parsons, D.; Redelsperger, J. L.

Tropical cyclones (TCs) are a typical weather threat. The threat can apply to humans, their properties, and activities. Their prediction, particularly their trajectory and intensity, remains difficult. In addition, TCs develop above the tropical oceans where the coverage by in situ observations is poor and within cloud clusters (mesoscale convective systems MCS) that limit the ability of numerical weather prediction (NWP) models to assimilate satellite data [18]. Improved forecast of TCs trajectories is a huge benefit in terms of material costs of evacuations and damage, not being able to quantify saved life.

Angular Distributions of Discrete Mesoscale Mapping Functions

NASA Astrophysics Data System (ADS)

Kroszczyński, Krzysztof

2015-08-01

The paper presents the results of analyses of numerical experiments concerning GPS signal propagation delays in the atmosphere and the discrete mapping functions defined on their basis. The delays were determined using data from the mesoscale non-hydrostatic weather model operated in the Centre of Applied Geomatics, Military University of Technology. A special attention was paid to investigating angular characteristics of GPS slant delays for low angles of elevation. The investigation proved that the temporal and spatial variability of the slant delays depends to a large extent on current weather conditions.

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

NASA Technical Reports Server (NTRS)

Teng, William; Shannon, Harlan

2011-01-01

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

Utilization of Live Localized Weather Information for Sustainable Agriculture

NASA Astrophysics Data System (ADS)

Anderson, J.; Usher, J.

2010-09-01

Authors: Jim Anderson VP, Global Network and Business Development WeatherBug® Professional Jeremy Usher Managing Director, Europe WeatherBug® Professional Localized, real-time weather information is vital for day-to-day agronomic management of all crops. The challenge for agriculture is twofold in that local and timely weather data is not often available for producers and farmers, and it is not integrated into decision-support tools they require. Many of the traditional sources of weather information are not sufficient for agricultural applications because of the long distances between weather stations, meaning the data is not always applicable for on-farm decision making processes. The second constraint with traditional weather information is the timeliness of the data. Most delivery systems are designed on a one-hour time step, whereas many decisions in agriculture are based on minute-by-minute weather conditions. This is especially true for decisions surrounding chemical and fertilizer application and frost events. This presentation will outline how the creation of an agricultural mesonet (weather network) can enable producers and farmers with live, local weather information from weather stations installed in farm/field locations. The live weather information collected from each weather station is integrated into a web-enabled decision support tool, supporting numerous on-farm agronomic activities such as pest management, or dealing with heavy rainfall and frost events. Agronomic models can be used to assess the potential of disease pressure, enhance the farmer's abilities to time pesticide applications, or assess conditions contributing to yield and quality fluctuations. Farmers and industry stakeholders may also view quality-assured historical weather variables at any location. This serves as a record-management tool for viewing previously uncharted agronomic weather events in graph or table form. This set of weather tools is unique and provides a significant enhancement to the agronomic decision-support process. Direct benefits to growers can take the form of increased yield and grade potential, as well as savings in money and time. Pest management strategies become more efficient due to timely and localized disease and pest modelling, and increased efficacy of pest and weed control. Examples from the Canadian Wheat Board (CWB) WeatherFarm weather network will be utilized to illustrate the processes, decision tools and benefits to producers and farmers.

Multiple Weather Factors Affect Apparent Survival of European Passerine Birds

PubMed Central

Salewski, Volker; Hochachka, Wesley M.; Fiedler, Wolfgang

2013-01-01

Weather affects the demography of animals and thus climate change will cause local changes in demographic rates. In birds numerous studies have correlated demographic factors with weather but few of those examined variation in the impacts of weather in different seasons and, in the case of migrants, in different regions. Using capture-recapture models we correlated weather with apparent survival of seven passerine bird species with different migration strategies to assess the importance of selected facets of weather throughout the year on apparent survival. Contrary to our expectations weather experienced during the breeding season did not affect apparent survival of the target species. However, measures for winter severity were associated with apparent survival of a resident species, two short-distance/partial migrants and a long-distance migrant. Apparent survival of two short distance migrants as well as two long-distance migrants was further correlated with conditions experienced during the non-breeding season in Spain. Conditions in Africa had statistically significant but relatively minor effects on the apparent survival of the two long-distance migrants but also of a presumably short-distance migrant and a short-distance/partial migrant. In general several weather effects independently explained similar amounts of variation in apparent survival for the majority of species and single factors explained only relatively low amounts of temporal variation of apparent survival. Although the directions of the effects on apparent survival mostly met our expectations and there are clear predictions for effects of future climate we caution against simple extrapolations of present conditions to predict future population dynamics. Not only did weather explains limited amounts of variation in apparent survival, but future demographics will likely be affected by changing interspecific interactions, opposing effects of weather in different seasons, and the potential for phenotypic and microevolutionary adaptations. PMID:23593131

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

Donner, Leo J.; O'Brien, Travis A.; Rieger, Daniel

Both climate forcing and climate sensitivity persist as stubborn uncertainties limiting the extent to which climate models can provide actionable scientific scenarios for climate change. A key, explicit control on cloud-aerosol interactions, the largest uncertainty in climate forcing, is the vertical velocity of cloud-scale updrafts. Model-based studies of climate sensitivity indicate that convective entrainment, which is closely related to updraft speeds, is an important control on climate sensitivity. Updraft vertical velocities also drive many physical processes essential to numerical weather prediction. Vertical velocities and their role in atmospheric physical processes have been given very limited attention in models for climatemore » and numerical weather prediction. The relevant physical scales range down to tens of meters and are thus frequently sub-grid and require parameterization. Many state-of-science convection parameterizations provide mass fluxes without specifying vertical velocities, and parameterizations which do provide vertical velocities have been subject to limited evaluation against what have until recently been scant observations. Atmospheric observations imply that the distribution of vertical velocities depends on the areas over which the vertical velocities are averaged. Distributions of vertical velocities in climate models may capture this behavior, but it has not been accounted for when parameterizing cloud and precipitation processes in current models. New observations of convective vertical velocities offer a potentially promising path toward developing process-level cloud models and parameterizations for climate and numerical weather prediction. Taking account of scale-dependence of resolved vertical velocities offers a path to matching cloud-scale physical processes and their driving dynamics more realistically, with a prospect of reduced uncertainty in both climate forcing and sensitivity.« less

Sea breeze: Induced mesoscale systems and severe weather

NASA Technical Reports Server (NTRS)

Nicholls, M. E.; Pielke, R. A.; Cotton, W. R.

1990-01-01

Sea-breeze-deep convective interactions over the Florida peninsula were investigated using a cloud/mesoscale numerical model. The objective was to gain a better understanding of sea-breeze and deep convective interactions over the Florida peninsula using a high resolution convectively explicit model and to use these results to evaluate convective parameterization schemes. A 3-D numerical investigation of Florida convection was completed. The Kuo and Fritsch-Chappell parameterization schemes are summarized and evaluated.

Key Issues for Seamless Integrated Chemistry–Meteorology Modeling

EPA Science Inventory

Online coupled meteorology–atmospheric chemistry models have greatly evolved in recent years. Although mainly developed by the air quality modeling community, these integrated models are also of interest for numerical weather prediction and climate modeling, as they can con...

NASA/MSFC FY90 Global Scale Atmospheric Processes Research Program Review

NASA Technical Reports Server (NTRS)

Leslie, Fred W. (Editor)

1990-01-01

Research supported by the Global Atmospheric Research Program at the Marshall Space Flight Center on atmospheric remote sensing, meteorology, numerical weather forecasting, satellite data analysis, cloud precipitation, atmospheric circulation, atmospheric models and related topics is discussed.

Application of a COSMO Mesoscale Model to Assess the Influence of Forest Cover Changes on Regional Weather Conditions

NASA Astrophysics Data System (ADS)

Olchev, A.; Rozinkina, I.; Kuzmina, E.; Nikitin, M.; Rivin, G. S.

2017-12-01

Modern changes in land use and forest cover have a significant influence on local, regional, and global weather and climate conditions. In this study, the mesoscale model COSMO is used to estimate the possible influence of forest cover change in the central part of the East European Plain on regional weather conditions. The "model region" of the study is surrounded by geographical coordinates 55° and 59°N and 28° and 37°E and situated in the central part of a large modeling domain (50° - 70° N and 15° 55° E), covering almost the entire East European Plain in Northern Eurasia. The forests cover about 50% of the area of the "model region". The modeling study includes 3 main numerical experiments. The first assumes total deforestation of the "model region" and replacement of forests by grasslands. The second is represented by afforestation of the "model region." In the third, weather conditions are simulated with present land use and vegetation structures of the "model region." Output of numerical experiments is at 13.2 km grid resolution, and the ERA-Interim global atmospheric reanalysis (with 6-h resolution in time and 0.75°×0.75° in space) is used to quantify initial and boundary conditions. Numerical experiments for the warm period of 2010 taken as an example show that deforestation and afforestation processes in the selected region can lead to significant changes in weather conditions. Deforestation processes in summer conditions can result in increased air temperature and wind speed, reduction of precipitation, lower clouds, and relative humidity. The afforestation process can result in opposite effects (decreased air temperature, increased precipitation, higher air humidity and fog frequency, and strengthened storm winds). Maximum meteorological changes under forest cover changes are projected for the summer months (July and August). It was also shown that changes of some meteorological characteristics (e.g., air temperature) is observed in the "model region" only, and changes in precipitation amount are seen in the entire territory of the East European Plain, even in areas which are a great distance from the boundaries of the "model region." The study was supported by a grant from the Russian Science Foundation (14-14-00956).

Analysis of biases from parallel observations of co-located manual and automatic weather stations in Indonesia

NASA Astrophysics Data System (ADS)

Sopaheluwakan, Ardhasena; Fajariana, Yuaning; Satyaningsih, Ratna; Aprilina, Kharisma; Astuti Nuraini, Tri; Ummiyatul Badriyah, Imelda; Lukita Sari, Dyah; Haryoko, Urip

2017-04-01

Inhomogeneities are often found in long records of climate data. These can occur because of various reasons, among others such as relocation of observation site, changes in observation method, and the transition to automated instruments. Changes to these automated systems are inevitable, and it is taking place worldwide in many of the National Meteorological Services. However this shift of observational practice must be done cautiously and a sufficient period of parallel observation of co-located manual and automated systems should take place as suggested by the World Meteorological Organization. With a sufficient parallel observation period, biases between the two systems can be analyzed. In this study we analyze the biases of a yearlong parallel observation of manual and automatic weather stations in 30 locations in Indonesia. The location of the sites spans from east to west of approximately 45 longitudinal degrees covering different climate characteristics and geographical settings. We study measurements taken by both sensors for temperature and rainfall parameters. We found that the biases from both systems vary from place to place and are more dependent to the setting of the instrument rather than to the climatic and geographical factors. For instance, daytime observations of the automatic weather stations are found to be consistently higher than the manual observation, and vice versa night time observations of the automatic weather stations are lower than the manual observation.

EarthNow: Weather and Climate Connections for 3D Spherical Displays

NASA Astrophysics Data System (ADS)

Rowley, P.; Ackerman, S. A.; Arkin, P. A.; Pisut, D.; Kohrs, R.; Mooney, M. E.; Schollaert, S. E.

2012-12-01

The NOAA Science on a Sphere (SOS) is one of the fastest growing museum and science center exhibits worldwide, with over 80 installations. Rightfully so—few other exhibits captivate and mystify audiences in the way SOS does. Harnessing audience excitement about the science, especially climate change and real-time weather, however, has been challenging for docents. The EarthNow project (http://sphere.ssec.wisc.edu) from the Cooperative Institute for Meteorological Satellite Studies (CIMSS) allows SOS institutions to go beyond the scientific facts to create meaningful visitor experiences about weather and climate connections. CIMSS, in collaboration with the NOAA Environmental Visualization Lab and the Cooperative Institute for Climate and Satellites, regularly updates a blog-style website, providing a central location for SOS facilitators to find timely weather and climate stories to speak about how current events affect and are affected by global change. Along with these stories, the website also provides relevant, visually appealing SOS-formatted datasets and animations with appropriate annotations, leading to easier comprehension by presenters and the public. Along with discussing the logistics and background of the EarthNow project, this presentation will review the results of our front-end and formative evaluations. The evaluation results will not only allow us to showcase how museums and science centers are using EarthNow, but also what museums need to tackle complex and contentious issues like global climate change.;

The Advanced Technology Microwave Sounder (ATMS): A New Operational Sensor Series

NASA Technical Reports Server (NTRS)

Kim, Edward; Lyu, Cheng-H Joseph; Leslie, R. Vince; Baker, Neal; Mo, Tsan; Sun, Ninghai; Bi, Li; Anderson, Mike; Landrum, Mike; DeAmici, Giovanni;

Forecasting Propagation and Evolution of CMEs in an Operational Setting: What Has Been Learned

NASA Technical Reports Server (NTRS)

Zheng, Yihua; Macneice, Peter; Odstrcil, Dusan; Mays, M. L.; Rastaetter, Lutz; Pulkkinen, Antti; Taktakishvili, Aleksandre; Hesse, Michael; Kuznetsova, M. Masha; Lee, Hyesook;

Forecasting propagation and evolution of CMEs in an operational setting: What has been learned

NASA Astrophysics Data System (ADS)

Zheng, Yihua; Macneice, Peter; Odstrcil, Dusan; Mays, M. L.; Rastaetter, Lutz; Pulkkinen, Antti; Taktakishvili, Aleksandre; Hesse, Michael; Masha Kuznetsova, M.; Lee, Hyesook; Chulaki, Anna

2013-10-01

of the major types of solar eruption, coronal mass ejections (CMEs) not only impact space weather, but also can have significant societal consequences. CMEs cause intense geomagnetic storms and drive fast mode shocks that accelerate charged particles, potentially resulting in enhanced radiation levels both in ions and electrons. Human and technological assets in space can be endangered as a result. CMEs are also the major contributor to generating large amplitude Geomagnetically Induced Currents (GICs), which are a source of concern for power grid safety. Due to their space weather significance, forecasting the evolution and impacts of CMEs has become a much desired capability for space weather operations worldwide. Based on our operational experience at Space Weather Research Center at NASA Goddard Space Flight Center (http://swrc.gsfc.nasa.gov), we present here some of the insights gained about accurately predicting CME impacts, particularly in relation to space weather operations. These include: 1. The need to maximize information to get an accurate handle of three-dimensional (3-D) CME kinetic parameters and therefore improve CME forecast; 2. The potential use of CME simulation results for qualitative prediction of regions of space where solar energetic particles (SEPs) may be found; 3. The need to include all CMEs occurring within a 24 h period for a better representation of the CME interactions; 4. Various other important parameters in forecasting CME evolution in interplanetary space, with special emphasis on the CME propagation direction. It is noted that a future direction for our CME forecasting is to employ the ensemble modeling approach.

Analysis of Spatial Autocorrelation for Optimal Observation Network in Korea

NASA Astrophysics Data System (ADS)

Park, S.; Lee, S.; Lee, E.; Park, S. K.

2016-12-01

Many studies for improving prediction of high-impact weather have been implemented, such as THORPEX (The Observing System Research and Predictability Experiment), FASTEX (Fronts and Atlantic Storm-Track Experiment), NORPEX (North Pacific Experiment), WSR/NOAA (Winter Storm Reconnaissance), and DOTSTAR (Dropwindsonde Observations for Typhoon Surveillance near the TAiwan Region). One of most important objectives in these studies is to find effects of observation on forecast, and to establish optimal observation network. However, there are lack of such studies on Korea, although Korean peninsula exhibits a highly complex terrain so it is difficult to predict its weather phenomena. Through building the future optimal observation network, it is necessary to increase utilization of numerical weather prediction and improve monitoring·tracking·prediction skills of high-impact weather in Korea. Therefore, we will perform preliminary study to understand the spatial scale for an expansion of observation system through Spatial Autocorrelation (SAC) analysis. In additions, we will develop a testbed system to design an optimal observation network. Analysis is conducted with Automatic Weather System (AWS) rainfall data, global upper air grid observation (i.e., temperature, pressure, humidity), Himawari satellite data (i.e., water vapor) during 2013-2015 of Korea. This study will provide a guideline to construct observation network for not only improving weather prediction skill but also cost-effectiveness.

The influence of weather on Golden Eagle migration in northwestern Montana

USGS Publications Warehouse

Yates, R.E.; McClelland, B.R.; Mcclelland, P.T.; Key, C.H.; Bennetts, R.E.

2001-01-01

We analyzed the influence of 17 weather factors on migrating Golden Eagles (Aquila chrysaetos) near the Continental Divide in Glacier National Park, Montana, U.S.A. Local weather measurements were recorded at automated stations on the flanks of two peaks within the migration path. During a total of 506 hr of observation, the yearly number of Golden Eagles in autumn counts (1994-96) averaged 1973; spring counts (1995 and 1996) averaged 605 eagles. Mean passage rates (eagles/hr) were 16.5 in autumn and 8.2 in spring. Maximum rates were 137 in autumn and 67 in spring. Using generalized linear modeling, we tested for the effects of weather factors on the number of eagles counted. In the autumn model, the number of eagles increased with increasing air temperature, rising barometric pressure, decreasing relative humidity, and interactions among those factors. In the spring model, the number of eagles increased with increasing wind speed, barometric pressure, and the interaction between these factors. Our data suggest that a complex interaction among weather factors influenced the number of eagles passing on a given day. We hypothesize that in complex landscapes with high topographic relief, such as Glacier National Park, numerous weather factors produce different daily combinations to which migrating eagles respond opportunistically. ?? 2001 The Raptor Research Foundation, Inc.

Does weather affect daily pain intensity levels in patients with acute low back pain? A prospective cohort study.

PubMed

Duong, Vicky; Maher, Chris G; Steffens, Daniel; Li, Qiang; Hancock, Mark J

2016-05-01

The aim of this study was to investigate the influence of various weather parameters on pain intensity levels in patients with acute low back pain (LBP). We performed a secondary analysis using data from the PACE trial that evaluated paracetamol (acetaminophen) in the treatment of acute LBP. Data on 1604 patients with LBP were included in the analysis. Weather parameters (precipitation, temperature, relative humidity, and air pressure) were obtained from the Australian Bureau of Meteorology. Pain intensity was assessed daily on a 0-10 numerical pain rating scale over a 2-week period. A generalised estimating equation analysis was used to examine the relationship between daily pain intensity levels and weather in three different time epochs (current day, previous day, and change between previous and current days). A second model was adjusted for important back pain prognostic factors. The analysis did not show any association between weather and pain intensity levels in patients with acute LBP in each of the time epochs. There was no change in strength of association after the model was adjusted for prognostic factors. Contrary to common belief, the results demonstrated that the weather parameters of precipitation, temperature, relative humidity, and air pressure did not influence the intensity of pain reported by patients during an episode of acute LBP.

Future Missions for Space Weather Specifications and Forecasts

NASA Astrophysics Data System (ADS)

Onsager, T. G.; Biesecker, D. A.; Anthes, R. A.; Maier, M. W.; Gallagher, F. W., III; St Germain, K.

2017-12-01

The progress of technology and the global integration of our economic and security infrastructures have introduced vulnerabilities to space weather that demand a more comprehensive ability to specify and to predict the dynamics of the space environment. This requires a comprehensive network of real-time space-based and ground-based observations with long-term continuity. In order to determine the most cost effective space architectures for NOAA's weather, space weather, and environmental missions, NOAA conducted the NOAA Satellite Observing System Architecture (NSOSA) study. This presentation will summarize the process used to document the future needs and the relative priorities for NOAA's operational space-based observations. This involves specifying the most important observations, defining the performance attributes at different levels of capability, and assigning priorities for achieving the higher capability levels. The highest priority observations recommended by the Space Platform Requirements Working Group (SPRWG) for improvement above a minimal capability level will be described. Finally, numerous possible satellite architectures have been explored to assess the costs and benefits of various architecture configurations.

Benefits of Sharing Information: Supermodel Ensemble and Applications in South America

NASA Astrophysics Data System (ADS)

Dias, P. L.

2006-05-01

A model intercomparison program involving a large number of academic and operational institutions has been implemented in South America since 2003, motivated by the SALLJEX Intercomparison Program in 2003 (a research program focused on the identification of the role of the Andes low level jet moisture transport from the Amazon to the Plata basin) and the WMO/THORPEX (www.wmo.int/thorpex) goals to improve predictability through the proper combination of numerical weather forecasts. This program also explores the potential predictability associated with the combination of a large number of possible scenarios in the time scale of a few days to up to 15 days. Five academic institutions and five operational forecasting centers in several countries in South America, 1 academic institution in the USA, and the main global forecasting centers (NCEP, UKMO, ECMWF) agreed to provide numerical products based on operational and experimental models. The metric for model validation is concentrated on the fit of the forecast to surface observations. Meteorological data from airports, synoptic stations operated by national weather services, automatic data platforms maintained by different institutions, the PIRATA buoys etc are all collected through LDM/NCAR or direct transmission. Approximately 40 models outputs are available on a daily basis, twice a day. A simple procedure based on data assimilation principles was quite successful in combining the available forecasts in order to produce temperature, dew point, wind, pressure and precipitation forecasts at station points in S. America. The procedure is based on removing each model bias at the observational point and a weighted average based on the mean square error of the forecasts. The base period for estimating the bias and mean square error is of the order of 15 to 30 days. Products of the intercomparison model program and the optimal statistical combination of the available forecasts are public and available in real time (www.master.iag.usp.br/). Monitoring of the use of the products reveal a growing trend in the last year (reaching about 10.000 accesses per day in recent months). The intercomparison program provides a rich data set for educational products (real time use in Synoptic Meteorology and Numerical Weather Forecasting lectures), operational weather forecasts in national or regional weather centers and for research purposes. During the first phase of the program it was difficult to convince potential participants to share the information in the public homepage. However, as the system evolved, more and more institutions became associated with the program. The general opinion of the participants is that the system provides an unified metric for evaluation, a forum for discussion of the physical origin of the model forecast differences and therefore improvement of the quality of the numerical guidance.

Explicit simulation of ice particle habits in a Numerical Weather Prediction Model

NASA Astrophysics Data System (ADS)

Hashino, Tempei

2007-05-01

This study developed a scheme for explicit simulation of ice particle habits in Numerical Weather Prediction (NWP) Models. The scheme is called Spectral Ice Habit Prediction System (SHIPS), and the goal is to retain growth history of ice particles in the Eulerian dynamics framework. It diagnoses characteristics of ice particles based on a series of particle property variables (PPVs) that reflect history of microphysieal processes and the transport between mass bins and air parcels in space. Therefore, categorization of ice particles typically used in bulk microphysical parameterization and traditional bin models is not necessary, so that errors that stem from the categorization can be avoided. SHIPS predicts polycrystals as well as hexagonal monocrystals based on empirically derived habit frequency and growth rate, and simulates the habit-dependent aggregation and riming processes by use of the stochastic collection equation with predicted PPVs. Idealized two dimensional simulations were performed with SHIPS in a NWP model. The predicted spatial distribution of ice particle habits and types, and evolution of particle size distributions showed good quantitative agreement with observation This comprehensive model of ice particle properties, distributions, and evolution in clouds can be used to better understand problems facing wide range of research disciplines, including microphysics processes, radiative transfer in a cloudy atmosphere, data assimilation, and weather modification.

Changing Weather Extremes Call for Early Warning of Potential for Catastrophic Fire

NASA Astrophysics Data System (ADS)

Boer, Matthias M.; Nolan, Rachael H.; Resco De Dios, Víctor; Clarke, Hamish; Price, Owen F.; Bradstock, Ross A.

2017-12-01

Changing frequencies of extreme weather events and shifting fire seasons call for enhanced capability to forecast where and when forested landscapes switch from a nonflammable (i.e., wet fuel) state to the highly flammable (i.e., dry fuel) state required for catastrophic forest fires. Current forest fire danger indices used in Europe, North America, and Australia rate potential fire behavior by combining numerical indices of fuel moisture content, potential rate of fire spread, and fire intensity. These numerical rating systems lack the physical basis required to reliably quantify forest flammability outside the environments of their development or under novel climate conditions. Here, we argue that exceedance of critical forest flammability thresholds is a prerequisite for major forest fires and therefore early warning systems should be based on a reliable prediction of fuel moisture content plus a regionally calibrated model of how forest fire activity responds to variation in fuel moisture content. We demonstrate the potential of this approach through a case study in Portugal. We use a physically based fuel moisture model with historical weather and fire records to identify critical fuel moisture thresholds for forest fire activity and then show that the catastrophic June 2017 forest fires in central Portugal erupted shortly after fuels in the region dried out to historically unprecedented levels.

The contributions of Lewis Fry Richardson to drainage theory, soil physics, and the soil-plant-atmosphere continuum

NASA Astrophysics Data System (ADS)

Knight, John; Raats, Peter

2016-04-01

The EGU Division on Nonlinear Processes in Geophysics awards the Lewis Fry Richardson Medal. Richardson's significance is highlighted in http://www.egu.eu/awards-medals/portrait-lewis-fry-richardson/, but his contributions to soil physics and to numerical solutions of heat and diffusion equations are not mentioned. We would like to draw attention to those little known contributions. Lewis Fry Richardson (1881-1953) made important contributions to many fields including numerical weather prediction, finite difference solutions of partial differential equations, turbulent flow and diffusion, fractals, quantitative psychology and studies of conflict. He invented numerical weather prediction during World War I, although his methods were not successfully applied until 1950, after the invention of fast digital computers. In 1922 he published the book `Numerical weather prediction', of which few copies were sold and even fewer were read until the 1950s. To model heat and mass transfer in the atmosphere, he did much original work on turbulent flow and defined what is now known as the Richardson number. His technique for improving the convergence of a finite difference calculation is known as Richardson extrapolation, and was used by John Philip in his 1957 semi-analytical solution of the Richards equation for water movement in unsaturated soil. Richardson's first papers in 1908 concerned the numerical solution of the free surface problem of unconfined flow of water in saturated soil, arising in the design of drain spacing in peat. Later, for the lower boundary of his atmospheric model he needed to understand the movement of heat, liquid water and water vapor in what is now called the vadose zone and the soil plant atmosphere system, and to model coupled transfer of heat and flow of water in unsaturated soil. Finding little previous work, he formulated partial differential equations for transient, vertical flow of liquid water and for transfer of heat and water vapor. He paid considerable attention to the balances of water and energy at the soil-atmosphere and plant-atmosphere interfaces, making use of the concept of transfer resistance introduced by Brown and Escombe (1900) for leaf-atmosphere interfaces. He incorporated finite difference versions of all equations into his numerical weather forecasting model. From 1916, Richardson drove an ambulance in France in World War I, did weather computations in his spare time, and wrote a draft of his book. Later researchers such as L.A. Richards, D.A. de Vries and J.R. Philip from the 1930s to the 1950s were unaware that Richardson had anticipated many of their ideas on soil liquid water, heat, water vapor, and the soil-plant-atmosphere system. The Richards (1931) equation could rightly be called the Richardson (1922) equation! Richardson (1910) developed what we now call the Crank Nicolson implicit method for the heat or diffusion equation. To save effort, he used an explicit three level method after the first time step. Crank and Nicolson (1947) pointed out the instability in the explicit method, and used his implicit method for all time steps. Hanks and Bowers (1962) adapted the Crank Nicolson method to solve the Richards equation. So we could say that Hanks and Bowers used the Richardson finite difference method to solve the Richardson equation for soil water flow!

Adventures in Computational Grids

NASA Technical Reports Server (NTRS)

Walatka, Pamela P.; Biegel, Bryan A. (Technical Monitor)

2002-01-01

Sometimes one supercomputer is not enough. Or your local supercomputers are busy, or not configured for your job. Or you don't have any supercomputers. You might be trying to simulate worldwide weather changes in real time, requiring more compute power than you could get from any one machine. Or you might be collecting microbiological samples on an island, and need to examine them with a special microscope located on the other side of the continent. These are the times when you need a computational grid.

Improving the Long-Term Stability of Atmospheric Surface Deformation Predictions by Mitigating the Effects of Orography Updates in Operational Weather Forecast Models

NASA Astrophysics Data System (ADS)

Dill, Robert; Bergmann-Wolf, Inga; Thomas, Maik; Dobslaw, Henryk

2016-04-01

The global numerical weather prediction model routinely operated at the European Centre for Medium-Range Weather Forecasts (ECMWF) is typically updated about two times a year to incorporate the most recent improvements in the numerical scheme, the physical model or the data assimilation procedures into the system for steadily improving daily weather forecasting quality. Even though such changes frequently affect the long-term stability of meteorological quantities, data from the ECMWF deterministic model is often preferred over alternatively available atmospheric re-analyses due to both the availability of the data in near real-time and the substantially higher spatial resolution. However, global surface pressure time-series, which are crucial for the interpretation of geodetic observables, such as Earth rotation, surface deformation, and the Earth's gravity field, are in particular affected by changes in the surface orography of the model associated with every major change in horizontal resolution happened, e.g., in February 2006, January 2010, and May 2015 in case of the ECMWF operational model. In this contribution, we present an algorithm to harmonize surface pressure time-series from the operational ECMWF model by projecting them onto a time-invariant reference topography under consideration of the time-variable atmospheric density structure. The effectiveness of the method will be assessed globally in terms of pressure anomalies. In addition, we will discuss the impact of the method on predictions of crustal deformations based on ECMWF input, which have been recently made available by GFZ Potsdam.

Application of Numerical Weather Models to Mitigating Atmospheric Artifacts in InSAR

NASA Astrophysics Data System (ADS)

Foster, J. H.; Kealy, J.; Businger, S.; Cherubini, T.; Brooks, B. A.; Albers, S. C.; Lu, Z.; Poland, M. P.; Chen, S.; Mass, C.

