WorldWideScience

Sample records for winter months model

  1. Forecasting and Analysis of Monthly Rainfalls in Ardabil Province by Arima, Autoregrressive, and Winters Models

    Directory of Open Access Journals (Sweden)

    B. Salahi

    2017-01-01

    Full Text Available Introduction: Rainfall has the highest variability at time and place scale. Rainfall fluctuation in different geographical areas reveals the necessity of investigating this climate element and suitable models to forecast the rate of precipitation for regional planning. Ardabil province has always faced rainfall fluctuations and shortage of water supply. Precipitation is one of the most important features of the environment. The amount of precipitation over time and in different places is subject to large fluctuations which may be periodical. Studies show that, due to the certain complexities of rainfall, the models which used to predict future values will also need greater accuracy and less error. Among the forecasting models, Arima has more applications and it has replaced with other models. Materials and Methods: In this research, through order 2 Autoregrressive, Winters, and Arima models, monthly rainfalls of Ardabil synoptic station (representing Ardabil province for a 31-year period (1977-2007 were investigated. To assess the presence or absence of significant changes in mean precipitation of Ardabil synoptic station, rainfall of this station was divided into two periods: 1977-1993 and 1994-2010. T-test was used to statistically examine the difference between the two periods. After adjusting the data, descriptive statistics were applied. In order to model the total monthly precipitation of Ardabil synoptic station, Winters, Autoregressive, and Arima models were used. Among different models, the best options were chosen to predict the time series including the mean absolute deviation (MAD, the mean squared errors (MSE, root mean square errors (RMSE and mean absolute percentage errors (MAPE. In order to select the best model among the available options under investigation, the predicted value of the deviation of the actual value was utilized for the months of 2006-2010. Results and Discussion: Statistical characteristics of the total monthly

  2. Characterizing and predicting ultrafine particle counts in Canadian classrooms during the winter months: model development and evaluation.

    Science.gov (United States)

    Weichenthal, Scott; Dufresne, André; Infante-Rivard, Claire; Joseph, Lawrence

    2008-03-01

    School classrooms are potentially important micro-environments for childhood exposures owing to the large amount of time children spend in these locations. While a number of airborne contaminants may be present in schools, to date few studies have examined ultrafine particle (0.02-1 microm) (UFP) levels in classrooms. In this study, our objective was to characterize UFP counts (cm(-3)) in classrooms during the winter months and to develop a model to predict such exposures based on ambient weather conditions and outdoor UFPs, as well as classroom characteristics such as size, temperature, relative humidity, and carbon dioxide levels. In total, UFP count data were collected on 60 occasions in 37 occupied classrooms at one elementary school and one secondary school in Pembroke, Ontario. On average, outdoor UFP levels exceeded indoor measures by 8989 cm(-3) (95% confidence interval (CI): 6382, 11596), and classroom UFP counts were similar at both schools with a combined average of 5017 cm(-3) (95% CI: 4300, 5734). Of the variables examined only wind speed and outdoor UFPs were important determinants of classrooms UFP levels. Specifically, each 10 km/h increase in wind speed corresponded to an 1873 cm(-3) (95% CI: 825, 2920) decrease in classroom UFP counts, and each 10000 cm(-3) increase in outdoor UFPs corresponded to a 1550 cm(-3) (95% CI: 930, 2171) increase in classroom UFP levels. However, high correlations between these two predictors meant that the independent effects of wind speed and outdoor UFPs could not be separated in multivariable models, and only outdoor UFP counts were included in the final predictive model. To evaluate model performance, classroom UFP counts were collected for 8 days at two new schools and compared to predicted values based on outdoor UFP measures. A moderate correlation was observed between measured and predicted classroom UFP counts (r=0.63) for both schools combined, but this relationship was not valid on days in which a strong

  3. Characterizing and predicting ultrafine particle counts in Canadian classrooms during the winter months: Model development and evaluation

    International Nuclear Information System (INIS)

    Weichenthal, Scott; Dufresne, Andre; Infante-Rivard, Claire; Joseph, Lawrence

    2008-01-01

    School classrooms are potentially important micro-environments for childhood exposures owing to the large amount of time children spend in these locations. While a number of airborne contaminants may be present in schools, to date few studies have examined ultrafine particle (0.02-1 μm) (UFP) levels in classrooms. In this study, our objective was to characterize UFP counts (cm -3 ) in classrooms during the winter months and to develop a model to predict such exposures based on ambient weather conditions and outdoor UFPs, as well as classroom characteristics such as size, temperature, relative humidity, and carbon dioxide levels. In total, UFP count data were collected on 60 occasions in 37 occupied classrooms at one elementary school and one secondary school in Pembroke, Ontario. On average, outdoor UFP levels exceeded indoor measures by 8989 cm -3 (95% confidence interval (CI): 6382, 11 596), and classroom UFP counts were similar at both schools with a combined average of 5017 cm -3 (95% CI: 4300, 5734). Of the variables examined only wind speed and outdoor UFPs were important determinants of classrooms UFP levels. Specifically, each 10 km/h increase in wind speed corresponded to an 1873 cm -3 (95% CI: 825, 2920) decrease in classroom UFP counts, and each 10 000 cm -3 increase in outdoor UFPs corresponded to a 1550 cm -3 (95% CI: 930, 2171) increase in classroom UFP levels. However, high correlations between these two predictors meant that the independent effects of wind speed and outdoor UFPs could not be separated in multivariable models, and only outdoor UFP counts were included in the final predictive model. To evaluate model performance, classroom UFP counts were collected for 8 days at two new schools and compared to predicted values based on outdoor UFP measures. A moderate correlation was observed between measured and predicted classroom UFP counts (r=0.63) for both schools combined, but this relationship was not valid on days in which a strong indoor UFP

  4. Incorporating Yearly Derived Winter Wheat Maps Into Winter Wheat Yield Forecasting Model

    Science.gov (United States)

    Skakun, S.; Franch, B.; Roger, J.-C.; Vermote, E.; Becker-Reshef, I.; Justice, C.; Santamaría-Artigas, A.

    2016-01-01

    Wheat is one of the most important cereal crops in the world. Timely and accurate forecast of wheat yield and production at global scale is vital in implementing food security policy. Becker-Reshef et al. (2010) developed a generalized empirical model for forecasting winter wheat production using remote sensing data and official statistics. This model was implemented using static wheat maps. In this paper, we analyze the impact of incorporating yearly wheat masks into the forecasting model. We propose a new approach of producing in season winter wheat maps exploiting satellite data and official statistics on crop area only. Validation on independent data showed that the proposed approach reached 6% to 23% of omission error and 10% to 16% of commission error when mapping winter wheat 2-3 months before harvest. In general, we found a limited impact of using yearly winter wheat masks over a static mask for the study regions.

  5. Talent identification and deliberate programming in skeleton: ice novice to Winter Olympian in 14 months.

    Science.gov (United States)

    Bullock, Nicola; Gulbin, Jason P; Martin, David T; Ross, Angus; Holland, Terry; Marino, Frank

    2009-02-15

    The aims of this study were to talent transfer, rapidly develop, and qualify an Australian female athlete in the skeleton event at the 2006 Torino Winter Olympic Games and quantify the volume of skeleton-specific training and competition that would enable this to be achieved. Initially, 26 athletes were recruited through a talent identification programme based on their 30-m sprint time. After attending a selection camp, 10 athletes were invited to undertake an intensified skeleton training programme. Four of these athletes were then selected to compete for Australia on the World Cup circuit. All completed runs and simulated push starts were documented over a 14-month period. The athlete who eventually represented Australia at the Torino Winter Olympic Games did so following approximately 300 start simulations and about 220 training/competition runs over a period of 14 months. Using a deliberate programming model, these findings provide a guide to the minimum exposure required for a novice skeleton athlete to reach Olympic representative standard following intensified sport-specific training. The findings of this study are discussed in the context of the deliberate practice theory and offer the term "deliberate programming" as an alternative way of incorporating all aspects of expert development.

  6. Risk management model of winter navigation operations

    International Nuclear Information System (INIS)

    Valdez Banda, Osiris A.; Goerlandt, Floris; Kuzmin, Vladimir; Kujala, Pentti; Montewka, Jakub

    2016-01-01

    The wintertime maritime traffic operations in the Gulf of Finland are managed through the Finnish–Swedish Winter Navigation System. This establishes the requirements and limitations for the vessels navigating when ice covers this area. During winter navigation in the Gulf of Finland, the largest risk stems from accidental ship collisions which may also trigger oil spills. In this article, a model for managing the risk of winter navigation operations is presented. The model analyses the probability of oil spills derived from collisions involving oil tanker vessels and other vessel types. The model structure is based on the steps provided in the Formal Safety Assessment (FSA) by the International Maritime Organization (IMO) and adapted into a Bayesian Network model. The results indicate that ship independent navigation and convoys are the operations with higher probability of oil spills. Minor spills are most probable, while major oil spills found very unlikely but possible. - Highlights: •A model to assess and manage the risk of winter navigation operations is proposed. •The risks of oil spills in winter navigation in the Gulf of Finland are analysed. •The model assesses and prioritizes actions to control the risk of the operations. •The model suggests navigational training as the most efficient risk control option.

  7. Probability of occurrence of monthly and seasonal winter precipitation over Northwest India based on antecedent-monthly precipitation

    Science.gov (United States)

    Nageswararao, M. M.; Mohanty, U. C.; Dimri, A. P.; Osuri, Krishna K.

    2018-05-01

    Winter (December, January, and February (DJF)) precipitation over northwest India (NWI) is mainly associated with the eastward moving mid-latitude synoptic systems, western disturbances (WDs), embedded within the subtropical westerly jet (SWJ), and is crucial for Rabi (DJF) crops. In this study, the role of winter precipitation at seasonal and monthly scale over NWI and its nine meteorological subdivisions has been analyzed. High-resolution (0.25° × 0.25°) gridded precipitation data set of India Meteorological Department (IMD) for the period of 1901-2013 is used. Results indicated that the seasonal precipitation over NWI is below (above) the long-term mean in most of the years, when precipitation in any of the month (December/January/February) is in deficit (excess). The contribution of December precipitation (15-20%) to the seasonal (DJF) precipitation is lesser than January (35-40%) and February (35-50%) over all the subdivisions. December (0.60), January (0.57), and February (0.69) precipitation is in-phase (correlation) with the corresponding winter season precipitation. However, January precipitation is not in-phase with the corresponding December (0.083) and February (-0.03) precipitation, while December is in-phase with the February (0.21). When monthly precipitation (December or January or December-January or February) at subdivision level over NWI is excess (deficit); then, the probability of occurrence of seasonal excess (deficit) precipitation is high (almost nil). When antecedent-monthly precipitation is a deficit or excess, the probability of monthly (January or February or January + February) precipitation to be a normal category is >60% over all the subdivisions. This study concludes that the December precipitation is a good indicator to estimate the performance of January, February, January-February, and the seasonal (DJF) precipitation.

  8. Neurosensory and vascular function after 14 months of military training comprising cold winter conditions.

    Science.gov (United States)

    Carlsson, Daniel; Pettersson, Hans; Burström, Lage; Nilsson, Tohr; Wahlström, Jens

    2016-01-01

    This study aimed to examine the effects of 14 months of military training comprising cold winter conditions on neurosensory and vascular function in the hands and feet. Military conscripts (N=54) were assessed with quantitative sensory testing comprising touch, temperature, and vibration perception thresholds and finger systolic blood pressure (FSBP) after local cooling and a questionnaire on neurosensory and vascular symptoms at both baseline and follow-up. Ambient air temperature was recorded with body worn temperature loggers. The subjects showed reduced sensitivity to perception of touch, warmth, cold and vibrations in both the hands and feet except from vibrotactile perception in digit two of the right hand (right dig 2). Cold sensations, white fingers, and pain/discomfort when exposed to cold as well as pain increased in both prevalence and severity. There were no statistically significant changes in FSBP after local cooling. Fourteen months of winter military training comprising cold winter conditions reduced sensation from touch, warmth, cold, and vibrotactile stimulus in both hands and feet and increased the severity and prevalence of symptoms and pain. The vascular function in the hands, measured by FSBP after local cooling, was not affected.

  9. Comparison of Performance Measurements of Photovoltaic Modules during Winter Months in Taxila, Pakistan

    Directory of Open Access Journals (Sweden)

    Muhammad Anser Bashir

    2014-01-01

    Full Text Available This paper presents the comparative performance evaluation of three commercially available photovoltaic modules (monocrystalline, polycrystalline, and single junction amorphous silicon in Taxila, Pakistan. The experimentation was carried out at outdoor conditions for winter months. Power output, module efficiency, and performance ratio were calculated for each module and the effect of module temperature and solar irradiance on these parameters was investigated. Module parameters showed strong dependence on the solar irradiance and module temperature. Monocrystalline and polycrystalline modules showed better performance in high irradiance condition whereas it decreased suddenly with decrease in irradiance. Amorphous solar module also showed good performance in low irradiance due to its better light absorbing characteristics and thus showed higher average performance ratio. Monocrystalline photovoltaic module showed higher monthly average module efficiency and was found to be more efficient at this site. Module efficiency and performance ratio showed a decreasing trend with increase of irradiance and photovoltaic module back surface temperature.

  10. Modeling winter moth Operophtera brumata egg phenology

    NARCIS (Netherlands)

    Salis, Lucia; Lof, Marjolein; Asch, van Margriet; Visser, Marcel E.

    2016-01-01

    Understanding the relationship between an insect's developmental rate and temperature is crucial to forecast insect phenology under climate change. In the winter moth Operophtera brumata timing of egg-hatching has severe fitness consequences on growth and reproduction as egg-hatching has to match

  11. High resolution reconstruction of monthly autumn and winter precipitation of Iberian Peninsula for last 150 years.

    Science.gov (United States)

    Cortesi, N.; Trigo, R.; González-Hidalgo, J. C.; Ramos, A.

    2012-04-01

    Precipitation over Iberian Peninsula (IP) presents large values of interannual variability and large spatial contrasts between wet mountainous regions in the north and dry regions in the southern plains. Unlike other European regions, IP was poorly monitored for precipitation during 19th century. Here we present a new approach to fill this gap. A set of 26 atmospheric circulation weather types (Trigo R.M. and DaCamara C.C., 2000) derived from a recent SLP dataset, the EMULATE (European and North Atlantic daily to multidecadal climate variability) Project, was used to reconstruct Iberian monthly precipitation from October to March during 1851-1947. Principal Component Regression Analysis was chosen to develop monthly precipitation reconstruction back to 1851 and calibrated over 1948-2003 period for 3030 monthly precipitation series of high-density homogenized MOPREDAS (Monthly Precipitation Database for Spain and Portugal) database. Validation was conducted over 1920-1947 at 15 key site locations. Results show high model performance for selected months, with a mean coefficient of variation (CV) around 0.6 during validation period. Lower CV values were achieved in western area of IP. Trigo, R. M., and DaCamara, C.C., 2000: "Circulation weather types and their impact on the precipitation regime in Portugal". Int. J. Climatol., 20, 1559-1581.

  12. Yearly, seasonal and monthly daily average diffuse sky radiation models

    International Nuclear Information System (INIS)

    Kassem, A.S.; Mujahid, A.M.; Turner, D.W.

    1993-01-01

    A daily average diffuse sky radiation regression model based on daily global radiation was developed utilizing two year data taken near Blytheville, Arkansas (Lat. =35.9 0 N, Long. = 89.9 0 W), U.S.A. The model has a determination coefficient of 0.91 and 0.092 standard error of estimate. The data were also analyzed for a seasonal dependence and four seasonal average daily models were developed for the spring, summer, fall and winter seasons. The coefficient of determination is 0.93, 0.81, 0.94 and 0.93, whereas the standard error of estimate is 0.08, 0.102, 0.042 and 0.075 for spring, summer, fall and winter, respectively. A monthly average daily diffuse sky radiation model was also developed. The coefficient of determination is 0.92 and the standard error of estimate is 0.083. A seasonal monthly average model was also developed which has 0.91 coefficient of determination and 0.085 standard error of estimate. The developed monthly daily average and daily models compare well with a selected number of previously developed models. (author). 11 ref., figs., tabs

  13. A stepwise model to predict monthly streamflow

    Science.gov (United States)

    Mahmood Al-Juboori, Anas; Guven, Aytac

    2016-12-01

    In this study, a stepwise model empowered with genetic programming is developed to predict the monthly flows of Hurman River in Turkey and Diyalah and Lesser Zab Rivers in Iraq. The model divides the monthly flow data to twelve intervals representing the number of months in a year. The flow of a month, t is considered as a function of the antecedent month's flow (t - 1) and it is predicted by multiplying the antecedent monthly flow by a constant value called K. The optimum value of K is obtained by a stepwise procedure which employs Gene Expression Programming (GEP) and Nonlinear Generalized Reduced Gradient Optimization (NGRGO) as alternative to traditional nonlinear regression technique. The degree of determination and root mean squared error are used to evaluate the performance of the proposed models. The results of the proposed model are compared with the conventional Markovian and Auto Regressive Integrated Moving Average (ARIMA) models based on observed monthly flow data. The comparison results based on five different statistic measures show that the proposed stepwise model performed better than Markovian model and ARIMA model. The R2 values of the proposed model range between 0.81 and 0.92 for the three rivers in this study.

  14. Longitude-dependent decadal ozone changes and ozone trends in boreal winter months during 1960–2000

    Directory of Open Access Journals (Sweden)

    D. H. W. Peters

    2008-05-01

    Full Text Available This study examines the longitude-dependent decadal changes and trends of ozone for the boreal winter months during the period of 1960–2000. These changes are caused primarily by changes in the planetary wave structure in the upper troposphere and lower stratosphere. The decadal changes and trends over 4 decades of geopotential perturbations, defined as a deviation from the zonal mean, are estimated by linear regression with time. The decadal changes in longitude-dependent ozone were calculated with a simple transport model of ozone based on the known planetary wave structure changes and prescribed zonal mean ozone gradients. For December of the 1960s and 1980s a statistically significant Rossby wave track appeared over the North Atlantic and Europe with an anticyclonic disturbance over the Eastern North Atlantic and Western Europe, flanked by cyclonic disturbances. In the 1970s and 1990s statistically significant cyclonic disturbances appeared over the Eastern North Atlantic and Europe, surrounded by anticyclonic anomalies over Northern Africa, Central Asia and Greenland. Similar patterns have been found for January. The Rossby wave track over the North Atlantic and Europe is stronger in the 1980s than in the 1960s. For February, the variability of the regression patterns is higher. For January we found a strong alteration in the modelled decadal changes in total ozone over Central and Northern Europe, showing a decrease of about 15 DU in the 1960s and 1980s and an increase of about 10 DU in the 1970s and 1990s. Over Central Europe the positive geopotential height trend (increase of 2.3 m/yr over 40 years is of the same order (about 100 m as the increase in the 1980s alone. This is important to recognize because it implies a total ozone decrease over Europe of the order of 14 DU for the 1960–2000 period, for January, if we use the standard change regression relation that about a 10-m geopotential height increase at 300 hPa is related to

  15. Representation of Northern Hemisphere winter storm tracks in climate models

    Energy Technology Data Exchange (ETDEWEB)

    Greeves, C.Z.; Pope, V.D.; Stratton, R.A.; Martin, G.M. [Met Office Hadley Centre for Climate Prediction and Research, Exeter (United Kingdom)

    2007-06-15

    Northern Hemisphere winter storm tracks are a key element of the winter weather and climate at mid-latitudes. Before projections of climate change are made for these regions, it is necessary to be sure that climate models are able to reproduce the main features of observed storm tracks. The simulated storm tracks are assessed for a variety of Hadley Centre models and are shown to be well modelled on the whole. The atmosphere-only model with the semi-Lagrangian dynamical core produces generally more realistic storm tracks than the model with the Eulerian dynamical core, provided the horizontal resolution is high enough. The two models respond in different ways to changes in horizontal resolution: the model with the semi-Lagrangian dynamical core has much reduced frequency and strength of cyclonic features at lower resolution due to reduced transient eddy kinetic energy. The model with Eulerian dynamical core displays much smaller changes in frequency and strength of features with changes in horizontal resolution, but the location of the storm tracks as well as secondary development are sensitive to resolution. Coupling the atmosphere-only model (with semi-Lagrangian dynamical core) to an ocean model seems to affect the storm tracks largely via errors in the tropical representation. For instance a cold SST bias in the Pacific and a lack of ENSO variability lead to large changes in the Pacific storm track. Extratropical SST biases appear to have a more localised effect on the storm tracks. (orig.)

  16. Modelling seasonal effects of temperature and precipitation on honey bee winter mortality in a temperate climate.

    Science.gov (United States)

    Switanek, Matthew; Crailsheim, Karl; Truhetz, Heimo; Brodschneider, Robert

    2017-02-01

    Insect pollinators are essential to global food production. For this reason, it is alarming that honey bee (Apis mellifera) populations across the world have recently seen increased rates of mortality. These changes in colony mortality are often ascribed to one or more factors including parasites, diseases, pesticides, nutrition, habitat dynamics, weather and/or climate. However, the effect of climate on colony mortality has never been demonstrated. Therefore, in this study, we focus on longer-term weather conditions and/or climate's influence on honey bee winter mortality rates across Austria. Statistical correlations between monthly climate variables and winter mortality rates were investigated. Our results indicate that warmer and drier weather conditions in the preceding year were accompanied by increased winter mortality. We subsequently built a statistical model to predict colony mortality using temperature and precipitation data as predictors. Our model reduces the mean absolute error between predicted and observed colony mortalities by 9% and is statistically significant at the 99.9% confidence level. This is the first study to show clear evidence of a link between climate variability and honey bee winter mortality. Copyright © 2016 British Geological Survey, NERC. Published by Elsevier B.V. All rights reserved.

  17. Clustering of European winter storms: A multi-model perspective

    Science.gov (United States)

    Renggli, Dominik; Buettner, Annemarie; Scherb, Anke; Straub, Daniel; Zimmerli, Peter

    2016-04-01

    The storm series over Europe in 1990 (Daria, Vivian, Wiebke, Herta) and 1999 (Anatol, Lothar, Martin) are very well known. Such clusters of severe events strongly affect the seasonally accumulated damage statistics. The (re)insurance industry has quantified clustering by using distribution assumptions deduced from the historical storm activity of the last 30 to 40 years. The use of storm series simulated by climate models has only started recently. Climate model runs can potentially represent 100s to 1000s of years, allowing a more detailed quantification of clustering than the history of the last few decades. However, it is unknown how sensitive the representation of clustering is to systematic biases. Using a multi-model ensemble allows quantifying that uncertainty. This work uses CMIP5 decadal ensemble hindcasts to study clustering of European winter storms from a multi-model perspective. An objective identification algorithm extracts winter storms (September to April) in the gridded 6-hourly wind data. Since the skill of European storm predictions is very limited on the decadal scale, the different hindcast runs are interpreted as independent realizations. As a consequence, the available hindcast ensemble represents several 1000 simulated storm seasons. The seasonal clustering of winter storms is quantified using the dispersion coefficient. The benchmark for the decadal prediction models is the 20th Century Reanalysis. The decadal prediction models are able to reproduce typical features of the clustering characteristics observed in the reanalysis data. Clustering occurs in all analyzed models over the North Atlantic and European region, in particular over Great Britain and Scandinavia as well as over Iberia (i.e. the exit regions of the North Atlantic storm track). Clustering is generally weaker in the models compared to reanalysis, although the differences between different models are substantial. In contrast to existing studies, clustering is driven by weak

  18. Sea surface salinity and temperature-based predictive modeling of southwestern US winter precipitation: improvements, errors, and potential mechanisms

    Science.gov (United States)

    Liu, T.; Schmitt, R. W.; Li, L.

    2017-12-01

    Using 69 years of historical data from 1948-2017, we developed a method to globally search for sea surface salinity (SSS) and temperature (SST) predictors of regional terrestrial precipitation. We then applied this method to build an autumn (SON) SSS and SST-based 3-month lead predictive model of winter (DJF) precipitation in southwestern United States. We also find that SSS-only models perform better than SST-only models. We previously used an arbitrary correlation coefficient (r) threshold, |r| > 0.25, to define SSS and SST predictor polygons for best subset regression of southwestern US winter precipitation; from preliminary sensitivity tests, we find that |r| > 0.18 yields the best models. The observed below-average precipitation (0.69 mm/day) in winter 2015-2016 falls within the 95% confidence interval of the prediction model. However, the model underestimates the anomalous high precipitation (1.78 mm/day) in winter 2016-2017 by more than three-fold. Moisture transport mainly attributed to "pineapple express" atmospheric rivers (ARs) in winter 2016-2017 suggests that the model falls short on a sub-seasonal scale, in which case storms from ARs contribute a significant portion of seasonal terrestrial precipitation. Further, we identify a potential mechanism for long-range SSS and precipitation teleconnections: standing Rossby waves. The heat applied to the atmosphere from anomalous tropical rainfall can generate standing Rossby waves that propagate to higher latitudes. SSS anomalies may be indicative of anomalous tropical rainfall, and by extension, standing Rossby waves that provide the long-range teleconnections.

  19. A global analysis of the comparability of winter chill models for fruit and nut trees.

    Science.gov (United States)

    Luedeling, Eike; Brown, Patrick H

    2011-05-01

    Many fruit and nut trees must fulfill a chilling requirement to break their winter dormancy and resume normal growth in spring. Several models exist for quantifying winter chill, and growers and researchers often tacitly assume that the choice of model is not important and estimates of species chilling requirements are valid across growing regions. To test this assumption, Safe Winter Chill (the amount of winter chill that is exceeded in 90% of years) was calculated for 5,078 weather stations around the world, using the Dynamic Model [in Chill Portions (CP)], the Chilling Hours (CH) Model and the Utah Model [Utah Chill Units (UCU)]. Distributions of the ratios between different winter chill metrics were mapped on a global scale. These ratios should be constant if the models were strictly proportional. Ratios between winter chill metrics varied substantially, with the CH/CP ratio ranging between 0 and 34, the UCU/CP ratio between -155 and +20 and the UCU/CH ratio between -10 and +5. The models are thus not proportional, and chilling requirements determined in a given location may not be valid elsewhere. The Utah Model produced negative winter chill totals in many Subtropical regions, where it does not seem to be useful. Mean annual temperature and daily temperature range influenced all winter chill ratios, but explained only between 12 and 27% of the variation. Data on chilling requirements should always be amended with information on the location and experimental conditions of the study in which they were determined, ideally including site-specific conversion factors between winter chill models. This would greatly facilitate the transfer of such information across growing regions, and help prepare growers for the impact of climate change.

  20. Winter wheat response to irrigation, nitrogen fertilization, and cold hazards in the Community Land Model 5

    Science.gov (United States)

    Lu, Y.

    2017-12-01

    Winter wheat is a staple crop for global food security, and is the dominant vegetation cover for a significant fraction of earth's croplands. As such, it plays an important role in soil carbon balance, and land-atmosphere interactions in these key regions. Accurate simulation of winter wheat growth is not only crucial for future yield prediction under changing climate, but also for understanding the energy and water cycles for winter wheat dominated regions. A winter wheat growth model has been developed in the Community Land Model 4.5 (CLM4.5), but its responses to irrigation and nitrogen fertilization have not been validated. In this study, I will validate winter wheat growth response to irrigation and nitrogen fertilization at five winter wheat field sites (TXLU, KSMA, NESA, NDMA, and ABLE) in North America, which were originally designed to understand winter wheat response to nitrogen fertilization and water treatments (4 nitrogen levels and 3 irrigation regimes). I also plan to further update the linkages between winter wheat yield and cold hazards. The previous cold damage function only indirectly affects yield through reduction on leaf area index (LAI) and hence photosynthesis, such approach could sometimes produce an unwanted higher yield when the reduced LAI saved more nutrient in the grain fill stage.

  1. Development of a model system to identify differences in spring and winter oat.

    Science.gov (United States)

    Chawade, Aakash; Lindén, Pernilla; Bräutigam, Marcus; Jonsson, Rickard; Jonsson, Anders; Moritz, Thomas; Olsson, Olof

    2012-01-01

    Our long-term goal is to develop a Swedish winter oat (Avena sativa). To identify molecular differences that correlate with winter hardiness, a winter oat model comprising of both non-hardy spring lines and winter hardy lines is needed. To achieve this, we selected 294 oat breeding lines, originating from various Russian, German, and American winter oat breeding programs and tested them in the field in south- and western Sweden. By assaying for winter survival and agricultural properties during four consecutive seasons, we identified 14 breeding lines of different origins that not only survived the winter but also were agronomically better than the rest. Laboratory tests including electrolytic leakage, controlled crown freezing assay, expression analysis of the AsVrn1 gene and monitoring of flowering time suggested that the American lines had the highest freezing tolerance, although the German lines performed better in the field. Finally, six lines constituting the two most freezing tolerant lines, two intermediate lines and two spring cultivars were chosen to build a winter oat model system. Metabolic profiling of non-acclimated and cold acclimated leaf tissue samples isolated from the six selected lines revealed differential expression patterns of 245 metabolites including several sugars, amino acids, organic acids and 181 hitherto unknown metabolites. The expression patterns of 107 metabolites showed significant interactions with either a cultivar or a time-point. Further identification, characterisation and validation of these metabolites will lead to an increased understanding of the cold acclimation process in oats. Furthermore, by using the winter oat model system, differential sequencing of crown mRNA populations would lead to identification of various biomarkers to facilitate winter oat breeding.

  2. Using species distribution model to estimate the wintering population size of the endangered scaly-sided merganser in China.

    Directory of Open Access Journals (Sweden)

    Qing Zeng

    Full Text Available Scaly-sided Merganser is a globally endangered species restricted to eastern Asia. Estimating its population is difficult and considerable gap exists between populations at its breeding grounds and wintering sites. In this study, we built a species distribution model (SDM using Maxent with presence-only data to predict the potential wintering habitat for Scaly-sided Merganser in China. Area under the receiver operating characteristic curve (AUC method suggests high predictive power of the model (training and testing AUC were 0.97 and 0.96 respectively. The most significant environmental variables included annual mean temperature, mean temperature of coldest quarter, minimum temperature of coldest month and precipitation of driest quarter. Suitable conditions for Scaly-sided Merganser are predicted in the middle and lower reaches of the Yangtze River, especially in Jiangxi, Hunan and Hubei Provinces. The predicted suitable habitat embraces 6,984 km of river. Based on survey results from three consecutive winters (2010-2012 and previous studies, we estimated that the entire wintering population of Scaly-sided Merganser in China to be 3,561 ± 478 individuals, which is consistent with estimate in its breeding ground.

  3. Modelling Monthly Mental Sickness Cases Using Principal ...

    African Journals Online (AJOL)

    The methodology was principal component analysis (PCA) using data obtained from the hospital to estimate regression coefficients and parameters. It was found that the principal component regression model that was derived was good predictive tool. The principal component regression model obtained was okay and this ...

  4. Assessing winter cover crop nutrient uptake efficiency using a water quality simulation model

    Science.gov (United States)

    Yeo, In-Young; Lee, Sangchui; Sadeghi, Ali M.; Beeson, Peter C.; Hively, W. Dean; McCarty, Greg W.; Lang, Megan W.

    2013-01-01

    Winter cover crops are an effective conservation management practice with potential to improve water quality. Throughout the Chesapeake Bay Watershed (CBW), which is located in the Mid-Atlantic US, winter cover crop use has been emphasized and federal and state cost-share programs are available to farmers to subsidize the cost of winter cover crop establishment. The objective of this study was to assess the long-term effect of planting winter cover crops at the watershed scale and to identify critical source areas of high nitrate export. A physically-based watershed simulation model, Soil and Water Assessment Tool (SWAT), was calibrated and validated using water quality monitoring data and satellite-based estimates of winter cover crop species performance to simulate hydrological processes and nutrient cycling over the period of 1991–2000. Multiple scenarios were developed to obtain baseline information on nitrate loading without winter cover crops planted and to investigate how nitrate loading could change with different winter cover crop planting scenarios, including different species, planting times, and implementation areas. The results indicate that winter cover crops had a negligible impact on water budget, but significantly reduced nitrate leaching to groundwater and delivery to the waterways. Without winter cover crops, annual nitrate loading was approximately 14 kg ha−1, but it decreased to 4.6–10.1 kg ha−1 with winter cover crops resulting in a reduction rate of 27–67% at the watershed scale. Rye was most effective, with a potential to reduce nitrate leaching by up to 93% with early planting at the field scale. Early planting of winter cover crops (~30 days of additional growing days) was crucial, as it lowered nitrate export by an additional ~2 kg ha−1 when compared to late planting scenarios. The effectiveness of cover cropping increased with increasing extent of winter cover crop implementation. Agricultural fields with well-drained soils

  5. Adaptive temperature regulation in the little bird in winter: predictions from a stochastic dynamic programming model.

    Science.gov (United States)

    Brodin, Anders; Nilsson, Jan-Åke; Nord, Andreas

    2017-09-01

    Several species of small birds are resident in boreal forests where environmental temperatures can be -20 to -30 °C, or even lower, in winter. As winter days are short, and food is scarce, winter survival is a challenge for small endothermic animals. A bird of this size will have to gain almost 10% of its lean body mass in fat every day to sustain overnight metabolism. Birds such as parids (titmice and chickadees) can use facultative hypothermia, a process in which body temperature is actively down-regulated to a specific level, to reduce heat loss and thus save energy. During cold winter nights, these birds may decrease body temperature from the normal from 42 ° down to 35 °C, or even lower in some species. However, birds are unable to move in this deep hypothermic state, making it a risky strategy if predators are around. Why, then, do small northern birds enter a potentially dangerous physiological state for a relatively small reduction in energy expenditure? We used stochastic dynamic programming to investigate this. Our model suggests that the use of nocturnal hypothermia at night is paramount in these biomes, as it would increase winter survival for a small northern bird by 58% over a winter of 100 days. Our model also explains the phenomenon known as winter fattening, and its relationship to thermoregulation, in northern birds.

  6. Is Hosting the Games Enough to Win? A predictive economic model of medal wins at 2014 Winter Olympics

    OpenAIRE

    Wladimir Andreff

    2012-01-01

    An econometric model which has first been estimated on medal wins at Summer Olympics and has predicted 88% of medal distribution at Beijing Games 2008, is revisited for Winter Olympics. After changing some variables to take into account the winter sports specificity, the model is estimated again on all Winter Games since 1964.Then it is used to predict (forecast) the medal distribution per country at the 2014 Sochi Winter Olympics.

  7. Modeling winter precipitation over the Juneau Icefield, Alaska, using a linear model of orographic precipitation

    Science.gov (United States)

    Roth, Aurora; Hock, Regine; Schuler, Thomas V.; Bieniek, Peter A.; Pelto, Mauri; Aschwanden, Andy

    2018-03-01

    Assessing and modeling precipitation in mountainous areas remains a major challenge in glacier mass balance modeling. Observations are typically scarce and reanalysis data and similar climate products are too coarse to accurately capture orographic effects. Here we use the linear theory of orographic precipitation model (LT model) to downscale winter precipitation from a regional climate model over the Juneau Icefield, one of the largest ice masses in North America (>4000 km2), for the period 1979-2013. The LT model is physically-based yet computationally efficient, combining airflow dynamics and simple cloud microphysics. The resulting 1 km resolution precipitation fields show substantially reduced precipitation on the northeastern portion of the icefield compared to the southwestern side, a pattern that is not well captured in the coarse resolution (20 km) WRF data. Net snow accumulation derived from the LT model precipitation agrees well with point observations across the icefield. To investigate the robustness of the LT model results, we perform a series of sensitivity experiments varying hydrometeor fall speeds, the horizontal resolution of the underlying grid, and the source of the meteorological forcing data. The resulting normalized spatial precipitation pattern is similar for all sensitivity experiments, but local precipitation amounts vary strongly, with greatest sensitivity to variations in snow fall speed. Results indicate that the LT model has great potential to provide improved spatial patterns of winter precipitation for glacier mass balance modeling purposes in complex terrain, but ground observations are necessary to constrain model parameters to match total amounts.

  8. An Evaluation of Mesoscale Model Based Model Output Statistics (MOS) During the 2002 Olympic and Paralympic Winter Games

    National Research Council Canada - National Science Library

    Hart, Kenneth

    2003-01-01

    The skill of a mesoscale model based Model Output Statistics (MOS) system that provided hourly forecasts for 18 sites over northern Utah during the 2002 Winter Olympic and Paralympic Games is evaluated...

  9. Bioclimatic conditions of the winter months in Western Kazakhstan and their dynamics in relation to climate change

    Science.gov (United States)

    Nyssanbayeva, Aiman S.; Cherednichenko, Alexandr V.; Cherednichenko, Vladimir S.; Abayev, Nurlan N.; Madibekov, Azamat S.

    2018-03-01

    The territory of West Kazakhstan is an intensively developing region. The main oil and gas fields are concentrated there. In addition, this region is well-known as a region of nomad cattle breeding. Both of industry and agriculture demand a lot of employees, working in the open air in wintertime. Severe winter conditions, primary very low temperatures, and strong winds characterize the region. In this work, we calculated and analyzed the spatial and temporal distributions of effective temperatures in the region and their dynamics due to the global warming in the last decades. To calculate the equivalent temperature (WCET) was used the method of OFCM 2003. Nowadays, it is known as a common method for similar studies. It was shown that in the observed region, WCET is significantly lower than the ambient temperature. Repeatability of WCET, corresponding to «increasing risk», «high risk» is high in the main part of the region. Global warming in the region results in returning extremely high temperatures of the air, decreasing repeatability of the average gradation of WCET approximately on 4%, but there is no any visible changing repeatability of extreme WCET. Obtained results can be used for planning any construction work in the open air and agriculture branches.

  10. Winter Wonderlands

    Science.gov (United States)

    Coy, Mary

    2011-01-01

    Listening to people complain about the hardships of winter and the dreariness of the nearly constant gray sky prompted the author to help her sixth graders recognize and appreciate the beauty that surrounds them for nearly five months of the year in western New York. The author opines that if students could see things more artistically, the winter…

  11. A study of urban heat island and its association with particulate matter during winter months over Delhi

    International Nuclear Information System (INIS)

    Pandey, Puneeta; Kumar, Dinesh; Prakash, Amit; Masih, Jamson; Singh, Manoj; Kumar, Surendra; Jain, Vinod Kumar; Kumar, Krishan

    2012-01-01

    Day and night time thermal mapping of Delhi has been done with MODIS satellite data for the months of November and December for years 2007, 2008, 2009 and 2010. The study reveals the formation of day time “cool island” over central parts of Delhi which are found to be cooler by a maximum of 4–6 °C than the surrounding rural areas. During the night time, however, the central parts of Delhi are found to be warmer by a maximum of 4–7 °C or even more than the surrounding rural areas thus confirming the formation of nocturnal urban heat island over Delhi. Measurements of solar spectral irradiance over Delhi reveal significantly lower values as compared to a rural site located south-west of Delhi, during the low wind conditions in the months of November and December. Analysis of average monthly temporal data of surface wind speed and particulate matter concentration over Delhi reveals a strong anti-correlation between wind speed and particulate matter concentration. High values of particulate matter during low wind conditions seem to favor the so called “cool island” over Delhi. Analysis of radiosonde data of 975 hPa and 850 hPa temperatures over Delhi during November and December from 1973 to 2010 reveals a warming trend at the 850 hPa level and an overall declining trend of ∆T between 975 hPa temperatures and 850 hPa temperatures, thus indicating a weakening of vertical thermal gradients over Delhi during these months. The study suggests that urban areas behave more like moderators of diurnal temperature variation in low wind conditions. - Highlights: ► Daytime cool island forms over central parts of Delhi in November and December. ► Central parts of Delhi are cooler by a maximum of 4–6 °C during daytime and warmer by a maximum of 4–7 °C during night. ► Significant negative correlations exist between daytime surface temperatures and AOD levels. ► Land use parameters have significant correlations with surface temperatures. ► The day time

  12. Comparing Model Ozone Loss during the SOLVE and SOLVE-2 Winters

    Science.gov (United States)

    Drdla, K.

