Assessment of Fire Occurrence and Future Fire Potential in Arctic Alaska

NASA Astrophysics Data System (ADS)

French, N. H. F.; Jenkins, L. K.; Loboda, T. V.; Bourgeau-Chavez, L. L.; Whitley, M. A.

2014-12-01

An analysis of the occurrence of fire in Alaskan tundra was completed using the relatively complete historical record of fire for the region from 1950 to 2013. Spatial fire data for Alaskan tundra regions were obtained from the Alaska Large Fire Database for the region defined from vegetation and ecoregion maps. A detailed presentation of fire records available for assessing the fire regime of the tundra regions of Alaska as well as results evaluating fire size, seasonality, and general geographic and temporal trends is included. Assessment of future fire potential was determined for three future climate scenarios at four locations across the Alaskan tundra using the Canadian Forest Fire Weather Index (FWI). Canadian Earth System Model (CanESM2) weather variables were used for historical (1850-2005) and future (2006-2100) time periods. The database includes 908 fire points and 463 fire polygons within the 482,931 km2 of Alaskan tundra. Based on the polygon database 25,656 km2 (6,340,000 acres) has burned across the six tundra ecoregions since 1950. Approximately 87% of tundra fires start in June and July across all ecoregions. Combining information from the polygon and points data records, the estimated average fire size for fire in the Alaskan Arctic region is 28.1 km2 (7,070 acres), which is much smaller than in the adjacent boreal forest region, averaging 203 km2 for high fire years. The largest fire in the database is the Imuruk Basin Fire which burned 1,680 km2 in 1954 in the Seward Peninsula region (Table 1). Assessment of future fire potential shows that, in comparison with the historical fire record, fire occurrence in Alaskan tundra is expected to increase under all three climate scenarios. Occurrences of high fire weather danger (>10 FWI) are projected to increase in frequency and magnitude in all regions modeled. The changes in fire weather conditions are expected to vary from one region to another in seasonal occurrence as well as severity and frequency of high fire weather danger. While the Alaska Large Fire Database represents the best data available for the Alaskan Arctic, and is superior to many other regions around the world, particularly Arctic regions, these fire records need to be used with some caution due to the mixed origin and minimal validation of the data; this is reviewed in the presentation.

Complete Decoding and Reporting of Aviation Routine Weather Reports (METARs)

NASA Technical Reports Server (NTRS)

Lui, Man-Cheung Max

2014-01-01

Aviation Routine Weather Report (METAR) provides surface weather information at and around observation stations, including airport terminals. These weather observations are used by pilots for flight planning and by air traffic service providers for managing departure and arrival flights. The METARs are also an important source of weather data for Air Traffic Management (ATM) analysts and researchers at NASA and elsewhere. These researchers use METAR to correlate severe weather events with local or national air traffic actions that restrict air traffic, as one example. A METAR is made up of multiple groups of coded text, each with a specific standard coding format. These groups of coded text are located in two sections of a report: Body and Remarks. The coded text groups in a U.S. METAR are intended to follow the coding standards set by National Oceanic and Atmospheric Administration (NOAA). However, manual data entry and edits made by a human report observer may result in coded text elements that do not follow the standards, especially in the Remarks section. And contrary to the standards, some significant weather observations are noted only in the Remarks section and not in the Body section of the reports. While human readers can infer the intended meaning of non-standard coding of weather conditions, doing so with a computer program is far more challenging. However such programmatic pre-processing is necessary to enable efficient and faster database query when researchers need to perform any significant historical weather analysis. Therefore, to support such analysis, a computer algorithm was developed to identify groups of coded text anywhere in a report and to perform subsequent decoding in software. The algorithm considers common deviations from the standards and data entry mistakes made by observers. The implemented software code was tested to decode 12 million reports and the decoding process was able to completely interpret 99.93 of the reports. This document presents the deviations from the standards and the decoding algorithm. Storing all decoded data in a database allows users to quickly query a large amount of data and to perform data mining on the data. Users can specify complex query criteria not only on date or airport but also on weather condition. This document also describes the design of a database schema for storing the decoded data, and a Data Warehouse web application that allows users to perform reporting and analysis on the decoded data. Finally, this document presents a case study correlating dust storms reported in METARs from the Phoenix International airport with Ground Stops issued by Air Route Traffic Control Centers (ATCSCC). Blowing widespread dust is one of the weather conditions when dust storm occurs. By querying the database, 294 METARs were found to report blowing widespread dust at the Phoenix airport and 41 of them reported such condition only in the Remarks section of the reports. When METAR is a data source for an ATM research, it is important to include weather conditions not only from the Body section but also from the Remarks section of METARs.

Progress on Updating the 1961-1990 National Solar Radiation Database

NASA Technical Reports Server (NTRS)

Renne, D.; Wilcox, S.; Marion, B.; George, R.; Myers, D.

2003-01-01

The 1961-1990 National Solar Radiation Data Base (NSRDB) provides a 30-year climate summary and solar characterization of 239 locations throughout the United States. Over the past several years, the National Renewable Energy Laboratory (NREL) has received numerous inquiries from a range of constituents as to whether an update of the database to include the 1990s will be developed. However, there are formidable challenges to creating an update of the serially complete station-specific database for the 1971-2000 period. During the 1990s, the National Weather Service changed its observational procedures from a human-based to an automated system, resulting in the loss of important input variables to the model used to complete the 1961-1990 NSRDB. As a result, alternative techniques are required for an update that covers the 1990s. This paper examines several alternative approaches for creating this update and describes preliminary NREL plans for implementing the update.

Genetically optimizing weather predictions

NASA Astrophysics Data System (ADS)

Potter, S. B.; Staats, Kai; Romero-Colmenero, Encarni

2016-07-01

humidity, air pressure, wind speed and wind direction) into a database. Built upon this database, we have developed a remarkably simple approach to derive a functional weather predictor. The aim is provide up to the minute local weather predictions in order to e.g. prepare dome environment conditions ready for night time operations or plan, prioritize and update weather dependent observing queues. In order to predict the weather for the next 24 hours, we take the current live weather readings and search the entire archive for similar conditions. Predictions are made against an averaged, subsequent 24 hours of the closest matches for the current readings. We use an Evolutionary Algorithm to optimize our formula through weighted parameters. The accuracy of the predictor is routinely tested and tuned against the full, updated archive to account for seasonal trends and total, climate shifts. The live (updated every 5 minutes) SALT weather predictor can be viewed here: http://www.saao.ac.za/ sbp/suthweather_predict.html

Changes in fire weather distributions: effects on predicted fire behavior

Treesearch

Lucy A. Salazar; Larry S. Bradshaw

1984-01-01

Data that represent average worst fire weather for a particular area are used to index daily fire danger; however, they do not account for different locations or diurnal weather changes that significantly affect fire behavior potential. To study the effects that selected changes in weather databases have on computed fire behavior parameters, weather data for the...

Impact of derived global weather data on simulated crop yields

PubMed Central

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

2013-01-01

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

Impact of derived global weather data on simulated crop yields.

PubMed

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

2013-12-01

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

Space Weather Studies Using Ground-based Experimental Complex in Kazakhstan

NASA Astrophysics Data System (ADS)

Kryakunova, O.; Yakovets, A.; Monstein, C.; Nikolayevskiy, N.; Zhumabayev, B.; Gordienko, G.; Andreyev, A.; Malimbayev, A.; Levin, Yu.; Salikhov, N.; Sokolova, O.; Tsepakina, I.

2015-12-01

Kazakhstan ground-based experimental complex for space weather study is situated near Almaty. Results of space environment monitoring are accessible via Internet on the web-site of the Institute of Ionosphere (http://www.ionos.kz/?q=en/node/21) in real time. There is a complex database with hourly data of cosmic ray intensity, geomagnetic field intensity, and solar radio flux at 10.7 cm and 27.8 cm wavelengths. Several studies using those data are reported. They are an estimation of speed of a coronal mass ejection, a study of large scale traveling distrubances, an analysis of geomagnetically induced currents using the geomagnetic field data, and a solar energetic proton event on 27 January 2012.

LIGHT NONAQUEOUS-PHASE LIQUID HYDROCARBON WEATHERING AT SOME JP-4 FUEL RELEASE SITES

EPA Science Inventory

A fuel weathering study was conducted for database entries to estimate natural light, nonaqueousphase
liquid weathering and source-term reduction rates for use in natural attenuation models. A range of BTEX
weathering rates from mobile LNAPL plumes at eight field sites with...

Monitoring Wildlife Interactions with Their Environment: An Interdisciplinary Approach

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

Charles-Smith, Lauren E.; Domnguez, Ignacio X.; Fornaro, Robert J.

In a rapidly changing world, wildlife ecologists strive to correctly model and predict complex relationships between animals and their environment, which facilitates management decisions impacting public policy to conserve and protect delicate ecosystems. Recent advances in monitoring systems span scientific domains, including animal and weather monitoring devices and landscape classification mapping techniques. The current challenge is how to combine and use detailed output from various sources to address questions spanning multiple disciplines. WolfScout wildlife and weather tracking system is a software tool capable of filling this niche. WolfScout automates integration of the latest technological advances in wildlife GPS collars, weathermore » stations, drought conditions, and severe weather reports, and animal demographic information. The WolfScout database stores a variety of classified landscape maps including natural and manmade features. Additionally, WolfScout’s spatial database management system allows users to calculate distances between animals’ location and landscape characteristics, which are linked to the best approximation of environmental conditions at the animal’s location during the interaction. Through a secure website, data are exported in formats compatible with multiple software programs including R and ArcGIS. The WolfScout design promotes interoperability in data, between researchers, and software applications while standardizing analyses of animal interactions with their environment.« less

Comparison of Online Agricultural Information Services.

ERIC Educational Resources Information Center

Reneau, Fred; Patterson, Richard

1984-01-01

Outlines major online agricultural information services--agricultural databases, databases with agricultural services, educational databases in agriculture--noting services provided, access to the database, and costs. Benefits of online agricultural database sources (availability of agricultural marketing, weather, commodity prices, management…

Evaluation of thunderstorm indices from ECMWF analyses, lightning data and severe storm reports

NASA Astrophysics Data System (ADS)

Kaltenböck, Rudolf; Diendorfer, Gerhard; Dotzek, Nikolai

This study describes the environmental atmospheric characteristics in the vicinity of different types of severe convective storms in Europe during the warm seasons in 2006 and 2007. 3406 severe weather events from the European Severe Weather Database ESWD were investigated to get information about different types of severe local storms, such as significant or weak tornadoes, large hail, damaging winds, and heavy precipitation. These data were combined with EUCLID (European Cooperation for Lightning Detection) lightning data to distinguish and classify thunderstorm activity on a European scale into seven categories: none, weak and 5 types of severe thunderstorms. Sounding parameters in close proximity to reported events were derived from daily high-resolution T799 ECMWF (European Centre for Medium-range Weather Forecasts) analyses. We found from the sounding-derived parameters in Europe: 1) Instability indices and CAPE have considerable skill to predict the occurrence of thunderstorms and the probability of severe events. 2) Low level moisture can be used as a predictor to distinguish between significant tornadoes or non-severe convection. 3) Most of the events associated with wind gusts during strong synoptic flow situations reveal the downward transport of momentum as a very important factor. 4) While deep-layer shear discriminates well between severe and non-severe events, the storm-relative helicity in the 0-1 km and especially in the 0-3 km layer adjacent to the ground has more skill in distinguishing between environments favouring significant tornadoes and wind gusts versus other severe events. Additionally, composite parameters that combine measurements of buoyancy, vertical shear and low level moisture have been tested to discriminate between severe events.

Introducing GFWED: The Global Fire Weather Database

NASA Technical Reports Server (NTRS)

Field, R. D.; Spessa, A. C.; Aziz, N. A.; Camia, A.; Cantin, A.; Carr, R.; de Groot, W. J.; Dowdy, A. J.; Flannigan, M. D.; Manomaiphiboon, K.;

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.

Remote collection and analysis of witness reports on flash floods

NASA Astrophysics Data System (ADS)

Gourley, Jonathan; Erlingis, Jessica; Smith, Travis; Ortega, Kiel; Hong, Yang

2010-05-01

Typically, flash floods are studied ex post facto in response to a major impact event. A complement to field investigations is developing a detailed database of flash flood events, including minor events and null reports (i.e., where heavy rain occurred but there was no flash flooding), based on public survey questions conducted in near-real time. The Severe Hazards Analysis and Verification Experiment (SHAVE) has been in operation at the National Severe Storms Laboratory (NSSL) in Norman, OK, USA during the summers since 2006. The experiment employs undergraduate students to analyse real-time products from weather radars, target specific regions within the conterminous US, and poll public residences and businesses regarding the occurrence and severity of hail, wind, tornadoes, and now flash floods. In addition to providing a rich learning experience for students, SHAVE has been successful in creating high-resolution datasets of severe hazards used for algorithm and model verification. This talk describes the criteria used to initiate the flash flood survey, the specific questions asked and information entered to the database, and then provides an analysis of results for flash flood data collected during the summer of 2008. It is envisioned that specific details provided by the SHAVE flash flood observation database will complement databases collected by operational agencies and thus lead to better tools to predict the likelihood of flash floods and ultimately reduce their impacts on society.

A Quality-Control-Oriented Database for a Mesoscale Meteorological Observation Network

NASA Astrophysics Data System (ADS)

Lussana, C.; Ranci, M.; Uboldi, F.

2012-04-01

In the operational context of a local weather service, data accessibility and quality related issues must be managed by taking into account a wide set of user needs. This work describes the structure and the operational choices made for the operational implementation of a database system storing data from highly automated observing stations, metadata and information on data quality. Lombardy's environmental protection agency, ARPA Lombardia, manages a highly automated mesoscale meteorological network. A Quality Assurance System (QAS) ensures that reliable observational information is collected and disseminated to the users. The weather unit in ARPA Lombardia, at the same time an important QAS component and an intensive data user, has developed a database specifically aimed to: 1) providing quick access to data for operational activities and 2) ensuring data quality for real-time applications, by means of an Automatic Data Quality Control (ADQC) procedure. Quantities stored in the archive include hourly aggregated observations of: precipitation amount, temperature, wind, relative humidity, pressure, global and net solar radiation. The ADQC performs several independent tests on raw data and compares their results in a decision-making procedure. An important ADQC component is the Spatial Consistency Test based on Optimal Interpolation. Interpolated and Cross-Validation analysis values are also stored in the database, providing further information to human operators and useful estimates in case of missing data. The technical solution adopted is based on a LAMP (Linux, Apache, MySQL and Php) system, constituting an open source environment suitable for both development and operational practice. The ADQC procedure itself is performed by R scripts directly interacting with the MySQL database. Users and network managers can access the database by using a set of web-based Php applications.

Development of a Global Fire Weather Database

NASA Technical Reports Server (NTRS)

Field, R. D.; Spessa, A. C.; Aziz, N. A.; Camia, A.; Cantin, A.; Carr, R.; de Groot, W. J.; Dowdy, A. J.; Flannigan, M. D.; Manomaiphiboon, K.;

Uncertainty forecasts improve weather-related decisions and attenuate the effects of forecast error.

PubMed

Joslyn, Susan L; LeClerc, Jared E

2012-03-01

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 warning system is used. The work reported here tested the relative benefits of several forecast formats, comparing decisions made with and without uncertainty forecasts. In three experiments, participants assumed the role of a manager of a road maintenance company in charge of deciding whether to pay to salt the roads and avoid a potential penalty associated with icy conditions. Participants used overnight low temperature forecasts accompanied in some conditions by uncertainty estimates and in others by decision advice comparable to categorical warnings. Results suggested that uncertainty information improved decision quality overall and increased trust in the forecast. Participants with uncertainty forecasts took appropriate precautionary action and withheld unnecessary action more often than did participants using deterministic forecasts. When error in the forecast increased, participants with conventional forecasts were reluctant to act. However, this effect was attenuated by uncertainty forecasts. Providing categorical decision advice alone did not improve decisions. However, combining decision advice with uncertainty estimates resulted in the best performance overall. The results reported here have important implications for the development of forecast formats to increase compliance with severe weather warnings as well as other domains in which one must act in the face of uncertainty. PsycINFO Database Record (c) 2012 APA, all rights reserved.

Introducing the Global Fire WEather Database (GFWED)

NASA Astrophysics Data System (ADS)

Field, R. D.

2015-12-01

The Canadian Fire Weather Index (FWI) System is the mostly widely used fire danger rating system in the world. We have developed a global database of daily FWI System calculations beginning in 1980 called the Global Fire WEather Database (GFWED) gridded to a spatial resolution of 0.5° latitude by 2/3° longitude. Input weather data were obtained from the NASA Modern Era Retrospective-Analysis for Research (MERRA), and two different estimates of daily precipitation from rain gauges over land. FWI System Drought Code calculations from the gridded datasets were compared to calculations from individual weather station data for a representative set of 48 stations in North, Central and South America, Europe, Russia, Southeast Asia and Australia. Agreement between gridded calculations and the station-based calculations tended to be most different at low latitudes for strictly MERRA-based calculations. Strong biases could be seen in either direction: MERRA DC over the Mato Grosso in Brazil reached unrealistically high values exceeding DC=1500 during the dry season but was too low over Southeast Asia during the dry season. These biases are consistent with those previously-identified in MERRA's precipitation and reinforce the need to consider alternative sources of precipitation data. GFWED is being used by researchers around the world for analyzing historical relationships between fire weather and fire activity at large scales, in identifying large-scale atmosphere-ocean controls on fire weather, and calibration of FWI-based fire prediction models. These applications will be discussed. More information on GFWED can be found at http://data.giss.nasa.gov/impacts/gfwed/

Decreasing trend in severe weather occurrence over China during the past 50 years.

PubMed

Zhang, Qinghong; Ni, Xiang; Zhang, Fuqing

2017-02-17

Understanding the trend of localized severe weather under the changing climate is of great significance but remains challenging which is at least partially due to the lack of persistent and homogeneous severe weather observations at climate scales while the detailed physical processes of severe weather cannot be resolved in global climate models. Based on continuous and coherent severe weather reports from over 500 manned stations, for the first time, this study shows a significant decreasing trend in severe weather occurrence across China during the past five decades. The total number of severe weather days that have either thunderstorm, hail and/or damaging wind decrease about 50% from 1961 to 2010. It is further shown that the reduction in severe weather occurrences correlates strongly with the weakening of East Asian summer monsoon which is the primary source of moisture and dynamic forcing conducive for warm-season severe weather over China.

Decreasing trend in severe weather occurrence over China during the past 50 years

PubMed Central

Zhang, Qinghong; Ni, Xiang; Zhang, Fuqing

2017-01-01

Understanding the trend of localized severe weather under the changing climate is of great significance but remains challenging which is at least partially due to the lack of persistent and homogeneous severe weather observations at climate scales while the detailed physical processes of severe weather cannot be resolved in global climate models. Based on continuous and coherent severe weather reports from over 500 manned stations, for the first time, this study shows a significant decreasing trend in severe weather occurrence across China during the past five decades. The total number of severe weather days that have either thunderstorm, hail and/or damaging wind decrease about 50% from 1961 to 2010. It is further shown that the reduction in severe weather occurrences correlates strongly with the weakening of East Asian summer monsoon which is the primary source of moisture and dynamic forcing conducive for warm-season severe weather over China. PMID:28211465

Decreasing trend in severe weather occurrence over China during the past 50 years

NASA Astrophysics Data System (ADS)

Zhang, Qinghong; Ni, Xiang; Zhang, Fuqing

2017-04-01

Understanding the trend of localized severe weather under the changing climate is of great significance but remains challenging which is at least partially due to the lack of persistent and homogeneous severe weather observations at climate scales while the detailed physical processes of severe weather cannot be resolved in global climate models. Based on continuous and coherent severe weather reports from over 500 manned stations, for the first time, this study shows a significant decreasing trend in severe weather occurrence across China during the past five decades. The total number of severe weather days that have either thunderstorm, hail and/or damaging wind decrease about 50% from 1961 to 2010. It is further shown that the reduction in severe weather occurrences correlates strongly with the weakening of East Asian summer monsoon which is the primary source of moisture and dynamic forcing conducive for warm-season severe weather over China.

Decreasing trend in severe weather occurrence over China during the past 50 years

NASA Astrophysics Data System (ADS)

Zhang, Qinghong; Ni, Xiang; Zhang, Fuqing

2017-02-01

Understanding the trend of localized severe weather under the changing climate is of great significance but remains challenging which is at least partially due to the lack of persistent and homogeneous severe weather observations at climate scales while the detailed physical processes of severe weather cannot be resolved in global climate models. Based on continuous and coherent severe weather reports from over 500 manned stations, for the first time, this study shows a significant decreasing trend in severe weather occurrence across China during the past five decades. The total number of severe weather days that have either thunderstorm, hail and/or damaging wind decrease about 50% from 1961 to 2010. It is further shown that the reduction in severe weather occurrences correlates strongly with the weakening of East Asian summer monsoon which is the primary source of moisture and dynamic forcing conducive for warm-season severe weather over China.

Parametric vs. non-parametric daily weather generator: validation and comparison

NASA Astrophysics Data System (ADS)

Dubrovsky, Martin

2016-04-01

As the climate models (GCMs and RCMs) fail to satisfactorily reproduce the real-world surface weather regime, various statistical methods are applied to downscale GCM/RCM outputs into site-specific weather series. The stochastic weather generators are among the most favourite downscaling methods capable to produce realistic (observed like) meteorological inputs for agrological, hydrological and other impact models used in assessing sensitivity of various ecosystems to climate change/variability. To name their advantages, the generators may (i) produce arbitrarily long multi-variate synthetic weather series representing both present and changed climates (in the latter case, the generators are commonly modified by GCM/RCM-based climate change scenarios), (ii) be run in various time steps and for multiple weather variables (the generators reproduce the correlations among variables), (iii) be interpolated (and run also for sites where no weather data are available to calibrate the generator). This contribution will compare two stochastic daily weather generators in terms of their ability to reproduce various features of the daily weather series. M&Rfi is a parametric generator: Markov chain model is used to model precipitation occurrence, precipitation amount is modelled by the Gamma distribution, and the 1st order autoregressive model is used to generate non-precipitation surface weather variables. The non-parametric GoMeZ generator is based on the nearest neighbours resampling technique making no assumption on the distribution of the variables being generated. Various settings of both weather generators will be assumed in the present validation tests. The generators will be validated in terms of (a) extreme temperature and precipitation characteristics (annual and 30 years extremes and maxima of duration of hot/cold/dry/wet spells); (b) selected validation statistics developed within the frame of VALUE project. The tests will be based on observational weather series from several European stations available from the ECA&D database.

Severe Weather

ERIC Educational Resources Information Center

Forde, Evan B.

2004-01-01

Educating the public about safety issues related to severe weather is part of the National Oceanic and Atmospheric Administration's (NOAA) mission. This month's insert, Severe Weather, has been created by NOAA to help educate the public about hazardous weather conditions. The four types of severe weather highlighted in this poster are hurricanes,…

Severe Weather

ERIC Educational Resources Information Center

Forde, Evan B.

2004-01-01

Educating the public about safety issues related to severe weather is part of the National Oceanic and Atmospheric Administration's (NOAA) mission. This article deals with a poster entitled, "Severe Weather," that has been created by NOAA to help educate the public about hazardous weather conditions. The four types of severe weather highlighted in…

Exploring the Architectural Tradespace of Severe Weather Monitoring Nanosatellite Constellations

NASA Astrophysics Data System (ADS)

Hitomi, N.; Selva, D.; Blackwell, W. J.

2014-12-01

MicroMAS-1, a 3U nanosatellite developed by MIT/LL, MIT/SSL, and University of Massachusetts, was launched on July 13, 2014 and is scheduled for deployment from the International Space Station in September. The development of MicroMAS motivates an architectural analysis of a constellation of nanosatellites with the goal of drastically reducing the cost of observing severe storms compared with current monolithic missions such as the Precision and All-Weather Temperature and Humidity (PATH) mission from the NASA Decadal Survey. Our goal is to evolve the instrument capability on weather monitoring nanosatellites to achieve higher performance and better satisfy stakeholder needs. Clear definitions of performance requirements are critical in the conceptual design phase when much of the project's lifecycle cost and performance will be fixed. Ability to perform trade studies and optimization of performance needs with instrument capability will enable design teams to focus on key technologies that will introduce high value and high return on investment. In this work, we approach the significant trades and trends of constellations for monitoring severe storms by applying our rule-based decision support tool. We examine a subset of stakeholder groups listed in the OSCAR online database (e.g., weather, climate) that would benefit from severe storm weather data and their respective observation requirements (e.g. spatial resolution, accuracy). We use ten parameters in our analysis, including atmospheric temperature, humidity, and precipitation. We compare the performance and cost of thousands of different possible constellations. The constellations support hyperspectral sounders that cover different portions of the millimeter-wave spectrum (50-60 GHz, 118GHz, 183GHz) in different orbits, and the performance results are compared against those of the monolithic PATH mission. Our preliminary results indicate that constellations using the hyperspectral millimeter wave sounders can better satisfy stakeholder needs compared to the PATH mission. Well-architected constellations have increased coverage, improved horizontal resolution from lower orbits, and improved temporal resolution. Furthermore, this improved performance can be achieved at a lower cost than what is estimated for the PATH mission.

Cluster analyses of association of weather, daily factors and emergent medical conditions.

PubMed

Malkić, Jasmin; Sarajlić, Nermin; Smrke, Barbara U R; Smrke, Dragica

2013-03-01

The goal of this study was to evaluate associations between the meteorological conditions and the number of emergency cases for five distinctive causes of dispatch groups reported to SOS dispatch centre in Uppsala, Sweden. Center's responsibility include alerting to 17 ambulances in whole Uppsala County, area of 8,209 km2 with around 320,000 inhabitants representing the target patient group. Source of the medical data for this study is the database of dispatch data for the year of 2009, while the metrological data have been provided from Uppsala University Department of Earth Sciences yearly weather report. Medical and meteorological data were summoned into the unified data space where each point represents a day with its weather parameters and dispatch cause group cardinality. DBSCAN data mining algorithm was implemented to five distinctive groups of dispatch causes after the data spaces have gone through the variance adjustment and the principal component analyses. As the result, several point clusters were discovered in each of the examined data spaces indicating the distinctive conditions regarding the weather and daily cardinality of the dispatch cause, as well as the associations between these two. Most interesting finding is that specific type of winter weather formed a cluster only around the days with the high count of breathing difficulties, while one of the summer weather clusters made similar association with the days with low number of cases. Findings were confirmed by confidence level estimation based on signal to noise ratio for the observed data points.

A regressive storm model for extreme space weather

NASA Astrophysics Data System (ADS)

Terkildsen, Michael; Steward, Graham; Neudegg, Dave; Marshall, Richard

2012-07-01

Extreme space weather events, while rare, pose significant risk to society in the form of impacts on critical infrastructure such as power grids, and the disruption of high end technological systems such as satellites and precision navigation and timing systems. There has been an increased focus on modelling the effects of extreme space weather, as well as improving the ability of space weather forecast centres to identify, with sufficient lead time, solar activity with the potential to produce extreme events. This paper describes the development of a data-based model for predicting the occurrence of extreme space weather events from solar observation. The motivation for this work was to develop a tool to assist space weather forecasters in early identification of solar activity conditions with the potential to produce extreme space weather, and with sufficient lead time to notify relevant customer groups. Data-based modelling techniques were used to construct the model, and an extensive archive of solar observation data used to train, optimise and test the model. The optimisation of the base model aimed to eliminate false negatives (missed events) at the expense of a tolerable increase in false positives, under the assumption of an iterative improvement in forecast accuracy during progression of the solar disturbance, as subsequent data becomes available.

Severe Weather Planning for Schools

ERIC Educational Resources Information Center

Watson, Barbara McNaught; Strong, Christopher; Bunting, Bill

2008-01-01

Flash floods, severe thunderstorms, and tornadoes occur with rapid onset and often no warning. Decisions must be made quickly and actions taken immediately. This paper provides tips for schools on: (1) Preparing for Severe Weather Emergencies; (2) Activating a Severe Weather Plan; (3) Severe Weather Plan Checklist; and (4) Periodic Drills and…

Validation of two (parametric vs non-parametric) daily weather generators

NASA Astrophysics Data System (ADS)

Dubrovsky, M.; Skalak, P.

2015-12-01

As the climate models (GCMs and RCMs) fail to satisfactorily reproduce the real-world surface weather regime, various statistical methods are applied to downscale GCM/RCM outputs into site-specific weather series. The stochastic weather generators are among the most favourite downscaling methods capable to produce realistic (observed-like) meteorological inputs for agrological, hydrological and other impact models used in assessing sensitivity of various ecosystems to climate change/variability. To name their advantages, the generators may (i) produce arbitrarily long multi-variate synthetic weather series representing both present and changed climates (in the latter case, the generators are commonly modified by GCM/RCM-based climate change scenarios), (ii) be run in various time steps and for multiple weather variables (the generators reproduce the correlations among variables), (iii) be interpolated (and run also for sites where no weather data are available to calibrate the generator). This contribution will compare two stochastic daily weather generators in terms of their ability to reproduce various features of the daily weather series. M&Rfi is a parametric generator: Markov chain model is used to model precipitation occurrence, precipitation amount is modelled by the Gamma distribution, and the 1st order autoregressive model is used to generate non-precipitation surface weather variables. The non-parametric GoMeZ generator is based on the nearest neighbours resampling technique making no assumption on the distribution of the variables being generated. Various settings of both weather generators will be assumed in the present validation tests. The generators will be validated in terms of (a) extreme temperature and precipitation characteristics (annual and 30-years extremes and maxima of duration of hot/cold/dry/wet spells); (b) selected validation statistics developed within the frame of VALUE project. The tests will be based on observational weather series from several European stations available from the ECA&D database. Acknowledgements: The weather generator is developed and validated within the frame of projects WG4VALUE (sponsored by the Ministry of Education, Youth and Sports of CR), and VALUE (COST ES 1102 action).

CLIGEN: Addressing deficiencies in the generator and its databases

USDA-ARS?s Scientific Manuscript database

CLIGEN is a stochastic generator that estimates daily temperatures, precipitation and other weather related phenomena. It is an intermediate model used by the Water Erosion Prediction Program (WEPP), the Wind Erosion Prediction System (WEPS), and other models that require daily weather observations....

Wet weather highway accident analysis and skid resistance data management system (volume I).

DOT National Transportation Integrated Search

1992-06-01

The objectives and scope of this research are to establish an effective methodology for wet weather accident analysis and to develop a database management system to facilitate information processing and storage for the accident analysis process, skid...

A Sounding-based Severe Weather Tool to Support Daily Operations at Kennedy Space Center and Cape Canaveral Air Force Station

NASA Technical Reports Server (NTRS)

Bauman, William H.; Roeder, William P.

2014-01-01

People and property at Kennedy Space Center (KSC) and Cape Canaveral Air Force Station (CCAFS) are at risk when severe weather occurs. Strong winds, hail and tornadoes can injure individuals and cause costly damage to structures if not properly protected. NASA's Launch Services Program and Ground Systems Development and Operations Program and other KSC programs use the daily and weekly severe weather forecasts issued by the 45th Weather Squadron (45 WS) to determine if they need to limit an activity such as working on gantries, or protect property such as a vehicle on a pad. The 45 WS requested the Applied Meteorology Unit (AMU) develop a warm season (May-September) severe weather tool for use in the Meteorological Interactive Data Display System (MIDDS) based on the late morning, 1500 UTC (1100 local time), CCAFS (XMR) sounding. The 45 WS frequently makes decisions to issue a severe weather watch and other severe weather warning support products to NASA and the 45th Space Wing in the late morning, after the 1500 UTC sounding. The results of this work indicate that certain stability indices based on the late morning XMR soundings can depict differences between days with reported severe weather and days with no reported severe weather. The AMU determined a frequency of reported severe weather for the stability indices and implemented an operational tool in MIDDS.

Severe Weather Tool using 1500 UTC Cape Canaveral Air Force Station Soundings

NASA Technical Reports Server (NTRS)

Bauman, William H., III

2013-01-01

People and property at Kennedy Space Center (KSC) and Cape Canaveral Air Force Station (CCAFS) are at risk when severe weather occurs. Strong winds, hail and tornadoes can injure individuals and cause costly damage to structures if not properly protected. NASA's Launch Services Program and Ground Systems Development and Operations Program and other KSC programs use the daily and weekly severe weather forecasts issued by the 45th Weather Squadron (45 WS) to determine if they need to limit an activity such as working on gantries, or protect property such as a vehicle on a pad. The 45 WS requested the Applied Meteorology Unit (AMU) develop a warm season (May-September) severe weather tool for use in the Meteorological Interactive Data Display System (MIDDS) based on the late morning, 1500 UTC (1100 local time), CCAFS (XMR) sounding. The 45 WS frequently makes decisions to issue a severe weather watch and other severe weather warning support products to NASA and the 45th Space Wing in the late morning, after the 1500 UTC sounding. The results of this work indicate that certain stability indices based on the late morning XMR soundings can depict differences between days with reported severe weather and days with no reported severe weather. The AMU determined a frequency of reported severe weather for the stability indices and implemented an operational tool in MIDDS.

A Severe Weather Laboratory Exercise for an Introductory Weather and Climate Class Using Active Learning Techniques

ERIC Educational Resources Information Center

Grundstein, Andrew; Durkee, Joshua; Frye, John; Andersen, Theresa; Lieberman, Jordan

2011-01-01

This paper describes a new severe weather laboratory exercise for an Introductory Weather and Climate class, appropriate for first and second year college students (including nonscience majors), that incorporates inquiry-based learning techniques. In the lab, students play the role of meteorologists making forecasts for severe weather. The…

Wet weather highway accident analysis and skid resistance data management system (volume II : user's manual).

DOT National Transportation Integrated Search

1992-06-01

The objectives and scope of this research are to establish an effective methodology for wet weather accident analysis and to develop a database management system to facilitate information processing and storage for the accident analysis process, skid...

Aerial thermography studies of power plant heated lakes

NASA Astrophysics Data System (ADS)

Villa-Aleman, Eliel; Garrett, Alfred J.; Kurzeja, Robert J.; Pendergast, Malcolm M.

2000-03-01

Remote sensing temperature measurements of water bodies is complicated by the temperature differences between the true surface or `skin' water and the bulk water below. Weather conditions control the reduction of the skin temperature relative to the bulk water temperature. Typical skin temperature depressions range from a few tenths of a degree Celsius to more than one degree. In this research project, the Savannah River Technology Center used aerial thermography and surface-based meteorological and water temperature measurements to study a power plant cooling lake in South Carolina. Skin and bulk water temperatures were measured simultaneously for imagery calibration and to product a database for modeling of skin temperature depressions as a function of weather and bulk water temperatures. This paper will present imagery that illustrates how the skin temperature depression was affected by different conditions in several locations on the lake and will present skin temperature modeling results.

Hail frequency estimation across Europe based on a combination of overshooting top detections and the ERA-INTERIM reanalysis

NASA Astrophysics Data System (ADS)

Punge, H. J.; Bedka, K. M.; Kunz, M.; Reinbold, A.

2017-12-01

This article presents a hail frequency estimation based on the detection of cold overshooting cloud tops (OTs) from the Meteosat Second Generation (MSG) operational weather satellites, in combination with a hail-specific filter derived from the ERA-INTERIM reanalysis. This filter has been designed based on the atmospheric properties in the vicinity of hail reports registered in the European Severe Weather Database (ESWD). These include Convective Available Potential Energy (CAPE), 0-6-km bulk wind shear and freezing level height, evaluated at the nearest time step and interpolated from the reanalysis grid to the location of the hail report. Regions highly exposed to hail events include Northern Italy, followed by South-Eastern Austria and Eastern Spain. Pronounced hail frequency is also found in large parts of Eastern Europe, around the Alps, the Czech Republic, Southern Germany, Southern and Eastern France, and in the Iberic and Apennine mountain ranges.

A two year (2008-2009) analysis of severe convective storms in the Mediterranean basin as observed by satellite imagery

NASA Astrophysics Data System (ADS)

Gozzini, B.; Melani, S.; Pasi, F.; Ortolani, A.

2010-09-01

The increasing damages caused by natural disasters, a great part of them being direct or indirect effects of severe convective storms (SCS), seem to suggest that extreme events occur with greater frequency, also as a consequence of climate changes. A better comprehension of the genesis and evolution of SCS is then necessary to clarify if and what is changing in these extreme events. The major reason to go through the mechanisms driving such events is given by the growing need to have timely and precise predictions of severe weather events, especially in areas that show to be more and more sensitive to their occurrence. When dealing with severe weather events, either from a researcher or an operational point of view, it is necessary to know precisely the conditions under which these events take place to upgrade conceptual models or theories, and consequently to improve the quality of forecasts as well as to establish effective warning decision procedures. The Mediterranean basin is, in general terms, a sea of small areal extent, characterised by the presence of several islands; thus, a severe convection phenomenon originating over the sea, that lasts several hours, is very likely to make landfall during its lifetime. On the other hand, these storms are quasi-stationary or very slow moving so that, when convection happens close to the shoreline, it is normally very dangerous and in many cases can cause very severe weather, with flash floods or tornadoes. An example of these extreme events is one of the case study analysed in this work, regarding the flash flood occurred in Giampileri (Sicily, Italy) the evening of 1st October 2009, where 18 people died, other 79 injured and the historical centre of the village seriously damaged. Severe weather systems and strong convection occurring in the Mediterranean basin have been investigated for two years (2008-2009) using geostationary (MSG) and polar orbiting (AVHRR) satellite data, supported by ECMWF analyses and severe weather reports. The spatial and seasonal variability of storm occurrence have been also analysed, as well as the most favourable synoptic conditions for their formation. The analysis shows the existence of preferential areas of genesis of these extreme events, mainly located in the central Mediterranean (i.e., Ionic and Tyrrhenian seas), where the storms develop and grow preferentially in fall. The synoptic features, identified as precursors of severe convective events genesis, show how the totality of the identified cases occur in mid-troposphere (500 hPa) troughs or cut-off circulation within southerly flow, with values of deep level shear of at least 15 m s-1 and high θe (850 hPa) values. Among all the detected cases of severe convection, two selected cases of enhanced-V features are presented in detail, either for the different synoptic environments in which they are embedded, and for being long-lived or severe in terms of heavy rainfall and damages they produced at the ground. In a long-term perspective, this preliminary study aims to make a climatological database of severe weather events occurring in the Mediterranean sea which may critically impact on the Italian peninsula and potentially affect population, in order to develop an objective procedure which can support regional meteorological services in forecasting extreme events, their development and impact, for taking proper early decisions.

What is the effect of the weather on trauma workload? A systematic review of the literature.

PubMed

Ali, A M; Willett, K

2015-01-01

Hospital admission rates for a number of conditions have been linked to variations in the weather. It is well established that trauma workload displays significant seasonal variation. A reliable predictive model might enable targeting of high-risk groups for intervention and planning of hospital staff levels. To our knowledge there have been no systematic reviews of the literature on the relationship between weather and trauma workload, and predictive models have thus far been informed by the results of single studies. We conducted a systematic review of bibliographic databases and reference lists up to June 2014 to identify primary research papers assessing the effect of specified weather conditions including temperature, rainfall, snow, fog, hail, humidity and wind speed on trauma workload, defined as admission to hospital, fracture or a Road Traffic Accident (RTA) resulting in a seriously injured casualty or fatality. 11,083 papers were found through electronic and reference search. 83 full papers were assessed for eligibility. 28 met inclusion criteria and were included in the final review; 6 of these related to the effect of the weather on trauma admissions, one to ambulance call out for trauma, 13 to fracture rate and 8 to RTAs. Increased temperature is positively correlated with trauma admissions. The rate of distal radius fractures is more sensitive to adverse weather than the rate of hip fractures. Paediatric trauma, both in respect of trauma admissions and fracture rate, is more sensitive to the weather than adult trauma. Adverse weather influences both RTA frequency and severity, but the nature of the relationship is dependent upon the timecourse of the weather event and the population studied. Important methodological differences between studies limit the value of the existing literature in building consensus for a generalisable predictive model. Weather conditions may have a substantial effect on trauma workload independent of the effects of seasonal variation; the population studied and timecourse of weather events appear critical in determining this relationship. Methodological differences between studies limit the validity of conclusions drawn from analysis of the literature, and we identify a number of areas that future research might address. Copyright © 2015 Elsevier Ltd. All rights reserved.

Building a Massive Volcano Archive and the Development of a Tool for the Science Community

NASA Technical Reports Server (NTRS)

Linick, Justin

2012-01-01

The Jet Propulsion Laboratory has traditionally housed one of the world's largest databases of volcanic satellite imagery, the ASTER Volcano Archive (10Tb), making these data accessible online for public and scientific use. However, a series of changes in how satellite imagery is housed by the Earth Observing System (EOS) Data Information System has meant that JPL has been unable to systematically maintain its database for the last several years. We have provided a fast, transparent, machine-to-machine client that has updated JPL's database and will keep it current in near real-time. The development of this client has also given us the capability to retrieve any data provided by NASA's Earth Observing System Clearinghouse (ECHO) that covers a volcanic event reported by U.S. Air Force Weather Agency (AFWA). We will also provide a publicly available tool that interfaces with ECHO that can provide functionality not available in any of ECHO's Earth science discovery tools.

Static and dynamic controls on fire activity at moderate spatial and temporal scales in the Alaskan boreal forest

USGS Publications Warehouse

Barrett, Kirsten; Loboda, Tatiana; McGuire, A. David; Genet, Hélène; Hoy, Elizabeth; Kasischke, Eric

2016-01-01

Wildfire, a dominant disturbance in boreal forests, is highly variable in occurrence and behavior at multiple spatiotemporal scales. New data sets provide more detailed spatial and temporal observations of active fires and the post-burn environment in Alaska. In this study, we employ some of these new data to analyze variations in fire activity by developing three explanatory models to examine the occurrence of (1) seasonal periods of elevated fire activity using the number of MODIS active fire detections data set (MCD14DL) within an 11-day moving window, (2) unburned patches within a burned area using the Monitoring Trends in Burn Severity fire severity product, and (3) short-to-moderate interval (<60 yr) fires using areas of burned area overlap in the Alaska Large Fire Database. Explanatory variables for these three models included dynamic variables that can change over the course of the fire season, such as weather and burn date, as well as static variables that remain constant over a fire season, such as topography, drainage, vegetation cover, and fire history. We found that seasonal periods of high fire activity are associated with both seasonal timing and aggregated weather conditions, as well as the landscape composition of areas that are burning. Important static inputs to the model of seasonal fire activity indicate that when fire weather conditions are suitable, areas that typically resist fire (e.g., deciduous stands) may become more vulnerable to burning and therefore less effective as fire breaks. The occurrence of short-to-moderate interval fires appears to be primarily driven by weather conditions, as these were the only relevant explanatory variables in the model. The unique importance of weather in explaining short-to-moderate interval fires implies that fire return intervals (FRIs) will be sensitive to projected climate changes in the region. Unburned patches occur most often in younger stands, which may be related to a greater deciduous fraction of vegetation as well as lower fuel loads compared with mature stands. The fraction of unburned patches may therefore increase in response to decreasing FRIs and increased deciduousness in the region, or these may decrease if fire weather conditions become more severe.

Analysis of 2015 Winter In-Flight Icing Case Studies with Ground-Based Remote Sensing Systems Compared to In-Situ SLW Sondes

NASA Technical Reports Server (NTRS)

Serke, David J.; King, Michael Christopher; Hansen, Reid; Reehorst, Andrew L.

2016-01-01

National Aeronautics and Space Administration (NASA) and the National Center for Atmospheric Research (NCAR) have developed an icing remote sensing technology that has demonstrated skill at detecting and classifying icing hazards in a vertical column above an instrumented ground station. This technology has recently been extended to provide volumetric coverage surrounding an airport. Building on the existing vertical pointing system, the new method for providing volumetric coverage utilizes a vertical pointing cloud radar, a multi-frequency microwave radiometer with azimuth and elevation pointing, and a NEXRAD radar. The new terminal area icing remote sensing system processes the data streams from these instruments to derive temperature, liquid water content, and cloud droplet size for each examined point in space. These data are then combined to ultimately provide icing hazard classification along defined approach paths into an airport. To date, statistical comparisons of the vertical profiling technology have been made to Pilot Reports and Icing Forecast Products. With the extension into relatively large area coverage and the output of microphysical properties in addition to icing severity, the use of these comparators is not appropriate and a more rigorous assessment is required. NASA conducted a field campaign during the early months of 2015 to develop a database to enable the assessment of the new terminal area icing remote sensing system and further refinement of terminal area icing weather information technologies in general. In addition to the ground-based remote sensors listed earlier, in-situ icing environment measurements by weather balloons were performed to produce a comprehensive comparison database. Balloon data gathered consisted of temperature, humidity, pressure, super-cooled liquid water content, and 3-D position with time. Comparison data plots of weather balloon and remote measurements, weather balloon flight paths, bulk comparisons of integrated liquid water content and icing cloud extent agreement, and terminal-area hazard displays are presented. Discussions of agreement quality and paths for future development are also included.

NATIONAL URBAN DATABASE AND ACCESS PROTAL TOOL

EPA Science Inventory

Current mesoscale weather prediction and microscale dispersion models are limited in their ability to perform accurate assessments in urban areas. A project called the National Urban Database with Access Portal Tool (NUDAPT) is beginning to provide urban data and improve the para...

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.

Lightning jump as a nowcast predictor: Application to severe weather events in Catalonia

NASA Astrophysics Data System (ADS)

Farnell, C.; Rigo, T.; Pineda, N.

2017-01-01

Several studies reported sudden increases in the total lightning flash rate (intra-cloud+cloud-to-ground) preceding the occurrence of severe weather (large hail, wind gusts associated to thunderstorms and/or tornadoes). Named ;Lightning Jump;, this pattern has demonstrated to be of operational applicability in the forecasting of severe weather phenomena. The present study introduces the application of a lightning jump algorithm, with an identification of cells based solely on total lightning data, revealing that there is no need of radar data to trigger severe weather warnings. The algorithm was validated by means of a dataset severe weather events occurred in Catalonia in the period 2009-2014. Results obtained revealed very promising.

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).

Physical Patterns Associated with 27 April 2011 Tornado Outbreak

NASA Astrophysics Data System (ADS)

Ramos, Fernanda; Salem, Thomas

2012-02-01

The National Weather Service office in Memphis, Tennessee has aimed their efforts to improve severe tornado forecasting. Everything is not known about tornadogenesis, but one thing is: tornadoes tend to form within supercell thunderstorms. Hence, 27 April 2011 and 25 May 2011 were days when a Tornado Outbreak was expected to arise. Although 22 tornadoes struck the region on 27 April 2011, only 1 impacted the area on 25 May 2011. In order to understand both events, comparisons of their physical features were made. These parameters were studied using the Weather Event Simulator system and the NOAA/NWS Storm Prediction database. This research concentrated on the Surface Frontal Analysis, NAM40 700mb Dew-Points, NAM80 250mb Wind Speed and NAM20 500mb Vorticity images as well as 0-6 km Shear, MUCAPE and VGP mesoscale patterns. As result of this research a Dry-Line ahead of a Cold Front, Dew-points 5C and higher, and high Vorticity values^ were synoptic patterns that influenced to the formation of supercell tornadoes. Finally, MUCAPE and VGP favored the possibility of tornadoes occurrence on 25 May 2011, but shear was the factor that made 27 April 2011 a day for a Tornado Outbreak weather event.

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.

Extreme Weather Risk Assessment: The Case of Jiquilisco, El Salvador

NASA Astrophysics Data System (ADS)

Melendez, Karla; Ceppi, Claudia; Molero, Juanjo; Rios Insua, David

2014-05-01

All major climate models predict increases in both global and regional mean temperatures throughout this century, under different scenarios concerning future trends in population growth or economic and technological development. This consistency of results across models has strengthened the evidence about global warming. Despite the convincing facts and findings of climate researchers, there is still a great deal of skepticism around climate change. There is somewhat less consensus about some of the consequences of climate change, for example in reference to extreme weather changes, in particular as regards more local scales. However, such changes seem to have already considerable impact in many regions across the world in terms of lives, economic losses, and required changes in lifestyles. This may demand appropriate policy responses both at national and local levels. Our work provides a framework for extreme weather multithreat risk management, based on probabilistic risk assessment (PRA). This may be useful in comparing the effectiveness of different actions to manage risks and inform judgment concerning the appropriate resource allocation to mitigate the risks. The methodology has been applied to the case study of the "El Marillo II" community, located in the municipality of Jiquilisco in El Salvador. There, the main problem related with extreme weather conditions are the frequent floods caused by rainfall, hurricanes , and water increases in the Lempa river nearby located. However, droughts are also very relevant. Based on several sources like SNET, newspapers, field visits to the region and interviews, we have built a detailed database that comprises extreme weather daily data from January 1971 until December 2011. Forecasting models for floods and droughts were built suggesting the need to properly manage the risks. We subsequently obtained the optimal portfolio of countermeasures, given the budget constraints. KEYWORDS: CLIMATE CHANGE, EXTREME WEATHER, RISK ANALYSIS, DECISION ANALYSIS, EL SALVADOR.

Using PBL to Prepare Educators and Emergency Managers to Plan for Severe Weather

ERIC Educational Resources Information Center

Stalker, Sarah L.; Cullen, Theresa A.; Kloesel, Kevin

2015-01-01

Within the past 10 years severe weather has been responsible for an annual average of 278 fatalities in the United States (National Weather Service, 2013). During severe weather special populations are populations of high concentrations of people that cannot respond quickly. Schools show both of these characteristics. The average lead time for…

A stability analysis of AVE-4 severe weather soundings

NASA Technical Reports Server (NTRS)

Johnson, D. L.

1982-01-01

The stability and vertical structure of an average severe storm sounding, consisting of both thermodynamic and wind vertical profiles, were investigated to determine if they could be distinguished from an average lag sounding taken 3 to 6 hours prior to severe weather occurrence. The term average is defined here to indicate the arithmetic mean of a parameter, as a function of altitude, determined from a large number of available observations taken either close to severe weather occurrence, or else more than 3 hours before it occurs. The investigative computations were also done to help determine if a severe storm forecast or index could possibly be used or developed. These mean vertical profiles of thermodynamic and wind parameters as a function of severity of the weather, determined from manually digitized radar (MDR) categories are presented. Profile differences and stability index differences are presented along with the development of the Johnson Lag Index (JLI) which is determined entirely upon environmental vertical parameter differences between conditions 3 hours prior to severe weather, and severe weather itself.

SUVI Thematic Maps: A new tool for space weather forecasting

NASA Astrophysics Data System (ADS)

Hughes, J. M.; Seaton, D. B.; Darnel, J.

2017-12-01

The new Solar Ultraviolet Imager (SUVI) instruments aboard NOAA's GOES-R series satellites collect continuous, high-quality imagery of the Sun in six wavelengths. SUVI imagers produce at least one image every 10 seconds, or 8,640 images per day, considerably more data than observers can digest in real time. Over the projected 20-year lifetime of the four GOES-R series spacecraft, SUVI will provide critical imagery for space weather forecasters and produce an extensive but unwieldy archive. In order to condense the database into a dynamic and searchable form we have developed solar thematic maps, maps of the Sun with key features, such as coronal holes, flares, bright regions, quiet corona, and filaments, identified. Thematic maps will be used in NOAA's Space Weather Prediction Center to improve forecaster response time to solar events and generate several derivative products. Likewise, scientists use thematic maps to find observations of interest more easily. Using an expert-trained, naive Bayesian classifier to label each pixel, we create thematic maps in real-time. We created software to collect expert classifications of solar features based on SUVI images. Using this software, we compiled a database of expert classifications, from which we could characterize the distribution of pixels associated with each theme. Given new images, the classifier assigns each pixel the most appropriate label according to the trained distribution. Here we describe the software to collect expert training and the successes and limitations of the classifier. The algorithm excellently identifies coronal holes but fails to consistently detect filaments and prominences. We compare the Bayesian classifier to an artificial neural network, one of our attempts to overcome the aforementioned limitations. These results are very promising and encourage future research into an ensemble classification approach.

Probabilistic flood warning using grand ensemble weather forecasts

NASA Astrophysics Data System (ADS)

He, Y.; Wetterhall, F.; Cloke, H.; Pappenberger, F.; Wilson, M.; Freer, J.; McGregor, G.

2009-04-01

As the severity of floods increases, possibly due to climate and landuse change, there is urgent need for more effective and reliable warning systems. The incorporation of numerical weather predictions (NWP) into a flood warning system can increase forecast lead times from a few hours to a few days. A single NWP forecast from a single forecast centre, however, is insufficient as it involves considerable non-predictable uncertainties and can lead to a high number of false or missed warnings. An ensemble of weather forecasts from one Ensemble Prediction System (EPS), when used on catchment hydrology, can provide improved early flood warning as some of the uncertainties can be quantified. EPS forecasts from a single weather centre only account for part of the uncertainties originating from initial conditions and stochastic physics. Other sources of uncertainties, including numerical implementations and/or data assimilation, can only be assessed if a grand ensemble of EPSs from different weather centres is used. When various models that produce EPS from different weather centres are aggregated, the probabilistic nature of the ensemble precipitation forecasts can be better retained and accounted for. The availability of twelve global EPSs through the 'THORPEX Interactive Grand Global Ensemble' (TIGGE) offers a new opportunity for the design of an improved probabilistic flood forecasting framework. This work presents a case study using the TIGGE database for flood warning on a meso-scale catchment. The upper reach of the River Severn catchment located in the Midlands Region of England is selected due to its abundant data for investigation and its relatively small size (4062 km2) (compared to the resolution of the NWPs). This choice was deliberate as we hypothesize that the uncertainty in the forcing of smaller catchments cannot be represented by a single EPS with a very limited number of ensemble members, but only through the variance given by a large number ensembles and ensemble system. A coupled atmospheric-hydrologic-hydraulic cascade system driven by the TIGGE ensemble forecasts is set up to study the potential benefits of using the TIGGE database in early flood warning. Physically based and fully distributed LISFLOOD suite of models is selected to simulate discharge and flood inundation consecutively. The results show the TIGGE database is a promising tool to produce forecasts of discharge and flood inundation comparable with the observed discharge and simulated inundation driven by the observed discharge. The spread of discharge forecasts varies from centre to centre, but it is generally large, implying a significant level of uncertainties. Precipitation input uncertainties dominate and propagate through the cascade chain. The current NWPs fall short of representing the spatial variability of precipitation on a comparatively small catchment. This perhaps indicates the need to improve NWPs resolution and/or disaggregation techniques to narrow down the spatial gap between meteorology and hydrology. It is not necessarily true that early flood warning becomes more reliable when more ensemble forecasts are employed. It is difficult to identify the best forecast centre(s), but in general the chance of detecting floods is increased by using the TIGGE database. Only one flood event was studied because most of the TIGGE data became available after October 2007. It is necessary to test the TIGGE ensemble forecasts with other flood events in other catchments with different hydrological and climatic regimes before general conclusions can be made on its robustness and applicability.

Improved Dust Forecast Products for Southwest Asia Forecasters through Dust Source Database Advancements

NASA Astrophysics Data System (ADS)

Brooks, G. R.

2011-12-01

Dust storm forecasting is a critical part of military theater operations in Afghanistan and Iraq as well as other strategic areas of the globe. The Air Force Weather Agency (AFWA) has been using the Dust Transport Application (DTA) as a forecasting tool since 2001. Initially developed by The Johns Hopkins University Applied Physics Laboratory (JHUAPL), output products include dust concentration and reduction of visibility due to dust. The performance of the products depends on several factors including the underlying dust source database, treatment of soil moisture, parameterization of dust processes, and validity of the input atmospheric model data. Over many years of analysis, seasonal dust forecast biases of the DTA have been observed and documented. As these products are unique and indispensible for U.S. and NATO forces, amendments were required to provide the best forecasts possible. One of the quickest ways to scientifically address the dust concentration biases noted over time was to analyze the weaknesses in, and adjust the dust source database. Dust source database strengths and weaknesses, the satellite analysis and adjustment process, and tests which confirmed the resulting improvements in the final dust concentration and visibility products will be shown.

SPAGETTA: a Multi-Purpose Gridded Stochastic Weather Generator

NASA Astrophysics Data System (ADS)

Dubrovsky, M.; Huth, R.; Rotach, M. W.; Dabhi, H.

2017-12-01

SPAGETTA is a new multisite/gridded multivariate parametric stochastic weather generator (WG). Site-specific precipitation occurrence and amount are modelled by Markov chain and Gamma distribution, the non-precipitation variables are modelled by an autoregressive (AR) model conditioned on precipitation occurrence, and the spatial coherence of all variables is modelled following the Wilks' (2009) approach. SPAGETTA may be run in two modes. Mode 1: it is run as a classical WG, which is calibrated using weather series from multiple sites, and only then it may produce arbitrarily long synthetic series mimicking the spatial and temporal structure of the calibration data. To generate the weather series representing the future climate, the WG parameters are modified according to the climate change scenario, typically derived from GCM or RCM simulations. Mode 2: the user provides only basic information (not necessarily to be realistic) on the temporal and spatial auto-correlation structure of the weather variables and their mean annual cycle; the generator itself derives the parameters of the underlying AR model, which produces the multi-site weather series. Optionally, the user may add the spatially varying trend, which is superimposed to the synthetic series. The contribution consists of following parts: (a) Model of the WG. (b) Validation of WG in terms of the spatial temperature and precipitation characteristics, including characteristics of spatial hot/cold/dry/wet spells. (c) Results of the climate change impact experiment, in which the WG parameters representing the spatial and temporal variability are modified using the climate change scenarios and the effect on the above spatial validation indices is analysed. In this experiment, the WG is calibrated using the E-OBS gridded daily weather data for several European regions, and the climate change scenarios are derived from the selected RCM simulations (CORDEX database). (d) The second mode of operation will be demonstrated by results obtained while developing the methodology for assessing collective significance of trends in multi-site weather series. The performance of the proposed test statistics is assessed based on large number of realisations of synthetic series produced by WG assuming a given statistical structure and trend of the weather series.

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.

Discrimination of Sedimentary Lithologies Through Unmixing of EO-1 Hyperion Data: Melville Island, Canadian High Arctic

NASA Astrophysics Data System (ADS)

Leverington, D. W.

