Objective local weather types with applications on urban air pollution and on mortality with chronicle illnesses

NASA Astrophysics Data System (ADS)

Mika, Janos; Ivady, Anett; Fulop, Andrea; Makra, László

2010-05-01

Synoptic climatology i.e. classification of the endless variability of the everyday weather states according to the pressure configuration and frontal systems relative to the point, or region of interest has long history in meteorology. Its logical alternative, i.e. classification of weather according to the observed local weather elements was less popular until the recent times when the numerical weather forecasts became able to outline not only the synoptic situation, but the near-surface meteorological variables, as well. Nowadays the computer-based statistical facilities are able to operate with matrices of multivariate diurnal samples, as well. The paper presents an attempt to define a set of local weather types using point-wise series at five rural stations, Szombathely, Pécs, Budapest, Szeged és Debrecen in the 1961-1990 reference period. Ten local variables are used, i.e. the diurnal mean temperature, the diurnal temperature range; the cloudiness, the sunshine duration, the water vapour pressure, the precipitation in a logarithmic scale, also differing trace (below 0.1 mm) and no precipitation, the relative humidity and wind speed, including the more extremity indicators of the two latter parameters, i.e. number of hours with over 80 % relative humidity and over 15 m/s wind gusts. Factor analysis of these ten variables was performed leading to 5 fairly independent variables retained for cluster analysis to obtain the local weather types. Hierarchical cluster analysis was performed to classify the 840-930 days within each month of the 30 years period. Furthers neighbour approach was preferred based on Euclidean metrics to establish optimum number of types. The 12 months and the 5 stations exhibited slightly different results but the optimum number of the types was always between 4 and 12 which is a quite reasonable number from practical considerations. According to a further reasonable compromise, the common number of the types not too bad in either stations or months defines that the common optimum number of local weather types is nine. This set of weather types, specified for each station, was used to "explain" the possible portion of local inter-diurnal variance of seven daily urban air quality measurements, i.e. CO, NO, NO2, NOx, O3, SO2 and PM10. Another set of data for testing the types are the mortalities with chronicle illnesses, i.e. cardio-vascular and respiratory illnesses. This set of 35 years data (1971-2005) is layered for capital city (Budapest, 2 million inhabitants) and rest of the countries (max. 200 000 inhab.). The use of complex weather types is likely better than the common use of individual weather elements, e.g. diurnal mean temperature or a kind of bioclimatic index. The ability of the types to decrease the variability is also compared for both sets of target variables to the analogous ability of macrosynoptic classification by Peczely. The results are also discussed by grouping the investigated contaminants according to their origin.

Influence of solar variability on the occurrence of central European weather types from 1763 to 2009

NASA Astrophysics Data System (ADS)

Schwander, Mikhaël; Rohrer, Marco; Brönnimann, Stefan; Malik, Abdul

2017-09-01

The impact of solar variability on weather and climate in central Europe is still not well understood. In this paper we use a new time series of daily weather types to analyse the influence of the 11-year solar cycle on the tropospheric weather of central Europe. We employ a novel, daily weather type classification over the period 1763-2009 and investigate the occurrence frequency of weather types under low, moderate, and high solar activity level. Results show a tendency towards fewer days with westerly and west-southwesterly flow over central Europe under low solar activity. In parallel, the occurrence of northerly and easterly types increases. For the 1958-2009 period, a more detailed view can be gained from reanalysis data. Mean sea level pressure composites under low solar activity also show a reduced zonal flow, with an increase of the mean blocking frequency between Iceland and Scandinavia. Weather types and reanalysis data show that the 11-year solar cycle influences the late winter atmospheric circulation over central Europe with colder (warmer) conditions under low (high) solar activity.

Types of Crude Oil

EPA Pesticide Factsheets

The petroleum industry often classifies these types by geographical source, but the classification scheme here is more useful in a spill cleanup scenario. It indicates general toxicity, physical state, and changes caused by time and weathering.

Spatio-temporal atmospheric circulation variability around the Antarctic Peninsula based on hemispheric circulation modes and weather types

NASA Astrophysics Data System (ADS)

Wachter, Paul; Beck, Christoph; Philipp, Andreas; Jacobeit, Jucundus; Höppner, Kathrin

2017-04-01

Large parts of the Polar Regions are affected by a warming trend associated with substantial changes in the cryosphere. In Antarctica this positive trend pattern is most dominant in the western part of the continent and on the Antarctic Peninsula (AP). An important driving mechanism of temperature variability and trends in this region is the atmospheric circulation. Changes in atmospheric circulation modes and frequencies of circulation types have major impacts on temperature characteristics at a certain station or region. We present results of a statistical downscaling study focused on AP temperature variability showing both results of large-scale atmospheric circulation modes and regional weather type classifications derived from monthly and daily gridded reanalysis data sets. In order to investigate spatial trends and variabilities of the Southern Annular Mode (SAM), we analyze spatio-temporally resolved SAM-pattern maps from 1979 to 2015. First results show dominant multi-annual to decadal pattern variabilities which can be directly linked to temperature variabilities at the Antarctic Peninsula. A sub-continental to regional view on the influence of atmospheric circulation on AP temperature variability is given by the analysis of weather type classifications (WTC). With this analysis we identify significant changes in the frequency of occurrence of highly temperature-relevant circulation patterns. The investigated characteristics of weather type frequencies can also be related to the identified changes of the SAM.

An automatic aerosol classification for earlinet: application and results

NASA Astrophysics Data System (ADS)

Papagiannopoulos, Nikolaos; Mona, Lucia; Amiridis, Vassilis; Binietoglou, Ioannis; D'Amico, Giuseppe; Guma-Claramunt, P.; Schwarz, Anja; Alados-Arboledas, Lucas; Amodeo, Aldo; Apituley, Arnoud; Baars, Holger; Bortoli, Daniele; Comeron, Adolfo; Guerrero-Rascado, Juan Luis; Kokkalis, Panos; Nicolae, Doina; Papayannis, Alex; Pappalardo, Gelsomina; Wandinger, Ulla; Wiegner, Matthias

2018-04-01

Aerosol typing is essential for understanding the impact of the different aerosol sources on climate, weather system and air quality. An aerosol classification method for EARLINET (European Aerosol Research Lidar Network) measurements is introduced which makes use the Mahalanobis distance classifier. The performance of the automatic classification is tested against manually classified EARLINET data. Results of the application of the method to an extensive aerosol dataset will be presented.

Effects of weather on the retrieval of sea ice concentration and ice type from passive microwave data

NASA Technical Reports Server (NTRS)

Maslanik, J. A.

1992-01-01

Effects of wind, water vapor, and cloud liquid water on ice concentration and ice type calculated from passive microwave data are assessed through radiative transfer calculations and observations. These weather effects can cause overestimates in ice concentration and more substantial underestimates in multi-year ice percentage by decreasing polarization and by decreasing the gradient between frequencies. The effect of surface temperature and air temperature on the magnitudes of weather-related errors is small for ice concentration and substantial for multiyear ice percentage. The existing weather filter in the NASA Team Algorithm addresses only weather effects over open ocean; the additional use of local open-ocean tie points and an alternative weather correction for the marginal ice zone can further reduce errors due to weather. Ice concentrations calculated using 37 versus 18 GHz data show little difference in total ice covered area, but greater differences in intermediate concentration classes. Given the magnitude of weather-related errors in ice classification from passive microwave data, corrections for weather effects may be necessary to detect small trends in ice covered area and ice type for climate studies.

Weather types and the regime of wildfires in Portugal

NASA Astrophysics Data System (ADS)

Pereira, M. G.; Trigo, R. M.; Dacamara, C. C.

2009-04-01

An objective classification scheme, as developed by Trigo and DaCamara (2000), was applied to classify the daily atmospheric circulation affecting Portugal between 1980 and 2007 into a set of 10 basic weather types (WTs). The classification scheme relies on a set of atmospheric circulation indices, namely southerly flow (SF), westerly flow (WF), total flow (F), southerly shear vorticity (ZS), westerly shear vorticity (ZW) and total vorticity (Z). The weather-typing approach, together with surfacemeteorological variables (e.g. intensity and direction of geostrophic wind, maximum and minimum temperature and precipitation) were then associated to wildfire events as recorded in the official Portuguese fire database consisting of information on each fire occurred in the 18 districts of Continental Portugal within the same period (>450.000 events). The objective of this study is to explore the dependence of wildfire activity on weather and climate and then evaluate the potential of WTs to discriminate among recorded wildfires on what respects to their occurrence and development. Results show that days characterised by surface flow with an eastern component (i.e. NE, E and SE) account for a high percentage of daily burnt area, as opposed to surface westerly flow (NW, W and SW), which represents about a quarter of the total number of days but only accounts for a very low percentage of active fires and of burnt area. Meteorological variables such as minimum and maximum temperatures, that are closely associated to surface wind intensity and direction, also present a good ability to discriminate between the different types of fire events.. Trigo R.M., DaCamara C. (2000) "Circulation Weather Types and their impact on the precipitation regime in Portugal". Int J of Climatology, 20, 1559-1581.

Relationship between atmospheric circulation weather types and seasonal precipitation in Serbia

NASA Astrophysics Data System (ADS)

Putniković, Suzana; Tošić, Ivana

2017-04-01

An automated version of the Lamb weather type classification scheme was used to classify daily circulation types over Serbia. The synoptic characteristics of 26 weather types and their relative frequencies are discussed for spring and autumn, complementing research previously published by Putniković et al. (Meteorol Atmos Phys 128:649-662, 2016) for winter and summer. Trends of the circulation types are presented, as well as precipitation trends during the period 1961-2010. Precipitation was modeled by the stepwise regression at six stations, defining weather types as independent variables. The anticyclonic (A) type is the most frequent class occurring in autumn (23.87%), displaying a positive trend for spring and significant negative trend for autumn. The frequencies of anticyclonic and cyclonic (C) types are almost the same for spring: 14.33 and 14.02%, respectively. The C type shows a significant negative trend only in spring. The increasing trend of the frequency of the C types and decreasing trend of the A types are in agreement with the increasing trend of precipitation in Serbia during autumn. Results suggest that the C type affects precipitation occurrence over most of the country, while the remaining 25 types provide more negligible or regional contributions to precipitation.

Atmospheric circulation classification comparison based on wildfires in Portugal

NASA Astrophysics Data System (ADS)

Pereira, M. G.; Trigo, R. M.

2009-04-01

Atmospheric circulation classifications are not a simple description of atmospheric states but a tool to understand and interpret the atmospheric processes and to model the relation between atmospheric circulation and surface climate and other related variables (Radan Huth et al., 2008). Classifications were initially developed with weather forecasting purposes, however with the progress in computer processing capability, new and more robust objective methods were developed and applied to large datasets prompting atmospheric circulation classification methods to one of the most important fields in synoptic and statistical climatology. Classification studies have been extensively used in climate change studies (e.g. reconstructed past climates, recent observed changes and future climates), in bioclimatological research (e.g. relating human mortality to climatic factors) and in a wide variety of synoptic climatological applications (e.g. comparison between datasets, air pollution, snow avalanches, wine quality, fish captures and forest fires). Likewise, atmospheric circulation classifications are important for the study of the role of weather in wildfire occurrence in Portugal because the daily synoptic variability is the most important driver of local weather conditions (Pereira et al., 2005). In particular, the objective classification scheme developed by Trigo and DaCamara (2000) to classify the atmospheric circulation affecting Portugal have proved to be quite useful in discriminating the occurrence and development of wildfires as well as the distribution over Portugal of surface climatic variables with impact in wildfire activity such as maximum and minimum temperature and precipitation. This work aims to present: (i) an overview the existing circulation classification for the Iberian Peninsula, and (ii) the results of a comparison study between these atmospheric circulation classifications based on its relation with wildfires and relevant meteorological variables. To achieve these objectives we consider the main classifications for Iberia developed within the framework of COST action 733 (Radan Huth et al., 2008). This European project aims to provide a wide range of atmospheric circulation classifications for Europe and sub-regions (http://www.cost733.org/) with an ambitious objective of assessing, comparing and classifying all relevant weather situations in Europe. Pereira et al. (2005) "Synoptic patterns associated with large summer forest fires in Portugal". Agricultural and Forest Meteorology,129, 11-25. Radan Huth et al. (2008) "Classifications of Atmospheric circulation patterns. Recent advances and applications". Trends and Directions in Climate Research: Ann. N.Y. Acad. Sci. 1146: 105-152. doi: 10.1196/annals.1446.019. Trigo R.M., DaCamara C. (2000) "Circulation Weather Types and their impact on the precipitation regime in Portugal". Int J of Climatology, 20, 1559-1581.

Improving crop classification through attention to the timing of airborne radar acquisitions

NASA Technical Reports Server (NTRS)

Brisco, B.; Ulaby, F. T.; Protz, R.

1984-01-01

Radar remote sensors may provide valuable input to crop classification procedures because of (1) their independence of weather conditions and solar illumination, and (2) their ability to respond to differences in crop type. Manual classification of multidate synthetic aperture radar (SAR) imagery resulted in an overall accuracy of 83 percent for corn, forest, grain, and 'other' cover types. Forests and corn fields were identified with accuracies approaching or exceeding 90 percent. Grain fields and 'other' fields were often confused with each other, resulting in classification accuracies of 51 and 66 percent, respectively. The 83 percent correct classification represents a 10 percent improvement when compared to similar SAR data for the same area collected at alternate time periods in 1978. These results demonstrate that improvements in crop classification accuracy can be achieved with SAR data by synchronizing data collection times with crop growth stages in order to maximize differences in the geometric and dielectric properties of the cover types of interest.

The effects of synoptic weather on influenza infection incidences: a retrospective study utilizing digital disease surveillance

NASA Astrophysics Data System (ADS)

Zhao, Naizhuo; Cao, Guofeng; Vanos, Jennifer K.; Vecellio, Daniel J.

2018-01-01

The environmental drivers and mechanisms of influenza dynamics remain unclear. The recent development of influenza surveillance-particularly the emergence of digital epidemiology-provides an opportunity to further understand this puzzle as an area within applied human biometeorology. This paper investigates the short-term weather effects on human influenza activity at a synoptic scale during cold seasons. Using 10 years (2005-2014) of municipal level influenza surveillance data (an adjustment of the Google Flu Trends estimation from the Centers for Disease Control's virologic surveillance data) and daily spatial synoptic classification weather types, we explore and compare the effects of weather exposure on the influenza infection incidences in 79 cities across the USA. We find that during the cold seasons the presence of the polar [i.e., dry polar (DP) and moist polar (MP)] weather types is significantly associated with increasing influenza likelihood in 62 and 68% of the studied cities, respectively, while the presence of tropical [i.e., dry tropical (DT) and moist tropical (MT)] weather types is associated with a significantly decreasing occurrence of influenza in 56 and 43% of the cities, respectively. The MP and the DP weather types exhibit similar close positive correlations with influenza infection incidences, indicating that both cold-dry and cold-moist air provide favorable conditions for the occurrence of influenza in the cold seasons. Additionally, when tropical weather types are present, the humid (MT) and the dry (DT) weather types have similar strong impacts to inhibit the occurrence of influenza. These findings suggest that temperature is a more dominating atmospheric factor than moisture that impacts the occurrences of influenza in cold seasons.

Antarctic meteorite descriptions 1976-1977-1978-1979

NASA Technical Reports Server (NTRS)

Score, R.; Schwarz, C. M.; King, T. V. V.; Mason, B.; Bogard, D. D.; Gabel, E. M.

1981-01-01

All previously distributed meteorite data sheets, plus a number of new ones for 1979 chondrites are included. A comprehensive sample index listing meteorite name/number, classification, and weathering category is also included. Separate indexes listing all petrologic type 3 and type 4 chondrites, all irons, all achondrites, and all carbonaceous chondrites in the collection is provided.

Examining Multiple Dimensions of Word Knowledge for Content Vocabulary Understanding

ERIC Educational Resources Information Center

Cervetti, Gina N.; Tilson, Jennifer L.; Castek, Jill; Bravo, Marco A.; Trainin, Guy

2012-01-01

This study traces the development of a vocabulary measure designed to assess multiple types of word knowledge. The assessment, which was administered in conjunction with a science unit about weather and the water cycle for third-and-fourth graders, included items for six knowledge types--recognition, definition, classification/example, context,…

Analysis of the synoptic winter mortality climatology in five regions of England: Searching for evidence of weather signals.

PubMed

Paschalidou, A K; Kassomenos, P A; McGregor, G R

2017-11-15

Although heat-related mortality has received considerable research attention, the impact of cold weather on public health is less well-developed, probably due to the fact that physiological responses to cold weather can vary substantially among individuals, age groups, diseases etc., depending on a number of behavioral and physiological factors. In the current work we use the classification techniques provided by the COST-733 software to link synoptic circulation patterns with excess cold-related mortality in 5 regions of England. We conclude that, regardless of the classification scheme used, the most hazardous conditions for public health in England are associated with the prevalence of the Easterly type of weather, favoring advection of cold air from continental Europe. It is noteworthy that there has been observed little-to-no regional variation with regards to the classification results among the 5 regions, suggestive of a spatially homogenous response of mortality to the atmospheric patterns identified. In general, the 10 different groupings of days used reveal that excess winter mortality is linked with the lowest daily minimum/maximum temperatures in the area. However it is not uncommon to observe high mortality rates during days with higher, in relative terms, temperatures, when rapidly changing weather results in an increase of mortality. Such a finding confirms the complexity of cold-related mortality and highlights the importance of synoptic climatology in understanding of the phenomenon. Copyright © 2017 Elsevier B.V. All rights reserved.

Classification of circulation type sequences applied to snow avalanches over the eastern Pyrenees (Andorra and Catalonia)

NASA Astrophysics Data System (ADS)

Esteban, Pere; Beck, Christoph; Philipp, Andreas

2010-05-01

Using data associated with accidents or damages caused by snow avalanches over the eastern Pyrenees (Andorra and Catalonia) several atmospheric circulation type catalogues have been obtained. For this purpose, different circulation type classification methods based on Principal Component Analysis (T-mode and S-mode using the extreme scores) and on optimization procedures (Improved K-means and SANDRA) were applied . Considering the characteristics of the phenomena studied, not only single day circulation patterns were taken into account but also sequences of circulation types of varying length. Thus different classifications with different numbers of types and for different sequence lengths were obtained using the different classification methods. Simple between type variability, within type variability, and outlier detection procedures have been applied for selecting the best result concerning snow avalanches type classifications. Furthermore, days without occurrence of the hazards were also related to the avalanche centroids using pattern-correlations, facilitating the calculation of the anomalies between hazardous and no hazardous days, and also frequencies of occurrence of hazardous events for each circulation type. Finally, the catalogues statistically considered the best results are evaluated using the avalanche forecaster expert knowledge. Consistent explanation of snow avalanches occurrence by means of circulation sequences is obtained, but always considering results from classifications with different sequence length. This work has been developed in the framework of the COST Action 733 (Harmonisation and Applications of Weather Type Classifications for European regions).

Asian Dust Weather Categorization with Satellite and Surface Observations

NASA Technical Reports Server (NTRS)

Lin, Tang-Huang; Hsu, N. Christina; Tsay, Si-Chee; Huang, Shih-Jen

2011-01-01

This study categorizes various dust weather types by means of satellite remote sensing over central Asia. Airborne dust particles can be identified by satellite remote sensing because of the different optical properties exhibited by coarse and fine particles (i.e. varying particle sizes). If a correlation can be established between the retrieved aerosol optical properties and surface visibility, the intensity of dust weather can be more effectively and consistently discerned using satellite rather than surface observations. In this article, datasets consisting of collocated products from Moderate Resolution Imaging Spectroradiometer Aqua and surface measurements are analysed. The results indicate an exponential relationship between the surface visibility and the satellite-retrieved aerosol optical depth, which is subsequently used to categorize the dust weather. The satellite-derived spatial frequency distributions in the dust weather types are consistent with China s weather station reports during 2003, indicating that dust weather classification using satellite data is highly feasible. Although the period during the springtime from 2004 to 2007 may be not sufficient for statistical significance, our results reveal an increasing tendency in both intensity and frequency of dust weather over central Asia during this time period.

Association of weather and air pollution interactions on daily mortality in 12 Canadian cities.

PubMed

Vanos, J K; Cakmak, S; Kalkstein, L S; Yagouti, Abderrahmane

It has been well established that both meteorological attributes and air pollution concentrations affect human health outcomes. We examined all cause nonaccident mortality relationships for 28 years (1981-2008) in relation to air pollution and synoptic weather type (encompassing air mass) data in 12 Canadian cities. This study first determines the likelihood of summertime extreme air pollution events within weather types using spatial synoptic classification. Second, it examines the modifying effect of weather types on the relative risk of mortality (RR) due to daily concentrations of air pollution (nitrogen dioxide, ozone, sulfur dioxide, and particulate matter <2.5 μm). We assess both single- and two-pollutant interactions to determine dependent and independent pollutant effects using the relatively new time series technique of distributed lag nonlinear modeling (DLNM). Results display dry tropical (DT) and moist tropical plus (MT+) weathers to result in a fourfold and twofold increased likelihood, respectively, of an extreme pollution event (top 5 % of pollution concentrations throughout the 28 years) occurring. We also demonstrate statistically significant effects of single-pollutant exposure on mortality ( p  < 0.05) to be dependent on summer weather type, where stronger results occur in dry moderate (fair weather) and DT or MT+ weather types. The overall average single-effect RR increases due to pollutant exposure within DT and MT+ weather types are 14.9 and 11.9 %, respectively. Adjusted exposures (two-way pollutant effect estimates) generally results in decreased RR estimates, indicating that the pollutants are not independent. Adjusting for ozone significantly lowers 67 % of the single-pollutant RR estimates and reduces model variability, which demonstrates that ozone significantly controls a portion of the mortality signal from the model. Our findings demonstrate the mortality risks of air pollution exposure to differ by weather type, with increased accuracy obtained when accounting for interactive effects through adjustment for dependent pollutants using a DLNM.

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.

An objective daily Weather Type classification for Iberia since 1850; patterns, trends, variability and impact in precipitation

NASA Astrophysics Data System (ADS)

Ramos, A. M.; Trigo, R. M.; Lorenzo, M. N.; Vaquero, J. M.; Gallego, M. C.; Valente, M. A.; Gimeno, L.

2009-04-01

In recent years a large number of automated classifications of atmospheric circulation patterns have been published covering the entire European continent or specific sub-regions (Huth et al., 2008). This generalized use of objective classifications results from their relatively straightforward computation but crucially from their capacity to provide simple description of typical synoptic conditions as well as their climatic and environmental impact. For this purpose, the vast majority of authors has employed the Reanalyses datasets, namely from either NCEP/NCAR or ECMWF projects. However, both these widely used datasets suffer from important caveats, namely their restricted temporal coverage, that is limited to the last six decades (NCEP/NCAR since 1948 and ECMWF since 1958). This limitation has been partially mitigated by the recent availability of continuous daily mean sea level pressure obtained within the European project EMULATE, that extended the historic records over the extra-tropical Atlantic and Europe (70°-25° N by 70° W-50° E), for the period 1850 to the present (Ansell, T. J. et al. 2006). Here we have used the extended EMULATE dataset to construct an automated version of the Lamb Weather type (WTs) classification scheme (Jones et al 1993) adapted for the center of the Iberian Peninsula. We have identified 10 basic WTs (Cyclonic, Anticyclonic and 8 directional types) following a similar methodology to that previously adopted by Trigo and DaCamara, 2000 (for Portugal) and Lorenzo et al. 2008 (for Galicia, northwestern Iberia). We have evaluated trends of monthly/seasonal frequency of each WT for the entire period and several shorter periods. Finally, we use the long-term precipitation time series from Lisbon (recently digitized) and Cadiz (southern Spain) to evaluate, the impact of each WT on the precipitation regime. It is shown that the Anticyclonic (A) type, although being the most frequent class in winter, gives a rather small contribution to the winter precipitation amount, observed on a daily basis. On the other hand, the three wettest WTs, namely the Cyclonic (C), South-westerly (SW) and Westerly (W) types, together representing roughly a third of all winter days, do account for more than 60% of the observed daily precipitation. It is shown that the large inter-annual variability of precipitation in both cities is highly related with the corresponding inter-annual variability of the wet WTs. Ansell, T. J. et al. (2006) Daily mean sea level pressure reconstructions for the European - North Atlantic region for the period 1850-2003, Journal of Climate, 19, 2717-2742, doi: 10.1175/JCLI3775.1 Huth R., Beck C., Philipp A., Demuzere M, Ustrnul Z, Cahynová M., Kyselý J., Tveito O.E. (2008) Classifications of atmospheric circulation patterns: recent advances and applications. Trends and Directions in Climate Research: Ann. N.Y. Acad. Sci. 1146:, 105-152 Jones, P. D. , M. Hulme , K. R. Briffa. (1993) A comparison of Lamb circulation types with an objective classification scheme. Int. J. Climatol. 13: 655- 663. Lorenzo M.N., Taboada J.J. and Gimeno L. (2008) Links between circulation weather types and teleconnection patterns and their influence on precipitation patterns in Galicia (NW Spain). Int. J. Climatol. Published Online: Nov 12 2007 5:30AM DOI: 10.1002/joc.1646. Trigo R.M. and Da Camara C.C. (2000) Circulation weather types and their influence on the precipitation regime in Portugal. Int. J. Climatol., 20, 1559-1581.

Space weathering trends on carbonaceous asteroids: A possible explanation for Bennu's blue slope?

NASA Astrophysics Data System (ADS)

Lantz, C.; Binzel, R. P.; DeMeo, F. E.

2018-03-01

We compare primitive near-Earth asteroid spectral properties to the irradiated carbonaceous chondrite samples of Lantz et al. (2017) in order to assess how space weathering processes might influence taxonomic classification. Using the same eigenvectors from the asteroid taxonomy by DeMeo et al. (2009), we calculate the principal components for fresh and irradiated meteorites and find that change in spectral slope (blueing or reddening) causes a corresponding shift in the two first principal components along the same line that the C- and X-complexes track. Using a sample of B-, C-, X-, and D-type NEOs with visible and near-infrared spectral data, we further investigated the correlation between prinicipal components and the spectral curvature for the primitive asteroids. We find that space weathering effects are not just slope and albedo, but also include spectral curvature. We show how, through space weathering, surfaces having an original "C-type" reflectance can thus turn into a redder P-type or a bluer B-type, and that space weathering can also decrease (and disguise) the D-type population. Finally we take a look at the case of OSIRIS-REx target (101955) Bennu and propose an explanation for the blue and possibly red spectra that were previously observed on different locations of its surface: parts of Bennu's surface could have become blue due to space weathering, while fresher areas are redder. No clear prediction can be made on Hayabusa-2 target (162173) Ryugu.

Weathering Grade Classification of Granite Stone Monument Using Reflectance Spectroscopy

NASA Astrophysics Data System (ADS)

Hyun, C.; Roh, T.; Choi, M.; Park, H.

2009-05-01

Stone monument has been placed in field and exposed to rain and wind. This outdoor environment and air pollution induced weathering of stone monument. Weathering grade classification is necessary to manage and conserve stone monuments. Visual interpretation by geologist and laboratory experiments using specimens fallen off from the monument to avoid damage on the monument have been applied to classify weathering grade conventionally. Rocks and minerals absorb some particular wavelength ranges of electromagnetic energy by electronic process and vibrational process of composing elements and these phenomena produce intrinsic diagnostic spectral reflectance curve. Non-destructive technique for weathering degree assessment measures those diagnostic absorption features of weathering products and converts the depths of features related to abundance of the materials to relative weathering degree. We selected granite outcrop to apply conventional six folded weathering grade classification method using Schmidt hammer rebound teste. The correlations between Schmidt hammer rebound values and absorption depths of iron oxides such as ferric oxide in the vicinity of 0.9 micrometer wavelength and clay minerals such as illite and kaolinite in the vicinity of 2.2 micrometer wavelength, representative weathering products of granite, were analyzed. The Schmidt hammer rebound value decreased according to increase of absorption depths induced from those weathering products. Weathering grade classification on the granite stone monument was conducted by using absorption depths of weathering products This research is supported from National Research Institute of Cultural Heritage and we appreciate for this.

Real-time classification of vehicles by type within infrared imagery

NASA Astrophysics Data System (ADS)

Kundegorski, Mikolaj E.; Akçay, Samet; Payen de La Garanderie, Grégoire; Breckon, Toby P.

2016-10-01

Real-time classification of vehicles into sub-category types poses a significant challenge within infra-red imagery due to the high levels of intra-class variation in thermal vehicle signatures caused by aspects of design, current operating duration and ambient thermal conditions. Despite these challenges, infra-red sensing offers significant generalized target object detection advantages in terms of all-weather operation and invariance to visual camouflage techniques. This work investigates the accuracy of a number of real-time object classification approaches for this task within the wider context of an existing initial object detection and tracking framework. Specifically we evaluate the use of traditional feature-driven bag of visual words and histogram of oriented gradient classification approaches against modern convolutional neural network architectures. Furthermore, we use classical photogrammetry, within the context of current target detection and classification techniques, as a means of approximating 3D target position within the scene based on this vehicle type classification. Based on photogrammetric estimation of target position, we then illustrate the use of regular Kalman filter based tracking operating on actual 3D vehicle trajectories. Results are presented using a conventional thermal-band infra-red (IR) sensor arrangement where targets are tracked over a range of evaluation scenarios.

A systematic evaluation of the lagged effects of spatiotemporally relative surface weather types on wintertime cardiovascular-related mortality across 19 US cities.

PubMed

Lee, Cameron C

2015-11-01

Previous research using varying methods has shown that the day-to-day variability in cardiovascular (CV)-related mortality is correlated with a number of different meteorological variables, though these relationships can vary geographically. This research systematically examines the relationship between anomalous winter CV-related mortality and geographically and seasonally relative multivariate surface weather types derived from a recently developed gridded weather typing classification (GWTC) for cities in varying climate regions of the United States of America (USA). Results indicate that for all locations examined, during winter, a dry and cool (DC) weather type is significantly related to increased CV-related mortality, especially in the 2 weeks immediately after it occurs, with no apparent mortality displacement. Across the USA as a whole, the peak of this relationship is a 4.1% increase in CV-related mortality at a lag of 3 days. Spike days in CV-related mortality show similar trends, being over 50% more likely 2 to 4 days after the DC type occurs. A humid and warm (HW) weather type exhibited a significant and opposite relationship to that of DC. While these results for DC and HW were statistically significant at every location examined, the magnitudes were larger in the warmer locations. Among other weather types, Warm Front Passages (WFP) were also related to significant increases in CV-related mortality, especially 1 day after they occurred. Though this link was much more varied geographically than results found with DC or HW, it suggests that sequences of multiple DC days followed by WFP may result in increased CV-related mortality.

A systematic evaluation of the lagged effects of spatiotemporally relative surface weather types on wintertime cardiovascular-related mortality across 19 US cities

NASA Astrophysics Data System (ADS)

Lee, Cameron C.

2015-11-01

Previous research using varying methods has shown that the day-to-day variability in cardiovascular (CV)-related mortality is correlated with a number of different meteorological variables, though these relationships can vary geographically. This research systematically examines the relationship between anomalous winter CV-related mortality and geographically and seasonally relative multivariate surface weather types derived from a recently developed gridded weather typing classification (GWTC) for cities in varying climate regions of the United States of America (USA). Results indicate that for all locations examined, during winter, a dry and cool (DC) weather type is significantly related to increased CV-related mortality, especially in the 2 weeks immediately after it occurs, with no apparent mortality displacement. Across the USA as a whole, the peak of this relationship is a 4.1% increase in CV-related mortality at a lag of 3 days. Spike days in CV-related mortality show similar trends, being over 50% more likely 2 to 4 days after the DC type occurs. A humid and warm (HW) weather type exhibited a significant and opposite relationship to that of DC. While these results for DC and HW were statistically significant at every location examined, the magnitudes were larger in the warmer locations. Among other weather types, Warm Front Passages (WFP) were also related to significant increases in CV-related mortality, especially 1 day after they occurred. Though this link was much more varied geographically than results found with DC or HW, it suggests that sequences of multiple DC days followed by WFP may result in increased CV-related mortality.

Effects of synoptic weather on ground-level PM2.5 concentrations in the United States

NASA Astrophysics Data System (ADS)

Liu, Ying; Zhao, Naizhuo; Vanos, Jennifer K.; Cao, Guofeng

2017-01-01

It is known that individual meteorological factors affect the concentrations of fine particulate matter with aerodynamic diameters ≤2.5 μm (PM2.5), yet the specific meteorological effects found in previous studies are largely inconsistent and even conflicting. This study investigates influences of daily and short term changes in synoptic weather on ground-level PM2.5 concentrations in a large geographical area (75 cities across the contiguous United States (U.S.)) by using ten-year (2001-2010) spatial synoptic classification (SSC) data. We find that in the spring, summer, and fall the presence of the tropical weather types (i.e., dry-tropical (DT) and moist-tropical (MT)) is likely to associate with significantly higher levels of PM2.5 as compared to an all-weather-type-day average, and the presence of the polar weather types (i.e., dry-polar (DP) and moist-polar (MP)) is associated with significantly lower PM2.5 concentrations. The short-term (day to day) changes in synoptic weather types in a region are also likely to lead to significant variance in PM2.5 concentrations. For example, the largest increase in PM2.5 concentration occurs with the synoptic weather type changing from DP-to-MT. Conversely, a MT-to-DP weather type change results in the largest decrease in PM2.5 concentrations. Compared to air temperature, the effects of atmospheric moisture on PM2.5 concentration tend to be subtle, demonstrating that in conjunction with moderate temperature, neither the dry nor the moist air (except moist-moderate (MM) in summer) are associated with significantly high or low PM2.5 concentrations. Finally, we find that the effects of the synoptic weather type on PM2.5 concentrations may vary for different seasons and geographical areas. These findings suggest that interactions between atmospheric factors and seasonal and/or geographical factors have considerable impacts on the PM2.5 concentrations, and therefore should be considered in addition to the SSC when conducting environment health assessments.

Doppler Feature Based Classification of Wind Profiler Data

NASA Astrophysics Data System (ADS)

Sinha, Swati; Chandrasekhar Sarma, T. V.; Lourde. R, Mary

2017-01-01

Wind Profilers (WP) are coherent pulsed Doppler radars in UHF and VHF bands. They are used for vertical profiling of wind velocity and direction. This information is very useful for weather modeling, study of climatic patterns and weather prediction. Observations at different height and different wind velocities are possible by changing the operating parameters of WP. A set of Doppler power spectra is the standard form of WP data. Wind velocity, direction and wind velocity turbulence at different heights can be derived from it. Modern wind profilers operate for long duration and generate approximately 4 megabytes of data per hour. The radar data stream contains Doppler power spectra from different radar configurations with echoes from different atmospheric targets. In order to facilitate systematic study, this data needs to be segregated according the type of target. A reliable automated target classification technique is required to do this job. Classical techniques of radar target identification use pattern matching and minimization of mean squared error, Euclidean distance etc. These techniques are not effective for the classification of WP echoes, as these targets do not have well-defined signature in Doppler power spectra. This paper presents an effective target classification technique based on range-Doppler features.

Future projections of synoptic weather types over the Arabian Peninsula during the twenty-first century using an ensemble of CMIP5 models

NASA Astrophysics Data System (ADS)

El Kenawy, Ahmed M.; McCabe, Matthew F.

2017-10-01

An assessment of future change in synoptic conditions over the Arabian Peninsula throughout the twenty-first century was performed using 20 climate models from the Coupled Model Intercomparison Project Phase 5 (CMIP5) database. We employed the mean sea level pressure (SLP) data from model output together with NCEP/NCAR reanalysis data and compared the relevant circulation types produced by the Lamb classification scheme for the base period 1975-2000. Overall, model results illustrated good agreement with the reanalysis, albeit with a tendency to underestimate cyclonic (C) and southeasterly (SE) patterns and to overestimate anticyclones and directional flows. We also investigated future projections for each circulation-type during the rainy season (December-May) using three Representative Concentration Pathways (RCPs), comprising RCP2.6, RCP4.5, and RCP8.5. Overall, two scenarios (RCP4.5 and RCP 8.5) revealed a statistically significant increase in weather types favoring above normal rainfall in the region (e.g., C and E-types). In contrast, weather types associated with lower amounts of rainfall (e.g., anticyclones) are projected to decrease in winter but increase in spring. For all scenarios, there was consistent agreement on the sign of change (i.e., positive/negative) for the most frequent patterns (e.g., C, SE, E and A-types), whereas the sign was uncertain for less recurrent types (e.g., N, NW, SE, and W). The projected changes in weather type frequencies in the region can be viewed not only as indicators of change in rainfall response but may also be used to inform impact studies pertinent to water resource planning and management, extreme weather analysis, and agricultural production.

Relationship of Ground-level Ozone with Synoptic Weather Conditions in the Midwestern U.S.

NASA Astrophysics Data System (ADS)

Jing, P.

2017-12-01

This study investigates the relationship between ground-level ozone (O3) and synoptic weather conditions in the Midwestern U.S. over the period 1990-2015 using the air quality data obtained from the U.S. EPA Air Quality System (AQS) and meteorological data from NASA's Modern Era Retrospective Analysis for Research and Applications (MERRA) reanalysis. The results show that among the six different types of Spatial Synoptic Classification (SSC) weather, the occurrence of dry tropical (DT) weather conditions is most likely to lead to high O3 concentrations. The summertime O3 concentrations in the Midwest decreased at an average rate of 0.7 ppb yr-1 in the 95th percentiles from 1990 to 2015 in response to NO2 emission controls. However, O3 has become more dependent on temperature since 2008 and this was accompanied by more frequent DT weather and air stagnation. The results have implications for the likely effect of future climate change on O3 as a result of modified synoptic weather conditions.

Analysis of the relationship between the monthly temperatures and weather types in Iberian Peninsula

NASA Astrophysics Data System (ADS)

Peña Angulo, Dhais; Trigo, Ricardo; Nicola, Cortesi; José Carlos, González-Hidalgo

2016-04-01

In this study, the relationship between the atmospheric circulation and weather types and the monthly average maximum and minimum temperatures in the Iberian Peninsula is modeled (period 1950-2010). The temperature data used were obtained from a high spatial resolution (10km x 10km) dataset (MOTEDAS dataset, Gonzalez-Hidalgo et al., 2015a). In addition, a dataset of Portuguese temperatures was used (obtained from the Portuguese Institute of Sea and Atmosphere). The weather type classification used was the one developed by Jenkinson and Collison, which was adapted for the Iberian Peninsula by Trigo and DaCamara (2000), using Sea Level Pressure data from NCAR/NCEP Reanalysis dataset (period 1951-2010). The analysis of the behaviour of monthly temperatures based on the weather types was carried out using a stepwise regression procedure of type forward to estimate temperatures in each cell of the considered grid, for each month, and for both maximum and minimum monthly average temperatures. The model selects the weather types that best estimate the temperatures. From the validation model it was obtained the error distribution in the time (months) and space (Iberian Peninsula). The results show that best estimations are obtained for minimum temperatures, during the winter months and in coastal areas. González-Hidalgo J.C., Peña-Angulo D., Brunetti M., Cortesi, C. (2015a): MOTEDAS: a new monthly temperature database for mainland Spain and the trend in temperature (1951-2010). International Journal of Climatology 31, 715-731. DOI: 10.1002/joc.4298

Terrain Classification of Norwegian Slab Avalanche Accidents

ERIC Educational Resources Information Center

Hallandvik, Linda; Aadland, Eivind; Vikene, Odd Lennart

2016-01-01

It is difficult to rely on snow conditions, weather, and human factors when making judgments about avalanche risk because these variables are dynamic and complex; terrain, however, is more easily observed and interpreted. Therefore, this study aimed to investigate (1) the type of terrain in which historical fatal snow avalanche accidents in Norway…

Hydrometeorological application of an extratropical cyclone classification scheme in the southern United States

NASA Astrophysics Data System (ADS)

Senkbeil, J. C.; Brommer, D. M.; Comstock, I. J.; Loyd, T.

2012-07-01

Extratropical cyclones (ETCs) in the southern United States are often overlooked when compared with tropical cyclones in the region and ETCs in the northern United States. Although southern ETCs are significant weather events, there is currently not an operational scheme used for identifying and discussing these nameless storms. In this research, we classified 84 ETCs (1970-2009). We manually identified five distinct formation regions and seven unique ETC types using statistical classification. Statistical classification employed the use of principal components analysis and two methods of cluster analysis. Both manual and statistical storm types generally showed positive (negative) relationships with El Niño (La Niña). Manual storm types displayed precipitation swaths consistent with discrete storm tracks which further legitimizes the existence of multiple modes of southern ETCs. Statistical storm types also displayed unique precipitation intensity swaths, but these swaths were less indicative of track location. It is hoped that by classifying southern ETCs into types, that forecasters, hydrologists, and broadcast meteorologists might be able to better anticipate projected amounts of precipitation at their locations.

Analysis of Synoptic Weather Types and Its Influence on Precipitation in the Marmara Region (NW Turkey)

NASA Astrophysics Data System (ADS)

Baltaci, H.; Kindap, T.; Unal, A.; Karaca, M.

2012-04-01

In this study, we investigated the relationship between synoptic weather types and rainfall patterns in the Marmara region, northwestern part of Turkey. For this purpose, the automated Lamb weather type classification method was applied to the NCEP/NCAR reanalysis daily mean sea level pressure data for the period between 2001 and 2010. Ten synoptic weather types were found that represent the 90% of the synoptic patterns that affect the Marmara region. Based on the annual frequency analysis, mainly six synoptic weather types, 24% (NorthEast), 21% (North), 11% (South), 9% (SouthWest), 7% (Anticyclonic), 5% (Cyclonic), were found dominant in the region. Multiple comparison tests suggest that (i.e., Bonferroni test) northerly patterns (i.e., North and NorthEast) have statistically significantly higher percentages as compared to the southerly (i.e., South and SouthWest) and the rest of the patterns (i.e., Anticylonic and Cylonic). During winter months, N- and NE-patterns observed less frequently than the annual frequencies of them, 18% and 13% of the period, respectively. On the other hand, due to the formation of the low pressure center located over the central Mediterranean Sea, S- and SW-patterns were observed more frequently than their annual mean frequencies, 16% and 17%, respectively. During summer months, N- and NE-patterns become dominant in the region, and they constitute about three quarters of the period, 25% and 44%, respectively. The low pressure center located over central Anatolia and Black Sea brings moist and cool air to the region, preventing excessive heating during the summer season. Cyclonic patterns observed less frequent during the winter and fall months, about 3%. They become more frequent during the summer season, 9% as a result of the shifting of the subtropical jet stream to the south, and the seasonal movement of the Basra low pressure toward the inner and northern parts of the Anatolian peninsula. On the other hand, Anticyclonic patterns are more common in the fall season 11% due to the expansion of spatial extent of the anticyclone center located over the Caspian Sea. Daily precipitation records for the period of between 2001 and 2010 belong to 14 meteorological stations in the region were investigated to understand the influence of synoptic weather types on precipitation. Based on daily precipitation records, about one-third of the NE-patterns result in precipitation which is slightly larger than patterns from other directions. The corresponding values for SW-, N- and S-patterns are 29%, 25% and 25%, respectively. Northerly patterns (N and NE) causes more frequent precipitation on the northern and eastern parts of the region. On the other hand, southerly patterns (S and SW) are more influential and cause more frequent precipitation on the south and northwestern parts of the region. Therefore, frequency of synoptic weather types and daily precipitation records suggest that precipitation regimes are of a different nature in northern and southern parts of the Marmara region. Keywords Synoptic weather types; Marmara Region; Lamb classification; Rainfall patterns

Statistical relationship between surface PM10 concentration and aerosol optical depth over the Sahel as a function of weather type, using neural network methodology

NASA Astrophysics Data System (ADS)

Yahi, H.; Marticorena, B.; Thiria, S.; Chatenet, B.; Schmechtig, C.; Rajot, J. L.; Crepon, M.

2013-12-01

work aims at assessing the capability of passive remote-sensed measurements such as aerosol optical depth (AOD) to monitor the surface dust concentration during the dry season in the Sahel region (West Africa). We processed continuous measurements of AODs and surface concentrations for the period (2006-2010) in Banizoumbou (Niger) and Cinzana (Mali). In order to account for the influence of meteorological condition on the relationship between PM10 surface concentration and AOD, we decomposed the mesoscale meteorological fields surrounding the stations into five weather types having similar 3-dimensional atmospheric characteristics. This classification was obtained by a clustering method based on nonlinear artificial neural networks, the so-called self-organizing map. The weather types were identified by processing tridimensional fields of meridional and zonal winds and air temperature obtained from European Centre for Medium-Range Weather Forecasts (ECMWF) model output centered on each measurement station. Five similar weather types have been identified at the two stations. Three of them are associated with the Harmattan flux; the other two correspond to northward inflow of the monsoon flow at the beginning or the end of the dry season. An improved relationship has been found between the surface PM10 concentrations and the AOD by using a dedicated statistical relationship for each weather type. The performances of the statistical inversion computed on the test data sets show satisfactory skills for most of the classes, much better than a linear regression. This should permit the inversion of the mineral dust concentration from AODs derived from satellite observations over the Sahel.

Improving surface stability of elevated spoil landforms using natural landform analogy and geological information

NASA Astrophysics Data System (ADS)

Emmerton, Bevan; Burgess, Jon; Esterle, Joan; Erskine, Peter; Baumgartl, Thomas

2017-04-01

Large-scale open cut mining in the Bowen Basin, Queensland, Australia has undergone an evolutionary process over the period of a few decades, transitioning from shallow mining depths, limited spoil elevation and pasture based rehabilitation to increased mining depths, escalating pre-stripping, elevated mesa-like landforms and native woody species rehabilitation. As a consequence of this development, the stabilisation of recent constructed landforms has to be assured through means other than the establishment of vegetative cover. Recent developments are the specific selection and partitioning of resilient fragmental spoil types for the construction of final landform surface. They can also be used as cladding resources for stabilizing steep erosive batters and this has been identified as a practical methodology that has the potential to significantly improve rehabilitation outcomes. Examples of improvements are an increase of the surface rock cover, roughness and infiltration and reducing inherent erodibility and runoff and velocity of surface flow. However, a thorough understanding of the properties and behavior of individual spoil materials disturbed during mining is required. Relevant information from published literature on the geological origins, lithology and weathering characteristics of individual strata within the Bowen Basin Coal Measures located in Queensland, Australia (and younger overlying weathered strata) has been studied, and related both to natural landforms and to the surface stability of major strata types when disturbed by mining. The resulting spoil classification developed from this study is based primarily on inherent geological characteristics and weathering behaviour of identifiable lithologic components, and as such describes the expected fragmental resilience likely within disturbed materials at Bowen Basin coal mines. The proposed classification system allows the allocation of spoil types to use categories which have application in pre-mine feasibility investigations, landform design and material selection and placement. It finds its application by practitioners who find encouragement in using this approach of a relatively easy usable classification system to improve the overall outcome of rehabilitation through selection of optimal substrates.

Circulation weather types and their influence on precipitation in Serbia

NASA Astrophysics Data System (ADS)

Putniković, Suzana; Tošić, Ivana; Đurđević, Vladimir

2016-10-01

An objective classification scheme of atmospheric circulation, in which daily circulation is determined by the strength, direction, and vorticity of geostrophic flow, has been applied to the atmosphere over Serbia for the time period 1961-2010. The results for the sea level and isobaric level of 500 hPa for winter and summer are presented. The 26 circulation types (eight pure direction, 16 hybrid, cyclonic, and anticyclonic types) are determined and described. Each of the circulation types has a distinct underlying synoptic pattern that produces the expected type and direction of flow over the study area. The relative frequencies of the circulation types, and the relationship between the precipitation and circulation types at three stations on a seasonal time scale are analyzed. The anticyclonic weather type dominates in winter (18.93 %) and summer (18.70 %), followed by the northeasterly type (16.65 %) in summer, and the cyclonic type (12.83 %) in winter. The cyclonic types (C and hybrid) have a higher than average probability of rain at all stations. Conversely, the anticyclonic types are associated with a lower than average probability and intensity of rainfall.

Classification of rainfall events for weather forecasting purposes in andean region of Colombia

NASA Astrophysics Data System (ADS)

Suárez Hincapié, Joan Nathalie; Romo Melo, Liliana; Vélez Upegui, Jorge Julian; Chang, Philippe

2016-04-01

This work presents a comparative analysis of the results of applying different methodologies for the identification and classification of rainfall events of different duration in meteorological records of the Colombian Andean region. In this study the work area is the urban and rural area of Manizales that counts with a monitoring hydro-meteorological network. This network is composed of forty-five (45) strategically located stations, this network is composed of forty-five (45) strategically located stations where automatic weather stations record seven climate variables: air temperature, relative humidity, wind speed and direction, rainfall, solar radiation and barometric pressure. All this information is sent wirelessly every five (5) minutes to a data warehouse located at the Institute of Environmental Studies-IDEA. With obtaining the series of rainfall recorded by the hydrometeorological station Palogrande operated by the National University of Colombia in Manizales (http://froac.manizales.unal.edu.co/bodegaIdea/); it is with this information that we proceed to perform behavior analysis of other meteorological variables, monitored at surface level and that influence the occurrence of such rainfall events. To classify rainfall events different methodologies were used: The first according to Monjo (2009) where the index n of the heavy rainfall was calculated through which various types of precipitation are defined according to the intensity variability. A second methodology that permitted to produce a classification in terms of a parameter β introduced by Rice and Holmberg (1973) and adapted by Llasat and Puigcerver, (1985, 1997) and the last one where a rainfall classification is performed according to the value of its intensity following the issues raised by Linsley (1977) where the rains can be considered light, moderate and strong fall rates to 2.5 mm / h; from 2.5 to 7.6 mm / h and above this value respectively for the previous classifications. The main contribution which is done with this research is the obtainment elements to optimize and to improve the spatial resolution of the results obtained with mesoscale models such as the Weather Research & Forecasting Model- WRF, used in Colombia for the purposes of weather forecasting and that in addition produces other tools used in current issues such as risk management.

Weather patterns as a downscaling tool - evaluating their skill in stratifying local climate variables

NASA Astrophysics Data System (ADS)

Murawski, Aline; Bürger, Gerd; Vorogushyn, Sergiy; Merz, Bruno

2016-04-01

The use of a weather pattern based approach for downscaling of coarse, gridded atmospheric data, as usually obtained from the output of general circulation models (GCM), allows for investigating the impact of anthropogenic greenhouse gas emissions on fluxes and state variables of the hydrological cycle such as e.g. on runoff in large river catchments. Here we aim at attributing changes in high flows in the Rhine catchment to anthropogenic climate change. Therefore we run an objective classification scheme (simulated annealing and diversified randomisation - SANDRA, available from the cost733 classification software) on ERA20C reanalyses data and apply the established classification to GCMs from the CMIP5 project. After deriving weather pattern time series from GCM runs using forcing from all greenhouse gases (All-Hist) and using natural greenhouse gas forcing only (Nat-Hist), a weather generator will be employed to obtain climate data time series for the hydrological model. The parameters of the weather pattern classification (i.e. spatial extent, number of patterns, classification variables) need to be selected in a way that allows for good stratification of the meteorological variables that are of interest for the hydrological modelling. We evaluate the skill of the classification in stratifying meteorological data using a multi-variable approach. This allows for estimating the stratification skill for all meteorological variables together, not separately as usually done in existing similar work. The advantage of the multi-variable approach is to properly account for situations where e.g. two patterns are associated with similar mean daily temperature, but one pattern is dry while the other one is related to considerable amounts of precipitation. Thus, the separation of these two patterns would not be justified when considering temperature only, but is perfectly reasonable when accounting for precipitation as well. Besides that, the weather patterns derived from reanalyses data should be well represented in the All-Hist GCM runs in terms of e.g. frequency, seasonality, and persistence. In this contribution we show how to select the most appropriate weather pattern classification and how the classes derived from it are reflected in the GCMs.

Classification and prediction of pilot weather encounters: A discriminant function analysis.

PubMed

O'Hare, David; Hunter, David R; Martinussen, Monica; Wiggins, Mark

2011-05-01

Flight into adverse weather continues to be a significant hazard for General Aviation (GA) pilots. Weather-related crashes have a significantly higher fatality rate than other GA crashes. Previous research has identified lack of situational awareness, risk perception, and risk tolerance as possible explanations for why pilots would continue into adverse weather. However, very little is known about the nature of these encounters or the differences between pilots who avoid adverse weather and those who do not. Visitors to a web site described an experience with adverse weather and completed a range of measures of personal characteristics. The resulting data from 364 pilots were carefully screened and subject to a discriminant function analysis. Two significant functions were found. The first, accounting for 69% of the variance, reflected measures of risk awareness and pilot judgment while the second differentiated pilots in terms of their experience levels. The variables measured in this study enabled us to correctly discriminate between the three groups of pilots considerably better (53% correct classifications) than would have been possible by chance (33% correct classifications). The implications of these findings for targeting safety interventions are discussed.

Extreme weather and air pollution effects on cardiovascular and respiratory hospital admissions in Cyprus.

PubMed

Tsangari, H; Paschalidou, A K; Kassomenos, A P; Vardoulakis, S; Heaviside, C; Georgiou, K E; Yamasaki, E N

2016-01-15

In many regions of the world, climatic change is associated with increased extreme temperatures, which can have severe effects on mortality and morbidity. In this study, we examine the effect of extreme weather on hospital admissions in Cyprus, for inland and coastal areas, through the use of synoptic weather classifications (air mass types). In addition, the effect of particulate air pollution (PM10) on morbidity is examined. Our results show that two air mass types, namely (a) warm, rainy days with increased levels of water vapour in the atmosphere and (b) cold, cloudy days with increased levels of precipitation, were associated with increased morbidity in the form of hospital admissions. This was true both for cardiovascular and respiratory conditions, for all age groups, but particularly for the elderly, aged over 65. Particulate air pollution was also associated with increased morbidity in Cyprus, where the effect was more pronounced for cardiovascular diseases. Copyright © 2015 Elsevier B.V. All rights reserved.

Summarising climate and air quality (ozone) data on self-organising maps: a Sydney case study.

PubMed

Jiang, Ningbo; Betts, Alan; Riley, Matt

2016-02-01

This paper explores the classification and visualisation utility of the self-organising map (SOM) method in the context of New South Wales (NSW), Australia, using gridded NCEP/NCAR geopotential height reanalysis for east Australia, together with multi-site meteorological and air quality data for Sydney from the NSW Office of Environment and Heritage Air Quality Monitoring Network. A twice-daily synoptic classification has been derived for east Australia for the period of 1958-2012. The classification has not only reproduced the typical synoptic patterns previously identified in the literature but also provided an opportunity to visualise the subtle, non-linear change in the eastward-migrating synoptic systems influencing NSW (including Sydney). The summarisation of long-term, multi-site air quality/meteorological data from the Sydney basin on the SOM plane has identified a set of typical air pollution/meteorological spatial patterns in the region. Importantly, the examination of these patterns in relation to synoptic weather types has provided important visual insights into how local and synoptic meteorological conditions interact with each other and affect the variability of air quality in tandem. The study illustrates that while synoptic circulation types are influential, the within-type variability in mesoscale flows plays a critical role in determining local ozone levels in Sydney. These results indicate that the SOM can be a useful tool for assessing the impact of weather and climatic conditions on air quality in the regional airshed. This study further promotes the use of the SOM method in environmental research.

Extreme weather events in southern Germany - Climatological risk and development of a large-scale identification procedure

NASA Astrophysics Data System (ADS)

Matthies, A.; Leckebusch, G. C.; Rohlfing, G.; Ulbrich, U.

2009-04-01

Extreme weather events such as thunderstorms, hail and heavy rain or snowfall can pose a threat to human life and to considerable tangible assets. Yet there is a lack of knowledge about present day climatological risk and its economic effects, and its changes due to rising greenhouse gas concentrations. Therefore, parts of economy particularly sensitve to extreme weather events such as insurance companies and airports require regional risk-analyses, early warning and prediction systems to cope with such events. Such an attempt is made for southern Germany, in close cooperation with stakeholders. Comparing ERA40 and station data with impact records of Munich Re and Munich Airport, the 90th percentile was found to be a suitable threshold for extreme impact relevant precipitation events. Different methods for the classification of causing synoptic situations have been tested on ERA40 reanalyses. An objective scheme for the classification of Lamb's circulation weather types (CWT's) has proved to be most suitable for correct classification of the large-scale flow conditions. Certain CWT's have been turned out to be prone to heavy precipitation or on the other side to have a very low risk of such events. Other large-scale parameters are tested in connection with CWT's to find out a combination that has the highest skill to identify extreme precipitation events in climate model data (ECHAM5 and CLM). For example vorticity advection in 700 hPa shows good results, but assumes knowledge of regional orographic particularities. Therefore ongoing work is focused on additional testing of parameters that indicate deviations of a basic state of the atmosphere like the Eady Growth Rate or the newly developed Dynamic State Index. Evaluation results will be used to estimate the skill of the regional climate model CLM concerning the simulation of frequency and intensity of the extreme weather events. Data of the A1B scenario (2000-2050) will be examined for a possible climate change signal.

Analyzing pedestrian crash injury severity under different weather conditions.

PubMed

Li, Duo; Ranjitkar, Prakash; Zhao, Yifei; Yi, Hui; Rashidi, Soroush

2017-05-19

Pedestrians are the most vulnerable road users due to the lack of mass, speed, and protection compared to other types of road users. Adverse weather conditions may reduce road friction and visibility and thus increase crash risk. There is limited evidence and considerable discrepancy with regard to impacts of weather conditions on injury severity in the literature. This article investigated factors affecting pedestrian injury severity level under different weather conditions based on a publicly available accident database in Great Britain. Accident data from Great Britain that are publicly available through the STATS19 database were analyzed. Factors associated with pedestrian, driver, and environment were investigated using a novel approach that combines a classification and regression tree with random forest approach. Significant severity predictors under fine weather conditions from the models included speed limits, pedestrian age, light conditions, and vehicle maneuver. Under adverse weather conditions, the significant predictors were pedestrian age, vehicle maneuver, and speed limit. Elderly pedestrians are associated with higher pedestrian injury severities. Higher speed limits increase pedestrian injury severity. Based on the research findings, recommendations are provided to improve pedestrian safety.

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.

Discrimination of tornadic and non-tornadic severe weather outbreaks

NASA Astrophysics Data System (ADS)

Mercer, Andrew Edward

Outbreaks of severe weather affect the majority of the conterminous United States. An outbreak is characterized by multiple severe weather occurrences within a single synoptic system. Outbreaks can be categorized by whether or not they produce tornadoes. It is hypothesized that the antecedent synoptic signal contains important information about outbreak type. Accordingly, the scope of this research is to determine the extent that the synoptic signal can be utilized to classify outbreak type at various lead times. Outbreak types are classified using the NCEP/NCAR reanalysis data, which are arranged on a global 2.5° latitude-longitude grid, include 17 vertical pressure levels, and span from 1948 to the present (2008). Fifty major tornado outbreak (TO) cases and fifty major non-tornadic severe weather outbreak (NTO) cases are selected for this work. Two types of analyses are performed on these cases to assess discrimination ability. One analysis involves outbreak classification using the Weather Research and Forecasting (WRF) model initialized with the NCEP/NCAR reanalysis dataset. Meteorological covariates are computed from the WRF output and used in training and testing of statistical classification models. The covariate fields are depicted on a 21 X 21 gridpoint field with an 18 km grid spacing centered on the outbreak. Covariates with large discrimination potential are determined using permutation testing. A P-mode principal component analysis (PCA) is used on the subset of covariates determined by permutation testing to reduce data dimensionality, since numerous redundancies exist in the initial covariate set. Three statistical classification models are trained and tested with the resulting PC scores: a support vector machine (SVM), a logistic regression model (LogR), and a multiple linear regression model (LR). Promising results emerge from these methods, as a probability of detection (POD) of 0.89 and a false alarm ratio (FAR) of 0.13 are obtained from the best discriminating statistical technique (SVM) at 24-hours lead time. Results degrade only slightly by 72-hours lead time (maximum POD of 0.833 and minimum FAR of 0.276). Synoptic composites of the outbreak types are the second analysis considered. Composites are used to reveal synoptic features of outbreak types, which can be utilized to diagnose the differences between classes (in this case, TOs and NTOs). The composites are created using PCA. Five raw variables, height, temperature, relative humidity, and u and v wind components, are extracted from the NCEP/NCAR reanalysis data for North America. Converging longitude lines with increasing latitude on the reanalysis grid introduce bias into correlation calculations in higher latitudes; hence, the data are mapped onto both a latitudinal density grid and a Fibonacci grid. The resulting PCA produces two significant principal components (PCs), and a cluster analysis on these PCs for each outbreak type results in two types of TOs and NTOs. TO composites are characterized by a trough of low pressure over the central United States and major quasigeostrophic forcing features such as an upper level jet streak, cyclonic vorticity advection increasing with height, and warm air advection. These dynamics result in a strong surface cyclone in most tornado outbreaks. These features are considerably less pronounced in NTOs. The statistical analyses presented herein were successful in classifying outbreak types at various lead times, using synoptic scale data as input.