    2003-01-01

    Model simulations have been used to analyze the factors influencing ozone loss during the 1999-2000 and 2002-2003 js. For both winters, the evolution of the Arctic vortex from November to April has been simulated using a trajectory-based microphysical and photochemical model. Extensive PSC formation and strong ozone depletion are evident in both winters. However, the ozone loss begins earlier in the 2002-2003 winter, with significant ozone depletion by early January. Analysis of the model results shows that during December 2002 not only cold temperatures but also the vortex structure was critical, allowing PSC-processed air parcels to experience significant solar exposure. The resultant ozone loss can be differentiated from ozone loss that occurs in the springtime, in particular because of the continued exposure to PSCs. For example, chlorine reactivation by the PSCs causes ozone loss to be insensitive to denitrification. Therefore, diagnosing the extent of ozone loss early in the winter is critical In understanding the overall winter-long ozone depletion.

  13. Analysis of monthly, winter, and annual temperatures in Zagreb, Croatia, from 1864 to 2010: the 7.7-year cycle and the North Atlantic Oscillation

    Science.gov (United States)

    Sen, Asok K.; Ogrin, Darko

    2016-02-01

    Long instrumental records of meteorological variables such as temperature and precipitation are very useful for studying regional climate in the past, present, and future. They can also be useful for understanding the influence of large-scale atmospheric circulation processes on the regional climate. This paper investigates the monthly, winter, and annual temperature time series obtained from the instrumental records in Zagreb, Croatia, for the period 1864-2010. Using wavelet analysis, the dominant modes of variability in these temperature series are identified, and the time intervals over which these modes may persist are delineated. The results reveal that all three temperature records exhibit low-frequency variability with a dominant periodicity at around 7.7 years. The 7.7-year cycle has also been observed in the temperature data recorded at several other stations in Europe, especially in Northern and Western Europe, and may be linked to the North Atlantic Oscillation (NAO) and/or solar/geomagnetic activity.

  14. Spatially explicit modeling of conflict zones between wildlife and snow sports: prioritizing areas for winter refuges.

    Science.gov (United States)

    Braunisch, Veronika; Patthey, Patrick; Arlettaz, Raphaël

    2011-04-01

    Outdoor winter recreation exerts an increasing pressure upon mountain ecosystems, with unpredictable, free-ranging activities (e.g., ski mountaineering, snowboarding, and snowshoeing) representing a major source of stress for wildlife. Mitigating anthropogenic disturbance requires the spatially explicit prediction of the interference between the activities of humans and wildlife. We applied spatial modeling to localize conflict zones between wintering Black Grouse (Tetrao tetrix), a declining species of Alpine timberline ecosystems, and two free-ranging winter sports (off-piste skiing [including snow-boarding] and snowshoeing). Track data (snow-sports and birds' traces) obtained from aerial photographs taken over a 585-km transect running along the timberline, implemented within a maximum entropy model, were used to predict the occurrence of snow sports and Black Grouse as a function of landscape characteristics. By modeling Black Grouse presence in the theoretical absence of free-ranging activities and ski infrastructure, we first estimated the amount of habitat reduction caused by these two factors. The models were then extrapolated to the altitudinal range occupied by Black Grouse, while the spatial extent and intensity of potential conflict were assessed by calculating the probability of human-wildlife co-occurrence. The two snow-sports showed different distribution patterns. Skiers' occurrence was mainly determined by ski-lift presence and a smooth terrain, while snowshoers' occurrence was linked to hiking or skiing routes and moderate slopes. Wintering Black Grouse avoided ski lifts and areas frequented by free-ranging snow sports. According to the models, Black Grouse have faced a substantial reduction of suitable wintering habitat along the timberline transect: 12% due to ski infrastructure and another 16% when adding free-ranging activities. Extrapolating the models over the whole study area results in an overall habitat loss due to ski infrastructure of

  15. Winter precipitation characteristics in western US related to atmospheric river landfalls: observations and model evaluations

    Science.gov (United States)

    Kim, J.; Guan, B.; Waliser, D. E.; Ferraro, R. D.; Case, J. L.; Iguchi, T.; Kemp, E.; Putman, W.; Wang, W.; Wu, D.; Tian, B.

    2018-01-01

    Winter precipitation (PR) characteristics in western United States (WUS) related to atmospheric river (AR) landfalls are examined using the observation-based PRISM data. The observed AR-related precipitation characteristics are in turn used to evaluate model precipitation data from the NASA MERRA2 reanalysis and from seven dynamical downscaling simulations driven by the MERRA2. Multiple metrics including mean bias, Taylor diagram, and two skill scores are used to measure model performance for three climatological sub-regions in WUS, Pacific Northwest (PNW), Pacific Southwest (PSW) and Great Basin (GB). All model data well represent the winter-mean PR with spatial pattern correlations of 0.8 or higher with PRISM for the three sub-regions. Higher spatial resolutions and/or the use of spectral nudging generally yield higher skill scores in simulating the geographical distribution of PR for the entire winter. The PRISM data shows that the AR-related fraction of winter PR and associated daily PR PDFs in each region vary strongly for landfall locations; AR landfalls in the northern WUS coast (NC) affect mostly PNW while those in the southern WUS coast (SC) affect both PSW and GB. NC (SC) landfalls increase the frequency of heavy PR in PNW (PSW and GB) but reduce it in PSW (PNW). All model data reasonably represent these observed variations in the AR-related winter PR fractions and the daily PR PDFs according to AR landfall locations. However, unlike for the entire winter period, no systematic effects of resolution and/or spectral nudging are identified in these AR-related PR characteristics. Dynamical downscaling in this study generally yield positive added values to the MERRA2 PR in the AR-related PR fraction for most sub-regions and landfall locations, most noticeably for PSW by NU-WRF. The downscaling also generate positive added value in p95 for PNW, but negative values for PSW and GB due to overestimation of heavy precipitation events.

  16. Early Season Large-Area Winter Crop Mapping Using MODIS NDVI Data, Growing Degree Days Information and a Gaussian Mixture Model

    Science.gov (United States)

    Skakun, Sergii; Franch, Belen; Vermote, Eric; Roger, Jean-Claude; Becker-Reshef, Inbal; Justice, Christopher; Kussul, Nataliia

    2017-01-01

    Knowledge on geographical location and distribution of crops at global, national and regional scales is an extremely valuable source of information applications. Traditional approaches to crop mapping using remote sensing data rely heavily on reference or ground truth data in order to train/calibrate classification models. As a rule, such models are only applicable to a single vegetation season and should be recalibrated to be applicable for other seasons. This paper addresses the problem of early season large-area winter crop mapping using Moderate Resolution Imaging Spectroradiometer (MODIS) derived Normalized Difference Vegetation Index (NDVI) time-series and growing degree days (GDD) information derived from the Modern-Era Retrospective analysis for Research and Applications (MERRA-2) product. The model is based on the assumption that winter crops have developed biomass during early spring while other crops (spring and summer) have no biomass. As winter crop development is temporally and spatially non-uniform due to the presence of different agro-climatic zones, we use GDD to account for such discrepancies. A Gaussian mixture model (GMM) is applied to discriminate winter crops from other crops (spring and summer). The proposed method has the following advantages: low input data requirements, robustness, applicability to global scale application and can provide winter crop maps 1.5-2 months before harvest. The model is applied to two study regions, the State of Kansas in the US and Ukraine, and for multiple seasons (2001-2014). Validation using the US Department of Agriculture (USDA) Crop Data Layer (CDL) for Kansas and ground measurements for Ukraine shows that accuracies of greater than 90% can be achieved in mapping winter crops 1.5-2 months before harvest. Results also show good correspondence to official statistics with average coefficients of determination R(exp. 2) greater than 0.85.

  17. From Cyclone Tracks to the Costs of European Winter Storms: A Probabilistic Loss Assessment Model

    Science.gov (United States)

    Orwig, K.; Renggli, D.; Corti, T.; Reese, S.; Wueest, M.; Viktor, E.; Zimmerli, P.

    2014-12-01

    European winter storms cause billions of dollars of insured losses every year. Therefore, it is essential to understand potential impacts of future events, and the role reinsurance can play to mitigate the losses. The authors will present an overview on natural catastrophe risk assessment modeling in the reinsurance industry, and the development of a new innovative approach for modeling the risk associated with European winter storms.The new innovative approach includes the development of physically meaningful probabilistic (i.e. simulated) events for European winter storm loss assessment. The meteorological hazard component of the new model is based on cyclone and windstorm tracks identified in the 20thCentury Reanalysis data. The knowledge of the evolution of winter storms both in time and space allows the physically meaningful perturbation of historical event properties (e.g. track, intensity, etc.). The perturbation includes a random element but also takes the local climatology and the evolution of the historical event into account.The low-resolution wind footprints taken from the 20thCentury Reanalysis are processed by a statistical-dynamical downscaling to generate high-resolution footprints for both the simulated and historical events. Downscaling transfer functions are generated using ENSEMBLES regional climate model data. The result is a set of reliable probabilistic events representing thousands of years. The event set is then combined with country and site-specific vulnerability functions and detailed market- or client-specific information to compute annual expected losses.

  18. Assessing winter cover crop nutrient uptake efficiency using a water quality simulation model

    Science.gov (United States)

    Yeo, I.-Y.; Lee, S.; Sadeghi, A. M.; Beeson, P. C.; Hively, W. D.; McCarty, G. W.; Lang, M. W.

    2014-12-01

    Winter cover crops are an effective conservation management practice with potential to improve water quality. Throughout the Chesapeake Bay watershed (CBW), which is located in the mid-Atlantic US, winter cover crop use has been emphasized, and federal and state cost-share programs are available to farmers to subsidize the cost of cover crop establishment. The objective of this study was to assess the long-term effect of planting winter cover crops to improve water quality at the watershed scale (~ 50 km2) and to identify critical source areas of high nitrate export. A physically based watershed simulation model, Soil and Water Assessment Tool (SWAT), was calibrated and validated using water quality monitoring data to simulate hydrological processes and agricultural nutrient cycling over the period of 1990-2000. To accurately simulate winter cover crop biomass in relation to growing conditions, a new approach was developed to further calibrate plant growth parameters that control the leaf area development curve using multitemporal satellite-based measurements of species-specific winter cover crop performance. Multiple SWAT scenarios were developed to obtain baseline information on nitrate loading without winter cover crops and to investigate how nitrate loading could change under different winter cover crop planting scenarios, including different species, planting dates, and implementation areas. The simulation results indicate that winter cover crops have a negligible impact on the water budget but significantly reduce nitrate leaching to groundwater and delivery to the waterways. Without winter cover crops, annual nitrate loading from agricultural lands was approximately 14 kg ha-1, but decreased to 4.6-10.1 kg ha-1 with cover crops resulting in a reduction rate of 27-67% at the watershed scale. Rye was the most effective species, with a potential to reduce nitrate leaching by up to 93% with early planting at the field scale. Early planting of cover crops (~ 30

  19. Intra-Seasonal Monthly Oscillations in Stratospheric NCEP Data and Model Results

    Science.gov (United States)

    Mayr, H. G.; Mengel, J. G.; Huang, F. T.; Nash, E. R.

    2009-01-01

    Intra-seasonal oscillations (ISO) are observed in the zonal-mean of mesospheric wind and temperature measurements-and the numerical spectral model (NSM) generates such oscillations. Relatively large temperature ISO are evident also in stratospheric CPC (NCEP) data at high latitudes, where the NSM produces amplitudes around 3 K at 30 km. Analyzing the NCEP data for the years 1996-2006, we find in Fourier spectra signatures of oscillations with periods between 1.7 and 3 months. With statistical confidence levels exceeding 70%, the spectral features are induced by nonlinear interactions involving the annual and semi-annual variations. The synthesized data show for the 10-year average that the temperature ISO peak in winter, having amplitudes close to 4 K. The synthesized complete spectrum for periods around 2 months produces oscillations, varying from year to year, which can reach peak amplitudes of 15 and 5 K respectively at northern and southern polar latitudes.

  20. An analysis, sensitivity and prediction of winter fog events using FASP model over Indo-Gangetic plains, India

    Science.gov (United States)

    Srivastava, S. K., Sr.; Sharma, D. A.; Sachdeva, K.

    2017-12-01

    Indo-Gangetic plains of India experience severe fog conditions during the peak winter months of December and January every year. In this paper an attempt has been to analyze the spatial and temporal variability of winter fog over Indo-Gangetic plains. Further, an attempt has also been made to configure an efficient meso-scale numerical weather prediction model using different parameterization schemes and develop a forecasting tool for prediction of fog during winter months over Indo-Gangetic plains. The study revealed that an alarming increasing positive trend of fog frequency prevails over many locations of IGP. Hot spot and cluster analysis were conducted to identify the high fog prone zones using GIS and inferential statistical tools respectively. Hot spots on an average experiences fog on 68.27% days, it is followed by moderate and cold spots with 48.03% and 21.79% respectively. The study proposes a new FASP (Fog Analysis, sensitivity and prediction) Model for overall analysis and prediction of fog at a particular location and period over IGP. In the first phase of this model long term climatological fog data of a location is analyzed to determine its characteristics and prevailing trend using various advanced statistical techniques. During a second phase a sensitivity test is conducted with different combination of parameterization schemes to determine the most suitable combination for fog simulation over a particular location and period and in the third and final phase, first ARIMA model is used to predict the number of fog days in future . Thereafter, Numerical model is used to predict the various meteorological parameters favourable for fog forecast. Finally, Hybrid model is used for fog forecast over the study location. The results of the FASP model are validated with actual ground based fog data using statistical tools. Forecast Fog-gram generated using hybrid model during Jan 2017 shows highly encouraging results for fog occurrence/Non occurrence between

  1. Modeling of the Monthly Rainfall-Runoff Process Through Regressions

    Directory of Open Access Journals (Sweden)

    Campos-Aranda Daniel Francisco

    2014-10-01

    Full Text Available To solve the problems associated with the assessment of water resources of a river, the modeling of the rainfall-runoff process (RRP allows the deduction of runoff missing data and to extend its record, since generally the information available on precipitation is larger. It also enables the estimation of inputs to reservoirs, when their building led to the suppression of the gauging station. The simplest mathematical model that can be set for the RRP is the linear regression or curve on a monthly basis. Such a model is described in detail and is calibrated with the simultaneous record of monthly rainfall and runoff in Ballesmi hydrometric station, which covers 35 years. Since the runoff of this station has an important contribution from the spring discharge, the record is corrected first by removing that contribution. In order to do this a procedure was developed based either on the monthly average regional runoff coefficients or on nearby and similar watershed; in this case the Tancuilín gauging station was used. Both stations belong to the Partial Hydrologic Region No. 26 (Lower Rio Panuco and are located within the state of San Luis Potosi, México. The study performed indicates that the monthly regression model, due to its conceptual approach, faithfully reproduces monthly average runoff volumes and achieves an excellent approximation in relation to the dispersion, proved by calculation of the means and standard deviations.

  2. REGIONAL FIRST ORDER PERIODIC AUTOREGRESSIVE MODELS FOR MONTHLY FLOWS

    Directory of Open Access Journals (Sweden)

    Ceyhun ÖZÇELİK

    2008-01-01

    Full Text Available First order periodic autoregressive models is of mostly used models in modeling of time dependency of hydrological flow processes. In these models, periodicity of the correlogram is preserved as well as time dependency of processes. However, the parameters of these models, namely, inter-monthly lag-1 autocorrelation coefficients may be often estimated erroneously from short samples, since they are statistics of high order moments. Therefore, to constitute a regional model may be a solution that can produce more reliable and decisive estimates, and derive models and model parameters in any required point of the basin considered. In this study, definitions of homogeneous region for lag-1 autocorrelation coefficients are made; five parametric and non parametric models are proposed to set regional models of lag-1 autocorrelation coefficients. Regional models are applied on 30 stream flow gauging stations in Seyhan and Ceyhan basins, and tested by criteria of relative absolute bias, simple and relative root of mean square errors.

  3. Modelling the winter distribution of a rare and endangered migrant, the Aquatic Warbler Acrocephalus paludicola

    DEFF Research Database (Denmark)

    Walther, Bruno A; Schäffer, Norbert; van Niekerk, Adriaan

    2007-01-01

    . Such model predictions may be useful guidelines to focus further field research on the Aquatic Warbler. Given the excellent model predictions in this study, this novel technique may prove useful to model the distribution of other rare and endangered species, thus providing a means to guide future survey......The Aquatic Warbler Acrocephalus paludicola is one of the most threatened Western Palearctic passerine species, classified as globally Vulnerable. With its breeding grounds relatively secure, a clear need remains for the monitoring and protection of the migration and wintering grounds of this rare...... and endangered migrant. Recent research has shown that the Aquatic Warbler migrates through northwest Africa in autumn and spring. The wintering grounds are apparently limited to wetlands of sub-Saharan West Africa, with records from only about 20 localities in Mauritania, Mali, Senegal and Ghana. Given the lack...

  4. Modeling influences on winter distribution of caribou in northwestern Alaska through use of satellite telemetry

    Directory of Open Access Journals (Sweden)

    Kyle Joly

    2011-09-01

    Full Text Available I hypothesize that the distribution of barren-ground caribou (Rangifer tarandus granti is affected by multiple, interrelated factors. These factors include, but are not limited to, terrain and snow characteristics as well as predation pressure and habitat. To test this hypothesis, I attributed caribou locations derived from satellite telemetry over a 6 year period with terrain (elevation, slope, aspect, and ruggedness, habitat characteristics, and moose density - potentially an index of wolf predation pressure. These locations were compared to random locations, attributed using the same data layers, using logistic regression techniques to develop resource selection functions (RSFs. I found that caribou moved significantly less during mid-winter than early- or late-winter and that cows moved significantly more in April than bulls due to their earlier departure on their spring migration. Distribution was different between cows and bulls. Terrain variables were important factors but were scale-dependent. Cows avoided forested areas, highlighting the importance of tundra habitats, and selected for dwarf shrub, with relatively high lichen cover, and sedge habitat types. Bulls selected for dryas, coniferous forest and dwarf shrub habitats but against lowland sedge, upland shrub and burned tundra. Cow distribution was negatively correlated with moose density at the scale of the Seward Peninsula. My results support the hypothesis that caribou distribution during winter in northwest Alaska is affected by multiple, interrelated factors. These results may be useful for researchers to track and/or model changes in future patterns of range use over winter.

  5. Exceptional winter storms affecting Western Iberia and extremes: diagnosis, modelling and multi-model ensemble projection

    Science.gov (United States)

    Liberato, M. L. R.; Pinto, J. G.; Gil, V.; Ramos, A. M.; Trigo, R. M.

    2017-12-01

    Extratropical cyclones dominate autumn and winter weather over Western Europe and particularly over the Iberian Peninsula. Intense, high-impact storms are one of the major weather risks in the region, mostly due to the simultaneous occurrence of high winds and extreme precipitation events. These intense extratropical cyclones may result in windstorm damage, flooding and coastal storm surges, with large societal impacts. In Portugal, due to the extensive human use of coastal areas, the natural and built coastal environments have been amongst the most affected. In this work several historical winter storms that adversely affected the Western Iberian Peninsula are studied in detail in order to contribute to an improved assessment of the characteristics of these events. The diagnosis has been performed based on instrumental daily precipitation and wind records, on satellite images, on reanalysis data and through model simulations. For several examples the synoptic evolution and upper-level dynamics analysis of physical processes controlling the life cycle of extratropical storms associated with the triggering of the considered extreme events has also been accomplished. Furthermore, the space-time variability of the exceptionally severe storms affecting Western Iberia over the last century and under three climate scenarios (the historical simulation, the RCP4.5 and RCP8.5 scenarios) is presented. These studies contribute to improving the knowledge of atmospheric dynamics controlling the life cycle of midlatitude storms associated to severe weather (precipitation and wind) in the Iberian Peninsula. AcknowledgementsThis work is supported by the Portuguese Foundation for Science and Technology (FCT), Portugal, through project UID/GEO/50019/2013 - Instituto Dom Luiz. A. M. Ramos is also supported by a FCT postdoctoral grant (FCT/DFRH/SFRH/BPD/84328/2012).

  6. Changes in the zonal mean flow, temperature, and planetary waves observed in the Northern Hemisphere mid-winter months during the last decades

    Science.gov (United States)

    Rakushina, E. V.; Ermakova, T. S.; Pogoreltsev, A. I.

    2018-06-01

    Four sets of data: the UK Met Office, Modern Era Retrospective-analysis for Research and Applications (MERRA), Japanese 55-year Reanalysis data (JRA-55), and ERA-Interim data (ERA) have been used to estimate the climatic variability of the zonal mean flow, temperature, and Stationary Planetary Waves (SPW1, SPW2) from the troposphere up to the lower mesosphere levels. The composites of the meteorological fields during mid-winter month have been averaged over the first (1995-2005) and second (2006-2016) 11 years intervals and have been compared mainly paying attention to interannual and intraseasonal variability. Results show that changes in the mean fields and SPW2 are weaker and statistical significance of these changes is lower in comparison with the changes observed in the intraseasonal variability of these characteristics. All data sets demonstrate a decrease of SPW1 amplitude at the higher-middle latitudes in the lower stratosphere and opposite effect in the upper stratosphere. However, there is an increase of the intraseasonal variability for all meteorological parameters and this rise is statistically significant. The results obtained show that UK Met Office data demonstrate stronger changes and increase of the intraseasonal variability in comparison with other data sets.

  7. Winter weather demand considerations.

    Science.gov (United States)

    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...

  8. Statistical models to predict flows at monthly level in Salvajina

    International Nuclear Information System (INIS)

    Gonzalez, Harold O

    1994-01-01

    It thinks about and models of lineal regression evaluate at monthly level that they allow to predict flows in Salvajina, with base in predictions variable, like the difference of pressure between Darwin and Tahiti, precipitation in Piendamo Cauca), temperature in Port Chicama (Peru) and pressure in Tahiti

  9. Modeling organic aerosol concentrations and properties during winter 2014 in the northwestern Mediterranean region

    OpenAIRE

    Chrit, Mounir; Sartelet, Karine; Sciare, Jean; Majdi, Marwa; Nicolas, José; Petit, Jean-Eudes; Dulac, François

    2018-01-01

    Organic aerosols are measured at a remote site (Ersa) on Corsica Cape in the northwestern Mediterranean basin during the Chemistry-Aerosol Mediterranean Experiment (CharMEx) winter campaign of 2014, when high organic concentrations from anthropogenic origin are observed. This work aims at representing the observed organic aerosol concentrations and properties (oxidation state) using the air-quality model Polyphemus with a surrogate approach for secondary organic aerosol (SOA) formation. Becau...

  10. A complex autoregressive model and application to monthly temperature forecasts

    Directory of Open Access Journals (Sweden)

    X. Gu

    2005-11-01

    Full Text Available A complex autoregressive model was established based on the mathematic derivation of the least squares for the complex number domain which is referred to as the complex least squares. The model is different from the conventional way that the real number and the imaginary number are separately calculated. An application of this new model shows a better forecast than forecasts from other conventional statistical models, in predicting monthly temperature anomalies in July at 160 meteorological stations in mainland China. The conventional statistical models include an autoregressive model, where the real number and the imaginary number are separately disposed, an autoregressive model in the real number domain, and a persistence-forecast model.

  11. [Adaptability of APSIM model in Southwestern China: A case study of winter wheat in Chongqing City].

    Science.gov (United States)

    Dai, Tong; Wang, Jing; He, Di; Zhang, Jian-ping; Wang, Na

    2015-04-01

    Field experimental data of winter wheat and parallel daily meteorological data at four typical stations in Chongqing City were used to calibrate and validate APSIM-wheat model and determine the genetic parameters for 12 varieties of winter wheat. The results showed that there was a good agreement between the simulated and observed growth periods from sowing to emergence, flowering and maturity of wheat. Root mean squared errors (RMSEs) between simulated and observed emergence, flowering and maturity were 0-3, 1-8, and 0-8 d, respectively. Normalized root mean squared errors (NRMSEs) between simulated and observed above-ground biomass for 12 study varieties were less than 30%. NRMSE between simulated and observed yields for 10 varieties out of 12 study varieties were less than 30%. APSIM-wheat model performed well in simulating phenology, aboveground biomass and yield of winter wheat in Chongqing City, which could provide a foundational support for assessing the impact of climate change on wheat production in the study area based on the model.

  12. Climate model assessment of changes in winter-spring streamflow timing over North America

    Science.gov (United States)

    Kam, Jonghun; Knutson, Thomas R.; Milly, Paul C. D.

    2018-01-01

    Over regions where snow-melt runoff substantially contributes to winter-spring streamflows, warming can accelerate snow melt and reduce dry-season streamflows. However, conclusive detection of changes and attribution to anthropogenic forcing is hindered by brevity of observational records, model uncertainty, and uncertainty concerning internal variability. In this study, a detection/attribution of changes in mid-latitude North American winter-spring streamflow timing is examined using nine global climate models under multiple forcing scenarios. In this study, robustness across models, start/end dates for trends, and assumptions about internal variability is evaluated. Marginal evidence for an emerging detectable anthropogenic influence (according to four or five of nine models) is found in the north-central U.S., where winter-spring streamflows have been coming earlier. Weaker indications of detectable anthropogenic influence (three of nine models) are found in the mountainous western U.S./southwestern Canada and in extreme northeastern U.S./Canadian Maritimes. In the former region, a recent shift toward later streamflows has rendered the full-record trend toward earlier streamflows only marginally significant, with possible implications for previously published climate change detection findings for streamflow timing in this region. In the latter region, no forced model shows as large a shift toward earlier streamflow timing as the detectable observed shift. In other (including warm, snow-free) regions, observed trends are typically not detectable, although in the U.S. central plains we find detectable delays in streamflow, which are inconsistent with forced model experiments.

  13. Reduced-fat Gouda-type cheese enriched with vitamin D3 effectively prevents vitamin D deficiency during winter months in postmenopausal women in Greece.

    Science.gov (United States)

    Manios, Yannis; Moschonis, George; Mavrogianni, Christina; van den Heuvel, Eghm; Singh-Povel, Cécile M; Kiely, Mairead; Cashman, Kevin D

    2017-10-01

    The primary aim of the present study was to examine the effectiveness of daily consumption of vitamin D 3 -enriched, reduced-fat Gouda-type cheese on 25-hydroxyvitamin D (25(OH)D) concentration in postmenopausal women. Health-related quality of life (HRQL) indices were examined as secondary outcomes. This is a single-blinded (i.e., to study participants), randomized, controlled food-based dietary intervention study. A sample of 79 postmenopausal women (55-75 years old) was randomized either to a control group (CG: n = 39) or an intervention group (IG: n = 40) that consumed, as part of their usual diet, 60 g of either non-enriched or vitamin D 3 enriched Gouda-type cheese, respectively, for eight consecutive weeks (i.e., from January to March 2015). Sixty grams of enriched cheese provided a daily dose of 5.7 μg of vitamin D 3 . There was a differential response of mean (95 % CI) serum 25(OH)D levels in the IG and CG, with the former increasing and the latter decreasing significantly over the eight weeks of the trial [i.e., by 5.1 (3.4, 6.9) nmol/L vs. -4.6 (-6.4, -2.8) nmol/L, P D levels  0.1). Consumption of 60 g of vitamin D 3 -enriched, reduced-fat Gouda-type cheese provided a daily dose of 5.7 μg of additional vitamin D 3 and was effective in increasing mean serum 25(OH)D concentration and in counteracting vitamin D deficiency during winter months in postmenopausal women in Greece.

  14. Application of regional climate models to the Indian winter monsoon over the western Himalayas.

    Science.gov (United States)

    Dimri, A P; Yasunari, T; Wiltshire, A; Kumar, P; Mathison, C; Ridley, J; Jacob, D

    2013-12-01

    The Himalayan region is characterized by pronounced topographic heterogeneity and land use variability from west to east, with a large variation in regional climate patterns. Over the western part of the region, almost one-third of the annual precipitation is received in winter during cyclonic storms embedded in westerlies, known locally as the western disturbance. In the present paper, the regional winter climate over the western Himalayas is analyzed from simulations produced by two regional climate models (RCMs) forced with large-scale fields from ERA-Interim. The analysis was conducted by the composition of contrasting (wet and dry) winter precipitation years. The findings showed that RCMs could simulate the regional climate of the western Himalayas and represent the atmospheric circulation during extreme precipitation years in accordance with observations. The results suggest the important role of topography in moisture fluxes, transport and vertical flows. Dynamical downscaling with RCMs represented regional climates at the mountain or even event scale. However, uncertainties of precipitation scale and liquid-solid precipitation ratios within RCMs are still large for the purposes of hydrological and glaciological studies. Copyright © 2013 Elsevier B.V. All rights reserved.

  15. Modelling soil water content variations under drought stress on soil column cropped with winter wheat

    Directory of Open Access Journals (Sweden)

    Csorba Szilveszter

    2014-12-01

    Full Text Available Mathematical models are effective tools for evaluating the impact of predicted climate change on agricultural production, but it is difficult to test their applicability to future weather conditions. We applied the SWAP model to assess its applicability to climate conditions, differing from those, for which the model was developed. We used a database obtained from a winter wheat drought stress experiment. Winter wheat was grown in six soil columns, three having optimal water supply (NS, while three were kept under drought-stressed conditions (S. The SWAP model was successfully calibrated against measured values of potential evapotranspiration (PET, potential evaporation (PE and total amount of water (TSW in the soil columns. The Nash-Sutcliffe model efficiency coefficient (N-S for TWS for the stressed columns was 0.92. For the NS treatment, we applied temporally variable soil hydraulic properties because of soil consolidation caused by regular irrigation. This approach improved the N-S values for the wetting-drying cycle from -1.77 to 0.54. We concluded that the model could be used for assessing the effects of climate change on soil water regime. Our results indicate that soil water balance studies should put more focus on the time variability of structuredependent soil properties.

  16. Wintering habitat model for the North Atlantic Right Whale (Eubalaena glacialis) in the southeastern United States.

    Science.gov (United States)

    Gowan, Timothy A; Ortega-Ortiz, Joel G

    2014-01-01

    The coastal waters off the southeastern United States (SEUS) are a primary wintering ground for the endangered North Atlantic right whale (Eubalaena glacialis), used by calving females along with other adult and juvenile whales. Management actions implemented in this area for the recovery of the right whale population rely on accurate habitat characterization and the ability to predict whale distribution over time. We developed a temporally dynamic habitat model to predict wintering right whale distribution in the SEUS using a generalized additive model framework and aerial survey data from 2003/2004 through 2012/2013. We built upon previous habitat models for right whales in the SEUS and include data from new aerial surveys that extend the spatial coverage of the analysis, particularly in the northern portion of this wintering ground. We summarized whale sightings, survey effort corrected for probability of whale detection, and environmental data at a semimonthly resolution. Consistent with previous studies, sea surface temperature (SST), water depth, and survey year were significant predictors of right whale relative abundance. Additionally, distance to shore, distance to the 22°C SST isotherm, and an interaction between time of year and latitude (to account for the latitudinal migration of whales) were also selected in the analysis presented here. Predictions from the model revealed that the location of preferred habitat differs within and between years in correspondence with variation in environmental conditions. Although cow-calf pairs were rarely sighted in the company of other whales, there was minimal evidence that the preferred habitat of cow-calf pairs was different than that of whale groups without calves at the scale of this study. The results of this updated habitat model can be used to inform management decisions for a migratory species in a dynamic oceanic environment.

  17. Modelling raster-based monthly water balance components for Europe

    Energy Technology Data Exchange (ETDEWEB)

    Ulmen, C.

    2000-11-01

    The terrestrial runoff component is a comparatively small but sensitive and thus significant quantity in the global energy and water cycle at the interface between landmass and atmosphere. As opposed to soil moisture and evapotranspiration which critically determine water vapour fluxes and thus water and energy transport, it can be measured as an integrated quantity over a large area, i.e. the river basin. This peculiarity makes terrestrial runoff ideally suited for the calibration, verification and validation of general circulation models (GCMs). Gauging stations are not homogeneously distributed in space. Moreover, time series are not necessarily continuously measured nor do they in general have overlapping time periods. To overcome this problems with regard to regular grid spacing used in GCMs, different methods can be applied to transform irregular data to regular so called gridded runoff fields. The present work aims to directly compute the gridded components of the monthly water balance (including gridded runoff fields) for Europe by application of the well-established raster-based macro-scale water balance model WABIMON used at the Federal Institute of Hydrology, Germany. Model calibration and validation is performed by separated examination of 29 representative European catchments. Results indicate a general applicability of the model delivering reliable overall patterns and integrated quantities on a monthly basis. For time steps less then too weeks further research and structural improvements of the model are suggested. (orig.)

  18. Modelling and forecasting monthly swordfish catches in the Eastern Mediterranean

    Directory of Open Access Journals (Sweden)

    Konstantinos I. Stergiou

    2003-04-01

    Full Text Available In this study, we used the X-11 census technique for modelling and forecasting the monthly swordfish (Xiphias gladius catches in the Greek Seas during 1982-1996 and 1997 respectively, using catches reported by the National Statistical Service of Greece (NSSG. Forecasts built with X-11 were also compared with those derived from ARIMA andWinter’s exponential smoothing (WES models. The X-11 method captured the features of the study series and outperformed the other two methods, in terms of both fitting and forecasting performance, for all the accuracy measures used. Thus, with the exception of October, November and December 1997, when the corresponding absolute percentage error(APE values were very high (as high as 178.6% because of the low level of the catches, monthly catches during the remaining months of 1997 were predicted accurately, with a mean APE of 12.5%. In contrast, the mean APE values of the other two methods for the same months were higher (ARIMA: 14.6%; WES: 16.6%. The overall good performance of X-11 andthe fact that it provides an insight into the various components (i.e. the seasonal, trend-cycle and irregular components of the time series of interest justify its use in fisheries research. The basic features of the swordfish catches revealed by the application of the X-11 method, the effect of the length of the forecasting horizon on forecasting accuracy and the accuracy of the catches reported by NSSG are also discussed.

  19. Validation of a limited area model over Dome C, Antarctic Plateau, during winter

    Energy Technology Data Exchange (ETDEWEB)

    Gallee, Hubert; Gorodetskaya, Irina V. [Laboratoire de Glaciologie et de Geophysique de l' Environnement, CNRS, 54, rue Moliere, BP. 96, St Martin d' Heres Cedex (France)

    2010-01-15

    The limited area model MAR (Modele Atmospherique Regional) is validated over the Antarctic Plateau for the period 2004-2006, focussing on Dome C during the cold season. MAR simulations are made by initializing the model once and by forcing it through its lateral and top boundaries by the ECMWF operational analyses. Model outputs compare favourably with observations from automatic weather station (AWS), radiometers and atmospheric soundings. MAR is able to simulate the succession of cold and warm events which occur at Dome C during winter. Larger longwave downwelling fluxes (LWD) are responsible for higher surface air temperatures and weaker surface inversions during winter. Warm events are better simulated when the small Antarctic precipitating snow particles are taken into account in radiative transfer computations. MAR stratosphere cools during the cold season, with the coldest temperatures occurring in conjunction with warm events at the surface. The decrease of saturation specific humidity associated with these coldest temperatures is responsible for the formation of polar stratospheric clouds (PSCs) especially in August-September. PSCs then contribute to the surface warming by increasing the surface downwelling longwave flux. (orig.)

  20. A model for making field-based nitrogen recommendations for winter wheat in western oregon

    International Nuclear Information System (INIS)

    Baloch, D.M.; Malghani, M.A.K.; Khan, M.A.; Kakar, E.

    2010-01-01

    A model based on early spring soil and tissue analysis was developed and evaluated for predicting the need for additional nitrogen (N) fertilizer on winter wheat. To develop the model, On-farm trials were' established over three years 1994-95 in grower's fields at three different locations across the Willamette Valley of western Oregon. Two field-scale validation trials were run in 1996-97. Rotations were soft white winter wheat following grass seed, sweet corn or a legume. Four treatments, including a check receiving no nitrogen, were used at each site At the site where wheat followed corn, the predicted optimum N rate was 168 kg N ha/sup -1/ however, the 112 kg N ha/sup -1/ rate was the optimum rate predicted by the developed model. The 84 kgN ha/sup -1/ and 140 kgN ha/sup -1/ rates were selected to bracket the recommended rate (+- 28 kg N ha/sup -1/). Wheat following grass seed had high soil supplied N which depressed the yield even at moderate fertilizer N rates. The model overall accurately assess field-specific optimum fertilizer N status. (author)

  1. Evaluation of a model for predicting Avena fatua and Descurainia sophia seed emergence in winter rapeseed

    Energy Technology Data Exchange (ETDEWEB)

    Aboutalebian, M.A.; Nazari, S.; Gonzalez-Andujar, J.L.

    2017-07-01

    Avena fatua and Descurainia sophia are two important annual weeds throughout winter rapeseed (Brassica napus L.) production systems in the semiarid region of Iran. Timely and more accurate control of both species may be developed if there is a better understanding of its emergence patterns. Non-linear regression techniques are usually unable to accurately predict field emergence under such environmental conditions. The objectives of this research were to evaluate the emergence patterns of A. fatua and D. sophia and determine if emergence could be predicted using cumulative soil thermal time in degree days (CTT). In the present work, cumulative seedling emergence from a winter rapeseed field during 3 years data set was fitted to cumulative soil CTT using Weibull and Gompertz functions. The Weibull model provided a better fit, based on coefficient of determination (R2sqr), root mean square of error (RMSE) and Akaike index (AICd), compared to the Gompertz model between 2013 and 2016 seasons for both species. Maximum emergence of A. fatua occured 70-119 days after sowing or after equals 329-426 °Cd, while in D. sophia it occurred 119-134 days after sowing rapeseed equals 373-470 °Cd. Both models can aid in the future study of A. fatua and D. sophia emergence and assist growers and agricultural professionals with planning timely and more accurate A. fatua and D. sophia control.