2008-12-01

The use of remote-sensing techniques in the discrimination of rock and soil classes in northern regions can help support a diverse range of activities including environmental characterization, mineral exploration, and the study of Quaternary paleoenvironments. Images of low spectral resolution can commonly be used in the mapping of lithological classes possessing distinct spectral characteristics, but hyperspectral databases offer greater potential for discrimination of materials distinguished by more subtle reflectance properties. Orbiting sensors offer an especially flexible and cost-effective means for acquisition of data to workers unable to conduct airborne surveys. In an effort to better constrain the utility of hyperspectral datasets in northern research, this study undertook to investigate the effectiveness of EO-1 Hyperion data in the discrimination and mapping of surface classes at a study area on Melville Island, Nunavut. Bedrock units in the immediate study area consist of late-Paleozoic clastic and carbonate sequences of the Sverdrup Basin. Weathered and frost-shattered felsenmeer, predominantly taking the form of boulder- to pebble-sized clasts that have accumulated in place and that mantle parent bedrock units, is the most common surface material in the study area. Hyperion data were converted from at-sensor radiance to reflectance, and were then linearly unmixed on the basis of end-member spectra measured from field samples. Hyperion unmixing results effectively portray the general fractional cover of six end members, although the fraction images of several materials contain background values that in some areas overestimate surface exposure. The best separated end members include the snow, green vegetation, and red-weathering sandstone classes, whereas the classes most negatively affected by elevated fraction values include the mudstone, limestone, and 'other' sandstone classes. Local overestimates of fractional cover are likely related to the shared lithological and weathering characteristics of several clastic and carbonate units, and may also be related to the lower radiometric precision characteristic of Hyperion data. Despite these issues, the databases generated in this study successfully provide useful complementary information to that provided by maps of local bedrock geology.

Assessment of WRF Simulated Precipitation by Meteorological Regimes

NASA Astrophysics Data System (ADS)

Hagenhoff, Brooke Anne

This study evaluated warm-season precipitation events in a multi-year (2007-2014) database of Weather Research and Forecasting (WRF) simulations over the Northern Plains and Southern Great Plains. These WRF simulations were run daily in support of the National Oceanic and Atmospheric Administration (NOAA) Hazardous Weather Testbed (HWT) by the National Severe Storms Laboratory (NSSL) for operational forecasts. Evaluating model skill by synoptic pattern allows for an understanding of how model performance varies with particular atmospheric states and will aid forecasters with pattern recognition. To conduct this analysis, a competitive neural network known as the Self-Organizing Map (SOM) was used. SOMs allow the user to represent atmospheric patterns in an array of nodes that represent a continuum of synoptic categorizations. North American Regional Reanalysis (NARR) data during the warm season (April-September) was used to perform the synoptic typing over the study domains. Simulated precipitation was evaluated against observations provided by the National Centers for Environmental Prediction (NCEP) Stage IV precipitation analysis.

Weather impacts on single-vehicle truck crash injury severity.

PubMed

Naik, Bhaven; Tung, Li-Wei; Zhao, Shanshan; Khattak, Aemal J

2016-09-01

The focus of this paper is on illustrating the feasibility of aggregating data from disparate sources to investigate the relationship between single-vehicle truck crash injury severity and detailed weather conditions. Specifically, this paper presents: (a) a methodology that combines detailed 15-min weather station data with crash and roadway data, and (b) an empirical investigation of the effects of weather on crash-related injury severities of single-vehicle truck crashes. Random parameters ordinal and multinomial regression models were used to investigate crash injury severity under different weather conditions, taking into account the individual unobserved heterogeneity. The adopted methodology allowed consideration of environmental, roadway, and climate-related variables in single-vehicle truck crash injury severity. Results showed that wind speed, rain, humidity, and air temperature were linked with single-vehicle truck crash injury severity. Greater recorded wind speed added to the severity of injuries in single-vehicle truck crashes in general. Rain and warmer air temperatures were linked to more severe crash injuries in single-vehicle truck crashes while higher levels of humidity were linked to less severe injuries. Random parameters ordered logit and multinomial logit, respectively, revealed some individual heterogeneity in the data and showed that integrating comprehensive weather data with crash data provided useful insights into factors associated with single-vehicle truck crash injury severity. The research provided a practical method that combined comprehensive 15-min weather station data with crash and roadway data, thereby providing useful insights into crash injury severity of single-vehicle trucks. Those insights are useful for future truck driver educational programs and for truck safety in different weather conditions. Copyright © 2016 Elsevier Ltd and National Safety Council. All rights reserved.

Finite element techniques in computational time series analysis of turbulent flows

NASA Astrophysics Data System (ADS)

Horenko, I.

2009-04-01

In recent years there has been considerable increase of interest in the mathematical modeling and analysis of complex systems that undergo transitions between several phases or regimes. Such systems can be found, e.g., in weather forecast (transitions between weather conditions), climate research (ice and warm ages), computational drug design (conformational transitions) and in econometrics (e.g., transitions between different phases of the market). In all cases, the accumulation of sufficiently detailed time series has led to the formation of huge databases, containing enormous but still undiscovered treasures of information. However, the extraction of essential dynamics and identification of the phases is usually hindered by the multidimensional nature of the signal, i.e., the information is "hidden" in the time series. The standard filtering approaches (like f.~e. wavelets-based spectral methods) have in general unfeasible numerical complexity in high-dimensions, other standard methods (like f.~e. Kalman-filter, MVAR, ARCH/GARCH etc.) impose some strong assumptions about the type of the underlying dynamics. Approach based on optimization of the specially constructed regularized functional (describing the quality of data description in terms of the certain amount of specified models) will be introduced. Based on this approach, several new adaptive mathematical methods for simultaneous EOF/SSA-like data-based dimension reduction and identification of hidden phases in high-dimensional time series will be presented. The methods exploit the topological structure of the analysed data an do not impose severe assumptions on the underlying dynamics. Special emphasis will be done on the mathematical assumptions and numerical cost of the constructed methods. The application of the presented methods will be first demonstrated on a toy example and the results will be compared with the ones obtained by standard approaches. The importance of accounting for the mathematical assumptions used in the analysis will be pointed up in this example. Finally, applications to analysis of meteorological and climate data will be presented.

The STP (Solar-Terrestrial Physics) Semantic Web based on the RSS1.0 and the RDF

NASA Astrophysics Data System (ADS)

Kubo, T.; Murata, K. T.; Kimura, E.; Ishikura, S.; Shinohara, I.; Kasaba, Y.; Watari, S.; Matsuoka, D.

2006-12-01

In the Solar-Terrestrial Physics (STP), it is pointed out that circulation and utilization of observation data among researchers are insufficient. To archive interdisciplinary researches, we need to overcome this circulation and utilization problems. Under such a background, authors' group has developed a world-wide database that manages meta-data of satellite and ground-based observation data files. It is noted that retrieving meta-data from the observation data and registering them to database have been carried out by hand so far. Our goal is to establish the STP Semantic Web. The Semantic Web provides a common framework that allows a variety of data shared and reused across applications, enterprises, and communities. We also expect that the secondary information related with observations, such as event information and associated news, are also shared over the networks. The most fundamental issue on the establishment is who generates, manages and provides meta-data in the Semantic Web. We developed an automatic meta-data collection system for the observation data using the RSS (RDF Site Summary) 1.0. The RSS1.0 is one of the XML-based markup languages based on the RDF (Resource Description Framework), which is designed for syndicating news and contents of news-like sites. The RSS1.0 is used to describe the STP meta-data, such as data file name, file server address and observation date. To describe the meta-data of the STP beyond RSS1.0 vocabulary, we defined original vocabularies for the STP resources using the RDF Schema. The RDF describes technical terms on the STP along with the Dublin Core Metadata Element Set, which is standard for cross-domain information resource descriptions. Researchers' information on the STP by FOAF, which is known as an RDF/XML vocabulary, creates a machine-readable metadata describing people. Using the RSS1.0 as a meta-data distribution method, the workflow from retrieving meta-data to registering them into the database is automated. This technique is applied for several database systems, such as the DARTS database system and NICT Space Weather Report Service. The DARTS is a science database managed by ISAS/JAXA in Japan. We succeeded in generating and collecting the meta-data automatically for the CDF (Common data Format) data, such as Reimei satellite data, provided by the DARTS. We also create an RDF service for space weather report and real-time global MHD simulation 3D data provided by the NICT. Our Semantic Web system works as follows: The RSS1.0 documents generated on the data sites (ISAS and NICT) are automatically collected by a meta-data collection agent. The RDF documents are registered and the agent extracts meta-data to store them in the Sesame, which is an open source RDF database with support for RDF Schema inferencing and querying. The RDF database provides advanced retrieval processing that has considered property and relation. Finally, the STP Semantic Web provides automatic processing or high level search for the data which are not only for observation data but for space weather news, physical events, technical terms and researches information related to the STP.

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.

National Weather Service: Watch, Warning, Advisory Display

MedlinePlus

... Education & Outreach About the SPC SPC FAQ About Tornadoes About Derechos Video Lecture Series WCM Page Enh. ... Convective/Tropical Weather Flooding Winter Weather Non-Precipitation Tornado Watch Tornado Warning* Severe Thunderstorm Watch Severe Thunderstorm ...

Forecasting Safe or Dangerous Space Weather from HMI Magnetograms

NASA Technical Reports Server (NTRS)

Falconer, David; Barghouty, Abdulnasser F.; Khazanov, Igor; Moore, Ron

2011-01-01

We have developed a space-weather forecasting tool using an active-region free-energy proxy that was measured from MDI line-of-sight magnetograms. To develop this forecasting tool (Falconer et al 2011, Space Weather Journal, in press), we used a database of 40,000 MDI magnetograms of 1300 active regions observed by MDI during the previous solar cycle (cycle 23). From each magnetogram we measured our free-energy proxy and for each active region we determined its history of major flare, CME and Solar Particle Event (SPE) production. This database determines from the value of an active region s free-energy proxy the active region s expected rate of production of 1) major flares, 2) CMEs, 3) fast CMEs, and 4) SPEs during the next few days. This tool was delivered to NASA/SRAG in 2010. With MDI observations ending, we have to be able to use HMI magnetograms instead of MDI magnetograms. One of the difficulties is that the measured value of the free-energy proxy is sensitive to the spatial resolution of the measured magnetogram: the 0.5 /pixel resolution of HMI gives a different value for the free-energy proxy than the 2 /pixels resolution of MDI. To use our MDI-database forecasting curves until a comparably large HMI database is accumulated, we smooth HMI line-of-sight magnetograms to MDI resolution, so that we can use HMI to find the value of the free-energy proxy that MDI would have measured, and then use the forecasting curves given by the MDI database. The new version for use with HMI magnetograms was delivered to NASA/SRAG (March 2011). It can also use GONG magnetograms, as a backup.

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".

Improving Large-scale Biomass Burning Carbon Consumption and Emissions Estimates in the Former Soviet Union based on Fire Weather

NASA Astrophysics Data System (ADS)

Westberg, D. J.; Soja, A. J.; Tchebakova, N.; Parfenova, E. I.; Kukavskaya, E.; de Groot, B.; McRae, D.; Conard, S. G.; Stackhouse, P. W., Jr.

2012-12-01

Estimating the amount of biomass burned during fire events is challenging, particularly in remote and diverse regions, like those of the Former Soviet Union (FSU). Historically, we have typically assumed 25 tons of carbon per hectare (tC/ha) is emitted, however depending on the ecosystem and severity, biomass burning emissions can range from 2 to 75 tC/ha. Ecosystems in the FSU span from the tundra through the taiga to the forest-steppe, steppe and desserts and include the extensive West Siberian lowlands, permafrost-lain forests and agricultural lands. Excluding this landscape disparity results in inaccurate emissions estimates and incorrect assumptions in the transport of these emissions. In this work, we present emissions based on a hybrid ecosystem map and explicit estimates of fuel that consider the depth of burning based on the Canadian Forest Fire Weather Index System. Specifically, the ecosystem map is a fusion of satellite-based data, a detailed ecosystem map and Alexeyev and Birdsey carbon storage data, which is used to build carbon databases that include the forest overstory and understory, litter, peatlands and soil organic material for the FSU. We provide a range of potential carbon consumption estimates for low- to high-severity fires across the FSU that can be used with fire weather indices to more accurately estimate fire emissions. These data can be incorporated at ecoregion and administrative territory scales and are optimized for use in large-scale Chemical Transport Models. Additionally, paired with future climate scenarios and ecoregion cover, these carbon consumption data can be used to estimate potential emissions.

Aurorasaurus Database of Real-Time, Soft-Sensor Sourced Aurora Data for Space Weather Research

NASA Astrophysics Data System (ADS)

Kosar, B.; MacDonald, E.; Heavner, M.

2017-12-01

Aurorasaurus is an innovative citizen science project focused on two fundamental objectives i.e., collecting real-time, ground-based signals of auroral visibility from citizen scientists (soft-sensors) and incorporating this new type of data into scientific investigations pertaining to aurora. The project has been live since the Fall of 2014, and as of Summer 2017, the database compiled approximately 12,000 observations (5295 direct reports and 6413 verified tweets). In this presentation, we will focus on demonstrating the utility of this robust science quality data for space weather research needs. These data scale with the size of the event and are well-suited to capture the largest, rarest events. Emerging state-of-the-art computational methods based on statistical inference such as machine learning frameworks and data-model integration methods can offer new insights that could potentially lead to better real-time assessment and space weather prediction when citizen science data are combined with traditional sources.

Evaluation of several finishes on severely weathered wood

Treesearch

R. Sam Williams; Peter Sotos; William Feist

1999-01-01

Alkyd-, oil-modified-latex-, and latex-based finishes were applied to severely weathered western redcedar and redwood boards that did not have any surface treatment to ameliorate the weathered surface prior to painting. Six finishes were evaluated annually for 11 years for cracking, flaking, erosion, mildew growth, discoloration, and general appearance. Low-solids-...

Constructing Data Albums for Significant Severe Weather Events

NASA Technical Reports Server (NTRS)

Greene, Ethan; Zavodsky, Bradley; Ramachandran, Rahul; Kulkarni, Ajinkya; Li, Xiang; Bakare, Rohan; Basyal, Sabin; Conover, Helen

2014-01-01

Data Albums provide a one-stop-shop combining datasets from NASA, NWS, online new sources, and social media. Data Albums will help meteorologists better understand severe weather events to improve predictive models. Developed a new ontology for severe weather based off current hurricane Data Album and selected relevant NASA datasets for inclusion.

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).

The effect of age and gender on motor vehicle driver injury severity at highway-rail grade crossings in the United States.

PubMed

Hao, Wei; Kamga, Camille; Daniel, Janice

2015-12-01

Based on the Federal Railway Administration (FRA) database, there were 25,945 highway-rail crossing accidents in the United States between 2002 and 2011. With an extensive database of highway-rail grade crossing accidents in the United States from 2002 to 2011, estimation results showed that there were substantial differences across age/gender groups for driver's injury severity. The study applied an ordered probit model to explore the determinants of driver injury severity for motor vehicle drivers at highway-rail grade crossings. The analysis found that there are important behavioral and physical differences between male and female drivers given a highway-rail grade crossing accident happened. Older drivers have higher fatality probabilities when driving in open space under passive control especially during bad weather condition. Younger male drivers are found to be more likely to have severe injuries at rush hour with high vehicle speed passing unpaved highway-rail grade crossings under passive control. Synthesizing these results led to the conclusion that the primary problem with young is risk-taking and lack of vehicle handling skills. The strength of older drivers lies in their aversion to risk, but physical degradation issues which result in longer reaction/perception times and degradation in vision and hearing often counterbalance this attribute. Copyright © 2015 Elsevier Ltd and National Safety Council. All rights reserved.

Damage to southern Michigan conifers during the winter of 1976-77

Treesearch

Jonathan W. Wright; Donald DeHayes; Walter A. Lemmien

1977-01-01

In southern Michigan, the winter of 1976-1977 was marked by unseasonably cold weather in early December, prolonged cold weather in December and January, severe drought at the onset of cold weather, and by higher than average absolute minimum temperatures. Damage, presumably from the early December cold weather, was severe to southern seedlots of ponderosa pine,...

Hail statistic in Western Europe based on a hyrid cell-tracking algorithm combining radar signals with hailstone observations

NASA Astrophysics Data System (ADS)

Fluck, Elody

2015-04-01

Hail statistic in Western Europe based on a hybrid cell-tracking algorithm combining radar signals with hailstone observations Elody Fluck¹, Michael Kunz¹ , Peter Geissbühler², Stefan P. Ritz² With hail damage estimated over Billions of Euros for a single event (e.g., hailstorm Andreas on 27/28 July 2013), hail constitute one of the major atmospheric risks in various parts of Europe. The project HAMLET (Hail Model for Europe) in cooperation with the insurance company Tokio Millennium Re aims at estimating hail probability, hail hazard and, combined with vulnerability, hail risk for several European countries (Germany, Switzerland, France, Netherlands, Austria, Belgium and Luxembourg). Hail signals are obtained from radar reflectivity since this proxy is available with a high temporal and spatial resolution using several hail proxies, especially radar data. The focus in the first step is on Germany and France for the periods 2005- 2013 and 1999 - 2013, respectively. In the next step, the methods will be transferred and extended to other regions. A cell-tracking algorithm TRACE2D was adjusted and applied to two dimensional radar reflectivity data from different radars operated by European weather services such as German weather service (DWD) and French weather service (Météo-France). Strong convective cells are detected by considering 3 connected pixels over 45 dBZ (Reflectivity Cores RCs) in a radar scan. Afterwards, the algorithm tries to find the same RCs in the next 5 minute radar scan and, thus, track the RCs centers over time and space. Additional information about hailstone diameters provided by ESWD (European Severe Weather Database) is used to determine hail intensity of the detected hail swaths. Maximum hailstone diameters are interpolated along and close to the individual hail tracks giving an estimation of mean diameters for the detected hail swaths. Furthermore, a stochastic event set is created by randomizing the parameters obtained from the tracking approach of the historical event catalogue (length, width, orientation, diameter). This stochastic event set will be used to quantify hail risk and to estimate probable maximum loss (e.g., PML200) for a given industry motor or property (building) portfolio.

Evaluation of Hydrometeor Classification for Winter Mixed-Phase Precipitation Events

NASA Astrophysics Data System (ADS)

Hickman, B.; Troemel, S.; Ryzhkov, A.; Simmer, C.

2016-12-01

Hydrometeor classification algorithms (HCL) typically discriminate radar echoes into several classes including rain (light, medium, heavy), hail, dry snow, wet snow, ice crystals, graupel and rain-hail mixtures. Despite the strength of HCL for precipitation dominated by a single phase - especially warm-season classification - shortcomings exist for mixed-phase precipitation classification. Properly identifying mixed-phase can lead to more accurate precipitation estimates, and better forecasts for aviation weather and ground warnings. Cold season precipitation classification is also highly important due to their potentially high impact on society (e.g. black ice, ice accumulation, snow loads), but due to the varying nature of the hydrometeor - density, dielectric constant, shape - reliable classification via radar alone is not capable. With the addition of thermodynamic information of the atmosphere, either from weather models or sounding data, it has been possible to extend more and more into winter time precipitation events. Yet, inaccuracies still exist in separating more benign (ice pellets) from more the more hazardous (freezing rain) events. We have investigated winter mixed-phase precipitation cases which include freezing rain, ice pellets, and rain-snow transitions from several events in Germany in order to move towards a reliable nowcasting of winter precipitation in hopes to provide faster, more accurate winter time warnings. All events have been confirmed to have the specified precipitation from ground reports. Classification of the events is achieved via a combination of inputs from a bulk microphysics numerical weather prediction model and the German dual-polarimetric C-band radar network, into a 1D spectral bin microphysical model (SBC) which explicitly treats the processes of melting, refreezing, and ice nucleation to predict four near-surface precipitation types: rain, snow, freezing rain, ice pellets, rain/snow mixture, and freezing rain/pellet mixture. Evaluation of the classification is performed by means of disdrometer data, in-situ ground observations, and eye-witness reports from the European Severe Weather Database (ESWD). Additionally, a comparison to an existing radar based HCL is performed as a sanity check and a performance evaluator.

Comparison Between GOES-12 Overshooting-Top Detections, WSR-88D Radar Reflectivity, and Severe Storm Reports

NASA Technical Reports Server (NTRS)

Dworak, Richard; Bedka, Kristopher; Brunner, Jason; Feltz, Wayne

2012-01-01

Studies have found that convective storms with overshooting-top (OT) signatures in weather satellite imagery are often associated with hazardous weather, such as heavy rainfall, tornadoes, damaging winds, and large hail. An objective satellite-based OT detection product has been developed using 11-micrometer infrared window (IRW) channel brightness temperatures (BTs) for the upcoming R series of the Geostationary Operational Environmental Satellite (GOES-R) Advanced Baseline Imager. In this study, this method is applied to GOES-12 IRW data and the OT detections are compared with radar data, severe storm reports, and severe weather warnings over the eastern United States. The goals of this study are to 1) improve forecaster understanding of satellite OT signatures relative to commonly available radar products, 2) assess OT detection product accuracy, and 3) evaluate the utility of an OT detection product for diagnosing hazardous convective storms. The coevolution of radar-derived products and satellite OT signatures indicates that an OT often corresponds with the highest radar echo top and reflectivity maximum aloft. Validation of OT detections relative to composite reflectivity indicates an algorithm false-alarm ratio of 16%, with OTs within the coldest IRW BT range (less than 200 K) being the most accurate. A significant IRW BT minimum typically present with an OT is more often associated with heavy precipitation than a region with a spatially uniform BT. Severe weather was often associated with OT detections during the warm season (April September) and over the southern United States. The severe weather to OT relationship increased by 15% when GOES operated in rapid-scan mode, showing the importance of high temporal resolution for observing and detecting rapidly evolving cloud-top features. Comparison of the earliest OT detection associated with a severe weather report showed that 75% of the cases occur before severe weather and that 42% of collocated severe weather reports had either an OT detected before a severe weather warning or no warning issued at all. The relationships between satellite OT signatures, severe weather, and heavy rainfall shown in this paper suggest that 1) when an OT is detected, the particular storm is likely producing heavy rainfall and/or possibly severe weather; 2) an objective OT detection product can be used to increase situational awareness and forecaster confidence that a given storm is severe; and 3) this product may be particularly useful in regions with insufficient radar coverage.

A study of the connection between TV meteorologists and their viewers during severe weather broadcasts

NASA Astrophysics Data System (ADS)

Ebner, Daniel M.

After the devastating tornadoes in Joplin, MO and in the Deep South in 2011, it seemed appropriate to look at the impact that broadcast meteorologists (and their TV coverage) have on their viewers during severe weather events. Broadcast meteorologists play a vital role in the severe weather warning process and in persuading the public to take the appropriate actions during severe weather. This research was done by developing a survey that addressed the following questions: 1) Is the media doing everything they can persuade viewers to take shelter and protect themselves and their property?; 2) What do you do when a tornado warning is issued?; 3) Is there anything broadcast meteorologists can do or say that will make you take immediate action during severe weather? The survey was disseminated through television markets in Missouri. The goal of this research was to find new, improved and different ways of "connecting" with viewing during severe weather coverage. After looking at the results, we want to see if there are specific words, images or anything else a broadcaster can do that will trigger a response by viewers to take cover. It is my hope the results and analyses from this survey will provide broadcast meteorologists with new and improved techniques to connect with the public and to assist them in making an informed decision during severe weather events.

The weather diaries of a hunting and fishing estate in Connemara, Co. Galway, Ireland from 1898 to 1972

NASA Astrophysics Data System (ADS)

Hickey, Kieran

2017-04-01

A game diary from 1898-1917, fishing diary from 1899-1951 and daily work and weather diaries from 1933 -1972 have survived from the Fermoyle Lodge estate, Connemara, Co. Galway, Ireland. The diaries come from three generations of the Spellman family who retained their role as estate managers despite a number of changes in ownership over this time period. Using the information preserved in these volumes this paper will reconstruct the role of weather in the daily activities of this hunting and fishing estate. Severe weather generally only limited the numbers of days when hunting took place. In the case of fishing again severe weather could limit the number of days of fishing, however flood waters on the streams from the various small lakes on the estate improved fish runs during the spawning season which led to much improved fishing on the lakes. In addition different lakes were fished depending on the wind direction. The weather and especially severe weather played an important role in the general operation of the estate and the lives of the estate manager's family. This was especially true of severe weather, whether storms, flooding or cold in this relatively isolated location e.g. the cold spell of 1947 which is captured in the weather diaries.

Method for detecting and avoiding flight hazards

NASA Astrophysics Data System (ADS)

von Viebahn, Harro; Schiefele, Jens

1997-06-01

Today's aircraft equipment comprise several independent warning and hazard avoidance systems like GPWS, TCAS or weather radar. It is the pilot's task to monitor all these systems and take the appropriate action in case of an emerging hazardous situation. The developed method for detecting and avoiding flight hazards combines all potential external threats for an aircraft into a single system. It is based on an aircraft surrounding airspace model consisting of discrete volume elements. For each element of the volume the threat probability is derived or computed from sensor output, databases, or information provided via datalink. The position of the own aircraft is predicted by utilizing a probability distribution. This approach ensures that all potential positions of the aircraft within the near future are considered while weighting the most likely flight path. A conflict detection algorithm initiates an alarm in case the threat probability exceeds a threshold. An escape manoeuvre is generated taking into account all potential hazards in the vicinity, not only the one which caused the alarm. The pilot gets a visual information about the type, the locating, and severeness o the threat. The algorithm was implemented and tested in a flight simulator environment. The current version comprises traffic, terrain and obstacle hazards avoidance functions. Its general formulation allows an easy integration of e.g. weather information or airspace restrictions.

Food Price Volatility and Decadal Climate Variability

NASA Astrophysics Data System (ADS)

Brown, M. E.

2013-12-01

The agriculture system is under pressure to increase production every year as global population expands and more people move from a diet mostly made up of grains, to one with more meat, dairy and processed foods. Weather shocks and large changes in international commodity prices in the last decade have increased pressure on local food prices. This paper will review several studies that link climate variability as measured with satellite remote sensing to food price dynamics in 36 developing countries where local monthly food price data is available. The focus of the research is to understand how weather and climate, as measured by variations in the growing season using satellite remote sensing, has affected agricultural production, food prices and access to food in agricultural societies. Economies are vulnerable to extreme weather at multiple levels. Subsistence small holders who hold livestock and consume much of the food they produce are vulnerable to food production variability. The broader society, however, is also vulnerable to extreme weather because of the secondary effects on market functioning, resource availability, and large-scale impacts on employment in trading, trucking and wage labor that are caused by weather-related shocks. Food price variability captures many of these broad impacts and can be used to diagnose weather-related vulnerability across multiple sectors. The paper will trace these connections using market-level data and analysis. The context of the analysis is the humanitarian aid community, using the guidance of the USAID Famine Early Warning Systems Network and the United Nation's World Food Program in their response to food security crises. These organizations have worked over the past three decades to provide baseline information on food production through satellite remote sensing data and agricultural yield models, as well as assessments of food access through a food price database. Econometric models and spatial analysis are used to describe the connection between shocks and food prices, and to demonstrate the importance of these metrics in overall outcomes in food-insecure communities.

Forest fires and lightning activity during the outstanding 2003 and 2005 fire seasons

NASA Astrophysics Data System (ADS)

Russo, Ana; Ramos, Alexandre; Trigo, Ricardo

2013-04-01

Wildfires in southern Europe cause frequent extensive economical and ecological losses and, even human casualties. Comparatively to other Mediterranean countries, Portugal is the country with more burnt area and fires per unit area in the last decade, mainly during the summer season (Pereira et al., 2011). According to the fire records available, between 1980 and 2009, wildfires have affected over 3 million hectares in Portugal (JRC, 2011), which corresponds to approximately a third of the Portuguese Continental territory. The main factors that influence fire ignition and propagation are: (1) the presence of fuel (i.e. vegetation); (2) climate and weather; (3) socioeconomic conditions that affect land use/land cover patterns, fire-prevention and fire-fighting capacity and (4) topography. Specifically, weather (e.g. wind, temperature, precipitation, humidity, and lightning occurrence) plays an important role in fire behavior, affecting both ignition and spread of wildfires. Some countries have a relatively large fraction of fires caused by lightning, e.g. northwestern USA, Canada, Russia (). In contrast, Portugal has only a small percentage of fire records caused by lightning. Although significant doubts remain for the majority of fires in the catalog since they were cataloged without a likely cause. The recent years of 2003 and 2005 were particularly outstanding for fire activity in Portugal, registering, respectively, total burned areas of 425 726 ha and 338 262 ha. However, while the 2003 was triggered by an exceptional heatwave that struck the entire western Europe, the 2005 fire season registered was coincident with one of the most severe droughts of the 20th century. In this work we have used mainly two different databases: 1) the Portuguese Rural Fire Database (PRFD) which is representative of rural fires that have occurred in Continental Portugal, 2001-2011, with the original data provided by the Autoridade Florestal Nacional (AFN, 2011); 2) lightning discharges location which were extracted from the Portuguese Lightning Location System that has been in service since June of 2002 and is operated by the national weather service - Instituto de Meteorologia (IM). The main objective of this work is to analyze for possible relations between the PRFD and the Portuguese lightning database for the 2003 and 2005 extreme fire seasons. In particularly we were able to verify the forest fires labeled as "ignited by lightning" by comparing its location to the lightning discharges location database. Furthermore we have also investigated possible fire ignition by lightning discharges that have not yet been labeled in the PRFD by comparing daily data from both datasets.

Investigating Mesoscale Convective Systems and their Predictability Using Machine Learning

NASA Astrophysics Data System (ADS)

Daher, H.; Duffy, D.; Bowen, M. K.

2016-12-01

A mesoscale convective system (MCS) is a thunderstorm region that lasts several hours long and forms near weather fronts and can often develop into tornadoes. Here we seek to answer the question of whether these tornadoes are "predictable" by looking for a defining characteristic(s) separating MCSs that evolve into tornadoes versus those that do not. Using NASA's Modern Era Retrospective-analysis for Research and Applications 2 reanalysis data (M2R12K), we apply several state of the art machine learning techniques to investigate this question. The spatial region examined in this experiment is Tornado Alley in the United States over the peak tornado months. A database containing select variables from M2R12K is created using PostgreSQL. This database is then analyzed using machine learning methods such as Symbolic Aggregate approXimation (SAX) and DBSCAN (an unsupervised density-based data clustering algorithm). The incentive behind using these methods is to mathematically define a MCS so that association rule mining techniques can be used to uncover some sort of signal or teleconnection that will help us forecast which MCSs will result in tornadoes and therefore give society more time to prepare and in turn reduce casualties and destruction.

NASA Cold Land Processes Experiment (CLPX 2002/03): Ground-based and near-surface meteorological observations

Treesearch

Kelly Elder; Don Cline; Angus Goodbody; Paul Houser; Glen E. Liston; Larry Mahrt; Nick Rutter

2009-01-01

A short-term meteorological database has been developed for the Cold Land Processes Experiment (CLPX). This database includes meteorological observations from stations designed and deployed exclusively for CLPXas well as observations available from other sources located in the small regional study area (SRSA) in north-central Colorado. The measured weather parameters...

The Behavior of Total Lightning Activity in Severe Florida Thunderstorms

NASA Technical Reports Server (NTRS)

Williams, Earle; Boldi, Bob; Matlin, Anne; Weber, Mark; Hodanish, Steve; Sharp, Dave; Goodman, Steve; Raghavan, Ravi; Buechler, Dennis

1998-01-01

The development of a new observational system called LISDAD (Lightning Imaging Sensor Demonstration and Display) has enabled a study of severe weather in central Florida. The total flash rates for storms verified to be severe are found to exceed 60 flashes/min, with some values reaching 500 flashes/min. Similar to earlier results for thunderstorm microbursts, the peak flash rate precedes the severe weather at the ground by 5-20 minutes. A distinguishing feature of severe storms is the presence of lightning "jumps"-abrupt increases in flash rate in advance of the maximum rate for the storm. ne systematic total lightning precursor to severe weather of all kinds-wind, hail, tornadoes-is interpreted in terms of the updraft that sows the seeds aloft for severe weather at the surface and simultaneously stimulates the ice microphysics that drives the lightning activity.

Terrestrial Sediments of the Earth: Development of a Global Unconsolidated Sediments Map Database (GUM)

NASA Astrophysics Data System (ADS)

Börker, J.; Hartmann, J.; Amann, T.; Romero-Mujalli, G.

2018-04-01

Mapped unconsolidated sediments cover half of the global land surface. They are of considerable importance for many Earth surface processes like weathering, hydrological fluxes or biogeochemical cycles. Ignoring their characteristics or spatial extent may lead to misinterpretations in Earth System studies. Therefore, a new Global Unconsolidated Sediments Map database (GUM) was compiled, using regional maps specifically representing unconsolidated and quaternary sediments. The new GUM database provides insights into the regional distribution of unconsolidated sediments and their properties. The GUM comprises 911,551 polygons and describes not only sediment types and subtypes, but also parameters like grain size, mineralogy, age and thickness where available. Previous global lithological maps or databases lacked detail for reported unconsolidated sediment areas or missed large areas, and reported a global coverage of 25 to 30%, considering the ice-free land area. Here, alluvial sediments cover about 23% of the mapped total ice-free area, followed by aeolian sediments (˜21%), glacial sediments (˜20%), and colluvial sediments (˜16%). A specific focus during the creation of the database was on the distribution of loess deposits, since loess is highly reactive and relevant to understand geochemical cycles related to dust deposition and weathering processes. An additional layer compiling pyroclastic sediment is added, which merges consolidated and unconsolidated pyroclastic sediments. The compilation shows latitudinal abundances of sediment types related to climate of the past. The GUM database is available at the PANGAEA database (https://doi.org/10.1594/PANGAEA.884822).

14 CFR 135.293 - Initial and recurrent pilot testing requirements.

Code of Federal Regulations, 2011 CFR

2011-01-01

..., high altitude weather; (7) Procedures for— (i) Recognizing and avoiding severe weather situations; (ii) Escaping from severe weather situations, in case of inadvertent encounters, including low-altitude windshear (except that rotorcraft pilots are not required to be tested on escaping from low-altitude...

14 CFR 135.293 - Initial and recurrent pilot testing requirements.

Code of Federal Regulations, 2010 CFR

2010-01-01

..., high altitude weather; (7) Procedures for— (i) Recognizing and avoiding severe weather situations; (ii) Escaping from severe weather situations, in case of inadvertent encounters, including low-altitude windshear (except that rotorcraft pilots are not required to be tested on escaping from low-altitude...

Locations Where Space Weather Energy Impacts the Atmosphere

NASA Astrophysics Data System (ADS)

Sojka, Jan J.

2017-11-01

In this review we consider aspects of space weather that can have a severe impact on the terrestrial atmosphere. We begin by identifying the pre-conditioning role of the Sun on the temperature and density of the upper atmosphere. This effect we define as "space climatology". Space weather effects are then defined as severe departures from this state of the atmospheric energy and density. Three specific forms of space weather are reviewed and we show that each generates severe space weather impacts. The three forms of space weather being considered are the solar photon flux (flares), particle precipitation (aurora), and electromagnetic Joule heating (magnetosphere-ionospheric (M-I) coupling). We provide an overview of the physical processes associated with each of these space weather forms. In each case a very specific altitude range exists over which the processes can most effectively impact the atmosphere. Our argument is that a severe change in the local atmosphere's state leads to atmospheric heating and other dynamic changes at locations beyond the input heat source region. All three space weather forms have their greatest atmospheric impact between 100 and 130 km. This altitude region comprises the transition between the atmosphere's mesosphere and thermosphere and is the ionosphere's E-region. This region is commonly referred to as the Space Atmosphere Interaction Region (SAIR). The SAIR also acts to insulate the lower atmosphere from the space weather impact of energy deposition. A similar space weather zone would be present in atmospheres of other planets and exoplanets.

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.

Extended Edited Synoptic Cloud Reports from Ships and Land Stations Over the Globe, 1952-2009 (NDP-026C)

DOE Data Explorer

Hahn, C. J. [University of Arizona; Warren, S. G. [University of Washington; Eastman, R.

1999-08-01

This database contains surface synoptic weather reports for the entire globe, gathered from various available data sets. The reports were processed, edited, and rewritten to provide a single dataset of individual observations of clouds, spanning the 57 years 1952-2008 for ship data and the 39 years 1971-2009 for land station data. In addition to the cloud portion of the synoptic report, each edited report also includes the associated pressure, present weather, wind, air temperature, and dew point (and sea surface temperature over oceans). This data set is called the "Extended Edited Cloud Report Archive" (EECRA). The EECRA is based solely on visual cloud observations from weather stations, reported in the WMO synoptic code (WMO, 1974). Reports must contain cloud-type information to be included in the archive. Past data sources include those from the Fleet Numerical Oceanographic Center (FNOC, 1971-1976) and the National Centers for Environmental Prediction (NCEP, 1977-1996). This update uses data from a new source, the 'Integrated Surface Database' (ISD, 1997-2009; Smith et al., 2011). Our past analyses of the EECRA identified a subset of 5388 weather stations that were determined to produce reliable day and night observations of cloud amount and type. The update contains observations only from this subset of stations. Details concerning processing, previous problems, contents, and comments are available in the archive's original documentation . The EECRA contains about 81 million cloud observations from ships and 380 million from land stations. The data files have been compressed using unix. Unix/linux users can "uncompress" or "gunzip" the files after downloading. If you're interested in the NDP-026C database, then you'll also want to explore its related data products, NDP-026D and NDP-026E.

Forest fire weather in western Oregon and western Washington in 1957.

Treesearch

Owen P. Cramer

1957-01-01

Severity of 1957 fire weather west of the Cascade Range summit in Oregon and Washington was near the average of the previous 10 years. The season (April 1 through October 31) was slightly more severe than 1956 in western Oregon and about the same as 1956 in western Washington. Spring fire weather was near average severity in both western Washington and western Oregon....

Observation of severe weather activities by Doppler sounder array

NASA Technical Reports Server (NTRS)

Smith, R. E.; Hung, R. J.

1975-01-01

A three-dimensional, nine-element, high-frequency CW Doppler sounder array has been used to detect ionospheric disturbances during periods of severe weather, particularly during periods with severe thunderstorms and tornadoes. One typical disturbance recorded during a period of severe thunderstorm activity and one during a period of tornado activity have been chosen for analysis in this note. The observations indicate that wave-like disturbances possibly generated by the severe weather have wave periods in the range 2-8 min which place them in the infrasonic wave category.

The Early Years: Navigating Natural Disasters

ERIC Educational Resources Information Center

Ashbrook, Peggy

2016-01-01

Keeping track of the weather is especially important in communities where severe weather endangers property and lives. Science education may mean talking with children about scary or tragic events. Although teachers should not avoid teaching about severe weather events, they can be sensitive to students' fears and stress by first asking families…

COSMIC Payload in NCAR-NASPO GPS Satellite System for Severe Weather Prediction

NASA Astrophysics Data System (ADS)

Lai-Chen, C.

Severe weather, such as cyclones, heavy rainfall, outburst of cold air, etc., results in great disaster all the world. It is the mission for the scientists to design a warning system, to predict the severe weather systems and to reduce the damage of the society. In Taiwan, National Satellite Project Office (NSPO) initiated ROCSAT-3 program at 1997. She scheduled the Phase I conceptual design to determine the mission for observation weather system. Cooperating with National Center of Atmospheric Research (NCAR), NSPO involved an international cooperation research and operation program to build a 32 GPS satellites system. NCAR will offer 24 GPS satellites. The total expanse will be US 100 millions. NSPO also provide US 80 millions for launching and system engineering operation. And NCAR will be responsible for Payload Control Center and Fiducial Network. The cooperative program contract has been signed by Taiwan National Science Council, Taipei Economic Cultural Office of United States and American Institute in Taiwan. One of the payload is COSMIC, Constellation Observation System for Meteorology, Ionosphere and Climate. It is a GPS meteorology instrument system. The system will observe the weather information, e. g. electron density profiles, horizontal and vertical TEC and CFT scintillation and communication outage maps. The mission is to obtain the weather data such as vertical temperature profiles, water vapor distribution and pressure distribution over the world for global weather forecasting, especially during the severe weather period. The COSMIC Conference held on November, 1998. The export license was also issued by Department of Commerce of Unites States at November, 1998. Recently, NSPO begun to train their scientists to investigate the system. Scientists simulate the observation data to combine the existing routine satellite infrared cloud maps, radar echo and synoptic weather analysis for severe weather forecasting. It is hopeful to provide more accurate weather analysis for forecasting and decreasing the damage of the disasters over the area concerned.

Lightning fatalities and injuries in Turkey

NASA Astrophysics Data System (ADS)

Tilev-Tanriover, Ş.; Kahraman, A.; Kadioğlu, M.; Schultz, D. M.

2015-08-01

A database of lightning-related fatalities and injuries in Turkey was constructed by collecting data from the Turkish State Meteorological Service, newspaper archives, European Severe Weather Database, and the internet. The database covers January 1930 to June 2014. In total, 742 lightning incidents causing human fatalities and injuries were found. Within these 742 incidents, there were 895 fatalities, 149 serious injuries, and 535 other injuries. Most of the incidents (89 %) occurred during April through September, with a peak in May and June (26 and 28 %) followed by July (14 %). Lightning-related fatalities and injuries were most frequent in the afternoon. Most of the incidents (86 %) occurred in rural areas, with only 14 % in the urban areas. Approximately, two thirds of the victims with known gender were male. Because of the unrepresentativeness of the historical data, determining an average mortality rate over a long period is not possible. Nevertheless, there were 31 fatalities (0.42 per million) in 2012, 26 fatalities (0.35 per million) in 2013, and 25 fatalities (0.34 per million) in 2014 (as of June). There were 36 injuries (0.49 per million) in each of 2012 and 2013, and 62 injuries (0.84 per million) in 2014 (as of June).

Lightning fatalities and injuries in Turkey

NASA Astrophysics Data System (ADS)

Tilev-Tanriover, Ş.; Kahraman, A.; Kadioğlu, M.; Schultz, D. M.

2015-03-01

A database of lightning-related fatalities and injuries in Turkey was constructed by collecting data from the Turkish State Meteorological Service, newspaper archives, European Severe Weather Database, and the internet. The database covers January 1930 to June 2014. In total, 742 lightning incidents causing human fatalities and injuries were found. Within these 742 incidents, there were 895 fatalities, 149 serious injuries, and 535 other injuries. Most of the incidents (89%) occurred during April through September, with a peak in May and June (26 and 28 %) followed by July (14%). Lightning-related fatalities and injuries were most frequent in the afternoon. Most of the incidents (86%) occurred in the rural areas, with only 14% in the urban areas. Approximately, two thirds of the victims with known gender were male. Because of the unrepresentativeness of the historical data, determining an average mortality rate over a long period is not possible. Nevertheless, there were 31 fatalities (0.42 per million) in 2012, 26 fatalities (0.35 per million) in 2013, and 25 fatalities (0.34 per million) in 2014 (as of June). There were 36 injuries (0.49 per million) in each of 2012 and 2013, and 62 injuries (0.84 per million) in 2014 (as of June).

An improved database of coastal flooding in the United Kingdom from 1915 to 2016

PubMed Central

Haigh, Ivan D.; Ozsoy, Ozgun; Wadey, Matthew P.; Nicholls, Robert J.; Gallop, Shari L.; Wahl, Thomas; Brown, Jennifer M.

2017-01-01

Coastal flooding caused by extreme sea levels can produce devastating and wide-ranging consequences. The ‘SurgeWatch’ v1.0 database systematically documents and assesses the consequences of historical coastal flood events around the UK. The original database was inevitably biased due to the inconsistent spatial and temporal coverage of sea-level observations utilised. Therefore, we present an improved version integrating a variety of ‘soft’ data such as journal papers, newspapers, weather reports, and social media. SurgeWatch2.0 identifies 329 coastal flooding events from 1915 to 2016, a more than fivefold increase compared to the 59 events in v1.0. Moreover, each flood event is now ranked using a multi-level categorisation based on inundation, transport disruption, costs, and fatalities: from 1 (Nuisance) to 6 (Disaster). For the 53 most severe events ranked Category 3 and above, an accompanying event description based upon the Source-Pathway-Receptor-Consequence framework was produced. Thus, SurgeWatch v2.0 provides the most comprehensive and coherent historical record of UK coastal flooding. It is designed to be a resource for research, planning, management and education. PMID:28763054

Hydro-geomorphologic events in Portugal and its association with Circulation weather types

NASA Astrophysics Data System (ADS)

Pereira, Susana; Ramos, Alexandre M.; Rebelo, Luís; Trigo, Ricardo M.; Zêzere, José L.

2017-04-01

Floods and landslides correspond to the most hazardous weather driven natural disasters in Portugal. A recent improvement on their characterization has been achieved with the gathering of basic information on past floods and landslides that caused social consequences in Portugal for the period 1865-2015 through the DISASTER database (Zêzere et al., 2014). This database was built under the assumption that strong social impacts of floods and landslides are sufficient relevant to be reported consistently by national and regional newspapers. The DISASTER database contains detailed information on the location, date of occurrence and social impacts (fatalities, injuries, missing people, evacuated and homeless people) of each individual hydro-geomorphologic case (1677 flood cases and 292 landslide cases). These hydro-geomorphologic disaster cases are grouped in a restrict number of DISASTER events that were selected according to the following criteria: a set of at least 3 DISASTER cases sharing the same trigger in time (with no more than 3 days without cases), which have a widespread spatial extension related to the triggering mechanism and a certain magnitude. In total, the DISASTER database includes 134 events (3.7 average days of duration) that generated high social impacts in Portugal (962 fatalities and 40878 homeless people). Each DISASTER event was characterized with the following attributes: hydro-geomorphologic event type (e.g landslides, floods, flash floods, urban floods); date of occurrence (year, month and days); duration in days; spatial location in GIS; number of fatalities, injured, evacuated and homeless people; and weather type responsible for triggering the event. The atmospheric forcing at different time scales is the main trigger for the hydro-meteorological DISASTER events occurred in Portugal. In this regard there is an urge for a more systematic assessment of the weather types associated to flood and landslide damaging events to correctly characterize the climatic forcing of hydro-geomorphologic risk in Portugal. The weather type classification used herein is an automated version of the Lamb weather type procedure, initially developed for the United Kingdom and often named circulation weather types (CWT) and latter adapted for Portugal. We computed the daily CWT for the 1865-2015 period by means of the daily SLP retrieved from the 20 Century Reanalysis dataset. The relationship between the CWTs and the hydro-meteorological events in Portugal shows that the cyclonic, westerly and southwesterly are CWTs frequently associated with major socio-economic impacts of DISASTER events. In addition, CWT basic variables (flow strength, vorticity and direction) were used to better understand the impacts of the meteorological conditions in the hydro-meteorological events in Portugal. Reference: Zêzere, J. L., Pereira, S., Tavares, A. O., Bateira, C., Trigo, R. M., Quaresma, I., Santos, P. P., Santos, M. and Verde, J.: DISASTER: a GIS database on hydro-geomorphologic disasters in Portugal, Nat. Hazards, 72(2), 503-532, doi:10.1007/s11069-013-1018-y, 2014. This work was supported by the project FORLAND - Hydrogeomorphologic risk in Portugal: driving forces and application for land use planning [grant number PTDC/ATPGEO/1660/2014] funded by the Portuguese Foundation for Science and Technology (FCT), Portugal. A. M. Ramos was also supported by a FCT postdoctoral grant (FCT/DFRH/ SFRH/BPD/84328/2012).

Driver injury severity related to inclement weather at highway-rail grade crossings in the United States.

PubMed

Hao, Wei; Daniel, Janice

2016-01-01

Previous studies on crash modeling at highway-rail grade crossings were aimed at exploring the factors that are likely to increase the crash frequencies at highway-rail grade crossings. In recent years, modeling driver's injury severity at highway-rail grade crossings has received interest. Because there were substantial differences among different weather conditions for driver's injury severity, this study attempts to explore the impact of weather influence on driver injury at highway-rail grade crossing. Utilizing the most recent 10 years (2002-2011) of highway-rail grade crossing accident data, this study applied a mixed logit model to explore the determinants of driver injury severity under different weather conditions at highway-rail grade crossing. Analysis results indicate that drivers' injury severity at highway-rail grade crossings is strongly different for different weather conditions. It was found that the factors significantly impacting driver injury severity at highway-rail grade crossings include motor vehicle speed, train speed, driver's age, gender, area type, lighting condition, highway pavement, traffic volume, and time of day. The findings of this study indicate that crashes are more prevalent if vehicle drivers are driving at high speed or the oncoming trains are high speed. Hence, a reduction in speed limit during inclement weather conditions could be particularly effective in moderating injury severity, allowing more reaction time for last-minute maneuvering and braking in moments before impacts. In addition, inclement weather-related crashes were more likely to occur in open areas and highway-rail grade crossings without pavement and lighting. Paved highway-rail grade crossings with installation of lights could be particularly effective in moderating injury severity.

The efficacy of fuel treatment in mitigating property loss during wildfires: Insights from analysis of the severity of the catastrophic fires in 2009 in Victoria, Australia.

PubMed

Price, Owen F; Bradstock, Ross A

2012-12-30

Treatment of fuel (e.g. prescribed fire, logging) in fire-prone ecosystems is done to reduce risks to people and their property but effects require quantification, particularly under severe weather conditions when the destructive potential of fires on human infrastructure is maximised. We analysed the relative effects of fuel age (i.e. indicative of the effectiveness of prescribed fire) and logging on remotely sensed (SPOT imagery) severity of fires which occurred in eucalypt forests in Victoria, Australia in 2009. These fires burned under the most severe weather conditions recorded in Australia and caused large losses of life and property. Statistical models of the probability of contrasting extremes of severity (crown fire versus fire confined to the understorey) were developed based on effects of fuel age, logging, weather, topography and forest type. Weather was the primary influence on severity, though it was reduced at low fuel ages in Moderate but not Catastrophic, Very High or Low fire-weather conditions. Probability of crown fires was higher in recently logged areas than in areas logged decades before, indicating likely ineffectiveness as a fuel treatment. The results suggest that recently burnt areas (up to 5-10 years) may reduce the intensity of the fire but not sufficiently to increase the chance of effective suppression under severe weather conditions. Since house loss was most likely under these conditions (67%), effects of prescribed burning across landscapes on house loss are likely to be small when weather conditions are severe. Fuel treatments need to be located close to houses in order to effectively mitigate risk of loss. Copyright © 2012 Elsevier Ltd. All rights reserved.

A new open-source Python-based Space Weather data access, visualization, and analysis toolkit

NASA Astrophysics Data System (ADS)

de Larquier, S.; Ribeiro, A.; Frissell, N. A.; Spaleta, J.; Kunduri, B.; Thomas, E. G.; Ruohoniemi, J.; Baker, J. B.

2013-12-01

Space weather research relies heavily on combining and comparing data from multiple observational platforms. Current frameworks exist to aggregate some of the data sources, most based on file downloads via web or ftp interfaces. Empirical models are mostly fortran based and lack interfaces with more useful scripting languages. In an effort to improve data and model access, the SuperDARN community has been developing a Python-based Space Science Data Visualization Toolkit (DaViTpy). At the center of this development was a redesign of how our data (from 30 years of SuperDARN radars) was made available. Several access solutions are now wrapped into one convenient Python interface which probes local directories, a new remote NoSQL database, and an FTP server to retrieve the requested data based on availability. Motivated by the efficiency of this interface and the inherent need for data from multiple instruments, we implemented similar modules for other space science datasets (POES, OMNI, Kp, AE...), and also included fundamental empirical models with Python interfaces to enhance data analysis (IRI, HWM, MSIS...). All these modules and more are gathered in a single convenient toolkit, which is collaboratively developed and distributed using Github and continues to grow. While still in its early stages, we expect this toolkit will facilitate multi-instrument space weather research and improve scientific productivity.

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

NASA Astrophysics Data System (ADS)

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

2015-12-01

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

SPAGETTA, a Gridded Weather Generator: Calibration, Validation and its Use for Future Climate

NASA Astrophysics Data System (ADS)

Dubrovsky, Martin; Rotach, Mathias W.; Huth, Radan

2017-04-01

Spagetta is a new (started in 2016) stochastic multi-site multi-variate weather generator (WG). It can produce realistic synthetic daily (or monthly, or annual) weather series representing both present and future climate conditions at multiple sites (grids or stations irregularly distributed in space). The generator, whose model is based on the Wilks' (1999) multi-site extension of the parametric (Richardson's type) single site M&Rfi generator, may be run in two modes: In the first mode, it is run as a classical generator, which is calibrated in the first step using weather data from multiple sites, and only then it may produce arbitrarily long synthetic time series mimicking the spatial and temporal structure of the calibration weather data. To generate the weather series representing the future climate, the WG parameters are modified according to the climate change scenario, typically derived from GCM or RCM simulations. In the second mode, the user provides only basic information (not necessarily to be realistic) on the temporal and spatial auto-correlation structure of the surface weather variables and their mean annual cycle; the generator itself derives the parameters of the underlying autoregressive model, which produces the multi-site weather series. In the latter mode of operation, the user is allowed to prescribe the spatially varying trend, which is superimposed to the values produced by the generator; this feature has been implemented for use in developing the methodology for assessing significance of trends in multi-site weather series (for more details see another EGU-2017 contribution: Huth and Dubrovsky, 2017, Evaluating collective significance of climatic trends: A comparison of methods on synthetic data; EGU2017-4993). This contribution will focus on the first (classical) mode. The poster will present (a) model of the generator, (b) results of the validation tests made in terms of the spatial hot/cold/dry/wet spells, and (c) results of the pilot climate change impact experiment, in which (i) the WG parameters representing the spatial and temporal variability are modified using the climate change scenarios and then (ii) the effect on the above spatial validation indices derived from the synthetic series produced by the modified WG is analysed. In this experiment, the generator is calibrated using the E-OBS gridded daily weather data for several European regions, and the climate change scenarios are derived from the selected RCM simulation (taken from the CORDEX database).

Teaching through Trade Books: Forecasting Hazardous Conditions

ERIC Educational Resources Information Center

Royce, Christine Anne

2016-01-01

For students to know how to prepare for severe weather, they must first understand what types of weather they might experience in their location. Much of students' interactions with and learning about severe weather events will happen through printed text resources and video excerpts. Through the use of such resources, young students can begin to…

Assessing Individual Weather Risk-Taking and Its Role in Modeling Likelihood of Hurricane Evacuation

NASA Astrophysics Data System (ADS)

Stewart, A. E.

2017-12-01

This research focuses upon measuring an individual's level of perceived risk of different severe and extreme weather conditions using a new self-report measure, the Weather Risk-Taking Scale (WRTS). For 32 severe and extreme situations in which people could perform an unsafe behavior (e. g., remaining outside with lightning striking close by, driving over roadways covered with water, not evacuating ahead of an approaching hurricane, etc.), people rated: 1.their likelihood of performing the behavior, 2. The perceived risk of performing the behavior, 3. the expected benefits of performing the behavior, and 4. whether the behavior has actually been performed in the past. Initial development research with the measure using 246 undergraduate students examined its psychometric properties and found that it was internally consistent (Cronbach's a ranged from .87 to .93 for the four scales) and that the scales possessed good temporal (test-retest) reliability (r's ranged from .84 to .91). A second regression study involving 86 undergraduate students found that taking weather risks was associated with having taken similar risks in one's past and with the personality trait of sensation-seeking. Being more attentive to the weather and perceiving its risks when it became extreme was associated with lower likelihoods of taking weather risks (overall regression model, R2adj = 0.60). A third study involving 334 people examined the contributions of weather risk perceptions and risk-taking in modeling the self-reported likelihood of complying with a recommended evacuation ahead of a hurricane. Here, higher perceptions of hurricane risks and lower perceived benefits of risk-taking along with fear of severe weather and hurricane personal self-efficacy ratings were all statistically significant contributors to the likelihood of evacuating ahead of a hurricane. Psychological rootedness and attachment to one's home also tend to predict lack of evacuation. This research highlights the contributions that a psychological approach can offer in understanding preparations for severe weather. This approach also suggests that a great deal of individual variation exists in weather-protective behaviors, which may explain in part why some people take weather-related risks despite receiving warnings for severe weather.

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.

Estimation of daily reference evapotranspiration (ETo) using artificial intelligence methods: Offering a new approach for lagged ETo data-based modeling

NASA Astrophysics Data System (ADS)

Mehdizadeh, Saeid

2018-04-01

Evapotranspiration (ET) is considered as a key factor in hydrological and climatological studies, agricultural water management, irrigation scheduling, etc. It can be directly measured using lysimeters. Moreover, other methods such as empirical equations and artificial intelligence methods can be used to model ET. In the recent years, artificial intelligence methods have been widely utilized to estimate reference evapotranspiration (ETo). In the present study, local and external performances of multivariate adaptive regression splines (MARS) and gene expression programming (GEP) were assessed for estimating daily ETo. For this aim, daily weather data of six stations with different climates in Iran, namely Urmia and Tabriz (semi-arid), Isfahan and Shiraz (arid), Yazd and Zahedan (hyper-arid) were employed during 2000-2014. Two types of input patterns consisting of weather data-based and lagged ETo data-based scenarios were considered to develop the models. Four statistical indicators including root mean square error (RMSE), mean absolute error (MAE), coefficient of determination (R2), and mean absolute percentage error (MAPE) were used to check the accuracy of models. The local performance of models revealed that the MARS and GEP approaches have the capability to estimate daily ETo using the meteorological parameters and the lagged ETo data as inputs. Nevertheless, the MARS had the best performance in the weather data-based scenarios. On the other hand, considerable differences were not observed in the models' accuracy for the lagged ETo data-based scenarios. In the innovation of this study, novel hybrid models were proposed in the lagged ETo data-based scenarios through combination of MARS and GEP models with autoregressive conditional heteroscedasticity (ARCH) time series model. It was concluded that the proposed novel models named MARS-ARCH and GEP-ARCH improved the performance of ETo modeling compared to the single MARS and GEP. In addition, the external analysis of the performance of models at stations with similar climatic conditions denoted the applicability of nearby station' data for estimation of the daily ETo at target station.

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

NASA Technical Reports Server (NTRS)

2009-01-01

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

A Multiscale Analysis of Upstream Precursors associated with High Impact Severe Weather Events across the Upper Midwest

NASA Astrophysics Data System (ADS)

Metz, N. D.; Cordeira, J. M.

2014-12-01

Between 30 June and 1 July 2011, a heavy-rain-producing mesoscale convective system (MCS) occurred over Lake Michigan. A second MCS subsequently occurred over Minnesota, Iowa, and Wisconsin on 1 July 2011 resulting in more than 200 severe weather reports. The antecedent large-scale flow evolution was strongly influenced by early-season tropical cyclones (TCs) Haima and Meari in the western North Pacific. The recurvature and subsequent interaction of these TCs with the extratropical large-scale flow was associated with Rossby wave train (RWT) amplification on 22-26 June 2011 over the western North Pacific and dispersion across North America on 28-30 June 2011. The RWT dispersion was associated with trough (ridge) development over western (central) North America at the time of MCS development over the Midwestern United States. This evolution of the large-scale flow and attendant meso-synoptic scale forcing for ascent were particularly conducive to heavy rainfall and severe weather as a surface-based mixed layer over the Intermountain Western United States was advected eastward, transitioning to an elevated mixed layer (EML) over the Midwestern United States. These two MCSs serve as motivation for a climatology of EML days and their relationship to severe weather over the Midwestern United States. The climatology illustrates that severe weather reports near Minneapolis, MN during the summer are twice as numerous on EML days as compared to normal. The increase in severe weather reports are primarily driven by more large hail and severe wind, which account for 95% of all severe weather reports on EML days. A time-lagged composite analysis indicates that RWT amplification over the central North Pacific and RWT dispersion across the eastern North Pacific and North American, as occurred prior to the 30 June-1 July period, is a common upstream precursor to EML days over the Midwestern United States. These results suggest that investigations of far upstream precursors to RWT amplification and dispersion over the North Pacific may be particularly useful in better understanding warm-season severe weather outbreaks over North America.