Impacts of future changes in weather condition on U.S. transportation

NASA Astrophysics Data System (ADS)

Ashfaq, M.; Pagan, B. R.; Bonds, B. W.; Rastogi, D.

2016-12-01

High-resolution near-term climate projections suggest an intensification of the regional hydrological cycle over the U.S., leading to stronger and more frequent precipitation events. Increase in precipitation extremes is driven by both warm season convection driven rainstorms and frontal based cold season snowstorms. Results also indicate that future warming is driven more by hot extremes, as decrease in cold extremes is three times less than increase in hot extremes. While projected changes may likely impact the transportation system across the U.S., accurate estimation of such impacts requires knowledge of changes in precipitation types (rain, snow, ice, freezing rain). Here we apply four commonly used precipitation typing algorithms to determine different types of precipitation in an 11-memebr high-resolution (18 km) climate projections dataset that covers 40 years (1966-2005) in the baseline and 40 years (2011-2050) in the future period under Representative Concentration Pathway 8.5. The results are compared with the NARR-based precipitation classification in the historical period at the county level. Documented weather related county level fatal crash data for the CONUS and non-fatal crash data for selected states in the eastern half of the U.S. is compiled to develop the historical baseline for the impact of weather conditions on transportation. Further analysis is carried out to understand the ability of an ensemble of high-resolution simulations to produce different precipitation types in the baseline period, potential changes in the occurrence of each type of weather condition in the future period and that how such changes may impact road conditions, vehicle crashes and human fatalities. Additional analysis will also be explored to understand the impact of changes in winter weather conditions on the cost associated with road maintenance.

Effects of climate change on phenology in two French LTER (Alps and Brittany) for the period 1998-2009

NASA Astrophysics Data System (ADS)

Perrimond, B.; Bigot, S.; Quénol, H.; Spielgelberger, T.; Baudry, J.

2012-04-01

Climate and vegetation are linked all over the world. In this study, we work on a seasonal weather classification based on air temperature and precipitation to deduce a link with different phenological stage (greening up, senescence, ...) over a 12 year period (1998-2009) for two different domains in France (Alps and Brittany). In temperate land, the main climatic variable with a potential effect on vegetation is the mean temperature followed by the rainfall deficit. A better understanding in season and their climatic characteristic is need to establish link between climate and phenology; so a weather classification is proposed based on empirical orthogonal functions and ascending hierarchical classification on atmospheric variables. This classification allows us to exhibit the inter-annual and intra-seasonal climatic spatiotemporal variability for both experimental site. Relationships between climate and phenology consist in a comparison between advance and delay in phenological stage and weather type issue from the classification. Experiment field are two french Long Term Ecological Research (LTER). The first one (LTER 'Alps' ) have mountain characteristics about 1000 to 4780 m ASL, ~65% of forest occupation ; the second one (LTER Armorique) is an Atlantic coastal landscape, 0-360 m ASL, ~70% of agricultural field. Climatic data are SAFRAN-France reanalysis which are developed to run SVAT model and come from the French meteorological service 'Météo-France'. All atmospheric variable needed to run a hydrological model are available (air temperature, rainfall/snowfall, wind speed, relative humidity, incoming/outcoming radiation) at a 8-8 km2 space resolution and with a daily time resolution. The phenological data are extracted from SPOT-VGT product 1-1 km2 space resolution and 10 days time resolution) by time series analysis process. Such of study is particularly important to understand relationships between environmental and ecological variables and it will allow to better predict ecological reaction under climate change constraint.

Atmospheric circulation types and daily mortality in Athens, Greece.

PubMed Central

Kassomenos, P; Gryparis, A; Samoli, E; Katsouyanni, K; Lykoudis, S; Flocas, H A

2001-01-01

We investigated the short-term effects of synoptic and mesoscale atmospheric circulation types on mortality in Athens, Greece. The synoptic patterns in the lower troposphere were classified in 8 a priori defined categories. The mesoscale weather types were classified into 11 categories, using meteorologic parameters from the Athens area surface monitoring network; the daily number of deaths was available for 1987-1991. We applied generalized additive models (GAM), extending Poisson regression, using a LOESS smoother to control for the confounding effects of seasonal patterns. We adjusted for long-term trends, day of the week, ambient particle concentrations, and additional temperature effects. Both classifications, synoptic and mesoscale, explain the daily variation of mortality to a statistically significant degree. The highest daily mortality was observed on days characterized by southeasterly flow [increase 10%; 95% confidence interval (CI), 6.1-13.9% compared to the high-low pressure system), followed by zonal flow (5.8%; 95% CI, 1.8-10%). The high-low pressure system and the northwesterly flow are associated with the lowest mortality. The seasonal patterns are consistent with the annual pattern. For mesoscale categories, in the cold period the highest mortality is observed during days characterized by the easterly flow category (increase 9.4%; 95% CI, 1.0-18.5% compared to flow without the main component). In the warm period, the highest mortality occurs during the strong southerly flow category (8.5% increase; 95% CI, 2.0-15.4% compared again to flow without the main component). Adjusting for ambient particle levels leaves the estimated associations unchanged for the synoptic categories and slightly increases the effects of mesoscale categories. In conclusion, synoptic and mesoscale weather classification is a useful tool for studying the weather-health associations in a warm Mediterranean climate situation. PMID:11445513

Instabilities in the relation between European Weather Types and mid-latitude circulation in the Atlantic

NASA Astrophysics Data System (ADS)

Alvarez Castro, Maria del Carmen; Gallego, David; Trigo, Ricardo M.; García-Herrera, Ricardo; Ribera, Pedro

2015-04-01

Recently, a new instrumental index (Westerly Index or "WI") measuring the frequency of the westerlies over the English Channel has been developed for the period 1685-1750 (Wheeler et al. 2009) and further extended to the present (Barriopedro et al. 2014). This index holds a climatic signal similar to the North Atlantic Oscillation (NAO) in the temperature and precipitation over large areas of Europe. Nevertheless we are confident that the WI offers two major advantages: first the WI signatures are not restricted to the winter being significant during the entire year and second, the WI does not rely on proxy data and, as such, it is less prone to the uncertainties associated to the calibration process of the NAO reconstructions. During the last decades, regional mid-latitude circulation has also been quantified objectively through the widespread use of so-called Weather Types (WT). WT are used to identify and classify the different patterns of Sea Level Pressure configurations originating particular weather in a given area. In consequence, WT over most Western Europe should be closely related to atmospheric circulation indexes such as the WI. Here we adopted a similar WT classification of the classical WTs developed empirically by Hubert Lamb for the UK and automated by Jones et al. (1993) but centered at the English Channel latitudinal band to be compatible with the window used to define the WI (Wheeler et al., 2009). In this work we compare the long-term (1850-2003) monthly values of WI with the corresponding monthly frequency of directional weather types in the WI area. As expected, we found significant positive (negative) correlation values with WTs dominated by a westerly (easterly) component but interestingly, some quasi periodic intervals of lack of correlation have been found, suggesting an oscillating behaviour on the lack of stationarity between the large-scale north Atlantic circulation and local weather types. Wheeler, D.; García-Herrera, R.; Wilkinson, C.W. and Ward, C., 2009: Atmospheric circulation and storminess derived from Royal Navy logbooks: 1685 to 1750, Climatic Change, DOI: 10.1007/s10584-009-9732-x Barriopedro, D.; Gallego, D.; Alvarez-Castro, M.C.; Garcia-Herrera, R.; Wheeler, D.; Peña-Ortiz, C.; Barbosa, S.M.,2014: Witnessing North Atlantic westerlies variability from ships' logbooks (1685-2008). Clim Dym, 43, 939-955 Jones, P. D., Hulme, M., and Briffa, K. R. 1993: A comparison of Lamb circulation types with an objective classification scheme, Int. J. Climatol., 13, 655-663.

An advanced method for classifying atmospheric circulation types based on prototypes connectivity graph

NASA Astrophysics Data System (ADS)

Zagouras, Athanassios; Argiriou, Athanassios A.; Flocas, Helena A.; Economou, George; Fotopoulos, Spiros

2012-11-01

Classification of weather maps at various isobaric levels as a methodological tool is used in several problems related to meteorology, climatology, atmospheric pollution and to other fields for many years. Initially the classification was performed manually. The criteria used by the person performing the classification are features of isobars or isopleths of geopotential height, depending on the type of maps to be classified. Although manual classifications integrate the perceptual experience and other unquantifiable qualities of the meteorology specialists involved, these are typically subjective and time consuming. Furthermore, during the last years different approaches of automated methods for atmospheric circulation classification have been proposed, which present automated and so-called objective classifications. In this paper a new method of atmospheric circulation classification of isobaric maps is presented. The method is based on graph theory. It starts with an intelligent prototype selection using an over-partitioning mode of fuzzy c-means (FCM) algorithm, proceeds to a graph formulation for the entire dataset and produces the clusters based on the contemporary dominant sets clustering method. Graph theory is a novel mathematical approach, allowing a more efficient representation of spatially correlated data, compared to the classical Euclidian space representation approaches, used in conventional classification methods. The method has been applied to the classification of 850 hPa atmospheric circulation over the Eastern Mediterranean. The evaluation of the automated methods is performed by statistical indexes; results indicate that the classification is adequately comparable with other state-of-the-art automated map classification methods, for a variable number of clusters.

Classification of Clouds in Satellite Imagery Using Adaptive Fuzzy Sparse Representation.

PubMed

Jin, Wei; Gong, Fei; Zeng, Xingbin; Fu, Randi

2016-12-16

Automatic cloud detection and classification using satellite cloud imagery have various meteorological applications such as weather forecasting and climate monitoring. Cloud pattern analysis is one of the research hotspots recently. Since satellites sense the clouds remotely from space, and different cloud types often overlap and convert into each other, there must be some fuzziness and uncertainty in satellite cloud imagery. Satellite observation is susceptible to noises, while traditional cloud classification methods are sensitive to noises and outliers; it is hard for traditional cloud classification methods to achieve reliable results. To deal with these problems, a satellite cloud classification method using adaptive fuzzy sparse representation-based classification (AFSRC) is proposed. Firstly, by defining adaptive parameters related to attenuation rate and critical membership, an improved fuzzy membership is introduced to accommodate the fuzziness and uncertainty of satellite cloud imagery; secondly, by effective combination of the improved fuzzy membership function and sparse representation-based classification (SRC), atoms in training dictionary are optimized; finally, an adaptive fuzzy sparse representation classifier for cloud classification is proposed. Experiment results on FY-2G satellite cloud image show that, the proposed method not only improves the accuracy of cloud classification, but also has strong stability and adaptability with high computational efficiency.

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.

High-Luminance Road Surfaces,

DTIC Science & Technology

1980-12-01

condition was changed with the decreased use of snow chains and increasing use of studded tires. The studded tires wear down the road surface in a...region, white anorthosite of a uniform and unweathered type is usable as an additive to asphalt con- crete and wear surfacing for asphalt gravel...CLASSIFICATION Of THIS PAGE(W/em Daateoo 20. Abstract (cont’d) resistance to weathering, and the degree of luminosity. Quartzites have the best wear

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.

A two-tier atmospheric circulation classification scheme for the European-North Atlantic region

NASA Astrophysics Data System (ADS)

Guentchev, Galina S.; Winkler, Julie A.

A two-tier classification of large-scale atmospheric circulation was developed for the European-North-Atlantic domain. The classification was constructed using a combination of principal components and k-means cluster analysis applied to reanalysis fields of mean sea-level pressure for 1951-2004. Separate classifications were developed for the winter, spring, summer, and fall seasons. For each season, the two classification tiers were identified independently, such that the definition of one tier does not depend on the other tier having already been defined. The first tier of the classification is comprised of supertype patterns. These broad-scale circulation classes are useful for generalized analyses such as investigations of the temporal trends in circulation frequency and persistence. The second, more detailed tier consists of circulation types and is useful for numerous applied research questions regarding the relationships between large-scale circulation and local and regional climate. Three to five supertypes and up to 19 circulation types were identified for each season. An intuitive nomenclature scheme based on the physical entities (i.e., anomaly centers) which dominate the specific patterns was used to label each of the supertypes and types. Two example applications illustrate the potential usefulness of a two-tier classification. In the first application, the temporal variability of the supertypes was evaluated. In general, the frequency and persistence of supertypes dominated by anticyclonic circulation increased during the study period, whereas the supertypes dominated by cyclonic features decreased in frequency and persistence. The usefulness of the derived circulation types was exemplified by an analysis of the circulation associated with heat waves and cold spells reported at several cities in Bulgaria. These extreme temperature events were found to occur with a small number of circulation types, a finding that can be helpful in understanding past variability and projecting future changes in the occurrence of extreme weather and climate events.

On the role of snow cover ablation variability and synoptic-scale atmospheric forcings at the sub-basin scale within the Great Lakes watershed

NASA Astrophysics Data System (ADS)

Suriano, Zachary J.

2018-02-01

Synoptic-scale atmospheric conditions play a critical role in determining the frequency and intensity of snow cover ablation in the mid-latitudes. Using a synoptic classification technique, distinct regional circulation patterns influencing the Great Lakes basin of North America are identified and examined in conjunction with daily snow ablation events from 1960 to 2009. This approach allows for the influence of each synoptic weather type on ablation to be examined independently and for the monthly and inter-annual frequencies of the weather types to be tracked over time. Because of the spatial heterogeneity of snow cover and the relatively large geographic extent of the Great Lakes basin, snow cover ablation events and the synoptic-scale patterns that cause them are examined for each of the Great Lakes watershed's five primary sub-basins to understand the regional complexities of snow cover ablation variability. Results indicate that while many synoptic weather patterns lead to ablation across the basins, they can be generally grouped into one of only a few primary patterns: southerly flow, high-pressure overhead, and rain-on-snow patterns. As expected, the patterns leading to ablation are not necessarily consistent between the five sub-basins due to the seasonality of snow cover and the spatial variability of temperature, moisture, wind, and incoming solar radiation associated with the particular synoptic weather types. Significant trends in the inter-annual frequency of ablation-inducing synoptic types do exist for some sub-basins, indicating a potential change in the hydrologic impact of these patterns over time.

Using self-organizing maps to develop ambient air quality classifications: a time series example

PubMed Central

2014-01-01

Background Development of exposure metrics that capture features of the multipollutant environment are needed to investigate health effects of pollutant mixtures. This is a complex problem that requires development of new methodologies. Objective Present a self-organizing map (SOM) framework for creating ambient air quality classifications that group days with similar multipollutant profiles. Methods Eight years of day-level data from Atlanta, GA, for ten ambient air pollutants collected at a central monitor location were classified using SOM into a set of day types based on their day-level multipollutant profiles. We present strategies for using SOM to develop a multipollutant metric of air quality and compare results with more traditional techniques. Results Our analysis found that 16 types of days reasonably describe the day-level multipollutant combinations that appear most frequently in our data. Multipollutant day types ranged from conditions when all pollutants measured low to days exhibiting relatively high concentrations for either primary or secondary pollutants or both. The temporal nature of class assignments indicated substantial heterogeneity in day type frequency distributions (~1%-14%), relatively short-term durations (<2 day persistence), and long-term and seasonal trends. Meteorological summaries revealed strong day type weather dependencies and pollutant concentration summaries provided interesting scenarios for further investigation. Comparison with traditional methods found SOM produced similar classifications with added insight regarding between-class relationships. Conclusion We find SOM to be an attractive framework for developing ambient air quality classification because the approach eases interpretation of results by allowing users to visualize classifications on an organized map. The presented approach provides an appealing tool for developing multipollutant metrics of air quality that can be used to support multipollutant health studies. PMID:24990361

Classification of surface types using SIR-C/X-SAR, Mount Everest Area, Tibet

USGS Publications Warehouse

Albright, Thomas P.; Painter, Thomas H.; Roberts, Dar A.; Shi, Jiancheng; Dozier, Jeff; Fielding, Eric

1998-01-01

Imaging radar is a promising tool for mapping snow and ice cover in alpine regions. It combines a high-resolution, day or night, all-weather imaging capability with sensitivity to hydrologic and climatic snow and ice parameters. We use the spaceborne imaging radar-C/X-band synthetic aperture radar (SIR-C/X-SAR) to map snow and glacial ice on the rugged north slope of Mount Everest. From interferometrically derived digital elevation data, we compute the terrain calibration factor and cosine of the local illumination angle. We then process and terrain-correct radar data sets acquired on April 16, 1994. In addition to the spectral data, we include surface slope to improve discrimination among several surface types. These data sets are then used in a decision tree to generate an image classification. This method is successful in identifying and mapping scree/talus, dry snow, dry snow-covered glacier, wet snow-covered glacier, and rock-covered glacier, as corroborated by comparison with existing surface cover maps and other ancillary information. Application of the classification scheme to data acquired on October 7 of the same year yields accurate results for most surface types but underreports the extent of dry snow cover.

Above the weathering front: contrasting approaches to the study and classification of weathered mantle

NASA Astrophysics Data System (ADS)

Ehlen, Judy

2005-04-01

Weathered mantle comprises the materials above bedrock and below the soil. It can vary in thickness from millimeters to hundreds of meters, depending primarily on climate and parent material. Study of the weathered mantle comes within the realms of four disciplines: geology, geomorphology, soil science, and civil engineering, each of which uses a different approach to describe and classify the material. The approaches of engineers, geomorphologists, and geologists are contrasted and compared using example papers from the published literature. Soil scientists rarely study the weathering profile as such, and instead concentrate upon soil-forming processes and spatial distribution primarily in the solum. Engineers, including engineering geologists, study the stability and durability of the weathered mantle and the strength of the materials using sophisticated procedures to classify weathered materials, but their approach tends to be one-dimensional. Furthermore, they believe that the study of mineralogy and chemistry is not useful. Geomorphologists deal with weathering in terms of process—how the weathered mantle is formed—and with respect to landform evolution using a spatial approach. Geologists tend to ignore the weathered mantle because it is not bedrock, or to study its mineralogy and/or chemistry in the laboratory. I recommend that the approaches of the various disciplines be integrated—geomorphologists and geologists should consider using engineering weathering classifications, and geologists should adopt a spatial perspective to weathering, as should engineers and engineering geologists.

Classification of Baltic Sea ice types by airborne multifrequency microwave radiometer

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

Kurvonen, L.; Hallikainen, M.

An airborne multifrequency radiometer (24, 34, 48, and 94 GHz, vertical polarization) was used to investigate the behavior of the brightness temperature of different sea ice types in the Gulf of Bothnia (Baltic Sea). The measurements and the main results of the analysis are presented. The measurements were made in dry and wet conditions (air temperature above and below 0 C). The angle of incidence was 45{degree} in all measurements. The following topics are evaluated: (a) frequency dependency of the brightness temperature of different ice types, (b) the capability of the multifrequency radiometer to classify ice types for winter navigationmore » purposes, and (c) the optimum measurement frequencies for mapping sea ice. The weather conditions had a significant impact on the radiometric signatures of some ice types (snow-covered compact pack ice and frost-covered new ice); the impact was the highest at 94 GHz. In all cases the overall classification accuracy was around 90% (the kappa coefficient was from 0.86 to 0.96) when the optimum channel combination (24/34 GHz and 94 GHz) was used.« less

Vessel classification in overhead satellite imagery using weighted "bag of visual words"

NASA Astrophysics Data System (ADS)

Parameswaran, Shibin; Rainey, Katie

2015-05-01

Vessel type classification in maritime imagery is a challenging problem and has applications to many military and surveillance applications. The ability to classify a vessel correctly varies significantly depending on its appearance which in turn is affected by external factors such as lighting or weather conditions, viewing geometry and sea state. The difficulty in classifying vessels also varies among different ship types as some types of vessels show more within-class variation than others. In our previous work, we showed that the bag of visual words" (V-BoW) was an effective feature representation for this classification task in the maritime domain. The V-BoW feature representation is analogous to the bag of words" (BoW) representation used in information retrieval (IR) application in text or natural language processing (NLP) domain. It has been shown in the textual IR applications that the performance of the BoW feature representation can be improved significantly by applying appropriate term-weighting such as log term frequency, inverse document frequency etc. Given the close correspondence between textual BoW (T-BoW) and V-BoW feature representations, we propose to apply several well-known term weighting schemes from the text IR domain on V-BoW feature representation to increase its ability to discriminate between ship types.

Classification of Clouds in Satellite Imagery Using Adaptive Fuzzy Sparse Representation

PubMed Central

Jin, Wei; Gong, Fei; Zeng, Xingbin; Fu, Randi

2016-01-01

Automatic cloud detection and classification using satellite cloud imagery have various meteorological applications such as weather forecasting and climate monitoring. Cloud pattern analysis is one of the research hotspots recently. Since satellites sense the clouds remotely from space, and different cloud types often overlap and convert into each other, there must be some fuzziness and uncertainty in satellite cloud imagery. Satellite observation is susceptible to noises, while traditional cloud classification methods are sensitive to noises and outliers; it is hard for traditional cloud classification methods to achieve reliable results. To deal with these problems, a satellite cloud classification method using adaptive fuzzy sparse representation-based classification (AFSRC) is proposed. Firstly, by defining adaptive parameters related to attenuation rate and critical membership, an improved fuzzy membership is introduced to accommodate the fuzziness and uncertainty of satellite cloud imagery; secondly, by effective combination of the improved fuzzy membership function and sparse representation-based classification (SRC), atoms in training dictionary are optimized; finally, an adaptive fuzzy sparse representation classifier for cloud classification is proposed. Experiment results on FY-2G satellite cloud image show that, the proposed method not only improves the accuracy of cloud classification, but also has strong stability and adaptability with high computational efficiency. PMID:27999261

Winter air-mass-based synoptic climatological approach and hospital admissions for myocardial infarction in Florence, Italy.

PubMed

Morabito, Marco; Crisci, Alfonso; Grifoni, Daniele; Orlandini, Simone; Cecchi, Lorenzo; Bacci, Laura; Modesti, Pietro Amedeo; Gensini, Gian Franco; Maracchi, Giampiero

2006-09-01

The aim of this study was to evaluate the relationship between the risk of hospital admission for myocardial infarction (MI) and the daily weather conditions during the winters of 1998-2003, according to an air-mass-based synoptic climatological approach. The effects of time lag and 2-day sequences with specific air mass types were also investigated. Studies concerning the relationship between atmospheric conditions and human health need to take into consideration simultaneous effects of many weather variables. At the moment few studies have surveyed these effects on hospitalizations for MI. Analyses were concentrated on winter, when the maximum peak of hospitalization occurred. An objective daily air mass classification by means of statistical analyses based on ground meteorological data was carried out. A comparison between air mass classification and hospital admissions was made by the calculation of a MI admission index, and to detect significant relationships the Mann-Whitney U test, the analysis of variance, and the Bonferroni test were used. Significant increases in hospital admissions for MI were evident 24h after a day characterized by an anticyclonic continental air mass and 6 days after a day characterized by a cyclonic air mass. Increased risk of hospitalization was found even when specific 2-day air mass sequences occurred. These results represent an important step in identifying reliable linkages between weather and health.

Use of Dual Polarization Radar in Validation of Satellite Precipitation Measurements: Rationale and Opportunities

NASA Technical Reports Server (NTRS)

Chandrasekar, V.; Hou, Arthur; Smith, Eric; Bringi, V. N.; Rutledge, S. A.; Gorgucci, E.; Petersen, W. A.; SkofronickJackson, Gail

2008-01-01

Dual-polarization weather radars have evolved significantly in the last three decades culminating in the operational deployment by the National Weather Service. In addition to operational applications in the weather service, dual-polarization radars have shown significant potential in contributing to the research fields of ground based remote sensing of rainfall microphysics, study of precipitation evolution and hydrometeor classification. Furthermore the dual-polarization radars have also raised the awareness of radar system aspects such as calibration. Microphysical characterization of precipitation and quantitative precipitation estimation are important applications that are critical in the validation of satellite borne precipitation measurements and also serves as a valuable tool in algorithm development. This paper presents the important role played by dual-polarization radar in validating space borne precipitation measurements. Starting from a historical evolution, the various configurations of dual-polarization radar are presented. Examples of raindrop size distribution retrievals and hydrometeor type classification are discussed. The quantitative precipitation estimation is a product of direct relevance to space borne observations. During the TRMM program substantial advancement was made with ground based polarization radars specially collecting unique observations in the tropics which are noted. The scientific accomplishments of relevance to space borne measurements of precipitation are summarized. The potential of dual-polarization radars and opportunities in the era of global precipitation measurement mission is also discussed.

Looking at Earth from Space: Teacher's Guide with Activities for Earth and Space Science

NASA Technical Reports Server (NTRS)

Steele, Colleen (Editor); Steele, Colleen; Ryan, William F.

1995-01-01

The Maryland Pilot Earth Science and Technology Education Network (MAPS-NET) project was sponsored by the National Aeronautics and Space Administration (NASA) to enrich teacher preparation and classroom learning in the area of Earth system science. This publication includes a teacher's guide that replicates material taught during a graduate-level course of the project and activities developed by the teachers. The publication was developed to provide teachers with a comprehensive approach to using satellite imagery to enhance science education. The teacher's guide is divided into topical chapters and enables teachers to expand their knowledge of the atmosphere, common weather patterns, and remote sensing. Topics include: weather systems and satellite imagery including mid-latitude weather systems; wave motion and the general circulation; cyclonic disturbances and baroclinic instability; clouds; additional common weather patterns; satellite images and the internet; environmental satellites; orbits; and ground station set-up. Activities are listed by suggested grade level and include the following topics: using weather symbols; forecasting the weather; cloud families and identification; classification of cloud types through infrared Automatic Picture Transmission (APT) imagery; comparison of visible and infrared imagery; cold fronts; to ski or not to ski (imagery as a decision making tool), infrared and visible satellite images; thunderstorms; looping satellite images; hurricanes; intertropical convergence zone; and using weather satellite images to enhance a study of the Chesapeake Bay. A list of resources is also included.

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.

Optimal Day-Ahead Scheduling of a Hybrid Electric Grid Using Weather Forecasts

DTIC Science & Technology

2013-12-01

ahead scheduling, Weather forecast , Wind power , Photovoltaic Power 15. NUMBER OF PAGES 107 16. PRICE CODE 17. SECURITY CLASSIFICATION OF...cost can be reached by accurately anticipating the future renewable power productions. This thesis suggests the use of weather forecasts to establish...reached by accurately anticipating the future renewable power productions. This thesis suggests the use of weather forecasts to establish day-ahead

Corn and soybean Landsat MSS classification performance as a function of scene characteristics

NASA Technical Reports Server (NTRS)

Batista, G. T.; Hixson, M. M.; Bauer, M. E.

1982-01-01

In order to fully utilize remote sensing to inventory crop production, it is important to identify the factors that affect the accuracy of Landsat classifications. The objective of this study was to investigate the effect of scene characteristics involving crop, soil, and weather variables on the accuracy of Landsat classifications of corn and soybeans. Segments sampling the U.S. Corn Belt were classified using a Gaussian maximum likelihood classifier on multitemporally registered data from two key acquisition periods. Field size had a strong effect on classification accuracy with small fields tending to have low accuracies even when the effect of mixed pixels was eliminated. Other scene characteristics accounting for variability in classification accuracy included proportions of corn and soybeans, crop diversity index, proportion of all field crops, soil drainage, slope, soil order, long-term average soybean yield, maximum yield, relative position of the segment in the Corn Belt, weather, and crop development stage.

Excavatability and the effect of weathering degree on the excavatability of rock masses: An example from Eastern Turkey

NASA Astrophysics Data System (ADS)

Gurocak, Zulfu; Yalcin, Erkut

2016-06-01

In this study, the effect of the weathering degree on the excavatability of rock masses was investigated. The ophiolitic rock mass along the route of Komurhan Tunnel was chosen as the case study. Both laboratory and field studies were carried out for this purpose. In the first stage, the ophiolitic rock mass along the tunnel route was classified into three subzones according to the weathering degree and the ophiolitic rock masses of the each subzones were classified using the empirical excavatability classifications proposed by the different researchers. Furthermore, in-situ excavatability classes of rock masses in each zone were determined and the results were compared. The in-situ excavatability class of fresh (Zone-I) and slightly weathered (Zone-II) rock masses was determined as Blasting and that of moderately weathered (Zone-III) rock mass was determined as Very Hard/Very Difficult. As the obtained results were compared, it was found that the weathering degree has a significant effect on the excavatability and that it is more appropriate to prefer empirical classifications in the empirical determination of excavatability classes of rock masses having the same lithology by taking the weathering degree into account.

On the relationship between atmospheric rivers, weather types and floods in Galicia (NW Spain)

NASA Astrophysics Data System (ADS)

Eiras-Barca, Jorge; Lorenzo, Nieves; Taboada, Juan; Robles, Alba; Miguez-Macho, Gonzalo

2018-06-01

Atmospheric rivers (ARs) - long and narrow structures of anomalously high water vapor flux located in the warm sector of extratropical cyclones - have been shown to be closely related to extreme precipitation and flooding. In this paper we analyze the connection between ARs and flooding in the northwestern Spanish region of Galicia under a variety of synoptic conditions represented by the so-called weather types, a classification of daily sea-level pressure patterns obtained by means of a simple scheme that adopts the subjective procedure of Lamb. Flood events are identified from official reports conducted by the Spanish emergency management agency (Protección Civil) from 1979 to 2010. Our results suggest that, although most flood events in Galicia do not coincide with the presence of an overhead AR, ARs are present in the majority of severe cases, particularly in coastal areas. Flood events associated with ARs are connected to cyclonic weather types with westerly and southwesterly flows, which occur mostly in winter months. The link between ARs and severe flooding is not very apparent in inland areas or during summer months, in which case heavy precipitation is usually not frontal in nature but rather convective. Nevertheless, our results show that, in general, the amount of precipitation in flood events in Galicia more than doubles when an AR is present.

The COST733 circulation type classification software: an example for surface ozone concentrations in Central Europe

NASA Astrophysics Data System (ADS)

Demuzere, Matthias; Kassomenos, P.; Philipp, A.

2011-08-01

In the framework of the COST733 Action "Harmonisation and Applications of Weather Types Classifications for European Regions" a new circulation type classification software (hereafter, referred to as cost733class software) is developed. The cost733class software contains a variety of (European) classification methods and is flexible towards choice of domain of interest, input variables, time step, number of circulation types, sequencing and (weighted) target variables. This work introduces the capabilities of the cost733class software in which the resulting circulation types (CTs) from various circulation type classifications (CTCs) are applied on observed summer surface ozone concentrations in Central Europe. Firstly, the main characteristics of the CTCs in terms of circulation pattern frequencies are addressed using the baseline COST733 catalogue (cat 2.0), at present the latest product of the new cost733class software. In a second step, the probabilistic Brier skill score is used to quantify the explanatory power of all classifications in terms of the maximum 8 hourly mean ozone concentrations exceeding the 120-μg/m3 threshold; this was based on ozone concentrations from 130 Central European measurement stations. Averaged evaluation results over all stations indicate generally higher performance of CTCs with a higher number of types. Within the subset of methodologies with a similar number of types, the results suggest that the use of CTCs based on optimisation algorithms are performing slightly better than those which are based on other algorithms (predefined thresholds, principal component analysis and leader algorithms). The results are further elaborated by exploring additional capabilities of the cost733class software. Sensitivity experiments are performed using different domain sizes, input variables, seasonally based classifications and multiple-day sequencing. As an illustration, CTCs which are also conditioned towards temperature with various weights are derived and tested similarly. All results exploit a physical interpretation by adapting the environment-to-circulation approach, providing more detailed information on specific synoptic conditions prevailing on days with high surface ozone concentrations. This research does not intend to bring forward a favourite classification methodology or construct a statistical ozone forecasting tool but should be seen as an introduction to the possibilities of the cost733class software. It this respect, the results presented here can provide a basic user support for the cost733class software and the development of a more user- or application-specific CTC approach.

Antarctic meteorite newsletter. Volume 4: Number 1, February 1981: Antarctic meteorite descriptions, 1976, 1977, 1978, 1979

NASA Technical Reports Server (NTRS)

Stone, R.; Schwarz, C. M.; King, T. V. V.; Mason, B.; Bogard, D. D.; Gabel, E. M.

1981-01-01

This issue of the Newsletter is essentially a catalog of all antarctic meteorites in the collections of the Johnson Space Center Curation Facility and the Smithsonian except for 288 pebbles now being classed. It includes listings of all previously distributed data sheets plus a number of new ones for 1979. Indexes of samples include meteorite name/number, classification, and weathering category. Separate indexes list type 3 and 4 chondrites, all irons, all achondrites, and all carbonaceous chondrites.

Variation and co-variation of PM10, particle number concentration, NOx and NO2 in the urban air - Relationships with wind speed, vertical temperature gradient and weather type

NASA Astrophysics Data System (ADS)

Grundström, M.; Hak, C.; Chen, D.; Hallquist, M.; Pleijel, H.

2015-11-01

Atmospheric ultrafine particles (UFP; diameter < 0.1 μm) represent a growing global health concern in urban environments and has a strong link to traffic related emissions. UFP is usually the dominating fraction of atmospheric particle number concentrations (PNC) despite being a minor part of total particle mass. The aim of this study was to empirically investigate the relationship between PNC and other air pollutants (NOX, NO2 and PM10) in the urban environment and their dependence on meteorology and weather type, using the Lamb Weather Type (LWT) classification scheme. The study was carried out in Gothenburg, Sweden, at an urban background site during April 2007-May 2008. It was found that daily average [PNC] correlated very well with [NOx] (R2 = 0.73) during inversion days, to a lesser extent with [NO2] (R2 = 0.58) and poorly with [PM10] (R2 = 0.07). Both PNC and NOx had similar response patterns to wind speed and to the strength of temperature inversions. PNC displayed two regimes, one strongly correlated to NOx and a second poorly correlated to NOx which was characterised by high wind speed. For concentration averages based on LWTs, the PNC-[NOx] relationship remained strong (R2 = 0.70) where the windy LWT W deviated noticeably. Exclusion of observations with wind speed >5 ms-1 or ΔT < 0 °C from LWTs produced more uniform and stronger relationships (R2 = 0.90; R2 = 0.93). Low wind speeds and positive vertical temperature gradients were most common during LWTs A, NW, N and NE. These weather types were also associated with the highest daily means of NOx (∼30 ppb) and PNC (∼10 000 # cm-3). A conclusion from this study is that NOx (but not PM10) is a good proxy for PNC especially during calm and stable conditions and that LWTs A, NW, N and NE are high risk weather types for elevated NOx and PNC.

Correlations between the modelled potato crop yield and the general atmospheric circulation

NASA Astrophysics Data System (ADS)

Sepp, Mait; Saue, Triin

2012-07-01

Biology-related indicators do not usually depend on just one meteorological element but on a combination of several weather indicators. One way to establish such integral indicators is to classify the general atmospheric circulation into a small number of circulation types. The aim of present study is to analyse connections between general atmospheric circulation and potato crop yield in Estonia. Meteorologically possible yield (MPY), calculated by the model POMOD, is used to characterise potato crop yield. Data of three meteorological stations and the biological parameters of two potato sorts were applied to the model, and 73 different classifications of atmospheric circulation from catalogue 1.2 of COST 733, domain 05 are used to qualify circulation conditions. Correlation analysis showed that there is at least one circulation type in each of the classifications with at least one statistically significant (99%) correlation with potato crop yield, whether in Kuressaare, Tallinn or Tartu. However, no classifications with circulation types correlating with MPY in all three stations at the same time were revealed. Circulation types inducing a decrease in the potato crop yield are more clearly represented. Clear differences occurred between the observed geographical locations as well as between the seasons: derived from the number of significant circulation types, summer and Kuressaare stand out. Of potato varieties, late 'Anti' is more influenced by circulation. Analysis of MSLP maps of circulation types revealed that the seaside stations (Tallinn, Kuressaare) suffer from negative effects of anti-cyclonic conditions (drought), while Tartu suffers from the cyclonic activity (excessive water).

The Weather Forecast Using Data Mining Research Based on Cloud Computing.

NASA Astrophysics Data System (ADS)

Wang, ZhanJie; Mazharul Mujib, A. B. M.

2017-10-01

Weather forecasting has been an important application in meteorology and one of the most scientifically and technologically challenging problem around the world. In my study, we have analyzed the use of data mining techniques in forecasting weather. This paper proposes a modern method to develop a service oriented architecture for the weather information systems which forecast weather using these data mining techniques. This can be carried out by using Artificial Neural Network and Decision tree Algorithms and meteorological data collected in Specific time. Algorithm has presented the best results to generate classification rules for the mean weather variables. The results showed that these data mining techniques can be enough for weather forecasting.

NASA Space Weather Center Services: Potential for Space Weather Research

NASA Technical Reports Server (NTRS)

Zheng, Yihua; Kuznetsova, Masha; Pulkkinen, Antti; Taktakishvili, A.; Mays, M. L.; Chulaki, A.; Lee, H.; Hesse, M.

2012-01-01

The NASA Space Weather Center's primary objective is to provide the latest space weather information and forecasting for NASA's robotic missions and its partners and to bring space weather knowledge to the public. At the same time, the tools and services it possesses can be invaluable for research purposes. Here we show how our archive and real-time modeling of space weather events can aid research in a variety of ways, with different classification criteria. We will list and discuss major CME events, major geomagnetic storms, and major SEP events that occurred during the years 2010 - 2012. Highlights of major tools/resources will be provided.

The Aleutian Low and Winter Climatic Conditions in the Bering Sea. Part I: Classification

NASA Astrophysics Data System (ADS)

Rodionov, S. N.; Overland, J. E.; Bond, N. A.

2005-01-01

The Aleutian low is examined as a primary determinant of surface air temperature (SAT) variability in the Bering Sea during the winter (December-January-February-March (DJFM)) months. The Classification and Regression Tree (CART) method is used to classify five types of atmospheric circulation for anomalously warm months (W1-W5) and cold months (C1-C5). For the Bering Sea, changes in the position of the Aleutian low are shown to be more important than changes in its central pressure. The first two types, W1 and C1, account for 51% of the "warm" and 37% of the "cold" months. The W1-type pattern is characterized by the anomalously deep Aleutian low shifted west and north of its mean position. In this situation, an increased cyclonic activity occurs in the western Bering Sea. The C1-type pattern represents a split Aleutian low with one center in the northwestern Pacific and the other in the Gulf of Alaska. The relative frequency of the W1 to C1 types of atmospheric circulation varies on decadal time scales, which helps to explain the predominance of fluctuations on these time scales in the weather of the Bering Sea. Previous work has noted the prominence of multidecadal variability in the North Pacific. The present study finds multidecadal variations in frequencies of the W3 and C3 patterns, both of which are characterized by increased cyclonic activity south of 51°N. In general, the CART method is found to be a suitable means for characterizing the wintertime atmospheric circulation of the North Pacific in terms of its impact on the Bering Sea. The results show that similar pressure anomaly patterns for the North Pacific as a whole can actually result in different conditions for the Bering Sea, and that similar weather conditions in the Bering Sea can arise from decidedly different large-scale pressure patterns.

A HIERARCHIAL STOCHASTIC MODEL OF LARGE SCALE ATMOSPHERIC CIRCULATION PATTERNS AND MULTIPLE STATION DAILY PRECIPITATION

EPA Science Inventory

A stochastic model of weather states and concurrent daily precipitation at multiple precipitation stations is described. our algorithms are invested for classification of daily weather states; k means, fuzzy clustering, principal components, and principal components coupled with ...

Toward autonomous driving: The CMU Navlab. I - Perception

NASA Technical Reports Server (NTRS)

Thorpe, Charles; Hebert, Martial; Kanade, Takeo; Shafer, Steven

1991-01-01

The Navlab project, which seeks to build an autonomous robot that can operate in a realistic environment with bad weather, bad lighting, and bad or changing roads, is discussed. The perception techniques developed for the Navlab include road-following techniques using color classification and neural nets. These are discussed with reference to three road-following systems, SCARF, YARF, and ALVINN. Three-dimensional perception using three types of terrain representation (obstacle maps, terrain feature maps, and high-resolution maps) is examined. It is noted that perception continues to be an obstacle in developing autonomous vehicles.

Weather Types, temperature and relief relationship in the Iberian Peninsula: A regional adiabatic processes under directional weather types

NASA Astrophysics Data System (ADS)

Peña Angulo, Dhais; Trigo, Ricardo; Cortesi, Nicola; Gonzalez-Hidalgo, Jose Carlos

2016-04-01

We have analyzed at monthly scale the spatial distribution of Pearson correlation between monthly mean of maximum (Tmax) and minimum (Tmin) temperatures with weather types (WTs) in the Iberian Peninsula (IP), represent them in a high spatial resolution grid (10km x 10km) from MOTEDAS dataset (Gonzalez-Hidalgo et al., 2015a). The WT classification was that developed by Jenkinson and Collison, adapted to the Iberian Peninsula by Trigo and DaCamara, using Sea Level Pressure data from NCAR/NCEP Reanalysis dataset (period 1951-2010). The spatial distribution of Pearson correlations shows a clear zonal gradient in Tmax under the zonal advection produced in westerly (W) and easterly (E) flows, with negative correlation in the coastland where the air mass come from but positive correlation to the inland areas. The same is true under North-West (NW), North-East (NE), South-West (SW) and South-East (SE) WTs. These spatial gradients are coherent with the spatial distribution of the main mountain chain and offer an example of regional adiabatic phenomena that affect the entire IP (Peña-Angulo et al., 2015b). These spatial gradients have not been observed in Tmin. We suggest that Tmin values are less sensitive to changes in Sea Level Pressure and more related to local factors. These directional WT present a monthly frequency over 10 days and could be a valuable tool for downscaling processes. González-Hidalgo J.C., Peña-Angulo D., Brunetti M., Cortesi, C. (2015a): MOTEDAS: a new monthly temperature database for mainland Spain and the trend in temperature (1951-2010). International Journal of Climatology 31, 715-731. DOI: 10.1002/joc.4298 Peña-Angulo, D., Trigo, R., Cortesi, C., González-Hidalgo, J.C. (2015b): The influence of weather types on the monthly average maximum and minimum temperatures in the Iberian Peninsula. Submitted to Hydrology and Earth System Sciences.

The Optimization of Trained and Untrained Image Classification Algorithms for Use on Large Spatial Datasets

NASA Technical Reports Server (NTRS)

Kocurek, Michael J.

2005-01-01

The HARVIST project seeks to automatically provide an accurate, interactive interface to predict crop yield over the entire United States. In order to accomplish this goal, large images must be quickly and automatically classified by crop type. Current trained and untrained classification algorithms, while accurate, are highly inefficient when operating on large datasets. This project sought to develop new variants of two standard trained and untrained classification algorithms that are optimized to take advantage of the spatial nature of image data. The first algorithm, harvist-cluster, utilizes divide-and-conquer techniques to precluster an image in the hopes of increasing overall clustering speed. The second algorithm, harvistSVM, utilizes support vector machines (SVMs), a type of trained classifier. It seeks to increase classification speed by applying a "meta-SVM" to a quick (but inaccurate) SVM to approximate a slower, yet more accurate, SVM. Speedups were achieved by tuning the algorithm to quickly identify when the quick SVM was incorrect, and then reclassifying low-confidence pixels as necessary. Comparing the classification speeds of both algorithms to known baselines showed a slight speedup for large values of k (the number of clusters) for harvist-cluster, and a significant speedup for harvistSVM. Future work aims to automate the parameter tuning process required for harvistSVM, and further improve classification accuracy and speed. Additionally, this research will move documents created in Canvas into ArcGIS. The launch of the Mars Reconnaissance Orbiter (MRO) will provide a wealth of image data such as global maps of Martian weather and high resolution global images of Mars. The ability to store this new data in a georeferenced format will support future Mars missions by providing data for landing site selection and the search for water on Mars.

Silesia Dryvit

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

Presz, K.

1995-12-31

MT International, as a manufacturer and distributor for of US company named Dryvit Systems is focused on weatherization techniques as well as on facade and external wall finishing. The materials manufactured by Dryvit for building and construction purposes (plaster masses, building binders, insulating materials, reinforced fabric, etc.) are used at many sites. The consistent and well-selected composition of these materials guarantees highest quality of facade finishing in building structures of any type. The first implementation of Dryvit system in Warsaw was completed in 1974 and it remains the first exampled of professionally weatherized building in Poland. Different versions of Dryvitmore » system have been elaborated for various plaster base types. Consequently the assembling procedure differs, too. The main classification includes methods used directly on-site by a specialized contractor as well as prefabrication systems in which the ready-made elements prefabricated in a central plant or in a moveable unit are mounted on the walls. Distribution of materials and systems is based upon a network of branch offices and plaster mass mixter plants located in Warsaw, Szczecin, Lublin, Gdansk and Zabrze.« less

Probabilistic Space Weather Forecasting: a Bayesian Perspective

NASA Astrophysics Data System (ADS)

Camporeale, E.; Chandorkar, M.; Borovsky, J.; Care', A.

2017-12-01

Most of the Space Weather forecasts, both at operational and research level, are not probabilistic in nature. Unfortunately, a prediction that does not provide a confidence level is not very useful in a decision-making scenario. Nowadays, forecast models range from purely data-driven, machine learning algorithms, to physics-based approximation of first-principle equations (and everything that sits in between). Uncertainties pervade all such models, at every level: from the raw data to finite-precision implementation of numerical methods. The most rigorous way of quantifying the propagation of uncertainties is by embracing a Bayesian probabilistic approach. One of the simplest and most robust machine learning technique in the Bayesian framework is Gaussian Process regression and classification. Here, we present the application of Gaussian Processes to the problems of the DST geomagnetic index forecast, the solar wind type classification, and the estimation of diffusion parameters in radiation belt modeling. In each of these very diverse problems, the GP approach rigorously provide forecasts in the form of predictive distributions. In turn, these distributions can be used as input for ensemble simulations in order to quantify the amplification of uncertainties. We show that we have achieved excellent results in all of the standard metrics to evaluate our models, with very modest computational cost.

Classification of weather patterns to study the influence of meteorological characteristics on PM2.5 concentrations in Yunlin County, Taiwan

NASA Astrophysics Data System (ADS)

Hsu, Chia-Hua; Cheng, Fang-Yi

2016-11-01

Yunlin County is located in the central part of western Taiwan with major emissions from the Mailiao industrial park, the Taichung Power Plants and heavy traffic. In order to understand the influence of meteorological conditions on PM2.5 concentrations in Yunlin County, we applied a two-stage cluster analysis method using the daily averaged surface winds from four air quality monitoring stations in Yunlin County to classify the weather pattern. The study period includes 1095 days from Jan 2013 to December 2015. The classification results show that the low PM2.5 concentration occurs when the synoptic weather in Taiwan is affected by the strong southwesterly monsoonal flow. The high PM2.5 concentration occurs when Taiwan is under the influence of weak synoptic weather conditions and continental high-pressure peripheral circulation. A high PM2.5 event was studied and the Weather Research and Forecasting (WRF) meteorological model was performed. The result indicated that due to being blocked by the Central Mountain Range, Yunlin County, which is situated on the leeside of the mountains, exhibits low wind speed and strong subsidence behavior that favors PM2.5 accumulation.

Pattern recognition of satellite cloud imagery for improved weather prediction

NASA Technical Reports Server (NTRS)

Gautier, Catherine; Somerville, Richard C. J.; Volfson, Leonid B.

1986-01-01

The major accomplishment was the successful development of a method for extracting time derivative information from geostationary meteorological satellite imagery. This research is a proof-of-concept study which demonstrates the feasibility of using pattern recognition techniques and a statistical cloud classification method to estimate time rate of change of large-scale meteorological fields from remote sensing data. The cloud classification methodology is based on typical shape function analysis of parameter sets characterizing the cloud fields. The three specific technical objectives, all of which were successfully achieved, are as follows: develop and test a cloud classification technique based on pattern recognition methods, suitable for the analysis of visible and infrared geostationary satellite VISSR imagery; develop and test a methodology for intercomparing successive images using the cloud classification technique, so as to obtain estimates of the time rate of change of meteorological fields; and implement this technique in a testbed system incorporating an interactive graphics terminal to determine the feasibility of extracting time derivative information suitable for comparison with numerical weather prediction products.

Hydrogeochemistry for the assessment of groundwater quality in Varanasi: a fast-urbanizing center in Uttar Pradesh, India.

PubMed

Janardhana Raju, Nandimandalam; Shukla, U K; Ram, Prahlad

2011-02-01

The hydrogeochemical parameters for groundwater samples of the Varanasi area, a fast-urbanizing region in India, were studied to evaluate the major ion chemistry, weathering and solute acquisition processes controlling water composition, and suitability of water quality for domestic and irrigation uses. Sixty-eight groundwater samples were collected randomly from dug wells and hand pumps in the urban Varanasi area and analyzed for various chemical parameters. Geologically, the study area comprises Quaternary alluvium made up of an alternating succession of clay, silty clay, and sand deposits. The Total dissolved solids classification reveals that except two locations, the groundwater samples are desirable for drinking, and all are useful for irrigation purposes. The cationic and anionic concentrations indicated that the majority of the groundwater samples belong to the order of Na>Ca>Mg>K and HCO3>Cl>SO4 types, respectively. Geochemical classification of groundwater based on the Chadha rectangular diagram shows that the majority (81%) of groundwater samples belong to the calcium-bicarbonate type. The HCO3/(HCO3+SO4) ratio (0.87) indicates mostly carbonic acid weathering process due to presence of kankar carbonate mixed with clay/fine sand. The high nitrate concentration (>45 mg/l) of about 18% of the groundwater samples may be due to the local domestic sewage, leakage of septic tanks, and improper management of sanitary landfills. In general, the calculated values of sodium adsorption ratio, percent sodium, residual sodium carbonate, and permeability index indicate good to permissible use of water for irrigation, and only a few locations demand remedial measures for better crop yields.

Automated cloud classification using a ground based infra-red camera and texture analysis techniques

NASA Astrophysics Data System (ADS)

Rumi, Emal; Kerr, David; Coupland, Jeremy M.; Sandford, Andrew P.; Brettle, Mike J.

2013-10-01

Clouds play an important role in influencing the dynamics of local and global weather and climate conditions. Continuous monitoring of clouds is vital for weather forecasting and for air-traffic control. Convective clouds such as Towering Cumulus (TCU) and Cumulonimbus clouds (CB) are associated with thunderstorms, turbulence and atmospheric instability. Human observers periodically report the presence of CB and TCU clouds during operational hours at airports and observatories; however such observations are expensive and time limited. Robust, automatic classification of cloud type using infrared ground-based instrumentation offers the advantage of continuous, real-time (24/7) data capture and the representation of cloud structure in the form of a thermal map, which can greatly help to characterise certain cloud formations. The work presented here utilised a ground based infrared (8-14 μm) imaging device mounted on a pan/tilt unit for capturing high spatial resolution sky images. These images were processed to extract 45 separate textural features using statistical and spatial frequency based analytical techniques. These features were used to train a weighted k-nearest neighbour (KNN) classifier in order to determine cloud type. Ground truth data were obtained by inspection of images captured simultaneously from a visible wavelength colour camera at the same installation, with approximately the same field of view as the infrared device. These images were classified by a trained cloud observer. Results from the KNN classifier gave an encouraging success rate. A Probability of Detection (POD) of up to 90% with a Probability of False Alarm (POFA) as low as 16% was achieved.

Classifying Urban Space Types of Seoul using Time-series Heat Island map

NASA Astrophysics Data System (ADS)

Jung, S.; KIM, H.; JE, M.

2017-12-01

In August 2016, the hottest heat occurred in Korea since the weather observation started in Korea. Due to climate changes, this heat phenomenon is expected to be severe more in the future. Thus, this study analyzed the heatwave occurred in 2016 with regard to Seoul from various angles to identify the characteristics of urban regions where the heat island phenomenon occurred. To do this, first, temperature data for two days on August 6 and 12 in 2016 when the hottest heatwave occurred were collected from 287 places of automatic weather stations (AWS) installed in Seoul and adjacent suburbs. The temperature distribution of Seoul was mapped using interpolation in every hour using the collected temperature data. Second, regions in Seoul were classified using statistical methods based on spatial characteristics such as land coverage, density, use type, and traffic volume in Seoul. Third, a daily pattern of change in temperature in the classified regions was depicted with a graph, and regions were re-classified based on the daily pattern of change in temperature. Finally, the characteristics of the classified regions were re-reviewed and then, heat island occurrence, continuation, and reduction measure by region type were discussed. The analysis results showed that a pattern of heatwave occurrence was exhibited differently by the classified region type. The results also showed that not only physical characteristics such as land coverage but also socioeconomic index such as population density and floating population that induced a traffic volume influenced the pattern of heatwave occurrence despite of the same land usage regions. This study not only classified urban climate regions by existing mean temperature and specific time-point temperature but also proposed a methodology that analyzed heat island phenomenon inside cities by using time-series temperature data in a day. Furthermore, this study enabled regional classification based on heat island characteristics to contribute to establishment of measure for each regional classification.

Using Conditional Analysis to Investigate Spatial and Temporal patterns in Upland Rainfall

NASA Astrophysics Data System (ADS)

Sakamoto Ferranti, Emma Jayne; Whyatt, James Duncan; Timmis, Roger James

2010-05-01

The seasonality and characteristics of rainfall in the UK are altering under a changing climate. Summer rainfall is generally decreasing whereas winter rainfall is increasing, particularly in northern and western areas (Maraun et al., 2008) and recent research suggests these rainfall increases are amplified in upland areas (Burt and Ferranti, 2010). Conditional analysis has been used to investigate these rainfall patterns in Cumbria, an upland area in northwest England. Cumbria was selected as an example of a topographically diverse mid-latitude region that has a predominately maritime and westerly-defined climate. Moreover it has a dense network of more than 400 rain gauges that have operated for periods between 1900 and present day. Cumbria has experienced unprecedented flooding in the past decade and understanding the spatial and temporal changes in this and other upland regions is important for water resource and ecosystem management. The conditional analysis method examines the spatial and temporal variations in rainfall under different synoptic conditions and in different geographic sub-regions (Ferranti et al., 2009). A daily synoptic typing scheme, the Lamb Weather Catalogue, was applied to classify rainfall into different weather types, for example: south-westerly, westerly, easterly or cyclonic. Topographic descriptors developed using GIS were used to classify rain gauges into 6 directionally-dependant geographic sub-regions: coastal, windward-lowland, windward-upland, leeward-upland, leeward-lowland, secondary upland. Combining these classification methods enabled seasonal rainfall climatologies to be produced for specific weather types and sub-regions. Winter rainfall climatologies were constructed for all 6 sub-regions for 3 weather types - south-westerly (SW), westerly (W), and cyclonic (C); these weather types contribute more than 50% of total winter rainfall. The frequency of wet-days (>0.3mm), the total winter rainfall and the average wet day rainfall amount were analysed for each rainfall sub-region and weather type from 1961-2007 (Ferranti et al., 2010). The conditional analysis showed total rainfall under SW and W weather types to be increasing, with the greatest increases observed in the upland sub-regions. The increase in total SW rainfall is driven by a greater occurrence of SW rain days, and there has been little change to the average wet-day rainfall amount. The increase in total W rainfall is driven in part by an increase in the frequency of wet-days, but more significantly by an increase in the average wet-day rainfall amount. In contrast, total rainfall under C weather types has decreased. Further analysis will investigate how spring, summer and autumn rainfall climatologies have changed for the different weather types and sub-regions. Conditional analysis that combines GIS and synoptic climatology provides greater insights into the processes underlying readily available meteorological data. Dissecting Cumbrian rainfall data under different synoptic and geographic conditions showed the observed changes in winter rainfall are not uniform for the different weather types, nor for the different geographic sub-regions. These intricate details are often lost during coarser resolution analysis, and conditional analysis will provide a detailed synopsis of Cumbrian rainfall processes against which Regional Climate Model (RCM) performance can be tested. Conventionally RCMs try to simulate composite rainfall over many different weather types and sub-regions and by undertaking conditional validation the model performance for individual processes can be tested. This will help to target improvements in model performance, and ultimately lead to better simulation of rainfall in areas of complex topography. BURT, T. P. & FERRANTI, E. J. S. (2010) Changing patterns of heavy rainfall in upland areas: a case study from northern England. Atmospheric Environment, [in review]. FERRANTI, E. J. S., WHYATT, J. D. & TIMMIS, R. J. (2009) Development and application of topographic descriptors for conditional analysis of rainfall. Atmospheric Science Letters, 10, 177-184. FERRANTI, E. J. S., WHYATT, J. D., TIMMIS, R. J. & DAVIES, G. (2010) Using GIS to investigate spatial and temporal variations in upland rainfall. Transactions in GIS, [in press]. MARAUN, D., OSBORN, T. J. & GILLETT, N. P. (2008) United Kingdom daily precipitation intensity: improved early data, error estimates and an update from 2000 to 2006. International Journal of Climatology, 28, 833-842.

Survival analysis and classification methods for forest fire size

PubMed Central

2018-01-01

Factors affecting wildland-fire size distribution include weather, fuels, and fire suppression activities. We present a novel application of survival analysis to quantify the effects of these factors on a sample of sizes of lightning-caused fires from Alberta, Canada. Two events were observed for each fire: the size at initial assessment (by the first fire fighters to arrive at the scene) and the size at “being held” (a state when no further increase in size is expected). We developed a statistical classifier to try to predict cases where there will be a growth in fire size (i.e., the size at “being held” exceeds the size at initial assessment). Logistic regression was preferred over two alternative classifiers, with covariates consistent with similar past analyses. We conducted survival analysis on the group of fires exhibiting a size increase. A screening process selected three covariates: an index of fire weather at the day the fire started, the fuel type burning at initial assessment, and a factor for the type and capabilities of the method of initial attack. The Cox proportional hazards model performed better than three accelerated failure time alternatives. Both fire weather and fuel type were highly significant, with effects consistent with known fire behaviour. The effects of initial attack method were not statistically significant, but did suggest a reverse causality that could arise if fire management agencies were to dispatch resources based on a-priori assessment of fire growth potentials. We discuss how a more sophisticated analysis of larger data sets could produce unbiased estimates of fire suppression effect under such circumstances. PMID:29320497

Survival analysis and classification methods for forest fire size.

PubMed

Tremblay, Pier-Olivier; Duchesne, Thierry; Cumming, Steven G

2018-01-01

Factors affecting wildland-fire size distribution include weather, fuels, and fire suppression activities. We present a novel application of survival analysis to quantify the effects of these factors on a sample of sizes of lightning-caused fires from Alberta, Canada. Two events were observed for each fire: the size at initial assessment (by the first fire fighters to arrive at the scene) and the size at "being held" (a state when no further increase in size is expected). We developed a statistical classifier to try to predict cases where there will be a growth in fire size (i.e., the size at "being held" exceeds the size at initial assessment). Logistic regression was preferred over two alternative classifiers, with covariates consistent with similar past analyses. We conducted survival analysis on the group of fires exhibiting a size increase. A screening process selected three covariates: an index of fire weather at the day the fire started, the fuel type burning at initial assessment, and a factor for the type and capabilities of the method of initial attack. The Cox proportional hazards model performed better than three accelerated failure time alternatives. Both fire weather and fuel type were highly significant, with effects consistent with known fire behaviour. The effects of initial attack method were not statistically significant, but did suggest a reverse causality that could arise if fire management agencies were to dispatch resources based on a-priori assessment of fire growth potentials. We discuss how a more sophisticated analysis of larger data sets could produce unbiased estimates of fire suppression effect under such circumstances.

Influence of Climate on PM2.5 Concentrations over Europe : a Meteorological Analysis using a 9-year Model Simulation

NASA Astrophysics Data System (ADS)

Lecoeur, À.; Seigneur, C.; Terray, L.; Pagé, C.