2011-12-01

A high-resolution weather "hindcasting" system to model the atmosphere at the time of SAR scene acquisitions has been established to investigate and mitigate the impact of atmospheric water vapor on InSAR deformation maps. Variations in the distributions of water vapor in the atmosphere between SAR acquisitions lead to artifacts in interferograms that can mask real ground motion signals. A database of regional numerical weather prediction model outputs generated by the University of Washington and U.C. Davis for times matching SAR acquisitions was used as "background" for higher resolution analyses of the atmosphere for Mount St Helens volcano in Washington, and Los Angeles in southern California. Using this background, we use LAPS to incrementally incorporate all other available meteorological data sets, including GPS, to explore the impact of additional observations on model accuracy. Our results suggest that, even with significant quantities of contemporaneously measured data, high-resolution atmospheric analyses are unable to model the timing and location of water vapor perturbations accurately enough to produce robust and reliable phase screens that can be directly subtracted from interferograms. Despite this, the analyses are able to reproduce the statistical character of the atmosphere with some confidence, suggesting that, in the absence of unusually dense in-situ measurements (such as is the case with GPS data for Los Angeles), weather analysis can play a valuable role in constraining the power-spectrum expected in an interferogram due to the troposphere. This could be used to provide objective weights to scenes during traditional stacking or to tune the filter parameters in time-series analyses.

Introduction to Global Urban Climatology

NASA Astrophysics Data System (ADS)

Varquez, A. C. G.; Kanda, M.; Kawano, N.; Darmanto, N. S.; Dong, Y.

2016-12-01

Urban heat island (UHI) is a widely investigated phenomenon in the field of urban climate characterized by the warming of urban areas relative to its surrounding rural environs. Being able to understand the mechanism behind the UHI formation of a city and distinguish its impact from that of global climate change is indispensable when identifying adaptation and mitigation strategies. However, the lack of UHI studies many cities especially for developing countries makes it difficult to generalize the mechanism for UHI formation. Thus, there is an impending demand for studies that focus on the simultaneous analyses of UHI and its trends throughout the world. Hence, we propose a subfield of urban climatology, called "global urban climatology" (GUC), which mainly focuses on the uniform understanding of urban climates across all cities, globally. By using globally applicable methodologies to quantify and compare urban heat islands of cities with diverse backgrounds, including their geography, climate, socio-demography, and other factors, a universal understanding of the mechanisms underlying the formation of the phenomenon can be established. The implementation of GUC involves the use of globally acquired historical observation networks, gridded meteorological parameters from climate models, global geographic information system datasets; the construction of a distributed urban parameter database; and the development of techniques necessary to model the urban climate. Research under GUC can be categorized into three approaches. The collaborative approach (1st) relies on the collection of data from micro-scale experiments conducted worldwide with the aid or development of professional social networking platforms; the analytical approach (2nd) relies on the use of global weather station datasets and their corresponding objectively analysed global outputs; and the numerical approach (3rd) relies on the global estimation of high-resolution urban-representative parameters as inputs to global weather modelling. The GUC concept, the pathways through which GUC assessments can be undertaken, and current implementations are introduced. Acknowledgment: This research was supported by the Environment Research and Technology Development Fund (S-14) of the Ministry of the Environment, Japan.

Evaluation of the Weather Research and Forecasting (WRF) Model over Portugal: Case study

NASA Astrophysics Data System (ADS)

Rodrigues, Mónica; Rocha, Alfredo; Monteiro, Ana

2013-04-01

Established in 1756 the Demarcated Douro Region, became the first viticulturist region to be delimited and regulated under worldwide scale. The region has an area of 250000 hectares, from which 45000 are occupied by continuous vineyards (IVDP, 2010). It stretches along the Douro river valleys and its main streams, from the region of Mesão Frio, about 100 kilometers east from Porto town where this river discharges till attaining the frontier with Spain in the east border. Due to its stretching and extension in the W-E direction accompanying the Douro Valley, it is not strange that the region is not homogeneous having, therefore, three sub-regions: Baixo Corgo, Cima Corgo and Douro Superior. The Baixo Corgo the most western region is the "birthplace" of the viticulturalist region. The main purpose of this work is to evaluate and test the quality of a criterion developed to determine the occurrence of frost. This criterion is to be used latter by numerical weather forecasts (WRF-ARW) and put into practice in 16 meteorological stations in the Demarcated Douro Region. Firstly, the criterion was developed to calculate the occurrence of frost based on the meteorological data observed in those 16 stations. Time series of temperatures and precipitation were used for a period of approximately 20 years. It was verified that the meteorological conditions associated to days with frost (SG) and without frost (CG) are different in each station. Afterwards, the model was validated, especially in what concerns the simulation of the daily minimal temperature. Correcting functions were applied to the data of the model, having considerably diminished the errors of simulation. Then the criterion of frost estimate was applied do the output of the model for a period of 2 frost seasons. The results show that WRF simulates successfully the appearance of frost episodes and so can be used in the frost forecasting.

Long range forecasts of the Northern Hemisphere anomalies with antecedent sea surface temperature patterns

NASA Technical Reports Server (NTRS)

Kung, Ernest C.

1994-01-01

The contract research has been conducted in the following three major areas: analysis of numerical simulations and parallel observations of atmospheric blocking, diagnosis of the lower boundary heating and the response of the atmospheric circulation, and comprehensive assessment of long-range forecasting with numerical and regression methods. The essential scientific and developmental purpose of this contract research is to extend our capability of numerical weather forecasting by the comprehensive general circulation model. The systematic work as listed above is thus geared to developing a technological basis for future NASA long-range forecasting.

Characterizing Space Weather Effects in the Post-DMSP Era

NASA Astrophysics Data System (ADS)

Groves, K. M.

2015-12-01

Space weather generally refers to heliophysical phenomena or events that produce a negative impact on manmade systems. While many space weather events originate with impulsive disturbances on the sun, others result from complex internal interactions in the ionosphere-thermosphere system. The reliance of mankind on satellite-based services continues to increase rapidly, yet the global capacity for sensing space weather in the ionosphere seems headed towards decline. A number of recent ionospheric-focused space-based missions are either presently, or soon-to-be, no longer available, and the end of the multi-decade Defense Meteorological Satellite Program is now in sight. The challenge facing the space weather community is how to maintain or increase sensing capabilities in an operational environment constrained by a decreasing numbers of sensors. The upcoming launch of COSMIC-2 in 2016/2018 represents the most significant new capability planned for the future. GNSS RO data has some benefit for background ionospheric models, particularly over regions where ground-based GNSS TEC measurements are unavailable, but the space weather community has a dire need to leverage such missions for far more knowledge of the ionosphere, and specifically for information related to space weather impacts. Meanwhile, the number of ground-based GNSS sensors worldwide has increased substantially, yet progress instrumenting some vastly undersampled regions, such as Africa, remains slow. In fact, the recent loss of support for many existing ground stations in such areas under the former Scintillation Network Decision Aid (SCINDA) program may actually result in a decrease in such sensing sites over the next 1-2 years, abruptly reversing a positive trend established over the last decade. Here we present potential solutions to the challenges these developments pose to the space weather enterprise. Specific topics include modeling advances required to detect and accurately characterize irregularities and associated scintillations from GNSS RO measurements, the exploitation of existing/planned radio beacons for improved bottomside definition and scintillations, and an affordable approach to leverage existing ground stations to expand sensing capacity at critical locations in otherwise data-sparse regions.

WWOSC 2014: Research Needs for Better Health Resilience to Weather Hazards

PubMed Central

Jancloes, Michel; Anderson, Vidya; Gosselin, Pierre; Mee, Carol; Chong, Nicholas J.

2015-01-01

The first World Weather Open Science Conference (WWOSC, held from 17–21 August 2014 in Montreal, Québec), provided an open forum where the experience and perspective of a variety of weather information providers and users was combined with the latest application advances in social sciences. A special session devoted to health focused on how best the most recent weather information and communication technologies (ICT) could improve the health emergency responses to disasters resulting from natural hazards. Speakers from a plenary presentation and its corresponding panel shared lessons learnt from different international multidisciplinary initiatives against weather-related epidemics, such as malaria, leptospirosis and meningitis and from public health responses to floods and heat waves such as in Ontario and Quebec, Canada. Participants could bear witness to recent progress made in the use of forecasting tools and in the application of increased spatiotemporal resolutions in the management of weather related health risks through anticipative interventions, early alert and warning and early responses especially by vulnerable groups. There was an agreement that resilience to weather hazards is best developed based on evidence of their health impact and when, at local level, there is a close interaction between health care providers, epidemiologists, climate services, public health authorities and communities. Using near real time health data (such as hospital admission, disease incidence monitoring…) combined with weather information has been recommended to appraise the relevance of decisions and the effectiveness of interventions and to make adjustments when needed. It also helps appraising how people may be more or less vulnerable to a particular hazard depending on the resilience infrastructures and services. This session was mainly attended by climate, environment and social scientists from North American and European countries. Producing a commentary appears to be an effective way to share this session’s conclusions to research institutions and public health experts worldwide. It also advocates for better linking operational research and decision making and for appraising the impact of ICT and public health interventions on health. PMID:25809508

Effect of woody and herbaceous plants on chemical weathering of basalt material

NASA Astrophysics Data System (ADS)

Mark, N.; Dontsova, K.; Barron-Gafford, G. A.

2011-12-01

Worldwide, semi-arid landscapes are transitioning from shallow-rooted grasslands to mixed vegetation savannas composed of deeper-rooted shrubs. These contrasting growth forms differentially drive below-ground processes because they occupy different soil horizons, are differentially stressed by periods of drought, and unequally stimulate soil weathering. Our study aims to determine the effect of woody and herbaceous plants on weathering of granular basalt serving as a model for soil. We established pots with velvet mesquite (Prosopis veluntina), sideoats grama (Bouteloua curtipendula), and bare-soil pots within two temperature treatments in University of Arizona Biosphere 2. The Desert biome served as the ambient temperature treatment, while the Savanna biome was maintained 4°C warmer to simulate projected air temperatures if climate change continues unabated. Rhizon water samplers were installed at a depth of one inch from the soil surface to monitor root zone exudates (total dissolved carbon and nitrogen), dissolved inorganic carbon, and lithogenic elements resulting from basalt weathering. Soil leachates were collected through the course of the experiment. The anion content of the leachates was determined using the ICS-5000 Reagent-Free ion chromatography system. Dissolved carbon and nitrogen were analyzed by combustion using the Shimadzu TOC-VCSH with TN module. Metals and metalloids were measured using inductively coupled plasma mass spectrometry. Irrigation of the pots was varied in time to simulate periods of drought and determine the effect of stress on root exudation. Leachates from all treatments displayed higher pH and electrical conductivity than water used for irrigation indicating weathering. On average, leachates from the potted grasses displayed higher pH and electrical conductivity than mesquites. This agreed with higher concentrations of organic carbon, a measure of root exudation, and inorganic carbon, measure of soil respiration. Both organic acids exuded by plants and respired CO2 have been linked to mineral weathering. Increased weathering in grass treatments also resulted in higher concentrations of plant nutrients. No effect of temperature on plant exudation or basalt weathering was observed in the course of the experiment. This work links physiological plant responses to temperature and water stress by two vegetation types with below-ground processes that result in soil evolution.

AC-67/FLTSATCOM Launch with Isolated Cam Views/ Freeze of Lightning/ Press Conference

NASA Technical Reports Server (NTRS)

1987-01-01

The FLTSATCOM system provides worldwide, high-priority UHF communications between naval aircraft, ships, submarines, and ground stations and between the Strategic Air Command and the national command authority network. This videotape shows the attempted launch of the 6th member of the satellite system on an Atlas Centaur rocket. Within a minute of launch a problem developed. The initial sign of the problem was the loss of telemetry data. The videotape shows three isolated views of the launch, and then a freeze shot of a lightning strike shortly after the launch. The tape then shows a press conference, with Mr. Wolmaster, Mr. Gibbs, and Air Force Colonel Alsbrooke. Mr. Gibbs summarizes the steps that would be taken to review the launch failure. The questions from the press mostly concern the weather conditions, and the possibility that the weather might have caused the mission failure.

Quantitative assessment of relative roles of drivers of acute respiratory diseases

PubMed Central

Goswami, Prashant; Baruah, Jurismita

2014-01-01

Several thousands of people, including children, suffer from acute respiratory disease (ARD) every year worldwide. Pro-active planning and mitigation for these diseases require identification of the major drivers in a location-specific manner. While the importance of air pollutants in ARD has been extensively studied and emphasized, the role of weather variables has been less explored. With Delhi with its large population and pollution as a test case, we examine the relative roles of air pollution and weather (cold days) in ARD. It is shown that both the number of cold days and air pollution play important roles in ARD load; however, the number of cold days emerges as the major driver. These conclusions are consistent with analyses for several other states in India. The robust association between ARD load and cold days provides basis for estimating and predicting ARD load through dynamical model, as well as impact of climate change. PMID:25322687

Development of Rail Temperature Prediction Model : Research Results

DOT National Transportation Integrated Search

2008-06-01

Preventing track buckling is important to the railroad industry's goal of operational safety. It is a common practice for railroads to impose slow orders during hot weather when the risk of track buckling is high. Numerous factors affect track buckli...

Numerical simulation of the rapid intensification of Hurricane Katrina (2005): Sensitivity to boundary layer parameterization schemes

NASA Astrophysics Data System (ADS)

Liu, Jianjun; Zhang, Feimin; Pu, Zhaoxia

2017-04-01

Accurate forecasting of the intensity changes of hurricanes is an important yet challenging problem in numerical weather prediction. The rapid intensification of Hurricane Katrina (2005) before its landfall in the southern US is studied with the Advanced Research version of the WRF (Weather Research and Forecasting) model. The sensitivity of numerical simulations to two popular planetary boundary layer (PBL) schemes, the Mellor-Yamada-Janjic (MYJ) and the Yonsei University (YSU) schemes, is investigated. It is found that, compared with the YSU simulation, the simulation with the MYJ scheme produces better track and intensity evolution, better vortex structure, and more accurate landfall time and location. Large discrepancies (e.g., over 10 hPa in simulated minimum sea level pressure) are found between the two simulations during the rapid intensification period. Further diagnosis indicates that stronger surface fluxes and vertical mixing in the PBL from the simulation with the MYJ scheme lead to enhanced air-sea interaction, which helps generate more realistic simulations of the rapid intensification process. Overall, the results from this study suggest that improved representation of surface fluxes and vertical mixing in the PBL is essential for accurate prediction of hurricane intensity changes.

The sensitivity of precipitation simulations to the soot aerosol presence

NASA Astrophysics Data System (ADS)

Palamarchuk, Iuliia; Ivanov, Sergiy; Mahura, Alexander; Ruban, Igor

2016-04-01

The role of aerosols in nonlinear feedbacks on atmospheric processes is in a focus of many researches. Particularly, the importance of black carbon particles for evolution of physical weather including precipitation formation and release is investigated by numerical modelling as well as observation networks. However, certain discrepancies between results obtained by different methods are remained. The increasing of complexity in numerical weather modelling systems leads to enlarging a volume of output data and promises to reveal new aspects in complexity of interactions and feedbacks. The Harmonie-38h1.2 model with the AROME physical package is used to study changes in precipitation life-cycle under black carbon polluted conditions. A model configuration includes a radar data assimilation procedure on a high resolution domain covering the Scandinavia region. Model results show that precipitation rate and distribution as well as other variables of atmospheric dynamics and physics over the domain are sensitive to aerosol concentrations. The attention should also be paid to numerical aspects, such as a list of observation types involved in assimilation. The use of high resolution radar information allows to include mesoscale features in initial conditions and to decrease the growth rate of a model error with the lead time.

Regional Climate Change and Development of Public Health Decision Aids

NASA Astrophysics Data System (ADS)

Hegedus, A. M.; Darmenova, K.; Grant, F.; Kiley, H.; Higgins, G. J.; Apling, D.

2011-12-01

According to the World Heath Organization (WHO) climate change is a significant and emerging threat to public health, and changes the way we must look at protecting vulnerable populations. Worldwide, the occurrence of some diseases and other threats to human health depend predominantly on local climate patterns. Rising average temperatures, in combination with changing rainfall patterns and humidity levels, alter the lifecycle and regional distribution of certain disease-carrying vectors, such as mosquitoes, ticks and rodents. In addition, higher surface temperatures will bring heat waves and heat stress to urban regions worldwide and will likely increase heat-related health risks. A growing body of scientific evidence also suggests an increase in extreme weather events such as floods, droughts and hurricanes that can be destructive to human health and well-being. Therefore, climate adaptation and health decision aids are urgently needed by city planners and health officials to determine high risk areas, evaluate vulnerable populations and develop public health infrastructure and surveillance systems. To address current deficiencies in local planning and decision making with respect to regional climate change and its effect on human health, our research is focused on performing a dynamical downscaling with the Weather Research and Forecasting (WRF) model to develop decision aids that translate the regional climate data into actionable information for users. WRF model is initialized with the Max Planck Institute European Center/Hamburg Model version 5 (ECHAM5) General Circulation Model simulations forced with the Special Report on Emissions (SRES) A1B emissions scenario. Our methodology involves development of climatological indices of extreme weather, quantifying the risk of occurrence of water/rodent/vector-borne diseases as well as developing various heat stress related decision aids. Our results indicate that the downscale simulations provide the necessary detailed output required by state and local governments and the private sector to develop climate adaptation plans with respect to human health.

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

NASA Astrophysics Data System (ADS)

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

2006-12-01

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

Uranium adsorption on weathered schist - Intercomparison of modeling approaches

USGS Publications Warehouse

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

2004-01-01

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

Plants and microorganisms as drivers of mineral weathering

NASA Astrophysics Data System (ADS)

Dontsova, K.; Chorover, J.; Maier, R.; Hunt, E.; Zaharescu, D. G.

2011-12-01

Plants and microorganisms play important role in mineral weathering and soil formation modifying their environment to make it more hospitable for life. This presentation summarizes several collaborative studies that focused on understanding how interactions between plants and microorganisms, where plants provide the energy through photosynthesis, drive mineral weathering and result in soil formation. Plants influence weathering through multiple mechanisms that have been previously established, such as increase in CO2 concentration in the soil through root respiration and degradation of plant residues and exudates by heterotrophic microorganisms, release of organic acids that promote mineral dissolution, removal of weathering products from soil solution through uptake, and water redistribution. Weathering processes result in nutrient release that satisfies immediate needs of the plants and microorganisms, as well as precipitation of secondary phases, that provide surfaces for retention of nutrients and organic carbon accumulation. What makes understanding contribution of plants and microorganisms, such as bacteria and fungi, to mineral weathering challenging is the fact that they closely interact, enhancing and amplifying each other's contribution. In order to address multiple processes that contribute to and result from biological weathering a combination of chemical, biological, mineralogical, and computational techniques and methodologies is needed. This complex array of methodologies includes bulk techniques, such as determination of total dissolved organic and inorganic carbon and nitrogen, ion chromatography and high performance liquid chromatography to characterize amount and composition of exuded organic acids, inductively coupled plasma mass spectrometry to determine concentrations of lithogenic elements in solution, X-ray diffraction to characterize changes in mineral composition of the material, DNA extraction to characterize community structure, as well as microscopic techniques. These techniques in combination with numerical geochemical modeling are being employed to improve our understanding of biological weathering.

Numerical simulation of tornadoes' meteorological conditions over Greece: A case study of tornadic activity over NW Peloponnese on March 25, 2009

NASA Astrophysics Data System (ADS)

Matsangouras, Ioannis T.; Nastos, Panagiotis T.; Pytharoulis, Ioannis

2014-05-01

Recent research revealed that NW Peloponnese, Greece is an area that favours pre-frontal tornadic incidence. This study presents the results of the synoptic analysis of the meteorological conditions during a tornado event over NW Peloponnese on March 25, 2009. Further, the role of topography in tornado genesis is examined. The tornado was formed approximately at 10:30 UTC, south-west of Vardas village, crossed the Nea Manolada and faded away at Lappas village, causing several damage. The length of its track was approximately 9-10 km and this tornado was characterized as F2 (Fujita scale) or T4-T5 in TORRO intensity scale. Synoptic analysis was based on ECMWF datasets, as well as on daily composite mean and anomaly of the geopotential heights at the middle and lower troposphere from NCEP/NCAR reanalysis. In addition, numerous datasets derived from weather observations and remote sensing were used in order to interpret better the examined extreme event. Finally, a numerical simulation was performed using the non-hydrostatic Weather Research and Forecasting model (WRF), initialized with ECMWF gridded analyses, with telescoping nested grids that allow the representation of atmospheric circulations ranging from the synoptic scale down to the meso-scale. In the numerical simulations the topography of the inner grid was modified by: a) 0% (actual topography) and b) -100% (without topography).

Modeling AWSoM CMEs with EEGGL: A New Approach for Space Weather Forecasting

NASA Astrophysics Data System (ADS)

Jin, M.; Manchester, W.; van der Holst, B.; Sokolov, I.; Toth, G.; Vourlidas, A.; de Koning, C. A.; Gombosi, T. I.

2015-12-01

The major source of destructive space weather is coronal mass ejections (CMEs). However, our understanding of CMEs and their propagation in the heliosphere is limited by the insufficient observations. Therefore, the development of first-principals numerical models plays a vital role in both theoretical investigation and providing space weather forecasts. Here, we present results of the simulation of CME propagation from the Sun to 1AU by combining the analytical Gibson & Low (GL) flux rope model with the state-of-art solar wind model AWSoM. We also provide an approach for transferring this research model to a space weather forecasting tool by demonstrating how the free parameters of the GL flux rope can be prescribed based on remote observations via the new Eruptive Event Generator by Gibson-Low (EEGGL) toolkit. This capability allows us to predict the long-term evolution of the CME in interplanetary space. We perform proof-of-concept case studies to show the capability of the model to capture physical processes that determine CME evolution while also reproducing many observed features both in the corona and at 1 AU. We discuss the potential and limitations of this model as a future space weather forecasting tool.

Activity of Science and Operational Research of NICT Space Weather

NASA Astrophysics Data System (ADS)

Ishii, Mamoru; Nagatsuma, Tsutomu; Watari, Shinichi; Shinagawa, Hiroyuki; Tsugawa, Takuya; Kubo, Yuki

Operational space weather forecast is for contribution to social infrastructure than for academic interests. These user need will determine the target of research, e.g., the precision level, spatial and temporal resolution and/or required lead time. We, NICT, aim two target in the present mid-term strategic plan, which are (1) forecast of ionospheric disturbance influencing to satellite positioning, and (2) forecast of disturbance in radiation belt influencing to satellite operation. We have our own observation network and develop empirical and numerical models for achieving each target. However in actual situation, it is much difficult to know the user needs quantitatively. Most of space weather phenomena makes the performance of social infrastructure poor, for example disconnect of HF communication, increase of GNSS error. Most of organizations related to these operation are negative to open these information. We have personal interviews to solve this issue. In this interview, we try to collect incident information related to space weather in each field, and to retrieve which space weather information is necessary for users. In this presentation we will introduce our research and corresponding new service, in addition to our recent scientific results.

Metal stable isotopes in weathering and hydrology: Chapter 10

USGS Publications Warehouse

Bullen, Thomas D.; Holland, Heinrich; Turekian, K.

2014-01-01

This chapter highlights some of the major developments in the understanding of the causes of metal stable isotope compositional variability in and isotope fractionation between natural materials and provides numerous examples of how that understanding is providing new insights into weathering and hydrology. At this stage, our knowledge of causes of stable isotope compositional variability among natural materials is greatest for the metals lithium, magnesium, calcium, and iron, the isotopes of which have already provided important information on weathering and hydrological processes. Stable isotope compositional variability for other metals such as strontium, copper, zinc, chromium, barium, molybdenum, mercury, cadmium, and nickel has been demonstrated but is only beginning to be applied to questions related to weathering and hydrology, and several research groups are currently exploring the potential. And then there are other metals such as titanium, vanadium, rhenium, and tungsten that have yet to be explored for variability of stable isotope composition in natural materials, but which may hold untold surprises in their utility. This impressive list of metals having either demonstrated or potential stable isotope signals that could be used to address important unsolved questions related to weathering and hydrology, constitutes a powerful toolbox that will be increasingly utilized in the coming decades.

Weather Effects on Crop Diseases in Eastern Germany

NASA Astrophysics Data System (ADS)

Conradt, Tobias

2017-04-01

Since the 1970s there are several long-term monitoring programmes for plant diseases and pests in Germany. Within the framework of a national research project, some otherwise confidential databases comprising 77 111 samples from numerous sites accross Eastern Germany could be accessed and analysed. The pest data covered leaf rust (Puccinia triticina) and powdery mildew (Blumeria graminis) in winter wheat, aphids (Aphididae, four genera) on wheat and other cereal crops, late blight (Phytophthora infestans) in potatoes, and pollen beetles (Brassicogethes aeneus) on rape. These data were complemented by daily weather observations from the German Weather Service (DWD). In a first step, Pearson correlations between weather variables and pest frequencies were calculated for seasonal time periods of different start months and durations and ordered into so-called correlograms. This revealed principal weather effects on disease spread - e. g. that wind is favourable for mildew throughout the year or that rape pollen beetles like it warm, but not during wintertime. Secondly, the pest frequency samples were found to resemble gamma distributions, and a generalised linear model was fitted to describe their parameter shift depending on end-of-winter temperatures for aphids on cereals. The method clearly shows potential for systematic pest risk assessments regarding climate change.

Automated shock detection and analysis algorithm for space weather application

NASA Astrophysics Data System (ADS)

Vorotnikov, Vasiliy S.; Smith, Charles W.; Hu, Qiang; Szabo, Adam; Skoug, Ruth M.; Cohen, Christina M. S.

2008-03-01

Space weather applications have grown steadily as real-time data have become increasingly available. Numerous industrial applications have arisen with safeguarding of the power distribution grids being a particular interest. NASA uses short-term and long-term space weather predictions in its launch facilities. Researchers studying ionospheric, auroral, and magnetospheric disturbances use real-time space weather services to determine launch times. Commercial airlines, communication companies, and the military use space weather measurements to manage their resources and activities. As the effects of solar transients upon the Earth's environment and society grow with the increasing complexity of technology, better tools are needed to monitor and evaluate the characteristics of the incoming disturbances. A need is for automated shock detection and analysis methods that are applicable to in situ measurements upstream of the Earth. Such tools can provide advance warning of approaching disturbances that have significant space weather impacts. Knowledge of the shock strength and speed can also provide insight into the nature of the approaching solar transient prior to arrival at the magnetopause. We report on efforts to develop a tool that can find and analyze shocks in interplanetary plasma data without operator intervention. This method will run with sufficient speed to be a practical space weather tool providing useful shock information within 1 min of having the necessary data to ground. The ability to run without human intervention frees space weather operators to perform other vital services. We describe ways of handling upstream data that minimize the frequency of false positive alerts while providing the most complete description of approaching disturbances that is reasonably possible.

Impact of atmospheric CO2 levels on continental silicate weathering

NASA Astrophysics Data System (ADS)

Beaulieu, E.; GoddéRis, Y.; Labat, D.; Roelandt, C.; Oliva, P.; Guerrero, B.

2010-07-01

Anthropogenic sources are widely accepted as the dominant cause for the increase in atmospheric CO2 concentrations since the beginning of the industrial revolution. Here we use the B-WITCH model to quantify the impact of increased CO2 concentrations on CO2 consumption by weathering of continental surfaces. B-WITCH couples a dynamic biogeochemistry model (LPJ) and a process-based numerical model of continental weathering (WITCH). It allows simultaneous calculations of the different components of continental weathering fluxes, terrestrial vegetation dynamics, and carbon and water fluxes. The CO2 consumption rates are estimated at four different atmospheric CO2 concentrations, from 280 up to 1120 ppmv, for 22 sites characterized by silicate lithologies (basalt, granite, or sandstones). The sensitivity to atmospheric CO2 variations is explored, while temperature and rainfall are held constant. First, we show that under 355 ppmv of atmospheric CO2, B-WITCH is able to reproduce the global pattern of weathering rates as a function of annual runoff, mean annual temperature, or latitude for silicate lithologies. When atmospheric CO2 increases, evapotranspiration generally decreases due to progressive stomatal closure, and the soil CO2 pressure increases due to enhanced biospheric productivity. As a result, vertical drainage and soil acidity increase, promoting CO2 consumption by mineral weathering. We calculate an increase of about 3% of the CO2 consumption through silicate weathering (mol ha-1 yr-1) for 100 ppmv rise in CO2. Importantly, the sensitivity of the weathering system to the CO2 rise is not uniform and heavily depends on the climatic, lithologic, pedologic, and biospheric settings.

RAMSES: a nowcasting system for mitigating geo-hydrological risk along the railway

NASA Astrophysics Data System (ADS)

Gabriele, Salvatore; Terranova, Oreste G.; Pascale, Stefania; Rago, Valeria; Chiaravalloti, Francesco; Sabatino, Pietro; Brocca, Luca; Laviola, Sante; Baldini, Luca; Federico, Stefano; Miglietta, Mario M.; Marra, Gian Paolo; Niccoli, Raffaele; Arcuri, Salvatore; Catalano, Filippo; Stassi, Sergio; Baccillieri, Maurizio; Agostino, Mario; Iovine, Giulio G. R.

2016-04-01

In recent years, a number of exceptional rainfall events of short / very short duration (from 15 minutes to about 2 hours) caused incidents and service interruptions due to landslides, collapses of bridges, and erosion of the ballast, along the Calabrian railway. RAMSES (RAilway Meteorological SEcurity System) is a pilot CNR project, recently co-funded by RFI S.p.A. and aimed at mitigating the risk along the railway. Forecasting of weather events responsible of heavy convective rainfall, even when provided with some advance, is not generally performed with reliable localization. In fact, objective limits of the numerical weather prediction derive from grid resolution, often exceeding the size of convective cells. These phenomena, whose recurrence periods seem to show a reduction due to climate changes, affect limited areas and are characterized by a very short life cycle. As a consequence, failures of hydraulic crossings are increasingly being recorded together with landslide-related debris invasion along the drainage network and slopes. RAMSES aims at improving short term (3-6 hours) weather forecasts and ground effects at local scale. The employed approach is base on synergistic and integrated operational tools to provide weather information on small-size basins. The system will also allow to promptly identify and track the short-term evolution (15-60 min) of convective cells, by means of imaging techniques based on quasi-real time radar and Meteosat data. The extension of the temporal horizon of the forecast up to three hours will be performed by using the Local Analysis and Prediction System (LAPS) model. This latter employs, as a "first guess", the output of the WRF numerical model: such analyses are updated and improved by means of observational data from different instruments (e.g. on land weather stations, radar, satellites, etc.). Finally, the assessment of ground effects will be accomplished for selected study areas, by means of landslide susceptibility mapping combined with hydrological, rainfall-runoff and hydraulic flow modeling.