77 FR 39647 - Fisheries of the Caribbean, Gulf of Mexico, and South Atlantic; Reef Fish Fishery of the Gulf of...

Federal Register 2010, 2011, 2012, 2013, 2014

2012-07-05

...., local time, July 11, 2012. However, due to severe weather conditions in the central and northeastern..., the central and northeastern Gulf experienced severe weather conditions during the first 26 days of... less than projected. In addition to tropical storm Debby in late June, poor weather conditions...

78 FR 17178 - Fisheries of the Caribbean, Gulf of Mexico, and South Atlantic; Shrimp Fishery Off the Southern...

Federal Register 2010, 2011, 2012, 2013, 2014

2013-03-20

... waters close as a result of severe winter weather. Amendment 9 would also revise the overfished and... has been severely depleted by cold weather. Based on information from standardized assessments, if a... changes to the current regulatory text within Sec. 622.35(d), ``South Atlantic shrimp cold weather closure...

76 FR 16698 - Fisheries of the Caribbean, Gulf of Mexico, and South Atlantic; Shrimp Fishery Off the Southern...

Federal Register 2010, 2011, 2012, 2013, 2014

2011-03-25

... severely depleted by unusually cold weather conditions. DATES: The closure is effective March 22, 2011... shrimp spawning stock that has been severely depleted by cold weather. Consistent with those procedures... time and would potentially further harm the spawning stock that has been impacted due to cold weather...

A new precipitation and drought climatology based on weather patterns.

PubMed

Richardson, Douglas; Fowler, Hayley J; Kilsby, Christopher G; Neal, Robert

2018-02-01

Weather-pattern, or weather-type, classifications are a valuable tool in many applications as they characterize the broad-scale atmospheric circulation over a given region. This study analyses the aspects of regional UK precipitation and meteorological drought climatology with respect to a new set of objectively defined weather patterns. These new patterns are currently being used by the Met Office in several probabilistic forecasting applications driven by ensemble forecasting systems. Weather pattern definitions and daily occurrences are mapped to Lamb weather types (LWTs), and parallels between the two classifications are drawn. Daily precipitation distributions are associated with each weather pattern and LWT. Standardized precipitation index (SPI) and drought severity index (DSI) series are calculated for a range of aggregation periods and seasons. Monthly weather-pattern frequency anomalies are calculated for SPI wet and dry periods and for the 5% most intense DSI-based drought months. The new weather-pattern definitions and daily occurrences largely agree with their respective LWTs, allowing comparison between the two classifications. There is also broad agreement between weather pattern and LWT changes in frequencies. The new data set is shown to be adequate for precipitation-based analyses in the UK, although a smaller set of clustered weather patterns is not. Furthermore, intra-pattern precipitation variability is lower in the new classification compared to the LWTs, which is an advantage in this context. Six of the new weather patterns are associated with drought over the entire UK, with several other patterns linked to regional drought. It is demonstrated that the new data set of weather patterns offers a new opportunity for classification-based analyses in the UK.

Real-time, rapidly updating severe weather products for virtual globes

NASA Astrophysics Data System (ADS)

Smith, Travis M.; Lakshmanan, Valliappa

2011-01-01

It is critical that weather forecasters are able to put severe weather information from a variety of observational and modeling platforms into a geographic context so that warning information can be effectively conveyed to the public, emergency managers, and disaster response teams. The availability of standards for the specification and transport of virtual globe data products has made it possible to generate spatially precise, geo-referenced images and to distribute these centrally created products via a web server to a wide audience. In this paper, we describe the data and methods for enabling severe weather threat analysis information inside a KML framework. The method of creating severe weather diagnosis products that are generated and translating them to KML and image files is described. We illustrate some of the practical applications of these data when they are integrated into a virtual globe display. The availability of standards for interoperable virtual globe clients has not completely alleviated the need for custom solutions. We conclude by pointing out several of the limitations of the general-purpose virtual globe clients currently available.

Energy, Weatherization and Indoor Air Quality

EPA Pesticide Factsheets

Climate change presents many challenges, including the production of severe weather events. These events and efforts to minimize their effects through weatherization can adversely affect indoor environments.

Motivational Meteorology.

ERIC Educational Resources Information Center

Benjamin, Lee

1993-01-01

Describes an introductory meteorology course for nonacademic high school students. The course is made hands-on by the use of an educational software program offered by Accu-Weather. The program contains a meteorology database and instructional modules. (PR)

Snow model analysis.

DOT National Transportation Integrated Search

2014-01-01

This study developed a new snow model and a database which warehouses geometric, weather and traffic : data on New Jersey highways. The complexity of the model development lies in considering variable road : width, different spreading/plowing pattern...

The Relationships Between Weather and Climate and Attacks of Bronchitis

NASA Astrophysics Data System (ADS)

Talaia, M. A. R.; Saraiva, M. A. C.; Vieira da Cruz, A. A.

The area of Aveiro, more concretely Aveiro lagoon, a natural laboratory has been con- sidered, for promoting the development and the application of several investigations worked. The importance of the influences of weather and climate on human health has been well known since ancient teams and many decisions concerning human be- haviour it are clearly weather related. However, decisions related to weather criteria can be important and economically significant, but the real economic effect of the weather is difficult to assess. Talaia et al. (2000) and Talaia and Vieira da Cruz (2001) have shown the possible harmful effect of certain meteorological factors on respiratory conditions. Bronchitis is a disease caused by inflammation of the bronchi as a result of infectious agents or air pollutants. In this study our attention is to relate, the be- ginning of bronchitis attacks in the services of urgency of the Hospital of Aveiro with meteorological factors, and the risk group are studied. We used the medical records and the database of meteorological factors. The obtained analysis allows to conclude that some meteorological factors have correlation with the occurrences of the disease and to allow improving the work in the urgency services in the requested periods. The knowledge that will be extracted of this study can be used later in studies that inte- grate other important components for the characterisation of the environmental impact in the area. References: Talaia, M.A.R., Vieira da Cruz, A.A., Saraiva, M.A.C., Amaro, G.S., Oliveira, C.J. and Carvalho, C.F., 2000, The Influence of Meteorological Fac- tors on Pneumonia Emergencies in Aveiro, International Symposium on Human- Biometeorology, St. Petersburg (Pushkin), Russia, pp. 67-68. Talaia, M.A.R. and Vieira of Cruz, A.A., (2001), Meteorological Effects on the Resistance of the Body to Influenza - One Study in Aveiro Region, Proceedings 2nd Symposium of Meteorol- ogy and Geophysics of APMG and 3rd Meeting Portuguese-Spanish of Meteorology (in press).

Space Weather Influence on the Earth wheat markets: past, present, and future.

NASA Astrophysics Data System (ADS)

Pustil'Nik, Lev

We consider problem of a possible influence of unfavorable states of the space weather on agriculture market through 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 last time allow to revise wide field of expected solar-terrestrial connections. In the previous works we proposed possible mechanisms of wheat market reaction in the form of price bursts on the specific unfavorable states of space weather. We show that implementation of considered "price reaction scenarios" is possible only for condition of simultaneous realization of several necessary conditions: high sensitivity of local earth weather in selected region to space weather; state of "high risk agriculture" in selected agriculture zone; high sensitivity of agricultural market to possible deficit of supply. Results of previous works (I, II) included application of this approach to wheat market in Medieval England and to modern USA durum market showed that real connection between wheat price bursts and space weather state is observed with high confidence level. The aim of present work is answer on the question, why wheat markets in one region are sensitive to space weather factor, while another regional wheat markets demonstrate absolute indifferent reaction on this factor. For this aim we consider distribution of sensitivity of wheat markets in Europe to space weather as function of localization in different climatic zones. We analyze giant database of 95 European wheat markets from 14 countries during about 600-year period (1260-1912). We show that observed sensitivity of wheat market to space weather effects controlled, first of all, by type of predominant climate in different zones of agriculture. Wheat markets in the North and part of Central Europe (England, Iceland, Holland) shows reliable sensitivity to space weather in minimum states of solar activity with low solar wind, high cosmic ray flux and North Atlantic cloudiness, caused by CR excess, with negative sequences for wheat agriculture in this humid zone. In the same time wheat markets in the South Europe (Spain, Italy) show reliable sensitivity to space weather state in the opposite (maximum) phase of solar activity with strong solar wind, low cosmic ray flux and deficit of CR input in cloudiness in North Atlantic with next deficit of precipitations in the arid zones of the South Europe. In the same time the large part of markets in the Central Europe zone, functioned far from "high risk agriculture state" show the absence of any effects-responses on space weather. This asymmetry is in accordance with model expectation in the frame of proposed approach. For extremely case of the Iceland agriculture we show that drop of agriculture production in unfavorable states of space weather leads to mass mortality from famines correlated with phase of solar activity with high confi- dence level. We discuss possible increasing of sensitivity of wheat markets to space weather effects in condition of drastic and fast change of modern climate, caused by global warming of the Earth atmosphere with fast and unexpected shift of numerous agriculture regions in the world to state of "high risk agriculture zone". Publications on the theme of review: I. "INFLUENCE OF SOLAR ACTIVITY ON THE STATE OF THE WHEAT MARKET IN MEDIEVAL ENGLAND", Solar Physics 223: 335-356, 2004. c 2004 Kluwer Academic Publishers II. "SPACE CLIMATE MANIFESTATION IN EARTH PRICES - FROM MEDIEVAL ENGLAND UP TO MODERN U.S.A.", LEV PUSTIL'NIK and GREGORY YOM DIN, Solar Physics, 224: 473-481 c Springer 2005

Detection and attribution of extreme weather disasters

NASA Astrophysics Data System (ADS)

Huggel, Christian; Stone, Dáithí; Hansen, Gerrit

2014-05-01

Single disasters related to extreme weather events have caused loss and damage on the order of up to tens of billions US dollars over the past years. Recent disasters fueled the debate about whether and to what extent these events are related to climate change. In international climate negotiations disaster loss and damage is now high on the agenda, and related policy mechanisms have been discussed or are being implemented. In view of funding allocation and effective risk reduction strategies detection and attribution to climate change of extreme weather events and disasters is a key issue. Different avenues have so far been taken to address detection and attribution in this context. Physical climate sciences have developed approaches, among others, where variables that are reasonably sampled over climatically relevant time periods and related to the meteorological characteristics of the extreme event are examined. Trends in these variables (e.g. air or sea surface temperatures) are compared between observations and climate simulations with and without anthropogenic forcing. Generally, progress has been made in recent years in attribution of changes in the chance of some single extreme weather events to anthropogenic climate change but there remain important challenges. A different line of research is primarily concerned with losses related to the extreme weather events over time, using disaster databases. A growing consensus is that the increase in asset values and in exposure are main drivers of the strong increase of economic losses over the past several decades, and only a limited number of studies have found trends consistent with expectations from climate change. Here we propose a better integration of existing lines of research in detection and attribution of extreme weather events and disasters by applying a risk framework. Risk is thereby defined as a function of the probability of occurrence of an extreme weather event, and the associated consequences, with consequences being a function of the intensity of the physical weather event, the exposure and value of assets, and vulnerabilities. We have examined selected major extreme events and disasters, including superstorm Sandy in 2012, the Pakistan floods and the heat wave in Russia in 2010, the 2010 floods in Colombia and the 2011 floods in Australia. We systematically analyzed to what extent (anthropogenic) climate change may have contributed to intensity and frequency of the event, along with changes in the other risk variables, to eventually reach a more comprehensive understanding of the relative role of climate change in recent loss and damage of extreme weather events.

Evaluation of Lightning Jumps as a Predictor of Severe Weather in the Northeastern United States

NASA Astrophysics Data System (ADS)

Eck, Pamela

Severe weather events in the northeastern United States can be challenging to forecast, given how the evolution of deep convection can be influenced by complex terrain and the lack of quality observations in complex terrain. To supplement existing observations, this study explores using lightning to forecast severe convection in areas of complex terrain in the northeastern United States. A sudden increase in lightning flash rate by two standard deviations (2sigma), also known as a lightning jump, may be indicative of a strengthening updraft and an increased probability of severe weather. This study assesses the value of using lightning jumps to forecast severe weather during July 2015 in the northeastern United States. Total lightning data from the National Lightning Detection Network (NLDN) is used to calculate lightning jumps using a 2sigma lightning jump algorithm with a minimum threshold of 5 flashes min-1. Lightning jumps are used to predict the occurrence of severe weather, as given by whether a Storm Prediction Center (SPC) severe weather report occurred 45 min after a lightning jump in the same cell. Results indicate a high probability of detection (POD; 85%) and a high false alarm rate (FAR; 89%), suggesting that lightning jumps occur in sub-severe storms. The interaction between convection and complex terrain results in a locally enhanced updraft and an increased probability of severe weather. Thus, it is hypothesized that conditioning on an upslope variable may reduce the FAR. A random forest is introduced to objectively combine upslope flow, calculated using data from the High Resolution Rapid Refresh (HRRR), flash rate (FR), and flash rate changes with time (DFRDT). The random forest, a machine-learning algorithm, uses pattern recognition to predict a severe or non-severe classification based on the predictors. In addition to upslope flow, FR, and DFRDT, Next-Generation Radar (NEXRAD) Level III radar data was also included as a predictor to compare its value to that of lightning data. Results indicate a high POD (82%), a low FAR (28%), and that lightning data and upslope flow data account for 39% and 32% of variable importance, respectively.

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

Lopez, Anthony

Presentation at ASHRAE about the spatial and temporal variability of gridded TMYs, discussing advanced GIS and Web services that allow for direct access to data, surface-based observations for thousands of stations, climate reanalysis data, and products derived from satellite data; new developments in NREL's solar databases based on both observed data and satellite-derived gridded data, status of TMY3 weather files, and NREL's plans for the next-generation TMY weather files; and also covers what is new and different in the Climatic Design Conditions Table in the 2013 ASHRAE Handbook of Fundamentals.

Severe weather study. [for evaluating dissemination of storm forecasts meteorological services

NASA Technical Reports Server (NTRS)

Mills, C. J.

1973-01-01

Current methods of severe weather information dissemination and the impact of this information on the general public are studied. The study is based on the responses of the general public and the local broadcasters to a severe weather incident which occurred on August 14, 1972 in the Dane County-Madison Metropolitan area. The results of the study were somewhat startling. From the sample, for instance, it was found that 45% of the Dane County population was not aware of the severe thunderstorm warning. In this case this may or may not have been critical, but had the storm been extremely severe or had a tornado and flooding been associated with the storm, a large segment of the population would have been in great danger. What this study has shown, is that the real problem with the dissemination of severe weather information is not the lack of it, but the inability to transfer it in useful form to an overwhelming majority of the general public.

Severe weather as a spectacle: the Meteo-Show

NASA Astrophysics Data System (ADS)

Orbe, Iñaki; Gaztelumendi, Santiago

2017-06-01

In this work we focus on perhaps one of the worst journalist practice when dealing with severe weather, the Meteo-Show or the extended practice, especially in TV, for using weather and meteorology for spectacle. Journalism today has found weather information in a real goldmine in terms of audience due to the growing public interest in this matter. However, as it happens with other content, sensationalism and exaggeration have also reached weather information, primarily when episodes of adverse nature (snow, heavy rain, floods, etc.) are addressed. In this paper we look to identify the worst practices in weather communication through analysis of examples from real journalist work. We present some keys to understand this trend, highlighting the ingredients that are present in the worst Meteo-show.

[Climate change and hygienic assessment of weather conditions in Omsk and the Omsk Region].

PubMed

Gudinova, Zh V; Akimova, I S; Klochikhina, A V

2010-01-01

The paper deals with trends in climate change in the Omsk Region: the increases in average annual air temperatures and rainfall, which are attended by the higher number of abnormal weather events, as shown by the data of the Omsk Regional Board, Russian Federal Service for Hydrometeorology and Environmental Monitoring. There is information on weather severity in 2008: there was mild weather in spring and severe weather in winter, in January in particular. A survey of physicians has revealed that medical workers are concerned about climate problems and global warming and ascertained weather events mostly affecting the population's health. People worry most frequently about a drastic temperature drop or rise (as high as 71%), atmospheric pressure change (53%), and "when it is too hot in summer (47%).

The Synoptic Climatology of Severe Thunderstorms in Manitoba.

NASA Astrophysics Data System (ADS)

Ladochy, Stephen Eugene Gabriel

The thesis presents the climatologies for Manitoba thunderstorms, hailstorms and tornadoes as well as investigates the synoptic weather conditions conducive for their development. The study not only uses standard meteorological information, but also various kinds of proxy data, in the form of damage reports. These damage reports complement the meteorological data by providing a higher resolution of observations, particularly in the sparsely populated regions. The synoptic conditions are relatively similar for all forms of severe thunderstorms, though the upper level jet stream (ULJ) is stronger for tornadoes, in general. Composite charts, drawn for 50 larger, more damaging hail days and 48 tornado days in the 1970's, helped identify important surface and upper air weather parameters and their inter -relationships with each other and the location of the storm. Time sequence composite charts were used to also show the development process in severe weather occurrences. From the composites, a synoptic weather type classification was devised with 10 categories to identify each storm by type. The most common pattern for severe weather has a strong southwesterly ULJ, with the storm occurring ahead of an advancing cold front. The ULJ patterns were drawn for each synoptic type days, showing differences between categories. The average conditions during tornado touchdowns were also seen from composite maps of surface and upper air isobaric charts. While severe thunderstorms are seen to occur under the "ideal" conditions, often described for U.S. severe weather, they can also be produced under other weather patterns and combinations of atmospheric parameters thought less favorable. The ULJ and LLJ (low-level jet stream) models used in U.S. studies do not always fit Manitoba storms, however, less favorable jet positions, at specific levels, can be compensated for by low-level advection of warm, and moist air.

Weathered stony meteorites from Victoria Land, Antarctica, as possible guides to rock weathering on Mars

NASA Technical Reports Server (NTRS)

Gooding, J. L.

1984-01-01

Parallel studies of Martian geomorphic features and their analogs on Earth continue to be fruitful in deciphering the geologic history of Mars. In the context of rock weathering, the Earth-analog approach is admirably served by the study of meteorites recovered from ice sheets in Antarctica. The weathering environment of Victoria Land possesses several Mars-like attributes. Four of the five Antarctic meteorites being studied contain rust and EETA79005 further possesses a conspicuous, dark, weathering rind on one side. Secondary minerals (rust and salts) occur both on the surfaces and interiors of some of the samples and textural evidence indicates that such secondary mineralization contributed to physical weathering (by salt riving) of the rocks. Several different rust morphologies occur and emphasis is being placed on identifying the phase compositions of the various rust occurrances. A thorough understanding of terrestrial weathering features of the meteorites is a prerequisite for identifying possible Martian weathering features (if such features exist) that might be postulated to occur in some meteorites.

75 FR 20918 - Drawbridge Operation Regulations; Duluth Ship Canal, Duluth, MN

Federal Register 2010, 2011, 2012, 2013, 2014

2010-04-22

... salvage operations, vessels engaged in pilot duties, vessels seeking shelter from severe weather, and all... operations, vessels engaged in pilot duties, vessels seeking shelter from severe weather, and all commercial...

Weather severity index on a mule deer winter range. [Odocoileus hemionus hemionus

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

Leckenby, D.A.; Adams, A.W.

1986-05-01

Temperature, wind, and snow conditions predictably affect the nutrition, behavior, distribution, productivity, and mortality of free-ranging cattle and big game in winter. Indexing of data obtained with commonly available weather instruments to reflect episodes of positive and negative energy balances of free-ranging ruminants could aid scheduling of feeding programs and planning of cover-forage manipulations. Such a weather severity index was developed and tested over 11 winters. Plausible levels of stress and episodes of relative severity were depicted during winters when mule deer exhibited low, moderate, and high mortality. The index curves mirrored over-winter declines of fat reserves probably sustained bymore » mule deer. Lesser weather severity was predicted and measured in a western juniper woodland than in an adjacent rabbitbrush steppe community in southcentral Oregon. 32 references, 3 figures, 2 tables.« less

Automated Flight Routing Using Stochastic Dynamic Programming

NASA Technical Reports Server (NTRS)

Ng, Hok K.; Morando, Alex; Grabbe, Shon

2010-01-01

Airspace capacity reduction due to convective weather impedes air traffic flows and causes traffic congestion. This study presents an algorithm that reroutes flights in the presence of winds, enroute convective weather, and congested airspace based on stochastic dynamic programming. A stochastic disturbance model incorporates into the reroute design process the capacity uncertainty. A trajectory-based airspace demand model is employed for calculating current and future airspace demand. The optimal routes minimize the total expected traveling time, weather incursion, and induced congestion costs. They are compared to weather-avoidance routes calculated using deterministic dynamic programming. The stochastic reroutes have smaller deviation probability than the deterministic counterpart when both reroutes have similar total flight distance. The stochastic rerouting algorithm takes into account all convective weather fields with all severity levels while the deterministic algorithm only accounts for convective weather systems exceeding a specified level of severity. When the stochastic reroutes are compared to the actual flight routes, they have similar total flight time, and both have about 1% of travel time crossing congested enroute sectors on average. The actual flight routes induce slightly less traffic congestion than the stochastic reroutes but intercept more severe convective weather.

Severe weather phobia: an exploratory study.

PubMed

Westefeld, J S

1996-09-01

Eighty-one persons with an intense fear of severe thunderstorms and tornadoes were interviewed to learn more about the phenomenon of "severe weather phobia," a term introduced for the first time in this investigation. Possible causes and methods of treatment are discussed, as well as implications for future research.

Forest fire weather in western Oregon and western Washington in 1956.

Treesearch

Owen P. Cramer

1956-01-01

The 1956 fire season will be remembered for the record number of lightning storms in nearly all parts of the area. In other respects, fire-weather severity was slightly below the average of the previous ten years. In western Oregon, fire weather over the entire season (April through October) was slightly less severe than in 1955, while in western Washington it was...

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

Groups Call for Better Protection From Climate Change and Severe Weather

NASA Astrophysics Data System (ADS)

Fellows, Jack

2008-11-01

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

Efficient Ways to Learn Weather Radar Polarimetry

ERIC Educational Resources Information Center

Cao, Qing; Yeary, M. B.; Zhang, Guifu

2012-01-01

The U.S. weather radar network is currently being upgraded with dual-polarization capability. Weather radar polarimetry is an interdisciplinary area of engineering and meteorology. This paper presents efficient ways to learn weather radar polarimetry through several basic and practical topics. These topics include: 1) hydrometeor scattering model…

Ecological Effects of Weather Modification: A Problem Analysis.

ERIC Educational Resources Information Center

Cooper, Charles F.; Jolly, William C.

This publication reviews the potential hazards to the environment of weather modification techniques as they eventually become capable of producing large scale weather pattern modifications. Such weather modifications could result in ecological changes which would generally require several years to be fully evident, including the alteration of…

Tool for Automated Retrieval of Generic Event Tracks (TARGET)

NASA Technical Reports Server (NTRS)

Clune, Thomas; Freeman, Shawn; Cruz, Carlos; Burns, Robert; Kuo, Kwo-Sen; Kouatchou, Jules

2013-01-01

Methods have been developed to identify and track tornado-producing mesoscale convective systems (MCSs) automatically over the continental United States, in order to facilitate systematic studies of these powerful and often destructive events. Several data sources were combined to ensure event identification accuracy. Records of watches and warnings issued by National Weather Service (NWS), and tornado locations and tracks from the Tornado History Project (THP) were used to locate MCSs in high-resolution precipitation observations and GOES infrared (11-micron) Rapid Scan Operation (RSO) imagery. Thresholds are then applied to the latter two data sets to define MCS events and track their developments. MCSs produce a broad range of severe convective weather events that are significantly affecting the living conditions of the populations exposed to them. Understanding how MCSs grow and develop could help scientists improve their weather prediction models, and also provide tools to decision-makers whose goals are to protect populations and their property. Associating storm cells across frames of remotely sensed images poses a difficult problem because storms evolve, split, and merge. Any storm-tracking method should include the following processes: storm identification, storm tracking, and quantification of storm intensity and activity. The spatiotemporal coordinates of the tracks will enable researchers to obtain other coincident observations to conduct more thorough studies of these events. In addition to their tracked locations, their areal extents, precipitation intensities, and accumulations all as functions of their evolutions in time were also obtained and recorded for these events. All parameters so derived can be catalogued into a moving object database (MODB) for custom queries. The purpose of this software is to provide a generalized, cross-platform, pluggable tool for identifying events within a set of scientific data based upon specified criteria with the possibility of storing identified events into a searchable database. The core of the application uses an implementation of the connected component labeling (CCL) algorithm to identify areas of interest, then uses a set of criteria to establish spatial and temporal relationships between identified components. The CCL algorithm is used for identifying objects within images for computer vision. This application applies it to scientific data sets using arbitrary criteria. The most novel concept was applying a generalized CCL implementation to scientific data sets for establishing events both spatially and temporally. The combination of several existing concepts (pluggable components, generalized CCL algorithm, etc.) into one application is also novel. In addition, how the system is designed, i.e., its extensibility with pluggable components, and its configurability with a simple configuration file, is innovative. This allows the system to be applied to new scenarios with ease.

Piloting and Evaluating a Workshop to Teach Georgia Teachers about Weather Science and Safety

ERIC Educational Resources Information Center

Stewart, Alan E.; Knox, John A.; Schneider, Pat

2015-01-01

A survey of 691 Georgia teachers suggested that their students generally were not prepared for severe weather. Teachers also were somewhat dissatisfied with the quality of the teaching resources on weather and weather safety. Only 46 (7%) of the teachers were aware of the American Red Cross Masters of Disaster (MoD) weather science and safety…

Proactive approach to transportation resource allocation under severe winter weather emergencies.

DOT National Transportation Integrated Search

2012-01-01

Severe winter weather dramatically reduces road transportation infrastructure : serviceability and decreases safety throughout Oklahoma. Although it has relatively mild winters : when compared with northern regions of the United States, Oklahoma has ...

Historical Space Climate Data from Finland: Compilation and Analysis

NASA Astrophysics Data System (ADS)

Nevanlinna, Heikki

2004-10-01

We have compiled archived geomagnetic observations from the Helsinki magnetic observatory as well as visual sightings of auroral occurrence in Finland. The magnetic database comprises about 2 000 000 observations of H- and D-components measured during 1844-1909 with time resolution of 10 min to 1 h. In addition, magnetic observations carried out in the First and Second Polar Years in Finland have been recompiled. Magnetic activity indices (three-hour K-and daily Ak-figures) have been derived from the magnetic observations. Comparisons between the Finnish indices and simultaneous global aa-index (starting in 1868) show a good mutual correlation. The Helsinki activity index series can be used as a (pseudo) extension of the aa-index series for about two solar cycles 1844d -1868. On the annual level the correlation coefficient is about 0.9 during the overlapped time interval 1868-1897. The auroral database consists of about 20 000 single observations observed in Finland since the year 1748. The database of visual auroras has been completed by auroral occurrence (AO) index data derived from the Finnish all-sky camera recordings during 1973 -1997 at several sites in Lapland. The AO-index reveals both spatial and temporal variations of auroras from diurnal to solar cycle time scales in different space weather conditions.

Build an Emergency Preparedness Kit

MedlinePlus

... tire traction -Red or brightly- colored cloth -NOAA weather radio For more information on building emergency kits, ... and a flashlight with extra batteries. A NOAA weather radio warns the public of severe weather and ...

Correlation of Rock Spectra with Quantitative Morphologic Indices: Evidence for a Single Rock Type at the Mars Pathfinder Landing Site

NASA Technical Reports Server (NTRS)

Yingst, R. A.; Biedermann, K. L.; Pierre, N. M.; Haldemann, A. F. C.; Johnson, J. R.

2005-01-01

The Mars Pathfinder (MPF) landing site was predicted to contain a broad sampling of rock types varying in mineralogical, physical, mechanical and geochemical characteristics. Although rocks have been divided into several spectral categories based on Imager for Mars Pathfinder (IMP) visible/near-infrared data, efforts in isolating and classifying spectral units among MPF rocks and soils have met with varying degrees of success, as many factors influencing spectral signatures cannot be quantified to a sufficient level to be removed. It has not been fully determined which spectral categories stem from intrinsic mineralogical differences between rocks or rock surfaces, and which result from factors such as physical or chemical weathering. This has made isolation of unique rock mineralogies difficult. Morphology, like composition, is a characteristic tied to the intrinsic properties and geologic and weathering history of rocks. Rock morphologies can be assessed quantitatively and compared with spectral data, to identify and classify rock types at the MPF landing site. They can also isolate actual rock spectra from spectral types that are surficial in origin, as compositions associated with mantling dust or chemical coatings would presumably not influence rock morphology during weathering events. We previously reported on an initial classification of rocks using the quantitative morphologic indices of size, roundness, sphericity and elongation. Here, we compare this database of rock characteristics with associated rock surface spectra to improve our ability to discriminate between spectra associated with rock types and those from other sources.

Updated global soil map for the Weather Research and Forecasting model and soil moisture initialization for the Noah land surface model

NASA Astrophysics Data System (ADS)

DY, C. Y.; Fung, J. C. H.

2016-08-01

A meteorological model requires accurate initial conditions and boundary conditions to obtain realistic numerical weather predictions. The land surface controls the surface heat and moisture exchanges, which can be determined by the physical properties of the soil and soil state variables, subsequently exerting an effect on the boundary layer meteorology. The initial and boundary conditions of soil moisture are currently obtained via National Centers for Environmental Prediction FNL (Final) Operational Global Analysis data, which are collected operationally in 1° by 1° resolutions every 6 h. Another input to the model is the soil map generated by the Food and Agriculture Organization of the United Nations - United Nations Educational, Scientific and Cultural Organization (FAO-UNESCO) soil database, which combines several soil surveys from around the world. Both soil moisture from the FNL analysis data and the default soil map lack accuracy and feature coarse resolutions, particularly for certain areas of China. In this study, we update the global soil map with data from Beijing Normal University in 1 km by 1 km grids and propose an alternative method of soil moisture initialization. Simulations of the Weather Research and Forecasting model show that spinning-up the soil moisture improves near-surface temperature and relative humidity prediction using different types of soil moisture initialization. Explanations of that improvement and improvement of the planetary boundary layer height in performing process analysis are provided.

Fire occurrence prediction in the Mediterranean: Application to Southern France

NASA Astrophysics Data System (ADS)

Papakosta, Panagiota; Öster, Jan; Scherb, Anke; Straub, Daniel

2013-04-01

The areas that extend in the Mediterranean basin have a long fire history. The climatic conditions of wet winters and long hot drying summers support seasonal fire events, mainly ignited by humans. Extended land fragmentation hinders fire spread, but seasonal winds (e.g. Mistral in South France or Meltemia in Greece) can drive fire events to become uncontrollable fires with severe impacts to humans and the environment [1]. Prediction models in these areas should incorporate both natural and anthropogenic factors. Several indices have been developed worldwide to express fire weather conditions. The Canadian Fire Weather Index (FWI) is currently adapted by many countries in Europe due to the easily observable input weather parameters (temperature, wind speed, relative humidity, precipitation) and the easy-to-implement algorithms of the Canadian formulation describing fuel moisture relations [2],[3]. Human influence can be expressed directly by human presence (e.g. population density) or indirectly by proxy indicators (e.g. street density [4], land cover type). The random nature of fire occurrences and the uncertainties associated with the influencing factors motivate probabilistic prediction models. The aim of this study is to develop a prediction model of fire occurrence probability under natural and anthropogenic influence in Southern France and to compare it with earlier developed predictions in other Mediterranean areas [5]. Fire occurrence is modeled as a Poisson process. Two interpolation methods (Kriging and Inverse Distance Weighting) are used to interpolate daily weather observations from weather stations to a 1 km² spatial grid and their results are compared. Poisson regression estimates the parameters of the model and the resulting daily predictions are provided in terms of maps displaying fire occurrence rates. The model is applied to the regions Provence-Alpes-Côtes D'Azur und Languedoc-Roussillon in the South of France. Weather data are obtained from the German and French Weather Services (Deutscher Wetterdienst and Météo-France). Historical fire events are taken from Prométhée database. Time series 2000-2010 are used as learning data and data from 2011 is used as the validation data. The resulting model can support real-time fire risk estimation for improved allocation of firefighting resources and planning of other mitigation actions. [1] Keeley, J.E.; Bond, W.J.; Bradstock, R.A.; Pausas, J.G.; Rundel, P.W. (2012): Fire in Mediterranean ecosystems: ecology, evolution and management. Cambridge University Press, New York, USA, pp.515 [2] Lawson, B.D.; Armitage, O.B. (2008): Weather Guide for the Canadian Forest Fire Danger Rating System. Natural Resources Canada, Canadian Forest Service, Northern Forestry Centre, Edmonton, Alberta, Canada. [3] Van Wagner, C.E.; Pickett, T.L. (1985): Equations and FORTRAN Program for the Canadian Forest Fire Weather Index System. Forestry Technical Report 33. Canadian Forestry Service, Government of Canada, Ottawa, Ontario, Canada [4] Syphard, A.D.; Radeloff, V.C.; Keuler, N.S.; Taylor, R.S.; Hawbaker, T.J.; Stewart, S.I.; Clayton, M.K. (2008): Predicting spatial patterns of fire on a southern California landscape. International Journal of Wildland Fire, 17, pp.602-613 [5] Papakosta, P.; Klein, F.; König, S.; Straub, D. (2012): Linking spatio-temporal data to the Fire Weather Index to estimate the probability of wildfire in the Mediterranean. Geophysical Research Abstracts, Vol.14, EGU2012-12737, EGU General Assembly 2012

Influence of climate change on productivity of American White Pelicans, Pelecanus erythrorhynchos

USGS Publications Warehouse

Sovada, Marsha A.; Igl, Lawrence D.; Pietz, Pamela J.; Bartos, Alisa J.

2014-01-01

In the past decade, severe weather and West Nile virus were major causes of chick mortality at American white pelican (Pelecanus erythrorhynchos) colonies in the northern plains of North America. At one of these colonies, Chase Lake National Wildlife Refuge in North Dakota, spring arrival by pelicans has advanced approximately 16 days over a period of 44 years (1965–2008). We examined phenology patterns of pelicans and timing of inclement weather through the 44-year period, and evaluated the consequence of earlier breeding relative to weather-related chick mortality. We found severe weather patterns to be random through time, rather than concurrently shifting with the advanced arrival of pelicans. In recent years, if nest initiations had followed the phenology patterns of 1965 (i.e., nesting initiated 16 days later), fewer chicks likely would have died from weather-related causes. That is, there would be fewer chicks exposed to severe weather during a vulnerable transition period that occurs between the stage when chicks are being brooded by adults and the stage when chicks from multiple nests become part of a thermally protective crèche.

A high-resolution modelling approach on spatial wildfire distribution in the Tyrolean Alps

NASA Astrophysics Data System (ADS)

Malowerschnig, Bodo; Sass, Oliver

2013-04-01

Global warming will cause increasing danger of wildfires in Austria, which can have long-lasting consequences on woodland ecosystems. The protective effect of forest can be severely diminished, leading to natural hazards like avalanches and rockfall. However, data on wildfire frequency and distribution have been sparse and incomplete for Austria. Long-lasting postfire degradation under adverse preconditions (steep slopes, limestone) was a common phenomenon in parts of the Tyrolean Alps several decades ago and should become relevant again under a changing fire frequency. The FIRIA project compiles historical wildfire data, information on fuel loads, fire weather indices (FWI) and vegetation recovery patterns. The governing climatic, topographic and socio-economic factors of forest fire distribution were assessed to trigger a distribution model of currently fire-prone areas in Tyrol. By collecting data from different sources like old newspapers archives and fire-fighter databases, we were able to build up a fire database of wildfire occurrences containing more than 1400 forest fires since the 15th century in Tyrol. For the period from 1993 to 2011, the database is widely complete and covers 482 fires. Using a non-parametrical statistical method it was possible to select the best suited fire weather index (FWI) for the prediction. The testing of 19 FWI's shows that it is necessary to use two discriminative indices to differentiate between summer and winter season. Together with compiled topographic, socio-economic, infrastructure and forest maps, the dataset was the base for a multifactorial analysis, performed by comparing the maximum entropy approach (Maxent) with an ensemble classifier (Random Forests). Both approaches have their background in the spatial habitat distribution and are easy to adapt to the requirements of a wildfire ignition model. The aim of this modelling approach was to determine areas which are particularly prone to wildfire. Due to the pronounced relief curvature we based our model on 100 x 100 m cells to identify individual slopes and their topography. The first provisional result is a map of fire probability under current climate conditions (fire hot-spots). Our modelling approach indicates the fire weather index as the main driver, which is followed closely by socioeconomic (population density) and infrastructure factors (roads density, aerial railways, building density). The leverage of the forest community or its management is rather low; the same applies to topographic influences like aspect or sea level. The derived fire hot-spots are either placed close to the valley ground or around touristic infrastructure, with an overall preference for inner alpine areas and south-facing slopes. In the next step, the impact of climate change on the distribution and frequency of fires will be assessed by calculating a climate change model adapted to the 1x1km INCA dataset and based on different regional climate change models. Finally, a selection of fire-hot-spots from the previous modelling steps will be used for enhanced 3D-modelling approaches of natural hazards after wildfire-driven deforestation.

COMET Multimedia modules and objects in the digital library system

NASA Astrophysics Data System (ADS)

Spangler, T. C.; Lamos, J. P.

2003-12-01

Over the past ten years of developing Web- and CD-ROM-based training materials, the Cooperative Program for Operational Meteorology, Education and Training (COMET) has created a unique archive of almost 10,000 multimedia objects and some 50 web based interactive multimedia modules on various aspects of weather and weather forecasting. These objects and modules, containing illustrations, photographs, animations,video sequences, audio files, are potentially a valuable resource for university faculty and students, forecasters, emergency managers, public school educators, and other individuals and groups needing such materials for educational use. The COMET Modules are available on the COMET educational web site http://www.meted.ucar.edu, and the COMET Multimedia Database (MMDB) makes a collection of the multimedia objects available in a searchable online database for viewing and download over the Internet. Some 3200 objects are already available at the MMDB Website: http://archive.comet.ucar.edu/moria/

Map Database for Surficial Materials in the Conterminous United States

USGS Publications Warehouse

Soller, David R.; Reheis, Marith C.; Garrity, Christopher P.; Van Sistine, D. R.

2009-01-01

The Earth's bedrock is overlain in many places by a loosely compacted and mostly unconsolidated blanket of sediments in which soils commonly are developed. These sediments generally were eroded from underlying rock, and then were transported and deposited. In places, they exceed 1000 ft (330 m) in thickness. Where the sediment blanket is absent, bedrock is either exposed or has been weathered to produce a residual soil. For the conterminous United States, a map by Soller and Reheis (2004, scale 1:5,000,000; http://pubs.usgs.gov/of/2003/of03-275/) shows these sediments and the weathered, residual material; for ease of discussion, these are referred to as 'surficial materials'. That map was produced as a PDF file, from an Adobe Illustrator-formatted version of the provisional GIS database. The provisional GIS files were further processed without modifying the content of the published map, and are here published.

Winter Weather Emergencies

MedlinePlus

Severe winter weather can lead to health and safety challenges. You may have to cope with Cold related health problems, including ... there are no guarantees of safety during winter weather emergencies, you can take actions to protect yourself. ...

Online model evaluation of large-eddy simulations covering Germany with a horizontal resolution of 156 m

NASA Astrophysics Data System (ADS)

Hansen, Akio; Ament, Felix; Lammert, Andrea

2017-04-01

Large-eddy simulations have been performed since several decades, but due to computational limits most studies were restricted to small domains or idealised initial-/boundary conditions. Within the High definition clouds and precipitation for advancing climate prediction (HD(CP)2) project realistic weather forecasting like LES simulations were performed with the newly developed ICON LES model for several days. The domain covers central Europe with a horizontal resolution down to 156 m. The setup consists of more than 3 billion grid cells, by what one 3D dump requires roughly 500 GB. A newly developed online evaluation toolbox was created to check instantaneously for realistic model simulations. The toolbox automatically combines model results with observations and generates several quicklooks for various variables. So far temperature-/humidity profiles, cloud cover, integrated water vapour, precipitation and many more are included. All kind of observations like aircraft observations, soundings or precipitation radar networks are used. For each dataset, a specific module is created, which allows for an easy handling and enhancement of the toolbox. Most of the observations are automatically downloaded from the Standardized Atmospheric Measurement Database (SAMD). The evaluation tool should support scientists at monitoring computational costly model simulations as well as to give a first overview about model's performance. The structure of the toolbox as well as the SAMD database are presented. Furthermore, the toolbox was applied on an ICON LES sensitivity study, where example results are shown.

Physical Oceanography Program Science Abstracts.

DTIC Science & Technology

1985-04-01

substantial part of the database used by the U.S. Navy and the U.S. National Weather Service to generate, in real-time, subsurface tempera- ture maps...quality, 1ST database which incorporates GTS bathymessagss and on-sbip recordings from the Pacific for the period 1979 through 1983. Access to these data...Investigator: Stanley M. FlattE Frank S. Henyey INTERNAL-WAVE NONLINEAR INTERACTIONS BY THE EIKONAL METHOD We have been involved in the study of

Positive lightning and severe weather

NASA Astrophysics Data System (ADS)

Price, C.; Murphy, B.

2003-04-01

In recent years researchers have noticed that severe weather (tornados, hail and damaging winds) are closely related to the amount of positive lightning occurring in thunderstorms. On 4 July 1999, a severe derecho (wind storm) caused extensive damage to forested regions along the United States/Canada border, west of Lake Superior. There were 665,000 acres of forest destroyed in the Boundary Waters Canoe Area Wilderness (BWCAW) in Minnesota and Quetico Provincial Park in Canada, with approximately 12.5 million trees blown down. This storm resulted in additional severe weather before and after the occurrence of the derecho, with continuous cloud-to-ground (CG) lightning occurring for more than 34 hours during its path across North America. At the time of the derecho the percentage of positive cloud-to-ground (+CG) lightning measured by the Canadian Lightning Detection Network (CLDN) was greater than 70% for more than three hours, with peak values reaching 97% positive CG lightning. Such high ratios of +CG are rare, and may be useful indicators for short-term forecasts of severe weather.

Total Lightning as a Severe Weather Diagnostic in Strongly Baroclinic Systems in Central Florida

NASA Technical Reports Server (NTRS)

Williams, E.; Boldi, B.; Matlin, A.; Weber, M.; Hodanish, S.; Sharp, D.; Goodman, Steven J.; Raghavan, R.; Buechler, Dennis

1998-01-01

The establishment of a consistent behavior of total lightning activity in severe convective storms has been challenged historically by the relative scarcity of these storms combined with the difficulties inherent in documenting the (dominant) intracloud component of total lightning. This situation has changed recently with the abundance of severe weather in central Florida during 1997-98, including the tornado outbreak of February 23, 1998, and with the development of the operational LISDAD system (Boldi et al, this conference) to document these cases. This paper is concerned primarily with the behavior of total lightning in severe weather during the dry season when the Florida atmosphere is most strongly baroclinic. It has been found that all three manifestations of severe weather (ie., hall, wind, tornadoes) are consistently preceded by rapid increases in total flash rate with values often in excess of 100 flashes/minute. Preliminary analysis suggests that this systematic electrical behavior observed in summertime 'pulse severe' storms (Hodanish et al, this conference) also pertains to the more strongly baroclinic, long-track tornadic storms (more common in Oklahoma), as evidenced by the February 23, 1998 outbreak case in central Florida exhibiting two long-tracking F3 tornadoes. The largest flash rates in severe weather anywhere occur in baroclinic conditions at midlatitude. The physical plausibility of flash rates in excess of 100 per minute will be assessed. We will also consider the differences in storm structure for high flash rate storms that are non-severe.

Data deluxe

NASA Astrophysics Data System (ADS)

Carlowicz, Michael

Several new web pages from the National Oceanic and Atmospheric Administration (NOAA) will allow scientists and nonscientists alike to view graphic displays of weather and space weather data from around the world. Users can select a region of the Earth and a time period to see plots and data sets of everything from severe storms to aurorae.The National Climate Data Center has made available weather data from 8000 stations around the world, 160 satellite images of hurricanes from the GOES satellites, and technical reports about weather events such as the East Coast blizzard of 1996. The web address is http://www.ncdc.noaa.gov.

Extreme water-related weather events and waterborne disease.

PubMed

Cann, K F; Thomas, D Rh; Salmon, R L; Wyn-Jones, A P; Kay, D

2013-04-01

Global climate change is expected to affect the frequency, intensity and duration of extreme water-related weather events such as excessive precipitation, floods, and drought. We conducted a systematic review to examine waterborne outbreaks following such events and explored their distribution between the different types of extreme water-related weather events. Four medical and meteorological databases (Medline, Embase, GeoRef, PubMed) and a global electronic reporting system (ProMED) were searched, from 1910 to 2010. Eighty-seven waterborne outbreaks involving extreme water-related weather events were identified and included, alongside 235 ProMED reports. Heavy rainfall and flooding were the most common events preceding outbreaks associated with extreme weather and were reported in 55·2% and 52·9% of accounts, respectively. The most common pathogens reported in these outbreaks were Vibrio spp. (21·6%) and Leptospira spp. (12·7%). Outbreaks following extreme water-related weather events were often the result of contamination of the drinking-water supply (53·7%). Differences in reporting of outbreaks were seen between the scientific literature and ProMED. Extreme water-related weather events represent a risk to public health in both developed and developing countries, but impact will be disproportionate and likely to compound existing health disparities.

NASA GSFC Space Weather Center - Innovative Space Weather Dissemination: Web-Interfaces, Mobile Applications, and More

NASA Technical Reports Server (NTRS)

Maddox, Marlo; Zheng, Yihua; Rastaetter, Lutz; Taktakishvili, A.; Mays, M. L.; Kuznetsova, M.; Lee, Hyesook; Chulaki, Anna; Hesse, Michael; Mullinix, Richard;

Severe Weather Field Experience: An Undergraduate Field Course on Career Enhancement and Severe Convective Storms

ERIC Educational Resources Information Center

Godfrey, Christopher M.; Barrett, Bradford S.; Godfrey, Elaine S.

2011-01-01

Undergraduate students acquire a deeper understanding of scientific principles through first-hand experience. To enhance the learning environment for atmospheric science majors, the University of North Carolina at Asheville has developed the severe weather field experience. Participants travel to Tornado Alley in the Great Plains to forecast and…

Shuttle landing facility cloud cover study: Climatological analysis and two tenths cloud cover rule evaluation

NASA Technical Reports Server (NTRS)

Atchison, Michael K.; Schumann, Robin; Taylor, Greg; Warburton, John; Wheeler, Mark; Yersavich, Ann

1993-01-01

The two-tenths cloud cover rule in effect for all End Of Mission (EOM) STS landings at the Kennedy Space Center (KSC) states: 'for scattered cloud layers below 10,000 feet, cloud cover must be observed to be less than or equal to 0.2 at the de-orbit burn go/no-go decision time (approximately 90 minutes before landing time)'. This rule was designed to protect against a ceiling (below 10,000 feet) developing unexpectedly within the next 90 minutes (i.e., after the de-orbit burn decision and before landing). The Applied Meteorological Unit (AMU) developed and analyzed a database of cloud cover amounts and weather conditions at the Shuttle Landing Facility for a five-year (1986-1990) period. The data indicate the best time to land the shuttle at KSC is during the summer while the worst time is during the winter. The analysis also shows the highest frequency of landing opportunities occurs for the 0100-0600 UTC and 1300-1600 UTC time periods. The worst time of the day to land a shuttle is near sunrise and during the afternoon. An evaluation of the two-tenths cloud cover rule for most data categorizations has shown that there is a significant difference in the proportions of weather violations one and two hours subsequent to initial conditions of 0.2 and 0.3 cloud cover. However, for May, Oct., 700 mb northerly wind category, 1500 UTC category, and 1600 UTC category there is some evidence that the 0.2 cloud cover rule may be overly conservative. This possibility requires further investigation. As a result of these analyses, the AMU developed nomograms to help the Spaceflight Meteorological Group (SMG) and the Cape Canaveral Forecast Facility (CCFF) forecast cloud cover for EOM and Return to Launch Site (RTLS) at KSC. Future work will include updating the two tenths database, further analysis of the data for several categorizations, and developing a proof of concept artificial neural network to provide forecast guidance of weather constraint violations for shuttle landings.

The effect of ambient exposure to PM2.5 on the transfusion usage of blood components and adverse transfusion reactions in the haze weather.

PubMed

Chang, Chih-Chun; Lin, Hui-Jung; Sun, Jen-Tang; Li, Pei-Yu; Lee, Tai-Chen; Su, Ming-Jang; Yen, Tzung-Hai; Chu, Fang-Yeh

2016-10-01

Accumulating evidence has shown that ambient exposure to PM 2.5 , especially in the haze weather, increased the risk of various diseases. However, the association of air pollution status with blood transfusion utilization and the prevalence and severity of adverse transfusion reactions remain to be clarified. The data of monthly transfusion usage of blood components, adverse transfusion reactions, as well as PM 2.5 and PM 10 levels from 2013 to 2015 were obtained. During the study interval, both PM 2.5 and PM 10 levels were significantly increased in the haze weather when compared with the non-haze weather. The utilization of total blood components per patient-month in the haze weather was prone to be increased when compared with that in the non-haze weather (13.28 ± 1.66 vs. 12.33 ± 1.30, p = 0.068). The usage of RBC products per patient-month in the haze weather was significantly increased when compared with that in the non-haze weather (4.39 ± 0.39 vs. 4.07 ± 0.30, p = 0.009). There was no obvious difference between the haze and non-haze weathers for the usage of platelet and plasma products per patient-month. Besides, no definite differences of the prevalence and severity of transfusion-associated adverse reaction were observed between the haze and non-haze weathers. Our study first indicated that transfusion utilization, particularly the RBC products, was significantly increased in the haze weather when compared with that in the non-haze weather. There was no obvious association of air pollution with the prevalence and severity of adverse transfusion reactions and further research is required. Copyright © 2016 Elsevier Ltd. All rights reserved.

Climatological Data Option in My Weather Impacts Decision Aid (MyWIDA) Overview

DTIC Science & Technology

2017-07-18

rules. It consists of 2 databases, a data service server, a collection of web service, and web applications that show weather impacts on selected...3.1.2 ClimoDB 5 3.2 Data Service 5 3.2.1 Data Requestor 5 3.2.2 Data Decoder 6 3.2.3 Post Processor 6 3.2.4 Job Scheduler 6 3.3 Web Service 6...6.1 Additional Data Option 9 6.2 Impact Overlay Web Service 9 6.3 Graphical User Interface 9 7. References 10 List of Symbols, Abbreviations, and

Air Weather Service Master Station Catalog: USAFETAC Climatic Database Users Handbook No. 6

DTIC Science & Technology

1993-03-01

4) . ... .4 • FIELD NO. DESCRIPTION OF FIELD AND COMMENTS 01 STN NUM. A 6- digit number with the first 5 digits assigned to a particular weather...reporting location lAW WMO ,ules plus a sixth digit as follows: 0 = The first five digits are the actual block/station number (WMO number) assigned to...it is considered inactive for that hour. A digit (1-9) tells how many months it has been since a report was received from the station for that hour

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.

Crowdsourcing of weather observations at national meteorological and hydrological services in Europe

NASA Astrophysics Data System (ADS)

Krennert, Thomas; Pistotnik, Georg; Kaltenberger, Rainer; Csekits, Christian

2018-05-01

National Meteorological and Hydrological Services (NMHSs) increase their efforts to deliver impact-based weather forecasts and warnings. At the same time, a desired increase in cost-efficiency prompts these services to automatize their weather station networks and to reduce the number of human observers, which leads to a lack of ground truth information about weather phenomena and their impact. A possible alternative is to encourage the general public to submit weather observations, which may include crucial information especially in high-impact situations. We wish to provide an overview of the state and properties of existing collaborations between NMHSs and voluntary weather observers or storm spotters across Europe. For that purpose, we performed a survey among 30 European NMHSs, from which 22 NMHSs returned our questionnaire. This study summarizes the most important findings and evaluates the use of crowdsourced information. 86 % of the surveyed NMHSs utilize information provided by the general public, 50 % have established official collaborations with spotter groups, and 18 % have formalized them. The observations are most commonly used for a real-time improvement of severe weather warnings, their verification, and an establishment of a climatology of severe weather events. The importance of these volunteered weather and impact observations has strongly risen over the past decade. We expect that this trend will continue and that storm spotters will become an essential part in severe weather warning, like they have been for decades in the United States of America. A rising number of incoming reports implies that quality management will become an increasing issue, and we finally discuss an idea how to handle this challenge.

Forecasting the Solar Drivers of Severe Space Weather from Active-Region Magnetograms

NASA Technical Reports Server (NTRS)

Falconer, David A.; Moore, Ronald L.; Barghouty, Abdulnasser F.; Khazanov, Igor

2012-01-01

Large flares and fast CMEs are the drivers of the most severe space weather including Solar Energetic Particle Events (SEP Events). Large flares and their co-produced CMEs are powered by the explosive release of free magnetic energy stored in non-potential magnetic fields of sunspot active regions. The free energy is stored in and released from the low-beta regime of the active region s magnetic field above the photosphere, in the chromosphere and low corona. From our work over the past decade and from similar work of several other groups, it is now well established that (1) a proxy of the free magnetic energy stored above the photosphere can be measured from photospheric magnetograms, and (2) an active region s rate of production of major CME/flare eruptions in the coming day or so is strongly correlated with its present measured value of the free-energy proxy. These results have led us to use the large database of SOHO/MDI full-disk magnetograms spanning Solar Cycle 23 to obtain empirical forecasting curves that from an active region s present measured value of the free-energy proxy give the active region s expected rates of production of major flares, CMEs, fast CMEs, and SEP Events in the coming day or so (Falconer et al 2011, Space Weather, 9, S04003). We will present these forecasting curves and demonstrate the accuracy of their forecasts. In addition, we will show that the forecasts for major flares and fast CMEs can be made significantly more accurate by taking into account not only the value of the free energy proxy but also the active region s recent productivity of major flares; specifically, whether the active region has produced a major flare (GOES class M or X) during the past 24 hours before the time of the measured magnetogram. By empirically determining the conversion of the value of free-energy proxy measured from a GONG or HMI magnetogram to that which would be measured from an MDI magnetogram, we have made GONG and HMI magnetograms useable with our MDI-based forecasting curves to forecast event rates.

Severe weather detection by using Japanese Total Lightning Network

NASA Astrophysics Data System (ADS)

Hobara, Yasuhide; Ishii, Hayato; Kumagai, Yuri; Liu, Charlie; Heckman, Stan; Price, Colin

2015-04-01

In this paper we demonstrate the preliminary results from the first Japanese Total Lightning Network. The University of Electro-Communications (UEC) recently deployed Earth Networks Total Lightning System over Japan to conduct various lightning research projects. Here we analyzed the total lightning data in relation with 10 severe events such as gust fronts and tornadoes occurred in 2014 in mainland Japan. For the analysis of these events, lightning jump algorithm was used to identify the increase of the flash rate in prior to the severe weather events. We found that lightning jumps associated with significant increasing lightning activities for total lightning and IC clearly indicate the severe weather occurrence than those for CGs.

How to explain variations in sea cliff erosion rate?

NASA Astrophysics Data System (ADS)

Prémaillon, Melody; Regard, Vincent; Dewez, Thomas

2017-04-01

Every rocky coast of the world is eroding at different rate (cliff retreat rates). Erosion is caused by a complex interaction of multiple sea weather factors. While numerous local studies exist and explain erosion processes on specific sites, global studies lack. We started to compile many of those local studies and analyse their results with a global point of view in order to quantify the various parameters influencing erosion rates. In other words: is erosion more important in energetic seas? Are chalk cliff eroding faster in rainy environment? etc. In order to do this, we built a database based on literature and national erosion databases. It now contains 80 publications which represents 2500 cliffs studied and more than 3500 erosion rate estimates. A statistical analysis was conducted on this database. On a first approximation, cliff lithology is the only clear signal explaining erosion rate variation: hard lithologies are eroding at 1cm/y or less, whereas unconsolidated lithologies commonly erode faster than 10cm/y. No clear statistical relation were found between erosion rate and external parameters such as sea energy (swell, tide) or weather condition, even on cliff with similar lithology.

Characterizing rainfall in the Tenerife island

NASA Astrophysics Data System (ADS)

Díez-Sierra, Javier; del Jesus, Manuel; Losada Rodriguez, Inigo

2017-04-01

In many locations, rainfall data are collected through networks of meteorological stations. The data collection process is nowadays automated in many places, leading to the development of big databases of rainfall data covering extensive areas of territory. However, managers, decision makers and engineering consultants tend not to extract most of the information contained in these databases due to the lack of specific software tools for their exploitation. Here we present the modeling and development effort put in place in the Tenerife island in order to develop MENSEI-L, a software tool capable of automatically analyzing a complete rainfall database to simplify the extraction of information from observations. MENSEI-L makes use of weather type information derived from atmospheric conditions to separate the complete time series into homogeneous groups where statistical distributions are fitted. Normal and extreme regimes are obtained in this manner. MENSEI-L is also able to complete missing data in the time series and to generate synthetic stations by using Kriging techniques. These techniques also serve to generate the spatial regimes of precipitation, both normal and extreme ones. MENSEI-L makes use of weather type information to also provide a stochastic three-day probability forecast for rainfall.

Cost of Lightning Strike Related Outages of Visual Navigational Aids at Airports in the United States

NASA Astrophysics Data System (ADS)

Rakas, J.; Nikolic, M.; Bauranov, A.

2017-12-01

Lightning storms are a serious hazard that can cause damage to vital human infrastructure. In aviation, lightning strikes cause outages to air traffic control equipment and facilities that result in major disruptions in the network, causing delays and financial costs measured in the millions of dollars. Failure of critical systems, such as Visual Navigational Aids (Visual NAVAIDS), are particularly dangerous since NAVAIDS are an essential part of landing procedures. Precision instrument approach, an operation utilized during the poor visibility conditions, utilizes several of these systems, and their failure leads to holding patterns and ultimately diversions to other airports. These disruptions lead to both ground and airborne delay. Accurate prediction of these outages and their costs is a key prerequisite for successful investment planning. The air traffic management and control sector need accurate information to successfully plan maintenance and develop a more robust system under the threat of increasing lightning rates. To analyze the issue, we couple the Remote Monitoring and Logging System (RMLS) database and the Aviation System Performance Metrics (ASPM) databases to identify lightning-induced outages, and connect them with weather conditions, demand and landing runway to calculate the total delays induced by the outages, as well as the number of cancellations and diversions. The costs are then determined by calculating direct costs to aircraft operators and costs of passengers' time for delays, cancellations and diversions. The results indicate that 1) not all NAVAIDS are created equal, and 2) outside conditions matter. The cost of an outage depends on the importance of the failed system and the conditions that prevailed before, during and after the failure. The outage that occurs during high demand and poor weather conditions is more likely to result in more delays and higher costs.