  2. Dynamic linear modeling of monthly electricity demand in Japan: Time variation of electricity conservation effect.

    Science.gov (United States)

    Honjo, Keita; Shiraki, Hiroto; Ashina, Shuichi

    2018-01-01

    After the severe nuclear disaster in Fukushima, which was triggered by the Great East Japan earthquake in March 2011, nuclear power plants in Japan were temporarily shut down for mandatory inspections. To prevent large-scale blackouts, the Japanese government requested companies and households to reduce electricity consumption in summer and winter. It is reported that the domestic electricity demand had a structural decrease because of the electricity conservation effect (ECE). However, quantitative analysis of the ECE is not sufficient, and especially time variation of the ECE remains unclear. Understanding the ECE is important because Japan's NDC (nationally determined contribution) assumes the reduction of CO2 emissions through aggressive energy conservation. In this study, we develop a time series model of monthly electricity demand in Japan and estimate time variation of the ECE. Moreover, we evaluate the impact of electricity conservation on CO2 emissions from power plants. The dynamic linear model is used to separate the ECE from the effects of other irrelevant factors (e.g. air temperature, economic production, and electricity price). Our result clearly shows that consumers' electricity conservation behavior after the earthquake was not temporary but became established as a habit. Between March 2011 and March 2016, the ECE on industrial electricity demand ranged from 3.9% to 5.4%, and the ECE on residential electricity demand ranged from 1.6% to 7.6%. The ECE on the total electricity demand was estimated at 3.2%-6.0%. We found a seasonal pattern that the residential ECE in summer is higher than that in winter. The emissions increase from the shutdown of nuclear power plants was mitigated by electricity conservation. The emissions reduction effect was estimated at 0.82 MtCO2-2.26 MtCO2 (-4.5% on average compared to the zero-ECE case). The time-varying ECE is necessary for predicting Japan's electricity demand and CO2 emissions after the earthquake.

  3. Monthly to seasonal low flow prediction: statistical versus dynamical models

    Science.gov (United States)

    Ionita-Scholz, Monica; Klein, Bastian; Meissner, Dennis; Rademacher, Silke

    2016-04-01

    While the societal and economical impacts of floods are well documented and assessable, the impacts of lows flows are less studied and sometimes overlooked. For example, over the western part of Europe, due to intense inland waterway transportation, the economical loses due to low flows are often similar compared to the ones due to floods. In general, the low flow aspect has the tendency to be underestimated by the scientific community. One of the best examples in this respect is the facts that at European level most of the countries have an (early) flood alert system, but in many cases no real information regarding the development, evolution and impacts of droughts. Low flows, occurring during dry periods, may result in several types of problems to society and economy: e.g. lack of water for drinking, irrigation, industrial use and power production, deterioration of water quality, inland waterway transport, agriculture, tourism, issuing and renewing waste disposal permits, and for assessing the impact of prolonged drought on aquatic ecosystems. As such, the ever-increasing demand on water resources calls for better a management, understanding and prediction of the water deficit situation and for more reliable and extended studies regarding the evolution of the low flow situations. In order to find an optimized monthly to seasonal forecast procedure for the German waterways, the Federal Institute of Hydrology (BfG) is exploring multiple approaches at the moment. On the one hand, based on the operational short- to medium-range forecasting chain, existing hydrological models are forced with two different hydro-meteorological inputs: (i) resampled historical meteorology generated by the Ensemble Streamflow Prediction approach and (ii) ensemble (re-) forecasts of ECMWF's global coupled ocean-atmosphere general circulation model, which have to be downscaled and bias corrected before feeding the hydrological models. As a second approach BfG evaluates in cooperation with

  4. Forecasting of primary energy consumption data in the United States: A comparison between ARIMA and Holter-Winters models

    Science.gov (United States)

    Rahman, A.; Ahmar, A. S.

    2017-09-01

    This research has a purpose to compare ARIMA Model and Holt-Winters Model based on MAE, RSS, MSE, and RMS criteria in predicting Primary Energy Consumption Total data in the US. The data from this research ranges from January 1973 to December 2016. This data will be processed by using R Software. Based on the results of data analysis that has been done, it is found that the model of Holt-Winters Additive type (MSE: 258350.1) is the most appropriate model in predicting Primary Energy Consumption Total data in the US. This model is more appropriate when compared with Holt-Winters Multiplicative type (MSE: 262260,4) and ARIMA Seasonal model (MSE: 723502,2).

  5. Modeling Root Growth, Crop Growth and N Uptake of Winter Wheat Based on SWMS_2D: Model and Validation

    Directory of Open Access Journals (Sweden)

    Dejun Yang

    Full Text Available ABSTRACT Simulations for root growth, crop growth, and N uptake in agro-hydrological models are of significant concern to researchers. SWMS_2D is one of the most widely used physical hydrologically related models. This model solves equations that govern soil-water movement by the finite element method, and has a public access source code. Incorporating key agricultural components into the SWMS_2D model is of practical importance, especially for modeling some critical cereal crops such as winter wheat. We added root growth, crop growth, and N uptake modules into SWMS_2D. The root growth model had two sub-models, one for root penetration and the other for root length distribution. The crop growth model used was adapted from EU-ROTATE_N, linked to the N uptake model. Soil-water limitation, nitrogen limitation, and temperature effects were all considered in dry-weight modeling. Field experiments for winter wheat in Bouwing, the Netherlands, in 1983-1984 were selected for validation. Good agreements were achieved between simulations and measurements, including soil water content at different depths, normalized root length distribution, dry weight and nitrogen uptake. This indicated that the proposed new modules used in the SWMS_2D model are robust and reliable. In the future, more rigorous validation should be carried out, ideally under 2D situations, and attention should be paid to improve some modules, including the module simulating soil N mineralization.

  6. Empirical models of monthly and annual surface albedo in managed boreal forests of Norway

    Science.gov (United States)

    Bright, Ryan M.; Astrup, Rasmus; Strømman, Anders H.

    2013-04-01

    As forest management activities play an increasingly important role in climate change mitigation strategies of Nordic regions such as Norway, Sweden, and Finland -- the need for a more comprehensive understanding of the types and magnitude of biogeophysical climate effects and their various tradeoffs with the global carbon cycle becomes essential to avoid implementation of sub-optimal policy. Forest harvest in these regions reduces the albedo "masking effect" and impacts Earth's radiation budget in opposing ways to that of concomitant carbon cycle perturbations; thus, policies based solely on biogeochemical considerations in these regions risk being counterproductive. There is therefore a need to better understand how human disturbances (i.e., forest management activities) affect important biophysical factors like surface albedo. An 11-year remotely sensed surface albedo dataset coupled with stand-level forest management data for a variety of stands in Norway's most productive logging region are used to develop regression models describing temporal changes in monthly and annual forest albedo following clear-cut harvest disturbance events. Datasets are grouped by dominant tree species and site indices (productivity), and two alternate multiple regression models are developed and tested following a potential plus modifier approach. This resulted in an annual albedo model with statistically significant parameters that explains a large proportion of the observed variation, requiring as few as two predictor variables: i) average stand age - a canopy modifier predictor of albedo, and ii) stand elevation - a local climate predictor of a forest's potential albedo. The same model structure is used to derive monthly albedo models, with models for winter months generally found superior to summer models, and conifer models generally outperforming deciduous. We demonstrate how these statistical models can be applied to routine forest inventory data to predict the albedo

  7. Numerical Modeling of Persistent Winter Fog over the Indo-Gangetic Plains

    Science.gov (United States)

    Ghimire, S.; Adhikary, B.; Praveen, P. S.; Panday, A. K.

    2017-12-01

    Every winter the Indo-Gangetic Plains (IGP) in northern South Asia; bounded by the great Himalayas in the north, are periodically covered by dense and persistent fog that severely impacts day-to-day activities of several hundred million people. The fog can stretch over several hundred kilometers and last several days in many locations. Despite the fog's high impact, there are very limited in-situ observations available to characterize persistent fog episodes. Also, there has been very little success to date in accurately predicting the fog occurrence and extent over a larger area such as IGP. This study will present insights into the performance of the Weather Research and Forecasting (WRF) model simulating persistent winter fog prediction in the IGP region, compared to satellite observations and in-situ measurements. Since fog is not a prognostic variable in WRF, the study presents results based on multi-rule diagnostic algorithms published in peer reviewed journals. In addition, fog episodes were analyzed using the Air Force Weather Agency (AFWA) diagnostics package available for WRF. On a regional scale, MODIS data onboard the TERRA and AQUA satellites are used to evaluate model performance skills. At a local scale, the model is evaluated at two sites in the southern Nepal, Lumbini and Chitwan, located in the IGP. Lumbini and Chitwan observatories have Luftt and Biral weather sensors which allow monitoring presence of fog, visibility range and surface meteorology. In addition, for Chitwan, data from DMT Fog Monitor (FM 120) and Luftt CHM 15K Ceilometer were used to compare model performance for liquid-water content and planetary boundary layer during foggy and non-foggy days.

  8. Diagnosis and Modeling of the Explosive Development of Winter Storms: Sensitivity to PBL Schemes

    Science.gov (United States)

    Liberato, Margarida L. R.; Pradhan, Prabodha K.

    2014-05-01

    The correct representation of extreme windstorms in regional models is of great importance for impact studies of climate change. The Iberian Peninsula has recently witnessed major damage from winter extratropical intense cyclones like Klaus (January 2009), Xynthia (February 2010) and Gong (January 2013) which formed over the mid-Atlantic, experienced explosive intensification while travelling eastwards at lower latitudes than usual [Liberato et al. 2011; 2013]. In this paper the explosive development of these storms is simulated by the advanced mesoscale Weather Research and Forecasting Model (WRF v 3.4.1), initialized with NCEP Final Analysis (FNL) data as initial and lateral boundary conditions (boundary conditions updated in every 3 hours intervals). The simulation experiments are conducted with two domains, a coarser (25km) and nested (8.333km), covering the entire North Atlantic and Iberian Peninsula region. The characteristics of these storms (e.g. wind speed, precipitation) are studied from WRF model and compared with multiple observations. In this context simulations with different Planetary Boundary Layer (PBL) schemes are performed. This approach aims at understanding which mechanisms favor the explosive intensification of these storms at a lower than usual latitudes, thus improving the knowledge of atmospheric dynamics (including small-scale processes) on controlling the life cycle of midlatitude extreme storms and contributing to the improvement in predictability and in our ability to forecast storms' impacts over Iberian Peninsula. Acknowledgments: This work was partially supported by FEDER (Fundo Europeu de Desenvolvimento Regional) funds through the COMPETE (Programa Operacional Factores de Competitividade) and by national funds through FCT (Fundação para a Ciência e a Tecnologia, Portugal) under project STORMEx FCOMP-01-0124-FEDER- 019524 (PTDC/AAC-CLI/121339/2010). References: Liberato M.L.R., J.G. Pinto, I.F. Trigo, R.M. Trigo (2011) Klaus - an

  9. Development of groundwater pesticide exposure modeling scenarios for vulnerable spring and winter wheat-growing areas.

    Science.gov (United States)

    Padilla, Lauren; Winchell, Michael; Peranginangin, Natalia; Grant, Shanique

    2017-11-01

    Wheat crops and the major wheat-growing regions of the United States are not included in the 6 crop- and region-specific scenarios developed by the US Environmental Protection Agency (USEPA) for exposure modeling with the Pesticide Root Zone Model conceptualized for groundwater (PRZM-GW). The present work augments the current scenarios by defining appropriately vulnerable PRZM-GW scenarios for high-producing spring and winter wheat-growing regions that are appropriate for use in refined pesticide exposure assessments. Initial screening-level modeling was conducted for all wheat areas across the conterminous United States as defined by multiple years of the Cropland Data Layer land-use data set. Soil, weather, groundwater temperature, evaporation depth, and crop growth and management practices were characterized for each wheat area from publicly and nationally available data sets and converted to input parameters for PRZM. Approximately 150 000 unique combinations of weather, soil, and input parameters were simulated with PRZM for an herbicide applied for postemergence weed control in wheat. The resulting postbreakthrough average herbicide concentrations in a theoretical shallow aquifer were ranked to identify states with the largest regions of relatively vulnerable wheat areas. For these states, input parameters resulting in near 90 th percentile postbreakthrough average concentrations corresponding to significant wheat areas with shallow depth to groundwater formed the basis for 4 new spring wheat scenarios and 4 new winter wheat scenarios to be used in PRZM-GW simulations. Spring wheat scenarios were identified in North Dakota, Montana, Washington, and Texas. Winter wheat scenarios were identified in Oklahoma, Texas, Kansas, and Colorado. Compared to the USEPA's original 6 scenarios, postbreakthrough average herbicide concentrations in the new scenarios were lower than all but Florida Potato and Georgia Coastal Peanuts of the original scenarios and better

  10. Assessing winter cover crop nutrient uptake efficiency using a water quality simulation model

    OpenAIRE

    Yeo, I.-Y.; Lee, S.; Sadeghi, A. M.; Beeson, P. C.; Hively, W. D.; McCarty, G. W.; Lang, M. W.

    2014-01-01

    Winter cover crops are an effective conservation management practice with potential to improve water quality. Throughout the Chesapeake Bay watershed (CBW), which is located in the mid-Atlantic US, winter cover crop use has been emphasized, and federal and state cost-share programs are available to farmers to subsidize the cost of cover crop establishment. The objective of this study was to assess the long-term effect of planting winter cover crops to improve water quality a...

  11. The influence of boreal spring Arctic Oscillation on the subsequent winter ENSO in CMIP5 models

    Science.gov (United States)

    Chen, Shangfeng; Chen, Wen; Yu, Bin

    2017-05-01

    This study examines the influence of boreal spring Arctic Oscillation (AO) on the subsequent winter El Niño-Southern Oscillation (ENSO) using 15 climate model outputs from the Coupled Model Intercomparison Project Phase 5 (CMIP5). Results show that, out of the 15 CMIP5 models, CCSM4 and CNRM-CM5 can well reproduce the significant AO-ENSO connection. These two models capture the observed spring AO related anomalous cyclone (anticyclone) over the subtropical western-central North Pacific, and westerly (easterly) winds over the tropical western-central Pacific. In contrast, the spring AO-related anomalous circulation over the subtropical North Pacific is insignificant in the other 13 models, and the simulations in these models cannot capture the significant influence of the spring AO on ENSO. Further analyses indicate that the performance of the CMIP5 simulations in reproducing the AO-ENSO connection is related to the ability in simulating the spring North Pacific synoptic eddy intensity and the spring AO's Pacific component. Strong synoptic-scale eddy intensity results in a strong synoptic eddy feedback on the mean flow, leading to strong cyclonic circulation anomalies over the subtropical North Pacific, which contributes to a significant AO-ENSO connection. In addition, a strong spring AO's Pacific component and associated easterly wind anomalies to its south may provide more favorable conditions for the development of spring AO-related cyclonic circulation anomalies over the subtropical North Pacific.

  12. A Winter Distribution Model for Bicknell’s Thrush (Catharus bicknelli), a Conservation Tool for a Threatened Migratory Songbird

    Science.gov (United States)

    McFarland, Kent P.; Rimmer, Christopher C.; Goetz, James E.; Aubry, Yves; Wunderle, Joseph M.; Sutton, Anne; Townsend, Jason M.; Sosa, Alejandro Llanes; Kirkconnell, Arturo

    2013-01-01

    Conservation planning and implementation require identifying pertinent habitats and locations where protection and management may improve viability of targeted species. The winter range of Bicknell’s Thrush (Catharus bicknelli), a threatened Nearctic-Neotropical migratory songbird, is restricted to the Greater Antilles. We analyzed winter records from the mid-1970s to 2009 to quantitatively evaluate winter distribution and habitat selection. Additionally, we conducted targeted surveys in Jamaica (n = 433), Cuba (n = 363), Dominican Republic (n = 1,000), Haiti (n = 131) and Puerto Rico (n = 242) yielding 179 sites with thrush presence. We modeled Bicknell’s Thrush winter habitat selection and distribution in the Greater Antilles in Maxent version 3.3.1. using environmental predictors represented in 30 arc second study area rasters. These included nine landform, land cover and climatic variables that were thought a priori to have potentially high predictive power. We used the average training gain from ten model runs to select the best subset of predictors. Total winter precipitation, aspect and land cover, particularly broadleaf forests, emerged as important variables. A five-variable model that contained land cover, winter precipitation, aspect, slope, and elevation was the most parsimonious and not significantly different than the models with more variables. We used the best fitting model to depict potential winter habitat. Using the 10 percentile threshold (>0.25), we estimated winter habitat to cover 33,170 km2, nearly 10% of the study area. The Dominican Republic contained half of all potential habitat (51%), followed by Cuba (15.1%), Jamaica (13.5%), Haiti (10.6%), and Puerto Rico (9.9%). Nearly one-third of the range was found to be in protected areas. By providing the first detailed predictive map of Bicknell’s Thrush winter distribution, our study provides a useful tool to prioritize and direct conservation planning for this and

  13. Route prediction model of infectious diseases for 2018 Winter Olympics in Korea

    International Nuclear Information System (INIS)

    Kim, Eungyeong; Lee, Seok; Byun, Young Tae; Kim, Jae Hun; Lee, Taikjin; Lee, Hyuk-jae

    2014-01-01

    There are many types of respiratory infectious diseases caused by germs, virus, mycetes and parasites. Researchers recently have tried to develop mathematical models to predict the epidemic of infectious diseases. However, with the development of ground transportation system in modern society, the spread of infectious diseases became faster and more complicated in terms of the speed and the pathways. The route of infectious diseases during Vancouver Olympics was predicted based on the Susceptible-Infectious-Recovered (SIR) model. In this model only the air traffic as an essential factor for the intercity migration of infectious diseases was involved. Here, we propose a multi-city transmission model to predict the infection route during 2018 Winter Olympics in Korea based on the pre-existing SIR model. Various types of transportation system such as a train, a car, a bus, and an airplane for the interpersonal contact in both inter- and intra-city are considered. Simulation is performed with assumptions and scenarios based on realistic factors including demographic, transportation and diseases data in Korea. Finally, we analyze an economic profit and loss caused by the variation of the number of tourists during the Olympics

  14. Route prediction model of infectious diseases for 2018 Winter Olympics in Korea

    Science.gov (United States)

    Kim, Eungyeong; Lee, Seok; Byun, Young Tae; Kim, Jae Hun; Lee, Hyuk-jae; Lee, Taikjin

    2014-03-01

    There are many types of respiratory infectious diseases caused by germs, virus, mycetes and parasites. Researchers recently have tried to develop mathematical models to predict the epidemic of infectious diseases. However, with the development of ground transportation system in modern society, the spread of infectious diseases became faster and more complicated in terms of the speed and the pathways. The route of infectious diseases during Vancouver Olympics was predicted based on the Susceptible-Infectious-Recovered (SIR) model. In this model only the air traffic as an essential factor for the intercity migration of infectious diseases was involved. Here, we propose a multi-city transmission model to predict the infection route during 2018 Winter Olympics in Korea based on the pre-existing SIR model. Various types of transportation system such as a train, a car, a bus, and an airplane for the interpersonal contact in both inter- and intra-city are considered. Simulation is performed with assumptions and scenarios based on realistic factors including demographic, transportation and diseases data in Korea. Finally, we analyze an economic profit and loss caused by the variation of the number of tourists during the Olympics.

  15. Modeling large-scale winter recreation terrain selection with implications for recreation management and wildlife

    Science.gov (United States)

    Lucretia E. Olson; John R. Squires; Elizabeth K. Roberts; Aubrey D. Miller; Jacob S. Ivan; Mark Hebblewhite

    2017-01-01

    Winter recreation is a rapidly growing activity, and advances in technology make it possible for increasing numbers of people to access remote backcountry terrain. Increased winter recreation may lead to more frequent conflict between recreationists, as well as greater potential disturbance to wildlife. To better understand the environmental characteristics favored by...

  16. Interannual control of plankton communities by deep winter mixing and prey/predator interactions in the NW Mediterranean: Results from a 30-year 3D modeling study

    Science.gov (United States)

    Auger, P. A.; Ulses, C.; Estournel, C.; Stemmann, L.; Somot, S.; Diaz, F.

    2014-05-01

    A realistic modeling approach is designed to address the role of winter mixing on the interannual variability of plankton dynamics in the north-western (NW) Mediterranean basin. For the first time, a high-resolution coupled hydrodynamic-biogeochemical model (Eco3m-S) covering a 30-year period (1976-2005) is validated on available in situ and satellite data for the NW Mediterranean. In this region, cold, dry winds in winter often lead to deep convection and strong upwelling of nutrients into the euphotic layer. High nutrient contents at the end of winter then support the development of a strong spring bloom of phytoplankton. Model results indicate that annual primary production is not affected by winter mixing due to seasonal balance (minimum in winter and maximum in spring). However, the total annual water column-integrated phytoplankton biomass appears to be favored by winter mixing because zooplankton grazing activity is low in winter and early spring. This reduced grazing is explained here by the rarefaction of prey due to both light limitation and the effect of mixing-induced dilution on prey/predator interactions. A negative impact of winter mixing on winter zooplankton biomass is generally simulated except for mesozooplankton. This difference is assumed to stem from the lower parameterized mortality, top trophic position and detritivorous diet of mesozooplankton in the model. Moreover, model suggests that the variability of annual mesozooplankton biomass is principally modulated by the effects of winter mixing on winter biomass. Thus, interannual variability of winter nutrient contents in the euphotic layer, resulting from winter mixing, would control spring primary production and thus annual mesozooplankton biomass. Our results show a bottom-up control of mesozooplankton communities, as observed at a coastal location of the Ligurian Sea.

  17. Modelling economic losses of historic and present-day high-impact winter storms in Switzerland

    Science.gov (United States)

    Welker, Christoph; Martius, Olivia; Stucki, Peter; Bresch, David; Dierer, Silke; Brönnimann, Stefan

    2015-04-01

    simulate the wind field and related economic impact of both historic and present-day high-impact winter storms in Switzerland since end of the 19th century. Our technique involves the dynamical downscaling of the 20CR to 3 km horizontal resolution using the numerical Weather Research and Forecasting model and the subsequent loss simulation using an open-source impact model. This impact model estimates, for modern economic and social conditions, storm-related economic losses at municipality level, and thus allows a numerical simulation of the impact from both historic and present-day severe winter storms in Switzerland on a relatively fine spatial scale. In this study, we apply the modelling chain to a storm sample of almost 90 high-impact winter storms in Switzerland since 1871, and we are thus able to make a statement of the typical wind and loss patterns of hazardous windstorms in Switzerland. To evaluate our modelling chain, we compare simulated storm losses with insurance loss data for the present-day windstorms "Lothar" and "Joachim" in December 1999 and December 2011, respectively. Our study further includes a range of sensitivity experiments and a discussion of the main sources of uncertainty.

  18. Simulation model for longterm management of Avena fatua L. in winter wheat

    Directory of Open Access Journals (Sweden)

    Jäck, Ortrud

    2014-02-01

    Full Text Available Decision support systems (DSS are used for weed control decisions worldwide. Several DSS for weed management have been published. However they mostly rely on full herbicide dosages and do not take weed population dynamics into account. We developed a modular DSS for long-term Avena fatua L. control in winter wheat. The DSS was parameterized with three year field experiment datasets covering yield loss data, densitydependent population dynamics data as well as data on dose dependent herbicide efficacy and dosedependent population dynamics. The DSS aims to control the A. fatua in the long run. Our hypothesis is that the optimized DSS reduces herbicide input while keeping the population density at low level, maintaining high grain yields and net return. The DSS comprises four sub-models calculating crop yield loss, A. fatua population dynamics as well as dose dependent herbicide efficacy and economics of the weed control decision. The economic sub-model calculates net return in dependency of the herbicide dosage and thus the resulting crop yield. First results of a 10-year simulation showed that herbicide input could be reduced by 40% compared to the economic threshold strategy, while the population density of A. fatua is controlled. Up to now the DSS has been parameterized for the herbicides Ralon Super, Axial 50 and Broadway. The results show the great potential of reducing herbicide input and point out the importance of including population dynamics models into DSS.

  19. Dynamic linear modeling of monthly electricity demand in Japan: Time variation of electricity conservation effect.

    Directory of Open Access Journals (Sweden)

    Keita Honjo

    Full Text Available After the severe nuclear disaster in Fukushima, which was triggered by the Great East Japan earthquake in March 2011, nuclear power plants in Japan were temporarily shut down for mandatory inspections. To prevent large-scale blackouts, the Japanese government requested companies and households to reduce electricity consumption in summer and winter. It is reported that the domestic electricity demand had a structural decrease because of the electricity conservation effect (ECE. However, quantitative analysis of the ECE is not sufficient, and especially time variation of the ECE remains unclear. Understanding the ECE is important because Japan's NDC (nationally determined contribution assumes the reduction of CO2 emissions through aggressive energy conservation. In this study, we develop a time series model of monthly electricity demand in Japan and estimate time variation of the ECE. Moreover, we evaluate the impact of electricity conservation on CO2 emissions from power plants. The dynamic linear model is used to separate the ECE from the effects of other irrelevant factors (e.g. air temperature, economic production, and electricity price. Our result clearly shows that consumers' electricity conservation behavior after the earthquake was not temporary but became established as a habit. Between March 2011 and March 2016, the ECE on industrial electricity demand ranged from 3.9% to 5.4%, and the ECE on residential electricity demand ranged from 1.6% to 7.6%. The ECE on the total electricity demand was estimated at 3.2%-6.0%. We found a seasonal pattern that the residential ECE in summer is higher than that in winter. The emissions increase from the shutdown of nuclear power plants was mitigated by electricity conservation. The emissions reduction effect was estimated at 0.82 MtCO2-2.26 MtCO2 (-4.5% on average compared to the zero-ECE case. The time-varying ECE is necessary for predicting Japan's electricity demand and CO2 emissions after the

  20. Dynamic linear modeling of monthly electricity demand in Japan: Time variation of electricity conservation effect

    Science.gov (United States)

    Shiraki, Hiroto; Ashina, Shuichi

    2018-01-01

    After the severe nuclear disaster in Fukushima, which was triggered by the Great East Japan earthquake in March 2011, nuclear power plants in Japan were temporarily shut down for mandatory inspections. To prevent large-scale blackouts, the Japanese government requested companies and households to reduce electricity consumption in summer and winter. It is reported that the domestic electricity demand had a structural decrease because of the electricity conservation effect (ECE). However, quantitative analysis of the ECE is not sufficient, and especially time variation of the ECE remains unclear. Understanding the ECE is important because Japan’s NDC (nationally determined contribution) assumes the reduction of CO2 emissions through aggressive energy conservation. In this study, we develop a time series model of monthly electricity demand in Japan and estimate time variation of the ECE. Moreover, we evaluate the impact of electricity conservation on CO2 emissions from power plants. The dynamic linear model is used to separate the ECE from the effects of other irrelevant factors (e.g. air temperature, economic production, and electricity price). Our result clearly shows that consumers’ electricity conservation behavior after the earthquake was not temporary but became established as a habit. Between March 2011 and March 2016, the ECE on industrial electricity demand ranged from 3.9% to 5.4%, and the ECE on residential electricity demand ranged from 1.6% to 7.6%. The ECE on the total electricity demand was estimated at 3.2%–6.0%. We found a seasonal pattern that the residential ECE in summer is higher than that in winter. The emissions increase from the shutdown of nuclear power plants was mitigated by electricity conservation. The emissions reduction effect was estimated at 0.82 MtCO2–2.26 MtCO2 (−4.5% on average compared to the zero-ECE case). The time-varying ECE is necessary for predicting Japan’s electricity demand and CO2 emissions after the

  1. Sensitivities of crop models to extreme weather conditions during flowering period demonstrated for maize and winter wheat in Austria

    Czech Academy of Sciences Publication Activity Database

    Eitzinger, Josef; Thaler, S.; Schmid, E.; Strauss, F.; Ferrise, R.; Moriondo, M.; Bindi, M.; Palosuo, T.; Rötter, R.; Kersebaum, K. C.; Olesen, J. E.; Patil, R. H.; Saylan, L.; Çaldag, B.; Caylak, O.

    2013-01-01

    Roč. 151, č. 6 (2013), s. 813-835 ISSN 0021-8596 R&D Projects: GA MŠk(CZ) ED1.1.00/02.0073 Institutional support: RVO:67179843 Keywords : crop models * weather conditions * winter wheat * Austria Subject RIV: EH - Ecology, Behaviour Impact factor: 2.891, year: 2013

  2. The influence of winter convection on primary production: A parameterisation using a hydrostatic three-dimensional biogeochemical model

    DEFF Research Database (Denmark)

    Grosse, Fabian; Lindemann, Christian; Pätch, Johannes

    2014-01-01

    organic carbon. The carbon export during late winter/early spring significantly exceeded the export of the reference run. Furthermore, a non-hydrostatic convection model was used to evaluate the major assumption of the presented parameterisation which implies the matching of the mixed layer depth...

  3. Predicting Pre-planting Risk of Stagonospora nodorum blotch in Winter Wheat Using Machine Learning Models

    Directory of Open Access Journals (Sweden)

    Lucky eMehra

    2016-03-01

    Full Text Available Pre-planting factors have been associated with the late-season severity of Stagonospora nodorum blotch (SNB, caused by the fungal pathogen Parastagonospora nodorum, in winter wheat (Triticum aestivum. The relative importance of these factors in the risk of SNB has not been determined and this knowledge can facilitate disease management decisions prior to planting of the wheat crop. In this study, we examined the performance of multiple regression (MR and three machine learning algorithms namely artificial neural networks, categorical and regression trees, and random forests (RF in predicting the pre-planting risk of SNB in wheat. Pre-planting factors tested as potential predictor variables were cultivar resistance, latitude, longitude, previous crop, seeding rate, seed treatment, tillage type, and wheat residue. Disease severity assessed at the end of the growing season was used as the response variable. The models were developed using 431 disease cases (unique combinations of predictors collected from 2012 to 2014 and these cases were randomly divided into training, validation, and test datasets. Models were evaluated based on the regression of observed against predicted severity values of SNB, sensitivity-specificity ROC analysis, and the Kappa statistic. A strong relationship was observed between late-season severity of SNB and specific pre-planting factors in which latitude, longitude, wheat residue, and cultivar resistance were the most important predictors. The MR model explained 33% of variability in the data, while machine learning models explained 47 to 79% of the total variability. Similarly, the MR model correctly classified 74% of the disease cases, while machine learning models correctly classified 81 to 83% of these cases. Results show that the RF algorithm, which explained 79% of the variability within the data, was the most accurate in predicting the risk of SNB, with an accuracy rate of 93%. The RF algorithm could allow early

  4. Predicting Pre-planting Risk of Stagonospora nodorum blotch in Winter Wheat Using Machine Learning Models.

    Science.gov (United States)

    Mehra, Lucky K; Cowger, Christina; Gross, Kevin; Ojiambo, Peter S

    2016-01-01

    Pre-planting factors have been associated with the late-season severity of Stagonospora nodorum blotch (SNB), caused by the fungal pathogen Parastagonospora nodorum, in winter wheat (Triticum aestivum). The relative importance of these factors in the risk of SNB has not been determined and this knowledge can facilitate disease management decisions prior to planting of the wheat crop. In this study, we examined the performance of multiple regression (MR) and three machine learning algorithms namely artificial neural networks, categorical and regression trees, and random forests (RF), in predicting the pre-planting risk of SNB in wheat. Pre-planting factors tested as potential predictor variables were cultivar resistance, latitude, longitude, previous crop, seeding rate, seed treatment, tillage type, and wheat residue. Disease severity assessed at the end of the growing season was used as the response variable. The models were developed using 431 disease cases (unique combinations of predictors) collected from 2012 to 2014 and these cases were randomly divided into training, validation, and test datasets. Models were evaluated based on the regression of observed against predicted severity values of SNB, sensitivity-specificity ROC analysis, and the Kappa statistic. A strong relationship was observed between late-season severity of SNB and specific pre-planting factors in which latitude, longitude, wheat residue, and cultivar resistance were the most important predictors. The MR model explained 33% of variability in the data, while machine learning models explained 47 to 79% of the total variability. Similarly, the MR model correctly classified 74% of the disease cases, while machine learning models correctly classified 81 to 83% of these cases. Results show that the RF algorithm, which explained 79% of the variability within the data, was the most accurate in predicting the risk of SNB, with an accuracy rate of 93%. The RF algorithm could allow early assessment of

  5. Statistical modelling of monthly mean sea level at coastal tide gauge stations along the Indian subcontinent

    Digital Repository Service at National Institute of Oceanography (India)

    Srinivas, K.; Das, V.K.; DineshKumar, P.K.

    This study investigates the suitability of statistical models for their predictive potential for the monthly mean sea level at different stations along the west and east coasts of the Indian subcontinent. Statistical modelling of the monthly mean...

  6. Modeling a typical winter-time dust event over the Arabian Peninsula and the Red Sea

    Directory of Open Access Journals (Sweden)

    S. Kalenderski

    2013-02-01

    Full Text Available We used WRF-Chem, a regional meteorological model coupled with an aerosol-chemistry component, to simulate various aspects of the dust phenomena over the Arabian Peninsula and Red Sea during a typical winter-time dust event that occurred in January 2009. The model predicted that the total amount of emitted dust was 18.3 Tg for the entire dust outburst period and that the two maximum daily rates were ~2.4 Tg day−1 and ~1.5 Tg day−1, corresponding to two periods with the highest aerosol optical depth that were well captured by ground- and satellite-based observations. The model predicted that the dust plume was thick, extensive, and mixed in a deep boundary layer at an altitude of 3–4 km. Its spatial distribution was modeled to be consistent with typical spatial patterns of dust emissions. We utilized MODIS-Aqua and Solar Village AERONET measurements of the aerosol optical depth (AOD to evaluate the radiative impact of aerosols. Our results clearly indicated that the presence of dust particles in the atmosphere caused a significant reduction in the amount of solar radiation reaching the surface during the dust event. We also found that dust aerosols have significant impact on the energy and nutrient balances of the Red Sea. Our results showed that the simulated cooling under the dust plume reached 100 W m−2, which could have profound effects on both the sea surface temperature and circulation. Further analysis of dust generation and its spatial and temporal variability is extremely important for future projections and for better understanding of the climate and ecological history of the Red Sea.

  7. Modeling a typical winter-time dust event over the Arabian Peninsula and the Red Sea

    KAUST Repository

    Kalenderski, Stoitchko

    2013-02-20

    We used WRF-Chem, a regional meteorological model coupled with an aerosol-chemistry component, to simulate various aspects of the dust phenomena over the Arabian Peninsula and Red Sea during a typical winter-time dust event that occurred in January 2009. The model predicted that the total amount of emitted dust was 18.3 Tg for the entire dust outburst period and that the two maximum daily rates were ?2.4 Tg day-1 and ?1.5 Tg day-1, corresponding to two periods with the highest aerosol optical depth that were well captured by ground-and satellite-based observations. The model predicted that the dust plume was thick, extensive, and mixed in a deep boundary layer at an altitude of 3-4 km. Its spatial distribution was modeled to be consistent with typical spatial patterns of dust emissions. We utilized MODIS-Aqua and Solar Village AERONET measurements of the aerosol optical depth (AOD) to evaluate the radiative impact of aerosols. Our results clearly indicated that the presence of dust particles in the atmosphere caused a significant reduction in the amount of solar radiation reaching the surface during the dust event. We also found that dust aerosols have significant impact on the energy and nutrient balances of the Red Sea. Our results showed that the simulated cooling under the dust plume reached 100 W m-2, which could have profound effects on both the sea surface temperature and circulation. Further analysis of dust generation and its spatial and temporal variability is extremely important for future projections and for better understanding of the climate and ecological history of the Red Sea.

  8. Modelling and Evaluation of Non-Linear Rootwater Uptake for Winter Cropping of Wheat and Berseem

    Science.gov (United States)

    GS, K.; Prasad, K. S. H.

    2017-12-01

    The plant water uptake is significant for study to monitor the irrigation supplied to the plant. The Richards equation has been the key governing equation to quantify the root water uptake in the vadose zone and it takes all the sources and sink terms into consideration. The β parameter or the non linearity parameter is used in this modeling to bring the non linearity in the plant root water uptake. The soil parameters are obtained by experimentation and are employed in the Van-Genuchten equation for soil moisture study. Field experiments were carried out at Civil Engineering Department IIT Roorkee, Uttarakhand, India, during the winter season of 2013 and 2014 for berseem and 2016 for wheat as per the local cropping practices. Drainage type lysimeters were installed to study the soil water balance. Soil moisture was monitored using profile probe. Precipitation and all meteorological data were obtained from the nearby gauges located at the National Institute of Hydrology, Roorkee.The moisture data and the deep percolation data were collected on a daily basis and the irrigation supply was controlled and monitored to satisfy the moisture requirements of the crops respectively.In order to study the effect of water scarcity on the crops, the plot was divided and deficited irrigation was applied for the second cropping season for Berseem.The yields for both the seasons was also measured. The solution of Richards equation as applied to the moisture movement in the root zone was modeled. For estimation of root water uptake, the governing equation is the one-dimensional mixed form of Richards' equation is employed (Ji et al., 2007; Shankar et al., 2012).The sink term in the model accounts for the root water uptake, which is utilized by the plant for transpiration. Smaxor the maximum root water uptake for the root zone on a given day must be equal to the maximum transpiration on the corresponding day The model computed moisture content and pressure head is calibrated with

  9. Mediterranean Thermohaline Response to Large-Scale Winter Atmospheric Forcing in a High-Resolution Ocean Model Simulation

    Science.gov (United States)

    Cusinato, Eleonora; Zanchettin, Davide; Sannino, Gianmaria; Rubino, Angelo

    2018-04-01

    Large-scale circulation anomalies over the North Atlantic and Euro-Mediterranean regions described by dominant climate modes, such as the North Atlantic Oscillation (NAO), the East Atlantic pattern (EA), the East Atlantic/Western Russian (EAWR) and the Mediterranean Oscillation Index (MOI), significantly affect interannual-to-decadal climatic and hydroclimatic variability in the Euro-Mediterranean region. However, whereas previous studies assessed the impact of such climate modes on air-sea heat and freshwater fluxes in the Mediterranean Sea, the propagation of these atmospheric forcing signals from the surface toward the interior and the abyss of the Mediterranean Sea remains unexplored. Here, we use a high-resolution ocean model simulation covering the 1979-2013 period to investigate spatial patterns and time scales of the Mediterranean thermohaline response to winter forcing from NAO, EA, EAWR and MOI. We find that these modes significantly imprint on the thermohaline properties in key areas of the Mediterranean Sea through a variety of mechanisms. Typically, density anomalies induced by all modes remain confined in the upper 600 m depth and remain significant for up to 18-24 months. One of the clearest propagation signals refers to the EA in the Adriatic and northern Ionian seas: There, negative EA anomalies are associated to an extensive positive density response, with anomalies that sink to the bottom of the South Adriatic Pit within a 2-year time. Other strong responses are the thermally driven responses to the EA in the Gulf of Lions and to the EAWR in the Aegean Sea. MOI and EAWR forcing of thermohaline properties in the Eastern Mediterranean sub-basins seems to be determined by reinforcement processes linked to the persistency of these modes in multiannual anomalous states. Our study also suggests that NAO, EA, EAWR and MOI could critically interfere with internal, deep and abyssal ocean dynamics and variability in the Mediterranean Sea.