2012-04-01

In the early 1970s, it has been demonstrated that a large number of deaths and health problems are associated with particulate pollution. As a consequence, several governments have set health-based air quality standards to protect public health. Particulate matter with an aerodynamical diameter of 2.5 μg.m-3 or less (PM2.5) is particularly concerned by these measures. As PM2.5 concentrations are strongly dependent on meteorological conditions, it is important to investigate the relationships between PM2.5 and meteorological parameters. This will help to understand the processes at play and anticipate the effects of climate change on PM2.5 air quality. Most of the previous work agree that temperature, wind speed, humidity, rain rate and mixing height are the meteorological variables that impact PM2.5 concentrations the most. A large number of those studies used Global Circulation Models (GCM) and Chemical Transport Models (CTM) and focus on the USA. They typically predict a diminution of PM2.5 concentrations in the future, with some geographical and/or temporal discrepancies, when only the climate evolution is considered. When considering changes in emissions along with climate, no consensus has yet been found. Furthermore, the correlations between PM2.5 concentrations and meteorological variables are often low, which prevents a straightforward analysis of their relationships. In this work, we consider that PM2.5 concentrations depend on both large-scale atmospheric circulation and local meteorological variables. We thus investigate the influence of present climate on PM2.5 concentrations over Europe by representing it using a weather regimes/types approach. We start by exploring the relationships between classical weather regimes, meteorological variables and PM2.5 concentrations over five stations in Europe, using the EMEP air quality database. The pressure at sea level is used in the classification as it effectively describes the atmospheric circulation. We experimentally verify some intuitive results: weather regimes associated with weak (resp. high) precipitation, wind and low (resp. high) temperatures correspond to higher (resp. lower) PM2.5 concentrations. We also observe that rain rate is the variable that impacts PM2.5 concentrations the most. Next, we search for better relationships by adding this second variable to the classification: we therefore build new weather regimes, called weather types. Because of the low number of the EMEP observations, we compute PM2.5 concentrations with the Polyphemus/Polair3D CTM for years between 2000 and 2008 in order to obtain a spatially and temporally complete dataset of PM2.5 concentrations and chemical components, which can be used to relate PM2.5 concentrations to meteorological regimes and specific variables. By classifying both a large-scale variable and a local variable that influence the PM2.5 concentrations and using gridded data of the modeled concentrations of PM2.5, we obtain a more robust analysis. The results of this work will provide the basis to predict the effects of climate change (via the evolution of weather regimes/types frequencies) on PM2.5 chemical composition and concentrations.

Land use survey and mapping and water resources investigation in Korea

NASA Technical Reports Server (NTRS)

Choi, J. H.; Kim, W. I.; Son, D. S. (Principal Investigator)

1978-01-01

The author has identified the following significant results. Land use imagery is applicable to land use classification for small scale land use mapping less than 1:250,000. Land use mapping by satellite is more efficient and more cost-effective than land use mapping from conventional medium altitude aerial photographs. Six categories of level 1 land use classification are recognizable from MSS imagery. A hydrogeomorphological study of the Han River basin indicates that band 7 is useful for recognizing the soil and the weathering part of bed rock. The morphological change of the main river is accurately recognized and the drainage system in the area observed is easily classified because of the more or less simple rock type. Although the direct hydrological characteristics are not obtained from the MSS imagery, the indirect information such as the permeability of the soil and the vegetation cover, is helpful in interpreting the hydrological aspects.

Discovery of Ni-smectite-rich saprolite at Loma Ortega, Falcondo mining district (Dominican Republic): geochemistry and mineralogy of an unusual case of "hybrid hydrous Mg silicate - clay silicate" type Ni-laterite

NASA Astrophysics Data System (ADS)

Tauler, Esperança; Lewis, John F.; Villanova-de-Benavent, Cristina; Aiglsperger, Thomas; Proenza, Joaquín A.; Domènech, Cristina; Gallardo, Tamara; Longo, Francisco; Galí, Salvador

2017-10-01

Hydrous Mg silicate-type Ni-laterite deposits, like those in the Falcondo district, Dominican Republic, are dominated by Ni-enriched serpentine and garnierite. Recently, abundant Ni-smectite in the saprolite zone have been discovered in Loma Ortega, one of the nine Ni-laterite deposits in Falcondo. A first detailed study on these Ni-smectites has been performed (μXRD, SEM, EPMA), in addition to a geochemical and mineralogical characterisation of the Loma Ortega profile (XRF, ICP-MS, XRD). Unlike other smectite occurrences in laterite profiles worldwide, the Loma Ortega smectites are trioctahedral and exhibit high Ni contents never reported before. These Ni-smectites may be formed from weathering of pyroxene and olivine, and their composition can be explained by the mineralogy and the composition of the Al-depleted, olivine-rich parent ultramafic rock. Our study shows that Ni-laterites are mineralogically complex, and that a hydrous Mg silicate ore and a clay silicate ore can be confined to the same horizon in the weathering profile, which has significant implications from a recovery perspective. In accordance, the classification of "hybrid hydrous Mg silicate - clay silicate" type Ni-laterite deposit for Loma Ortega would be more appropriate.

The geography of hypothermia in the United States: An analysis of mortality, morbidity, thresholds, and messaging

NASA Astrophysics Data System (ADS)

Spencer, Jeremy M.

Hypothermia within the United States has seldom been studied from a geographic perspective. This dissertation assessed the following aspects of hypothermia: 1) A cataloging of Internet web pages containing hypothermia-related guidance, with a summary of the information contained within. The summarized hypothermia information was assessed for scientific validity through an extensive assessment of the peer-reviewed medical literature; 2) the spatio-temporal distribution of hypothermia deaths in U.S. Combined Statistical areas for the years 1979-2004, and their association with National Weather Service windchill advisory and warning thresholds; 3) the spatio-temporal distribution of hypothermia morbidity in the State of New York from 1991-1992 to 2005-2006 and its association with Spatial Synoptic Classification weather types. The results indicate that web-based hypothermia information has generally poor content not supported by the scientific literature, and there are many prominent omissions of well-established hypothermia information. A total of 9,185 hypothermia fatalities attributable to cold exposure occurred in 89 metro areas from 1979 to 2004. The southeastern US had the greatest vulnerability to hypothermia, with high rates of deaths occurring at higher temperatures than northern states. Median windchill temperature associated with deaths was generally latitudinal, with southern deaths occurring at higher temperatures. For all regions, hypothermia deaths occurred at temperatures considerably higher than windchill advisory criteria. Hypothermia morbidity within New York State was associated with long-lasting polar weather types. There are a number of findings common to these three papers. Information about hypothermia tends to be under-communicated (no central location for wind chill alerts, unsupported statements on many websites). Hypothermia deaths and hospitalizations increase when locally cold and long-lasting weather types occur, which fits in with what is known concerning heat and cold mortality. A lack of health outcome or health information to develop website information/wind chill alerts was noted. Overall, it was determined that hypothermia is a good metric for assessing cold weather-related vulnerability and that implementing health outcome-based information will help limit the hazards associated with this public health problem.

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 %.

Operationalizing Space Weather Products - Process and Issues

NASA Astrophysics Data System (ADS)

Scro, K. D.; Quigley, S.

2006-12-01

Developing and transitioning operational products for any customer base is a complicated process. This is the case for operational space weather products and services for the USAF. This presentation will provide information on the current state of affairs regarding the process required to take an idea from the research field to the real-time application of 24-hour space weather operations support. General principles and specific issues are discussed and will include: customer requirements, organizations in-play, funding, product types, acquisition of engineering and validation data, security classification, version control, and various important changes that occur during the process. The author's viewpoint is as an individual developing space environmental system-impact products for the US Air Force: 1) as a member of its primary research organization (Air Force Research Laboratory), 2) working with its primary space environment technology transition organization (Technology Application Division of the Space and Missile Systems Center, SMC/WXT), and 3) delivering to the primary sponsor/customer of such system-impact products (Air Force Space Command). The experience and focus is obviously on specific military operationalization process and issues, but most of the paradigm may apply to other (commercial) enterprises as well.

Moderate to heavy cold-weather precipitation occurrences in Tehran and the associated circulation types

NASA Astrophysics Data System (ADS)

Khansalari, Sakineh; Raziei, Tayeb; Mohebalhojeh, Ali Reza; Ahmadi-Givi, Farhang

2018-02-01

Large-scale atmospheric circulations associated with 133 moderate to heavy cold-weather precipitation events recorded at Mehrabad station in Tehran, Iran, during the period 1951-2013 are analysed. To this end, the performance of un-rotated, orthogonally rotated and obliquely rotated solutions of T-mode principal component analysis (PCA) is examined in classifying the atmospheric circulations into a few representative circulation types (CTs). The T-mode PCAs were applied to the 500-hPa geopotential height for the events in a domain from 10∘E to 70∘E and from 20∘N to 50∘N. The first six leading principal components were retained and then orthogonally and obliquely rotated using varimax and promax solutions, respectively. Statistical inter-comparison of the CTs obtained using the three solutions suggests that the obliquely rotated solution is the better choice for circulation classification in the present study. The six CTs obtained using the oblique rotation were then linked to the daily total precipitation and daily mean temperature variability at Tehran station as well as to the standardized anomalies of the daily total precipitation and mean daily temperature of a dense network of stations distributed across Iran. It is found that the CTs identified, though generally comparable in producing significant precipitation in Tehran, vary in their potential to bring cold weather and generate snowfall in Tehran specifically and in the country in general. While the first three CTs give rise to regional patterns of standardized precipitation anomalies centred in Tehran, the next three CTs leave a pronounced precipitation signature almost across the whole country. As regards the standardized temperature anomalies, with the exception of one CT that causes deep and widespread negative standardized anomalies over most parts of the country, the other CTs are characterized with a dipolar structure of a deep intrusion of cold weather to the west and prevailing warm weather to the east of the country.

Enhanced outage prediction modeling for strong extratropical storms and hurricanes in the Northeastern United States

NASA Astrophysics Data System (ADS)

Cerrai, D.; Anagnostou, E. N.; Wanik, D. W.; Bhuiyan, M. A. E.; Zhang, X.; Yang, J.; Astitha, M.; Frediani, M. E.; Schwartz, C. S.; Pardakhti, M.

2016-12-01

The overwhelming majority of human activities need reliable electric power. Severe weather events can cause power outages, resulting in substantial economic losses and a temporary worsening of living conditions. Accurate prediction of these events and the communication of forecasted impacts to the affected utilities is necessary for efficient emergency preparedness and mitigation. The University of Connecticut Outage Prediction Model (OPM) uses regression tree models, high-resolution weather reanalysis and real-time weather forecasts (WRF and NCAR ensemble), airport station data, vegetation and electric grid characteristics and historical outage data to forecast the number and spatial distribution of outages in the power distribution grid located within dense vegetation. Recent OPM improvements consist of improved storm classification and addition of new predictive weather-related variables and are demonstrated using a leave-one-storm-out cross-validation based on 130 severe extratropical storms and two hurricanes (Sandy and Irene) in the Northeast US. We show that it is possible to predict the number of trouble spots causing outages in the electric grid with a median absolute percentage error as low as 27% for some storm types, and at most around 40%, in a scale that varies between four orders of magnitude, from few outages to tens of thousands. This outage information can be communicated to the electric utility to manage allocation of crews and equipment and minimize the recovery time for an upcoming storm hazard.

An objective classification system of air mass types for Szeged, Hungary, with special attention to plant pollen levels.

PubMed

Makra, László; Juhász, Miklós; Mika, János; Bartzokas, Aristides; Béczi, Rita; Sümeghy, Zoltán

2006-07-01

This paper discusses the characteristic air mass types over the Carpathian Basin in relation to plant pollen levels over annual pollination periods. Based on the European Centre for Medium-Range Weather Forecasts dataset, daily sea-level pressure fields analysed at 00 UTC were prepared for each air mass type (cluster) in order to relate sea-level pressure patterns to pollen levels in Szeged, Hungary. The database comprises daily values of 12 meteorological parameters and daily pollen concentrations of 24 species for their pollination periods from 1997 to 2001. Characteristic air mass types were objectively defined via factor analysis and cluster analysis. According to the results, nine air mass types (clusters) were detected for pollination periods of the year corresponding to pollen levels that appear with higher concentration when irradiance is moderate while wind speed is moderate or high. This is the case when an anticyclone prevails in the region west of the Carpathian Basin and when Hungary is under the influence of zonal currents (wind speed is high). The sea level pressure systems associated with low pollen concentrations are mostly similar to those connected to higher pollen concentrations, and arise when wind speed is low or moderate. Low pollen levels occur when an anticyclone prevails in the region west of the Carpathian Basin, as well as when an anticyclone covers the region with Hungary at its centre. Hence, anticyclonic or anticyclonic ridge weather situations seem to be relevant in classifying pollen levels.

Odour-impact assessment around a landfill site from weather-type classification, complaint inventory and numerical simulation.

PubMed

Chemel, C; Riesenmey, C; Batton-Hubert, M; Vaillant, H

2012-01-01

Gases released from landfill sites into the atmosphere have the potential to cause olfactory nuisances within the surrounding communities. Landfill sites are often located over complex topography for convenience mainly related to waste disposal and environmental masking. Dispersion of odours is strongly conditioned by local atmospheric dynamics. Assessment of odour impacts needs to take into account the variability of local atmospheric dynamics. In this study, we discuss a method to assess odour impacts around a landfill site located over complex terrain in order to provide information to be used subsequently to identify management strategies to reduce olfactory nuisances in the residential neighbourhoods. A weather-type classification is defined in order to identify meteorological conditions under which olfactory nuisances are to be expected. A non-steady state Gaussian model and a full-physics meteorological model are used to predict olfactory nuisances, for both the winter and summer scenarios that lead to the majority of complaints in neighbourhoods surrounding the landfill site. Simulating representative scenarios rather than full years make a high resolution simulation of local atmospheric dynamics in space and time possible. Results underline the key role of local atmospheric dynamics in driving the dispersion of odours. The odour concentration simulated by the full-physics meteorological model is combined with the density of the population in order to calculate an average population exposure for the two scenarios. Results of this study are expected to provide helpful information to develop technical solutions for an effective management of landfill operations, which would reduce odour impacts within the surrounding communities. Copyright © 2011 Elsevier Ltd. All rights reserved.

Probabilistic discrimination between liquid rainfall events, hailstorms, biomass burning and industrial fires from C-Band Radar Polarimetric Variables

NASA Astrophysics Data System (ADS)

Valencia, J. M.; Sepúlveda, J.; Hoyos, C.; Herrera, L.

2017-12-01

Characterization and identification of fire and hailstorm events using weather radar data in a tropical complex topography region is an important task in risk management and agriculture. Polarimetric variables from a C-Band Dual polarization weather radar have potential uses in particle classification, due to the relationship their sensitivity to shape, spatial orientation, size and fall behavior of particles. In this sense, three forest fires and two chemical fires were identified for the Áburra Valley regions. Measurements were compared between each fire event type and with typical data radar retrievals for liquid precipitation events. Results of this analysis show different probability density functions for each type of event according to the particles present in them. This is very important and useful result for early warning systems to avoid precipitation false alarms during fire events within the study region, as well as for the early detection of fires using radar retrievals in remote cases. The comparative methodology is extended to hailstorm cases. Complementary sensors like laser precipitation sensors (LPM) disdrometers and meteorological stations were used to select dates of solid precipitation occurrence. Then, in this dates weather radar data variables were taken in pixels surrounding the stations and solid precipitation polar values were statistically compared with liquid precipitation values. Spectrum precipitation measured by LPM disdrometer helps to define typical features like particles number, fall velocities and diameters for both precipitation types. In addition, to achieve a complete hailstorm characterization, other meteorological variables were analyzed: wind field from meteorological stations and radar wind profiler, profiling data from Micro Rain Radar (MRR), and thermodynamic data from a microwave radiometer.

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.

Synoptic weather types and aeroallergens modify the effect of air pollution on hospitalisations for asthma hospitalisations in Canadian cities.

PubMed

Hebbern, Christopher; Cakmak, Sabit

2015-09-01

Pollution levels and the effect of air pollution on human health can be modified by synoptic weather type and aeroallergens. We investigated the effect modification of aeroallergens on the association between CO, O3, NO2, SO2, PM10, PM2.5 and asthma hospitalisation rates in seven synoptic weather types. We developed single air pollutant models, adjusted for the effect of aeroallergens and stratified by synoptic weather type, and pooled relative risk estimates for asthma hospitalisation in ten Canadian cities. Aeroallergens significantly modified the relative risk in 19 pollutant-weather type combinations, reducing the size and variance for each single pollutant model. However, aeroallergens did not significantly modify relative risk for any pollutant in the DT or MT weather types, or for PM10 in any weather type. Thus, there is a modifying effect of aeroallergens on the association between CO, O3, NO2, SO2, PM2.5 and asthma hospitalisations that differs under specific synoptic weather types. Crown Copyright © 2015. Published by Elsevier Ltd. All rights reserved.

Potential Vorticity Analysis of Low Level Thunderstorm Dynamics in an Idealized Supercell Simulation

DTIC Science & Technology

2009-03-01

Severe Weather, Supercell, Weather Research and Forecasting Model , Advanced WRF 16. PRICE CODE 17. SECURITY CLASSIFICATION OF REPORT...27 A. ADVANCED RESEARCH WRF MODEL .................................................27 1. Data, Model Setup, and Methodology...03/11/2006 GFS model run. Top row: 11/12Z initialization. Middle row: 12 hour forecast valid at 12/00Z. Bottom row: 24 hour forecast valid at

Discrimination and supervised classification of volcanic flows of the Puna-Altiplano, Central Andes Mountains using Landsat TM data

NASA Technical Reports Server (NTRS)

Mcbride, J. H.; Fielding, E. J.; Isacks, B. L.

1987-01-01

Landsat Thematic Mapper (TM) images of portions of the Central Andean Puna-Altiplano volcanic belt have been tested for the feasibility of discriminating individual volcanic flows using supervised classifications. This technique distinguishes volcanic rock classes as well as individual phases (i.e., relative age groups) within each class. The spectral signature of a volcanic rock class appears to depend on original texture and composition and on the degree of erosion, weathering, and chemical alteration. Basalts and basaltic andesite stand out as a clearly distinguishable class. The age dependent degree of weathering of these generally dark volcanic rocks can be correlated with reflectance: older rocks have a higher reflectance. On the basis of this relationship, basaltaic lava flows can be separated into several subclasses. These individual subclasses would correspond to mappable geologic units on the ground at a reconnaissance scale. The supervised classification maps are therefore useful for establishing a general stratigraphic framework for later detailed surface mapping of volcanic sequences.

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.

SALINITY AND SODICITY INTERACTIONS OF WEATHERED MINESOILS IN NORTHWESTERN NEW MEXICO AND NORTH EASTERN ARIZONA

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

Brent Musslewhite; Song Jin

2006-05-01

Weathering characteristics of minesoils and rooting patterns of key shrub and grass species were evaluated at sites reclaimed for 6 to 14 years from three surface coal mine operations in northwestern New Mexico and northeastern Arizona. Non-weathered minesoils were grouped into 11 classifications based on electrical conductivity (EC) and sodium adsorption ratio (SAR). Comparisons of saturated paste extracts, from non-weathered and weathered minesoils show significant (p < 0.05) reductions in SAR levels and increased EC. Weathering increased the apparent stability of saline and sodic minesoils thereby reducing concerns of aggregate slaking and clay particle dispersion. Root density of four-wing saltbushmore » (Atriplex canascens), alkali sacaton (Sporobolus airoides), and Russian wildrye (Psathyrostachys junceus) were nominally affected by increasing EC and SAR levels in minesoil. Results suggest that saline and sodic minesoils can be successfully reclaimed when covered with topsoil and seeded with salt tolerant plant species.« less

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).

Temporal optimisation of image acquisition for land cover classification with Random Forest and MODIS time-series

NASA Astrophysics Data System (ADS)

Nitze, Ingmar; Barrett, Brian; Cawkwell, Fiona

2015-02-01

The analysis and classification of land cover is one of the principal applications in terrestrial remote sensing. Due to the seasonal variability of different vegetation types and land surface characteristics, the ability to discriminate land cover types changes over time. Multi-temporal classification can help to improve the classification accuracies, but different constraints, such as financial restrictions or atmospheric conditions, may impede their application. The optimisation of image acquisition timing and frequencies can help to increase the effectiveness of the classification process. For this purpose, the Feature Importance (FI) measure of the state-of-the art machine learning method Random Forest was used to determine the optimal image acquisition periods for a general (Grassland, Forest, Water, Settlement, Peatland) and Grassland specific (Improved Grassland, Semi-Improved Grassland) land cover classification in central Ireland based on a 9-year time-series of MODIS Terra 16 day composite data (MOD13Q1). Feature Importances for each acquisition period of the Enhanced Vegetation Index (EVI) and Normalised Difference Vegetation Index (NDVI) were calculated for both classification scenarios. In the general land cover classification, the months December and January showed the highest, and July and August the lowest separability for both VIs over the entire nine-year period. This temporal separability was reflected in the classification accuracies, where the optimal choice of image dates outperformed the worst image date by 13% using NDVI and 5% using EVI on a mono-temporal analysis. With the addition of the next best image periods to the data input the classification accuracies converged quickly to their limit at around 8-10 images. The binary classification schemes, using two classes only, showed a stronger seasonal dependency with a higher intra-annual, but lower inter-annual variation. Nonetheless anomalous weather conditions, such as the cold winter of 2009/2010 can alter the temporal separability pattern significantly. Due to the extensive use of the NDVI for land cover discrimination, the findings of this study should be transferrable to data from other optical sensors with a higher spatial resolution. However, the high impact of outliers from the general climatic pattern highlights the limitation of spatial transferability to locations with different climatic and land cover conditions. The use of high-temporal, moderate resolution data such as MODIS in conjunction with machine-learning techniques proved to be a good base for the prediction of image acquisition timing for optimal land cover classification results.

Quantifying the past and future impact of climate on outbreak patterns of bank voles (Myodes glareolus).

PubMed

Imholt, Christian; Reil, Daniela; Eccard, Jana A; Jacob, Daniela; Hempelmann, Nils; Jacob, Jens

2015-02-01

Central European outbreak populations of the bank vole (Myodes glareolus Schreber) are known to cause damage in forestry and to transmit the most common type of Hantavirus (Puumala virus, PUUV) to humans. A sound estimation of potential effects of future climate scenarios on population dynamics is a prerequisite for long-term management strategies. Historic abundance time series were used to identify the key weather conditions associated with bank vole abundance, and were extrapolated to future climate scenarios to derive potential long-term changes in bank vole abundance dynamics. Classification and regression tree analysis revealed the most relevant weather parameters associated with high and low bank vole abundances. Summer temperatures 2 years prior to trapping had the highest impact on abundance fluctuation. Extrapolation of the identified parameters to future climate conditions revealed an increase in years with high vole abundance. Key weather patterns associated with vole abundance reflect the importance of superabundant food supply through masting to the occurrence of bank vole outbreaks. Owing to changing climate, these outbreaks are predicted potentially to increase in frequency 3-4-fold by the end of this century. This may negatively affect damage patterns in forestry and the risk of human PUUV infection in the long term. © 2014 Society of Chemical Industry.

Santa Ana Forecasting and Classification

NASA Astrophysics Data System (ADS)

Rolinski, T.; Eichhorn, D.; D'Agostino, B. J.; Vanderburg, S.; Means, J. D.

2011-12-01

Southern California experiences wildfires every year, but under certain circumstances these fires grow into extremely large and destructive fires, such as the Cedar Fire of 2003 and the Witch Fire of 2007. The Cedar Fire burned over 1100 km2 , destroyed more than 2200 homes and killed 15 people; the Witch fire burned more than 800 km2, destroyed more than 1000 homes and killed 2 people. Fires can quickly become too large and dangerous to fight if they are accompanied by a very strong "Santa Ana" condition, which is a foehn-like wind that may bring strong winds and very low humidities. However there is an entire range of specific weather conditions that fall into the broad category of Santa Anas, from cold and blustery to hot with very little wind. All types are characterized by clear skies and low humidity. Since the potential for destructive fire is dependent on the characteristics of Santa Anas, as well as the level of fuel moisture, there exists a need for further classification, such as is done with tropical cyclones and after-the-fact with tornadoes. We use surface data and fuel moisture combined with reanalysis to diagnose those conditions that result in Santa Anas with the greatest potential for destructive fires. We use this data to produce a new classification system for Santa Anas. This classification system should be useful for informing the relevant agencies for mitigation and response planning. In the future this same classification may be made available to the general public.

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

DTIC Science & Technology

2014-04-01

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

Topological data analyses and machine learning for detection, classification and characterization of atmospheric rivers

NASA Astrophysics Data System (ADS)

Muszynski, G.; Kashinath, K.; Wehner, M. F.; Prabhat, M.; Kurlin, V.

2017-12-01

We investigate novel approaches to detecting, classifying and characterizing extreme weather events, such as atmospheric rivers (ARs), in large high-dimensional climate datasets. ARs are narrow filaments of concentrated water vapour in the atmosphere that bring much of the precipitation in many mid-latitude regions. The precipitation associated with ARs is also responsible for major flooding events in many coastal regions of the world, including the west coast of the United States and western Europe. In this study we combine ideas from Topological Data Analysis (TDA) with Machine Learning (ML) for detecting, classifying and characterizing extreme weather events, like ARs. TDA is a new field that sits at the interface between topology and computer science, that studies "shape" - hidden topological structure - in raw data. It has been applied successfully in many areas of applied sciences, including complex networks, signal processing and image recognition. Using TDA we provide ARs with a shape characteristic as a new feature descriptor for the task of AR classification. In particular, we track the change in topology in precipitable water (integrated water vapour) fields using the Union-Find algorithm. We use the generated feature descriptors with ML classifiers to establish reliability and classification performance of our approach. We utilize the parallel toolkit for extreme climate events analysis (TECA: Petascale Pattern Recognition for Climate Science, Prabhat et al., Computer Analysis of Images and Patterns, 2015) for comparison (it is assumed that events identified by TECA is ground truth). Preliminary results indicate that our approach brings new insight into the study of ARs and provides quantitative information about the relevance of topological feature descriptors in analyses of a large climate datasets. We illustrate this method on climate model output and NCEP reanalysis datasets. Further, our method outperforms existing methods on detection and classification of ARs. This work illustrates that TDA combined with ML may provide a uniquely powerful approach for detection, classification and characterization of extreme weather phenomena.

Deep Learning for Extreme Weather Detection

NASA Astrophysics Data System (ADS)

Prabhat, M.; Racah, E.; Biard, J.; Liu, Y.; Mudigonda, M.; Kashinath, K.; Beckham, C.; Maharaj, T.; Kahou, S.; Pal, C.; O'Brien, T. A.; Wehner, M. F.; Kunkel, K.; Collins, W. D.

2017-12-01

We will present our latest results from the application of Deep Learning methods for detecting, localizing and segmenting extreme weather patterns in climate data. We have successfully applied supervised convolutional architectures for the binary classification tasks of detecting tropical cyclones and atmospheric rivers in centered, cropped patches. We have subsequently extended our architecture to a semi-supervised formulation, which is capable of learning a unified representation of multiple weather patterns, predicting bounding boxes and object categories, and has the capability to detect novel patterns (w/ few, or no labels). We will briefly present our efforts in scaling the semi-supervised architecture to 9600 nodes of the Cori supercomputer, obtaining 15PF performance. Time permitting, we will highlight our efforts in pixel-level segmentation of weather patterns.

Potential of turbidity monitoring for real time control of pollutant discharge in sewers during rainfall events.

PubMed

Lacour, C; Joannis, C; Gromaire, M-C; Chebbo, G

2009-01-01

Turbidity sensors can be used to continuously monitor the evolution of pollutant mass discharge. For two sites within the Paris combined sewer system, continuous turbidity, conductivity and flow data were recorded at one-minute time intervals over a one-year period. This paper is intended to highlight the variability in turbidity dynamics during wet weather. For each storm event, turbidity response aspects were analysed through different classifications. The correlation between classification and common parameters, such as the antecedent dry weather period, total event volume per impervious hectare and both the mean and maximum hydraulic flow for each event, was also studied. Moreover, the dynamics of flow and turbidity signals were compared at the event scale. No simple relation between turbidity responses, hydraulic flow dynamics and the chosen parameters was derived from this effort. Knowledge of turbidity dynamics could therefore potentially improve wet weather management, especially when using pollution-based real-time control (P-RTC) since turbidity contains information not included in hydraulic flow dynamics and not readily predictable from such dynamics.

Synoptic weather typing applied to air pollution mortality among the elderly in 10 Canadian cities.

PubMed

Vanos, Jennifer K; Cakmak, Sabit; Bristow, Corben; Brion, Vladislav; Tremblay, Neil; Martin, Sara L; Sheridan, Scott S

2013-10-01

Synoptic circulation patterns (large-scale weather systems) affect ambient levels of air pollution, as well as the relationship between air pollution and human health. To investigate the air pollution-mortality relationship within weather types and seasons, and to determine which combination of atmospheric conditions may pose increased health threats in the elderly age categories. The relative risk of mortality (RR) due to air pollution was examined using Poisson generalized linear models (GLMs) within specific weather types. Analysis was completed by weather type and age group (all ages, ≤64, 65-74, 75-84, ≥85 years) in ten Canadian cities from 1981 to 1999. There was significant modification of RR by weather type and age. When examining the entire population, weather type was shown to have the greatest modifying effect on the risk of dying due to ozone (O3). This effect was highest on average for the dry tropical (DT) weather type, with the all-age RR of mortality at a population weighted mean (PWM) found to be 1.055 (95% CI 1.026-1.085). All-weather type risk estimates increased with age due to exposure to carbon monoxide (CO), nitrogen dioxide (NO2), and sulphur dioxide (SO2). On average, RR increased by 2.6, 3.8 and 1.5% for the respective pollutants between the ≤64 and ≥85 age categories. Conversely, mean ozone estimates remained relatively consistent with age. Elevated levels of air pollution were found to be detrimental to the health of elderly individuals for all weather types. However, the entire population was negatively effected by air pollution on the hot dry (DT) and hot humid (MT) days. We identified a significant modification of RR for mortality due to air pollution by age, which is enhanced under specific weather types. Efforts should be targeted at minimizing pollutant exposure to the elderly and/or all age groups with respect to weather type in question. Crown Copyright © 2013 Published by Elsevier Inc. All rights reserved.

Modelling wildfire activity in Iberia with different Atmospheric Circulation WTs

NASA Astrophysics Data System (ADS)

Sousa, P. M.; Trigo, R.; Pereira, M. G.; Rasilla, D.; Gouveia, C.

2012-04-01

This work focuses on the spatial and temporal variability of burnt area (BA) for the entire Iberian Peninsula (IP) and on the construction of statistical models to reproduce the inter-annual variability, based on Weather Types Classification (WTC). A common BA dataset was assembled for the first time for the entire Iberian Peninsula, by merging BA records for the 66 administrative regions of Portugal and Spain. A normalization procedure was then applied to the various size regions before performing a k-means cluster analysis to identify large areas characterized by similar fire regimes. The most compelling results were obtained for 4 clusters (Northwestern, Northern, Southwestern and Eastern) whose spatial patterns and seasonal fire regimes are shown to be related with constraining factors such as topography, vegetation cover and climate conditions. The response of fire burnt surface at monthly time scales to both long-term climatic pre-conditions and short-term synoptic forcing was assessed through correlation and regression analysis using: (i) temperature and precipitation from 2 to 7 months in advance to fire peak season; (ii) synoptic weather patterns derived from 11 distinct classifications derived under the COSTaction-733. Different responses were obtained for each of the considered regions: (i) a relevant link between BA and short-term synoptic forcing (represented by monthly frequencies of WTC) was identified for all clusters; (ii) long-term climatic preconditioning was relevant for all but one cluster (Northern). Taking into account these links, we developed stepwise regression models with the aim of reproducing the observed BA series (i.e. in hindcast mode). These models were based on the best climatic and synoptic circulation predictors identified previously. All models were cross-validated and their performance varies between clusters, though models exclusively based on WTCs tend to better reproduce annual BA time series than those only based on pre-conditioning climatic information. Nevertheless, the best results are attained when both synoptic and climatic predictors are used simultaneously as predictors, in particular for the two western clusters, where correlation coefficient values are higher than 0.7. Finally, we have used WTC composite maps to characterize the typical synoptic configurations that favor high values of BA. These patterns correspond to dry and warm fluxes, associated with anticyclonic regimes, which foster fire ignition (Pereira et al., 2005). Pereira, M.G., Trigo, R.M., DaCamara, C.C., Pereira, J.M.C., Leite, S.M., 2005: "Synoptic patterns associated with large summer forest fires in Portugal". Agricultural and Forest Meteorology. 129, 11-25. COST733, 2011: "COST 733 Wiki - Harmonisation and Applications of Weather Type Classifications for European regions or COST733 spatial domains for Europe". Available at http://geo21.geo.uni-augsburg.de/cost733wiki/Cost733_Wiki_Main [accessed 1 September 2011].

Analysis of terrestrial and Martian volcanic compositions using thermal emission spectroscopy

NASA Astrophysics Data System (ADS)

Wyatt, Michael Bruce

2002-11-01

This dissertation comprises four separate parts that address the Mars Global Surveyor (MGS) Thermal Emission Spectrometer (TES) investigation objective of determining and mapping the composition and distribution of surface minerals and rocks on Mars from orbit. In Part 1, laboratory thermal infrared spectra (5 25 μm, at 2 cm-1 spectral sampling), deconvolved modal mineralogies, and derived mineral and bulk rock chemistries of basalt, basaltic andesite, andesite, and dacite were used to evaluate and revise volcanic rock classification schemes. Multiple steps of classification were required to distinguish volcanic rocks, reflecting the mineralogic diversity and continuum of compositions that exists in volcanic rock types. In Part 2, laboratory spectral data were convolved to TES 10 cm-1 sampling to ascertain whether adequate results for volcanic rock classification can be obtained with lower spectral resolution, comparable to that obtained from Mars orbit. Modeled spectra, modeled modal mineralogies, and derived bulk rock chemistries at low (10 cm-1) spectral sampling provide good matches to measured and high (2 cm-1) spectral sampling modeled values. These results demonstrate the feasibility of using similar techniques and classification schemes for the interpretation of terrestrial laboratory samples and TES-resolution data. In Part 3, new deconvolved mineral abundances from TES data and terrestrial basalts using a spectral end-member set representing minerals common in unaltered and low-temperature aqueously altered basalts were used to reclassify martian surface lithologies. The new formulations maintain the dominance of unaltered basalt in the southern highlands, but indicate the northern lowlands can be interpreted as weathered basalt. The coincidence between locations of altered basalt and a previously suggested northern ocean basin implies that lowland plains materials may be basalts altered under submarine conditions and/or weathered basaltic sediment transported into this depocenter. In Part 4, results from the previous parts are applied to examine the distribution of TES-derived surface compositions in the Oxia Palus region on Mars through high-spatial resolution mapping. Features of interest within Oxia Palus include volcanic/sedimentary materials in southern Acidalia Planitia, low-albedo crater floors and wind streaks in western Arabia Terra, and channel outflow deposits of the Mars Pathfinder (MP) landing site.

CMSAF products Cloud Fraction Coverage and Cloud Type used for solar global irradiance estimation

NASA Astrophysics Data System (ADS)

Badescu, Viorel; Dumitrescu, Alexandru

2016-08-01

Two products provided by the climate monitoring satellite application facility (CMSAF) are the instantaneous Cloud Fractional Coverage (iCFC) and the instantaneous Cloud Type (iCTY) products. Previous studies based on the iCFC product show that the simple solar radiation models belonging to the cloudiness index class n CFC = 0.1-1.0 have rRMSE values ranging between 68 and 71 %. The products iCFC and iCTY are used here to develop simple models providing hourly estimates for solar global irradiance. Measurements performed at five weather stations of Romania (South-Eastern Europe) are used. Two three-class characterizations of the state-of-the-sky, based on the iCTY product, are defined. In case of the first new sky state classification, which is roughly related with cloud altitude, the solar radiation models proposed here perform worst for the iCTY class 4-15, with rRMSE values ranging between 46 and 57 %. The spreading error of the simple models is lower than that of the MAGIC model for the iCTY classes 1-4 and 15-19, but larger for iCTY classes 4-15. In case of the second new sky state classification, which takes into account in a weighted manner the chance for the sun to be covered by different types of clouds, the solar radiation models proposed here perform worst for the cloudiness index class n CTY = 0.7-0.1, with rRMSE values ranging between 51 and 66 %. Therefore, the two new sky state classifications based on the iCTY product are useful in increasing the accuracy of solar radiation models.

Why is it so difficult to classify Renazzo-type (CR) carbonaceous chondrites? - Implications from TEM observations of matrices for the sequences of aqueous alteration

NASA Astrophysics Data System (ADS)

Abreu, Neyda M.

2016-12-01

A number of different classifications have been proposed for the CR chondrites; this study aims at reconciling these different schemes. Mineralogy-based classification has proved particularly challenging for weakly to moderately altered CRs because incipient mineral replacement and elemental mobilization arising from aqueous alteration only affected the most susceptible primary phases, which are generally located in the matrix. Secondary matrix phases are extremely fine-grained (generally sub-micron) and heterogeneously mixed with primary nebular materials. Compositional and isotopic classification parameters are fraught with confounding factors, such as terrestrial weathering, impact processes, and variable abundance of clasts from different regions of the CR parent body or from altogether different planetary bodies. Here, detailed TEM observations from eighteen FIB sections retrieved from the matrices of nine Antarctic CR chondrites (EET 96259, GRA 95229, GRO 95577, GRO 03116, LAP 02342, LAP 04516, LAP 04720, MIL 07525, and MIL 090001) are presented, representing a range of petrologic types. Amorphous Fe-Mg silicates are found to be the dominant phase in all but the most altered CR chondrite matrices, which still retain significant amounts of these amorphous materials. Amorphous Fe-Mg silicates are mixed with phyllosilicates at the nanometer scale. The ratio of amorphous Fe-Mg silicates to phyllosilicates decreases as: (1) the size of phyllosilicates, (2) abundance of magnetite, and (3) replacement of Fe-Ni sulfides increase. Carbonates are only abundant in the most altered CR chondrite, GRO 95577. Nanophase Fe-Ni metal and tochilinite are present small abundances in most CR matrices. Based on the presence, abundance and size of phyllosilicates with respect to amorphous Fe-Mg silicates, the sub-micron features of CR chondrites have been linked to existing classification sequences, and possible reasons for inconsistencies among classification schemes are discussed.

Development of the Rice Convection Model as a Space Weather Tool

DTIC Science & Technology

2015-05-31

coupled to the ionosphere that is suitable for both scientific studies as well as a prediction tool. We are able to run the model faster than “real...of work by finding ways to fund a more systematic effort in making the RCM a space weather prediction tool for magnetospheric and ionospheric studies...convection electric field, total electron content, TEC, ionospheric convection, plasmasphere 16. SECURITY CLASSIFICATION OF: 17. LIMITATION OF ABSTRACT

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

NASA Technical Reports Server (NTRS)

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

1985-01-01

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

Insect remote sensing using a polarization sensitive cw lidar system in chinese rice fields

NASA Astrophysics Data System (ADS)

Zhu, Shiming; Malmqvist, Elin; Li, Yiyun; Jansson, Samuel; Li, Wansha; Duan, Zheng; Fu, Wei; Svanberg, Katarina; Bood, Joakim; Feng, Hongqiang; Åkesson, Susanne; Song, Ziwei; Zhang, Baoxin; Zhao, Guangyu; Li, Dunsong; Brydegaard, Mikkel; Svanberg, Sune

2018-04-01

A joint Chinese-Swedish field campaign of Scheimpflug continuous-wave lidar monitoring of rice-field flying pest insects was pursued in very hot July weather conditions close to Guangzhou, China. The occurrence of insects, birds and bats with almost 200 hours of round-the-clock polarization-sensitive recordings was studied. Wing-beat frequency recordings and depolarization properties were used for target classification. Influence of weather conditions on the flying fauna was also investigated.

Preliminary lithogeochemical map showing near-surface rock types in the Chesapeake Bay watershed, Virginia and Maryland

USGS Publications Warehouse

Peper, John D.; McCartan, Lucy; Horton, J. Wright; Reddy, James E.

2001-01-01

This preliminary experimental lithogeochemical map shows the distribution of rock types in the Virginia and Maryland parts of the Chesapeake Bay watershed. The map was produced digitally by classifying geologic-map units according to composition, mineralogy, and texture; rather than by age and stratigraphic relationships as shown on traditional geologic maps. This map differs from most lithologic maps in that the lithogeochemical unit classification distinguishes those rock units having key water-reactive minerals that may induce acid neutralization, or reduction, of hosted water at the weathering interface. The validity of these rock units, however, is independent of water chemistry, because the rock units are derived from geologic maps and rock descriptions. Areas of high soil carbon content, and sulfide metal deposits are also shown. Water-reactive minerals and their weathering reactions yield five lithogeochemical unit classes: 1) carbonate rock and calcareous rocks and sediments, the most acid-neutralizing; 2)carbonaceous-sulfidic rocks and sediments, oxygen-depleting and reducing; 3) quartzofeldspathic rocks and siliciclastic sediments, relatively weakly reactive with water; 4) mafic silicate rocks/sediments, oxygen consuming and high solute-load delivering; and, 5) the rarer calcareous-sulfidic (carbonaceous) rocks, neutralizing and reducing. Earlier studies in some parts of the map area have related solute loads in ground and stream waters to some aspects of bedrock lithology. More recent preliminary tests of relationships between four of the classes of mapped lithogeochemical units and ground water chemistry, in the Mid-Atlantic area using this map, have focused on and verified the nitrate-reducing and acid-neutralizing properties of some bedrock and unconsolidated aquifer rock types. Sulfide mineral deposits and their mine-tailings effects on waters are beginning to be studied by others. Additional testing of relationships among the lithogeochemical units and aspects of ground and surface water chemistry could help to refine the lithogeochemical classification, and this map. The testing could also improve the usefulness of the map for assessing aquifer reactivity and the transport properties of reactive contaminants such as acid rain, and nitrate from agricultural sources, in the Chesapeake Bay watershed.

ClimateNet: A Machine Learning dataset for Climate Science Research

NASA Astrophysics Data System (ADS)

Prabhat, M.; Biard, J.; Ganguly, S.; Ames, S.; Kashinath, K.; Kim, S. K.; Kahou, S.; Maharaj, T.; Beckham, C.; O'Brien, T. A.; Wehner, M. F.; Williams, D. N.; Kunkel, K.; Collins, W. D.

2017-12-01

Deep Learning techniques have revolutionized commercial applications in Computer vision, speech recognition and control systems. The key for all of these developments was the creation of a curated, labeled dataset ImageNet, for enabling multiple research groups around the world to develop methods, benchmark performance and compete with each other. The success of Deep Learning can be largely attributed to the broad availability of this dataset. Our empirical investigations have revealed that Deep Learning is similarly poised to benefit the task of pattern detection in climate science. Unfortunately, labeled datasets, a key pre-requisite for training, are hard to find. Individual research groups are typically interested in specialized weather patterns, making it hard to unify, and share datasets across groups and institutions. In this work, we are proposing ClimateNet: a labeled dataset that provides labeled instances of extreme weather patterns, as well as associated raw fields in model and observational output. We develop a schema in NetCDF to enumerate weather pattern classes/types, store bounding boxes, and pixel-masks. We are also working on a TensorFlow implementation to natively import such NetCDF datasets, and are providing a reference convolutional architecture for binary classification tasks. Our hope is that researchers in Climate Science, as well as ML/DL, will be able to use (and extend) ClimateNet to make rapid progress in the application of Deep Learning for Climate Science research.

Kuduck Dwsr-88c Radar Rainfall Estimation and Z-r Relationship By Poss During 2001 In Korea

NASA Astrophysics Data System (ADS)

Lee, D. I.; Jang, M.; You, C. H.; Kim, K. E.; Suh, A. S.

The Z-R relationship is derived by linear regression and is used to convert the radar reflectivity Z into the rainfall rate R. It is expressed in terms of an equation of the form as Z=aR^b. The a and b are constant values which have been determined empirically and carried out studies on the calibration of Z-R relationship by many people in many places. However our operational weather radars have been using such as Z=200R^1.6 which can be applied in the case of stratiform clouds. In considering the seasonal vari- ation and rainfall type, this equation is not adequate for many kinds of rainfall events. This fact gives an uncertain result for rainfall estimation and has damage of proper- ties by the incorrect forecast. A statistical Z-R relationship and correction of rainrate were obtained by the drop size distribution(DSD) with calibration of the radar Z-R relationship in Busan city. Precipitation data were observed and measured by a dis- drometer(POSS), a weather radar and a rain gauge of AWS from March to September 2001. As a result, Z-R relationship obtained by disdrometer(POSS) was Z=415R^1.51, even though they can not be sufficiently coverd at all precipitation, since it was not considered the classification of precipitation type and long terms data. New calculated Z-R relationship which was converted to the correlation reflectivity(Zc) between radar reflectivity(Zr) and POSS reflectivity(Zp) was well applied to the estimation of rain- fall rate and it was very variable according to the precipitation events. Therefore, it is found that Kuduck DWSR-88C weather radar has to be operated at more accurate one calibrated and calculated to the new Z-R relationship. In addition, through long precipitation observations with drop size distribution measurements, Z-R relationship has to be continuously provided at each precipitation type.

Integrating K-means Clustering with Kernel Density Estimation for the Development of a Conditional Weather Generation Downscaling Model

NASA Astrophysics Data System (ADS)

Chen, Y.; Ho, C.; Chang, L.

2011-12-01

In previous decades, the climate change caused by global warming increases the occurrence frequency of extreme hydrological events. Water supply shortages caused by extreme events create great challenges for water resource management. To evaluate future climate variations, general circulation models (GCMs) are the most wildly known tools which shows possible weather conditions under pre-defined CO2 emission scenarios announced by IPCC. Because the study area of GCMs is the entire earth, the grid sizes of GCMs are much larger than the basin scale. To overcome the gap, a statistic downscaling technique can transform the regional scale weather factors into basin scale precipitations. The statistic downscaling technique can be divided into three categories include transfer function, weather generator and weather type. The first two categories describe the relationships between the weather factors and precipitations respectively based on deterministic algorithms, such as linear or nonlinear regression and ANN, and stochastic approaches, such as Markov chain theory and statistical distributions. In the weather type, the method has ability to cluster weather factors, which are high dimensional and continuous variables, into weather types, which are limited number of discrete states. In this study, the proposed downscaling model integrates the weather type, using the K-means clustering algorithm, and the weather generator, using the kernel density estimation. The study area is Shihmen basin in northern of Taiwan. In this study, the research process contains two steps, a calibration step and a synthesis step. Three sub-steps were used in the calibration step. First, weather factors, such as pressures, humidities and wind speeds, obtained from NCEP and the precipitations observed from rainfall stations were collected for downscaling. Second, the K-means clustering grouped the weather factors into four weather types. Third, the Markov chain transition matrixes and the conditional probability density function (PDF) of precipitations approximated by the kernel density estimation are calculated respectively for each weather types. In the synthesis step, 100 patterns of synthesis data are generated. First, the weather type of the n-th day are determined by the results of K-means clustering. The associated transition matrix and PDF of the weather type were also determined for the usage of the next sub-step in the synthesis process. Second, the precipitation condition, dry or wet, can be synthesized basing on the transition matrix. If the synthesized condition is dry, the quantity of precipitation is zero; otherwise, the quantity should be further determined in the third sub-step. Third, the quantity of the synthesized precipitation is assigned as the random variable of the PDF defined above. The synthesis efficiency compares the gap of the monthly mean curves and monthly standard deviation curves between the historical precipitation data and the 100 patterns of synthesis data.

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

Mainzer, A.; Masiero, J.; Hand, E.

The NEOWISE data set offers the opportunity to study the variations in albedo for asteroid classification schemes based on visible and near-infrared observations for a large sample of minor planets. We have determined the albedos for nearly 1900 asteroids classified by the Tholen, Bus, and Bus-DeMeo taxonomic classification schemes. We find that the S-complex spans a broad range of bright albedos, partially overlapping the low albedo C-complex at small sizes. As expected, the X-complex covers a wide range of albedos. The multiwavelength infrared coverage provided by NEOWISE allows determination of the reflectivity at 3.4 and 4.6 {mu}m relative to themore » visible albedo. The direct computation of the reflectivity at 3.4 and 4.6 {mu}m enables a new means of comparing the various taxonomic classes. Although C, B, D, and T asteroids all have similarly low visible albedos, the D and T types can be distinguished from the C and B types by examining their relative reflectance at 3.4 and 4.6 {mu}m. All of the albedo distributions are strongly affected by selection biases against small, low albedo objects, as all objects selected for taxonomic classification were chosen according to their visible light brightness. Due to these strong selection biases, we are unable to determine whether or not there are correlations between size, albedo, and space weathering. We argue that the current set of classified asteroids makes any such correlations difficult to verify. A sample of taxonomically classified asteroids drawn without significant albedo bias is needed in order to perform such an analysis.« less

Analysis and Prediction of Weather Impacted Ground Stop Operations

NASA Technical Reports Server (NTRS)

Wang, Yao Xun

2014-01-01

When the air traffic demand is expected to exceed the available airport's capacity for a short period of time, Ground Stop (GS) operations are implemented by Federal Aviation Administration (FAA) Traffic Flow Management (TFM). The GS requires departing aircraft meeting specific criteria to remain on the ground to achieve reduced demands at the constrained destination airport until the end of the GS. This paper provides a high-level overview of the statistical distributions as well as causal factors for the GSs at the major airports in the United States. The GS's character, the weather impact on GSs, GS variations with delays, and the interaction between GSs and Ground Delay Programs (GDPs) at Newark Liberty International Airport (EWR) are investigated. The machine learning methods are used to generate classification models that map the historical airport weather forecast, schedule traffic, and other airport conditions to implemented GS/GDP operations and the models are evaluated using the cross-validations. This modeling approach produced promising results as it yielded an 85% overall classification accuracy to distinguish the implemented GS days from the normal days without GS and GDP operations and a 71% accuracy to differentiate the GS and GDP implemented days from the GDP only days.

Lakenheath, United Kingdom. Revised Uniform Summary of Surface Weather Observations (RUSSWO). Parts A-F.

DTIC Science & Technology

1984-03-01

035831625 N 52 24 E 000 34 ELEV 32 FT EGUL PARTS A-F HOURS 5UM04RIZEDs OOOOZ - 230OZ 06 aR IERIOD OF RECORD: HOURLY OBSERVATIONSt JUN 73 - MAY 83 SIM4&R! OF...Summary of Surface Weather Observations (RUSSWO)- Lakenheath- Final rept. United Kingdom. S. PERFORMING ORG. REPORT NUMBER 7. AUTHOR( e ) S. CONTRACT...Ceiling Versus Visibility; Sky Cover; ( E ) Psychr metric SECURITY CLASSIFICATION OF THIS PAGE(When Date Entered) 19. Percentqge frequency of distribution

Development and Application of integrated monitoring platform for the Doppler Weather SA-BAND Radar

NASA Astrophysics Data System (ADS)

Zhang, Q.; Sun, J.; Zhao, C. C.; Chen, H. Y.

2017-10-01

The doppler weather SA-band radar is an important part of modern meteorological observation methods, monitoring the running status of radar and the data transmission is important.This paper introduced the composition of radar system and classification of radar data,analysed the characteristics and laws of the radar when is normal or abnormal. Using Macromedia Dreamweaver and PHP, developed the integrated monitoring platform for the doppler weather SA-band radar which could monitor the real-time radar system running status and important performance indicators such as radar power,status parameters and others on Web page,and when the status is abnormal it will trigger the audio alarm.

Thin-section microscopy of decayed crystalline marble from the garden sculptures of Schoenbrunn Palace in Vienna

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

Weber, J.; Beseler, S.; Sterflinger, K.

2007-11-15

Sterzing marble, a crystalline white marble used in the late-Baroque garden sculptures of Schoenbrunn Palace in Vienna, was studied by means of thin-section and scanning electron microscopy in order to obtain a better understanding of its surface decay caused by atmospheric weathering. Following the classification of distinct phenomena of deterioration by visual on-site inspection, the microstructural features including surface erosion, micro-cracking, soiling, black crust formation, and microbiological infestation are exemplified by microscopical images and are briefly discussed. The results proved useful for evaluating and understanding the various types of marble decay for creating a safer basis for establishing the proceduralmore » principles aimed at conservation and maintenance of the sculptures.« less

Effects of ENSO on weather-type frequencies and properties at New Orleans, Louisiana, USA

USGS Publications Warehouse

McCabe, G.J.; Muller, R.A.

2002-01-01

Examination of historical climate records indicates a significant relation between the El Nin??o/Southern Oscillation (ENSO) and seasonal temperature and precipitation in Louisiana. In this study, a 40 yr record of twice daily (06:00 and 15:00 h local time) weather types are used to study the effects of ENSO variability on the local climate at New Orleans, Louisiana. Tropical Pacific sea-surface temperatures (SSTs) for the NINO3.4 region are used to define ENSO events (i.e. El Nin??o and La Nin??a events), and daily precipitation and temperature data for New Orleans are used to define weather-type precipitation and temperature properties. Data for winters (December through February) 1962-2000 are analyzed. The 39 winters are divided into 3 categories; winters with NINO3.4 SST anomalies 1??C (El Nin??o events), and neutral conditions (all other years). For each category, weather-type frequencies and properties (i.e. precipitation and temperature) are determined and analyzed. Results indicate that El Nin??o events primarily affect precipitation characteristics of weather types at New Orleans, whereas the effects of La Nin??a events are most apparent in weather-type frequencies. During El Nin??o events, precipitation for some of the weather types is greater than during neutral and La Nin??a conditions and is related to increased water vapor transport from the Tropics to the Gulf of Mexico. The changes in weather-type frequencies during La Nin??a events are indicative of a northward shift in storm tracks and/or a decrease in storm frequency in southern Louisiana.

Classification and source determination of medium petroleum distillates by chemometric and artificial neural networks: a self organizing feature approach.

PubMed

Mat-Desa, Wan N S; Ismail, Dzulkiflee; NicDaeid, Niamh

2011-10-15

Three different medium petroleum distillate (MPD) products (white spirit, paint brush cleaner, and lamp oil) were purchased from commercial stores in Glasgow, Scotland. Samples of 10, 25, 50, 75, 90, and 95% evaporated product were prepared, resulting in 56 samples in total which were analyzed using gas chromatography-mass spectrometry. Data sets from the chromatographic patterns were examined and preprocessed for unsupervised multivariate analyses using principal component analysis (PCA), hierarchical cluster analysis (HCA), and a self organizing feature map (SOFM) artificial neural network. It was revealed that data sets comprised of higher boiling point hydrocarbon compounds provided a good means for the classification of the samples and successfully linked highly weathered samples back to their unevaporated counterpart in every case. The classification abilities of SOFM were further tested and validated for their predictive abilities where one set of weather data in each case was withdrawn from the sample set and used as a test set of the retrained network. This revealed SOFM to be an outstanding mechanism for sample discrimination and linkage over the more conventional PCA and HCA methods often suggested for such data analysis. SOFM also has the advantage of providing additional information through the evaluation of component planes facilitating the investigation of underlying variables that account for the classification. © 2011 American Chemical Society

Innovative use of self-organising maps (SOMs) in model validation.

NASA Astrophysics Data System (ADS)

Jolly, Ben; McDonald, Adrian; Coggins, Jack

2016-04-01

We present an innovative combination of techniques for validation of numerical weather prediction (NWP) output against both observations and reanalyses using two classification schemes, demonstrated by a validation of the operational NWP 'AMPS' (the Antarctic Mesoscale Prediction System). Historically, model validation techniques have centred on case studies or statistics at various time scales (yearly/seasonal/monthly). Within the past decade the latter technique has been expanded by the addition of classification schemes in place of time scales, allowing more precise analysis. Classifications are typically generated for either the model or the observations, then used to create composites for both which are compared. Our method creates and trains a single self-organising map (SOM) on both the model output and observations, which is then used to classify both datasets using the same class definitions. In addition to the standard statistics on class composites, we compare the classifications themselves between the model and the observations. To add further context to the area studied, we use the same techniques to compare the SOM classifications with regimes developed for another study to great effect. The AMPS validation study compares model output against surface observations from SNOWWEB and existing University of Wisconsin-Madison Antarctic Automatic Weather Stations (AWS) during two months over the austral summer of 2014-15. Twelve SOM classes were defined in a '4 x 3' pattern, trained on both model output and observations of 2 m wind components, then used to classify both training datasets. Simple statistics (correlation, bias and normalised root-mean-square-difference) computed for SOM class composites showed that AMPS performed well during extreme weather events, but less well during lighter winds and poorly during the more changeable conditions between either extreme. Comparison of the classification time-series showed that, while correlations were lower during lighter wind periods, AMPS actually forecast the existence of those periods well suggesting that the correlations may be unfairly low. Further investigation showed poor temporal alignment during more changeable conditions, highlighting problems AMPS has around the exact timing of events. There was also a tendency for AMPS to over-predict certain wind flow patterns at the expense of others. In order to gain a larger scale perspective, we compared our mesoscale SOM classification time-series with synoptic scale regimes developed by another study using ERA-Interim reanalysis output and k-means clustering. There was good alignment between the regimes and the observations classifications (observations/regimes), highlighting the effect of synoptic scale forcing on the area. However, comparing the alignment between observations/regimes and AMPS/regimes showed that AMPS may have problems accurately resolving the strength and location of cyclones in the Ross Sea to the north of the target area.

Activities in Teaching Weather

ERIC Educational Resources Information Center

Tonn, Martin

1977-01-01

Presented is a unit composed of activities for teaching weather. Topics include cloud types and formation, simple weather instruments, and the weather station. Illustrations include a weather chart and instruments. A bibliography is given. (MA)

Synoptic weather types associated with critical fire weather

Treesearch

Mark J. Schroeder; Monte Glovinsky; Virgil F. Hendricks; Frank C. Hood; Melvin K. Hull; Henry L. Jacobson; Robert Kirkpatrick; Daniel W. Krueger; Lester P. Mallory; Albert G. Oeztel; Robert H. Reese; Leo A. Sergius; Charles E. Syverson

1964-01-01

Recognizing that weather is an important factor in the spread of both urban and wildland fires, a study was made of the synoptic weather patterns and types which produce strong winds, low relative humidities, high temperatures, and lack of rainfall--the conditions conducive to rapid fire spread. Such historic fires as the San Francisco fire of 1906, the Berkeley fire...

Seasonal differences in climate in the Chianti region of Tuscany and the relationship to vintage wine quality

NASA Astrophysics Data System (ADS)

Salinger, Michael James; Baldi, Marina; Grifoni, Daniele; Jones, Greg; Bartolini, Giorgio; Cecchi, Stefano; Messeri, Gianni; Dalla Marta, Anna; Orlandini, Simone; Dalu, Giovanni A.; Maracchi, Gianpiero

2015-12-01

Climatic factors and weather type frequencies affecting Tuscany are examined to discriminate between vintages ranked into the upper- and lower-quartile years as a consensus from six rating sources of Chianti wine during the period 1980 to 2011. These rankings represent a considerable improvement on any individual publisher ranking, displaying an overall good consensus for the best and worst vintage years. Climate variables are calculated and weather type frequencies are matched between the eight highest and the eight lowest ranked vintages in the main phenological phases of Sangiovese grapevine. Results show that higher heat units; mean, maximum and minimum temperature; and more days with temperature above 35 °C were the most important discriminators between good- and poor-quality vintages in the spring and summer growth phases, with heat units important during ripening. Precipitation influences on vintage quality are significant only during veraison where low precipitation amounts and precipitation days are important for better quality vintages. In agreement with these findings, weather type analysis shows good vintages are favoured by weather type 4 (more anticyclones over central Mediterranean Europe (CME)), giving warm dry growing season conditions. Poor vintages all relate to higher frequencies of either weather type 3, which, by producing perturbation crossing CME, favours cooler and wetter conditions, and/or weather type 7 which favours cold dry continental air masses from the east and north east over CME. This approach shows there are important weather type frequency differences between good- and poor-quality vintages. Trend analysis shows that changes in weather type frequencies are more important than any due to global warming.

Seasonal differences in climate in the Chianti region of Tuscany and the relationship to vintage wine quality.

PubMed

Salinger, Michael James; Baldi, Marina; Grifoni, Daniele; Jones, Greg; Bartolini, Giorgio; Cecchi, Stefano; Messeri, Gianni; Dalla Marta, Anna; Orlandini, Simone; Dalu, Giovanni A; Maracchi, Gianpiero

2015-12-01

Climatic factors and weather type frequencies affecting Tuscany are examined to discriminate between vintages ranked into the upper- and lower-quartile years as a consensus from six rating sources of Chianti wine during the period 1980 to 2011. These rankings represent a considerable improvement on any individual publisher ranking, displaying an overall good consensus for the best and worst vintage years. Climate variables are calculated and weather type frequencies are matched between the eight highest and the eight lowest ranked vintages in the main phenological phases of Sangiovese grapevine. Results show that higher heat units; mean, maximum and minimum temperature; and more days with temperature above 35 °C were the most important discriminators between good- and poor-quality vintages in the spring and summer growth phases, with heat units important during ripening. Precipitation influences on vintage quality are significant only during veraison where low precipitation amounts and precipitation days are important for better quality vintages. In agreement with these findings, weather type analysis shows good vintages are favoured by weather type 4 (more anticyclones over central Mediterranean Europe (CME)), giving warm dry growing season conditions. Poor vintages all relate to higher frequencies of either weather type 3, which, by producing perturbation crossing CME, favours cooler and wetter conditions, and/or weather type 7 which favours cold dry continental air masses from the east and north east over CME. This approach shows there are important weather type frequency differences between good- and poor-quality vintages. Trend analysis shows that changes in weather type frequencies are more important than any due to global warming.