Understanding and Analyzing Latency of Near Real-time Satellite Data

NASA Astrophysics Data System (ADS)

Han, W.; Jochum, M.; Brust, J.

2016-12-01

Acquiring and disseminating time-sensitive satellite data in a timely manner is much concerned by researchers and decision makers of weather forecast, severe weather warning, disaster and emergency response, environmental monitoring, and so on. Understanding and analyzing the latency of near real-time satellite data is very useful and helpful to explore the whole data transmission flow, indentify the possible issues, and connect data providers and users better. The STAR (Center for Satellite Applications and Research of NOAA) Central Data Repository (SCDR) is a central repository to acquire, manipulate, and disseminate various types of near real-time satellite datasets to internal and external users. In this system, important timestamps, including observation beginning/end, processing, uploading, downloading, and ingestion, are retrieved and organized in the database, so the time length of each transmission phase can be figured out easily. Open source NoSQL database MongoDB is selected to manage the timestamp information because of features of dynamic schema, aggregation and data processing. A user-friendly user interface is developed to visualize and characterize the latency interactively. Taking the Himawari-8 HSD (Himawari Standard Data) file as an example, the data transmission phases, including creating HSD file from satellite observation, uploading the file to HimawariCloud, updating file link in the webpage, downloading and ingesting the file to SCDR, are worked out from the above mentioned timestamps. The latencies can be observed by time of period, day of week, or hour of day in chart or table format, and the anomaly latencies can be detected and reported through the user interface. Latency analysis provides data providers and users actionable insight on how to improve the data transmission of near real-time satellite data, and enhance its acquisition and management.

The iMeteo is a web-based weather visualization tool

NASA Astrophysics Data System (ADS)

Tuni San-Martín, Max; San-Martín, Daniel; Cofiño, Antonio S.

2010-05-01

iMeteo is a web-based weather visualization tool. Designed with an extensible J2EE architecture, it is capable of displaying information from heterogeneous data sources such as gridded data from numerical models (in NetCDF format) or databases of local predictions. All this information is presented in a user-friendly way, being able to choose the specific tool to display data (maps, graphs, information tables) and customize it to desired locations. *Modular Display System* Visualization of the data is achieved through a set of mini tools called widgets. A user can add them at will and arrange them around the screen easily with a drag and drop movement. They can be of various types and each can be configured separately, forming a really powerful and configurable system. The "Map" is the most complex widget, since it can show several variables simultaneously (either gridded or point-based) through a layered display. Other useful widgets are the the "Histogram", which generates a graph with the frequency characteristics of a variable and the "Timeline" which shows the time evolution of a variable at a given location in an interactive way. *Customization and security* Following the trends in web development, the user can easily customize the way data is displayed. Due to programming in client side with technologies like AJAX, the interaction with the application is similar to the desktop ones because there are rapid respone times. If a user is registered then he could also save his settings in the database, allowing access from any system with Internet access with his particular setup. There is particular emphasis on application security. The administrator can define a set of user profiles, which may have associated restrictions on access to certain data sources, geographic areas or time intervals.

Analysis of weather condition influencing fire regime in Italy

NASA Astrophysics Data System (ADS)

Bacciu, Valentina; Masala, Francesco; Salis, Michele; Sirca, Costantino; Spano, Donatella

2014-05-01

Fires have a crucial role within Mediterranean ecosystems, with both negative and positive impacts on all biosphere components and with reverberations on different scales. Fire determines the landscape structure and plant composition, but it is also the cause of enormous economic and ecological damages, beside the loss of human life. In addition, several authors are in agreement suggesting that, during the past decades, changes on fire patterns have occurred, especially in terms of fire-prone areas expansion and fire season lengthening. Climate and weather are two of the main controlling agents, directly and indirectly, of fire regime influencing vegetation productivity, causing water stress, igniting fires through lightning, or modulating fire behavior through wind. On the other hand, these relationships could be not warranted in areas where most ignitions are caused by people (Moreno et al. 2009). Specific analyses of the driving forces of fire regime across countries and scales are thus still required in order to better anticipate fire seasons and also to advance our knowledge of future fire regimes. The objective of this work was to improve our knowledge of the relative effects of several weather variables on forest fires in Italy for the period 1985-2008. Meteorological data were obtained through the MARS (Monitoring Agricultural Resources) database, interpolated at 25x25 km scale. Fire data were provided by the JRC (Join Research Center) and the CFVA (Corpo Forestale e di Vigilanza Ambientale, Sardinia). A hierarchical cluster analysis, based on fire and weather data, allowed the identification of six homogeneous areas in terms of fire occurrence and climate (pyro-climatic areas). Two statistical techniques (linear and non-parametric models) were applied in order to assess if inter-annual variability in weather pattern and fire events had a significant trend. Then, through correlation analysis and multi-linear regression modeling, we investigated the influence of weather variables on fire activity across a range of time- and spatial-scales. The analysis revealed a general decrease of both number of fires and burned area, although not everywhere with the same magnitude. Overall, regression models where highly significant (p<0.001), and the explained variance ranged from 36% to 80% for fire number and from 37% to 76% for burned area, depending on pyro-climatic area. Moreover, our results contributed in determining the relative importance of climate variables acting at different timescales as control on intrinsic (i.e. flammability and moisture) and extrinsic (i.e. fuel amount and structure) characteristics of vegetation, thus strongly influencing fire occurrence. The good performance of our models, especially in the most fire affected pyro-climatic areas of Italy, and the better understanding of the main driver of fire variability gained through this work could be of great help for fire management among the different pyro-climatic areas.

Incorporating real-time traffic and weather data to explore road accident likelihood and severity in urban arterials.

PubMed

Theofilatos, Athanasios

2017-06-01

The effective treatment of road accidents and thus the enhancement of road safety is a major concern to societies due to the losses in human lives and the economic and social costs. The investigation of road accident likelihood and severity by utilizing real-time traffic and weather data has recently received significant attention by researchers. However, collected data mainly stem from freeways and expressways. Consequently, the aim of the present paper is to add to the current knowledge by investigating accident likelihood and severity by exploiting real-time traffic and weather data collected from urban arterials in Athens, Greece. Random Forests (RF) are firstly applied for preliminary analysis purposes. More specifically, it is aimed to rank candidate variables according to their relevant importance and provide a first insight on the potential significant variables. Then, Bayesian logistic regression as well finite mixture and mixed effects logit models are applied to further explore factors associated with accident likelihood and severity respectively. Regarding accident likelihood, the Bayesian logistic regression showed that variations in traffic significantly influence accident occurrence. On the other hand, accident severity analysis revealed a generally mixed influence of traffic variations on accident severity, although international literature states that traffic variations increase severity. Lastly, weather parameters did not find to have a direct influence on accident likelihood or severity. The study added to the current knowledge by incorporating real-time traffic and weather data from urban arterials to investigate accident occurrence and accident severity mechanisms. The identification of risk factors can lead to the development of effective traffic management strategies to reduce accident occurrence and severity of injuries in urban arterials. Copyright © 2017 Elsevier Ltd and National Safety Council. All rights reserved.

Aviation weather services

NASA Technical Reports Server (NTRS)

Sprinkle, C. H.

1983-01-01

The primary responsibilities of the National Weather Service (NWS) are to: provide warnings of severe weather and flooding for the protection of life and property; provide public forecasts for land and adjacent ocean areas for planning and operation; and provide weather support for: production of food and fiber; management of water resources; production, distribution and use of energy; and efficient and safe air operations.

77 FR 53886 - February 2011 Southwest Cold Weather Event Follow-up Technical Conference; Notice of Technical...

Federal Register 2010, 2011, 2012, 2013, 2014

2012-09-04

... Southwest Cold Weather Event Follow-up Technical Conference; Notice of Technical Conference Take notice that... August 16, 2011 Report on Outages and Curtailments During the Southwest Cold Weather Event of February 1... severe cold weather issues that led to rolling blackouts affecting over 4 million customers and natural...

Socio-Economic Impacts of Space Weather and User Needs for Space Weather Information

NASA Astrophysics Data System (ADS)

Worman, S. L.; Taylor, S. M.; Onsager, T. G.; Adkins, J. E.; Baker, D. N.; Forbes, K. F.

2017-12-01

The 2015 National Space Weather Strategy and Space Weather Action Plan (SWAP) details the activities, outcomes, and timelines to build a "Space Weather Ready Nation." NOAA's Space Weather Prediction Center and Abt Associates are working together on two SWAP initiatives: (1) identifying, describing, and quantifying the socio-economic impacts of moderate and severe space weather; and (2) outreach to engineers and operators to better understand user requirements for space weather products and services. Both studies cover four technological sectors (electric power, commercial aviation, satellites, and GNSS users) and rely heavily on industry input. Findings from both studies are essential for decreasing vulnerabilities and enhancing preparedness.

DEVELOPMENT OF A COMPOSITION DATABASE FOR SELECTED MULTICOMPONENT OILS

EPA Science Inventory

During any oil spill incident, the properties of the spilled oil, including its chemical composition, physical properties, and changes due to weathering, are immediately important. U.S. EPA is currently developing new models for application to environmental problems associated...

The ICARDA agro-climate tool

USDA-ARS?s Scientific Manuscript database

A Visual Basic agro-climate application by climatologists at the International Center for Agricultural Research in the Dry Areas and the U.S. Department of Agriculture is described here. The database from which the application derives climate information consists of weather generator parameters der...

The ICARDA Agro-Climate Tool

USDA-ARS?s Scientific Manuscript database

A Visual Basic agro-climate application developed by climatologists at the International Center for Agricultural Research in the Dry Areas and the U.S. Department of Agriculture is described here. The database from which the application derives climate information consists of weather generator param...

Data Dealers Face Stormy Weather.

ERIC Educational Resources Information Center

Tenopir, Carol; Barry, Jeff

1998-01-01

This report, the second annual Database Marketplace survey, analyzes information gathered from 29 companies that distribute and produce information available through online, Web, or CD-ROM systems. In addition to data, topics include company mergers, takeovers, sales, accomplishments, and future plans. (Author/LRW)

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

NASA Technical Reports Server (NTRS)

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

2002-01-01

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

Impact of Probabilistic Weather on Flight Routing Decisions

NASA Technical Reports Server (NTRS)

Sheth, Kapil; Sridhar, Banavar; Mulfinger, Daniel

2006-01-01

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

The Road Weather Bulletin : Road Weather Management Publications and Training Materials

DOT National Transportation Integrated Search

2011-01-01

This document summarizes results from the Road Weather Policy Forum held November 8-9, 2010 in Washington, D.C. The agenda outlines a research framework, broad research needs, and the various roles and responsibilities of several stakeholder sectors.

Implementation of the ground level enhancement alert software at NMDB database

NASA Astrophysics Data System (ADS)

Mavromichalaki, Helen; Souvatzoglou, George; Sarlanis, Christos; Mariatos, George; Papaioannou, Athanasios; Belov, Anatoly; Eroshenko, Eugenia; Yanke, Victor; NMDB Team

2010-11-01

The European Commission is supporting the real-time database for high-resolution neutron monitor measurements (NMDB) as an e-Infrastructures project in the Seventh Framework Programme in the Capacities section. The realization of the NMDB will provide the opportunity for several applications most of which will be implemented in real-time. An important application will be the establishment of an Alert signal when dangerous solar particle events are heading to the Earth, resulting into a ground level enhancement (GLE) registered by neutron monitors (NMs). The cosmic ray community has been occupied with the question of establishing such an Alert for many years and recently several groups succeeded in creating a proper algorithm capable of detecting space weather threats in an off-line mode. A lot of original work has been done to this direction and every group working in this field performed routine runs for all GLE cases, resulting into statistical analyses of GLE events. The next step was to make this algorithm as accurate as possible and most importantly, working in real-time. This was achieved when, during the last GLE observed so far, a real-time GLE Alert signal was produced. In this work, the steps of this procedure as well as the functionality of this algorithm for both the scientific community and users are being discussed. Nevertheless, the transition of the Alert algorithm to the NMDB is also being discussed.

A predictive model for spotted wilt epidemics in peanut based on local weather conditions and the tomato spotted wilt virus risk index.

PubMed

Olatinwo, R O; Paz, J O; Brown, S L; Kemerait, R C; Culbreath, A K; Beasley, J P; Hoogenboom, G

2008-10-01

Tomato spotted wilt virus (TSWV), a member of the genus Tospovirus (family Bunyaviridae), is an important plant virus that causes severe damage to peanut (Arachis hypogaea) in the southeastern United States. Disease severity has been extremely variable in individual fields in Georgia, due to several factors including variability in weather patterns. A TSWV risk index has been developed by the University of Georgia to aid peanut growers with the assessment and avoidance of high risk situations. This study was conducted to examine the relationship between weather parameters and spotted wilt severity in peanut, and to develop a predictive model that integrates localized weather information into the risk index. On-farm survey data collected during 1999, 2002, 2004, and 2005 growing seasons, and derived weather variables during the same years were analyzed using nonlinear and multiple regression analyses. Meteorological data were obtained from the Georgia Automated Environmental Monitoring Network. The best model explained 61% of the variation in spotted wilt severity (square root transformed) as a function of the interactions between the TSWV risk index, the average daily temperature in April (TavA), the average daily minimum temperature between March and April (TminMA), the accumulated rainfall in March (RainfallM), the accumulated rainfall in April (RainfallA), the number of rain days in April (RainDayA), evapotranspiration in April (EVTA), and the number of days from 1 January to the planting date (JulianDay). Integrating this weather-based model with the TSWV risk index may help peanut growers more effectively manage tomato spotted wilt disease.

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.

Mountain ranges, climate and weathering. Do orogens strengthen or weaken the silicate weathering carbon sink?

NASA Astrophysics Data System (ADS)

Maffre, Pierre; Ladant, Jean-Baptiste; Moquet, Jean-Sébastien; Carretier, Sébastien; Labat, David; Goddéris, Yves

2018-07-01

The role of mountains in the geological evolution of the carbon cycle has been intensively debated for the last decades. Mountains are thought to increase the local physical erosion, which in turns promotes silicate weathering, organic carbon transport and burial, and release of sulfuric acid by dissolution of sulfides. In this contribution, we explore the impact of mountain ranges on silicate weathering. Mountains modify the global pattern of atmospheric circulation as well as the local erosion conditions. Using an IPCC-class climate model, we first estimate the climatic impact of mountains by comparing the present day climate with the climate when all the continents are assumed to be flat. We then use these climate output to calculate weathering changes when mountains are present or absent, using standard expression for physical erosion and a 1D vertical model for rock weathering. We found that large-scale climate changes and enhanced rock supply by erosion due to mountain uplift have opposite effect, with similar orders of magnitude. A thorough testing of the weathering model parameters by data-model comparison shows that best-fit parameterizations lead to a decrease of weathering rate in the absence of mountain by about 20%. However, we demonstrate that solutions predicting an increase in weathering in the absence of mountain cannot be excluded. A clear discrimination between the solutions predicting an increase or a decrease in global weathering is pending on the improvement of the existing global databases for silicate weathering. Nevertheless, imposing a constant and homogeneous erosion rate for models without relief, we found that weathering decrease becomes unequivocal for very low erosion rates (below 10 t/km2/yr). We conclude that further monitoring of continental silicate weathering should be performed with a spatial distribution allowing to discriminate between the various continental landscapes (mountains, plains …).

Using fire-weather forecasts and local weather observations in predicting burning index for individual fire-danger stations.

Treesearch

Owen P. Cramer

1958-01-01

Any agency engaged in forest-fire control needs accurate weather forecasts and systematic procedures for making the best use of predicted and reported weather information. This study explores the practicability of using several tabular and graphical aids for converting area forecasts and local observations of relative humidity and wind speed into predicted values for...

National Weather- RFC Development Management

Science.gov Websites

Map News Organization Search NWS ALL NOAA Go RFC Development Management Presentations Projects & ; Plans RFC Development Program RFC Archive Database Documentation Outline Workshops Contact Us resources and services. Description Graphic The RFC Development Management component of the Office of

Forecast and virtual weather driven plant disease risk modeling system

USDA-ARS?s Scientific Manuscript database

We describe a system in use and development that leverages public weather station data, several spatialized weather forecast types, leaf wetness estimation, generic plant disease models, and online statistical evaluation. Convergent technological developments in all these areas allow, with funding f...

Weather-Related Hazards and Population Change: A Study of Hurricanes and Tropical Storms in the United States, 1980–2012

PubMed Central

FUSSELL, ELIZABETH; CURRAN, SARA R.; DUNBAR, MATTHEW D.; BABB, MICHAEL A.; THOMPSON, LUANNE; MEIJER-IRONS, JACQUELINE

2017-01-01

Environmental determinists predict that people move away from places experiencing frequent weather hazards, yet some of these areas have rapidly growing populations. This analysis examines the relationship between weather events and population change in all U.S. counties that experienced hurricanes and tropical storms between 1980 and 2012. Our database allows for more generalizable conclusions by accounting for heterogeneity in current and past hurricane events and losses and past population trends. We find that hurricanes and tropical storms affect future population growth only in counties with growing, high-density populations, which are only 2 percent of all counties. In those counties, current year hurricane events and related losses suppress future population growth, although cumulative hurricane-related losses actually elevate population growth. Low-density counties and counties with stable or declining populations experience no effect of these weather events. Our analysis provides a methodologically informed explanation for contradictory findings in prior studies. PMID:29326480

Weather-Related Hazards and Population Change: A Study of Hurricanes and Tropical Storms in the United States, 1980-2012.

PubMed

Fussell, Elizabeth; Curran, Sara R; Dunbar, Matthew D; Babb, Michael A; Thompson, Luanne; Meijer-Irons, Jacqueline

2017-01-01

Environmental determinists predict that people move away from places experiencing frequent weather hazards, yet some of these areas have rapidly growing populations. This analysis examines the relationship between weather events and population change in all U.S. counties that experienced hurricanes and tropical storms between 1980 and 2012. Our database allows for more generalizable conclusions by accounting for heterogeneity in current and past hurricane events and losses and past population trends. We find that hurricanes and tropical storms affect future population growth only in counties with growing, high-density populations, which are only 2 percent of all counties. In those counties, current year hurricane events and related losses suppress future population growth, although cumulative hurricane-related losses actually elevate population growth. Low-density counties and counties with stable or declining populations experience no effect of these weather events. Our analysis provides a methodologically informed explanation for contradictory findings in prior studies.

A new precipitation and drought climatology based on weather patterns

PubMed Central

Fowler, Hayley J.; Kilsby, Christopher G.; Neal, Robert

2017-01-01

ABSTRACT Weather‐pattern, or weather‐type, classifications are a valuable tool in many applications as they characterize the broad‐scale atmospheric circulation over a given region. This study analyses the aspects of regional UK precipitation and meteorological drought climatology with respect to a new set of objectively defined weather patterns. These new patterns are currently being used by the Met Office in several probabilistic forecasting applications driven by ensemble forecasting systems. Weather pattern definitions and daily occurrences are mapped to Lamb weather types (LWTs), and parallels between the two classifications are drawn. Daily precipitation distributions are associated with each weather pattern and LWT. Standardized precipitation index (SPI) and drought severity index (DSI) series are calculated for a range of aggregation periods and seasons. Monthly weather‐pattern frequency anomalies are calculated for SPI wet and dry periods and for the 5% most intense DSI‐based drought months. The new weather‐pattern definitions and daily occurrences largely agree with their respective LWTs, allowing comparison between the two classifications. There is also broad agreement between weather pattern and LWT changes in frequencies. The new data set is shown to be adequate for precipitation‐based analyses in the UK, although a smaller set of clustered weather patterns is not. Furthermore, intra‐pattern precipitation variability is lower in the new classification compared to the LWTs, which is an advantage in this context. Six of the new weather patterns are associated with drought over the entire UK, with several other patterns linked to regional drought. It is demonstrated that the new data set of weather patterns offers a new opportunity for classification‐based analyses in the UK. PMID:29456290

Severe Weather Forecast Decision Aid

NASA Technical Reports Server (NTRS)

Bauman, William H., III; Wheeler, Mark

2005-01-01

The Applied Meteorology Unit developed a forecast tool that provides an assessment of the likelihood of local convective severe weather for the day in order to enhance protection of personnel and material assets of the 45th Space Wing Cape Canaveral Air Force Station (CCAFS), and Kennedy Space Center (KSC).

Uncertainty Comparison of Visual Sensing in Adverse Weather Conditions†

PubMed Central

Lo, Shi-Wei; Wu, Jyh-Horng; Chen, Lun-Chi; Tseng, Chien-Hao; Lin, Fang-Pang; Hsu, Ching-Han

2016-01-01

This paper focuses on flood-region detection using monitoring images. However, adverse weather affects the outcome of image segmentation methods. In this paper, we present an experimental comparison of an outdoor visual sensing system using region-growing methods with two different growing rules—namely, GrowCut and RegGro. For each growing rule, several tests on adverse weather and lens-stained scenes were performed, taking into account and analyzing different weather conditions with the outdoor visual sensing system. The influence of several weather conditions was analyzed, highlighting their effect on the outdoor visual sensing system with different growing rules. Furthermore, experimental errors and uncertainties obtained with the growing rules were compared. The segmentation accuracy of flood regions yielded by the GrowCut, RegGro, and hybrid methods was 75%, 85%, and 87.7%, respectively. PMID:27447642

Pilot behaviors in the face of adverse weather: A new look at an old problem.

PubMed

Batt, Richard; O'Hare, David

2005-06-01

Weather-related general aviation accidents remain one of the most significant causes for concern in aviation safety. Previous studies have typically compared accident and non-accident cases. In contrast, the current study does not concentrate on occurrence outcome. Instead, the emphasis is on the different behaviors that pilots exhibit in the face of adverse weather and, by inference, on the decision-making processes that underlie those behaviors. This study compares three weather-related behaviors that reflect different levels of risk: visual flight rules flight into instrument meteorological conditions ('VFR into IMC'); precautionary landing; and other significant weather avoidance actions. Occurrence data (n=491) were drawn from the Australian Transport Safety Bureau database of aviation occurrences, and included weather-related accidents, incidents, and 'normal operationsd.' There were few significant differences between the three weather-related behavior groups in terms of pilot demographics, aircraft characteristics, geographic or environmental factors, or absolute flight distances. The pattern of relative flight distances (a psychological construct) was markedly different for the three groups, with pilots in the weather avoidance group being distinguished by taking timely action. The relative distance results suggest that the mid-point of the flight can be a 'psychological turning point' for pilots, irrespective of the absolute flight distance involved. Hence, pilots' behavior was sometimes influenced by psychological factors not related to any particular operational aspect of the flight. The results of the weather avoidance group indicate that a safe pilot is a proactive pilot. Dealing with adverse weather is not a one-off decision but a continually evolving process. This aspect is discussed in terms of the concept of 'mindfulness'.

A database to manage flood risk in Catalonia

NASA Astrophysics Data System (ADS)

Echeverria, S.; Toldrà, R.; Verdaguer, I.

2009-09-01

We call priority action spots those local sites where heavy rain, increased river flow, sea storms and other flooding phenomena can cause human casualties or severe damage to property. Some examples are campsites, car parks, roads, chemical factories… In order to keep to a minimum the risk of these spots, both a prevention programme and an emergency response programme are required. The flood emergency plan of Catalonia (INUNCAT) prepared in 2005 included already a listing of priority action spots compiled by the Catalan Water Agency (ACA), which was elaborated taking into account past experience, hydraulic studies and information available by several knowledgeable sources. However, since land use evolves with time this listing of priority action spots has become outdated and incomplete. A new database is being built. Not only does this new database update and expand the previous listing, but adds to each entry information regarding prevention measures and emergency response: which spots are the most hazardous, under which weather conditions problems arise, which ones should have their access closed as soon as these conditions are forecast or actually given, which ones should be evacuated, who is in charge of the preventive actions or emergency response and so on. Carrying out this programme has to be done with the help and collaboration of all the organizations involved, foremost with the local authorities in the areas at risk. In order to achieve this goal a suitable geographical information system is necessary which can be easily used by all actors involved in this project. The best option has turned out to be the Spatial Data Infrastructure of Catalonia (IDEC), a platform to share spatial data on the Internet involving the Generalitat de Catalunya, Localret (a consortium of local authorities that promotes information technology) and other institutions.

Seasonality and Children’s Blood Lead Levels: Developing a Predictive Model Using Climatic Variables and Blood Lead Data from Indianapolis, Indiana, Syracuse, New York, and New Orleans, Louisiana (USA)

PubMed Central

Laidlaw, Mark A.S.; Mielke, Howard W.; Filippelli, Gabriel M.; Johnson, David L.; Gonzales, Christopher R.

2005-01-01

On a community basis, urban soil contains a potentially large reservoir of accumulated lead. This study was undertaken to explore the temporal relationship between pediatric blood lead (BPb), weather, soil moisture, and dust in Indianapolis, Indiana; Syracuse, New York; and New Orleans, Louisiana. The Indianapolis, Syracuse, and New Orleans pediatric BPb data were obtained from databases of 15,969, 14,467, and 2,295 screenings, respectively, collected between December 1999 and November 2002, January 1994 and March 1998, and January 1998 and May 2003, respectively. These average monthly child BPb levels were regressed against several independent variables: average monthly soil moisture, particulate matter < 10 μm in diameter (PM10), wind speed, and temperature. Of temporal variation in urban children’s BPb, 87% in Indianapolis (R2 = 0.87, p = 0.0004), 61% in Syracuse (R2 = 0.61, p = 0.0012), and 59% in New Orleans (R2 = 0.59, p = 0.0000078) are explained by these variables. A conceptual model of urban Pb poisoning is suggested: When temperature is high and evapotranspiration maximized, soil moisture decreases and soil dust is deposited. Under these combined weather conditions, Pb-enriched PM10 dust disperses in the urban environment and causes elevated Pb dust loading. Thus, seasonal variation of children’s Pb exposure is probably caused by inhalation and ingestion of Pb brought about by the effect of weather on soils and the resulting fluctuation in Pb loading. PMID:15929906

Redefining climate regions in the United States of America using satellite remote sensing and machine learning for public health applications.

PubMed

Liss, Alexander; Koch, Magaly; Naumova, Elena N

2014-12-01

Existing climate classification has not been designed for an efficient handling of public health scenarios. This work aims to design an objective spatial climate regionalization method for assessing health risks in response to extreme weather. Specific climate regions for the conterminous United States of America (USA) were defined using satellite remote sensing (RS) data and compared with the conventional Köppen-Geiger (KG) divisions. Using the nationwide database of hospitalisations among the elderly (≥65 year olds), we examined the utility of a RS-based climate regionalization to assess public health risk due to extreme weather, by comparing the rate of hospitalisations in response to thermal extremes across climatic regions. Satellite image composites from 2002-2012 were aggregated, masked and compiled into a multi-dimensional dataset. The conterminous USA was classified into 8 distinct regions using a stepwise regionalization approach to limit noise and collinearity (LKN), which exhibited a high degree of consistency with the KG regions and a well-defined regional delineation by annual and seasonal temperature and precipitation values. The most populous was a temperate wet region (10.9 million), while the highest rate of hospitalisations due to exposure to heat and cold (9.6 and 17.7 cases per 100,000 persons at risk, respectively) was observed in the relatively warm and humid south-eastern region. RS-based regionalization demonstrates strong potential for assessing the adverse effects of severe weather on human health and for decision support. Its utility in forecasting and mitigating these effects has to be further explored.

Verification of National Weather Service spot forecasts using surface observations

NASA Astrophysics Data System (ADS)

Lammers, Matthew Robert

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

The influence of weather and fuel type on the fuel composition of the area burned by forest fires in Ontario, 1996-2006.

PubMed

Podur, Justin J; Martell, David L

2009-07-01

Forest fires are influenced by weather, fuels, and topography, but the relative influence of these factors may vary in different forest types. Compositional analysis can be used to assess the relative importance of fuels and weather in the boreal forest. Do forest or wild land fires burn more flammable fuels preferentially or, because most large fires burn in extreme weather conditions, do fires burn fuels in the proportions they are available despite differences in flammability? In the Canadian boreal forest, aspen (Populus tremuloides) has been found to burn in less than the proportion in which it is available. We used the province of Ontario's Provincial Fuels Database and fire records provided by the Ontario Ministry of Natural Resources to compare the fuel composition of area burned by 594 large (>40 ha) fires that occurred in Ontario's boreal forest region, a study area some 430,000 km2 in size, between 1996 and 2006 with the fuel composition of the neighborhoods around the fires. We found that, over the range of fire weather conditions in which large fires burned and in a study area with 8% aspen, fires burn fuels in the proportions that they are available, results which are consistent with the dominance of weather in controlling large fires.

76 FR 52229 - Establishment of Area Navigation Route Q-37; Texas

Federal Register 2010, 2011, 2012, 2013, 2014

2011-08-22

... route around potentially constrained airspace during convective weather events in west Texas. DATES... around potentially constrained airspace during convective weather events in west Texas. Additionally, the new route is being integrated into the existing severe weather national playbook routes to Houston, TX...

Identifying Hail Signatures in Satellite Imagery from the 9-10 August 2011 Severe Weather Event

NASA Technical Reports Server (NTRS)

Dryden, Rachel L.; Molthan, Andrew L.; Cole, Tony A.; Bell, Jordan

2014-01-01

Severe thunderstorms can produce large hail that causes property damage, livestock fatalities, and crop failure. However, detailed storm surveys of hail damage conducted by the National Weather Service (NWS) are not required. Current gaps also exist between Storm Prediction Center (SPC) hail damage estimates and crop-insurance payouts. NASA's Moderate Resolution Imaging Spectroradiometer (MODIS) instrument aboard the Terra and Aqua satellites can be used to support NWS damage assessments, particularly to crops during the growing season. The two-day severe weather event across western Nebraska and central Kansas during 9-10 August 2011 offers a case study for investigating hail damage signatures by examining changes in Normalized Difference Vegetation Index (NDVI) derived from MODIS imagery. By analyzing hail damage swaths in satellite imagery, potential economic losses due to crop damage can be quantified and further improve the estimation of weather impacts on agriculture without significantly increasing manpower requirements.

Techniques for Efficiently Managing Large Geosciences Data Sets

NASA Astrophysics Data System (ADS)

Kruger, A.; Krajewski, W. F.; Bradley, A. A.; Smith, J. A.; Baeck, M. L.; Steiner, M.; Lawrence, R. E.; Ramamurthy, M. K.; Weber, J.; Delgreco, S. A.; Domaszczynski, P.; Seo, B.; Gunyon, C. A.

2007-12-01

We have developed techniques and software tools for efficiently managing large geosciences data sets. While the techniques were developed as part of an NSF-Funded ITR project that focuses on making NEXRAD weather data and rainfall products available to hydrologists and other scientists, they are relevant to other geosciences disciplines that deal with large data sets. Metadata, relational databases, data compression, and networking are central to our methodology. Data and derived products are stored on file servers in a compressed format. URLs to, and metadata about the data and derived products are managed in a PostgreSQL database. Virtually all access to the data and products is through this database. Geosciences data normally require a number of processing steps to transform the raw data into useful products: data quality assurance, coordinate transformations and georeferencing, applying calibration information, and many more. We have developed the concept of crawlers that manage this scientific workflow. Crawlers are unattended processes that run indefinitely, and at set intervals query the database for their next assignment. A database table functions as a roster for the crawlers. Crawlers perform well-defined tasks that are, except for perhaps sequencing, largely independent from other crawlers. Once a crawler is done with its current assignment, it updates the database roster table, and gets its next assignment by querying the database. We have developed a library that enables one to quickly add crawlers. The library provides hooks to external (i.e., C-language) compiled codes, so that developers can work and contribute independently. Processes called ingesters inject data into the system. The bulk of the data are from a real-time feed using UCAR/Unidata's IDD/LDM software. An exciting recent development is the establishment of a Unidata HYDRO feed that feeds value-added metadata over the IDD/LDM. Ingesters grab the metadata and populate the PostgreSQL tables. These and other concepts we have developed have enabled us to efficiently manage a 70 Tb (and growing) data weather radar data set.

The North Alabama Lightning Mapping Array: Recent Severe Storm Observations and Future Prospects

NASA Technical Reports Server (NTRS)

Goodman, S. J.; Blakeslee, R.; Christian, H.; Koshak, W.; Bailey, J.; Hall, J.; McCaul, E.; Buechler, D.; Darden, C.; Burks, J.

2004-01-01

The North Alabama Lightning Mapping Array became operational in November 2001 as a principal component of a severe weather test bed to infuse new science and technology into the short-term forecasting of severe and hazardous weather, principally within nearby National Weather Service forecast offices. Since the installation of the LMA, it has measured the total lightning activity of a large number of severe weather events, including three supercell tornado outbreaks, two supercell hailstorm events, and numerous microburst-producing storms and ordinary non-severe thunderstorms. The key components of evolving storm morphology examined are the time rate-of-change (temporal trending) of storm convective and precipitation characteristics that can be diagnosed in real-time using NEXRAD WSR-88D Doppler radar (echo growth and decay, precipitation structures and velocity features, outflow boundaries), LMA (total lightning flash rate and its trend) and National Lightning Detection Network (cloud-to- ground lightning, its polarity and trends). For example, in a transitional season supercell tornado outbreak, peak total flash rates for typical supercells in Tennessee reached 70-100/min, and increases in the total flash rate occurred during storm intensification as much as 20-25 min prior to at least some of the tornadoes. The most intense total flash rate measured during this outbreak (over 800 flashes/min) occurred in a storm in Alabama. In the case of a severe summertime pulse thunderstorm in North Alabama, the peak total flash rate reached 300/min, with a strong increase in total lightning evident some 9 min before damaging winds were observed at the surface. In this paper we provide a sampling of LMA observations and products during severe weather events to illustrate the capability of the system, and discuss the prospects for improving the short-term forecasting of convective weather using total lightning data.

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

NASA Astrophysics Data System (ADS)

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

2017-02-01

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

National Space Weather Program Advances on Several Fronts

NASA Astrophysics Data System (ADS)

Gunzelman, Mark; Babcock, Michael

2008-10-01

The National Space Weather Program (NSWP; http://www.nswp.gov) is a U.S. federal government interagency initiative through the Office of the Federal Coordinator for Meteorology that was created to speed the improvement of space weather services for the nation. The Committee for Space Weather (CSW) under the NSWP has continued to advance the program on a number of fronts over the past 12 months.

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.

Utilization of satellite imagery by in-flight aircraft. [for weather information

NASA Technical Reports Server (NTRS)

Luers, J. K.

1976-01-01

Present and future utilization of satellite weather data by commercial aircraft while in flight was assessed. Weather information of interest to aviation that is available or will become available with future geostationary satellites includes the following: severe weather areas, jet stream location, weather observation at destination airport, fog areas, and vertical temperature profiles. Utilization of this information by in-flight aircraft is especially beneficial for flights over the oceans or over remote land areas where surface-based observations and communications are sparse and inadequate.

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

Analyses of factors of crash avoidance maneuvers using the general estimates system.

PubMed

Yan, Xuedong; Harb, Rami; Radwan, Essam

2008-06-01

Taking an effective corrective action to a critical traffic situation provides drivers an opportunity to avoid crash occurrence and minimize crash severity. The objective of this study is to investigate the relationship between the probability of taking corrective actions and the characteristics of drivers, vehicles, and driving environments. Using the 2004 GES crash database, this study classified drivers who encountered critical traffic events (identified as P_CRASH3 in the GES database) into two pre-crash groups: corrective avoidance actions group and no corrective avoidance actions group. Single and multiple logistic regression analyses were performed to identify potential traffic factors associated with the probability of drivers taking corrective actions. The regression results showed that the driver/vehicle factors associated with the probability of taking corrective actions include: driver age, gender, alcohol use, drug use, physical impairments, distraction, sight obstruction, and vehicle type. In particular, older drivers, female drivers, drug/alcohol use, physical impairment, distraction, or poor visibility may increase the probability of failing to attempt to avoid crashes. Moreover, drivers of larger size vehicles are 42.5% more likely to take corrective avoidance actions than passenger car drivers. On the other hand, the significant environmental factors correlated with the drivers' crash avoidance maneuver include: highway type, number of lanes, divided/undivided highway, speed limit, highway alignment, highway profile, weather condition, and surface condition. Some adverse highway environmental factors, such as horizontal curves, vertical curves, worse weather conditions, and slippery road surface conditions are correlated with a higher probability of crash avoidance maneuvers. These results may seem counterintuitive but they can be explained by the fact that motorists may be more likely to drive cautiously in those adverse driving environments. The analyses revealed that drivers' distraction could be the highest risk factor leading to the failure of attempting to avoid crashes. Further analyses entailing distraction causes (e.g., cellular phone use) and their possible countermeasures need to be conducted. The age and gender factors are overrepresented in the "no avoidance maneuver." A possible solution could involve the integration of a new function in the current ITS technologies. A personalized system, which could be related to the expected type of maneuver for a driver with certain characteristics, would assist different drivers with different characteristics to avoid crashes. Further crash database studies are recommended to investigate the association of drivers' emergency maneuvers such as braking, steering, or their combination with crash severity.

Wacky Weather

ERIC Educational Resources Information Center

Sabarre, Amy; Gulino, Jacqueline

2013-01-01

What do a leaf blower, water hose, fan, and ice cubes have in common? Ask the students who participated in an integrative science, technology, engineering, and mathematics (I-STEM) education unit, "Wacky Weather," and they will tell say "fun and severe weather"--words one might not have expected! The purpose of the unit…

Phenology Information Contributes to Reduce Temporal Basis Risk in Agricultural Weather Index Insurance.

PubMed

Dalhaus, Tobias; Musshoff, Oliver; Finger, Robert

2018-01-08

Weather risks are an essential and increasingly important driver of agricultural income volatility. Agricultural insurances contribute to support farmers to cope with these risks. Among these insurances, weather index insurances (WII) are an innovative tool to cope with climatic risks in agriculture. Using WII, farmers receive an indemnification not based on actual yield reductions but are compensated based on a measured weather index, such as rainfall at a nearby weather station. The discrepancy between experienced losses and actual indemnification, basis risk, is a key challenge. In particular, specifications of WII used so far do not capture critical plant growth phases adequately. Here, we contribute to reduce basis risk by proposing novel procedures how occurrence dates and shifts of growth phases over time and space can be considered and test for their risk reducing potential. Our empirical example addresses drought risks in the critical growth phase around the anthesis stage in winter wheat production in Germany. We find spatially explicit, public and open databases of phenology reports to contribute to reduce basis risk and thus improve the attractiveness of WII. In contrast, we find growth stage modelling based on growing degree days (thermal time) not to result in significant improvements.

Effects of television weather broadcasters on viewers during severe weather: To be or not to be on-screen

NASA Astrophysics Data System (ADS)

Lea, Amanda Marie

An association was tested between the presence of a television weather broadcaster on-screen and viewers' likelihood to seek shelter, measured via risk perception and preventative behavior. Social networking websites were used to recruit respondents. Four clips of archived severe weather videos, one pair (on-screen and off-screen broadcaster) using the reflectivity product and another pair (on-screen and off-screen broadcaster) using velocity product, were presented to participants. Viewers' trust and weather salience were also quantified for additional interactions. A relationship between viewers' risk perception (preflectivity = 0.821, pvelocity = 0.625) and preventative behavior (preflectivity = 0.217, p velocity = 0.236) and the presence of the broadcaster on-screen was not found. The reflectivity product was associated with higher risk perception and preventative behavior scores than the velocity product (prp = 0.000, ppb = 0.000).

Assessment of the contribution of sewer deposits to suspended solids loads in combined sewer systems during rain events.

PubMed

Hannouche, A; Chebbo, G; Joannis, C

2014-04-01

Within the French observatories network SOERE "URBIS," databases of continuous turbidity measurements accumulating hundreds of events and many dry weather days are available for two sites with different features (Clichy in Paris and Ecully in Lyon). These measurements, converted into total suspended solids (TSS) concentration using TSS-turbidity relationships and combined with a model of runoff event mean concentration, enable the assessment of the contribution of sewer deposits to wet weather TSS loads observed at the outlet of the two watersheds. Results show that the contribution of sewer deposits to wet weather suspended solid's discharges is important but variable (between 20 and 80 % of the mass at the outlet depending on the event), including a site allegedly free of (coarse) sewer deposits. The uncertainties associated to these results are assessed too.

Current uses of ground penetrating radar in groundwater-dependent ecosystems research.

PubMed

Paz, Catarina; Alcalá, Francisco J; Carvalho, Jorge M; Ribeiro, Luís

2017-10-01

Ground penetrating radar (GPR) is a high-resolution technique widely used in shallow groundwater prospecting. This makes GPR ideal to characterize the hydrogeological functioning of groundwater-dependent ecosystems (GDE). This paper reviews current uses of GPR in GDE research through the construction of a database comprising 91 worldwide GPR case studies selected from the literature and classified according to (1) geological environments favouring GDE; (2) hydrogeological research interests; and (3) field technical and (4) hydrogeological conditions of the survey. The database analysis showed that inland alluvial, colluvial, and glacial formations were the most widely covered geological environments. Water-table depth was the most repeated research interest. By contrast, weathered-marl and crystalline-rock environments as well as the delineation of salinity interfaces in coastal and inland areas were less studied. Despite that shallow groundwater propitiated GDE in almost all the GPR case studies compiled, only one case expressly addressed GDE research. Common ranges of prospecting depth, water-table depth, and volumetric water content deduced by GPR and other techniques were identified. Antenna frequency of 100MHz and the common offset acquisition technique predominated in the database. Most of GPR case studies were in 30-50° N temperate latitudes, mainly in Europe and North America. Eight original radargrams were selected from several GPR profiles performed in 2014 and 2015 to document database classes and identified gaps, as well as to define experimental ranges of operability in GDE environments. The results contribute to the design of proper GPR surveys in GDE research. Copyright © 2017 Elsevier B.V. All rights reserved.

M4AST - A Tool for Asteroid Modelling

NASA Astrophysics Data System (ADS)

Birlan, Mirel; Popescu, Marcel; Irimiea, Lucian; Binzel, Richard

2016-10-01

M4AST (Modelling for asteroids) is an online tool devoted to the analysis and interpretation of reflection spectra of asteroids in the visible and near-infrared spectral intervals. It consists into a spectral database of individual objects and a set of routines for analysis which address scientific aspects such as: taxonomy, curve matching with laboratory spectra, space weathering models, and mineralogical diagnosis. Spectral data were obtained using groundbased facilities; part of these data are precompiled from the literature[1].The database is composed by permanent and temporary files. Each permanent file contains a header and two or three columns (wavelength, spectral reflectance, and the error on spectral reflectance). Temporary files can be uploaded anonymously, and are purged for the property of submitted data. The computing routines are organized in order to accomplish several scientific objectives: visualize spectra, compute the asteroid taxonomic class, compare an asteroid spectrum with similar spectra of meteorites, and computing mineralogical parameters. One facility of using the Virtual Observatory protocols was also developed.A new version of the service was released in June 2016. This new release of M4AST contains a database and facilities to model more than 6,000 spectra of asteroids. A new web-interface was designed. This development allows new functionalities into a user-friendly environment. A bridge system of access and exploiting the database SMASS-MIT (http://smass.mit.edu) allows the treatment and analysis of these data in the framework of M4AST environment.Reference:[1] M. Popescu, M. Birlan, and D.A. Nedelcu, "Modeling of asteroids: M4AST," Astronomy & Astrophysics 544, EDP Sciences, pp. A130, 2012.

Using Predictive Analytics to Predict Power Outages from Severe Weather

NASA Astrophysics Data System (ADS)

Wanik, D. W.; Anagnostou, E. N.; Hartman, B.; Frediani, M. E.; Astitha, M.

2015-12-01

The distribution of reliable power is essential to businesses, public services, and our daily lives. With the growing abundance of data being collected and created by industry (i.e. outage data), government agencies (i.e. land cover), and academia (i.e. weather forecasts), we can begin to tackle problems that previously seemed too complex to solve. In this session, we will present newly developed tools to aid decision-support challenges at electric distribution utilities that must mitigate, prepare for, respond to and recover from severe weather. We will show a performance evaluation of outage predictive models built for Eversource Energy (formerly Connecticut Light & Power) for storms of all types (i.e. blizzards, thunderstorms and hurricanes) and magnitudes (from 20 to >15,000 outages). High resolution weather simulations (simulated with the Weather and Research Forecast Model) were joined with utility outage data to calibrate four types of models: a decision tree (DT), random forest (RF), boosted gradient tree (BT) and an ensemble (ENS) decision tree regression that combined predictions from DT, RF and BT. The study shows that the ENS model forced with weather, infrastructure and land cover data was superior to the other models we evaluated, especially in terms of predicting the spatial distribution of outages. This research has the potential to be used for other critical infrastructure systems (such as telecommunications, drinking water and gas distribution networks), and can be readily expanded to the entire New England region to facilitate better planning and coordination among decision-makers when severe weather strikes.

A multi-site stochastic weather generator of daily precipitation and temperature

USDA-ARS?s Scientific Manuscript database

Stochastic weather generators are used to generate time series of climate variables that have statistical properties similar to those of observed data. Most stochastic weather generators work for a single site, and can only generate climate data at a single point, or independent time series at sever...

7 CFR 1945.20 - Making EM loans available.

Code of Federal Regulations, 2011 CFR

2011-01-01

... weather condition or natural phenomenon has substantially affected farmers, causing qualifying severe... § 1945.6(c)(3)(iii) on the basis of the same unusual and adverse weather condition or natural phenomenon... chapter. (2) When a series of unusual and adverse weather conditions or natural phenomena occur in a...

Hazards of Extreme Weather: Flood Fatalities in Texas

NASA Astrophysics Data System (ADS)

Sharif, H. O.; Jackson, T.; Bin-Shafique, S.

2009-12-01

The Federal Emergency Management Agency (FEMA) considers flooding “America’s Number One Natural Hazard”. Despite flood management efforts in many communities, U.S. flood damages remain high, due, in large part, to increasing population and property development in flood-prone areas. Floods are the leading cause of fatalities related to natural disasters in Texas. Texas leads the nation in flash flood fatalities. There are three times more fatalities in Texas (840) than the following state Pennsylvania (265). This study examined flood fatalities that occurred in Texas between 1960 and 2008. Flood fatality statistics were extracted from three sources: flood fatality databases from the National Climatic Data Center, the Spatial Hazard Event and Loss Database for the United States, and the Texas Department of State Health Services. The data collected for flood fatalities include the date, time, gender, age, location, and weather conditions. Inconsistencies among the three databases were identified and discussed. Analysis reveals that most fatalities result from driving into flood water (about 65%). Spatial analysis indicates that more fatalities occurred in counties containing major urban centers. Hydrologic analysis of a flood event that resulted in five fatalities was performed. A hydrologic model was able to simulate the water level at a location where a vehicle was swept away by flood water resulting in the death of the driver.

The Future of Planetary Climate Modeling and Weather Prediction

NASA Technical Reports Server (NTRS)

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

2017-01-01

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

MSFC Doppler Lidar Science experiments and operations plans for 1981 airborne test flight

NASA Technical Reports Server (NTRS)

Fichtl, G. H.; Bilbro, J. W.; Kaufman, J. W.

1981-01-01

The flight experiment and operations plans for the Doppler Lidar System (DLS) are provided. Application of DLS to the study of severe storms and local weather penomena is addressed. Test plans involve 66 hours of flight time. Plans also include ground based severe storm and local weather data acquisition.

Restoration of severely weathered wood

Treesearch

R. Sam Williams; Mark Knaebe

2000-01-01

Severely weathered window units were used to test various restoration methods and pretreatments. Sanded and unsanded units were pretreated with a consolidant or water repellent preservative, finished with an oil- or latex-based paint system, and exposed outdoors near Madison, WI, for five years. Pretreatments were applied to both window sashes (stiles and rails) and...

A comparison of command center activations versus disaster drills at three institutions from 2013 to 2015.

PubMed

Ebbeling, Laura G; Goralnick, Eric; Bivens, Matthew J; Femino, Meg; Berube, Claire G; Sears, Bryan; Sanchez, Leon D

2016-01-01

Disaster exercises often simulate rare, worst-case scenario events that range from mass casualty incidents to severe weather events. In actuality, situations such as information system downtimes and physical plant failures may affect hospital continuity of operations far more significantly. The objective of this study is to evaluate disaster drills at two academic and one community hospital to compare the frequency of planned drills versus real-world events that led to emergency management command center activation. Emergency management exercise and command center activation data from January 1, 2013 to October 1, 2015 were collected from a database. The activations and drills were categorized according to the nature of the event. Frequency of each type of event was compared to determine if the drills were representative of actual activations. From 2013 to 2015, there were a total of 136 command center activations and 126 drills at the three hospital sites. The most common reasons for command center activations included severe weather (25 percent, n = 34), maintenance failure (19.9 percent, n = 27), and planned mass gathering events (16.9 percent, n = 23). The most frequent drills were process tests (32.5 percent, n = 41), hazardous material-related events (22.2 percent, n = 28), and in-house fires (15.10 percent, n = 19). Further study of the reasons behind why hospitals activate emergency management plans may inform better preparedness drills. There is no clear methodology used among all hospitals to create drills and their descriptions are often vague. There is an opportunity to better design drills to address specific purposes and events.

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

Farm Management, Environment, and Weather Factors Jointly Affect the Probability of Spinach Contamination by Generic Escherichia coli at the Preharvest Stage

PubMed Central

Navratil, Sarah; Gregory, Ashley; Bauer, Arin; Srinath, Indumathi; Szonyi, Barbara; Nightingale, Kendra; Anciso, Juan; Jun, Mikyoung; Han, Daikwon; Lawhon, Sara; Ivanek, Renata

2014-01-01

The National Resources Information (NRI) databases provide underutilized information on the local farm conditions that may predict microbial contamination of leafy greens at preharvest. Our objective was to identify NRI weather and landscape factors affecting spinach contamination with generic Escherichia coli individually and jointly with farm management and environmental factors. For each of the 955 georeferenced spinach samples (including 63 positive samples) collected between 2010 and 2012 on 12 farms in Colorado and Texas, we extracted variables describing the local weather (ambient temperature, precipitation, and wind speed) and landscape (soil characteristics and proximity to roads and water bodies) from NRI databases. Variables describing farm management and environment were obtained from a survey of the enrolled farms. The variables were evaluated using a mixed-effect logistic regression model with random effects for farm and date. The model identified precipitation as a single NRI predictor of spinach contamination with generic E. coli, indicating that the contamination probability increases with an increasing mean amount of rain (mm) in the past 29 days (odds ratio [OR] = 3.5). The model also identified the farm's hygiene practices as a protective factor (OR = 0.06) and manure application (OR = 52.2) and state (OR = 108.1) as risk factors. In cross-validation, the model showed a solid predictive performance, with an area under the receiver operating characteristic (ROC) curve of 81%. Overall, the findings highlighted the utility of NRI precipitation data in predicting contamination and demonstrated that farm management, environment, and weather factors should be considered jointly in development of good agricultural practices and measures to reduce produce contamination. PMID:24509926

Geographic Region, Weather, Pilot Age and Air Carrier Crashes: a Case-Control Study

PubMed Central

Li, Guohua; Pressley, Joyce C.; Qiang, Yandong; Grabowski, Jurek G.; Baker, Susan P.; Rebok, George W.

2009-01-01

Background Information about risk factors of aviation crashes is crucial for developing effective intervention programs. Previous studies assessing factors associated with crash risk were conducted primarily in general aviation, air taxis and commuter air carriers. Methods A matched case-control design was used to examine the associations of geographic region, basic weather condition, and pilot age with the risk of air carrier (14 CFR Part 121) crash involvement. Cases (n=373) were air carrier crashes involving aircraft made by Boeing, McDonnell Douglas, and Airbus, recorded in the National Transportation Safety Board’s aviation crash database during 1983 through 2002, and controls (n=746) were air carrier incidents involving aircraft of the same three makes selected at random from the Federal Aviation Administration’s aviation incident database. Each case was matched with two controls on the calendar year when the index crash occurred. Conditional logistic regression was used for statistical analysis. Results With adjustment for basic weather condition, pilot age, and total flight time, the risk of air carrier crashes in Alaska was more than three times the risk for other regions [adjusted odds ratio (OR) 3.18, 95% confidence interval (CI) 1.35 – 7.49]. Instrument meteorological conditions were associated with an increased risk for air carrier crashes involving pilot error (adjusted OR 2.26, 95% CI 1.15 – 4.44) and a decreased risk for air carrier crashes without pilot error (adjusted OR 0.57, 95% CI 0.40 – 0.87). Neither pilot age nor total flight time was significantly associated with the risk of air carrier crashes. Conclusions The excess risk of air carrier crashes in Alaska and the effect of adverse weather on pilot-error crashes underscore the importance of environmental hazards in flight safety. PMID:19378910

Geographic region, weather, pilot age, and air carrier crashes: a case-control study.

PubMed

Li, Guohua; Pressley, Joyce C; Qiang, Yandong; Grabowski, Jurek G; Baker, Susan P; Rebok, George W

2009-04-01

Information about risk factors of aviation crashes is crucial for developing effective intervention programs. Previous studies assessing factors associated with crash risk were conducted primarily in general aviation, air taxis, and commuter air carriers. A matched case-control design was used to examine the associations of geographic region, basic weather condition, and pilot age with the risk of air carrier (14 CFR Part 121) crash involvement. Cases (N = 373) were air carrier crashes involving aircraft made by Boeing, McDonnell Douglas, and Airbus recorded in the National Transportation Safety Board's aviation crash database during 1983 through 2002, and controls (N = 746) were air carrier incidents involving aircraft of the same three makes selected at random from the Federal Aviation Administration's aviation incident database. Each case was matched with two controls on the calendar year when the index crash occurred. Conditional logistic regression was used for statistical analysis. With adjustment for basic weather condition, pilot age, and total flight time, the risk of air carrier crashes in Alaska was more than three times the risk for other regions ladjusted odds ratio (OR) 3.18, 95% confidence interval (CI) 1.35-7.49]. Instrument meteorological conditions were associated with an increased risk for air carrier crashes involving pilot error (adjusted OR 2.26, 95% CI 1.15-4.44) and a decreased risk for air carrier crashes without pilot error (adjusted OR 0.60, 95% CI 0.37-0.96). Neither pilot age nor total flight time were significantly associated with the risk of air carrier crashes. The excess risk of air carrier crashes in Alaska and the effect of adverse weather on pilot-error crashes underscore the importance of environmental hazards in flight safety.

Ionosphere Waves Service (IWS) - a problem-oriented tool in ionosphere and Space Weather research produced by POPDAT project

NASA Astrophysics Data System (ADS)

Ferencz, Csaba; Lizunov, Georgii; Crespon, François; Price, Ivan; Bankov, Ludmil; Przepiórka, Dorota; Brieß, Klaus; Dudkin, Denis; Girenko, Andrey; Korepanov, Valery; Kuzmych, Andrii; Skorokhod, Tetiana; Marinov, Pencho; Piankova, Olena; Rothkaehl, Hanna; Shtus, Tetyana; Steinbach, Péter; Lichtenberger, János; Sterenharz, Arnold; Vassileva, Any

2014-05-01

In the frame of the FP7 POPDAT project the Ionosphere Waves Service (IWS) has been developed and opened for public access by ionosphere experts. IWS is forming a database, derived from archived ionospheric wave records to assist the ionosphere and Space Weather research, and to answer the following questions: How can the data of earlier ionospheric missions be reprocessed with current algorithms to gain more profitable results? How could the scientific community be provided with a new insight on wave processes that take place in the ionosphere? The answer is a specific and unique data mining service accessing a collection of topical catalogs that characterize a huge number of recorded occurrences of Whistler-like Electromagnetic Wave Phenomena, Atmosphere Gravity Waves, and Traveling Ionosphere Disturbances. IWS online service (http://popdat.cbk.waw.pl) offers end users to query optional set of predefined wave phenomena, their detailed characteristics. These were collected by target specific event detection algorithms in selected satellite records during database buildup phase. Result of performed wave processing thus represents useful information on statistical or comparative investigations of wave types, listed in a detailed catalog of ionospheric wave phenomena. The IWS provides wave event characteristics, extracted by specific software systems from data records of the selected satellite missions. The end-user can access targets by making specific searches and use statistical modules within the service in their field of interest. Therefore the IWS opens a new way in ionosphere and Space Weather research. The scientific applications covered by IWS concern beyond Space Weather also other fields like earthquake precursors, ionosphere climatology, geomagnetic storms, troposphere-ionosphere energy transfer, and trans-ionosphere link perturbations.

General-aviation's view of progress in the aviation weather system

NASA Technical Reports Server (NTRS)

Lundgren, Douglas J.

1988-01-01

For all its activity statistics, general-aviation is the most vulnerable to hazardous weather. Of concern to the general aviation industry are: (1) the slow pace of getting units of the Automated Weather Observation System (AWOS) to the field; (2) the efforts of the National Weather Service to withdraw from both the observation and dissemination roles of the aviation weather system; (3) the need for more observation points to improve the accuracy of terminal and area forecasts; (4) the need for improvements in all area forecasts, terminal forecasts, and winds aloft forecasts; (5) slow progress in cockpit weather displays; (6) the erosion of transcribed weather broadcasts (TWEB) and other deficiencies in weather information dissemination; (7) the need to push to make the Direct User Access Terminal (DUAT) a reality; and (7) the need to improve severe weather (thunderstorm) warning systems.

Predicting motorcycle crash injury severity using weather data and alternative Bayesian multivariate crash frequency models.

PubMed

Cheng, Wen; Gill, Gurdiljot Singh; Sakrani, Taha; Dasu, Mohan; Zhou, Jiao

2017-11-01

Motorcycle crashes constitute a very high proportion of the overall motor vehicle fatalities in the United States, and many studies have examined the influential factors under various conditions. However, research on the impact of weather conditions on the motorcycle crash severity is not well documented. In this study, we examined the impact of weather conditions on motorcycle crash injuries at four different severity levels using San Francisco motorcycle crash injury data. Five models were developed using Full Bayesian formulation accounting for different correlations commonly seen in crash data and then compared for fitness and performance. Results indicate that the models with serial and severity variations of parameters had superior fit, and the capability of accurate crash prediction. The inferences from the parameter estimates from the five models were: an increase in the air temperature reduced the possibility of a fatal crash but had a reverse impact on crashes of other severity levels; humidity in air was not observed to have a predictable or strong impact on crashes; the occurrence of rainfall decreased the possibility of crashes for all severity levels. Transportation agencies might benefit from the research results to improve road safety by providing motorcyclists with information regarding the risk of certain crash severity levels for special weather conditions. Copyright © 2017 Elsevier Ltd. All rights reserved.

Fourth National Aeronautics and Space Administration Weather and Climate Program Science Review

NASA Technical Reports Server (NTRS)

Kreins, E. R. (Editor)

1979-01-01

The NASA Weather and Climate Program has two major thrusts. The first involves the development of experimental and prototype operational satellite systems, sensors, and space facilities for monitoring and understanding the atmosphere. The second thrust involves basic scientific investigation aimed at studying the physical and chemical processes which control weather and climate. This fourth science review concentrated on the scientific research rather than the hardware development aspect of the program. These proceedings contain 65 papers covering the three general areas: severe storms and local weather research, global weather, and climate.