  10. Modeling of meteorology, chemistry and aerosol for the 2017 Utah Winter Fine Particle Study

    Science.gov (United States)

    McKeen, S. A.; Angevine, W. M.; McDonald, B.; Ahmadov, R.; Franchin, A.; Middlebrook, A. M.; Fibiger, D. L.; McDuffie, E. E.; Womack, C.; Brown, S. S.; Moravek, A.; Murphy, J. G.; Trainer, M.

    2017-12-01

    The Utah Winter Fine Particle Study (UWFPS-17) field project took place during January and February of 2017 within the populated region of the Great Salt Lake, Utah. The study focused on understanding the meteorology and chemistry associated with high particulate matter (PM) levels often observed near Salt Lake City during stable wintertime conditions. Detailed composition and meteorological observations were taken from the NOAA Twin-Otter aircraft and several surface sites during the study period, and extremely high aerosol conditions were encountered for two cold-pool episodes occurring in the last 2 weeks of January. A clear understanding of the photochemical and aerosol processes leading to these high PM events is still lacking. Here we present high spatiotemporal resolution simulations of meteorology, PM and chemistry over Utah from January 13 to February 1, 2017 using the WRF/Chem photochemical model. Correctly characterizing the meteorology is difficult due to the complex terrain and shallow inversion layers. We discuss the approach and limitations of the simulated meteorology, and evaluate low-level pollutant mixing using vertical profiles from missed airport approaches by the NOAA Twin-Otter performed routinely during each flight. Full photochemical simulations are calculated using NOx, ammonia and VOC emissions from the U.S. EPA NEI-2011 emissions inventory. Comparisons of the observed vertical column amounts of NOx, ammonia, aerosol nitrate and ammonium with model results shows the inventory estimates for ammonia emissions are low by a factor of four and NOx emissions are low by nearly a factor of two. The partitioning of both nitrate and NH3 between gas and particle phase depends strongly on the NH3 and NOx emissions to the model and calculated NOx to nitrate conversion rates. These rates are underestimated by gas-phase chemistry alone, even though surface snow albedo increases photolysis rates by nearly a factor of two. Several additional conversion

  11. Winter Dew Harvest in Mexico City

    Directory of Open Access Journals (Sweden)

    Arias-Torres Jorge Ernesto

    2015-12-01

    Full Text Available This study presents experimental and theoretical results of winter dew harvest in México City in terms of condensation rate. A simplified theoretical model based on a steady-state energy balance on a radiator-condenser was fitted, as a function of the ambient temperature, the relative humidity and the wind velocity. A glass sheet and aluminum sheet white-painted were used as samples over the outdoor experiments. A good correlation was obtained between the theoretical and experimental data. The experimental results show that there was condensation in 68% of the winter nights on both condensers. The total winter condensed mass was 2977 g/m2 and 2888 g/m2 on the glass sheet and aluminum sheet white-painted, respectively. Thus, the condensed mass on the glass was only 3% higher than that on the painted surface. The maximum nightly dew harvests occurred during December, which linearly reduced from 50 g/m2 night to 22 g/m2 night as the winter months went by. The condensation occurred from 1:00 a.m. to 9:00 a.m., with maximum condensation rates between 6:00 a.m. and 7:00 a.m. The dew harvest can provide a partial alternative to the winter water shortage in certain locations with similar climates to the winter in Mexico City, as long as pollution is not significant.

  12. Investigating added value of regional climate modeling in North American winter storm track simulations

    Science.gov (United States)

    Poan, E. D.; Gachon, P.; Laprise, R.; Aider, R.; Dueymes, G.

    2018-03-01

    Extratropical Cyclone (EC) characteristics depend on a combination of large-scale factors and regional processes. However, the latter are considered to be poorly represented in global climate models (GCMs), partly because their resolution is too coarse. This paper describes a framework using possibilities given by regional climate models (RCMs) to gain insight into storm activity during winter over North America (NA). Recent past climate period (1981-2005) is considered to assess EC activity over NA using the NCEP regional reanalysis (NARR) as a reference, along with the European reanalysis ERA-Interim (ERAI) and two CMIP5 GCMs used to drive the Canadian Regional Climate Model—version 5 (CRCM5) and the corresponding regional-scale simulations. While ERAI and GCM simulations show basic agreement with NARR in terms of climatological storm track patterns, detailed bias analyses show that, on the one hand, ERAI presents statistically significant positive biases in terms of EC genesis and therefore occurrence while capturing their intensity fairly well. On the other hand, GCMs present large negative intensity biases in the overall NA domain and particularly over NA eastern coast. In addition, storm occurrence over the northwestern topographic regions is highly overestimated. When the CRCM5 is driven by ERAI, no significant skill deterioration arises and, more importantly, all storm characteristics near areas with marked relief and over regions with large water masses are significantly improved with respect to ERAI. Conversely, in GCM-driven simulations, the added value contributed by CRCM5 is less prominent and systematic, except over western NA areas with high topography and over the Western Atlantic coastlines where the most frequent and intense ECs are located. Despite this significant added-value on seasonal-mean characteristics, a caveat is raised on the RCM ability to handle storm temporal `seriality', as a measure of their temporal variability at a given

  13. Winter is losing its cool

    Science.gov (United States)

    Feng, S.

    2017-12-01

    Winter seasons have significant societal impacts across all sectors ranging from direct human health to ecosystems, transportation, and recreation. This study quantifies the severity of winter and its spatial-temporal variations using a newly developed winter severity index and daily temperature, snowfall and snow depth. The winter severity and the number of extreme winter days are decreasing across the global terrestrial areas during 1901-2015 except the southeast United States and isolated regions in the Southern Hemisphere. These changes are dominated by winter warming, while the changes in daily snowfall and snow depth played a secondary role. The simulations of multiple CMIP5 climate models can well capture the spatial and temporal variations of the observed changes in winter severity and extremes during 1951-2005. The models are consistent in projecting a future milder winter under various scenarios. The winter severity is projected to decrease 60-80% in the middle-latitude Northern Hemisphere under the business-as-usual scenario. The winter arrives later, ends earlier and the length of winter season will be notably shorter. The changes in harsh winter in the polar regions are weak, mainly because the warming leads to more snowfall in the high latitudes.

  14. A general predictive model for estimating monthly ecosystem evapotranspiration

    Science.gov (United States)

    Ge Sun; Karrin Alstad; Jiquan Chen; Shiping Chen; Chelcy R. Ford; al. et.

    2011-01-01

    Accurately quantifying evapotranspiration (ET) is essential for modelling regional-scale ecosystem water balances. This study assembled an ET data set estimated from eddy flux and sapflow measurements for 13 ecosystems across a large climatic and management gradient from the United States, China, and Australia. Our objectives were to determine the relationships among...

  15. Predicting pre-planting risk of Stagonospora nodorum blotch in winter wheat using machine learning models

    Science.gov (United States)

    Pre-planting factors have been associated with the late-season severity of Stagonospora nodorum blotch (SNB), caused by the fungal pathogen Parastagonospora nodorum, in winter wheat (Triticum aestivum). The relative importance of these factors in the risk of SNB has not been determined and this know...

  16. Winter radiation extinction and reflection in a boreal pine canopy: measurements and modelling

    International Nuclear Information System (INIS)

    Pomeroy, J.W.; Dion, K.

    1996-01-01

    Predicting the rate of snow melt and intercepted snow sublimation in boreal forests requires an understanding of the effects of snow-covered conifers on the exchange of radiant energy. This study examined the amount of intercepted snow on a jack pine canopy in the boreal forest of central Saskatchewan and the shortwave and net radiation exchange with this canopy, to determine the effect of intercepted snow and canopy structure on shortwave radiation reflection and extinction and net radiation attenuation in a boreal forest. The study focused on clear sky conditions, which are common during winter in the continental boreal forest. Intercepted snow was found to have no influence on the clear-sky albedo of the canopy, the extinction of short wave radiation by the canopy or ratio of net radiation at the canopy top to that at the surface snow cover. Because of the low albedo of the snow-covered canopy, net radiation at the canopy top remains positive and a large potential source of energy for sublimation. The canopy albedo declines somewhat as the extinction efficiency of the underlying canopy increases. The extinction efficiency of short wave radiation in the canopy depends on solar angle because of the approximately horizontal orientation of pine branches. For low solar angles above the horizon, the extinction efficiency is quite low and short wave transmissivity through the canopy is relatively high. As the solar angle increases, extinction increases up to angles of about 50°, and then declines. Extinction of short wave radiation in the canopy strongly influences the attenuation of net radiation by the canopy. Short wave radiation that is extinguished by branches is radiated as long wave, partly downwards to the snow cover. The ratio of net radiation at the canopy top to that at the snow cover surface increases with the extinction of short wave radiation and is negative for low extinction efficiencies. For the pine canopy examined, the daily mean net radiation at

  17. Simulation of Wild oat (Avena ludoviciana L. Competition on Winter Wheat (Triticum astivum Growth and Yield. I: Model Description and Validation

    Directory of Open Access Journals (Sweden)

    F Mondani

    2015-09-01

    Full Text Available Crop growth models could stimulate growth and development based on science principles and mathematical equations. They also able to evaluate effects of climate, soil, water and agronomic management practices on crop yield. In the present study, an eco-physiological simulation model developed to assess wild oat damage to winter wheat growth and yield. The general structure of this model is derived from LINTUL1 model which modified to wild oat competition against winter wheat. LINTUL1 model was developed for simulation of spring wheat potential production level. In this study, first, we added development stage (DVS and vernalization to LINTUL1 for simulation of winter wheat growth and development and then the model calibrated for potential production level. Finally, we incorporate harmful effects of wild oat to winter wheat growth and yield. Weather data used as input were average daily minimum and maximum temperature (°C and daily global radiation (MJ m-2 in Mashhad, Iran. Parameter values were derived from the literature. The model is written in Fortran Simulation Translator (FST programming language and then validated based on an experiment data. For these purposes different wild oat plant densities were arranged. The data of this experiment does not use for calibration. The results showed that this model was in general able to simulate the temporal changes in DVS of winter wheat and wild oat, total dry matter (TDM of winter wheat and wild oat and yield loss of wheat due to wild oat competition in all treatments, satisfactorily. Root mean square error (RMSE for winter wheat DVS, wild oat DVS, average winter wheat TDM, average wild oat TDM, and yield loss of winter wheat was 10.4, 14.5, 5.8, 7.6 and 7.5, respectively.

  18. A Monthly Water-Balance Model Driven By a Graphical User Interface

    Science.gov (United States)

    McCabe, Gregory J.; Markstrom, Steven L.

    2007-01-01

    This report describes a monthly water-balance model driven by a graphical user interface, referred to as the Thornthwaite monthly water-balance program. Computations of monthly water-balance components of the hydrologic cycle are made for a specified location. The program can be used as a research tool, an assessment tool, and a tool for classroom instruction.

  19. Winter Radiation Extinction and Reflection in a Boreal Pine Canopy: Measurements and Modelling

    Science.gov (United States)

    Pomeroy, J. W.; Dion, K.

    1996-12-01

    Predicting the rate of snowmelt and intercepted snow sublimation in boreal forests requires an understanding of the effects of snow-covered conifers on the exchange of radiant energy. This study examined the amount of intercepted snow on a jack pine canopy in the boreal forest of central Saskatchewan and the shortwave and net radiation exchange with this canopy, to determine the effect of intercepted snow and canopy structure on shortwave radiation reflection and extinction and net radiation attenuation in a boreal forest. The study focused on clear sky conditions, which are common during winter in the continental boreal forest. Intercepted snow was found to have no influence on the clear-sky albedo of the canopy, the extinction of short wave radiation by the canopy or ratio of net radiation at the canopy top to that at the surface snow cover. Because of the low albedo of the snow-covered canopy, net radiation at the canopy top remains positive and a large potential source of energy for sublimation. The canopy albedo declines somewhat as the extinction efficiency of the underlying canopy increases. The extinction efficiency of short wave radiation in the canopy depends on solar angle because of the approximately horizontal orientation of pine branches. For low solar angles above the horizon, the extinction efficiency is quite low and short wave transmissivity through the canopy is relatively high. As the solar angle increases, extinction increases up to angles of about 50̂, and then declines. Extinction of short wave radiation in the canopy strongly influences the attenuation of net radiation by the canopy. Short wave radiation that is extinguished by branches is radiated as long wave, partly downwards to the snow cover. The ratio of net radiation at the canopy top to that at the snow cover surface increases with the extinction of short wave radiation and is negative for low extinction efficiencies. For the pine canopy examined, the daily mean net radiation at the

  20. Yield response of winter wheat cultivars to environments modeled by different variance-covariance structures in linear mixed models

    Energy Technology Data Exchange (ETDEWEB)

    Studnicki, M.; Mądry, W.; Noras, K.; Wójcik-Gront, E.; Gacek, E.

    2016-11-01

    The main objectives of multi-environmental trials (METs) are to assess cultivar adaptation patterns under different environmental conditions and to investigate genotype by environment (G×E) interactions. Linear mixed models (LMMs) with more complex variance-covariance structures have become recognized and widely used for analyzing METs data. Best practice in METs analysis is to carry out a comparison of competing models with different variance-covariance structures. Improperly chosen variance-covariance structures may lead to biased estimation of means resulting in incorrect conclusions. In this work we focused on adaptive response of cultivars on the environments modeled by the LMMs with different variance-covariance structures. We identified possible limitations of inference when using an inadequate variance-covariance structure. In the presented study we used the dataset on grain yield for 63 winter wheat cultivars, evaluated across 18 locations, during three growing seasons (2008/2009-2010/2011) from the Polish Post-registration Variety Testing System. For the evaluation of variance-covariance structures and the description of cultivars adaptation to environments, we calculated adjusted means for the combination of cultivar and location in models with different variance-covariance structures. We concluded that in order to fully describe cultivars adaptive patterns modelers should use the unrestricted variance-covariance structure. The restricted compound symmetry structure may interfere with proper interpretation of cultivars adaptive patterns. We found, that the factor-analytic structure is also a good tool to describe cultivars reaction on environments, and it can be successfully used in METs data after determining the optimal component number for each dataset. (Author)

  1. Improving winter leaf area index estimation in evergreen coniferous forests and its significance in carbon and water fluxes modeling

    Science.gov (United States)

    Wang, R.; Chen, J. M.; Luo, X.

    2016-12-01

    Modeling of carbon and water fluxes at the continental and global scales requires remotely sensed LAI as inputs. For evergreen coniferous forests (ENF), severely underestimated winter LAI has been one of the issues for mostly available remote sensing products, which could cause negative bias in the modeling of Gross Primary Productivity (GPP) and evapotranspiration (ET). Unlike deciduous trees which shed all the leaves in winter, conifers retains part of their needles and the proportion of the retained needles depends on the needle longevity. In this work, the Boreal Ecosystem Productivity Simulator (BEPS) was used to model GPP and ET at eight FLUXNET Canada ENF sites. Two sets of LAI were used as the model inputs: the 250m 10-day University of Toronto (U of T) LAI product Version 2 and the corrected LAI based on the U of T LAI product and the needle longevity of the corresponding tree species at individual sites. Validating model daily GPP (gC/m2) against site measurements, the mean RMSE over eight sites decreases from 1.85 to 1.15, and the bias changes from -0.99 to -0.19. For daily ET (mm), mean RMSE decreases from 0.63 to 0.33, and the bias changes from -0.31 to -0.16. Most of the improvements occur in the beginning and at the end of the growing season when there is large correction of LAI and meanwhile temperature is still suitable for photosynthesis and transpiration. For the dormant season, the improvement in ET simulation mostly comes from the increased interception of precipitation brought by the elevated LAI during that time. The results indicate that model performance can be improved by the application the corrected LAI. Improving the winter RS LAI can make a large impact on land surface carbon and energy budget.

  2. The 2009–2010 Arctic stratospheric winter – general evolution, mountain waves and predictability of an operational weather forecast model

    Directory of Open Access Journals (Sweden)

    A. Dörnbrack

    2012-04-01

    Full Text Available The relatively warm 2009–2010 Arctic winter was an exceptional one as the North Atlantic Oscillation index attained persistent extreme negative values. Here, selected aspects of the Arctic stratosphere during this winter inspired by the analysis of the international field experiment RECONCILE are presented. First of all, and as a kind of reference, the evolution of the polar vortex in its different phases is documented. Special emphasis is put on explaining the formation of the exceptionally cold vortex in mid winter after a sequence of stratospheric disturbances which were caused by upward propagating planetary waves. A major sudden stratospheric warming (SSW occurring near the end of January 2010 concluded the anomalous cold vortex period. Wave ice polar stratospheric clouds were frequently observed by spaceborne remote-sensing instruments over the Arctic during the cold period in January 2010. Here, one such case observed over Greenland is analysed in more detail and an attempt is made to correlate flow information of an operational numerical weather prediction model to the magnitude of the mountain-wave induced temperature fluctuations. Finally, it is shown that the forecasts of the ECMWF ensemble prediction system for the onset of the major SSW were very skilful and the ensemble spread was very small. However, the ensemble spread increased dramatically after the major SSW, displaying the strong non-linearity and internal variability involved in the SSW event.

  3. Winter Season Mortality: Will Climate Warming Bring Benefits?

    Science.gov (United States)

    Kinney, Patrick L; Schwartz, Joel; Pascal, Mathilde; Petkova, Elisaveta; Tertre, Alain Le; Medina, Sylvia; Vautard, Robert

    2015-06-01

    Extreme heat events are associated with spikes in mortality, yet death rates are on average highest during the coldest months of the year. Under the assumption that most winter excess mortality is due to cold temperature, many previous studies have concluded that winter mortality will substantially decline in a warming climate. We analyzed whether and to what extent cold temperatures are associated with excess winter mortality across multiple cities and over multiple years within individual cities, using daily temperature and mortality data from 36 US cities (1985-2006) and 3 French cities (1971-2007). Comparing across cities, we found that excess winter mortality did not depend on seasonal temperature range, and was no lower in warmer vs. colder cities, suggesting that temperature is not a key driver of winter excess mortality. Using regression models within monthly strata, we found that variability in daily mortality within cities was not strongly influenced by winter temperature. Finally we found that inadequate control for seasonality in analyses of the effects of cold temperatures led to spuriously large assumed cold effects, and erroneous attribution of winter mortality to cold temperatures. Our findings suggest that reductions in cold-related mortality under warming climate may be much smaller than some have assumed. This should be of interest to researchers and policy makers concerned with projecting future health effects of climate change and developing relevant adaptation strategies.

  4. Modelling the economic losses of historic and present-day high-impact winter storms in Switzerland

    Science.gov (United States)

    Welker, Christoph; Stucki, Peter; Bresch, David; Dierer, Silke; Martius, Olivia; Brönnimann, Stefan

    2014-05-01

    Severe winter storms such as "Vivian" in February 1990 and "Lothar" in December 1999 are among the most destructive meteorological hazards in Switzerland. Disaster severity resulting from such windstorms is attributable, on the one hand, to hazardous weather conditions such as high wind gust speeds; and on the other hand to socio-economic factors such as population density, distribution of values at risk, and damage susceptibility. For present-day winter storms, the data basis is generally good to describe the meteorological development and wind forces as well as the associated socio-economic impacts. In contrast, the information on historic windstorms is overall sparse and the available historic weather and loss reports mostly do not provide quantitative information. This study illustrates a promising technique to simulate the economic impacts of both historic and present winter storms in Switzerland since end of the 19th century. Our approach makes use of the novel Twentieth Century Reanalysis (20CR) spanning 1871-present. The 2-degree spatial resolution of the global 20CR dataset is relatively coarse. Thus, the complex orography of Switzerland is not realistically represented, which has considerable ramifications for the representation of wind systems that are strongly influenced by the local orography, such as Föhn winds. Therefore, a dynamical downscaling of the 20CR to 3 km resolution using the Weather Research and Forecasting (WRF) model was performed, for in total 40 high-impact winter storms in Switzerland since 1871. Based on the downscaled wind gust speeds and the climada loss model, the estimated economic losses were calculated at municipality level for current economic and social conditions. With this approach, we find an answer to the question what would be the economic losses of e.g. a hazardous Föhn storm - which occurred in northern Switzerland in February 1925 - today, i.e. under current socio-economic conditions. Encouragingly, the pattern of

  5. The Year Without a Ski Season: An Analysis of the Winter of 2015 for Three Ski Resorts in Western Canada Using Historical and Simulation Model Forecasted Climate Data

    Science.gov (United States)

    Pidwirny, M. J.; Goode, J. D.; Pedersen, S.

    2015-12-01

    The winter of 2015 will go down as "the year without a ski season" for many ski resorts located close to the west coast of Canada and the USA. During this winter season, a large area of the eastern North Pacific Ocean had extremely high sea surface temperatures. These high sea surface temperatures influenced weather patterns on the west coast of North America producing very mild temperatures inland. Further, in alpine environments precipitation that normally arrives in the form of snow instead fell as rain. This research examines the climate characteristics of the winter of 2015 in greater detail for three ski resorts in British Columbia, Canada: Mount Washington, Cypress Mountain and Hemlock Valley. For these resorts, historical (1901 to 2013) and IPCC AR5 climate model forecasted climate data (RCP8.5 for 2025, 2055, and 2085) was generated for the variable winter degree days climate database ClimateBC. A value for winter degree days climate data at nearby meteorological stations for comparative analysis. For all three resorts, the winter of 2015 proved to be warmer than any individual year in the period 1901 to 2013. Interpolations involving the multi-model ensemble forecast means suggest that the climate associated with winter of 2015 will become the average normal for these resorts in only 35 to 45 years under the RCP8.5 emission scenario.

  6. [Prediction model of meteorological grade of wheat stripe rust in winter-reproductive area, Sichuan Basin, China].

    Science.gov (United States)

    Guo, Xiang; Wang, Ming Tian; Zhang, Guo Zhi

    2017-12-01

    The winter reproductive areas of Puccinia striiformis var. striiformis in Sichuan Basin are often the places mostly affected by wheat stripe rust. With data on the meteorological condition and stripe rust situation at typical stations in the winter reproductive area in Sichuan Basin from 1999 to 2016, this paper classified the meteorological conditions inducing wheat stripe rust into 5 grades, based on the incidence area ratio of the disease. The meteorological factors which were biologically related to wheat stripe rust were determined through multiple analytical methods, and a meteorological grade model for forecasting wheat stripe rust was created. The result showed that wheat stripe rust in Sichuan Basin was significantly correlated with many meteorological factors, such as the ave-rage (maximum and minimum) temperature, precipitation and its anomaly percentage, relative humidity and its anomaly percentage, average wind speed and sunshine duration. Among these, the average temperature and the anomaly percentage of relative humidity were the determining factors. According to a historical retrospective test, the accuracy of the forecast based on the model was 64% for samples in the county-level test, and 89% for samples in the municipal-level test. In a meteorological grade forecast of wheat stripe rust in the winter reproductive areas in Sichuan Basin in 2017, the prediction was accurate for 62.8% of the samples, with 27.9% error by one grade and only 9.3% error by two or more grades. As a result, the model could deliver satisfactory forecast results, and predicate future wheat stripe rust from a meteorological point of view.

  7. Prediction of winter wheat high yield from remote sensing based model: application in United States and Ukraine

    Science.gov (United States)

    Franch, B.; Vermote, E.; Roger, J. C.; Skakun, S.; Becker-Reshef, I.; Justice, C. O.

    2017-12-01

    Accurate and timely crop yield forecasts are critical for making informed agricultural policies and investments, as well as increasing market efficiency and stability. In Becker-Reshef et al. (2010) and Franch et al. (2015) we developed an empirical generalized model for forecasting winter wheat yield. It is based on the relationship between the Normalized Difference Vegetation Index (NDVI) at the peak of the growing season and the Growing Degree Day (GDD) information extracted from NCEP/NCAR reanalysis data. These methods were applied to MODIS CMG data in Ukraine, the US and China with errors around 10%. However, the NDVI is saturated for yield values higher than 4 MT/ha. As a consequence, the model had to be re-calibrated in each country and the validation of the national yields showed low correlation coefficients. In this study we present a new model based on the extrapolation of the pure wheat signal (100% of wheat within the pixel) from MODIS data at 1km resolution and using the Difference Vegetation Index (DVI). The model has been applied to monitor the national yield of winter wheat in the United States and Ukraine from 2001 to 2016.

  8. Accounting for anthropic energy flux of traffic in winter urban road surface temperature simulations with the TEB model

    Science.gov (United States)

    Khalifa, A.; Marchetti, M.; Bouilloud, L.; Martin, E.; Bues, M.; Chancibaut, K.

    2016-02-01

    Snowfall forecasts help winter maintenance of road networks, ensure better coordination between services, cost control, and a reduction in environmental impacts caused by an inappropriate use of de-icers. In order to determine the possible accumulation of snow on pavements, forecasting the road surface temperature (RST) is mandatory. Weather outstations are used along these networks to identify changes in pavement status, and to make forecasts by analyzing the data they provide. Physical numerical models provide such forecasts, and require an accurate description of the infrastructure along with meteorological parameters. The objective of this study was to build a reliable urban RST forecast with a detailed integration of traffic in the Town Energy Balance (TEB) numerical model for winter maintenance. The study first consisted in generating a physical and consistent description of traffic in the model with two approaches to evaluate traffic incidence on RST. Experiments were then conducted to measure the effect of traffic on RST increase with respect to non-circulated areas. These field data were then used for comparison with the forecast provided by this traffic-implemented TEB version.

  9. Accounting for anthropic energy flux of traffic in winter urban road surface temperature simulations with TEB model

    Science.gov (United States)

    Khalifa, A.; Marchetti, M.; Bouilloud, L.; Martin, E.; Bues, M.; Chancibaut, K.

    2015-06-01

    A forecast of the snowfall helps winter coordination operating services, reducing the cost of the maintenance actions, and the environmental impacts caused by an inappropriate use of de-icing. In order to determine the possible accumulation of snow on pavement, the forecast of the road surface temperature (RST) is mandatory. Physical numerical models provide such forecast, and do need an accurate description of the infrastructure along with meteorological parameters. The objective of this study was to build a reliable urban RST forecast with a detailed integration of traffic in the Town Energy Balance (TEB) numerical model for winter maintenance. The study first consisted in generating a physical and consistent description of traffic in the model with all the energy interactions, with two approaches to evaluate the traffic incidence on RST. Experiments were then conducted to measure the traffic effect on RST increase with respect to non circulated areas. These field data were then used for comparison with forecast provided by this traffic-implemented TEB version.

  10. [Study of building quantitative analysis model for chlorophyll in winter wheat with reflective spectrum using MSC-ANN algorithm].

    Science.gov (United States)

    Liang, Xue; Ji, Hai-yan; Wang, Peng-xin; Rao, Zhen-hong; Shen, Bing-hui

    2010-01-01

    Preprocess method of multiplicative scatter correction (MSC) was used to reject noises in the original spectra produced by the environmental physical factor effectively, then the principal components of near-infrared spectroscopy were calculated by nonlinear iterative partial least squares (NIPALS) before building the back propagation artificial neural networks method (BP-ANN), and the numbers of principal components were calculated by the method of cross validation. The calculated principal components were used as the inputs of the artificial neural networks model, and the artificial neural networks model was used to find the relation between chlorophyll in winter wheat and reflective spectrum, which can predict the content of chlorophyll in winter wheat. The correlation coefficient (r) of calibration set was 0.9604, while the standard deviation (SD) and relative standard deviation (RSD) was 0.187 and 5.18% respectively. The correlation coefficient (r) of predicted set was 0.9600, and the standard deviation (SD) and relative standard deviation (RSD) was 0.145 and 4.21% respectively. It means that the MSC-ANN algorithm can reject noises in the original spectra produced by the environmental physical factor effectively and set up an exact model to predict the contents of chlorophyll in living leaves veraciously to replace the classical method and meet the needs of fast analysis of agricultural products.

  11. Short communication: Evaluation of a model for predicting Avena fatua and Descurainia sophia seed emergence in winter rapeseed

    Directory of Open Access Journals (Sweden)

    Mohammad A. Aboutalebian

    2017-07-01

    Full Text Available Avena fatua and Descurainia sophia are two important annual weeds throughout winter rapeseed (Brassica napus L. production systems in the semiarid region of Iran. Timely and more accurate control of both species may be developed if there is a better understanding of its emergence patterns. Non-linear regression techniques are usually unable to accurately predict field emergence under such environmental conditions. The objectives of this research were to evaluate the emergence patterns of A. fatua and D. sophia and determine if emergence could be predicted using cumulative soil thermal time in degree days (CTT. In the present work, cumulative seedling emergence from a winter rapeseed field during 3 years data set was fitted to cumulative soil CTT using Weibull and Gompertz functions. The Weibull model provided a better fit, based on coefficient of determination (R2sqr, root mean square of error (RMSE and Akaike index (AICd, compared to the Gompertz model between 2013 and 2016 seasons for both species. Maximum emergence of A. fatua occured 70-119 days after sowing or after equals 329-426 °Cd, while in D. sophia it occurred 119-134 days after sowing rapeseed equals 373-470 °Cd. Both models can aid in the future study of A. fatua and D. sophia emergence and assist growers and agricultural professionals with planning timely and more accurate A. fatua and D. sophia control.

  12. Outcome for Children Receiving the Early Start Denver Model before and after 48 Months

    Science.gov (United States)

    Vivanti, Giacomo; Dissanayake, Cheryl

    2016-01-01

    The Early Start Denver Model (ESDM) is an intervention program recommended for pre-schoolers with autism ages 12-48 months. The rationale for this recommendation is the potential for intervention to affect developmental trajectories during early sensitive periods. We investigated outcomes of 32 children aged 18-48 months and 28 children aged…

  13. Implications of climate change on winter road networks in Ontario's Far North and northern Manitoba, Canada, based on climate model projections

    Science.gov (United States)

    Hori, Y.; Cheng, V. Y. S.; Gough, W. A.

    2017-12-01

    A network of winter roads in northern Canada connects a number of remote First Nations communities to all-season roads and rails. The extent of the winter road networks depends on the geographic features, socio-economic activities, and the numbers of remote First Nations so that it differs among the provinces. The most extensive winter road networks below the 60th parallel south are located in Ontario and Manitoba, serving 32 and 18 communities respectively. In recent years, a warmer climate has resulted in a shorter winter road season and an increase in unreliable road conditions; thus, limiting access among remote communities. This study focused on examining the future freezing degree-days (FDDs) accumulations during the winter road season at selected locations throughout Ontario's Far North and northern Manitoba using recent climate model projections from the multi-model ensembles of General Circulation Models (GCMs) under the Representative Concentration Pathway (RCP) scenarios. First, the non-parametric Mann-Kendall correlation test and the Theil-Sen method were used to identify any statistically significant trends between FDDs and time for the base period (1981-2010). Second, future climate scenarios are developed for the study areas using statistical downscaling methods. This study also examined the lowest threshold of FDDs during the winter road construction in a future period. Our previous study established the lowest threshold of 380 FDDs, which derived from the relationship between the FDDs and the opening dates of James Bay Winter Road near the Hudson-James Bay coast. Thus, this study applied the threshold measure as a conservative estimate of the minimum threshold of FDDs to examine the effects of climate change on the winter road construction period.

  14. Fine-particle pH for Beijing winter haze as inferred from different thermodynamic equilibrium models

    Directory of Open Access Journals (Sweden)

    S. Song

    2018-05-01

    Full Text Available pH is an important property of aerosol particles but is difficult to measure directly. Several studies have estimated the pH values for fine particles in northern China winter haze using thermodynamic models (i.e., E-AIM and ISORROPIA and ambient measurements. The reported pH values differ widely, ranging from close to 0 (highly acidic to as high as 7 (neutral. In order to understand the reason for this discrepancy, we calculated pH values using these models with different assumptions with regard to model inputs and particle phase states. We find that the large discrepancy is due primarily to differences in the model assumptions adopted in previous studies. Calculations using only aerosol-phase composition as inputs (i.e., reverse mode are sensitive to the measurement errors of ionic species, and inferred pH values exhibit a bimodal distribution, with peaks between −2 and 2 and between 7 and 10, depending on whether anions or cations are in excess. Calculations using total (gas plus aerosol phase measurements as inputs (i.e., forward mode are affected much less by these measurement errors. In future studies, the reverse mode should be avoided whereas the forward mode should be used. Forward-mode calculations in this and previous studies collectively indicate a moderately acidic condition (pH from about 4 to about 5 for fine particles in northern China winter haze, indicating further that ammonia plays an important role in determining this property. The assumed particle phase state, either stable (solid plus liquid or metastable (only liquid, does not significantly impact pH predictions. The unrealistic pH values of about 7 in a few previous studies (using the standard ISORROPIA model and stable state assumption resulted from coding errors in the model, which have been identified and fixed in this study.

  15. Simulation of Relationship between ENSO and winter precipitation over Western Himalayas: Application of Regional climate model (RegT-Band)

    Science.gov (United States)

    Tiwari, P. R.; Mohanty, U. C.; Dey, S.; Acharaya, N.; Sinha, P.

    2012-12-01

    Precipitation over the Western Himalayas region during winter is mainly associated with the passage of midlatitude synoptic systems known as western disturbances (WDs). Recently, many observational and modeling studies reported that the relationship of the Indian southwest monsoon rainfall with El Niño- Southern Oscillation (ENSO) has weakened since around 1980. But, in contrast, only very few observational studies are reported so far to examine the relationship between ENSO and the winter precipitation over the Western Himalayas region from December to February (DJF). But there is a huge gap of modeling this phenomenon. So keeping in view of the absence of modeling studies, an attempt is made to simulate the relationship between wintertime precipitations associated with large scale global forcing of ENSO over the Western Himalayas. In the present study, RegT-Band, a tropical band version of the regional climate model RegCM4 is integrated for a set of 5 El Niño (1986-87, 1991-92, 1997-98, 2002-03, 2009-10) and 4 La Niña (1984-85, 1988-89, 1999-2000, 2007-08) years with the observed sea-surface temperature and lateral boundary condition. The domain extends from 50° S to 50° N and covers the entire tropics at a grid spacing of about 45 km, i.e. it includes lateral boundary forcing only at the southern and northern boundaries. The performance evaluation of the model in capturing the large scale fields followed by ENSO response with wintertime precipitation over the Western Himalayas region has been carried out by using National Center for Environmental Prediction (NCEP)-Department of Energy (DOE) reanalysis 2 (NNRP2) data (2.5° x 2.5°) and Aphrodite precipitation data (0.25° x 0.25°). The model is able to delineate the mean circulation associated with ENSO over the region during DJF reasonably well and shows strong southwesterly to northwesterly wind flow, which is there in verification analysis also. The vertical structure of the low as well as upper level

  16. Output fields from the NOAA WAVEWATCH III® wave model monthly hindcasts

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The NOAA WAVEWATCH III® hindcast dataset comprises output fields from the monthly WAVEWATCH III® hindcast model runs conducted at the National Centers for...

  17. Realizing User-Relevant Conceptual Model for the Ski Jump Venue of the Vancouver 2010 Winter Olympics

    Science.gov (United States)

    Teakles, Andrew; Mo, Ruping; Dierking, Carl F.; Emond, Chris; Smith, Trevor; McLennan, Neil; Joe, Paul I.

    2014-01-01

    As was the case for most other Olympic competitions, providing weather guidance for the ski jump and Nordic combined events involved its own set of unique challenges. The extent of these challenges was brought to light before the Vancouver 2010 Winter Olympics during a series of outflow wind events in the 2008/2009 winter season. The interactions with the race officials during the difficult race conditions brought on by the outflows provided a new perspective on the service delivery requirements for the upcoming Olympic Games. In particular, the turbulent nature of the winds and its impact on the ski jump practice events that season highlighted the need of race officials for nowcasting advice at very short time scales (from 2 min to 1 h) and forecast products tailored to their decision-making process. These realizations resulted in last minute modifications to the monitoring strategy leading up to the Olympic Games and required forecasters' conceptual models for flow within the Callaghan Valley to be downscaled further to reflect the evolution of turbulence at the ski jump site. The SNOW-V10 (Science of Nowcasting Olympic Weather for Vancouver 2010) team provided support for these efforts by supplying diagnostic case analyses of important events using numerical weather data and by enhancing the real-time monitoring capabilities at the ski jump venue.

  18. Assessment of winter air pollution episodes using long-range transport modeling in Hangzhou, China, during World Internet Conference, 2015.

    Science.gov (United States)

    Ni, Zhi-Zhen; Luo, Kun; Zhang, Jun-Xi; Feng, Rui; Zheng, He-Xin; Zhu, Hao-Ran; Wang, Jing-Fan; Fan, Jian-Ren; Gao, Xiang; Cen, Ke-Fa

    2018-05-01

    A winter air pollution episode was observed in Hangzhou, South China, during the Second World Internet Conference, 2015. To study the pollution characteristics and underlying causes, the Weather Research and Forecasting with Chemistry model was used to simulate the spatial and temporal evolution of the pollution episode from December 8 to 19, 2015. In addition to scenario simulations, analysis of the atmospheric trajectory and synoptic weather conditions were also performed. The results demonstrated that control measures implemented during the week preceding the conference reduced the fine particulate matter (PM 2.5 ) pollution level to some extent, with a decline in the total PM 2.5 concentration in Hangzhou of 15% (7%-25% daily). Pollutant long-range transport, which occurred due to a southward intrusion of strong cold air driven by the Siberia High, led to severe pollution in Hangzhou on December 15, 2015, accounting for 85% of the PM 2.5 concentration. This study provides new insights into the challenge of winter pollution prevention in Hangzhou. For adequate pollution prevention, more regional collaborations should be fostered when creating policies for northern China. Copyright © 2018 Elsevier Ltd. All rights reserved.