Circulation types related to lightning activity over Catalonia and the Principality of Andorra

NASA Astrophysics Data System (ADS)

Pineda, N.; Esteban, P.; Trapero, L.; Soler, X.; Beck, C.

In the present study, we use a Principal Component Analysis (PCA) to characterize the surface 6-h circulation types related to substantial lightning activity over the Catalonia area (north-eastern Iberia) and the Principality of Andorra (eastern Pyrenees) from January 2003 to December 2007. The gridded data used for classification of the circulation types is the NCEP Final Analyses of the Global Tropospheric Analyses at 1° resolution over the region 35°N-48°N by 5°W-8°E. Lightning information was collected by the SAFIR lightning detection system operated by the Meteorological Service of Catalonia (SMC), which covers the region studied. We determined nine circulation types on the basis of the S-mode orthogonal rotated Principal Component Analysis. The “extreme scores” principle was used previous to the assignation of all cases, to obtain the number of final types and their centroids. The distinct differences identified in the resulting mean Sea Level Pressure (SLP) fields enabled us to group the types into three main patterns, taking into account their scale/dynamical origin. The first group of types shows the different distribution of the centres of action at synoptic scale associated with the occurrence of lightning. The second group is connected to mesoscale dynamics, mainly induced by the relief of the Pyrenees. The third group shows types with low gradient SLP patterns in which the lightning activity is a consequence of thermal dynamics (coastal and mountain breezes). Apart from reinforcing the consistency of the groups obtained, analysis of the resulting classification improves our understanding of the geographical distribution and genesis factors of thunderstorm activity in the study area, and provides complementary information for supporting weather forecasting. Thus, the catalogue obtained will provide advances in different climatological and meteorological applications, such as nowcasting products or detection of climate change trends.

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.

Risk assessment for cardiovascular and respiratory mortality due to air pollution and synoptic meteorology in 10 Canadian cities.

PubMed

Vanos, Jennifer K; Hebbern, Christopher; Cakmak, Sabit

2014-02-01

Synoptic weather and ambient air quality synergistically influence human health. We report the relative risk of mortality from all non-accidental, respiratory-, and cardiovascular-related causes, associated with exposure to four air pollutants, by weather type and season, in 10 major Canadian cities for 1981 through 1999. We conducted this multi-city time-series study using Poisson generalized linear models stratified by season and each of six distinctive synoptic weather types. Statistically significant relationships of mortality due to short-term exposure to carbon monoxide, nitrogen dioxide, sulphur dioxide, and ozone were found, with significant modifications of risk by weather type, season, and mortality cause. In total, 61% of the respiratory-related mortality relative risk estimates were significantly higher than for cardiovascular-related mortality. The combined effect of weather and air pollution is greatest when tropical-type weather is present in the spring or summer. Crown Copyright © 2013. Published by Elsevier Ltd. All rights reserved.

Divergence in Forest-Type Response to Climate and Weather: Evidence for Regional Links Between Forest-Type Evenness and Net Primary Productivity

USGS Publications Warehouse

Bradford, J.B.

2011-01-01

Climate change is altering long-term climatic conditions and increasing the magnitude of weather fluctuations. Assessing the consequences of these changes for terrestrial ecosystems requires understanding how different vegetation types respond to climate and weather. This study examined 20 years of regional-scale remotely sensed net primary productivity (NPP) in forests of the northern Lake States to identify how the relationship between NPP and climate or weather differ among forest types, and if NPP patterns are influenced by landscape-scale evenness of forest-type abundance. These results underscore the positive relationship between temperature and NPP. Importantly, these results indicate significant differences among broadly defined forest types in response to both climate and weather. Essentially all weather variables that were strongly related to annual NPP displayed significant differences among forest types, suggesting complementarity in response to environmental fluctuations. In addition, this study found that forest-type evenness (within 8 ?? 8 km2 areas) is positively related to long-term NPP mean and negatively related to NPP variability, suggesting that NPP in pixels with greater forest-type evenness is both higher and more stable through time. This is landscape- to subcontinental-scale evidence of a relationship between primary productivity and one measure of biological diversity. These results imply that anthropogenic or natural processes that influence the proportional abundance of forest types within landscapes may influence long-term productivity patterns. ?? 2011 Springer Science+Business Media, LLC (outside the USA).

Comparing exposure metrics for classifying ‘dangerous heat’ in heat wave and health warning systems

PubMed Central

Zhang, Kai; Rood, Richard B.; Michailidis, George; Oswald, Evan M.; Schwartz, Joel D.; Zanobetti, Antonella; Ebi, Kristie L.; O’Neill, Marie S.

2012-01-01

Heat waves have been linked to excess mortality and morbidity, and are projected to increase in frequency and intensity with a warming climate. This study compares exposure metrics to trigger heat wave and health warning systems (HHWS), and introduces a novel multi-level hybrid clustering method to identify potential dangerously hot days. Two-level and three-level hybrid clustering analysis as well as common indices used to trigger HHWS, including spatial synoptic classification (SSC); and 90th, 95th, and 99th percentiles of minimum and relative minimum temperature (using a 10 day reference period), were calculated using a summertime weather dataset in Detroit from 1976 to 2006. The days classified as ‘hot’ with hybrid clustering analysis, SSC, minimum and relative minimum temperature methods differed by method type. SSC tended to include the days with, on average, 2.6 °C lower daily minimum temperature and 5.3 °C lower dew point than days identified by other methods. These metrics were evaluated by comparing their performance in predicting excess daily mortality. The 99th percentile of minimum temperature was generally the most predictive, followed by the three-level hybrid clustering method, the 95th percentile of minimum temperature, SSC and others. Our proposed clustering framework has more flexibility and requires less substantial meteorological prior information than the synoptic classification methods. Comparison of these metrics in predicting excess daily mortality suggests that metrics thought to better characterize physiological heat stress by considering several weather conditions simultaneously may not be the same metrics that are better at predicting heat-related mortality, which has significant implications in HHWSs. PMID:22673187

Science Unlimited: Grades K-6 Competency Matrix.

ERIC Educational Resources Information Center

Pennsylvania State Dept. of Education, Harrisburg. Div. of Arts and Sciences.

This competency matrix matches the primary and intermediate Science Unlimited lessons with the established competencies which appear in the Science Unlimited competency continuum. Primary lessons deal with: investigating dripping faucets; classification/sorting; smell; eyes; color; air; weather; observation and description; mystery boxes; change;…

About the National Forecast Chart

Science.gov Websites

General Weather WPC Quantitative Precipitation Forecasts for coverage, and weather type from the NWS NDFD Weather Prediction Center 5830 University Research Court College Park, Maryland 20740 Weather Prediction

Investigation of Health Risks and Their Prevention in the Rapid Climate Changes and the Rise of Pollution of the Atmosphere in the Mountain Region of the North Caucasus

NASA Astrophysics Data System (ADS)

Babyakin, Alexander; Polozkov, Igor; Golitsyn, Georgy; Efimenko, Natalia; Zherlitsina, Liubov; Povolotskaya, Nina; Senik, Irina; Chalaya, Elena; Artamonova, Maria; Pogarski, Fedor

2010-05-01

The current global climate change is determined by changes in the structure of weather conditions, whose impact on the health of various regions of the planet has not been studied sufficiently. To study this effect on the low-altitude mountains resort of Kislovodsk (southern Russia) multi-factor assessment of the impact of the environment on human health is carried out. There were taking in account atmosphere condition, atmospheric aerosol pollution relationship with atmospheric circulation, the level of pollution matching with different types of weather, and, on the base of analysis of meteopathic reactions (MPR), the extent of their biotropism was revealed. Two sides of weather-climatic influences - specific and nonspecific - are interconnected. They manifest themselves differently in humans with different levels of regulation of vital activity and the adaptive capacity of the organism to the complex environmental effects. This complicates the precise physiological basis of quantitative criteria for the prediction of "biotropic" (adverse) weathers. Nevertheless, clinical observations have shown the existence of the "limiting" physiological bound on the size of medical-meteorological modules (MMM). The reactions of the organism to unfavorable weather factors on the results of a questionnaire monitoring surveillance of patients treated in clinics of Federal State Institution "Pyatigorsk State Research Institute of Curortology, FMBA of Russia" (PSRIC), in comparison with clinical data, have identified various MPR of the organism, the clinical manifestation of which depends on age, sex of the patient, the availability of principal and attendant pathology, reactivity, etc. Analysis of the results of clinical observation, cases of medical aid appealability to the station an ambulance at the sudden ill health, as well as the uptake of advice of sick people among immigrants during their short stay at the resort, and the local population, allowed the first approximation to clarify the criteria for "pathogenicity" of various weather conditions and the factors of air pollution. These criteria were put in a new technology of the Medical Weather Forecast (MWF). In this technology it is proposed to use the integrated Weather Pathogenicity Index (WPI), which is calculated as a weighted average of biotropism indices of various MMM, which include: the dynamics and day to day variability of temperature, pressure and humidity, wind speed, weight content of oxygen and natural air ions in the surface atmosphere, cloudiness, atmospheric phenomena, geomagnetic activity, the ultraviolet index (by UVB solar radiation), the integrated illumination by the sun, the heat conditions of the human. For each of the MMM the five physiological grades of the effects of weather on human adaptation to weather of magnitude and dynamics of WPI are marked out: indifferent, weak, moderate, harsh and overly harsh, according to which the degree of "pathogenicity" of the weather is estimating. Pathogenicity is indicated by quantitative number of medical types of weather (I - a very good weather, II - good weather, III - adverse weather, and IV - a particularly adverse weather). According to the forms of the pressure relief on the sea level, 850 hPa, and 500 hPa, the nature of atmospheric stratification and the presence of atmospheric fronts in the medical types of weather the type of atmospheric circulation is evaluating (anticyclonic - "A", cyclonic - "B", frontal - "C"), which defines a subtype of weather and the possible nature of meteopathia (hypotensive, hypoxic, spastic, etc.). Innovations of the new technology are associated with the introduction of a methodology for the preparation of MWF the modified classifiers to determine the gradation of biotropism degree for various MMM, confirmed by the results of comprehensive empirical medical and climatic studies using dynamic and synoptic weather forecasting making by Hydrometeocenter of Russia and forecast of atmospheric pollution making by Obukhov Institute of Atmospheric Physics RAS. The average weighted WPI forms the basis of weather type number, synoptic weather forecast allows you to define a subtype of the weather. This classification is used in the system of MWF in the resorts of Caucasian Mineral Waters (mountainous region of Northern Caucasus), making for the purpose of timely warnings of medical personnel of medical institutions to strengthen health surveillance and, if necessary, conduct prevention of MPR. MPR to changing weather conditions are most manifest in connection with resettlement of patients from their places of permanent residence to the unusual climatic conditions of the resort. In this regard, in order to enhance the spa rehabilitation of meteosensitive patients with coronary artery disease at PSRIC a physiological method was developed for early and routine prophylaxis of maladaptive pathological and, above all, MPR using the method of transcranial electric-pulse meso-diencephalic modulation by MDMK-4 apparatus with a frontooccipital location of the electrodes. Clinical manifestation of the MPR in adverse weather conditions in patients with coronary artery disease, hypertension with dysadaptation syndrome is characterized by frequent recurrences of angina, rhythm disorders, cerebral symptoms, vascular crisis, violations in the field of psycho-emotional area and other disorders. These meteopathies are eliminated with high efficiency using the MDMK-4 apparatus in individually selected modes at the planned rate of prophylaxis for 10 procedures. In order to urgent MPR prevention the procedures can be used situationally. The high preventive and curative effects of transcranial electric-pulse meso-diencephalic modulation of the MDMK-4 apparatus is shown by positive dynamics of the clinical status of patients, including data on the MPR test survey, the Kerdem vegetative index, rheoencephalography indicators, electrocardiography, neurovascular reactivity, Holter monitoring of blood pressure and ECG. For children with respiratory diseases PSRIC developed a number of effective methods to increase organism resistance to the effects of environmental factors through the use of artificial microclimate chambers and methods of climatic treatment. Thus, a comprehensive study has expanded our understanding of the impact of the environment on human health, to refine the criteria of selected biotropic situations related to the influence of atmospheric pollution, to improve the efficiency of the MWF system in mountain resorts of the North Caucasus, to develop ways to prevent meteopathies of patients with cardio-vascular and respiratory systems. The investigation was fulfilled in the frames of Program of Presidium of the Russian Academy of Sciences "Basic Sciences - for Medicine" and RFBR grant No. 07-05-12069-ofi_a.

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.

Space-Weathered Anorthosite as Spectral D-Type Material on the Martian Satellites

NASA Astrophysics Data System (ADS)

Yamamoto, S.; Watanabe, S.; Matsunaga, T.

2018-02-01

Spectral D-type asteroids are characterized by dark, red-sloped, and featureless spectra at visible and near-infrared wavelengths and are thought to be composed of rocks rich in organic compounds. The Martian satellites, Phobos and Deimos, spectrally resemble D-type asteroids, suggesting that they are captured D-type asteroids from outside the Martian system. Here we show that the spectral features of lunar space-weathered anorthosite are consistent with D-type spectra, including those of Phobos and Deimos. This can also explain the distinct spectral features on Phobos, the red and blue units, as arising from different degrees of space weathering. Thus, D-type spectra of the Martian satellites can be explained by space-weathered anorthosite, indicating that D-type spectra do not necessarily support the existence of organic compounds, which would be strong evidence for the capture scenario.

Incidence of myocardial infarction and weather

NASA Astrophysics Data System (ADS)

Staiger, Henning

1982-08-01

Extreme values of temperature and/or humidity in the temperate climate of Hamburg are not able to explain the influence of weather on day-to-day fluctuations of morbidity. Short term changes in weather are described by two objective classifications as deviation from the meteorological past: 1. the temperature-humidity-environment, derived from values of temperature and water vapour pressure at 07.00 h, 2. changes in the cyclonality, derived from the difference of 500 and 850 mbar vorticity values. Their suitability for human biometeorology is illustrated with a material of 1262 subjects who suffered from acute myocardial infarction. For these investigated cases it was known whether angina pectoris was already manifest before the infarction or not. The daily weather conditions have a significant effect on the incidence of acute myocardial infarction according to angina pectoris. Compared to subjects with angina pectoris those without angina pectoris show an increased susceptibility to infarction during changes in weather conditions to warmer/more humid and also during all strong changes in the cyclonality whereby the temperature-humidity-environment seems to leave only the role of an indicator too. Persons with a preceeding angina pectoris are more sensitive agains rapid changes in weather conditions.

Meteorological conditions during the formation of ice on aircraft

NASA Technical Reports Server (NTRS)

Samuels, L T

1932-01-01

These are the results of a number of records recently secured from autographic meteorological instruments mounted on airplanes at times when ice formed. Ice is found to collect on an airplane only when the airplane is in some form of visible moisture, such as cloud, fog, mist, rain. etc., and the air temperature is within certain critical limits. Described here are the characteristics of clear ice and rime ice and the specific types of hazards they present to airplanes and lighter than air vehicles. The weather records are classified according to the two general types of formation (clear ice and rime) together with the respective temperatures, relative humidities, clouds, and elevations above ground at which formations occurred. This classification includes 108 cases where rime formed, 43 cases in which clear ice formed, and 4 cases when both rime and clear ice formed during the same flight. It is evident from the above figures that there was a preponderance of rime by the ratio of 2.5 to 1, while in only a few cases both types of ice formation occurred during the same flight.

The Influence of Weather Conditions on Outdoor Physical Activity Among Older People With and Without Osteoarthritis in 6 European Countries.

PubMed

Timmermans, Erik J; van der Pas, Suzan; Dennison, Elaine M; Maggi, Stefania; Peter, Richard; Castell, Maria Victoria; Pedersen, Nancy L; Denkinger, Michael D; Edwards, Mark H; Limongi, Federica; Herbolsheimer, Florian; Sánchez-Martínez, Mercedes; Siviero, Paola; Queipo, Rocio; Schaap, Laura A; Deeg, Dorly J H

2016-12-01

Older adults with osteoarthritis (OA) often report that their disease symptoms are exacerbated by weather conditions. This study examines the association between outdoor physical activity (PA) and weather conditions in older adults from 6 European countries and assesses whether outdoor PA and weather conditions are more strongly associated in older persons with OA than in those without the condition. The American College of Rheumatology classification criteria were used to diagnose OA. Outdoor PA was assessed using the LASA Physical Activity Questionnaire. Data on weather parameters were obtained from weather stations. Of the 2439 participants (65-85 years), 29.6% had OA in knee, hand and/or hip. Participants with OA spent fewer minutes in PA than participants without OA (Median = 42.9, IQR = 20.0 to 83.1 versus Median = 51.4, IQR = 23.6 to 98.6; P < .01). In the full sample, temperature (B = 1.52; P < .001) and relative humidity (B = -0.77; P < .001) were associated with PA. Temperature was more strongly associated with PA in participants without OA (B = 1.98; P < .001) than in those with the condition (B = 0.48; P = .47). Weather conditions are associated with outdoor PA in older adults in the general population. Outdoor PA and weather conditions were more strongly associated in older adults without OA than in their counterparts with OA.

An Automated Solar Synoptic Analysis Software System

NASA Astrophysics Data System (ADS)

Hong, S.; Lee, S.; Oh, S.; Kim, J.; Lee, J.; Kim, Y.; Lee, J.; Moon, Y.; Lee, D.

2012-12-01

We have developed an automated software system of identifying solar active regions, filament channels, and coronal holes, those are three major solar sources causing the space weather. Space weather forecasters of NOAA Space Weather Prediction Center produce the solar synoptic drawings as a daily basis to predict solar activities, i.e., solar flares, filament eruptions, high speed solar wind streams, and co-rotating interaction regions as well as their possible effects to the Earth. As an attempt to emulate this process with a fully automated and consistent way, we developed a software system named ASSA(Automated Solar Synoptic Analysis). When identifying solar active regions, ASSA uses high-resolution SDO HMI intensitygram and magnetogram as inputs and providing McIntosh classification and Mt. Wilson magnetic classification of each active region by applying appropriate image processing techniques such as thresholding, morphology extraction, and region growing. At the same time, it also extracts morphological and physical properties of active regions in a quantitative way for the short-term prediction of flares and CMEs. When identifying filament channels and coronal holes, images of global H-alpha network and SDO AIA 193 are used for morphological identification and also SDO HMI magnetograms for quantitative verification. The output results of ASSA are routinely checked and validated against NOAA's daily SRS(Solar Region Summary) and UCOHO(URSIgram code for coronal hole information). A couple of preliminary scientific results are to be presented using available output results. ASSA will be deployed at the Korean Space Weather Center and serve its customers in an operational status by the end of 2012.

Antarctic Meteorite Newsletter, volume 6, number 2

NASA Technical Reports Server (NTRS)

1983-01-01

Meteorites from the 1981 and 1982 Antarctic collection are listed showing classification, weight, degree of weathering, degree of fractionation, % Fa, and % Fs. Physical and petrigraphic characteristics are described for 23 samples from the Allan Hills, Thiel Mountains, the Pecora Escarpment, and the Elephant Moraine locations.

Microwave emission characteristics of sea ice

NASA Technical Reports Server (NTRS)

Edgerton, A. T.; Poe, G.

1972-01-01

A general classification is presented for sea ice brightness temperatures with categories of high and low emission, corresponding to young and weathered sea ice, respectively. A sea ice emission model was developed which allows variations of ice salinity and temperature in directions perpendicular to the ice surface.

Elementary Science Resource Guide.

ERIC Educational Resources Information Center

Texas Education Agency, Austin. Div. of Curriculum Development.

This guide for elementary teachers provides information on getting ideas into action, designing and implementing the right situation, ways in which to evaluate science process activities with students, and seven sample units. The units cover using the senses, magnets, forces, weather forecasting, classification of living things, and the physical…

Short-Term Global Horizontal Irradiance Forecasting Based on Sky Imaging and Pattern Recognition

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

Hodge, Brian S; Feng, Cong; Cui, Mingjian

Accurate short-term forecasting is crucial for solar integration in the power grid. In this paper, a classification forecasting framework based on pattern recognition is developed for 1-hour-ahead global horizontal irradiance (GHI) forecasting. Three sets of models in the forecasting framework are trained by the data partitioned from the preprocessing analysis. The first two sets of models forecast GHI for the first four daylight hours of each day. Then the GHI values in the remaining hours are forecasted by an optimal machine learning model determined based on a weather pattern classification model in the third model set. The weather pattern ismore » determined by a support vector machine (SVM) classifier. The developed framework is validated by the GHI and sky imaging data from the National Renewable Energy Laboratory (NREL). Results show that the developed short-term forecasting framework outperforms the persistence benchmark by 16% in terms of the normalized mean absolute error and 25% in terms of the normalized root mean square error.« less

The Influence of Weather Conditions on Joint Pain in Older People with Osteoarthritis: Results from the European Project on OSteoArthritis.

PubMed

Timmermans, Erik J; Schaap, Laura A; Herbolsheimer, Florian; Dennison, Elaine M; Maggi, Stefania; Pedersen, Nancy L; Castell, Maria Victoria; Denkinger, Michael D; Edwards, Mark H; Limongi, Federica; Sánchez-Martínez, Mercedes; Siviero, Paola; Queipo, Rocio; Peter, Richard; van der Pas, Suzan; Deeg, Dorly J H

2015-10-01

This study examined whether daily weather conditions, 3-day average weather conditions, and changes in weather conditions influence joint pain in older people with osteoarthritis (OA) in 6 European countries. Data from the population-based European Project on OSteoArthritis were used. The American College of Rheumatology classification criteria were used to diagnose OA in older people (65-85 yrs). After the baseline interview, at 6 months, and after the 12-18 months followup interview, joint pain was assessed using 2-week pain calendars. Daily values for temperature, precipitation, atmospheric pressure, relative humidity, and wind speed were obtained from local weather stations. Multilevel regression modelling was used to examine the pain-weather associations, adjusted for several confounders. The study included 810 participants with OA in the knee, hand, and/or hip. After adjustment, there were significant associations of joint pain with daily average humidity (B = 0.004, p < 0.01) and 3-day average humidity (B = 0.004, p = 0.01). A significant interaction effect was found between daily average humidity and temperature on joint pain. The effect of humidity on pain was stronger in relatively cold weather conditions. Changes in weather variables between 2 consecutive days were not significantly associated with reported joint pain. The associations between pain and daily average weather conditions suggest that a causal relationship exist between joint pain and weather variables, but the associations between day-to-day weather changes and pain do not confirm causation. Knowledge about the relationship between joint pain in OA and weather may help individuals with OA, physicians, and therapists to better understand and manage fluctuations in pain.

Classification and Distribution of Mars Pathfinder Rocks Using Quantitative Morphologic Indices

NASA Technical Reports Server (NTRS)

Yingst, R. A.; Biederman, K. L.; Monhead, A. M.; Haldemann, A. F. C.; Kowalczyk, M. R.

2004-01-01

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 visible/near-infrared spectra, it has not been fully determined which of these 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 mineralogy's difficult. Efforts in isolating and classifying spectral units among MPF rocks and soils have met with varying degrees of success, and the current understanding is such that many factors influencing spectral signatures cannot be quantified to a sufficient level so they may be removed. The result is that fundamental questions regarding information needed to reveal the present and past interactions between the rocks and rock surfaces and the Martian environment remain unanswered. But it is possible to approach the issue of identifying distinct rock and rock surface types from a different angle.

Cloud Impacts on Pavement Temperature in Energy Balance Models

NASA Astrophysics Data System (ADS)

Walker, C. L.

2013-12-01

Forecast systems provide decision support for end-users ranging from the solar energy industry to municipalities concerned with road safety. Pavement temperature is an important variable when considering vehicle response to various weather conditions. A complex, yet direct relationship exists between tire and pavement temperatures. Literature has shown that as tire temperature increases, friction decreases which affects vehicle performance. Many forecast systems suffer from inaccurate radiation forecasts resulting in part from the inability to model different types of clouds and their influence on radiation. This research focused on forecast improvement by determining how cloud type impacts the amount of shortwave radiation reaching the surface and subsequent pavement temperatures. The study region was the Great Plains where surface solar radiation data were obtained from the High Plains Regional Climate Center's Automated Weather Data Network stations. Road pavement temperature data were obtained from the Meteorological Assimilation Data Ingest System. Cloud properties and radiative transfer quantities were obtained from the Clouds and Earth's Radiant Energy System mission via Aqua and Terra Moderate Resolution Imaging Spectroradiometer satellite products. An additional cloud data set was incorporated from the Naval Research Laboratory Cloud Classification algorithm. Statistical analyses using a modified nearest neighbor approach were first performed relating shortwave radiation variability with road pavement temperature fluctuations. Then statistical associations were determined between the shortwave radiation and cloud property data sets. Preliminary results suggest that substantial pavement forecasting improvement is possible with the inclusion of cloud-specific information. Future model sensitivity testing seeks to quantify the magnitude of forecast improvement.

Comparison of tibial shaft ski fractures in children and adults.

PubMed

Hamada, Tomo; Matsumoto, Kazu; Ishimaru, Daichi; Sumi, Hiroshi; Shimizu, Katsuji

2014-09-01

To examine whether child and adult skiers have different risk factors or mechanisms of injury for tibial shaft fractures. Descriptive epidemiological study. Prospectively analyzed the epidemiologic factors, injury types, and injury mechanisms at Sumi Memorial Hospital. This study analyzed information obtained from 276 patients with tibial fractures sustained during skiing between 2004 and 2012. We focused on 174 ski-related tibial shaft fractures with respect to the following factors: age, gender, laterality of fracture, skill level, mechanism of fracture (fall vs collision), scene of injury (steepness of slope), snow condition, and weather. Fracture pattern was graded according to Arbeitsgemeinschaft für Osteosynthesefragen (AO) classification and mechanical direction [external (ER) or internal rotation (IR)]. Tibial shaft fractures were the most common in both children (89.3%) and adults (47.4%). There were no significant differences in gender, side of fracture, mechanism of fracture, snow condition, or weather between children and adults. Skill levels were significantly lower in children than in adults (P < 0.0001). Type A fractures were more dominant in children (73 cases, 72.3%) than in adults (39 cases, 53.4%). There was significantly more ER in children than in adults (P < 0.0001). Among children, female patients had significantly more IR than ER; in contrast, among adults, women were injured by ER. We found significant differences in some of these parameters, suggesting that child and adult skiers have different risk factors or mechanisms of injury for tibial shaft fractures.

Cold-Weather Sports and Your Family

MedlinePlus

... Videos for Educators Search English Español Cold-Weather Sports and Your Family KidsHealth / For Parents / Cold-Weather ... kids while being active. Types of Cold-Weather Sports Skiing, snowboarding, ice skating, and snowshoeing are just ...

A Synoptic Weather Typing Approach and Its application to Assess Climate Change Impacts on Extreme Weather Events at Local Scale in South-Central Canada

NASA Astrophysics Data System (ADS)

Shouquan Cheng, Chad; Li, Qian; Li, Guilong

2010-05-01

The synoptic weather typing approach has become popular in evaluating the impacts of climate change on a variety of environmental problems. One of the reasons is its ability to categorize a complex set of meteorological variables as a coherent index, which can facilitate analyses of local climate change impacts. The weather typing method has been successfully applied in Environment Canada for several research projects to analyze climatic change impacts on a number of extreme weather events, such as freezing rain, heavy rainfall, high-/low-flow events, air pollution, and human health. These studies comprise of three major parts: (1) historical simulation modeling to verify the extreme weather events, (2) statistical downscaling to provide station-scale future hourly/daily climate data, and (3) projections of changes in frequency and intensity of future extreme weather events in this century. To achieve these goals, in addition to synoptic weather typing, the modeling conceptualizations in meteorology and hydrology and a number of linear/nonlinear regression techniques were applied. Furthermore, a formal model result verification process has been built into each of the three parts of the projects. The results of the verification, based on historical observations of the outcome variables predicted by the models, showed very good agreement. The modeled results from these projects found that the frequency and intensity of future extreme weather events are projected to significantly increase under a changing climate in this century. This talk will introduce these research projects and outline the modeling exercise and result verification process. The major findings on future projections from the studies will be summarized in the presentation as well. One of the major conclusions from the studies is that the procedures (including synoptic weather typing) used in the studies are useful for climate change impact analysis on future extreme weather events. The implication of the significant increases in frequency and intensity of future extreme weather events would be useful to be considered when revising engineering infrastructure design standards and developing adaptation strategies and policies.

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…

Resurfacing asteroids from YORP spin-up and failure

NASA Astrophysics Data System (ADS)

Graves, Kevin J.; Minton, David A.; Hirabayashi, Masatoshi; DeMeo, Francesca E.; Carry, Benoit

2018-04-01

The spectral properties of S and Q-type asteroids can change over time due to interaction with the solar wind and micrometeorite impacts in a process known as 'space weathering.' Space weathering raises the spectral slope and decreases the 1 μm absorption band depth in the spectra of S and Q-type asteroids. Over time, Q-type asteroids, which have very similar spectra to ordinary chondrite meteorites, will change into S-type asteroids. Because there are a significant number of Q-type asteroids, there must be some process which is resurfacing S-type asteroids into Q-types. In this study, we use asteroid data from the Sloan Digital Sky Survey to show a trend between the slope through the g‧, r‧, and i‧ filters, called the gri-slope, and size that holds for all populations of S and Q-type asteroids in the inner solar system, regardless of orbit. We model the evolution of a suite of asteroids in a Monte Carlo YORP rotational evolution and space weathering model. We show that spin-up and failure from YORP is one of the key resurfacing mechanisms that creates the observed weathering trends with size. By varying the non-dimensional YORP coefficient and running time of the present model over the range 475-1425 Myr, we find a range of values for the space weathering timescale, τSW ≈ 19-80 Myr at 2.2 AU. We also estimate the time to weather a newly resurfaced Q-type asteroid into an S-complex asteroid at 1 AU, τQ → S(1AU) ≈ 2-7 Myr.

47 CFR 73.314 - Field strength measurements.

Code of Federal Regulations, 2011 CFR

2011-10-01

..., such as topography, height and types of vegetation, buildings, obstacles, weather, and other local... the approximate time of measurement, weather, topography, overhead wiring, heights and types of...

47 CFR 73.314 - Field strength measurements.

Code of Federal Regulations, 2014 CFR

2014-10-01

..., such as topography, height and types of vegetation, buildings, obstacles, weather, and other local... the approximate time of measurement, weather, topography, overhead wiring, heights and types of...

47 CFR 73.314 - Field strength measurements.

Code of Federal Regulations, 2012 CFR

2012-10-01

..., such as topography, height and types of vegetation, buildings, obstacles, weather, and other local... the approximate time of measurement, weather, topography, overhead wiring, heights and types of...

47 CFR 73.314 - Field strength measurements.

Code of Federal Regulations, 2013 CFR

2013-10-01

..., such as topography, height and types of vegetation, buildings, obstacles, weather, and other local... the approximate time of measurement, weather, topography, overhead wiring, heights and types of...

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

NASA Astrophysics Data System (ADS)

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

2013-04-01

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

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

NASA Astrophysics Data System (ADS)

Fowler, P.; Basu, S.

2008-12-01

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

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.

Weather conditions drive dynamic habitat selection in a generalist predator.

PubMed

Sunde, Peter; Thorup, Kasper; Jacobsen, Lars B; Rahbek, Carsten

2014-01-01

Despite the dynamic nature of habitat selection, temporal variation as arising from factors such as weather are rarely quantified in species-habitat relationships. We analysed habitat use and selection (use/availability) of foraging, radio-tagged little owls (Athene noctua), a nocturnal, year-round resident generalist predator, to see how this varied as a function of weather, season and availability. Use of the two most frequently used land cover types, gardens/buildings and cultivated fields varied more than 3-fold as a simple function of season and weather through linear effects of wind and quadratic effects of temperature. Even when controlling for the temporal context, both land cover types were used more evenly than predicted from variation in availability (functional response in habitat selection). Use of two other land cover categories (pastures and moist areas) increased linearly with temperature and was proportional to their availability. The study shows that habitat selection by generalist foragers may be highly dependent on temporal variables such as weather, probably because such foragers switch between weather dependent feeding opportunities offered by different land cover types. An opportunistic foraging strategy in a landscape with erratically appearing feeding opportunities in different land cover types, may possibly also explain decreasing selection of the two most frequently used land cover types with increasing availability.

Automotive System for Remote Surface Classification.

PubMed

Bystrov, Aleksandr; Hoare, Edward; Tran, Thuy-Yung; Clarke, Nigel; Gashinova, Marina; Cherniakov, Mikhail

2017-04-01

In this paper we shall discuss a novel approach to road surface recognition, based on the analysis of backscattered microwave and ultrasonic signals. The novelty of our method is sonar and polarimetric radar data fusion, extraction of features for separate swathes of illuminated surface (segmentation), and using of multi-stage artificial neural network for surface classification. The developed system consists of 24 GHz radar and 40 kHz ultrasonic sensor. The features are extracted from backscattered signals and then the procedures of principal component analysis and supervised classification are applied to feature data. The special attention is paid to multi-stage artificial neural network which allows an overall increase in classification accuracy. The proposed technique was tested for recognition of a large number of real surfaces in different weather conditions with the average accuracy of correct classification of 95%. The obtained results thereby demonstrate that the use of proposed system architecture and statistical methods allow for reliable discrimination of various road surfaces in real conditions.

Automotive System for Remote Surface Classification

PubMed Central

Bystrov, Aleksandr; Hoare, Edward; Tran, Thuy-Yung; Clarke, Nigel; Gashinova, Marina; Cherniakov, Mikhail

2017-01-01

In this paper we shall discuss a novel approach to road surface recognition, based on the analysis of backscattered microwave and ultrasonic signals. The novelty of our method is sonar and polarimetric radar data fusion, extraction of features for separate swathes of illuminated surface (segmentation), and using of multi-stage artificial neural network for surface classification. The developed system consists of 24 GHz radar and 40 kHz ultrasonic sensor. The features are extracted from backscattered signals and then the procedures of principal component analysis and supervised classification are applied to feature data. The special attention is paid to multi-stage artificial neural network which allows an overall increase in classification accuracy. The proposed technique was tested for recognition of a large number of real surfaces in different weather conditions with the average accuracy of correct classification of 95%. The obtained results thereby demonstrate that the use of proposed system architecture and statistical methods allow for reliable discrimination of various road surfaces in real conditions. PMID:28368297

Knowledge-based approach to video content classification

NASA Astrophysics Data System (ADS)

Chen, Yu; Wong, Edward K.

2001-01-01

A framework for video content classification using a knowledge-based approach is herein proposed. This approach is motivated by the fact that videos are rich in semantic contents, which can best be interpreted and analyzed by human experts. We demonstrate the concept by implementing a prototype video classification system using the rule-based programming language CLIPS 6.05. Knowledge for video classification is encoded as a set of rules in the rule base. The left-hand-sides of rules contain high level and low level features, while the right-hand-sides of rules contain intermediate results or conclusions. Our current implementation includes features computed from motion, color, and text extracted from video frames. Our current rule set allows us to classify input video into one of five classes: news, weather, reporting, commercial, basketball and football. We use MYCIN's inexact reasoning method for combining evidences, and to handle the uncertainties in the features and in the classification results. We obtained good results in a preliminary experiment, and it demonstrated the validity of the proposed approach.

Knowledge-based approach to video content classification

NASA Astrophysics Data System (ADS)

Chen, Yu; Wong, Edward K.

2000-12-01

A framework for video content classification using a knowledge-based approach is herein proposed. This approach is motivated by the fact that videos are rich in semantic contents, which can best be interpreted and analyzed by human experts. We demonstrate the concept by implementing a prototype video classification system using the rule-based programming language CLIPS 6.05. Knowledge for video classification is encoded as a set of rules in the rule base. The left-hand-sides of rules contain high level and low level features, while the right-hand-sides of rules contain intermediate results or conclusions. Our current implementation includes features computed from motion, color, and text extracted from video frames. Our current rule set allows us to classify input video into one of five classes: news, weather, reporting, commercial, basketball and football. We use MYCIN's inexact reasoning method for combining evidences, and to handle the uncertainties in the features and in the classification results. We obtained good results in a preliminary experiment, and it demonstrated the validity of the proposed approach.

The influence of weather conditions on outdoor physical activity among older people with and without osteoarthritis in six European countries

PubMed Central

Timmermans, Erik J; van der Pas, Suzan; Dennison, Elaine M; Maggi, Stefania; Peter, Richard; Castell, Maria Victoria; Pedersen, Nancy L; Denkinger, Michael D; Edwards, Mark H; Limongi, Federica; Herbolsheimer, Florian; Sánchez-Martínez, Mercedes; Siviero, Paola; Queipo, Rocio; Schaap, Laura A; Deeg, Dorly JH

2017-01-01

Objectives Older adults with osteoarthritis (OA) often report that their disease symptoms are exacerbated by weather conditions. This study examines the association between outdoor physical activity (PA) and weather conditions in older adults from six European countries and assesses whether outdoor PA and weather conditions are more strongly associated in older persons with OA than in those without the condition. Methods The American College of Rheumatology classification criteria were used to diagnose OA. Outdoor PA was assessed using the LASA Physical Activity Questionnaire. Data on weather parameters were obtained from weather stations. Results Of the 2,439 participants (65-85 years), 29.6% had OA in knee, hand and/or hip. Participants with OA spent fewer minutes in PA than participants without OA (Median=42.9, IQR=20.0-83.1 versus Median=51.4, IQR=23.6-98.6; p<0.01). In the full sample, temperature (B=1.52; p<0.001) and relative humidity (B=-0.77; p<0.001) were associated with PA. Temperature was more strongly associated with PA in participants without OA (B=1.98; p<0.001) than in those with the condition (B=0.48; p=0.47). Conclusions Weather conditions are associated with outdoor PA in older adults in the general population. Outdoor PA and weather conditions were more strongly associated in older adults without OA than in their counterparts with OA. PMID:27633622

Teaching through Trade Books: Cloud Watchers

ERIC Educational Resources Information Center

Morgan, Emily; Ansberry, Karen; Phillips-Birdsong, Colleen

2010-01-01

Weather is a topic in science that is applicable to our lives on an everyday basis. The weather often determines what we wear, where we go, and what we do. This month's column focuses on clouds and the part they play in determining our weather. In the K-3 lesson, students learn about different cloud types and sculpt each type out of shaving cream.…

Using synoptic weather types to predict visitor attendance at Atlanta and Indianapolis zoological parks

NASA Astrophysics Data System (ADS)

Perkins, David R.

2018-01-01

Defining an ideal "tourism climate" has been an often-visited research topic where explanations have evolved from global- to location-specific indices tailored to tourists' recreational behavior. Unfortunately, as indices become increasingly specific, they are less translatable across geographies because they may only apply to specific activities, locales, climates, or populations. A key need in the future development of weather and climate indices for tourism has been a translatable, meteorologically based index capturing the generalized ambient atmospheric conditions yet considering local climatology. To address this need, this paper tests the applicability of the spatial synoptic classification (SSC) as a tool to predict visitor attendance response in the tourism, recreation, and leisure (TRL) sector across different climate regimes. Daily attendance data is paired with the prevailing synoptic weather condition at Atlanta and Indianapolis zoological parks from September 2001 to June 2011, to review potential impacts ambient atmospheric conditions may have on visitor attendances. Results indicate that "dry moderate" conditions are most associated with high levels of attendance and "moist polar" synoptic conditions are most associated with low levels of attendance at both zoological parks. Comparing visitor response at these zoo locations, visitors in Indianapolis showed lower levels of tolerance to synoptic conditions which were not "ideal." Visitors in Indianapolis also displayed more aversion to "polar" synoptic regimes while visitors in Atlanta displayed more tolerance to "moist tropical" synoptic regimes. Using a comprehensive atmospheric measure such as the SSC may be a key to broadening application when assessing tourism climates across diverse geographies.

Using synoptic weather types to predict visitor attendance at Atlanta and Indianapolis zoological parks.

PubMed

Perkins, David R

2018-01-01

Defining an ideal "tourism climate" has been an often-visited research topic where explanations have evolved from global- to location-specific indices tailored to tourists' recreational behavior. Unfortunately, as indices become increasingly specific, they are less translatable across geographies because they may only apply to specific activities, locales, climates, or populations. A key need in the future development of weather and climate indices for tourism has been a translatable, meteorologically based index capturing the generalized ambient atmospheric conditions yet considering local climatology. To address this need, this paper tests the applicability of the spatial synoptic classification (SSC) as a tool to predict visitor attendance response in the tourism, recreation, and leisure (TRL) sector across different climate regimes. Daily attendance data is paired with the prevailing synoptic weather condition at Atlanta and Indianapolis zoological parks from September 2001 to June 2011, to review potential impacts ambient atmospheric conditions may have on visitor attendances. Results indicate that "dry moderate" conditions are most associated with high levels of attendance and "moist polar" synoptic conditions are most associated with low levels of attendance at both zoological parks. Comparing visitor response at these zoo locations, visitors in Indianapolis showed lower levels of tolerance to synoptic conditions which were not "ideal." Visitors in Indianapolis also displayed more aversion to "polar" synoptic regimes while visitors in Atlanta displayed more tolerance to "moist tropical" synoptic regimes. Using a comprehensive atmospheric measure such as the SSC may be a key to broadening application when assessing tourism climates across diverse geographies.

Studies of saharan dust intrusions over bucharest using ceilometer's measurements and satellite data

NASA Astrophysics Data System (ADS)

Urlea, Denisa; Boscornea, Andreea; Nicolae Vâjâiac, Sorin; Ţoancă, Florica; Barbu, Nicu; Ştefan, Sabina; Bunescu, Ionuț

2018-04-01

Three case studies of Saharan dust intrusions over southern Romania were performed. For these studies the database from the ceilometers located at Magurele and Strejnic was used. In addition, the meteorological conditions were analyzed using the WLK Catalogue based on the Objektive Wetterlagenklassifikation classification of the weather types [1]. This catalogue uses information from three basic tropospheric levels: 925, 700 and 500 hPa, and information on the precipitable water content over the entire atmosphere column. Geopotential fields at 925hPa and 500hPa are used for establishing the cyclonicity or anticyclonicity, while the U and V components of wind at 700hPa for establishing the dominant direction of the wind flow. For better understanding of the atmospheric parameters we performed HYSPLIT dispersion and trajectories analysis in conjunction with DREAM model output data.

Spectral decomposition of asteroid Itokawa based on principal component analysis

NASA Astrophysics Data System (ADS)

Koga, Sumire C.; Sugita, Seiji; Kamata, Shunichi; Ishiguro, Masateru; Hiroi, Takahiro; Tatsumi, Eri; Sasaki, Sho

2018-01-01

The heliocentric stratification of asteroid spectral types may hold important information on the early evolution of the Solar System. Asteroid spectral taxonomy is based largely on principal component analysis. However, how the surface properties of asteroids, such as the composition and age, are projected in the principal-component (PC) space is not understood well. We decompose multi-band disk-resolved visible spectra of the Itokawa surface with principal component analysis (PCA) in comparison with main-belt asteroids. The obtained distribution of Itokawa spectra projected in the PC space of main-belt asteroids follows a linear trend linking the Q-type and S-type regions and is consistent with the results of space-weathering experiments on ordinary chondrites and olivine, suggesting that this trend may be a space-weathering-induced spectral evolution track for S-type asteroids. Comparison with space-weathering experiments also yield a short average surface age (< a few million years) for Itokawa, consistent with the cosmic-ray-exposure time of returned samples from Itokawa. The Itokawa PC score distribution exhibits asymmetry along the evolution track, strongly suggesting that space weathering has begun saturated on this young asteroid. The freshest spectrum found on Itokawa exhibits a clear sign for space weathering, indicating again that space weathering occurs very rapidly on this body. We also conducted PCA on Itokawa spectra alone and compared the results with space-weathering experiments. The obtained results indicate that the first principal component of Itokawa surface spectra is consistent with spectral change due to space weathering and that the spatial variation in the degree of space weathering is very large (a factor of three in surface age), which would strongly suggest the presence of strong regional/local resurfacing process(es) on this small asteroid.

Classification of forest land attributes using multi-source remotely sensed data

NASA Astrophysics Data System (ADS)

Pippuri, Inka; Suvanto, Aki; Maltamo, Matti; Korhonen, Kari T.; Pitkänen, Juho; Packalen, Petteri

2016-02-01

The aim of the study was to (1) examine the classification of forest land using airborne laser scanning (ALS) data, satellite images and sample plots of the Finnish National Forest Inventory (NFI) as training data and to (2) identify best performing metrics for classifying forest land attributes. Six different schemes of forest land classification were studied: land use/land cover (LU/LC) classification using both national classes and FAO (Food and Agricultural Organization of the United Nations) classes, main type, site type, peat land type and drainage status. Special interest was to test different ALS-based surface metrics in classification of forest land attributes. Field data consisted of 828 NFI plots collected in 2008-2012 in southern Finland and remotely sensed data was from summer 2010. Multinomial logistic regression was used as the classification method. Classification of LU/LC classes were highly accurate (kappa-values 0.90 and 0.91) but also the classification of site type, peat land type and drainage status succeeded moderately well (kappa-values 0.51, 0.69 and 0.52). ALS-based surface metrics were found to be the most important predictor variables in classification of LU/LC class, main type and drainage status. In best classification models of forest site types both spectral metrics from satellite data and point cloud metrics from ALS were used. In turn, in the classification of peat land types ALS point cloud metrics played the most important role. Results indicated that the prediction of site type and forest land category could be incorporated into stand level forest management inventory system in Finland.

Severe Weather Guide - Mediterranean Ports. 2. Naples

DTIC Science & Technology

1988-01-01

Include Security Classification) S^ere Weather Guide - Mediterranean Ports - 2. Naples (U) ? SONAi <^UTHOR(S) .■/ L,^glebretson, Ronald E. (LCDR...AN ( j. ) HIJ-H F’B (2i 040200 ■ CI ’ 3) (U) C A (b) o I..; i E W C E A F’ P L. IC A T.[ G N Ei IN ! E R N...threatened try actual or -forecast 51 r D n q w i n d s , n i g n a e a s , r s s t r i c t e d v i s i D1111 y o i- thunderstcjrms m the port

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

NASA Astrophysics Data System (ADS)

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

2010-12-01

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

Dynamics in cyanobacterial communities from a relatively stable environment in an urbanised area (ambient springs in Central Poland).

PubMed

Nowicka-Krawczyk, Paulina; Żelazna-Wieczorek, Joanna

2017-02-01

Ambient springs are often cited as an example of an ecosystem with stable environmental conditions. A static biotope fosters the development of constant communities with a stable qualitative and relatively stable quantitative structure. Two years of studying cyanobacteria in different microhabitats of the rheocrenic and limnocrenic ambient springs located in urban areas showed that there is a high degree of cyanobacterial diversity and spatial and seasonal dynamics in communities. Spatial heterogeneity in relation to the type of spring and the type of microhabitat is reflected not only by a change in the quantitative structure (the number of species and their biomass), but also by a change in the composition of species. Seasonal changes depended on the type of spring and the type of microhabitat, where weather conditions influenced the communities by different degrees. Cyanobacterial communities of limnocrenes were more diverse in terms of composition and biomass, but they revealed a low seasonal dynamic in contrast to the communities of rheocrenes. The classification of springs based on their environmental conditions revealed that some springs were similar. The resemblance stemmed from the origin of human impact, which was reflected to a high degree in changes in the natural hydrochemical conditions of the springs. For the purpose of understanding which environmental factors had the greatest influence on cyanobacterial communities, a BIO-ENV procedure was performed. The procedure revealed that of most importance was a group of ions not related to the nature of the spring environment - NH 4 + , NO 2 - , NO 3 - , and PO 4 3- . The presence of these ions in groundwater was a result of direct and indirect human activity in the area of aquifers. The dynamics in communities in the studied springs were accelerated by human impact and weather conditions. Copyright © 2016 Elsevier B.V. All rights reserved.

Spatio-temporal dynamics and synoptic characteristics of wet and drought extremes in Northern Eurasia

NASA Astrophysics Data System (ADS)

Utkuzova, Dilyara; Khan, Valentina

2015-04-01

Synoptical-statistical analysis has been conducted using SPI index calculated for 478 stations with records from 1966 through 2013. Different parameters of SPI frequency distribution and long-term tendencies were calculated as well as spatial characteristics indicating drought and wetness propagation. Results of analysis demonstrate that during last years there is a tendency of increasing of the intensity of draught and wetness extremes over Russia. There are fewer droughts in the northern regions. The drought propagation for the European territory of Russia is decreasing in June and August, and increasing in July. The situation is opposite for the wetness tendencies. For the Asian territory of Russia, the drought propagation is significantly increasing in July along with decreasing wetness trend. Synoptic conditions favorable for the formation of wet and drought extremes were identified by comparing synoptic charts with the spatial patterns of SPI. For synoptic analysis, episodes of extremely wet (6 episodes for the APR and 7 episodes for the EPR) and drought (6 episodes for the APR and 6 for the EPR) events were classified using A. Katz' typology of weather regimes. For European part of Russia, extreme DROUGHT events are linked to the weather type named "MIXED", for Asian part of Russia - the type "CENTRAL". For European part of Russia, extreme WET events associated with "CENTRAL" type. There is a displacement of the planetary frontal zone into southward direction approximately for 5-25 degrees relatively to normal climatological position during WET extreme events linked to «EASTERN» classification type. Intercomparison of SPI calculated on the base of NOAA NCEP CPC CAMS for the same period and with the resolution 0,5 degree, month precipitation data, Era-Interim Daily fields archive for the period 1979-2014 with the resolution 0,5 degree reanalysis and observational precipitation data was done. The results of comparative analysis has been discussed.

Combining Passive Microwave Rain Rate Retrieval with Visible and Infrared Cloud Classification.

NASA Astrophysics Data System (ADS)

Miller, Shawn William

The relation between cloud type and rain rate has been investigated here from different approaches. Previous studies and intercomparisons have indicated that no single passive microwave rain rate algorithm is an optimal choice for all types of precipitating systems. Motivated by the upcoming Tropical Rainfall Measuring Mission (TRMM), an algorithm which combines visible and infrared cloud classification with passive microwave rain rate estimation was developed and analyzed in a preliminary manner using data from the Tropical Ocean Global Atmosphere-Coupled Ocean Atmosphere Response Experiment (TOGA-COARE). Overall correlation with radar rain rate measurements across five case studies showed substantial improvement in the combined algorithm approach when compared to the use of any single microwave algorithm. An automated neural network cloud classifier for use over both land and ocean was independently developed and tested on Advanced Very High Resolution Radiometer (AVHRR) data. The global classifier achieved strict accuracy for 82% of the test samples, while a more localized version achieved strict accuracy for 89% of its own test set. These numbers provide hope for the eventual development of a global automated cloud classifier for use throughout the tropics and the temperate zones. The localized classifier was used in conjunction with gridded 15-minute averaged radar rain rates at 8km resolution produced from the current operational network of National Weather Service (NWS) radars, to investigate the relation between cloud type and rain rate over three regions of the continental United States and adjacent waters. The results indicate a substantially lower amount of available moisture in the Front Range of the Rocky Mountains than in the Midwest or in the eastern Gulf of Mexico.

Classification of community types, successional sequences, and landscapes of the Copper River Delta, Alaska.

Treesearch

Keith. Boggs

2000-01-01

A classification of community types, successional sequences, and landscapes is presented for the piedmont of the Copper River Delta. The classification was based on a sampling of 471 sites. A total of 75 community types, 42 successional sequences, and 6 landscapes are described. The classification of community types reflects the existing vegetation communities on the...

Using Music to Communicate Weather and Climate

NASA Astrophysics Data System (ADS)

Williams, P.; Aplin, K. L.; Brown, S.; Jenkins, K.; Mander, S.; Walsh, C.

2016-12-01

Depictions of weather and other atmospheric phenomena are common throughout the arts. Unlike in the visual arts, however, there has been little study of meteorological inspiration in music. This presentation will discuss the frequencies with which different weather types have been depicted in music over time, covering the period from the seventeenth century to the present day. Beginning with classical orchestral music, we find that composers were generally influenced by their own country's climate in the type of weather they chose to represent. Depictions of weather vary from explicit mimicry using traditional and specialized orchestral instruments, through to subtle suggestions. Pieces depicting stormy weather tend to be in minor keys, whereas pieces depicting fair weather tend to be in major keys. As befits the national stereotype, British composers seem disproportionately keen to depict the UK's variable weather patterns and stormy coastline. Moving onto modern popular music, we have identified and analyzed over 750 songs referring to different weather types. We find that lyrical references to bad weather peaked in songs written during the stormy 1950s and 60s, when there were many hurricanes, before declining in the relatively calm 1970s and 80s. This finding again suggests a causal link between song-writers' meteorological environments and compositional outputs. Composers and song-writers have a unique ability to emotionally connect their listeners to the environment. This ability could be exploited to communicate environmental science to a broader audience. Our work provides a catalogue of cultural responses to weather before (and during the early stages of) climate change. The effects of global warming may influence musical expression in future, in which case our work will provide a baseline for comparison.

Using Music to Communicate Weather and Climate

NASA Astrophysics Data System (ADS)

Williams, P.; Aplin, K. L.; Brown, S.

2017-12-01

Depictions of weather and other atmospheric phenomena are common throughout the arts. Unlike in the visual arts, however, there has been little study of meteorological inspiration in music. This presentation will discuss the frequencies with which different weather types have been depicted in music over time, covering the period from the seventeenth century to the present day. Beginning with classical orchestral music, we find that composers were generally influenced by their own country's climate in the type of weather they chose to represent. Depictions of weather vary from explicit mimicry using traditional and specialized orchestral instruments, through to subtle suggestions. Pieces depicting stormy weather tend to be in minor keys, whereas pieces depicting fair weather tend to be in major keys. As befits the national stereotype, British composers seem disproportionately keen to depict the UK's variable weather patterns and stormy coastline. Moving onto modern popular music, we have identified and analyzed over 750 songs referring to different weather types. We find that lyrical references to bad weather peaked in songs written during the stormy 1950s and 60s, when there were many hurricanes, before declining in the relatively calm 1970s and 80s. This finding again suggests a causal link between song-writers' meteorological environments and compositional outputs. Composers and song-writers have a unique ability to emotionally connect their listeners to the environment. This ability could be exploited to communicate environmental science to a broader audience. Our work provides a catalogue of cultural responses to weather before (and during the early stages of) climate change. The effects of global warming may influence musical expression in future, in which case our work will provide a baseline for comparison.

Statistical wave climate projections for coastal impact assessments

NASA Astrophysics Data System (ADS)

Camus, P.; Losada, I. J.; Izaguirre, C.; Espejo, A.; Menéndez, M.; Pérez, J.

2017-09-01

Global multimodel wave climate projections are obtained at 1.0° × 1.0° scale from 30 Coupled Model Intercomparison Project Phase 5 (CMIP5) global circulation model (GCM) realizations. A semi-supervised weather-typing approach based on a characterization of the ocean wave generation areas and the historical wave information from the recent GOW2 database are used to train the statistical model. This framework is also applied to obtain high resolution projections of coastal wave climate and coastal impacts as port operability and coastal flooding. Regional projections are estimated using the collection of weather types at spacing of 1.0°. This assumption is feasible because the predictor is defined based on the wave generation area and the classification is guided by the local wave climate. The assessment of future changes in coastal impacts is based on direct downscaling of indicators defined by empirical formulations (total water level for coastal flooding and number of hours per year with overtopping for port operability). Global multimodel projections of the significant wave height and peak period are consistent with changes obtained in previous studies. Statistical confidence of expected changes is obtained due to the large number of GCMs to construct the ensemble. The proposed methodology is proved to be flexible to project wave climate at different spatial scales. Regional changes of additional variables as wave direction or other statistics can be estimated from the future empirical distribution with extreme values restricted to high percentiles (i.e., 95th, 99th percentiles). The statistical framework can also be applied to evaluate regional coastal impacts integrating changes in storminess and sea level rise.

Addressing the mischaracterization of extreme rainfall in regional climate model simulations - A synoptic pattern based bias correction approach

NASA Astrophysics Data System (ADS)

Li, Jingwan; Sharma, Ashish; Evans, Jason; Johnson, Fiona

2018-01-01

Addressing systematic biases in regional climate model simulations of extreme rainfall is a necessary first step before assessing changes in future rainfall extremes. Commonly used bias correction methods are designed to match statistics of the overall simulated rainfall with observations. This assumes that change in the mix of different types of extreme rainfall events (i.e. convective and non-convective) in a warmer climate is of little relevance in the estimation of overall change, an assumption that is not supported by empirical or physical evidence. This study proposes an alternative approach to account for the potential change of alternate rainfall types, characterized here by synoptic weather patterns (SPs) using self-organizing maps classification. The objective of this study is to evaluate the added influence of SPs on the bias correction, which is achieved by comparing the corrected distribution of future extreme rainfall with that using conventional quantile mapping. A comprehensive synthetic experiment is first defined to investigate the conditions under which the additional information of SPs makes a significant difference to the bias correction. Using over 600,000 synthetic cases, statistically significant differences are found to be present in 46% cases. This is followed by a case study over the Sydney region using a high-resolution run of the Weather Research and Forecasting (WRF) regional climate model, which indicates a small change in the proportions of the SPs and a statistically significant change in the extreme rainfall over the region, although the differences between the changes obtained from the two bias correction methods are not statistically significant.

Weathering of wood

Treesearch

R. Sam Williams

2005-01-01

Weathering is the general term used to define the slow degradation of materials exposed to the weather. The degradation mechanism depends on the type of material, but the cause is a combination of factors found in nature: moisture, sunlight, heat/cold, chemicals, abrasion by windblown materials, and biological agents. Tall mountains weather by the complex and...

Weather Fundamentals: Climate & Seasons. [Videotape].

ERIC Educational Resources Information Center

1998

The videos in this educational series for grades 4-7, help students understand the science behind weather phenomena through dramatic live-action footage, vivid animated graphics, detailed weather maps, and hands-on experiments. This episode (23 minutes), describes weather patterns and cycles around the globe. The various types of climates around…

Efficient crop type mapping based on remote sensing in the Central Valley, California

NASA Astrophysics Data System (ADS)

Zhong, Liheng

Most agricultural systems in California's Central Valley are purposely flexible and intentionally designed to meet the demands of dynamic markets. Agricultural land use is also impacted by climate change and urban development. As a result, crops change annually and semiannually, which makes estimating agricultural water use difficult, especially given the existing method by which agricultural land use is identified and mapped. A minor portion of agricultural land is surveyed annually for land-use type, and every 5 to 8 years the entire valley is completely evaluated. So far no effort has been made to effectively and efficiently identify specific crop types on an annual basis in this area. The potential of satellite imagery to map agricultural land cover and estimate water usage in the Central Valley is explored. Efforts are made to minimize the cost and reduce the time of production during the mapping process. The land use change analysis shows that a remote sensing based mapping method is the only means to map the frequent change of major crop types. The traditional maximum likelihood classification approach is first utilized to map crop types to test the classification capacity of existing algorithms. High accuracy is achieved with sufficient ground truth data for training, and crop maps of moderate quality can be timely produced to facilitate a near-real-time water use estimate. However, the large set of ground truth data required by this method results in high costs in data collection. It is difficult to reduce the cost because a trained classification algorithm is not transferable between different years or different regions. A phenology based classification (PBC) approach is developed which extracts phenological metrics from annual vegetation index profiles and identifies crop types based on these metrics using decision trees. According to the comparison with traditional maximum likelihood classification, this phenology-based approach shows great advantages when the size of the training set is limited by ground truth availability. Once developed, the classifier is able to be applied to different years and a vast area with only a few adjustments according to local agricultural and annual weather conditions. 250 m MODIS imagery is utilized as the main input to the PBC algorithm and displays promising capacity in crop identification in several counties in the Central Valley. A time series of Landsat TM/ETM+ images at a 30 m resolution is necessary in the crop mapping of counties with smaller land parcels, although the processing time is longer. Spectral characteristics are also employed to identify crops in PBC. Spectral signatures are associated with phenological stages instead of imaging dates, which highly increases the stability of the classifier performance and overcomes the problem of over-fitting. Moderate accuracies are achieved by PBC, with confusions mostly within the same crop categories. Based on a quantitative analysis, misclassification in PBC has very trivial impacts on the accuracy of agricultural water use estimate. The cost of the entire PBC procedure is controlled to a very low level, which will enable its usage in routine annual crop mapping in the Central Valley.