Self-perceived weather sensitivity and joint pain in older people with osteoarthritis in six European countries: results from the European Project on OSteoArthritis (EPOSA)

PubMed Central

2014-01-01

Background People with osteoarthritis (OA) frequently report that their joint pain is influenced by weather conditions. This study aimed to examine whether there are differences in perceived joint pain between older people with OA who reported to be weather-sensitive versus those who did not in six European countries with different climates and to identify characteristics of older persons with OA that are most predictive of perceived weather sensitivity. Methods Baseline data from the European Project on OSteoArthritis (EPOSA) were used. ACR classification criteria were used to determine OA. Participants with OA were asked about their perception of weather as influencing their pain. Using a two-week follow-up pain calendar, average self-reported joint pain was assessed (range: 0 (no pain)-10 (greatest pain intensity)). Linear regression analyses, logistic regression analyses and an independent t-test were used. Analyses were adjusted for several confounders. Results The majority of participants with OA (67.2%) perceived the weather as affecting their pain. Weather-sensitive participants reported more pain than non-weather-sensitive participants (M = 4.1, SD = 2.4 versus M = 3.1, SD = 2.4; p < 0.001). After adjusting for several confounding factors, the association between self-perceived weather sensitivity and joint pain remained present (B = 0.37, p = 0.03). Logistic regression analyses revealed that women and more anxious people were more likely to report weather sensitivity. Older people with OA from Southern Europe were more likely to indicate themselves as weather-sensitive persons than those from Northern Europe. Conclusions Weather (in)stability may have a greater impact on joint structures and pain perception in people from Southern Europe. The results emphasize the importance of considering weather sensitivity in daily life of older people with OA and may help to identify weather-sensitive older people with OA. PMID:24597710

Self-perceived weather sensitivity and joint pain in older people with osteoarthritis in six European countries: results from the European Project on OSteoArthritis (EPOSA).

PubMed

Timmermans, Erik J; van der Pas, Suzan; Schaap, Laura A; Sánchez-Martínez, Mercedes; Zambon, Sabina; Peter, Richard; Pedersen, Nancy L; Dennison, Elaine M; Denkinger, Michael; Castell, Maria Victoria; Siviero, Paola; Herbolsheimer, Florian; Edwards, Mark H; Otero, Angel; Deeg, Dorly J H

2014-03-05

People with osteoarthritis (OA) frequently report that their joint pain is influenced by weather conditions. This study aimed to examine whether there are differences in perceived joint pain between older people with OA who reported to be weather-sensitive versus those who did not in six European countries with different climates and to identify characteristics of older persons with OA that are most predictive of perceived weather sensitivity. Baseline data from the European Project on OSteoArthritis (EPOSA) were used. ACR classification criteria were used to determine OA. Participants with OA were asked about their perception of weather as influencing their pain. Using a two-week follow-up pain calendar, average self-reported joint pain was assessed (range: 0 (no pain)-10 (greatest pain intensity)). Linear regression analyses, logistic regression analyses and an independent t-test were used. Analyses were adjusted for several confounders. The majority of participants with OA (67.2%) perceived the weather as affecting their pain. Weather-sensitive participants reported more pain than non-weather-sensitive participants (M = 4.1, SD = 2.4 versus M = 3.1, SD = 2.4; p < 0.001). After adjusting for several confounding factors, the association between self-perceived weather sensitivity and joint pain remained present (B = 0.37, p = 0.03). Logistic regression analyses revealed that women and more anxious people were more likely to report weather sensitivity. Older people with OA from Southern Europe were more likely to indicate themselves as weather-sensitive persons than those from Northern Europe. Weather (in)stability may have a greater impact on joint structures and pain perception in people from Southern Europe. The results emphasize the importance of considering weather sensitivity in daily life of older people with OA and may help to identify weather-sensitive older people with OA.

Prevalence of weather sensitivity in Germany and Canada

NASA Astrophysics Data System (ADS)

Mackensen, Sylvia; Hoeppe, Peter; Maarouf, Abdel; Tourigny, Pierre; Nowak, Dennis

2005-01-01

Several studies have shown that atmospheric conditions can affect well-being or disease, and that some individuals seem to be more sensitive to weather than others. Since epidemiological data on the prevalence of weather-related health effects are lacking, two representative weather sensitivity (WS) surveys were conducted independently in Germany and Canada. The objectives of this paper are: (1) to identify the prevalence of WS in Germany and Canada, (2) to describe weather-related symptoms and the corresponding weather conditions, and (3) to compare the findings in the two countries. In Germany 1,064 citizens (age >16 years) were interviewed in January 2001, and in Canada 1,506 persons (age >18 years) were interviewed in January 1994. The results showed that 19.2% of the German population thought that weather affected their health “to a strong degree,” 35.3% that weather had “some influence on their health” (sum of both = 54.5% weather sensitive), whereas the remaining 45.5% did not consider that weather had an effect on their health status. In Canada 61% of the respondents considered themselves to be sensitive to the weather. The highest prevalence of WS (high + some influence) in Germans was found in the age group older than 60 years (68%), which was almost identical in the Canadian population (69%). The highest frequencies of weather-related symptoms were reported in Germany for stormy weather (30%) and when it became colder (29%). In Canada mainly cold weather (46%), dampness (21%) and rain (20%) were considered to affect health more than other weather types. The most frequent symptoms reported in Germany were headache/migraine (61%), lethargy (47%), sleep disturbances (46%), fatigue (42%), joint pain (40%), irritation (31%), depression (27%), vertigo (26%), concentration problems (26%) and scar pain (23%). Canadian weather-sensitive persons reported colds (29%), psychological effects (28%) and painful joints, muscles or arthritis (10%). In Germany 32% of the weather-sensitive subjects reported themselves to be unable to do their regular work because of weather-related symptoms at least once in the previous year, and 22% of them several times. Co-morbidity was significantly higher in weather-sensitive subjects both in Germany and Canada. These results clearly showed the important impact of WS on public health and the economy. These findings prompted us to start studies on the causal factors of weather-related health effects.

Extreme Space Weather Events: From Cradle to Grave

NASA Astrophysics Data System (ADS)

Riley, Pete; Baker, Dan; Liu, Ying D.; Verronen, Pekka; Singer, Howard; Güdel, Manuel

2018-02-01

Extreme space weather events, while rare, can have a substantial impact on our technologically-dependent society. And, although such events have only occasionally been observed, through careful analysis of a wealth of space-based and ground-based observations, historical records, and extrapolations from more moderate events, we have developed a basic picture of the components required to produce them. Several key issues, however, remain unresolved. For example, what limits are imposed on the maximum size of such events? What are the likely societal consequences of a so-called "100-year" solar storm? In this review, we summarize our current scientific understanding about extreme space weather events as we follow several examples from the Sun, through the solar corona and inner heliosphere, across the magnetospheric boundary, into the ionosphere and atmosphere, into the Earth's lithosphere, and, finally, its impact on man-made structures and activities, such as spacecraft, GPS signals, radio communication, and the electric power grid. We describe preliminary attempts to provide probabilistic forecasts of extreme space weather phenomena, and we conclude by identifying several key areas that must be addressed if we are better able to understand, and, ultimately, predict extreme space weather events.

Development of a fire weather index using meteorological observations within the Northeast United States

Treesearch

Michael J. Erickson; Joseph J. Charney; Brian A. Colle

2016-01-01

A fire weather index (FWI) is developed using wildfire occurrence data and Automated Surface Observing System weather observations within a subregion of the northeastern United States (NEUS) from 1999 to 2008. Average values of several meteorological variables, including near-surface temperature, relative humidity, dewpoint, wind speed, and cumulative daily...

Climatic and weather factors affecting fire occurrence and behavior

Treesearch

Randall P. Benson; John O. Roads; David R. Weise

2009-01-01

Weather and climate have a profound influence on wildland fire ignition potential, fire behavior, and fire severity. Local weather and climate are affected by large-scale patterns of winds over the hemispheres that predispose wildland fuels to fire. The characteristics of wildland fuels, especially the moisture content, ultimately determine fire behavior and the impact...

Importance of the Gulf of Mexico as a climate driver for U.S. severe thunderstorm activity

NASA Astrophysics Data System (ADS)

Molina, M. J.; Timmer, R. P.; Allen, J. T.

2016-12-01

Different features of the Gulf of Mexico (GOM), such as the Loop Current and warm-core rings, are found to influence monthly-to-seasonal severe weather occurrence in different regions of the United States (U.S.). The warmer (cooler) the GOM sea surface temperatures, the more (less) hail and tornadoes occur during March-May over the southern U.S. This pattern is reflected physically in boundary layer specific humidity and mixed-layer convective available potential energy, two large-scale atmospheric conditions favorable for severe weather occurrence. This relationship is complicated by interactions between the GOM and El Niño-Southern Oscillation (ENSO) but persists when analyzing ENSO neutral conditions. This suggests that the GOM can influence hail and tornado occurrence and provides another source of regional predictability for seasonal severe weather.

Applied Meteorology Unit (AMU)

NASA Technical Reports Server (NTRS)

Bauman, William; Crawford, Winifred; Watson, Leela; Wheeler, Mark

2011-01-01

The AMU Team began four new tasks in this quarter: (1) began work to improve the AMU-developed tool that provides the launch weather officers information on peak wind speeds that helps them assess their launch commit criteria; (2) began updating lightning climatologies for airfields around central Florida. These climatologies help National Weather Service and Air Force forecasters determine the probability of lightning occurrence at these sites; (3) began a study for the 30th Weather Squadron at Vandenberg Air Force Base in California to determine if precursors can be found in weather observations to help the forecasters determine when they will get strong wind gusts in their northern towers; and (4) began work to update the AMU-developed severe weather tool with more data and possibly improve its performance using a new statistical technique. Include is a section of summaries and detail reporting on the quarterly tasks: (1) Peak Wind Tool for user Meteorological Interactive Data Display System (LCC), Phase IV, (2) Situational Lightning climatologies for Central Florida, Phase V, (3) Vandenberg AFB North Base Wind Study and (4) Upgrade Summer Severe Weather Tool Meteorological Interactive Data Display System (MIDDS).

NCO Production Management Branch

Science.gov Websites

Climate Climate Prediction Climate Archives Weather Safety Storm Ready NOAA Central Library Photo Library Management Branch Production Management Branch About the Production Management Branch NCO REQUEST FOR CHANGE (RFC) DATABASE ACCESS NCO Request For Change (RFC) Archive [For INTERNAL Use Only] NCO Request For

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

NASA Astrophysics Data System (ADS)

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

2016-12-01

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

Development and Application of Syndromic Surveillance for Severe Weather Events Following Hurricane Sandy.

PubMed

Tsai, Stella; Hamby, Teresa; Chu, Alvin; Gleason, Jessie A; Goodrow, Gabrielle M; Gu, Hui; Lifshitz, Edward; Fagliano, Jerald A

2016-06-01

Following Hurricane Superstorm Sandy, the New Jersey Department of Health (NJDOH) developed indicators to enhance syndromic surveillance for extreme weather events in EpiCenter, an online system that collects and analyzes real-time chief complaint emergency department (ED) data and classifies each visit by indicator or syndrome. These severe weather indicators were finalized by using 2 steps: (1) key word inclusion by review of chief complaints from cases where diagnostic codes met selection criteria and (2) key word exclusion by evaluating cases with key words of interest that lacked selected diagnostic codes. Graphs compared 1-month, 3-month, and 1-year periods of 8 Hurricane Sandy-related severe weather event indicators against the same period in the following year. Spikes in overall ED visits were observed immediately after the hurricane for carbon monoxide (CO) poisoning, the 3 disrupted outpatient medical care indicators, asthma, and methadone-related substance use. Zip code level scan statistics indicated clusters of CO poisoning and increased medicine refill needs during the 2 weeks after Hurricane Sandy. CO poisoning clusters were identified in areas with power outages of 4 days or longer. This endeavor gave the NJDOH a clearer picture of the effects of Hurricane Sandy and yielded valuable state preparation information to monitor the effects of future severe weather events. (Disaster Med Public Health Preparedness. 2016;10:463-471).

76 FR 2762 - Proposed Information Collection (VAAR Clause 852.236.91, Special Notes) Activity: Comment Request

Federal Register 2010, 2011, 2012, 2013, 2014

2011-01-14

... support claims for price adjustment due to delay in construction caused by severe weather. DATES: Written... facilities available to perform the work. The clause also requires contractors submitting a claim for price adjustment due to severe weather delay to provide climatologically data covering the period of the claim and...

Global economic impacts of severe Space Weather.

NASA Astrophysics Data System (ADS)

Schulte In Den Baeumen, Hagen; Cairns, Iver

Coronal mass ejections (CMEs) strong enough to create electromagnetic effects at latitudes below the auroral oval are frequent events, and could have substantial impacts on electric power transmission and telecommunication grids. Modern society’s heavy reliance on these domestic and international networks increases our susceptibility to such a severe Space Weather event. Using a new high-resolution model of the global economy we simulate the economic impact of large CMEs for 3 different planetary orientations. We account for the economic impacts within the countries directly affected as well as the post-disaster economic shock in partner economies through international trade. For the CMEs modeled the total global economic impacts would range from US 380 billion to US 1 trillion. Of this total economic shock 50 % would be felt in countries outside the zone of direct impact, leading to a loss in global GDP of 0.1 - 1 %. A severe Space Weather event could lead to global economic damages of the same order as other weather disasters, climate change, and extreme financial crisis.

Optimum space shuttle launch times relative to natural environment

NASA Technical Reports Server (NTRS)

King, R. L.

1977-01-01

The probabilities of favorable and unfavorable weather conditions for launch and landing of the STS under different criteria were computed for every three hours on a yearly basis using 14 years of weather data. These temporal probability distributions were considered for three sets of weather criteria encompassing benign, moderate and severe weather conditions for both Kennedy Space Center and for Edwards Air Force Base. In addition, the conditional probabilities were computed for unfavorable weather conditions occurring after a delay which may or may not be due to weather conditions. Also for KSC, the probabilities of favorable landing conditions at various times after favorable launch conditions have prevailed. The probabilities were computed to indicate the significance of each weather element to the overall result.

Weather Impact on Airport Arrival Meter Fix Throughput

NASA Technical Reports Server (NTRS)

Wang, Yao

2017-01-01

Time-based flow management provides arrival aircraft schedules based on arrival airport conditions, airport capacity, required spacing, and weather conditions. In order to meet a scheduled time at which arrival aircraft can cross an airport arrival meter fix prior to entering the airport terminal airspace, air traffic controllers make regulations on air traffic. Severe weather may create an airport arrival bottleneck if one or more of airport arrival meter fixes are partially or completely blocked by the weather and the arrival demand has not been reduced accordingly. Under these conditions, aircraft are frequently being put in holding patterns until they can be rerouted. A model that predicts the weather impacted meter fix throughput may help air traffic controllers direct arrival flows into the airport more efficiently, minimizing arrival meter fix congestion. This paper presents an analysis of air traffic flows across arrival meter fixes at the Newark Liberty International Airport (EWR). Several scenarios of weather impacted EWR arrival fix flows are described. Furthermore, multiple linear regression and regression tree ensemble learning approaches for translating multiple sector Weather Impacted Traffic Indexes (WITI) to EWR arrival meter fix throughputs are examined. These weather translation models are developed and validated using the EWR arrival flight and weather data for the period of April-September in 2014. This study also compares the performance of the regression tree ensemble with traditional multiple linear regression models for estimating the weather impacted throughputs at each of the EWR arrival meter fixes. For all meter fixes investigated, the results from the regression tree ensemble weather translation models show a stronger correlation between model outputs and observed meter fix throughputs than that produced from multiple linear regression method.

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.

Home Fires

MedlinePlus

... to the touch and lights that flicker. Portable Space Heaters Keep combustible objects at least three feet ... Radiological Dispersion Device Severe Weather Snowstorms & Extreme Cold Space Weather Thunderstorms & Lightning Tornadoes Tsunamis Volcanoes Wildfires Ready. ...

Third Space Weather Summit Held for Industry and Government Agencies

NASA Astrophysics Data System (ADS)

Intriligator, Devrie S.

2009-12-01

The potential for space weather effects has been increasing significantly in recent years. For instance, in 2008 airlines flew about 8000 transpolar flights, which experience greater exposure to space weather than nontranspolar flights. This is up from 368 transpolar flights in 2000, and the number of such flights is expected to continue to grow. Transpolar flights are just one example of the diverse technologies susceptible to space weather effects identified by the National Research Council's Severe Space Weather Events—Understanding Societal and Economic Impacts: A Workshop Report (2008). To discuss issues related to the increasing need for reliable space weather information, experts from industry and government agencies met at the third summit of the Commercial Space Weather Interest Group (CSWIG) and the National Oceanic and Atmospheric Administration's (NOAA) Space Weather Prediction Center (SWPC), held 30 April 2009 during Space Weather Week (SWW), in Boulder, Colo.

[Influence of some weather factors and the geomagnetic activity on the development of severe cardiological pathologies].

PubMed

Ozheredov, V A; Breus, T K; Gurfinkel', Iu I; Revich, B A; Mitrofanova, T A

2010-01-01

The influence of weather factors (atmospheric pressure and temperature) and the geomagnetic activity on the development of severe cardiological pathologies has been studied using the daily data from two Moscow clinics, accumulated over a period of 12 and 7 years. It was shown that the most biotropic factors are variations of atmospheric temperature. The relative contribution of the geomagnetic activity to the development of diseases is only 20%; however, its action is combined with the effect of ordinary weather because both these factors affect the vascular tonus of humans.

A scientific database for real-time Neutron Monitor measurements - taking Neutron Monitors into the 21st century

NASA Astrophysics Data System (ADS)

Steigies, Christian

2012-07-01

The Neutron Monitor Database project, www.nmdb.eu, has been funded in 2008 and 2009 by the European Commission's 7th framework program (FP7). Neutron monitors (NMs) have been in use worldwide since the International Geophysical Year (IGY) in 1957 and cosmic ray data from the IGY and the improved NM64 NMs has been distributed since this time, but a common data format existed only for data with one hour resolution. This data was first distributed in printed books, later via the World Data Center ftp server. In the 1990's the first NM stations started to record data at higher resolutions (typically 1 minute) and publish in on their webpages. However, every NM station chose their own format, making it cumbersome to work with this distributed data. In NMDB all European and some neighboring NM stations came together to agree on a common format for high-resolution data and made this available via a centralized database. The goal of NMDB is to make all data from all NM stations available in real-time. The original NMDB network has recently been joined by the Bartol Research Institute (Newark DE, USA), the National Autonomous University of Mexico and the North-West University (Potchefstroom, South Africa). The data is accessible to everyone via an easy to use webinterface, but expert users can also directly access the database to build applications like real-time space weather alerts. Even though SQL databases are used today by most webservices (blogs, wikis, social media, e-commerce), the power of an SQL database has not yet been fully realized by the scientific community. In training courses, we are teaching how to make use of NMDB, how to join NMDB, and how to ensure the data quality. The present status of the extended NMDB will be presented. The consortium welcomes further data providers to help increase the scientific contributions of the worldwide neutron monitor network to heliospheric physics and space weather.

The Design and Evaluation of the Lighting Imaging Sensor Data Applications Display (LISDAD)

NASA Technical Reports Server (NTRS)

Boldi, B.; Hodanish, S.; Sharp, D.; Williams, E.; Goodman, Steven; Raghavan, R.; Matlin, A.; Weber, M.

1998-01-01

The design and evaluation of the Lightning Imaging Sensor Data Applications Display (LISDAD). The ultimate goal of the LISDAD system is to quantify the utility of total lightning information in short-term, severe-weather forecasting operations. To this end, scientists from NASA, NWS, and MIT organized an effort to study the relationship of lightning and severe-weather on a storm-by-storm, and even cell-by-cell basis for as many storms as possible near Melbourne, Florida. Melbourne was chosen as it offers a unique combination of high probability of severe weather and proximity to major relevant sensors - specifically: NASA's total lightning mapping system at Kennedy Space Center (the LDAR system at KSC); a NWS/NEXRAD radar (at Melbourne); and a prototype Integrated Terminal Weather System (ITWS, at Orlando), which obtains cloud-to-ground lightning Information from the National Lightning Detection Network (NLDN), and also uses NSSL's Severe Storm Algorithm (NSSL/SSAP) to obtain information about various storm-cell parameters. To assist in realizing this project's goal, an interactive, real-time data processing system (the LISDAD system) has been developed that supports both operational short-term weather forecasting and post facto severe-storm research. Suggestions have been drawn from the operational users (NWS/Melbourne) in the design of the data display and its salient behavior. The initial concept for the users Graphical Situation Display (GSD) was simply to overlay radar data with lightning data, but as the association between rapid upward trends in the total lightning rate and severe weather became evident, the display was significantly redesigned. The focus changed to support the display of time series of storm-parameter data and the automatic recognition of cells that display rapid changes in the total-lightning flash rate. The latter is calculated by grouping discrete LDAR radiation sources into lightning flashes using a time-space association algorithm. Specifically, the GSD presents the user with the Composite Maximum Reflectivity obtained from the NWS/NEXRAD. Superimposed upon this background image are placed small black circles indicating the locations of storm cells identified by the NSSL/SSA. The circles become cyan if lightning is detected within the storm-cell; if the cell has lightning rates indicative of a severe-storm, the circle turns red. This paper will: (1) review the design of LISDAD system; (2) present some examples of its data display; and shown results of the lightning based severe-weather prediction algorithm.

Correlating weather and trauma admissions at a level I trauma center.

PubMed

Rising, William R; O'Daniel, Joseph A; Roberts, Craig S

2006-05-01

Popular emergency room wisdom touts higher temperatures, snowfall, weekends, and evenings as variables that increase trauma admissions. This study analyzed the possible correlation between trauma admissions and specific weather variables, and between trauma admissions and time of day or season. Trauma admission data from a Level I trauma center database from July 1, 1996 to January 31, 2002 was downloaded and linked with local weather data from the Archives of the National Oceanic and Atmospheric Administration website, and then analyzed. There were 8,269 trauma admissions over a total of 48,984 hours for an average of one admission every 6 hours. Daily high temperature and precipitation were valid predictors of trauma admission volume, with a 5.25% increase in hourly incidents for each 10-degree difference in temperature, and a 60% to 78% increase in the incident rate for each inch of precipitation in the previous 3 hours. Weather and seasonal variations affect admissions at a Level I trauma center. Data from this study could be useful for determining staffing requirements and resource allocation.

Development of a Predictive Corrosion Model Using Locality-Specific Corrosion Indices

DTIC Science & Technology

2009-08-01

exposure data project in FY05, datasets from several other variables were needed. Specif- ically, historic data from weather stations was collected...from the weather agency closest to the sample exposure rack was collected. The distance from the weather station to the exposure rack was also noted...occurring within the first ½ mile or so of the coast. Often, the weather station will be somewhat further inland and not near the corrosion samples

Severe Weather in a Changing Climate: Getting to Adaptation

NASA Astrophysics Data System (ADS)

Wuebbles, D. J.; Janssen, E.; Kunkel, K.

2011-12-01

Analyses of observation records from U.S. weather stations indicate there is an increasing trend over recent decades in certain types of severe weather, especially large precipitation events. Widespread changes in temperature extremes have been observed over the last 50 years. In particular, the number of heat waves globally (and some parts of the U.S.) has increased, and there have been widespread increases in the numbers of warm nights. Also, analyses show that we are now breaking twice as many heat records as cold records in the U.S. Since 1957, there has been an increase in the number of historically top 1% of heavy precipitation events across the U.S. Our new analyses of the repeat or reoccurrence frequencies of large precipitation storms are showing that such events are occurring more often than in the past. The pattern of precipitation change is one of increases generally at higher northern latitudes and drying in the tropics and subtropics over land. It needs to be recognized that every weather event that happens nowadays takes place in the context of the changes in the background climate system. So nothing is entirely "natural" anymore. It's a fallacy to think that individual events are caused entirely by any one thing, either natural variation or human-induced climate change. Every event is influenced by many factors. Human-induced climate change is now a factor in weather events. The changes occurring in precipitation are consistent with the analyses of our changing climate. For extreme precipitation, we know that more precipitation is falling in very heavy events. And we know key reasons why; warmer air holds more water vapor, and so when any given weather system moves through, the extra water dumps can lead to a heavy downpour. As the climate system continues to warm, models of the Earth's climate system indicate severe precipitation events will likely become more commonplace. Water vapor will continue to increase in the atmosphere along with the warming, and large precipitation events will likely increase in intensity and frequency. In the presentation, we will not only discuss the recent trends in severe weather and the projections of the impacts of climate change on severe weather in the future, but also specific examples of how this information is being used in developing and applying adaptation policies.

Interactive effects of prey and weather on golden eagle reproduction

USGS Publications Warehouse

Steenhof, Karen; Kochert, Michael N.; McDonald, T.L.

1997-01-01

1. The reproduction of the golden eagle Aquila chrysaetos was studied in southwestern Idaho for 23 years, and the relationship between eagle reproduction and jackrabbit Lepus californicus abundance, weather factors, and their interactions, was modelled using general linear models. Backward elimination procedures were used to arrive at parsimonious models.2. The number of golden eagle pairs occupying nesting territories each year showed a significant decline through time that was unrelated to either annual rabbit abundance or winter severity. However, eagle hatching dates were significantly related to both winter severity and jackrabbit abundance. Eagles hatched earlier when jackrabbits were abundant, and they hatched later after severe winters.3. Jackrabbit abundance influenced the proportion of pairs that laid eggs, the proportion of pairs that were successful, mean brood size at fledging, and the number of young fledged per pair. Weather interacted with prey to influence eagle reproductive rates.4. Both jackrabbit abundance and winter severity were important in predicting the percentage of eagle pairs that laid eggs. Percentage laying was related positively to jackrabbit abundance and inversely related to winter severity.5. The variables most useful in predicting percentage of laying pairs successful were rabbit abundance and the number of extremely hot days during brood-rearing. The number of hot days and rabbit abundance were also significant in a model predicting eagle brood size at fledging. Both success and brood size were positively related to jackrabbit abundance and inversely related to the frequency of hot days in spring.6. Eagle reproduction was limited by rabbit abundance during approximately twothirds of the years studied. Weather influenced how severely eagle reproduction declined in those years.7. This study demonstrates that prey and weather can interact to limit a large raptor population's productivity. Smaller raptors could be affected more strongly, especially in colder or wetter climates.

Adapting Buildings for Indoor Air Quality in a Changing Climate

EPA Pesticide Factsheets

Climate change presents many challenges, including the production of severe weather events. These events and efforts to minimize their effects through weatherization can adversely affect indoor environments.

Magnetogram Forecast: An All-Clear Space Weather Forecasting System

NASA Technical Reports Server (NTRS)

Barghouty, Nasser; Falconer, David

2015-01-01

Solar flares and coronal mass ejections (CMEs) are the drivers of severe space weather. Forecasting the probability of their occurrence is critical in improving space weather forecasts. The National Oceanic and Atmospheric Administration (NOAA) currently uses the McIntosh active region category system, in which each active region on the disk is assigned to one of 60 categories, and uses the historical flare rates of that category to make an initial forecast that can then be adjusted by the NOAA forecaster. Flares and CMEs are caused by the sudden release of energy from the coronal magnetic field by magnetic reconnection. It is believed that the rate of flare and CME occurrence in an active region is correlated with the free energy of an active region. While the free energy cannot be measured directly with present observations, proxies of the free energy can instead be used to characterize the relative free energy of an active region. The Magnetogram Forecast (MAG4) (output is available at the Community Coordinated Modeling Center) was conceived and designed to be a databased, all-clear forecasting system to support the operational goals of NASA's Space Radiation Analysis Group. The MAG4 system automatically downloads nearreal- time line-of-sight Helioseismic and Magnetic Imager (HMI) magnetograms on the Solar Dynamics Observatory (SDO) satellite, identifies active regions on the solar disk, measures a free-energy proxy, and then applies forecasting curves to convert the free-energy proxy into predicted event rates for X-class flares, M- and X-class flares, CMEs, fast CMEs, and solar energetic particle events (SPEs). The forecast curves themselves are derived from a sample of 40,000 magnetograms from 1,300 active region samples, observed by the Solar and Heliospheric Observatory Michelson Doppler Imager. Figure 1 is an example of MAG4 visual output

A Databank of Antarctic Surface Temperature and Pressure Data (NDP-032)

DOE Data Explorer

Jones, P. D. [University of East Anglia; Reid, P. A. [University of East Anglia; Kaiser, D. P.

2001-10-01

This database contains monthly mean surface temperature and mean sea level pressure data from twenty-nine meteorological stations within the Antarctic region. The first version of this database was compiled at the Climatic Research Unit (CRU) of University of East Anglia, Norwich, United Kingdom. The database extended through 1988 and was made available in 1989 by the Carbon Dioxide Information Analysis Center (CDIAC) as a Numeric Data Package (NDP), NDP-032. This update of the database includes data through early 1999 for most stations (through 2000 for a few), and also includes all available mean monthly maximum and minimum temperature data. For many stations this means that over 40 years of data are now available, enough for many of the trends associated with recent warming to be more thoroughly examined. Much of the original version of this dataset was obtained from the World Weather Records (WWR) volumes (1951-1970), Monthly Climatic Data for the World (since 1961), and several other sources. Updating the station surface data involved requesting data from countries who have weather stations on Antarctica. Of particular importance within this study are the additional data obtained from Australia, Britain and New Zealand. Recording Antarctic station data is particularly prone to errors. This is mostly due to climatic extremes, the nature of Antarctic science, and the variability of meteorological staff at Antarctic stations (high turnover and sometimes untrained meteorological staff). For this compilation, as many sources as possible were contacted in order to obtain as close to official `source' data as possible. Some error checking has been undertaken and hopefully the final result is as close to a definitive database as possible. This NDP consists of this html documentation file, an ASCII text version of this file, six temperature files (three original CRU files for monthly maximum, monthly minimum, and monthly mean temperature and three equivalent files slightly reformatted at CDIAC), two monthly mean pressure data files (one original CRU file and one slightly reformatted CDIAC version of the file), four graphics files that describe the station network and the nature of temperature and pressure trends, a file summarizing annual and mean-monthly trends in surface temperatures over Antarctica, a file summarizing monthly Antarctic surface temperature anomalies with respect to the period 1961-90, a station inventory file, and 3 FORTRAN and 3 SAS routines for reading the data that may be incorporated into analysis programs that users may devise. These 23 files have a total size of approximately 2 megabytes and are available via the Internet through CDIAC's Web site or anonymous FTP (File Transfer Protocol) server, and, upon request, various magnetic media.

Post-fire vegetation and fuel development influences fire severity patterns in reburns.

PubMed

Coppoletta, Michelle; Merriam, Kyle E; Collins, Brandon M

2016-04-01

In areas where fire regimes and forest structure have been dramatically altered, there is increasing concern that contemporary fires have the potential to set forests on a positive feedback trajectory with successive reburns, one in which extensive stand-replacing fire could promote more stand-replacing fire. Our study utilized an extensive set of field plots established following four fires that occurred between 2000 and 2010 in the northern Sierra Nevada, California, USA that were subsequently reburned in 2012. The information obtained from these field plots allowed for a unique set of analyses investigating the effect of vegetation, fuels, topography, fire weather, and forest management on reburn severity. We also examined the influence of initial fire severity and time since initial fire on influential predictors of reburn severity. Our results suggest that high- to moderate-severity fire in the initial fires led to an increase in standing snags and shrub vegetation, which in combination with severe fire weather promoted high-severity fire effects in the subsequent reburn. Although fire behavior is largely driven by weather, our study demonstrates that post-fire vegetation composition and structure are also important drivers of reburn severity. In the face of changing climatic regimes and increases in extreme fire weather, these results may provide managers with options to create more fire-resilient ecosystems. In areas where frequent high-severity fire is undesirable, management activities such as thinning, prescribed fire, or managed wildland fire can be used to moderate fire behavior not only prior to initial fires, but also before subsequent reburns.

C3Winds: A Novel 3D Wind Observing System to Characterize Severe Weather Events

NASA Astrophysics Data System (ADS)

Kelly, M. A.; Wu, D. L.; Yee, J. H.; Boldt, J.; Demajistre, R.; Reynolds, E.; Tripoli, G. J.; Oman, L.; Prive, N.; Heidinger, A. K.; Wanzong, S.

2015-12-01

The CubeSat Constellation Cloud Winds (C3Winds) is a NASA Earth Venture Instrument (EV-I) concept with the primary objective to resolve high-resolution 3D dynamic structures of severe wind events. Rapid evolution of severe weather events highlights the need for high-resolution mesoscale wind observations. Yet mesoscale observations of severe weather dynamics are quite rare, especially over the ocean where extratropical and tropical cyclones (ETCs and TCs) can undergo explosive development. Measuring wind velocity at the mesoscale from space remains a great challenge, but is critically needed to understand and improve prediction of severe weather and tropical cyclones. Based on compact, visible/IR imagers and a mature stereoscopic technique, C3Winds has the capability to measure high-resolution (~2 km) cloud motion vectors and cloud geometric heights accurately by tracking cloud features from two formation-flying CubeSats, separated by 5-15 minutes. Complementary to lidar wind measurements from space, C3Winds will provide high-resolution wind fields needed for detailed investigations of severe wind events in occluded ETCs, rotational structures inside TC eyewalls, and ozone injections associated with tropopause folding events. Built upon mature imaging technologies and long history of stereoscopic remote sensing, C3Winds provides an innovative, cost-effective solution to global wind observations with the potential for increased diurnal sampling via CubeSat constellation.

Mapping fire probability and severity in a Mediterranean area using different weather and fuel moisture scenarios

NASA Astrophysics Data System (ADS)

Arca, B.; Salis, M.; Bacciu, V.; Duce, P.; Pellizzaro, G.; Ventura, A.; Spano, D.

2009-04-01

Although in many countries lightning is the main cause of ignition, in the Mediterranean Basin the forest fires are predominantly ignited by arson, or by human negligence. The fire season peaks coincide with extreme weather conditions (mainly strong winds, hot temperatures, low atmospheric water vapour content) and high tourist presence. Many works reported that in the Mediterranean Basin the projected impacts of climate change will cause greater weather variability and extreme weather conditions, with drier and hotter summers and heat waves. At long-term scale, climate changes could affect the fuel load and the dead/live fuel ratio, and therefore could change the vegetation flammability. At short-time scale, the increase of extreme weather events could directly affect fuel water status, and it could increase large fire occurrence. In this context, detecting the areas characterized by both high probability of large fire occurrence and high fire severity could represent an important component of the fire management planning. In this work we compared several fire probability and severity maps (fire occurrence, rate of spread, fireline intensity, flame length) obtained for a study area located in North Sardinia, Italy, using FlamMap simulator (USDA Forest Service, Missoula). FlamMap computes the potential fire behaviour characteristics over a defined landscape for given weather, wind and fuel moisture data. Different weather and fuel moisture scenarios were tested to predict the potential impact of climate changes on fire parameters. The study area, characterized by a mosaic of urban areas, protected areas, and other areas subject to anthropogenic disturbances, is mainly composed by fire-prone Mediterranean maquis. The input themes needed to run FlamMap were input as grid of 10 meters; the wind data, obtained using a computational fluid-dynamic model, were inserted as gridded file, with a resolution of 50 m. The analysis revealed high fire probability and severity in most of the areas, and therefore a high potential danger. The FlamMap outputs and the derived fire probability maps can be used in decision support systems for fire spread and behaviour and for fire danger assessment with actual and future fire regimes.

Resilient Grid Operational Strategies

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

Pasqualini, Donatella

Extreme weather-related disturbances, such as hurricanes, are a leading cause of grid outages historically. Although physical asset hardening is perhaps the most common way to mitigate the impacts of severe weather, operational strategies may be deployed to limit the extent of societal and economic losses associated with weather-related physical damage.1 The purpose of this study is to examine bulk power-system operational strategies that can be deployed to mitigate the impact of severe weather disruptions caused by hurricanes, thereby increasing grid resilience to maintain continuity of critical infrastructure during extreme weather. To estimate the impacts of resilient grid operational strategies, Losmore » Alamos National Laboratory (LANL) developed a framework for hurricane probabilistic risk analysis (PRA). The probabilistic nature of this framework allows us to estimate the probability distribution of likely impacts, as opposed to the worst-case impacts. The project scope does not include strategies that are not operations related, such as transmission system hardening (e.g., undergrounding, transmission tower reinforcement and substation flood protection) and solutions in the distribution network.« less

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?

Weather assessment and forecasting

NASA Technical Reports Server (NTRS)

1977-01-01

Data management program activities centered around the analyses of selected far-term Office of Applications (OA) objectives, with the intent of determining if significant data-related problems would be encountered and if so what alternative solutions would be possible. Three far-term (1985 and beyond) OA objectives selected for analyses as having potential significant data problems were large-scale weather forecasting, local weather and severe storms forecasting, and global marine weather forecasting. An overview of general weather forecasting activities and their implications upon the ground based data system is provided. Selected topics were specifically oriented to the use of satellites.

Detection of Allophane on Mars Through Orbital and In-Situ Thermal-Infrared Spectroscopy

NASA Technical Reports Server (NTRS)

Rampe, E. B.; Kraft, M. D.; Sharp, T. G.; Golden, D. C.; Ming, Douglas W.

2011-01-01

We have collected laboratory thermal IR spectra of the mineraloid allophane and aluminosilicate gels. Using those spectra to model regional TES spectra, we suggest that several areas of Mars contain significant amounts of allophane-like weathering products. The presence of allophane on Mars indicates that 1) significant Al sources, such as feldspar or glass, were weathered; 2) weathering on Mars produced poorly-crystalline aluminosilicates, rather than easily identifiable crystalline minerals; and 3) some Martian weathering proceeded under moderate pH environments, suggesting acid weathering is not the only major alteration mechanism on Mars.

Colluvial deposits as a possible weathering reservoir in uplifting mountains

NASA Astrophysics Data System (ADS)

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

2018-03-01

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

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

NASA Astrophysics Data System (ADS)

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

2013-12-01

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

Science basis for changing forest structure to modify wildfire behavior and severity

Treesearch

Russell T. Graham; Sarah McCaffrey; Theresa B. Jain

2004-01-01

Fire, other disturbances, physical setting, weather, and climate shape the structure and function of forests throughout the Western United States. More than 80 years of fire research have shown that physical setting, fuels, and weather combine to determine wildfire intensity (the rate at which it consumes fuel) and severity (the effect fire has on vegetation, soils,...

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.

The use of normalized climatological anomalies to rank synoptic-scale events and their relation to Weather Types

NASA Astrophysics Data System (ADS)

Ramos, A. M.; Lorenzo, M. N.; Gimeno, L.; Nieto, R.; Añel, J. A.

2009-09-01

Several methods have been developed to rank meteorological events in terms of severity, social impact or economic impacts. These classifications are not always objective since they depend of several factors, for instance, the observation network is biased towards the densely populated urban areas against rural or oceanic areas. It is also very important to note that not all rare synoptic-scale meteorological events attract significant media attention. In this work we use a comprehensive method of classifying synoptic-scale events adapted from Hart and Grumm, 2001, to the European region (30N-60N, 30W-15E). The main motivation behind this method is that the more unusual the event (a cold outbreak, a heat wave, or a flood), for a given region, the higher ranked it must be. To do so, we use four basic meteorological variables (Height, Temperature, Wind and Specific Humidity) from NCEP reanalysis dataset over the range of 1000hPa to 200hPa at a daily basis from 1948 to 2004. The climatology used embraces the 1961-1990 period. For each variable, the analysis of raking climatological anomalies was computed taking into account the daily normalized departure from climatology at different levels. For each day (from 1948 to 2004) we have four anomaly measures, one for each variable, and another, a combined where the anomaly (total anomaly) is the average of the anomaly of the four variables. Results will be analyzed on a monthly, seasonal and annual basis. Seasonal trends and variability will also be shown. In addition, and given the extent of the database, the expected return periods associated with the anomalies are revealed. Moreover, we also use an automated version of the Lamb weather type (WT) classification scheme (Jones et al, 1993) adapted for the Galicia area (Northwestern corner of the Iberian Peninsula) by Lorenzo et al (2008) in order to compute the daily local circulation regimes in this area. By combining the corresponding daily WT with the five anomaly measures we can evaluate if there is any preferable WT responsible for high or low values of anomalies. Hart, R.E and R.H. Grumm (2001) Using normalized climatological anomalies to rank synoptic-scale events objectivily. Monthly Weather Review, 129, 2426-2442. Jones, P. D., M. Hulme, K. R. Briffa (1993) A comparison of Lamb circulation types with anobjective classification scheme. International Journal of Climatology, 13: 655- 663. Lorenzo M.N., J.J. Taboada and L.Gimeno (2008). Links between circulation weather types and teleconnection patterns and their influence on precipitation patterns in Galicia (NW Spain). International Journal of Climatology 28(11): 1493:1505 DOI: 10.1002/joc.1646.

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.

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

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

Makhmalbaf, Atefe; Srivastava, Viraj; Wang, Na

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

Use of the LANDSAT-2 Data Collection System in the Colorado River Basin Weather Modification Program. [San Juan Mountains, Colorado

NASA Technical Reports Server (NTRS)

Kahan, A. M. (Principal Investigator)

1975-01-01

The author has identified the following significant results. The LANDSAT data collection system has proven itself to be a valuable tool for control of cloud seeding operations and for verification of weather forecasts. These platforms have proven to be reliable weather resistant units suitable for the collection of hydrometeorological data from remote severe weather environments. The detailed design of the wind speed and direction system and the wire-wrapping of the logic boards were completed.

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.

Multi-viewpoint Coronal Mass Ejection Catalog Based on STEREO COR2 Observations

NASA Astrophysics Data System (ADS)

Vourlidas, Angelos; Balmaceda, Laura A.; Stenborg, Guillermo; Dal Lago, Alisson

2017-04-01

We present the first multi-viewpoint coronal mass ejection (CME) catalog. The events are identified visually in simultaneous total brightness observations from the twin SECCHI/COR2 coronagraphs on board the Solar Terrestrial Relations Observatory mission. The Multi-View CME Catalog differs from past catalogs in three key aspects: (1) all events between the two viewpoints are cross-linked, (2) each event is assigned a physics-motivated morphological classification (e.g., jet, wave, and flux rope), and (3) kinematic and geometric information is extracted semi-automatically via a supervised image segmentation algorithm. The database extends from the beginning of the COR2 synoptic program (2007 March) to the end of dual-viewpoint observations (2014 September). It contains 4473 unique events with 3358 events identified in both COR2s. Kinematic properties exist currently for 1747 events (26% of COR2-A events and 17% of COR2-B events). We examine several issues, made possible by this cross-linked CME database, including the role of projection on the perceived morphology of events, the missing CME rate, the existence of cool material in CMEs, the solar cycle dependence on CME rate, speeds and width, and the existence of flux rope within CMEs. We discuss the implications for past single-viewpoint studies and for Space Weather research. The database is publicly available on the web including all available measurements. We hope that it will become a useful resource for the community.

Developing the U.S. Wildland Fire Decision Support System

Treesearch

Erin Noonan-Wright; Tonja S. Opperman; Mark A. Finney; Tom Zimmerman; Robert C. Seli; Lisa M. Elenz; David E. Calkin; John R. Fiedler

2011-01-01

A new decision support tool, the Wildland Fire Decision Support System (WFDSS) has been developed to support risk-informed decision-making for individual fires in the United States. WFDSS accesses national weather data and forecasts, fire behavior prediction, economic assessment, smoke management assessment, and landscape databases to efficiently formulate and apply...

Meteorological phenomena in Western classical orchestral music

NASA Astrophysics Data System (ADS)

Williams, P. D.; Aplin, K. L.

2012-12-01

The creative output of composers, writers, and artists is often influenced by their surroundings. To give a literary example, it has been claimed recently that some of the characters in Oliver Twist and A Christmas Carol were based on real-life people who lived near Charles Dickens in London. Of course, an important part of what we see and hear is not only the people with whom we interact, but also our geophysical surroundings. Of all the geophysical phenomena to influence us, the weather is arguably the most significant, because we are exposed to it directly and daily. The weather was a great source of inspiration for Monet, Constable, and Turner, who are known for their scientifically accurate paintings of the skies. But to what extent does weather inspire composers? The authors of this presentation, who are atmospheric scientists by day but amateur classical musicians by night, have been contemplating this question. We have built a systematic musical database, which has allowed us to catalogue and analyze the frequencies with which weather is depicted in a sample of classical orchestral music. The depictions vary from explicit mimicry using traditional and specialized orchestral instruments, through to subtle suggestions. We have found that composers are generally influenced by their own environment in the type of weather they choose to represent. As befits the national stereotype, British composers seem disproportionately keen to depict the UK's variable weather patterns and stormy coastline. Reference: Aplin KL and Williams PD (2011) Meteorological phenomena in Western classical orchestral music. Weather, 66(11), pp 300-306. doi:10.1002/wea.765

Using Weather Types to Understand and Communicate Weather and Climate Impacts

NASA Astrophysics Data System (ADS)

Prein, A. F.; Hale, B.; Holland, G. J.; Bruyere, C. L.; Done, J.; Mearns, L.

2017-12-01

A common challenge in atmospheric research is the translation of scientific advancements and breakthroughs to decision relevant and actionable information. This challenge is central to the mission of NCAR's Capacity Center for Climate and Weather Extremes (C3WE, www.c3we.ucar.edu). C3WE advances our understanding of weather and climate impacts and integrates these advances with distributed information technology to create tools that promote a global culture of resilience to weather and climate extremes. Here we will present an interactive web-based tool that connects historic U.S. losses and fatalities from extreme weather and climate events to 12 large-scale weather types. Weather types are dominant weather situations such as winter high-pressure systems over the U.S. leading to very cold temperatures or summertime moist humid air masses over the central U.S. leading to severe thunderstorms. Each weather type has a specific fingerprint of economic losses and fatalities in a region that is quantified. Therefore, weather types enable a direct connection of observed or forecasted weather situation to loss of life and property. The presented tool allows the user to explore these connections, raise awareness of existing vulnerabilities, and build resilience to weather and climate extremes.

Radar Scan Strategies for the Patrick Air Force Base Weather Surveillance Radar, Model-74C, Replacement

NASA Technical Reports Server (NTRS)

Short, David

2008-01-01

The 45th Weather Squadron (45 WS) is replacing the Weather Surveillance Radar, Model 74C (WSR-74C) at Patrick Air Force Base (PAFB), with a Doppler, dual polarization radar, the Radtec 43/250. A new scan strategy is needed for the Radtec 43/250, to provide high vertical resolution data over the Kennedy Space Center (KSC) and Cape Canaveral Air Force Station (CCAFS) launch pads, while taking advantage of the new radar's advanced capabilities for detecting severe weather phenomena associated with convection within the 45 WS area of responsibility. The Applied Meteorology Unit (AMU) developed several scan strategies customized for the operational needs of the 45 WS. The AMU also developed a plan for evaluating the scan strategies in the period prior to operational acceptance, currently scheduled for November 2008.

Relationships between Long-Term Demography and Weather in a Sub-Arctic Population of Common Eider

PubMed Central

Jónsson, Jón Einar; Gardarsson, Arnthor; Gill, Jennifer A.; Pétursdóttir, Una Krístín; Petersen, Aevar; Gunnarsson, Tómas Grétar

2013-01-01

Effects of local weather on individuals and populations are key drivers of wildlife responses to climatic changes. However, studies often do not last long enough to identify weather conditions that influence demographic processes, or to capture rare but extreme weather events at appropriate scales. In Iceland, farmers collect nest down of wild common eider Somateria mollissima and many farmers count nests within colonies annually, which reflects annual variation in the number of breeding females. We collated these data for 17 colonies. Synchrony in breeding numbers was generally low between colonies. We evaluated 1) demographic relationships with weather in nesting colonies of common eider across Iceland during 1900–2007; and 2) impacts of episodic weather events (aberrantly cold seasons or years) on subsequent breeding numbers. Except for episodic events, breeding numbers within a colony generally had no relationship to local weather conditions in the preceding year. However, common eider are sexually mature at 2–3 years of age and we found a 3-year time lag between summer weather and breeding numbers for three colonies, indicating a positive effect of higher pressure, drier summers for one colony, and a negative effect of warmer, calmer summers for two colonies. These findings may represent weather effects on duckling production and subsequent recruitment. Weather effects were mostly limited to a few aberrant years causing reductions in breeding numbers, i.e. declines in several colonies followed severe winters (1918) and some years with high NAO (1992, 1995). In terms of life history, adult survival generally is high and stable and probably only markedly affected by inclement weather or aberrantly bad years. Conversely, breeding propensity of adults and duckling production probably do respond more to annual weather variations; i.e. unfavorable winter conditions for adults increase probability of death or skipped breeding, whereas favorable summers can promote boom years for recruitment. PMID:23805292

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

Integration of Infrasound, Atmospheric Pressure, and Seismic Observations with the NSF EarthScope USArray Transportable Array

NASA Astrophysics Data System (ADS)

Vernon, F.; Tytell, J.; Hedlin, M. A. H.; Walker, K.; Busby, R.; Woodward, R.

2012-04-01

Earthscope's USArray Transportable Array (TA) network serves as a real-time monitoring and recording platform for both seismic and weather phenomena. To date, most of the approximately 500 TA stations have been retrofitted with VTI SCP1000 MEMS barometric pressure gauges capable of recording data at 1 sample per second (sps). Additionally, over 300 of the TA stations have also been retrofitted with Setra 278 barometric gauges and NCPA infrasound sensors capable of recording data at 1 and 40 sps. While individual seismic events have been successfully researched via the TA network, observations of powerful weather events by the TA network have yet to be embraced by the scientific community. This presentation will focus on case studies involving severe weather passage across portions of the TA network throughout 2011 in order to highlight its viability as a platform for real-time weather monitoring and research. It will also highlight the coupling of atmospheric signals into the seismic observations. Examples of gust front passages and pressure couplets from severe thunderstorms will be presented, as will observations of multiple tornados occurred in the Spring of 2011. These data will demonstrate the overall viability of the TA network for monitoring severe weather events in real-time.

A Conceptual Model of the Severe-Storm Environment for Inclusion into Air Weather Service Severe-Storm Analysis and Forecast Procedures.

DTIC Science & Technology

1984-11-16

thunderstorm forecasting , Bull. Am. Meteorol. Soc. 34:250-252. 19. Galway , J.G. (1956) The lifted index as a prediction of latent instability, Bull...downwind, which are geographically related and can be traced through time by a forecaster . In fact, a typical Great Plains severe-storm situation has...weather station setting, only one sounding can be plotted and anal- yzed because of time constraints. Appendix C contains two single-station forecast

Space Weather Services of Korea

NASA Astrophysics Data System (ADS)

Yoon, K.; Hong, S.; Park, S.; Kim, Y. Y.; Wi, G.

2015-12-01

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. 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. In this study, we will present KSWC's recent efforts on development of application-oriented space weather research products and services on user needs, and introduce new international collaborative projects, such as IPS-Driven Enlil model, global network of DSCOVR and STEREO satellites tracking, and ARMAS (Automated Radiation Measurement for Aviation Safety).

Space Weather Services of Korea

NASA Astrophysics Data System (ADS)

Yoon, KiChang; Kim, Jae-Hun; Kim, Young Yun; Kwon, Yongki; Wi, Gwan-sik

2016-07-01

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. 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. In this study, we will present KSWC's recent efforts on development of application-oriented space weather research products and services on user needs, and introduce new international collaborative projects, such as IPS-Driven Enlil model, DREAM model estimating electron in satellite orbit, global network of DSCOVR and STEREO satellites tracking, and ARMAS (Automated Radiation Measurement for Aviation Safety).

Space Weather Services of Korea

NASA Astrophysics Data System (ADS)

Yoon, K.; Hong, S.; Jangsuk, C.; Dong Kyu, K.; Jinyee, C.; Yeongoh, C.

2016-12-01

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. 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. In this study, we will present KSWC's recent efforts on development of application-oriented space weather research products and services on user needs, and introduce new international collaborative projects, such as IPS-Driven Enlil model, DREAM model estimating electron in satellite orbit, global network of DSCOVR and STEREO satellites tracking, and ARMAS (Automated Radiation Measurement for Aviation Safety).

Comparative ratings of 1951 forest fire weather in western Oregon.

Treesearch

Owen P. Cramer; Robert Kirkpatrick

1951-01-01

The 1951 forest fire weather in western Oregon is generally conceded to have been unusually severe. In order to compare this season with others, this report uses a scheme for rating fire seasons recently developed by the Fire Research section of the Experiment Station, The rating is based on indices of three weather characteristics which generally control burning...

Unweathered and weathered aviation kerosine: Chemical characterization and effects on hatching success of duck eggs

USGS Publications Warehouse

Albers, P.H.; Gay, M.L.

1982-01-01

Effects of weathered aviation kerosine from a pipeline rupture in northern Virginia on mallard egg hatchability. Artificially-incubated mallard eggs were exposed by eggshell application to several amounts of weathered and unweathered aviation kerosine on day 6 of incubation. Measured hatching success of eggs and characterized the kerosine according to 14 aliphatic and 9 aromatic compounds.

1954 forest fire weather in western Oregon and Washington.

Treesearch

Owen P. Cramer

1954-01-01

For the second successive fire season forest fire weather in western Oregon and Washington was far below normal severity. The low danger is reflected in record low numbers of fires reported by forestry offices of both States and by the U. S. Forest Service for their respective protection areas. Although spring and fall fire weather was near normal, a rain-producing...

Relative impact of weather vs. fuels on fire regimes in coastal California

Treesearch

Jon E. Keeley

2008-01-01

Extreme fire weather is of over riding importance in determining fire behavior in coastal chaparral and on these landscapes fire suppression policy has not resulted in fire exclusion. There is regional variation in foehn winds, which are most important in southern California. Under these severe fire weather conditions fuel age does not constrain fire behavior. As a...

1955 forest fire weather in western Oregon and Washington.

Treesearch

Owen P. Cramer

1955-01-01

While fire-weather severity remained low for the third successive year in western Washington, 1955 brought near normal fire weather to western Oregon for the first time since 1952. Temperatures were cooler than normal throughout the season in both half States, with record or near record lows for April, May, and July. April, July, and October were unusually rainy while...

78 FR 35571 - Fisheries of the Caribbean, Gulf of Mexico, and South Atlantic; Shrimp Fishery Off the Southern...

Federal Register 2010, 2011, 2012, 2013, 2014

2013-06-13

...) when state waters close as a result of severe winter weather. Amendment 9 also revises the overfished... Atlantic shrimp cold weather closure.'' This is because the current regulations refer to the FMP for the... weather and a closure of state waters. Currently, a state must demonstrate at least an 80-percent...

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.

The potential impact of regional climate change on fire weather in the United States

Treesearch

Ying Tang; Shiyuan Zhong; Lifeng Luo; Xindi Bian; Warren E. Heilman; Julie. Winkler

2015-01-01

Climate change is expected to alter the frequency and severity of atmospheric conditions conducive for wildfires. In this study, we assess potential changes in fire weather conditions for the contiguous United States using the Haines Index (HI), a fire weather index that has been employed operationally to detect atmospheric conditions favorable for large and erratic...

Vulnerability and adaptation to severe weather events in the American southwest

DOE PAGES

Boero, Riccardo; Bianchini, Laura; Pasqualini, Donatella

2015-05-04

Climate change can induce changes in the frequency of severe weather events representing a threat to socio-economic development. It is thus of uttermost importance to understand how the vulnerability to the weather of local communities is determined and how adaptation public policies can be effectively put in place. We focused our empirical analysis on the American Southwest. Results show that, consistently with the predictions of an investment model, economic characteristics signaling local economic growth in the near future decrease the level of vulnerability. We also show that federal governments transfers and grants neither work to support recovery from and adaptationmore » to weather events nor to distribute their costs over a broader tax base. Finally, we show that communities relying on municipal bonds to finance adaptation and recovery policies can benefit from local acknowledgment of the need for such policies and that they do not have to pay lenders a premium for the risk induced by weather events. In conclusion, our findings suggest that determinants of economic growth support lower vulnerability to the weather and increase options for financing adaptation and recovery policies, but also that only some communities are likely to benefit from those processes.« 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

Risk Communication: The Role of the South Carolina State Climatology Office.

NASA Astrophysics Data System (ADS)

Smith, David J.; Purvis, John C.; Felts, Arthur

1995-12-01

The federally supported state climatologist program ended in 1972. Thereafter, most states supported these endeavors in coordination with the National Climatic Data Center, but the current state programs vary widely. One of the functions of state climate programs that evolved since 1972 is acting as a liaison between the National Weather Service and various state agencies. This role is most apparent and controversial in coordinating state and local government response to severe weather and extreme climate anomalies such as drought, flood, winter storms, and tropical cyclones. The activities of the climate office in South Carolina during Hurricane Hugo in September 1989 and the October 1990 floods reveal how these interactions occur in one state that mandated these activities. The state climate office had to react to shifting weather conditions and to variable political conditions that affect public organizations. The climate office in South Carolina acts to interpret weather information, develop scenarios and predictions, and to assist in postevent damage surveys. This review is presented to acknowledge and document the expanding role of the state climate office in South Carolina in response to state and local government needs for weather forecast interpretation and expert guidance in the event of severe weather.

Vulnerability and adaptation to severe weather events in the American southwest

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

Boero, Riccardo; Bianchini, Laura; Pasqualini, Donatella

Climate change can induce changes in the frequency of severe weather events representing a threat to socio-economic development. It is thus of uttermost importance to understand how the vulnerability to the weather of local communities is determined and how adaptation public policies can be effectively put in place. We focused our empirical analysis on the American Southwest. Results show that, consistently with the predictions of an investment model, economic characteristics signaling local economic growth in the near future decrease the level of vulnerability. We also show that federal governments transfers and grants neither work to support recovery from and adaptationmore » to weather events nor to distribute their costs over a broader tax base. Finally, we show that communities relying on municipal bonds to finance adaptation and recovery policies can benefit from local acknowledgment of the need for such policies and that they do not have to pay lenders a premium for the risk induced by weather events. In conclusion, our findings suggest that determinants of economic growth support lower vulnerability to the weather and increase options for financing adaptation and recovery policies, but also that only some communities are likely to benefit from those processes.« less

Applied Meteorology Unit Quarterly Report, Second Quarter FY-13

NASA Technical Reports Server (NTRS)

Bauman, William; Crawford, Winifred; Watson, Leela; Shafer, Jaclyn; Huddleston, Lisa

2013-01-01

The AMU team worked on six tasks for their customers: (1) Ms. Crawford continued work on the objective lightning forecast task for airports in east-central Florida, and began work on developing a dual-Doppler analysis with local Doppler radars, (2) Ms. Shafer continued work for Vandenberg Air Force Base on an automated tool to relate pressure gradients to peak winds, (3) Dr. Huddleston continued work to develop a lightning timing forecast tool for the Kennedy Space Center/Cape Canaveral Air Force Station area, (4) Dr. Bauman continued work on a severe weather forecast tool focused on east-central Florida, (5) Mr. Decker began developing a wind pairs database for the Launch Services Program to use when evaluating upper-level winds for launch vehicles, and (6) Dr. Watson began work to assimilate observational data into the high-resolution model configurations, she created for Wallops Flight Facility and the Eastern Range.