  19. Eurasian Winter Storm Activity at the End of the Century: A CMIP5 Multi-model Ensemble Projection

    Science.gov (United States)

    Basu, Soumik; Zhang, Xiangdong; Wang, Zhaomin

    2018-01-01

    Extratropical cyclone activity over Eurasia has exhibited a weakening trend in the recent decade. Extratropical cyclones bring precipitation and hence supply fresh water for winter crops in the mid- and high-latitude regions of Eurasia. Any changes in extratropical cyclone activity over Eurasia in the future may have a critical impact on winter agriculture and the economies of affected communities. However, potential future changes in regional storm activity over Eurasia have not been studied in detail. Therefore, in this study, we investigate anticipated changes in extratropical storm activity by the end of the century through a detailed examination of the historical and future emission scenarios from six different models from CMIP5. A statistical analysis of different parameters of storm activity using a storm identification and tracking algorithm reveals a decrease in the number of storms over mid-latitude regions. However, intense storms with longer duration are projected over high latitude Eurasia. A further examination of the physical mechanism for these changes reveals that a decrease in the meridional temperature gradient and a weakening of the vertical wind shear over the mid-latitudes are responsible for these changes in storm activity.

  20. Temporal variation and scaling of parameters for a monthly hydrologic model

    Science.gov (United States)

    Deng, Chao; Liu, Pan; Wang, Dingbao; Wang, Weiguang

    2018-03-01

    The temporal variation of model parameters is affected by the catchment conditions and has a significant impact on hydrological simulation. This study aims to evaluate the seasonality and downscaling of model parameter across time scales based on monthly and mean annual water balance models with a common model framework. Two parameters of the monthly model, i.e., k and m, are assumed to be time-variant at different months. Based on the hydrological data set from 121 MOPEX catchments in the United States, we firstly analyzed the correlation between parameters (k and m) and catchment properties (NDVI and frequency of rainfall events, α). The results show that parameter k is positively correlated with NDVI or α, while the correlation is opposite for parameter m, indicating that precipitation and vegetation affect monthly water balance by controlling temporal variation of parameters k and m. The multiple linear regression is then used to fit the relationship between ε and the means and coefficient of variations of parameters k and m. Based on the empirical equation and the correlations between the time-variant parameters and NDVI, the mean annual parameter ε is downscaled to monthly k and m. The results show that it has lower NSEs than these from model with time-variant k and m being calibrated through SCE-UA, while for several study catchments, it has higher NSEs than that of the model with constant parameters. The proposed method is feasible and provides a useful tool for temporal scaling of model parameter.

  1. Editorial - The winter Atomiades

    CERN Multimedia

    Staff Association

    2011-01-01

    As we wrote in our previous editorial, the Staff Association gives direct support to sports events, such as the Atomiades, a section of the Association of Sports Communities of European Research Institutes, which brings together sportsmen and women from 38 European research centres in 13 countries (Austria, Belgium, Czech Republic, United Kingdom, Finland, France, Germany, Hungary, Italy, Luxemburg, the Netherlands, Russia, and Switzerland). The summer Atomiades take place between the months of June and September every three years. Thirteen such events have taken place since 1973, the last one in June 2009 in Berlin. As far as the winter Atomiades are concerned, also organized every three years, and alternating with the summer Atomiades, there have been eleven since 1981, the last one at the end of January this year in neighbouring France. The following article tells the wonderful adventure of the CERN staff who took part in this event. A positive outcome for CERN skiers at the winter Atomiades The 11t...

  2. Incorporating Daily Flood Control Objectives Into a Monthly Stochastic Dynamic Programing Model for a Hydroelectric Complex

    Science.gov (United States)

    Druce, Donald J.

    1990-01-01

    A monthly stochastic dynamic programing model was recently developed and implemented at British Columbia (B.C.) Hydro to provide decision support for short-term energy exports and, if necessary, for flood control on the Peace River in northern British Columbia. The model establishes the marginal cost of supplying energy from the B.C. Hydro system, as well as a monthly operating policy for the G.M. Shrum and Peace Canyon hydroelectric plants and the Williston Lake storage reservoir. A simulation model capable of following the operating policy then determines the probability of refilling Williston Lake and possible spill rates and volumes. Reservoir inflows are input to both models in daily and monthly formats. The results indicate that flood control can be accommodated without sacrificing significant export revenue.

  3. Incorporating daily flood control objectives into a monthly stochastic dynamic programming model for a hydroelectric complex

    Energy Technology Data Exchange (ETDEWEB)

    Druce, D.J. (British Columbia Hydro and Power Authority, Vancouver, British Columbia (Canada))

    1990-01-01

    A monthly stochastic dynamic programing model was recently developed and implemented at British Columbia (B.C.) Hydro to provide decision support for short-term energy exports and, if necessary, for flood control on the Peace River in northern British Columbia. The model established the marginal cost of supplying energy from the B.C. Hydro system, as well as a monthly operating policy for the G.M. Shrum and Peace Canyon hydroelectric plants and the Williston Lake storage reservoir. A simulation model capable of following the operating policy then determines the probability of refilling Williston Lake and possible spill rates and volumes. Reservoir inflows are input to both models in daily and monthly formats. The results indicate that flood control can be accommodated without sacrificing significant export revenue.

  4. Deferred Imitation in 9-Month-Olds: How Do Model and Task Characteristics Matter across Cultures?

    Science.gov (United States)

    Teiser, Johanna; Lamm, Bettina; Böning, Mirjam; Graf, Frauke; Gudi, Helene; Goertz, Claudia; Fassbender, Ina; Freitag, Claudia; Spangler, Sibylle; Teubert, Manuel; Lohaus, Arnold; Schwarzer, Gudrun; Knopf, Monika; Keller, Heidi

    2014-01-01

    Studies investigating imitation are usually conducted with adult models in Western contexts; therefore, the influence of cultural context and the model's age on infants' imitation is largely unknown. This study assessed deferred imitation in 9-month-old infants from the German middle-class ("N" = 44) and the ethnic group of Nso in rural…

  5. Stochastic modelling of the monthly average maximum and minimum temperature patterns in India 1981-2015

    Science.gov (United States)

    Narasimha Murthy, K. V.; Saravana, R.; Vijaya Kumar, K.

    2018-04-01

    The paper investigates the stochastic modelling and forecasting of monthly average maximum and minimum temperature patterns through suitable seasonal auto regressive integrated moving average (SARIMA) model for the period 1981-2015 in India. The variations and distributions of monthly maximum and minimum temperatures are analyzed through Box plots and cumulative distribution functions. The time series plot indicates that the maximum temperature series contain sharp peaks in almost all the years, while it is not true for the minimum temperature series, so both the series are modelled separately. The possible SARIMA model has been chosen based on observing autocorrelation function (ACF), partial autocorrelation function (PACF), and inverse autocorrelation function (IACF) of the logarithmic transformed temperature series. The SARIMA (1, 0, 0) × (0, 1, 1)12 model is selected for monthly average maximum and minimum temperature series based on minimum Bayesian information criteria. The model parameters are obtained using maximum-likelihood method with the help of standard error of residuals. The adequacy of the selected model is determined using correlation diagnostic checking through ACF, PACF, IACF, and p values of Ljung-Box test statistic of residuals and using normal diagnostic checking through the kernel and normal density curves of histogram and Q-Q plot. Finally, the forecasting of monthly maximum and minimum temperature patterns of India for the next 3 years has been noticed with the help of selected model.

  6. a multi-period markov model for monthly rainfall in lagos, nigeria

    African Journals Online (AJOL)

    PUBLICATIONS1

    A twelve-period. Markov model has been developed for the monthly rainfall data for Lagos, along the coast of .... autoregressive process to model river flow; Deo et al. (2015) utilized an ...... quences for the analysis of river basins by simulation.

  7. Generation of Natural Runoff Monthly Series at Ungauged Sites Using a Regional Regressive Model

    Directory of Open Access Journals (Sweden)

    Dario Pumo

    2016-05-01

    Full Text Available Many hydrologic applications require reliable estimates of runoff in river basins to face the widespread lack of data, both in time and in space. A regional method for the reconstruction of monthly runoff series is here developed and applied to Sicily (Italy. A simple modeling structure is adopted, consisting of a regression-based rainfall–runoff model with four model parameters, calibrated through a two-step procedure. Monthly runoff estimates are based on precipitation, temperature, and exploiting the autocorrelation with runoff at the previous month. Model parameters are assessed by specific regional equations as a function of easily measurable physical and climate basin descriptors. The first calibration step is aimed at the identification of a set of parameters optimizing model performances at the level of single basin. Such “optimal” sets are used at the second step, part of a regional regression analysis, to establish the regional equations for model parameters assessment as a function of basin attributes. All the gauged watersheds across the region have been analyzed, selecting 53 basins for model calibration and using the other six basins exclusively for validation. Performances, quantitatively evaluated by different statistical indexes, demonstrate relevant model ability in reproducing the observed hydrological time-series at both the monthly and coarser time resolutions. The methodology, which is easily transferable to other arid and semi-arid areas, provides a reliable tool for filling/reconstructing runoff time series at any gauged or ungauged basin of a region.

  8. Winter wheat yield estimation of remote sensing research based on WOFOST crop model and leaf area index assimilation

    Science.gov (United States)

    Chen, Yanling; Gong, Adu; Li, Jing; Wang, Jingmei

    2017-04-01

    Accurate crop growth monitoring and yield predictive information are significant to improve the sustainable development of agriculture and ensure the security of national food. Remote sensing observation and crop growth simulation models are two new technologies, which have highly potential applications in crop growth monitoring and yield forecasting in recent years. However, both of them have limitations in mechanism or regional application respectively. Remote sensing information can not reveal crop growth and development, inner mechanism of yield formation and the affection of environmental meteorological conditions. Crop growth simulation models have difficulties in obtaining data and parameterization from single-point to regional application. In order to make good use of the advantages of these two technologies, the coupling technique of remote sensing information and crop growth simulation models has been studied. Filtering and optimizing model parameters are key to yield estimation by remote sensing and crop model based on regional crop assimilation. Winter wheat of GaoCheng was selected as the experiment object in this paper. And then the essential data was collected, such as biochemical data and farmland environmental data and meteorological data about several critical growing periods. Meanwhile, the image of environmental mitigation small satellite HJ-CCD was obtained. In this paper, research work and major conclusions are as follows. (1) Seven vegetation indexes were selected to retrieve LAI, and then linear regression model was built up between each of these indexes and the measured LAI. The result shows that the accuracy of EVI model was the highest (R2=0.964 at anthesis stage and R2=0.920 at filling stage). Thus, EVI as the most optimal vegetation index to predict LAI in this paper. (2) EFAST method was adopted in this paper to conduct the sensitive analysis to the 26 initial parameters of the WOFOST model and then a sensitivity index was constructed

  9. The U.S. Geological Survey Monthly Water Balance Model Futures Portal

    Science.gov (United States)

    Bock, Andrew R.; Hay, Lauren E.; Markstrom, Steven L.; Emmerich, Christopher; Talbert, Marian

    2017-05-03

    The U.S. Geological Survey Monthly Water Balance Model Futures Portal (https://my.usgs.gov/mows/) is a user-friendly interface that summarizes monthly historical and simulated future conditions for seven hydrologic and meteorological variables (actual evapotranspiration, potential evapotranspiration, precipitation, runoff, snow water equivalent, atmospheric temperature, and streamflow) at locations across the conterminous United States (CONUS).The estimates of these hydrologic and meteorological variables were derived using a Monthly Water Balance Model (MWBM), a modular system that simulates monthly estimates of components of the hydrologic cycle using monthly precipitation and atmospheric temperature inputs. Precipitation and atmospheric temperature from 222 climate datasets spanning historical conditions (1952 through 2005) and simulated future conditions (2020 through 2099) were summarized for hydrographic features and used to drive the MWBM for the CONUS. The MWBM input and output variables were organized into an open-access database. An Open Geospatial Consortium, Inc., Web Feature Service allows the querying and identification of hydrographic features across the CONUS. To connect the Web Feature Service to the open-access database, a user interface—the Monthly Water Balance Model Futures Portal—was developed to allow the dynamic generation of summary files and plots  based on plot type, geographic location, specific climate datasets, period of record, MWBM variable, and other options. Both the plots and the data files are made available to the user for download 

  10. WINTER SAECULUM

    Directory of Open Access Journals (Sweden)

    Emil Mihalina

    2017-03-01

    Full Text Available Accumulated imbalances in the economy and on the markets cause specific financial market dynamics that have formed characteristic patterns kept throughout long financial history. In 2008 Authors presented their expectations of key macroeconomic and selected asset class markets developments for period ahead based on Saeculum theory. Use of term Secular describes a specific valuation environment during prolonged period. If valuations as well as selected macro variables are considered as a tool for understanding business cycles then market cycles become much more obvious and easily understandable. Therefore over the long run, certain asset classes do better in terms of risk reward profile than others. Further on, there is no need for frequent portfolio rebalancing and timing of specific investment positions within a particular asset class market. Current stage in cycle development suggests a need for reassessment of trends and prevailing phenomena due to cyclical nture of long lasting Saeculums. Paper reviews developments in recognizable patterns of selected metrics in current Winter Saeculum dominated with prevailing forces of delivering, deflation and decrease in velocity of money.

  11. Balance sheet method assessment for nitrogen fertilization in winter wheat: II. alternative strategies using the CropSyst simulation model

    Directory of Open Access Journals (Sweden)

    Maria Corbellini

    2006-09-01

    Full Text Available It is important, both for farmer profit and for the environment, to correctly dose fertilizer nitrogen (N for winter wheat growth. Balance-sheet methods are often used to calculate the recommended dose of N fertilizer. Other methods are based on the dynamic simulation of cropping systems. Aim of the work was to evaluate the balance-sheet method set up by the Region Emilia-Romagna (DPI, by comparing it with the cropping systems simulation model CropSyst (CS, and with an approach based on fixed supplies of N (T. A 3-year trial was structured as a series of N fertility regimes at 3 sites (Papiano di Marsciano, Ravenna, San Pancrazio. The N-regimes were generated at each site-year as separate trials in which 3 N rates were applied: N1 (DPI, N2 (DPI+50 kg ha-1 N at spike initiation, N3 (DPI + 50 kg ha-1 N at early booting. Above ground biomass and soil data (NO3-N and water were sampled and used to calibrate CS. Doses of fertilizer N were calculated by both DPI and CS for winter wheat included in three typical rotations for Central and Northern Italy. Both these methods and method T were simulated at each site over 50 years, by using daily generated weather data. The long-term simulation allowed evaluating such alternative fertilization strategies. DPI and CS estimated comparable crop yields and N leached amounts, and both resulted better than T. Minor risk of leaching emerged for all N doses. The N2 and N3 rates allowed slightly higher crop yields than N1.

  12. A winter distribution model for Bicknell's Thrush (Catharus bicknelli), a conservation tool for a threatened migratory songbird

    Science.gov (United States)

    K. P. McFarland; C. C. Rimmer; J. E. Goetz; Y. Aubry; J. M. Wunderle Jr.; A. Hayes-Sutton; J. M. Townsend; A. Llanes Sosa; A. Kirkconnell

    2013-01-01

    Conservation planning and implementation require identifying pertinent habitats and locations where protection and management may improve viability of targeted species. The winter range of Bicknell’s Thrush (Catharus bicknelli), a threatened Nearctic-Neotropical migratory songbird, is restricted to the Greater Antilles. We analyzed winter records from the mid-1970s to...

  13. Comparisons of patch-use models for wintering American tree sparrows

    Science.gov (United States)

    Tome, M.W.

    1990-01-01

    Optimal foraging theory has stimulated numerous theoretical and empirical studies of foraging behavior for >20 years. These models provide a valuable tool for studying the foraging behavior of an organism. As with any other tool, the models are most effective when properly used. For example, to obtain a robust test of a foraging model, Stephens and Krebs (1986) recommend experimental designs in which four questions are answered in the affirmative. First, do the foragers play the same "game" as the model? Sec- ond, are the assumptions of the model met? Third, does the test rule out alternative possibilities? Finally, are the appropriate variables measured? Negative an- swers to any of these questions could invalidate the model and lead to confusion over the usefulness of foraging theory in conducting ecological studies. Gaines (1989) attempted to determine whether American Tree Sparrows (Spizella arborea) foraged by a time (Krebs 1973) or number expectation rule (Gibb 1962), or in a manner consistent with the predictions of Charnov's (1976) marginal value theorem (MVT). Gaines (1989: 118) noted appropriately that field tests of foraging models frequently involve uncontrollable circumstances; thus, it is often difficult to meet the assumptions of the models. Gaines also states (1989: 118) that "violations of the assumptions are also in- formative but do not constitute robust tests of predicted hypotheses," and that "the problem can be avoided by experimental analyses which concurrently test mutually exclusive hypotheses so that alter- native predictions will be eliminated if falsified." There is a problem with this approach because, when major assumptions of models are not satisfied, it is not justifiable to compare a predator's foraging behavior with the model's predictions. I submit that failing to follow the advice offered by Stephens and Krebs (1986) can invalidate tests of foraging models.

  14. Evaluation of air-soil temperature relationships simulated by land surface models during winter across the permafrost region

    Science.gov (United States)

    Wang, Wenli; Rinke, Annette; Moore, John C.; Ji, Duoying; Cui, Xuefeng; Peng, Shushi; Lawrence, David M.; McGuire, A. David; Burke, Eleanor J.; Chen, Xiaodong; Delire, Christine; Koven, Charles; MacDougall, Andrew; Saito, Kazuyuki; Zhang, Wenxin; Alkama, Ramdane; Bohn, Theodore J.; Ciais, Philippe; Decharme, Bertrand; Gouttevin, Isabelle; Hajima, Tomohiro; Krinner, Gerhard; Lettenmaier, Dennis P.; Miller, Paul A.; Smith, Benjamin; Sueyoshi, Tetsuo

    2016-01-01

     A realistic simulation of snow cover and its thermal properties are important for accurate modelling of permafrost. We analyze simulated relationships between air and near-surface (20 cm) soil temperatures in the Northern Hemisphere permafrost region during winter, with a particular focus on snow insulation effects in nine land surface models and compare them with observations from 268 Russian stations. There are large across-model differences as expressed by simulated differences between near-surface soil and air temperatures, (ΔT), of 3 to 14 K, in the gradients between soil and air temperatures (0.13 to 0.96°C/°C), and in the relationship between ΔT and snow depth. The observed relationship between ΔT and snow depth can be used as a metric to evaluate the effects of each model's representation of snow insulation, and hence guide improvements to the model’s conceptual structure and process parameterizations. Models with better performance apply multi-layer snow schemes and consider complex snow processes. Some models show poor performance in representing snow insulation due to underestimation of snow depth and/or overestimation of snow conductivity. Generally, models identified as most acceptable with respect to snow insulation simulate reasonable areas of near-surface permafrost (12–16 million km2). However, there is not a simple relationship between the quality of the snow insulation in the acceptable models and the simulated area of Northern Hemisphere near-surface permafrost, likely because several other factors such as differences in the treatment of soil organic matter, soil hydrology, surface energy calculations, and vegetation also provide important controls on simulated permafrost distribution.

  15. Fronts and precipitation in CMIP5 models for the austral winter of the Southern Hemisphere

    Science.gov (United States)

    Blázquez, Josefina; Solman, Silvina A.

    2018-04-01

    Wintertime fronts climatology and the relationship between fronts and precipitation as depicted by a group of CMIP5 models are evaluated over the Southern Hemisphere (SH). The frontal activity is represented by an index that takes into account the vorticity, the gradient of temperature and the specific humidity at the 850 hPa level. ERA-Interim reanalysis and GPCP datasets are used to assess the performance of the models in the present climate. Overall, it is found that the models can reproduce adequately the main features of frontal activity and front frequency over the SH. The total precipitation is overestimated in most of the models, especially the maximum values over the mid latitudes. This overestimation could be related to the high values of precipitation frequency that are identified in some of the models evaluated. The relationship between fronts and precipitation has also been evaluated in terms of both frequency of frontal precipitation and percentage of precipitation due to fronts. In general terms, the models overestimate the proportion between frontal and total precipitation. In contrast with frequency of total precipitation, the frequency of frontal precipitation is well reproduced by the models, with the higher values located at the mid latitudes. The results suggest that models represent very well the dynamic forcing (fronts) and the frequency of frontal precipitation, though the amount of precipitation due to fronts is overestimated.

  16. Winter-to-Summer Precipitation Phasing in Southwestern North America: A Multi-Century Perspective from Paleoclimatic Model-Data Comparisons

    Science.gov (United States)

    Coats, Sloan; Smerdon, Jason E.; Seager, Richard; Griffin, Daniel; Cook, Benjamin I.

    2015-01-01

    The phasing of winter-to-summer precipitation anomalies in the North American monsoon (NAM) region 2 (113.25 deg W-107.75 deg W, 30 deg N-35.25 deg N-NAM2) of southwestern North America is analyzed in fully coupled simulations of the Last Millennium and compared to tree ring reconstructed winter and summer precipitation variability. The models simulate periods with in-phase seasonal precipitation anomalies, but the strength of this relationship is variable on multidecadal time scales, behavior that is also exhibited by the reconstructions. The models, however, are unable to simulate periods with consistently out-of-phase winter-to-summer precipitation anomalies as observed in the latter part of the instrumental interval. The periods with predominantly in-phase winter-to-summer precipitation anomalies in the models are significant against randomness, and while this result is suggestive of a potential for dual-season drought on interannual and longer time scales, models do not consistently exhibit the persistent dual-season drought seen in the dendroclimatic reconstructions. These collective findings indicate that model-derived drought risk assessments may underestimate the potential for dual-season drought in 21st century projections of hydroclimate in the American Southwest and parts of Mexico.

  17. Regional parametrisation of a monthly hydrological model for estimating discharges in ungaued catchments

    Science.gov (United States)

    Hlavcova, K.; Szolgay, J.; Kohnova, S.; Kalas, M.

    2003-04-01

    In the case of the absence of measured runoff optimisation techniques cannot be used to estimate the parameters of monthly rainfall-runoff models. In such a case usually empirical regression methods were used for relating the model parameters to the catchment characteristics in a given region. In the paper a different method for the regional calibration of a monthly water balance model, which can be used for planning purposes, is proposed. Instead of using the regional regression approach a method is proposed, which involves the calibration of a monthly water balance model to gauged sites in the given region simultaneously. A regional objective function was constructed and for the calibration a genetic programming algorithm was employed. It is expected, that the regionally calibrated model parameters can be used in ungauged basins with similar physiographic conditions. The comparison of the performance of such a regional calibration scheme was compared with two single site calibration methods in a region of West Slovakia. The results are based on a study that aimed at computing surface water inflow into a lowland area with valuable groundwater resources. Monthly discharge time series had to be estimated in small ungauged rivers entering the study area.

  18. Assessing Uncertainties of Water Footprints Using an Ensemble of Crop Growth Models on Winter Wheat

    Directory of Open Access Journals (Sweden)

    Kurt Christian Kersebaum

    2016-12-01

    Full Text Available Crop productivity and water consumption form the basis to calculate the water footprint (WF of a specific crop. Under current climate conditions, calculated evapotranspiration is related to observed crop yields to calculate WF. The assessment of WF under future climate conditions requires the simulation of crop yields adding further uncertainty. To assess the uncertainty of model based assessments of WF, an ensemble of crop models was applied to data from five field experiments across Europe. Only limited data were provided for a rough calibration, which corresponds to a typical situation for regional assessments, where data availability is limited. Up to eight models were applied for wheat. The coefficient of variation for the simulated actual evapotranspiration between models was in the range of 13%–19%, which was higher than the inter-annual variability. Simulated yields showed a higher variability between models in the range of 17%–39%. Models responded differently to elevated CO2 in a FACE (Free-Air Carbon Dioxide Enrichment experiment, especially regarding the reduction of water consumption. The variability of calculated WF between models was in the range of 15%–49%. Yield predictions contributed more to this variance than the estimation of water consumption. Transpiration accounts on average for 51%–68% of the total actual evapotranspiration.

  19. Evaluation of the Community Multiscale Air Quality Model for Simulating Winter Ozone Formation in the Uinta Basin

    Science.gov (United States)

    Matichuk, Rebecca; Tonnesen, Gail; Luecken, Deborah; Gilliam, Rob; Napelenok, Sergey L.; Baker, Kirk R.; Schwede, Donna; Murphy, Ben; Helmig, Detlev; Lyman, Seth N.; Roselle, Shawn

    2017-12-01

    The Weather Research and Forecasting (WRF) and Community Multiscale Air Quality (CMAQ) models were used to simulate a 10 day high-ozone episode observed during the 2013 Uinta Basin Winter Ozone Study (UBWOS). The baseline model had a large negative bias when compared to ozone (O3) and volatile organic compound (VOC) measurements across the basin. Contrary to other wintertime Uinta Basin studies, predicted nitrogen oxides (NOx) were typically low compared to measurements. Increases to oil and gas VOC emissions resulted in O3 predictions closer to observations, and nighttime O3 improved when reducing the deposition velocity for all chemical species. Vertical structures of these pollutants were similar to observations on multiple days. However, the predicted surface layer VOC mixing ratios were generally found to be underestimated during the day and overestimated at night. While temperature profiles compared well to observations, WRF was found to have a warm temperature bias and too low nighttime mixing heights. Analyses of more realistic snow heat capacity in WRF to account for the warm bias and vertical mixing resulted in improved temperature profiles, although the improved temperature profiles seldom resulted in improved O3 profiles. While additional work is needed to investigate meteorological impacts, results suggest that the uncertainty in the oil and gas emissions contributes more to the underestimation of O3. Further, model adjustments based on a single site may not be suitable across all sites within the basin.

  20. Modelling of air quality for Winter and Summer episodes in Switzerland. Final report

    Energy Technology Data Exchange (ETDEWEB)

    Andreani-Aksoyoglu, S.; Keller, J.; Barmpadimos, L.; Oderbolz, D.; Tinguely, M.; Prevot, A. [Paul Scherrer Institute (PSI), Laboratory of Atmospheric Chemistry, Villigen (Switzerland); Alfarra, R. [University of Manchester, Manchester (United Kingdom); Sandradewi, J. [Jisca Sandradewi, Hoexter (Germany)

    2009-05-15

    This final report issued by the General Energy Research Department and its Laboratory of Atmospheric Chemistry at the Paul Scherrer Institute (PSI) reports on the results obtained from the modelling of regional air quality for three episodes, January-February 2006, June 2006 and January 2007. The focus of the calculations is on particulate matter concentrations, as well as on ozone levels in summer. The model results were compared with the aerosol data collected by an Aerosol Mass Spectrometer (AMS), which was operated during all three episodes as well as with the air quality monitoring data from further monitoring programs. The air quality model used in this study is described and the results obtained for various types of locations - rural, city, high-altitude and motorway-near - are presented and discussed. The models used are described.

  1. Coupled climate model simulations of Mediterranean winter cyclones and large-scale flow patterns

    Directory of Open Access Journals (Sweden)

    B. Ziv

    2013-03-01

    Full Text Available The study aims to evaluate the ability of global, coupled climate models to reproduce the synoptic regime of the Mediterranean Basin. The output of simulations of the 9 models included in the IPCC CMIP3 effort is compared to the NCEP-NCAR reanalyzed data for the period 1961–1990. The study examined the spatial distribution of cyclone occurrence, the mean Mediterranean upper- and lower-level troughs, the inter-annual variation and trend in the occurrence of the Mediterranean cyclones, and the main large-scale circulation patterns, represented by rotated EOFs of 500 hPa and sea level pressure. The models reproduce successfully the two maxima in cyclone density in the Mediterranean and their locations, the location of the average upper- and lower-level troughs, the relative inter-annual variation in cyclone occurrences and the structure of the four leading large scale EOFs. The main discrepancy is the models' underestimation of the cyclone density in the Mediterranean, especially in its western part. The models' skill in reproducing the cyclone distribution is found correlated with their spatial resolution, especially in the vertical. The current improvement in model spatial resolution suggests that their ability to reproduce the Mediterranean cyclones would be improved as well.

  2. Analysis Monthly Import of Palm Oil Products Using Box-Jenkins Model

    Science.gov (United States)

    Ahmad, Nurul F. Y.; Khalid, Kamil; Saifullah Rusiman, Mohd; Ghazali Kamardan, M.; Roslan, Rozaini; Che-Him, Norziha

    2018-04-01

    The palm oil industry has been an important component of the national economy especially the agriculture sector. The aim of this study is to identify the pattern of import of palm oil products, to model the time series using Box-Jenkins model and to forecast the monthly import of palm oil products. The method approach is included in the statistical test for verifying the equivalence model and statistical measurement of three models, namely Autoregressive (AR) model, Moving Average (MA) model and Autoregressive Moving Average (ARMA) model. The model identification of all product import palm oil is different in which the AR(1) was found to be the best model for product import palm oil while MA(3) was found to be the best model for products import palm kernel oil. For the palm kernel, MA(4) was found to be the best model. The results forecast for the next four months for products import palm oil, palm kernel oil and palm kernel showed the most significant decrease compared to the actual data.

  3. Prediction of Monthly Summer Monsoon Rainfall Using Global Climate Models Through Artificial Neural Network Technique

    Science.gov (United States)

    Nair, Archana; Singh, Gurjeet; Mohanty, U. C.

    2018-01-01

    The monthly prediction of summer monsoon rainfall is very challenging because of its complex and chaotic nature. In this study, a non-linear technique known as Artificial Neural Network (ANN) has been employed on the outputs of Global Climate Models (GCMs) to bring out the vagaries inherent in monthly rainfall prediction. The GCMs that are considered in the study are from the International Research Institute (IRI) (2-tier CCM3v6) and the National Centre for Environmental Prediction (Coupled-CFSv2). The ANN technique is applied on different ensemble members of the individual GCMs to obtain monthly scale prediction over India as a whole and over its spatial grid points. In the present study, a double-cross-validation and simple randomization technique was used to avoid the over-fitting during training process of the ANN model. The performance of the ANN-predicted rainfall from GCMs is judged by analysing the absolute error, box plots, percentile and difference in linear error in probability space. Results suggest that there is significant improvement in prediction skill of these GCMs after applying the ANN technique. The performance analysis reveals that the ANN model is able to capture the year to year variations in monsoon months with fairly good accuracy in extreme years as well. ANN model is also able to simulate the correct signs of rainfall anomalies over different spatial points of the Indian domain.

  4. Desert locust populations, rainfall and climate change: insights from phenomenological models using gridded monthly data

    OpenAIRE

    Tratalos, Jamie A.; Cheke, Robert A.; Healey, Richard G.; Stenseth, Nils Chr.

    2010-01-01

    Using autocorrelation analysis and autoregressive integrated moving average (ARIMA)modelling, we analysed a time series of the monthly number of 1° grid squares infested with desert locust Schistocerca gregaria swarms throughout the geographical range of the species from 1930–1987. Statistically significant first- and higher-order autocorrelations were found in the series. Although endogenous components captured much of the variance, adding rainfall data improved endogenous ARIMA models and r...

  5. A Conditionally Beta Distributed Time-Series Model With Application to Monthly US Corporate Default Rates

    DEFF Research Database (Denmark)

    Nielsen, Thor Pajhede

    2017-01-01

    We consider an observation driven, conditionally Beta distributed model for variables restricted to the unit interval. The model includes both explanatory variables and autoregressive dependence in the mean and precision parameters using the mean-precision parametrization of the beta distribution...... the monthly default rate. (3) There is evidence for volatility clustering beyond what is accounted for by the inherent mean-precision relationship of the Beta distribution in the default rate data....

  6. Modeling a typical winter-time dust event over the Arabian Peninsula and the Red Sea

    KAUST Repository

    Kalenderski, Stoitchko; Stenchikov, Georgiy L.; Zhao, C.

    2013-01-01

    2009. The model predicted that the total amount of emitted dust was 18.3 Tg for the entire dust outburst period and that the two maximum daily rates were ?2.4 Tg day-1 and ?1.5 Tg day-1, corresponding to two periods with the highest aerosol optical

  7. Assessing uncertainties of water footprints using an ensemble of crop growth models on winter wheat

    Czech Academy of Sciences Publication Activity Database

    Kersebaum, K. C.; Kroes, J.; Gobin, A.; Takáč, J.; Hlavinka, Petr; Trnka, Miroslav; Ventrella, D.; Giglio, L.; Ferrise, R.; Moriondo, M.; Marta, A. D.; Luo, Q.; Eitzinger, Josef; Mirschel, W.; Weigel, H-J.; Manderscheid, R.; Hofmann, M.; Nejedlík, P.; Hösch, J.

    2016-01-01

    Roč. 8, č. 12 (2016), č. článku 571. ISSN 2073-4441 R&D Projects: GA MŠk(CZ) LO1415; GA MŠk(CZ) LD13030 Institutional support: RVO:67179843 Keywords : water footprint * uncertainty * model ensemble * wheat Subject RIV: DA - Hydrology ; Limnology Impact factor: 1.832, year: 2016

  8. Numerical model simulations of boundary-layer dynamics during winter conditions

    DEFF Research Database (Denmark)

    Melas, D.; Persson, T.; Bruin, H. de

    2001-01-01

    A mesoscale numerical model, incorporating a land-surface scheme based on Deardorffs' approach, is used to study the diurnal variation of the boundary layer structure and surface fluxes during four consecutive days with air temperatures well below zero, snow covered ground and changing synoptic f...

  9. Investigating the role of chemical and physical processes on organic aerosol modelling with CAMx in the Po Valley during a winter episode

    Science.gov (United States)

    Meroni, A.; Pirovano, G.; Gilardoni, S.; Lonati, G.; Colombi, C.; Gianelle, V.; Paglione, M.; Poluzzi, V.; Riva, G. M.; Toppetti, A.

    2017-12-01

    Traditional aerosol mechanisms underestimate the observed organic aerosol concentration, especially due to the lack of information on secondary organic aerosol (SOA) formation and processing. In this study we evaluate the chemical and transport model CAMx during a one-month in winter (February 2013) over a 5 km resolution domain, covering the whole Po valley (Northern Italy). This works aims at investigating the effects of chemical and physical atmospheric processing on modelling results and, in particular, to evaluate the CAMx sensitivity to organic aerosol (OA) modelling schemes: we will compare the recent 1.5D-VBS algorithm (CAMx-VBS) with the traditional Odum 2-product model (CAMx-SOAP). Additionally, the thorough diagnostic analysis of the reproduction of meteorology, precursors and aerosol components was intended to point put strength and weaknesses of the modelling system and address its improvement. Firstly, we evaluate model performance for criteria PM concentration. PM10 concentration was underestimated both by CAMx-SOAP and even more by CAMx-VBS, with the latter showing a bias ranging between -4.7 and -7.1 μg m-3. PM2.5 model performance was to some extent better than PM10, showing a mean bias ranging between -0.5 μg m-3 at rural sites and -5.5 μg m-3 at urban and suburban sites. CAMx performance for OA was clearly worse than for the other PM compounds (negative bias ranging between -40% and -75%). The comparisons of model results with OA sources (identified by PMF analysis) shows that the VBS scheme underestimates freshly emitted organic aerosol while SOAP overestimates. The VBS scheme correctly reproduces biomass burning (BBOA) contributions to primary OA concentrations (POA). In contrast VBS slightly underestimates the contribution from fossil-fuel combustion (HOA), indicating that POA emissions related to road transport are either underestimated or associated to higher volatility classes. The VBS scheme under-predictes the SOA too, but to a lesser

  10. Learning at old age: a study on winter bees

    Directory of Open Access Journals (Sweden)

    Andreas Behrends

    2010-04-01

    Full Text Available Ageing is often accompanied by a decline in learning and memory abilities across the animal kingdom. Understanding age-related changes in cognitive abilities is therefore a major goal of current research. The honey bee is emerging as a novel model organism for age-related changes in brain function, because learning and memory can easily be studied in bees under controlled laboratory conditions. In addition, genetically similar workers naturally display life expectancies from six weeks (summer bees to six months (winter bees. We studied whether in honey bees, extreme longevity leads to a decline in cognitive functions. Six-month-old winter bees were conditioned either to odours or to tactile stimuli. Afterwards, long-term memory and discrimination abilities were analysed. Winter bees were kept under different conditions (flight /no flight opportunity to test for effects of foraging activity on learning performance. Despite their extreme age, winter bees did not display an age-related decline in learning or discrimination abilities, but had a slightly impaired olfactory long-term memory. The opportunity to forage indoors led to a slight decrease in learning performance. This suggests that in honey bees, unlike in most other animals, age per se does not impair associative learning. Future research will show which mechanisms protect winter bees from age-related deficits in learning.

  11. The isotopic composition of precipitation from a winter storm – a case study with the limited-area model COSMOiso

    Directory of Open Access Journals (Sweden)

    K. Yoshimura

    2012-02-01

    Full Text Available Stable water isotopes are valuable tracers of the atmospheric water cycle, and potentially provide useful information also on weather-related processes. In order to further explore this potential, the water isotopes H218O and HDO are incorporated into the limited-area model COSMO. In a first case study, the new COSMOiso model is used for simulating a winter storm event in January 1986 over the eastern United States associated with intense frontal precipitation. The modelled isotope ratios in precipitation and water vapour are compared to spatially distributed δ18O observations. COSMOiso very accurately reproduces the statistical distribution of δ18O in precipitation, and also the synoptic-scale spatial pattern and temporal evolution agree well with the measurements. Perpendicular to the front that triggers most of the rainfall during the event, the model simulates a gradient in the isotopic composition of the precipitation, with high δ18O values in the warm air and lower values in the cold sector behind the front. This spatial pattern is created through an interplay of large scale air mass advection, removal of heavy isotopes by precipitation at the front and microphysical interactions between rain drops and water vapour beneath the cloud base. This investigation illustrates the usefulness of high resolution, event-based model simulations for understanding the complex processes that cause synoptic-scale variability of the isotopic composition of atmospheric waters. In future research, this will be particularly beneficial in combination with laser spectrometric isotope observations with high temporal resolution.

  12. Modeling the winter-to-summer transition of prokaryotic and viral abundance in the Arctic Ocean.

    Science.gov (United States)

    Winter, Christian; Payet, Jérôme P; Suttle, Curtis A

    2012-01-01

    One of the challenges in oceanography is to understand the influence of environmental factors on the abundances of prokaryotes and viruses. Generally, conventional statistical methods resolve trends well, but more complex relationships are difficult to explore. In such cases, Artificial Neural Networks (ANNs) offer an alternative way for data analysis. Here, we developed ANN-based models of prokaryotic and viral abundances in the Arctic Ocean. The models were used to identify the best predictors for prokaryotic and viral abundances including cytometrically-distinguishable populations of prokaryotes (high and low nucleic acid cells) and viruses (high- and low-fluorescent viruses) among salinity, temperature, depth, day length, and the concentration of Chlorophyll-a. The best performing ANNs to model the abundances of high and low nucleic acid cells used temperature and Chl-a as input parameters, while the abundances of high- and low-fluorescent viruses used depth, Chl-a, and day length as input parameters. Decreasing viral abundance with increasing depth and decreasing system productivity was captured well by the ANNs. Despite identifying the same predictors for the two populations of prokaryotes and viruses, respectively, the structure of the best performing ANNs differed between high and low nucleic acid cells and between high- and low-fluorescent viruses. Also, the two prokaryotic and viral groups responded differently to changes in the predictor parameters; hence, the cytometric distinction between these populations is ecologically relevant. The models imply that temperature is the main factor explaining most of the variation in the abundances of high nucleic acid cells and total prokaryotes and that the mechanisms governing the reaction to changes in the environment are distinctly different among the prokaryotic and viral populations.