Geology and recognition criteria for veinlike uranium deposits of the lower to middle Proterozoic unconformity and strata-related types. Final report

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

Dahlkamp, F.J.; Adams, S.S.

1981-01-01

The discovery of the Rabbit Lake deposit, Saskatchewan, in 1968 and the East Alligator Rivers district, Northern Territory, Australia, in 1970 established the Lower-Middle Proterozoic veinlike-type deposits as one of the major types of uranium deposits. The term veinlike is used in order to distinguish it from the classical magmatic-hydrothermal vein or veintype deposits. The veinlike deposits account for between a quarter and a third of the Western World's proven uranium reserves. Lower-Middle Proterozoic veinlike deposits, as discussed in this report include several subtypes of deposits, which have some significantly different geologic characteristics. These various subtypes appear to have formedmore » from various combinations of geologic processes ranging from synsedimentary uranium precipitation through some combination of diagenesis, metamorphism, metasomatism, weathering, and deep burial diagenesis. Some of the deposit subtypes are based on only one or two incompletely described examples; hence, even the classification presented in this report may be expected to change. Geologic characteristics of the deposits differ significantly between most districts and in some cases even between deposits within districts. Emphasis in this report is placed on deposit descriptions and the interpretations of the observers.« less

Assessment of Slope Stability of Various Cut Slopes with Effects of Weathering by Using Slope Stability Probability Classification (SSPC)

NASA Astrophysics Data System (ADS)

Ersöz, Timur; Topal, Tamer

2017-04-01

Rocks containing pore spaces, fractures, joints, bedding planes and faults are prone to weathering due to temperature differences, wetting-drying, chemistry of solutions absorbed, and other physical and chemical agents. Especially cut slopes are very sensitive to weathering activities because of disturbed rock mass and topographical condition by excavation. During and right after an excavation process of a cut slope, weathering and erosion may act on this newly exposed rock material. These acting on the material may degrade and change its properties and the stability of the cut slope in its engineering lifetime. In this study, the effect of physical and chemical weathering agents on shear strength parameters of the rocks are investigated in order to observe the differences between weathered and unweathered rocks. Also, slope stability assessment of cut slopes affected by these weathering agents which may disturb the parameters like strength, cohesion, internal friction angle, unit weight, water absorption and porosity are studied. In order to compare the condition of the rock materials and analyze the slope stability, the parameters of weathered and fresh rock materials are found with in-situ tests such as Schmidt hammer and laboratory tests like uniaxial compressive strength, point load and direct shear. Moreover, slake durability and methylene blue tests are applied to investigate the response of the rock to weathering and presence of clays in rock materials, respectively. In addition to these studies, both rock strength parameters and any kind of failure mechanism are determined by probabilistic approach with the help of SSPC system. With these observations, the performances of the weathered and fresh zones of the cut slopes are evaluated and 2-D slope stability analysis are modeled with further recommendations for the cut slopes. Keywords: 2-D Modeling, Rock Strength, Slope Stability, SSPC, Weathering

NASA Dryden Flight Research Center's Space Weather Needs

NASA Technical Reports Server (NTRS)

Wiley, Scott

2011-01-01

Presentation involves educating Goddard Space Weather staff about what our needs are, what type of aircraft we have and to learn what we have done in the past to minimize our exposure to Space Weather Hazards.

14 CFR 21.93 - Classification of changes in type design.

Code of Federal Regulations, 2010 CFR

2010-01-01

... 14 Aeronautics and Space 1 2010-01-01 2010-01-01 false Classification of changes in type design... TRANSPORTATION AIRCRAFT CERTIFICATION PROCEDURES FOR PRODUCTS AND PARTS Changes to Type Certificates § 21.93 Classification of changes in type design. (a) In addition to changes in type design specified in paragraph (b) of...

Evolution in Cloud Population Statistics of the MJO: From AMIE Field Observations to Global-Cloud Permitting Models Final Report

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

Kollias, Pavlos

This is a multi-institutional, collaborative project using a three-tier modeling approach to bridge field observations and global cloud-permitting models, with emphases on cloud population structural evolution through various large-scale environments. Our contribution was in data analysis for the generation of high value cloud and precipitation products and derive cloud statistics for model validation. There are two areas in data analysis that we contributed: the development of a synergistic cloud and precipitation cloud classification that identify different cloud (e.g. shallow cumulus, cirrus) and precipitation types (shallow, deep, convective, stratiform) using profiling ARM observations and the development of a quantitative precipitation ratemore » retrieval algorithm using profiling ARM observations. Similar efforts have been developed in the past for precipitation (weather radars), but not for the millimeter-wavelength (cloud) radar deployed at the ARM sites.« less

Multi-Sensor Investigation of a Regional High-Arctic Cloudy Event

NASA Astrophysics Data System (ADS)

Ivanescu, L.; O'Neill, N. T.; Blanchet, J. P.; Baibakov, K.; Chaubey, J. P.; Perro, C. W.; Duck, T. J.

2014-12-01

A regional high-Arctic cloud event observed in March, 2011 at the PEARL Observatory, near the Eureka Weather Station (80°N, 86°W), was investigated with a view to better understanding cloud formation mechanisms during the Polar night. We analysed the temporal cloud evolution with a suite of nighttime, ground-based remote sensing (RS) instruments, supplemented by radiosonde profiles and surface weather measurements. The RS suite included Raman lidar, cloud radar, a star-photometer and microwave-radiometers. In order to estimate the spatial extent and vertical variability of the cloud mass, we employed satellite-based lidar (CALIPSO) and radar (CloudSat) profiles in the regional neighbourhood of Eureka (at a latitude of 80°N, Eureka benefits from a high frequency of CALIPSO and CloudSat overpasses). The ground-based and satellite-based observations provide quantitative measurements of extensive (bulk) properties (cloud and aerosol optical depths), and intensive (per particle properties) such as aerosol and cloud particle size as well as shape, density and aggregation phase of the cloud particulates. All observations were then compared with the upper atmosphere NCEP/NCAR reanalyses in order to understand better the synoptic context of the cloud mass dynamics as a function of key meteorological parameters such as upper air temperature and water vapor circulation. Preliminary results indicated the presence of a particular type of thin ice cloud (TIC-2) associated with a deep and stable atmospheric low. A classification into small and large ice crystal size (< 40 μm and > 40 μm, respectively), identifies the clouds as TIC-1 or TIC-2. This classification is hypothesized to be associated with the nature of the aerosols (non-anthropogenic versus anthropogenic) serving as ice nuclei in their formation. Such a distinction has important implications on the initiation of precipitation, removal rate of the cloud particles and, in consequence, the radiative forcing properties on a regional basis.

Creation and implementation of a certification system for insurability and fire risk classification for forest plantations

Treesearch

Veronica Loewe M.; Victor Vargas; Juan Miguel Ruiz; Andrea Alvarez C.; Felipe Lobo Q.

2015-01-01

Currently, the Chilean insurance market sells forest fire insurance policies and agricultural weather risk policies. However, access to forest fire insurance is difficult for small and medium enterprises (SMEs), with a significant proportion (close to 50%) of forest plantations being without coverage. Indeed, the insurance market that sells forest fire insurance...

Practical aspects of chemometrics for oil spill fingerprinting.

PubMed

Christensen, Jan H; Tomasi, Giorgio

2007-10-26

Tiered approaches for oil spill fingerprinting have evolved rapidly since the 1990s. Chemometrics provides a large number of tools for pattern recognition, calibration and classification that can increase the speed and the objectivity of the analysis and allow for more extensive use of the available data in this field. However, although the chemometric literature is extensive, it does not focus on practical issues that are relevant to oil spill fingerprinting. The aim of this review is to provide a framework for the use of chemometric approaches in tiered oil spill fingerprinting and to provide clear-cut practical details and experiences that can be used by the forensic chemist. The framework is based on methods for initial screening, which include classification of samples into oil type, detection of non matches and of weathering state, and detailed oil spill fingerprinting, in which a more rigorous matching of an oil spill sample to suspected source oils is obtained. This review is intended as a tutorial, and is based on two examples of initial screening using respectively gas chromatography with flame ionization detection and fluorescence spectroscopy; and two of detailed oil spill fingerprinting where gas chromatography-mass spectrometry data are analyzed according to two approaches: The first relying on sections of processed chromatograms and the second on diagnostic ratios.

Do thoraco-lumbar spinal injuries classification systems exhibit lower inter- and intra-observer agreement than other fractures classifications?: A comparison using fractures of the trochanteric area of the proximal femur as contrast model.

PubMed

Urrutia, Julio; Zamora, Tomas; Klaber, Ianiv; Carmona, Maximiliano; Palma, Joaquin; Campos, Mauricio; Yurac, Ratko

2016-04-01

It has been postulated that the complex patterns of spinal injuries have prevented adequate agreement using thoraco-lumbar spinal injuries (TLSI) classifications; however, limb fracture classifications have also shown variable agreements. This study compared agreement using two TLSI classifications with agreement using two classifications of fractures of the trochanteric area of the proximal femur (FTAPF). Six evaluators classified the radiographs and computed tomography scans of 70 patients with acute TLSI using the Denis and the new AO Spine thoraco-lumbar injury classifications. Additionally, six evaluators classified the radiographs of 70 patients with FTAPF using the Tronzo and the AO schemes. Six weeks later, all cases were presented in a random sequence for repeat assessment. The Kappa coefficient (κ) was used to determine agreement. Inter-observer agreement: For TLSI, using the AOSpine classification, the mean κ was 0.62 (0.57-0.66) considering fracture types, and 0.55 (0.52-0.57) considering sub-types; using the Denis classification, κ was 0.62 (0.59-0.65). For FTAPF, with the AO scheme, the mean κ was 0.58 (0.54-0.63) considering fracture types and 0.31 (0.28-0.33) considering sub-types; for the Tronzo classification, κ was 0.54 (0.50-0.57). Intra-observer agreement: For TLSI, using the AOSpine scheme, the mean κ was 0.77 (0.72-0.83) considering fracture types, and 0.71 (0.67-0.76) considering sub-types; for the Denis classification, κ was 0.76 (0.71-0.81). For FTAPF, with the AO scheme, the mean κ was 0.75 (0.69-0.81) considering fracture types and 0.45 (0.39-0.51) considering sub-types; for the Tronzo classification, κ was 0.64 (0.58-0.70). Using the main types of AO classifications, inter- and intra-observer agreement of TLSI were comparable to agreement evaluating FTAPF; including sub-types, inter- and intra-observer agreement evaluating TLSI were significantly better than assessing FTAPF. Inter- and intra-observer agreements using the Denis classification were also significantly better than agreement using the Tronzo scheme. Copyright © 2015 Elsevier Ltd. All rights reserved.

Gender classification from video under challenging operating conditions

NASA Astrophysics Data System (ADS)

Mendoza-Schrock, Olga; Dong, Guozhu

2014-06-01

The literature is abundant with papers on gender classification research. However the majority of such research is based on the assumption that there is enough resolution so that the subject's face can be resolved. Hence the majority of the research is actually in the face recognition and facial feature area. A gap exists for gender classification under challenging operating conditions—different seasonal conditions, different clothing, etc.—and when the subject's face cannot be resolved due to lack of resolution. The Seasonal Weather and Gender (SWAG) Database is a novel database that contains subjects walking through a scene under operating conditions that span a calendar year. This paper exploits a subset of that database—the SWAG One dataset—using data mining techniques, traditional classifiers (ex. Naïve Bayes, Support Vector Machine, etc.) and traditional (canny edge detection, etc.) and non-traditional (height/width ratios, etc.) feature extractors to achieve high correct gender classification rates (greater than 85%). Another novelty includes exploiting frame differentials.

Bulk chemical compositions of Antarctic meteorites in the NIPR collection

NASA Astrophysics Data System (ADS)

Kimura, M.; Imae, N.; Yamaguchi, A.; Haramura, H.; Kojima, H.

2018-03-01

Bulk chemical compositions of meteorites were traditionally analyzed by wet chemical analysis, and NIPR has data for 1162 meteorites as of September 2017. We discuss the classification of meteorites on the basis of these data. Chondrite data are distributed in an anomalously wide range of compositions on the Urey-Craig diagram. One of the reasons for such wide distribution is terrestrial weathering producing Fe2O3-bearing phases from Fe-Ni metal and sulfides. Another important factor affecting the bulk compositional data is brecciation. Our observations indicate that many brecciated chondrites contain anomalously abundant opaque minerals, or are depleted in them, resulting in unusual compositions. In case of enstatite and some carbonaceous chondrites, the bulk compositions are distributed in wider ranges than reported before. The bulk compositions of HED meteorites are consistent with their mineralogy and classification. Our study suggests that wet chemical data are still significant for the meteorite classification. However, petrographic observation is indispensable for evaluating the bulk chemistry and classification of meteorites.

Weathering profiles in granitoid rocks of the Sila Massif uplands, Calabria, southern Italy: New insights into their formation processes and rates

NASA Astrophysics Data System (ADS)

Scarciglia, Fabio; Critelli, Salvatore; Borrelli, Luigi; Coniglio, Sabrina; Muto, Francesco; Perri, Francesco

2016-05-01

In this paper we characterized several weathering profiles developed on granitoid rocks in the Sila Massif upland (Calabria, southern Italy), integrating detailed macro- and micromorphological observations with physico-mechanical field tests and petrographic, mineralogical and geochemical analyses. We focused our attention on the main weathering and pedogenetic processes, trying to understand apparent discrepancies between weathering grade classes based on field description and geomechanical properties, and two common weathering indices, such as the micropetrographic index (Ip) and the chemical index of alteration (CIA). Our results showed that sericite on plagioclase and biotite chloritization, that represent inherited features formed during late-stage hydrothermal alteration of granitoid rocks, may cause an overestimation of the real degree of weathering of primary mineral grains under meteoric conditions, especially in lower weathering grade classes. Moreover, the frequent identification of Fe-Mn oxides and clay coatings of illuvial origin (rather than or in addition to those formed in situ), both at the macro- and microscale, may also explain an overestimation of the weathering degree with respect to field-based classifications. Finally, some apparent inconsistencies between field geomechanical responses and chemical weathering were interpreted as related to physical weathering processes (cryoclastism and thermoclastism), that lead to rock breakdown even when chemical weathering is not well developed. Hence, our study showed that particular caution is needed for evaluating weathering grades, because traditional field and geochemical-petrographic tools may be biased by inherited hydrothermal alteration, physical weathering and illuvial processes. On the basis of chronological constraints to soil formation obtained from a 42 ka-old volcanic input (mixed to granite parent materials) detected in the soil cover of the Sila Massif upland, a first attempt to estimate soil formation rates was achieved for different depths of corresponding weathering profile zones. Soil formation rates ranged from 0.01-0.07 mm a- 1 for A and Bw horizons (weathering class VI) to 0.04-0.36 mm a- 1 for the underlying saprolite (C and Cr layers; class V). By comparing these results with the corresponding erosion rates available in the literature for the study area, that range from < 0.01-0.05 to 0.10-0.21 mm a- 1, we suggest that the upland landscape of the Sila Massif is close to steady-state conditions between weathering and erosive processes.

Developing a system of multi-evaluation of the impact of global climate change on human health in Russia

NASA Astrophysics Data System (ADS)

Granberg, I.; Golitsyn, G.; Istoshin, N.; Efimenko, N.; Alekhin, A.; Rogoza, A.; Povolotskaya, N.; Artamonova, M.; Maximenkov, L.; Pogarski, F.

2009-04-01

High people sensitivity to weather and space factors, particularly encumbered by various illnesses, was from time immemorial. Now, in terms of global climate change, accompanied by frequent and severe restructuring of atmospheric processes, thermal anomalies, droughts, environmental change through meteorological and heliogeophysical factors affect the human body particularly intense, causing adverse effects to health. There are currently beginning to develop methods for evaluating multifactor of the external environment and prevention of their negative influence on people. For those sensitive to such influences, with adverse weather in response to sudden changes in weather factors pathological of meteopathic reactions may arise. In doing so, even among healthy individuals it is up to 35-45% of meteosensitive. Meteopathic reactions lead to the appearance and progression of pathological disorders, and the associated increase in chronic diseases. In this connection the tasks solution related to assessing the impact of meteorological and climatic variations of different space-time scale on the health of the population of Russia becomes extremely important, especially for the people with cardiovascular disease. This is confirmed by as clinical observations, and the state of vital systems of meteosensitive people. Based on the results of comprehensive research of Pyatigorsk State Research Institute of Curortology (PSRIC), the A. M. Obukhov Institute of Atmospheric Physics of the Russian Academy of Sciences (IAP), and Hydrometeocenter of Russia in the region of Caucasian Mineral Waters (CMW) by scientists of IAP and PSRIC there was established a system of Operational Medical Weather Forecast (OMWF), which aims to have possibility on time to host events for the prevention of meteopathic reactions of people with high meteodependence. Also, we have introduced improved definition of Weather Pathogenicity Index (WPI) for medical weather forecast. As a basis of medical weather forecasts we use developed by the joint efforts of our two institutions (PSRIC and IAP) typification of biotropic weather conditions on the basis of climatograms analysis (synoptic-meteorological conditions, helio-geomagnetic activity) and monitoring the health of people with various illnesses in the process of health resort treatment for CMW low-altitude resorts. This classification in modified form is now being adapted to the megapolis conditions by the example of Moscow. In the originating methodology of multiple-factor estimation of the impact of global climate change on human health in Russia a complex study of the atmosphere condition (especially in the case of inversions, leading to a sharp escalation of air pollution) is included, with simultaneous control of weather biotropy degree at meteosensitivity patients during different types of weather: anticyclonic, cyclonic, and frontal, causing changes in blood pressure and other adverse reactions of the organism. In the course of the works there are studied meteopathic reactions in patients with ischemic heart disease (IHD), including those with concomitant hypertension (CH) in connection with the combined influence of dynamic, meteorological, geophysical and environmental factors in the Moscow megalopolis and at the mountain cardiology resort of Kislovodsk. There are compared the results of resort treatment from the group of patients who had in obtaining information about the occurrence of pathogenic meteotropic weathers appointed preventive measures, designed for individual nosological forms, with a control group of patients, for which, regardless the type of weather, the standard complex of resort treatment had been set, without special measures for meteotropic reactions prevention. As a measure to improve meteo-prophylaxis of patients with cardiovascular diseases and improve the system of medical weather forecast for low-mountain resort a methodology of planned meteo-prophylaxis by directed using unique natural healing factors (natural aero-ionization, volatile phytoorganic substances, etc.) in the complex with a standard resort treatment has been developed and proposed to introduce. It was found that on days with high temperature, there is a higher level of air pollution in the territory of Moscow, that may be related to temperature inversions in the surface layer, the lack of movement of air masses (calm), which impede the scattering of chemicals air pollutants. The criteria for calculating the pathogenicity index of different types of weather depending on ozone and submicron aerosol concentration in the surface air in Moscow and Kislovodsk are specified. The results indicate a crucial theoretical and practical significance and prospects of organization of occurring everywhere monitoring of air, features of cross-border transfer of aerosol pollution of the atmosphere (for the concentration and physical and chemical characteristics of the aerosol and its distribution on the territory). The results of the work serve as the basis for a system of multi-evaluation of the impact of global climate change on human health in Russia, with the effective use of medical weather forecast that, in general, aimed at raising the health of Russian citizens within the National Project "Health". The investigation was fulfilled in the frames of Program of Presidium of the Russian Academy of Sciences "Basic Sciences - for Medicine" and RFBR grant No. 07-05-12069-ofi_a.

Weather-responsive traffic management : real solutions for serious traffic problems.

DOT National Transportation Integrated Search

2009-04-01

This flyer describes how weather responsive traffic management (WRTM) can prevent or mitigate the effects of weather on traffic operations and reduce congestion. The three types of WRTM described in the flyer include 1) Advisory strategies that provi...

Sources and air carrier use of aviation weather information

DOT National Transportation Integrated Search

1991-06-01

This report is concerned with the use of weather information by air carriers. It : describes the type of information obtained, the sources of that information, and the : training provided to flight crews in the interpretation and use of weather infor...

The Advanced Transportation Weather Information System (ATWIS)

DOT National Transportation Integrated Search

2000-01-01

Understanding and interpreting weather information can be critical to the success of any winter snow and ice removal operation. Knowing when, where and what type of deicing material to use for a particular winter weather event can be a challenge to e...

Trends in winter circulation over the British Isles and central Europe in twenty-first century projections by 25 CMIP5 GCMs

NASA Astrophysics Data System (ADS)

Stryhal, Jan; Huth, Radan

2018-03-01

Winter midlatitude atmospheric circulation has been extensively studied for its tight link to surface weather, and automated circulation classifications have often been used to this end. Here, eight such classifications are applied to daily sea level pressure patterns simulated by an ensemble of CMIP5 GCMs twenty-first century projections for the British Isles and central Europe in order to robustly estimate future changes in frequency, persistence, and strength of synoptic-scale circulation there. All methods are able to identify present-day biases of models reported before, such as an overestimated occurrence of zonal flow and underestimation of anticyclonic conditions and easterly advection, although the strength of these biases varies among the methods. In future, models show that the zonal flow will become more frequent while the strength of the mean flow is not projected to change. Over the British Isles, the models that better simulate the latitude of zonal flow over the historical period indicate a slight equatorward shift of westerlies in their projections, while the poleward expansion of circulation—expected in future at global scale—is apparent in those models that have large errors. Over central Europe, some classifications indicate an increase in persistence and especially in frequency of anticyclonic types, which is, however, shown to be rather an artifact of some methods than a real feature. On the other hand, the easterly flow is robustly projected to become markedly weaker in central Europe, which we hypothesize might be an important factor contributing to the projected decrease of cold extremes there.

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

Deng, Min; Kollias, Pavlos; Feng, Zhe

The motivation for this research is to develop a precipitation classification and rain rate estimation method using cloud radar-only measurements for Atmospheric Radiation Measurement (ARM) long-term cloud observation analysis, which are crucial and unique for studying cloud lifecycle and precipitation features under different weather and climate regimes. Based on simultaneous and collocated observations of the Ka-band ARM zenith radar (KAZR), two precipitation radars (NCAR S-PolKa and Texas A&M University SMART-R), and surface precipitation during the DYNAMO/AMIE field campaign, a new cloud radar-only based precipitation classification and rain rate estimation method has been developed and evaluated. The resulting precipitation classification ismore » equivalent to those collocated SMART-R and S-PolKa observations. Both cloud and precipitation radars detected about 5% precipitation occurrence during this period. The convective (stratiform) precipitation fraction is about 18% (82%). The 2-day collocated disdrometer observations show an increased number concentration of large raindrops in convective rain compared to dominant concentration of small raindrops in stratiform rain. The composite distributions of KAZR reflectivity and Doppler velocity also show two distinct structures for convective and stratiform rain. These indicate that the method produces physically consistent results for two types of rain. The cloud radar-only rainfall estimation is developed based on the gradient of accumulative radar reflectivity below 1 km, near-surface Ze, and collocated surface rainfall (R) measurement. The parameterization is compared with the Z-R exponential relation. The relative difference between estimated and surface measured rainfall rate shows that the two-parameter relation can improve rainfall estimation.« less

Synthetic aperture radar for a crop information system: A multipolarization and multitemporal approach

NASA Astrophysics Data System (ADS)

Ban, Yifang

Acquisition of timely information is a critical requirement for successful management of an agricultural monitoring system. Crop identification and crop-area estimation can be done fairly successfully using satellite sensors operating in the visible and near-infrared (VIR) regions of the spectrum. However, data collection can be unreliable due to problems of cloud cover at critical stages of the growing season. The all-weather capability of synthetic aperture radar (SAR) imagery acquired from satellites provides data over large areas whenever crop information is required. At the same time, SAR is sensitive to surface roughness and should be able to provide surface information such as tillage-system characteristics. With the launch of ERS-1, the first long-duration SAR system became available. The analysis of airborne multipolarization SAR data, multitemporal ERS-1 SAR data, and their combinations with VIR data, is necessary for the development of image-analysis methodologies that can be applied to RADARSAT data for extracting agricultural crop information. The overall objective of this research is to evaluate multipolarization airborne SAR data, multitemporal ERS-1 SAR data, and combinations of ERS-1 SAR and satellite VIR data for crop classification using non-conventional algorithms. The study area is situated in Norwich Township, an agricultural area in Oxford County, southern Ontario, Canada. It has been selected as one of the few representative agricultural 'supersites' across Canada at which the relationships between radar data and agriculture are being studied. The major field crops are corn, soybeans, winter wheat, oats, barley, alfalfa, hay, and pasture. Using airborne C-HH and C-HV SAR data, it was found that approaches using contextual information, texture information and per-field classification for improving agricultural crop classification proved to be effective, especially the per-field classification method. Results show that three of the four best per-field classification accuracies (\\ K=0.91) are achieved using combinations of C-HH and C-VV SAR data. This confirms the strong potential of multipolarization data for crop classification. The synergistic effects of multitemporal ERS-1 SAR and Landsat TM data are evaluated for crop classification using an artificial neural network (ANN) approach. The results show that the per-field approach using a feed-forward ANN significantly improves the overall classification accuracy of both single-date and multitemporal SAR data. Using the combination of TM3,4,5 and Aug. 5 SAR data, the best per-field ANN classification of 96.8% was achieved. It represents an 8.5% improvement over a single TM3,4,5 classification alone. Using multitemporal ERS-1 SAR data acquired during the 1992 and 1993 growing seasons, the radar backscatter characteristics of crops and their underlying soils are analyzed. The SAR temporal backscatter profiles were generated for each crop type and the earliest times of the year for differentiation of individual crop types were determined. Orbital (incidence-angle) effects were also observed on all crops. The average difference between the two orbits was about 3 dB. Thus attention should be given to the local incidence-angle effects when using ERS-1 SAR data, especially when comparing fields from different scenes or different areas within the same scene. Finally, early- and mid-season multitemporal SAR data for crop classification using sequential-masking techniques are evaluated, based on the temporal backscatter profiles. It was found that all crops studied could be identified by July 21.

A classification scheme for edge-localized modes based on their probability distributions

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

Shabbir, A., E-mail: aqsa.shabbir@ugent.be; Max Planck Institute for Plasma Physics, D-85748 Garching; Hornung, G.

We present here an automated classification scheme which is particularly well suited to scenarios where the parameters have significant uncertainties or are stochastic quantities. To this end, the parameters are modeled with probability distributions in a metric space and classification is conducted using the notion of nearest neighbors. The presented framework is then applied to the classification of type I and type III edge-localized modes (ELMs) from a set of carbon-wall plasmas at JET. This provides a fast, standardized classification of ELM types which is expected to significantly reduce the effort of ELM experts in identifying ELM types. Further, themore » classification scheme is general and can be applied to various other plasma phenomena as well.« less

Winter Weather Tips: Understanding Alerts and Staying Safe this Season | Poster

Cancer.gov

By Jenna Seiss and Kylie Tomlin, Guest Writers, and Ashley DeVine, Staff Writer Maryland residents face the possibility of dangerous winter weather each year—from icy conditions to frigid temperatures. You may be familiar with the different types of winter weather alerts issued by the National Weather Service (NWS), but do you know what each alert means?  

URBAN WET-WEATHER FLOW MANAGEMENT: RESEARCH DIRECTIONS

EPA Science Inventory

There are three types of urban wet-weather flow (WWF) discharges: 1) combined-sewer overflow (CSO), which is a mixture of storm drainage and municipal-industrial wastewater discharged from combined sewers or dry-weather flow discharged from combined sewers due to clogged intercep...

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...

Standardizing Foot-Type Classification Using Arch Index Values

PubMed Central

Weil, Rich; de Boer, Emily

2012-01-01

ABSTRACT Purpose: The lack of a reliable classification standard for foot type makes drawing conclusions from existing research and clinical decisions difficult, since different foot types may move and respond to treatment differently. The purpose of this study was to determine interrater agreement for foot-type classification based on photo-box-derived arch index values. Method: For this correlational study with two raters, a sample of 11 healthy volunteers with normal to obese body mass indices was recruited from both a community weight-loss programme and a programme in physical therapy. Arch index was calculated using AutoCAD software from footprint photographs obtained via mirrored photo-box. Classification as high-arched, normal, or low-arched foot type was based on arch index values. Reliability of the arch index was determined with intra-class correlations; agreement on foot-type classification was determined using quadratic weighted kappa (κw). Results: Average arch index was 0.215 for one tester and 0.219 for the second tester, with an overall range of 0.017 to 0.370. Both testers classified 6 feet as low-arched, 9 feet as normal, and 7 feet as high-arched. Interrater reliability for the arch index was ICC=0.90; interrater agreement for foot-type classification was κw=0.923. Conclusions: Classification of foot type based on arch index values derived from plantar footprint photographs obtained via mirrored photo-box showed excellent reliability in people with varying BMI. Foot-type classification may help clinicians and researchers subdivide sample populations to better differentiate mobility, gait, or treatment effects among foot types. PMID:23729964

Regolith-geology mapping with support vector machine: A case study over weathered Ni-bearing peridotites, New Caledonia

NASA Astrophysics Data System (ADS)

De Boissieu, Florian; Sevin, Brice; Cudahy, Thomas; Mangeas, Morgan; Chevrel, Stéphane; Ong, Cindy; Rodger, Andrew; Maurizot, Pierre; Laukamp, Carsten; Lau, Ian; Touraivane, Touraivane; Cluzel, Dominique; Despinoy, Marc

2018-02-01

Accurate maps of Earth's geology, especially its regolith, are required for managing the sustainable exploration and development of mineral resources. This paper shows how airborne imaging hyperspectral data collected over weathered peridotite rocks in vegetated, mountainous terrane in New Caledonia were processed using a combination of methods to generate a regolith-geology map that could be used for more efficiently targeting Ni exploration. The image processing combined two usual methods, which are spectral feature extraction and support vector machine (SVM). This rationale being the spectral features extraction can rapidly reduce data complexity by both targeting only the diagnostic mineral absorptions and masking those pixels complicated by vegetation, cloud and deep shade. SVM is a supervised classification method able to generate an optimal non-linear classifier with these features that generalises well even with limited training data. Key minerals targeted are serpentine, which is considered as an indicator for hydrolysed peridotitic rock, and iron oxy-hydroxides (hematite and goethite), which are considered as diagnostic of laterite development. The final classified regolith map was assessed against interpreted regolith field sites, which yielded approximately 70% similarity for all unit types, as well as against a regolith-geology map interpreted using traditional datasets (not hyperspectral imagery). Importantly, the hyperspectral derived mineral map provided much greater detail enabling a more precise understanding of the regolith-geological architecture where there are exposed soils and rocks.

Landslide risk mitigation by means of early warning systems

NASA Astrophysics Data System (ADS)

Calvello, Michele

2017-04-01

Among the many options available to mitigate landslide risk, early warning systems may be used where, in specific circumstances, the risk to life increases above tolerable levels. A coherent framework to classify and analyse landslide early warning systems (LEWS) is herein presented. Once the objectives of an early warning strategy are defined depending on the scale of analysis and the type of landslides to address, the process of designing and managing a LEWS should synergically employ technical and social skills. A classification scheme for the main components of LEWSs is proposed for weather-induced landslides. The scheme is based on a clear distinction among: i) the landslide model, i.e. a functional relationship between weather characteristics and landslide events considering the geotechnical, geomorphological and hydro-geological characterization of the area as well as an adequate monitoring strategy; ii) the warning model, i.e. the landslide model plus procedures to define the warning events and to issue the warnings; iii) the warning system, i.e. the warning model plus warning dissemination procedures, communication and education tools, strategies for community involvement and emergency plans. Each component of a LEWS is related to a number of actors involved with their deployment, operational activities and management. For instance, communication and education, community involvement and emergency plans are all significantly influenced by people's risk perception and by operational aspects system managers need to address in cooperation with scientists.

A respiratory alert model for the Shenandoah Valley, Virginia, USA

NASA Astrophysics Data System (ADS)

Hondula, David M.; Davis, Robert E.; Knight, David B.; Sitka, Luke J.; Enfield, Kyle; Gawtry, Stephen B.; Stenger, Phillip J.; Deaton, Michael L.; Normile, Caroline P.; Lee, Temple R.

2013-01-01

Respiratory morbidity (particularly COPD and asthma) can be influenced by short-term weather fluctuations that affect air quality and lung function. We developed a model to evaluate meteorological conditions associated with respiratory hospital admissions in the Shenandoah Valley of Virginia, USA. We generated ensembles of classification trees based on six years of respiratory-related hospital admissions (64,620 cases) and a suite of 83 potential environmental predictor variables. As our goal was to identify short-term weather linkages to high admission periods, the dependent variable was formulated as a binary classification of five-day moving average respiratory admission departures from the seasonal mean value. Accounting for seasonality removed the long-term apparent inverse relationship between temperature and admissions. We generated eight total models specific to the northern and southern portions of the valley for each season. All eight models demonstrate predictive skill (mean odds ratio = 3.635) when evaluated using a randomization procedure. The predictor variables selected by the ensembling algorithm vary across models, and both meteorological and air quality variables are included. In general, the models indicate complex linkages between respiratory health and environmental conditions that may be difficult to identify using more traditional approaches.

Biological forest ecosystems diversity and there impact in semi arid land, analysis and followed by remote sensing (Alsat-1 data, Steppe of Algeria)

NASA Astrophysics Data System (ADS)

Zegrar, A.

2008-05-01

The Algerian forests present an important ecological diversity, due to the different type of weather, from the sub humid to arid. These type of weather have a direct influence on the forests ecosystem and condition the flours composition of these forests as well as their regeneration. The ecological diversity of some forests as part as it's constitution, plays an important role in the natural regeneration, following some natural curses (Forest fire, phenomenon of Chablis, stroke of wood...). The conservation of the biologic diversity and the bets in permanent value of some Forests ecosystem take moreover importance. Because the forest ecosystem have the aspect of uniting the biologic wealth of forests, some interior waters, some agricultural earths and some arid and sub humid earths. In this survey, the utilization of remote sensing data respectively satellite ALSAT-1 and satellite LANDSAT TM in different dates, inform us about impact of arid weather on the ecological diversity in the middle of some vegetal steppe formations and in particular on the regressive evolution of some forests ecosystem under the name of the DEFORESTATION. We have used data of satellite LANDSAT TM of the year 1989 and those of satellite ALSAT-1 of the year 2007, for a multistage study of the regressive evolution of forests ecosystem. an application of the specific treatments especially the classification supervised by the method of maximum of verisimilitude is used in order to identify the most important formations of the zone of survey. The index: NDVI, MSAVI2 and the index of IV verdure is used for characterized and determined the forests formations changes. The arithmetic combinations are used in the system of information geographical IDRISI. And after application of the method of the rations we obtained a picture of the changes. A map of the Vulnerability of the forests ecosystem was realized, this map informs us on the process of deforestation in the natural forests following the different aggression and permit us a possible perspectives of harnessing.

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

NASA Astrophysics Data System (ADS)

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

1987-03-01

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

Fabulous Weather Day

ERIC Educational Resources Information Center

Marshall, Candice; Mogil, H. Michael

2007-01-01

Each year, first graders at Kensington Parkwood Elementary School in Kensington, Maryland, look forward to Fabulous Weather Day. Students learn how meteorologists collect data about the weather, how they study wind, temperature, precipitation, basic types/characteristics of clouds, and how they forecast. The project helps the students grow in…

Iowa DOT weather information system to support winter maintenance operations

DOT National Transportation Integrated Search

2000-01-01

Understanding and interpreting weather information can be critical to the success of any winter snow and ice removal operation. Knowing when, where and what type of deicing material to use for a particular winter weather event can be a challenge to e...

Temperature extremes in Alaska: temporal variability and circulation background

NASA Astrophysics Data System (ADS)

Sulikowska, Agnieszka; Walawender, Jakub P.; Walawender, Ewelina

2018-06-01

The aims of this study are to characterize the spatial and temporal variability of extremely warm days (WDs) and warm spells (WSs) in summer as well as extremely cold days (CDs) and cold spells (CSs) in winter in Alaska in the years 1951-2015 and to determine the role of atmospheric circulation in their occurrence. The analysis is performed using daily temperature maxima (T MAX) and minima (T MIN) measured at 10 weather stations in Alaska as well as mean daily values of sea level pressure and wind direction at the 850 hPa isobaric level. WD (CD) is defined as a day with T MAX above the 95th (T MIN below the 5th) percentile of a probability density function calculated from observations, and WS (CS) equals at least three consecutive WDs (CDs). Frequency of the occurrence and severity of warm and cold extremes as well as duration of WSs and CSs is analyzed. In order to characterize synoptic conditions during temperature extremes, the objective classification scheme of advection types considering jointly the direction of the air influx and type of pressure system is employed. The results show that the general trend is towards the warmer temperatures, and the warming is greater in the winter than summer and for T MAX as opposed to T MIN. This is reflected in changes in the frequency of occurrence and intensity of temperature extremes which are much more pronounced in the case of winter cold extremes (decreasing tendencies) than summer warm extremes (increasing tendencies). The occurrence of temperature extremes is generally favored by anticyclonic weather with advection direction indicating air mass flows from the interior of the North American continent as well as the south (warm extremes in summer) and north (cold extremes in winter).

Industry and Government Officials Meet for Space Weather Summit

NASA Astrophysics Data System (ADS)

Intriligator, Devrie S.

2008-10-01

Commercial airlines, electric power grids, cell phones, handheld Global Positioning Systems: Although the Sun is less active due to solar minimum, the number and types of situations and technologies that can benefit from up-to-date space weather information are growing. To address this, the second annual summit of the Commercial Space Weather Interest Group (CSWIG) and the National Oceanic and Atmospheric Administration's Space Weather Prediction Center (SWPC) was held on 1 May 2008 during Space Weather Workshop (SWW), in Boulder, Colo.

Strontium and cesium release mechanisms during unsaturated flow through waste-weathered Hanford sediments.

PubMed

Chang, Hyun-Shik; Um, Wooyong; Rod, Kenton; Serne, R Jeff; Thompson, Aaron; Perdrial, Nicolas; Steefel, Carl I; Chorover, Jon

2011-10-01

Leaching behavior of Sr and Cs in the vadose zone of Hanford site (Washington) was studied with laboratory-weathered sediments mimicking realistic conditions beneath the leaking radioactive waste storage tanks. Unsaturated column leaching experiments were conducted using background Hanford pore water focused on first 200 pore volumes. The weathered sediments were prepared by 6 months reaction with a synthetic Hanford tank waste leachate containing Sr and Cs (10(-5) and 10(-3) molal representative of LO- and HI-sediment, respectively) as surrogates for (90)Sr and (137)Cs. The mineral composition of the weathered sediments showed that zeolite (chabazite-type) and feldspathoid (sodalite-type) were the major byproducts but different contents depending on the weathering conditions. Reactive transport modeling indicated that Cs leaching was controlled by ion-exchange, while Sr release was affected primarily by dissolution of the secondary minerals. The later release of K, Al, and Si from the HI-column indicated the additional dissolution of a more crystalline mineral (cancrinite-type). A two-site ion-exchange model successfully simulated the Cs release from the LO-column. However, a three-site ion-exchange model was needed for the HI-column. The study implied that the weathering conditions greatly impact the speciation of the secondary minerals and leaching behavior of sequestrated Sr and Cs.

Automated classification of dolphin echolocation click types from the Gulf of Mexico.

PubMed

Frasier, Kaitlin E; Roch, Marie A; Soldevilla, Melissa S; Wiggins, Sean M; Garrison, Lance P; Hildebrand, John A

2017-12-01

Delphinids produce large numbers of short duration, broadband echolocation clicks which may be useful for species classification in passive acoustic monitoring efforts. A challenge in echolocation click classification is to overcome the many sources of variability to recognize underlying patterns across many detections. An automated unsupervised network-based classification method was developed to simulate the approach a human analyst uses when categorizing click types: Clusters of similar clicks were identified by incorporating multiple click characteristics (spectral shape and inter-click interval distributions) to distinguish within-type from between-type variation, and identify distinct, persistent click types. Once click types were established, an algorithm for classifying novel detections using existing clusters was tested. The automated classification method was applied to a dataset of 52 million clicks detected across five monitoring sites over two years in the Gulf of Mexico (GOM). Seven distinct click types were identified, one of which is known to be associated with an acoustically identifiable delphinid (Risso's dolphin) and six of which are not yet identified. All types occurred at multiple monitoring locations, but the relative occurrence of types varied, particularly between continental shelf and slope locations. Automatically-identified click types from autonomous seafloor recorders without verifiable species identification were compared with clicks detected on sea-surface towed hydrophone arrays in the presence of visually identified delphinid species. These comparisons suggest potential species identities for the animals producing some echolocation click types. The network-based classification method presented here is effective for rapid, unsupervised delphinid click classification across large datasets in which the click types may not be known a priori.

Automated classification of dolphin echolocation click types from the Gulf of Mexico

PubMed Central

Roch, Marie A.; Soldevilla, Melissa S.; Wiggins, Sean M.; Garrison, Lance P.; Hildebrand, John A.

2017-01-01

Delphinids produce large numbers of short duration, broadband echolocation clicks which may be useful for species classification in passive acoustic monitoring efforts. A challenge in echolocation click classification is to overcome the many sources of variability to recognize underlying patterns across many detections. An automated unsupervised network-based classification method was developed to simulate the approach a human analyst uses when categorizing click types: Clusters of similar clicks were identified by incorporating multiple click characteristics (spectral shape and inter-click interval distributions) to distinguish within-type from between-type variation, and identify distinct, persistent click types. Once click types were established, an algorithm for classifying novel detections using existing clusters was tested. The automated classification method was applied to a dataset of 52 million clicks detected across five monitoring sites over two years in the Gulf of Mexico (GOM). Seven distinct click types were identified, one of which is known to be associated with an acoustically identifiable delphinid (Risso’s dolphin) and six of which are not yet identified. All types occurred at multiple monitoring locations, but the relative occurrence of types varied, particularly between continental shelf and slope locations. Automatically-identified click types from autonomous seafloor recorders without verifiable species identification were compared with clicks detected on sea-surface towed hydrophone arrays in the presence of visually identified delphinid species. These comparisons suggest potential species identities for the animals producing some echolocation click types. The network-based classification method presented here is effective for rapid, unsupervised delphinid click classification across large datasets in which the click types may not be known a priori. PMID:29216184

Results of the Clarus demonstrations : evaluation of enhanced road weather forecasting enabled by Clarus.

DOT National Transportation Integrated Search

2011-06-14

This document is the final report of an evaluation of Clarus-enabled enhanced road weather forecasting used in the Clarus Demonstrations. This report examines the use of Clarus data to enhance four types of weather models and forecasts: The Local Ana...

Robotic Spectroscopy at the Dark Sky Observatory

NASA Astrophysics Data System (ADS)

Rosenberg, Daniel E.; Gray, Richard O.; Mashburn, Jonathan; Swenson, Aaron W.; McGahee, Courtney E.; Briley, Michael M.

2018-06-01

Spectroscopic observations using the classification-resolution Gray-Miller spectrograph attached to the Dark Sky Observatory 32 inch telescope (Appalachian State University, North Carolina) have been automated with a robotic script called the “Robotic Spectroscopist” (RS). RS runs autonomously during the night and controls all operations related to spectroscopic observing. At the heart of RS are a number of algorithms that first select and center the target star in the field of an imaging camera and then on the spectrograph slit. RS monitors the observatory weather station, and suspends operations and closes the dome when weather conditions warrant, and can reopen and resume observations when the weather improves. RS selects targets from a list using a queue-observing protocol based on observer-assigned priorities, but also uses target-selection criteria based on weather conditions, especially seeing. At the end of the night RS transfers the data files to the main campus, where they are reduced with an automatic pipeline. Our experience has shown that RS is more efficient and consistent than a human observer, and produces data sets that are ideal for automatic reduction. RS should be adaptable for use at other similar observatories, and so we are making the code freely available to the astronomical community.

Detecting Nanophase Weathering Products with CheMin: Reference Intensity Ratios of Allophane, Aluminosilicate Gel, and Ferrihydrite

NASA Technical Reports Server (NTRS)

Rampe, E. B.; Bish, D. L.; Chipera, S. J.; Morris, R. V.; Achilles, C. N.; Ming, D W.; Blake, D. F.; Anderson, R. C.; Bristow, T. F.; Crisp, A.;

A deep belief network approach using VDRAS data for nowcasting

NASA Astrophysics Data System (ADS)

Han, Lei; Dai, Jie; Zhang, Wei; Zhang, Changjiang; Feng, Hanlei

2018-04-01

Nowcasting or very short-term forecasting convective storms is still a challenging problem due to the high nonlinearity and insufficient observation of convective weather. As the understanding of the physical mechanism of convective weather is also insufficient, the numerical weather model cannot predict convective storms well. Machine learning approaches provide a potential way to nowcast convective storms using various meteorological data. In this study, a deep belief network (DBN) is proposed to nowcast convective storms using the real-time re-analysis meteorological data. The nowcasting problem is formulated as a classification problem. The 3D meteorological variables are fed directly to the DBN with dimension of input layer 6*6*80. Three hidden layers are used in the DBN and the dimension of output layer is two. A box-moving method is presented to provide the input features containing the temporal and spatial information. The results show that the DNB can generate reasonable prediction results of the movement and growth of convective storms.

Ion Irradiation Experiments on the Murchison CM2 Carbonaceous Chondrite: Simulating Space Weathering of Primitive Asteroids

NASA Technical Reports Server (NTRS)

Keller, L. P.; Christoffersen, R.; Dukes, C. A.; Baragiola, R. A.; Rahman, Z.

2015-01-01

Remote sensing observations show that space weathering processes affect all airless bodies in the Solar System to some degree. Sample analyses and lab experiments provide insights into the chemical, spectroscopic and mineralogic effects of space weathering and aid in the interpretation of remote- sensing data. For example, analyses of particles returned from the S-type asteroid Itokawa by the Hayabusa mission revealed that space-weathering on that body was dominated by interactions with the solar wind acting on LL ordinary chondrite-like materials [1, 2]. Understanding and predicting how the surface regoliths of primitive carbonaceous asteroids respond to space weathering processes is important for future sample return missions (Hayabusa 2 and OSIRIS-REx) that are targeting objects of this type. Here, we report the results of our preliminary ion irradiation experiments on a hydrated carbonaceous chondrite with emphasis on microstructural and infrared spectral changes.

Identification of weather variables sensitive to dysentery in disease-affected county of China.

PubMed

Liu, Jianing; Wu, Xiaoxu; Li, Chenlu; Xu, Bing; Hu, Luojia; Chen, Jin; Dai, Shuang

2017-01-01

Climate change mainly refers to long-term change in weather variables, and it has significant impact on sustainability and spread of infectious diseases. Among three leading infectious diseases in China, dysentery is exclusively sensitive to climate change. Previous researches on weather variables and dysentery mainly focus on determining correlation between dysentery incidence and weather variables. However, the contribution of each variable to dysentery incidence has been rarely clarified. Therefore, we chose a typical county in epidemic of dysentery as the study area. Based on data of dysentery incidence, weather variables (monthly mean temperature, precipitation, wind speed, relative humidity, absolute humidity, maximum temperature, and minimum temperature) and lagged analysis, we used principal component analysis (PCA) and classification and regression trees (CART) to examine the relationships between the incidence of dysentery and weather variables. Principal component analysis showed that temperature, precipitation, and humidity played a key role in determining transmission of dysentery. We further selected weather variables including minimum temperature, precipitation, and relative humidity based on results of PCA, and used CART to clarify contributions of these three weather variables to dysentery incidence. We found when minimum temperature was at a high level, the high incidence of dysentery occurred if relative humidity or precipitation was at a high level. We compared our results with other studies on dysentery incidence and meteorological factors in areas both in China and abroad, and good agreement has been achieved. Yet, some differences remain for three reasons: not identifying all key weather variables, climate condition difference caused by local factors, and human factors that also affect dysentery incidence. This study hopes to shed light on potential early warnings for dysentery transmission as climate change occurs, and provide a theoretical basis for the control and prevention of dysentery. Copyright © 2016 Elsevier B.V. All rights reserved.

Applicability of geomechanical classifications for estimation of strength properties in Brazilian rock masses.

PubMed

Santos, Tatiana B; Lana, Milene S; Santos, Allan E M; Silveira, Larissa R C

2017-01-01

Many authors have been proposed several correlation equations between geomechanical classifications and strength parameters. However, these correlation equations have been based in rock masses with different characteristics when compared to Brazilian rock masses. This paper aims to study the applicability of the geomechanical classifications to obtain strength parameters of three Brazilian rock masses. Four classification systems have been used; the Rock Mass Rating (RMR), the Rock Mass Quality (Q), the Geological Strength Index (GSI) and the Rock Mass Index (RMi). A strong rock mass and two soft rock masses with different degrees of weathering located in the cities of Ouro Preto and Mariana, Brazil; were selected for the study. Correlation equations were used to estimate the strength properties of these rock masses. However, such correlations do not always provide compatible results with the rock mass behavior. For the calibration of the strength values obtained through the use of classification systems, ​​stability analyses of failures in these rock masses have been done. After calibration of these parameters, the applicability of the various correlation equations found in the literature have been discussed. According to the results presented in this paper, some of these equations are not suitable for the studied rock masses.

The Early Years: About the Weather

ERIC Educational Resources Information Center

Ashbrook, Peggy

2015-01-01

Observing and documenting elements of weather teach children about using tools and their senses to learn about the environment. This column discusses resources and science topics related to students in grades preK to 2. This month's issue describes an activity where students indirectly document local weather by counting outdoor clothing types worn…

Weather Fundamentals: Rain & Snow. [Videotape].

ERIC Educational Resources Information Center

1998

The videos in this educational series, for grades 4-7, help students understand the science behind weather phenomena through dramatic live-action footage, vivid animated graphics, detailed weather maps, and hands-on experiments. This episode (23 minutes) gives concise explanations of the various types of precipitation and describes how the water…

NOAA WEATHER SATELLITES

Science.gov Websites

extent of snow cover. In addition, satellite sensors detect ice fields and map the movement of sea and greater danger near shore or any shallow waters? NATIONAL WEATHER SERVICE SATELLITE PRODUCTS NOAA's operational weather satellite system is composed of two types of satellites: geostationary operational

Weather Fundamentals: Clouds. [Videotape].

ERIC Educational Resources Information Center

1998

The videos in this educational series, for grades 4-7, help students understand the science behind weather phenomena through dramatic live-action footage, vivid animated graphics, detailed weather maps, and hands-on experiments. This episode (23 minutes) discusses how clouds form, the different types of clouds, and the important role they play in…

The Effects of Space Weathering at UV Wavelengths: S-Class Asteroids

NASA Technical Reports Server (NTRS)

Hendrix, Amanda R.; Vilas, Faith

2006-01-01

We present evidence that space weathering manifests itself at near-UV wavelengths as a bluing of the spectrum, in contrast with the spectral reddening that has been seen at visible-near-IR wavelengths. Furthermore, the effects of space weathering at UV wavelengths tend to appear with less weathering than do the longer wavelength effects, suggesting that the UV wavelength range is a more sensitive indicator of weathering, and thus age. We report results from analysis of existing near-UV (approx.220-350 nm) measurements of S-type asteroids from the International Ultraviolet Explorer and the Hubble Space Telescope and comparisons with laboratory measurements of meteorites to support this hypothesis. Composite spectra of S asteroids are produced by combining UV spacecraft data with ground-based longer wavelength data. At visible-near-IR wavelengths, S-type asteroids are generally spectrally redder (and darker) than ordinary chondrite meteorites, whereas the opposite is generally true at near-UV wavelengths. Similarly, laboratory measurements of lunar samples show that lunar soils (presumably more weathered) are spectrally redder at longer wavelengths, and spectrally bluer at near-UV wavelengths, than less weathered crushed lunar rocks. The UV spectral bluing may be a result of the addition of nanophase iron to the regolith through the weathering process. The UV bluing is most prominent in the 300-400 nm range, where the strong UV absorption edge is degraded with weathering.

Analysis of biliary anatomy according to different classification systems.

PubMed

Deka, Pranjal; Islam, Mahibul; Jindal, Deepti; Kumar, Niteen; Arora, Ankur; Negi, Sanjay Singh

2014-01-01

Variations in biliary anatomy are common, and different classifications have been described. These classification systems have not been compared to each other in a single cohort. We report such variations in biliary anatomy on magnetic resonance cholangiopancreatography (MRCP) using six different classification systems. In 299 patients undergoing MRCP for various indications, biliary anatomy was classified as described by Couinaud (1957), Huang (1996), Karakas (2008), Choi (2003), Champetier (1994), and Ohkubo (2004). Correlation with direct cholangiography and vascular anatomy was done. Bile duct dimensions were measured. Cystic duct junction and pancreaticobiliary ductal junction (PBDJ) were classified. Normal biliary anatomy was noted in 57.8 %. The most common variants were Couinaud type D2, Choi type 3A, Huang type A1, Champetier type a, Ohkubo types D and J, and Karakas type 2a. The Ohkubo classification was the most appropriate; 3.1 % of right ducts and 6.3 % of left ducts with variant anatomy could not be classified using the Ohkubo classification. There was a good agreement between MRCP and direct cholangiography (ĸ = 0.9). Anomalous PBDJ was noted in 8.7 %. Variant biliary anatomy was not associated with gender (p = 0.194) or variant vascular anatomy (p = 0.24). Although each classification system has its merits and demerits, some anatomical variations cannot be classified using any of the previously described classifications. The Ohkubo classification system is the most applicable as it considers most clinically relevant variations pertinent to hepatobiliary surgery.

The effect of weather and its changes on emotional state - individual characteristics that make us vulnerable

NASA Astrophysics Data System (ADS)

Spasova, Z.

2011-03-01

Given the proven effects of weather on the human organism, an attempt to examine its effects on a psychological and emotional level has been made. Emotions affect the bio tone, working ability, and concentration; hence their significance in various domains of economic life such as health care, education, transportation, and tourism. The present pilot study was conducted in Sofia, Bulgaria over a period of eight months, using five psychological methods: Eysenck Personality Questionnaire, State-Trait Anxiety Inventory, Test for Self-assessment of the emotional state, Test for evaluation of moods and Test ''Self-confidence-Activity-Mood''. The Fiodorov-Chubukov's complex-climatic method was used to characterize meteorological conditions in order to include a maximal number of meteorological elements in the analysis. Sixteen weather types are defined depending on the meteorological elements values according to this method. Abrupt weather changes from one day to another, defined by the same method, were also considered. The results obtained by t-test showed that the different categories of weather led to changes in the emotional status, which indicates a character either positive or negative for the organism. The abrupt weather changes, according to expectations, have negative effects on human emotions - but only when a transition to the cloudy weather or weather type, classified as ''unfavorable'', has been realized. The relationship between weather and human emotions is rather complicated since it depends on individual characteristics of people. One of these individual psychological characteristics, marked by the dimension ''neuroticism'', has a strong effect on emotional reactions in different weather conditions. Emotionally stable individuals are more ''resistant'' to the weather influence on their emotions, while those who are emotionally unstable have a stronger dependence on the impacts of weather.

Characterization and parameterization of aerosol cloud condensation nuclei activation under different pollution conditions

PubMed Central

Che, H. C.; Zhang, X. Y.; Wang, Y. Q.; Zhang, L.; Shen, X. J.; Zhang, Y. M.; Ma, Q. L.; Sun, J. Y.; Zhang, Y. W.; Wang, T. T.

2016-01-01

To better understand the cloud condensation nuclei (CCN) activation capacity of aerosol particles in different pollution conditions, a long-term field experiment was carried out at a regional GAW (Global Atmosphere Watch) station in the Yangtze River Delta area of China. The homogeneity of aerosol particles was the highest in clean weather, with the highest active fraction of all the weather types. For pollution with the same visibility, the residual aerosol particles in higher relative humidity weather conditions were more externally mixed and heterogeneous, with a lower hygroscopic capacity. The hygroscopic capacity (κ) of organic aerosols can be classified into 0.1 and 0.2 in different weather types. The particles at ~150 nm were easily activated in haze weather conditions. For CCN predictions, the bulk chemical composition method was closer to observations at low supersaturations (≤0.1%), whereas when the supersaturation was ≥0.2%, the size-resolved chemical composition method was more accurate. As for the mixing state of the aerosol particles, in haze, heavy haze, and severe haze weather conditions CCN predictions based on the internal mixing assumption were robust, whereas for other weather conditions, predictions based on the external mixing assumption were more accurate. PMID:27075947

Weather Regulates Location, Timing, and Intensity of Dengue Virus Transmission between Humans and Mosquitoes.

PubMed

Campbell, Karen M; Haldeman, Kristin; Lehnig, Chris; Munayco, Cesar V; Halsey, Eric S; Laguna-Torres, V Alberto; Yagui, Martín; Morrison, Amy C; Lin, Chii-Dean; Scott, Thomas W

2015-01-01

Dengue is one of the most aggressively expanding mosquito-transmitted viruses. The human burden approaches 400 million infections annually. Complex transmission dynamics pose challenges for predicting location, timing, and magnitude of risk; thus, models are needed to guide prevention strategies and policy development locally and globally. Weather regulates transmission-potential via its effects on vector dynamics. An important gap in understanding risk and roadblock in model development is an empirical perspective clarifying how weather impacts transmission in diverse ecological settings. We sought to determine if location, timing, and potential-intensity of transmission are systematically defined by weather. We developed a high-resolution empirical profile of the local weather-disease connection across Peru, a country with considerable ecological diversity. Applying 2-dimensional weather-space that pairs temperature versus humidity, we mapped local transmission-potential in weather-space by week during 1994-2012. A binary classification-tree was developed to test whether weather data could classify 1828 Peruvian districts as positive/negative for transmission and into ranks of transmission-potential with respect to observed disease. We show that transmission-potential is regulated by temperature-humidity coupling, enabling epidemics in a limited area of weather-space. Duration within a specific temperature range defines transmission-potential that is amplified exponentially in higher humidity. Dengue-positive districts were identified by mean temperature >22°C for 7+ weeks and minimum temperature >14°C for 33+ weeks annually with 95% sensitivity and specificity. In elevated-risk locations, seasonal peak-incidence occurred when mean temperature was 26-29°C, coincident with humidity at its local maximum; highest incidence when humidity >80%. We profile transmission-potential in weather-space for temperature-humidity ranging 0-38°C and 5-100% at 1°C x 2% resolution. Local duration in limited areas of temperature-humidity weather-space identifies potential locations, timing, and magnitude of transmission. The weather-space profile of transmission-potential provides needed data that define a systematic and highly-sensitive weather-disease connection, demonstrating separate but coupled roles of temperature and humidity. New insights regarding natural regulation of human-mosquito transmission across diverse ecological settings advance our understanding of risk locally and globally for dengue and other mosquito-borne diseases and support advances in public health policy/operations, providing an evidence-base for modeling, predicting risk, and surveillance-prevention planning.

On the dual nature of lichen-induced rock surface weathering in contrasting micro-environments.

PubMed

Marques, Joana; Gonçalves, João; Oliveira, Cláudia; Favero-Longo, Sergio E; Paz-Bermúdez, Graciela; Almeida, Rubim; Prieto, Beatriz

2016-10-01

Contradictory evidence from biogeomorphological studies has increased the debate on the extent of lichen contribution to differential rock surface weathering in both natural and cultural settings. This study, undertaken in Côa Valley Archaeological Park, aimed at evaluating the effect of rock surface orientation on the weathering ability of dominant lichens. Hyphal penetration and oxalate formation at the lichen-rock interface were evaluated as proxies of physical and chemical weathering, respectively. A new protocol of pixel-based supervised image classification for the analysis of periodic acid-Schiff stained cross-sections of colonized schist revealed that hyphal spread of individual species was not influenced by surface orientation. However, hyphal spread was significantly higher in species dominant on northwest facing surfaces. An apparently opposite effect was noticed in terms of calcium oxalate accumulation at the lichen-rock interface; it was detected by Raman spectroscopy and complementary X-ray microdiffraction on southeast facing surfaces only. These results suggest that lichen-induced physical weathering may be most severe on northwest facing surfaces by means of an indirect effect of surface orientation on species abundance, and thus dependent on the species, whereas lichen-induced chemical weathering is apparently higher on southeast facing surfaces and dependent on micro-environmental conditions, giving only weak support to the hypothesis that lichens are responsible for the currently observed pattern of rock-art distribution in Côa Valley. Assumptions about the drivers of open-air rock-art distribution patterns elsewhere should also consider the micro-environmental controls of lichen-induced weathering, to avoid biased measures of lichen contribution to rock-art deterioration. © 2016 by the Ecological Society of America.