Preparing for Operational Use of High Priority Products from the Joint Polar Satellite System (JPSS) in Numerical Weather Prediction

NASA Astrophysics Data System (ADS)

Nandi, S.; Layns, A. L.; Goldberg, M.; Gambacorta, A.; Ling, Y.; Collard, A.; Grumbine, R. W.; Sapper, J.; Ignatov, A.; Yoe, J. G.

2017-12-01

This work describes end to end operational implementation of high priority products from National Oceanic and Atmospheric Administration's (NOAA) operational polar-orbiting satellite constellation, to include Suomi National Polar-orbiting Partnership (S-NPP) and the Joint Polar Satellite System series initial satellite (JPSS-1), into numerical weather prediction and earth systems models. Development and evaluation needed for the initial implementations of VIIRS Environmental Data Records (EDR) for Sea Surface Temperature ingestion in the Real-Time Global Sea Surface Temperature Analysis (RTG) and Polar Winds assimilated in the National Weather Service (NWS) Global Forecast System (GFS) is presented. These implementations ensure continuity of data in these models in the event of loss of legacy sensor data. Also discussed is accelerated operational implementation of Advanced Technology Microwave Sounder (ATMS) Temperature Data Records (TDR) and Cross-track Infrared Sounder (CrIS) Sensor Data Records, identified as Key Performance Parameters by the National Weather Service. Operational use of SNPP after 28 October, 2011 launch took more than one year due to the learning curve and development needed for full exploitation of new remote sensing capabilities. Today, ATMS and CrIS data positively impact weather forecast accuracy. For NOAA's JPSS initial satellite (JPSS-1), scheduled for launch in late 2017, we identify scope and timelines for pre-launch and post-launch activities needed to efficiently transition these capabilities into operations. As part of these alignment efforts, operational readiness for KPPs will be possible as soon as 90 days after launch. The schedule acceleration is possible because of the experience with S-NPP. NOAA operational polar-orbiting satellite constellation provides continuity and enhancement of earth systems observations out to 2036. Program best practices and lessons learned will inform future implementation for follow-on JPSS-3 and -4 missions ensuring benefits and enhancements during the system's design life.

Quantitative Precipitation Nowcasting: A Lagrangian Pixel-Based Approach

DTIC Science & Technology

2012-01-01

Sorooshian, T. Bellerby, and G. Huffman, 2010: REFAME: Rain Estimation Using Forward-Adjusted Advection of Microwave Estimates. J. of Hydromet ., 11...precipitation forecasting using information from radar and Numerical Weather Prediction models. J. of Hydromet ., 4(6):1168-1180. Germann, U., and I

Meteorological Processes Affecting Air Quality – Research and Model Development Needs

EPA Science Inventory

Meteorology modeling is an important component of air quality modeling systems that defines the physical and dynamical environment for atmospheric chemistry. The meteorology models used for air quality applications are based on numerical weather prediction models that were devel...

Spatio-temporal modelling for assessing air pollution in Santiago de Chile

NASA Astrophysics Data System (ADS)

Nicolis, Orietta; Camaño, Christian; Mařın, Julio C.; Sahu, Sujit K.

2017-01-01

In this work, we propose a space-time approach for studying the PM2.5 concentration in the city of Santiago de Chile. In particular, we apply the autoregressive hierarchical model proposed by [1] using the PM2.5 observations collected by a monitoring network as a response variable and numerical weather forecasts from the Weather Research and Forecasting (WRF) model as covariate together with spatial and temporal (periodic) components. The approach is able to provide short-term spatio-temporal predictions of PM2.5 concentrations on a fine spatial grid (at 1km × 1km horizontal resolution.)

Strategies for Near Real Time Estimation of Precipitable Water Vapor

NASA Technical Reports Server (NTRS)

Bar-Sever, Yoaz E.

1996-01-01

Traditionally used for high precision geodesy, the GPS system has recently emerged as an equally powerful tool in atmospheric studies, in particular, climatology and meteorology. There are several products of GPS-based systems that are of interest to climatologists and meteorologists. One of the most useful is the GPS-based estimate of the amount of Precipitable Water Vapor (PWV) in the troposphere. Water vapor is an important variable in the study of climate changes and atmospheric convection (Yuan et al., 1993), and is of crucial importance for severe weather forecasting and operational numerical weather prediction (Kuo et al., 1993).

Recent Progress of Solar Weather Forecasting at Naoc

NASA Astrophysics Data System (ADS)

He, Han; Wang, Huaning; Du, Zhanle; Zhang, Liyun; Huang, Xin; Yan, Yan; Fan, Yuliang; Zhu, Xiaoshuai; Guo, Xiaobo; Dai, Xinghua

The history of solar weather forecasting services at National Astronomical Observatories, Chinese Academy of Sciences (NAOC) can be traced back to 1960s. Nowadays, NAOC is the headquarters of the Regional Warning Center of China (RWC-China), which is one of the members of the International Space Environment Service (ISES). NAOC is responsible for exchanging data, information and space weather forecasts of RWC-China with other RWCs. The solar weather forecasting services at NAOC cover short-term prediction (within two or three days), medium-term prediction (within several weeks), and long-term prediction (in time scale of solar cycle) of solar activities. Most efforts of the short-term prediction research are concentrated on the solar eruptive phenomena, such as flares, coronal mass ejections (CMEs) and solar proton events, which are the key driving sources of strong space weather disturbances. Based on the high quality observation data of the latest space-based and ground-based solar telescopes and with the help of artificial intelligence techniques, new numerical models with quantitative analyses and physical consideration are being developed for the predictions of solar eruptive events. The 3-D computer simulation technology is being introduced for the operational solar weather service platform to visualize the monitoring of solar activities, the running of the prediction models, as well as the presenting of the forecasting results. A new generation operational solar weather monitoring and forecasting system is expected to be constructed in the near future at NAOC.

Sources and Uses of Weather Information for Agricultural Decision Makers.

NASA Astrophysics Data System (ADS)

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

1991-04-01

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

Monthly forecasting of agricultural pests in Switzerland

NASA Astrophysics Data System (ADS)

Hirschi, M.; Dubrovsky, M.; Spirig, C.; Samietz, J.; Calanca, P.; Weigel, A. P.; Fischer, A. M.; Rotach, M. W.

2012-04-01

Given the repercussions of pests and diseases on agricultural production, detailed forecasting tools have been developed to simulate the degree of infestation depending on actual weather conditions. The life cycle of pests is most successfully predicted if the micro-climate of the immediate environment (habitat) of the causative organisms can be simulated. Sub-seasonal pest forecasts therefore require weather information for the relevant habitats and the appropriate time scale. The pest forecasting system SOPRA (www.sopra.info) currently in operation in Switzerland relies on such detailed weather information, using hourly weather observations up to the day the forecast is issued, but only a climatology for the forecasting period. Here, we aim at improving the skill of SOPRA forecasts by transforming the weekly information provided by ECMWF monthly forecasts (MOFCs) into hourly weather series as required for the prediction of upcoming life phases of the codling moth, the major insect pest in apple orchards worldwide. Due to the probabilistic nature of operational monthly forecasts and the limited spatial and temporal resolution, their information needs to be post-processed for use in a pest model. In this study, we developed a statistical downscaling approach for MOFCs that includes the following steps: (i) application of a stochastic weather generator to generate a large pool of daily weather series consistent with the climate at a specific location, (ii) a subsequent re-sampling of weather series from this pool to optimally represent the evolution of the weekly MOFC anomalies, and (iii) a final extension to hourly weather series suitable for the pest forecasting model. Results show a clear improvement in the forecast skill of occurrences of upcoming codling moth life phases when incorporating MOFCs as compared to the operational pest forecasting system. This is true both in terms of root mean squared errors and of the continuous rank probability scores of the probabilistic forecasts vs. the mean absolute errors of the deterministic system. Also, the application of the climate conserving recalibration (CCR, Weigel et al. 2009) technique allows for successful correction of the under-confidence in the forecasted occurrences of codling moth life phases. Reference: Weigel, A. P.; Liniger, M. A. & Appenzeller, C. (2009). Seasonal Ensemble Forecasts: Are Recalibrated Single Models Better than Multimodels? Mon. Wea. Rev., 137, 1460-1479.

Weather types and strokes in the Augsburg region (Southern Germany)

NASA Astrophysics Data System (ADS)

Beck, Christoph; Ertl, Michael; Giemsa, Esther; Jacobeit, Jucundus; Naumann, Markus; Seubert, Stefanie

2017-04-01

Strokes are one of the leading causes of morbidity and mortality worldwide and the main reason for longterm care dependency in Germany. Concerning the economical impact on patients and healthcare systems it is of particular importance to prevent this disease as well as to improve the outcome of the affected persons. Beside the primary well-known risk factors like hypertension, cigarette smoking, physical inactivity and others, also weather seems to have pronounced influence on the occurrence and frequency of strokes. Previous studies most often focused on effects of singular meteorological variables like ambient air temperature, air pressure or humidity. An advanced approach is to link the entire suite of daily weather elements classified to air mass- or weather types to cerebrovascular morbidity or mortality. In a joint pilot study bringing together climatologists, environmental scientists and physicians from the University of Augsburg and the clinical centre Augsburg, we analysed relationships between singular meteorological parameters as well as combined weather effects (e.g. weather types) and strokes in the urban area of Augsburg and the surrounding rural region. A total of 17.501 stroke admissions to Neurological Clinic and Clinical Neurophysiology at Klinikum Augsburg between 2006 and 2015 are classified to either "ischaemic" (16.354) or "haemorrhagic" (1.147) subtype according to etiology (based on the International Classification of Diseases - 10th Revision). Spearman correlations between daily frequencies of ischaemic and haemorrhagic strokes and singular atmospheric parameters (T, Tmin, Tmax, air pressure, humidity etc.) measured at the DWD (German weather service) meteorological station at Augsburg Muehlhausen are rather low. However, higher correlations are achieved when considering sub-samples of "homogenous weather conditions" derived from synoptic circulation classifications: e.g. within almost all of 10 types arising from a classification of central European mean sea level pressure fields into "Großwettertypes" (Beck 2000) the relationships between meteorological variables and stroke frequencies are increasing. Mainly temperature variables (Tmin, Tmax, Tmean) appear to be important particularly in winter and summer. Moreover distinct correlations of similar magnitude are obtained with other variables like wind speed or precipitation for specific weather types (e.g. westerly type). In how far these initial findings do really point to additional health impacts beyond temperature effects is subject of ongoing work.

A Geosynchronous Lidar System for Atmospheric Winds and Moisture Measurements

NASA Technical Reports Server (NTRS)

Emmitt, G. D.

2001-01-01

An observing system comprised of two lidars in geosychronous orbit would enable the synoptic and meso-scale measurement of atmospheric winds and moisture both of which are key first-order variables of the Earth's weather equation. Simultaneous measurement of these parameters at fast revisit rates promises large advancements in our weather prediction skills. Such capabilities would be unprecedented and a) yield greatly improved and finer resolution initial conditions for models, b) make existing costly and cumbersome measurement approaches obsolete, and c) obviate the use of numerical techniques needed to correct data obtained using present observing systems. Additionally, simultaneous synoptic wind and moisture observations would lead to improvements in model parameterizations, and in our knowledge of small-scale weather processes. Technology and science data product assessments are ongoing. Results will be presented during the conference.

Verification of the skill of numerical weather prediction models in forecasting rainfall from U.S. landfalling tropical cyclones

NASA Astrophysics Data System (ADS)

Luitel, Beda; Villarini, Gabriele; Vecchi, Gabriel A.

2018-01-01

The goal of this study is the evaluation of the skill of five state-of-the-art numerical weather prediction (NWP) systems [European Centre for Medium-Range Weather Forecasts (ECMWF), UK Met Office (UKMO), National Centers for Environmental Prediction (NCEP), China Meteorological Administration (CMA), and Canadian Meteorological Center (CMC)] in forecasting rainfall from North Atlantic tropical cyclones (TCs). Analyses focus on 15 North Atlantic TCs that made landfall along the U.S. coast over the 2007-2012 period. As reference data we use gridded rainfall provided by the Climate Prediction Center (CPC). We consider forecast lead-times up to five days. To benchmark the skill of these models, we consider rainfall estimates from one radar-based (Stage IV) and four satellite-based [Tropical Rainfall Measuring Mission - Multi-satellite Precipitation Analysis (TMPA, both real-time and research version); Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks (PERSIANN); the CPC MORPHing Technique (CMORPH)] rainfall products. Daily and storm total rainfall fields from each of these remote sensing products are compared to the reference data to obtain information about the range of errors we can expect from "observational data." The skill of the NWP models is quantified: (1) by visual examination of the distribution of the errors in storm total rainfall for the different lead-times, and numerical examination of the first three moments of the error distribution; (2) relative to climatology at the daily scale. Considering these skill metrics, we conclude that the NWP models can provide skillful forecasts of TC rainfall with lead-times up to 48 h, without a consistently best or worst NWP model.

Are Atmospheric Updrafts a Key to Unlocking Climate Forcing and Sensitivity?

DOE PAGES

Donner, Leo J.; O'Brien, Travis A.; Rieger, Daniel; ...

2016-06-08

Both climate forcing and climate sensitivity persist as stubborn uncertainties limiting the extent to which climate models can provide actionable scientific scenarios for climate change. A key, explicit control on cloud-aerosol interactions, the largest uncertainty in climate forcing, is the vertical velocity of cloud-scale updrafts. Model-based studies of climate sensitivity indicate that convective entrainment, which is closely related to updraft speeds, is an important control on climate sensitivity. Updraft vertical velocities also drive many physical processes essential to numerical weather prediction. Vertical velocities and their role in atmospheric physical processes have been given very limited attention in models for climatemore » and numerical weather prediction. The relevant physical scales range down to tens of meters and are thus frequently sub-grid and require parameterization. Many state-of-science convection parameterizations provide mass fluxes without specifying vertical velocities, and parameterizations which do provide vertical velocities have been subject to limited evaluation against what have until recently been scant observations. Atmospheric observations imply that the distribution of vertical velocities depends on the areas over which the vertical velocities are averaged. Distributions of vertical velocities in climate models may capture this behavior, but it has not been accounted for when parameterizing cloud and precipitation processes in current models. New observations of convective vertical velocities offer a potentially promising path toward developing process-level cloud models and parameterizations for climate and numerical weather prediction. Taking account of scale-dependence of resolved vertical velocities offers a path to matching cloud-scale physical processes and their driving dynamics more realistically, with a prospect of reduced uncertainty in both climate forcing and sensitivity.« less

Numerical simulation of raindrop scattering for C-band dual-polarization Doppler weather radar parameters

NASA Astrophysics Data System (ADS)

Teng, Shiwen; Hu, Hanfeng; Liu, Chao; Hu, Fangchao; Wang, Zhenhui; Yin, Yan

2018-07-01

The dual-polarization Doppler weather radar plays an important role in precipitation estimation and weather monitoring. For radar applications, the retrieval of precipitation microphysical characteristics is of great importance, and requires assumed scattering properties of raindrops. This study numerically investigates the scattering properties of raindrops and considers the capability of numerical models for raindrop scattering simulations. Besides the widely used spherical and oblate spheroid models, a non-spheroidal model based on realistic raindrop geometries with a flattened base and a smoothly rounded top is also considered. To study the effects of scattering simulations on radar applications, the polarization radar parameters are modeled based on the scattering properties calculated by different scattering models (i.e. the extended boundary condition T-matrix (EBCM) method and discretize dipole approximation (DDA)) and given size distributions, and compared with observations of a C-band dual-polarization radar. Note that, when the spatial resolution of the DDA simulation is large enough, the DDA results can be very close to those of the EBCM. Most simulated radar variables, except copolar correlation coefficient, match closely with radar observations, and the results based on different non-spheroidal models considered in this study show little differences. The comparison indicates that, even for the C-band radar, the effects of raindrop shape and canting angle on scattering properties are relatively minor due to relatively small size parameters. However, although more realistic particle geometry model may provide better representation on raindrop shape, considering the relatively time-consuming and complex scattering simulations for those particles, the oblate spheroid model with appropriate axis ratio variation is suggested for polarization radar applications.

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

NASA Astrophysics Data System (ADS)

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

2006-12-01

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

Techniques and resources for storm-scale numerical weather prediction

NASA Technical Reports Server (NTRS)

Droegemeier, Kelvin; Grell, Georg; Doyle, James; Soong, Su-Tzai; Skamarock, William; Bacon, David; Staniforth, Andrew; Crook, Andrew; Wilhelmson, Robert

1993-01-01

The topics discussed include the following: multiscale application of the 5th-generation PSU/NCAR mesoscale model, the coupling of nonhydrostatic atmospheric and hydrostatic ocean models for air-sea interaction studies; a numerical simulation of cloud formation over complex topography; adaptive grid simulations of convection; an unstructured grid, nonhydrostatic meso/cloud scale model; efficient mesoscale modeling for multiple scales using variable resolution; initialization of cloud-scale models with Doppler radar data; and making effective use of future computing architectures, networks, and visualization software.

Sports Facilities, Zapopan, Jalisco, Mexico.

ERIC Educational Resources Information Center

Amelar, Sarah

2001-01-01

Highlights a new K-12 school gymnasium in Mexico that changes and reacts to weather conditions, requires no air conditioning, and, on typical days, uses sunlight filtering through its ample clerestory as the sole source of illumination. Includes numerous photographs, a section drawing, and a site plan. (GR)

The Impact of Satellite-Derived Land Surface Temperatures on Numerical Weather Prediction Analyses and Forecasts

NASA Astrophysics Data System (ADS)

Candy, B.; Saunders, R. W.; Ghent, D.; Bulgin, C. E.

2017-09-01

Land surface temperature (LST) observations from a variety of satellite instruments operating in the infrared have been compared to estimates of surface temperature from the Met Office operational numerical weather prediction (NWP) model. The comparisons show that during the day the NWP model can underpredict the surface temperature by up to 10 K in certain regions such as the Sahel and southern Africa. By contrast at night the differences are generally smaller. Matchups have also been performed between satellite LSTs and observations from an in situ radiometer located in Southern England within a region of mixed land use. These matchups demonstrate good agreement at night and suggest that the satellite uncertainties in LST are less than 2 K. The Met Office surface analysis scheme has been adapted to utilize nighttime LST observations. Experiments using these analyses in an NWP model have shown a benefit to the resulting forecasts of near-surface air temperature, particularly over Africa.

Methods of sequential estimation for determining initial data in numerical weather prediction. Ph.D. Thesis

NASA Technical Reports Server (NTRS)

Cohn, S. E.

1982-01-01

Numerical weather prediction (NWP) is an initial-value problem for a system of nonlinear differential equations, in which initial values are known incompletely and inaccurately. Observational data available at the initial time must therefore be supplemented by data available prior to the initial time, a problem known as meteorological data assimilation. A further complication in NWP is that solutions of the governing equations evolve on two different time scales, a fast one and a slow one, whereas fast scale motions in the atmosphere are not reliably observed. This leads to the so called initialization problem: initial values must be constrained to result in a slowly evolving forecast. The theory of estimation of stochastic dynamic systems provides a natural approach to such problems. For linear stochastic dynamic models, the Kalman-Bucy (KB) sequential filter is the optimal data assimilation method, for linear models, the optimal combined data assimilation-initialization method is a modified version of the KB filter.

Operational atmospheric modeling system CARIS for effective emergency response associated with hazardous chemical releases in Korea.

PubMed

Kim, Cheol-Hee; Park, Jin-Ho; Park, Cheol-Jin; Na, Jin-Gyun

2004-03-01

The Chemical Accidents Response Information System (CARIS) was developed at the Center for Chemical Safety Management in South Korea in order to track and predict the dispersion of hazardous chemicals in the case of an accident or terrorist attack involving chemical companies. The main objective of CARIS is to facilitate an efficient emergency response to hazardous chemical accidents by rapidly providing key information in the decision-making process. In particular, the atmospheric modeling system implemented in CARIS, which is composed of a real-time numerical weather forecasting model and an air pollution dispersion model, can be used as a tool to forecast concentrations and to provide a wide range of assessments associated with various hazardous chemicals in real time. This article introduces the components of CARIS and describes its operational modeling system. Some examples of the operational modeling system and its use for emergency preparedness are presented and discussed. Finally, this article evaluates the current numerical weather prediction model for Korea.

On the sensitivity of numerical weather prediction to remotely sensed marine surface wind data - A simulation study

NASA Technical Reports Server (NTRS)

Cane, M. A.; Cardone, V. J.; Halem, M.; Halberstam, I.

1981-01-01

The reported investigation has the objective to assess the potential impact on numerical weather prediction (NWP) of remotely sensed surface wind data. Other investigations conducted with similar objectives have not been satisfactory in connection with a use of procedures providing an unrealistic distribution of initial errors. In the current study, care has been taken to duplicate the actual distribution of information in the conventional observing system, thus shifting the emphasis from accuracy of the data to the data coverage. It is pointed out that this is an important consideration in assessing satellite observing systems since experience with sounder data has shown that improvements in forecasts due to satellite-derived information is due less to a general error reduction than to the ability to fill data-sparse regions. The reported study concentrates on the evaluation of the observing system simulation experimental design and on the assessment of the potential of remotely sensed marine surface wind data.

A combination of HARMONIE short time direct normal irradiance forecasts and machine learning: The #hashtdim procedure

NASA Astrophysics Data System (ADS)

Gastón, Martín; Fernández-Peruchena, Carlos; Körnich, Heiner; Landelius, Tomas

2017-06-01

The present work describes the first approach of a new procedure to forecast Direct Normal Irradiance (DNI): the #hashtdim that treats to combine ground information and Numerical Weather Predictions. The system is centered in generate predictions for the very short time. It combines the outputs from the Numerical Weather Prediction Model HARMONIE with an adaptive methodology based on Machine Learning. The DNI predictions are generated with 15-minute and hourly temporal resolutions and presents 3-hourly updates. Each update offers forecasts to the next 12 hours, the first nine hours are generated with 15-minute temporal resolution meanwhile the last three hours present hourly temporal resolution. The system is proved over a Spanish emplacement with BSRN operative station in south of Spain (PSA station). The #hashtdim has been implemented in the framework of the Direct Normal Irradiance Nowcasting methods for optimized operation of concentrating solar technologies (DNICast) project, under the European Union's Seventh Programme for research, technological development and demonstration framework.

The role of MEXART in the National Space Weather Laboratory of Mexico: Detection of solar wind, CMEs, ionosphere, active regions and flares.

NASA Astrophysics Data System (ADS)

Mejia-Ambriz, J.; Gonzalez-Esparza, A.; De la Luz, V.; Villanueva-Hernandez, P.; Andrade, E.; Aguilar-Rodriguez, E.; Chang, O.; Romero Hernandez, E.; Sergeeva, M. A.; Perez Alanis, C. A.; Reyes-Marin, P. A.

2017-12-01

The National Space Weather Laboratory - Laboratorio Nacional de Clima Espacial (LANCE) - of Mexico has different ground based instruments to study and monitor the space weather. One of these instruments is the Mexican Array Radio Telescope (MEXART) which is principally dedicated to remote sensing the solar wind and coronal mass ejections (CMEs) at 140 MHz, the instrument can detect solar wind densities and speeds from about 0.4 to 1 AU by modeling observations of interplanetary scintillation (IPS). MEXART is also able to detect ionospheric disturbances associated with transient space weather events by the analysis of ionospheric scintillation (IONS) . Additionally, MEXART has followed the Sun since the beginning of the current Solar Cycle 24 with records of 8 minutes per day, and occasionally, has partially detected the process of strong solar flares. Here we show the contributions of MEXART to the LANCE by reporting recent detections of CMEs by IPS, the arrive of transient events at Earth by IONS, the influence of active regions in the flux of the Sun at 140 MHz and the detection of a M6.5 class flare. Furthermore we report the status of a near real time analysis of IPS data for forecast purposes and the potential contribution to the Worldwide IPS Stations network (WIPSS), which is an effort to achieve a better coverage of the solar wind observations in the inner heliosphere.

Application of Metaheuristic and Deterministic Algorithms for Aircraft Reference Trajectory Optimization =

NASA Astrophysics Data System (ADS)

Murrieta Mendoza, Alejandro

Aircraft reference trajectory is an alternative method to reduce fuel consumption, thus the pollution released to the atmosphere. Fuel consumption reduction is of special importance for two reasons: first, because the aeronautical industry is responsible of 2% of the CO2 released to the atmosphere, and second, because it will reduce the flight cost. The aircraft fuel model was obtained from a numerical performance database which was created and validated by our industrial partner from flight experimental test data. A new methodology using the numerical database was proposed in this thesis to compute the fuel burn for a given trajectory. Weather parameters such as wind and temperature were taken into account as they have an important effect in fuel burn. The open source model used to obtain the weather forecast was provided by Weather Canada. A combination of linear and bi-linear interpolations allowed finding the required weather data. The search space was modelled using different graphs: one graph was used for mapping the different flight phases such as climb, cruise and descent, and another graph was used for mapping the physical space in which the aircraft would perform its flight. The trajectory was optimized in its vertical reference trajectory using the Beam Search algorithm, and a combination of the Beam Search algorithm with a search space reduction technique. The trajectory was optimized simultaneously for the vertical and lateral reference navigation plans while fulfilling a Required Time of Arrival constraint using three different metaheuristic algorithms: the artificial bee's colony, and the ant colony optimization. Results were validated using the software FlightSIMRTM, a commercial Flight Management System, an exhaustive search algorithm, and as flown flights obtained from flightawareRTM. All algorithms were able to reduce the fuel burn, and the flight costs. None None None None None None None

Development and validation of a weather-based warning system to advise fungicide applications to control dollar spot on turfgrass.

PubMed

Smith, D L; Kerns, J P; Walker, N R; Payne, A F; Horvath, B; Inguagiato, J C; Kaminski, J E; Tomaso-Peterson, M; Koch, P L

2018-01-01

Dollar spot is one of the most common diseases of golf course turfgrass and numerous fungicide applications are often required to provide adequate control. Weather-based disease warning systems have been developed to more accurately time fungicide applications; however, they tend to be ineffective and are not currently in widespread use. The primary objective of this research was to develop a new weather-based disease warning system to more accurately advise fungicide applications to control dollar spot activity across a broad geographic and climactic range. The new dollar spot warning system was developed from data collected at field sites in Madison, WI and Stillwater, OK in 2008 and warning system validation sites were established in Madison, WI, Stillwater, OK, Knoxville, TN, State College, PA, Starkville, MS, and Storrs, CT between 2011 and 2016. A meta-analysis of all site-years was conducted and the most effective warning system for dollar spot development consisted of a five-day moving average of relative humidity and average daily temperature. Using this model the highest effective probability that provided dollar spot control similar to that of a calendar-based program across the numerous sites and years was 20%. Additional analysis found that the 20% spray threshold provided comparable control to the calendar-based program while reducing fungicide usage by up to 30%, though further refinement may be needed as practitioners implement this warning system in a range of environments not tested here. The weather-based dollar spot warning system presented here will likely become an important tool for implementing precision disease management strategies for future turfgrass managers, especially as financial and regulatory pressures increase the need to reduce pesticide usage on golf course turfgrass.

Development and validation of a weather-based warning system to advise fungicide applications to control dollar spot on turfgrass

PubMed Central

Smith, D. L.; Kerns, J. P.; Walker, N. R.; Payne, A. F.; Horvath, B.; Inguagiato, J. C.; Kaminski, J. E.; Tomaso-Peterson, M.

2018-01-01

Dollar spot is one of the most common diseases of golf course turfgrass and numerous fungicide applications are often required to provide adequate control. Weather-based disease warning systems have been developed to more accurately time fungicide applications; however, they tend to be ineffective and are not currently in widespread use. The primary objective of this research was to develop a new weather-based disease warning system to more accurately advise fungicide applications to control dollar spot activity across a broad geographic and climactic range. The new dollar spot warning system was developed from data collected at field sites in Madison, WI and Stillwater, OK in 2008 and warning system validation sites were established in Madison, WI, Stillwater, OK, Knoxville, TN, State College, PA, Starkville, MS, and Storrs, CT between 2011 and 2016. A meta-analysis of all site-years was conducted and the most effective warning system for dollar spot development consisted of a five-day moving average of relative humidity and average daily temperature. Using this model the highest effective probability that provided dollar spot control similar to that of a calendar-based program across the numerous sites and years was 20%. Additional analysis found that the 20% spray threshold provided comparable control to the calendar-based program while reducing fungicide usage by up to 30%, though further refinement may be needed as practitioners implement this warning system in a range of environments not tested here. The weather-based dollar spot warning system presented here will likely become an important tool for implementing precision disease management strategies for future turfgrass managers, especially as financial and regulatory pressures increase the need to reduce pesticide usage on golf course turfgrass. PMID:29522560

A Self-Organizing Map Based Evaluation of the Antarctic Mesoscale Prediction System Using Observations from a 30-m Instrumented Tower on the Ross Ice Shelf, Antarctica

NASA Astrophysics Data System (ADS)

Nigro, M. A.; Cassano, J. J.; Wille, J.; Bromwich, D. H.; Lazzara, M. A.