The Economic Impact of Space Weather: Where Do We Stand?

PubMed

Eastwood, J P; Biffis, E; Hapgood, M A; Green, L; Bisi, M M; Bentley, R D; Wicks, R; McKinnell, L-A; Gibbs, M; Burnett, C

2017-02-01

Space weather describes the way in which the Sun, and conditions in space more generally, impact human activity and technology both in space and on the ground. It is now well understood that space weather represents a significant threat to infrastructure resilience, and is a source of risk that is wide-ranging in its impact and the pathways by which this impact may occur. Although space weather is growing rapidly as a field, work rigorously assessing the overall economic cost of space weather appears to be in its infancy. Here, we provide an initial literature review to gather and assess the quality of any published assessments of space weather impacts and socioeconomic studies. Generally speaking, there is a good volume of scientific peer-reviewed literature detailing the likelihood and statistics of different types of space weather phenomena. These phenomena all typically exhibit "power-law" behavior in their severity. The literature on documented impacts is not as extensive, with many case studies, but few statistical studies. The literature on the economic impacts of space weather is rather sparse and not as well developed when compared to the other sections, most probably due to the somewhat limited data that are available from end-users. The major risk is attached to power distribution systems and there is disagreement as to the severity of the technological footprint. This strongly controls the economic impact. Consequently, urgent work is required to better quantify the risk of future space weather events. © 2017 The Authors Risk Analysis published by Wiley Periodicals, Inc. on behalf of Society for Risk Analysis.

The main pillar: Assessment of space weather observational asset performance supporting nowcasting, forecasting, and research to operations.

PubMed

Posner, A; Hesse, M; St Cyr, O C

2014-04-01

Space weather forecasting critically depends upon availability of timely and reliable observational data. It is therefore particularly important to understand how existing and newly planned observational assets perform during periods of severe space weather. Extreme space weather creates challenging conditions under which instrumentation and spacecraft may be impeded or in which parameters reach values that are outside the nominal observational range. This paper analyzes existing and upcoming observational capabilities for forecasting, and discusses how the findings may impact space weather research and its transition to operations. A single limitation to the assessment is lack of information provided to us on radiation monitor performance, which caused us not to fully assess (i.e., not assess short term) radiation storm forecasting. The assessment finds that at least two widely spaced coronagraphs including L4 would provide reliability for Earth-bound CMEs. Furthermore, all magnetic field measurements assessed fully meet requirements. However, with current or even with near term new assets in place, in the worst-case scenario there could be a near-complete lack of key near-real-time solar wind plasma data of severe disturbances heading toward and impacting Earth's magnetosphere. Models that attempt to simulate the effects of these disturbances in near real time or with archival data require solar wind plasma observations as input. Moreover, the study finds that near-future observational assets will be less capable of advancing the understanding of extreme geomagnetic disturbances at Earth, which might make the resulting space weather models unsuitable for transition to operations. Manuscript assesses current and near-future space weather assetsCurrent assets unreliable for forecasting of severe geomagnetic stormsNear-future assets will not improve the situation.

The main pillar: Assessment of space weather observational asset performance supporting nowcasting, forecasting, and research to operations

PubMed Central

Posner, A; Hesse, M; St Cyr, O C

2014-01-01

Space weather forecasting critically depends upon availability of timely and reliable observational data. It is therefore particularly important to understand how existing and newly planned observational assets perform during periods of severe space weather. Extreme space weather creates challenging conditions under which instrumentation and spacecraft may be impeded or in which parameters reach values that are outside the nominal observational range. This paper analyzes existing and upcoming observational capabilities for forecasting, and discusses how the findings may impact space weather research and its transition to operations. A single limitation to the assessment is lack of information provided to us on radiation monitor performance, which caused us not to fully assess (i.e., not assess short term) radiation storm forecasting. The assessment finds that at least two widely spaced coronagraphs including L4 would provide reliability for Earth-bound CMEs. Furthermore, all magnetic field measurements assessed fully meet requirements. However, with current or even with near term new assets in place, in the worst-case scenario there could be a near-complete lack of key near-real-time solar wind plasma data of severe disturbances heading toward and impacting Earth's magnetosphere. Models that attempt to simulate the effects of these disturbances in near real time or with archival data require solar wind plasma observations as input. Moreover, the study finds that near-future observational assets will be less capable of advancing the understanding of extreme geomagnetic disturbances at Earth, which might make the resulting space weather models unsuitable for transition to operations. Key Points Manuscript assesses current and near-future space weather assets Current assets unreliable for forecasting of severe geomagnetic storms Near-future assets will not improve the situation PMID:26213516

Assessment of the 1998–2001 drought impact on forest health in southeastern forests: an analysis of drought severity using FHM data

Treesearch

R. J. Klos; G. G. Wang; W. L. Bauerle

2010-01-01

Analyses of forest health indicators monitored through the Forest Health and Monitoring (FHM) program suggested that weather was the most important cause of tree mortality. Drought is of particular importance among weather variables because several global climate change scenarios predicted more frequent and/or intense drought in the Southeastern United States. During...

Forest fire weather in eastern Oregon and central Washington in 1960.

Treesearch

Owen P. Cramer; Howard E. Graham

1961-01-01

In 1960, the first analysis of fire season weather was made for forests east of the Cascade Range. Highlights were: The 1960 season was among the most severe since 1939 in eastern Oregon, was more severe than normal in central Washington, and will long be remembered for the rainless lightning storm that hit northeast Oregon with devastating effect the evening of July...

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.

Comprehensive national database of tree effects on air quality and human health in the United States.

PubMed

Hirabayashi, Satoshi; Nowak, David J

2016-08-01

Trees remove air pollutants through dry deposition processes depending upon forest structure, meteorology, and air quality that vary across space and time. Employing nationally available forest, weather, air pollution and human population data for 2010, computer simulations were performed for deciduous and evergreen trees with varying leaf area index for rural and urban areas in every county in the conterminous United States. The results populated a national database of annual air pollutant removal, concentration changes, and reductions in adverse health incidences and costs for NO2, O3, PM2.5 and SO2. The developed database enabled a first order approximation of air quality and associated human health benefits provided by trees with any forest configurations anywhere in the conterminous United States over time. Comprehensive national database of tree effects on air quality and human health in the United States was developed. Copyright © 2016 Elsevier Ltd. All rights reserved.

Physiological responses of pilots to severe weather flying.

DOT National Transportation Integrated Search

1966-07-01

Selected measurements of stress-related and other physiological variables were made on jet aircraft pilots participating in USWB-NSSL turbulent weather programs. Data were gathered from two categories of flying conditions: (1) storm penetration fligh...

NASA/MSFC FY-80 Atmospheric Processes Research Review

NASA Technical Reports Server (NTRS)

Turner, R. E. (Compiler)

1980-01-01

Three general areas of research were discussed: Global Weather, Upper Atmosphere, and Severe Storms and Local Weather. Research project summaries, in narrative outline form, stating objectives, significant accomplishments, and recommendations for future research are presented.

NASA/MSFC FY-81 Atmospheric Processes Research Review

NASA Technical Reports Server (NTRS)

Turner, R. E. (Compiler)

1981-01-01

Progress in ongoing research programs and future plans for satellite investigations into global weather, upper atmospheric phenomena, and severe storms and local weather are summarized. Principle investigators and publications since June 1980 are listed.

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.

Space Science

NASA Image and Video Library

2002-06-01

NASA's Marshall Space Flight Center (MSFC) and university scientists from the National Space Science and Technology Center (NSSTC) in Huntsville, Alabama, are watching the Sun in an effort to better predict space weather - blasts of particles and magnetic fields from the Sun that impact the magnetosphere, the magnetic bubble around the Earth. Filled by charged particles trapped in the Earth's magnetic field, the spherical comet-shaped magnetosphere extends out 40,000 miles from Earth's surface in the sunward direction and more in other directions. This image illustrates the Sun-Earth cornection. When massive solar explosions, known as coronal mass ejections, blast through the Sun's outer atmosphere and plow toward Earth at speeds of thousands of miles per second, the resulting effects can be harmful to communication satellites and astronauts outside the Earth's magnetosphere. Like severe weather on Earth, severe space weather can be costly. On the ground, magnetic storms wrought by these solar particles can knock out electric power. By using the Solar Vector Magnetograph, a solar observation facility at MSFC, scientists are learning what signs to look for as indicators of potential severe space weather.

A New Tool for Forecasting Solar Drivers of Severe Space Weather

NASA Technical Reports Server (NTRS)

Adams, J. H.; Falconer, D.; Barghouty, A. F.; Khazanov, I.; Moore, R.

2010-01-01

This poster describes a tool that is designed to forecast solar drivers for severe space weather. Since most severe space weather is driven by Solar flares and Coronal Mass Ejections (CMEs) - the strongest of these originate in active regions and are driven by the release of coronal free magnetic energy and There is a positive correlation between an active region's free magnetic energy and the likelihood of flare and CME production therefore we can use this positive correlation as the basis of our empirical space weather forecasting tool. The new tool takes a full disk Michelson Doppler Imager (MDI) magnetogram, identifies strong magnetic field areas, identifies these with NOAA active regions, and measures a free-magnetic-energy proxy. It uses an empirically derived forecasting function to convert the free-magnetic-energy proxy to an expected event rate. It adds up the expected event rates from all active regions on the disk to forecast the expected rate and probability of each class of events -- X-class flares, X&M class flares, CMEs, fast CMEs, and solar particle events (SPEs).

Coupling river hydrochemical information with catchment properties for multi-scale-analysis of lateral matter fluxes in the Earth system

NASA Astrophysics Data System (ADS)

Hartmann, Jens; Lauerwald, Ronny; Moosdorf, Nils

2016-04-01

Over the last decade the number of regional to global scale studies of river chemical fluxes and their steering factors increased rapidly, entailing a growing demand for appropriate databases to calculate mass budgets, to calibrate models, or to test hypotheses [1, 2]. Research applying compilations of hydrochemical data are related to questions targeting different time and spatial scales, as for example the annual to centennial scale. In focus are often the alteration of land-ocean matter fluxes due anthropogenic disturbance, the climate sensitivity of chemical weathering fluxes [3], or nutrient fluxes and their evolution [2, 4]. We present an overview of the GLObal RIver CHemistry database GLORICH, which combines an assemblage of hydrochemical data from varying sources with catchment characteristics of the sampling locations [1]. The information provided include e.g. catchment size, lithology, soil, climate, land cover, net primary production, population density and average slope gradient. The data base comprises 1.27 million samples distributed over 17,000 sampling locations [1]. It will be shown how large assemblages of data are useful to target some major questions about the alteration of land ocean element fluxes due to climate or land use change while coupling hydrochemical data with catchment properties in a homogenized database. An extension by isotopic data will be in the focus of future work [c.f. 5]. Further, applications in climate change studies for understanding feedbacks in the Earth system will be discussed [6]. References: [1] Hartmann, J., Lauerwald, R., & Moosdorf, N. (2014). A brief overview of the GLObal RIver CHemistry Database, GLORICH. Procedia Earth and Planetary Science, 10, 23-27. [2] Hartmann, J., Levy, J., & Kempe, S. (2011). Increasing dissolved silica trends in the Rhine River: an effect of recovery from high P loads?. Limnology, 12(1), 63-73. [3] Hartmann, J., Moosdorf, N., Lauerwald, R., Hinderer, M., & West, A. J. (2014). Global chemical weathering and associated P-release - the role of lithology, temperature and soil properties. Chemical Geology, 363, 145-163. [4] Hartmann, J., West, A. J., Renforth, P., Köhler, P., De La Rocha, C. L., Wolf-Gladrow, D. A., Dürr, H.H. & Scheffran, J. (2013). Enhanced chemical weathering as a geoengineering strategy to reduce atmospheric carbon dioxide, supply nutrients, and mitigate ocean acidification. Reviews of Geophysics, 51(2), 113-149. [5] Bataille, C. P., Brennan, S. R., Hartmann, J., Moosdorf, N., Wooller, M. J., & Bowen, G. J. (2014). A geostatistical framework for predicting variations in strontium concentrations and isotope ratios in Alaskan rivers. Chemical Geology, 389, 1-15. [6] Goll, D. S., Moosdorf, N., Hartmann, J., & Brovkin, V. (2014). Climate-driven changes in chemical weathering and associated phosphorus release since 1850: Implications for the land carbon balance. Geophysical Research Letters, 41(10), 3553-3558.

Municipalities' Preparedness for Weather Hazards and Response to Weather Warnings

PubMed Central

Mehiriz, Kaddour; Gosselin, Pierre

2016-01-01

The study of the management of weather-related disaster risks by municipalities has attracted little attention even though these organizations play a key role in protecting the population from extreme meteorological conditions. This article contributes to filling this gap with new evidence on the level and determinants of Quebec municipalities’ preparedness for weather hazards and response to related weather warnings. Using survey data from municipal emergency management coordinators and secondary data on the financial and demographic characteristics of municipalities, the study shows that most Quebec municipalities are sufficiently prepared for weather hazards and undertake measures to protect the population when informed of imminent extreme weather events. Significant differences between municipalities were noted though. Specifically, the level of preparedness was positively correlated with the municipalities’ capacity and population support for weather-related disaster management policies. In addition, the risk of weather-related disasters increases the preparedness level through its effect on population support. We also found that the response to weather warnings depended on the risk of weather-related disasters, the preparedness level and the quality of weather warnings. These results highlight areas for improvement in the context of increasing frequency and/or severity of such events with current climate change. PMID:27649547

Municipalities' Preparedness for Weather Hazards and Response to Weather Warnings.

PubMed

Mehiriz, Kaddour; Gosselin, Pierre

2016-01-01

The study of the management of weather-related disaster risks by municipalities has attracted little attention even though these organizations play a key role in protecting the population from extreme meteorological conditions. This article contributes to filling this gap with new evidence on the level and determinants of Quebec municipalities' preparedness for weather hazards and response to related weather warnings. Using survey data from municipal emergency management coordinators and secondary data on the financial and demographic characteristics of municipalities, the study shows that most Quebec municipalities are sufficiently prepared for weather hazards and undertake measures to protect the population when informed of imminent extreme weather events. Significant differences between municipalities were noted though. Specifically, the level of preparedness was positively correlated with the municipalities' capacity and population support for weather-related disaster management policies. In addition, the risk of weather-related disasters increases the preparedness level through its effect on population support. We also found that the response to weather warnings depended on the risk of weather-related disasters, the preparedness level and the quality of weather warnings. These results highlight areas for improvement in the context of increasing frequency and/or severity of such events with current climate change.

An Open-source Meteorological Operational System and its Installation in Portuguese- speaking Countries

NASA Astrophysics Data System (ADS)

Almeida, W. G.; Ferreira, A. L.; Mendes, M. V.; Ribeiro, A.; Yoksas, T.

2007-05-01

CPTEC, a division of Brazil’s INPE, has been using several open-source software packages for a variety of tasks in its Data Division. Among these tools are ones traditionally used in research and educational communities such as GrADs (Grid Analysis and Display System from the Center for Ocean-Land-Atmosphere Studies (COLA)), the Local Data Manager (LDM) and GEMPAK (from Unidata), andl operational tools such the Automatic File Distributor (AFD) that are popular among National Meteorological Services. In addition, some tools developed locally at CPTEC are also being made available as open-source packages. One package is being used to manage the data from Automatic Weather Stations that INPE operates. This system uses only open- source tools such as MySQL database, PERL scripts and Java programs for web access, and Unidata’s Internet Data Distribution (IDD) system and AFD for data delivery. All of these packages are get bundled into a low-cost and easy to install and package called the Meteorological Data Operational System. Recently, in a cooperation with the SICLIMAD project, this system has been modified for use by Portuguese- speaking countries in Africa to manage data from many Automatic Weather Stations that are being installed in these countries under SICLIMAD sponsorship. In this presentation we describe the tools included-in and and architecture-of the Meteorological Data Operational System.

Economic Evaluations of the Health Impacts of Weather-Related Extreme Events: A Scoping Review

PubMed Central

Schmitt, Laetitia H. M.; Graham, Hilary M.; White, Piran C. L.

2016-01-01

The frequency and severity of extreme events is expected to increase under climate change. There is a need to understand the economic consequences of human exposure to these extreme events, to underpin decisions on risk reduction. We undertook a scoping review of economic evaluations of the adverse health effects from exposure to weather-related extreme events. We searched PubMed, Embase and Web of Science databases with no restrictions to the type of evaluations. Twenty studies were included, most of which were recently published. Most studies have been undertaken in the U.S. (nine studies) or Asia (seven studies), whereas we found no studies in Africa, Central and Latin America nor the Middle East. Extreme temperatures accounted for more than a third of the pool of studies (seven studies), closely followed by flooding (six studies). No economic study was found on drought. Whilst studies were heterogeneous in terms of objectives and methodology, they clearly indicate that extreme events will become a pressing public health issue with strong welfare and distributional implications. The current body of evidence, however, provides little information to support decisions on the allocation of scarce resources between risk reduction options. In particular, the review highlights a significant lack of research attention to the potential cost-effectiveness of interventions that exploit the capacity of natural ecosystems to reduce our exposure to, or ameliorate the consequences of, extreme events. PMID:27834843

Weather and children's physical activity; how and why do relationships vary between countries?

PubMed

Harrison, Flo; Goodman, Anna; van Sluijs, Esther M F; Andersen, Lars Bo; Cardon, Greet; Davey, Rachel; Janz, Kathleen F; Kriemler, Susi; Molloy, Lynn; Page, Angie S; Pate, Russ; Puder, Jardena J; Sardinha, Luis B; Timperio, Anna; Wedderkopp, Niels; Jones, Andy P

2017-05-30

Globally most children do not engage in enough physical activity. Day length and weather conditions have been identified as determinants of physical activity, although how they may be overcome as barriers is not clear. We aim to examine if and how relationships between children's physical activity and weather and day length vary between countries and identify settings in which children were better able to maintain activity levels given the weather conditions they experienced. In this repeated measures study, we used data from 23,451 participants in the International Children's Accelerometry Database (ICAD). Daily accelerometer-measured physical activity (counts per minute; cpm) was matched to local weather conditions and the relationships assessed using multilevel regression models. Multilevel models accounted for clustering of days within occasions within children within study-cities, and allowed us to explore if and how the relationships between weather variables and physical activity differ by setting. Increased precipitation and wind speed were associated with decreased cpm while better visibility and more hours of daylight were associated with increased cpm. Models indicated that increases in these variables resulted in average changes in mean cpm of 7.6/h of day length, -13.2/cm precipitation, 10.3/10 km visibility and -10.3/10kph wind speed (all p < 0.01). Temperature showed a cubic relationship with cpm, although between 0 and 20 degrees C the relationship was broadly linear. Age showed interactions with temperature and precipitation, with the associations larger among younger children. In terms of geographic trends, participants from Northern European countries and Melbourne, Australia were the most active, and also better maintained their activity levels given the weather conditions they experienced compared to those in the US and Western Europe. We found variation in the relationship between weather conditions and physical activity between ICAD studies and settings. Children in Northern Europe and Melbourne, Australia were not only more active on average, but also more active given the weather conditions they experienced. Future work should consider strategies to mitigate the impacts of weather conditions, especially among young children, and interventions involving changes to the physical environment should consider how they will operate in different weather conditions.

National Severe Storms Forecast Center

NASA Technical Reports Server (NTRS)

1977-01-01

The principal mission of the National Severe Storms Forecast Center (NSSFC) is to maintain a continuous watch of weather developments that are capable of producing severe local storms, including tornadoes, and to prepare and issue messages designated as either Weather Outlooks or Tornado or Severe Thunderstorm Watches for dissemination to the public and aviation services. In addition to its assigned responsibility at the national level, the NSSFC is involved in a number of programs at the regional and local levels. Subsequent subsections and paragraphs describe the NSSFC, its users, inputs, outputs, interfaces, capabilities, workload, problem areas, and future plans in more detail.

The Social and Economic Impacts of Space Weather (US Project)

NASA Astrophysics Data System (ADS)

Pulkkinen, A. A.; Bisi, M. M.; Webb, D. F.; Oughton, E. J.; Worman, S. L.; Taylor, S. M.; Onsager, T. G.; Adkins, J. E.; Baker, D. N.; Forbes, K. F.; Basoli, D.; Griot, O.

2017-12-01

The National Space Weather Action Plan calls for new research into the social and economic impacts of space weather and for the development of quantitative estimates of potential costs. In response to this call, NOAA's Space Weather Prediction Center (SWPC) and Abt Associates are working together to identify, describe, and quantify the impact of space weather to U.S. interests. This study covers impacts resulting from both moderate and severe space weather events across four technological sectors: Electric power, commercial aviation, satellites, and Global Navigation Satellite System (GNSS) users. It captures the full range of potential impacts, identified from an extensive literature review and from additional conversations with more than 50 sector stakeholders of diverse expertise from engineering to operations to end users. We organize and discuss our findings in terms of five broad but interrelated impact categories including Defensive Investments, Mitigating Actions, Asset Damages, Service Interruptions, and Health Effects. We also present simple, tractable estimates of the potential costs where we focused on quantifying a subset of all identified impacts that are apt to be largest and are also most plausible during moderate and more severe space weather scenarios. We hope that our systematic exploration of the social and economic impacts provides a foundation for the future work that is critical for designing technologies, developing procedures, and implementing policies that can effectively reduce our known and evolving vulnerabilities to this natural hazard.

Space weather monitoring and forecasting in South America: products from the user requests to the development of regional magnetic indices and GNSS vertical error maps

NASA Astrophysics Data System (ADS)

Denardini, Clezio Marcos; Padilha, Antonio; Takahashi, Hisao; Souza, Jonas; Mendes, Odim; Batista, Inez S.; SantAnna, Nilson; Gatto, Rubens; Costa, D. Joaquim

On August 2007 the National Institute for Space Research started a task force to develop and operate a space weather program, which is kwon by the acronyms Embrace that stands for the Portuguese statement “Estudo e Monitoramento BRAasileiro de Clima Espacial” Program (Brazilian Space Weather Study and Monitoring program). The main purpose of the Embrace Program is to monitor the space climate and weather from sun, interplanetary space, magnetosphere and ionosphere-atmosphere, and to provide useful information to space related communities, technological, industrial and academic areas. Since then we have being visiting several different space weather costumers and we have host two workshops of Brazilian space weather users at the Embrace facilities. From the inputs and requests collected from the users the Embrace Program decided to monitored several physical parameters of the sun-earth environment through a large ground base network of scientific sensors and under collaboration with space weather centers partners. Most of these physical parameters are daily published on the Brazilian space weather program web portal, related to the entire network sensors available. A comprehensive data bank and an interface layer are under development to allow an easy and direct access to the useful information. Nowadays, the users will count on products derived from a GNSS monitor network that covers most of the South American territory; a digisonde network that monitors the ionospheric profiles in two equatorial sites and in one low latitude site; several solar radio telescopes to monitor solar activity, and a magnetometer network, besides a global ionospheric physical model. Regarding outreach, we publish a daily bulletin in Portuguese with the status of the space weather environment on the Sun, in the Interplanetary Medium and close to the Earth. Since December 2011, all these activities are carried out at the Embrace Headquarter, a building located at the INPE's main campus. Recently, we have release brand new products, among them, some regional magnetic indices and the GNSS vertical error map over South America. Contacting Author: C. M. Denardini (clezio.denardin@inpe.br)

2004 New Mexico traffic crash information

DOT National Transportation Integrated Search

2006-01-01

Severe weather conditions, i.e. snowfall, floods, ice storms, etc. can have major effects on traffic volumes along the highway network. Unlike passenger vehicles, which may choose not to travel during inclement weather, freight trucks need to adhere ...

All-weather-landing operations bibliography

DOT National Transportation Integrated Search

1972-06-01

The bibliography provides a selected coverage of several topic areas within the general subject : of all-weather landing. The period covers the recent years of 1966 through 1971. The areas are : as follows: Approach and Landing, Human-Factors, Naviga...

Measurement of fog and haze extinction characteristics and availability evaluation of free space optical link under the sea surface environment.

PubMed

Wu, Xiaojun; Wang, Hongxing; Song, Bo

2015-02-10

Fog and haze can lead to changes in extinction characteristics. Therefore, the performance of the free space optical link is highly influenced by severe weather conditions. Considering the influential behavior of weather conditions, a state-of-the-art solution for the observation of fog and haze over the sea surface is presented in this paper. A Mie scattering laser radar, with a wavelength of 532 nm, is used to observe the weather conditions of the sea surface environment. The horizontal extinction coefficients and visibilities are obtained from the observation data, and the results are presented in the paper. The changes in the characteristics of extinction coefficients and visibilities are analyzed based on both the short-term (6 days) severe weather data and long-term (6 months) data. Finally, the availability performance of the free space optical communication link is evaluated under the sea surface environment.

A statistical model to estimate the local vulnerability to severe weather

NASA Astrophysics Data System (ADS)

Pardowitz, Tobias

2018-06-01

We present a spatial analysis of weather-related fire brigade operations in Berlin. By comparing operation occurrences to insured losses for a set of severe weather events we demonstrate the representativeness and usefulness of such data in the analysis of weather impacts on local scales. We investigate factors influencing the local rate of operation occurrence. While depending on multiple factors - which are often not available - we focus on publicly available quantities. These include topographic features, land use information based on satellite data and information on urban structure based on data from the OpenStreetMap project. After identifying suitable predictors such as housing coverage or local density of the road network we set up a statistical model to be able to predict the average occurrence frequency of local fire brigade operations. Such model can be used to determine potential hotspots for weather impacts even in areas or cities where no systematic records are available and can thus serve as a basis for a broad range of tools or applications in emergency management and planning.

The state of broadcast meteorology in the United States

NASA Astrophysics Data System (ADS)

Trobec, J.

2010-09-01

According to a 2010 study by the Radio, Television Digital News Association, there are 762 television stations in the U.S. producing local news (and presumably weather) content. Those stations reported staff reductions of 400 news department jobs in 2009, following a cut of 1,200 local news jobs in 2008. Even as the number of news employees declined, local stations increased the amount of local news programming from an average of 4.7 hours to 5.0 hours per weekday in the past year. The phrase "doing more with less" has become a common theme in television newsrooms. Broadcasting economics have also impacted the approximately 2,200 weather presenters on local television stations. Several high-profile, on-air meteorologists have lost their jobs. The workload of weather presenters is evolving as television stations extend their reach beyond broadcasting — to the internet, and wireless (e.g. cellular telephone) delivery of information. Technological advancements have improved televised severe weather coverage. The number of amateur storm chasers possessing video streaming equipment has grown signicantly, and social networks such as Twitter have become a useful source of weather reports from the public.

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

User perception and interpretation of tornado probabilistic hazard information: Comparison of four graphical designs.

PubMed

Miran, Seyed M; Ling, Chen; James, Joseph J; Gerard, Alan; Rothfusz, Lans

2017-11-01

Effective design for presenting severe weather information is important to reduce devastating consequences of severe weather. The Probabilistic Hazard Information (PHI) system for severe weather is being developed by NOAA National Severe Storms Laboratory (NSSL) to communicate probabilistic hazardous weather information. This study investigates the effects of four PHI graphical designs for tornado threat, namely, "four-color"," red-scale", "grayscale" and "contour", on users' perception, interpretation, and reaction to threat information. PHI is presented on either a map background or a radar background. Analysis showed that the accuracy was significantly higher and response time faster when PHI was displayed on map background as compared to radar background due to better contrast. When displayed on a radar background, "grayscale" design resulted in a higher accuracy of responses. Possibly due to familiarity, participants reported four-color design as their favorite design, which also resulted in the fastest recognition of probability levels on both backgrounds. Our study shows the importance of using intuitive color-coding and sufficient contrast in conveying probabilistic threat information via graphical design. We also found that users follows a rational perceiving-judging-feeling-and acting approach in processing probabilistic hazard information for tornado. Copyright © 2017 Elsevier Ltd. All rights reserved.

Weather conditions conducive to Beijing severe haze more frequent under climate change

NASA Astrophysics Data System (ADS)

Cai, Wenju; Li, Ke; Liao, Hong; Wang, Huijun; Wu, Lixin

2017-03-01

The frequency of Beijing winter severe haze episodes has increased substantially over the past decades, and is commonly attributed to increased pollutant emissions from China’s rapid economic development. During such episodes, levels of fine particulate matter are harmful to human health and the environment, and cause massive disruption to economic activities, as occurred in January 2013. Conducive weather conditions are an important ingredient of severe haze episodes, and include reduced surface winter northerlies, weakened northwesterlies in the midtroposphere, and enhanced thermal stability of the lower atmosphere. How such weather conditions may respond to climate change is not clear. Here we project a 50% increase in the frequency and an 80% increase in the persistence of conducive weather conditions similar to those in January 2013, in response to climate change. The frequency and persistence between the historical (1950-1999) and future (2050-2099) climate were compared in 15 models under Representative Concentration Pathway 8.5 (RCP8.5). The increased frequency is consistent with large-scale circulation changes, including an Arctic Oscillation upward trend, weakening East Asian winter monsoon, and faster warming in the lower troposphere. Thus, circulation changes induced by global greenhouse gas emissions can contribute to the increased Beijing severe haze frequency.

AN overview of the FLYSAFE datalink solution for the exchange of weather information: supporting aircrew decision making processes.

NASA Astrophysics Data System (ADS)

Mirza, A.; Drouin, A.

2009-09-01

FLYSAFE is an Integrated Project of the 6th framework of the European Commission with the aim to improve flight safety through the development of an avionics solution the Next Generation Integrated Surveillance System (NGISS), which is supported by a ground based network of Weather Information Management Systems (WIMS) and access points in the form of the Ground Weather Processor (GWP). The NGISS provides information to the flight crew on the three major external hazards for aviation: weather, air traffic and terrain. The NGISS has the capability of displaying data about all three hazards on a single display screen, facilitating rapid appreciation of the situation by the flight crew. Weather Information Management Systems (WIMS) were developed to provide the NGISS and the flight crew with weather related information on in-flight icing, thunderstorms and clear-air turbulence. These products are generated on the ground from observations and model forecasts. WIMS will supply relevant information on three different scales: global, regional and local (over airport Terminal Manoeuvring Area). The Ground Weather Processor is a client-server architecture that utilises open source components, which include a geospatial database and web feature services. The GWP stores Weather Objects generated by the WIMS. An aviation user can retrieve on-demand all Weather Objects that intersect the volume of space that is of interest to them. The Weather Objects are fused with in-situ observation data and can be used by the flight management system to propose a route to avoid the hazard. In addition they can be used to display the current hazardous weather to the Flight Crew thereby raising their awareness. Within the FLYSAFE program, around 120 hours of flight trials were performed during February 2008 and August 2008. Two aircraft were involved each with separate objectives: - to assess FLYSAFE's innovative solutions for the data-link, on-board data-fusion and data-display and data-updates during flight; - to evaluate the new weather information management systems (in-flight icing and thunderstorms) using in-situ measurements recorded on-board the test aircraft. In this presentation we will focus on the data link solution to uplink the Weather Objects to the NGISS. As part of the solution, a brief description is given on how grid data created by the WIMS are transformed to Weather Objects; which describe the weather hazard and are formatted using the Geospatial Mark-up Language.

Generation of Fine Scale Wind and Wave Climatologies

NASA Astrophysics Data System (ADS)

Vandenberghe, F. C.; Filipot, J.; Mouche, A.

2013-12-01

A tool to generate 'on demand' large databases of atmospheric parameters at high resolution has been developed for defense applications. The approach takes advantage of the zooming and relocation capabilities of the embedded domains that can be found in regional models like the community Weather Research and Forecast model (WRF). The WRF model is applied to dynamically downscale NNRP, CFSR and ERA40 global analyses and to generate long records, up to 30 years, of hourly gridded data over 200km2 domains at 3km grid increment. To insure accuracy, observational data from the NCAR ADP historical database are used in combination with the Four-Dimensional Data Assimilation (FDDA) techniques to constantly nudge the model analysis toward observations. The atmospheric model is coupled to secondary applications such as the NOAA's Wave Watch III model the Navy's APM Electromagnetic Propagation model, allowing the creation of high-resolution climatologies of surface winds, waves and electromagnetic propagation parameters. The system was applied at several coastal locations of the Mediterranean Sea where SAR wind and wave observations were available during the entire year of 2008. Statistical comparisons between the model output and SAR observations are presented. Issues related to the global input data, and the model drift, as well as the impact of the wind biases on wave simulations will be discussed.

Initial Results from the Variable Intensity Sonic Boom Propagation Database

NASA Technical Reports Server (NTRS)

Haering, Edward A., Jr.; Cliatt, Larry J., II; Bunce, Thomas J.; Gabrielson, Thomas B.; Sparrow, Victor W.; Locey, Lance L.

2008-01-01

An extensive sonic boom propagation database with low- to normal-intensity booms (overpressures of 0.08 lbf/sq ft to 2.20 lbf/sq ft) was collected for propagation code validation, and initial results and flight research techniques are presented. Several arrays of microphones were used, including a 10 m tall tower to measure shock wave directionality and the effect of height above ground on acoustic level. A sailplane was employed to measure sonic booms above and within the atmospheric turbulent boundary layer, and the sailplane was positioned to intercept the shock waves between the supersonic airplane and the ground sensors. Sailplane and ground-level sonic boom recordings were used to generate atmospheric turbulence filter functions showing excellent agreement with ground measurements. The sonic boom prediction software PCBoom4 was employed as a preflight planning tool using preflight weather data. The measured data of shock wave directionality, arrival time, and overpressure gave excellent agreement with the PCBoom4-calculated results using the measured aircraft and atmospheric data as inputs. C-weighted acoustic levels generally decreased with increasing height above the ground. A-weighted and perceived levels usually were at a minimum for a height where the elevated microphone pressure rise time history was the straightest, which is a result of incident and ground-reflected shock waves interacting.

The effect of inclement weather on ankle fracture management in an Irish trauma unit.

PubMed

O'Neill, B J; Kelly, E G; Breathnach, O C; Keogh, P; Kenny, P J; O'Flanagan, S J

2013-09-01

Ireland is unfamiliar with extreme weather conditions. Such conditions occurred in winter 2009-2010 and 2010-2011, with much of the country being affected by snow and ice. We reviewed the effect that these conditions had on the treatment of ankle fractures in our trauma unit. The study period was from November until February for four consecutive years from 2008-2009 until 2011-2012. We compared two winters with extreme weather with two winters with regular weather conditions. Information from Met Eireann was compared with demographics from patient records to differentiate ice-related injuries from non-ice-related injuries. Ankle fractures were classified using the Lauge-Hansen classification. We compared waiting times in A&E, waiting times for theatre, delays relating to injury severity, and overall length of stay for both groups. We identified 44 ice-related injuries and 67 non-ice-related injuries. Ice-related injuries trended towards more severe fracture configurations using the Lauge-Hansen classification. Patients sustaining ankle injuries during inclement weather were significantly younger than patients sustaining injuries during regular weather conditions. There were no other significant differences between the two groups. Ice-related injuries trended towards a greater severity of fracture configuration. We identified no significant increase in the time to treatment or overall length of stay of patients sustaining ankle fractures during these times. Ice-related injuries did not have greater rates of complications. These results are a testament to the trauma staff in this unit who absorbed the increased workload without compromising patient care.

GOES-S Mission Science Briefing

NASA Image and Video Library

2018-02-27

In the Kennedy Space Center's Press Site auditorium, Kristin Calhoun, a research scientist with NOAA's National Severe Storms Laboratory, speaks to members of the media at a mission briefing on National Oceanic and Atmospheric Administration's, or NOAA's, Geostationary Operational Environmental Satellite, or GOES-S. The spacecraft is the second satellite in a series of next-generation NOAA weather satellites. It will launch to a geostationary position over the U.S. to provide images of storms and help predict weather forecasts, severe weather outlooks, watches, warnings, lightning conditions and longer-term forecasting. GOES-S is slated to lift off at 5:02 p.m. EST on March 1, 2018 aboard a United Launch Alliance Atlas V rocket.

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.

Is It Going to Rain Today? Understanding the Weather Forecast.

ERIC Educational Resources Information Center

Allsopp, Jim; And Others

1996-01-01

Presents a resource for science teachers to develop a better understanding of weather forecasts, including outlooks, watches, warnings, advisories, severe local storms, winter storms, floods, hurricanes, nonprecipitation hazards, precipitation probabilities, sky condition, and UV index. (MKR)

Classification and machine recognition of severe weather patterns

NASA Technical Reports Server (NTRS)

Wang, P. P.; Burns, R. C.

1976-01-01

Forecasting and warning of severe weather conditions are treated from the vantage point of pattern recognition by machine. Pictorial patterns and waveform patterns are distinguished. Time series data on sferics are dealt with by considering waveform patterns. A severe storm patterns recognition machine is described, along with schemes for detection via cross-correlation of time series (same channel or different channels). Syntactic and decision-theoretic approaches to feature extraction are discussed. Active and decayed tornados and thunderstorms, lightning discharges, and funnels and their related time series data are studied.

The North Alabama Severe Thunderstorm Observations, Research, and Monitoring Network (STORMnet)

NASA Technical Reports Server (NTRS)

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

Weather forecasting expert system study

NASA Technical Reports Server (NTRS)

1985-01-01

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

Browsing Space Weather Data and Models with the Integrated Space Weather Analysis (iSWA) System

NASA Technical Reports Server (NTRS)

Maddox, Marlo M.; Mullinix, Richard E.; Berrios, David H.; Hesse, Michael; Rastaetter, Lutz; Pulkkinen, Antti; Hourcle, Joseph A.; Thompson, Barbara J.

2011-01-01

The Integrated Space Weather Analysis (iSWA) System is a comprehensive web-based platform for space weather information that combines data from solar, heliospheric and geospace observatories with forecasts based on the most advanced space weather models. The iSWA system collects, generates, and presents a wide array of space weather resources in an intuitive, user-configurable, and adaptable format - thus enabling users to respond to current and future space weather impacts as well as enabling post-impact analysis. iSWA currently provides over 200 data and modeling products, and features a variety of tools that allow the user to browse, combine, and examine data and models from various sources. This presentation will consist of a summary of the iSWA products and an overview of the customizable user interfaces, and will feature several tutorial demonstrations highlighting the interactive tools and advanced capabilities.

Public health vulnerability to wintertime weather: time-series regression and episode analyses of national mortality and morbidity databases to inform the Cold Weather Plan for England.

PubMed

Hajat, S; Chalabi, Z; Wilkinson, P; Erens, B; Jones, L; Mays, N

2016-08-01

To inform development of Public Health England's Cold Weather Plan (CWP) by characterizing pre-existing relationships between wintertime weather and mortality and morbidity outcomes, and identification of groups most at risk. Time-series regression analysis and episode analysis of daily mortality, emergency hospital admissions, and accident and emergency visits for each region of England. Seasonally-adjusted Poisson regression models estimating the percent change in daily health events per 1 °C fall in temperature or during individual episodes of extreme weather. Adverse cold effects were observed in all regions, with the North East, North West and London having the greatest risk of cold-related mortality. Nationally, there was a 3.44% (95% CI: 3.01, 3.87) increase in all-cause deaths and 0.78% (95% CI: 0.53, 1.04) increase in all-cause emergency admissions for every 1 °C drop in temperature below identified thresholds. The very elderly and people with COPD were most at risk from low temperatures. A&E visits for fractures were elevated during heavy snowfall periods, with adults (16-64 years) being the most sensitive age-group. Since even moderately cold days are associated with adverse health effects, by far the greatest health burdens of cold weather fell outside of the alert periods currently used in the CWP. Our findings indicate that levels 0 ('year round planning') and 1 ('winter preparedness and action') are crucial components of the CWP in comparison to the alerts. Those most vulnerable during winter may vary depending on the type of weather conditions being experienced. Recommendations are made for the CWP. Copyright © 2016 The Royal Society for Public Health. Published by Elsevier Ltd. All rights reserved.

An introduction to Space Weather Integrated Modeling

NASA Astrophysics Data System (ADS)

Zhong, D.; Feng, X.

2012-12-01

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

Roles of weathered bedrock and soil in seasonal water relations of Pinus Jeffreyi and Arctostaphylos patula

Treesearch

K.R. Hubbert; J.L. Beyers; R.C. Graham

2001-01-01

In the southern Sierra Nevada, California, relatively thin soils overlie granitic bedrock that is weathered to depths of several metres. The weathered granitic bedrock is porous and has a plant-available water capacity of 0.124 m3•m–3, compared with 0.196 m3•m–3 for the...

Weather Information Processing

NASA Technical Reports Server (NTRS)

1991-01-01

Science Communications International (SCI), formerly General Science Corporation, has developed several commercial products based upon experience acquired as a NASA Contractor. Among them are METPRO, a meteorological data acquisition and processing system, which has been widely used, RISKPRO, an environmental assessment system, and MAPPRO, a geographic information system. METPRO software is used to collect weather data from satellites, ground-based observation systems and radio weather broadcasts to generate weather maps, enabling potential disaster areas to receive advance warning. GSC's initial work for NASA Goddard Space Flight Center resulted in METPAK, a weather satellite data analysis system. METPAK led to the commercial METPRO system. The company also provides data to other government agencies, U.S. embassies and foreign countries.

A Photo Storm Report Mobile Application, Processing/Distribution System, and AWIPS-II Display Concept

NASA Astrophysics Data System (ADS)

Longmore, S. P.; Bikos, D.; Szoke, E.; Miller, S. D.; Brummer, R.; Lindsey, D. T.; Hillger, D.

2014-12-01

The increasing use of mobile phones equipped with digital cameras and the ability to post images and information to the Internet in real-time has significantly improved the ability to report events almost instantaneously. In the context of severe weather reports, a representative digital image conveys significantly more information than a simple text or phone relayed report to a weather forecaster issuing severe weather warnings. It also allows the forecaster to reasonably discern the validity and quality of a storm report. Posting geo-located, time stamped storm report photographs utilizing a mobile phone application to NWS social media weather forecast office pages has generated recent positive feedback from forecasters. Building upon this feedback, this discussion advances the concept, development, and implementation of a formalized Photo Storm Report (PSR) mobile application, processing and distribution system and Advanced Weather Interactive Processing System II (AWIPS-II) plug-in display software.The PSR system would be composed of three core components: i) a mobile phone application, ii) a processing and distribution software and hardware system, and iii) AWIPS-II data, exchange and visualization plug-in software. i) The mobile phone application would allow web-registered users to send geo-location, view direction, and time stamped PSRs along with severe weather type and comments to the processing and distribution servers. ii) The servers would receive PSRs, convert images and information to NWS network bandwidth manageable sizes in an AWIPS-II data format, distribute them on the NWS data communications network, and archive the original PSRs for possible future research datasets. iii) The AWIPS-II data and exchange plug-ins would archive PSRs, and the visualization plug-in would display PSR locations, times and directions by hour, similar to surface observations. Hovering on individual PSRs would reveal photo thumbnails and clicking on them would display the full resolution photograph.Here, we present initial NWS forecaster feedback received from social media posted PSRs, motivating the possible advantages of PSRs within AWIPS-II, the details of developing and implementing a PSR system, and possible future applications beyond severe weather reports and AWIPS-II.

KSC-06pd1278

NASA Image and Video Library

2006-06-28

KENNEDY SPACE CENTER, FLA. - At the Cape Canaveral weather station in Florida, workers release an upper-level weather balloon while several newscasters watch. The release of the balloon was part of a media tour prior to the launch of Space Shuttle Discovery on mission STS-121 July 1. The radar-tracked balloon detects wind shears that can affect a shuttle launch. At the facility, which is operated by the U.S. Air Force 45th Weather Squadron, media saw the tools used by the weather team to create the forecast for launch day. They received a briefing on how the launch weather forecast is developed by Shuttle Weather Officer Kathy Winters and met the forecasters for the space shuttle and the expendable launch vehicles. Also participating were members of the Applied Meteorology Unit who provide special expertise to the forecasters by analyzing and interpreting unusual or inconsistent weather data. The media were able to see the release of the Rawinsonde weather balloon carrying instruments aloft to be used as part of developing the forecast. Photo credit: NASA/George Shelton

Tools in Support of Planning for Weather and Climate Extremes

NASA Astrophysics Data System (ADS)

Done, J.; Bruyere, C. L.; Hauser, R.; Holland, G. J.; Tye, M. R.

2016-12-01

A major limitation to planning for weather and climate extremes is the lack of maintained and readily available tools that can provide robust and well-communicated predictions and advice on their impacts. The National Center for Atmospheric Research is facilitating a collaborative international program to develop and support such tools within its Capacity Center for Climate and Weather Extremes aimed at improving community resilience planning and reducing weather and climate impacts. A Global Risk, Resilience and Impacts Toolbox is in development and will provide: A portable web-based interface to process work requests from a variety of users and locations; A sophisticated framework that enables specialized community tools to access a comprehensive database (public and private) of geo-located hazard, vulnerability, exposure, and loss data; A community development toolkit that enables and encourages community tool developments geared towards specific user man­agement and planning needs, and A comprehensive community sup­port facilitated by NCAR utilizing tutorials and a help desk. A number of applications are in development, built off the latest climate science, and in collaboration with private industry and local and state governments. Example applications will be described, including a hurricane damage tool in collaboration with the reinsurance sector, and a weather management tool for the construction industry. These examples will serve as starting points to discuss the broader potential of the toolbox.

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.

Preliminary Development and Evaluation of Lightning Jump Algorithms for the Real-Time Detection of Severe Weather

NASA Technical Reports Server (NTRS)

Schultz, Christopher J.; Petersen, Walter A.; Carey, Lawrence D.

2009-01-01

Previous studies have demonstrated that rapid increases in total lightning activity (intracloud + cloud-to-ground) are often observed tens of minutes in advance of the occurrence of severe weather at the ground. These rapid increases in lightning activity have been termed "lightning jumps." Herein, we document a positive correlation between lightning jumps and the manifestation of severe weather in thunderstorms occurring across the Tennessee Valley and Washington D.C. A total of 107 thunderstorms were examined in this study, with 69 of the 107 thunderstorms falling into the category of non-severe, and 38 into the category of severe. From the dataset of 69 isolated non-severe thunderstorms, an average peak 1 minute flash rate of 10 flashes/min was determined. A variety of severe thunderstorm types were examined for this study including an MCS, MCV, tornadic outer rainbands of tropical remnants, supercells, and pulse severe thunderstorms. Of the 107 thunderstorms, 85 thunderstorms (47 non-severe, 38 severe) from the Tennessee Valley and Washington D.C tested 6 lightning jump algorithm configurations (Gatlin, Gatlin 45, 2(sigma), 3(sigma), Threshold 10, and Threshold 8). Performance metrics for each algorithm were then calculated, yielding encouraging results from the limited sample of 85 thunderstorms. The 2(sigma) lightning jump algorithm had a high probability of detection (POD; 87%), a modest false alarm rate (FAR; 33%), and a solid Heidke Skill Score (HSS; 0.75). A second and more simplistic lightning jump algorithm named the Threshold 8 lightning jump algorithm also shows promise, with a POD of 81% and a FAR of 41%. Average lead times to severe weather occurrence for these two algorithms were 23 minutes and 20 minutes, respectively. The overall goal of this study is to advance the development of an operationally-applicable jump algorithm that can be used with either total lightning observations made from the ground, or in the near future from space using the GOES-R Geostationary Lightning Mapper.

Severe fire weather and intensive forest management increase fire severity in a multi-ownership landscape.

PubMed

Zald, Harold S J; Dunn, Christopher J

2018-04-26

Many studies have examined how fuels, topography, climate, and fire weather influence fire severity. Less is known about how different forest management practices influence fire severity in multi-owner landscapes, despite costly and controversial suppression of wildfires that do not acknowledge ownership boundaries. In 2013, the Douglas Complex burned over 19,000 ha of Oregon & California Railroad (O&C) lands in Southwestern Oregon, USA. O&C lands are composed of a checkerboard of private industrial and federal forestland (Bureau of Land Management, BLM) with contrasting management objectives, providing a unique experimental landscape to understand how different management practices influence wildfire severity. Leveraging Landsat based estimates of fire severity (Relative differenced Normalized Burn Ratio, RdNBR) and geospatial data on fire progression, weather, topography, pre-fire forest conditions, and land ownership, we asked (1) what is the relative importance of different variables driving fire severity, and (2) is intensive plantation forestry associated with higher fire severity? Using Random Forest ensemble machine learning, we found daily fire weather was the most important predictor of fire severity, followed by stand age and ownership, followed by topographic features. Estimates of pre-fire forest biomass were not an important predictor of fire severity. Adjusting for all other predictor variables in a general least squares model incorporating spatial autocorrelation, mean predicted RdNBR was higher on private industrial forests (RdNBR 521.85 ± 18.67 [mean ± SE]) vs. BLM forests (398.87 ± 18.23) with a much greater proportion of older forests. Our findings suggest intensive plantation forestry characterized by young forests and spatially homogenized fuels, rather than pre-fire biomass, were significant drivers of wildfire severity. This has implications for perceptions of wildfire risk, shared fire management responsibilities, and developing fire resilience for multiple objectives in multi-owner landscapes. © 2018 by the Ecological Society of America.

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.

75 FR 3333 - Irish Potatoes Grown in Colorado; Modification of the Handling Regulation for Area No. 2

Federal Register 2010, 2011, 2012, 2013, 2014

2010-01-21

... 2008-2009 season, when adverse weather conditions damaged the crop and resulted in the Committee... been the industry standard in place prior to the 2008-2009 season. Because severe and adverse weather...

Implementation and evaluation of the Sacramento Regional Transportation Management Center Weather Alert Notification System.

DOT National Transportation Integrated Search

2010-08-01

This report presents the results of an evaluation of Caltrans District 3 Regional Transportation Management Centers (RTMC) implementation of a weather alert notification system. This alert system was selected for implementation from among several ...

Microscopic analysis of traffic flow in inclement weather.

DOT National Transportation Integrated Search

2009-11-01

Weather causes a variety of impacts on the transportation system. An Oak Ridge National Laboratory study estimated the delay experienced by American drivers due to snow, ice, and fog in 1999 at 46 million hours. While severe winter storms, hurricanes...

AWE: Aviation Weather Data Visualization Environment

NASA Technical Reports Server (NTRS)

Spirkovska, Lilly; Lodha, Suresh K.; Norvig, Peter (Technical Monitor)

2000-01-01

Weather is one of the major causes of aviation accidents. General aviation (GA) flights account for 92% of all the aviation accidents, In spite of all the official and unofficial sources of weather visualization tools available to pilots, there is an urgent need for visualizing several weather related data tailored for general aviation pilots. Our system, Aviation Weather Data Visualization Environment AWE), presents graphical displays of meteorological observations, terminal area forecasts, and winds aloft forecasts onto a cartographic grid specific to the pilot's area of interest. Decisions regarding the graphical display and design are made based on careful consideration of user needs. Integral visual display of these elements of weather reports is designed for the use of GA pilots as a weather briefing and route selection tool. AWE provides linking of the weather information to the flight's path and schedule. The pilot can interact with the system to obtain aviation-specific weather for the entire area or for his specific route to explore what-if scenarios and make "go/no-go" decisions. The system, as evaluated by some pilots at NASA Ames Research Center, was found to be useful.

Enhancing understanding and improving prediction of severe weather through spatiotemporal relational learning.

PubMed

McGovern, Amy; Gagne, David J; Williams, John K; Brown, Rodger A; Basara, Jeffrey B

Severe weather, including tornadoes, thunderstorms, wind, and hail annually cause significant loss of life and property. We are developing spatiotemporal machine learning techniques that will enable meteorologists to improve the prediction of these events by improving their understanding of the fundamental causes of the phenomena and by building skillful empirical predictive models. In this paper, we present significant enhancements of our Spatiotemporal Relational Probability Trees that enable autonomous discovery of spatiotemporal relationships as well as learning with arbitrary shapes. We focus our evaluation on two real-world case studies using our technique: predicting tornadoes in Oklahoma and predicting aircraft turbulence in the United States. We also discuss how to evaluate success for a machine learning algorithm in the severe weather domain, which will enable new methods such as ours to transfer from research to operations, provide a set of lessons learned for embedded machine learning applications, and discuss how to field our technique.

Development of the Centralized Storm Information System (CSIS) for use in severe weather prediction

NASA Technical Reports Server (NTRS)

Mosher, F. R.

1984-01-01

The centralized storm information system is now capable of ingesting and remapping radar scope presentations on a satellite projection. This can be color enhanced and superposed on other data types. Presentations from more than one radar can be composited on a single image. As with most other data sources, a simple macro establishes the loops and scheduling of the radar ingestions as well as the autodialing. There are approximately 60 NWS network 10 cm radars that can be interrogated. NSSFC forecasters have found this data source to be extremely helpful in severe weather situations. The capability to access lightning frequency data stored in a National Weather Service computer was added. Plans call for an interface with the National Meteorological Center to receive and display prognostic fields from operational computer forecast models. Programs are to be developed to plot and display locations of reported severe local storm events.

Making Connections to Students' Lives and Careers Throughout a General Education Science Course

NASA Astrophysics Data System (ADS)

LaDue, D. S.

2014-12-01

The University of Oklahoma's general education lecture course Severe & Unusual Weather, taught in two sections each fall and spring, covers about nine topics. The sections are taught by different instructors, each of whom has flexibility to employ a variety of instructional strategies and choose specific topics to cover while meeting the requirement that general education courses in the natural sciences help students understand the importance of the science for appreciating the world around them. Students enrolled have been approximately 6-10% returning adult students, some of whom were veterans or active duty military, and about 10% members of racial or ethnic groups. Their majors are mostly in the humanities (theater, photography) and social sciences (education, English, journalism, sociology), with some natural science majors (psychology, aviation). For the past two years, Section 001 has been designed with adult and active learning concepts in mind, using deliberate connections between course content and students' lives and careers to motivate meaningful learning. Students were grouped in teams according to similar majors and assigned group presentations connecting course content to topics that should interest them, such as economic impacts of weather, societal and personal impacts of severe weather, risks to aviation, media coverage of weather, and psychological and sociological responses to weather risks. Students learn about the peer review process for scientific papers while also exploring a connection of course content to their future career or life interests through papers that are run through a mock peer review process. Public policy is discussed in several sections of the course, such as hurricane building codes, wind-resistant construction in tornado alley, and the disproportionate impacts of weather and climate on certain socioeconomic groups. Most students deeply appreciate the opportunity to explore how course content intersects with their lives. Several examples of these connections will be described.

Observational Simulation of Icing in Extreme Weather Conditions

NASA Astrophysics Data System (ADS)

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

2017-04-01

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

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.

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.;

Effective Utilization of Satellite Observations for Assessing Transnational Impact of Disasters

NASA Astrophysics Data System (ADS)

Alozie, J. E.; Anuforom, A. C.

2014-12-01

General meteorological observations sources for the surface, upper air and outer space are conducted using different technological equipment and instruments that meet international standards prescribed and approved by the United Nations organizations such as the International Civil Aviation Organization (ICAO) and the World Meteorological Organization (WMO). Satellite weather observations are critical for effective monitoring of the developments, propagations and disseminations of cold clouds and their expected adverse weather conditions as they move across national and transnational boundaries. The Nigerian Meteorological Agency (NiMet) which is the national weather service provider for Nigeria, utilizes an array of satellite products obtained from mainly the European Meteorological Satellite (EUMETSAT) for its routine weather and climate monitoring and forecasts. Overtime, NiMet has used weather workstations such as MSG, SYNERGIE and now PUMA for accessing satellite products such as RGB, Infra-red, Water vapour and the Multi-sensor Precipitation Estimate (MPE) obtained at near real-time periods. The satellite imageries find extensive applications in the delivery of early warning of raising of severe weather conditions such as dust storm and dust haze during the harmattan season (November - February); and thunderstorm accompanied by severe lightning and destructive strong winds. The paper will showcase some special cases of the tracking of squall lines and issuance of weather alerts through the media. The good result is that there was limited damage to infrastructure and no loss of life from the flash floods caused by the heavy rainfall from the squally thunderstorm.

Use of EOS Data in AWIPS for Weather Forecasting

NASA Technical Reports Server (NTRS)

Jedlovec, Gary J.; Haines, Stephanie L.; Suggs, Ron J.; Bradshaw, Tom; Darden, Chris; Burks, Jason

2003-01-01

Operational weather forecasting relies heavily on real time data and modeling products for forecast preparation and dissemination of significant weather information to the public. The synthesis of this information (observations and model products) by the meteorologist is facilitated by a decision support system to display and integrate the information in a useful fashion. For the NWS this system is called Advanced Weather Interactive Processing System (AWIPS). Over the last few years NASA has launched a series of new Earth Observation Satellites (EOS) for climate monitoring that include several instruments that provide high-resolution measurements of atmospheric and surface features important for weather forecasting and analysis. The key to the utilization of these unique new measurements by the NWS is the real time integration of the EOS data into the AWIPS system. This is currently being done in the Huntsville and Birmingham NWS Forecast Offices under the NASA Short-term Prediction Research and Transition (SPORT) Program. This paper describes the use of near real time MODIS and AIRS data in AWIPS to improve the detection of clouds, moisture variations, atmospheric stability, and thermal signatures that can lead to significant weather development. The paper and the conference presentation will focus on several examples where MODIS and AIRS data have made a positive impact on forecast accuracy. The results of an assessment of the utility of these products for weather forecast improvement made at the Huntsville NWS Forecast Office will be presented.

National Weather Service Warning Performance Based on the WSR-88D.

NASA Astrophysics Data System (ADS)

Polger, Paul D.; Goldsmith, Barry S.; Przywarty, Richard C.; Bocchieri, Joseph R.

1994-02-01

The National Weather Service (NWS) began operational use of the Weather Surveillance Radar-1988 Doppler (WSR-88D) system in March 1991 at Norman, Oklahoma. WSR-88D data have been available to forecasters at five additional offices: Melbourne, Florida, and sterling, Virginia (since January 1992); St. Louis, Missouri, and Dodge City, Kansas (since March 1992); and Houston, Texas (since April 1992). The performance of the severe local storm and flash flood warning programs at the six offices before and after the availability of the WSR-88D was measured quantitatively. The verification procedures and statistical measures used in the quantitative evaluation were those used operationally by the NWS.The statistics show that the warnings improved dramatically when the WSR-88D was in operation. Specifically, the probability of detection of severe weather events increased and the number of false alarms decreased. There was also a marked improvement in the lead time for all severe local storm and flash flood events. These improvements were evident throughout the effective range of the radar. Stratification of severe local storm data by severe thunderstorms versus tornadoes revealed an improvement in the NWS's ability to differentiate between tornadic and nontornadic storms when the WSR-88D was in operation. Four individual cases are examined to illustrate how forecasters used the WSR-88D to achieve the improved results. These cases focus on the unique features of the WSR-88D that provide an advantage over conventional NWS radars.