An approach for assessing the sensitivity of floods to regional climate change

NASA Astrophysics Data System (ADS)

Hughes, James P.; Lettenmaier, Dennis P.; Wood, Eric F.

1992-06-01

A high visibility afforded climate change issues is recent years has led to conflicts between and among decision makers and scientists. Decision makers inevitably feel pressure to assess the effect of climate change on the public welfare, while most climate modelers are, to a greater or lesser degree, concerned about the extent to which known inaccuracies in their models limit or preclude the use of modeling results for policy making. The water resources sector affords a good example of the limitations of the use of alternative climate scenarios derived from GCMs for decision making. GCM simulations of precipitation agree poorly between GCMs, and GCM predictions of runoff and evapotranspiration are even more uncertain. Further, water resources managers must be concerned about hydrologic extremes (floods and droughts) which are much more difficult to predict than ``average'' conditions. Most studies of the sensitivity of water resource systems and operating policies to climate change to data have been based on simple perturbations of historic hydroclimatological time series to reflect the difference between large area GCM simulations for an altered climate (e.g., CO2 doubling) and a GCM simulation of present climate. Such approaches are especially limited for assessment of the sensitivity of water resources systems under extreme conditions, conditions, since the distribution of storm inter-arrival times, for instance, is kept identical to that observed in the historic past. Further, such approaches have generally been based on the difference between the GCM altered and present climates for a single grid cell, primarily because the GCM spatial scale is often much larger than the scale at which climate interpretations are desired. The use of single grid cell GCM results is considered inadvisable by many GCM modelers, who feel the spatial scale for which interpretation of GCM results is most reasonable is on the order of several grid cells. In this paper, we demonstrate an alternative approach to assessing the implications of altered climates as predicted by GCMs for extreme (flooding) conditions. The approach is based on the characterization of regional atmospheric circulation patterns through a weather typing procedure, from which a stochastic model of the weather class occurrences is formulated. Weather types are identified through a CART (Classification and Regression Tree) approach. Precipitation occurence/non-occurence at multiple precipitation station is then predicted through a second stage stochastic model. Precipitation amounts are predicted conditional on the weather class identified from the large area circulation information.

Chinese and Russian Policies on Climate Change: Implications for U.S. National Security Policy

DTIC Science & Technology

2016-06-01

Second Reader: Naazneen Barma THIS PAGE INTENTIONALLY LEFT BLANK i REPORT DOCUMENTATION PAGE Form ...Unclassified 19. SECURITY CLASSIFICATION OF ABSTRACT Unclassified 20. LIMITATION OF ABSTRACT UU NSN 7540-01-280-5500 Standard Form 298 (Rev. 2...Effects in Russia These same imbalances in rainfall and other weather phenomena are being experienced throughout Russia in the form of floods, droughts

IPS Space Weather Research: Korea-Japan-UCSD

DTIC Science & Technology

2015-04-27

SUBJECT TERMS Solar Physics , Solar Wind, interplanetary scintillation 16. SECURITY CLASSIFICATION OF: 17. LIMITATION OF ABSTRACT SAR 18. NUMBER...Institution : Center for Astrophysics and space science (CASS), University of California, San Diego (UCSD) - Mailing Address : 9500 Gilman Dr. #0424...the physical parameters like solar wind velocities and densities. This is the one of the unique way to observer the solar wind from the earth. The

The groningen laryngomalacia classification system--based on systematic review and dynamic airway changes.

PubMed

van der Heijden, Martijn; Dikkers, Frederik G; Halmos, Gyorgy B

2015-12-01

Laryngomalacia is the most common cause of dyspnea and stridor in newborn infants. Laryngomalacia is a dynamic change of the upper airway based on abnormally pliable supraglottic structures, which causes upper airway obstruction. In the past, different classification systems have been introduced. Until now no classification system is widely accepted and applied. Our goal is to provide a simple and complete classification system based on systematic literature search and our experiences. Retrospective cohort study with literature review. All patients with laryngomalacia under the age of 5 at time of diagnosis were included. Photo and video documentation was used to confirm diagnosis and characteristics of dynamic airway change. Outcome was compared with available classification systems in literature. Eighty-five patients were included. In contrast to other classification systems, only three typical different dynamic changes have been identified in our series. Two existing classification systems covered 100% of our findings, but there was an unnecessary overlap between different types in most of the systems. Based on our finding, we propose a new a classification system for laryngomalacia, which is purely based on dynamic airway changes. The groningen laryngomalacia classification is a new, simplified classification system with three types, based on purely dynamic laryngeal changes, tested in a tertiary referral center: Type 1: inward collapse of arytenoids cartilages, Type 2: medial displacement of aryepiglottic folds, and Type 3: posterocaudal displacement of epiglottis against the posterior pharyngeal wall. © 2015 Wiley Periodicals, Inc.

Mapping of government land encroachment in Cameron Highlands using multiple remote sensing datasets

NASA Astrophysics Data System (ADS)

Zin, M. H. M.; Ahmad, B.

2014-02-01

The cold and refreshing highland weather is one of the factors that give impact to socio-economic growth in Cameron Highlands. This unique weather of the highland surrounded by tropical rain forest can only be found in a few places in Malaysia. It makes this place a famous tourism attraction and also provides a very suitable temperature for agriculture activities. Thus it makes agriculture such as tea plantation, vegetable, fruits and flowers one of the biggest economic activities in Cameron Highlands. However unauthorized agriculture activities are rampant. The government land, mostly forest area have been encroached by farmers, in many cases indiscriminately cutting down trees and hill slopes. This study is meant to detect and assess this encroachment using multiple remote sensing datasets. The datasets were used together with cadastral parcel data where survey lines describe property boundary, pieces of land are subdivided into lots of government and private. The general maximum likelihood classification method was used on remote sensing image to classify the land-cover in the study area. Ground truth data from field observation were used to assess the accuracy of the classification. Cadastral parcel data was overlaid on the classification map in order to detect the encroachment area. The result of this study shows that there is a land cover change of 93.535 ha in the government land of the study area between years 2001 to 2010, nevertheless almost no encroachment took place in the studied forest reserve area. The result of this study will be useful for the authority in monitoring and managing the forest.

Evaluation of operational numerical weather predictions in relation to the prevailing synoptic conditions

NASA Astrophysics Data System (ADS)

Pytharoulis, Ioannis; Tegoulias, Ioannis; Karacostas, Theodore; Kotsopoulos, Stylianos; Kartsios, Stergios; Bampzelis, Dimitrios

2015-04-01

The Thessaly plain, which is located in central Greece, has a vital role in the financial life of the country, because of its significant agricultural production. The aim of DAPHNE project (http://www.daphne-meteo.gr) is to tackle the problem of drought in this area by means of Weather Modification in convective clouds. This problem is reinforced by the increase of population and the water demand for irrigation, especially during the warm period of the year. The nonhydrostatic Weather Research and Forecasting model (WRF), is utilized for research and operational purposes of DAPHNE project. The WRF output fields are employed by the partners in order to provide high-resolution meteorological guidance and plan the project's operations. The model domains cover: i) Europe, the Mediterranean sea and northern Africa, ii) Greece and iii) the wider region of Thessaly (at selected periods), at horizontal grid-spacings of 15km, 5km and 1km, respectively, using 2-way telescoping nesting. The aim of this research work is to investigate the model performance in relation to the prevailing upper-air synoptic circulation. The statistical evaluation of the high-resolution operational forecasts of near-surface and upper air fields is performed at a selected period of the operational phase of the project using surface observations, gridded fields and weather radar data. The verification is based on gridded, point and object oriented techniques. The 10 upper-air circulation types, which describe the prevailing conditions over Greece, are employed in the synoptic classification. This methodology allows the identification of model errors that occur and/or are maximized at specific synoptic conditions and may otherwise be obscured in aggregate statistics. Preliminary analysis indicates that the largest errors are associated with cyclonic conditions. Acknowledgments This research work of Daphne project (11SYN_8_1088) is co-funded by the European Union (European Regional Development Fund) and Greek national funds, through the action "COOPERATION 2011: Partnerships of Production and Research Institutions in Focused Research and Technology Sectors" in the framework of the Operational Programme "Competitiveness and Entrepreneurship" and Regions in Transition (OPC II, NSRF 2007-2013).

Flight response of slope-soaring birds to seasonal variation in thermal generation

Treesearch

Adam E. Duerr; Tricia A. Miller; Michael Lanzone; David Brandes; Jeff Cooper; Kieran O' Malley; Charles Maisonneuve; Junior A. Tremblay; Todd Katzner

2014-01-01

Animals respond to a variety of environmental cues, including weather conditions, when migrating. Understanding the relationship between weather and migration behaviour is vital to assessing time- and energy limitations of soaring birds. Different soaring modes have different efficiencies, are dependent upon different types of subsidized lift and are weather dependent...

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…

Adverse Space Weather at the Solar Cycle Minimum

NASA Astrophysics Data System (ADS)

Baker, D. N.; Kanekal, S. G.; McCollough, J. P.; Singer, H. J.; Chappell, S. P.; Allen, J. H.

2008-05-01

It is commonly understood that many types of adverse space weather (solar flares, coronal mass ejections, geomagnetic storms) occur most commonly around the maximum of the 11-year sunspot activity cycle. Other types of well-known space weather such as relativistic electron events in the Earth's outer magnetosphere (that produce deep dielectric charging in spacecraft systems) are usually associated with the period just after sunspot maximum. At the present time, we are in the very lowest activity phase of the sunspot cycle (solar minimum). As such we would not expect much in the way of adverse space weather events. However, in early to mid-February of 2008 quite prominent solar coronal holes produced two high-speed streams that in turn stimulated very large, long-duration relativistic electron enhancements in Earth's magnetosphere. These seem to have been associated with several spacecraft operational anomalies at various spacecraft orbital locations. We describe these recent space weather events and assess their operational significance in this presentation. These results show that substantial space weather events can and do occur even during the quietest parts of the solar cycle.

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.

Automated classification of mouse pup isolation syllables: from cluster analysis to an Excel-based "mouse pup syllable classification calculator".

PubMed

Grimsley, Jasmine M S; Gadziola, Marie A; Wenstrup, Jeffrey J

2012-01-01

Mouse pups vocalize at high rates when they are cold or isolated from the nest. The proportions of each syllable type produced carry information about disease state and are being used as behavioral markers for the internal state of animals. Manual classifications of these vocalizations identified 10 syllable types based on their spectro-temporal features. However, manual classification of mouse syllables is time consuming and vulnerable to experimenter bias. This study uses an automated cluster analysis to identify acoustically distinct syllable types produced by CBA/CaJ mouse pups, and then compares the results to prior manual classification methods. The cluster analysis identified two syllable types, based on their frequency bands, that have continuous frequency-time structure, and two syllable types featuring abrupt frequency transitions. Although cluster analysis computed fewer syllable types than manual classification, the clusters represented well the probability distributions of the acoustic features within syllables. These probability distributions indicate that some of the manually classified syllable types are not statistically distinct. The characteristics of the four classified clusters were used to generate a Microsoft Excel-based mouse syllable classifier that rapidly categorizes syllables, with over a 90% match, into the syllable types determined by cluster analysis.

Strontium and cesium release mechanisms during unsaturated flow through waste-weathered Hanford sediments

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

Chang, Hyun-Shik; Um, Wooyong; Rod, Kenton A.

2011-10-01

Leaching behavior of Sr and Cs in the vadose zone of Hanford site (WA, USA) was studied with laboratory-weathered sediments mimicking realistic conditions beneath the leaking radioactive waste storage tanks. Unsaturated column leaching experiments were conducted using background Hanford pore water focused on first 200 pore volumes. The weathered sediments were prepared by 6 months reaction with a synthetic Hanford tank waste leachate containing Sr and Cs (10-5 and 10-3 molal representative of LO- and HI-sediment, respectively) as surrogates for 90Sr and 137Cs. The mineral composition of the weathered sediments showed that zeolite (chabazite-type) and feldspathoid (sodalite-type) were the majormore » byproducts but different contents depending on the weathering conditions. Reactive transport modeling indicated that Cs leaching was controlled by ion-exchange, while Sr release was affected primarily by dissolution of the secondary minerals. The later release of K, Al, and Si from the HI-column indicated the additional dissolution of a more crystalline mineral (cancrinite-type). A two-site ion-exchange model successfully simulated the Cs release from the LO-column. However, a three-site ion-exchange model was needed for the HI-column. The study implied that the weathering conditions greatly impact the speciation of the secondary minerals and leaching behavior of sequestrated Sr and Cs.« less

Extreme wildfire events are linked to global-change-type droughts in the northern Mediterranean

NASA Astrophysics Data System (ADS)

Ruffault, Julien; Curt, Thomas; Martin-StPaul, Nicolas K.; Moron, Vincent; Trigo, Ricardo M.

2018-03-01

Increasing drought conditions under global warming are expected to alter the frequency and distribution of large and high-intensity wildfires. However, our understanding of the impact of increasing drought on extreme wildfires events remains incomplete. Here, we analyzed the weather conditions associated with the extreme wildfires events that occurred in Mediterranean France during the exceptionally dry summers of 2003 and 2016. We identified that these fires were related to two distinct shifts in the fire weather space towards fire weather conditions that had not been explored before and resulting from specific interactions between different types of drought and different fire weather types. In 2016, a long-lasting press drought intensified wind-driven fires. In 2003, a hot drought combining a heat wave with a press drought intensified heat-induced fires. Our findings highlight that increasing drought conditions projected by climate change scenarios might affect the dryness of fuel compartments and lead to a higher frequency of extremes wildfires events.

Genetic programming applied to RFI mitigation in radio astronomy

NASA Astrophysics Data System (ADS)

Staats, K.

2016-12-01

Genetic Programming is a type of machine learning that employs a stochastic search of a solutions space, genetic operators, a fitness function, and multiple generations of evolved programs to resolve a user-defined task, such as the classification of data. At the time of this research, the application of machine learning to radio astronomy was relatively new, with a limited number of publications on the subject. Genetic Programming had never been applied, and as such, was a novel approach to this challenging arena. Foundational to this body of research, the application Karoo GP was developed in the programming language Python following the fundamentals of tree-based Genetic Programming described in "A Field Guide to Genetic Programming" by Poli, et al. Karoo GP was tasked with the classification of data points as signal or radio frequency interference (RFI) generated by instruments and machinery which makes challenging astronomers' ability to discern the desired targets. The training data was derived from the output of an observation run of the KAT-7 radio telescope array built by the South African Square Kilometre Array (SKA-SA). Karoo GP, kNN, and SVM were comparatively employed, the outcome of which provided noteworthy correlations between input parameters, the complexity of the evolved hypotheses, and performance of raw data versus engineered features. This dissertation includes description of novel approaches to GP, such as upper and lower limits to the size of syntax trees, an auto-scaling multiclass classifier, and a Numpy array element manager. In addition to the research conducted at the SKA-SA, it is described how Karoo GP was applied to fine-tuning parameters of a weather prediction model at the South African Astronomical Observatory (SAAO), to glitch classification at the Laser Interferometer Gravitational-wave Observatory (LIGO), and to astro-particle physics at The Ohio State University.

Geochemical assessments and classification of coal mine spoils for better understanding of potential salinity issues at closure.

PubMed

Park, Jin Hee; Li, Xiaofang; Edraki, Mansour; Baumgartl, Thomas; Kirsch, Bernie

2013-06-01

Coal mining wastes in the form of spoils, rejects and tailings deposited on a mine lease can cause various environmental issues including contamination by toxic metals, acid mine drainage and salinity. Dissolution of salt from saline mine spoil, in particular, during rainfall events may result in local or regional dispersion of salts through leaching or in the accumulation of dissolved salts in soil pore water and inhibition of plant growth. The salinity in coal mine environments is from the geogenic salt accumulations and weathering of spoils upon surface exposure. The salts are mainly sulfates and chlorides of calcium, magnesium and sodium. The objective of the research is to investigate and assess the source and mobility of salts and trace elements in various spoil types, thereby predicting the leaching behavior of the salts and trace elements from spoils which have similar geochemical properties. X-ray diffraction analysis, total digestion, sequential extraction and column experiments were conducted to achieve the objectives. Sodium and chloride concentrations best represented salinity of the spoils, which might originate from halite. Electrical conductivity, sodium and chloride concentrations in the leachate decreased sharply with increasing leaching cycles. Leaching of trace elements was not significant in the studied area. Geochemical classification of spoil/waste defined for rehabilitation purposes was useful to predict potential salinity, which corresponded with the classification from cluster analysis based on leaching data of major elements. Certain spoil groups showed high potential salinity by releasing high sodium and chloride concentrations. Therefore, the leaching characteristics of sites having saline susceptible spoils require monitoring, and suitable remediation technologies have to be applied.

Types of Forecast and Weather-Related Information Used among Tourism Businesses in Coastal North Carolina

NASA Astrophysics Data System (ADS)

Ayscue, Emily P.

This study profiles the coastal tourism sector, a large and diverse consumer of climate and weather information. It is crucial to provide reliable, accurate and relevant resources for the climate and weather-sensitive portions of this stakeholder group in order to guide them in capitalizing on current climate and weather conditions and to prepare them for potential changes. An online survey of tourism business owners, managers and support specialists was conducted within the eight North Carolina oceanfront counties asking respondents about forecasts they use and for what purposes as well as why certain forecasts are not used. Respondents were also asked about their perceived dependency of their business on climate and weather as well as how valuable different forecasts are to their decision-making. Business types represented include: Agriculture, Outdoor Recreation, Accommodations, Food Services, Parks and Heritage, and Other. Weekly forecasts were the most popular forecasts with Monthly and Seasonal being the least used. MANOVA and ANOVA analyses revealed outdoor-oriented businesses (Agriculture and Outdoor Recreation) as perceiving themselves significantly more dependent on climate and weather than indoor-oriented ones (Food Services and Accommodations). Outdoor businesses also valued short-range forecasts significantly more than indoor businesses. This suggests a positive relationship between perceived climate and weather dependency and forecast value. The low perceived dependency and value of short-range forecasts of indoor businesses presents an opportunity to create climate and weather information resources directed at how they can capitalize on positive climate and weather forecasts and how to counter negative effects with forecasted adverse conditions. The low use of long-range forecasts among all business types can be related to the low value placed on these forecasts. However, these forecasts are still important in that they are used to make more financially risky decisions such as investment decisions.

Image processing for hazard recognition in on-board weather radar

NASA Technical Reports Server (NTRS)

Kelly, Wallace E. (Inventor); Rand, Timothy W. (Inventor); Uckun, Serdar (Inventor); Ruokangas, Corinne C. (Inventor)

2003-01-01

A method of providing weather radar images to a user includes obtaining radar image data corresponding to a weather radar image to be displayed. The radar image data is image processed to identify a feature of the weather radar image which is potentially indicative of a hazardous weather condition. The weather radar image is displayed to the user along with a notification of the existence of the feature which is potentially indicative of the hazardous weather condition. Notification can take the form of textual information regarding the feature, including feature type and proximity information. Notification can also take the form of visually highlighting the feature, for example by forming a visual border around the feature. Other forms of notification can also be used.

Space Weathering of Ordinary Chondrite Parent Bodies, Its Impact on the Method of Distinguishing H, L, and LL Types and Implications for Itokawa Samples Returned by the Hayabusa Mission

NASA Technical Reports Server (NTRS)

Hiroi, T.; Sasaki, S.; Noble, S. K.; Pieters, C. M.

2011-01-01

As the most abundance meteorites in our collections, ordinary chondrites potentially have very important implications on the origin and formation of our Solar System. In order to map the distribution of ordinary chondrite-like asteroids through remote sensing, the space weathering effects of ordinary chondrite parent bodies must be addressed through experiments and modeling. Of particular importance is the impact on distinguishing different types (H/L/LL) of ordinary chondrites. In addition, samples of asteroid Itokawa returned by the Hayabusa spacecraft may re veal the mechanism of space weathering on an LLchondrite parent body. Results of space weathering simulations on ordinary chondrites and implications for Itokawa samples are presented here.

The Thermodynamic Structure of Arctic Coastal Fog Occurring During the Melt Season over East Greenland

NASA Astrophysics Data System (ADS)

Gilson, Gaëlle F.; Jiskoot, Hester; Cassano, John J.; Gultepe, Ismail; James, Timothy D.

2018-05-01

An automated method to classify Arctic fog into distinct thermodynamic profiles using historic in-situ surface and upper-air observations is presented. This classification is applied to low-resolution Integrated Global Radiosonde Archive (IGRA) soundings and high-resolution Arctic Summer Cloud Ocean Study (ASCOS) soundings in low- and high-Arctic coastal and pack-ice environments. Results allow investigation of fog macrophysical properties and processes in coastal East Greenland during melt seasons 1980-2012. Integrated with fog observations from three synoptic weather stations, 422 IGRA soundings are classified into six fog thermodynamic types based on surface saturation ratio, type of temperature inversion, fog-top height relative to inversion-base height and stability using the virtual potential temperature gradient. Between 65-80% of fog observations occur with a low-level inversion, and statically neutral or unstable surface layers occur frequently. Thermodynamic classification is sensitive to the assigned dew-point depression threshold, but categorization is robust. Despite differences in the vertical resolution of radiosonde observations, IGRA and ASCOS soundings yield the same six fog classes, with fog-class distribution varying with latitude and environmental conditions. High-Arctic fog frequently resides within an elevated inversion layer, whereas low-Arctic fog is more often restricted to the mixed layer. Using supplementary time-lapse images, ASCOS microwave radiometer retrievals and airmass back-trajectories, we hypothesize that the thermodynamic classes represent different stages of advection fog formation, development, and dissipation, including stratus-base lowering and fog lifting. This automated extraction of thermodynamic boundary-layer and inversion structure can be applied to radiosonde observations worldwide to better evaluate fog conditions that affect transportation and lead to improvements in numerical models.

Vs30 mapping at selected sites within the Greater Accra Metropolitan Area

NASA Astrophysics Data System (ADS)

Nortey, Grace; Armah, Thomas K.; Amponsah, Paulina

2018-06-01

A large part of Accra is underlain by a complex distribution of shallow soft soils. Within seismically active zones, these soils hold the most potential to significantly amplify seismic waves and cause severe damage, especially to structures sited on soils lacking sufficient stiffness. This paper presents preliminary site classification for the Greater Accra Metropolitan Area of Ghana (GAMA), using experimental data from two-dimensional (2-D) Multichannel Analysis of Surface Wave (MASW) technique. The dispersive characteristics of fundamental mode Rayleigh type surface waves were utilized for imaging the shallow subsurface layers (approx. up to 30 m depth) by estimating the 1D (depth) and 2D (depth and surface location) shear wave velocities at 5 selected sites. The average shear wave velocity for 30 m depth (Vs30), which is critical in evaluating the site response of the upper 30 m, was estimated and used for the preliminary site classification of the GAM area, as per NEHRP (National Earthquake Hazards Reduction Program). Based on the Vs30 values obtained in the study, two common site types C, and D corresponding to shallow (>6 m < 30 m) weathered rock and deep (up 30 m thick) stiff soils respectively, have been identified within the study area. Lower velocity profiles are inferred for the residual soils (sandy to silty clays), derived from the Accraian Formation that lies mainly within Accra central. Stiffer soil sites lie to the north of Accra, and to the west near Nyanyano. The seismic response characteristics over the residual soils in the GAMA have become apparent using the MASW technique. An extensive site effect map and a more robust probabilistic seismic hazard analysis can now be efficiently built for the metropolis, by considering the site classes and design parameters obtained from this study.

Improvement and further development of SSM/I overland parameter algorithms using the WetNet workstation

NASA Technical Reports Server (NTRS)

Neale, Christopher M. U.; Mcdonnell, Jeffrey J.; Ramsey, Douglas; Hipps, Lawrence; Tarboton, David

1993-01-01

Since the launch of the DMSP Special Sensor Microwave/Imager (SSM/I), several algorithms have been developed to retrieve overland parameters. These include the present operational algorithms resulting from the Navy calibration/validation effort such as land surface type (Neale et al. 1990), land surface temperature (McFarland et al. 1990), surface moisture (McFarland and Neale, 1991) and snow parameters (McFarland and Neale, 1991). In addition, other work has been done including the classification of snow cover and precipitation using the SSM/I (Grody, 1991). Due to the empirical nature of most of the above mentioned algorithms, further research is warranted and improvements can probably be obtained through a combination of radiative transfer modelling to study the physical processes governing the microwave emissions at the SSM/I frequencies, and the incorporation of additional ground truth data and special cases into the regression data sets. We have proposed specifically to improve the retrieval of surface moisture and snow parameters using the WetNet SSM/I data sets along with ground truth information namely climatic variables from the NOAA cooperative network of weather stations as well as imagery from other satellite sensors such as the AVHRR and Thematic Mapper. In the case of surface moisture retrievals the characterization of vegetation density is of primary concern. The higher spatial resolution satellite imagery collected at concurrent periods will be used to characterize vegetation types and amounts which, along with radiative transfer modelling should lead to more physically based retrievals. Snow parameter retrieval algorithm improvement will initially concentrate on the classification of snowpacks (dry snow, wet snow, refrozen snow) and later on specific products such as snow water equivalent. Significant accomplishments in the past year are presented.

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

NASA Technical Reports Server (NTRS)

McAdaragh, Raymon M.

2002-01-01

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

Global comparison reveals biogenic weathering as driven by nutrient limitation at ecosystem scale

NASA Astrophysics Data System (ADS)

Boy, Jens; Godoy, Roberto; Dechene, Annika; Shibistova, Olga; Amir, Hamid; Iskandar, Issi; Fogliano, Bruno; Boy, Diana; McCulloch, Robert; Andrino, Alberto; Gschwendtner, Silvia; Marin, Cesar; Sauheitl, Leopold; Dultz, Stefan; Mikutta, Robert; Guggenberger, Georg

2017-04-01

A substantial contribution of biogenic weathering in ecosystem nutrition, especially by symbiotic microorganisms, has often been proposed, but large-scale in vivo studies are still missing. Here we compare a set of ecosystems spanning from the Antarctic to tropical forests for their potential biogenic weathering and its drivers. To address biogenic weathering rates, we installed mineral mesocosms only accessible for bacteria and fungi for up to 4 years, which contained freshly broken and defined nutrient-baring minerals in soil A horizons of ecosystems along a gradient of soil development differing in climate and plant species communities. Alterations of the buried minerals were analyzed by grid-intersection, confocal lascer scanning microscopy, energy-dispersive X-ray spectroscopy, and X-ray photoelectron spectroscopy on the surface and on thin sections. On selected sites, carbon fluxes were tracked by 13C labeling, and microbial community was identified by DNA sequencing. In young ecosystems (protosoils) biogenic weathering is almost absent and starts after first carbon accumulation by aeolian (later litter) inputs and is mainly performed by bacteria. With ongoing soil development and appearance of symbiotic (mycorrhized) plants, nutrient availability in soil increasingly drove biogenic weathering, and fungi became the far more important players than bacteria. We found a close relation between fungal biogenic weathering and available potassium across all 16 forested sites in the study, regardless of the dominant mycorrhiza type (AM or EM), climate, and plant-species composition. We conclude that nutrient limitations at ecosystem scale are generally counteracted by adapted fungal biogenic weathering. The close relation between fungal weathering and plant-available nutrients over a large range of severely contrasting ecosystems points towards a direct energetic support of these weathering processes by the photoautotrophic community, making biogenic weathering a directional on-demand process common in all types of ecosystems.

Space weathering of small Koronis family members

NASA Astrophysics Data System (ADS)

Thomas, Cristina A.; Rivkin, Andrew S.; Trilling, David E.; Enga, Marie-therese; Grier, Jennifer A.

2011-03-01

The space weathering process and its implications for the relationships between S- and Q-type asteroids and ordinary chondrite meteorites is an often debated topic in asteroid science. Q-type asteroids have been shown to display the best spectral match to ordinary chondrites (McFadden, L.A., Gaffey, M.J., McCord, T.B. [1985]. Science 229, 160-163). While the Q-types and ordinary chondrites share some spectral features with S-type asteroids, the S-types have significantly redder spectral slopes than the Q-types in visible and near-infrared wavelengths. This reddening of spectral slope is attributed to the effects of space weathering on the observed surface composition. The analysis by Binzel et al. (Binzel, R.P., Rivkin, A.S., Stuart, J.S., Harris, A.W., Bus, S.J., Burbine, T.H. [2004]. Icarus 170, 259-294) provided a missing link between the Q- and S-type bodies in near-Earth space by showing a reddening of spectral slope in objects from 0.1 to 5 km that corresponded to a transition from Q-type to S-type asteroid spectra, implying that size, and therefore surface age, is related to the relationship between S- and Q-types. The existence of Q-type asteroids in the main-belt was not confirmed until Mothé-Diniz and Nesvorny (Mothé-Diniz, T., Nesvorny, D. [2008]. Astron. Astrophys. 486, L9-L12) found them in young S-type clusters. The young age of these families suggest that the unweathered surface could date to the formation of the family. This leads to the question of whether older S-type main-belt families can contain Q-type objects and display evidence of a transition from Q- to S-type. To answer this question we have carried out a photometric survey of the Koronis family using the Kitt Peak 2.1 m telescope. This provides a unique opportunity to compare the effects of the space weathering process on potentially ordinary chondrite-like bodies within a population of identical initial conditions. We find a trend in spectral slope for objects 1-5 km that shows the transition from Q- to S-type in the main-belt. This data set will prove crucial to our understanding of the space weathering process and its relevant timescales.

A Quantitative Geochemical, Mineralogical and Physical Study of Some Selected Rock Weathering Profiles from Brazil

DTIC Science & Technology

1977-08-17

weather to gibbsite (plus or minus iron oxides) in well-drained, and smectite in poorly-drained, environments. Kaolinite found in the vicinity of quartz...rock and completely weathered saprolite. Quartz-rich rock types exhibit wide, gradational weathered zones and usually form kaolinite or halloysite in...free rocks is either formed by re-silication of gibbsite , or is of secondary origin (transported). Texture of the rock (aphanitic vs. phaneric) has

Differences in forest area classification based on tree tally from variable- and fixed-radius plots

Treesearch

David Azuma; Vicente J. Monleon

2011-01-01

In forest inventory, it is not enough to formulate a definition; it is also necessary to define the "measurement procedure." In the classification of forestland by dominant cover type, the measurement design (the plot) can affect the outcome of the classification. We present results of a simulation study comparing classification of the dominant cover type...

Generalized Rainich conditions, generalized stress-energy conditions, and the Hawking-Ellis classification

NASA Astrophysics Data System (ADS)

Martín–Moruno, Prado; Visser, Matt

2017-11-01

The (generalized) Rainich conditions are algebraic conditions which are polynomial in the (mixed-component) stress-energy tensor. As such they are logically distinct from the usual classical energy conditions (NEC, WEC, SEC, DEC), and logically distinct from the usual Hawking-Ellis (Segré-Plebański) classification of stress-energy tensors (type I, type II, type III, type IV). There will of course be significant inter-connections between these classification schemes, which we explore in the current article. Overall, we shall argue that it is best to view the (generalized) Rainich conditions as a refinement of the classical energy conditions and the usual Hawking-Ellis classification.

Effect of weathering variables on the lightness of high-density polyethylene woodflour composites

Treesearch

Nicole M. Stark

2005-01-01

Wood-plastic lumber is promoted as a low-maintenance, high-durability product. After weathering, however, wood-plastic composites (WPCs) often fade. In the first part of this study, 50 percent woodflour-filled high- density polyethylene (HDPE) composite samples were manufactured. Composites were exposed to two accelerated weathering cycles in a xenon- arc type...

Extreme weather caused by concurrent cyclone, front and thunderstorm occurrences

PubMed Central

Dowdy, Andrew J.; Catto, Jennifer L.

2017-01-01

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

A weathering-related origin of widespread monazite in S-type granites

NASA Astrophysics Data System (ADS)

Sawka, Wayne N.; Banfield, Jillian F.; Chappell, Bruch W.

1986-01-01

The S-type granite suites comprising more than a quarter of the extensively developed granites in the Lachlan Fold Belt, Australia, contain monazite which may be related to the chemical weathering of the sedimentary source rocks. We report a process whereby chemical weathering fixes mobile rare-earth elements (REE) in hydrous phosphate phases such as florencite and rhabdophane. This material contains up to 50 wt% LREE and occurs as very small particles (~3μm). Dehydration of these hydrous REE phases during anatexis directly yields monazite. The low solubility of phosphorus in S-type granite melts inhibits dissolution of both monazite and apatite. Refractory monazite may be thus entrained and transported in S-type granites in a manner similar to processes resulting in inherited zircon. Since both Th and the light REE are major components in monazite, materials containing this minute phase may be of widespread geochemical significance in both granites and metamorphic rocks.

Lessons Learned Using Fractions to Assess Risk at Petroleum Release Sites

DTIC Science & Technology

2004-04-01

Jet Fuel Bioavailability Hydrocarbon fractions Total Petroleum Hydrocarbons Weathered petroleum Sequestration 16. SECURITY CLASSIFICATION OF: 17...requirements at sites that were contaminated with petroleum products such as gasoline, diesel fuel , jet fuel , heating oil, lubricants and used motor oils...December 2002. Four of the demonstration sites were contaminated with jet fuel (i.e., JP-4, JP-5 or JP-8). The Misawa Air Base site was contaminated with

46 CFR 164.018-3 - Classification.

Code of Federal Regulations, 2011 CFR

2011-10-01

... 46 Shipping 6 2011-10-01 2011-10-01 false Classification. 164.018-3 Section 164.018-3 Shipping COAST GUARD, DEPARTMENT OF HOMELAND SECURITY (CONTINUED) EQUIPMENT, CONSTRUCTION, AND MATERIALS... Classification. The following types of retroreflective material are approved under this specification: (a) Type I...

46 CFR 164.018-3 - Classification.

Code of Federal Regulations, 2012 CFR

2012-10-01

... 46 Shipping 6 2012-10-01 2012-10-01 false Classification. 164.018-3 Section 164.018-3 Shipping COAST GUARD, DEPARTMENT OF HOMELAND SECURITY (CONTINUED) EQUIPMENT, CONSTRUCTION, AND MATERIALS... Classification. The following types of retroreflective material are approved under this specification: (a) Type I...

46 CFR 164.018-3 - Classification.

Code of Federal Regulations, 2013 CFR

2013-10-01

... 46 Shipping 6 2013-10-01 2013-10-01 false Classification. 164.018-3 Section 164.018-3 Shipping COAST GUARD, DEPARTMENT OF HOMELAND SECURITY (CONTINUED) EQUIPMENT, CONSTRUCTION, AND MATERIALS... Classification. The following types of retroreflective material are approved under this specification: (a) Type I...

46 CFR 164.018-3 - Classification.

Code of Federal Regulations, 2014 CFR

2014-10-01

... 46 Shipping 6 2014-10-01 2014-10-01 false Classification. 164.018-3 Section 164.018-3 Shipping COAST GUARD, DEPARTMENT OF HOMELAND SECURITY (CONTINUED) EQUIPMENT, CONSTRUCTION, AND MATERIALS... Classification. The following types of retroreflective material are approved under this specification: (a) Type I...

46 CFR 164.018-3 - Classification.

Code of Federal Regulations, 2010 CFR

2010-10-01

... 46 Shipping 6 2010-10-01 2010-10-01 false Classification. 164.018-3 Section 164.018-3 Shipping COAST GUARD, DEPARTMENT OF HOMELAND SECURITY (CONTINUED) EQUIPMENT, CONSTRUCTION, AND MATERIALS... Classification. The following types of retroreflective material are approved under this specification: (a) Type I...

Applications of ISES for meteorology

NASA Technical Reports Server (NTRS)

Try, Paul D.

1990-01-01

The results are summarized from an initial assessment of the potential real-time meteorological requirements for the data from Eos systems. Eos research scientists associated with facility instruments, investigator instruments, and interdisciplinary groups with data related to meteorological support were contacted, along with those from the normal operational user and technique development groups. Two types of activities indicated the greatest need for real-time Eos data: technology transfer groups (e.g., NOAA's Forecasting System Laboratory and the DOD development laboratories), and field testing groups with airborne operations. A special concern was expressed by several non-U.S. participants who desire a direct downlink to be sure of rapid receipt of the data for their area of interest. Several potential experiments or demonstrations are recommended for ISES which include support for hurricane/typhoon forecasting, space shuttle reentry, severe weather forecasting (using microphysical cloud classification techniques), field testing, and quick reaction of instrumented aircraft to measure such events as polar stratospheric clouds and volcanic eruptions.

Sub-pixel image classification for forest types in East Texas

NASA Astrophysics Data System (ADS)

Westbrook, Joey

Sub-pixel classification is the extraction of information about the proportion of individual materials of interest within a pixel. Landcover classification at the sub-pixel scale provides more discrimination than traditional per-pixel multispectral classifiers for pixels where the material of interest is mixed with other materials. It allows for the un-mixing of pixels to show the proportion of each material of interest. The materials of interest for this study are pine, hardwood, mixed forest and non-forest. The goal of this project was to perform a sub-pixel classification, which allows a pixel to have multiple labels, and compare the result to a traditional supervised classification, which allows a pixel to have only one label. The satellite image used was a Landsat 5 Thematic Mapper (TM) scene of the Stephen F. Austin Experimental Forest in Nacogdoches County, Texas and the four cover type classes are pine, hardwood, mixed forest and non-forest. Once classified, a multi-layer raster datasets was created that comprised four raster layers where each layer showed the percentage of that cover type within the pixel area. Percentage cover type maps were then produced and the accuracy of each was assessed using a fuzzy error matrix for the sub-pixel classifications, and the results were compared to the supervised classification in which a traditional error matrix was used. The overall accuracy of the sub-pixel classification using the aerial photo for both training and reference data had the highest (65% overall) out of the three sub-pixel classifications. This was understandable because the analyst can visually observe the cover types actually on the ground for training data and reference data, whereas using the FIA (Forest Inventory and Analysis) plot data, the analyst must assume that an entire pixel contains the exact percentage of a cover type found in a plot. An increase in accuracy was found after reclassifying each sub-pixel classification from nine classes with 10 percent interval each to five classes with 20 percent interval each. When compared to the supervised classification which has a satisfactory overall accuracy of 90%, none of the sub-pixel classification achieved the same level. However, since traditional per-pixel classifiers assign only one label to pixels throughout the landscape while sub-pixel classifications assign multiple labels to each pixel, the traditional 85% accuracy of acceptance for pixel-based classifications should not apply to sub-pixel classifications. More research is needed in order to define the level of accuracy that is deemed acceptable for sub-pixel classifications.

An analysis of high-impact, low-predictive skill severe weather events in the northeast U.S

NASA Astrophysics Data System (ADS)

Vaughan, Matthew T.

An objective evaluation of Storm Prediction Center slight risk convective outlooks, as well as a method to identify high-impact severe weather events with poor-predictive skill are presented in this study. The objectives are to assess severe weather forecast skill over the northeast U.S. relative to the continental U.S., build a climatology of high-impact, low-predictive skill events between 1980--2013, and investigate the dynamic and thermodynamic differences between severe weather events with low-predictive skill and high-predictive skill over the northeast U.S. Severe storm reports of hail, wind, and tornadoes are used to calculate skill scores including probability of detection (POD), false alarm ratio (FAR) and threat scores (TS) for each convective outlook. Low predictive skill events are binned into low POD (type 1) and high FAR (type 2) categories to assess temporal variability of low-predictive skill events. Type 1 events were found to occur in every year of the dataset with an average of 6 events per year. Type 2 events occur less frequently and are more common in the earlier half of the study period. An event-centered composite analysis is performed on the low-predictive skill database using the National Centers for Environmental Prediction Climate Forecast System Reanalysis 0.5° gridded dataset to analyze the dynamic and thermodynamic conditions prior to high-impact severe weather events with varying predictive skill. Deep-layer vertical shear between 1000--500 hPa is found to be a significant discriminator in slight risk forecast skill where high-impact events with less than 31-kt shear have lower threat scores than high-impact events with higher shear values. Case study analysis of type 1 events suggests the environment over which severe weather occurs is characterized by high downdraft convective available potential energy, steep low-level lapse rates, and high lifting condensation level heights that contribute to an elevated risk of severe wind.

Models of Weather Impact on Air Traffic

NASA Technical Reports Server (NTRS)

Kulkarni, Deepak; Wang, Yao

2017-01-01

Flight delays have been a serious problem in the national airspace system costing about $30B per year. About 70 of the delays are attributed to weather and upto two thirds of these are avoidable. Better decision support tools would reduce these delays and improve air traffic management tools. Such tools would benefit from models of weather impacts on the airspace operations. This presentation discusses use of machine learning methods to mine various types of weather and traffic data to develop such models.

Classification and reduction of pilot error

NASA Technical Reports Server (NTRS)

Rogers, W. H.; Logan, A. L.; Boley, G. D.

1989-01-01

Human error is a primary or contributing factor in about two-thirds of commercial aviation accidents worldwide. With the ultimate goal of reducing pilot error accidents, this contract effort is aimed at understanding the factors underlying error events and reducing the probability of certain types of errors by modifying underlying factors such as flight deck design and procedures. A review of the literature relevant to error classification was conducted. Classification includes categorizing types of errors, the information processing mechanisms and factors underlying them, and identifying factor-mechanism-error relationships. The classification scheme developed by Jens Rasmussen was adopted because it provided a comprehensive yet basic error classification shell or structure that could easily accommodate addition of details on domain-specific factors. For these purposes, factors specific to the aviation environment were incorporated. Hypotheses concerning the relationship of a small number of underlying factors, information processing mechanisms, and error types types identified in the classification scheme were formulated. ASRS data were reviewed and a simulation experiment was performed to evaluate and quantify the hypotheses.

Spectral characterization of V-type asteroids - I. Space weathering effects and implications for V-type NEAs

NASA Astrophysics Data System (ADS)

Fulvio, Daniele; Perna, Davide; Ieva, Simone; Brunetto, Rosario; Kanuchova, Zuzana; Blanco, Carlo; Strazzulla, Giovanni; Dotto, Elisabetta

2016-01-01

Among main belt asteroids, V-types belonging to Vesta's dynamical family are known as `Vestoids' while those lying outside Vesta's family as `non-Vestoids'. V-types have also been found within the population of Near Earth Asteroids (NEAs). Several questions on Vesta, the V-types, and the Howardite-Eucrite-Diogenite meteorites are still unsolved, such as the genesis of each class/subclass, their evolution and mutual relationship, and the existence of other basaltic parent bodies. We present new NIR (0.8-2.4 μm) spectroscopic observations of seven non-Vestoids, carried out at the Telescopio Nazionale Galileo (TNG - INAF). We derived a number of spectral parameters (BI and BII centres, band separations, and BI slopes) and compared them with available spectra of V-types belonging to different subclasses (102 V-types in total), to highlight possible spectral differences useful to shed light on the questions mentioned above. We also considered the data from ion irradiation experiments performed on different samples of eucrites, simulating space weathering effects. Net discrepancies are seen for the BI slope distributions: NEAs show a distribution strongly different from all other V-type subclasses. Ion irradiation experiments induce strong effects on BI slope values and, as irradiation proceeds, the BI slope of eucrites quickly increases, changing the overall aspect of their VIS-NIR spectra (0.4-2.5 μm). Space weathering may explain the whole range of spectral slopes observed for all V-type subclasses. An exception is represented by NEAs, where moderate space weathering effects are evidenced. We propose that this is due to tidal perturbations exposing `fresh' unweathered surface grains during close encounters with the Earth, as previously found for Q-type NEAs.

Simulation of precipitation by weather pattern and frontal analysis

NASA Astrophysics Data System (ADS)

Wilby, Robert

1995-12-01

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

Enhanced seasonal predictability of the summer mean temperature in Central Europe favored by new dominant weather patterns

NASA Astrophysics Data System (ADS)

Hoffmann, P.

2018-04-01

In this study two complementary approaches have been combined to estimate the reliability of the data-driven seasonal predictability of the meteorological summer mean temperature (T_{JJA}) over Europe. The developed model is based on linear regressions and uses early season predictors to estimate the target value T_{JJA}. We found for the Potsdam (Germany) climate station that the monthly standard deviations (σ) from January to April and the temperature mean ( m) in April are good predictors to describe T_{JJA} after 1990. However, before 1990 the model failed. The core region where this model works is the north-eastern part of Central Europe. We also analyzed long-term trends of monthly Hess/Brezowsky weather types as possible causes of the dynamical changes. In spring, a significant increase of the occurrences for two opposite weather patterns was found: Zonal Ridge across Central Europe (BM) and Trough over Central Europe (TRM). Both currently make up about 30% of the total alternating weather systems over Europe. Other weather types are predominantly decreasing or their trends are not significant. Thus, the predictability may be attributed to these two weather types where the difference between the two Z500 composite patterns is large. This also applies to the north-eastern part of Central Europe. Finally, the detected enhanced seasonal predictability over Europe is alarming, because severe side effects may occur. One of these are more frequent climate extremes in summer half-year.

Intensifying postfire weather and biological invasion drive species loss in a Mediterranean-type biodiversity hotspot.

PubMed

Slingsby, Jasper A; Merow, Cory; Aiello-Lammens, Matthew; Allsopp, Nicky; Hall, Stuart; Kilroy Mollmann, Hayley; Turner, Ross; Wilson, Adam M; Silander, John A

2017-05-02

Prolonged periods of extreme heat or drought in the first year after fire affect the resilience and diversity of fire-dependent ecosystems by inhibiting seed germination or increasing mortality of seedlings and resprouting individuals. This interaction between weather and fire is of growing concern as climate changes, particularly in systems subject to stand-replacing crown fires, such as most Mediterranean-type ecosystems. We examined the longest running set of permanent vegetation plots in the Fynbos of South Africa (44 y), finding a significant decline in the diversity of plots driven by increasingly severe postfire summer weather events (number of consecutive days with high temperatures and no rain) and legacy effects of historical woody alien plant densities 30 y after clearing. Species that resprout after fire and/or have graminoid or herb growth forms were particularly affected by postfire weather, whereas all species were sensitive to invasive plants. Observed differences in the response of functional types to extreme postfire weather could drive major shifts in ecosystem structure and function such as altered fire behavior, hydrology, and carbon storage. An estimated 0.5 °C increase in maximum temperature tolerance of the species sets unique to each survey further suggests selection for species adapted to hotter conditions. Taken together, our results show climate change impacts on biodiversity in the hyperdiverse Cape Floristic Region and demonstrate an important interaction between extreme weather and disturbance by fire that may make flammable ecosystems particularly sensitive to climate change.

Fully Convolutional Networks for Ground Classification from LIDAR Point Clouds

NASA Astrophysics Data System (ADS)

Rizaldy, A.; Persello, C.; Gevaert, C. M.; Oude Elberink, S. J.

2018-05-01

Deep Learning has been massively used for image classification in recent years. The use of deep learning for ground classification from LIDAR point clouds has also been recently studied. However, point clouds need to be converted into an image in order to use Convolutional Neural Networks (CNNs). In state-of-the-art techniques, this conversion is slow because each point is converted into a separate image. This approach leads to highly redundant computation during conversion and classification. The goal of this study is to design a more efficient data conversion and ground classification. This goal is achieved by first converting the whole point cloud into a single image. The classification is then performed by a Fully Convolutional Network (FCN), a modified version of CNN designed for pixel-wise image classification. The proposed method is significantly faster than state-of-the-art techniques. On the ISPRS Filter Test dataset, it is 78 times faster for conversion and 16 times faster for classification. Our experimental analysis on the same dataset shows that the proposed method results in 5.22 % of total error, 4.10 % of type I error, and 15.07 % of type II error. Compared to the previous CNN-based technique and LAStools software, the proposed method reduces the total error and type I error (while type II error is slightly higher). The method was also tested on a very high point density LIDAR point clouds resulting in 4.02 % of total error, 2.15 % of type I error and 6.14 % of type II error.

Current Assessment and Classification of Suicidal Phenomena using the FDA 2012 Draft Guidance Document on Suicide Assessment: A Critical Review.

PubMed

Sheehan, David V; Giddens, Jennifer M; Sheehan, Kathy Harnett

2014-09-01

Standard international classification criteria require that classification categories be comprehensive to avoid type II error. Categories should be mutually exclusive and definitions should be clear and unambiguous (to avoid type I and type II errors). In addition, the classification system should be robust enough to last over time and provide comparability between data collections. This article was designed to evaluate the extent to which the classification system contained in the United States Food and Drug Administration 2012 Draft Guidance for the prospective assessment and classification of suicidal ideation and behavior in clinical trials meets these criteria. A critical review is used to assess the extent to which the proposed categories contained in the Food and Drug Administration 2012 Draft Guidance are comprehensive, unambiguous, and robust. Assumptions that underlie the classification system are also explored. The Food and Drug Administration classification system contained in the 2012 Draft Guidance does not capture the full range of suicidal ideation and behavior (type II error). Definitions, moreover, are frequently ambiguous (susceptible to multiple interpretations), and the potential for misclassification (type I and type II errors) is compounded by frequent mismatches in category titles and definitions. These issues have the potential to compromise data comparability within clinical trial sites, across sites, and over time. These problems need to be remedied because of the potential for flawed data output and consequent threats to public health, to research on the safety of medications, and to the search for effective medication treatments for suicidality.

Weather and emotional state

NASA Astrophysics Data System (ADS)

Spasova, Z.

2010-09-01

Introduction Given the proven effects of weather on the human organism, an attempt to examine its effects on a psychic and emotional level has been made. Emotions affect the bio-tonus, working ability and concentration, hence their significance in various domains of economic life, such as health care, education, transportation, tourism, etc. Data and methods The research has been made in Sofia City within a period of 8 months, using 5 psychological methods (Eysenck Personality Questionnaire (EPQ), State-Trait Anxiety Inventory (STAI), Test for Self-assessment of the emotional state (developed by Wessman and Ricks), Test for evaluation of moods and Test "Self-confidence - Activity - Mood" (developed by the specialists from the Military Academy in Saint Petersburg). The Fiodorov-Chubukov's complex-climatic method was used to characterize meteorological conditions because of the purpose to include in the analysis a maximal number of meteorological elements. 16 weather types are defined in dependence of the meteorological elements values according to this method. Abrupt weather changes from one day to another, defined by the same method, were considered as well. Results and discussions The results obtained by t-test show that the different categories of weather lead to changes in the emotional status, which indicates a character either positive or negative for the organism. The abrupt weather changes, according to expectations, have negative effect on human emotions but only when a transition to the cloudy weather or weather type, classified as "unfavourable" has been realized. The relationship between weather and human emotions is rather complicated since it depends on individual characteristics of people. One of these individual psychological characteristics, marked by the dimension "neuroticism", has a strong effect on emotional reactions in different weather conditions. Emotionally stable individuals are more "protected" to the weather influence on their emotions, while those who are emotionally unstable have a stronger dependence to the impacts of the weather.

Weather impacts on leisure activities in Halifax, Nova Scotia

NASA Astrophysics Data System (ADS)

Spinney, Jamie E. L.; Millward, Hugh

2011-03-01

The aim of this study was to investigate the impact of daily atmospheric weather conditions on daily leisure activity engagement, with a focus on physically active leisure. The methods capitalize on time diary data that were collected in Halifax, Nova Scotia to calculate objective measures of leisure activity engagement. Daily meteorological data from Environment Canada and daily sunrise and sunset times from the National Research Council of Canada are used to develop objective measures of the natural atmospheric environment. The time diary data were merged with the meteorological data in order to quantify the statistical association between daily weather conditions and the type, participation rate, frequency, and duration of leisure activity engagement. The results indicate that inclement and uncomfortable weather conditions, especially relating to thermal comfort and mechanical comfort, pose barriers to physically active leisure engagement, while promoting sedentary and home-based leisure activities. Overall, daily weather conditions exhibit modest, but significant, effects on leisure activity engagement; the strongest associations being for outdoor active sports and outdoor active leisure time budgets. In conclusion, weather conditions influence the type, participation rate, frequency, and duration of leisure activity engagement, which is an important consideration for health-promotion programming.

A comparative agreement evaluation of two subaxial cervical spine injury classification systems: the AOSpine and the Allen and Ferguson schemes.

PubMed

Urrutia, Julio; Zamora, Tomas; Campos, Mauricio; Yurac, Ratko; Palma, Joaquin; Mobarec, Sebastian; Prada, Carlos

2016-07-01

We performed an agreement study using two subaxial cervical spine classification systems: the AOSpine and the Allen and Ferguson (A&F) classifications. We sought to determine which scheme allows better agreement by different evaluators and by the same evaluator on different occasions. Complete imaging studies of 65 patients with subaxial cervical spine injuries were classified by six evaluators (three spine sub-specialists and three senior orthopaedic surgery residents) using the AOSpine subaxial cervical spine classification system and the A&F scheme. The cases were displayed in a random sequence after a 6-week interval for repeat evaluation. The Kappa coefficient (κ) was used to determine inter- and intra-observer agreement. Inter-observer: considering the main AO injury types, the agreement was substantial for the AOSpine classification [κ = 0.61 (0.57-0.64)]; using AO sub-types, the agreement was moderate [κ = 0.57 (0.54-0.60)]. For the A&F classification, the agreement [κ = 0.46 (0.42-0.49)] was significantly lower than using the AOSpine scheme. Intra-observer: the agreement was substantial considering injury types [κ = 0.68 (0.62-0.74)] and considering sub-types [κ = 0.62 (0.57-0.66)]. Using the A&F classification, the agreement was also substantial [κ = 0.66 (0.61-0.71)]. No significant differences were observed between spine surgeons and orthopaedic residents in the overall inter- and intra-observer agreement, or in the inter- and intra-observer agreement of specific type of injuries. The AOSpine classification (using the four main injury types or at the sub-types level) allows a significantly better agreement than the A&F classification. The A&F scheme does not allow reliable communication between medical professionals.

Classification and description of world formation types

Treesearch

D. Faber-Langendoen; T. Keeler-Wolf; D. Meidinger; C. Josse; A. Weakley; D. Tart; G. Navarro; B. Hoagland; S. Ponomarenko; G. Fults; Eileen Helmer

2016-01-01

An ecological vegetation classification approach has been developed in which a combination of vegetation attributes (physiognomy, structure, and floristics) and their response to ecological and biogeographic factors are used as the basis for classifying vegetation types. This approach can help support international, national, and subnational classification efforts. The...

AWE: Aviation Weather Data Visualization Environment

NASA Technical Reports Server (NTRS)

Spirkovska, Lilly; Lodha, Suresh K.

2000-01-01

The two official sources for aviation weather reports both provide weather information to a pilot in a textual format. A number of systems have recently become available to help pilots with the visualization task by providing much of the data graphically. However, two types of aviation weather data are still not being presented graphically. These are airport-specific current weather reports (known as meteorological observations, or METARs) and forecast weather reports (known as terminal area forecasts, or TAFs). Our system, Aviation Weather Environment (AWE), presents intuitive graphical displays for both METARs and TAFs, as well as winds aloft forecasts. We start with a computer-generated textual aviation weather briefing. We map this briefing onto a cartographic grid specific to the pilot's area of interest. The pilot is able to obtain aviation-specific weather for the entire area or for his specific route. The route, altitude, true airspeed, and proposed departure time can each be modified in AWE. Integral visual display of these three elements of weather reports makes AWE a useful planning tool, as well as a weather briefing tool.

Weather Regulates Location, Timing, and Intensity of Dengue Virus Transmission between Humans and Mosquitoes

PubMed Central

Campbell, Karen M.; Haldeman, Kristin; Lehnig, Chris; Munayco, Cesar V.; Halsey, Eric S.; Laguna-Torres, V. Alberto; Yagui, Martín; Morrison, Amy C.; Lin, Chii-Dean; Scott, Thomas W.

2015-01-01

Background Dengue is one of the most aggressively expanding mosquito-transmitted viruses. The human burden approaches 400 million infections annually. Complex transmission dynamics pose challenges for predicting location, timing, and magnitude of risk; thus, models are needed to guide prevention strategies and policy development locally and globally. Weather regulates transmission-potential via its effects on vector dynamics. An important gap in understanding risk and roadblock in model development is an empirical perspective clarifying how weather impacts transmission in diverse ecological settings. We sought to determine if location, timing, and potential-intensity of transmission are systematically defined by weather. Methodology/Principal Findings We developed a high-resolution empirical profile of the local weather-disease connection across Peru, a country with considerable ecological diversity. Applying 2-dimensional weather-space that pairs temperature versus humidity, we mapped local transmission-potential in weather-space by week during 1994-2012. A binary classification-tree was developed to test whether weather data could classify 1828 Peruvian districts as positive/negative for transmission and into ranks of transmission-potential with respect to observed disease. We show that transmission-potential is regulated by temperature-humidity coupling, enabling epidemics in a limited area of weather-space. Duration within a specific temperature range defines transmission-potential that is amplified exponentially in higher humidity. Dengue-positive districts were identified by mean temperature >22°C for 7+ weeks and minimum temperature >14°C for 33+ weeks annually with 95% sensitivity and specificity. In elevated-risk locations, seasonal peak-incidence occurred when mean temperature was 26-29°C, coincident with humidity at its local maximum; highest incidence when humidity >80%. We profile transmission-potential in weather-space for temperature-humidity ranging 0-38°C and 5-100% at 1°C x 2% resolution. Conclusions/Significance Local duration in limited areas of temperature-humidity weather-space identifies potential locations, timing, and magnitude of transmission. The weather-space profile of transmission-potential provides needed data that define a systematic and highly-sensitive weather-disease connection, demonstrating separate but coupled roles of temperature and humidity. New insights regarding natural regulation of human-mosquito transmission across diverse ecological settings advance our understanding of risk locally and globally for dengue and other mosquito-borne diseases and support advances in public health policy/operations, providing an evidence-base for modeling, predicting risk, and surveillance-prevention planning. PMID:26222979

Taxonomy of asteroids. [according to polarimetric, spectrophotometric, radiometric, and UBV photometric data

NASA Technical Reports Server (NTRS)

Bowell, E.; Chapman, C. R.; Gradie, J. C.; Zellner, B.; Morrison, D.

1978-01-01

A taxonomic system for asteroids is discussed which is based on seven directly observable parameters from polarimetry, spectrophotometry, radiometry, and UBV photometry. The classification scheme is entirely empirical and independent of specific mineralogical interpretations. Five broad classes (designated C, S, M, E, and R), as well as an 'unclassifiable' designation, are defined on the basis of observational data for 523 asteroids. Computer-generated type classifications and derived diameters are given for the 523 asteroids, and the application of the classification procedure is illustrated. Of the 523 asteroids classified, 190 are identified as C objects, 141 as S type, 13 as type M, three as type E, three as type R, 55 as unclassifiable, and 118 as ambiguous. The present taxonomic system is compared with several other asteroid classification systems.

[An object-based information extraction technology for dominant tree species group types].

PubMed

Tian, Tian; Fan, Wen-yi; Lu, Wei; Xiao, Xiang

2015-06-01

Information extraction for dominant tree group types is difficult in remote sensing image classification, howevers, the object-oriented classification method using high spatial resolution remote sensing data is a new method to realize the accurate type information extraction. In this paper, taking the Jiangle Forest Farm in Fujian Province as the research area, based on the Quickbird image data in 2013, the object-oriented method was adopted to identify the farmland, shrub-herbaceous plant, young afforested land, Pinus massoniana, Cunninghamia lanceolata and broad-leave tree types. Three types of classification factors including spectral, texture, and different vegetation indices were used to establish a class hierarchy. According to the different levels, membership functions and the decision tree classification rules were adopted. The results showed that the method based on the object-oriented method by using texture, spectrum and the vegetation indices achieved the classification accuracy of 91.3%, which was increased by 5.7% compared with that by only using the texture and spectrum.

Convolutional neural network with transfer learning for rice type classification

NASA Astrophysics Data System (ADS)

Patel, Vaibhav Amit; Joshi, Manjunath V.

2018-04-01

Presently, rice type is identified manually by humans, which is time consuming and error prone. Therefore, there is a need to do this by machine which makes it faster with greater accuracy. This paper proposes a deep learning based method for classification of rice types. We propose two methods to classify the rice types. In the first method, we train a deep convolutional neural network (CNN) using the given segmented rice images. In the second method, we train a combination of a pretrained VGG16 network and the proposed method, while using transfer learning in which the weights of a pretrained network are used to achieve better accuracy. Our approach can also be used for classification of rice grain as broken or fine. We train a 5-class model for classifying rice types using 4000 training images and another 2- class model for the classification of broken and normal rice using 1600 training images. We observe that despite having distinct rice images, our architecture, pretrained on ImageNet data boosts classification accuracy significantly.

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.

Winter weather demand considerations.