2015-12-01

An accurate representation of the atmospheric boundary layer in numerical weather prediction models is important for predicting turbulence and energy exchange in the atmosphere. This study uses two years of observations from a 30-m automatic weather station (AWS) installed on the Ross Ice Shelf, Antarctica to evaluate forecasts from the Antarctic Mesoscale Prediction System (AMPS), a numerical weather prediction system based on the polar version of the Weather Research and Forecasting (Polar WRF) model that uses the MYJ planetary boundary layer scheme and that primarily supports the extensive aircraft operations of the U.S. Antarctic Program. The 30-m AWS has six levels of instrumentation, providing vertical profiles of temperature, wind speed, and wind direction. The observations show the atmospheric boundary layer over the Ross Ice Shelf is stable approximately 80% of the time, indicating the influence of the permanent ice surface in this region. The observations from the AWS are further analyzed using the method of self-organizing maps (SOM) to identify the range of potential temperature profiles that occur over the Ross Ice Shelf. The SOM analysis identified 30 patterns, which range from strong inversions to slightly unstable profiles. The corresponding AMPS forecasts were evaluated for each of the 30 patterns to understand the accuracy of the AMPS near surface layer under different atmospheric conditions. The results indicate that under stable conditions AMPS with MYJ under predicts the inversion strength by as much as 7.4 K over the 30-m depth of the tower and over predicts the near surface wind speed by as much as 3.8 m s-1. Conversely, under slightly unstable conditions, AMPS predicts both the inversion strength and near surface wind speeds with reasonable accuracy.

Weathering profiles in soils and rocks on Earth and Mars

NASA Astrophysics Data System (ADS)

Hausrath, E.; Adcock, C. T.; Bamisile, T.; Baumeister, J. L.; Gainey, S.; Ralston, S. J.; Steiner, M.; Tu, V.

2017-12-01

Interactions of liquid water with rock, soil, or sediments can result in significant chemical and mineralogical changes with depth. These changes can include transformation from one phase to another as well as translocation, addition, and loss of material. The resulting chemical and mineralogical depth profiles can record characteristics of the interacting liquid water such as pH, temperature, duration, and abundance. We use a combined field, laboratory, and modeling approach to interpret the environmental conditions preserved in soils and rocks. We study depth profiles in terrestrial field environments; perform dissolution experiments of primary and secondary phases important in soil environments; and perform numerical modeling to quantitatively interpret weathering environments. In our field studies we have measured time-integrated basaltic mineral dissolution rates, and interpreted the impact of pH and temperature on weathering in basaltic and serpentine-containing rocks and soils. These results help us interpret fundamental processes occurring in soils on Earth and on Mars, and can also be used to inform numerical modeling and laboratory experiments. Our laboratory experiments provide fundamental kinetic data to interpret processes occurring in soils. We have measured dissolution rates of Mars-relevant phosphate minerals, clay minerals, and amorphous phases, as well as dissolution rates under specific Mars-relevant conditions such as in concentrated brines. Finally, reactive transport modeling allows a quantitative interpretation of the kinetic, thermodynamic, and transport processes occurring in soil environments. Such modeling allows the testing of conditions under longer time frames and under different conditions than might be possible under either terrestrial field or laboratory conditions. We have used modeling to examine the weathering of basalt, olivine, carbonate, phosphate, and clay minerals, and placed constraints on the duration, pH, and solution chemistry of past aqueous alteration occurring on Mars.

On the assimilation of satellite derived soil moisture in numerical weather prediction models

NASA Astrophysics Data System (ADS)

Drusch, M.

2006-12-01

Satellite derived surface soil moisture data sets are readily available and have been used successfully in hydrological applications. In many operational numerical weather prediction systems the initial soil moisture conditions are analysed from the modelled background and 2 m temperature and relative humidity. This approach has proven its efficiency to improve surface latent and sensible heat fluxes and consequently the forecast on large geographical domains. However, since soil moisture is not always related to screen level variables, model errors and uncertainties in the forcing data can accumulate in root zone soil moisture. Remotely sensed surface soil moisture is directly linked to the model's uppermost soil layer and therefore is a stronger constraint for the soil moisture analysis. Three data assimilation experiments with the Integrated Forecast System (IFS) of the European Centre for Medium-range Weather Forecasts (ECMWF) have been performed for the two months period of June and July 2002: A control run based on the operational soil moisture analysis, an open loop run with freely evolving soil moisture, and an experimental run incorporating bias corrected TMI (TRMM Microwave Imager) derived soil moisture over the southern United States through a nudging scheme using 6-hourly departures. Apart from the soil moisture analysis, the system setup reflects the operational forecast configuration including the atmospheric 4D-Var analysis. Soil moisture analysed in the nudging experiment is the most accurate estimate when compared against in-situ observations from the Oklahoma Mesonet. The corresponding forecast for 2 m temperature and relative humidity is almost as accurate as in the control experiment. Furthermore, it is shown that the soil moisture analysis influences local weather parameters including the planetary boundary layer height and cloud coverage. The transferability of the results to other satellite derived soil moisture data sets will be discussed.

Automatic Real-Time Estimation of Plume Height and Mass Eruption Rate Using Radar Data During Explosive Volcanism

NASA Astrophysics Data System (ADS)

Arason, P.; Barsotti, S.; De'Michieli Vitturi, M.; Jónsson, S.; Arngrímsson, H.; Bergsson, B.; Pfeffer, M. A.; Petersen, G. N.; Bjornsson, H.

2016-12-01

Plume height and mass eruption rate are the principal scale parameters of explosive volcanic eruptions. Weather radars are important instruments in estimating plume height, due to their independence of daylight, weather and visibility. The Icelandic Meteorological Office (IMO) operates two fixed position C-band weather radars and two mobile X-band radars. All volcanoes in Iceland can be monitored by IMO's radar network, and during initial phases of an eruption all available radars will be set to a more detailed volcano scan. When the radar volume data is retrived at IMO-headquarters in Reykjavík, an automatic analysis is performed on the radar data above the proximity of the volcano. The plume height is automatically estimated taking into account the radar scanning strategy, beam width, and a likely reflectivity gradient at the plume top. This analysis provides a distribution of the likely plume height. The automatically determined plume height estimates from the radar data are used as input to a numerical suite that calculates the eruptive source parameters through an inversion algorithm. This is done by using the coupled system DAKOTA-PlumeMoM which solves the 1D plume model equations iteratively by varying the input values of vent radius and vertical velocity. The model accounts for the effect of wind on the plume dynamics, using atmospheric vertical profiles extracted from the ECMWF numerical weather prediction model. Finally, the resulting estimates of mass eruption rate are used to initialize the dispersal model VOL-CALPUFF to assess hazard due to tephra fallout, and communicated to London VAAC to support their modelling activity for aviation safety purposes.

Using Machine Learning as a fast emulator of physical processes within the Met Office's Unified Model

NASA Astrophysics Data System (ADS)

Prudden, R.; Arribas, A.; Tomlinson, J.; Robinson, N.

2017-12-01

The Unified Model is a numerical model of the atmosphere used at the UK Met Office (and numerous partner organisations including Korean Meteorological Agency, Australian Bureau of Meteorology and US Air Force) for both weather and climate applications.Especifically, dynamical models such as the Unified Model are now a central part of weather forecasting. Starting from basic physical laws, these models make it possible to predict events such as storms before they have even begun to form. The Unified Model can be simply described as having two components: one component solves the navier-stokes equations (usually referred to as the "dynamics"); the other solves relevant sub-grid physical processes (usually referred to as the "physics"). Running weather forecasts requires substantial computing resources - for example, the UK Met Office operates the largest operational High Performance Computer in Europe - and the cost of a typical simulation is spent roughly 50% in the "dynamics" and 50% in the "physics". Therefore there is a high incentive to reduce cost of weather forecasts and Machine Learning is a possible option because, once a machine learning model has been trained, it is often much faster to run than a full simulation. This is the motivation for a technique called model emulation, the idea being to build a fast statistical model which closely approximates a far more expensive simulation. In this paper we discuss the use of Machine Learning as an emulator to replace the "physics" component of the Unified Model. Various approaches and options will be presented and the implications for further model development, operational running of forecasting systems, development of data assimilation schemes, and development of ensemble prediction techniques will be discussed.

Investigating the Small-Scale Spatial Variabilty of Precipitable Water Vapor by Adding Single-Frequency Receivers into an Existing Dual-Frequency Receiver Network

NASA Astrophysics Data System (ADS)

Krietemeyer, Andreas; ten Veldhuis, Marie-claire; van de Giesen, Nick

2017-04-01

Exploiting GNSS signal delays is one possibility to obtain Precipitable Water Vapor (PWV) estimates in the atmosphere. The technique is well known since the early 1990s and by now an established method in the meteorological community. The data is crucial for weather forecasting and its assimilation into numerical weather forecasting models is a topic of ongoing research. However, the spatial resolution of ground based GNSS receivers is usually low, in the order of tens of kilometres. Since severe weather events such as convective storms can be concentrated in spatial extent, existing GNSS networks are often not sufficient to retrieve small scale PWV fluctuations and need to be densified. For economic reasons, the use of low-cost single-frequency receivers is a promising solution. In this study, we will deploy a network of single-frequency receivers to densify an existing dual-frequency network in order to investigate the spatial and temporal PWV variations. We demonstrate a test network consisting of four single-frequency receivers in the Rotterdam area (Netherlands). In order to eliminate the delay caused by the ionosphere, the Satellite-specific Epoch-differenced Ionospheric Delay model (SEID) is applied, using a surrounding dual-frequency network distributed over a radius of approximately 25 km. With the synthesized L2 frequency, the tropospheric delays are estimated using the Precise Point Positioning (PPP) strategy and International GNSS Service (IGS) final orbits. The PWV time series are validated by a comparison of a collocated single-frequency and a dual-frequency receiver. The time series themselves form the basis for potential further studies like data assimilation into numerical weather models and GNSS tomography to study the impact of the increased spatial resolution on local heavy rain forecast.

Increasing the temporal resolution of direct normal solar irradiance forecasted series

NASA Astrophysics Data System (ADS)

Fernández-Peruchena, Carlos M.; Gastón, Martin; Schroedter-Homscheidt, Marion; Marco, Isabel Martínez; Casado-Rubio, José L.; García-Moya, José Antonio

2017-06-01

A detailed knowledge of the solar resource is a critical point in the design and control of Concentrating Solar Power (CSP) plants. In particular, accurate forecasting of solar irradiance is essential for the efficient operation of solar thermal power plants, the management of energy markets, and the widespread implementation of this technology. Numerical weather prediction (NWP) models are commonly used for solar radiation forecasting. In the ECMWF deterministic forecasting system, all forecast parameters are commercially available worldwide at 3-hourly intervals. Unfortunately, as Direct Normal solar Irradiance (DNI) exhibits a great variability due to the dynamic effects of passing clouds, 3-h time resolution is insufficient for accurate simulations of CSP plants due to their nonlinear response to DNI, governed by various thermal inertias due to their complex response characteristics. DNI series of hourly or sub-hourly frequency resolution are normally used for an accurate modeling and analysis of transient processes in CSP technologies. In this context, the objective of this study is to propose a methodology for generating synthetic DNI time series at 1-h (or higher) temporal resolution from 3-h DNI series. The methodology is based upon patterns as being defined with help of the clear-sky envelope approach together with a forecast of maximum DNI value, and it has been validated with high quality measured DNI data.

Implication of climate change on urban drainage systems of Chicago and Mainstream and DesPlaines (MS/DP) Tunnel and Reservoir Plan (TARP)

NASA Astrophysics Data System (ADS)

Luo, H.; Schmidt, A.; Garcia, M. H.; Oberg, N.

2016-12-01

The impact of changing climate patterns and rainfall extremes on sewer system and river basin has been brought to attention to the researchers worldwide. In 1972, the Metropolitan Water Reclamation District of Greater Chicago (MWRDGC) adopted the Tunnel and Reservoir Plan (TARP) to address combined sewer overflow (CSO) pollution and flooding problems in the Chicago land area. The hydrosystem laboratory in University of Illinois at Urbana-Champaign developed a series of numerical models accordingly to analyze the complex hydraulic behavior of the as-built TARP system. Due to the interconnected nature of City of Chicago sewer network and MS/DP TARP system, a tightly coupled hydrological and hydraulic model MetroFlow was developed to facilitate such analysis by integrating previous developed models. This study utilized MetroFlow to predict the hydrologic/hydraulic response of the system for a set of pre-determined design and historical storm events. Accordingly, combined sewer overflows (CSO) of Chicago combined sewer system and MS/DP TARP system were evaluated under current and future weather scenarios. The total CSOs from TARP system can be considered as urban point pollution source to the surrounding receiving bodies, hence the potential impact of climate change on CSO fluxes is essential reference to wastewater infrastructure design and operations of the hydraulic regulating structures under storm events to mitigate predicted risks.

Towards assimilation of InSAR data in operational weather models

NASA Astrophysics Data System (ADS)

Mulder, Gert; van Leijen, Freek; Barkmeijer, Jan; de Haan, Siebren; Hanssen, Ramon

2017-04-01

InSAR signal delays due to the varying atmospheric refractivity are a potential data source to improve weather models [1]. Especially with the launch of the new Sentinel-1 satellites, which increases data coverage, latency and accessibility, it may become possible to operationalize the assimilation of differential integrated refractivity (DIR) values in numerical weather models. Although studies exist on comparison between InSAR data and weather models [2], the impact of assimilation of DIR values in an operational weather model has never been assessed. In this study we present different ways to assimilate DIR values in an operational weather model and show the first forecast results. There are different possibilities to assimilate InSAR-data in a weather model. For example, (i) absolute DIR values can be derived using additional GNSS zenith or slant delay values, (ii) DIR values can be converted to water vapor pressures, or (iii) water vapor pressures can be derived for different heights by combining GNSS and InSAR data. However, an increasing number of assumptions in these processing steps will increase the uncertainty in the final results. Therefore, we chose to insert the InSAR derived DIR values after minimal additional processing. In this study we use the HARMONIE model [3], which is a spectral, non-hydrostatic model with a resolution of about 2.5 km. Currently, this is the operational model in 11 European countries and based on the AROME model [4]. To assimilate the DIR values in the weather model we use a simple adjustment of the weather parameters over the full slant column to match the DIR values. This is a first step towards a more sophisticated approach based on the 3D-VAR or 4D-VAR schemes [5]. Where both assimilation schemes can correct for different weather parameters simultaneously, and 4D-VAR allow us to assimilate DIR values at the exact moment of satellite overpass instead of the start of the forecast window. The approach will be demonstrated based on several case studies. This research can be seen as a first step towards the operational use of InSAR data in state-of-the-art weather models and can be a driver for the design and development for new SAR missions, such as NISAR. References: [1] Hanssen, R. F., Weckwerth, T. M., Zebker, H. A., & Klees, R. (1999). High-resolution water vapor mapping from interferometric radar measurements.Science, 283(5406), 1297-1299. [2] P. Mateus, R. Tomé, G. Nico and J. Catalão, "Three-Dimensional Variational Assimilation of InSAR PWV Using the WRFDA Model," in IEEE Transactions on Geoscience and Remote Sensing, vol. 54, no. 12, pp. 7323-7330, Dec. 2016. [3] Navascués, B., Calvo, J., Morales, G., Santos, C., Callado, A., Cansado, A., ... & García-Colombo, O. (2013). Long-term verification of HIRLAM and ECMWF forecasts over southern europe: History and perspectives of numerical weather prediction at AEMET. Atmospheric Research, 125, 20-33. [4] Seity, Y., P. Brousseau, S. Malardel, G. Hello, P. Bénard, F. Bouttier, C. Lac, and V. Masson, 2011: The AROME-France Convective-Scale Operational Model. Mon. Wea. Rev., 139, 976-991. [5] Lorenc, A. C. and Rawlins, F. (2005), Why does 4D-Var beat 3D-Var?. Q.J.R. Meteorol. Soc., 131: 3247-3257.

Impact of Cloud Analysis on Numerical Weather Prediction in the Galician Region of Spain.

NASA Astrophysics Data System (ADS)

Souto, M. J.; Balseiro, C. F.; Pérez-Muñuzuri, V.; Xue, M.; Brewster, K.

2003-01-01

The Advanced Regional Prediction System (ARPS) is applied to operational numerical weather prediction in Galicia, northwest Spain. The model is run daily for 72-h forecasts at a 10-km horizontal spacing. Located on the northwest coast of Spain and influenced by the Atlantic weather systems, Galicia has a high percentage (nearly 50%) of rainy days per year. For these reasons, the precipitation processes and the initialization of moisture and cloud fields are very important. Even though the ARPS model has a sophisticated data analysis system (`ADAS') that includes a 3D cloud analysis package, because of operational constraints, the current forecast starts from the 12-h forecast of the National Centers for Environmental Prediction Aviation Model (AVN). Still, procedures from the ADAS cloud analysis are being used to construct the cloud fields based on AVN data and then are applied to initialize the microphysical variables in ARPS. Comparisons of the ARPS predictions with local observations show that ARPS can predict very well both the daily total precipitation and its spatial distribution. ARPS also shows skill in predicting heavy rains and high winds, as observed during November 2000, and especially in the prediction of the 5 November 2000 storm that caused widespread wind and rain damage in Galicia. It is demonstrated that the cloud analysis contributes to the success of the precipitation forecasts.

Improving Numerical Weather Predictions of Summertime Precipitation Over the Southeastern U.S. Through a High-Resolution Initialization of the Surface State

NASA Technical Reports Server (NTRS)

Case, Jonathan L.; Kumar, Sujay V.; Krikishen, Jayanthi; Jedlovec, Gary J.

2011-01-01

It is hypothesized that high-resolution, accurate representations of surface properties such as soil moisture and sea surface temperature are necessary to improve simulations of summertime pulse-type convective precipitation in high resolution models. This paper presents model verification results of a case study period from June-August 2008 over the Southeastern U.S. using the Weather Research and Forecasting numerical weather prediction model. Experimental simulations initialized with high-resolution land surface fields from the NASA Land Information System (LIS) and sea surface temperature (SST) derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) are compared to a set of control simulations initialized with interpolated fields from the National Centers for Environmental Prediction 12-km North American Mesoscale model. The LIS land surface and MODIS SSTs provide a more detailed surface initialization at a resolution comparable to the 4-km model grid spacing. Soil moisture from the LIS spin-up run is shown to respond better to the extreme rainfall of Tropical Storm Fay in August 2008 over the Florida peninsula. The LIS has slightly lower errors and higher anomaly correlations in the top soil layer, but exhibits a stronger dry bias in the root zone. The model sensitivity to the alternative surface initial conditions is examined for a sample case, showing that the LIS/MODIS data substantially impact surface and boundary layer properties.

A Comparison of Five Numerical Weather Prediction Analysis Climatologies in Southern High Latitudes.

NASA Astrophysics Data System (ADS)

Connolley, William M.; Harangozo, Stephen A.

2001-01-01

In this paper, numerical weather prediction analyses from four major centers are compared-the Australian Bureau of Meteorology (ABM), the European Centre for Medium-Range Weather Forecasts (ECMWF), the U.S. National Centers for Environmental Prediction-National Center for Atmospheric Research (NCEP-NCAR), and The Met. Office (UKMO). Two of the series-ECMWF reanalysis (ERA) and NCEP-NCAR reanalysis (NNR)-are `reanalyses'; that is, the data have recently been processed through a consistent, modern analysis system. The other three-ABM, ECMWF operational (EOP), and UKMO-are archived from operational analyses.The primary focus in this paper is on the period of 1979-93, the period used for the reanalyses, and on climatology. However, ABM and NNR are also compared for the period before 1979, for which the evidence tends to favor NNR. The authors are concerned with basic variables-mean sea level pressure, height of the 500-hPa surface, and near-surface temperature-that are available from the basic analysis step, rather than more derived quantities (such as precipitation), which are available only from the forecast step.Direct comparisons against station observations, intercomparisons of the spatial pattern of the analyses, and intercomparisons of the temporal variation indicate that ERA, EOP, and UKMO are best for sea level pressure;that UKMO and EOP are best for 500-hPa height; and that none of the analyses perform well for near-surface temperature.

Modeled Forecasts of Dengue Fever in San Juan, Puerto Rico Using NASA Satellite Enhanced Weather Forecasts

NASA Astrophysics Data System (ADS)

Morin, C.; Quattrochi, D. A.; Zavodsky, B.; Case, J.

2015-12-01

Dengue fever (DF) is an important mosquito transmitted disease that is strongly influenced by meteorological and environmental conditions. Recent research has focused on forecasting DF case numbers based on meteorological data. However, these forecasting tools have generally relied on empirical models that require long DF time series to train. Additionally, their accuracy has been tested retrospectively, using past meteorological data. Consequently, the operational utility of the forecasts are still in question because the error associated with weather and climate forecasts are not reflected in the results. Using up-to-date weekly dengue case numbers for model parameterization and weather forecast data as meteorological input, we produced weekly forecasts of DF cases in San Juan, Puerto Rico. Each week, the past weeks' case counts were used to re-parameterize a process-based DF model driven with updated weather forecast data to generate forecasts of DF case numbers. Real-time weather forecast data was produced using the Weather Research and Forecasting (WRF) numerical weather prediction (NWP) system enhanced using additional high-resolution NASA satellite data. This methodology was conducted in a weekly iterative process with each DF forecast being evaluated using county-level DF cases reported by the Puerto Rico Department of Health. The one week DF forecasts were accurate especially considering the two sources of model error. First, weather forecasts were sometimes inaccurate and generally produced lower than observed temperatures. Second, the DF model was often overly influenced by the previous weeks DF case numbers, though this phenomenon could be lessened by increasing the number of simulations included in the forecast. Although these results are promising, we would like to develop a methodology to produce longer range forecasts so that public health workers can better prepare for dengue epidemics.

Permeability and microstructural changes due to weathering of pyroclastic rocks in Cappadocia, central Turkey

NASA Astrophysics Data System (ADS)

Sato, M.; Takahashi, M.; Anma, R.; Shiomi, K.

2014-12-01

Studies of permeability changes of rocks during weathering are important to understand the processes of geomorphological development and how they are influenced by cyclic climatic conditions. Especially volcanic tuffs and pyroclastic flow deposits are easily affected by water absorption and freezing-thawing cycle (Erguler. 2009, Çelik and Ergül 2014). Peculiar erosional landscapes of Cappadocia, central Turkey, with numerous underground cities and carved churches, that made this area a world heritage site, are consists of volcanic tuffs and pyroclastic flow deposits. Understanding permeability changes of such rocks under different conditions are thus important not only to understand fundamental processes of weathering, but also to protect the landscapes of the world heritage sites and archaeological remains. In this study, we aim to evaluate internal void structures and bulk permeability of intact and weathered pyroclastic rocks from Cappadocia using X-ray CT, mercury intrusion porosimetry data and permeability measurement method of flow pump test. Samples of pyroclastic deposits that comprise the landscapes of Rose Valley and Ihlara Valley, were collected from the corresponding strata outside of the preservation areas. Porosity and pore-size distribution for the same samples measured by mercury intrusion porosimetry, indicate that the intact samples have lower porosity than weathered samples and pore sizes were dominantly 1-10μm in calculated radii, whereas weathered samples have more micropores (smaller than 1 μm). X-ray CT images were acquired to observe internal structure of samples. Micro-fractures, probably caused by repeated expansion and contraction due to temperature changes, were observed around clast grains. The higher micropore ratio in weathered samples could be attributed to the development of the micro-farctures. We will discuss fundamental processes of weathering and geomorphological development models using these data.

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.

Generation and Maintenance of Recirculations by Gulf Stream Instabilities

DTIC Science & Technology

1999-02-01

Francois Primeau for endless discus- sions of various scientific problems, Kirill Pankratov for useful advice on the numerical methods in fluid...recirculation. J. Phys. Oceanogr., 18, 662-682. [7] Davis C. A. and K. A. Emanuel, 1991 : Potential vorticity diagnostics of cyclo- genesis. Mon. Weather. Rev

Western states one-stop shop for rural traveler information : research on Clarus system data.

DOT National Transportation Integrated Search

2011-09-01

Weather is a primary item of interest to travelers, but generally scattered numerous sources and in varying formats, making it difficult to assemble prior travel. Within this project, a website was developed to display Clarus ESS data, along with oth...

ISSUES IN DIGITAL IMAGE PROCESSING OF AERIAL PHOTOGRAPHY FOR MAPPING SUBMERSED AQUATIC VEGETATION

EPA Science Inventory

The paper discusses the numerous issues that needed to be addressed when developing a methodology for mapping Submersed Aquatic Vegetation (SAV) from digital aerial photography. Specifically, we discuss 1) choice of film; 2) consideration of tide and weather constraints; 3) in-s...

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

DTIC Science & Technology

2000-09-30

MRY) and I developed a collaboration with the NRL/SSMIS Lower-Atmospheric Sounding Capability program; Gene Poe (NRL, Team Leader). The effort is...Geophysical Society Annual Meeting (Nice, Fance ; April 2000), the Extratropical Cyclone Workshop (Monterey, CA; Sept. 2000), and in seminars at NCAR

Silicate Weathering and Pervasive Authigenic Carbonate Precipitation Coupled to Methanogenesis in the Krishna-Godavari Basin, Offshore India

NASA Astrophysics Data System (ADS)

Solomon, E. A.; Spivack, A. J.; Kastner, M.; Torres, M. E.

2014-12-01

The cycling of methane in marine sediments has been actively studied for the past several decades, but less attention has been paid to the cycling of CO2 produced in methanogenic sediments. The National Gas Hydrate Program Expedition 01 cored 10 sites with the Joides Resolution drillship in the Krishna-Godavari basin, located on the southeastern margin of India. A comprehensive suite of pore water solute concentrations and isotope ratios were analyzed to investigate the distribution and concentration of gas hydrate along the margin, in situ diagenetic and metabolic reactions, fluid migration and flow pathways, and fluid and gas sources. This represents one of the most comprehensive pore water geochemical datasets collected at a continental margin to date, and provides the necessary tracers to better understand the processes and sinks controlling CO2 in margin sediments. Our results show that the CO2 produced through net microbial methanogenesis is effectively neutralized through silicate weathering throughout the sediment column drilled at each site (~100-300 m), buffering the pH of the sedimentary pore water and generating excess alkalinity through the same reaction sequence as continental silicate weathering. Most of the excess alkalinity produced through silicate weathering in the Krishna-Godavari basin is sequestered in Ca- and Fe-carbonates as a result of ubiquitous calcium release from weathering detrital silicates and Fe-reduction within the methanogenic sediments. Formation of secondary hydrous silicates (e.g. smectite) related to incongruent primary silicate dissolution acts as a significant sink for pore water Mg, K, Li, Rb, and B. The consumption of methane through anaerobic oxidation of methane, sequestration of methane in gas hydrate, and sequestration of dissolved inorganic carbon in authigenic carbonates keeps methanogenesis as a thermodynamically feasible catabolic pathway. Our results combined with previous indications of silicate weathering in anoxic sediments in the Sea of Okhotsk, suggest that silicate weathering coupled to microbial methanogenesis should be occurring in continental margins worldwide, providing a net sink of atmospheric CO2 over geologic timescales.

Numerical simulation study of polar lows in Russian Arctic: dynamical characteristics

NASA Astrophysics Data System (ADS)

Verezemskaya, Polina; Baranyuk, Anastasia; Stepanenko, Victor

2015-04-01

Polar Lows (hereafter PL) are intensive mesoscale cyclones, appearing above the sea surface, usually behind the arctic front and characterized by severe weather conditions [1]. All in consequence of the global warming PLs started to emerge in the arctic water area as well - in summer and autumn. The research goal is to examine PLs by considering multisensory data and the resulting numerical mesoscale model. The main purpose was to realize which conditions induce PL development in such thermodynamically unusual season and region as Kara sea. In order to conduct the analysis we used visible and infrared images from MODIS (Aqua). Atmospheric water vapor V, cloud liquid water Q content and surface wind fields W were resampled by examining AMSR-E microwave radiometer data (Aqua)[2], the last one was additionally extracted from QuickSCAT scatterometer. We have selected some PL cases in Kara sea, appeared in autumn of 2007-2008. Life span of the PL was between 24 to 36 hours. Vortexes' characteristics were: W from 15m/s, Q and V values: 0.08-0.11 kg/m2 and 8-15 kg/m2 relatively. Numerical experiments were carried out with Weather Research and Forecasting model (WRF), which was installed on supercomputer "Lomonosov" of Research Computing Center of Moscow State University [3]. As initial conditions was used reanalysis data ERA-Interim from European Centre for Medium-Range Weather Forecasts. Numerical experiments were made with 5 km spatial resolution, with Goddard center microphysical parameterization and explicit convection simulation. Modeling fields were compared with satellite observations and shown good accordance. Than dynamic characteristics were analyzed: evolution of potential and absolute vorticity [4], surface heat and momentum fluxes, and CAPE and WISHE mechanisms realization. 1. Polar lows, J. Turner, E.A. Rasmussen, 612, Cambridge University press, Cambridge, 2003. 2. Zabolotskikh, E. V., Mitnik, L. M., & Chapron, B. (2013). New approach for severe marine weather study using satellite passive microwave sensing. Geophysical Research Letters, 40(13), 3347-3350. doi:10.1002/grl.50664 3. V. Sadovnichy, A. Tikhonravov, Vl. Voevodin, and V. Opanasenko "Lomonosov": Supercomputing at Moscow State University. In Contemporary High Performance Computing: From Petascale toward Exascale (Chapman & Hall/CRC Computational Science), pp.283-307, Boca Raton, USA, CRC Press, 2013. 4. B. J. Hoskins, M.E. McIntyre, A.W. Robertson, On the use and significance of isentropic potential vorticity maps, Quarterly journal of the Royal Meteorological Society, OCTOBER 1985, № 470, vol. 111(6).