  13. The Adverse Effect of Spasticity on 3-Month Poststroke Outcome Using a Population-Based Model

    Directory of Open Access Journals (Sweden)

    S. R. Belagaje

    2014-01-01

    Full Text Available Several devices and medications have been used to address poststroke spasticity. Yet, spasticity’s impact on outcomes remains controversial. Using data from a cohort of 460 ischemic stroke patients, we previously published a validated multivariable regression model for predicting 3-month modified Rankin Score (mRS as an indicator of functional outcome. Here, we tested whether including spasticity improved model fit and estimated the effect spasticity had on the outcome. Spasticity was defined by a positive response to the question “Did you have spasticity following your stroke?” on direct interview at 3 months from stroke onset. Patients who had expired by 90 days (n=30 or did not have spasticity data available (n=102 were excluded. Spasticity affected the 3-month functional status (β=0.420, 95 CI=0.194 to 0.645 after accounting for age, diabetes, leukoaraiosis, and retrospective NIHSS. Using spasticity as a covariable, the model’s R2 changed from 0.599 to 0.622. In our model, the presence of spasticity in the cohort was associated with a worsened 3-month mRS by an average of 0.4 after adjusting for known covariables. This significant adverse effect on functional outcomes adds predictive value beyond previously established factors.

  14. Forecasting monthly inflow discharge of the Iffezheim reservoir using data-driven models

    Science.gov (United States)

    Zhang, Qing; Aljoumani, Basem; Hillebrand, Gudrun; Hoffmann, Thomas; Hinkelmann, Reinhard

    2017-04-01

    River stream flow is an essential element in hydrology study fields, especially for reservoir management, since it defines input into reservoirs. Forecasting this stream flow plays an important role in short or long-term planning and management in the reservoir, e.g. optimized reservoir and hydroelectric operation or agricultural irrigation. Highly accurate flow forecasting can significantly reduce economic losses and is always pursued by reservoir operators. Therefore, hydrologic time series forecasting has received tremendous attention of researchers. Many models have been proposed to improve the hydrological forecasting. Due to the fact that most natural phenomena occurring in environmental systems appear to behave in random or probabilistic ways, different cases may need a different methods to forecast the inflow and even a unique treatment to improve the forecast accuracy. The purpose of this study is to determine an appropriate model for forecasting monthly inflow to the Iffezheim reservoir in Germany, which is the last of the barrages in the Upper Rhine. Monthly time series of discharges, measured from 1946 to 2001 at the Plittersdorf station, which is located 6 km downstream of the Iffezheim reservoir, were applied. The accuracies of the used stochastic models - Fiering model and Auto-Regressive Integrated Moving Average models (ARIMA) are compared with Artificial Intelligence (AI) models - single Artificial Neural Network (ANN) and Wavelet ANN models (WANN). The Fiering model is a linear stochastic model and used for generating synthetic monthly data. The basic idea in modeling time series using ARIMA is to identify a simple model with as few model parameters as possible in order to provide a good statistical fit to the data. To identify and fit the ARIMA models, four phase approaches were used: identification, parameter estimation, diagnostic checking, and forecasting. An automatic selection criterion, such as the Akaike information criterion, is utilized

  15. Smoke inputs to climate models: optical properties and height distribution for nuclear winter studies

    International Nuclear Information System (INIS)

    Penner, J.E.; Haselman, L.C. Jr.

    1985-04-01

    Smoke from fires produced in the aftermath of a major nuclear exchange has been predicted to cause large decreases in land surface temperatures. The extent of the decrease and even the sign of the temperature change depend on the optical characteristics of the smoke and how it is distributed with altitude. The height distribution of smoke over a fire is determined by the amount of buoyant energy produced by the fire and the amount of energy released by the latent heat of condensation of water vapor. The optical properties of the smoke depend on the size distribution of smoke particles which changes due to coagulation within the lofted plume. We present calculations demonstrating these processes and estimate their importance for the smoke source term input for climate models. For high initial smoke densities and for absorbing smoke ( m = 1.75 - 0.3i), coagulation of smoke particles within the smoke plume is predicted to first increase, then decrease, the size-integrated extinction cross section. However, at the smoke densities predicted in our model (assuming a 3% emission rate for smoke) and for our assumed initial size distribution, the attachment rates for brownian and turbulent collision processes are not fast enough to alter the smoke size distribution enough to significantly change the integrated extinction cross section. Early-time coagulation is, however, fast enough to allow further coagulation, on longer time scales, to act to decrease the extinction cross section. On these longer time scales appropriate to climate models, coagulation can decrease the extinction cross section by almost a factor of two before the smoke becomes well mixed around the globe. This process has been neglected in past climate effect evaluations, but could have a significant effect, since the extinction cross section enters as an exponential factor in calculating the light attenuation due to smoke. 10 refs., 20 figs

  16. Factors limiting the grain protein content of organic winter wheat in south-eastern France: a mixed-model approach

    NARCIS (Netherlands)

    Casagrande, M.; David, C.; Valantin-Morison, M.; Makowski, D.; Jeuffroy, M.H.

    2009-01-01

    Organic agriculture could achieve the objectives of sustainable agriculture by banning the use of synthetic fertilizers and pesticides. However, organic crops generally show lower performances than conventional ones. In France, organic winter wheat production is characterized by low grain protein

  17. A Different View of Solar Spectral Irradiance Variations: Modeling Total Energy over Six-Month Intervals.

    Science.gov (United States)

    Woods, Thomas N; Snow, Martin; Harder, Jerald; Chapman, Gary; Cookson, Angela

    A different approach to studying solar spectral irradiance (SSI) variations, without the need for long-term (multi-year) instrument degradation corrections, is examining the total energy of the irradiance variation during 6-month periods. This duration is selected because a solar active region typically appears suddenly and then takes 5 to 7 months to decay and disperse back into the quiet-Sun network. The solar outburst energy, which is defined as the irradiance integrated over the 6-month period and thus includes the energy from all phases of active region evolution, could be considered the primary cause for the irradiance variations. Because solar cycle variation is the consequence of multiple active region outbursts, understanding the energy spectral variation may provide a reasonable estimate of the variations for the 11-year solar activity cycle. The moderate-term (6-month) variations from the Solar Radiation and Climate Experiment (SORCE) instruments can be decomposed into positive (in-phase with solar cycle) and negative (out-of-phase) contributions by modeling the variations using the San Fernando Observatory (SFO) facular excess and sunspot deficit proxies, respectively. These excess and deficit variations are fit over 6-month intervals every 2 months over the mission, and these fitted variations are then integrated over time for the 6-month energy. The dominant component indicates which wavelengths are in-phase and which are out-of-phase with solar activity. The results from this study indicate out-of-phase variations for the 1400 - 1600 nm range, with all other wavelengths having in-phase variations.

  18. Wavelet-linear genetic programming: A new approach for modeling monthly streamflow

    Science.gov (United States)

    Ravansalar, Masoud; Rajaee, Taher; Kisi, Ozgur

    2017-06-01

    The streamflows are important and effective factors in stream ecosystems and its accurate prediction is an essential and important issue in water resources and environmental engineering systems. A hybrid wavelet-linear genetic programming (WLGP) model, which includes a discrete wavelet transform (DWT) and a linear genetic programming (LGP) to predict the monthly streamflow (Q) in two gauging stations, Pataveh and Shahmokhtar, on the Beshar River at the Yasuj, Iran were used in this study. In the proposed WLGP model, the wavelet analysis was linked to the LGP model where the original time series of streamflow were decomposed into the sub-time series comprising wavelet coefficients. The results were compared with the single LGP, artificial neural network (ANN), a hybrid wavelet-ANN (WANN) and Multi Linear Regression (MLR) models. The comparisons were done by some of the commonly utilized relevant physical statistics. The Nash coefficients (E) were found as 0.877 and 0.817 for the WLGP model, for the Pataveh and Shahmokhtar stations, respectively. The comparison of the results showed that the WLGP model could significantly increase the streamflow prediction accuracy in both stations. Since, the results demonstrate a closer approximation of the peak streamflow values by the WLGP model, this model could be utilized for the simulation of cumulative streamflow data prediction in one month ahead.

  19. Modelling monthly runoff generation processes following land use changes: groundwater–surface runoff interactions

    Directory of Open Access Journals (Sweden)

    M. Bari

    2004-01-01

    Full Text Available A conceptual water balance model is presented to represent changes in monthly water balance following land use changes. Monthly rainfall–runoff, groundwater and soil moisture data from four experimental catchments in Western Australia have been analysed. Two of these catchments, 'Ernies' (control, fully forested and 'Lemon' (54% cleared are in a zone of mean annual rainfall of 725 mm, while 'Salmon' (control, fully forested and 'Wights' (100% cleared are in a zone with mean annual rainfall of 1125 mm. At the Salmon forested control catchment, streamflow comprises surface runoff, base flow and interflow components. In the Wights catchment, cleared of native forest for pasture development, all three components increased, groundwater levels rose significantly and stream zone saturated area increased from 1% to 15% of the catchment area. It took seven years after clearing for the rainfall–runoff generation process to stabilise in 1984. At the Ernies forested control catchment, the permanent groundwater system is 20 m below the stream bed and so does not contribute to streamflow. Following partial clearing of forest in the Lemon catchment, groundwater rose steadily and reached the stream bed by 1987. The streamflow increased in two phases: (i immediately after clearing due to reduced evapotranspiration, and (ii through an increase in the groundwater-induced stream zone saturated area after 1987. After analysing all the data available, a conceptual monthly model was created, comprising four inter-connecting stores: (i an upper zone unsaturated store, (ii a transient stream zone store, (ii a lower zone unsaturated store and (iv a saturated groundwater store. Data such as rooting depth, Leaf Area Index, soil porosity, profile thickness, depth to groundwater, stream length and surface slope were incorporated into the model as a priori defined attributes. The catchment average values for different stores were determined through matching observed and

  20. Modeling the Habitat of the Red-Crowned Crane (Grus japonensis Wintering in Cheorwon-Gun to Support Decision Making

    Directory of Open Access Journals (Sweden)

    Ho Gul Kim

    2016-06-01

    Full Text Available Cheorwon-gun is an important wintering area for the red-crowned crane (Grus japonensis. Although eco-tourism has been recently proposed as a means to stimulate the local economy, it may have adverse effects on the crane. We believe a science-based conservation plan is needed to mitigate these negative effects. To this end, our study had three objectives: (1 to analyze the red-crowned crane habitat and its suitability in Cheorwon-gun, using field surveys and habitat modeling; (2 to check the feasibility of alternative habitat patches across demilitarized zones (DMZs; and (3 to propose a conceptual diagram that minimizes habitat loss during development activities. We aim to quantify habitat suitability, the farmland area needed to support existing crane populations in wintertime, disturbance caused by human activities, and vehicular spatial patterns. These data could be used in spatial planning. The framework of this study and the process of making a conceptual diagram could be applied to other areas where there is a conflict between development and habitat conservation.

  1. Ecosystem function and service quantification and valuation in a conventional winter wheat production system with DAISY model in Denmark

    DEFF Research Database (Denmark)

    Ghaley, Bhim Bahadur; Porter, John Roy

    2014-01-01

    and ES provision. The objective was to quantify two EF: soil water storage and nitrogen mineralization and three ES: food and fodder production and carbon sequestration, in a conventional winter wheat production system at 2.6% SOM compared to 50% lower (1.3%) and 50% higher (3.9%) SOM in Denmark by DAISY...... model. At 2.6% SOM, the food and fodder production was 6.49 and 6.86tha-1year-1 respectively whereas carbon sequestration and soil water storage was 9.73tha-1year-1 and 684mmha-1year-1 respectively and nitrogen mineralisation was 83.58kgha-1year-1. At 2.6% SOM, the two EF and three ES values were US......$ 177 and US$ 2542ha-1year-1 respectively equivalent to US$ 96 and US$1370 millionyear-1 respectively in Denmark. The EF and ES quantities and values were positively correlated with SOM content. Hence, the quantification and valuation of EF and ES provides an empirical tool for optimising the EF and ES...

  2. Comparison of mesoscale model and tower measurements of surface fluxes during Winter Icing and Storms Program/Atmospheric Radiation Measurement 91

    International Nuclear Information System (INIS)

    Oncley, S.P.; Dudhia, J.

    1994-01-01

    This study is an evaluation of the ability of the Pennsylvania State University/National Center for Atmospheric Research (NCAR) mesoscale model (MM4) to determine surface fluxes to see if measured fluxes should be assimilated into model runs. Fluxes were compared from a high-resolution (5 km grid spacing) MM4 run during one day of the Winter Icing and Storms Programs/Atmospheric Radiation Measurement (WISP/ARM) experiment (over NE Colorado in winter 1991) with direct flux measurements made from a tower over a representative site by a three-dimensional sonic anemometer and fast response temperature and humidity sensors. This tower was part of the NCAR Atmosphere-Surface Turbulent Exchange Research (ASTER) facility. Also, mean values were compared to check whether any differences were due to the model parameterization or model variables

  3. Excess winter mortality and cold temperatures in a subtropical city, Guangzhou, China.

    Directory of Open Access Journals (Sweden)

    Chun-Quan Ou

    Full Text Available BACKGROUND: A significant increase in mortality was observed during cold winters in many temperate regions. However, there is a lack of evidence from tropical and subtropical regions, and the influence of ambient temperatures on seasonal variation of mortality was not well documented. METHODS: This study included 213,737 registered deaths from January 2003 to December 2011 in Guangzhou, a subtropical city in Southern China. Excess winter mortality was calculated by the excess percentage of monthly mortality in winters over that of non-winter months. A generalized linear model with a quasi-Poisson distribution was applied to analyze the association between monthly mean temperature and mortality, after controlling for other meteorological measures and air pollution. RESULTS: The mortality rate in the winter was 26% higher than the average rate in other seasons. On average, there were 1,848 excess winter deaths annually, with around half (52% from cardiovascular diseases and a quarter (24% from respiratory diseases. Excess winter mortality was higher in the elderly, females and those with low education level than the young, males and those with high education level, respectively. A much larger winter increase was observed in out-of-hospital mortality compared to in-hospital mortality (45% vs. 17%. We found a significant negative correlation of annual excess winter mortality with average winter temperature (rs=-0.738, P=0.037, but not with air pollution levels. A 1 °C decrease in monthly mean temperature was associated with an increase of 1.38% (95% CI:0.34%-2.40% and 0.88% (95% CI:0.11%-1.64% in monthly mortality at lags of 0-1 month, respectively. CONCLUSION: Similar to temperate regions, a subtropical city Guangzhou showed a clear seasonal pattern in mortality, with a sharper spike in winter. Our results highlight the role of cold temperature on the winter mortality even in warm climate. Precautionary measures should be strengthened to mitigate

  4. Modeling and forecasting monthly movement of annual average solar insolation based on the least-squares Fourier-model

    International Nuclear Information System (INIS)

    Yang, Zong-Chang

    2014-01-01

    Highlights: • Introduce a finite Fourier-series model for evaluating monthly movement of annual average solar insolation. • Present a forecast method for predicting its movement based on the extended Fourier-series model in the least-squares. • Shown its movement is well described by a low numbers of harmonics with approximately 6-term Fourier series. • Predict its movement most fitting with less than 6-term Fourier series. - Abstract: Solar insolation is one of the most important measurement parameters in many fields. Modeling and forecasting monthly movement of annual average solar insolation is of increasingly importance in areas of engineering, science and economics. In this study, Fourier-analysis employing finite Fourier-series is proposed for evaluating monthly movement of annual average solar insolation and extended in the least-squares for forecasting. The conventional Fourier analysis, which is the most common analysis method in the frequency domain, cannot be directly applied for prediction. Incorporated with the least-square method, the introduced Fourier-series model is extended to predict its movement. The extended Fourier-series forecasting model obtains its optimums Fourier coefficients in the least-square sense based on its previous monthly movements. The proposed method is applied to experiments and yields satisfying results in the different cities (states). It is indicated that monthly movement of annual average solar insolation is well described by a low numbers of harmonics with approximately 6-term Fourier series. The extended Fourier forecasting model predicts the monthly movement of annual average solar insolation most fitting with less than 6-term Fourier series

  5. A mathematical model of the nine-month pregnant woman for calculating specific absorbed fractions

    International Nuclear Information System (INIS)

    Watson, E.E.; Stabin, M.G.

    1987-01-01

    Existing models which allow calculation of internal doses from radionuclide intakes by both men and women are based on a mathematical model of Reference Man. No attempt has been made to allow for the changing geometric relationships that occur during pregnancy which would affect the doses to the mother's organs and to the fetus. As pregnancy progresses, many of the mother's abdominal organs are repositioned, and their shapes may be somewhat changed. Estimation of specific absorbed fractions requires that existing mathematical models be modified to accommodate these changes. Specific absorbed fractions for Reference Woman at three, six and nine months of pregnancy should be sufficient for estimating the doses to the pregnant woman and the fetus. This report describes a model for the pregnant woman at nine months. An enlarged uterus was incorporated into a model for Reference Woman. Several abdominal organs as well as the exterior of the trunk were modified to accommodate the new uterus. This model will allow calculation of specific absorbed fractions for the fetus from photon emitters in maternal organs. Specific absorbed fractions for the repositioned maternal organs from other organs can also be calculated. 14 refs.; 2 figs

  6. A mathematical model of the nine-month pregnant woman for calculating specific absorbed fractions

    International Nuclear Information System (INIS)

    Watson, E.E.; Stabin, M.G.

    1986-01-01

    Existing models that allow calculation of internal doses from radionuclide intakes by both men and women are based on a mathematical model of Reference Man. No attempt has been made to allow for the changing geometric relationships that occur during pregnancy which would affect the doses to the mother's organs and to the fetus. As pregnancy progresses, many of the mother's abdominal organs are repositioned, and their shapes may be somewhat changed. Estimation of specific absorbed fractions requires that existing mathematical models be modified to accommodate these changes. Specific absorbed fractions for Reference Woman at three, six, and nine months of pregnancy should be sufficient for estimating the doses to the pregnant woman and the fetus. This report describes a model for the pregnant woman at nine months. An enlarged uterus was incorporated into a model for Reference Woman. Several abdominal organs as well as the exterior of the trunk were modified to accommodate the new uterus. This model will allow calculation of specific absorbed fractions for the fetus from photon emitters in maternal organs. Specific absorbed fractions for the repositioned maternal organs from other organs can also be calculated. 14 refs., 2 figs

  7. Application of SARIMA model to forecasting monthly flows in Waterval River, South Africa

    Directory of Open Access Journals (Sweden)

    Tadesse Kassahun Birhanu

    2017-12-01

    Full Text Available Knowledge of future river flow information is fundamental for development and management of a river system. In this study, Waterval River flow was forecasted by SARIMA model using GRETL statistical software. Mean monthly flows from 1960 to 2016 were used for modelling and forecasting. Different unit root and Mann–Kendall trend analysis proved the stationarity of the observed flow time series. Based on seasonally differenced correlogram characteristics, different SARIMA models were evaluated; their parameters were optimized, and diagnostic check up of forecasts was made using white noise and heteroscedasticity tests. Finally, based on minimum Akaike Information (AI and Hannan–Quinn (HQ criteria, SARIMA (3, 0, 2 x (3, 1, 312 model was selected for Waterval River flow forecasting. Comparison of forecast performance of SARIMA models with that of computational intelligent forecasting techniques was recommended for future study.

  8. Modelling monthly runoff generation processes following land use changes: groundwater-surface runoff interactions

    Science.gov (United States)

    Bari, M.; Smettem, K. R. J.

    A conceptual water balance model is presented to represent changes in monthly water balance following land use changes. Monthly rainfall-runoff, groundwater and soil moisture data from four experimental catchments in Western Australia have been analysed. Two of these catchments, "Ernies" (control, fully forested) and "Lemon" (54% cleared) are in a zone of mean annual rainfall of 725 mm, while "Salmon" (control, fully forested) and "Wights" (100% cleared) are in a zone with mean annual rainfall of 1125 mm. At the Salmon forested control catchment, streamflow comprises surface runoff, base flow and interflow components. In the Wights catchment, cleared of native forest for pasture development, all three components increased, groundwater levels rose significantly and stream zone saturated area increased from 1% to 15% of the catchment area. It took seven years after clearing for the rainfall-runoff generation process to stabilise in 1984. At the Ernies forested control catchment, the permanent groundwater system is 20 m below the stream bed and so does not contribute to streamflow. Following partial clearing of forest in the Lemon catchment, groundwater rose steadily and reached the stream bed by 1987. The streamflow increased in two phases: (i) immediately after clearing due to reduced evapotranspiration, and (ii) through an increase in the groundwater-induced stream zone saturated area after 1987. After analysing all the data available, a conceptual monthly model was created, comprising four inter-connecting stores: (i) an upper zone unsaturated store, (ii) a transient stream zone store, (ii) a lower zone unsaturated store and (iv) a saturated groundwater store. Data such as rooting depth, Leaf Area Index, soil porosity, profile thickness, depth to groundwater, stream length and surface slope were incorporated into the model as a priori defined attributes. The catchment average values for different stores were determined through matching observed and predicted

  9. Moderate Traumatic Brain Injury: Clinical Characteristics and a Prognostic Model of 12-Month Outcome.

    Science.gov (United States)

    Einarsen, Cathrine Elisabeth; van der Naalt, Joukje; Jacobs, Bram; Follestad, Turid; Moen, Kent Gøran; Vik, Anne; Håberg, Asta Kristine; Skandsen, Toril

    2018-03-31

    Patients with moderate traumatic brain injury (TBI) often are studied together with patients with severe TBI, even though the expected outcome of the former is better. Therefore, we aimed to describe patient characteristics and 12-month outcomes, and to develop a prognostic model based on admission data, specifically for patients with moderate TBI. Patients with Glasgow Coma Scale scores of 9-13 and age ≥16 years were prospectively enrolled in 2 level I trauma centers in Europe. Glasgow Outcome Scale Extended (GOSE) score was assessed at 12 months. A prognostic model predicting moderate disability or worse (GOSE score ≤6), as opposed to a good recovery, was fitted by penalized regression. Model performance was evaluated by area under the curve of the receiver operating characteristics curves. Of the 395 enrolled patients, 81% had intracranial lesions on head computed tomography, and 71% were admitted to an intensive care unit. At 12 months, 44% were moderately disabled or worse (GOSE score ≤6), whereas 8% were severely disabled and 6% died (GOSE score ≤4). Older age, lower Glasgow Coma Scale score, no day-of-injury alcohol intoxication, presence of a subdural hematoma, occurrence of hypoxia and/or hypotension, and preinjury disability were significant predictors of GOSE score ≤6 (area under the curve = 0.80). Patients with moderate TBI exhibit characteristics of significant brain injury. Although few patients died or experienced severe disability, 44% did not experience good recovery, indicating that follow-up is needed. The model is a first step in development of prognostic models for moderate TBI that are valid across centers. Copyright © 2018 The Author(s). Published by Elsevier Inc. All rights reserved.

  10. Influence of daily versus monthly fire emissions on atmospheric model applications in the tropics

    Science.gov (United States)

    Marlier, M. E.; Voulgarakis, A.; Faluvegi, G.; Shindell, D. T.; DeFries, R. S.

    2012-12-01

    Fires are widely used throughout the tropics to create and maintain areas for agriculture, but are also significant contributors to atmospheric trace gas and aerosol concentrations. However, the timing and magnitude of fire activity can vary strongly by year and ecosystem type. For example, frequent, low intensity fires dominate in African savannas whereas Southeast Asian peatland forests are susceptible to huge pulses of emissions during regional El Niño droughts. Despite the potential implications for modeling interactions with atmospheric chemistry and transport, fire emissions have commonly been input into global models at a monthly resolution. Recognizing the uncertainty that this can introduce, several datasets have parsed fire emissions to daily and sub-daily scales with satellite active fire detections. In this study, we explore differences between utilizing the monthly and daily Global Fire Emissions Database version 3 (GFED3) products as inputs into the NASA GISS-E2 composition climate model. We aim to understand how the choice of the temporal resolution of fire emissions affects uncertainty with respect to several common applications of global models: atmospheric chemistry, air quality, and climate. Focusing our analysis on tropical ozone, carbon monoxide, and aerosols, we compare modeled concentrations with available ground and satellite observations. We find that increasing the temporal frequency of fire emissions from monthly to daily can improve correlations with observations, predominately in areas or during seasons more heavily affected by fires. Differences between the two datasets are more evident with public health applications: daily resolution fire emissions increases the number of days exceeding World Health Organization air quality targets.

  11. Diffuse radiation models and monthly-average, daily, diffuse data for a wide latitude range

    International Nuclear Information System (INIS)

    Gopinathan, K.K.; Soler, A.

    1995-01-01

    Several years of measured data on global and diffuse radiation and sunshine duration for 40 widely spread locations in the latitude range 36° S to 60° N are used to develop and test models for estimating monthly-mean, daily, diffuse radiation on horizontal surfaces. Applicability of the clearness-index (K) and sunshine fraction (SSO) models for diffuse estimation and the effect of combining several variables into a single multilinear equation are tested. Correlations connecting the diffuse to global fraction (HdH) with K and SSO predict Hd values more accurately than their separate use. Among clearness-index and sunshine-fraction models, SSO models are found to have better accuracy if correlations are developed for wide latitude ranges. By including a term for declinations in the correlation, the accuracy of the estimated data can be marginally improved. The addition of latitude to the equation does not help to improve the accuracy further. (author)

  12. Spirit Scans Winter Haven

    Science.gov (United States)

    2006-01-01

    At least three different kinds of rocks await scientific analysis at the place where NASA's Mars Exploration Rover Spirit will likely spend several months of Martian winter. They are visible in this picture, which the panoramic camera on Spirit acquired during the rover's 809th sol, or Martian day, of exploring Mars (April 12, 2006). Paper-thin layers of light-toned, jagged-edged rocks protrude horizontally from beneath small sand drifts; a light gray rock with smooth, rounded edges sits atop the sand drifts; and several dark gray to black, angular rocks with vesicles (small holes) typical of hardened lava lie scattered across the sand. This view is an approximately true-color rendering that combines images taken through the panoramic camera's 753-nanometer, 535-nanometer, and 432-nanometer filters.

  13. A system-theory-based model for monthly river runoff forecasting: model calibration and optimization

    Directory of Open Access Journals (Sweden)

    Wu Jianhua

    2014-03-01

    Full Text Available River runoff is not only a crucial part of the global water cycle, but it is also an important source for hydropower and an essential element of water balance. This study presents a system-theory-based model for river runoff forecasting taking the Hailiutu River as a case study. The forecasting model, designed for the Hailiutu watershed, was calibrated and verified by long-term precipitation observation data and groundwater exploitation data from the study area. Additionally, frequency analysis, taken as an optimization technique, was applied to improve prediction accuracy. Following model optimization, the overall relative prediction errors are below 10%. The system-theory-based prediction model is applicable to river runoff forecasting, and following optimization by frequency analysis, the prediction error is acceptable.

  14. Non-linear modelling of monthly mean vorticity time changes: an application to the western Mediterranean

    Directory of Open Access Journals (Sweden)

    M. Finizio

    Full Text Available Starting from a number of observables in the form of time-series of meteorological elements in various areas of the northern hemisphere, a model capable of fitting past records and predicting monthly vorticity time changes in the western Mediterranean is implemented. A new powerful statistical methodology is introduced (MARS in order to capture the non-linear dynamics of time-series representing the available 40-year history of the hemispheric circulation. The developed model is tested on a suitable independent data set. An ensemble forecast exercise is also carried out to check model stability in reference to the uncertainty of input quantities.

    Key words. Meteorology and atmospheric dynamics · General circulation ocean-atmosphere interactions · Synoptic-scale meteorology

  15. Modeling winter moth Operophtera brumata egg phenology: nonlinear effects of temperature and developmental stage on developmental rate

    NARCIS (Netherlands)

    Salis, Lucia; Lof, Marjolein; Van Asch, M.; Visser, Marcel E.

    2016-01-01

    Understanding the relationship between an insect's developmental rate and temperature is crucial to forecast insect phenology under climate change. In the winter moth Operophtera brumata timing of egg-hatching has severe fitness consequences on growth and reproduction as egg-hatching has to match

  16. Global Monthly CO2 Flux Inversion Based on Results of Terrestrial Ecosystem Modeling

    Science.gov (United States)

    Deng, F.; Chen, J.; Peters, W.; Krol, M.

    2008-12-01

    Most of our understanding of the sources and sinks of atmospheric CO2 has come from inverse studies of atmospheric CO2 concentration measurements. However, the number of currently available observation stations and our ability to simulate the diurnal planetary boundary layer evolution over continental regions essentially limit the number of regions that can be reliably inverted globally, especially over continental areas. In order to overcome these restrictions, a nested inverse modeling system was developed based on the Bayesian principle for estimating carbon fluxes of 30 regions in North America and 20 regions for the rest of the globe. Inverse modeling was conducted in monthly steps using CO2 concentration measurements of 5 years (2000 - 2005) with the following two models: (a) An atmospheric transport model (TM5) is used to generate the transport matrix where the diurnal variation n of atmospheric CO2 concentration is considered to enhance the use of the afternoon-hour average CO2 concentration measurements over the continental sites. (b) A process-based terrestrial ecosystem model (BEPS) is used to produce hourly step carbon fluxes, which could minimize the limitation due to our inability to solve the inverse problem in a high resolution, as the background of our inversion. We will present our recent results achieved through a combination of the bottom-up modeling with BEPS and the top-down modeling based on TM5 driven by offline meteorological fields generated by the European Centre for Medium Range Weather Forecast (ECMFW).

  17. Winter Weather Emergencies

    Science.gov (United States)

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

  18. Winter maintenance performance measure.

    Science.gov (United States)

    2016-01-01

    The Winter Performance Index is a method of quantifying winter storm events and the DOTs response to them. : It is a valuable tool for evaluating the States maintenance practices, performing post-storm analysis, training : maintenance personnel...

  19. Analysis of winter climate simulations performed with ARPEGE-Climat (T63) in the framework of PROVOST

    Energy Technology Data Exchange (ETDEWEB)

    Parey, S.; Dichampt-Martineu, Ch.; Caneill, J.Y. [Electricite de France, 78 - Chatou (France). Research Branch, Environment

    1997-12-01

    The interest of EDF for seasonal forecasting is a consequence of the high sensitivity of electricity consumption to temperature, especially during the winter season. That is why the Research branch of EDF is involved in the PROVOST project (PRediction Of climate Variations On Seasonal and inter-annual Timescales). Two sets of simulations are studied. The first one was calculated apart from the PROVOST experiments with the LMD model covering the 1970 to 1992 winters with eleven simulations per winter. The second one was calculated at EDF in the framework of PROVOST with ARPEGE-Climat model, covering the 1979 to 1994 winters (nine simulations per winter). The probabilistic formulation of climatic scenarios in function of the seasonal simulations with ARPEGE-Climat gives good results if the monthly mean temperature is taken into account. (R.P.) 3 refs.

  20. Two Monthly Continuous Dynamic Model Based on Nash Bargaining Theory for Conflict Resolution in Reservoir System.

    Science.gov (United States)

    Homayounfar, Mehran; Zomorodian, Mehdi; Martinez, Christopher J; Lai, Sai Hin

    2015-01-01

    So far many optimization models based on Nash Bargaining Theory associated with reservoir operation have been developed. Most of them have aimed to provide practical and efficient solutions for water allocation in order to alleviate conflicts among water users. These models can be discussed from two viewpoints: (i) having a discrete nature; and (ii) working on an annual basis. Although discrete dynamic game models provide appropriate reservoir operator policies, their discretization of variables increases the run time and causes dimensionality problems. In this study, two monthly based non-discrete optimization models based on the Nash Bargaining Solution are developed for a reservoir system. In the first model, based on constrained state formulation, the first and second moments (mean and variance) of the state variable (water level in the reservoir) is calculated. Using moment equations as the constraint, the long-term utility of the reservoir manager and water users are optimized. The second model is a dynamic approach structured based on continuous state Markov decision models. The corresponding solution based on the collocation method is structured for a reservoir system. In this model, the reward function is defined based on the Nash Bargaining Solution. Indeed, it is used to yield equilibrium in every proper sub-game, thereby satisfying the Markov perfect equilibrium. Both approaches are applicable for water allocation in arid and semi-arid regions. A case study was carried out at the Zayandeh-Rud river basin located in central Iran to identify the effectiveness of the presented methods. The results are compared with the results of an annual form of dynamic game, a classical stochastic dynamic programming model (e.g. Bayesian Stochastic Dynamic Programming model, BSDP), and a discrete stochastic dynamic game model (PSDNG). By comparing the results of alternative methods, it is shown that both models are capable of tackling conflict issues in water allocation

  1. Two Monthly Continuous Dynamic Model Based on Nash Bargaining Theory for Conflict Resolution in Reservoir System.

    Directory of Open Access Journals (Sweden)

    Mehran Homayounfar

    Full Text Available So far many optimization models based on Nash Bargaining Theory associated with reservoir operation have been developed. Most of them have aimed to provide practical and efficient solutions for water allocation in order to alleviate conflicts among water users. These models can be discussed from two viewpoints: (i having a discrete nature; and (ii working on an annual basis. Although discrete dynamic game models provide appropriate reservoir operator policies, their discretization of variables increases the run time and causes dimensionality problems. In this study, two monthly based non-discrete optimization models based on the Nash Bargaining Solution are developed for a reservoir system. In the first model, based on constrained state formulation, the first and second moments (mean and variance of the state variable (water level in the reservoir is calculated. Using moment equations as the constraint, the long-term utility of the reservoir manager and water users are optimized. The second model is a dynamic approach structured based on continuous state Markov decision models. The corresponding solution based on the collocation method is structured for a reservoir system. In this model, the reward function is defined based on the Nash Bargaining Solution. Indeed, it is used to yield equilibrium in every proper sub-game, thereby satisfying the Markov perfect equilibrium. Both approaches are applicable for water allocation in arid and semi-arid regions. A case study was carried out at the Zayandeh-Rud river basin located in central Iran to identify the effectiveness of the presented methods. The results are compared with the results of an annual form of dynamic game, a classical stochastic dynamic programming model (e.g. Bayesian Stochastic Dynamic Programming model, BSDP, and a discrete stochastic dynamic game model (PSDNG. By comparing the results of alternative methods, it is shown that both models are capable of tackling conflict issues in

  2. Action Prediction Allows Hypothesis Testing via Internal Forward Models at 6 Months of Age

    Directory of Open Access Journals (Sweden)

    Gustaf Gredebäck

    2018-03-01

    Full Text Available We propose that action prediction provides a cornerstone in a learning process known as internal forward models. According to this suggestion infants’ predictions (looking to the mouth of someone moving a spoon upward will moments later be validated or proven false (spoon was in fact directed toward a bowl, information that is directly perceived as the distance between the predicted and actual goal. Using an individual difference approach we demonstrate that action prediction correlates with the tendency to react with surprise when social interactions are not acted out as expected (action evaluation. This association is demonstrated across tasks and in a large sample (n = 118 at 6 months of age. These results provide the first indication that infants might rely on internal forward models to structure their social world. Additional analysis, consistent with prior work and assumptions from embodied cognition, demonstrates that the latency of infants’ action predictions correlate with the infant’s own manual proficiency.

  3. Winter-to-winter variations in indoor radon

    International Nuclear Information System (INIS)

    Mose, D.G.; Mushrush, G.W.; Kline, S.W.

    1989-01-01

    Indoor radon concentrations in northern Virginia and central Maryland show a strong dependence on weather. Winter tends to be associated with higher than average indoor radon, and summer with lower than average. However, compared to the winter of 1986-1987, the winter of 1987-1988 was warmer and drier. Consequently, winter-to-winter indoor radon decreased by about 25%. This winter-to-winter decrease is unexpectedly large, and simulates winter-to-summer variations that have been reported

  4. Global characteristics of extreme winters from a multi-millennial simulation

    Energy Technology Data Exchange (ETDEWEB)

    Hunt, B.G. [CSIRO Marine and Atmospheric Research, PO Box 1, Aspendale (Australia)

    2011-10-15

    Output from a multi-millennial simulation with the CSIRO Mark 2 coupled global climatic model has been analysed to determine the principal characteristics of extreme winters over the globe for ''present conditions''. Thus, this study is not concerned with possible changes in winter conditions associated with anthropogenically induced climatic change. Defining an extreme winter as having a surface temperature anomaly of below -2 standard deviations (sd) revealed a general occurrence rate over the globe of between 100 and 200 over a 6,000-year period of the simulation, with somewhat higher values over northwest North America. For temperature anomalies below -3 sd the corresponding occurrence rate drops to about 10. Spatial correlation studies revealed that extreme winters over regions in Europe, North America or Asia were very limited geographically, with time series of the surface temperature anomalies for these regions having mutual correlation coefficients of about 0.2. The temporal occurrence rates of winters (summers) having sd below -3 (above +3) were very asymmetric and sporadic, suggesting that such events arise from stochastic influences. Multi-year sequences of extreme winters were comparatively rare events. Detailed analysis revealed that the temporal and spatial evolution of the monthly surface temperature anomalies associated with an individual extreme winter were well replicated in the simulation, as were daily time series of such anomalies. Apart from an influence of the North Atlantic Oscillation on extreme winters in Europe, other prominent climatic oscillations were very poorly correlated with such winters. Rather modest winter temperature anomalies were found in the southern hemisphere. (orig.)

  5. Using Multiple Monthly Water Balance Models to Evaluate Gridded Precipitation Products over Peninsular Spain

    Directory of Open Access Journals (Sweden)

    Javier Senent-Aparicio

    2018-06-01

    Full Text Available The availability of precipitation data is the key driver in the application of hydrological models when simulating streamflow. Ground weather stations are regularly used to measure precipitation. However, spatial coverage is often limited in low-population areas and mountain areas. To overcome this limitation, gridded datasets from remote sensing have been widely used. This study evaluates four widely used global precipitation datasets (GPDs: The Tropical Rainfall Measuring Mission (TRMM 3B43, the Climate Forecast System Reanalysis (CFSR, the Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks (PERSIANN, and the Multi-Source Weighted-Ensemble Precipitation (MSWEP, against point gauge and gridded dataset observations using multiple monthly water balance models (MWBMs in four different meso-scale basins that cover the main climatic zones of Peninsular Spain. The volumes of precipitation obtained from the GPDs tend to be smaller than those from the gauged data. Results underscore the superiority of the national gridded dataset, although the TRMM provides satisfactory results in simulating streamflow, reaching similar Nash-Sutcliffe values, between 0.70 and 0.95, and an average total volume error of 12% when using the GR2M model. The performance of GPDs highly depends on the climate, so that the more humid the watershed is, the better results can be achieved. The procedures used can be applied in regions with similar case studies to more accurately assess the resources within a system in which there is scarcity of recorded data available.