DOT National Transportation Integrated Search

2015-04-01

Winter weather has varied effects on travel behavior. Using 418 survey responses from the Northern Virginia : commuting area of Washington, D.C. and binary logit models, this study examines travel related changes under : different types of winter wea...

Habitat typing versus advanced vegetation classification in western forests

Treesearch

Tony Kusbach; John Shaw; James Long; Helga Van Miegroet

2012-01-01

Major habitat and community types in northern Utah were compared with plant alliances and associations that were derived from fidelity- and diagnostic-species classification concepts. Each of these classification approaches was associated with important environmental factors. Within a 20,000-ha watershed, 103 forest ecosystems were described by physiographic features,...

Classifying Adverse Events in the Dental Office.

PubMed

Kalenderian, Elsbeth; Obadan-Udoh, Enihomo; Maramaldi, Peter; Etolue, Jini; Yansane, Alfa; Stewart, Denice; White, Joel; Vaderhobli, Ram; Kent, Karla; Hebballi, Nutan B; Delattre, Veronique; Kahn, Maria; Tokede, Oluwabunmi; Ramoni, Rachel B; Walji, Muhammad F

2017-06-30

Dentists strive to provide safe and effective oral healthcare. However, some patients may encounter an adverse event (AE) defined as "unnecessary harm due to dental treatment." In this research, we propose and evaluate two systems for categorizing the type and severity of AEs encountered at the dental office. Several existing medical AE type and severity classification systems were reviewed and adapted for dentistry. Using data collected in previous work, two initial dental AE type and severity classification systems were developed. Eight independent reviewers performed focused chart reviews, and AEs identified were used to evaluate and modify these newly developed classifications. A total of 958 charts were independently reviewed. Among the reviewed charts, 118 prospective AEs were found and 101 (85.6%) were verified as AEs through a consensus process. At the end of the study, a final AE type classification comprising 12 categories, and an AE severity classification comprising 7 categories emerged. Pain and infection were the most common AE types representing 73% of the cases reviewed (56% and 17%, respectively) and 88% were found to cause temporary, moderate to severe harm to the patient. Adverse events found during the chart review process were successfully classified using the novel dental AE type and severity classifications. Understanding the type of AEs and their severity are important steps if we are to learn from and prevent patient harm in the dental office.

A statistical approach to root system classification.

PubMed

Bodner, Gernot; Leitner, Daniel; Nakhforoosh, Alireza; Sobotik, Monika; Moder, Karl; Kaul, Hans-Peter

2013-01-01

Plant root systems have a key role in ecology and agronomy. In spite of fast increase in root studies, still there is no classification that allows distinguishing among distinctive characteristics within the diversity of rooting strategies. Our hypothesis is that a multivariate approach for "plant functional type" identification in ecology can be applied to the classification of root systems. The classification method presented is based on a data-defined statistical procedure without a priori decision on the classifiers. The study demonstrates that principal component based rooting types provide efficient and meaningful multi-trait classifiers. The classification method is exemplified with simulated root architectures and morphological field data. Simulated root architectures showed that morphological attributes with spatial distribution parameters capture most distinctive features within root system diversity. While developmental type (tap vs. shoot-borne systems) is a strong, but coarse classifier, topological traits provide the most detailed differentiation among distinctive groups. Adequacy of commonly available morphologic traits for classification is supported by field data. Rooting types emerging from measured data, mainly distinguished by diameter/weight and density dominated types. Similarity of root systems within distinctive groups was the joint result of phylogenetic relation and environmental as well as human selection pressure. We concluded that the data-define classification is appropriate for integration of knowledge obtained with different root measurement methods and at various scales. Currently root morphology is the most promising basis for classification due to widely used common measurement protocols. To capture details of root diversity efforts in architectural measurement techniques are essential.

Comparative Studies of Prediction Strategies for Solar X-ray Time Series

NASA Astrophysics Data System (ADS)

Muranushi, T.; Hattori, T.; Jin, Q.; Hishinuma, T.; Tominaga, M.; Nakagawa, K.; Fujiwara, Y.; Nakamura, T.; Sakaue, T.; Takahashi, T.; Seki, D.; Namekata, K.; Tei, A.; Ban, M.; Kawamura, A. D.; Hada-Muranushi, Y.; Asai, A.; Nemoto, S.; Shibata, K.

2016-12-01

Crucial virtues for operational space weather forecast are real-timeforecast ability, forecast precision and customizability to userneeds. The recent development of deep-learning makes it veryattractive to space weather, because (1) it learns gradually incomingdata, (2) it exhibits superior accuracy over conventional algorithmsin many fields, and (3) it makes the customization of the forecasteasier because it accepts raw images.However, the best deep-learning applications are only attainable bycareful human designers that understands both the mechanism of deeplearning and the application field. Therefore, we need to foster youngresearchers to enter the field of machine-learning aided forecast. So,we have held a seminar every Monday with undergraduate and graduatestudents from May to August 2016.We will review the current status of space weather science and theautomated real-time space weather forecast engine UFCORIN. Then, weintroduce the deep-learning space weather forecast environments wehave set up using Python and Chainer on students' laptop computers.We have started from simple image classification neural network, thenimplemented space-weather neural network that predicts future X-rayflux of the Sun based on the past X-ray lightcurve and magnetic fieldline-of-sight images.In order to perform each forecast faster, we have focused on simplelightcurve-to-lightcurve forecast, and performed comparative surveysby changing following parameters: The size and topology of the neural network Batchsize Neural network hyperparameters such as learning rates to optimize the preduction accuracy, and time for prediction.We have found how to design compact, fast but accurate neural networkto perform forecast. Our forecasters can perform predictionexperiment for four-year timespan in a few minutes, and achieveslog-scale errors of the order of 1. Our studies is ongoing, and inour talk we will review our progress till December.

Future Changes in Autumn Flood Type and Frequency in Pacific Northwest North America

NASA Astrophysics Data System (ADS)

Menounos, B.; Cannon, A. J.; Radic, V.; Moore, R. D.; Dery, S. J.; Jackson, P. L.; Anslow, F. S.

2013-12-01

During the 20th and early 21st century, autumn storms in the Pacific Northwest of North America - PNWNA (coastal British Columbia and Washington) caused widespread flooding and landslides. Understanding how these intense storms are likely to change in the future is important given their potential to harm people and cause widespread damage, but assessing these changes using climate models is difficult. Parameterization of precipitation in general circulation and regional climate models (GCM, RCM) is prone to error, especially in the mountainous terrain of the PNWNA. High computational demands of RCMs also limits their use in assessing changes in flood type and frequency for a suite of GCM and emission scenarios. We instead focus our efforts on understanding atmospheric circulation patterns responsible for historical autumn flooding (15 August - 31 December) and examine how these synoptic conditions are likely to change under future emission scenarios. Our analysis includes identification of extreme events (runoff and precipitation) in streamflow and precipitation records from coastal Washington and British Columbia for the period 1948-2010. Our methods to link the instrumental record of extreme autumn events to atmospheric conditions (500 and 850 hPa geopotential height and integrated vapor transport obtained from NCEP and CFSR reanalysis) include: (1) compositing of streamflow and precipitation events (environment-to-circulation); (2) self organizing map synoptic classification (circulation-to-environment); and (3) regression tree synoptic classification (hybrid of environment-to-circulation and circulation-to-environment). We then evaluate changes in flood-generating synoptic types in the CMIP5 ensemble over the period 2010-2100. Our analysis indicates that, as expected, most floods are associated with atmospheric river events that are commonly associated with upper level, quasi stationary low- and high-pressure systems respectively located in the Gulf of Alaska and east of the PNWNA. Based on our initial analysis of the CMIP5 data, we note an increase in autumn flood-producing synoptic weather types for the PNWNA. We discuss the implications of increased autumn flooding to communities and infrastructure.

A climatology of polar stratospheric cloud composition between 2002 and 2012 based on MIPAS/Envisat observations

NASA Astrophysics Data System (ADS)

Spang, Reinhold; Hoffmann, Lars; Müller, Rolf; Grooß, Jens-Uwe; Tritscher, Ines; Höpfner, Michael; Pitts, Michael; Orr, Andrew; Riese, Martin

2018-04-01

The Michelson Interferometer for Passive Atmospheric Sounding (MIPAS) instrument aboard the European Space Agency (ESA) Envisat satellite operated from July 2002 to April 2012. The infrared limb emission measurements provide a unique dataset of day and night observations of polar stratospheric clouds (PSCs) up to both poles. A recent classification method for PSC types in infrared (IR) limb spectra using spectral measurements in different atmospheric window regions has been applied to the complete mission period of MIPAS. The method uses a simple probabilistic classifier based on Bayes' theorem with a strong independence assumption on a combination of a well-established two-colour ratio method and multiple 2-D probability density functions of brightness temperature differences. The Bayesian classifier distinguishes between solid particles of ice, nitric acid trihydrate (NAT), and liquid droplets of supercooled ternary solution (STS), as well as mixed types. A climatology of MIPAS PSC occurrence and specific PSC classes has been compiled. Comparisons with results from the classification scheme of the spaceborne lidar Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) on the Cloud-Aerosol-Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) satellite show excellent correspondence in the spatial and temporal evolution for the area of PSC coverage (APSC) even for each PSC class. Probability density functions of the PSC temperature, retrieved for each class with respect to equilibrium temperature of ice and based on coincident temperatures from meteorological reanalyses, are in accordance with the microphysical knowledge of the formation processes with respect to temperature for all three PSC types.This paper represents unprecedented pole-covering day- and nighttime climatology of the PSC distributions and their composition of different particle types. The dataset allows analyses on the temporal and spatial development of the PSC formation process over multiple winters. At first view, a more general comparison of APSC and AICE retrieved from the observations and from the existence temperature for NAT and ice particles based on the European Centre for Medium-Range Weather Forecasts (ECMWF) reanalysis temperature data shows the high potential of the climatology for the validation and improvement of PSC schemes in chemical transport and chemistry-climate models.

Classification of change detection and change blindness from near-infrared spectroscopy signals

NASA Astrophysics Data System (ADS)

Tanaka, Hirokazu; Katura, Takusige

2011-08-01

Using a machine-learning classification algorithm applied to near-infrared spectroscopy (NIRS) signals, we classify a success (change detection) or a failure (change blindness) in detecting visual changes for a change-detection task. Five subjects perform a change-detection task, and their brain activities are continuously monitored. A support-vector-machine algorithm is applied to classify the change-detection and change-blindness trials, and correct classification probability of 70-90% is obtained for four subjects. Two types of temporal shapes in classification probabilities are found: one exhibiting a maximum value after the task is completed (postdictive type), and another exhibiting a maximum value during the task (predictive type). As for the postdictive type, the classification probability begins to increase immediately after the task completion and reaches its maximum in about the time scale of neuronal hemodynamic response, reflecting a subjective report of change detection. As for the predictive type, the classification probability shows an increase at the task initiation and is maximal while subjects are performing the task, predicting the task performance in detecting a change. We conclude that decoding change detection and change blindness from NIRS signal is possible and argue some future applications toward brain-machine interfaces.

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

PubMed Central

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

2013-01-01

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

Ramstein AB (Germany, F.R.) Revised Uniform Summary of Surface Weather Observations (RUSSWO). Parts A-F

DTIC Science & Technology

1985-05-01

All other editions ere obsolete. 22b TELEPHONE 0nc/ude Are« Code ) (610) 256-2625 22( OFFICE SYMBOL USAFETAC/LDD SECURITY CLASSIFICATION OF ’HIS...lii isaia bt&l TOTAL NUMIE« 3F 0«S»VATIONS 913_ ■V <?’’■... J f. H r : T » : PERCENTAGf fR.QUENCY OF WIND 0’R!:CV(ON! AND SPEED (FROM HOURLY

Tests of Spectral Cloud Classification Using DMSP Fine Mode Satellite Data.

DTIC Science & Technology

1980-06-02

processing techniques of potential value. Fourier spectral analysis was identified as the most promising technique to upgrade automated processing of...these measurements on the Earth’s surface is 0. 3 n mi. 3. Pickett, R.M., and Blackman, E.S. (1976) Automated Processing of Satellite Imagery Data at Air...and Pickett. R. Al. (1977) Automated Processing of Satellite Imagery Data at the Air Force Global Weather Central: Demonstrations of Spectral Analysis

Evaluation of a stream channel-type system for southeast Alaska.

Treesearch

M.D. Bryant; P.E. Porter; S.J. Paustian

1991-01-01

Nine channel types within a hierarchical channel-type classification system (CTCS) were surveyed to determine relations between salmonid densities and species distribution, and channel type. Two other habitat classification systems and the amount of large woody debris also were compared to species distribution and salmonid densities, and to stream channel types....

Moisture source classification of heavy precipitation events in Switzerland in the last 130 years (1871-2011)

NASA Astrophysics Data System (ADS)

Aemisegger, Franziska; Piaget, Nicolas

2017-04-01

A new weather-system oriented classification framework of extreme precipitation events leading to large-scale floods in Switzerland is presented on this poster. Thirty-six high impact floods in the last 130 years are assigned to three representative categories of atmospheric moisture origin and transport patterns. The methodology underlying this moisture source classification combines information of the airmass history in the twenty days preceding the precipitation event with humidity variations along the large-scale atmospheric transport systems in a Lagrangian approach. The classification scheme is defined using the 33-year ERA-Interim reanalysis dataset (1979-2011) and is then applied to the Twentieth Century Reanalysis (1871-2011) extreme precipitation events as well as the 36 selected floods. The three defined categories are characterised by different dominant moisture uptake regions including the North Atlantic, the Mediterranean and continental Europe. Furthermore, distinct anomalies in the large-scale atmospheric flow are associated with the different categories. The temporal variations in the relative importance of the three categories over the last 130 years provides new insights into the impact of changing climate conditions on the dynamical mechanisms leading to heavy precipitation in Switzerland.

Flight Deck Weather Avoidance Decision Support: Implementation and Evaluation

NASA Technical Reports Server (NTRS)

Wu, Shu-Chieh; Luna, Rocio; Johnson, Walter W.

2013-01-01

Weather related disruptions account for seventy percent of the delays in the National Airspace System (NAS). A key component in the weather plan of the Next Generation of Air Transportation System (NextGen) is to assimilate observed weather information and probabilistic forecasts into the decision process of flight crews and air traffic controllers. In this research we explore supporting flight crew weather decision making through the development of a flight deck predicted weather display system that utilizes weather predictions generated by ground-based radar. This system integrates and presents this weather information, together with in-flight trajectory modification tools, within a cockpit display of traffic information (CDTI) prototype. that the CDTI features 2D and perspective 3D visualization models of weather. The weather forecast products that we implemented were the Corridor Integrated Weather System (CIWS) and the Convective Weather Avoidance Model (CWAM), both developed by MIT Lincoln Lab. We evaluated the use of CIWS and CWAM for flight deck weather avoidance in two part-task experiments. Experiment 1 compared pilots' en route weather avoidance performance in four weather information conditions that differed in the type and amount of predicted forecast (CIWS current weather only, CIWS current and historical weather, CIWS current and forecast weather, CIWS current and forecast weather and CWAM predictions). Experiment 2 compared the use of perspective 3D and 21/2D presentations of weather for flight deck weather avoidance. Results showed that pilots could take advantage of longer range predicted weather forecasts in performing en route weather avoidance but more research will be needed to determine what combinations of information are optimal and how best to present them.

The distance function effect on k-nearest neighbor classification for medical datasets.

PubMed

Hu, Li-Yu; Huang, Min-Wei; Ke, Shih-Wen; Tsai, Chih-Fong

2016-01-01

K-nearest neighbor (k-NN) classification is conventional non-parametric classifier, which has been used as the baseline classifier in many pattern classification problems. It is based on measuring the distances between the test data and each of the training data to decide the final classification output. Since the Euclidean distance function is the most widely used distance metric in k-NN, no study examines the classification performance of k-NN by different distance functions, especially for various medical domain problems. Therefore, the aim of this paper is to investigate whether the distance function can affect the k-NN performance over different medical datasets. Our experiments are based on three different types of medical datasets containing categorical, numerical, and mixed types of data and four different distance functions including Euclidean, cosine, Chi square, and Minkowsky are used during k-NN classification individually. The experimental results show that using the Chi square distance function is the best choice for the three different types of datasets. However, using the cosine and Euclidean (and Minkowsky) distance function perform the worst over the mixed type of datasets. In this paper, we demonstrate that the chosen distance function can affect the classification accuracy of the k-NN classifier. For the medical domain datasets including the categorical, numerical, and mixed types of data, K-NN based on the Chi square distance function performs the best.

Iron-sulfur mineralogy of Mars - Magmatic evolution and chemical weathering products

NASA Technical Reports Server (NTRS)

Burns, Roger G.; Fisher, Duncan S.

1990-01-01

Models are developed for the magmatic evolution and the oxidative weathering of sulfide minerals on Mars, based on petrogenetic associations among komatiitic rock types, Viking geochemical data, SNC meteorites, and terrestrial Fi-Ni deposits. The weathering model was tested by exposing komatiitic pyrrhotites and olivines to sulfuric acid solutions, with or without dissolved ferric iron, and identifying the reaction products by Moessbauer spectroscopy. The results suggest that, on Mars, acidic groundwater has induced oxidative weathering of pyrrhotite, yielding FeS2 and then FeOOH.

Errata, nursing homes. Budget percentiles for baseline and redesigned commercial type buildings: cities with try weather tapes; based on resource utilization factors (RUF); based on price weighting factors (PWF)

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

Not Available

Corrected data are presented for the P50 Redesign figure for nursing homes in the following documents in the series entitled Budget Percentiles for Baseline and Redesigned Commercial Type Buildings: For Cities with TRY Weather Tapes, Based on Price Weighing Factors (PWF), and Based on Resource Utilization Factors (RUF). (MCW)

A Synoptic Weather Typing Approach to Assess Climate Change Impacts on Meteorological and Hydrological Risks at Local Scale in South-Central Canada

NASA Astrophysics Data System (ADS)

Cheng, Chad Shouquan; Li, Qian; Li, Guilong

2010-05-01

The synoptic weather typing approach has become popular in evaluating the impacts of climate change on a variety of environmental problems. One of the reasons is its ability to categorize a complex set of meteorological variables as a coherent index, which can facilitate analyses of local climate change impacts. The weather typing method has been applied in Environment Canada to analyze climatic change impacts on various meteorological/hydrological risks, such as freezing rain, heavy rainfall, high-/low-flow events, air pollution, and human health. These studies comprise of three major parts: (1) historical simulation modeling to verify the hazardous events, (2) statistical downscaling to provide station-scale future climate information, and (3) estimates of changes in frequency and magnitude of future hazardous meteorological/hydrological events in this century. To achieve these goals, in addition to synoptic weather typing, the modeling conceptualizations in meteorology and hydrology and various linear/nonlinear regression techniques were applied. Furthermore, a formal model result verification process has been built into the entire modeling exercise. The results of the verification, based on historical observations of the outcome variables predicted by the models, showed very good agreement. This paper will briefly summarize these research projects, focusing on the modeling exercise and results.

A discrimlnant function approach to ecological site classification in northern New England

Treesearch

James M. Fincher; Marie-Louise Smith

1994-01-01

Describes one approach to ecologically based classification of upland forest community types of the White and Green Mountain physiographic regions. The classification approach is based on an intensive statistical analysis of the relationship between the communities and soil-site factors. Discriminant functions useful in distinguishing between types based on soil-site...

Creating a classification of image types in the medical literature for visual categorization

NASA Astrophysics Data System (ADS)

Müller, Henning; Kalpathy-Cramer, Jayashree; Demner-Fushman, Dina; Antani, Sameer

2012-02-01

Content-based image retrieval (CBIR) from specialized collections has often been proposed for use in such areas as diagnostic aid, clinical decision support, and teaching. The visual retrieval from broad image collections such as teaching files, the medical literature or web images, by contrast, has not yet reached a high maturity level compared to textual information retrieval. Visual image classification into a relatively small number of classes (20-100) on the other hand, has shown to deliver good results in several benchmarks. It is, however, currently underused as a basic technology for retrieval tasks, for example, to limit the search space. Most classification schemes for medical images are focused on specific areas and consider mainly the medical image types (modalities), imaged anatomy, and view, and merge them into a single descriptor or classification hierarchy. Furthermore, they often ignore other important image types such as biological images, statistical figures, flowcharts, and diagrams that frequently occur in the biomedical literature. Most of the current classifications have also been created for radiology images, which are not the only types to be taken into account. With Open Access becoming increasingly widespread particularly in medicine, images from the biomedical literature are more easily available for use. Visual information from these images and knowledge that an image is of a specific type or medical modality could enrich retrieval. This enrichment is hampered by the lack of a commonly agreed image classification scheme. This paper presents a hierarchy for classification of biomedical illustrations with the goal of using it for visual classification and thus as a basis for retrieval. The proposed hierarchy is based on relevant parts of existing terminologies, such as the IRMA-code (Image Retrieval in Medical Applications), ad hoc classifications and hierarchies used in imageCLEF (Image retrieval task at the Cross-Language Evaluation Forum) and NLM's (National Library of Medicine) OpenI. Furtheron, mappings to NLM's MeSH (Medical Subject Headings), RSNA's RadLex (Radiological Society of North America, Radiology Lexicon), and the IRMA code are also attempted for relevant image types. Advantages derived from such hierarchical classification for medical image retrieval are being evaluated through benchmarks such as imageCLEF, and R&D systems such as NLM's OpenI. The goal is to extend this hierarchy progressively and (through adding image types occurring in the biomedical literature) to have a terminology for visual image classification based on image types distinguishable by visual means and occurring in the medical open access literature.

Forest succession on four habitat types in western Montana

Treesearch

Stephen F. Arno; Dennis G. Simmerman; Robert E. Keane

1985-01-01

Presents classifications of successional community types on four major forest habitat types in western Montana. Classifications show the sequences of seral community types developing after stand-replacing wildfire and clearcutting with broadcast burning, mechanical scarification, or no followup treatment. Information is provided for associating vegetational response to...

Geomorphic knobs of Candor Chasma, Mars: New Mars Reconnaissance Orbiter data and comparisons to terrestrial analogs

USGS Publications Warehouse

Chan, M.A.; Ormo, J.; Murchie, S.; Okubo, C.H.; Komatsu, G.; Wray, J.J.; McGuire, P.; McGovern, J.A.

2010-01-01

High Resolution Imaging Science Experiment (HiRISE) imagery and digital elevation models of the Candor Chasma region of Valles Marineris, Mars, reveal prominent and distinctive positive-relief knobs amidst light-toned layers. Three classifications of knobs, Types 1, 2, and 3, are distinguished from a combination of HiRISE and Thermal Emission Imaging System (THEMIS) images based on physical expressions (geometries, spatial relationships), and spectral data from Compact Reconnaissance Imaging Spectrometer for Mars (CRISM). Type 1 knobs are abundant, concentrated, topographically resistant features with their highest frequency in West Candor, which have consistent stratigraphic correlations of the peak altitude (height). These Type 1 knobs could be erosional remnants of a simple dissected terrain, possibly derived from a more continuous, resistant, capping layer of pre-existing material diagenetically altered through recrystallization or cementation. Types 2 and 3 knobs are not linked to a single stratigraphic layer and are generally solitary to isolated, with variable heights. Type 3 are the largest knobs at nearly an order of magnitude larger than Type 1 knobs. The variable sizes and occasional pits on the tops of Type 2 and 3 knobs suggest a different origin, possibly related to more developed erosion, preferential cementation, or textural differences from sediment/water injection or intrusion, or from a buried impact crater. Enhanced color HiRISE images show a brown coloration of the knob peak crests that is attributable to processing and photometric effects; CRISM data do not show any detectable spectral differences between the knobs and the host rock layers, other than albedo. These intriguing knobs hold important clues to deducing relative rock properties, timing of events, and weathering conditions of Mars history. ?? 2009 Elsevier Inc. All rights reserved.

Cluster Method Analysis of K. S. C. Image

NASA Technical Reports Server (NTRS)

Rodriguez, Joe, Jr.; Desai, M.

1997-01-01

Information obtained from satellite-based systems has moved to the forefront as a method in the identification of many land cover types. Identification of different land features through remote sensing is an effective tool for regional and global assessment of geometric characteristics. Classification data acquired from remote sensing images have a wide variety of applications. In particular, analysis of remote sensing images have special applications in the classification of various types of vegetation. Results obtained from classification studies of a particular area or region serve towards a greater understanding of what parameters (ecological, temporal, etc.) affect the region being analyzed. In this paper, we make a distinction between both types of classification approaches although, focus is given to the unsupervised classification method using 1987 Thematic Mapped (TM) images of Kennedy Space Center.

Conceptual Models of Frontal Cyclones.

ERIC Educational Resources Information Center

Eagleman, Joe R.

1981-01-01

This discussion of weather models uses maps to illustrate the differences among three types of frontal cyclones (long wave, short wave, and troughs). Awareness of these cyclones can provide clues to atmospheric conditions which can lead toward accurate weather forecasting. (AM)

Mapping forest types in Worcester County, Maryland, using LANDSAT data

NASA Technical Reports Server (NTRS)

Burtis, J., Jr.; Witt, R. G.

1981-01-01

The feasibility of mapping Level 2 forest cover types for a county-sized area on Maryland's Eastern Shore was demonstrated. A Level 1 land use/land cover classification was carried out for all of Worcester County as well. A June 1978 LANDSAT scene was utilized in a classification which employed two software packages on different computers (IDIMS on an HP 3000 and ASTEP-II on a Univac 1108). A twelve category classification scheme was devised for the study area. Resulting products include black and white line printer maps, final color coded classification maps, digitally enhanced color imagery and tabulated acreage statistics for all land use and land cover types.

The Influence of Tactile Perception on Classification of Bone Tissue at Dental Implant Insertion.

PubMed

Linck, Gláucia Kelly Silva Barbosa; Ferreira, Geovane Miranda; De Oliveira, Rubelisa Cândido Gomes; Lindh, Christina; Leles, Cláudio Rodrigues; Ribeiro-Rotta, Rejane Faria

2016-06-01

Various ways of using the Lekholm and Zarb (L&Z) classification have added to the lack of scientific evidence of the effectiveness of this clinical method in the evaluation of implant treatment. The study aims to assess subjective jawbone classifications in patients referred for implant treatment, using L&Z classification with and without surgeon's hand perception at implant insertion. The association between bone type classifications and quantitative parameters of primary implant stability was also assessed. One hundred thirty-five implants were inserted using conventional loading protocol. Three surgeons classified bone quality at implant sites using two methods: one based on periapical and panoramic images (modified L&Z) and one based on the same images associated with the surgeon's tactile perception during drilling (original L&Z). Peak insertion torque and implant stability quotient (ISQ) were recorded. The modified and original L&Z were strongly correlated (rho = 0.79; p < .001); Wilcoxon signed-rank test showed no significant difference in the distribution of bone type classification between pairs using the two methods (p = .538). Spearman correlation tested the association between primary stability parameters and bone type classifications (-0.34 to -0.57 [p < .001]). Tactile surgical perception has a minor influence on rating of subjective bone type for dental implant treatment using the L&Z classification. © 2015 Wiley Periodicals, Inc.

SEM and TEM Observation of the Surfaces of the Fine-Grained Particles Retrieved from the Muses-C Regio on the Asteroid 25413 Itokawa

NASA Technical Reports Server (NTRS)

Noguchi, T.; Nakamura, T.; Zolensky, Michael E.; Tanaka, M.; Hashimoto, T.; Konno, M.; Nakato, A.; Ogami, T.; Fujimura, A.; Abe, M.;

Towards the challenging REE exploration in Indonesia

NASA Astrophysics Data System (ADS)

Setiawan, Iwan

2018-02-01

Rare earth elements (REE) are the seventeen elements, including fifteen from 57La to 71Lu, in addition to 21Sc and 39Y. In rock-forming minerals, rare earth elements typically occur in compounds as trivalent cations in carbonates, oxides, phosphates, and silicates. The REE occur in a wide range of rock types: igneous, sedimentary and metamorphic rocks. REE are one of the critical metals in the world. Their occurrences are important to supply the world needs on high technology materials. Indonesia has a lot of potential sources of REE that are mainly from residual tin mining processes in Bangka islands, which are associated with radioactive minerals e.g. monazite and xenotime. However, the REE from monazite and xenotime are difficult to extract and contain high radioactivity. Granitoids are widely distributed in Sumatra, Sulawesi, Kalimantan and Papua. They also have a very thick weathering crusts. Important REE-bearing minerals are allanite and titanite. Their low susceptibilities during weathering result an economically potential REE concentration. I-/A- type granitoids and their weathered crusts are important REE sources in Indonesia. Unfortunately, their distribution and genesis have not been deeply studied. Future REE explorations challenge are mainly of the granitoids their weathered crusts. Geochemical and mineralogical characterization of type of granitoids and their weathered crusts, the hydrothermally altered rocks, and clear REE regulation will help discover REE deposits in Indonesia.

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.

Changes in climate variability with reference to land quality and agriculture in Scotland.

PubMed

Brown, Iain; Castellazzi, Marie

2015-06-01

Classification and mapping of land capability represents an established format for summarising spatial information on land quality and land-use potential. By convention, this information incorporates bioclimatic constraints through the use of a long-term average. However, climate change means that land capability classification should also have a dynamic temporal component. Using an analysis based upon Land Capability for Agriculture in Scotland, it is shown that this dynamism not only involves the long-term average but also shorter term spatiotemporal patterns, particularly through changes in interannual variability. Interannual and interdecadal variations occur both in the likelihood of land being in prime condition (top three capability class divisions) and in class volatility from year to year. These changing patterns are most apparent in relation to the west-east climatic gradient which is mainly a function of precipitation regime and soil moisture. Analysis is also extended into the future using climate results for the 2050s from a weather generator which show a complex interaction between climate interannual variability and different soil types for land quality. In some locations, variability of land capability is more likely to decrease because the variable climatic constraints are relaxed and the dominant constraint becomes intrinsic soil properties. Elsewhere, climatic constraints will continue to be influential. Changing climate variability has important implications for land-use planning and agricultural management because it modifies local risk profiles in combination with the current trend towards agricultural intensification and specialisation.

Seismic Microzonation of Breginjski Kot (NW Slovenia) Based on Detailed Engineering Geological Mapping

PubMed Central

2013-01-01

Breginjski kot is among the most endangered seismic zones in Slovenia with the seismic hazard assessed to intensity IX MSK and the design ground acceleration of 0.250 g, both for 500-year return period. The most destructive was the 1976 Friuli Mw = 6.4 earthquake which had maximum intensity VIII-IX. Since the previous microzonation of the area was based solely on the basic geological map and did not include supplementary field research, we have performed a new soil classification of the area. First, a detailed engineering geological mapping in scale 1 : 5.000 was conducted. Mapped units were described in detail and some of them interpreted anew. Stiff sites are composed of hard to medium-hard rocks which were subjected to erosion mainly evoked by glacial and postglacial age. At that time a prominent topography was formed and different types of sediments were deposited in valleys by mass flows. A distinction between sediments and weathered rocks, their exact position, and thickness are of significant importance for microzonation. On the basis of geological mapping, a soil classification was carried out according to the Medvedev method (intensity increments) and the Eurocode 8 standard (soil factors) and two microzonation maps were prepared. The bulk of the studied area is covered by soft sediments and nine out of ten settlements are situated on them. The microzonation clearly points out the dependence of damage distribution in the case of 1976 Friuli earthquake to local site effects. PMID:24453884

Land use and topography influence in a complex terrain area: A high resolution mesoscale modelling study over the Eastern Pyrenees using the WRF model

NASA Astrophysics Data System (ADS)

Jiménez-Esteve, B.; Udina, M.; Soler, M. R.; Pepin, N.; Miró, J. R.

2018-04-01

Different types of land use (LU) have different physical properties which can change local energy balance and hence vertical fluxes of moisture, heat and momentum. This in turn leads to changes in near-surface temperature and moisture fields. Simulating atmospheric flow over complex terrain requires accurate local-scale energy balance and therefore model grid spacing must be sufficient to represent both topography and land-use. In this study we use both the Corine Land Cover (CLC) and United States Geological Survey (USGS) land use databases for use with the Weather Research and Forecasting (WRF) model and evaluate the importance of both land-use classification and horizontal resolution in contributing to successful modelling of surface temperatures and humidities observed from a network of 39 sensors over a 9 day period in summer 2013. We examine case studies of the effects of thermal inertia and soil moisture availability at individual locations. The scale at which the LU classification is observed influences the success of the model in reproducing observed patterns of temperature and moisture. Statistical validation of model output demonstrates model sensitivity to both the choice of LU database used and the horizontal resolution. In general, results show that on average, by a) using CLC instead of USGS and/or b) increasing horizontal resolution, model performance is improved. We also show that the sensitivity to these changes in the model performance shows a daily cycle.

7 CFR 51.2836 - Size classifications.

Code of Federal Regulations, 2013 CFR

2013-01-01

... 7 Agriculture 2 2013-01-01 2013-01-01 false Size classifications. 51.2836 Section 51.2836...-Granex-Grano and Creole Types) Size Classifications § 51.2836 Size classifications. The size of onions may be specified in accordance with one of the following classifications. Size designation Minimum...

7 CFR 51.2836 - Size classifications.

Code of Federal Regulations, 2014 CFR

2014-01-01

... 7 Agriculture 2 2014-01-01 2014-01-01 false Size classifications. 51.2836 Section 51.2836...-Granex-Grano and Creole Types) Size Classifications § 51.2836 Size classifications. The size of onions may be specified in accordance with one of the following classifications. Size designation Minimum...

Diagnostic discrepancies in retinopathy of prematurity classification

PubMed Central

Campbell, J. Peter; Ryan, Michael C.; Lore, Emily; Tian, Peng; Ostmo, Susan; Jonas, Karyn; Chan, R.V. Paul; Chiang, Michael F.

2016-01-01

Objective To identify the most common areas for discrepancy in retinopathy of prematurity (ROP) classification between experts. Design Prospective cohort study. Subjects, Participants, and/or Controls 281 infants were identified as part of a multi-center, prospective, ROP cohort study from 7 participating centers. Each site had participating ophthalmologists who provided the clinical classification after routine examination using binocular indirect ophthalmoscopy (BIO), and obtained wide-angle retinal images, which were independently classified by two study experts. Methods Wide-angle retinal images (RetCam; Clarity Medical Systems, Pleasanton, CA) were obtained from study subjects, and two experts evaluated each image using a secure web-based module. Image-based classifications for zone, stage, plus disease, overall disease category (no ROP, mild ROP, Type II or pre-plus, and Type I) were compared between the two experts, and to the clinical classification obtained by BIO. Main Outcome Measures Inter-expert image-based agreement and image-based vs. ophthalmoscopic diagnostic agreement using absolute agreement and weighted kappa statistic. Results 1553 study eye examinations from 281 infants were included in the study. Experts disagreed on the stage classification in 620/1553 (40%) of comparisons, plus disease classification (including pre-plus) in 287/1553 (18%), zone in 117/1553 (8%), and overall ROP category in 618/1553 (40%). However, agreement for presence vs. absence of type 1 disease was >95%. There were no differences between image-based and clinical classification except for zone III disease. Conclusions The most common area of discrepancy in ROP classification is stage, although inter-expert agreement for clinically-significant disease such as presence vs. absence of type 1 and type 2 disease is high. There were no differences between image-based grading and the clinical exam in the ability to detect clinically-significant disease. This study provides additional evidence that image-based classification of ROP reliably detects clinically significant levels of ROP with high accuracy compared to the clinical exam. PMID:27238376

Tropical Ocean Surface Energy Balance Variability: Linking Weather to Climate Scales

NASA Technical Reports Server (NTRS)

Roberts, J. Brent; Clayson, Carol Anne

2013-01-01

Radiative and turbulent surface exchanges of heat and moisture across the atmosphere-ocean interface are fundamental components of the Earth s energy and water balance. Characterizing the spatiotemporal variability of these exchanges of heat and moisture is critical to understanding the global water and energy cycle variations, quantifying atmosphere-ocean feedbacks, and improving model predictability. These fluxes are integral components to tropical ocean-atmosphere variability; they can drive ocean mixed layer variations and modify the atmospheric boundary layer properties including moist static stability, thereby influencing larger-scale tropical dynamics. Non-parametric cluster-based classification of atmospheric and ocean surface properties has shown an ability to identify coherent weather regimes, each typically associated with similar properties and processes. Using satellite-based observational radiative and turbulent energy flux products, this study investigates the relationship between these weather states and surface energy processes within the context of tropical climate variability. Investigations of surface energy variations accompanying intraseasonal and interannual tropical variability often use composite-based analyses of the mean quantities of interest. Here, a similar compositing technique is employed, but the focus is on the distribution of the heat and moisture fluxes within their weather regimes. Are the observed changes in surface energy components dominated by changes in the frequency of the weather regimes or through changes in the associated fluxes within those regimes? It is this question that the presented work intends to address. The distribution of the surface heat and moisture fluxes is evaluated for both normal and non-normal states. By examining both phases of the climatic oscillations, the symmetry of energy and water cycle responses are considered.

Optimizing biomass feedstock blends with respect to cost, supply, and quality for catalyzed and uncatalyzed fast pyrolysis applications

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

Thompson, Vicki S.; Aston, John E.; Lacey, Jeffrey A.

Here, biomass cost, quality and quantity are important parameters to consider when choosing feedstocks and locations for biorefineries. Biomass cost is dependent upon type, location, quantities available in a given area and logistics costs as well the quality needed for the biorefinery. Biomass quality depends upon type, growth conditions, weather, harvesting methods, storage conditions as well as any preprocessing methods used to improve quality. Biomass quantity depends heavily on location as well as growth conditions, weather, harvesting methods and storage conditions. This study examines how all three of these parameters affect the biomass mixture that is needed in a biomassmore » depot or biorefinery to achieve the lowest cost with the highest quality and at the quantities needed for biorefinery operation. Four biomass depots were proposed in South Carolina that would each process the predominant type of biomass available in that area and each produce 200,000 tons of feedstock per year. These depots would then feed a centrally located 800,000 ton biorefinery that would convert the feedstocks to pyrolysis oil using either catalyzed or uncatalyzed fast pyrolysis. The four depots each needed to produce different blends of biomass based upon the quantities available to them but still meet the minimum quality requirements for the biorefinery. Costs were minimized by using waste biomass resources such as construction and demolition waste, logging residues and forest residuals. Depending upon the quality specification required by the biorefinery, it was necessary to utilize preprocessing methods such as air classification and acid leaching to upgrade biomass quality. In the case of uncatalyzed fast pyrolysis, all four depots could produce biomass blends that were lower cost than the the preferred pyrolysis feedstock, clean pine, and meet quality and quantity specifications. For catalyzed fast pyrolysis, three of the four depots were able to produce blends that met both quality and quantity specifications at minimum cost. The fourth depot would not be able to produce a blend meeting specifications without increasing the supply radius for the depot.« less

Optimizing biomass feedstock blends with respect to cost, supply, and quality for catalyzed and uncatalyzed fast pyrolysis applications

DOE PAGES

Thompson, Vicki S.; Aston, John E.; Lacey, Jeffrey A.; ...

2017-05-24

Here, biomass cost, quality and quantity are important parameters to consider when choosing feedstocks and locations for biorefineries. Biomass cost is dependent upon type, location, quantities available in a given area and logistics costs as well the quality needed for the biorefinery. Biomass quality depends upon type, growth conditions, weather, harvesting methods, storage conditions as well as any preprocessing methods used to improve quality. Biomass quantity depends heavily on location as well as growth conditions, weather, harvesting methods and storage conditions. This study examines how all three of these parameters affect the biomass mixture that is needed in a biomassmore » depot or biorefinery to achieve the lowest cost with the highest quality and at the quantities needed for biorefinery operation. Four biomass depots were proposed in South Carolina that would each process the predominant type of biomass available in that area and each produce 200,000 tons of feedstock per year. These depots would then feed a centrally located 800,000 ton biorefinery that would convert the feedstocks to pyrolysis oil using either catalyzed or uncatalyzed fast pyrolysis. The four depots each needed to produce different blends of biomass based upon the quantities available to them but still meet the minimum quality requirements for the biorefinery. Costs were minimized by using waste biomass resources such as construction and demolition waste, logging residues and forest residuals. Depending upon the quality specification required by the biorefinery, it was necessary to utilize preprocessing methods such as air classification and acid leaching to upgrade biomass quality. In the case of uncatalyzed fast pyrolysis, all four depots could produce biomass blends that were lower cost than the the preferred pyrolysis feedstock, clean pine, and meet quality and quantity specifications. For catalyzed fast pyrolysis, three of the four depots were able to produce blends that met both quality and quantity specifications at minimum cost. The fourth depot would not be able to produce a blend meeting specifications without increasing the supply radius for the depot.« less

Modelling fire frequency and area burned across phytoclimatic regions in Spain using reanalysis data and the Canadian Fire Weather Index System

NASA Astrophysics Data System (ADS)

Bedia, J.; Herrera, S.; Gutiérrez, J. M.

2013-09-01

We develop fire occurrence and burned area models in peninsular Spain, an area of high variability in climate and fuel types, for the period 1990-2008. We based the analysis on a phytoclimatic classification aiming to the stratification of the territory into homogeneous units in terms of climatic and fuel type characteristics, allowing to test model performance under different climatic and fuel conditions. We used generalized linear models (GLM) and multivariate adaptive regression splines (MARS) as modelling algorithms and temperature, relative humidity, precipitation and wind speed, taken from the ERA-Interim reanalysis, as well as the components of the Canadian Forest Fire Weather Index (FWI) System as predictors. We also computed the standardized precipitation-evapotranspiration index (SPEI) as an additional predictor for the models of burned area. We found two contrasting fire regimes in terms of area burned and number of fires: one characterized by a bimodal annual pattern, characterizing the Nemoral and Oro-boreal phytoclimatic types, and another one exhibiting an unimodal annual cycle, with the fire season concentrated in the summer months in the Mediterranean and Arid regions. The fire occurrence models attained good skill in most of the phytoclimatic zones considered, yielding in some zones notably high correlation coefficients between the observed and modelled inter-annual fire frequencies. Total area burned also exhibited a high dependence on the meteorological drivers, although their ability to reproduce the observed annual burned area time series was poor in most cases. We identified temperature and some FWI system components as the most important explanatory variables, and also SPEI in some of the burned area models, highlighting the adequacy of the FWI system for fire modelling applications and leaving the door opened to the development a more complex modelling framework based on these predictors. Furthermore, we demonstrate the potential usefulness of ERA-Interim reanalysis data for the reconstruction of historical fire-climate relationships at the scale of analysis. Fire frequency predictions may provide a preferable basis for past fire history reconstruction, long-term monitoring and the assessment of future climate impacts on fire regimes across regions, posing several advantages over burned area as response variable.

Forest habitat types of central Idaho

Treesearch

Robert Steele; Robert D. Pfister; Russell A. Ryker; Jay A. Kittams

1981-01-01

A land-classification system based upon potential natural vegetation is presented for the forests of central Idaho. It is based on reconnaissance sampling of about 800 stands. A hierarchical taxonomic classification of forest sites was developed using the habitat type concept. A total of eight climax series, 64 habitat types, and 55 additional phases of habitat types...

Spatial Prediction of Soil Classes by Using Soil Weathering Parameters Derived from vis-NIR Spectroscopy

NASA Astrophysics Data System (ADS)

Ramirez-Lopez, Leonardo; Alexandre Dematte, Jose

2010-05-01

There is consensus in the scientific community about the great need of spatial soil information. Conventional mapping methods are time consuming and involve high costs. Digital soil mapping has emerged as an area in which the soil mapping is optimized by the application of mathematical and statistical approaches, as well as the application of expert knowledge in pedology. In this sense, the objective of the study was to develop a methodology for the spatial prediction of soil classes by using soil spectroscopy methodologies related with fieldwork, spectral data from satellite image and terrain attributes in simultaneous. The studied area is located in São Paulo State, and comprised an area of 473 ha, which was covered by a regular grid (100 x 100 m). In each grid node was collected soil samples at two depths (layers A and B). There were extracted 206 samples from transect sections and submitted to soil analysis (clay, Al2O3, Fe2O3, SiO2 TiO2, and weathering index). The first analog soil class map (ASC-N) contains only soil information regarding from orders to subgroups of the USDA Soil Taxonomy System. The second (ASC-H) map contains some additional information related to some soil attributes like color, ferric levels and base sum. For the elaboration of the digital soil maps the data was divided into three groups: i) Predicted soil attributes of the layer B (related to the soil weathering) which were obtained by using a local soil spectral library; ii) Spectral bands data extracted from a Landsat image; and iii) Terrain parameters. This information was summarized by a principal component analysis (PCA) in each group. Digital soil maps were generated by supervised classification using a maximum likelihood method. The trainee information for this classification was extracted from five toposequences based on the analog soil class maps. The spectral models of weathering soil attributes shown a high predictive performance with low error (R2 0.71 to 0.90). The spatial prediction of these attributes also showed a high performance (validations with R2> 0.78). These models allowed to increase spatial resolution of soil weathering information. On the other hand, the comparison between the analog and digital soil maps showed a global accuracy of 69% for the ASC-N map and 62% in the ASC-H map, with kappa indices of 0.52 and 0.45 respectively.

OVERVIEW OF EPA'S WET-WEATHER FLOW RESEARCH PROGRAM

EPA Science Inventory

Surface waters receive three types of urban wet-weather flow discharges: combined-sewer overflow (CSO), stormwater, and sanitary-sewer overflow (SSO); all are principally untreated discharges that occur during storm-flow events. WWFs have proven to generate a substantial amount o...

Analyses of rear-end crashes based on classification tree models.

PubMed

Yan, Xuedong; Radwan, Essam

2006-09-01

Signalized intersections are accident-prone areas especially for rear-end crashes due to the fact that the diversity of the braking behaviors of drivers increases during the signal change. The objective of this article is to improve knowledge of the relationship between rear-end crashes occurring at signalized intersections and a series of potential traffic risk factors classified by driver characteristics, environments, and vehicle types. Based on the 2001 Florida crash database, the classification tree method and Quasi-induced exposure concept were used to perform the statistical analysis. Two binary classification tree models were developed in this study. One was used for the crash comparison between rear-end and non-rear-end to identify those specific trends of the rear-end crashes. The other was constructed for the comparison between striking vehicles/drivers (at-fault) and struck vehicles/drivers (not-at-fault) to find more complex crash pattern associated with the traffic attributes of driver, vehicle, and environment. The modeling results showed that the rear-end crashes are over-presented in the higher speed limits (45-55 mph); the rear-end crash propensity for daytime is apparently larger than nighttime; and the reduction of braking capacity due to wet and slippery road surface conditions would definitely contribute to rear-end crashes, especially at intersections with higher speed limits. The tree model segmented drivers into four homogeneous age groups: < 21 years, 21-31 years, 32-75 years, and > 75 years. The youngest driver group shows the largest crash propensity; in the 21-31 age group, the male drivers are over-involved in rear-end crashes under adverse weather conditions and the 32-75 years drivers driving large size vehicles have a larger crash propensity compared to those driving passenger vehicles. Combined with the quasi-induced exposure concept, the classification tree method is a proper statistical tool for traffic-safety analysis to investigate crash propensity. Compared to the logistic regression models, tree models have advantages for handling continuous independent variables and easily explaining the complex interaction effect with more than two independent variables. This research recommended that at signalized intersections with higher speed limits, reducing the speed limit to 40 mph efficiently contribute to a lower accident rate. Drivers involved in alcohol use may increase not only rear-end crash risk but also the driver injury severity. Education and enforcement countermeasures should focus on the driver group younger than 21 years. Further studies are suggested to compare crash risk distributions of the driver age for other main crash types to seek corresponding traffic countermeasures.

An ionospheric index suitable for estimating the degree of ionospheric perturbations

NASA Astrophysics Data System (ADS)

Wilken, Volker; Kriegel, Martin; Jakowski, Norbert; Berdermann, Jens

2018-03-01

Space weather can strongly affect trans-ionospheric radio signals depending on the used frequency. In order to assess the strength of a space weather event from its origin at the sun towards its impact on the ionosphere a number of physical quantities need to be derived from scientific measurements. These are for example the Wolf number sunspot index, the solar flux density F10.7, measurements of the interplanetary magnetic field, the proton density, the solar wind speed, the dynamical pressure, the geomagnetic indices Auroral Electrojet, Kp, Ap and Dst as well as the Total Electron Content (TEC), the Rate of TEC, the scintillation indices S4 and σ(ϕ) and the Along-Arc TEC Rate index index. All these quantities provide in combination with an additional classification an orientation in a physical complex environment. Hence, they are used for brief communication of a simplified but appropriate space situation awareness. However, space weather driven ionospheric phenomena can affect many customers in the communication and navigation domain, which are still served inadequately by the existing indices. We present a new robust index, that is able to properly characterize temporal and spatial ionospheric variations of small to medium scales. The proposed ionospheric disturbance index can overcome several drawbacks of other ionospheric measures and might be suitable as potential driver for an ionospheric space weather scale.

Severe Weather Guide - Mediterranean Ports. 3. Catania

DTIC Science & Technology

1988-03-01

CLASSIFICATION 99.’iC,;ASSiPIED 1,NLIM!TED 0 SAME AS RPT 0 OTIC USERS UNCLASSIFIED a,. jAME OF RESPONSIBLE INDII.DUAL I22b TELEPHONE (include 4rea...event. (3) triigdprighro, a) Vessel control may be affected at slow SGA. Smal boa~peatios. ) Smll oati mabe restricted/curtailed in a strong event * 0...Pub. No. 603, Practical Methods for Observing and Forecasting Ocean Waves (Pierson, Neumann, and James , 1955). The information on fully arisen wave

Cannon AFB, Clovis, New Mexico. Revised Uniform Summary of Surface Weather Observations (RUSSWO), Parts A-F

DTIC Science & Technology

1975-06-16

dry -bulb temperature, means and standard d~viatinne nf eirg-hiiih- wM~e-.h,lh (y DD 1473 ~ UNCLASSIFIED SECURIS- CLASSIFICATION OF THIS PAGE(Ifnon...Val. Entoted) 19. Percentqge frequency of distribution tables Dry -bulb temperature versus wet-bulb temperature Cumulative percentage frequency of...ATMOSPHERIC PHENOMENA EXTREME MAX & MIN TEMP PART B PRECIPITATION PSYCHROMETRIC- DRY VS WET BULB SNOWFALL MEAN & STD DEV - ( DRY BULB, WET BULB, & DEW

The new intra-articular calcaneal fracture classification system in term of sustentacular fragment configurations and incorporation of posterior calcaneal facet fractures with fracture components of the calcaneal body.

PubMed

Harnroongroj, Thossart; Harnroongroj, Thos; Suntharapa, Thongchai; Arunakul, Marut

2016-10-01

The aim of this study was to develop a new calcaneal fracture classification system which will consider sustentacular fragment configuration and relation of posterior calcaneal facet to calcaneal body. The new classification system used sustentacular fragment configuration and relation of posterior calcaneal facet fracture with fracture components of calcaneal body as key aspects of main types and subtypes. Between 2000 and 2014, 126 intraarticular calcaneal fractures were classified according to the new classification system by using computed tomography images. The new classification system was studied in term of reliability, correlation to choices of treatment, implant fixation and quality of fracture reduction. Types of sustentacular fragment comprised type A, B and C. Type A sustentacular fragment included sustentacular tali containing middle calcaneal facet. In Type B and C fractures sustentacular fragment included medial aspect and entire posterior calcaneal facet as a single unit, respectively. The fractures with type A, B and C sustentacular fragments were classified as main type A, B and C intra-articular calcaneal fractures. The main type A and B comprised 4 subtypes. Subtypes A1, A3, B1, and B3 associated with avulsion and bending fragments of calcaneal body. Subtype A2, B2, and B4 associated with burst calcaneal body. Subtype B4 was not found in the study. Main type C had no subtype and associated with burst calcaneal body. The data showed good reliability. The study showed that our new intra-articular calcaneal fracture classification system correlates to choices of treatment, implant fixation and quality of fracture reduction. Level IV, Study of Diagnostic Test. Copyright © 2016 Turkish Association of Orthopaedics and Traumatology. Production and hosting by Elsevier B.V. All rights reserved.

Validating the Danish adaptation of the World Health Organization's International Classification for Patient Safety classification of patient safety incident types

PubMed Central

Mikkelsen, Kim Lyngby; Thommesen, Jacob; Andersen, Henning Boje

2013-01-01

Objectives Validation of a Danish patient safety incident classification adapted from the World Health Organizaton's International Classification for Patient Safety (ICPS-WHO). Design Thirty-three hospital safety management experts classified 58 safety incident cases selected to represent all types and subtypes of the Danish adaptation of the ICPS (ICPS-DK). Outcome Measures Two measures of inter-rater agreement: kappa and intra-class correlation (ICC). Results An average number of incident types used per case per rater was 2.5. The mean ICC was 0.521 (range: 0.199–0.809) and the mean kappa was 0.513 (range: 0.193–0.804). Kappa and ICC showed high correlation (r = 0.99). An inverse correlation was found between the prevalence of type and inter-rater reliability. Results are discussed according to four factors known to determine the inter-rater agreement: skill and motivation of raters; clarity of case descriptions; clarity of the operational definitions of the types and the instructions guiding the coding process; adequacy of the underlying classification scheme. Conclusions The incident types of the ICPS-DK are adequate, exhaustive and well suited for classifying and structuring incident reports. With a mean kappa a little above 0.5 the inter-rater agreement of the classification system is considered ‘fair’ to ‘good’. The wide variation in the inter-rater reliability and low reliability and poor discrimination among the highly prevalent incident types suggest that for these types, precisely defined incident sub-types may be preferred. This evaluation of the reliability and usability of WHO's ICPS should be useful for healthcare administrations that consider or are in the process of adapting the ICPS. PMID:23287641

Mineralogy, petrography, geochemistry, and classification of the Košice meteorite

NASA Astrophysics Data System (ADS)

OzdíN, Daniel; PlavčAn, Jozef; HoråáčKová, Michaela; Uher, Pavel; PorubčAn, VladimíR.; Veis, Pavel; Rakovský, Jozef; Tóth, Juraj; KonečNý, Patrik; Svoreå, JáN.

2015-05-01

The Košice meteorite was observed to fall on 28 February 2010 at 23:25 UT near the city of Košice in eastern Slovakia and its mineralogy, petrology, and geochemistry are described. The characteristic features of the meteorite fragments are fan-like, mosaic, lamellar, and granular chondrules, which were up to 1.2 mm in diameter. The fusion crust has a black-gray color with a thickness up to 0.6 mm. The matrix of the meteorite is formed mainly by forsterite (Fo80.6); diopside; enstatite (Fs16.7); albite; troilite; Fe-Ni metals such as iron and taenite; and some augite, chlorapatite, merrillite, chromite, and tetrataenite. Plagioclase-like glass was also identified. Relative uniform chemical composition of basic silicates, partially brecciated textures, as well as skeletal taenite crystals into troilite veinlets suggest monomict breccia formed at conditions of rapid cooling. The Košice meteorite is classified as ordinary chondrite of the H5 type which has been slightly weathered, and only short veinlets of Fe hydroxides are present. The textural relationships indicate an S3 degree of shock metamorphism and W0 weathering grade. Some fragments of the meteorite Košice are formed by monomict breccia of the petrological type H5. On the basis of REE content, we suggest the Košice chondrite is probably from the same parent body as H5 chondrite Morávka from Czech Republic. Electron-microprobe analysis (EMPA) with focused and defocused electron beam, whole-rock analysis (WRA), inductively coupled plasma mass and optical emission spectroscopy (ICP MS, ICP OES), and calibration-free laser induced breakdown spectroscopy (CF-LIBS) were used to characterize the Košice fragments. The results provide further evidence that whole-rock analysis gives the most accurate analyses, but this method is completely destructive. Two other proposed methods are partially destructive (EMPA) or nondestructive (CF-LIBS), but only major and minor elements can be evaluated due to the significantly lower sample consumption.

Photometric brown-dwarf classification. I. A method to identify and accurately classify large samples of brown dwarfs without spectroscopy

NASA Astrophysics Data System (ADS)

Skrzypek, N.; Warren, S. J.; Faherty, J. K.; Mortlock, D. J.; Burgasser, A. J.; Hewett, P. C.

2015-02-01

Aims: We present a method, named photo-type, to identify and accurately classify L and T dwarfs onto the standard spectral classification system using photometry alone. This enables the creation of large and deep homogeneous samples of these objects efficiently, without the need for spectroscopy. Methods: We created a catalogue of point sources with photometry in 8 bands, ranging from 0.75 to 4.6 μm, selected from an area of 3344 deg2, by combining SDSS, UKIDSS LAS, and WISE data. Sources with 13.0 0.8, were then classified by comparison against template colours of quasars, stars, and brown dwarfs. The L and T templates, spectral types L0 to T8, were created by identifying previously known sources with spectroscopic classifications, and fitting polynomial relations between colour and spectral type. Results: Of the 192 known L and T dwarfs with reliable photometry in the surveyed area and magnitude range, 189 are recovered by our selection and classification method. We have quantified the accuracy of the classification method both externally, with spectroscopy, and internally, by creating synthetic catalogues and accounting for the uncertainties. We find that, brighter than J = 17.5, photo-type classifications are accurate to one spectral sub-type, and are therefore competitive with spectroscopic classifications. The resultant catalogue of 1157 L and T dwarfs will be presented in a companion paper.

Large-scale classification of traffic signs under real-world conditions

NASA Astrophysics Data System (ADS)

Hazelhoff, Lykele; Creusen, Ivo; van de Wouw, Dennis; de With, Peter H. N.

2012-02-01

Traffic sign inventories are important to governmental agencies as they facilitate evaluation of traffic sign locations and are beneficial for road and sign maintenance. These inventories can be created (semi-)automatically based on street-level panoramic images. In these images, object detection is employed to detect the signs in each image, followed by a classification stage to retrieve the specific sign type. Classification of traffic signs is a complicated matter, since sign types are very similar with only minor differences within the sign, a high number of different signs is involved and multiple distortions occur, including variations in capturing conditions, occlusions, viewpoints and sign deformations. Therefore, we propose a method for robust classification of traffic signs, based on the Bag of Words approach for generic object classification. We extend the approach with a flexible, modular codebook to model the specific features of each sign type independently, in order to emphasize at the inter-sign differences instead of the parts common for all sign types. Additionally, this allows us to model and label the present false detections. Furthermore, analysis of the classification output provides the unreliable results. This classification system has been extensively tested for three different sign classes, covering 60 different sign types in total. These three data sets contain the sign detection results on street-level panoramic images, extracted from a country-wide database. The introduction of the modular codebook shows a significant improvement for all three sets, where the system is able to classify about 98% of the reliable results correctly.

Prediction of CMEs and Type II Bursts from Sun to Earth

NASA Astrophysics Data System (ADS)

Cairns, I. H.; Schmidt, J. M.; Gopalswamy, N.; van der Holst, B.

2017-12-01

Most major space weather events are due to fast CMEs and their shocks interacting with Earth's magnetosphere. SImilarly, type II solar radio bursts are well-known signatures of CMEs and their shocks moving through the corona and solar wind. The properties of the space weather events and the type II radio bursts depend sensitively on the CME velocity, shape, and evolution as functions of position and time, as well as on the magnetic field vector in the coronal and solar wind plasma, downstream of the CME shock, and inside the CME. We report simulations of CMEs and type II bursts from the Sun to Earth with the Space Weather Modelling Framework (2015 and 2016 versions), set up carefully using relevant data, and a kinetic radio emission theory. Excellent agreement between observations, simulations, and theory are found for the coronal (metric) type II burst of 7 September 2014 and associated CME, including the lack of radio emission in the solar wind beyond about 10 solar radii. Similarly, simulation of a CME and type II burst from the Sun to 1 AU over the period 29 November - 1 December 2013 yield excellent agreement for the radio burst from 10 MHz to 30 kHz for STEREO A and B and Wind, arrival of the CME at STEREO A within 1 hour reported time, deceleration of the CME in agreement with the Gopalswamy et al. [2011] observational analyses, and Bz rotations at STEREO A from upstream of the CME shock to within the CME. These results provide strong support for the type II theory and also that the Space WeatherModeling Framework can accurately predict the properties and evolution of CMEs and the interplanetary magnetic field and plasma from the Sun to 1 AU when sufficiently carefully initialized.

Dual-Polarization Radar Observations of Upward Lightning-Producing Storms

NASA Astrophysics Data System (ADS)

Lueck, R.; Helsdon, J. H.; Warner, T.