Experimentelles FMCW-Radar zur hochfrequenten Charakterisierung von Windenergieanlagen

NASA Astrophysics Data System (ADS)

Schubert, Karsten; Werner, Jens; Schwartau, Fabian

2017-09-01

During the increasing dissemination of renewable energy sources the potential and actual interference effects of wind turbine plants became obvious. Turbines reflect the signals of weather radar and other radar systems. In addition to the static radar echoes, in particular the Doppler echoes are to be mentioned as an undesirable impairment Keränen (2014). As a result, building permit is refused for numerous new wind turbines, as the potential interference can not be reliably predicted. As a contribution to the improvement of this predictability, measurements are planned which aim at the high-frequency characterisation of wind energy installations. In this paper, a cost-effective FMCW radar is presented, which is operated in the same frequency band (C-band) as the weather radars of the German weather service. Here, the focus is on the description of the hardware design including the considerations used for its dimensioning.

Seasat-A ASVT: Commercial demonstration experiments. Results analysis methodology for the Seasat-A case studies

NASA Technical Reports Server (NTRS)

1979-01-01

The SEASAT-A commercial demonstration program ASVT is described. The program consists of a set of experiments involving the evaluation of a real time data distributions system, the SEASAT-A user data distribution system, that provides the capability for near real time dissemination of ocean conditions and weather data products from the U.S. Navy Fleet Numerical Weather Central to a selected set of commercial and industrial users and case studies, performed by commercial and industrial users, using the data gathered by SEASAT-A during its operational life. The impact of the SEASAT-A data on business operations is evaluated by the commercial and industrial users. The approach followed in the performance of the case studies, and the methodology used in the analysis and integration of the case study results to estimate the actual and potential economic benefits of improved ocean condition and weather forecast data are described.

Nowcasting system MeteoExpert at Irkutsk airport

NASA Astrophysics Data System (ADS)

Bazlova, Tatiana; Bocharnikov, Nikolai; Solonin, Alexander

2016-04-01

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

Preliminary Observing System Simulation Experiments for Doppler Wind Lidars Deployed on the International Space Station

NASA Technical Reports Server (NTRS)

Kemp, E.; Jacob, J.; Rosenberg, R.; Jusem, J. C.; Emmitt, G. D.; Wood, S.; Greco, L. P.; Riishojgaard, L. P.; Masutani, M.; Ma, Z.;

Understanding, representing and communicating earth system processes in weather and climate within CNRCWP

NASA Astrophysics Data System (ADS)

Sushama, Laxmi; Arora, Vivek; de Elia, Ramon; Déry, Stephen; Duguay, Claude; Gachon, Philippe; Gyakum, John; Laprise, René; Marshall, Shawn; Monahan, Adam; Scinocca, John; Thériault, Julie; Verseghy, Diana; Zwiers, Francis

2017-04-01

The Canadian Network for Regional Climate and Weather Processes (CNRCWP) provides significant advances and innovative research towards the ultimate goal of reducing uncertainty in numerical weather prediction and climate projections for Canada's Northern and Arctic regions. This talk will provide an overview of the Network and selected results related to the assessment of the added value of high-resolution modelling that has helped fill critical knowledge gaps in understanding the dynamics of extreme temperature and precipitation events and the complex land-atmosphere interactions and feedbacks in Canada's northern and Arctic regions. In addition, targeted developments in the Canadian regional climate model, that facilitate direct application of model outputs in impact and adaptation studies, particularly those related to the water, energy and infrastructure sectors will also be discussed. The close collaboration between the Network and its partners and end users contributed significantly to this effort.

Demystifying the Complexities of Gravity Wave Dynamics in the Middle Atmosphere: a Roadmap to Improved Weather Forecasts through High-Fidelity Modeling

NASA Astrophysics Data System (ADS)

Mixa, T.; Fritts, D. C.; Bossert, K.; Laughman, B.; Wang, L.; Lund, T.; Kantha, L. H.

2017-12-01

Gravity waves play a profound role in the mixing of the atmosphere, transporting vast amounts of momentum and energy among different altitudes as they propagate vertically. Above 60km in the middle atmosphere, high wave amplitudes enable a series of complex, nonlinear interactions with the background environment that produce highly-localized wind and temperature variations which alter the layering structure of the atmosphere. These small-scale interactions account for a significant portion of energy transport in the middle atmosphere, but they are difficult to characterize, occurring at spatial scales that are both challenging to observe with ground instruments and prohibitively small to include in weather forecasting models. Using high fidelity numerical simulations, these nuanced wave interactions are analyzed to better our understanding of these dynamics and improve the accuracy of long-term weather forecasting.

NASA's Advancements in Space-Based Spectrometry Lead to Improvements in Weather Prediction and Understanding of Climate Processes

NASA Technical Reports Server (NTRS)

Susskind, Joel

2010-01-01

AIRS is a precision state of the art High Spectral Resolution Multi-detector IR grating array spectrometer that was launched into a polar orbit on EOS Aqua in 2002. AIRS measures most of the infra-red spectrum with very low noise from 650/cm to 2660/cm with a resolving power of 2400 at a spatial resolution of 13 km. The objectives of AIRS were to perform accurate determination of atmospheric temperature and moisture profiles in up to 90% partial cloud cover conditions for the purpose of improving numerical weather prediction and understanding climate processes. AIRS data has also been used to determine accurate trace gas profiles. A brief overview of the retrieval methodology used to analyze AIRS observations under partial cloud cover will be presented and sample results will be shown from the weather and climate perspectives.

Integrating Multiple Space Ground Sensors to Track Volcanic Activity

NASA Technical Reports Server (NTRS)

Chien, Steve; Davies, Ashley; Doubleday, Joshua; Tran, Daniel; Jones, Samuel; Kjartansson, Einar; Thorsteinsson, Hrobjartur; Vogfjord, Kristin; Guomundsson, Magnus; Thordarson, Thor;

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

NASA Astrophysics Data System (ADS)

Castro, C.

2013-05-01

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

Fibonacci Grids

NASA Technical Reports Server (NTRS)

Swinbank, Richard; Purser, James

2006-01-01

Recent years have seen a resurgence of interest in a variety of non-standard computational grids for global numerical prediction. The motivation has been to reduce problems associated with the converging meridians and the polar singularities of conventional regular latitude-longitude grids. A further impetus has come from the adoption of massively parallel computers, for which it is necessary to distribute work equitably across the processors; this is more practicable for some non-standard grids. Desirable attributes of a grid for high-order spatial finite differencing are: (i) geometrical regularity; (ii) a homogeneous and approximately isotropic spatial resolution; (iii) a low proportion of the grid points where the numerical procedures require special customization (such as near coordinate singularities or grid edges). One family of grid arrangements which, to our knowledge, has never before been applied to numerical weather prediction, but which appears to offer several technical advantages, are what we shall refer to as "Fibonacci grids". They can be thought of as mathematically ideal generalizations of the patterns occurring naturally in the spiral arrangements of seeds and fruit found in sunflower heads and pineapples (to give two of the many botanical examples). These grids possess virtually uniform and highly isotropic resolution, with an equal area for each grid point. There are only two compact singular regions on a sphere that require customized numerics. We demonstrate the practicality of these grids in shallow water simulations, and discuss the prospects for efficiently using these frameworks in three-dimensional semi-implicit and semi-Lagrangian weather prediction or climate models.

The SURFEXv7.2 land and ocean surface platform for coupled or offline simulation of earth surface variables and fluxes

NASA Astrophysics Data System (ADS)

Masson, V.; Le Moigne, P.; Martin, E.; Faroux, S.; Alias, A.; Alkama, R.; Belamari, S.; Barbu, A.; Boone, A.; Bouyssel, F.; Brousseau, P.; Brun, E.; Calvet, J.-C.; Carrer, D.; Decharme, B.; Delire, C.; Donier, S.; Essaouini, K.; Gibelin, A.-L.; Giordani, H.; Habets, F.; Jidane, M.; Kerdraon, G.; Kourzeneva, E.; Lafaysse, M.; Lafont, S.; Lebeaupin Brossier, C.; Lemonsu, A.; Mahfouf, J.-F.; Marguinaud, P.; Mokhtari, M.; Morin, S.; Pigeon, G.; Salgado, R.; Seity, Y.; Taillefer, F.; Tanguy, G.; Tulet, P.; Vincendon, B.; Vionnet, V.; Voldoire, A.

2013-07-01

SURFEX is a new externalized land and ocean surface platform that describes the surface fluxes and the evolution of four types of surfaces: nature, town, inland water and ocean. It is mostly based on pre-existing, well-validated scientific models that are continuously improved. The motivation for the building of SURFEX is to use strictly identical scientific models in a high range of applications in order to mutualise the research and development efforts. SURFEX can be run in offline mode (0-D or 2-D runs) or in coupled mode (from mesoscale models to numerical weather prediction and climate models). An assimilation mode is included for numerical weather prediction and monitoring. In addition to momentum, heat and water fluxes, SURFEX is able to simulate fluxes of carbon dioxide, chemical species, continental aerosols, sea salt and snow particles. The main principles of the organisation of the surface are described first. Then, a survey is made of the scientific module (including the coupling strategy). Finally, the main applications of the code are summarised. The validation work undertaken shows that replacing the pre-existing surface models by SURFEX in these applications is usually associated with improved skill, as the numerous scientific developments contained in this community code are used to good advantage.

The Impact of Current and Future Polar Orbiting Satellite Data on Numerical Weather Prediction at NASA/GSFC

NASA Technical Reports Server (NTRS)

Atlas, Robert

2004-01-01

The lack of adequate observational data continues to be recognized as a major factor limiting both atmospheric research and numerical prediction on a variety of temporal and spatial scales. Since the advent of meteorological satellites in the 1960's, a considerable research effort has been directed toward the design of space-borne meteorological sensors, the development of optimal methods for the utilization of these data, (and an assessment of the influence of existing satellite data and the potential influence of future satellite observations on numerical weather prediction. This has included both Observing System Experiments (OSEs) and Observing System Simulation Experiments (OSSEs). OSEs are conducted to evaluate the impact of specific observations or classes of observations on analyses and forecasts. While OSEs are performed with existing data, OSSEs are conducted to evaluate the potential for future observing systems to improve-NWP, as well as to evaluate trade-offs in observing system design, and to develop and test improved methods for data assimilation. At the conference, results from OSEs to evaluate satellite data sets that have recently become available to the global observing system, such as AIRS and Seawinds, and results from OSSEs to determine the potential impact of space-based lidar winds will be presented.

The birth of numerical weather prediction

NASA Astrophysics Data System (ADS)

Wiin-Nielsen, A.

1991-08-01

The paper describes the major events leading gradually to operational, numerical, short-range predictions for the large-scale atmospheric flow. The theoretical foundation starting with Rossby's studies of the linearized, barotropic equation and ending a decade and a half later with the general formulation of the quasi-geostrophic, baroclinic model by Charney and Phillips is described. The problems connected with the very long waves and the inconsistences of the geostrophic approximation which were major obstacles in the first experimental forecasts are discussed. The resulting changes to divergent barotropic and baroclinic models and to the use of the balance equation are described. After the discussion of the theoretical foundation, the paper describes the major developments leading to the Meteorology Project at the Institute for Advanced Studied under the leadership of John von Neumann and Jule Charney followed by the establishment of the Joint Numerical Weather Prediction Unit in Suitland, Maryland. The interconnected developments in Europe, taking place more-or-less at the same time, are described by concentrating on the activities in Stockholm where the barotropic model was used in many experiments leading also to operational forecasts. The further developments resulting in the use of the primitive equations and the formulation of medium-range forecasting models are not included in the paper.

The birth of numerical weather prediction

NASA Astrophysics Data System (ADS)

Wiin-Nielsen, A.

1991-09-01

The paper describes the major events leading gradually to operational, numerical, short-range predictions for the large-scale atmospheric flow. The theoretical foundation starting with Rossby's studies of the linearized, barotropic equation and ending a decade and a half later with the general formulation of the quasi-geostrophic, baroclinic model by Charney and Phillips is described. The problems connected with the very long waves and the inconsistences of the geostrophic approximation which were major obstacles in the first experimental forecasts are discussed. The resulting changes to divergent barotropic and baroclinic models and to the use of the balance equation are described. After the discussion of the theoretical foundation, the paper describes the major developments leading to the Meteorology Project at the Institute for Advanced Studied under the leadership of John von Neumann and Jule Charney followed by the establishment of the Joint Numerical Weather Prediction Unit in Suitland, Maryland. The inter-connected developments in Europe, taking place more-or-less at the same time, are described by concentrating on the activities in Stockholm where the barotropic model was used in many experiments leading also to operational forecasts. The further developments resulting in the use of the primitive equations and the formulation of medium-range forecasting models are not included in the paper.

Analysis of GEO spacecraft anomalies: Space weather relationships

NASA Astrophysics Data System (ADS)

Choi, Ho-Sung; Lee, Jaejin; Cho, Kyung-Suk; Kwak, Young-Sil; Cho, Il-Hyun; Park, Young-Deuk; Kim, Yeon-Han; Baker, Daniel N.; Reeves, Geoffrey D.; Lee, Dong-Kyu

2011-06-01

While numerous anomalies and failures of spacecraft have been reported since the beginning of the space age, space weather effects on modern spacecraft systems have been emphasized more and more with the increase of their complexity and capability. However, the relationship between space weather and commercial satellite anomalies has not been studied extensively. In this paper, we investigate the geostationary Earth orbit (GEO) satellite anomalies archived by Satellite News Digest during 1997-2009 in order to search for possible influences of space weather on the anomaly occurrences. We analyze spacecraft anomalies for the Kp index, local time, and season and then compare them with the tendencies of charged particles observed by Los Alamos National Laboratory (LANL) satellites. We obtain the following results: (1) there are good relationships between geomagnetic activity (as measured by the Kp index) and anomaly occurrences of the GEO satellites; (2) the satellite anomalies occurred mainly in the midnight to morning sector; and (3) the anomalies are found more frequently in spring and fall than summer and winter. While we cannot fully explain how space weather is involved in producing such anomalies, our analysis of LANL data shows that low-energy (<100 keV) electrons have similar behaviors with spacecraft anomalies and implies the spacecraft charging might dominantly contribute to the GEO spacecraft anomalies reported in Satellite News Digest.

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

NASA Astrophysics Data System (ADS)

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

2017-01-01

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

Studying Weather and Climate Using Atmospheric Retrospective Analyses

NASA Astrophysics Data System (ADS)

Bosilovich, M. G.

2014-12-01

Over the last 35 years, tremendous amounts of satellite observations of the Earth's atmosphere have been collected along side the much longer and diverse record of in situ measurements. The satellite data records have disparate qualities, structure and uncertainty which make comparing weather from the 80s and 2000s a challenging prospect. Likewise, in-situ data records lack complete coverage of the earth in both space and time. Atmospheric reanalyses use the observations with numerical models and data assimilation to produce continuous and consistent weather data records for periods longer than decades. The result is a simplified data format with a relatively straightforward learning curve that includes many more variables available (through the modeling component of the system), but driven by a full suite of observational data. The simplified data format allows introduction into weather and climate data analysis. Some examples are provided from undergraduate meteorology program internship projects. We will present the students progression through the projects from their initial understanding and competencies to some final results and the skills learned along the way. Reanalyses are a leading research tool in weather and climate, but can also provide an introductory experience as well, allowing students to develop an understanding of the physical system while learning basic programming and analysis skills.

Development of NASA-DeBakey Ventricular Assist Device Using Numerical Aerospace Simulation Technology

NASA Technical Reports Server (NTRS)

Kwak, Dochan

2000-01-01

Over three million Americans and 20 million people worldwide suffer from some form of heart failure. Mechanical heart assist devices are being used as a temporary support to sick ventricle and valves as a bridge-to-transplant or bridge-to-recovery. This viewgraph presentation gives an overview of the development of NASA-DeBakey Ventricular Assist Device (VAD) using numerical aerospace simulation technology.

Overview and Meteorological Validation of the Wind Integration National Dataset toolkit

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

Draxl, C.; Hodge, B. M.; Clifton, A.

2015-04-13

The Wind Integration National Dataset (WIND) Toolkit described in this report fulfills these requirements, and constitutes a state-of-the-art national wind resource data set covering the contiguous United States from 2007 to 2013 for use in a variety of next-generation wind integration analyses and wind power planning. The toolkit is a wind resource data set, wind forecast data set, and wind power production and forecast data set derived from the Weather Research and Forecasting (WRF) numerical weather prediction model. WIND Toolkit data are available online for over 116,000 land-based and 10,000 offshore sites representing existing and potential wind facilities.

Description of atmospheric conditions at the Pierre Auger Observatory using the Global Data Assimilation System (GDAS)

NASA Astrophysics Data System (ADS)

Pierre Auger Collaboration; Abreu, P.; Aglietta, M.; Ahlers, M.; Ahn, E. J.; Albuquerque, I. F. M.; Allard, D.; Allekotte, I.; Allen, J.; Allison, P.; Almela, A.; Alvarez Castillo, J.; Alvarez-Muñiz, J.; Ambrosio, M.; Aminaei, A.; Anchordoqui, L.; Andringa, S.; Antiči'C, T.; Aramo, C.; Arganda, E.; Arqueros, F.; Asorey, H.; Assis, P.; Aublin, J.; Ave, M.; Avenier, M.; Avila, G.; Bäcker, T.; Badescu, A. M.; Balzer, M.; Barber, K. B.; Barbosa, A. F.; Bardenet, R.; Barroso, S. L. C.; Baughman, B.; Bäuml, J.; Beatty, J. J.; Becker, B. R.; Becker, K. H.; Bellétoile, A.; Bellido, J. A.; Benzvi, S.; Berat, C.; Bertou, X.; Biermann, P. L.; Billoir, P.; Blanco, F.; Blanco, M.; Bleve, C.; Blümer, H.; Boháčová, M.; Boncioli, D.; Bonifazi, C.; Bonino, R.; Borodai, N.; Brack, J.; Brancus, I.; Brogueira, P.; Brown, W. C.; Bruijn, R.; Buchholz, P.; Bueno, A.; Burton, R. E.; Caballero-Mora, K. S.; Caccianiga, B.; Caramete, L.; Caruso, R.; Castellina, A.; Catalano, O.; Cataldi, G.; Cazon, L.; Cester, R.; Chauvin, J.; Cheng, S. H.; Chiavassa, A.; Chinellato, J. A.; Chirinos Diaz, J.; Chudoba, J.; Clay, R. W.; Coluccia, M. R.; Conceição, R.; Contreras, F.; Cook, H.; Cooper, M. J.; Coppens, J.; Cordier, A.; Coutu, S.; Covault, C. E.; Creusot, A.; Criss, A.; Cronin, J.; Curutiu, A.; Dagoret-Campagne, S.; Dallier, R.; Daniel, B.; Dasso, S.; Daumiller, K.; Dawson, B. R.; de Almeida, R. M.; de Domenico, M.; de Donato, C.; de Jong, S. J.; de La Vega, G.; de Mello Junior, W. J. M.; de Mello Neto, J. R. T.; de Mitri, I.; de Souza, V.; de Vries, K. D.; Del Peral, L.; Del Río, M.; Deligny, O.; Dembinski, H.; Dhital, N.; di Giulio, C.; Díaz Castro, M. L.; Diep, P. N.; Diogo, F.; Dobrigkeit, C.; Docters, W.; D'Olivo, J. C.; Dong, P. N.; Dorofeev, A.; Dos Anjos, J. C.; Dova, M. T.; D'Urso, D.; Dutan, I.; Ebr, J.; Engel, R.; Erdmann, M.; Escobar, C. O.; Espadanal, J.; Etchegoyen, A.; Facal San Luis, P.; Fajardo Tapia, I.; Falcke, H.; Farrar, G.; Fauth, A. C.; Fazzini, N.; Ferguson, A. P.; Fick, B.; Filevich, A.; Filipčič, A.; Fliescher, S.; Fracchiolla, C. E.; Fraenkel, E. D.; Fratu, O.; Fröhlich, U.; Fuchs, B.; Gaior, R.; Gamarra, R. F.; Gambetta, S.; García, B.; Garcia Roca, S. T.; Garcia-Gamez, D.; Garcia-Pinto, D.; Gascon, A.; Gemmeke, H.; Ghia, P. L.; Giaccari, U.; Giller, M.; Glass, H.; Gold, M. S.; Golup, G.; Gomez Albarracin, F.; Gómez Berisso, M.; Gómez Vitale, P. F.; Gonçalves, P.; Gonzalez, D.; Gonzalez, J. G.; Gookin, B.; Gorgi, A.; Gouffon, P.; Grashorn, E.; Grebe, S.; Griffith, N.; Grigat, M.; Grillo, A. F.; Guardincerri, Y.; Guarino, F.; Guedes, G. P.; Guzman, A.; Hansen, P.; Harari, D.; Harrison, T. A.; Harton, J. L.; Haungs, A.; Hebbeker, T.; Heck, D.; Herve, A. E.; Hojvat, C.; Hollon, N.; Holmes, V. C.; Homola, P.; Hörandel, J. R.; Horneffer, A.; Horvath, P.; Hrabovský, M.; Huber, D.; Huege, T.; Insolia, A.; Ionita, F.; Italiano, A.; Jarne, C.; Jiraskova, S.; Josebachuili, M.; Kadija, K.; Kampert, K. H.; Karhan, P.; Kasper, P.; Kégl, B.; Keilhauer, B.; Keivani, A.; Kelley, J. L.; Kemp, E.; Kieckhafer, R. M.; Klages, H. O.; Kleifges, M.; Kleinfeller, J.; Knapp, J.; Koang, D.-H.; Kotera, K.; Krohm, N.; Krömer, O.; Kruppke-Hansen, D.; Kuehn, F.; Kuempel, D.; Kulbartz, J. K.; Kunka, N.; La Rosa, G.; Lachaud, C.; Lahurd, D.; Latronico, L.; Lauer, R.; Lautridou, P.; Le Coz, S.; Leão, M. S. A. B.; Lebrun, D.; Lebrun, P.; Leigui de Oliveira, M. A.; Letessier-Selvon, A.; Lhenry-Yvon, I.; Link, K.; López, R.; Lopez Agüera, A.; Louedec, K.; Lozano Bahilo, J.; Lu, L.; Lucero, A.; Ludwig, M.; Lyberis, H.; Maccarone, M. C.; Macolino, C.; Maldera, S.; Mandat, D.; Mantsch, P.; Mariazzi, A. G.; Marin, J.; Marin, V.; Maris, I. C.; Marquez Falcon, H. R.; Marsella, G.; Martello, D.; Martin, L.; Martinez, H.; Martínez Bravo, O.; Mathes, H. J.; Matthews, J.; Matthews, J. A. J.; Matthiae, G.; Maurel, D.; Maurizio, D.; Mazur, P. O.; Medina-Tanco, G.; Melissas, M.; Melo, D.; Menichetti, E.; Menshikov, A.; Mertsch, P.; Meurer, C.; Mi'Canovi'C, S.; Micheletti, M. I.; Minaya, I. A.; Miramonti, L.; Molina-Bueno, L.; Mollerach, S.; Monasor, M.; Monnier Ragaigne, D.; Montanet, F.; Morales, B.; Morello, C.; Moreno, E.; Moreno, J. C.; Mostafá, M.; Moura, C. A.; Muller, M. A.; Müller, G.; Münchmeyer, M.; Mussa, R.; Navarra, G.; Navarro, J. L.; Navas, S.; Necesal, P.; Nellen, L.; Nelles, A.; Neuser, J.; Nhung, P. T.; Niechciol, M.; Niemietz, L.; Nierstenhoefer, N.; Nitz, D.; Nosek, D.; Nožka, L.; Oehlschläger, J.; Olinto, A.; Ortiz, M.; Pacheco, N.; Pakk Selmi-Dei, D.; Palatka, M.; Pallotta, J.; Palmieri, N.; Parente, G.; Parizot, E.; Parra, A.; Pastor, S.; Paul, T.; Pech, M.; Pȩkala, J.; Pelayo, R.; Pepe, I. M.; Perrone, L.; Pesce, R.; Petermann, E.; Petrera, S.; Petrinca, P.; Petrolini, A.; Petrov, Y.; Pfendner, C.; Piegaia, R.; Pierog, T.; Pieroni, P.; Pimenta, M.; Pirronello, V.; Platino, M.; Ponce, V. H.; Pontz, M.; Porcelli, A.; Privitera, P.; Prouza, M.; Quel, E. J.; Querchfeld, S.; Rautenberg, J.; Ravel, O.; Ravignani, D.; Revenu, B.; Ridky, J.; Riggi, S.; Risse, M.; Ristori, P.; Rivera, H.; Rizi, V.; Roberts, J.; Rodrigues de Carvalho, W.; Rodriguez, G.; Rodriguez Martino, J.; Rodriguez Rojo, J.; Rodriguez-Cabo, I.; Rodríguez-Frías, M. D.; Ros, G.; Rosado, J.; Rossler, T.; Roth, M.; Rouillé-D'Orfeuil, B.; Roulet, E.; Rovero, A. C.; Rühle, C.; Saftoiu, A.; Salamida, F.; Salazar, H.; Salesa Greus, F.; Salina, G.; Sánchez, F.; Santo, C. E.; Santos, E.; Santos, E. M.; Sarazin, F.; Sarkar, B.; Sarkar, S.; Sato, R.; Scharf, N.; Scherini, V.; Schieler, H.; Schiffer, P.; Schmidt, A.; Scholten, O.; Schoorlemmer, H.; Schovancova, J.; Schovánek, P.; Schröder, F.; Schulte, S.; Schuster, D.; Sciutto, S. J.; Scuderi, M.; Segreto, A.; Settimo, M.; Shadkam, A.; Shellard, R. C.; Sidelnik, I.; Sigl, G.; Silva Lopez, H. H.; Sima, O.; 'Smiałkowski, A.; Šmída, R.; Snow, G. R.; Sommers, P.; Sorokin, J.; Spinka, H.; Squartini, R.; Srivastava, Y. N.; Stanic, S.; Stapleton, J.; Stasielak, J.; Stephan, M.; Stutz, A.; Suarez, F.; Suomijärvi, T.; Supanitsky, A. D.; Šuša, T.; Sutherland, M. S.; Swain, J.; Szadkowski, Z.; Szuba, M.; Tapia, A.; Tartare, M.; Taşcău, O.; Tavera Ruiz, C. G.; Tcaciuc, R.; Thao, N. T.; Thomas, D.; Tiffenberg, J.; Timmermans, C.; Tkaczyk, W.; Todero Peixoto, C. J.; Toma, G.; Tomankova, L.; Tomé, B.; Tonachini, A.; Travnicek, P.; Tridapalli, D. B.; Tristram, G.; Trovato, E.; Tueros, M.; Ulrich, R.; Unger, M.; Urban, M.; Valdés Galicia, J. F.; Valiño, I.; Valore, L.; van den Berg, A. M.; Varela, E.; Vargascárdenas, B.; Vázquez, J. R.; Vázquez, R. A.; Veberič, D.; Verzi, V.; Vicha, J.; Videla, M.; Villaseñor, L.; Wahlberg, H.; Wahrlich, P.; Wainberg, O.; Walz, D.; Watson, A. A.; Weber, M.; Weidenhaupt, K.; Weindl, A.; Werner, F.; Westerhoff, S.; Whelan, B. J.; Widom, A.; Wieczorek, G.; Wiencke, L.; Wilczyńska, B.; Wilczyński, H.; Will, M.; Williams, C.; Winchen, T.; Wommer, M.; Wundheiler, B.; Yamamoto, T.; Yapici, T.; Younk, P.; Yuan, G.; Yushkov, A.; Zamorano, B.; Zas, E.; Zavrtanik, D.; Zavrtanik, M.; Zaw, I.; Zepeda, A.; Zhu, Y.; Zimbres Silva, M.; Ziolkowski, M.

2012-04-01

Atmospheric conditions at the site of a cosmic ray observatory must be known for reconstructing observed extensive air showers. The Global Data Assimilation System (GDAS) is a global atmospheric model predicated on meteorological measurements and numerical weather predictions. GDAS provides altitude-dependent profiles of the main state variables of the atmosphere like temperature, pressure, and humidity. The original data and their application to the air shower reconstruction of the Pierre Auger Observatory are described. By comparisons with radiosonde and weather station measurements obtained on-site in Malargüe and averaged monthly models, the utility of the GDAS data is shown.

AIRS: Improving Weather Forecasting and Providing New Data on Greenhouse Gases

NASA Technical Reports Server (NTRS)

Chahine, Moustafa T.; Pagano, Thomas S.; Aumann, Hartmut H.; Atlas, Robert; Barnet, Christopher; Blaisdell, John; Chen, Luke; Divakarla, Murty; Fetzer, Eric J.; Goldberg, Mitch;

The scientific challenges to forecasting and nowcasting the solar origins of space weather (Invited)

NASA Astrophysics Data System (ADS)

Schrijver, C. J.; Title, A. M.

2013-12-01

With the full-sphere continuous coverage of the Sun achieved by combining SDO and STEREO imagery comes the realization that solar activity is a manifestation of local processes that respond to long-range if not global influences. Numerical experiments provide insights into these couplings, as well as into the intricacies of destabilizations of field emerging into pre-existing configurations and evolving within the context of their dynamic surroundings. With these capabilities grows an understanding of the difficulties in forecasting of the solar origins of space weather: we need assimilative global non-potential field models, but our observational resources are too limited to meet that need.

Description of Atmospheric Conditions at the Pierre Auger Observatory using the Global Data Assimilation System (GDAS)

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

Abreu, P.; /Lisbon, IST; Aglietta, M.

2012-01-01

Atmospheric conditions at the site of a cosmic ray observatory must be known for reconstructing observed extensive air showers. The Global Data Assimilation System (GDAS) is a global atmospheric model predicated on meteorological measurements and numerical weather predictions. GDAS provides altitude-dependent profiles of the main state variables of the atmosphere like temperature, pressure, and humidity. The original data and their application to the air shower reconstruction of the Pierre Auger Observatory are described. By comparisons with radiosonde and weather station measurements obtained on-site in Malargue and averaged monthly models, the utility of the GDAS data is shown.