  6. Student Mental Models of the Greenhouse Effect: Retention Months After Interventions

    Science.gov (United States)

    Harris, S. E.; Gold, A. U.

    2013-12-01

    Individual understanding of climate science, and the greenhouse effect in particular, is one factor important for societal decision-making. Ideally, learning opportunities about the greenhouse effect will not only move people toward expert-like ideas but will also have long-lasting effects for those individuals. We assessed university students' mental models of the greenhouse effect before and after specific learning experiences, on a final exam, then again a few months later. Our aim was to measure retention after students had not necessarily been thinking about, nor studying, the greenhouse effect recently. How sticky were the ideas learned? 164 students in an introductory science course participated in a sequence of two learning activities and assessments regarding the greenhouse effect. The first lesson involved the full class, then, for the second lesson, half the students completed a simulation-based activity and the other half completed a data-driven activity. We assessed student thinking through concept sketches, multiple choice and short answer questions. All students generated concept sketches four times, and completed a set of multiple choice (MCQs) and short answer questions twice. Later, 3-4 months after the course ended, 27 students ('retention students') completed an additional concept sketch and answered the questions again, as a retention assessment. These 27 students were nearly evenly split between the two contrasting second lessons in the sequence and included both high and low-achieving students. We then compared student sketches and scores to 'expert' answers. The general pattern over time showed a significant increase in student scores from before the lesson sequence to after, both on concept sketches and MCQs, then an additional increase in concept sketch score on the final exam (MCQs were not asked on the final exam). The scores for the retention students were not significantly different from the full class. Within the retention group

  7. A Poisson regression approach to model monthly hail occurrence in Northern Switzerland using large-scale environmental variables

    Science.gov (United States)

    Madonna, Erica; Ginsbourger, David; Martius, Olivia

    2018-05-01

    In Switzerland, hail regularly causes substantial damage to agriculture, cars and infrastructure, however, little is known about its long-term variability. To study the variability, the monthly number of days with hail in northern Switzerland is modeled in a regression framework using large-scale predictors derived from ERA-Interim reanalysis. The model is developed and verified using radar-based hail observations for the extended summer season (April-September) in the period 2002-2014. The seasonality of hail is explicitly modeled with a categorical predictor (month) and monthly anomalies of several large-scale predictors are used to capture the year-to-year variability. Several regression models are applied and their performance tested with respect to standard scores and cross-validation. The chosen model includes four predictors: the monthly anomaly of the two meter temperature, the monthly anomaly of the logarithm of the convective available potential energy (CAPE), the monthly anomaly of the wind shear and the month. This model well captures the intra-annual variability and slightly underestimates its inter-annual variability. The regression model is applied to the reanalysis data back in time to 1980. The resulting hail day time series shows an increase of the number of hail days per month, which is (in the model) related to an increase in temperature and CAPE. The trend corresponds to approximately 0.5 days per month per decade. The results of the regression model have been compared to two independent data sets. All data sets agree on the sign of the trend, but the trend is weaker in the other data sets.

  8. Adaptive Blending of Model and Observations for Automated Short-Range Forecasting: Examples from the Vancouver 2010 Olympic and Paralympic Winter Games

    Science.gov (United States)

    Bailey, Monika E.; Isaac, George A.; Gultepe, Ismail; Heckman, Ivan; Reid, Janti

    2014-01-01

    An automated short-range forecasting system, adaptive blending of observations and model (ABOM), was tested in real time during the 2010 Vancouver Olympic and Paralympic Winter Games in British Columbia. Data at 1-min time resolution were available from a newly established, dense network of surface observation stations. Climatological data were not available at these new stations. This, combined with output from new high-resolution numerical models, provided a unique and exciting setting to test nowcasting systems in mountainous terrain during winter weather conditions. The ABOM method blends extrapolations in time of recent local observations with numerical weather predictions (NWP) model predictions to generate short-range point forecasts of surface variables out to 6 h. The relative weights of the model forecast and the observation extrapolation are based on performance over recent history. The average performance of ABOM nowcasts during February and March 2010 was evaluated using standard scores and thresholds important for Olympic events. Significant improvements over the model forecasts alone were obtained for continuous variables such as temperature, relative humidity and wind speed. The small improvements to forecasts of variables such as visibility and ceiling, subject to discontinuous changes, are attributed to the persistence component of ABOM.

  9. Abnormal storm waves in the winter East/Japan Sea: generation process and hindcasting using an atmosphere-wind wave modelling system

    Directory of Open Access Journals (Sweden)

    H. S. Lee

    2010-04-01

    Full Text Available Abnormal storm waves cause coastal disasters along the coasts of Korean Peninsula and Japan in the East/Japan Sea (EJS in winter, arising due to developed low pressures during the East Asia winter monsoon. The generation of these abnormal storm waves during rough sea states were studied and hindcast using an atmosphere-wave coupled modelling system. Wind waves and swell due to developed low pressures were found to be the main components of abnormal storm waves. The meteorological conditions that generate these waves are classified into three patterns based on past literature that describes historical events as well as on numerical modelling. In hindcasting the abnormal storm waves, a bogussing scheme originally designed to simulate a tropical storm in a mesoscale meteorological model was introduced into the modelling system to enhance the resolution of developed low pressures. The modelling results with a bogussing scheme showed improvements in terms of resolved low pressure, surface wind field, and wave characteristics obtained with the wind field as an input.

  10. Transfer function modeling of the monthly accumulated rainfall series over the Iberian Peninsula

    Energy Technology Data Exchange (ETDEWEB)

    Mateos, Vidal L.; Garcia, Jose A.; Serrano, Antonio; De la Cruz Gallego, Maria [Departamento de Fisica, Universidad de Extremadura, Badajoz (Spain)

    2002-10-01

    In order to improve the results given by Autoregressive Moving-Average (ARMA) modeling for the monthly accumulated rainfall series taken at 19 observatories of the Iberian Peninsula, a Discrete Linear Transfer Function Noise (DLTFN) model was applied taking the local pressure series (LP), North Atlantic sea level pressure series (SLP) and North Atlantic sea surface temperature (SST) as input variables, and the rainfall series as the output series. In all cases, the performance of the DLTFN models, measured by the explained variance of the rainfall series, is better than the performance given by the ARMA modeling. The best performance is given by the models that take the local pressure as the input variable, followed by the sea level pressure models and the sea surface temperature models. Geographically speaking, the models fitted to those observatories located in the west of the Iberian Peninsula work better than those on the north and east of the Peninsula. Also, it was found that there is a region located between 0 N and 20 N, which shows the highest cross-correlation between SST and the peninsula rainfalls. This region moves to the west and northwest off the Peninsula when the SLP series are used. [Spanish] Con el objeto de mejorar los resultados porporcionados por los modelos Autorregresivo Media Movil (ARMA) ajustados a las precipitaciones mensuales acumuladas registradas en 19 observatorios de la Peninsula Iberica se han usado modelos de funcion de transferencia (DLTFN) en los que se han empleado como variable independiente la presion local (LP), la presion a nivel del mar (SLP) o la temperatura de agua del mar (SST) en el Atlantico Norte. En todos los casos analizados, los resultados obtenidos con los modelos DLTFN, medidos mediante la varianza explicada por el modelo, han sido mejores que los resultados proporcionados por los modelos ARMA. Los mejores resultados han sido dados por aquellos modelos que usan la presion local como variable de entrada, seguidos

  11. Climatological Modeling of Monthly Air Temperature and Precipitation in Egypt through GIS Techniques

    Science.gov (United States)

    El Kenawy, A.

    2009-09-01

    This paper describes a method for modeling and mapping four climatic variables (maximum temperature, minimum temperature, mean temperature and total precipitation) in Egypt using a multiple regression approach implemented in a GIS environment. In this model, a set of variables including latitude, longitude, elevation within a distance of 5, 10 and 15 km, slope, aspect, distance to the Mediterranean Sea, distance to the Red Sea, distance to the Nile, ratio between land and water masses within a radius of 5, 10, 15 km, the Normalized Difference Vegetation Index (NDVI), the Normalized Difference Water Index (NDWI), the Normalized Difference Temperature Index (NDTI) and reflectance are included as independent variables. These variables were integrated as raster layers in MiraMon software at a spatial resolution of 1 km. Climatic variables were considered as dependent variables and averaged from quality controlled and homogenized 39 series distributing across the entire country during the period of (1957-2006). For each climatic variable, digital and objective maps were finally obtained using the multiple regression coefficients at monthly, seasonal and annual timescale. The accuracy of these maps were assessed through cross-validation between predicted and observed values using a set of statistics including coefficient of determination (R2), root mean square error (RMSE), mean absolute error (MAE), mean bias Error (MBE) and D Willmott statistic. These maps are valuable in the sense of spatial resolution as well as the number of observatories involved in the current analysis.

  12. Monthly streamflow forecasting based on hidden Markov model and Gaussian Mixture Regression

    Science.gov (United States)

    Liu, Yongqi; Ye, Lei; Qin, Hui; Hong, Xiaofeng; Ye, Jiajun; Yin, Xingli

    2018-06-01

    Reliable streamflow forecasts can be highly valuable for water resources planning and management. In this study, we combined a hidden Markov model (HMM) and Gaussian Mixture Regression (GMR) for probabilistic monthly streamflow forecasting. The HMM is initialized using a kernelized K-medoids clustering method, and the Baum-Welch algorithm is then executed to learn the model parameters. GMR derives a conditional probability distribution for the predictand given covariate information, including the antecedent flow at a local station and two surrounding stations. The performance of HMM-GMR was verified based on the mean square error and continuous ranked probability score skill scores. The reliability of the forecasts was assessed by examining the uniformity of the probability integral transform values. The results show that HMM-GMR obtained reasonably high skill scores and the uncertainty spread was appropriate. Different HMM states were assumed to be different climate conditions, which would lead to different types of observed values. We demonstrated that the HMM-GMR approach can handle multimodal and heteroscedastic data.

  13. Modeling of Monthly Residential and Commercial Electricity Consumption Using Nonlinear Seasonal Models—The Case of Hong Kong

    Directory of Open Access Journals (Sweden)

    Wai-Ming To

    2017-06-01

    Full Text Available Accurate modeling and forecasting monthly electricity consumption are the keys to optimizing energy management and planning. This paper examines the seasonal characteristics of electricity consumption in Hong Kong—a subtropical city with 7 million people. Using the data from January 1970 to December 2014, two novel nonlinear seasonal models for electricity consumption in the residential and commercial sectors were obtained. The models show that the city’s monthly residential and commercial electricity consumption patterns have different seasonal variations. Specifically, monthly residential electricity consumption (mainly for appliances and cooling in summer has a quadratic relationship with monthly mean air temperature, while monthly commercial electricity consumption has a linear relationship with monthly mean air temperature. The nonlinear seasonal models were used to predict residential and commercial electricity consumption for the period January 2015–December 2016. The correlations between the predicted and actual values were 0.976 for residential electricity consumption and 0.962 for commercial electricity consumption, respectively. The root mean square percentage errors for the predicted monthly residential and commercial electricity consumption were 7.0% and 6.5%, respectively. The new nonlinear seasonal models can be applied to other subtropical urban areas, and recommendations on the reduction of commercial electricity consumption are given.

  14. Daddy Months

    OpenAIRE

    Volker Meier; Helmut Rainer

    2014-01-01

    We consider a bargaining model in which husband and wife decide on the allocation of time and disposable income. Since her bargaining power would go down otherwise more strongly, the wife agrees to having a child only if the husband also leaves the labor market for a while. The daddy months subsidy enables the couple to overcome a hold-up problem and thereby improves efficiency. However, the same ruling harms cooperative couples and may also reduce welfare in an endogenous taxation framework.

  15. Monthly and Fortnightly Tidal Variations of the Earth's Rotation Rate Predicted by a TOPEX/POSEIDON Empirical Ocean Tide Model

    Science.gov (United States)

    Desai, S.; Wahr, J.

    1998-01-01

    Empirical models of the two largest constituents of the long-period ocean tides, the monthly and the fortnightly constituents, are estimated from repeat cycles 10 to 210 of the TOPEX/POSEIDON (T/P) mission.

  16. Mapping monthly rainfall erosivity in Europe.

    Science.gov (United States)

    Ballabio, Cristiano; Borrelli, Pasquale; Spinoni, Jonathan; Meusburger, Katrin; Michaelides, Silas; Beguería, Santiago; Klik, Andreas; Petan, Sašo; Janeček, Miloslav; Olsen, Preben; Aalto, Juha; Lakatos, Mónika; Rymszewicz, Anna; Dumitrescu, Alexandru; Tadić, Melita Perčec; Diodato, Nazzareno; Kostalova, Julia; Rousseva, Svetla; Banasik, Kazimierz; Alewell, Christine; Panagos, Panos

    2017-02-01

    Rainfall erosivity as a dynamic factor of soil loss by water erosion is modelled intra-annually for the first time at European scale. The development of Rainfall Erosivity Database at European Scale (REDES) and its 2015 update with the extension to monthly component allowed to develop monthly and seasonal R-factor maps and assess rainfall erosivity both spatially and temporally. During winter months, significant rainfall erosivity is present only in part of the Mediterranean countries. A sudden increase of erosivity occurs in major part of European Union (except Mediterranean basin, western part of Britain and Ireland) in May and the highest values are registered during summer months. Starting from September, R-factor has a decreasing trend. The mean rainfall erosivity in summer is almost 4 times higher (315MJmmha -1 h -1 ) compared to winter (87MJmmha -1 h -1 ). The Cubist model has been selected among various statistical models to perform the spatial interpolation due to its excellent performance, ability to model non-linearity and interpretability. The monthly prediction is an order more difficult than the annual one as it is limited by the number of covariates and, for consistency, the sum of all months has to be close to annual erosivity. The performance of the Cubist models proved to be generally high, resulting in R 2 values between 0.40 and 0.64 in cross-validation. The obtained months show an increasing trend of erosivity occurring from winter to summer starting from western to Eastern Europe. The maps also show a clear delineation of areas with different erosivity seasonal patterns, whose spatial outline was evidenced by cluster analysis. The monthly erosivity maps can be used to develop composite indicators that map both intra-annual variability and concentration of erosive events. Consequently, spatio-temporal mapping of rainfall erosivity permits to identify the months and the areas with highest risk of soil loss where conservation measures should be

  17. Monthly water balance model for climate change analysis in agriculture with R

    Science.gov (United States)

    Kalicz, Péter; Herceg, András; Gribovszki, Zoltán

    2015-04-01

    For Hungary regional climate models projections suggest a warmer climate and some changes in annual precipitation distribution. These changes force the whole agrarian sector to consider the traditional cropping technologies. This situation is more serious in forestry because some forest populations are on their xeric distributional limits (Gálos et. al, 2014). Additionally, a decision has an impact sometimes longer than one hundred years. To support the stakeholder there is a project which develops a GIS (Geographic Information System) based decision support system. Hydrology plays significant role in this system because water is often one of the most important limiting factor in Hungary. A modified Thorntwaite-type monthly water balance model was choosen to produce hydrological estimations for the GIS modules. This model is calibrated with the available data between 2000 and 2008. Beside other meteorological data we used mainly an actual evapotranspiration map in the calibration phase, which was derived with the Complementary-relationship-based evapotranspiration mapping (CREMAP; Szilágyi and Kovács, 2011) technique. The calibration process is pixel based and it has several stochastic steps. We try to find a flexible solution for the model implementation which easy to automatize and can be integrate in GIS systems. The open source R programming language was selected which well satisfied these demands. The result of this development is summarized as an R package. This publication has been supported by AGRARKLIMA.2 VKSZ_12-1-2013-0034 project. References Gálos B., Antal V., Czimber K., Mátyás Cs. (2014) Forest ecosystems, sewage works and droughts - possibilities for climate change adaptation. In: Santamarta J.C., Hernandez-Gutiérrez L.E., Arraiza M.P. (eds) 2014. Natural Hazards and Climate Change/Riesgos Naturales y Cambio Climático. Madrid: Colegio de Ingenieros de Montes. ISBN 978-84-617-1060-7, D.L. TF 565-2014, 91-104 pp Szilágyi J., Kovács Á. (2011

  18. Assessment of ENSEMBLES regional climate models for the representation of monthly wind characteristics in the Aegean Sea (Greece): Mean and extremes analysis

    Science.gov (United States)

    Anagnostopoulou, Christina; Tolika, Konstantia; Tegoulias, Ioannis; Velikou, Kondylia; Vagenas, Christos

    2013-04-01

    The main scope of the present study is the assessment of the ability of three of the most updated regional climate models, developed under the frame of the European research project ENSEMBLES (http://www.ensembles-eu.org/), to simulate the wind characteristics in the Aegean Sea in Greece. The examined models are KNMI-RACMO2, MPI-MREMO, and ICTP - RegCM3. They all have the same spatial resolution (25x25km) and for their future projections they are using the A1B SRES emission scenarios. Their simulated wind data (speed and direction) were compared with observational data from several stations over the domain of study for a time period of 25 years, from 1980 to 2004 on a monthly basis. The primer data were available every three or six hours from which we computed the mean daily wind speed and the prevailing daily wind direction. It should be mentioned, that the comparison was made for the grid point that was the closest to each station over land. Moreover, the extreme speed values were also calculated both for the observational and the simulated data, in order to assess the ability of the models in capturing the most intense wind conditions. The first results of the study showed that the prevailing winds during the winter and spring months have a north - northeastern or a south - south western direction in most parts of the Aegean sea. The models under examination seem to capture quite satisfactorily this pattern as well as the general characteristics of the winds in this area. During summer, winds in the Aegean Sea have mainly north direction and the models have quite good agreement both in simulating this direction and the wind speed. Concerning the extreme wind speed (percentiles) it was found that for the stations in the northern Aegean all the models overestimate the extreme wind indices. For the eastern parts of the Aegean the KNMI and the MPI model underestimate the extreme wind speeds while on the other hand the ICTP model overestimates them. Finally for the

  19. Predicting the 6-month risk of severe hypoglycemia among adults with diabetes: Development and external validation of a prediction model.

    Science.gov (United States)

    Schroeder, Emily B; Xu, Stan; Goodrich, Glenn K; Nichols, Gregory A; O'Connor, Patrick J; Steiner, John F

    2017-07-01

    To develop and externally validate a prediction model for the 6-month risk of a severe hypoglycemic event among individuals with pharmacologically treated diabetes. The development cohort consisted of 31,674 Kaiser Permanente Colorado members with pharmacologically treated diabetes (2007-2015). The validation cohorts consisted of 38,764 Kaiser Permanente Northwest members and 12,035 HealthPartners members. Variables were chosen that would be available in electronic health records. We developed 16-variable and 6-variable models, using a Cox counting model process that allows for the inclusion of multiple 6-month observation periods per person. Across the three cohorts, there were 850,992 6-month observation periods, and 10,448 periods with at least one severe hypoglycemic event. The six-variable model contained age, diabetes type, HgbA1c, eGFR, history of a hypoglycemic event in the prior year, and insulin use. Both prediction models performed well, with good calibration and c-statistics of 0.84 and 0.81 for the 16-variable and 6-variable models, respectively. In the external validation cohorts, the c-statistics were 0.80-0.84. We developed and validated two prediction models for predicting the 6-month risk of hypoglycemia. The 16-variable model had slightly better performance than the 6-variable model, but in some practice settings, use of the simpler model may be preferred. Copyright © 2017 Elsevier Inc. All rights reserved.

  20. Winters fuels report

    International Nuclear Information System (INIS)

    1995-01-01

    The outlook for distillate fuel oil this winter is for increased demand and a return to normal inventory patterns, assuming a resumption of normal, cooler weather than last winter. With industrial production expected to grow slightly from last winter's pace, overall consumption is projected to increase 3 percent from last winter, to 3.4 million barrels per day during the heating season (October 1, 1995-March 31, 1996). Much of the supply win come from stock drawdowns and refinery production. Estimates for the winter are from the Energy Information Administration's (EIA) 4th Quarter 1995 Short-Tenn Energy Outlook (STEO) Mid-World Oil Price Case forecast. Inventories in place on September 30, 1995, of 132 million barrels were 9 percent below the unusually high year-earlier level. Inventories of high-sulfur distillate fuel oil, the principal type used for heating, were 13 percent lower than a year earlier. Supply problems are not anticipated because refinery production and the ready availability of imports should be adequate to meet demand. Residential heating off prices are expected to be somewhat higher than last winter's, as the effects of lower crude oil prices are offset by lower distillate inventories. Heating oil is forecast to average $0.92 per gallon, the highest price since the winter of 1992-93. Diesel fuel (including tax) is predicted to be slightly higher than last year at $1.13 per gallon. This article focuses on the winter assessment for distillate fuel oil, how well last year's STEO winter outlook compared to actual events, and expectations for the coming winter. Additional analyses include regional low-sulfur and high-sulfur distillate supply, demand, and prices, and recent trends in distillate fuel oil inventories

  1. Mapping monthly rainfall erosivity in Europe

    DEFF Research Database (Denmark)

    Ballabio, C; Meusburger, K; Klik, A

    2017-01-01

    to Eastern Europe. The maps also show a clear delineation of areas with different erosivity seasonal patterns, whose spatial outline was evidenced by cluster analysis. The monthly erosivity maps can be used to develop composite indicators that map both intra-annual variability and concentration of erosive...... and seasonal R-factor maps and assess rainfall erosivity both spatially and temporally. During winter months, significant rainfall erosivity is present only in part of the Mediterranean countries. A sudden increase of erosivity occurs in major part of European Union (except Mediterranean basin, western part...... selected among various statistical models to perform the spatial interpolation due to its excellent performance, ability to model non-linearity and interpretability. The monthly prediction is an order more difficult than the annual one as it is limited by the number of covariates and, for consistency...

  2. Long-term success and failure with SG is predictable by 3 months: a multivariate model using simple office markers.

    Science.gov (United States)

    Cottam, Austin; Billing, Josiah; Cottam, Daniel; Billing, Peter; Cottam, Samuel; Zaveri, Hinali; Surve, Amit

    2017-08-01

    Despite being the most common surgery in the United States, little is known about predicting weight loss success and failure with sleeve gastrectomy (SG). Papers that have been published are inconclusive. We decided to use multivariate analysis from 2 practices to design a model to predict weight loss outcomes using data widely available to any surgical practice at 3 months to determine weight loss outcomes at 1 year. Two private practices in the United States. A retrospective review of 613 patients from 2 bariatric institutions were included in this study. Co-morbidities and other preoperative characteristics were gathered, and %EWL was calculated for 1, 3, and 12 months. Excess weight loss (%EWL)failure. Multiple variate analysis was used to find factors that affect %EWL at 12 months. Preoperative sleep apnea, preoperative diabetes, %EWL at 1 month, and %EWL at 3 months all affect %EWL at 1 year. The positive predictive value and negative predictive value of our model was 72% and 91%, respectively. Sensitivity and specificity were 71% and 91%, respectively. One-year results of the SG can be predicted by diabetes, sleep apnea, and weight loss velocity at 3 months postoperatively. This can help surgeons direct surgical or medical interventions for patients at 3 months rather than at 1 year or beyond. Copyright © 2017 American Society for Bariatric Surgery. Published by Elsevier Inc. All rights reserved.

  3. Winter Arctic sea ice growth: current variability and projections for the coming decades

    Science.gov (United States)

    Petty, A.; Boisvert, L.; Webster, M.; Holland, M. M.; Bailey, D. A.; Kurtz, N. T.; Markus, T.

    2017-12-01

    Arctic sea ice increases in both extent and thickness during the cold winter months ( October to May). Winter sea ice growth is an important factor controlling ocean ventilation and winter water/deep water formation, as well as determining the state and vulnerability of the sea ice pack before the melt season begins. Key questions for the Arctic community thus include: (i) what is the current magnitude and variability of winter Arctic sea ice growth and (ii) how might this change in a warming Arctic climate? To address (i), our current best guess of pan-Arctic sea ice thickness, and thus volume, comes from satellite altimetry observations, e.g. from ESA's CryoSat-2 satellite. A significant source of uncertainty in these data come from poor knowledge of the overlying snow depth. Here we present new estimates of winter sea ice thickness from CryoSat-2 using snow depths from a simple snow model forced by reanalyses and satellite-derived ice drift estimates, combined with snow depth estimates from NASA's Operation IceBridge. To address (ii), we use data from the Community Earth System Model's Large Ensemble Project, to explore sea ice volume and growth variability, and how this variability might change over the coming decades. We compare and contrast the model simulations to observations and the PIOMAS ice-ocean model (over recent years/decades). The combination of model and observational analysis provide novel insight into Arctic sea ice volume variability.

  4. Winter Bottom Trawl Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The standardized NEFSC Winter Bottom Trawl Survey was initiated in 1992 and covered offshore areas from the Mid-Atlantic to Georges Bank. Inshore strata were covered...

  5. Deer Wintering Areas

    Data.gov (United States)

    Vermont Center for Geographic Information — Deer winter habitat is critical to the long term survival of white-tailed deer (Odocoileus virginianus) in Vermont. Being near the northern extreme of the...

  6. Estimating winter survival of winter wheat by simulations of plant frost tolerance

    NARCIS (Netherlands)

    Bergjord Olsen, A.K.; Persson, T.; Wit, de A.; Nkurunziza, L.; Sindhøj, E.; Eckersten, H.

    2018-01-01

    Based on soil temperature, snow depth and the grown cultivar's maximum attainable level of frost tolerance (LT50c), the FROSTOL model simulates development of frost tolerance (LT50) and winter damage, thereby enabling risk calculations for winter wheat survival. To explore the accuracy of this

  7. Modeling monthly meteorological and agronomic frost days, based on minimum air temperature, in Center-Southern Brazil

    Science.gov (United States)

    Alvares, Clayton Alcarde; Sentelhas, Paulo César; Stape, José Luiz

    2017-09-01

    Although Brazil is predominantly a tropical country, frosts are observed with relative high frequency in the Center-Southern states of the country, affecting mainly agriculture, forestry, and human activities. Therefore, information about the frost climatology is of high importance for planning of these activities. Based on that, the aims of the present study were to develop monthly meteorological (F MET) and agronomic (F AGR) frost day models, based on minimum shelter air temperature (T MN), in order to characterize the temporal and spatial frost days variability in Center-Southern Brazil. Daily minimum air temperature data from 244 weather stations distributed across the study area were used, being 195 for developing the models and 49 for validating them. Multivariate regression models were obtained to estimate the monthly T MN, once the frost day models were based on this variable. All T MN regression models were statistically significant (p Brazilian region are the first zoning of these variables for the country.

  8. Application of DSSAT models for an agronomic adaptation strategy under climate change in Southern of Italy: optimum sowing and transplanting time for winter durum wheat and tomato

    Directory of Open Access Journals (Sweden)

    Domenico Ventrella

    2012-03-01

    Full Text Available Many climate change studies have been carried out in different parts of the world to assess climate change vulnerability and adaptation capacity of agricultural crops for determined environments characterized from climatic, pedological and agronomical point of view. The objective of this study was to analyse the productive response of winter durum wheat and tomato to climate change and sowing/transplanting time in one of most productive areas of Italy (i.e. Capitanata, Puglia, using CERES-Wheat and CROPGRO cropping system models. Three climatic datasets were used: i a single dataset (50 km x 50 km provided by the JRC European centre for the period 1975-2005; two datasets from HadCM3 for the IPCC A2 GHG scenario for time slices with +2°C (centred over 2030-2060 and +5°C (centred over 2070-2099, respectively. All three datasets were used to generate synthetic climate series using a weather simulator (model LARS-WG. No negative yield effects of climate change were observed for winter durum wheat with delayed sowing (from 330 to 345 DOY increasing the average dry matter grain yield under forecasted scenarios. Instead, the warmer temperatures were primarily shown to accelerate the phenology, resulting in decreased yield for tomato under the + 5°C future climate scenario. In general, under global temperature increase by 5°C, early transplanting times could minimize the negative impact of climate change on crop productivity but the intensity of this effect was not sufficient to restore the current production levels of tomato cultivated in southern Italy.

  9. Measuring Transpiration to Regulate Winter Irrigation Rates

    Energy Technology Data Exchange (ETDEWEB)

    Samuelson, Lisa [Auburn University

    2006-11-08

    Periodic transpiration (monthly sums) in a young loblolly pine plantation between ages 3 and 6 was measured using thermal dissipation probes. Fertilization and fertilization with irrigation were better than irrigation alone in increasing transpiration of young loblolly pines during winter months, apparently because of increased leaf area in fertilized trees. Irrigation alone did not significantly increase transpiration compared with the non-fertilized and non-irrigated control plots.

  10. Modeling winter wheat phenological responses to water deficits in the Unified Plant Growth Model (UPGM) component of the spatially distributed Agricultural Ecosystem Services (AgES) model

    Science.gov (United States)

    Accurately predicting phenology in crop simulation models is critical for correctly simulating crop production. While extensive work in modeling phenology has focused on the temperature response function (resulting in robust phenology models), limited work on quantifying the phenological responses t...

  11. Estimating the monthly discharge of a photovoltaic water pumping system: Model verification

    International Nuclear Information System (INIS)

    Amer, E.H.; Younes, M.A.

    2006-01-01

    A simple algorithm has been adopted for estimating the long term performance of a photovoltaic water pumping system without battery storage. The method uses the standard solar utilizability correlation equation to calculate the flow rate of the system, knowing an insolation threshold value. The method uses the monthly average solar radiation as the only input. The nonlinear relation between flow rate and solar insolation has been obtained experimentally in a first step and then used for performance prediction. The meteorological data collected instantaneously at the site of the pumping system has been used to obtain the monthly average values for solar radiation that are needed by the method. The method has been validated by predicting the performance of two PV pumping systems. The average output of the systems predicted by the method has been compared with experimental measurements. The estimated discharge differs by about 5% from the experimental measurements

  12. Monthly Rainfall Erosivity Assessment for Switzerland

    Science.gov (United States)

    Schmidt, Simon; Meusburger, Katrin; Alewell, Christine

    2016-04-01

    Water erosion is crucially controlled by rainfall erosivity, which is quantified out of the kinetic energy of raindrop impact and associated surface runoff. Rainfall erosivity is often expressed as the R-factor in soil erosion risk models like the Universal Soil Loss Equation (USLE) and its revised version (RUSLE). Just like precipitation, the rainfall erosivity of Switzerland has a characteristic seasonal dynamic throughout the year. This inter-annual variability is to be assessed by a monthly and seasonal modelling approach. We used a network of 86 precipitation gauging stations with a 10-minute temporal resolution to calculate long-term average monthly R-factors. Stepwise regression and Monte Carlo Cross Validation (MCCV) was used to select spatial covariates to explain the spatial pattern of R-factor for each month across Switzerland. The regionalized monthly R-factor is mapped by its individual regression equation and the ordinary kriging interpolation of its residuals (Regression-Kriging). As covariates, a variety of precipitation indicator data has been included like snow height, a combination of hourly gauging measurements and radar observations (CombiPrecip), mean monthly alpine precipitation (EURO4M-APGD) and monthly precipitation sums (Rhires). Topographic parameters were also significant explanatory variables for single months. The comparison of all 12 monthly rainfall erosivity maps showed seasonality with highest rainfall erosivity in summer (June, July, and August) and lowest rainfall erosivity in winter months. Besides the inter-annual temporal regime, a seasonal spatial variability was detectable. Spatial maps of monthly rainfall erosivity are presented for the first time for Switzerland. The assessment of the spatial and temporal dynamic behaviour of the R-factor is valuable for the identification of more susceptible seasons and regions as well as for the application of selective erosion control measures. A combination with monthly vegetation

  13. Barriers to wheelchair use in the winter.

    Science.gov (United States)

    Ripat, Jacquie D; Brown, Cara L; Ethans, Karen D

    2015-06-01

    To test the hypothesis that challenges to community participation posed by winter weather are greater for individuals who use scooters, manual and power wheelchairs (wheeled mobility devices [WMDs]) than for the general ambulatory population, and to determine what WMD users identify as the most salient environmental barriers to community participation during the winter. Cross-sectional survey organized around 5 environmental domains: technological, natural, physical, social/attitudinal, and policy. Urban community in Canada. Convenience sample of WMD users or their proxy (N=99). Not applicable. Not applicable. Forty-two percent identified reduced outing frequency in winter months, associated with increased age (χ(3)=6.4, P=.04), lack of access to family/friends for transportation (χ(2)=8.1, P=.04), and primary type of WMD used in the winter (scooter χ(2)=8.8, P=.003). Most reported tires/casters becoming stuck in the snow (95%) or slipping on the ice (91%), difficulty ascending inclines/ramps (92%), and cold hands while using controls or pushing rims (85%); fewer identified frozen wheelchair/scooter batteries, seat cushions/backrests, or electronics. Sidewalks/roads were reported to be problematic by 99%. Eighty percent reported needing additional help in the winter. Limited community access in winter led to a sense of loneliness/isolation, and fear/anxiety related to safety. Respondents identified policies that limited participation during winter. People who use WMDs decrease their community participation in cold weather because of multiple environmental barriers. Clinicians, researchers, and policymakers can take a multidimensional approach to mitigate these barriers in order to enhance community participation by WMD users in winter. Copyright © 2015 American Congress of Rehabilitation Medicine. Published by Elsevier Inc. All rights reserved.

  14. Computation of large scale currents in the Arabian Sea during winter using a semi-diagnostic model

    Digital Repository Service at National Institute of Oceanography (India)

    Shaji, C.; Bahulayan, N.; Rao, A.D.; Dube, S.K.

    A 3-dimensional, semi-diagnostic model with 331 levels in the vertical has been used for the computation of climatic circulation in the western tropical Indian Ocean. Model is driven with the seasonal mean data on wind stress, temperature...

  15. Assessment of the potential forecasting skill of a global hydrological model in reproducing the occurrence of monthly flow extremes

    Directory of Open Access Journals (Sweden)

    N. Candogan Yossef

    2012-11-01

    Full Text Available As an initial step in assessing the prospect of using global hydrological models (GHMs for hydrological forecasting, this study investigates the skill of the GHM PCR-GLOBWB in reproducing the occurrence of past extremes in monthly discharge on a global scale. Global terrestrial hydrology from 1958 until 2001 is simulated by forcing PCR-GLOBWB with daily meteorological data obtained by downscaling the CRU dataset to daily fields using the ERA-40 reanalysis. Simulated discharge values are compared with observed monthly streamflow records for a selection of 20 large river basins that represent all continents and a wide range of climatic zones.

    We assess model skill in three ways all of which contribute different information on the potential forecasting skill of a GHM. First, the general skill of the model in reproducing hydrographs is evaluated. Second, model skill in reproducing significantly higher and lower flows than the monthly normals is assessed in terms of skill scores used for forecasts of categorical events. Third, model skill in reproducing flood and drought events is assessed by constructing binary contingency tables for floods and droughts for each basin. The skill is then compared to that of a simple estimation of discharge from the water balance (PE.

    The results show that the model has skill in all three types of assessments. After bias correction the model skill in simulating hydrographs is improved considerably. For most basins it is higher than that of the climatology. The skill is highest in reproducing monthly anomalies. The model also has skill in reproducing floods and droughts, with a markedly higher skill in floods. The model skill far exceeds that of the water balance estimate. We conclude that the prospect for using PCR-GLOBWB for monthly and seasonal forecasting of the occurrence of hydrological extremes is positive. We argue that this conclusion applies equally to other similar GHMs and

  16. The Benefish consortium 24 month report WP6: productivity modelling of OWI's and welfare intervention measures

    NARCIS (Netherlands)

    Schneider, O.; Schram, E.; Noble, C.

    2009-01-01

    In order to accurately model all costs and benefits associated with welfare interventions for farmed fish it is necessary to establish how any welfare actions affect productivity. Productivity modelling within Benefish has been conducted in WP6. WP6 aimed to model relationships between welfare

  17. Implementation and evaluation of a monthly water balance model over the US on an 800 m grid

    Science.gov (United States)

    Hostetler, Steven W.; Alder, Jay R.

    2016-01-01

    We simulate the 1950–2010 water balance for the conterminous U.S. (CONUS) with a monthly water balance model (MWBM) using the 800 m Parameter-elevation Regression on Independent Slopes Model (PRISM) data set as model input. We employed observed snow and streamflow data sets to guide modification of the snow and potential evapotranspiration components in the default model and to evaluate model performance. Based on various metrics and sensitivity tests, the modified model yields reasonably good simulations of seasonal snowpack in the West (range of bias of ±50 mm at 68% of 713 SNOTEL sites), the gradients and magnitudes of actual evapotranspiration, and runoff (median correlation of 0.83 and median Nash-Sutcliff efficiency of 0.6 between simulated and observed annual time series at 1427 USGS gage sites). The model generally performs well along the Pacific Coast, the high elevations of the Basin and Range and over the Midwest and East, but not as well over the dry areas of the Southwest and upper Plains regions due, in part, to the apportioning of direct versus delayed runoff. Sensitivity testing and application of the MWBM to simulate the future water balance at four National Parks when driven by 30 climate models from the Climate Model Intercomparison Program Phase 5 (CMIP5) demonstrate that the model is useful for evaluating first-order, climate driven hydrologic change on monthly and annual time scales.

  18. Impact of partly ice-free Lake Ladoga on temperature and cloudiness in an anticyclonic winter situation – a case study using a limited area model

    Directory of Open Access Journals (Sweden)

    Kalle Eerola

    2014-12-01

    Full Text Available At the end of January 2012, a low-level cloud from partly ice-free Lake Ladoga caused very variable 2-m temperatures in Eastern Finland. The sensitivity of the High Resolution Limited Area Model (HIRLAM to the lake surface conditions was tested in this winter anticyclonic situation. The lake appeared to be (incorrectly totally covered by ice when the lake surface was described with its climatology. Both parametrisation of the lake surface state by using a lake model integrated to the NWP system and objective analysis based on satellite observations independently resulted in a correct description of the partly ice-free Lake Ladoga. In these cases, HIRLAM model forecasts were able to predict cloud formation and its movement as well as 2-m temperature variations in a realistic way. Three main conclusions were drawn. First, HIRLAM could predict the effect of Lake Ladoga on local weather, when the lake surface state was known. Second, the current parametrisation methods of air–surface interactions led to a reliable result in conditions where the different physical processes (local surface processes, radiation and turbulence were not strong, but their combined effect was important. Third, these results encourage work for a better description of the lake surface state in NWP models by fully utilising satellite observations, combined with advanced lake parametrisation and data assimilation methods.

  19. The Benefish consortium 24 month report WP6: productivity modelling of OWI's and welfare intervention measures

    OpenAIRE

    Schneider, O.; Schram, E.; Noble, C.

    2009-01-01

    In order to accurately model all costs and benefits associated with welfare interventions for farmed fish it is necessary to establish how any welfare actions affect productivity. Productivity modelling within Benefish has been conducted in WP6. WP6 aimed to model relationships between welfare interventions, changes in OWI’s and measures of productivity. It did so focusing only on the effects which were biological in nature: economic costs and benefits attributed to changes in productivity ar...