2013-12-01

The Upward Lightning Triggering Study (UPLIGHTS) seeks to determine how upward lightning, which originates from the tips of tall objects, is triggered by nearby flash activity. As a component of this study we analyze standard and dual-polarization weather radar data. The Correlation Coefficient (CC) in particular can be used to identify and quantify the melting layer associated with storms that produce upward lightning. It has been proposed that positive charge generation due to aggregate shedding at the melting layer results in a positive charge region just above the cloud base. This positive charge region may serve as a positive potential well favorable for negative leader propagation, which initiate upward positive leaders from tall objects. We characterize the horizontal coverage, thickness and height of the melting layer in addition to cloud base heights when upward lightning occurs to determine trends and possible threshold criteria relating to upward lightning production. Furthermore, we characterize storm type and morphology using relevant schemes as well as precipitation type using the Hydrometer Classification Algorithm (HCA) for upward lightning-producing storms. Ice-phase hydrometeors have been shown to be a significant factor in thunderstorm electrification. Only a small fraction of storms produce upward lightning, so null cases will be examined and compared as well.

A graduated food addiction classification approach significantly differentiates obesity among people with type 2 diabetes.

PubMed

Raymond, Karren-Lee; Kannis-Dymand, Lee; Lovell, Geoff P

2016-10-01

This study examined a graduated severity level approach to food addiction classification against associations with World Health Organization obesity classifications (body mass index, kg/m 2 ) among 408 people with type 2 diabetes. A survey including the Yale Food Addiction Scale and several demographic questions demonstrated four distinct Yale Food Addiction Scale symptom severity groups (in line with Diagnostic and Statistical Manual of Mental Disorders (5th ed.) severity indicators): non-food addiction, mild food addiction, moderate food addiction and severe food addiction. Analysis of variance with post hoc tests demonstrated each severity classification group was significantly different in body mass index, with each grouping being associated with increased World Health Organization obesity classifications. These findings have implications for diagnosing food addiction and implementing treatment and prevention methodologies of obesity among people with type 2 diabetes.

Three forms of immune myasthenia.

PubMed

Agius, Mark A; Richman, David P; Fairclough, Robert H; Aarli, Johan; Gilhus, Nils Erik; Romi, Fredrik

2003-09-01

We propose a new classification for immune myasthenia based on antibody pattern. The types of immune myasthenia presently characterized by known antibody targets segregate into three groups: type 1, in which the muscle target is the acetylcholine receptor only; type 2, in which titin antibodies are present in addition to acetylcholine receptor antibodies; and type 3, in which muscle-specific kinase antibodies are present in the absence of acetylcholine receptor antibodies. The immune target is unknown in the patients with immune myasthenia not associated with these antibodies. This classification has advantages over the present classifications as regards homogeneity of groups, etiology, mechanism of disease, and prognosis.

Weather during bloom affects pollination and yield of highbush blueberry.

PubMed

Tuell, Julianna K; Isaacs, Rufus

2010-06-01

Weather plays an important role in spring-blooming fruit crops due to the combined effects on bee activity, flower opening, pollen germination, and fertilization. To determine the effects of weather on highbush blueberry, Vaccinium corymbosum L., productivity, we monitored bee activity and compared fruit set, weight, and seed number in a field stocked with honey bees, Apis mellifera L., and common eastern bumble bees, Bombus impatiens (Cresson). Flowers were subjected to one of five treatments during bloom: enclosed, open, open during poor weather only, open during good weather only, or open during poor and good weather. Fewer bees of all types were observed foraging and fewer pollen foragers returned to colonies during poor weather than during good weather. There were also changes in foraging community composition: honey bees dominated during good weather, whereas bumble bees dominated during poor weather. Berries from flowers exposed only during poor weather had higher fruit set in 1 yr and higher berry weight in the other year compared with enclosed clusters. In both years, clusters exposed only during good weather had > 5 times as many mature seeds, weighed twice as much, and had double the fruit set of those not exposed. No significant increase over flowers exposed during good weather was observed when clusters were exposed during good and poor weather. Our results are discussed in terms of the role of weather during bloom on the contribution of bees adapted to foraging during cool conditions.

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.

7 CFR 30.31 - Classification of leaf tobacco.

Code of Federal Regulations, 2013 CFR

2013-01-01

... 7 Agriculture 2 2013-01-01 2013-01-01 false Classification of leaf tobacco. 30.31 Section 30.31... REGULATIONS TOBACCO STOCKS AND STANDARDS Classification of Leaf Tobacco Covering Classes, Types and Groups of Grades § 30.31 Classification of leaf tobacco. For the purpose of this classification leaf tobacco shall...

7 CFR 30.31 - Classification of leaf tobacco.

Code of Federal Regulations, 2012 CFR

2012-01-01

... 7 Agriculture 2 2012-01-01 2012-01-01 false Classification of leaf tobacco. 30.31 Section 30.31... REGULATIONS TOBACCO STOCKS AND STANDARDS Classification of Leaf Tobacco Covering Classes, Types and Groups of Grades § 30.31 Classification of leaf tobacco. For the purpose of this classification leaf tobacco shall...

7 CFR 30.31 - Classification of leaf tobacco.

Code of Federal Regulations, 2010 CFR

2010-01-01

... 7 Agriculture 2 2010-01-01 2010-01-01 false Classification of leaf tobacco. 30.31 Section 30.31... REGULATIONS TOBACCO STOCKS AND STANDARDS Classification of Leaf Tobacco Covering Classes, Types and Groups of Grades § 30.31 Classification of leaf tobacco. For the purpose of this classification leaf tobacco shall...

7 CFR 30.31 - Classification of leaf tobacco.

Code of Federal Regulations, 2011 CFR

2011-01-01

... 7 Agriculture 2 2011-01-01 2011-01-01 false Classification of leaf tobacco. 30.31 Section 30.31... REGULATIONS TOBACCO STOCKS AND STANDARDS Classification of Leaf Tobacco Covering Classes, Types and Groups of Grades § 30.31 Classification of leaf tobacco. For the purpose of this classification leaf tobacco shall...

7 CFR 30.31 - Classification of leaf tobacco.

Code of Federal Regulations, 2014 CFR

2014-01-01

... 7 Agriculture 2 2014-01-01 2014-01-01 false Classification of leaf tobacco. 30.31 Section 30.31... REGULATIONS TOBACCO STOCKS AND STANDARDS Classification of Leaf Tobacco Covering Classes, Types and Groups of Grades § 30.31 Classification of leaf tobacco. For the purpose of this classification leaf tobacco shall...

Land Covers Classification Based on Random Forest Method Using Features from Full-Waveform LIDAR Data

NASA Astrophysics Data System (ADS)

Ma, L.; Zhou, M.; Li, C.

2017-09-01

In this study, a Random Forest (RF) based land covers classification method is presented to predict the types of land covers in Miyun area. The returned full-waveforms which were acquired by a LiteMapper 5600 airborne LiDAR system were processed, including waveform filtering, waveform decomposition and features extraction. The commonly used features that were distance, intensity, Full Width at Half Maximum (FWHM), skewness and kurtosis were extracted. These waveform features were used as attributes of training data for generating the RF prediction model. The RF prediction model was applied to predict the types of land covers in Miyun area as trees, buildings, farmland and ground. The classification results of these four types of land covers were obtained according to the ground truth information acquired from CCD image data of the same region. The RF classification results were compared with that of SVM method and show better results. The RF classification accuracy reached 89.73% and the classification Kappa was 0.8631.

Classification and area estimation of land covers in Kansas using ground-gathered and LANDSAT digital data

NASA Technical Reports Server (NTRS)

May, G. A.; Holko, M. L.; Anderson, J. E.

1983-01-01

Ground-gathered data and LANDSAT multispectral scanner (MSS) digital data from 1981 were analyzed to produce a classification of Kansas land areas into specific types called land covers. The land covers included rangeland, forest, residential, commercial/industrial, and various types of water. The analysis produced two outputs: acreage estimates with measures of precision, and map-type or photo products of the classification which can be overlaid on maps at specific scales. State-level acreage estimates were obtained and substate-level land cover classification overlays and estimates were generated for selected geographical areas. These products were found to be of potential use in managing land and water resources.

Accelerated weathering of tough shales : final report.

DOT National Transportation Integrated Search

1977-01-01

The purpose of this study was to find or develop a test that would identify a very tough but relatively rapid weathering type of shale that has caused problems when used in embankments as rock. Eight shales, including the problem shale, were collecte...

Climate change and viticulture in Mediterranean climates: the complex response of socio-ecosystems. A comparative case study from France and Australia (1955-2040)

NASA Astrophysics Data System (ADS)

Lereboullet, A.-L.; Beltrando, G.; Bardsley, D. K.

2012-04-01

The wine industry is very sensitive to extreme weather events, especially to temperatures above 35°C and drought. In a context of global climate change, Mediterranean climate regions are predicted to experience higher variability in rainfall and temperatures and an increased occurrence of extreme weather events. Some viticultural systems could be particularly at risk in those regions, considering their marginal position in the growth climatic range of Vitis vinifera, the long commercial lifespan of a vineyard, the high added-value of wine and the volatile nature of global markets. The wine industry, like other agricultural systems, is inserted in complex networks of climatic and non-climatic (other physical, economical, social and legislative) components, with constant feedbacks. We use a socio-ecosystem approach to analyse the adaptation of two Mediterranean viticultural systems to recent and future increase of extreme weather events. The present analysis focuses on two wine regions with a hot-summer Mediterranean climate (CSb type in the Köppen classification): Côtes-du-Roussillon in southern France and McLaren Vale in southern Australia. Using climate data from two synoptic weather stations, Perpignan (France) and Adelaide (Australia), with time series running from 1955 to 2010, we highlight changes in rainfall patterns and an increase in the number of days with Tx >35°c since the last three decades in both regions. Climate models (DRIAS project data for France and CSIRO Mk3.5 for Australia) project similar trends in the future. To date, very few projects have focused on an international comparison of the adaptive capacity of viticultural systems to climate change with a holistic approach. Here, the analysis of climate data was complemented by twenty in-depth semi-structured interviews with key actors of the two regional wine industries, in order to analyse adaptation strategies put in place regarding recent climate evolution. This mixed-methods approach allows for a comprehensive assessment of adaptation capacity of the two viticultural systems to future climate change. The strategies of grape growers and wine producers focus on maintaining optimal yields and a constant wine style adapted to markets in a variable and uncertain climate. Their implementation and efficiency depend strongly on non-climatic factors. Thus, adaptation capacity to recent and future climate change depends strongly on adaptation to other non-climatic changes.

A non-parametric, supervised classification of vegetation types on the Kaibab National Forest using decision trees

Treesearch

Suzanne M. Joy; R. M. Reich; Richard T. Reynolds

2003-01-01

Traditional land classification techniques for large areas that use Landsat Thematic Mapper (TM) imagery are typically limited to the fixed spatial resolution of the sensors (30m). However, the study of some ecological processes requires land cover classifications at finer spatial resolutions. We model forest vegetation types on the Kaibab National Forest (KNF) in...

A statistical approach to root system classification

PubMed Central

Bodner, Gernot; Leitner, Daniel; Nakhforoosh, Alireza; Sobotik, Monika; Moder, Karl; Kaul, Hans-Peter

2013-01-01

Plant root systems have a key role in ecology and agronomy. In spite of fast increase in root studies, still there is no classification that allows distinguishing among distinctive characteristics within the diversity of rooting strategies. Our hypothesis is that a multivariate approach for “plant functional type” identification in ecology can be applied to the classification of root systems. The classification method presented is based on a data-defined statistical procedure without a priori decision on the classifiers. The study demonstrates that principal component based rooting types provide efficient and meaningful multi-trait classifiers. The classification method is exemplified with simulated root architectures and morphological field data. Simulated root architectures showed that morphological attributes with spatial distribution parameters capture most distinctive features within root system diversity. While developmental type (tap vs. shoot-borne systems) is a strong, but coarse classifier, topological traits provide the most detailed differentiation among distinctive groups. Adequacy of commonly available morphologic traits for classification is supported by field data. Rooting types emerging from measured data, mainly distinguished by diameter/weight and density dominated types. Similarity of root systems within distinctive groups was the joint result of phylogenetic relation and environmental as well as human selection pressure. We concluded that the data-define classification is appropriate for integration of knowledge obtained with different root measurement methods and at various scales. Currently root morphology is the most promising basis for classification due to widely used common measurement protocols. To capture details of root diversity efforts in architectural measurement techniques are essential. PMID:23914200

Comparison Between Supervised and Unsupervised Classifications of Neuronal Cell Types: A Case Study

PubMed Central

Guerra, Luis; McGarry, Laura M; Robles, Víctor; Bielza, Concha; Larrañaga, Pedro; Yuste, Rafael

2011-01-01

In the study of neural circuits, it becomes essential to discern the different neuronal cell types that build the circuit. Traditionally, neuronal cell types have been classified using qualitative descriptors. More recently, several attempts have been made to classify neurons quantitatively, using unsupervised clustering methods. While useful, these algorithms do not take advantage of previous information known to the investigator, which could improve the classification task. For neocortical GABAergic interneurons, the problem to discern among different cell types is particularly difficult and better methods are needed to perform objective classifications. Here we explore the use of supervised classification algorithms to classify neurons based on their morphological features, using a database of 128 pyramidal cells and 199 interneurons from mouse neocortex. To evaluate the performance of different algorithms we used, as a “benchmark,” the test to automatically distinguish between pyramidal cells and interneurons, defining “ground truth” by the presence or absence of an apical dendrite. We compared hierarchical clustering with a battery of different supervised classification algorithms, finding that supervised classifications outperformed hierarchical clustering. In addition, the selection of subsets of distinguishing features enhanced the classification accuracy for both sets of algorithms. The analysis of selected variables indicates that dendritic features were most useful to distinguish pyramidal cells from interneurons when compared with somatic and axonal morphological variables. We conclude that supervised classification algorithms are better matched to the general problem of distinguishing neuronal cell types when some information on these cell groups, in our case being pyramidal or interneuron, is known a priori. As a spin-off of this methodological study, we provide several methods to automatically distinguish neocortical pyramidal cells from interneurons, based on their morphologies. © 2010 Wiley Periodicals, Inc. Develop Neurobiol 71: 71–82, 2011 PMID:21154911

Acromioclavicular joint dislocations: radiological correlation between Rockwood classification system and injury patterns in human cadaver species.

PubMed

Eschler, Anica; Rösler, Klaus; Rotter, Robert; Gradl, Georg; Mittlmeier, Thomas; Gierer, Philip

2014-09-01

The classification system of Rockwood and Young is a commonly used classification for acromioclavicular joint separations subdividing types I-VI. This classification hypothesizes specific lesions to anatomical structures (acromioclavicular and coracoclavicular ligaments, capsule, attached muscles) leading to the injury. In recent literature, our understanding for anatomical correlates leading to the radiological-based Rockwood classification is questioned. The goal of this experimental-based investigation was to approve the correlation between the anatomical injury pattern and the Rockwood classification. In four human cadavers (seven shoulders), the acromioclavicular and coracoclavicular ligaments were transected stepwise. Radiological correlates were recorded (Zanca view) with 15-kg longitudinal tension applied at the wrist. The resulting acromio- and coracoclavicular distances were measured. Radiographs after acromioclavicular ligament transection showed joint space enlargement (8.6 ± 0.3 vs. 3.1 ± 0.5 mm, p < 0.05) and no significant change in coracoclavicular distance (10.4 ± 0.9 vs. 10.0 ± 0.8 mm). According to the Rockwood classification only type I and II lesions occurred. After additional coracoclavicular ligament cut, the acromioclavicular joint space width increased to 16.7 ± 2.7 vs. 8.6 ± 0.3 mm, p < 0.05. The mean coracoclavicular distance increased to 20.6 ± 2.1 mm resulting in type III-V lesions concerning the Rockwood classification. Trauma with intact coracoclavicular ligaments did not result in acromioclavicular joint lesions higher than Rockwood type I and II. The clinical consequence for reconstruction of low-grade injuries might be a solely surgical approach for the acromioclavicular ligaments or conservative treatment. High-grade injuries were always based on additional structural damage to the coracoclavicular ligaments. Rockwood type V lesions occurred while muscle attachments were intact.

Forest habitat types of eastern Idaho-western Wyoming

Treesearch

Robert Steele; Stephen V. Cooper; David M. Ondov; David W. Roberts; Robert D. Pfister

1983-01-01

A land-classification system based upon potential natural vegetation is presented for the forests of central Idaho. It is based on reconnaissance sampling of about 980 stands. A hierarchical taxonomic classification of forest sites was developed using the habitat type concept. A total of six climax series, 58 habitat types, and 24 additional phases of habitat types are...

The influence of synoptic weather regimes on UK air quality: regional model studies of tropospheric column NO2

NASA Astrophysics Data System (ADS)

Pope, R. J.; Savage, N. H.; Chipperfield, M. P.; Ordóñez, C.; Neal, L. S.

2015-07-01

Synoptic meteorology can have a significant influence on UK air quality. Cyclonic (anticyclonic) conditions lead to the dispersion (accumulation) of air pollutants away from (over) source regions. Meteorology also modifies atmospheric chemistry processes such as photolysis and wet deposition. Previous studies have shown a relationship between observed satellite tropospheric column NO2 and synoptic meteorology in different seasons. Here, we test whether the UK Met Office Air Quality in the Unified Model (AQUM) can reproduce these observations and then use the model to determine the controlling factors. We show that AQUM successfully captures the observed relationships, when sampled under the Lamb Weather Types, an objective classification of midday UK circulation patterns. By using a range of idealised NOx-like tracers with different e-folding lifetimes, we show that under different synoptic regimes the NO2 lifetime in AQUM is approximately 6 h in summer and 12 h in winter. The longer lifetime can explain why synoptic spatial column NO2 variations are more significant in winter compared to summer, due to less NO2 photochemical loss. We also show that cyclonic conditions have more seasonality in column NO2 than anticyclonic conditions as they result in more extreme spatial departures from the wintertime seasonal average. Within a season (summer or winter) under different synoptic regimes, a large proportion of the spatial pattern in the UK column NO2 field can be explained by the idealised model tracers, showing that transport is an important factor in governing the variability of UK air quality on seasonal synoptic timescales.

Nationwide classification of forest types of India using remote sensing and GIS.

PubMed

Reddy, C Sudhakar; Jha, C S; Diwakar, P G; Dadhwal, V K

2015-12-01

India, a mega-diverse country, possesses a wide range of climate and vegetation types along with a varied topography. The present study has classified forest types of India based on multi-season IRS Resourcesat-2 Advanced Wide Field Sensor (AWiFS) data. The study has characterized 29 land use/land cover classes including 14 forest types and seven scrub types. Hybrid classification approach has been used for the classification of forest types. The classification of vegetation has been carried out based on the ecological rule bases followed by Champion and Seth's (1968) scheme of forest types in India. The present classification scheme has been compared with the available global and national level land cover products. The natural vegetation cover was estimated to be 29.36% of total geographical area of India. The predominant forest types of India are tropical dry deciduous and tropical moist deciduous. Of the total forest cover, tropical dry deciduous forests occupy an area of 2,17,713 km(2) (34.80%) followed by 2,07,649 km(2) (33.19%) under tropical moist deciduous forests, 48,295 km(2) (7.72%) under tropical semi-evergreen forests and 47,192 km(2) (7.54%) under tropical wet evergreen forests. The study has brought out a comprehensive vegetation cover and forest type maps based on inputs critical in defining the various categories of vegetation and forest types. This spatially explicit database will be highly useful for the studies related to changes in various forest types, carbon stocks, climate-vegetation modeling and biogeochemical cycles.

Neyman-Pearson classification algorithms and NP receiver operating characteristics

PubMed Central

Tong, Xin; Feng, Yang; Li, Jingyi Jessica

2018-01-01

In many binary classification applications, such as disease diagnosis and spam detection, practitioners commonly face the need to limit type I error (that is, the conditional probability of misclassifying a class 0 observation as class 1) so that it remains below a desired threshold. To address this need, the Neyman-Pearson (NP) classification paradigm is a natural choice; it minimizes type II error (that is, the conditional probability of misclassifying a class 1 observation as class 0) while enforcing an upper bound, α, on the type I error. Despite its century-long history in hypothesis testing, the NP paradigm has not been well recognized and implemented in classification schemes. Common practices that directly limit the empirical type I error to no more than α do not satisfy the type I error control objective because the resulting classifiers are likely to have type I errors much larger than α, and the NP paradigm has not been properly implemented in practice. We develop the first umbrella algorithm that implements the NP paradigm for all scoring-type classification methods, such as logistic regression, support vector machines, and random forests. Powered by this algorithm, we propose a novel graphical tool for NP classification methods: NP receiver operating characteristic (NP-ROC) bands motivated by the popular ROC curves. NP-ROC bands will help choose α in a data-adaptive way and compare different NP classifiers. We demonstrate the use and properties of the NP umbrella algorithm and NP-ROC bands, available in the R package nproc, through simulation and real data studies. PMID:29423442

Neyman-Pearson classification algorithms and NP receiver operating characteristics.

PubMed

Tong, Xin; Feng, Yang; Li, Jingyi Jessica

2018-02-01

In many binary classification applications, such as disease diagnosis and spam detection, practitioners commonly face the need to limit type I error (that is, the conditional probability of misclassifying a class 0 observation as class 1) so that it remains below a desired threshold. To address this need, the Neyman-Pearson (NP) classification paradigm is a natural choice; it minimizes type II error (that is, the conditional probability of misclassifying a class 1 observation as class 0) while enforcing an upper bound, α, on the type I error. Despite its century-long history in hypothesis testing, the NP paradigm has not been well recognized and implemented in classification schemes. Common practices that directly limit the empirical type I error to no more than α do not satisfy the type I error control objective because the resulting classifiers are likely to have type I errors much larger than α, and the NP paradigm has not been properly implemented in practice. We develop the first umbrella algorithm that implements the NP paradigm for all scoring-type classification methods, such as logistic regression, support vector machines, and random forests. Powered by this algorithm, we propose a novel graphical tool for NP classification methods: NP receiver operating characteristic (NP-ROC) bands motivated by the popular ROC curves. NP-ROC bands will help choose α in a data-adaptive way and compare different NP classifiers. We demonstrate the use and properties of the NP umbrella algorithm and NP-ROC bands, available in the R package nproc, through simulation and real data studies.

A new classification and treatment protocol for gynecomastia.

PubMed

Ratnam, B Venkata

2009-01-01

It is not uncommon to encounter patients who have undergone surgery for gynecomastia but who were not fully satisfied with the results. Although various approaches and techniques based on presurgical classification systems aimed at yielding the best possible surgical outcomes have been offered, standardized recommendation that is generally accepted by surgeons is lacking. The author reports on a new classification system and treatment protocol for the surgical treatment of gynecomastia. A system was developed that classifies patients into 3 types based on skin elasticity, presence of an inframammary fold (IMF), and mammary ptosis. Surgical excision of the breast mass was followed by a combination of destruction of the IMF, ultrasound-assisted lipoplasty (UAL) of the chest wall, ultrasound stimulation of the breast skin, and periareolar deepithelialization, depending on the gyneocomastia classification. This classification and the treatment protocol were applied to 30 patients, 13 to 60 years of age, between January 2005 and December 2007. Among these patients, 12 were classified as type 1, 6 as type 2, and 12 as type 3. Follow-up ranged from 3 to 18 months. Complications were common to all types of cases and techniques. They included 2 hematomas, 1 wound dehiscence, 5 cases of residual gynecomastia in those patients who underwent UAL alone, and 3 minor aesthetic problems near areolae. The proposed new classification and treatment protocol were found to help solve problems associated with surgical outcomes for all types of gynecomastia, although the issue of residual gynecomastia in patients undergoing UAL alone requires further study.

Multifocal humeral fractures.

PubMed

Maresca, A; Pascarella, R; Bettuzzi, C; Amendola, L; Politano, R; Fantasia, R; Del Torto, M

2014-02-01

Multifocal humeral fractures are extremely rare. These may affect the neck and the shaft, the shaft alone, or the diaphysis and the distal humerus. There is no classification of these fractures in the literature. From 2004 to 2010, 717 patients with humeral fracture were treated surgically at our department. Thirty-five patients presented with an associated fracture of the proximal and diaphyseal humerus: synthesis was performed with plate and screws in 34 patients, and the remaining patient had an open fracture that was treated with an external fixator. Mean follow-up was 3 years and 3 months. A classification is proposed in which type A fractures are those affecting the proximal and the humeral shaft, type B the diaphysis alone, and type C the diaphysis in association with the distal humerus. Type A fractures are then divided into three subgroups: A-I, undisplaced fracture of the proximal humerus and displaced shaft fracture; A-II: displaced fracture of the proximal and humeral shaft; and A-III: multifragmentary fracture affecting the proximal humerus and extending to the diaphysis. Multifocal humeral fractures are very rare and little described in the literature, both for classification and treatment. The AO classification describes bifocal fracture of the humeral diaphysis, type B and C. The classification suggested in this article mainly concerns fractures involving the proximal and humeral shaft. A simple classification of multifocal fractures is suggested to help the surgeon choose the most suitable type of synthesis for surgical treatment. Copyright © 2013 Elsevier Ltd. All rights reserved.

Vessel Classification in Cosmo-Skymed SAR Data Using Hierarchical Feature Selection

NASA Astrophysics Data System (ADS)

Makedonas, A.; Theoharatos, C.; Tsagaris, V.; Anastasopoulos, V.; Costicoglou, S.

2015-04-01

SAR based ship detection and classification are important elements of maritime monitoring applications. Recently, high-resolution SAR data have opened new possibilities to researchers for achieving improved classification results. In this work, a hierarchical vessel classification procedure is presented based on a robust feature extraction and selection scheme that utilizes scale, shape and texture features in a hierarchical way. Initially, different types of feature extraction algorithms are implemented in order to form the utilized feature pool, able to represent the structure, material, orientation and other vessel type characteristics. A two-stage hierarchical feature selection algorithm is utilized next in order to be able to discriminate effectively civilian vessels into three distinct types, in COSMO-SkyMed SAR images: cargos, small ships and tankers. In our analysis, scale and shape features are utilized in order to discriminate smaller types of vessels present in the available SAR data, or shape specific vessels. Then, the most informative texture and intensity features are incorporated in order to be able to better distinguish the civilian types with high accuracy. A feature selection procedure that utilizes heuristic measures based on features' statistical characteristics, followed by an exhaustive research with feature sets formed by the most qualified features is carried out, in order to discriminate the most appropriate combination of features for the final classification. In our analysis, five COSMO-SkyMed SAR data with 2.2m x 2.2m resolution were used to analyse the detailed characteristics of these types of ships. A total of 111 ships with available AIS data were used in the classification process. The experimental results show that this method has good performance in ship classification, with an overall accuracy reaching 83%. Further investigation of additional features and proper feature selection is currently in progress.

Weatherization Works II - Summary of Findings from the ARRA Period Evaluation of the U.S. Department of Energy's Weatherization Assistance Program

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

Tonn, Bruce Edward; Carroll, David; Rose, Erin M.

2015-10-01

This report presents a summary of the American Recovery and Reinvestment Act of 2009 (ARRA) evaluation of the U.S. Department of Energy s low-income Weatherization Program. This evaluation focused on the WAP Program Year 2010. The ARRA evaluation produced fourteen separate reports, including this summary. Three separate reports address the energy savings, energy cost savings, and cost effectiveness of WAP across four housing types: single family, mobile home, and large multifamily. Other reports address the environmental emissions benefits attributable to WAP, and characterize the program. Special studies were conducted to: estimate the impacts of weatherization and healthy homes interventions onmore » asthma-related Medicaid claims in a small cohort in Washington State; assess how weatherization recipients communicate their weatherization experiences to those in their social network, and assess processes implemented to defer homes for weatherization. Small studies addressed energy use in refrigerators, WAP as implemented in the U.S. territories for the first time, and weatherization s impacts on air conditioning energy savings. The national occupant survey was mined for additional insights on the impacts of weatherization on household budgets and energy behaviors post-weatherization. Lastly, the results of a survey of weatherization training centers are summarized.« less

The science of space weather.

PubMed

Eastwood, Jonathan P

2008-12-13

The basic physics underpinning space weather is reviewed, beginning with a brief overview of the main causes of variability in the near-Earth space environment. Although many plasma phenomena contribute to space weather, one of the most important is magnetic reconnection, and recent cutting edge research in this field is reviewed. We then place this research in context by discussing a number of specific types of space weather in more detail. As society inexorably increases its dependence on space, the necessity of predicting and mitigating space weather will become ever more acute. This requires a deep understanding of the complexities inherent in the plasmas that fill space and has prompted the development of a new generation of scientific space missions at the international level.

Classification of Children Intelligence with Fuzzy Logic Method

NASA Astrophysics Data System (ADS)

Syahminan; ika Hidayati, Permata

2018-04-01

Intelligence of children s An Important Thing To Know The Parents Early on. Typing Can be done With a Child’s intelligence Grouping Dominant Characteristics Of each Type of Intelligence. To Make it easier for Parents in Determining The type of Children’s intelligence And How to Overcome them, for It Created A Classification System Intelligence Grouping Children By Using Fuzzy logic method For determination Of a Child’s degree of intelligence type. From the analysis We concluded that The presence of Intelligence Classification systems Pendulum Children With Fuzzy Logic Method Of determining The type of The Child’s intelligence Can be Done in a way That is easier And The results More accurate Conclusions Than Manual tests.

Blind equalization and automatic modulation classification based on subspace for subcarrier MPSK optical communications

NASA Astrophysics Data System (ADS)

Chen, Dan; Guo, Lin-yuan; Wang, Chen-hao; Ke, Xi-zheng

2017-07-01

Equalization can compensate channel distortion caused by channel multipath effects, and effectively improve convergent of modulation constellation diagram in optical wireless system. In this paper, the subspace blind equalization algorithm is used to preprocess M-ary phase shift keying (MPSK) subcarrier modulation signal in receiver. Mountain clustering is adopted to get the clustering centers of MPSK modulation constellation diagram, and the modulation order is automatically identified through the k-nearest neighbor (KNN) classifier. The experiment has been done under four different weather conditions. Experimental results show that the convergent of constellation diagram is improved effectively after using the subspace blind equalization algorithm, which means that the accuracy of modulation recognition is increased. The correct recognition rate of 16PSK can be up to 85% in any kind of weather condition which is mentioned in paper. Meanwhile, the correct recognition rate is the highest in cloudy and the lowest in heavy rain condition.

Spatial Pattern Classification for More Accurate Forecasting of Variable Energy Resources

NASA Astrophysics Data System (ADS)

Novakovskaia, E.; Hayes, C.; Collier, C.

2014-12-01

The accuracy of solar and wind forecasts is becoming increasingly essential as grid operators continue to integrate additional renewable generation onto the electric grid. Forecast errors affect rate payers, grid operators, wind and solar plant maintenance crews and energy traders through increases in prices, project down time or lost revenue. While extensive and beneficial efforts were undertaken in recent years to improve physical weather models for a broad spectrum of applications these improvements have generally not been sufficient to meet the accuracy demands of system planners. For renewables, these models are often used in conjunction with additional statistical models utilizing both meteorological observations and the power generation data. Forecast accuracy can be dependent on specific weather regimes for a given location. To account for these dependencies it is important that parameterizations used in statistical models change as the regime changes. An automated tool, based on an artificial neural network model, has been developed to identify different weather regimes as they impact power output forecast accuracy at wind or solar farms. In this study, improvements in forecast accuracy were analyzed for varying time horizons for wind farms and utility-scale PV plants located in different geographical regions.

A climatology of weather-driven mixing events in a dimictic Arctic lake

NASA Astrophysics Data System (ADS)

Cooke, Melanie; MacIntyre, Sally; Kushner, Paul

2014-05-01

For dimictic and polymictic Arctic lakes, mixing during the ice-free season is primarily controlled by the passage of cold fronts and their associated strong winds. At Toolik Lake, a Long Term Ecological Research site in Alaska, year-to-year variability in lake stability and mixing frequency has been considerable over the past 14 summers. Mixing is important for lake productivity, distributing dissolved gases and nutrients through the water column. Summertime Arctic warming might be expected to stabilize Arctic lakes such as Toolik, but the control of individual weather events on a season's mixing characteristics complicates the ability to predict trends in stability and mixing. With this motivation, this work aims to characterize weather systems that are conducive to mixing at Toolik. High resolution lake and meteorological data from the site were used to characterize mixing while atmospheric reanalysis data were used to describe the weather systems. Mixing events were first identified using an automated algorithm based on Lake Number and lake thermal structure. The algorithm identified mixing events that are separated by at least the timescale of weather systems, so that any given weather event should cause at most one mixing event. Because low Lake Number conditions typically highlight strong wind events, temperature profile data over time were used to identify thermocline deepening as a complementary indicator for mixing. Mixing events were found to be most often characterized by simultaneous occurrence of a low Lake Number condition and thermocline deepening. Once mixing events were identified, they were classified according to their corresponding atmospheric structures. Two primary weather system types with distinct characteristics were determined to be associated with mixing. The analysis suggests that changing the occurrence of these weather system types might change the summertime thermal structure of Toolik Lake, and by extension other lakes in the region.

Weathering process in Sør Rondane Mountains, East Antarctica

NASA Astrophysics Data System (ADS)

Kanamaru, T.; Suganuma, Y.; Oiwane, H.; Miura, M.; Okuno, J.; Hayakawa, H.

2016-12-01

Weathering process under the hyper-arid and hypothermal environment is a key to understand the geomorphogic process and landscape evolution in Antarctica and on Mars. A nunber of studies have focused on weathering process of basaltic rocks in Antarctica, however, the nature of the weathering process of plutonic type rock, a common rock type on the Earth, have been less focused and remain unclear. Here, we report the physical/chemical weathering process of the granitic rocks obtained from Dronning Maud Land in East Antarctica based on a multiplicity of petrological approaches. Loss on Ignition (LOI) and major element composition of the crust and core of the rock samples indicate that chemical weathering process in this area seems to be very limited. The microscopic observations and laser-Raman micro spectroscopy for thin sections from the crust and core indicate that goethite grains are formed mainly in the vein around the crust, which is consistent with the higher Fe3+/Fe2+ contrast from the core to crust. A negative correlation between the rock hardness and color strength index (CSI) values also indicate that crust of rock samples tend to less hard than core due to cracking of the rock samples and following goethite formation. On the other hand, EPMA analysis indicates that original Fe-Ti oxide grains in the core of rock samples are damaged by weathering, and altered to hematite, and to non-stoichiometric Fe-Ti compound associated with ilmenite grans in case of the higher relative height samples. These reveal that the weathering process of the plutonic rocks under the hyper-cold and hypothermal environment are mainly controlled by oxidation, including iron hydroxide formation in the veins formed by mechanical distraction, and Fe-Ti oxide alteration in rock interior.

A hybrid approach to software repository retrieval: Blending faceted classification and type signatures

NASA Technical Reports Server (NTRS)

Eichmann, David A.

1992-01-01

We present a user interface for software reuse repository that relies both on the informal semantics of faceted classification and the formal semantics of type signatures for abstract data types. The result is an interface providing both structural and qualitative feedback to a software reuser.

ASIST SIG/CR Classification Workshop 2000: Classification for User Support and Learning.

ERIC Educational Resources Information Center

Soergel, Dagobert

2001-01-01

Reports on papers presented at the 62nd Annual Meeting of ASIST (American Society for Information Science and Technology) for the Special Interest Group in Classification Research (SIG/CR). Topics include types of knowledge; developing user-oriented classifications, including domain analysis; classification in the user interface; and automatic…

Basis of Criminalistic Classification of a Person in Republic Kazakhstan and Republic Mongolia

ERIC Educational Resources Information Center

Abdilov, Kanat S.; Zusbaev, Baurzan T.; Naurysbaev, Erlan A.; Nukiev, Berik A.; Nurkina, Zanar B.; Myrzahanov, Erlan N.; Urazalin, Galym T.

2016-01-01

In this article reviewed problems of the criminalistic classification building of a person. In the work were used legal formal, logical, comparative legal methods. The author describes classification kinds. Reveal the meaning of classification in criminalistic systematics. Shows types of grounds of criminalistic classification of a person.…

New Classification of Focal Cortical Dysplasia: Application to Practical Diagnosis

PubMed Central

Bae, Yoon-Sung; Kang, Hoon-Chul; Kim, Heung Dong; Kim, Se Hoon

2012-01-01

Background and Purpose: Malformation of cortical development (MCD) is a well-known cause of drug-resistant epilepsy and focal cortical dysplasia (FCD) is the most common neuropathological finding in surgical specimens from drug-resistant epilepsy patients. Palmini’s classification proposed in 2004 is now widely used to categorize FCD. Recently, however, Blumcke et al. recommended a new system for classifying FCD in 2011. Methods: We applied the new classification system in practical diagnosis of a sample of 117 patients who underwent neurosurgical operations due to drug-resistant epilepsy at Severance Hospital in Seoul, Korea. Results: Among 117 cases, a total of 16 cases were shifted to other FCD subtypes under the new classification system. Five cases were reclassified to type IIIa and five cases were categorized as dual pathology. The other six cases were changed within the type I category. Conclusions: The most remarkable changes in the new classification system are the advent of dual pathology and FCD type III. Thus, it will be very important for pathologists and clinicians to discriminate between these new categories. More large-scale research needs to be conducted to elucidate the clinical influence of the alterations within the classification of type I disease. Although the new FCD classification system has several advantages compared to the former, the correlation with clinical characteristics is not yet clear. PMID:24649461

Using Landsat MSS data with soils information to identify wetland habitats

NASA Technical Reports Server (NTRS)

Ernst, C. L.; Hoffer, R. M.

1981-01-01

A previous study showed that certain fresh water wetland vegetation types can be spectrally separated when a maximum likelihood classification procedure is applied to Landsat spectral data. However, wetland and upland types which have similar vegetative life forms (e.g., upland hardwoods and hardwood swamps) are often confused because of spectral similarity. Therefore, the current investigation attempts to differentiate similar wetland and upland types by combining Landsat multispectral scanner (MSS) data with soils information. The Pigeon River area in northern Indiana used in the earlier study was also employed in this investigation. A layered classification algorithm which combined soils and spectral data was used to generate a wetland classification. The results of the spectral/soils wetland classification are compared to the previous classification that had been based on spectral data alone. The results indicate wetland habitat mapping can be improved by combining soils and other ancillary data with Landsat spectral data.

Reflecting on the structure of soil classification systems: insights from a proposal for integrating subsoil data into soil information systems

NASA Astrophysics Data System (ADS)

Dondeyne, Stefaan; Juilleret, Jérôme; Vancampenhout, Karen; Deckers, Jozef; Hissler, Christophe

2017-04-01

Classification of soils in both World Reference Base for soil resources (WRB) and Soil Taxonomy hinges on the identification of diagnostic horizons and characteristics. However as these features often occur within the first 100 cm, these classification systems convey little information on subsoil characteristics. An integrated knowledge of the soil, soil-to-substratum and deeper substratum continuum is required when dealing with environmental issues such as vegetation ecology, water quality or the Critical Zone in general. Therefore, we recently proposed a classification system of the subsolum complementing current soil classification systems. By reflecting on the structure of the subsoil classification system which is inspired by WRB, we aim at fostering a discussion on some potential future developments of WRB. For classifying the subsolum we define Regolite, Saprolite, Saprock and Bedrock as four Subsolum Reference Groups each corresponding to different weathering stages of the subsoil. Principal qualifiers can be used to categorize intergrades of these Subsoil Reference Groups while morphologic and lithologic characteristics can be presented with supplementary qualifiers. We argue that adopting a low hierarchical structure - akin to WRB and in contrast to a strong hierarchical structure as in Soil Taxonomy - offers the advantage of having an open classification system avoiding the need for a priori knowledge of all possible combinations which may be encountered in the field. Just as in WRB we also propose to use principal and supplementary qualifiers as a second level of classification. However, in contrast to WRB we propose to reserve the principal qualifiers for intergrades and to regroup the supplementary qualifiers into thematic categories (morphologic or lithologic). Structuring the qualifiers in this manner should facilitate the integration and handling of both soil and subsoil classification units into soil information systems and calls for paying attention to these structural issues in future developments of WRB.

Potentially efficient forest and range applications of remote sensing using earth orbital space craft, circa 1980

NASA Technical Reports Server (NTRS)

Wilson, R. C.

1970-01-01

Sixteen remote sensing applications or groups of related applications judged to be most important of any in the forestry and range disciplines were evaluated. In one application, major land classification, large amounts of useful data are anticipated to be contributed by space sensors in 1980. In four applications moderate amounts are anticipated to be so contributed. These are timber inventory, range inventory, fire weather forecasting, and monitoring snowfields. In the following seven applications small but significant amounts of data are anticipated to be contributed by space sensors: (1) detailed land classification; (2) inventory of wildlife habitat; (3) recreation resource inventory; (4) detecting stresses on the vegetation (5) monitoring air pollution caused by wildfires and prescribed burning; (6) monitoring water cycle, (7) pollution and erosion; and (8) evaluating damage to forests and ranges.

A Climatic Classification for Citrus Winter Survival in China.

NASA Astrophysics Data System (ADS)

Shou, Bo Huang

1991-05-01

The citrus tree is susceptible to frost damage. Winter injury to citrus from freezing weather is the major meteorological problem in the northern pail of citrus growing regions in China. Based on meteorological data collected at 120 stations in southern China and on the extent of citrus freezing injury, five climatic regions for citrus winter survival in China were developed. They were: 1) no citrus tree injury. 2) light injury to mandarins (citrus reticulate) or moderate injury to oranges (citrus sinensis), 3) moderate injury to mandarins or heavy injury to oranges, 4) heavy injury to mandarins, and 5) impossible citrus tree growth. This citrus climatic classification was an attempt to provide guidelines for regulation of citrus production, to effectively utilize land and climatic resources, to chose suitable citrus varieties, and to develop methods to prevent injury by freezing.

The Colony meteorite and variations in CO3 chondrite properties

NASA Technical Reports Server (NTRS)

Rubin, A. E.; James, J. A.; Keck, B. D.; Weeks, K. S.; Sears, D. W. G.

1985-01-01

The Colony meteorite is one of the least equilibrated CO3 chondrites, yet differs from normal CO chondrites in that, while Al, Sc, V, Cr, Ir, Fe, Au, and Ga abundances are consistent with a CO chondrite classification, certain lithophile, siderophile, and chalcophile contents are depleted by factors of 10-40 percent. Colony is badly weathered, and its Fe, Ni abundance of about 19 wt pct is similar to that of the Kainsaz CO3 unweathered fall but higher than all other CO3 chondrites.

Remote sensing applications to forest vegetation classification and conifer vigor loss due to dwarf mistletoe

NASA Technical Reports Server (NTRS)

Douglass, R. W.; Meyer, M. P.; French, D. W.

1972-01-01

Criteria was established for practical remote sensing of vegetation stress and mortality caused by dwarf mistletoe infections in black spruce subboreal forest stands. The project was accomplished in two stages: (1) A fixed tower-tramway site in an infected black spruce stand was used for periodic multispectral photo coverage to establish basic film/filter/scale/season/weather parameters; (2) The photographic combinations suggested by the tower-tramway tests were used in low, medium, and high altitude aerial photography.

Fort Devens AAF, Massachusetts. Revised Uniform Summary of Surface Weather Observations (RUSSWO)

DTIC Science & Technology

1977-04-07

uaay oI Surlace Weatherj .>jObservations (RUSSWO) - Fort Devens AAL’, al 6.PRFOMIG.REOTNMR t- iassachusett s 6 EFRIGO EOTNME 7. AUTNOR(o) S. CONTRACT...for Fort Devens AAP, M’assachusetts contains the following parts: (A) heather Conditions; Atmospheric e-henoinena; (B) Precipitation, Snowfall and Snow...SEUIYCLASSIFICATION OF THIS PAGE (nohn Data Entered) %- - - - - .~~ -V- 2, SECURITY CLASSIFICATION OF THIS PAGE(W4 Dat. Rnteted) 19. ** Fort Devens AAF, M’ass4

Socializing the human factors analysis and classification system: incorporating social psychological phenomena into a human factors error classification system.

PubMed

Paletz, Susannah B F; Bearman, Christopher; Orasanu, Judith; Holbrook, Jon

2009-08-01

The presence of social psychological pressures on pilot decision making was assessed using qualitative analyses of critical incident interviews. Social psychological phenomena have long been known to influence attitudes and behavior but have not been highlighted in accident investigation models. Using a critical incident method, 28 pilots who flew in Alaska were interviewed. The participants were asked to describe a situation involving weather when they were pilot in command and found their skills challenged. They were asked to describe the incident in detail but were not explicitly asked to identify social pressures. Pressures were extracted from transcripts in a bottom-up manner and then clustered into themes. Of the 28 pilots, 16 described social psychological pressures on their decision making, specifically, informational social influence, the foot-in-the-door persuasion technique, normalization of deviance, and impression management and self-consistency motives. We believe accident and incident investigations can benefit from explicit inclusion of common social psychological pressures. We recommend specific ways of incorporating these pressures into theHuman Factors Analysis and Classification System.

The NWRA Classification Infrastructure: description and extension to the Discriminant Analysis Flare Forecasting System (DAFFS)

NASA Astrophysics Data System (ADS)

Leka, K. D.; Barnes, Graham; Wagner, Eric

2018-04-01

A classification infrastructure built upon Discriminant Analysis (DA) has been developed at NorthWest Research Associates for examining the statistical differences between samples of two known populations. Originating to examine the physical differences between flare-quiet and flare-imminent solar active regions, we describe herein some details of the infrastructure including: parametrization of large datasets, schemes for handling "null" and "bad" data in multi-parameter analysis, application of non-parametric multi-dimensional DA, an extension through Bayes' theorem to probabilistic classification, and methods invoked for evaluating classifier success. The classifier infrastructure is applicable to a wide range of scientific questions in solar physics. We demonstrate its application to the question of distinguishing flare-imminent from flare-quiet solar active regions, updating results from the original publications that were based on different data and much smaller sample sizes. Finally, as a demonstration of "Research to Operations" efforts in the space-weather forecasting context, we present the Discriminant Analysis Flare Forecasting System (DAFFS), a near-real-time operationally-running solar flare forecasting tool that was developed from the research-directed infrastructure.

Does the Weather Really Matter?

NASA Astrophysics Data System (ADS)

Burroughs, William James

1997-09-01

We talk about it endlessly, write about it copiously, and predict it badly. It influences what we do, what we wear, and how we live. Weather--how does it really impact our lives? In this compelling look at weather, author Burroughs combines historical perspective and economic and political analysis to give the impact of weather and climate change relevance and weight. He examines whether the frequency of extreme events is changing and the consequences of these changes. He looks at the chaotic nature of the climate and how this unpredictability can impose serious limits on how we plan for the future. Finally, he poses the important question: what types of serious, even less predictable changes are around the corner? In balanced and accessible prose, Burroughs works these issues into lucid analysis. This refreshing and insightful look at the impact of weather will appeal to anyone who has ever worried about forgetting an umbrella. William James Burroughs is the author of Watching the World's Weather (CUP, 1991) and Weather Cycles: Real or Imaginary? (CUP, 1994).

Classification bias in commercial business lists for retail food stores in the U.S.

PubMed

Han, Euna; Powell, Lisa M; Zenk, Shannon N; Rimkus, Leah; Ohri-Vachaspati, Punam; Chaloupka, Frank J

2012-04-18

Aspects of the food environment such as the availability of different types of food stores have recently emerged as key modifiable factors that may contribute to the increased prevalence of obesity. Given that many of these studies have derived their results based on secondary datasets and the relationship of food stores with individual weight outcomes has been reported to vary by store type, it is important to understand the extent to which often-used secondary data correctly classify food stores. We evaluated the classification bias of food stores in Dun & Bradstreet (D&B) and InfoUSA commercial business lists. We performed a full census in 274 randomly selected census tracts in the Chicago metropolitan area and collected detailed store attributes inside stores for classification. Store attributes were compared by classification match status and store type. Systematic classification bias by census tract characteristics was assessed in multivariate regression. D&B had a higher classification match rate than InfoUSA for supermarkets and grocery stores, while InfoUSA was higher for convenience stores. Both lists were more likely to correctly classify large supermarkets, grocery stores, and convenience stores with more cash registers and different types of service counters (supermarkets and grocery stores only). The likelihood of a correct classification match for supermarkets and grocery stores did not vary systemically by tract characteristics whereas convenience stores were more likely to be misclassified in predominately Black tracts. Researches can rely on classification of food stores in commercial datasets for supermarkets and grocery stores whereas classifications for convenience and specialty food stores are subject to some systematic bias by neighborhood racial/ethnic composition.

Classification bias in commercial business lists for retail food stores in the U.S.

PubMed Central

2012-01-01

Background Aspects of the food environment such as the availability of different types of food stores have recently emerged as key modifiable factors that may contribute to the increased prevalence of obesity. Given that many of these studies have derived their results based on secondary datasets and the relationship of food stores with individual weight outcomes has been reported to vary by store type, it is important to understand the extent to which often-used secondary data correctly classify food stores. We evaluated the classification bias of food stores in Dun & Bradstreet (D&B) and InfoUSA commercial business lists. Methods We performed a full census in 274 randomly selected census tracts in the Chicago metropolitan area and collected detailed store attributes inside stores for classification. Store attributes were compared by classification match status and store type. Systematic classification bias by census tract characteristics was assessed in multivariate regression. Results D&B had a higher classification match rate than InfoUSA for supermarkets and grocery stores, while InfoUSA was higher for convenience stores. Both lists were more likely to correctly classify large supermarkets, grocery stores, and convenience stores with more cash registers and different types of service counters (supermarkets and grocery stores only). The likelihood of a correct classification match for supermarkets and grocery stores did not vary systemically by tract characteristics whereas convenience stores were more likely to be misclassified in predominately Black tracts. Conclusion Researches can rely on classification of food stores in commercial datasets for supermarkets and grocery stores whereas classifications for convenience and specialty food stores are subject to some systematic bias by neighborhood racial/ethnic composition. PMID:22512874

Automated spectral classification and the GAIA project

NASA Technical Reports Server (NTRS)

Lasala, Jerry; Kurtz, Michael J.

1995-01-01

Two dimensional spectral types for each of the stars observed in the global astrometric interferometer for astrophysics (GAIA) mission would provide additional information for the galactic structure and stellar evolution studies, as well as helping in the identification of unusual objects and populations. The classification of the large quantity generated spectra requires that automated techniques are implemented. Approaches for the automatic classification are reviewed, and a metric-distance method is discussed. In tests, the metric-distance method produced spectral types with mean errors comparable to those of human classifiers working at similar resolution. Data and equipment requirements for an automated classification survey, are discussed. A program of auxiliary observations is proposed to yield spectral types and radial velocities for the GAIA-observed stars.

Commission 45: Spectral Classification

NASA Astrophysics Data System (ADS)

Giridhar, Sunetra; Gray, Richard O.; Corbally, Christopher J.; Bailer-Jones, Coryn A. L.; Eyer, Laurent; Irwin, Michael J.; Kirkpatrick, J. Davy; Majewski, Steven; Minniti, Dante; Nordström, Birgitta

This report gives an update of developments (since the last General Assembly at Prague) in the areas that are of relevance to the commission. In addition to numerous papers, a new monograph entitled Stellar Spectral Classification with Richard Gray and Chris Corbally as leading authors will be published by Princeton University Press as part of their Princeton Series in Astrophysics in April 2009. This book is an up-to-date and encyclopedic review of stellar spectral classification across the H-R diagram, including the traditional MK system in the blue-violet, recent extensions into the ultraviolet and infrared, the newly defined L-type and T-type spectral classes, as well as spectral classification of carbon stars, S-type stars, white dwarfs, novae, supernovae and Wolf-Rayet stars.

RISK MANAGEMENT RESEARCH PLAN FOR WET WEATHER FLOWS

EPA Science Inventory

This plan was prepared by the National Risk Management Research Laboratory (NRMRL) of EPA's Office of Research and Development (ORD) to guide the risk management aspects of the urban wet weather flow (WWF) research for the next five years. There are three types of urban WWF dis...

Quad-polarized synthetic aperture radar and multispectral data classification using classification and regression tree and support vector machine-based data fusion system

NASA Astrophysics Data System (ADS)

Bigdeli, Behnaz; Pahlavani, Parham

2017-01-01

Interpretation of synthetic aperture radar (SAR) data processing is difficult because the geometry and spectral range of SAR are different from optical imagery. Consequently, SAR imaging can be a complementary data to multispectral (MS) optical remote sensing techniques because it does not depend on solar illumination and weather conditions. This study presents a multisensor fusion of SAR and MS data based on the use of classification and regression tree (CART) and support vector machine (SVM) through a decision fusion system. First, different feature extraction strategies were applied on SAR and MS data to produce more spectral and textural information. To overcome the redundancy and correlation between features, an intrinsic dimension estimation method based on noise-whitened Harsanyi, Farrand, and Chang determines the proper dimension of the features. Then, principal component analysis and independent component analysis were utilized on stacked feature space of two data. Afterward, SVM and CART classified each reduced feature space. Finally, a fusion strategy was utilized to fuse the classification results. To show the effectiveness of the proposed methodology, single classification on each data was compared to the obtained results. A coregistered Radarsat-2 and WorldView-2 data set from San Francisco, USA, was available to examine the effectiveness of the proposed method. The results show that combinations of SAR data with optical sensor based on the proposed methodology improve the classification results for most of the classes. The proposed fusion method provided approximately 93.24% and 95.44% for two different areas of the data.

Building an organic computing device with multiple interconnected brains

PubMed Central

Pais-Vieira, Miguel; Chiuffa, Gabriela; Lebedev, Mikhail; Yadav, Amol; Nicolelis, Miguel A. L.

2015-01-01

Recently, we proposed that Brainets, i.e. networks formed by multiple animal brains, cooperating and exchanging information in real time through direct brain-to-brain interfaces, could provide the core of a new type of computing device: an organic computer. Here, we describe the first experimental demonstration of such a Brainet, built by interconnecting four adult rat brains. Brainets worked by concurrently recording the extracellular electrical activity generated by populations of cortical neurons distributed across multiple rats chronically implanted with multi-electrode arrays. Cortical neuronal activity was recorded and analyzed in real time, and then delivered to the somatosensory cortices of other animals that participated in the Brainet using intracortical microstimulation (ICMS). Using this approach, different Brainet architectures solved a number of useful computational problems, such as discrete classification, image processing, storage and retrieval of tactile information, and even weather forecasting. Brainets consistently performed at the same or higher levels than single rats in these tasks. Based on these findings, we propose that Brainets could be used to investigate animal social behaviors as well as a test bed for exploring the properties and potential applications of organic computers. PMID:26158615

An Examination of the Nature of Global MODIS Cloud Regimes

NASA Technical Reports Server (NTRS)

Oreopoulos, Lazaros; Cho, Nayeong; Lee, Dongmin; Kato, Seiji; Huffman, George J.

2014-01-01

We introduce global cloud regimes (previously also referred to as "weather states") derived from cloud retrievals that use measurements by the Moderate Resolution Imaging Spectroradiometer (MODIS) instrument aboard the Aqua and Terra satellites. The regimes are obtained by applying clustering analysis on joint histograms of retrieved cloud top pressure and cloud optical thickness. By employing a compositing approach on data sets from satellites and other sources, we examine regime structural and thermodynamical characteristics. We establish that the MODIS cloud regimes tend to form in distinct dynamical and thermodynamical environments and have diverse profiles of cloud fraction and water content. When compositing radiative fluxes from the Clouds and the Earth's Radiant Energy System instrument and surface precipitation from the Global Precipitation Climatology Project, we find that regimes with a radiative warming effect on the atmosphere also produce the largest implied latent heat. Taken as a whole, the results of the study corroborate the usefulness of the cloud regime concept, reaffirm the fundamental nature of the regimes as appropriate building blocks for cloud system classification, clarify their association with standard cloud types, and underscore their distinct radiative and hydrological signatures.

Corrosion Behavior of Weathering Steel Under Thin Electrolyte Layer at Different Relative Humidity

NASA Astrophysics Data System (ADS)

Xia, Yan; Liu, Pan; Zhang, Jianqing; Cao, Fahe

2018-01-01

The corrosion behavior of weathering steel under thin electrolyte layer (TEL) at different relative humidity (RH) was investigated by cathodic polarization, electrochemical impedance spectroscopy, electrochemical noise, SEM/EDS, XRD and Raman spectroscopy. The results indicate that during the initial stage, the corrosion rate increases as the RH decreases when the initial thickness of TEL is above 100 μm. During the middle and final corrosion stages, the corrosion behavior of weathering steel is influenced by RH, the initial thickness of TEL and corrosion product. The TEL corrosion is divided into three types, and a weathering steel corrosion model under TEL and bulk solution is also proposed.

Neuro-classification of multi-type Landsat Thematic Mapper data

NASA Technical Reports Server (NTRS)

Zhuang, Xin; Engel, Bernard A.; Fernandez, R. N.; Johannsen, Chris J.

1991-01-01

Neural networks have been successful in image classification and have shown potential for classifying remotely sensed data. This paper presents classifications of multitype Landsat Thematic Mapper (TM) data using neural networks. The Landsat TM Image for March 23, 1987 with accompanying ground observation data for a study area In Miami County, Indiana, U.S.A. was utilized to assess recognition of crop residues. Principal components and spectral ratio transformations were performed on the TM data. In addition, a layer of the geographic information system (GIS) for the study site was incorporated to generate GIS-enhanced TM data. This paper discusses (1) the performance of neuro-classification on each type of data, (2) how neural networks recognized each type of data as a new image and (3) comparisons of the results for each type of data obtained using neural networks, maximum likelihood, and minimum distance classifiers.

46 CFR 132.210 - Classification.

Code of Federal Regulations, 2011 CFR

2011-10-01

... 46 Shipping 4 2011-10-01 2011-10-01 false Classification. 132.210 Section 132.210 Shipping COAST... Portable and Semiportable Fire Extinguishers § 132.210 Classification. (a) Each portable fire extinguisher... Classification Type Size Halon 1211, 1301, and 1211-1301 mixtures kgs. (lbs.) Foam, liters (gallons) Carbon...

46 CFR 132.210 - Classification.

Code of Federal Regulations, 2014 CFR

2014-10-01

... 46 Shipping 4 2014-10-01 2014-10-01 false Classification. 132.210 Section 132.210 Shipping COAST... Portable and Semiportable Fire Extinguishers § 132.210 Classification. (a) Each portable fire extinguisher... Classification Type Size Halon 1211, 1301, and 1211-1301 mixtures kgs. (lbs.) Foam, liters (gallons) Carbon...

46 CFR 132.210 - Classification.

Code of Federal Regulations, 2012 CFR

2012-10-01

... 46 Shipping 4 2012-10-01 2012-10-01 false Classification. 132.210 Section 132.210 Shipping COAST... Portable and Semiportable Fire Extinguishers § 132.210 Classification. (a) Each portable fire extinguisher... Classification Type Size Halon 1211, 1301, and 1211-1301 mixtures kgs. (lbs.) Foam, liters (gallons) Carbon...

46 CFR 132.210 - Classification.

Code of Federal Regulations, 2013 CFR

2013-10-01

... 46 Shipping 4 2013-10-01 2013-10-01 false Classification. 132.210 Section 132.210 Shipping COAST... Portable and Semiportable Fire Extinguishers § 132.210 Classification. (a) Each portable fire extinguisher... Classification Type Size Halon 1211, 1301, and 1211-1301 mixtures kgs. (lbs.) Foam, liters (gallons) Carbon...

75 FR 54419 - Notice: Elimination of Expiration Dates for Classification Approvals

Federal Register 2010, 2011, 2012, 2013, 2014

2010-09-07

.... PHMSA-2010-0245; Notice No. 10-6] Notice: Elimination of Expiration Dates for Classification Approvals... 2005, PHMSA initiated a policy imposing a 5-year expiration date on firework classification approvals... include all types of classification approvals, including explosives, oxidizing substances, organic...

46 CFR 132.210 - Classification.

Code of Federal Regulations, 2010 CFR

2010-10-01

... 46 Shipping 4 2010-10-01 2010-10-01 false Classification. 132.210 Section 132.210 Shipping COAST... Portable and Semiportable Fire Extinguishers § 132.210 Classification. (a) Each portable fire extinguisher... Classification Type Size Halon 1211, 1301, and 1211-1301 mixtures kgs. (lbs.) Foam, liters (gallons) Carbon...

33 CFR 145.05 - Classification of fire extinguishers.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 33 Navigation and Navigable Waters 2 2011-07-01 2011-07-01 false Classification of fire... SECURITY (CONTINUED) OUTER CONTINENTAL SHELF ACTIVITIES FIRE-FIGHTING EQUIPMENT § 145.05 Classification of....05(c)—Portable and Semiportable Extinguishers Classification Type Size Soda-acid and water, gallons...

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

NASA Astrophysics Data System (ADS)

Subramanian, Aneesh C.; Palmer, Tim N.

2017-06-01

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