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.

Foreword to the Special Issue on Remote Sensing and Modeling of Surface Properties

USDA-ARS?s Scientific Manuscript database

CURRENTLY, the Numerical Weather Prediction (NWP) community is striving for better ways to extract information on the lower layer using current and future satellite systems to improve short-term to medium-range forecasts. The surface emissivity is highly variable and may cause biases in the forward ...

Approaching messy problems: strategies for environmental analysis

Treesearch

L. M. Reid; R. R. Ziemer; T. E. Lisle

1996-01-01

Environmental problems are never neatly defined. Instead, each is a tangle of interacting processes whose manifestation and interpretation are warped by the vagaries of time, weather, expectation, and economics. Each problem involves livelihoods, values, and numerous specialized disciplines. Nevertheless, federal agencies in the Pacific Northwest have been given the...

MAPPING DISSEMINATION OF CHEMICAL AFTER DISPERSIVE EVENTS USING AN AMBIENT-AIR, SURFACE SAMPLING TIME-OF-FLIGHT MASS SPECTROMETER

EPA Science Inventory

Chemicals are dispersed by numerous accidental, deliberate, or weather-related events. Often, rapid analyses are desired to identify dispersed chemicals and to delineate areas of contamination. Hundreds of wipe samples might be collected from outdoor surfaces or building interi...

Application of Intel Many Integrated Core (MIC) architecture to the Yonsei University planetary boundary layer scheme in Weather Research and Forecasting model

NASA Astrophysics Data System (ADS)

Huang, Melin; Huang, Bormin; Huang, Allen H.

2014-10-01

The Weather Research and Forecasting (WRF) model provided operational services worldwide in many areas and has linked to our daily activity, in particular during severe weather events. The scheme of Yonsei University (YSU) is one of planetary boundary layer (PBL) models in WRF. The PBL is responsible for vertical sub-grid-scale fluxes due to eddy transports in the whole atmospheric column, determines the flux profiles within the well-mixed boundary layer and the stable layer, and thus provide atmospheric tendencies of temperature, moisture (including clouds), and horizontal momentum in the entire atmospheric column. The YSU scheme is very suitable for massively parallel computation as there are no interactions among horizontal grid points. To accelerate the computation process of the YSU scheme, we employ Intel Many Integrated Core (MIC) Architecture as it is a multiprocessor computer structure with merits of efficient parallelization and vectorization essentials. Our results show that the MIC-based optimization improved the performance of the first version of multi-threaded code on Xeon Phi 5110P by a factor of 2.4x. Furthermore, the same CPU-based optimizations improved the performance on Intel Xeon E5-2603 by a factor of 1.6x as compared to the first version of multi-threaded code.

Integrated site-specific quantification of faecal bacteria and detection of DNA markers in faecal contamination source tracking as a microbial risk tracking tool in urban Lake ecosystems

NASA Astrophysics Data System (ADS)

Donde, Oscar Omondi; Tian, Cuicui; Xiao, Bangding

2017-11-01

The presence of feacal-derived pathogens in water is responsible for several infectious diseases and deaths worldwide. As a solution, sources of fecal pollution in waters must be accurately assessed, properly determined and strictly controlled. However, the exercise has remained challenging due to the existing overlapping characteristics by different members of faecal coliform bacteria and the inadequacy of information pertaining to the contribution of seasonality and weather condition on tracking the possible sources of pollution. There are continued efforts to improve the Faecal Contamination Source Tracking (FCST) techniques such as Microbial Source Tracking (MST). This study aimed to make contribution to MST by evaluating the efficacy of combining site specific quantification of faecal contamination indicator bacteria and detection of DNA markers while accounting for seasonality and weather conditions' effects in tracking the major sources of faecal contamination in a freshwater system (Donghu Lake, China). The results showed that the use of cyd gene in addition to lacZ and uidA genes differentiates E. coli from other closely related faecal bacteria. The use of selective media increases the pollution source tracking accuracy. BSA addition boosts PCR detection and increases FCST efficiency. Seasonality and weather variability also influence the detection limit for DNA markers.

Microclimate Exposures of Surface-Based Weather Stations: Implications For The Assessment of Long-Term Temperature Trends.

NASA Astrophysics Data System (ADS)

Davey, Christopher A.; Pielke, Roger A., Sr.

2005-04-01

The U.S. Historical Climate Network is a subset of surface weather observation stations selected from the National Weather Service cooperative station network. The criteria used to select these stations do not sufficiently address station exposure characteristics. In addition, the current metadata available for cooperative network stations generally do not describe site exposure characteristics in sufficient detail. This paper focuses on site exposures with respect to air temperature measurements. A total of 57 stations were photographically surveyed in eastern Colorado, comparing existing exposures to the standards endorsed by the World Meteorological Organization. The exposures of most sites surveyed, including U.S. Historical Climate Network sites, were observed to fall short of these standards. This raises a critical question about the use of many Historical Climate Network sites in the development of long-term climate records and the detection of climate trends. Some of these sites clearly have poor exposures and therefore should be considered for removal from the Historical Climate Network. Candidate replacement sites do exist and should be considered for addition into the network to replace the removed sites. Documentation as performed for this study should be conducted worldwide in order to determine the extent of spatially nonrepresentative exposures and possible temperature biases.

How Satellites Have Contributed to Building a Weather Ready Nation

NASA Astrophysics Data System (ADS)

Lapenta, W.

2017-12-01

NOAA's primary mission since its inception has been to reduce the loss of life and property, as well as disruptions from, high impact weather and water-related events. In recent years, significant societal losses resulting even from well forecast extreme events have shifted attention from the forecast alone toward ensuring societal response is equal to the risks that exist for communities, businesses and the public. The responses relate to decisions ranging from coastal communities planning years in advance to mitigate impacts from rising sea level, to immediate lifesaving decisions such as a family seeking adequate shelter during a tornado warning. NOAA is committed to building a "Weather-Ready Nation" where communities are prepared for and respond appropriately to these events. The Weather-Ready Nation (WRN) strategic priority is building community resilience in the face of increasing vulnerability to extreme weather, water, climate and environmental threats. To build a Weather-Ready Nation, NOAA is enhancing Impact-Based Decision Support Services (IDSS), transitioning science and technology advances into forecast operations, applying social science research to improve the communication and usefulness of information, and expanding its dissemination efforts to achieve far-reaching readiness, responsiveness and resilience. These four components of Weather-Ready Nation are helping ensure NOAA data, products and services are fully utilized to minimize societal impacts from extreme events. Satellite data and satellite products have been important elements of the national Weather Service (NWS) operations for more than 40 years. When one examines the uses of satellite data specific to the internal forecast and warning operations of NWS, two main applications are evident. The first is the use of satellite data in numerical weather prediction models; the second is the use of satellite imagery and derived products for mesoscale and short-range weather warning and prediction. The purpose of this paper is to highlight the value of the satellite component of the global observing system to NWS operational weather forecasting and emphasize how these data form a critical component of the NWS ability to protect life and property and ensure economic well-being.

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

NASA Astrophysics Data System (ADS)

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

2014-12-01

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

Evaluating the Impacts of NASA/SPoRT Daily Greenness Vegetation Fraction on Land Surface Model and Numerical Weather Forecasts

NASA Technical Reports Server (NTRS)

Bell, Jordan R.; Case, Jonathan L.; Molthan, Andrew L.

2011-01-01

The NASA Short-term Prediction Research and Transition (SPoRT) Center develops new products and techniques that can be used in operational meteorology. The majority of these products are derived from NASA polar-orbiting satellite imagery from the Earth Observing System (EOS) platforms. One such product is a Greenness Vegetation Fraction (GVF) dataset, which is produced from Moderate Resolution Imaging Spectroradiometer (MODIS) data aboard the NASA EOS Aqua and Terra satellites. NASA SPoRT began generating daily real-time GVF composites at 1-km resolution over the Continental United States (CONUS) on 1 June 2010. The purpose of this study is to compare the National Centers for Environmental Prediction (NCEP) climatology GVF product (currently used in operational weather models) to the SPoRT-MODIS GVF during June to October 2010. The NASA Land Information System (LIS) was employed to study the impacts of the new SPoRT-MODIS GVF dataset on land surface models apart from a full numerical weather prediction (NWP) model. For the 2010 warm season, the SPoRT GVF in the western portion of the CONUS was generally higher than the NCEP climatology. The eastern CONUS GVF had variations both above and below the climatology during the period of study. These variations in GVF led to direct impacts on the rates of heating and evaporation from the land surface. The second phase of the project is to examine the impacts of the SPoRT GVF dataset on NWP using the Weather Research and Forecasting (WRF) model. Two separate WRF model simulations were made for individual severe weather case days using the NCEP GVF (control) and SPoRT GVF (experimental), with all other model parameters remaining the same. Based on the sensitivity results in these case studies, regions with higher GVF in the SPoRT model runs had higher evapotranspiration and lower direct surface heating, which typically resulted in lower (higher) predicted 2-m temperatures (2-m dewpoint temperatures). The opposite was true for areas with lower GVF in the SPoRT model runs. These differences in the heating and evaporation rates produced subtle yet quantifiable differences in the simulated convective precipitation systems for the selected severe weather case examined.

Weather Prediction Improvement Using Advanced Satellite Technology

NASA Technical Reports Server (NTRS)

Einaudi, Franco; Uccellini, L.; Purdom, J.; Rogers, D.; Gelaro, R.; Dodge, J.; Atlas, R.; Lord, S.

2001-01-01

We discuss in this paper some of the problems that exist today in the fall utilization of satellite data to improve weather forecasts and we propose specific recommendations to solve them. This discussion can be viewed as an aspect of the general debate on how best to organize the transition from research to operational satellites and how to evaluate the impact of a research instrument on numerical weather predictions. A method for providing this transition is offered by the National Polar-Orbiting Operational Environmental Satellite System (NPOESS) Preparatory Project (NPP). This mission will bridge the time between the present NOAA and Department of Defense (DOD) polar orbiting missions and the initiation of the converged NPOESS series and will evaluate some of the Earth Observing System (EOS) instruments as appropriate for operational missions. Thus, this mission can be viewed as an effort to meet the operational requirements of NOAA and DOD and the research requirements of NASA. More generally, however, it can be said that the process of going from the conception of new, more advanced instruments to their operational implementation and full utilization by the weather forecast communities is not optimal. Instruments developed for research purposes may have insufficient funding to explore their potential operational capabilities. Furthermore, instrument development programs designed for operational satellites typically have insufficient funding for assimilation algorithms needed to transform the satellite observations into data that can be used by sophisticated global weather forecast models. As a result, years often go by before satellite data are efficiently used for operational forecasts. NASA and NOAA each have unique expertise in the design of satellite instruments, their use for basic and applied research and their utilization in weather and climate research. At a time of limited resources, the two agencies must combine their efforts to work toward common goals of full utilization of satellite data. This is a challenge that requires the assimilation of myriad new data into increasingly sophisticated numerical forecast models that run on increasingly sophisticated computer systems. In section II, we briefly outline the impact of satellite data on the quality of the National Centers for Environmental Prediction (NCEP) forecasts. In section III, we describe the present status of the utilization of satellite data in NCEP models and the challenges that lie ahead. In section IV, we propose solutions whose goals are summarized in section V.

A Meteorological Supersite for Aviation and Cold Weather Applications

NASA Astrophysics Data System (ADS)

Gultepe, Ismail; Agelin-Chaab, M.; Komar, J.; Elfstrom, G.; Boudala, F.; Zhou, B.

2018-05-01

The goal of this study is to better understand atmospheric boundary layer processes and parameters, and to evaluate physical processes for aviation applications using data from a supersite observing site. Various meteorological sensors, including a weather and environmental unmanned aerial vehicle (WE-UAV), and a fog and snow tower (FSOS) observations are part of the project. The PanAm University of Ontario Institute of Technology (UOIT) Meteorological Supersite (PUMS) observations are being collected from April 2015 to date. The FSOS tower gathers observations related to rain, snow, fog, and visibility, aerosols, solar radiation, and wind and turbulence, as well as surface and sky temperature. The FSOSs are located at three locations at about 450-800 m away from the PUMS supersite. The WE-UAV measurements representing aerosol, wind speed and direction, as well as temperature (T) and relative humidity (RH) are provided during clear weather conditions. Other measurements at the PUMS site include cloud backscattering profiles from CL51 ceilometer, MWR observations of liquid water content (LWC), T, and RH, and Microwave Rain Radar (MRR) reflectivity profile, as well as the present weather type, snow water depth, icing rate, 3D-ultrasonic wind and turbulence, and conventional meteorological observations from compact weather stations, e.g., WXTs. The results based on important weather event studies, representing fog, snow, rain, blowing snow, wind gust, planetary boundary layer (PBL) wind research for UAV, and icing conditions are given. The microphysical parameterizations and analysis processes for each event are provided, but the results should not be generalized for all weather events and be used cautiously. Results suggested that integrated observing systems based on data from a supersite as well as satellite sites can provide better information applicable to aviation meteorology, including PBL weather research, validation of numerical weather model predictions, and remote-sensing retrievals. Overall, the results from the five cases are provided and challenges related to observations applicable to aviation meteorology are discussed.

Prediction of County-Level Corn Yields Using an Energy-Crop Growth Index.

NASA Astrophysics Data System (ADS)

Andresen, Jeffrey A.; Dale, Robert F.; Fletcher, Jerald J.; Preckel, Paul V.

1989-01-01

Weather conditions significantly affect corn yields. while weather remains as the major uncontrolled variable in crop production, an understanding of the influence of weather on yields can aid in early and accurate assessment of the impact of weather and climate on crop yields and allow for timely agricultural extension advisories to help reduce farm management costs and improve marketing, decisions. Based on data for four representative countries in Indiana from 1960 to 1984 (excluding 1970 because of the disastrous southern corn leaf blight), a model was developed to estimate corn (Zea mays L.) yields as a function of several composite soil-crop-weather variables and a technology-trend marker, applied nitrogen fertilizer (N). The model was tested by predicting corn yields for 15 other counties. A daily energy-crop growth (ECG) variable in which different weights were used for the three crop-weather variables which make up the daily ECG-solar radiation intercepted by the canopy, a temperature function, and the ratio of actual to potential evapotranspiration-performed better than when the ECG components were weighted equally. The summation of the weighted daily ECG over a relatively short period (36 days spanning silk) was found to provide the best index for predicting county average corn yield. Numerical estimation results indicate that the ratio of actual to potential evapotranspiration (ET/PET) is much more important than the other two ECG factors in estimating county average corn yield in Indiana.

Thermal stress weathering and the spalling of Antarctic rocks

NASA Astrophysics Data System (ADS)

Lamp, J. L.; Marchant, D. R.; Mackay, S. L.; Head, J. W.

2017-01-01

Using in situ field measurements, laboratory analyses, and numerical modeling, we test the potential efficacy of thermal stress weathering in the flaking of millimeter-thick alteration rinds observed on cobbles and boulders of Ferrar Dolerite on Mullins Glacier, McMurdo Dry Valleys (MDV). In particular, we examine whether low-magnitude stresses, arising from temperature variations over time, result in thermal fatigue weathering, yielding slow crack propagation along existing cracks and ultimate flake detachment. Our field results show that during summer months clasts of Ferrar Dolerite experience large-temperature gradients across partially detached alteration rinds (>4.7°C mm-1) and abrupt fluctuations in surface temperature (up to 12°C min-1); the latter are likely due to the combined effects of changing solar irradiation and cooling from episodic winds. The results of our thermal stress model, coupled with subcritical crack growth theory, suggest that thermal stresses induced at the base of thin alteration rinds 2 mm thick, common on rocks exposed for 105 years, may be sufficient to cause existing cracks to propagate under present-day meteorological forcing, eventually leading to rind detachment. The increase in porosity observed within alteration rinds relative to unaltered rock interiors, as well as predicted decreases in rind strength based on allied weathering studies, likely facilitates thermal stress crack propagation through a reduction of fracture toughness. We conclude that thermal stress weathering may be an active, though undervalued, weathering process in hyperarid, terrestrial polar deserts such as the stable upland region of the MDV.

Transforming the sensing and numerical prediction of high-impact local weather through dynamic adaptation.

PubMed

Droegemeier, Kelvin K

2009-03-13

Mesoscale weather, such as convective systems, intense local rainfall resulting in flash floods and lake effect snows, frequently is characterized by unpredictable rapid onset and evolution, heterogeneity and spatial and temporal intermittency. Ironically, most of the technologies used to observe the atmosphere, predict its evolution and compute, transmit or store information about it, operate in a static pre-scheduled framework that is fundamentally inconsistent with, and does not accommodate, the dynamic behaviour of mesoscale weather. As a result, today's weather technology is highly constrained and far from optimal when applied to any particular situation. This paper describes a new cyberinfrastructure framework, in which remote and in situ atmospheric sensors, data acquisition and storage systems, assimilation and prediction codes, data mining and visualization engines, and the information technology frameworks within which they operate, can change configuration automatically, in response to evolving weather. Such dynamic adaptation is designed to allow system components to achieve greater overall effectiveness, relative to their static counterparts, for any given situation. The associated service-oriented architecture, known as Linked Environments for Atmospheric Discovery (LEAD), makes advanced meteorological and cyber tools as easy to use as ordering a book on the web. LEAD has been applied in a variety of settings, including experimental forecasting by the US National Weather Service, and allows users to focus much more attention on the problem at hand and less on the nuances of data formats, communication protocols and job execution environments.

Main components and characteristics of landslide early warning systems operational worldwide

NASA Astrophysics Data System (ADS)

Piciullo, Luca; Cepeda, José

2017-04-01

During the last decades the number of victims and economic losses due to natural hazards are dramatically increased worldwide. The reason can be mainly ascribed to climate changes and urbanization in areas exposed at high level of risk. Among the many mitigation measures available for reducing the risk to life related to natural hazards, early warning systems certainly constitute a significant cost-effective option available to the authorities in charge of risk management and governance. The aim is to help and protect populations exposed to natural hazards, reducing fatalities when major events occur. Landslide is one of the natural hazards addressed by early warning systems. Landslide early warning systems (LEWSs) are mainly composed by the following four components: set-up, correlation laws, decisional algorithm and warning management. Within this framework, the set-up includes all the preliminary actions and choices necessary for designing a LEWS, such as: the area covered by the system, the types of landslides and the monitoring instruments. The monitoring phase provides a series of important information on different variables, considered as triggering factors for landslides, in order to define correlation laws and thresholds. Then, a decisional algorithm is necessary for defining the: number of warning levels to be employed in the system, decision making procedures, and everything else system managers may need for issuing warnings in different warning zones. Finally the warning management is composed by: monitoring and warning strategy; communication strategy; emergency plan and, everything connected to the social sphere. Among LEWSs operational worldwide, two categories can be defined as a function of the scale of analysis: "local" and "territorial" systems. The scale of analysis influences several actions and aspects connected to the design and employment of the system, such as: the actors involved, the monitoring systems, type of landslide phenomena addressed and variables to be considered for correlations. The characteristics of LEWSs at local scale are strongly affected by numerous constraints and factors, from time to time different, related to the characteristics of the problem they address. Monitoring measures, variables and correlation laws considered for the design and employment of local LEWSs, strongly depends on the type of landslide to be addressed. On the other hand, territorial LEWSs mainly deals with rainfall-induced landslides characterized by fast slope movement. These systems have become a risk management approach, employed worldwide over areas of relevant extension. Before 2005 only few experiences of LEWSs at a regional scale were carried out, such as in: Hong Kong, China; Zhejiang Province, China; San Francisco Bay, California, USA; Appalachians, USA; Oregon, USA; Rio de Janeiro, Brazil. Since the beginning of the XXI century, increased knowledge on rainfall-landslide correlations and upgraded technologies in weather forecast have promoted the development and improvement of territorial LEWSs around the world.

Toxicity of a glufosinate- and several glyphosate-based herbicides to juvenile amphibians from the Southern High Plains, USA.

PubMed

Dinehart, Simon K; Smith, Loren M; McMurry, Scott T; Anderson, Todd A; Smith, Philip N; Haukos, David A

2009-01-15

Pesticide toxicity is often proposed as a contributing factor to the world-wide decline of amphibian populations. We assessed acute toxicity (48 h) of a glufosinate-based herbicide (Ignite 280 SL) and several glyphosate-based herbicide formulations (Roundup WeatherMAX, Roundup Weed and Grass Killer Super Concentrate, Roundup Weed and Grass Killer Ready-To-Use Plus on two species of amphibians housed on soil or moist paper towels. Survival of juvenile Great Plains toads (Bufo cognatus) and New Mexico spadefoots (Spea multiplicata) was reduced by exposure to Roundup Weed and Grass Killer Ready-To-Use Plus on both substrates. Great Plains toad survival was also reduced by exposure to Roundup Weed and Grass Killer Super Concentrate on paper towels. New Mexico spadefoot and Great Plains toad survival was not affected by exposure to the two agricultural herbicides (Roundup WeatherMAX and Ignite 280 SL) on either substrate, suggesting that these herbicides likely do not pose an immediate risk to these species under field conditions.

Experience with a vectorized general circulation weather model on Star-100

NASA Technical Reports Server (NTRS)

Soll, D. B.; Habra, N. R.; Russell, G. L.

1977-01-01

A version of an atmospheric general circulation model was vectorized to run on a CDC STAR 100. The numerical model was coded and run in two different vector languages, CDC and LRLTRAN. A factor of 10 speed improvement over an IBM 360/95 was realized. Efficient use of the STAR machine required some redesigning of algorithms and logic. This precludes the application of vectorizing compilers on the original scalar code to achieve the same results. Vector languages permit a more natural and efficient formulation for such numerical codes.

The atmospheric boundary layer — advances in knowledge and application

NASA Astrophysics Data System (ADS)

Garratt, J. R.; Hess, G. D.; Physick, W. L.; Bougeault, P.

1996-02-01

We summarise major activities and advances in boundary-layer knowledge in the 25 years since 1970, with emphasis on the application of this knowledge to surface and boundary-layer parametrisation schemes in numerical models of the atmosphere. Progress in three areas is discussed: (i) the mesoscale modelling of selected phenomena; (ii) numerical weather prediction; and (iii) climate simulations. Future trends are identified, including the incorporation into models of advanced cloud schemes and interactive canopy schemes, and the nesting of high resolution boundary-layer schemes in global climate models.

Application of TRMM PR and TMI Measurements to Assess Cloud Microphysical Schemes in the MM5 Model for a Winter Storm

NASA Technical Reports Server (NTRS)

Han, Mei; Braun, Scott A.; Olson, William S.; Persson, P. Ola G.; Bao, Jian-Wen

2009-01-01

Seen by the human eye, precipitation particles are commonly drops of rain, flakes of snow, or lumps of hail that reach the ground. Remote sensors and numerical models usually deal with information about large collections of rain, snow, and hail (or graupel --also called soft hail ) in a volume of air. Therefore, the size and number of the precipitation particles and how particles interact, evolve, and fall within the volume of air need to be represented using physical laws and mathematical tools, which are often implemented as cloud and precipitation microphysical parameterizations in numerical models. To account for the complexity of the precipitation physical processes, scientists have developed various types of such schemes in models. The accuracy of numerical weather forecasting may vary dramatically when different types of these schemes are employed. Therefore, systematic evaluations of cloud and precipitation schemes are of great importance for improvement of weather forecasts. This study is one such endeavor; it pursues quantitative assessment of all the available cloud and precipitation microphysical schemes in a weather model (MM5) through comparison with the observations obtained by National Aeronautics and Space Administration (NASA) s and Japan Aerospace Exploration Agency (JAXA) s Tropical Rainfall Measuring Mission (TRMM) precipitation radar (PR) and microwave imager (TMI). When satellite sensors (like PR or TMI) detect information from precipitation particles, they cannot directly observe the microphysical quantities (e.g., water species phase, density, size, and amount etc.). Instead, they tell how much radiation is absorbed by rain, reflected away from the sensor by snow or graupel, or reflected back to the satellite. On the other hand, the microphysical quantities in the model are usually well represented in microphysical schemes and can be converted to radiative properties that can be directly compared to the corresponding PR and TMI observations. This study employs this method to evaluate the accuracy of the simulated radiative properties by the MM5 model with different microphysical schemes. It is found that the representations of particle density, size, and mass in the different schemes in the MM5 model determine the model s performance when predicting a winter storm over the eastern Pacific Ocean. Schemes lacking moderate density particles (i.e. graupel), with snow flakes that are too large, or with excessive mass of snow or graupel lead to degraded prediction of the radiative properties as observed by the TRMM satellite. This study demonstrates the uniqueness of the combination of both an active microwave sensor (PR) and passive microwave sensor (TMI) onboard TRMM on assessing the accuracy of numerical weather forecasting. It improves our understanding of the physical and radiative properties of different types of precipitation particles and provides suggestions for better representation of cloud and precipitation processes in numerical models. It would, ultimately, contribute to answering questions like "Why did it not rain when the forecast says it would?"

Overview of new GNSS tropospheric products for GNSS-meteorology and their assessment at Geodetic Observatory Pecny (CZ)

NASA Astrophysics Data System (ADS)

Dousa, J.; Vaclavovic, P.; Gyori, G.

2012-12-01

Geodetic Observatory Pecný (GOP) has a long-term experience in the estimation of precise tropospheric parameters from GNSS permanent stations, in particular under the limited timelines of near real time. More than a decade, the GOP zenith total delays (ZTD) contributed to various projects in Europe (COST-716, TOUGH, E-GVAP, E-GVAP II) and the operational ZTD hourly updated product flows via the meteorological observation exchange network - GTS - to the end users worldwide. Currently, the GOP regional ZTD product is operationally assimilated in Météo France and UK MetOffice at least and further exploited in various ways at many other meteorological institutions. New developments at GOP over last three years consist of a) implementation and assessment of the global hourly ZTD product of about 170 stations, b) implementation of routine multi-GNSS (GPS+GLONASS) ZTD European product, and c) implementation of ultra-fast/real-time ZTD product. The GOP global ZTD product has been implemented on request of the meteorological institutions running global numerical weather forecasting models. The global ZTD product was seriously evaluated over ten months (Oct 2009 - Aug 2011) when compared to reprocessed EUREF and IGS ZTDs, radiosondes and ZTDs derived from UK MetOffice's global numerical weather model. After the evaluation (and on special request of UK MetOffice) the product has been switched from testing to operational status within the framework of the EUMETNET EIG GPS Water Vapour Programme (E-GVAP) and officially disseminated via the GTS network. The GOP multi-GNSS ZTD solution has been tested since 2009 shortly after developing GOP ultra-rapid GPS+GLONASS orbits for the International GNSS Service (IGS). A specific bias of mean value 1.5 mm was identified between GPS- and GLONASS-only ZTD at that time, and relation to the IGS05 antenna phase centre offset and variation models (PCO+PCV) identified. Consequently, the implementation of a routine operation has been done after the GPS week 1632 together with adopting IGS08 PCO+PCVs, which eliminated the bias and demonstrated an overall general better consistence between GPS- and GLONASS-only ZTD estimates. The multi-GNSS ZTD product runs in parallel to the GPS-only and is going to replace the current official GPS-only product after more than a year assessment. This multi-GNSS product has assesses a satisfactory quality and robustness of unofficial IGS ultra-rapid GPS+GLONASS orbits necessary for multi-GNSS solution. The GOP ultra-fast and real-time ZTD estimation is being developed with in-house software application using own G-Nut library and Precise Point Positioning technique (in contrast to all other GOP ZTD products based on Bernese GPS software and based on double-difference observations). The IGS Real-time Pilot Project orbit and clock corrections are seriously exploited in these ultra-fast and real-time tropospheric products aimed for nowcasting and severe weather monitoring. Our implementation assesses an optimal balance between timelines and product quality required by these applications.

Decision Making and Risk Evaluation Frameworks for Extreme Space Weather Events

NASA Astrophysics Data System (ADS)

Uritskaya, O.; Robinson, R. M.; Pulkkinen, A. A.

2017-12-01

Extreme Space Weather events (ESWE) are in the spotlight nowadays because they can produce a significant impact not only due to their intensity and broad geographical scope, but also because of the widespread levels and the multiple sectors of the economy that could be involved. In the task of evaluation of the ESWE consequences, the most problematic and vulnerable aspect is the determination and calculation of the probability of statistically infrequent events and the subsequent assessment of the economic risks. In this work, we conduct a detailed analysis of the available frameworks of the general Decision-Making Theory in the presence of uncertainty, in the context of their applicability for the numerical estimation of the risks and losses associated with ESWE. The results of our study demonstrate that, unlike the Multiple-criteria decision analysis or Minimax approach to modeling of the possible scenarios for the ESWE effects, which prevail in the literature, the most suitable concept is the Games Against Nature (GAN). It enables an evaluation of every economically relevant aspect of space weather conditions and obtain more detailed results. Choosing the appropriate methods for solving GAN models, i.e. determining the most optimal strategy with a given level of uncertainty, requires estimating the conditional probabilities of Space Weather events for each outcome of possible scenarios of this natural disaster. Due to the specifics of complex natural and economic systems, with which we are dealing in this case, this problem remains unsolved, mainly because of inevitable loss of information at every stage of the decision-making process. The analysis is illustrated by deregulated electricity markets of the USA and Canada, whose power grid systems are known to be perceptive to ESWE. The GAN model is more appropriate in identifying potential risks in economic systems. The proposed approach, when applied to the existing database of Space Weather observations and numerical simulations, can provide more accurate forecasts of possible losses and allow for a more precise evaluation of the potential risks of the consequences of the ESWE for the vulnerable industries, such as electric power distribution systems, which have been shown to experience some of the most significant losses caused by ESWE.