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.

Weather it's Climate Change?

NASA Astrophysics Data System (ADS)

Bostrom, A.; Lashof, D.

2004-12-01

For almost two decades both national polls and in-depth studies of global warming perceptions have shown that people commonly conflate weather and global climate change. Not only are current weather events such as anecdotal heat waves, droughts or cold spells treated as evidence for or against global warming, but weather changes such as warmer weather and increased storm intensity and frequency are the consequences most likely to come to mind. Distinguishing weather from climate remains a challenge for many. This weather 'framing' of global warming may inhibit behavioral and policy change in several ways. Weather is understood as natural, on an immense scale that makes controlling it difficult to conceive. Further, these attributes contribute to perceptions that global warming, like weather, is uncontrollable. This talk presents an analysis of data from public opinion polls, focus groups, and cognitive studies regarding people's mental models of and 'frames' for global warming and climate change, and the role weather plays in these. This research suggests that priming people with a model of global warming as being caused by a "thickening blanket of carbon dioxide" that "traps heat" in the atmosphere solves some of these communications problems and makes it more likely that people will support policies to address global warming.

Thresholds for soil cover and weathering in mountainous landscapes

NASA Astrophysics Data System (ADS)

Dixon, Jean; Benjaram, Sarah

2017-04-01

The patterns of soil formation, weathering, and erosion shape terrestrial landscapes, forming the foundation on which ecosystems and human civilizations are built. Several fundamental questions remain regarding how soils evolve, especially in mountainous landscapes where tectonics and climate exert complex forcings on erosion and weathering. In these systems, quantifying weathering is made difficult by the fact that soil cover is discontinuous and heterogeneous. Therefore, studies that attempt to measure soil weathering in such systems face a difficult bias in measurements towards more weathered portions of the landscape. Here, we explore current understanding of erosion-weathering feedbacks, and present new data from mountain systems in Western Montana. Using field mapping, analysis of LiDAR and remotely sensed land-cover data, and soil chemical analyses, we measure soil cover and surface weathering intensity across multiple spatial scales, from the individual soil profile to a landscape perspective. Our data suggest that local emergence of bedrock cover at the surface marks a landscape transition from supply to kinetic weathering regimes in these systems, and highlights the importance of characterizing complex critical zone architecture in mountain landscapes. This work provides new insight into how landscape morphology and erosion may drive important thresholds for soil cover and weathering.

Numerical Model Sensitivity to Heterogeneous Satellite Derived Vegetation Roughness

NASA Technical Reports Server (NTRS)

Jasinski, Michael; Eastman, Joseph; Borak, Jordan

2011-01-01

The sensitivity of a mesoscale weather prediction model to a 1 km satellite-based vegetation roughness initialization is investigated for a domain within the south central United States. Three different roughness databases are employed: i) a control or standard lookup table roughness that is a function only of land cover type, ii) a spatially heterogeneous roughness database, specific to the domain, that was previously derived using a physically based procedure and Moderate Resolution Imaging Spectroradiometer (MODIS) imagery, and iii) a MODIS climatologic roughness database that like (i) is a function only of land cover type, but possesses domain specific mean values from (ii). The model used is the Weather Research and Forecast Model (WRF) coupled to the Community Land Model within the Land Information System (LIS). For each simulation, a statistical comparison is made between modeled results and ground observations within a domain including Oklahoma, Eastern Arkansas, and Northwest Louisiana during a 4-day period within IHOP 2002. Sensitivity analysis compares the impact the three roughness initializations on time-series temperature, precipitation probability of detection (POD), average wind speed, boundary layer height, and turbulent kinetic energy (TKE). Overall, the results indicate that, for the current investigation, replacement of the standard look-up table values with the satellite-derived values statistically improves model performance for most observed variables. Such natural roughness heterogeneity enhances the surface wind speed, PBL height and TKE production up to 10 percent, with a lesser effect over grassland, and greater effect over mixed land cover domains.

High-severity fire: evaluating its key drivers and mapping its probability across western US forests

NASA Astrophysics Data System (ADS)

Parks, Sean A.; Holsinger, Lisa M.; Panunto, Matthew H.; Jolly, W. Matt; Dobrowski, Solomon Z.; Dillon, Gregory K.

2018-04-01

Wildland fire is a critical process in forests of the western United States (US). Variation in fire behavior, which is heavily influenced by fuel loading, terrain, weather, and vegetation type, leads to heterogeneity in fire severity across landscapes. The relative influence of these factors in driving fire severity, however, is poorly understood. Here, we explore the drivers of high-severity fire for forested ecoregions in the western US over the period 2002–2015. Fire severity was quantified using a satellite-inferred index of severity, the relativized burn ratio. For each ecoregion, we used boosted regression trees to model high-severity fire as a function of live fuel, topography, climate, and fire weather. We found that live fuel, on average, was the most important factor driving high-severity fire among ecoregions (average relative influence = 53.1%) and was the most important factor in 14 of 19 ecoregions. Fire weather was the second most important factor among ecoregions (average relative influence = 22.9%) and was the most important factor in five ecoregions. Climate (13.7%) and topography (10.3%) were less influential. We also predicted the probability of high-severity fire, were a fire to occur, using recent (2016) satellite imagery to characterize live fuel for a subset of ecoregions in which the model skill was deemed acceptable (n = 13). These ‘wall-to-wall’ gridded ecoregional maps provide relevant and up-to-date information for scientists and managers who are tasked with managing fuel and wildland fire. Lastly, we provide an example of the predicted likelihood of high-severity fire under moderate and extreme fire weather before and after fuel reduction treatments, thereby demonstrating how our framework and model predictions can potentially serve as a performance metric for land management agencies tasked with reducing hazardous fuel across large landscapes.

A preliminary look at AVE-SESAME 3 conducted on 25-26 April 1979

NASA Technical Reports Server (NTRS)

Williams, S. F.; Horvath, N.; Turner, R. E.

1980-01-01

General weather conditions, including synoptic maps, radar reports, satellite photographs, precipitation areas and amounts, and a summary of severe weather reports are presented. These data provide researchers a preliminary look at conditions during the AVE-SESAME 3 period.

Assessment of opportunities for enhanced cooperation in acquiring and disseminating weather data among selected Virginia government agencies.

DOT National Transportation Integrated Search

1998-01-01

Accurate and timely information regarding impending weather conditions is important to several public agencies in Virginia. Potential problems including flooding, heavy snowfall, and damaging winds necessitate planning and pre-event deployment by man...

Data mining and gap analysis for weather responsive traffic management studies.

DOT National Transportation Integrated Search

2010-12-01

Weather causes a variety of impacts on the transportation system. An Oak Ridge National Laboratory study estimated the : delay experienced by American drivers due to snow, ice, and fog in 1999 at 46 million hours. While severe winter storms, : hurric...

sunstardb: A Database for the Study of Stellar Magnetism and the Solar-stellar Connection

NASA Astrophysics Data System (ADS)

Egeland, Ricky

2018-05-01

The “solar-stellar connection” began as a relatively small field of research focused on understanding the processes that generate magnetic fields in stars and sometimes lead to a cyclic pattern of long-term variability in activity, as demonstrated by our Sun. This area of study has recently become more broadly pertinent to questions of exoplanet habitability and exo-space weather, as well as stellar evolution. In contrast to other areas of stellar research, individual stars in the solar-stellar connection often have a distinct identity and character in the literature, due primarily to the rarity of the decades-long time-series that are necessary for studying stellar activity cycles. Furthermore, the underlying stellar dynamo is not well understood theoretically, and is thought to be sensitive to several stellar properties, e.g., luminosity, differential rotation, and the depth of the convection zone, which in turn are often parameterized by other more readily available properties. Relevant observations are scattered throughout the literature and existing stellar databases, and consolidating information for new studies is a tedious and laborious exercise. To accelerate research in this area I developed sunstardb, a relational database of stellar properties and magnetic activity proxy time-series keyed by individual named stars. The organization of the data eliminates the need for the problematic catalog cross-matching operations inherent when building an analysis data set from heterogeneous sources. In this article I describe the principles behind sunstardb, the data structures and programming interfaces, as well as use cases from solar-stellar connection research.

Contribution of human, climate and biophysical drivers to the spatial distribution of wildfires in a French Mediterranean area: where do wildfires start and spread?

NASA Astrophysics Data System (ADS)

Ruffault, Julien; Mouillot, Florent; Moebius, Flavia

2013-04-01

Understanding the contribution of biophysical and human drivers to the spatial distribution of fires at regional scale has many ecological and economical implications in a context of on-going global changes. However these fire drivers often interact in complex ways, such that disentangling and assessing the relative contribution of human vs. biophysical factors remains a major challenge. Indeed, the identification of biophysical conditions that promote fires are confused by the inherent stochasticity in fire occurrences and fire spread on the one hand and, by the influence of human factors -through both fire ignition and suppression - on the other. Moreover, different factors may drive fire ignition and fire spread, in such a way that the areas with the highest density of ignitions may not coincide with those where large fires occur. In the present study, we investigated the drivers of fires ignition and spread in a Mediterranean area of southern France. We used a 17 years fire database (the PROMETHEE database from 1989-2006) combined with a set of 8 explanatory variables describing the spatial pattern in ignitions, vegetation and fire weather. We first isolated the weather conditions affecting the fire occurrence and their spread using a statistical model of the weather/fuel water status for each fire event.. The results of these statistical models were used to map the fire weather in terms of average number of days with suitable conditions for burning. Then, we used Boosted regression trees (BRT) models to assess the relative importance of the different variables on the distribution of wildfire with different sizes and to assess the relationship between each variables and fire occurrence and spread probabilities. We found that human activities explained up to 50 % of the spatial distribution of fire ignitions (SDI). The distribution of large fire was chiefly explained by fuel characteristics (about 40%). Surprisingly, the weather indices explained only 20 % of the SDI and its contribution does no vary according to the size of considered fire events. These results suggest that changes in fuel characteristics and human settlements/ activities, rather than weather conditions are the most likely to modify the future distribution of fires in this Mediterranean area. These conclusions provide useful information on the scenarios that could arise from the interaction of changes in climate and land cover for the Mediterranean area in the near future.

Application of a DRAINMOD-based watershed model to a lower coastal plain watershed

Treesearch

Glenn P. Fernandez; George M. Chescheir; R. Wayne Skaggs; Devendra M. Amatya

2003-01-01

This is a case study for applying DRAINMOD-GIS, a DRAINMOD based lumped parameter watershed model to Chicod Creek, a 11300 ha coastal plain watershed in North Carolina which is not intensively instrumented or documented. The study utilized the current database of land-use, topography, stream network, soil, and weather data available to the State and Federal agencies....

Comprehensive national database of tree effects on air quality and human health in the United States

Treesearch

Satoshi Hirabayashi; David J. Nowak

2016-01-01

Trees remove air pollutants through dry deposition processes depending upon forest structure, meteorology, and air quality that vary across space and time. Employing nationally available forest, weather, air pollution and human population data for 2010, computer simulations were performed for deciduous and evergreen trees with varying leaf area index for rural and...

Using X-band Weather Radar Measurements to Monitor the Integrity of Digital Elevation Models for Synthetic Vision Systems

NASA Technical Reports Server (NTRS)

Young, Steve; UijtdeHaag, Maarten; Sayre, Jonathon

2003-01-01

Synthetic Vision Systems (SVS) provide pilots with displays of stored geo-spatial data representing terrain, obstacles, and cultural features. As comprehensive validation is impractical, these databases typically have no quantifiable level of integrity. Further, updates to the databases may not be provided as changes occur. These issues limit the certification level and constrain the operational context of SVS for civil aviation. Previous work demonstrated the feasibility of using a realtime monitor to bound the integrity of Digital Elevation Models (DEMs) by using radar altimeter measurements during flight. This paper describes an extension of this concept to include X-band Weather Radar (WxR) measurements. This enables the monitor to detect additional classes of DEM errors and to reduce the exposure time associated with integrity threats. Feature extraction techniques are used along with a statistical assessment of similarity measures between the sensed and stored features that are detected. Recent flight-testing in the area around the Juneau, Alaska Airport (JNU) has resulted in a comprehensive set of sensor data that is being used to assess the feasibility of the proposed monitor technology. Initial results of this assessment are presented.

Dynamics of pollutant discharge in combined sewer systems during rain events: chance or determinism?

PubMed

Hannouche, A; Chebbo, G; Joannis, C

2014-01-01

A large database of continuous flow and turbidity measurements cumulating data on hundreds of rain events and dry weather days from two sites in Paris (called Quais and Clichy) and one in Lyon (called Ecully) is presented. This database is used to characterize and compare the behaviour of the three sites at the inter-events scale. The analysis is probed through three various variables: total volumes and total suspended solids (TSS) masses and concentrations during both wet and dry weather periods in addition to the contributions of diverse-origin sources to event flow volume and TSS load values. The results obtained confirm the previous findings regarding the spatial consistency of TSS fluxes and concentrations between both sites in Paris having similar land uses. Moreover, masses and concentrations are proven to be correlated between Parisian sites in a way that implies the possibility of some deterministic processes being reproducible from one catchment to another for a particular rain event. The results also demonstrate the importance of the contribution of wastewater and sewer deposits to the total events' loads and show that such contributions are not specific to Paris sewer networks.

Dynamic Routing of Aircraft in the Presence of Adverse Weather Using a POMDP Framework

NASA Technical Reports Server (NTRS)

Balaban, Edward; Roychoudhury, Indranil; Spirkovska, Lilly; Sankararaman, Shankar; Kulkarni, Chetan; Arnon, Tomer

2017-01-01

Each year weather-related airline delays result in hundreds of millions of dollars in additional fuel burn, maintenance, and lost revenue, not to mention passenger inconvenience. The current approaches for aircraft route planning in the presence of adverse weather still mainly rely on deterministic methods. In contrast, this work aims to deal with the problem using a Partially Observable Markov Decision Processes (POMDPs) framework, which allows for reasoning over uncertainty (including uncertainty in weather evolution over time) and results in solutions that are more robust to disruptions. The POMDP-based decision support system is demonstrated on several scenarios involving convective weather cells and is benchmarked against a deterministic planning system with functionality similar to those currently in use or under development.

Severe Weather Guide Mediterranean Ports. 36. Limassol

DTIC Science & Technology

1991-06-01

EDITERRANEAN PORTS -s K 6 , IMASSOL 91-17537 1bV ~NJ * fr- ABSTRACT ’---This handbook for the port of Limassol,A one in a series of severe weather guides for...actions are suggested for various vessel situations. The handbook is organized in four sections for ready reference: general guidance on handbook content...and use; a quick-look captain’s summary; a more detailed review of general information on environmental conditions; and an appendix that provides

Space Weather Forecasting: An Enigma

NASA Astrophysics Data System (ADS)

Sojka, J. J.

2012-12-01

The space age began in earnest on October 4, 1957 with the launch of Sputnik 1 and was fuelled for over a decade by very strong national societal concerns. Prior to this single event the adverse effects of space weather had been registered on telegraph lines as well as interference on early WWII radar systems, while for countless eons the beauty of space weather as mid-latitude auroral displays were much appreciated. These prior space weather impacts were in themselves only a low-level science puzzle pursued by a few dedicated researchers. The technology boost and innovation that the post Sputnik era generated has almost single handedly defined our present day societal technology infrastructure. During the decade following Neil's walk on the moon on July 21, 1969 an international thrust to understand the science of space, and its weather, was in progress. However, the search for scientific understand was parsed into independent "stove pipe" categories: The ionosphere-aeronomy, the magnetosphere, the heliosphere-sun. The present day scientific infrastructure of funding agencies, learned societies, and international organizations are still hampered by these 1960's logical divisions which today are outdated in the pursuit of understanding space weather. As this era of intensive and well funded scientific research progressed so did societies innovative uses for space technologies and space "spin-offs". Well over a decade ago leaders in technology, science, and the military realized that there was indeed an adverse side to space weather that with each passing year became more severe. In 1994 several U.S. agencies established the National Space Weather Program (NSWP) to focus scientific attention on the system wide issue of the adverse effects of space weather on society and its technologies. Indeed for the past two decades a significant fraction of the scientific community has actively engaged in understanding space weather and hence crossing the "stove-pipe" disciplines. The perceived progress in space weather understanding differs significantly depending upon which community (scientific, technology, forecaster, society) is addressing the question. Even more divergent are these thoughts when the question is how valuable is the scientific capability of forecasting space weather. This talk will discuss present day as well as future potential for forecasting space weather for a few selected examples. The author will attempt to straddle the divergent community opinions.

Convective Weather Forecast Accuracy Analysis at Center and Sector Levels

NASA Technical Reports Server (NTRS)

Wang, Yao; Sridhar, Banavar

2010-01-01

This paper presents a detailed convective forecast accuracy analysis at center and sector levels. The study is aimed to provide more meaningful forecast verification measures to aviation community, as well as to obtain useful information leading to the improvements in the weather translation capacity models. In general, the vast majority of forecast verification efforts over past decades have been on the calculation of traditional standard verification measure scores over forecast and observation data analyses onto grids. These verification measures based on the binary classification have been applied in quality assurance of weather forecast products at the national level for many years. Our research focuses on the forecast at the center and sector levels. We calculate the standard forecast verification measure scores for en-route air traffic centers and sectors first, followed by conducting the forecast validation analysis and related verification measures for weather intensities and locations at centers and sectors levels. An approach to improve the prediction of sector weather coverage by multiple sector forecasts is then developed. The weather severe intensity assessment was carried out by using the correlations between forecast and actual weather observation airspace coverage. The weather forecast accuracy on horizontal location was assessed by examining the forecast errors. The improvement in prediction of weather coverage was determined by the correlation between actual sector weather coverage and prediction. observed and forecasted Convective Weather Avoidance Model (CWAM) data collected from June to September in 2007. CWAM zero-minute forecast data with aircraft avoidance probability of 60% and 80% are used as the actual weather observation. All forecast measurements are based on 30-minute, 60- minute, 90-minute, and 120-minute forecasts with the same avoidance probabilities. The forecast accuracy analysis for times under one-hour showed that the errors in intensity and location for center forecast are relatively low. For example, 1-hour forecast intensity and horizontal location errors for ZDC center were about 0.12 and 0.13. However, the correlation between sector 1-hour forecast and actual weather coverage was weak, for sector ZDC32, about 32% of the total variation of observation weather intensity was unexplained by forecast; the sector horizontal location error was about 0.10. The paper also introduces an approach to estimate the sector three-dimensional actual weather coverage by using multiple sector forecasts, which turned out to produce better predictions. Using Multiple Linear Regression (MLR) model for this approach, the correlations between actual observation and the multiple sector forecast model prediction improved by several percents at 95% confidence level in comparison with single sector forecast.

Anticipating the severity of the fire season in Northern Portugal using statistical models based on meteorological indices of fire danger

NASA Astrophysics Data System (ADS)

Nunes, Sílvia A.; DaCamara, Carlos C.; Turkman, Kamil F.; Ermida, Sofia L.; Calado, Teresa J.

2017-04-01

Like in other regions of Mediterranean Europe, climate and weather are major drivers of fire activity in Portugal. The aim of the present study is to assess the role played by meteorological factors on inter-annual variability of burned area over a region of Portugal characterized by large fire activity. Monthly cumulated values of burned area in August are obtained from the fire database of ICNF, the Portuguese authority for forests. The role of meteorological factors is characterized by means of Daily Severity Rating, DSR, an index of meteorological fire danger, which is derived from meteorological fields as obtained from ECMWF Interim Reanalysis. The study area is characterized by the predominance of forest, with high percentages of maritime pine and eucalyptus, two species with high flammability in summer. The time series of recorded burned area in August during 1980-2011 is highly correlated (correlation coefficient of 0.93) with the one for whole Portugal. First, a normal distribution model is fitted to the 32-year sample of decimal logarithms of monthly burned area. The model is improved by introducing two covariates:(1) the top-down meteorological factor (DSRtd) which consists of daily cumulated values of DSR since April 1 to July 31 and may be viewed as the cumulated stress on vegetation due to meteorological conditions during the pre-fire season; (2) the bottom-up factor (DSRbu) which consists of the square root of the mean of the squared daily deviations (restricted to days with positive departures of DSR from the corresponding long term mean) and may be viewed as the contribution of days characterized by extreme weather conditions favoring the onset and spreading of wildfires. Three different statistical models are then developed: the "climate anomaly" model, using DSRtd as covariate, the "weather anomaly", using DSRbu as covariate, and the "combined" model using both variables as covariates. These models are used to define background fire danger, fire weather danger and combined fire danger, respectively quantifying the contribution of DSRtd, DSRbu and both covariates to increasing or decreasing the probability of having extremely high/low values of burned area in August. Using the information obtained by the "combined" model it is possible to calculate the minimum/ maximum value of DSRbu for a given year to be modelled as severe/weak. The probability is then made using a normal distribution of the data series of DSRbu, if the probability is below 20% than the year will be considered as not belonging to that classification. This classification is able to correctly identify 34 out of the 36 years studied. This results can be of extreme use to forest managers and firefighters when deciding which the best fire preventing measures are and where to allocate the resources.

Multi-Spectral Stereo Atmospheric Remote Sensing (STARS) for Retrieval of Cloud Properties and Cloud-Motion Vectors

NASA Astrophysics Data System (ADS)

Kelly, M. A.; Boldt, J.; Wilson, J. P.; Yee, J. H.; Stoffler, R.

2017-12-01

The multi-spectral STereo Atmospheric Remote Sensing (STARS) concept has the objective to provide high-spatial and -temporal-resolution observations of 3D cloud structures related to hurricane development and other severe weather events. The rapid evolution of severe weather demonstrates a critical need for mesoscale observations of severe weather dynamics, but such observations are rare, particularly over the ocean where extratropical and tropical cyclones can undergo explosive development. Coincident space-based measurements of wind velocity and cloud properties at the mesoscale remain a great challenge, but are critically needed to improve the understanding and prediction of severe weather and cyclogenesis. STARS employs a mature stereoscopic imaging technique on two satellites (e.g. two CubeSats, two hosted payloads) to simultaneously retrieve cloud motion vectors (CMVs), cloud-top temperatures (CTTs), and cloud geometric heights (CGHs) from multi-angle, multi-spectral observations of cloud features. STARS is a pushbroom system based on separate wide-field-of-view co-boresighted multi-spectral cameras in the visible, midwave infrared (MWIR), and longwave infrared (LWIR) with high spatial resolution (better than 1 km). The visible system is based on a pan-chromatic, low-light imager to resolve cloud structures under nighttime illumination down to ¼ moon. The MWIR instrument, which is being developed as a NASA ESTO Instrument Incubator Program (IIP) project, is based on recent advances in MWIR detector technology that requires only modest cooling. The STARS payload provides flexible options for spaceflight due to its low size, weight, power (SWaP) and very modest cooling requirements. STARS also meets AF operational requirements for cloud characterization and theater weather imagery. In this paper, an overview of the STARS concept, including the high-level sensor design, the concept of operations, and measurement capability will be presented.

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

Weathering patterns of polycyclic aromatic hydrocarbons contained in submerged Deepwater Horizon oil spill residues when re-exposed to sunlight.

PubMed

John, Gerald F; Han, Yuling; Clement, T Prabhakar

2016-12-15

The Deepwater Horizon (DWH) oil spill event released a large amount of sweet crude oil into the Gulf of Mexico (GOM). An unknown portion of this oil that arrived along the Alabama shoreline interacted with nearshore sediments and sank forming submerged oil mats (SOMs). A considerable amount of hydrocarbons, including polycyclic aromatic hydrocarbons (PAHs), were trapped within these buried SOMs. Recent studies completed using the oil spill residues collected along the Alabama shoreline have shown that several PAHs, especially higher molecular weight PAHs (four or more aromatic rings), are slowly weathering compared to the weathering levels experienced by the oil when it was floating over the GOM. In this study we have hypothesized that the weathering rates of PAHs in SOMs have slowed down because the buried oil was isolated from direct exposure to sunlight, thus hindering the photodegradation pathway. We further hypothesized that re-exposing SOMs to sunlight can reactivate various weathering reactions. Also, SOMs contain 75-95% sand (by weight) and the entrapped sand could either block direct sunlight or form large oil agglomerates with very little exposed surface area; these processes could possibly interfere with weathering reactions. To test these hypotheses, we completed controlled experiments to study the weathering patterns of PAHs in a field recovered SOM sample after re-exposing it to sunlight. Our experimental results show that the weathering levels of several higher molecular weight PAHs have slowed down primarily due to the absence of sunlight-induced photodegradation reactions. The data also show that sand particles in SOM material could potentially interfere with photodegradation reactions. Copyright © 2016 Elsevier B.V. All rights reserved.

Precipitation Measurements From Space: Workshop report. An element of the climate observing system study

NASA Technical Reports Server (NTRS)

Atlas, D. (Editor); Thiele, O. W. (Editor)

1981-01-01

Global climate, agricultural uses for precipitation information, hydrological uses for precipitation, severe thunderstorms and local weather, global weather are addressed. Ground truth measurement, visible and infrared techniques, microwave radiometry and hybrid precipitation measurements, and spaceborne radar are discussed.

Study of the relationship between solar activity and terrestrial weather

NASA Technical Reports Server (NTRS)

Sturrock, P. A.; Brueckner, G. E.; Dickinson, R. E.; Fukuta, N.; Lanzerotti, L. J.; Lindzen, R. S.; Park, C. G.; Wilcox, J. M.

1976-01-01

Evidence for some connection between weather and solar related phenomena is presented. Historical data of world wide temperature variations with relationship to change in solar luminosity are examined. Several test methods for estimating the statistical significance of such phenomena are discussed in detail.

Preliminary Results form the Japanese Total Lightning Network

NASA Astrophysics Data System (ADS)

Hobara, Y.; Ishii, H.; Kumagai, Y.; Liu, C.; Heckman, S.; Price, C. G.; Williams, E. R.

2015-12-01

We report on the initial observational results from the first Japanese Total Lightning Detection Network (JTLN) in relation to severe weather phenomena. The University of Electro-Communications (UEC) has deployed the Earth Networks (EN) Total Lightning System over Japan to carry out research on the relationship between thunderstorm activity and severe weather phenomena since 2013. In this paper we first demonstrate the current status of our new network followed by the initial scientific results. The lightning jump algorithm was applied to our total lightning data to study the relationship between total lighting activity and hazardous weather events such as gust fronts and tornadoes over land reported by the JMA (Japanese Meteorological Agency) in 2014. As a result, a clear increase in total lighting flash rate as well as lightning jumps are observed prior to most hazardous weather events (~20 min) indicating potential usefulness for early warning in Japan. Furthermore we are going to demonstrate the relationship of total lightning activities with meteorological radar data focusing particularly on Japanese Tornadic storms.

GOES-S Mission Science Briefing

NASA Image and Video Library

2018-02-27

In the Kennedy Space Center's Press Site auditorium, members of the media participate in a mission briefing on National Oceanic and Atmospheric Administration's, or NOAA's, Geostationary Operational Environmental Satellite, or GOES-S. Briefing participants from left are: Steve Cole of NASA Communications; Dan Lindsey, GOES-R senior scientific advisor for NOAA; Louis Uccellini, director of the National Weather Service for NOAA; Jim Roberts, a scientist with the Earth System Research Laboratory's Office of Atmospheric Research for NOAA; Kristin Calhoun, a research scientist with NOAA's National Severe Storms Laboratory, and George Morrow, deputy director of NASA's Goddard Space Flight Center in Greenbelt, Maryland. GOES-S is the second satellite in a series of next-generation NOAA weather satellites. It will launch to a geostationary position over the U.S. to provide images of storms and help predict weather forecasts, severe weather outlooks, watches, warnings, lightning conditions and longer-term forecasting. GOES-S is slated to lift off at 5:02 p.m. EST on March 1, 2018 aboard a United Launch Alliance Atlas V rocket.

Identification of Weather Conditions Associated with the Occurrence, Severity, and Incidence of Black Seed Disease of Strawberry Caused by Mycosphaerella fragariae.

PubMed

Carisse, Odile; McNealis, Vanessa

2018-01-01

Black seed disease (BSD) of strawberry is a sporadic disease caused by Mycosphaerella fragariae. Because little is known about potential crop losses or the weather conditions conducive to disease development, fungicides are generally not applied or are applied based on a preset schedule. Data collected from 2000 to 2011 representing 50 farm-years (total of 186 strawberry fields) were used to determine potential crop losses and to study the influence of weather on disease occurrence and development. First, logistic regression was used to model the relationship between occurrence of BSD and weather variables. Second, linear and nonlinear regressions were used to model the number of black seed per berry (severity) and the percentage of diseased berries (incidence). Of the 186 fields monitored, 78 showed black seed symptoms, and the number of black seed per berry ranged from 1 to 10, whereas the percentage of diseased berries ranged from 3 to 32%. The most influential weather variable was total rainfall (in millimeters) in May, with a threshold of 103 mm of rain (absence of BSD < 103 mm < presence of BSD). Similarly, nonlinear models with the total rainfall in May accurately predicted both disease severity and incidence (r = 0.94 and 0.97, respectively). Considering that management actions such as fungicide application are not needed every year in every field, these models could be used to identify fields that are at risk of BSD.

Convective Weather Forecast Quality Metrics for Air Traffic Management Decision-Making

NASA Technical Reports Server (NTRS)

Chatterji, Gano B.; Gyarfas, Brett; Chan, William N.; Meyn, Larry A.

2006-01-01

Since numerical weather prediction models are unable to accurately forecast the severity and the location of the storm cells several hours into the future when compared with observation data, there has been a growing interest in probabilistic description of convective weather. The classical approach for generating uncertainty bounds consists of integrating the state equations and covariance propagation equations forward in time. This step is readily recognized as the process update step of the Kalman Filter algorithm. The second well known method, known as the Monte Carlo method, consists of generating output samples by driving the forecast algorithm with input samples selected from distributions. The statistical properties of the distributions of the output samples are then used for defining the uncertainty bounds of the output variables. This method is computationally expensive for a complex model compared to the covariance propagation method. The main advantage of the Monte Carlo method is that a complex non-linear model can be easily handled. Recently, a few different methods for probabilistic forecasting have appeared in the literature. A method for computing probability of convection in a region using forecast data is described in Ref. 5. Probability at a grid location is computed as the fraction of grid points, within a box of specified dimensions around the grid location, with forecast convection precipitation exceeding a specified threshold. The main limitation of this method is that the results are dependent on the chosen dimensions of the box. The examples presented Ref. 5 show that this process is equivalent to low-pass filtering of the forecast data with a finite support spatial filter. References 6 and 7 describe the technique for computing percentage coverage within a 92 x 92 square-kilometer box and assigning the value to the center 4 x 4 square-kilometer box. This technique is same as that described in Ref. 5. Characterizing the forecast, following the process described in Refs. 5 through 7, in terms of percentage coverage or confidence level is notionally sound compared to characterizing in terms of probabilities because the probability of the forecast being correct can only be determined using actual observations. References 5 through 7 only use the forecast data and not the observations. The method for computing the probability of detection, false alarm ratio and several forecast quality metrics (Skill Scores) using both the forecast and observation data are given in Ref. 2. This paper extends the statistical verification method in Ref. 2 to determine co-occurrence probabilities. The method consists of computing the probability that a severe weather cell (grid location) is detected in the observation data in the neighborhood of the severe weather cell in the forecast data. Probabilities of occurrence at the grid location and in its neighborhood with higher severity, and with lower severity in the observation data compared to that in the forecast data are examined. The method proposed in Refs. 5 through 7 is used for computing the probability that a certain number of cells in the neighborhood of severe weather cells in the forecast data are seen as severe weather cells in the observation data. Finally, the probability of existence of gaps in the observation data in the neighborhood of severe weather cells in forecast data is computed. Gaps are defined as openings between severe weather cells through which an aircraft can safely fly to its intended destination. The rest of the paper is organized as follows. Section II summarizes the statistical verification method described in Ref. 2. The extension of this method for computing the co-occurrence probabilities in discussed in Section HI. Numerical examples using NCWF forecast data and NCWD observation data are presented in Section III to elucidate the characteristics of the co-occurrence probabilities. This section also discusses the procedure for computing throbabilities that the severity of convection in the observation data will be higher or lower in the neighborhood of grid locations compared to that indicated at the grid locations in the forecast data. The probability of coverage of neighborhood grid cells is also described via examples in this section. Section IV discusses the gap detection algorithm and presents a numerical example to illustrate the method. The locations of the detected gaps in the observation data are used along with the locations of convective weather cells in the forecast data to determine the probability of existence of gaps in the neighborhood of these cells. Finally, the paper is concluded in Section V.

A new statistical tool for NOAA local climate studies

NASA Astrophysics Data System (ADS)

Timofeyeva, M. M.; Meyers, J. C.; Hollingshead, A.

2011-12-01

The National Weather Services (NWS) Local Climate Analysis Tool (LCAT) is evolving out of a need to support and enhance the National Oceanic and Atmospheric Administration (NOAA) National Weather Service (NWS) field offices' ability to efficiently access, manipulate, and interpret local climate data and characterize climate variability and change impacts. LCAT will enable NOAA's staff to conduct regional and local climate studies using state-of-the-art station and reanalysis gridded data and various statistical techniques for climate analysis. The analysis results will be used for climate services to guide local decision makers in weather and climate sensitive actions and to deliver information to the general public. LCAT will augment current climate reference materials with information pertinent to the local and regional levels as they apply to diverse variables appropriate to each locality. The LCAT main emphasis is to enable studies of extreme meteorological and hydrological events such as tornadoes, flood, drought, severe storms, etc. LCAT will close a very critical gap in NWS local climate services because it will allow addressing climate variables beyond average temperature and total precipitation. NWS external partners and government agencies will benefit from the LCAT outputs that could be easily incorporated into their own analysis and/or delivery systems. Presently we identified five existing requirements for local climate: (1) Local impacts of climate change; (2) Local impacts of climate variability; (3) Drought studies; (4) Attribution of severe meteorological and hydrological events; and (5) Climate studies for water resources. The methodologies for the first three requirements will be included in the LCAT first phase implementation. Local rate of climate change is defined as a slope of the mean trend estimated from the ensemble of three trend techniques: (1) hinge, (2) Optimal Climate Normals (running mean for optimal time periods), (3) exponentially-weighted moving average. Root mean squared error is used to determine the best fit of trend to the observations with the least error. The studies of climate variability impacts on local extremes use composite techniques applied to various definitions of local variables: from specified percentiles to critical thresholds. Drought studies combine visual capabilities of Google maps with statistical estimates of drought severity indices. The process of development will be linked to local office interactions with users to ensure the tool will meet their needs as well as provide adequate training. A rigorous internal and tiered peer-review process will be implemented to ensure the studies are scientifically-sound that will be published and submitted to the local studies catalog (database) and eventually to external sources, such as the Climate Portal.

Using Satellite Remote Sensing to Assist the National Weather Service (NWS) in Storm Damage Surveys

NASA Technical Reports Server (NTRS)

Schultz, Lori A.; Molthan, Andrew; McGrath, Kevin; Bell, Jordan; Cole, Tony; Burks, Jason

2016-01-01

In the United States, the National Oceanic and Atmospheric Administration (NOAA) National Weather Service (NWS) is charged with performing damage assessments when storm or tornado damage is suspected after a severe weather event. This has led to the development of the Damage Assessment Toolkit (DAT), an application for smartphones, tablets and web browsers that allows for the collection, geolocation, and aggregation of various damage indicators collected during storm surveys.

GOES-S Liftoff

NASA Image and Video Library

2018-03-01

A United Launch Alliance Atlas V rocket lifts off from Space Launch Complex 41 at Cape Canaveral Air Force Station carrying the NOAA Geostationary Operational Environmental Satellite, or GOES-S. Liftoff was at 5:02 p.m. EST. GOES-S is the second satellite in a series of next-generation weather satellites. It will launch to a geostationary position over the U.S. to provide images of storms and help predict weather forecasts, severe weather outlooks, watches, warnings, lightning conditions and longer-term forecasting.

Remote sensing optical instrumentation for enhanced space weather monitoring from the L1 and L5 Lagrange points

NASA Astrophysics Data System (ADS)

Kraft, S.; Puschmann, K. G.; Luntama, J. P.

2017-09-01

As part of the Space Situational Awareness Programme (SSA), ESA has initiated the assessment of two missions currently foreseen to be implemented to enable enhanced space weather monitoring. These missions utilize the positioning of satellites at the Lagrangian L1 and L5 points. These Phase 0 or Pre-Phase A mission studies are about to be completed and will thereby have soon passed the Mission Definition Review. Phase A studies are planned to start in 2017. The space weather monitoring system currently considers four remote sensing optical instruments and several in-situ instruments to analyse the Sun and the solar wind conditions, in order to provide early warnings of increased solar activity and to identify and mitigate potential threats to society and ground, airborne and space based infrastructure. The suggested optical instruments take heritage from ESA and NASA science missions like SOHO, STEREO and Solar Orbiter, but the instruments are foreseen to be optimized for operational space weather monitoring purposes with high reliability and robustness demands. The instruments are required to provide high quality measurements particularly during severe space weather events. The program intends to utilize the results of the on-going ESA instrument prototyping and technology development activities, and to initiate pre-developments of the operational space weather instruments to ensure the required maturity before the mission implementation.

Space Weather, Geomagnetic Disturbances and Impact on the High-Voltage Transmission Systems

NASA Technical Reports Server (NTRS)

Pullkkinen, A.

2011-01-01

Geomagnetically induced currents (GIC) affecting the performance of high-voltage power transmission systems are one of the most significant hazards space weather poses on the operability of critical US infrastructure. The severity of the threat was emphasized, for example, in two recent reports: the National Research Council (NRC) report "Severe Space Weather Events--Understanding Societal and Economic Impacts: A Workshop Report" and the North American Electric Reliability Corporation (NERC) report "HighImpact, Low-Frequency Event Risk to the North American Bulk Power System." The NRC and NERC reports demonstrated the important national security dimension of space weather and GIC and called for comprehensive actions to forecast and mitigate the hazard. In this paper we will give a brief overview of space weather storms and accompanying geomagnetic storm events that lead to GIC. We will also review the fundamental principles of how GIC can impact the power transmission systems. Space weather has been a subject of great scientific advances that have changed the wonder of the past to a quantitative field of physics with true predictive power of today. NASA's Solar Shield system aimed at forecasting of GIC in the North American high-voltage power transmission system can be considered as one of the ultimate fruits of those advances. We will review the fundamental principles of the Solar Shield system and provide our view of the way forward in the science of GIC.

The Weathering of Antarctic Meteorites: Climatic Controls on Weathering Rates and Implications for Meteorite Accumulation

NASA Technical Reports Server (NTRS)

Benoit, P. H.; Akridge, J. M. C.; Sears, D. W. G.; Bland, P. A.

1995-01-01

Weathering of meteorites includes a variety of chemical and mineralogical changes, including conversion of metal to iron oxides, or rust. Other changes include the devitrification of glass, especially in fusion crust. On a longer time scale, major minerals such as olivine, pyroxene, and feldspar are partially or wholly converted to various phyllosilicates. The degree of weathering of meteorite finds is often noted using a qualitative system based on visual inspection of hand specimens. Several quantitative weathering classification systems have been proposed or are currently under development. Wlotzka has proposed a classification system based on mineralogical changes observed in polished sections and Mossbauer properties of meteorite powders have also been used. In the current paper, we discuss induced thermoluminescence (TL) as an indicator of degree of weathering of individual meteorites. The quantitative measures of weathering, including induced TL, suffer from one major flaw, namely that their results only apply to small portions of the meteorite.

Optimum space shuttle launch times relative to natural environment

NASA Technical Reports Server (NTRS)

King, R. L.

1977-01-01

Three sets of meteorological criteria were analyzed to determine the probabilities of favorable launch and landing conditions. Probabilities were computed for every 3 hours on a yearly basis using 14 years of weather data. These temporal probability distributions, applicable to the three sets of weather criteria encompassing benign, moderate and severe weather conditions, were computed for both Kennedy Space Center (KSC) and Edwards Air Force Base. In addition, conditional probabilities were computed for unfavorable weather conditions occurring after a delay which may or may not be due to weather conditions. Also, for KSC, the probabilities of favorable landing conditions at various times after favorable launch conditions have prevailed have been computed so that mission probabilities may be more accurately computed for those time periods when persistence strongly correlates weather conditions. Moreover, the probabilities and conditional probabilities of the occurrence of both favorable and unfavorable events for each individual criterion were computed to indicate the significance of each weather element to the overall result.

An Examination of the Space Weathering Patina of Lunar Rock 76015

NASA Technical Reports Server (NTRS)

Noble, S.; Chrisoffersen, R.; Rahman, Z.

2011-01-01

Space weathering discussions have generally centered around soils but exposed rocks will also incur the effects of weathering. Rocks have much longer surface lifetimes than an individual soil grain and thus record a longer history of exposure. By studying the weathering products which have built up on a rock surface, we can gain a deeper perspective on the weathering process and better assess the relative importance of various weathering components. The weathered coating, or patina, of the lunar rock 76015 has been previously studied under SEM and also by TEM using ultramicrotome sample preparation methods. However, to really understand the products involved in creating these coatings, it is helpful to examine the patina in cross section, something which is now possible though the use of Focused Ion Beam (FIB) sample prep techniques, which allows us to preserve intact the delicate stratigraphy of the patina coating and provides a unique cross-sectional view of the space weathering process. Several samples have been prepared from the rock and the coatings are found to be quite variable in thickness and composition from one sample to the next.

Comparative assessment of several post-processing methods for correcting evapotranspiration forecasts derived from TIGGE datasets.

NASA Astrophysics Data System (ADS)

Tian, D.; Medina, H.

2017-12-01

Post-processing of medium range reference evapotranspiration (ETo) forecasts based on numerical weather prediction (NWP) models has the potential of improving the quality and utility of these forecasts. This work compares the performance of several post-processing methods for correcting ETo forecasts over the continental U.S. generated from The Observing System Research and Predictability Experiment (THORPEX) Interactive Grand Global Ensemble (TIGGE) database using data from Europe (EC), the United Kingdom (MO), and the United States (NCEP). The pondered post-processing techniques are: simple bias correction, the use of multimodels, the Ensemble Model Output Statistics (EMOS, Gneitting et al., 2005) and the Bayesian Model Averaging (BMA, Raftery et al., 2005). ETo estimates based on quality-controlled U.S. Regional Climate Reference Network measurements, and computed with the FAO 56 Penman Monteith equation, are adopted as baseline. EMOS and BMA are generally the most efficient post-processing techniques of the ETo forecasts. Nevertheless, the simple bias correction of the best model is commonly much more rewarding than using multimodel raw forecasts. Our results demonstrate the potential of different forecasting and post-processing frameworks in operational evapotranspiration and irrigation advisory systems at national scale.

Introduction to the Space Weather Monitoring System at KASI

NASA Astrophysics Data System (ADS)

Baek, J.; Choi, S.; Kim, Y.; Cho, K.; Bong, S.; Lee, J.; Kwak, Y.; Hwang, J.; Park, Y.; Hwang, E.

2014-05-01

We have developed the Space Weather Monitoring System (SWMS) at the Korea Astronomy and Space Science Institute (KASI). Since 2007, the system has continuously evolved into a better system. The SWMS consists of several subsystems: applications which acquire and process observational data, servers which run the applications, data storage, and display facilities which show the space weather information. The applications collect solar and space weather data from domestic and oversea sites. The collected data are converted to other format and/or visualized in real time as graphs and illustrations. We manage 3 data acquisition and processing servers, a file service server, a web server, and 3 sets of storage systems. We have developed 30 applications for a variety of data, and the volume of data is about 5.5 GB per day. We provide our customers with space weather contents displayed at the Space Weather Monitoring Lab (SWML) using web services.

Exceptional sequence of severe thunderstorms and related flash floods in May and June 2016 in Germany - Part 1: Meteorological background

NASA Astrophysics Data System (ADS)

Piper, David; Kunz, Michael; Ehmele, Florian; Mohr, Susanna; Mühr, Bernhard; Kron, Andreas; Daniell, James

2016-12-01

During a 15-day episode from 26 May to 9 June 2016, Germany was affected by an exceptionally large number of severe thunderstorms. Heavy rainfall, related flash floods and creek flooding, hail, and tornadoes caused substantial losses running into billions of euros (EUR). This paper analyzes the key features of the severe thunderstorm episode using extreme value statistics, an aggregated precipitation severity index, and two different objective weather-type classification schemes. It is shown that the thunderstorm episode was caused by the interaction of high moisture content, low thermal stability, weak wind speed, and large-scale lifting by surface lows, persisting over almost 2 weeks due to atmospheric blocking.For the long-term assessment of the recent thunderstorm episode, we draw comparisons to a 55-year period (1960-2014) regarding clusters of convective days with variable length (2-15 days) based on precipitation severity, convection-favoring weather patterns, and compound events with low stability and weak flow. It is found that clusters with more than 8 consecutive convective days are very rare. For example, a 10-day cluster with convective weather patterns prevailing during the recent thunderstorm episode has a probability of less than 1 %.

MASS MEDIA

Science.gov Websites

Office Marine, Tropical, and Tsunami Services Branch Items of Interest Marine Forecasts Text, Graphic , either directly or as a Secondary Audio Program (SAP). Scrolling of NWS text forecasts via specialized cable TV weather channels is becoming increasingly commonplace. In the case of severe weather, text is

Evidence of fuels management and fire weather influencing fire severity in an extreme fire event

USGS Publications Warehouse

Lydersen, Jamie M; Collins, Brandon M.; Brooks, Matthew L.; Matchett, John R.; Shive, Kristen L.; Povak, Nicholas A.; Kane, Van R.; Smith, Douglas F.

2017-01-01

Following changes in vegetation structure and pattern, along with a changing climate, large wildfire incidence has increased in forests throughout the western U.S. Given this increase there is great interest in whether fuels treatments and previous wildfire can alter fire severity patterns in large wildfires. We assessed the relative influence of previous fuels treatments (including wildfire), fire weather, vegetation and water balance on fire severity in the Rim Fire of 2013. We did this at three different spatial scales to investigate whether the influences on fire severity changed across scales. Both fuels treatments and previous low to moderate severity wildfire reduced the prevalence of high severity fire. In general, areas without recent fuels treatments and areas that previously burned at high severity tended to have a greater proportion of high severity fire in the Rim Fire. Areas treated with prescribed fire, especially when combined with thinning, had the lowest proportions of high severity. Proportion of the landscape burned at high severity was most strongly influenced by fire weather and proportional area previously treated for fuels or burned by low to moderate severity wildfire. The proportion treated needed to effectively reduce the amount of high fire severity fire varied by spatial scale of analysis, with smaller spatial scales requiring a greater proportion treated to see an effect on fire severity. When moderate and high severity fire encountered a previously treated area, fire severity was significantly reduced in the treated area relative to the adjacent untreated area. Our results show that fuels treatments and low to moderate severity wildfire can reduce fire severity in a subsequent wildfire, even when burning under fire growth conditions. These results serve as further evidence that both fuels treatments and lower severity wildfire can increase forest resilience.

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

Multi-model global assessment of subseasonal prediction skill of atmospheric rivers

NASA Astrophysics Data System (ADS)

Deflorio, M. J.

2017-12-01

Atmospheric rivers (ARs) are global phenomena that are characterized by long, narrow plumes of water vapor transport. They are most often observed in the midlatitudes near climatologically active storm track regions. Because of their frequent association with floods, landslides, and other hydrological impacts on society, there is significant incentive at the intersection of academic research, water management, and policymaking to understand the skill with which state-of-the-art operational weather models can predict ARs weeks-to-months in advance. We use the newly assembled Subseasonal-to-Seasonal (S2S) database, which includes extensive hindcast records of eleven operational weather models, to assess global prediction skill of atmospheric rivers on S2S timescales. We develop a metric to assess AR skill that is suitable for S2S timescales by counting the total number of AR days which occur over each model and observational grid cell during a 2-week time window. This "2-week AR occurrence" metric is suitable for S2S prediction skill assessment because it does not consider discrete hourly or daily AR objects, but rather a smoothed representation of AR occurrence over a longer period of time. Our results indicate that several of the S2S models, especially the ECMWF model, show useful prediction skill in the 2-week forecast window, with significant interannual variation in some regions. We also present results from an experimental forecast of S2S AR prediction skill using the ECMWF and NCEP models.

Projected changes in daily fire spread across Canada over the next century

NASA Astrophysics Data System (ADS)

Wang, Xianli; Parisien, Marc-André; Taylor, Steve W.; Candau, Jean-Noël; Stralberg, Diana; Marshall, Ginny A.; Little, John M.; Flannigan, Mike D.

2017-02-01

In the face of climate change, predicting and understanding future fire regimes across Canada is a high priority for wildland fire research and management. Due in large part to the difficulties in obtaining future daily fire weather projections, one of the major challenges in predicting future fire activity is to estimate how much of the change in weather potential could translate into on-the-ground fire spread. As a result, past studies have used monthly, annual, or multi-decadal weather projections to predict future fires, thereby sacrificing information relevant to day-to-day fire spread. Using climate projections from the fifth phase of the Coupled Model Intercomparison Project (CMIP5), historical weather observations, MODIS fire detection data, and the national fire database of Canada, this study investigated potential changes in the number of active burning days of wildfires by relating ‘spread days’ to patterns of daily fire-conducive weather. Results suggest that climate change over the next century may have significant impacts on fire spread days in almost all parts of Canada’s forested landmass; the number of fire spread days could experience a 2-to-3-fold increase under a high CO2 forcing scenario in eastern Canada, and a greater than 50% increase in western Canada, where the fire potential is already high. The change in future fire spread is critical in understanding fire regime changes, but is also imminently relevant to fire management operations and in fire risk mitigation.

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

NASA Astrophysics Data System (ADS)

Sommer, Philipp; Kaplan, Jed

2016-04-01

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

Search for an astronomical site on the Arabian Peninsula: meteorological and climatological analyses

NASA Astrophysics Data System (ADS)

Sultan, A. H.; Graham, E.

The Arabian Peninsula is the richest in oil but the poorest in A A -Astronomy and Astrophysics- the largest telescope in the region doesn t exceed 45cm To promote A A education and research we propose that all the countries of the region work together to install an optical regional observatory telescope diameter 2 meters on an accessible summit somewhere within the mountains of the Arabian Peninsula The first step is to make a climatological and meteorological study of the highest summits of the region A preliminary study has revealed only one mountain peak above 3000 meters in Saudi Arabia one in Oman but more than thirty in Yemen Of all these summits we have narrowed the selection to six candidate sites on which we are performing detailed meteorological and climatological analyses Our database is composed mainly of Reanalysis datasets from the European Centre for Medium Range Weather Forecasting ECMWF and the National Center for Environmental Protection National Center for Atmospheric Research NCEP-NCAR Reanalysis datasets are reconstructions of all available past weather station data aeroplane sensor data weather balloon data weather ship data and satellite data from the 1950s onwards using sophisticated numerical weather prediction and data assimilation models This paper discusses ECMWF and NCEP-NCAR images of Arabian Peninsula for the following parameters at a monthly mean temporal resolution begin enumerate item Temperature variability at 700hPa item Precipitation item Geopotential height of the

Day length is associated with physical activity and sedentary behavior among older women.

PubMed

Schepps, Mitchell A; Shiroma, Eric J; Kamada, Masamitsu; Harris, Tamara B; Lee, I-Min

2018-04-26

Physical activity may be influenced by one's physical environment, including day length and weather. Studies of physical activity, day length, and weather have primarily used self-reported activity, broad meteorological categorization, and limited geographic regions. We aim to examine the association of day length and physical activity in a large cohort of older women, covering a wide geographic range. Participants (N = 16,741; mean (SD) age = 72.0 (SD = 5.7) years) were drawn from the Women's Health Study and lived throughout the United States. Physical activity was assessed by accelerometer (ActiGraph GT3X+) between 2011 and 2015. Day length and weather information were obtained by matching weather stations to the participants' location using National Oceanic and Atmospheric Administration databases. Women who experienced day lengths greater than 14 hours had 5.5% more steps, 9.4% more moderate-to-vigorous physical activity, and 1.6% less sedentary behavior, compared to women who experienced day lengths less than 10 hours, after adjusting for age, accelerometer wear, temperature, and precipitation. Day length is associated with physical activity and sedentary behavior in older women, and needs to be considered in programs promoting physical activity as well as in the analyses of accelerometer data covering wide geographic regions.

Broadcast media and the dissemination of weather information

NASA Technical Reports Server (NTRS)

Byrnes, J.

1973-01-01

Although television is the public's most preferred source of weather information, it fails to provide weather reports to those groups who seek the information early in the day and during the day. The result is that many people most often use radio as a source of information, yet preferring the medium of television. The public actively seeks weather information from both radio and TV stations, usually seeking information on current conditions and short range forecasts. forecasts. Nearly all broadcast stations surveyed were eager to air severe weather bulletins quickly and often. Interest in Nowcasting was high among radio and TV broadcasters, with a significant portion indicating a willingness to pay something for the service. However, interest among TV stations in increasing the number of daily reports was small.

Water geochemistry of the Qiantangjiang River, East China: Chemical weathering and CO2 consumption in a basin affected by severe acid deposition

NASA Astrophysics Data System (ADS)

Liu, Wenjing; Shi, Chao; Xu, Zhifang; Zhao, Tong; Jiang, Hao; Liang, Chongshan; Zhang, Xuan; Zhou, Li; Yu, Chong

2016-09-01

The chemical composition of the Qiantangjiang River, the largest river in Zhejiang province in eastern China, was measured to understand the chemical weathering of rocks and the associated CO2 consumption and anthropogenic influences within a silicate-dominated river basin. The average total dissolved solids (TDS, 113 mg l-1) and total cation concentration (TZ+, 1357 μeq l-1) of the river waters are comparable with those of global major rivers. Ca2+ and HCO3- followed by Na2+ and SO42-, dominate the ionic composition of the river water. There are four major reservoirs (carbonates, silicates, atmospheric and anthropogenic inputs) contributing to the total dissolved load of the investigated rivers. The dissolved loads of the rivers are dominated by both carbonate and silicate weathering, which together account for about 76.3% of the total cationic load origin. The cationic chemical weathering rates of silicate and carbonate for the Qiantangjiang basin are estimated to be approximately 4.9 ton km-2 a-1 and 13.9 ton km-2 a-1, respectively. The calculated CO2 consumption rates with the assumption that all the protons involved in the weathering reaction are provided by carbonic acid are 369 × 103 mol km-2 a-1 and 273 × 103 mol km-2 a-1 by carbonate and silicate weathering, respectively. As one of the most severe impacted area by acid rain in China, H2SO4 from acid precipitation is also an important proton donor in weathering reactions. When H2SO4 is considered, the CO2 consumption rates for the river basin are estimated at 286 × 103 mol km-2 a-1 for carbonate weathering and 211 × 103 mol km-2 a-1 for silicate weathering, respectively. The results highlight that the drawdown effect of CO2 consumption by carbonate and silicate weathering can be largely overestimated if the role of sulfuric acid is ignored, especially in the area heavily impacted by acid deposition like Qiantangjiang basin. The actual CO2 consumption rates (after sulfuric acid weathering effect deduction) is only about 77% of the value calculated with the assumption that carbonic acid donates all the protons involved in the weathering reaction.

GOES-S Mission Science Briefing

NASA Image and Video Library

2018-02-27

In the Kennedy Space Center's Press Site auditorium, Jim Roberts, a scientist with the Earth System Research Laboratory's Office of Atmospheric Research for NOAA, left, and Kristin Calhoun, a research scientist with NOAA's National Severe Storms Laboratory, speak to members of the media at a mission briefing on National Oceanic and Atmospheric Administration's, or NOAA's, Geostationary Operational Environmental Satellite, or GOES-S. The spacecraft is the second satellite in a series of next-generation NOAA weather satellites. It will launch to a geostationary position over the U.S. to provide images of storms and help predict weather forecasts, severe weather outlooks, watches, warnings, lightning conditions and longer-term forecasting. GOES-S is slated to lift off at 5:02 p.m. EST on March 1, 2018 aboard a United Launch Alliance Atlas V rocket.

The Polygon-Ellipse Method of Data Compression of Weather Maps

DTIC Science & Technology

1994-03-28

Report No. DOT’•FAAJRD-9416 Pr•oject Report AD-A278 958 ATC-213 The Polygon-Ellipse Method of Data Compression of Weather Maps ELDCT E J.L. GerIz 28...a o means must he- found to Compress this image. The l’olygion.Ellip.e (PE.) encoding algorithm develop.ed in this report rt-premrnt. weather regions...severely compress the image. For example, Mode S would require approximately a 10-fold compression . In addition, the algorithms used to perform the

KSC-20180301-VP-CDC01_0001-GOES_S_Launch_Commentary-3182524

NASA Image and Video Library

2018-03-01

A United Launch Alliance Atlas V rocket lifts off from Space Launch Complex 41 at Cape Canaveral Air Force Station carrying the NOAA Geostationary Operational Environmental Satellite, or GOES-S. Liftoff was at 5:02 p.m. EST. GOES-S is the second satellite in a series of next-generation weather satellites. It will launch to a geostationary position over the U.S. to provide images of storms and help predict weather forecasts, severe weather outlooks, watches, warnings, lightning conditions and longer-term forecasting.

Defense Weather Satellites: Analysis of Alternatives is Useful for Certain Capabilities, but Ineffective Coordination Limited Assessment of Two Critical Capabilities

DTIC Science & Technology

2016-03-10

2015, DOD also inquired with NOAA about the possibility of using one of NOAA’s geostationary weather satellites to preserve coverage over the Indian...life of DMSP-20.” It further states, “This means there will always be geostationary coverage” of several regions, including the Indian Ocean, “by U.S...weather prediction. • Geostationary satellites maintain a fixed position relative to the earth, collecting data on a specific geographic region and

Projected Applications of a "Weather in a Box" Computing System at the NASA Short-Term Prediction Research and Transition (SPoRT) Center

NASA Technical Reports Server (NTRS)

Jedlovec, Gary J.; Molthan, Andrew; Zavodsky, Bradley T.; Case, Jonathan L.; LaFontaine, Frank J.; Srikishen, Jayanthi

2010-01-01

The NASA Short-term Prediction Research and Transition Center (SPoRT)'s new "Weather in a Box" resources will provide weather research and forecast modeling capabilities for real-time application. Model output will provide additional forecast guidance and research into the impacts of new NASA satellite data sets and software capabilities. By combining several research tools and satellite products, SPoRT can generate model guidance that is strongly influenced by unique NASA contributions.

Optimizing Placement of Weather Stations: Exploring Objective Functions of Meaningful Combinations of Multiple Weather Variables

NASA Astrophysics Data System (ADS)

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

2017-12-01

Many regions of the world lack ground-based weather data due to inadequate or unreliable weather station networks. For example, most countries in Sub-Saharan Africa have unreliable, sparse networks of weather stations. The absence of these data can have consequences on weather forecasting, prediction of severe weather events, agricultural planning, and climate change monitoring. 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 place weather stations within each country. We should consider how we can create accurate spatio-temporal maps of weather data and how to balance the desired accuracy of each weather variable of interest (precipitation, temperature, relative humidity, etc.). We can express this problem as a joint optimization of multiple weather variables, given a fixed number of weather stations. We use reanalysis data as the best representation of the "true" weather patterns that occur in the region of interest. For each possible combination of sites, we interpolate the reanalysis data between selected locations and calculate the mean average error between the reanalysis ("true") data and the interpolated data. In order to formulate our multi-variate optimization problem, we explore different methods of weighting each weather variable in our objective function. These methods include systematic variation of weights to determine which weather variables have the strongest influence on the network design, as well as combinations targeted for specific purposes. For example, we can use computed evapotranspiration as a metric that combines many weather variables in a way that is meaningful for agricultural and hydrological applications. We compare the errors of the weather station networks produced by each optimization problem formulation. We also compare these errors to those of manually designed weather station networks in West Africa, planned by the respective host-country's meteorological agency.

Dendroecological Analysis of Cordia alliodora, Pseudobombax septenatum and Annona spraguei in Central Panama

Treesearch

Margaret S. Devall; Bernard R. Parresol; S. Joseph Wright

1995-01-01

Several plant communities in central Panama, each community located near a weather station, contain trees with annual growth rings, i.e. Cordia alliodora, Pseudobombax septenatum, and Annona spraguei. Tree-ring data are particularly valuable when concomitant weather information is readily available. Patterns of...

image1goes5117.jpg

NASA Image and Video Library

2017-12-08

NASA Sees Severe Weather from Central to Eastern US A vigorous weather system has generated severe weather over the mid-section of the U.S. and satellites are providing a look at it as it is moving toward the East Coast. NASA and NOAA satellites have been tracking a storm system that has generated flooding and tornadic thunderstorms in the central U.S. and is expected bring severe weather to the U.S. Mid-Atlantic region. At NASA's Goddard Space Flight Center in Greenbelt, Maryland, data from NOAA's GOES-East satellite were used to create images and an animation of the movement of the powerful storm. On April 30, the Moderate Resolution Imaging Spectroradiometer, or MODIS, instrument aboard NASA's Aqua satellite captured a visible image of the storms moving over eastern Texas and Louisiana. Tornadoes in eastern Texas killed four people. The system generated heavy rainfall and caused additional fatalities and damages in Arkansas, Missouri, Mississippi, Alabama and Tennessee. On Monday, May 1, NOAA's National Weather Service noted, "Major to record flooding continues over portions of the central U.S. Severe thunderstorms are possible from the Mid-Atlantic to the northeastern U.S. "Major to record flooding will continue over portions of eastern Oklahoma, northern Arkansas, Missouri, Illinois and Indiana. Rivers will gradually recede over the next several days. Additional strong to severe thunderstorms will be possible Monday afternoon and evening over portions of the Mid-Atlantic and Northeast U.S. Damaging winds, large hail, and isolated tornadoes will be possible." Image caption: On May 1, 2017, at 10:37 a.m. EDT (1437 UTC) NOAA's GOES-East satellite captured this visible image of the storm system centered over Iowa with an associated cold front that stretches into the Gulf of Mexico. Credits: NASA/NOAA GOES Project NASA image use policy. NASA Goddard Space Flight Center enables NASA’s mission through four scientific endeavors: Earth Science, Heliophysics, Solar System Exploration, and Astrophysics. Goddard plays a leading role in NASA’s accomplishments by contributing compelling scientific knowledge to advance the Agency’s mission. Follow us on Twitter Like us on Facebook Find us on Instagram

Analysis of Multi-Flight Common Routes for Traffic Flow Management

NASA Technical Reports Server (NTRS)

Sheth, Kapil; Clymer, Alexis; Morando, Alex; Shih, Fu-Tai

2016-01-01

When severe convective weather requires rerouting aircraft, FAA traffic managers employ severe weather avoidance plans (e.g., Playbook routes, Coded Departure Routes, etc.) These routes provide pilots with safe paths around weather-affected regions, and provide controllers with predictable, and often well-established flight plans. However, they often introduce large deviations to the nominal flight plans, which may not be necessary as weather conditions change. If and when the imposed traffic management initiatives (TMIs) become stale, updated shorter path flight trajectories may be found en route, providing significant time-savings to the affected flights. Multiple Flight Common Routes (MFCR) is a concept that allows multiple flights that are within a specified proximity or region, to receive updated shorter flight plans in an operationally efficient manner. MFCR is believed to provide benefits to the National Airspace System (NAS) by allowing traffic managers to update several flight plans of en route aircraft simultaneously, reducing operational workload within the TMUs of all affected ARTCCs. This paper will explore some aspects of the MFCR concept by analyzing multiple flights that have been selected for rerouting by the NAS Constraint Evaluation and Notification Tool (NASCENT). Various methods of grouping aircraft with common or similar routes will be presented, along with a comparison of the efficacy of these methods.

CALIOP-based Biomass Burning Smoke Plume Injection Height

NASA Astrophysics Data System (ADS)

Soja, A. J.; Choi, H. D.; Fairlie, T. D.; Pouliot, G.; Baker, K. R.; Winker, D. M.; Trepte, C. R.; Szykman, J.

2017-12-01

Carbon and aerosols are cycled between terrestrial and atmosphere environments during fire events, and these emissions have strong feedbacks to near-field weather, air quality, and longer-term climate systems. Fire severity and burned area are under the control of weather and climate, and fire emissions have the potential to alter numerous land and atmospheric processes that, in turn, feedback to and interact with climate systems (e.g., changes in patterns of precipitation, black/brown carbon deposition on ice/snow, alteration in landscape and atmospheric/cloud albedo). If plume injection height is incorrectly estimated, then the transport and deposition of those emissions will also be incorrect. The heights to which smoke is injected governs short- or long-range transport, which influences surface pollution, cloud interaction (altered albedo), and modifies patterns of precipitation (cloud condensation nuclei). We are working with the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) science team and other stakeholder agencies, primarily the Environmental Protection Agency and regional partners, to generate a biomass burning (BB) plume injection height database using multiple platforms, sensors and models (CALIOP, MODIS, NOAA HMS, Langley Trajectory Model). These data have the capacity to provide enhanced smoke plume injection height parameterization in regional, national and international scientific and air quality models. Statistics that link fire behavior and weather to plume rise are crucial for verifying and enhancing plume rise parameterization in local-, regional- and global-scale models used for air quality, chemical transport and climate. Specifically, we will present: (1) a methodology that links BB injection height and CALIOP air parcels to specific fires; (2) the daily evolution of smoke plumes for specific fires; (3) plumes transport and deposited on the Greenland Ice Sheet; and (4) compare CALIOP-derived smoke plume injection to CMAQ modeled smoke plume injection. These results have the potential to provide value to national and international modeling communities (scientific and air quality) and to public land, fire, and air quality management and regulations communities.

Chemical Weathering in the Zambesi Basin: Assesment of the Carbon Dioxyde Comsumption by the Karu Basalt Province

NASA Astrophysics Data System (ADS)

Seyler, P. T.; Viers, J.; Aries, S.; Fournier, P.

2014-12-01

The quantification of the role of weathering in the carbon cycle and its interaction with climate and tectonics at the geological time scale is one of the key questions of the geoscientists. The consumption of atmospheric CO2 by silicate weathering indisputably plays the central role in the long term carbon budget and consequently on mean global climate. Through the composition of major elements in river waters, CO2 consumption by the alteration of continental rocks can be estimated. The aim of this study is to estimate of the chemical weathering rate of the Zambesi basin and the impact of Karoo basalt province on chemical atmospheric consumption, evaluated from a database of major elements. The Karroo basalts outcrop erupted around 183 +/2 2 106 take place in the Upper and the Middle Zambezi, covering a surface of 9600 km2. The Zambesi Basin, located between 8° and 20° south latitude and between 16.5 and 36 east longitude, is the fourth largest in Africa. The catchment has a total area of some 1,281,000 km2, the mean annual temperature is 19,3°C and the annual rainfall varies from nearly 2 000 mm to 600 mm. During the sampling period, the annual runoff at Victoria Fall gauging Station ranged between 50 to 2000 m3/s ie 6.9 to 0.6 l/s/km2. The consumption rate of atmospheric CO2 associated with the chemical weathering was calculated from riverine HCO3- concentrations. During the weathering of volcanic rocks, all dissolved carbonates originate from atmospheric/sil CO2. Values of CO2 consumption rates are relatively high, about 0.024 1012 mol/yr, and are comparable to Deccan Traps consumption rates.

Characteristics of ageostrophic flow in the vicinity of a severe weather outbreak - AVE-SESAME I

NASA Technical Reports Server (NTRS)

Arnold, J. E.

1982-01-01

GOES satellite data was used to examine the ageostrophic flow in the vicinity of severe weather outbreaks along the Red River between Texas and Oklahoma in April 1979. The observations were part of the NASA AVE-SESAME I data on atmospheric states close to severe weather conditions. The Barnes Objective Analysis Technique was employed to analyze the data on a 100 km grid. The ageostrophic wind was defined on a regional scale from satellite data on different levels of cloud wind vectors, with a height change signalling a short-wave system in a long-wave trough. The percentage of deviation of the subgeostrophic winds from the geostrophic wind was calculated, and maximum departure corresponded with the region of greatest storm development. Time cross sections of additions to the ageostrophic flow were made as a function of pressure at 100 mb intervals from 900-100 mb. The ageostrophic acceleration was consistently twice the geostrophic acceleration.

Observation of acoustic-gravity waves in the upper atmosphere during severe storm activity

NASA Technical Reports Server (NTRS)

Hung, R. J.

1975-01-01

A nine-element continuum wave spectrum, high-frequency, Doppler sounder array has been used to detect upper atmospheric wave-like disturbances during periods with severe weather activity, particularly severe thunderstorms and tornadoes. Five events of severe weather activity, including extreme tornado outbreak of April 3, 1974, were chosen for the present study. The analysis of Doppler records shows that both infrasonic waves and gravity waves were excited when severe storms appeared in the north Alabama area. Primarily, in the case of tornado activity, S-shaped Doppler fluctuations or Doppler fold-backs are observed, while quasi-sinusoidal fluctuations are more common in the case of thunderstorm activity. A criterion for the production of Doppler fold-backs is derived and compared with possible tornado conditions.

Severe Storm Identification with Satellite Microwave Radiometry: An Initial Investigation with Nimbus-7 SMMR Data.

NASA Astrophysics Data System (ADS)

Spencer, Roy W.; Howland, Michael R.; Santek, David A.

1987-06-01

In an attempt to determine the feasibility of detecting and monitoring severe weather with future satellite passive microwave observations, the severe weather characteristics of convective storms as observed by the Nimbus 7 Scanning Multichannel Microwave Radiometer (SMMR) are investigated. Low 37 GHz brightness temperatures (due to scattering of upwelling radiation by precipitation size ice) were related to the occurrence of severe weather (large hail, strong winds or wind damage, tornados and funnel clouds) within one hour of the satellite observation time. During 1979 and 1980 over the study area within the United States, there were 263 storms that had cold 37 GHz signatures. Of these storms, 15 percent were reported as severe. The relative number of storms falling in hail, wind, or tornadic categories did not differ from those expected climatologically. Critical Success Indices (CSIs) of 0.32, 0.48 and 0.38 were achieved for the low brightness temperature thresholding of severe versus nonsevere storms during 1979, 1980 and the two years combined, respectively. The preliminary indication is that a future geostationary passive microwave imaging capability at 37 GHz (or possibly higher frequencies), with sufficient spatial and temporal resolution, would facilitate the detection and monitoring of severe convective storms. This capability would provide a useful complement to radar, especially over most of the globe which is not covered by radar.

Can we predict seasonal changes in high impact weather in the United States?

NASA Astrophysics Data System (ADS)

Jung, Eunsil; Kirtman, Ben P.

2016-07-01

Severe convective storms cause catastrophic losses each year in the United States, suggesting that any predictive capability is of great societal benefit. While it is known that El Niño and the Southern Oscillation (ENSO) influence high impact weather events, such as a tornado activity and severe storms, in the US during early spring, this study highlights that the influence of ENSO on US severe storm characteristics is weak during May-July. Instead, warm water in the Gulf of Mexico is a potential predictor for moist instability, which is an important factor in influencing the storm characteristics in the US during May-July.

Road Risk Modeling and Cloud-Aided Safety-Based Route Planning.

PubMed

Li, Zhaojian; Kolmanovsky, Ilya; Atkins, Ella; Lu, Jianbo; Filev, Dimitar P; Michelini, John

2016-11-01

This paper presents a safety-based route planner that exploits vehicle-to-cloud-to-vehicle (V2C2V) connectivity. Time and road risk index (RRI) are considered as metrics to be balanced based on user preference. To evaluate road segment risk, a road and accident database from the highway safety information system is mined with a hybrid neural network model to predict RRI. Real-time factors such as time of day, day of the week, and weather are included as correction factors to the static RRI prediction. With real-time RRI and expected travel time, route planning is formulated as a multiobjective network flow problem and further reduced to a mixed-integer programming problem. A V2C2V implementation of our safety-based route planning approach is proposed to facilitate access to real-time information and computing resources. A real-world case study, route planning through the city of Columbus, Ohio, is presented. Several scenarios illustrate how the "best" route can be adjusted to favor time versus safety metrics.

Road Lane Detection Robust to Shadows Based on a Fuzzy System Using a Visible Light Camera Sensor.

PubMed

Hoang, Toan Minh; Baek, Na Rae; Cho, Se Woon; Kim, Ki Wan; Park, Kang Ryoung

2017-10-28

Recently, autonomous vehicles, particularly self-driving cars, have received significant attention owing to rapid advancements in sensor and computation technologies. In addition to traffic sign recognition, road lane detection is one of the most important factors used in lane departure warning systems and autonomous vehicles for maintaining the safety of semi-autonomous and fully autonomous systems. Unlike traffic signs, road lanes are easily damaged by both internal and external factors such as road quality, occlusion (traffic on the road), weather conditions, and illumination (shadows from objects such as cars, trees, and buildings). Obtaining clear road lane markings for recognition processing is a difficult challenge. Therefore, we propose a method to overcome various illumination problems, particularly severe shadows, by using fuzzy system and line segment detector algorithms to obtain better results for detecting road lanes by a visible light camera sensor. Experimental results from three open databases, Caltech dataset, Santiago Lanes dataset (SLD), and Road Marking dataset, showed that our method outperformed conventional lane detection methods.

Automatic road sign detecion and classification based on support vector machines and HOG descriptos

NASA Astrophysics Data System (ADS)

Adam, A.; Ioannidis, C.

2014-05-01

This paper examines the detection and classification of road signs in color-images acquired by a low cost camera mounted on a moving vehicle. A new method for the detection and classification of road signs is proposed based on color based detection, in order to locate regions of interest. Then, a circular Hough transform is applied to complete detection taking advantage of the shape properties of the road signs. The regions of interest are finally represented using HOG descriptors and are fed into trained Support Vector Machines (SVMs) in order to be recognized. For the training procedure, a database with several training examples depicting Greek road sings has been developed. Many experiments have been conducted and are presented, to measure the efficiency of the proposed methodology especially under adverse weather conditions and poor illumination. For the experiments training datasets consisting of different number of examples were used and the results are presented, along with some possible extensions of this work.

Applied Meteorology Unit (AMU) Quarterly Report Fourth Quarter FY-13

NASA Technical Reports Server (NTRS)

Bauman, William; Crawford, Winifred; Watson, Leela; Shafer, Jaclyn; Huddleston, Lisa

2013-01-01

Ms. Shafer completed the task to determine relationships between pressure gradients and peak winds at Vandenberg Air Force Base (VAFB), and began developing a climatology for the VAFB wind towers; Dr. Huddleston completed the task to develop a tool to help forecast the time of the first lightning strike of the day in the Kennedy Space Center (KSC)/Cape Canaveral Air Force Station (CCAFS) area; Dr. Bauman completed work on a severe weather forecast tool focused on the Eastern Range (ER), and also developed upper-winds analysis tools for VAFB and Wallops Fl ight Facility (WFF); Ms. Crawford processed and displayed radar data in the software she will use to create a dual-Doppler analysis over the east-central Florida and KSC/CCAFS areas; Mr. Decker completed developing a wind pairs database for the Launch Services Program to use when evaluating upper-level winds for launch vehicles; Dr. Watson continued work to assimilate observational data into the high-resolution model configurations she created for WFF and the ER.

Vibrating-Wire, Supercooled Liquid Water Content Sensor Calibration and Characterization Progress

NASA Technical Reports Server (NTRS)

King, Michael C.; Bognar, John A.; Guest, Daniel; Bunt, Fred

2016-01-01

NASA conducted a winter 2015 field campaign using weather balloons at the NASA Glenn Research Center to generate a validation database for the NASA Icing Remote Sensing System. The weather balloons carried a specialized, disposable, vibrating-wire sensor to determine supercooled liquid water content aloft. Significant progress has been made to calibrate and characterize these sensors. Calibration testing of the vibrating-wire sensors was carried out in a specially developed, low-speed, icing wind tunnel, and the results were analyzed. The sensor ice accretion behavior was also documented and analyzed. Finally, post-campaign evaluation of the balloon soundings revealed a gradual drift in the sensor data with increasing altitude. This behavior was analyzed and a method to correct for the drift in the data was developed.

National Airspace System Delay Estimation Using Weather Weighted Traffic Counts

NASA Technical Reports Server (NTRS)

Chatterji, Gano B.; Sridhar, Banavar

2004-01-01

Assessment of National Airspace System performance, which is usually measured in terms of delays resulting from the application of traffic flow management initiatives in response to weather conditions, volume, equipment outages and runway conditions, is needed both for guiding flow control decisions during the day of operations and for post operations analysis. Comparison of the actual delay, resulting from the traffic flow management initiatives, with the expected delay, based on traffic demand and other conditions, provides the assessment of the National Airspace System performance. This paper provides a method for estimating delay using the expected traffic demand and weather. In order to identify the cause of delays, 517 days of National Airspace System delay data reported by the Federal Aviation Administration s Operations Network were analyzed. This analysis shows that weather is the most important causal factor for delays followed by equipment and runway delays. Guided by these results, the concept of weather weighted traffic counts as a measure of system delay is described. Examples are given to show the variation of these counts as a function of time of the day. The various datasets, consisting of aircraft position data, enroute severe weather data, surface wind speed and visibility data, reported delay data and number of aircraft handled by the Centers data, and their sources are described. The procedure for selecting reference days on which traffic was minimally impacted by weather is described. Different traffic demand on each reference day of the week, determined by analysis of 42 days of traffic and delay data, was used as the expected traffic demand for each day of the week. Next, the method for computing the weather weighted traffic counts using the expected traffic demand, derived from reference days, and the expanded regions around severe weather cells is discussed. It is shown via a numerical example that this approach improves the dynamic range of the weather weighted traffic counts considerably. Time histories of these new weather weighted traffic counts are used for synthesizing two statistical features, six histogram features and six time domain features. In addition to these enroute weather features, two surface weather features of number of major airports in the United States with high mean winds and low mean visibility are also described. A least squares procedure for establishing a functional relation between the features, using combinations of these features, and system delays is explored using 36 days of data. Best correlations between the estimated delays using the functional relation and the actual delays provided by the Operations Network are obtained with two different combinations of features: 1) six time domain features of weather weighted traffic counts plus two surface weather features, and 2) six histogram features and mean of weather weighted traffic counts along with the two surface weather features. Correlation coefficient values of 0.73 and 0.83 were found in these two instances.

Space-time clustering analysis of wildfires: The influence of dataset characteristics, fire prevention policy decisions, weather and climate.

PubMed

Parente, Joana; Pereira, Mário G; Tonini, Marj

2016-07-15

The present study focuses on the dependence of the space-time permutation scan statistics (STPSS) (1) on the input database's characteristics and (2) on the use of this methodology to assess changes on the fire regime due to different type of climate and fire management activities. Based on the very strong relationship between weather and the fire incidence in Portugal, the detected clusters will be interpreted in terms of the atmospheric conditions. Apart from being the country most affected by the fires in the European context, Portugal meets all the conditions required to carry out this study, namely: (i) two long and comprehensive official datasets, i.e. the Portuguese Rural Fire Database (PRFD) and the National Mapping Burnt Areas (NMBA), respectively based on ground and satellite measurements; (ii) the two types of climate (Csb in the north and Csa in the south) that characterizes the Mediterranean basin regions most affected by the fires also divide the mainland Portuguese area; and, (iii) the national plan for the defence of forest against fires was approved a decade ago and it is now reasonable to assess its impacts. Results confirmed (1) the influence of the dataset's characteristics on the detected clusters, (2) the existence of two different fire regimes in the country promoted by the different types of climate, (3) the positive impacts of the fire prevention policy decisions and (4) the ability of the STPSS to correctly identify clusters, regarding their number, location, and space-time size in spite of eventual space and/or time splits of the datasets. Finally, the role of the weather on days when clustered fires were active was confirmed for the classes of small, medium and large fires. Copyright © 2016 Elsevier B.V. All rights reserved.

Advancing the LSST Operations Simulator

NASA Astrophysics Data System (ADS)

Saha, Abhijit; Ridgway, S. T.; Cook, K. H.; Delgado, F.; Chandrasekharan, S.; Petry, C. E.; Operations Simulator Group

2013-01-01

The Operations Simulator for the Large Synoptic Survey Telescope (LSST; http://lsst.org) allows the planning of LSST observations that obey explicit science driven observing specifications, patterns, schema, and priorities, while optimizing against the constraints placed by design-specific opto-mechanical system performance of the telescope facility, site specific conditions (including weather and seeing), as well as additional scheduled and unscheduled downtime. A simulation run records the characteristics of all observations (e.g., epoch, sky position, seeing, sky brightness) in a MySQL database, which can be queried for any desired purpose. Derivative information digests of the observing history database are made with an analysis package called Simulation Survey Tools for Analysis and Reporting (SSTAR). Merit functions and metrics have been designed to examine how suitable a specific simulation run is for several different science applications. This poster reports recent work which has focussed on an architectural restructuring of the code that will allow us to a) use "look-ahead" strategies that avoid cadence sequences that cannot be completed due to observing constraints; and b) examine alternate optimization strategies, so that the most efficient scheduling algorithm(s) can be identified and used: even few-percent efficiency gains will create substantive scientific opportunity. The enhanced simulator will be used to assess the feasibility of desired observing cadences, study the impact of changing science program priorities, and assist with performance margin investigations of the LSST system.

MesoNAM Verification Phase II

NASA Technical Reports Server (NTRS)

Watson, Leela R.

2011-01-01

The 45th Weather Squadron Launch Weather Officers use the 12-km resolution North American Mesoscale model (MesoNAM) forecasts to support launch weather operations. In Phase I, the performance of the model at KSC/CCAFS was measured objectively by conducting a detailed statistical analysis of model output compared to observed values. The objective analysis compared the MesoNAM forecast winds, temperature, and dew point to the observed values from the sensors in the KSC/CCAFS wind tower network. In Phase II, the AMU modified the current tool by adding an additional 15 months of model output to the database and recalculating the verification statistics. The bias, standard deviation of bias, Root Mean Square Error, and Hypothesis test for bias were calculated to verify the performance of the model. The results indicated that the accuracy decreased as the forecast progressed, there was a diurnal signal in temperature with a cool bias during the late night and a warm bias during the afternoon, and there was a diurnal signal in dewpoint temperature with a low bias during the afternoon and a high bias during the late night.

Development of an Irrigation Scheduling Tool for the High Plains Region

NASA Astrophysics Data System (ADS)

Shulski, M.; Hubbard, K. G.; You, J.

2009-12-01

The High Plains Regional Climate Center (HPRCC) at the University of Nebraska is one of NOAA’s six regional climate centers in the U.S. Primary objectives of the HPRCC are to conduct applied climate research, engage in climate education and outreach, and increase the use and availability of climate information by developing value-added products. Scientists at the center are engaged in utilizing regional weather data to develop tools that can be used directly by area stakeholders, particularly for agricultural sectors. A new study is proposed that will combine NOAA products (short-term forecasts and seasonal outlooks of temperature and precipitation) with existing capabilities to construct an irrigation scheduling tool that can be used by producers in the region. This tool will make use of weather observations from the regional mesonet (specifically the AWDN, Automated Weather Data Network) and the nation-wide relational database and web portal (ACIS, Applied Climate Information System). The primary benefit to stakeholders will be a more efficient use of water and energy resources owing to the reduction of uncertainty in the timing of irrigation.

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

USGS Publications Warehouse

Bera, Maitreyee; Ortel, Terry W.

2018-01-12

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

Kameleon Live: An Interactive Cloud Based Analysis and Visualization Platform for Space Weather Researchers

NASA Astrophysics Data System (ADS)

Pembroke, A. D.; Colbert, J. A.

2015-12-01

The Community Coordinated Modeling Center (CCMC) provides hosting for many of the simulations used by the space weather community of scientists, educators, and forecasters. CCMC users may submit model runs through the Runs on Request system, which produces static visualizations of model output in the browser, while further analysis may be performed off-line via Kameleon, CCMC's cross-language access and interpolation library. Off-line analysis may be suitable for power-users, but storage and coding requirements present a barrier to entry for non-experts. Moreover, a lack of a consistent framework for analysis hinders reproducibility of scientific findings. To that end, we have developed Kameleon Live, a cloud based interactive analysis and visualization platform. Kameleon Live allows users to create scientific studies built around selected runs from the Runs on Request database, perform analysis on those runs, collaborate with other users, and disseminate their findings among the space weather community. In addition to showcasing these novel collaborative analysis features, we invite feedback from CCMC users as we seek to advance and improve on the new platform.

[Perceived pain and weather changes in rheumatic patients].

PubMed

Miranda, L Cunha; Parente, M; Silva, C; Clemente-Coelho, P; Santos, H; Cortes, S; Medeiros, D; Ribeiro, J Saraiva; Barcelos, F; Sousa, M; Miguel, C; Figueiredo, R; Mediavilla, M; Simões, E; Silva, M; Patto, J Vaz; Madeira, H; Ferreira, J; Micaelo, M; Leitão, R; Las, V; Faustino, A; Teixeira, A

2007-01-01

Rheumatic patients with chronic pain describe in a vivid way the influence of climate on pain and disease activity. Several studies seem to confirm this association. To evaluate and compare in a population of rheumatic patients the perceived influence of weather changes on pain and disease activity This is a retrospective cross-sectional study. For three weeks an assisted self-reported questionnaire with nine dimensions and a VAS pain scale was performed on consecutive out-patients in our clinic. 955 patients 787 female 168 male mean age 57.9 years with several rheumatologic diagnosis were evaluated. Overall 70 of the patients believed that the weather influenced their disease and 40 believed that the influence was high. Morning stiffness was influenced in 54 high influenced in 34 . Autumn and Winter were the most influential periods as well as humidity 67 and low temperatures 59 . In our study as well as in literature we found that a high percentage of patients 70 perceived that weather conditions influenced their pain and disease. Fibromyalgia patients seemed to be strongly influenced by weather changes. Our study confirms that patients perception on the influence of climate on pain and therefore their disease is an important clinical factor and it should be considered when evaluating rheumatic patients.

Analysis of Multi-Flight Common Routes for Traffic Flow Management

NASA Technical Reports Server (NTRS)

Sheth, Kapil; Clymer, Alexis; Morando, Alex; Shih, Fu-Tai

2016-01-01

This paper presents an approach for creating common weather avoidance reroutes for multiple flights and the associated benefits analysis, which is an extension of the single flight advisories generated using the Dynamic Weather Routes (DWR) concept. These multiple flight advisories are implemented in the National Airspace System (NAS) Constraint Evaluation and Notification Tool (NASCENT), a nation-wide simulation environment to generate time- and fuel-saving alternate routes for flights during severe weather events. These single flight advisories are clustered together in the same Center by considering parameters such as a common return capture fix. The clustering helps propose routes called, Multi-Flight Common Routes (MFCR), that avoid weather and other airspace constraints, and save time and fuel. It is expected that these routes would also provide lower workload for traffic managers and controllers since a common route is found for several flights, and presumably the route clearances would be easier and faster. This study was based on 30-days in 2014 and 2015 each, which had most delays attributed to convective weather. The results indicate that many opportunities exist where individual flight routes can be clustered to fly along a common route to save a significant amount of time and fuel, and potentially reducing the amount of coordination needed.

A review of the effect of traffic and weather characteristics on road safety.

PubMed

Theofilatos, Athanasios; Yannis, George

2014-11-01

Taking into consideration the increasing availability of real-time traffic data and stimulated by the importance of proactive safety management, this paper attempts to provide a review of the effect of traffic and weather characteristics on road safety, identify the gaps and discuss the needs for further research. Despite the existence of generally mixed evidence on the effect of traffic parameters, a few patterns can be observed. For instance, traffic flow seems to have a non-linear relationship with accident rates, even though some studies suggest linear relationship with accidents. On the other hand, increased speed limits have found to have a straightforward positive relationship with accident occurrence. Regarding weather effects, the effect of precipitation is quite consistent and leads generally to increased accident frequency but does not seem to have a consistent effect on severity. The impact of other weather parameters on safety, such as visibility, wind speed and temperature is not found straightforward so far. The increasing use of real-time data not only makes easier to identify the safety impact of traffic and weather characteristics, but most importantly makes possible the identification of their combined effect. The more systematic use of these real-time data may address several of the research gaps identified in this research. Copyright © 2014 Elsevier Ltd. All rights reserved.

The Weather and Ménière's Disease: A Longitudinal Analysis in the UK.

PubMed

Schmidt, Wiebke; Sarran, Christophe; Ronan, Natalie; Barrett, George; Whinney, David J; Fleming, Lora E; Osborne, Nicholas J; Tyrrell, Jessica

2017-02-01

Changes in the weather influence symptom severity in Ménière's disease (MD). MD is an unpredictable condition that significantly impacts on quality of life. It is suggested that fluctuations in the weather, especially atmospheric pressure may influence the symptoms of MD. However, to date, limited research has investigated the impact of the weather on MD. In a longitudinal study, a mobile phone application collected data from 397 individuals (277 females and 120 males with an average age of 50 yr) from the UK reporting consultant-diagnosed MD. Daily symptoms (vertigo, aural fullness, tinnitus, hearing loss, and attack prevalence) and GPS locations were collected; these data were linked with Met Office weather data (including atmospheric pressure, humidity, temperature, visibility, and wind speed). Symptom severity and attack prevalence were reduced on days when atmospheric pressure was higher. When atmospheric pressure was below 1,013 hectopascals, the risk of an attack was 1.30 (95% confidence interval: 1.10, 1.54); when the humidity was above 90%, the risk of an attack was 1.26 (95% confidence interval 1.06, 1.49). This study provides the strongest evidence to date that changes in atmospheric pressure and humidity are associated with symptom exacerbation in MD. Improving our understanding of the role of weather and other environmental triggers in Ménière's may reduce the uncertainty associated with living with this condition, significantly contributing to improved quality of life.

The Weather and Ménière’s Disease: A Longitudinal Analysis in the UK

PubMed Central

Schmidt, Wiebke; Sarran, Christophe; Ronan, Natalie; Barrett, George; Whinney, David J.; Fleming, Lora E.; Osborne, Nicholas J.; Tyrrell, Jessica

2016-01-01

Hypothesis Changes in the weather influence symptom severity in Ménière’s disease (MD). Background MD is an unpredictable condition that significantly impacts on quality of life. It is suggested that fluctuations in the weather, especially atmospheric pressure may influence the symptoms of MD. However, to date, limited research has investigated the impact of the weather on MD. Methods In a longitudinal study, a mobile phone application collected data from 397 individuals (277 females and 120 males with an average age of 50 yr) from the UK reporting consultant-diagnosed MD. Daily symptoms (vertigo, aural fullness, tinnitus, hearing loss, and attack prevalence) and GPS locations were collected; these data were linked with Met Office weather data (including atmospheric pressure, humidity, temperature, visibility, and wind speed). Results Symptom severity and attack prevalence were reduced on days when atmospheric pressure was higher. When atmospheric pressure was below 1,013 hectopascals, the risk of an attack was 1.30 (95% confidence interval: 1.10, 1.54); when the humidity was above 90%, the risk of an attack was 1.26 (95% confidence interval 1.06, 1.49). Conclusion This study provides the strongest evidence to date that changes in atmospheric pressure and humidity are associated with symptom exacerbation in MD. Improving our understanding of the role of weather and other environmental triggers in Ménière’s may reduce the uncertainty associated with living with this condition, significantly contributing to improved quality of life. PMID:27861300

Seasonality in trauma admissions - Are daylight and weather variables better predictors than general cyclic effects?

PubMed

Røislien, Jo; Søvik, Signe; Eken, Torsten

2018-01-01

Trauma is a leading global cause of death, and predicting the burden of trauma admissions is vital for good planning of trauma care. Seasonality in trauma admissions has been found in several studies. Seasonal fluctuations in daylight hours, temperature and weather affect social and cultural practices but also individual neuroendocrine rhythms that may ultimately modify behaviour and potentially predispose to trauma. The aim of the present study was to explore to what extent the observed seasonality in daily trauma admissions could be explained by changes in daylight and weather variables throughout the year. Retrospective registry study on trauma admissions in the 10-year period 2001-2010 at Oslo University Hospital, Ullevål, Norway, where the amount of daylight varies from less than 6 hours to almost 19 hours per day throughout the year. Daily number of admissions was analysed by fitting non-linear Poisson time series regression models, simultaneously adjusting for several layers of temporal patterns, including a non-linear long-term trend and both seasonal and weekly cyclic effects. Five daylight and weather variables were explored, including hours of daylight and amount of precipitation. Models were compared using Akaike's Information Criterion (AIC). A regression model including daylight and weather variables significantly outperformed a traditional seasonality model in terms of AIC. A cyclic week effect was significant in all models. Daylight and weather variables are better predictors of seasonality in daily trauma admissions than mere information on day-of-year.

Ubiquitous Geo-Sensing for Context-Aware Analysis: Exploring Relationships between Environmental and Human Dynamics

PubMed Central

Sagl, Günther; Blaschke, Thomas; Beinat, Euro; Resch, Bernd

2012-01-01

Ubiquitous geo-sensing enables context-aware analyses of physical and social phenomena, i.e., analyzing one phenomenon in the context of another. Although such context-aware analysis can potentially enable a more holistic understanding of spatio-temporal processes, it is rarely documented in the scientific literature yet. In this paper we analyzed the collective human behavior in the context of the weather. We therefore explored the complex relationships between these two spatio-temporal phenomena to provide novel insights into the dynamics of urban systems. Aggregated mobile phone data, which served as a proxy for collective human behavior, was linked with the weather data from climate stations in the case study area, the city of Udine, Northern Italy. To identify and characterize potential patterns within the weather-human relationships, we developed a hybrid approach which integrates several spatio-temporal statistical analysis methods. Thereby we show that explanatory factor analysis, when applied to a number of meteorological variables, can be used to differentiate between normal and adverse weather conditions. Further, we measured the strength of the relationship between the ‘global’ adverse weather conditions and the spatially explicit effective variations in user-generated mobile network traffic for three distinct periods using the Maximal Information Coefficient (MIC). The analyses result in three spatially referenced maps of MICs which reveal interesting insights into collective human dynamics in the context of weather, but also initiate several new scientific challenges. PMID:23012571

Games and Simulations for Climate, Weather and Earth Science Education

NASA Astrophysics Data System (ADS)

Russell, R. M.

2013-12-01

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

GOES-S Mission Science Briefing

NASA Image and Video Library

2018-02-27

In the Kennedy Space Center's Press Site auditorium, Louis Uccellini, director of the National Weather Service for NOAA, speaks to members of the media at a mission briefing on National Oceanic and Atmospheric Administration's, or NOAA's, Geostationary Operational Environmental Satellite, or GOES-S. The spacecraft is the second satellite in a series of next-generation NOAA weather satellites. It will launch to a geostationary position over the U.S. to provide images of storms and help predict weather forecasts, severe weather outlooks, watches, warnings, lightning conditions and longer-term forecasting. GOES-S is slated to lift off at 5:02 p.m. EST on March 1, 2018 aboard a United Launch Alliance Atlas V rocket

GOES-S NASA Social

NASA Image and Video Library

2018-02-28

Joe Pica, director of the Office of Observations for the National Oceanic and Atmospheric Administration's, or NOAA’s, National Weather Service, speaks to members of social media in the Kennedy Space Center’s Press Site auditorium. The briefing focused on the Geostationary Operational Environmental Satellite, or GOES-S, the second spacecraft in a series of next-generation NOAA weather satellites. It will launch to a geostationary position over the U.S. to provide images of storms and help predict weather forecasts, severe weather outlooks, watches, warnings, lightning conditions and longer-term forecasting. GOES-S is slated to lift off at 5:02 p.m. EST on March 1, 2018 aboard a United Launch Alliance Atlas V rocket.

Applications of NASA and NOAA Satellite Observations by NASA's Short-term Prediction Research and Transition (SPoRT) Center in Response to Natural Disasters

NASA Technical Reports Server (NTRS)

Molthan, Andrew L.; Burks, Jason E.; McGrath, Kevin M.; Jedlovec, Gary J.

2012-01-01

NASA s Short-term Prediction Research and Transition (SPoRT) Center supports the transition of unique NASA and NOAA research activities to the operational weather forecasting community. SPoRT emphasizes real-time analysis and prediction out to 48 hours. SPoRT partners with NOAA s National Weather Service (NWS) Weather Forecast Offices (WFOs) and National Centers to improve current products, demonstrate future satellite capabilities and explore new data assimilation techniques. Recently, the SPoRT Center has been involved in several activities related to disaster response, in collaboration with NOAA s National Weather Service, NASA s Applied Sciences Disasters Program, and other partners.

Games and Simulations for Climate, Weather and Earth Science Education

NASA Astrophysics Data System (ADS)

Russell, R. M.; Clark, S.

2015-12-01

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

The Research-to-Operations-to-Research Cycle at NOAA's Space Weather Prediction Center

NASA Astrophysics Data System (ADS)

Singer, H. J.

2017-12-01

The provision of actionable space weather products and services by NOAA's Space Weather Prediction Center relies on observations, models and scientific understanding of our dynamic space environment. It also depends on a deep understanding of the systems and capabilities that are vulnerable to space weather, as well as national and international partnerships that bring together resources, skills and applications to support space weather forecasters and customers. While these activities have been evolving over many years, in October 2015, with the release of the National Space Weather Strategy and National Space Weather Action Plan (NSWAP) by National Science and Technology Council in the Executive Office of the President, there is a new coordinated focus on ensuring the Nation is prepared to respond to and recover from severe space weather storms. One activity highlighted in the NSWAP is the Operations to Research (O2R) and Research to Operations (R2O) process. In this presentation we will focus on current R2O and O2R activities that advance our ability to serve those affected by space weather and give a vision for future programs. We will also provide examples of recent research results that lead to improved operational capabilities, lessons learned in the transition of research to operations, and challenges for both the science and operations communities.

Intercontinental difference in extreme weather events for the Northern Hemisphere over the past half century

NASA Astrophysics Data System (ADS)

Chen, A.; Tan, J.; Piao, S.

2014-12-01

Weather events that are located in the tails of a weather distribution are called weather extremes. Weather extremes, including severe drought, flooding, heat and cold waves, usually can cause greatest damage to human lives and properties, and have profound implication on ecosystem productivity and carbon cycles. There is mounting evidence suggests that the frequency of temperature and hydrological weather extremes have steadily increased over the last decades, largely due to the ongoing climate change. On the other hand, the distribution and trend of weather extremes can be regionally heterogeneous, which have not been well understood. Here we investigate the spatial distribution and temporal trend of weather extremes in the Northern Hemisphere (NH) over the past half century (1961-2010), with emphasis on the intercontinental comparisons. Our results suggest that warming extremes have increased significantly in East Asia and West Europe; while coldness extremes have decreased globally. Heavy precipitation extremes significantly increased in eastern Northern America, boreal Eurasia, and some parts of China; while drought events showed an increasing trend in northern China-southern Mongolia and some parts of western United States. Our results highlight the regional difference in the trend of weather extremes, which need to be incorporated in the mitigation measures.

Analysis of Convective Weather Impact on Pre-Departure Routing of Flights from Fort Worth Center to New York Center

NASA Technical Reports Server (NTRS)

Arneson, Heather; Bombelli, Alessandro; Segarra-Torne, Adria; Tse, Elmer

2017-01-01

In response to severe weather conditions, Traffic Managers specify flow constraints and reroutes to route air traffic around affected regions of airspace. Providing analysis and recommendations of available reroute options and associated airspace capacities would assist Traffic Managers in making more efficient decisions in response to convective weather. These recommendations can be developed by examining historical data to determine which previous reroute options were used in similar weather and traffic conditions. This paper describes the initial steps and methodology used towards this goal. The focus of this work is flights departing from Fort Worth Center destined for New York Center. Dominant routing structures used in the absence of convective weather are identified. A method to extract relevant features from the large volume of weather data available to quantify the impact of convective weather on this routing structure over a given time range is presented. Finally, a method of estimating flow rate capacity along commonly used routes during convective weather events is described. Results show that the flow rates drop exponentially as a function of the values of the proposed feature and that convective weather on the final third of the route was found to have a greater impact on the flow rate restriction than other portions of the route.

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.

Convection Weather Detection by General Aviation Pilots with Convectional and Data-Linked Graphical Weather Information Sources

NASA Technical Reports Server (NTRS)

Chamberlain, James P.; Latorella, Kara A.

2001-01-01

This study compares how well general aviation (GA) pilots detect convective weather in flight with different weather information sources. A flight test was conducted in which GA pilot test subjects were given different in-flight weather information cues and flown toward convective weather of moderate or greater intensity. The test subjects were not actually flying the aircraft, but were given pilot tasks representative of the workload and position awareness requirements of the en route portion of a cross country GA flight. On each flight, one test subject received weather cues typical of a flight in visual meteorological conditions (VMC), another received cues typical of flight in instrument meteorological conditions (IMC), and a third received cues typical of flight in IMC but augmented with a graphical weather information system (GWIS). The GWIS provided the subject with near real time data-linked weather products, including a weather radar mosaic superimposed on a moving map with a symbol depicting the aircraft's present position and direction of track. At several points during each flight, the test subjects completed short questionnaires which included items addressing their weather situation awareness and flight decisions. In particular, test subjects were asked to identify the location of the nearest convective cells. After the point of nearest approach to convective weather, the test subjects were asked to draw the location of convective weather on an aeronautical chart, along with the aircraft's present position. This paper reports preliminary results on how accurately test subjects provided with these different weather sources could identify the nearest cell of moderate or greater intensity along their route of flight. Additional flight tests are currently being conducted to complete the data set.

Bringing Space Weather Down to Earth

NASA Astrophysics Data System (ADS)

Reiff, P. H.; Sumners, C.

2005-05-01

Most of the public has no idea what Space Weather is, but a number of innovative programs, web sites, magazine articles, TV shows and planetarium shows have taken space weather from an unknown quantity to a much more visible field. This paper reviews new developments, including the new Space Weather journal, the very popular spaceweather.com website, new immersive planetarium shows that can go "on the road", and well-publicized Sun-Earth Day activities. Real-time data and reasonably accurate spaceweather forecasts are available from several websites, with many subscribers. Even the renaissance of amateur radio because of Homeland Security brings a new generation of learners to wonder what is going on in the Sun today. The NSF Center for Integrated Space Weather Modeling has a dedicated team to reach both the public and a greater diversity of new scientists.

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…

Total Lightning as an Indicator of Mesocyclone Behavior

NASA Technical Reports Server (NTRS)

Stough, Sarah M.; Carey, Lawrence D.; Schultz, Christopher J.

2014-01-01

Apparent relationship between total lightning (in-cloud and cloud to ground) and severe weather suggests its operational utility. Goal of fusion of total lightning with proven tools (i.e., radar lightning algorithms. Preliminary work here investigates circulation from Weather Suveilance Radar- 1988 Doppler (WSR-88D) coupled with total lightning data from Lightning Mapping Arrays.

Hands-On Learning Modules for Interdisciplinary Environments: An Example with a Focus on Weather Radar Applications

ERIC Educational Resources Information Center

Chilson, P. B.; Yeary, M. B.

2012-01-01

Learning modules provide an effective means of encouraging cognition and active learning. This paper discusses several such modules that have been developed within a course on weather radar applications intended for students from Electrical Engineering and Meteorology. The modules were designed both to promote interdisciplinary exchange between…

KSC-01pp0873

NASA Image and Video Library

2001-04-16

Workers at Astrotech, Titusville, Fla., prepare to open the solar panel on the GOES-M satellite. The GOES-M provides weather imagery and quantitative sounding data used to support weather forecasting, severe storm tracking and meteorological research. The satellite is scheduled to launch July 12 on an Atlas-IIA booster, Centaur upper stage from Cape Canaveral Air Force Station

KSC-01pp0875

NASA Image and Video Library

2001-04-16

Workers at Astrotech, Titusville, Fla., check the solar panel on the GOES-M satellite. The GOES-M provides weather imagery and quantitative sounding data used to support weather forecasting, severe storm tracking and meteorological research. The satellite is scheduled to launch July 12 on an Atlas-IIA booster, Centaur upper stage from Cape Canaveral Air Force Station

KSC01pp0799

NASA Image and Video Library

2001-04-12

Workers at Astrotech, Titusville, Fla., work on the GOES-M satellite. The GOES-M provides weather imagery and quantitative sounding data used to support weather forecasting, severe storm tracking and meteorological research. The satellite is undergoing testing at Astrotech before its scheduled launch July 12 on an Atlas-IIA booster, Centaur upper stage from Cape Canaveral Air Force Station

KSC-01pp0881

NASA Image and Video Library

2001-04-16

At Astrotech, Titusville, Fla., a worker checks components of the GOES-M satellite. The GOES-M provides weather imagery and quantitative sounding data used to support weather forecasting, severe storm tracking and meteorological research. The satellite is scheduled to launch July 12 on an Atlas-IIA booster, Centaur upper stage from Cape Canaveral Air Force Station

Applications of Earth Remote Sensing for Identifying Tornado and Severe Weather Damage

NASA Technical Reports Server (NTRS)

Schultz, Lori; Molthan, Andrew; Burks, Jason E.; Bell, Jordan; McGrath, Kevin; Cole, Tony

2016-01-01

NASA SPoRT (Short-term Prediction Research and Transition Center) provided MODIS (Moderate Resolution Imaging Spectrometer) and ASTER (Advanced Spaceborne Thermal Emission and Reflection Radiometer) imagery to WFOs (Weather Forecast Offices) in Alabama to support April 27th, 2011 damage assessments across the state. SPoRT was awarded a NASA Applied Science: Disasters Feasibility award to investigate the applicability of including remote sensing imagery and derived products into the NOAA/NWS (National Oceanic and Atmospheric Administration/National Weather System) Damage Assessment Toolkit (DAT). Proposal team was awarded the 3-year proposal to implement a web mapping service and associate data feeds from the USGS (U.S. Geological Survey) to provide satellite imagery and derived products directly to the NWS thru the DAT. In the United States, NOAA/NWS is charged with performing damage assessments when storm or tornado damage is suspected after a severe weather event. This has led to the development of the Damage Assessment Toolkit (DAT), an application for smartphones, tablets and web browsers that allows for the collection, geo-location, and aggregation of various damage indicators collected during storm surveys.

Risk of Fall-Related Injury due to Adverse Weather Events, Philadelphia, Pennsylvania, 2006-2011.

PubMed

Gevitz, Kathryn; Madera, Robbie; Newbern, Claire; Lojo, José; Johnson, Caroline C

Following a surge in fall-related visits to local hospital emergency departments (EDs) after a severe ice storm, the Philadelphia Department of Public Health examined the association between inclement winter weather events and fall-related ED visits during a 5-year period. Using a standardized set of keywords, we identified fall-related injuries in ED chief complaint logs submitted as part of Philadelphia Department of Public Health's syndromic surveillance from December 2006 through March 2011. We compared days when falls exceeded the winter fall threshold (ie, "high-fall days") with control days within the same winter season. We then conducted matched case-control analysis to identify weather and patient characteristics related to increased fall-related ED visits. Fifteen high-fall days occurred during winter months in the 5-year period. In multivariable analysis, 18- to 64-year-olds were twice as likely to receive ED care for fall-related injuries on high-fall days than on control days. The crude odds of ED visits occurring from 7:00 am to 10:59 am were 70% higher on high-fall days vs control days. Snow was a predictor of a high-fall day: the adjusted odds of snow before a high-fall day as compared with snow before a control day was 13.4. The association between the number of fall-related ED visits and weather-related fall injuries, age, and timing suggests that many events occurred en route to work in the morning. Promoting work closures or delaying openings after severe winter weather would allow time for better snow or ice removal, and including "fall risk" in winter weather advisories might effectively warn morning commuters. Both strategies could help reduce the number of weather-related fall injuries.

Detecting climate variations and change: New challenges for observing and data management systems

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

Karl, T.R.; Quayle, R.G.; Groisman, P.Ya.

1993-08-01

Several essential aspects of weather observing and the management of weather data related to improving knowledge of climate variations and change in the surface boundary layer and the consequences for socioeconomic and biogeophysical systems, are discussed. The issues include long-term homogeneous time series of routine weather observations; time- and space-scale resolution of datasets derived from the observations; information about observing systems, data collection systems, and data reduction algorithms; and the enhancement of weather observing systems to serve as climate observing systems. Although much has been learned from existing weather networks and methods of data management, the system is far frommore » perfect. Several vital areas have not received adequate attention. Particular improvements are needed in the interaction between network designers and climatologists; operational analyses that focus on detecting and documenting outliers and time-dependent biases within datasets; developing the means to cope with and minimize potential inhomogeneities in weather observing systems; and authoritative documentation of how various aspects of climate have or have not changed. In this last area, close attention must be given to time and space resolution of the data. In many instances the time and space resolution requirements for understanding why the climate changes are not synonymous with understanding how it has changed or varied. This is particularly true within the surface boundary layer. A standard global daily/monthly climate message should also be introduced to supplement current Global Telecommunication System's CLIMAT data. Overall, a call is made for improvements in routine weather observing, data management, and analysis systems. Routine observations have provided (and will continue to provide) most of the information regarding how the climate has changed during the last 100 years affecting where we live, work, and grow our food. 58 refs., 8 figs., 1 tab.« less

Associations between weather conditions and clinical symptoms in patients with hip osteoarthritis: a 2-year cohort study.

PubMed

Dorleijn, Desirée M J; Luijsterburg, Pim A J; Burdorf, Alex; Rozendaal, Rianne M; Verhaar, Jan A N; Bos, Pieter K; Bierma-Zeinstra, Sita M A

2014-04-01

The goal of this study was to assess whether there is an association between ambient weather conditions and patients' clinical symptoms in patients with hip osteoarthritis (OA). The design was a cohort study with a 2-year follow-up and 3-monthly measurements and prospectively collected data on weather variables. The study population consisted of 222 primary care patients with hip OA. Weather variables included temperature, wind speed, total amount of sun hours, precipitation, barometric pressure, and relative humidity. The primary outcomes were severity of hip pain and hip disability as measured with the Western Ontario and McMasters University Osteoarthritis Index (WOMAC) pain and function subscales. Associations between hip pain and hip disability and the weather variables were assessed using crude and multivariate adjusted linear mixed-model analysis for repeated measurements. On the day of questionnaire completion, mean relative humidity was associated with WOMAC pain (estimate 0.1; 95% confidence interval=0.0-0.2; P=.02). Relative humidity contributed < or = 1% to the explained within-patient variance and between-patient variance of the WOMAC pain score. Mean barometric pressure was associated with WOMAC function (estimate 0.1; 95% confidence interval=0.0-0.1; P=.02). Barometric pressure contributed < or = 1% to the explained within-patient variance and between-patient variance of the WOMAC function score. The other weather variables were not associated with the WOMAC pain or function score. Our results support the general opinion of OA patients that barometric pressure and relative humidity influence perceived OA symptoms. However, the contribution of these weather variables (< or = 1%) to the severity of OA symptoms is not considered to be clinically relevant. Copyright © 2014 International Association for the Study of Pain. Published by Elsevier B.V. All rights reserved.

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.

Thunderstorm intensity as determined from satellite data

NASA Technical Reports Server (NTRS)

Adler, R. F.; Fenn, D. D.

1979-01-01

Digital infrared data from SMS 2 obtained on May 6, 1975 are used to study thunderstorm vertical growth rates and cloud top structure in relation to the occurrence of severe weather (tornadoes, hail, and high wind) on the ground. All thunderstorms from South Dakota to Texas along a N-S oriented cold front were monitored for a 4 h period with 5 min interval data. Thunderstorm growth rate, as determined by the rate of blackbody temperature isotherm expansion and minimum cloud top temperature, are shown to be correlated with reports of severe weather on the ground.

A virtual radiation belt observatory: Looking forward to the electronic geophysical year

NASA Astrophysics Data System (ADS)

Baker, D. N.; Green, J. C.; Kroehl, H. W.; Kihn, E.; Virbo Team

During the International Geophysical Year (1957-1958), member countries established many new capabilities pursuing the major IGY objectives of collecting geophysical data as widely as possible and providing free access to these data for all scientists around the globe. A key achievement of the IGY was the establishment of a worldwide system of data centers and physical observatories. The worldwide scientific community has now endorsed and is promoting an electronic Geophysical Year (eGY) initiative. The proposed eGY concept would both commemorate the 50th anniversary of the IGY in 2007-2008 and would provide a forward impetus to geophysics in the 21st century, similar to that provide by the IGY fifty years ago. The eGY concept advocates the establishment of a series of virtual geophysical observatories now being deployed in cyberspace. We are developing the concept of a Virtual Radiation Belt Observatory (ViRBO) that will bring together near-earth particle and field measurements acquired by NASA, NOAA, DoD, DOE, and other spacecraft. We discuss plans to aggregate these measurements into a readily accessible database along with analysis, visualization, and display tools that will make radiation belt information available and useful both to the scientific community and to the user community. We envision that data from the various agencies along with models being developed under the auspices of the National Science Foundation Center for Integrated Space Weather Modeling (CISM) will help us to provide an excellent `climatology' of the radiation belts over the past several decades. In particular, we would plan to use these data to drive physical models of the radiation belts to form a gridded database which would characterize particle and field properties on solar-cycle (11-year) time scales. ViRBO will also provide up-to-date specification of conditions for event analysis and anomaly resolution. We are even examining the possibilities for near-realtime acquisition of data and utilization of CISM-developed forecast tools in order to provide users with advanced space weather capabilities.

Tool for Constructing Data Albums for Significant Weather Events

NASA Astrophysics Data System (ADS)

Kulkarni, A.; Ramachandran, R.; Conover, H.; McEniry, M.; Goodman, H.; Zavodsky, B. T.; Braun, S. A.; Wilson, B. D.

2012-12-01

Case study analysis and climatology studies are common approaches used in Atmospheric Science research. Research based on case studies involves a detailed description of specific weather events using data from different sources, to characterize physical processes in play for a given event. Climatology-based research tends to focus on the representativeness of a given event, by studying the characteristics and distribution of a large number of events. To gather relevant data and information for case studies and climatology analysis is tedious and time consuming; current Earth Science data systems are not suited to assemble multi-instrument, multi mission datasets around specific events. For example, in hurricane science, finding airborne or satellite data relevant to a given storm requires searching through web pages and data archives. Background information related to damages, deaths, and injuries requires extensive online searches for news reports and official storm summaries. We will present a knowledge synthesis engine to create curated "Data Albums" to support case study analysis and climatology studies. The technological challenges in building such a reusable and scalable knowledge synthesis engine are several. First, how to encode domain knowledge in a machine usable form? This knowledge must capture what information and data resources are relevant and the semantic relationships between the various fragments of information and data. Second, how to extract semantic information from various heterogeneous sources including unstructured texts using the encoded knowledge? Finally, how to design a structured database from the encoded knowledge to store all information and to support querying? The structured database must allow both knowledge overviews of an event as well as drill down capability needed for detailed analysis. An application ontology driven framework is being used to design the knowledge synthesis engine. The knowledge synthesis engine is being applied to build a portal for hurricane case studies at the Global Hydrology and Resource Center (GHRC), a NASA Data Center. This portal will auto-generate Data Albums for specific hurricane events, compiling information from distributed resources such as NASA field campaign collections, relevant data sets, storm reports, pictures, videos and other useful sources.

AFTOMS Technology Issues and Alternatives Report

DTIC Science & Technology

1989-12-01

color , resolu- power requirements, physi- tion; memory , processor speed; cal and weather rugged- IAN interfaces, etc,) f,: these ness. display...Telephone and Telegraph 3 CD-I Compact Disk - Interactive CD-ROM Compact Disk-Read Only Memory CGM Computer Graphics Metafile CNWDI Critical Nuclear...Database Management System RFP Request For Proposal 3 RFS Remote File System ROM Read Only Memory 3 S SA-ALC San Antonio Air Logistics Center 3 SAC

Causes of salinization of the Gulf of Taganrog

NASA Astrophysics Data System (ADS)

Matishov, G. G.; Grigorenko, K. S.

2017-11-01

Using the database of automatic hydrometeorological stations, installed in the Don RIver delta and Taganrog Bay seashore, the sources of the anomalois scale water negative surge and salinization of the Azov Sea under conditions of low river flow in 2015-2016 are studied. The new schemes of stratification and advection of salty sea waters in the Don River mouth under different weather conditions, water discharge and levels are given.

Anomalous Lightning Behavior During the 26-27 August 2007 Northern Great Plains Severe Weather Event

NASA Astrophysics Data System (ADS)

Logan, Timothy

2018-02-01

Positive polarity lightning strokes can be useful indicators of thunderstorm behavior. A combination of National Lightning Detection Network and Next Generation Radar retrievals is used to analyze the anomalous positive cloud-to-ground (CG) lightning behavior of a rare, late summer severe weather event that occurred on 26-27 August 2007 in the Northern Great Plains region of the United States and southern Canada. Seven discrete supercells (SC1-SC7) exhibiting frequent and intense lightning were responsible for numerous reports of severe weather (e.g., severe hail and 16 tornadoes) including catastrophic damage to the town of Northwood, North Dakota, caused by SC2. Biomass burning smoke from wildfires in Idaho and Montana was present prior to convective initiation. A positive CG lightning stroke rate of nearly 30 strokes per minute was observed 10 min before the EF4 tornado struck Northwood. SC2 was also responsible for all the reports of tornadoes exceeding an EF2 rating. The strongest peak currents (>200 kA) were observed in SC1-SC4 with SC2 having a maximum value of 280 kA. SC2 dominated the statistics of the line of supercells accounting for 27% of all CG lightning strokes. Positive CG lightning accounted for over 40% of all CG lightning strokes in SC4-SC7 on average, and the maximum exceeded 90% in SC6 and SC7. Increasing positive CG lightning dominance was correlated with an increasing northward gradient of smoke aerosol loading in addition to severe weather being reported before the maximum in positive CG lighting stroke rate (SC5 and SC6). This suggests that a complex combination of synoptic forcing and aerosol perturbation likely led to the observed anomalous positive CG lightning behavior in the supercells.