ICE CONTROL - Towards optimizing wind energy production during icing events

NASA Astrophysics Data System (ADS)

Dorninger, Manfred; Strauss, Lukas; Serafin, Stefano; Beck, Alexander; Wittmann, Christoph; Weidle, Florian; Meier, Florian; Bourgeois, Saskia; Cattin, René; Burchhart, Thomas; Fink, Martin

2017-04-01

Forecasts of wind power production loss caused by icing weather conditions are produced by a chain of physical models. The model chain consists of a numerical weather prediction model, an icing model and a production loss model. Each element of the model chain is affected by significant uncertainty, which can be quantified using targeted observations and a probabilistic forecasting approach. In this contribution, we present preliminary results from the recently launched project ICE CONTROL, an Austrian research initiative on measurements, probabilistic forecasting, and verification of icing on wind turbine blades. ICE CONTROL includes an experimental field phase, consisting of measurement campaigns in a wind park in Rhineland-Palatinate, Germany, in the winters 2016/17 and 2017/18. Instruments deployed during the campaigns consist of a conventional icing detector on the turbine hub and newly devised ice sensors (eologix Sensor System) on the turbine blades, as well as meteorological sensors for wind, temperature, humidity, visibility, and precipitation type and spectra. Liquid water content and spectral characteristics of super-cooled water droplets are measured using a Fog Monitor FM-120. Three cameras document the icing conditions on the instruments and on the blades. Different modelling approaches are used to quantify the components of the model-chain uncertainties. The uncertainty related to the initial conditions of the weather prediction is evaluated using the existing global ensemble prediction system (EPS) of the European Centre for Medium-Range Weather Forecasts (ECMWF). Furthermore, observation system experiments are conducted with the AROME model and its 3D-Var data assimilation to investigate the impact of additional observations (such as Mode-S aircraft data, SCADA data and MSG cloud mask initialization) on the numerical icing forecast. The uncertainty related to model formulation is estimated from multi-physics ensembles based on the Weather Research and Forecasting model (WRF) by perturbing parameters in the physical parameterization schemes. In addition, uncertainties of the icing model and of its adaptations to the rotating turbine blade are addressed. The model forecasts combined with the suite of instruments and their measurements make it possible to conduct a step-wise verification of all the components of the model chain - a novel aspect compared to similar ongoing and completed forecasting projects.

It's the Physics: Organized Complexity in the Arctic/Midlatitude Weather Controversy

NASA Astrophysics Data System (ADS)

Overland, J. E.; Francis, J. A.; Wang, M.

2017-12-01

There is intense scientific and public interest in whether major Arctic changes can and will impact mid-latitude weather. Despite numerous workshops and a growing literature, convergence of understanding is lacking, with major objections about possible large impacts within the scientific community. Yet research on the Arctic as a new potential driver in improving subseasonal forecasting at midlatitudes remains a priority. A recent review laid part of the controversy on shortcomings in experimental design and ill-suited metrics, such as examining the influence of only sea-ice loss rather than overall Arctic temperature amplification, and/or calculating averages over large regions, long time periods, or many ensemble members that would tend to obscure event-like Arctic connections. The present analysis lays the difficulty at a deeper level owing to the inherently complex physics. Jet-stream dynamics and weather linkages on the scale of a week to months has characteristics of an organized complex system, with large-scale processes that operate in patterned, quasi-geostrophic ways but whose component feedbacks are continually changing. Arctic linkages may be state dependent, i.e., relationships may be more robust in one atmospheric wave pattern than another, generating intermittency. The observational network is insufficient to fully initialize such a system and the inherent noise obscures linkage signals, leading to an underdetermined problem; often more than one explanation can fit the data. Further, the problem may be computationally irreducible; the only way to know the result of these interactions is to trace out their path over time. Modeling is a suggested approach, but at present it is unclear whether previous model studies fully resolve anticipated complexity. The jet stream from autumn to early winter is characterized by non-linear interactions among enhanced atmospheric planetary waves, irregular transitions between the zonal and meridional flows, and the maintenance of atmospheric blocks (near stationary large amplitude atmospheric waves). For weather forecast improvement, but not necessarily to elucidate mechanism of linkages, a Numerical Weather Prediction (NWP) approach is appropriate; such is the plan for the upcoming Year of Polar Prediction (YOPP).

The Effects of Various Weather Conditions as a Potential Ischemic Stroke Trigger in Dogs

PubMed Central

Silver, Gena M.

2017-01-01

Stroke is the fifth leading cause of death in the United States, and is the leading cause of serious, long-term disability worldwide. There are at least 795,000 new or recurrent strokes each year, and approximately 85% of all stroke occurrences are ischemic. Unfortunately, companion animals are also at risk for ischemic stroke. Although the exact incidence of ischemic stroke in companion animals is unknown, some studies, and the veterinary information network (VIN), report that approximately 3% of neurological case referrals are due to a stroke. There is a long list of predisposing factors associated with the risk of ischemic stroke in both humans and canines; however, these factors do not explain why a stroke happens at a particular time on a particular day. Our understanding of these potential stroke “triggers” is limited, and the effect of transient environmental exposures may be one such “trigger”. The present study investigated the extent to which the natural occurrence of canine ischemic stroke was related to the weather conditions in the time-period immediately preceding the onset of stroke. The results of the present study demonstrated that the change in weather conditions could be a potential stroke trigger, with the strokes evaluated occurring after periods of rapid, large fluctuations in weather conditions. There are currently no epidemiological data on the seasonal variability of ischemic stroke in dogs, and determining whether canine stroke parallels human stroke would further validate the use of companion dogs as an appropriate naturally occurring model. PMID:29144407

Sensitivity of Earth Wheat Markets to Space Weather: Comparative Analysis based on data from Medieval European Markets

NASA Astrophysics Data System (ADS)

Pustil'Nik, Lev

We consider a problem of the possible influence of unfavorable states of the space weather on agriculture markets through the chain of connections: "space weather"-"earth weather"- "agriculture crops"-"price reaction". We show that new manifestations of "space weather"- "earth weather" relations discovered in the recent time allow revising a wide range of the expected solar-terrestrial connections. In the previous works we proposed possible mechanisms of wheat market reaction on the specific unfavorable states of space weather in the form of price bursts and price asymmetry. We point out that implementation of considered "price reaction scenarios" is possible only for the case of simultaneous realization of several necessary conditions: high sensitivity of local earth weather in the selected region to space weather; the state of "high risk agriculture" in the selected agriculture zone; high sensitivity of agricultural market to a possible deficit of yield. Results of our previous works (I, II), including application of this approach to the Medieval England wheat market (1250-1700) and to the modern USA durum market (1910-1992), showed that connection between wheat price bursts and space weather state in these cases was absolutely real. The aim of the present work is to answer the question why wheat markets in one selected region may be sensitive to a space weather factor, while in other regions wheat markets demonstrate absolutely indifferent reaction on the space weather. For this aim, we consider dependence of sensitivity of wheat markets to space weather as a function of their location in different climatic zones of Europe. We analyze a database of 95 European wheat markets from 14 countries for the 600-year period (1260-1912). We show that the observed sensitivity of wheat markets to space weather effects is controlled, first of all, by a type of predominant climate in different zones of agricultural production. Wheat markets in the Northern and, partly, in Central Europe (England, Holland, Belgium) show high sensitivity to space weather in minimum states of solar activity, when excess of the high energy cosmic ray stimulate additional cloudiness and precipitation. In the same time, wheat markets in the Southern Europe (Spain, Italy) show high sensitivity to space weather state in the opposite (maximum) phase of solar activity when a deficit of cosmic ray entering into the earth atmosphere leads to decrease of cloudiness and to increase of probability of drought weather periods. We demonstrate that the large part of markets in the Central Europe zone show absence of any effects of sensitivity to space weather state and show that this North-South asymmetry is in good accordance with the suggested model of expected wheat market reaction. We discuss possible increasing of sensitivity of wheat markets to space weather effects under conditions of fast and drastic change of modern climate with a shift of numerous agriculture regions to the state of "high risk agriculture zone".

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

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

Oglesby, Robert J; Erickson III, David J

2009-12-01

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

Science in Service to Society - A Review of Applied Science & Decision Support Development Serving Multiple Economic Sectors

NASA Astrophysics Data System (ADS)

Mahoney, W. P., III

2015-12-01

For more than 30 years, the Research Applications Laboratory (RAL) of the National Center for Atmospheric Research (NCAR) has conducted fundamental and applied research focused on developing decision support tools spanning multiple end-user groups representing a variety of economic sectors. Technology transfer is a primary mission of the laboratory where innovation is a key attribute and multidisciplinary research and development are the norm. Application areas include, aviation, surface transportation, wind and solar energy prediction, climate, weather and health, numerical weather prediction, biological and chemical plume dispersion for homeland security, flood prediction and water resource management, soil condition and crop maturity prediction among other application areas. The majority of the developed capabilities have been operationalized by the public, private, and academic sectors. Several commercial companies have been successfully formed around the technologies (e.g., Weather Information Technologies, Inc., Peak Weather Resources, Inc., and Global Weather Corporation) and many existing companies have improved their products by utilizing the RAL-developed weather system advancements (The Weather Channel, WSI, Schneider Electric, Xcel Energy, United Airlines, Vaisala, Panasonic, Idaho Power, etc.). The economic benefit estimates of implementing these technologies have ranged from billions of dollars in avoided commercial aircraft accidents over the last 30 years to 10s of millions of dollars of annual savings by state departments of transportation via more efficient ice and snow maintenance operations. Research and development at RAL is connected to the Broader Impacts Criterion of NSF and its focus on research that results in significant economic or societal impact. This talk will describe our research-to-operations process and discuss several technology transfer examples that have led to commercial opportunities.

Corrosion evaluation of mechanically stabilized earth walls.

DOT National Transportation Integrated Search

2005-09-01

Numerous reinforced walls and slopes have been built over the past four decades in Kentucky, the United States, as well as worldwide. Tensile elements used in constructing low-cost reinforcing walls and slopes consist of metal polymer strips or grids...

A Gridded Climatology of Clouds over Land (1971-1996) and Ocean (1954-2008) from Surface Observations Worldwide (NDP-026E)*

DOE Data Explorer

Hahn, C. J. [University of Arizona; Warren, S. G. [University of Washington

2007-01-01

Surface synoptic weather reports from ships and land stations worldwide were processed to produce a global cloud climatology which includes: total cloud cover, the amount and frequency of occurrence of nine cloud types within three levels of the troposphere, the frequency of occurrence of clear sky and of precipitation, the base heights of low clouds, and the non-overlapped amounts of middle and high clouds. Synoptic weather reports are made every three hours; the cloud information in a report is obtained visually by human observers. The reports used here cover the period 1971-96 for land and 1954-2008 for ocean. This digital archive provides multi-year monthly, seasonal, and annual averages in 5x5-degree grid boxes (or 10x10-degree boxes for some quantities over the ocean). Daytime and nighttime averages, as well as the diurnal average (average of day and night), are given. Nighttime averages were computed using only those reports that met an "illuminance criterion" (i.e., made under adequate moonlight or twilight), thus minimizing the "night-detection bias" and making possible the determination of diurnal cycles and nighttime trends for cloud types. The phase and amplitude of the first harmonic of both the diurnal cycle and the annual cycle are given for the various cloud types. Cloud averages for individual years are also given for the ocean for each of 4 seasons, and for each of the 12 months (daytime-only averages for the months). [Individual years for land are not gridded, but are given for individual stations in a companion data set, CDIAC's NDP-026D).] This analysis used 185 million reports from 5388 weather stations on continents and islands, and 50 million reports from ships; these reports passed a series of quality-control checks. This analysis updates (and in most ways supercedes) the previous cloud climatology constructed by the authors in the 1980s. Many of the long-term averages described here are mapped on the University of Washington, Department of Atmospheric Sciences Web site. The Online Cloud Atlas containing NDP-026E data is available via the University of Washington.

Simulation of all-scale atmospheric dynamics on unstructured meshes

NASA Astrophysics Data System (ADS)

Smolarkiewicz, Piotr K.; Szmelter, Joanna; Xiao, Feng

2016-10-01

The advance of massively parallel computing in the nineteen nineties and beyond encouraged finer grid intervals in numerical weather-prediction models. This has improved resolution of weather systems and enhanced the accuracy of forecasts, while setting the trend for development of unified all-scale atmospheric models. This paper first outlines the historical background to a wide range of numerical methods advanced in the process. Next, the trend is illustrated with a technical review of a versatile nonoscillatory forward-in-time finite-volume (NFTFV) approach, proven effective in simulations of atmospheric flows from small-scale dynamics to global circulations and climate. The outlined approach exploits the synergy of two specific ingredients: the MPDATA methods for the simulation of fluid flows based on the sign-preserving properties of upstream differencing; and the flexible finite-volume median-dual unstructured-mesh discretisation of the spatial differential operators comprising PDEs of atmospheric dynamics. The paper consolidates the concepts leading to a family of generalised nonhydrostatic NFTFV flow solvers that include soundproof PDEs of incompressible Boussinesq, anelastic and pseudo-incompressible systems, common in large-eddy simulation of small- and meso-scale dynamics, as well as all-scale compressible Euler equations. Such a framework naturally extends predictive skills of large-eddy simulation to the global atmosphere, providing a bottom-up alternative to the reverse approach pursued in the weather-prediction models. Theoretical considerations are substantiated by calculations attesting to the versatility and efficacy of the NFTFV approach. Some prospective developments are also discussed.

Ray-traced tropospheric total slant delays for GNSS processing

NASA Astrophysics Data System (ADS)

Hobiger, T.; Ichikawa, R.; Hatanaka, Y.; Yutsudo, T.; Iwashita, C.; Miyahara, B.; Koyama, Y.; Kondo, T.

2007-12-01

Numerical weather models have undergone an improvement of spatial and temporal resolution in the recent years, which made their use for GNSS applications feasible. Ray-tracing through such models permits the computation of total troposphere delays and ray-bending angles. At the National Institute of Information and Communications Technology (NICT), Japan the so-called KAshima RAy-tracing Tools (KARAT) have been developed which allow to obtain troposphere delay corrections in real-time. Together with fine-mesh weather models from the Japanese Meteorological Agency (JMA) huge parts of the East Asian region, including Japan, Korea, Taiwan and East China, can be covered. The Japanese GEONET with its more than 1300 GNSS receivers represent an ideal test-bed for the evaluation of the performance of KARAT. In cooperation with the Geographical Survey Institute (GSI), Japan more than 1.6 billion observations, covering measurements from July 1st until August 31st, 2006, were processed and the corresponding troposphere delays were used to modify the original RINEX files by subtraction of code- and phase delays. These modified observations were processed by a dedicated analysis run of the GEONET operation center, taking advantage of the computer cluster at GSI. First results from this study, together with an in-depth discussion about the assets and drawbacks of the reduction of troposphere total slant delays will be given in this presentation. Additionally an overview about KARAT, the treatment of observational data and the impact of future refined numerical weather models on GNSS analysis will be included in this contribution.

Evaluation of the Impact of AIRS Radiance and Profile Data Assimilation in Partly Cloudy Regions

NASA Technical Reports Server (NTRS)

Zavodsky, Bradley; Srikishen, Jayanthi; Jedlovec, Gary

2013-01-01

Improvements to global and regional numerical weather prediction have been demonstrated through assimilation of data from NASA s Atmospheric Infrared Sounder (AIRS). Current operational data assimilation systems use AIRS radiances, but impact on regional forecasts has been much smaller than for global forecasts. Retrieved profiles from AIRS contain much of the information that is contained in the radiances and may be able to reveal reasons for this reduced impact. Assimilating AIRS retrieved profiles in an identical analysis configuration to the radiances, tracking the quantity and quality of the assimilated data in each technique, and examining analysis increments and forecast impact from each data type can yield clues as to the reasons for the reduced impact. By doing this with regional scale models individual synoptic features (and the impact of AIRS on these features) can be more easily tracked. This project examines the assimilation of hyperspectral sounder data used in operational numerical weather prediction by comparing operational techniques used for AIRS radiances and research techniques used for AIRS retrieved profiles. Parallel versions of a configuration of the Weather Research and Forecasting (WRF) model with Gridpoint Statistical Interpolation (GSI) are run to examine the impact AIRS radiances and retrieved profiles. Statistical evaluation of a long-term series of forecast runs will be compared along with preliminary results of in-depth investigations for select case comparing the analysis increments in partly cloudy regions and short-term forecast impacts.

Evaluation of the Impact of Atmospheric Infrared Sounder (AIRS) Radiance and Profile Data Assimilation in Partly Cloudy Regions

NASA Technical Reports Server (NTRS)

Zavodsky, Bradley; Srikishen, Jayanthi; Jedlovec, Gary

2013-01-01

Improvements to global and regional numerical weather prediction have been demonstrated through assimilation of data from NASA s Atmospheric Infrared Sounder (AIRS). Current operational data assimilation systems use AIRS radiances, but impact on regional forecasts has been much smaller than for global forecasts. Retrieved profiles from AIRS contain much of the information that is contained in the radiances and may be able to reveal reasons for this reduced impact. Assimilating AIRS retrieved profiles in an identical analysis configuration to the radiances, tracking the quantity and quality of the assimilated data in each technique, and examining analysis increments and forecast impact from each data type can yield clues as to the reasons for the reduced impact. By doing this with regional scale models individual synoptic features (and the impact of AIRS on these features) can be more easily tracked. This project examines the assimilation of hyperspectral sounder data used in operational numerical weather prediction by comparing operational techniques used for AIRS radiances and research techniques used for AIRS retrieved profiles. Parallel versions of a configuration of the Weather Research and Forecasting (WRF) model with Gridpoint Statistical Interpolation (GSI) are run to examine the impact AIRS radiances and retrieved profiles. Statistical evaluation of 6 weeks of forecast runs will be compared along with preliminary results of in-depth investigations for select case comparing the analysis increments in partly cloudy regions and short-term forecast impacts.

Simulation and Data Analytics for Mobile Road Weather Sensors

NASA Astrophysics Data System (ADS)

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

2016-12-01

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

Real-Time Kennedy Space Center and Cape Canaveral Air Force Station High-Resolution Model Implementation and Verification

NASA Technical Reports Server (NTRS)

Shafer, Jaclyn; Watson, Leela R.

2015-01-01

NASA's Launch Services Program, Ground Systems Development and Operations, Space Launch System and other programs at Kennedy Space Center (KSC) and Cape Canaveral Air Force Station (CCAFS) use the daily and weekly weather forecasts issued by the 45th Weather Squadron (45 WS) as decision tools for their day-to-day and launch operations on the Eastern Range (ER). Examples include determining if they need to limit activities such as vehicle transport to the launch pad, protect people, structures or exposed launch vehicles given a threat of severe weather, or reschedule other critical operations. The 45 WS uses numerical weather prediction models as a guide for these weather forecasts, particularly the Air Force Weather Agency (AFWA) 1.67 km Weather Research and Forecasting (WRF) model. Considering the 45 WS forecasters' and Launch Weather Officers' (LWO) extensive use of the AFWA model, the 45 WS proposed a task at the September 2013 Applied Meteorology Unit (AMU) Tasking Meeting requesting the AMU verify this model. Due to the lack of archived model data available from AFWA, verification is not yet possible. Instead, the AMU proposed to implement and verify the performance of an ER version of the high-resolution WRF Environmental Modeling System (EMS) model configured by the AMU (Watson 2013) in real time. Implementing a real-time version of the ER WRF-EMS would generate a larger database of model output than in the previous AMU task for determining model performance, and allows the AMU more control over and access to the model output archive. The tasking group agreed to this proposal; therefore the AMU implemented the WRF-EMS model on the second of two NASA AMU modeling clusters. The AMU also calculated verification statistics to determine model performance compared to observational data. Finally, the AMU made the model output available on the AMU Advanced Weather Interactive Processing System II (AWIPS II) servers, which allows the 45 WS and AMU staff to customize the model output display on the AMU and Range Weather Operations (RWO) AWIPS II client computers and conduct real-time subjective analyses.

Climate of the Frank Church-River of No Return Wilderness, central Idaho

Treesearch

Arnold I. Finklin

1988-01-01

Describes the climate of the largest designated wilderness in the conterminous United States. Contains numerous maps, graphs, and tables. Shows annual patterns and 10-day details during the fire season. Includes both average values and frequency distributions. Examines relationship of climatic averages to topography, persistence of weather, and climatic trends.

Smart Climatology System

DTIC Science & Technology

2010-09-24

12 2.1 Downscaling /Reanalysis Data ................................................................................ 12 2.2 Downscaling of...Comparison of Resolutions of Maximum Significant Wave heights for La Niña >= 8 ft >= 6 ft 12 2 Data Production Issues 2.1 Downscaling /Reanalysis...numerical weather prediction systems. The usage of satellite data , for example, is markedly different than the past practice. This played havoc with

National Centers for Environmental Prediction

Science.gov Websites

Modeling Mesoscale Modeling Marine Modeling and Analysis Teams Climate Data Assimilation Ensembles and Post Contacts Change Log Events Calendar Numerical Forecast Systems NCEP Model Analysis and Guidance Page [< Modeling Center NOAA Center for Weather and Climate Prediction (NCWCP) 5830 University Research Court

Forest health in West Virginia: past, present and future

Treesearch

Ray R., Jr. Hicks; Darlene A. Mudrick

1995-01-01

This report chronicles the status of forest health in West Virginia as of 1993. Primary data sources are the Forest Inventory and Analysis reports, West Virginia state forest pest reports, National Oceanographic and Atmospheric Administration weather records and numerous other publications. We attempted to describe primary stressing agents affecting the forest,...

Modeling of the interactions between forest vegetation, disturbances, and sediment yields

Treesearch

Erkan Istanbulluoglu; David G. Tarboton; Robert T. Pack; Charles H. Luce

2004-01-01

The controls of forest vegetation, wildfires, and harvest vegetation disturbances on the frequency and magnitude of sediment delivery from a small watershed (~3.9 km2) in the Idaho batholith are investigated through numerical modeling. The model simulates soil development based on continuous bedrock weathering and the divergence of diffusive...

High performance equipped mirrors for MTG FCI-TA and IRS-FTO

NASA Astrophysics Data System (ADS)

Kazakov, T.; San Juan, J. L.; Serrano, J.; Moreno, J.; González, D.; Rodríguez, G.; López, D.; Vázquez, E.; Aivar, J.; Motos, A.; Rahmouni, Christophe; Imperiali, Stephan; Fappani, Denis

2017-09-01

The Meteosat Third Generation (MTG) Programme is being realised through the well established and successful Cooperation between EUMETSAT and ESA. It will ensure the future continuity of MSG with the capabilities to enhance nowcasting, global and regional numerical weather prediction, climate and atmospheric chemistry monitoring data from Geostationary Orbit.

Use of artificial landscapes to isolate controls on burn probability

Treesearch

Marc-Andre Parisien; Carol Miller; Alan A. Ager; Mark A. Finney

2010-01-01

Techniques for modeling burn probability (BP) combine the stochastic components of fire regimes (ignitions and weather) with sophisticated fire growth algorithms to produce high-resolution spatial estimates of the relative likelihood of burning. Despite the numerous investigations of fire patterns from either observed or simulated sources, the specific influence of...

Dance K-12 in the Vancouver Schools: Innovating, Advocating, Educating

ERIC Educational Resources Information Center

Gilsdorf, Rie Algeo

2004-01-01

A history of the outstanding K-12 dance program in Vancouver, Washington, is provided, including various strategies used to promote its growth from a few pilot elementary schools through middle schools to an arts magnet high school. Numerous changes have been weathered by the professional dance staff, including certification challenges instigated…

Wave Transformation Over Reefs: Evaluation of One-Dimensional Numerical Models

DTIC Science & Technology

2009-01-01

equations on an unstructured grid. Proceedings International Conference on Coastal Engineering ‘06 V1. San Diego, CA, 73-85. Baldock, T. E., P. Holmes , S...equations. Monthly Weather Review 91:99-164. Smith, J. M, A. R. Sherlock , and D. T. Resio. 2001. Steady state spectral wave model user’s manual

Variability of winds and temperature in the Bergen area

NASA Astrophysics Data System (ADS)

Schönbein, Daniel; Ólafsson, Haraldur; Asle Olseth, Jan; Furevik, Birgitte

2017-04-01

In recent years, observations have been made by a dense network of automatic weather stations in the Bergen area in W-Norway (Bergen School of Meteorology). Here, cases are presented that feature large spatial variability in winds and temperature and the ability of a numerical model to reproduce this variability is assessed.

A Decade Revisited and a Step toward the Future: Incremental but Quintessential Progress

ERIC Educational Resources Information Center

Jin, D.-S.; Kim, M. H.; Park, D.

2014-01-01

This study scrutinizes "Asia Pacific Education Review" ("APER") that has been weathered 13 years of journey from its inception. Numerically, 504 peer-reviewed articles have been published so far, and 0.5 of impact factor has been achieved. This article recollects the history of "APER," overhaul the accomplishment and…

Application, evaluation and sensitivity analysis of the coupled WRF-CMAQ system from regional to urban scales

EPA Science Inventory

The Community Multiscale Air Quality (CMAQ) model is a state-of-the-science chemical transport model (CTM) capable of simulating the emission, transport and fate of numerous air pollutants. Similarly, the Weather Research and Forecasting (WRF) model is a state-of-the-science mete...

A Prototype Windflow Modeling System for Tactical Weather Support Operations.

DTIC Science & Technology

1987-05-07

a system of numerical models that covers the mesoscale from horizontal scales of 200 km down to 5 km. Veazey and Tabor 2 1 used the windflow model to...821785 West Conference, Long Beach, Calif. 21. Veazey , D.R., and Tabor, P.A. (1985) Meteorological sensor density on the battlefield, Workshop on

Early warnings of hazardous thunderstorms over Lake Victoria

NASA Astrophysics Data System (ADS)

Thiery, Wim; Gudmundsson, Lukas; Bedka, Kristopher; Semazzi, Fredrick H. M.; Lhermitte, Stef; Willems, Patrick; van Lipzig, Nicole P. M.; Seneviratne, Sonia I.

2017-07-01

Weather extremes have harmful impacts on communities around Lake Victoria in East Africa. Every year, intense nighttime thunderstorms cause numerous boating accidents on the lake, resulting in thousands of deaths among fishermen. Operational storm warning systems are therefore crucial. Here we complement ongoing early warning efforts based on numerical weather prediction, by presenting a new satellite data-driven storm prediction system, the prototype Lake Victoria Intense storm Early Warning System (VIEWS). VIEWS derives predictability from the correlation between afternoon land storm activity and nighttime storm intensity on Lake Victoria, and relies on logistic regression techniques to forecast extreme thunderstorms from satellite observations. Evaluation of the statistical model reveals that predictive power is high and independent of the type of input dataset. We then optimise the configuration and show that false alarms also contain valuable information. Our results suggest that regression-based models that are motivated through process understanding have the potential to reduce the vulnerability of local fishing communities around Lake Victoria. The experimental prediction system is publicly available under the MIT licence at http://github.com/wthiery/VIEWS.

A time-spectral approach to numerical weather prediction

NASA Astrophysics Data System (ADS)

Scheffel, Jan; Lindvall, Kristoffer; Yik, Hiu Fai

2018-05-01

Finite difference methods are traditionally used for modelling the time domain in numerical weather prediction (NWP). Time-spectral solution is an attractive alternative for reasons of accuracy and efficiency and because time step limitations associated with causal CFL-like criteria, typical for explicit finite difference methods, are avoided. In this work, the Lorenz 1984 chaotic equations are solved using the time-spectral algorithm GWRM (Generalized Weighted Residual Method). Comparisons of accuracy and efficiency are carried out for both explicit and implicit time-stepping algorithms. It is found that the efficiency of the GWRM compares well with these methods, in particular at high accuracy. For perturbative scenarios, the GWRM was found to be as much as four times faster than the finite difference methods. A primary reason is that the GWRM time intervals typically are two orders of magnitude larger than those of the finite difference methods. The GWRM has the additional advantage to produce analytical solutions in the form of Chebyshev series expansions. The results are encouraging for pursuing further studies, including spatial dependence, of the relevance of time-spectral methods for NWP modelling.

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

Developing a regional retrospective ensemble precipitation dataset for watershed hydrology modeling, Idaho, USA

NASA Astrophysics Data System (ADS)

Flores, A. N.; Smith, K.; LaPorte, P.

2011-12-01

Applications like flood forecasting, military trafficability assessment, and slope stability analysis necessitate the use of models capable of resolving hydrologic states and fluxes at spatial scales of hillslopes (e.g., 10s to 100s m). These models typically require precipitation forcings at spatial scales of kilometers or better and time intervals of hours. Yet in especially rugged terrain that typifies much of the Western US and throughout much of the developing world, precipitation data at these spatiotemporal resolutions is difficult to come by. Ground-based weather radars have significant problems in high-relief settings and are sparsely located, leaving significant gaps in coverage and high uncertainties. Precipitation gages provide accurate data at points but are very sparsely located and their placement is often not representative, yielding significant coverage gaps in a spatial and physiographic sense. Numerical weather prediction efforts have made precipitation data, including critically important information on precipitation phase, available globally and in near real-time. However, these datasets present watershed modelers with two problems: (1) spatial scales of many of these datasets are tens of kilometers or coarser, (2) numerical weather models used to generate these datasets include a land surface parameterization that in some circumstances can significantly affect precipitation predictions. We report on the development of a regional precipitation dataset for Idaho that leverages: (1) a dataset derived from a numerical weather prediction model, (2) gages within Idaho that report hourly precipitation data, and (3) a long-term precipitation climatology dataset. Hourly precipitation estimates from the Modern Era Retrospective-analysis for Research and Applications (MERRA) are stochastically downscaled using a hybrid orographic and statistical model from their native resolution (1/2 x 2/3 degrees) to a resolution of approximately 1 km. Downscaled precipitation realizations are conditioned on hourly observations from reporting gages and then conditioned again on the Parameter-elevation Regressions on Independent Slopes Model (PRISM) at the monthly timescale to reflect orographic precipitation trends common to watersheds of the Western US. While this methodology potentially introduces cross-pollination of errors due to the re-use of precipitation gage data, it nevertheless achieves an ensemble-based precipitation estimate and appropriate measures of uncertainty at a spatiotemporal resolution appropriate for watershed modeling.

Weather Research and Forecasting Model Wind Sensitivity Study at Edwards Air Force Base, CA

NASA Technical Reports Server (NTRS)

Watson, Leela R.; Bauman, William H., III

2008-01-01

NASA prefers to land the space shuttle at Kennedy Space Center (KSC). When weather conditions violate Flight Rules at KSC, NASA will usually divert the shuttle landing to Edwards Air Force Base (EAFB) in Southern California. But forecasting surface winds at EAFB is a challenge for the Spaceflight Meteorology Group (SMG) forecasters due to the complex terrain that surrounds EAFB, One particular phenomena identified by SMG is that makes it difficult to forecast the EAFB surface winds is called "wind cycling". This occurs when wind speeds and directions oscillate among towers near the EAFB runway leading to a challenging deorbit bum forecast for shuttle landings. The large-scale numerical weather prediction models cannot properly resolve the wind field due to their coarse horizontal resolutions, so a properly tuned high-resolution mesoscale model is needed. The Weather Research and Forecasting (WRF) model meets this requirement. The AMU assessed the different WRF model options to determine which configuration best predicted surface wind speed and direction at EAFB, To do so, the AMU compared the WRF model performance using two hot start initializations with the Advanced Research WRF and Non-hydrostatic Mesoscale Model dynamical cores and compared model performance while varying the physics options.

A Comparison of Perturbed Initial Conditions and Multiphysics Ensembles in a Severe Weather Episode in Spain

NASA Technical Reports Server (NTRS)

Tapiador, Francisco; Tao, Wei-Kuo; Angelis, Carlos F.; Martinez, Miguel A.; Cecilia Marcos; Antonio Rodriguez; Hou, Arthur; Jong Shi, Jain

2012-01-01

Ensembles of numerical model forecasts are of interest to operational early warning forecasters as the spread of the ensemble provides an indication of the uncertainty of the alerts, and the mean value is deemed to outperform the forecasts of the individual models. This paper explores two ensembles on a severe weather episode in Spain, aiming to ascertain the relative usefulness of each one. One ensemble uses sensible choices of physical parameterizations (precipitation microphysics, land surface physics, and cumulus physics) while the other follows a perturbed initial conditions approach. The results show that, depending on the parameterizations, large differences can be expected in terms of storm location, spatial structure of the precipitation field, and rain intensity. It is also found that the spread of the perturbed initial conditions ensemble is smaller than the dispersion due to physical parameterizations. This confirms that in severe weather situations operational forecasts should address moist physics deficiencies to realize the full benefits of the ensemble approach, in addition to optimizing initial conditions. The results also provide insights into differences in simulations arising from ensembles of weather models using several combinations of different physical parameterizations.

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.

Predictability of short-range forecasting: a multimodel approach

NASA Astrophysics Data System (ADS)

García-Moya, Jose-Antonio; Callado, Alfons; Escribà, Pau; Santos, Carlos; Santos-Muñoz, Daniel; Simarro, Juan

2011-05-01

Numerical weather prediction (NWP) models (including mesoscale) have limitations when it comes to dealing with severe weather events because extreme weather is highly unpredictable, even in the short range. A probabilistic forecast based on an ensemble of slightly different model runs may help to address this issue. Among other ensemble techniques, Multimodel ensemble prediction systems (EPSs) are proving to be useful for adding probabilistic value to mesoscale deterministic models. A Multimodel Short Range Ensemble Prediction System (SREPS) focused on forecasting the weather up to 72 h has been developed at the Spanish Meteorological Service (AEMET). The system uses five different limited area models (LAMs), namely HIRLAM (HIRLAM Consortium), HRM (DWD), the UM (UKMO), MM5 (PSU/NCAR) and COSMO (COSMO Consortium). These models run with initial and boundary conditions provided by five different global deterministic models, namely IFS (ECMWF), UM (UKMO), GME (DWD), GFS (NCEP) and CMC (MSC). AEMET-SREPS (AE) validation on the large-scale flow, using ECMWF analysis, shows a consistent and slightly underdispersive system. For surface parameters, the system shows high skill forecasting binary events. 24-h precipitation probabilistic forecasts are verified using an up-scaling grid of observations from European high-resolution precipitation networks, and compared with ECMWF-EPS (EC).

Framework of distributed coupled atmosphere-ocean-wave modeling system

NASA Astrophysics Data System (ADS)

Wen, Yuanqiao; Huang, Liwen; Deng, Jian; Zhang, Jinfeng; Wang, Sisi; Wang, Lijun

2006-05-01

In order to research the interactions between the atmosphere and ocean as well as their important role in the intensive weather systems of coastal areas, and to improve the forecasting ability of the hazardous weather processes of coastal areas, a coupled atmosphere-ocean-wave modeling system has been developed. The agent-based environment framework for linking models allows flexible and dynamic information exchange between models. For the purpose of flexibility, portability and scalability, the framework of the whole system takes a multi-layer architecture that includes a user interface layer, computational layer and service-enabling layer. The numerical experiment presented in this paper demonstrates the performance of the distributed coupled modeling system.

P161 Improved Impact of Atmospheric Infrared Sounder (AIRS) Radiance Assimilation in Numerical Weather Prediction

NASA Technical Reports Server (NTRS)

Zavodsky, Bradley T.; Chou, Shih-Hung; Jedlovec, Gary J.

2012-01-01

For over 6 years, AIRS radiances have been assimilated operationally into National (e.g. Environmental Modeling Center (EMC)) and International (e.g. European Centre for Medium-Range Weather Forecasts (ECMWF)), operational centers; assimilated in the North American Mesoscale (NAM) since 2008. Due partly to data latency and operational constraints, hyperspectral radiance assimilation has had less impact on the Gridpoint Statistical Interpolation (GSI) system used in the NAM and GFS. Objective of this project is to use AIRS retrieved profiles as a proxy for the AIRS radiances in situations where AIRS radiances are unable to be assimilated in the current operational system by evaluating location and magnitude of analysis increments.

Development of a WRF-RTFDDA-based high-resolution hybrid data-assimilation and forecasting system toward to operation in the Middle East

NASA Astrophysics Data System (ADS)

Liu, Y.; Wu, W.; Zhang, Y.; Kucera, P. A.; Liu, Y.; Pan, L.

2012-12-01

Weather forecasting in the Middle East is challenging because of its complicated geographical nature including massive coastal area and heterogeneous land, and regional spare observational network. Strong air-land-sea interactions form multi-scale weather regimes in the area, which require a numerical weather prediction model capable of properly representing multi-scale atmospheric flow with appropriate initial conditions. The WRF-based Real-Time Four Dimensional Data Assimilation (RTFDDA) system is one of advanced multi-scale weather analysis and forecasting facilities developed at the Research Applications Laboratory (RAL) of NCAR. The forecasting system is applied for the Middle East with careful configuration. To overcome the limitation of the very sparsely available conventional observations in the region, we develop a hybrid data assimilation algorithm combining RTFDDA and WRF-3DVAR, which ingests remote sensing data from satellites and radar. This hybrid data assimilation blends Newtonian nudging FDDA and 3DVAR technology to effectively assimilate both conventional observations and remote sensing measurements and provide improved initial conditions for the forecasting system. For brevity, the forecasting system is called RTF3H (RTFDDA-3DVAR Hybrid). In this presentation, we will discuss the hybrid data assimilation algorithm, and its implementation, and the applications for high-impact weather events in the area. Sensitivity studies are conducted to understand the strength and limitations of this hybrid data assimilation algorithm.

Near-Real Time Satellite-Retrieved Cloud and Surface Properties for Weather and Aviation Safety Applications

NASA Technical Reports Server (NTRS)

Minnis, Patrick; Smith, William L., Jr.; Bedka, Kristopher M.; Nguyen, Louis; Palikonda, Rabindra; Hong, Gang; Trepte, Qing Z.; Chee, Thad; Scarino, Benjamin; Spangenberg, Douglas A.;

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.

Near-Real Time Satellite-Retrieved Cloud and Surface Properties for Weather and Aviation Safety Applications

NASA Astrophysics Data System (ADS)

Minnis, P.; Smith, W., Jr.; Bedka, K. M.; Nguyen, L.; Palikonda, R.; Hong, G.; Trepte, Q.; Chee, T.; Scarino, B. R.; Spangenberg, D.; Sun-Mack, S.; Fleeger, C.; Ayers, J. K.; Chang, F. L.; Heck, P. W.

2014-12-01

Cloud properties determined from satellite imager radiances provide a valuable source of information for nowcasting and weather forecasting. In recent years, it has been shown that assimilation of cloud top temperature, optical depth, and total water path can increase the accuracies of weather analyses and forecasts. Aircraft icing conditions can be accurately diagnosed in near-real time (NRT) retrievals of cloud effective particle size, phase, and water path, providing valuable data for pilots. NRT retrievals of surface skin temperature can also be assimilated in numerical weather prediction models to provide more accurate representations of solar heating and longwave cooling at the surface, where convective initiation. These and other applications are being exploited more frequently as the value of NRT cloud data become recognized. At NASA Langley, cloud properties and surface skin temperature are being retrieved in near-real time globally from both geostationary (GEO) and low-earth orbiting (LEO) satellite imagers for weather model assimilation and nowcasting for hazards such as aircraft icing. Cloud data from GEO satellites over North America are disseminated through NCEP, while those data and global LEO and GEO retrievals are disseminated from a Langley website. This paper presents an overview of the various available datasets, provides examples of their application, and discusses the use of the various datasets downstream. Future challenges and areas of improvement are also presented.

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.

NASA Prediction of Worldwide Energy Resource High Resolution Meteorology Data For Sustainable Building Design

NASA Technical Reports Server (NTRS)

Chandler, William S.; Hoell, James M.; Westberg, David; Zhang, Taiping; Stackhouse, Paul W., Jr.

2013-01-01

A primary objective of NASA's Prediction of Worldwide Energy Resource (POWER) project is to adapt and infuse NASA's solar and meteorological data into the energy, agricultural, and architectural industries. Improvements are continuously incorporated when higher resolution and longer-term data inputs become available. Climatological data previously provided via POWER web applications were three-hourly and 1x1 degree latitude/longitude. The NASA Modern Era Retrospective-analysis for Research and Applications (MERRA) data set provides higher resolution data products (hourly and 1/2x1/2 degree) covering the entire globe. Currently POWER solar and meteorological data are available for more than 30 years on hourly (meteorological only), daily, monthly and annual time scales. These data may be useful to several renewable energy sectors: solar and wind power generation, agricultural crop modeling, and sustainable buildings. A recent focus has been working with ASHRAE to assess complementing weather station data with MERRA data. ASHRAE building design parameters being investigated include heating/cooling degree days and climate zones.

A Goddard Multi-Scale Modeling System with Unified Physics

NASA Technical Reports Server (NTRS)

Tao, W.K.; Anderson, D.; Atlas, R.; Chern, J.; Houser, P.; Hou, A.; Lang, S.; Lau, W.; Peters-Lidard, C.; Kakar, R.;

The forgotten successes and sacrifices of Charles Kellaway, director of the Walter and Eliza Hall Institute, 1923-1944.

PubMed

Hobbins, Peter G; Winkel, Kenneth D

Charles Halliley Kellaway (1889-1952) was one of the first Australians to make a full-time career of medical research. He built his scientific reputation on studies of snake venoms and anaphylaxis. Under Kellaway's directorship, the Walter and Eliza Hall Institute gained worldwide acclaim, and he played a critical role in its success between the world wars. His administrative and financial strategies in the era before the National Health and Medical Research Council (NHMRC) helped local medical research weather the Depression and gain a strong foothold by World War II.

OVERVIEW AND EVALUATION OF NEUROBEHAVIORAL EFFECTS OF FLAME RETARDANTS IN LABORATORY ANIMALS.

EPA Science Inventory

Polybrominated diphenyl ether (PBDE) flame retardants are used worldwide and have been detected in numerous environmental, including human, samples. Concern has been raised regarding their potential developmental neurotoxic effects. There is an emerging literature on behavioral...

Near-real-time Estimation and Forecast of Total Precipitable Water in Europe

NASA Astrophysics Data System (ADS)

Bartholy, J.; Kern, A.; Barcza, Z.; Pongracz, R.; Ihasz, I.; Kovacs, R.; Ferencz, C.

2013-12-01

Information about the amount and spatial distribution of atmospheric water vapor (or total precipitable water) is essential for understanding weather and the environment including the greenhouse effect, the climate system with its feedbacks and the hydrological cycle. Numerical weather prediction (NWP) models need accurate estimations of water vapor content to provide realistic forecasts including representation of clouds and precipitation. In the present study we introduce our research activity for the estimation and forecast of atmospheric water vapor in Central Europe using both observations and models. The Eötvös Loránd University (Hungary) operates a polar orbiting satellite receiving station in Budapest since 2002. This station receives Earth observation data from polar orbiting satellites including MODerate resolution Imaging Spectroradiometer (MODIS) Direct Broadcast (DB) data stream from satellites Terra and Aqua. The received DB MODIS data are automatically processed using freely distributed software packages. Using the IMAPP Level2 software total precipitable water is calculated operationally using two different methods. Quality of the TPW estimations is a crucial question for further application of the results, thus validation of the remotely sensed total precipitable water fields is presented using radiosonde data. In a current research project in Hungary we aim to compare different estimations of atmospheric water vapor content. Within the frame of the project we use a NWP model (DBCRAS; Direct Broadcast CIMSS Regional Assimilation System numerical weather prediction software developed by the University of Wisconsin, Madison) to forecast TPW. DBCRAS uses near real time Level2 products from the MODIS data processing chain. From the wide range of the derived Level2 products the MODIS TPW parameter found within the so-called mod07 results (Atmospheric Profiles Product) and the cloud top pressure and cloud effective emissivity parameters from the so-called mod06 results (Cloud Product) are assimilated twice a day (at 00 and 12 UTC) by DBCRAS. DBCRAS creates 72 hours long weather forecasts with 48 km horizontal resolution. DBCRAS is operational at the University since 2009 which means that by now sufficient data is available for the verification of the model. In the present study verification results for the DBCRAS total precipitable water forecasts are presented based on analysis data from the European Centre for Medium-Range Weather Forecasts (ECMWF). Numerical indices are calculated to quantify the performance of DBCRAS. During a limited time period DBCRAS was also ran without assimilating MODIS products which means that there is possibility to quantify the effect of assimilating MODIS physical products on the quality of the forecasts. For this limited time period verification indices are compared to decide whether MODIS data improves forecast quality or not.

Emulation for probabilistic weather forecasting

NASA Astrophysics Data System (ADS)

Cornford, Dan; Barillec, Remi

2010-05-01

Numerical weather prediction models are typically very expensive to run due to their complexity and resolution. Characterising the sensitivity of the model to its initial condition and/or to its parameters requires numerous runs of the model, which is impractical for all but the simplest models. To produce probabilistic forecasts requires knowledge of the distribution of the model outputs, given the distribution over the inputs, where the inputs include the initial conditions, boundary conditions and model parameters. Such uncertainty analysis for complex weather prediction models seems a long way off, given current computing power, with ensembles providing only a partial answer. One possible way forward that we develop in this work is the use of statistical emulators. Emulators provide an efficient statistical approximation to the model (or simulator) while quantifying the uncertainty introduced. In the emulator framework, a Gaussian process is fitted to the simulator response as a function of the simulator inputs using some training data. The emulator is essentially an interpolator of the simulator output and the response in unobserved areas is dictated by the choice of covariance structure and parameters in the Gaussian process. Suitable parameters are inferred from the data in a maximum likelihood, or Bayesian framework. Once trained, the emulator allows operations such as sensitivity analysis or uncertainty analysis to be performed at a much lower computational cost. The efficiency of emulators can be further improved by exploiting the redundancy in the simulator output through appropriate dimension reduction techniques. We demonstrate this using both Principal Component Analysis on the model output and a new reduced-rank emulator in which an optimal linear projection operator is estimated jointly with other parameters, in the context of simple low order models, such as the Lorenz 40D system. We present the application of emulators to probabilistic weather forecasting, where the construction of the emulator training set replaces the traditional ensemble model runs. Thus the actual forecast distributions are computed using the emulator conditioned on the ‘ensemble runs' which are chosen to explore the plausible input space using relatively crude experimental design methods. One benefit here is that the ensemble does not need to be a sample from the true distribution of the input space, rather it should cover that input space in some sense. The probabilistic forecasts are computed using Monte Carlo methods sampling from the input distribution and using the emulator to produce the output distribution. Finally we discuss the limitations of this approach and briefly mention how we might use similar methods to learn the model error within a framework that incorporates a data assimilation like aspect, using emulators and learning complex model error representations. We suggest future directions for research in the area that will be necessary to apply the method to more realistic numerical weather prediction models.

Cholera - management and prevention.

PubMed

Davies, Hannah G; Bowman, Conor; Luby, Stephen P

2017-06-01

Cholera is an acute secretory diarrhoeal infection caused by the bacterium Vibrio cholerae. It is likely to have originated in the Indian sub-continent; however, it spread to cause six worldwide pandemics between 1817-1923. The ongoing seventh worldwide pandemic of cholera began in 1961. The intensity, duration and severity of cholera epidemics have been increasing, signaling the need for more effective control and prevention measures. The response to the cholera pandemics of the 19th century led to the development of safe and effective sanitation and water systems which have effectively removed the risk of cholera in many settings. However, such systems are not in place to protect billions of people worldwide. Although some progress has been made in expanding access to water in recent years, achieving optimal infrastructure will, in the most optimistic scenario, take decades. Climate change, extreme weather events and rapid urbanisation suggests that alternatives to the current paradigm of providing large centralised water and sanitation systems should be considered, including smaller decentralised systems. The aim of this review paper is to provide an overview of current knowledge regarding management of cholera with a focus on prevention measures including vaccination and water and sanitation interventions. © 2017 The British Infection Association. Published by 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.

Effects of Climate on Co-evolution of Weathering Profiles and Hillscapes

NASA Astrophysics Data System (ADS)

Anderson, R. S.; Rajaram, H.; Anderson, S. P.

2017-12-01

Considerable debate revolves around the relative importance of rock type, tectonics, and climate in creating the architecture of the critical zone. It has recently been proposed that differences in the depths and patterns of weathering between landscapes in Colorado's Front Range and South Carolina's piedmont can be attributed to the state of stress in the rock imposed by the magnitude and orientation the regional stresses with respect to the ridgelines (St. Claire et al., 2016). We argue for the importance of the climate, and in particular, in temperate regions, the amount of recharge. We employ numerical models of hillslope evolution between bounding erosional channels, in which the degree of rock weathering governs the rate of transformation of rock to soil. As the water table drapes between the stream channels, fresh rock is brought into the weathering zone at a rate governed by the rate of incision of the channels. We track the chemical weathering of rock, represented by alteration of feldspar to clays, which in turn requires calculation of the concentration of reactive species in the water along hydrologic flow paths. We present results from analytic solutions to the flow field in which travel times can be efficiently assessed. Below the water table, flow paths are hyperbolic, taking on considerable lateral components as they veer toward the bounding channels that serve as drains to the hillslope. We find that if water is far from equilibrium with respect to weatherable minerals at the water table, as occurs in wet, slowly-eroding landscapes, deep weathering can occur well below the water table to levels approximating the base of the bounding channels. In dry climates, on the other hand, the weathering zone is limited to a shallow surface - parallel layer. These models capture the essence of the observed differences in depth to fresh rock in both wet and dry climates without appeal to the state of stress in the rock.

Planetary Space Weather Services for the Europlanet 2020 Research Infrastructure

NASA Astrophysics Data System (ADS)

André, Nicolas; Grande, Manuel

2016-04-01

Under Horizon 2020, the Europlanet 2020 Research Infrastructure (EPN2020-RI) will include an entirely new Virtual Access Service, WP5 VA1 "Planetary Space Weather Services" (PSWS) that will extend the concepts of space weather and space situational awareness to other planets in our Solar System and in particular to spacecraft that voyage through it. VA1 will make five entirely new 'toolkits' accessible to the research community and to industrial partners planning for space missions: a general planetary space weather toolkit, as well as three toolkits dedicated to the following key planetary environments: Mars (in support ExoMars), comets (building on the expected success of the ESA Rosetta mission), and outer planets (in preparation for the ESA JUICE mission to be launched in 2022). This will give the European planetary science community new methods, interfaces, functionalities and/or plugins dedicated to planetary space weather in the tools and models available within the partner institutes. It will also create a novel event-diary toolkit aiming at predicting and detecting planetary events like meteor showers and impacts. A variety of tools (in the form of web applications, standalone software, or numerical models in various degrees of implementation) are available for tracing propagation of planetary and/or solar events through the Solar System and modelling the response of the planetary environment (surfaces, atmospheres, ionospheres, and magnetospheres) to those events. But these tools were not originally designed for planetary event prediction and space weather applications. So WP10 JRA4 "Planetary Space Weather Services" (PSWS) will provide the additional research and tailoring required to apply them for these purposes. The overall objectives of this Joint Research Aactivities will be to review, test, improve and adapt methods and tools available within the partner institutes in order to make prototype planetary event and space weather services operational in Europe at the end of the programme. Europlanet 2020 RI has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No 654208.

Climate change and mountain-front morphology: Estimating Late Glacial to Holocene erosion rates from the shape of fault-bounded hillslopes

NASA Astrophysics Data System (ADS)

Tucker, G. E.; McCoy, S. W.; Whittaker, A. C.; Roberts, G.; Lancaster, S. T.; Phillips, R. J.

2011-12-01

The existence of well-preserved Holocene bedrock fault scarps along active normal faults in the Mediterranean region and elsewhere suggests a dramatic reduction in rates of rock weathering and erosion that correlates with the transition from glacial to interglacial climate. We test and quantify this interpretation using a case study in the Italian Central Apennines. Holocene rates are derived from measurements of weathering-pit depth along the Magnola scarp, where previous cosmogenic 36Cl analyses constrain exposure history. To estimate the average hillslope erosion rate over ˜105 years, we introduce a simple geometric model of normal-fault footwall slope evolution. The model predicts that the gradient of a weathering-limited footwall hillslope is set by fault dip angle and by the ratio of slip rate to erosion rate; if either slip or erosion rate is known, the other can be derived. Applying this model to the Magnola fault yields an estimated average weathering rate on the order of 0.2-0.4 mm/yr, more than 10x higher than either the Holocene scarp weathering rate or modern regional limestone weathering rates. A numerical model of footwall growth and erosion, in which erosion rate tracks the oxygen-isotope curve, reproduces the main features of hillslope and scarp morphology and suggests that the hillslope erosion rate has varied by about a factor of 30 over the past one to two glacial cycles. We conclude that preservation of carbonate fault scarps reflects strong climatic control on rock breakdown by frost cracking.

Improved Weather and Power Forecasts for Energy Operations - the German Research Project EWeLiNE

NASA Astrophysics Data System (ADS)

Lundgren, Kristina; Siefert, Malte; Hagedorn, Renate; Majewski, Detlev

2014-05-01

The German energy system is going through a fundamental change. Based on the energy plans of the German federal government, the share of electrical power production from renewables should increase to 35% by 2020. This means that, in the near future at certain times renewable energies will provide a major part of Germany's power production. Operating a power supply system with a large share of weather-dependent power sources in a secure way requires improved power forecasts. One of the most promising strategies to improve the existing wind power and PV power forecasts is to optimize the underlying weather forecasts and to enhance the collaboration between the meteorology and energy sectors. Deutscher Wetterdienst addresses these challenges in collaboration with Fraunhofer IWES within the research project EWeLiNE. The overarching goal of the project is to improve the wind and PV power forecasts by combining improved power forecast models and optimized weather forecasts. During the project, the numerical weather prediction models COSMO-DE and COSMO-DE-EPS (Ensemble Prediction System) by Deutscher Wetterdienst will be generally optimized towards improved wind power and PV forecasts. For instance, it will be investigated whether the assimilation of new types of data, e.g. power production data, can lead to improved weather forecasts. With regard to the probabilistic forecasts, the focus is on the generation of ensembles and ensemble calibration. One important aspect of the project is to integrate the probabilistic information into decision making processes by developing user-specified products. In this paper we give an overview of the project and present first results.

Geostationary Communications Satellites as Sensors for the Space Weather Environment: Telemetry Event Identification Algorithms

NASA Astrophysics Data System (ADS)

Carlton, A.; Cahoy, K.

2015-12-01

Reliability of geostationary communication satellites (GEO ComSats) is critical to many industries worldwide. The space radiation environment poses a significant threat and manufacturers and operators expend considerable effort to maintain reliability for users. Knowledge of the space radiation environment at the orbital location of a satellite is of critical importance for diagnosing and resolving issues resulting from space weather, for optimizing cost and reliability, and for space situational awareness. For decades, operators and manufacturers have collected large amounts of telemetry from geostationary (GEO) communications satellites to monitor system health and performance, yet this data is rarely mined for scientific purposes. The goal of this work is to acquire and analyze archived data from commercial operators using new algorithms that can detect when a space weather (or non-space weather) event of interest has occurred or is in progress. We have developed algorithms, collectively called SEER (System Event Evaluation Routine), to statistically analyze power amplifier current and temperature telemetry by identifying deviations from nominal operations or other events and trends of interest. This paper focuses on our work in progress, which currently includes methods for detection of jumps ("spikes", outliers) and step changes (changes in the local mean) in the telemetry. We then examine available space weather data from the NOAA GOES and the NOAA-computed Kp index and sunspot numbers to see what role, if any, it might have played. By combining the results of the algorithm for many components, the spacecraft can be used as a "sensor" for the space radiation environment. Similar events occurring at one time across many component telemetry streams may be indicative of a space radiation event or system-wide health and safety concern. Using SEER on representative datasets of telemetry from Inmarsat and Intelsat, we find events that occur across all or many of telemetry files at certain dates. We compare these system-wide events to known space weather storms, such as the 2003 Halloween storms, and to spacecraft operational events, such as maneuvers. We also present future applications and expansions of SEER for robust space environment sensing and system health and safety monitoring.

Wind laws for shockless initialization. [numerical forecasting model

NASA Technical Reports Server (NTRS)

Ghil, M.; Shkoller, B.

1976-01-01

A system of diagnostic equations for the velocity field, or wind laws, was derived for each of a number of models of large-scale atmospheric flow. The derivation in each case is mathematically exact and does not involve any physical assumptions not already present in the prognostic equations, such as nondivergence or vanishing of derivatives of the divergence. Therefore, initial states computed by solving these diagnostic equations should be compatible with the type of motion described by the prognostic equations of the model and should not generate initialization shocks when inserted into the model. Numerical solutions of the diagnostic system corresponding to a barotropic model are exhibited. Some problems concerning the possibility of implementing such a system in operational numerical weather prediction are discussed.

A deep belief network approach using VDRAS data for nowcasting

NASA Astrophysics Data System (ADS)

Han, Lei; Dai, Jie; Zhang, Wei; Zhang, Changjiang; Feng, Hanlei

2018-04-01

Nowcasting or very short-term forecasting convective storms is still a challenging problem due to the high nonlinearity and insufficient observation of convective weather. As the understanding of the physical mechanism of convective weather is also insufficient, the numerical weather model cannot predict convective storms well. Machine learning approaches provide a potential way to nowcast convective storms using various meteorological data. In this study, a deep belief network (DBN) is proposed to nowcast convective storms using the real-time re-analysis meteorological data. The nowcasting problem is formulated as a classification problem. The 3D meteorological variables are fed directly to the DBN with dimension of input layer 6*6*80. Three hidden layers are used in the DBN and the dimension of output layer is two. A box-moving method is presented to provide the input features containing the temporal and spatial information. The results show that the DNB can generate reasonable prediction results of the movement and growth of convective storms.

Development and Implementation of Dynamic Scripts to Execute Cycled GSI/WRF Forecasts

NASA Technical Reports Server (NTRS)

Zavodsky, Bradley; Srikishen, Jayanthi; Berndt, Emily; Li, Xuanli; Watson, Leela

2014-01-01

The Weather Research and Forecasting (WRF) numerical weather prediction (NWP) model and Gridpoint Statistical Interpolation (GSI) data assimilation (DA) are the operational systems that make up the North American Mesoscale (NAM) model and the NAM Data Assimilation System (NDAS) analysis used by National Weather Service forecasters. The Developmental Testbed Center (DTC) manages and distributes the code for the WRF and GSI, but it is up to individual researchers to link the systems together and write scripts to run the systems, which can take considerable time for those not familiar with the code. The objective of this project is to develop and disseminate a set of dynamic scripts that mimic the unique cycling configuration of the operational NAM to enable researchers to develop new modeling and data assimilation techniques that can be easily transferred to operations. The current version of the SPoRT GSI/WRF Scripts (v3.0.1) is compatible with WRF v3.3 and GSI v3.0.

Scatterometer capabilities in remotely sensing geophysical parameters over the ocean: The status and the possibilities

NASA Technical Reports Server (NTRS)

Brown, R. A.

1984-01-01

Extensive comparison between surface measurements and satellite Scatt signal and predicted winds show successful wind and weather analysis comparable with conventional weather service analyses. However, in regions often of the most interest, e.g., fronts and local storms, inadequacies in the latter fields leaves an inability to establish the satellite sensor capabilities. Thus, comparisons must be made between wind detecting measurements and other satellite measurements of clouds, moisture, waves or any other parameter which responds to sharp gradients in the wind. At least for the windfields and the derived surface pressure field analysis, occasional surface measurements are required to anchor and monitor the satellite analyses. Their averaging times must be made compatible with the satellite sensor measurement. Careful attention must be paid to the complex fields which contain many scales of turbulence and coherent structures affecting the averaging process. The satellite microwave system is capable of replacing the conventional point observation/numerical analysis for the ocean weather.