  20. The nuclear winter

    International Nuclear Information System (INIS)

    Velikhow, Y.P.

    1986-01-01

    Nuclear winter is an example of possible secondary effects, and if we speak of secondary we are thinking of small-scale second-order effects, but a nuclear winter is not a second-order effect. If you calculate the amount of heat produced by a nuclear explosion, it is a very small amount which does not have any chance of changing the Earth's climate, but a nuclear explosion drives or stars some new mechanism - the mechanism of nuclear winter - after 100 megatons of dust are transferred to the upper atmosphere. Another example of such amplification is radioactive fall-out, especially long-life radioactive fall-out after the possible elimination of the nuclear power industry, nuclear storage and distribution of storage waste around the globe. This is a very powerful amplification mechanism

  1. Modeling Coupled Water and Heat Transport in the Root Zone of Winter Wheat under Non-Isothermal Conditions

    Directory of Open Access Journals (Sweden)

    Rong Ren

    2017-04-01

    Full Text Available Temperature is an integral part of soil quality in terms of moisture content; coupling between water and heat can render a soil fertile, and plays a role in water conservation. Although it is widely recognized that both water and heat transport are fundamental factors in the quantification of soil mass and energy balance, their computation is still limited in most models or practical applications in the root zone under non-isothermal conditions. This research was conducted to: (a implement a fully coupled mathematical model that contains the full coupled process of soil water and heat transport with plants focused on the influence of temperature gradient on soil water redistribution and on the influence of change in soil water movement on soil heat flux transport; (b verify the mathematical model with detailed field monitoring data; and (c analyze the accuracy of the model. Results show the high accuracy of the model in predicting the actual changes in soil water content and temperature as a function of time and soil depth. Moreover, the model can accurately reflect changes in soil moisture and heat transfer in different periods. With only a few empirical parameters, the proposed model will serve as guide in the field of surface irrigation.

  2. Assessment of Brown Bear\\'s (Ursus arctos syriacus Winter Habitat Using Geographically Weighted Regression and Generalized Linear Model in South of Iran

    Directory of Open Access Journals (Sweden)

    A. A. Zarei

    2016-03-01

    Full Text Available Winter dens are one of the important components of brown bear's (Ursus arctos syriacus habitat, affecting their reproduction and survival. Therefore identification of factors affecting the habitat selection and suitable denning areas in the conservation of our largest carnivore is necessary. We used Geographically Weighted Logistic Regression (GWLR and Generalized Linear Model (GLM for modeling suitability of denning habitat in Kouhkhom region in Fars province. In the present research, 20 dens (presence locations and 20 caves where signs of bear were not found (absence locations were used as dependent variables and six environmental factors were used for each location as independent variables. The results of GLM showed that variables of distance to settlements, altitude, and distance to water were the most important parameters affecting suitability of the brown bear's denning habitat. The results of GWLR showed the significant local variations in the relationship between occurrence of brown bear dens and the variable of distance to settlements. Based on the results of both models, suitable habitats for denning of the species are impassable areas in the mountains and inaccessible for humans.

  3. Evaluation of the Community Multiscale Air Quality Model for Simulating Winter Ozone Formation in the Uinta Basin with Intensive Oil and Gas Production

    Science.gov (United States)

    Matichuk, R.; Tonnesen, G.; Luecken, D.; Roselle, S. J.; Napelenok, S. L.; Baker, K. R.; Gilliam, R. C.; Misenis, C.; Murphy, B.; Schwede, D. B.

    2015-12-01

    The western United States is an important source of domestic energy resources. One of the primary environmental impacts associated with oil and natural gas production is related to air emission releases of a number of air pollutants. Some of these pollutants are important precursors to the formation of ground-level ozone. To better understand ozone impacts and other air quality issues, photochemical air quality models are used to simulate the changes in pollutant concentrations in the atmosphere on local, regional, and national spatial scales. These models are important for air quality management because they assist in identifying source contributions to air quality problems and designing effective strategies to reduce harmful air pollutants. The success of predicting oil and natural gas air quality impacts depends on the accuracy of the input information, including emissions inventories, meteorological information, and boundary conditions. The treatment of chemical and physical processes within these models is equally important. However, given the limited amount of data collected for oil and natural gas production emissions in the past and the complex terrain and meteorological conditions in western states, the ability of these models to accurately predict pollution concentrations from these sources is uncertain. Therefore, this presentation will focus on understanding the Community Multiscale Air Quality (CMAQ) model's ability to predict air quality impacts associated with oil and natural gas production and its sensitivity to input uncertainties. The results will focus on winter ozone issues in the Uinta Basin, Utah and identify the factors contributing to model performance issues. The results of this study will help support future air quality model development, policy and regulatory decisions for the oil and gas sector.

  4. The Shifting Seasonal Mean Autoregressive Model and Seasonality in the Central England Monthly Temperature Series, 1772-2016

    DEFF Research Database (Denmark)

    He, Changli; Kang, Jian; Terasvirta, Timo

    In this paper we introduce an autoregressive model with seasonal dummy variables in which coefficients of seasonal dummies vary smoothly and deterministically over time. The error variance of the model is seasonally heteroskedastic and multiplicatively decomposed, the decomposition being similar ...... temperature series. More specifically, the idea is to find out in which way and by how much the monthly temperatures are varying over time during the period of more than 240 years, if they do. Misspecification tests are applied to the estimated model and the findings discussed....

  5. Diagnosing sea ice from the north american multi model ensemble and implications on mid-latitude winter climate

    Science.gov (United States)

    Elders, Akiko; Pegion, Kathy

    2017-12-01

    Arctic sea ice plays an important role in the climate system, moderating the exchange of energy and moisture between the ocean and the atmosphere. An emerging area of research investigates how changes, particularly declines, in sea ice extent (SIE) impact climate in regions local to and remote from the Arctic. Therefore, both observations and model estimates of sea ice become important. This study investigates the skill of sea ice predictions from models participating in the North American Multi-Model Ensemble (NMME) project. Three of the models in this project provide sea-ice predictions. The ensemble average of these models is used to determine seasonal climate impacts on surface air temperature (SAT) and sea level pressure (SLP) in remote regions such as the mid-latitudes. It is found that declines in fall SIE are associated with cold temperatures in the mid-latitudes and pressure patterns across the Arctic and mid-latitudes similar to the negative phase of the Arctic Oscillation (AO). These findings are consistent with other studies that have investigated the relationship between declines in SIE and mid-latitude weather and climate. In an attempt to include additional NMME models for sea-ice predictions, a proxy for SIE is used to estimate ice extent in the remaining models, using sea surface temperature (SST). It is found that SST is a reasonable proxy for SIE estimation when compared to model SIE forecasts and observations. The proxy sea-ice estimates also show similar relationships to mid-latitude temperature and pressure as the actual sea-ice predictions.

  6. Payment mechanisms for winter road maintenance services

    Directory of Open Access Journals (Sweden)

    Adel Abdi

    2013-12-01

    Full Text Available In countries with severe winters a major part of the annual budget for road maintenance is allocated on performance of winter road maintenance tasks. Finding appropriate remuneration forms to compensate entrepreneurs for performed road measures during winter is not an easy task in order to minimise or eliminate disputes and satisfy both client organisations and contractors. On the other hand improper reimbursement models lead either to the client’s annual budget imbalance due to unnecessary cost overruns or affect contractor’s cash-flow. Such cases in turn affect just-in-time winter road maintenance and then traffic safety. To solve such problems, a number of countries in cold regions like Sweden have developed different remuneration models based more on weather data called Weather Index. Therefore the objective of this paper is to investigate and evaluate the payment models applied in Sweden. The study uses a number of approaches namely; domestic questionnaire survey, analysis of a number of contract documents, a series of meetings with the project managers and an international benchmarking. The study recognised four remuneration models for winter maintenance service of which one based on weather data statistics. The study reveals the payment model based on weather data statistics is only applied for the roads with higher traffic flow and the model generates most uncertainty.

  7. Uncertainty in a monthly water balance model using the generalized likelihood uncertainty estimation methodology

    Science.gov (United States)

    Rivera, Diego; Rivas, Yessica; Godoy, Alex

    2015-02-01

    Hydrological models are simplified representations of natural processes and subject to errors. Uncertainty bounds are a commonly used way to assess the impact of an input or model architecture uncertainty in model outputs. Different sets of parameters could have equally robust goodness-of-fit indicators, which is known as Equifinality. We assessed the outputs from a lumped conceptual hydrological model to an agricultural watershed in central Chile under strong interannual variability (coefficient of variability of 25%) by using the Equifinality concept and uncertainty bounds. The simulation period ran from January 1999 to December 2006. Equifinality and uncertainty bounds from GLUE methodology (Generalized Likelihood Uncertainty Estimation) were used to identify parameter sets as potential representations of the system. The aim of this paper is to exploit the use of uncertainty bounds to differentiate behavioural parameter sets in a simple hydrological model. Then, we analyze the presence of equifinality in order to improve the identification of relevant hydrological processes. The water balance model for Chillan River exhibits, at a first stage, equifinality. However, it was possible to narrow the range for the parameters and eventually identify a set of parameters representing the behaviour of the watershed (a behavioural model) in agreement with observational and soft data (calculation of areal precipitation over the watershed using an isohyetal map). The mean width of the uncertainty bound around the predicted runoff for the simulation period decreased from 50 to 20 m3s-1 after fixing the parameter controlling the areal precipitation over the watershed. This decrement is equivalent to decreasing the ratio between simulated and observed discharge from 5.2 to 2.5. Despite the criticisms against the GLUE methodology, such as the lack of statistical formality, it is identified as a useful tool assisting the modeller with the identification of critical parameters.

  8. Drinking behaviour in sows kept outdoors during the winter months

    DEFF Research Database (Denmark)

    Andersen, Heidi Mai-Lis; Pedersen, Lene Juul

    2014-01-01

    alive, stillborn and weaned piglets were recorded. The recordingperiod was divided into two temperature categories; control days (CD) with daily averageair temperature at or above 0◦C and frosty days (FD) with daily average air temperaturebelow 0◦C. The FD included data from 22 days representing 11 sows...

  9. Simulation of winter wheat yield and its variability in different climates of Europe: A comparison of eight crop growth models

    DEFF Research Database (Denmark)

    Palosuo, Taru; Kersebaum, Kurt Christian; Angulo, Carlos

    2011-01-01

    observations at all sites and in all years, and none could unequivocally be labelled robust and accurate in terms of yield prediction across different environments and crop cultivars with only minimum calibration. The best performance regarding yield estimation was for DAISY and DSSAT, for which the RMSE...... and WOFOST furnished high total above-ground biomass estimates, whereas CROPSYST, DSSAT and FASSET provided low total above-ground estimates. Consequently, DSSAT and FASSET produced very high harvest index values, followed by HERMES and WOFOST. APES and DAISY, on the other hand, returned low harvest index...... of grain yield estimates provided by the models for all sites and years reflects substantial uncertainties in model estimates achieved with only minimum calibration. Mean predictions from the eight models, on the other hand, were in good agreement with measured data. This applies to both results across all...

  10. Employment and winter construction

    DEFF Research Database (Denmark)

    Hansen, Ernst Jan de Place; Larsen, Jacob Norvig

    2011-01-01

    Reduced seasonal building activity in the construction sector is often assumed to be related to hard winter conditions for building activities and poor working conditions for construction workers, resulting in higher costs and poor quality of building products, particularly in the northern hemisp...... of contracts for workers is more likely to explain differences in seasonal activity than climatic or technological factors....

  11. Titan's Emergence from Winter

    Science.gov (United States)

    Flasar, F. Michael; Achterberg, Richard; Jennings, Donald; Schinder, Paul

    2011-01-01

    We summarize the changes in Titans thermal structure derived from Cassini CIRS and radio-occultation data during the transition from winter to early spring. Titan's surface, and middle atmosphere show noticeable seasonal change, whereas that in most of the troposphere is mated. This can be understood in terms of the relatively small radiative relaxation time in the middle atmosphere and much larger time scale in the troposphere. The surface exhibits seasonal change because the heat capacity in an annual skin depth is much smaller than that in the lowest scale height of the troposphere. Surface temperatures rise 1 K at raid and high latitudes in the winter northern hemisphere and cool in the southern hemisphere. Changes in in the middle atmosphere are more complicated. Temperatures in the middle stratosphere (approximately 1 mbar) increase by a few kelvin at mid northern latitudes, but those at high latitudes first increase as that region moves out of winter shadow, and then decrease. This probably results from the combined effect of increased solar heating as the suit moves higher in the sky and the decreased adiabatic warming as the sinking motions associated with the cross-equatorial meridional cell weaken. Consistent with this interpretation, the warm temperatures observed higher up at the winter polar stratopause cool significantly.

  12. Observation and Modelling of the OH, HO2 and RO2 Radicals at a Regional Site of Beijing in Winter 2016.

    Science.gov (United States)

    Tan, Z.; Lu, K.; Ma, X.; Bohn, B.; Hofzumahaus, A.; Broch, S.; Fuchs, H.; Holland, F.; Liu, Y.; Li, X.; Novelli, A.; Rohrer, F.; Wang, H.; Wu, Y.; Shao, M.; Zeng, L.; Kiendler-Scharr, A.; Wahner, A.; Zhang, Y.

    2017-12-01

    A comprehensive field campaign was carried out in winter 2016 in the campus of UCAS (University of Chinese Academy of Science), located in a small town 60 km northeast of urban Beijing. Concentrations of OH, HO2 and RO2 radicals as well as the total OH reactivity were measured by a laser induced fluorescence instrument. Maximum hourly averaged OH, HO2 and RO2 radical concentrations were (3±2)×106cm-3, (8±6)×107 cm-3 and (7±5)×107 cm-3, respectively. These radical concentrations were smaller than those observed during summer because of the reduced solar radiation. A chemical modulation device to separate atmospheric OH radicals from any interfering species was applied for few days showing negligible interference for both clean and polluted air masses.HONO and HCHO photolysis were found to be the most important primary sources of ROx radicals. CO and NOx were the important OH reactants which contributed more than half of the total OH reactivity. The relative high OH concentrations in polluted episode enabled a fast oxidation of fresh emitted pollutants and the formation of secondary air products. The observed radical concentrations were compared with the results from a chemical box model. The model is capable of reproducing radical concentrations for moderate NOx conditions but larger discrepancies are observed for both low and high NOx regimes for the peroxy radical concentrations. The underestimation of RO2 radical concentrations for high NOx conditions is discussed in the context of recent campaigns.

  13. The usefulness of fungicide mixtures and alternation for delaying the selection for resistance in populations of Mycosphaerella graminicola on winter wheat: a modeling analysis.

    Science.gov (United States)

    Hobbelen, P H F; Paveley, N D; Oliver, R P; van den Bosch, F

    2013-07-01

    A fungicide resistance model (reported and tested previously) was amended to describe the development of resistance in Mycosphaerella graminicola populations in winter wheat (Triticum aestivum) crops in two sets of fields, connected by spore dispersal. The model was used to evaluate the usefulness of concurrent, alternating, or mixture use of two high-resistance-risk fungicides as resistance management strategies. We determined the effect on the usefulness of each strategy of (i) fitness costs of resistance, (ii) partial resistance to fungicides, (iii) differences in the dose-response curves and decay rates between fungicides, and (iv) different frequencies of the double-resistant strain at the start of a treatment strategy. Parameter values for the quinine outside inhibitor pyraclostrobin were used to represent two fungicides with differing modes of action. The effectiveness of each strategy was quantified as the maximum number of growing seasons that disease was effectively controlled in both sets of fields. For all scenarios, the maximum effective lives achieved by the use of the strategies were in the order mixtures ≥ alternation ≥ concurrent use. Mixtures were of particular benefit where the pathogen strain resistant to both modes of action incurred a fitness penalty or was present at a low initial frequency.

  14. Assessing the impacts of future climate conditions on the effectiveness of winter cover crops in reducing nitrate loads into the Chesapeake Bay Watershed using SWAT model

    Science.gov (United States)

    Lee, Sangchul; Sadeghi, Ali M.; Yeo, In-Young; McCarty, Gregory W.; Hively, W. Dean

    2017-01-01

    Winter cover crops (WCCs) have been widely implemented in the Coastal Plain of the Chesapeake Bay watershed (CBW) due to their high effectiveness at reducing nitrate loads. However, future climate conditions (FCCs) are expected to exacerbate water quality degradation in the CBW by increasing nitrate loads from agriculture. Accordingly, the question remains whether WCCs are sufficient to mitigate increased nutrient loads caused by FCCs. In this study, we assessed the impacts of FCCs on WCC nitrate reduction efficiency on the Coastal Plain of the CBW using Soil and Water Assessment Tool (SWAT) model. Three FCC scenarios (2085 – 2098) were prepared using General Circulation Models (GCMs), considering three Intergovernmnental Panel on Climate Change (IPCC) Special Report on Emissions Scenarios (SRES) greenhouse gas emission scenarios. We also developed six representative WCC implementation scenarios based on the most commonly used planting dates and species of WCCs in this region. Simulation results showed that WCC biomass increased by ~ 58 % under FCC scenarios, due to climate conditions conducive to the WCC growth. Prior to implementing WCCs, annual nitrate loads increased by ~ 43 % under FCC scenarios compared to the baseline scenario (2001 – 2014). When WCCs were planted, annual nitrate loads were substantially reduced by ~ 48 % and WCC nitrate reduction efficiency water ~ 5 % higher under FCC scenarios relative to the baseline. The increase rate of WCC nitrate reduction efficiency varied by FCC scenarios and WCC planting methods. As CO2 concentration was higher and winters were warmer under FCC scenarios, WCCs had greater biomass and therefore showed higher nitrate reduction efficiency. In response to FCC scenarios, the performance of less effective WCC practices (e.g., barley, wheat, and late planting) under the baseline indicated ~ 14 % higher increase rate of nitrate reduction efficiency compared to ones with better effectiveness under the baseline (e

  15. Predictive model for serious bacterial infections among infants younger than 3 months of age.

    Science.gov (United States)

    Bachur, R G; Harper, M B

    2001-08-01

    To develop a data-derived model for predicting serious bacterial infection (SBI) among febrile infants /=38.0 degrees C seen in an urban emergency department (ED) were retrospectively identified. SBI was defined as a positive culture of urine, blood, or cerebrospinal fluid. Tree-structured analysis via recursive partitioning was used to develop the model. SBI or No-SBI was the dichotomous outcome variable, and age, temperature, urinalysis (UA), white blood cell (WBC) count, absolute neutrophil count, and cerebrospinal fluid WBC were entered as potential predictors. The model was tested by V-fold cross-validation. Of 5279 febrile infants studied, SBI was diagnosed in 373 patients (7%): 316 urinary tract infections (UTIs), 17 meningitis, and 59 bacteremia (8 with meningitis, 11 with UTIs). The model sequentially used 4 clinical parameters to define high-risk patients: positive UA, WBC count >/=20 000/mm(3) or /=39.6 degrees C, and age <13 days. The sensitivity of the model for SBI is 82% (95% confidence interval [CI]: 78%-86%) and the negative predictive value is 98.3% (95% CI: 97.8%-98.7%). The negative predictive value for bacteremia or meningitis is 99.6% (95% CI: 99.4%-99.8%). The relative risk between high- and low-risk groups is 12.1 (95% CI: 9.3-15.6). Sixty-six SBI patients (18%) were misclassified into the lower risk group: 51 UTIs, 14 with bacteremia, and 1 with meningitis. Decision-tree analysis using common clinical variables can reasonably predict febrile infants at high-risk for SBI. Sequential use of UA, WBC count, temperature, and age can identify infants who are at high risk of SBI with a relative risk of 12.1 compared with lower-risk infants.

  16. Application of IEUBK model in lead risk assessment of children aged 61–84 months old in central China

    Energy Technology Data Exchange (ETDEWEB)

    Li, Yanyan [MOE Key Lab of Environment and Health, Institute of Environmental Medicine, School of Public Health, Tongji Medical College, Huazhong University of Science & Technology, Wuhan, Hubei (China); Hu, Jia [Suzhou Center for Disease Prevention and Control, Suzhou, Jiangsu (China); Wu, Wei [MOE Key Lab of Environment and Health, Institute of Environmental Medicine, School of Public Health, Tongji Medical College, Huazhong University of Science & Technology, Wuhan, Hubei (China); Liu, Shuyun [Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Science & Technology, Wuhan, Hubei (China); Li, Mei [Hanyang Center for Disease Prevention and Control, Wuhan, Hubei (China); Yao, Na; Chen, Jianwei [MOE Key Lab of Environment and Health, Institute of Environmental Medicine, School of Public Health, Tongji Medical College, Huazhong University of Science & Technology, Wuhan, Hubei (China); Ye, Linxiang [Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Science & Technology, Wuhan, Hubei (China); Wang, Qi, E-mail: lwq95@126.com [MOE Key Lab of Environment and Health, Institute of Environmental Medicine, School of Public Health, Tongji Medical College, Huazhong University of Science & Technology, Wuhan, Hubei (China); Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Science & Technology, Wuhan, Hubei (China); Zhou, Yikai, E-mail: zhouyk@mails.tjmu.edu.cn [MOE Key Lab of Environment and Health, Institute of Environmental Medicine, School of Public Health, Tongji Medical College, Huazhong University of Science & Technology, Wuhan, Hubei (China)

    2016-01-15

    Few studies have focused on the accuracy of using the Integrated Exposure Uptake Biokinetic (IEUBK) model in Chinese children with site- and age-specific exposure data. This study aimed to validate the accuracy and sensitivity of the IEUBK model in lead risk assessment of Chinese children aged 61–84 months old. A total of 760 children were enrolled from two respective counties in Central China by using random cluster sampling method. Blood lead levels (BLLs) of all subjects were determined using graphite furnace atomic absorption spectrometry, as well as that in the environmental media, such as air, drinking water, soil, dust and food. Age- and site-specific time-activity patterns and water consumption were evaluated by using questionnaires for children. Exposure parameters including outdoor and indoor activity time, ventilation rate and water consumption in this study were different from the default values of the IEUBK model. Statistical analysis revealed no significant differences between the predicted and observed BLLs. Diet and soil/dust lead intake contributed approximately 83.39% (57.40%–93.84% range) and 15.18% (3.25%–41.60% range) of total lead intake, respectively. These findings showed that the IEUBK model is suitable for lead risk assessment of Chinese children aged 61–84 months old and diet acts as an important lead source. - Highlights: • The first time to fit and discuss the IEUBK model in China based on comprehensive local children exposure parameters. • Two different exposure scenarios to apply the IEUBK model in different conditions. • The first time to report the ventilation rate in Chinese children aged 61 to 84 months. • Highlight the role of dietary to lead intake for Chinese children.

  17. Application of IEUBK model in lead risk assessment of children aged 61–84 months old in central China

    International Nuclear Information System (INIS)

    Li, Yanyan; Hu, Jia; Wu, Wei; Liu, Shuyun; Li, Mei; Yao, Na; Chen, Jianwei; Ye, Linxiang; Wang, Qi; Zhou, Yikai

    2016-01-01

    Few studies have focused on the accuracy of using the Integrated Exposure Uptake Biokinetic (IEUBK) model in Chinese children with site- and age-specific exposure data. This study aimed to validate the accuracy and sensitivity of the IEUBK model in lead risk assessment of Chinese children aged 61–84 months old. A total of 760 children were enrolled from two respective counties in Central China by using random cluster sampling method. Blood lead levels (BLLs) of all subjects were determined using graphite furnace atomic absorption spectrometry, as well as that in the environmental media, such as air, drinking water, soil, dust and food. Age- and site-specific time-activity patterns and water consumption were evaluated by using questionnaires for children. Exposure parameters including outdoor and indoor activity time, ventilation rate and water consumption in this study were different from the default values of the IEUBK model. Statistical analysis revealed no significant differences between the predicted and observed BLLs. Diet and soil/dust lead intake contributed approximately 83.39% (57.40%–93.84% range) and 15.18% (3.25%–41.60% range) of total lead intake, respectively. These findings showed that the IEUBK model is suitable for lead risk assessment of Chinese children aged 61–84 months old and diet acts as an important lead source. - Highlights: • The first time to fit and discuss the IEUBK model in China based on comprehensive local children exposure parameters. • Two different exposure scenarios to apply the IEUBK model in different conditions. • The first time to report the ventilation rate in Chinese children aged 61 to 84 months. • Highlight the role of dietary to lead intake for Chinese children.

  18. [Construction of a diagnostic prediction model of severe bacterial infection in febrile infants under 3 months old].

    Science.gov (United States)

    Villalobos Pinto, Enrique; Sánchez-Bayle, Marciano

    2017-12-01

    Fever is a common cause of paediatric admissions in emergency departments. An aetiological diagnosis is difficult to obtain in those less than 3 months of age, as they tend to have a higher rate of serious bacterial infection (SBI). The aim of this study is to find a predictor index of SBI in children under 3 months old with fever of unknown origin. A study was conducted on all children under 3 months of age with fever admitted to hospital, with additional tests being performed according to the clinical protocol. Rochester criteria for identifying febrile infants at low risk for SBI were also analysed. A predictive model for SBI and positive cultures was designed, including the following variables in the maximum model: C-reactive protein (CRP), procalcitonin (PCT), and meeting not less than four of the Rochester criteria. A total of 702 subjects were included, of which 22.64% had an SBI and 20.65% had positive cultures. Children who had SBI and a positive culture showed higher values of white cells, total neutrophils, CRP and PCT. A statistical significance was observed with less than 4 Rochester criteria, CRP and PCT levels, an SBI (area under the curve [AUC] 0.877), or for positive cultures (AUC 0.888). Using regression analysis a predictive index was calculated for SBI or a positive culture, with a sensitivity of 87.7 and 91%, a specificity of 70.1 and 87.7%, an LR+ of 2.93 and 3.62, and a LR- of 0.17 and 0.10, respectively. The predictive models are valid and slightly improve the validity of the Rochester criteria for positive culture in children less than 3 months admitted with fever. Copyright © 2016 Asociación Española de Pediatría. Publicado por Elsevier España, S.L.U. All rights reserved.

  19. Assessing the impacts of climate change on winter crop production in Uruguay and Argentina using crop simulation models

    Energy Technology Data Exchange (ETDEWEB)

    Baethgen, W.E. [International Fertilizer Development Center, Muscle Shoals, AL (United States); Magrin, G.O. [Inst. Nacional de Tecnologia Agropecuaria Castelar, Buenos Aires (Argentina). Inst. de Clima y Agua

    1995-12-31

    Enhanced greenhouse effect caused by the increase in atmospheric concentration of CO{sub 2} and other trace gases could lead to higher global surface temperature and altered hydrological cycles. Most possible climate change scenarios include higher atmospheric CO{sub 2} concentrations, higher temperatures, and changes in precipitation. Three global climate models (GCMs) were applied to generate climate change scenarios for the Pampas region in southern South America. The generated scenarios were then used with crop simulation models to study the possible impact of climate change on wheat (Triticum aestivum L.) and barley (Hordeum vulgare L.) production in the Pampas. The authors evaluated the impact of possible climate change scenarios on wheat and barley production in Uruguay for a wide range of soil and crop management strategies including planting dates, cultivar types, fertilizer management, and tillage practices. They also studied the impact of climate change on wheat production across two transects of the Pampas: north to south transect with decreasing temperature, and east to west transect with decreasing precipitation. Finally, sensitivity analyses were conducted for both, the Uruguayan site and the transects, by increasing daily maximum and minimum temperature by 0, 2, and 4 C, and changing the precipitation by {minus}20, 0, and +20%.

  20. Genome-Wide Association Studies and Comparison of Models and Cross-Validation Strategies for Genomic Prediction of Quality Traits in Advanced Winter Wheat Breeding Lines

    Directory of Open Access Journals (Sweden)

    Peter S. Kristensen

    2018-02-01

    Full Text Available The aim of the this study was to identify SNP markers associated with five important wheat quality traits (grain protein content, Zeleny sedimentation, test weight, thousand-kernel weight, and falling number, and to investigate the predictive abilities of GBLUP and Bayesian Power Lasso models for genomic prediction of these traits. In total, 635 winter wheat lines from two breeding cycles in the Danish plant breeding company Nordic Seed A/S were phenotyped for the quality traits and genotyped for 10,802 SNPs. GWAS were performed using single marker regression and Bayesian Power Lasso models. SNPs with large effects on Zeleny sedimentation were found on chromosome 1B, 1D, and 5D. However, GWAS failed to identify single SNPs with significant effects on the other traits, indicating that these traits were controlled by many QTL with small effects. The predictive abilities of the models for genomic prediction were studied using different cross-validation strategies. Leave-One-Out cross-validations resulted in correlations between observed phenotypes corrected for fixed effects and genomic estimated breeding values of 0.50 for grain protein content, 0.66 for thousand-kernel weight, 0.70 for falling number, 0.71 for test weight, and 0.79 for Zeleny sedimentation. Alternative cross-validations showed that the genetic relationship between lines in training and validation sets had a bigger impact on predictive abilities than the number of lines included in the training set. Using Bayesian Power Lasso instead of GBLUP models, gave similar or slightly higher predictive abilities. Genomic prediction based on all SNPs was more effective than prediction based on few associated SNPs.

  1. Physical activity levels of community-dwelling older adults are influenced by winter weather variables.

    Science.gov (United States)

    Jones, G R; Brandon, C; Gill, D P

    2017-07-01

    Winter weather conditions may negatively influence participation of older adults in daily physical activity (PA). Assess the influence of winter meteorological variables, day-time peak ambient temperature, windchill, humidity, and snow accumulation on the ground to accelerometer measured PA values in older adults. 50 community-dwelling older adults (77.4±4.7yrs; range 71-89; 12 females) living in Southwestern Ontario (Latitude 42.9°N Longitude 81.2° W) Canada, wore a waist-borne accelerometer during active waking hours (12h) for 7 consecutive days between February and April 2007. Hourly temperature, windchill, humidity, and snowfall accumulation were obtained from meteorological records and time locked to hourly accelerometer PA values. Regression analysis revealed significant relationships between time of day, ambient daytime high temperature and a humidity for participation in PA. Windchill temperature added no additional influence over PA acclamation already influenced by ambient day-time temperature and the observed variability in PA patterns relative to snow accumulation over the study period was too great to warrant its inclusion in the model. Most PA was completed in the morning hours and increased as the winter month's transitioned to spring (February through April). An equation was developed to adjust for winter weather conditions using temperature, humidity and time of day. Accurate PA assessment during the winter months must account for the ambient daytime high temperatures, humidity, and time of day. These older adults were more physically active during the morning hours and became more active as the winter season transitioned to spring. Copyright © 2017 Elsevier B.V. All rights reserved.

  2. Kansas environmental and resource study: A Great Plains model. [land use, image enhancement, winter wheat, agriculture, water resources, and pattern recognition

    Science.gov (United States)

    Haralick, R. M.; Kanemasu, E. T.; Morain, S. A.; Yarger, H. L.; Ulaby, F. T.; Davis, J. C. (Principal Investigator); Bosley, R. J.; Williams, D. L.; Mccauley, J. R.; Mcnaughton, J. L.

    1973-01-01

    The author has identified the following significant results. Improvement in the land use classification accuracy of ERTS-1 MSS multi-images over Kansas can be made using two distances between neighboring grey tone N-tuples instead of one distance. Much more information is contained texturally than spectrally on the Kansas image. Ground truth measurements indicate that reflectance ratios of the 545 and 655 nm wavebands provide an index of plant development and possibly physiological stress. Preliminary analysis of MSS 4 and 5 channels substantiate the ground truth interpretation. Results of the land use mapping experiment indicate that ERTS-1 imagery has major potential in regionalization. The ways in which land is utilized within these regions may then be studied more effectively than if no adequate regionalization is available. A model for estimating wheat yield per acre has been applied to acreage estimates derived from ERTS-1 imagery to project the 1973 wheat yields for a ten county area in southwest Kansas. The results are within 3% of the preharvest estimates for the same area prepared by the USDA. Visual identification of winter wheat is readily achieved by using a temporal sequence of images. Identification can be improve by stratifying the project area into subregions having more or less homogeneous agricultural practices and crop mixes.

  3. Wintertime Overnight NOx Removal in a Southeastern United States Coal-Fired Power Plant Plume: A Model for Understanding Winter NOx Processing and Its Implications

    Science.gov (United States)

    Fibiger, Dorothy L.; McDuffie, Erin E.; Dube, William P.; Aikin, Kenneth C.; Lopez-Hilifiker, Felipe D.; Lee, Ben H.; Green, Jaime R.; Fiddler, Marc N.; Holloway, John S.; Ebben, Carlena; hide

    2018-01-01

    Nitric oxide (NO) is emitted in large quantities from coal-�burning power plants. During the day, the plumes from these sources are efficiently mixed into the boundary layer, while at night, they may remain concentrated due to limited vertical mixing during which they undergo horizontal fanning. At night, the degree to which NO is converted to HNO3 and therefore unable to participate in next-�day ozone (O3) formation depends on the mixing rate of the plume, the composition of power plant emissions, and the composition of the background atmosphere. In this study, we use observed plume intercepts from the Wintertime INvestigation of Transport, Emissions and Reactivity (WINTER) campaign to test sensitivity of overnight NOx removal to the N2O5 loss rate constant, plume mixing rate, background O3, and background levels of volatile organic compounds using a 2-�D box model of power plant plume transport and chemistry. The factor that exerted the greatest control over NOx removal was the loss rate constant of N2O5. At the lowest observed N2O5 loss rate constant, no other combination of conditions converts more than 10 percent of the initial NOx to HNO3. The other factors did not influence NOx removal to the same degree.

  4. Assessing Intelligent Models in Forecasting Monthly Rainfall by Means of Teleconnection Patterns (Case Study: Khorasan Razavi Province

    Directory of Open Access Journals (Sweden)

    Farzaneh Nazarieh

    2016-02-01

    Full Text Available Introduction: Rainfall is affected by changes in the global sea level change, especially changes in sea surface temperature SST Sea Surface Temperature and sea level pressure SLP Sea level Pressure. Climate anomalies being related to each other at large distance is called teleconnection. As physical relationships between rainfall and teleconnection patterns are not defined clearly, we used intelligent models for forecasting rainfall. The intelligent models used in this study included Fuzzy Inference Systems, neural network and Neuro-fuzzy. In this study, first the teleconnection indices that could affect rainfall in the study area were identified. Then intelligent models were trained for rainfall forecasting. Finally, the most capable model for forecasting rainfall was presented. The study area for this research is the Khorasan Razavi Province. In order to present a model for rainfall forecasting, rainfall data of seven synoptic stations including Mashhad, Golmakan, Nishapur, Sabzevar, Kashmar, Torbate and Sharks since 1991 to 2010 were used. Materials and Methods: Based on previous studies about Teleconnection Patterns in the study area, effective Teleconnection indexes were identified. After calculating the correlation between the identified teleconnection indices and rainfall in one, two and three months ahead for all stations, fourteen teleconnection indices were chosen as inputs for intelligent models. These indices include, SLP Adriatic , SLP northern Red Sea, SLP Mediterranean Sea, SLP Aral sea, SST Sea surface temperature Labrador sea, SST Oman Sea, SST Caspian Sea, SST Persian Gulf, North Pacific pattern, SST Tropical Pacific in NINO12 and NINO3 regions, North Pacific Oscillation, Trans-Nino Index, Multivariable Enso Index. Inputs of the intelligent models include fourteen teleconnection indices, latitude and altitude of each station and their outputs are the prediction of rainfall for one, two and three months ahead. For calibration of

  5. Severe European winters in a secular perspective

    Science.gov (United States)

    Hoy, Andreas; Hänsel, Stephanie

    2017-04-01

    Temperature conditions during the winter time are substantially shaped by a strong year-to-year variability. European winters since the late 1980s - compared to previous decades and centuries - were mainly characterised by a high temperature level, including recent record-warm winters. Yet, comparably cold winters and severe cold spells still occur nowadays, like recently observed from 2009 to 2013 and in early 2017. Central England experienced its second coldest December since start of observations more than 350 years ago in 2010, and some of the lowest temperatures ever measured in northern Europe (below -50 °C in Lapland) were recorded in January 1999. Analysing thermal characteristics and spatial distribution of severe (historical) winters - using early instrumental data - helps expanding and consolidating our knowledge of past weather extremes. This contribution presents efforts towards this direction. We focus on a) compiling and assessing a very long-term instrumental, spatially widespread and well-distributed, high-quality meteorological data set to b) investigate very cold winter temperatures in Europe from early measurements until today. In a first step, we analyse the longest available time series of monthly temperature averages within Europe. Our dataset extends from the Nordic countries up to the Mediterranean and from the British Isles up to Russia. We utilise as much as possible homogenised times series in order to ensure reliable results. Homogenised data derive from the NORDHOM (Scandinavia) and HISTALP (greater alpine region) datasets or were obtained from national weather services and universities. Other (not specifically homogenised) data were derived from the ECA&D dataset or national institutions. The employed time series often start already during the 18th century, with Paris & Central England being the longest datasets (from 1659). In a second step, daily temperature averages are involved. Only some of those series are homogenised, but

  6. In vitro dynamic model simulating the digestive tract of 6-month-old infants.

    Science.gov (United States)

    Passannanti, Francesca; Nigro, Federica; Gallo, Marianna; Tornatore, Fabio; Frasso, Annalisa; Saccone, Giulia; Budelli, Andrea; Barone, Maria V; Nigro, Roberto

    2017-01-01

    In vivo assays cannot always be conducted because of ethical reasons, technical constraints or costs, but a better understanding of the digestive process, especially in infants, could be of great help in preventing food-related pathologies and in developing new formulas with health benefits. In this context, in vitro dynamic systems to simulate human digestion and, in particular, infant digestion could become increasingly valuable. To simulate the digestive process through the use of a dynamic model of the infant gastroenteric apparatus to study the digestibility of starch-based infant foods. Using M.I.D.A (Model of an Infant Digestive Apparatus), the oral, gastric and intestinal digestibility of two starch-based products were measured: 1) rice starch mixed with distilled water and treated using two different sterilization methods (the classical method with a holding temperature of 121°C for 37 min and the HTST method with a holding temperature of 137°C for 70 sec) and 2) a rice cream with (premium product) or without (basic product) an aliquot of rice flour fermented by Lactobacillus paracasei CBA L74. After the digestion the foods were analyzed for the starch concentration, the amount of D-glucose released and the percentage of hydrolyzed starch. An in vitro dynamic system, which was referred to as M.I.D.A., was obtained. Using this system, the starch digestion occurred only during the oral and intestinal phase, as expected. The D-glucose released during the intestinal phase was different between the classical and HTST methods (0.795 grams for the HTST versus 0.512 for the classical product). The same analysis was performed for the basic and premium products. In this case, the premium product had a significant difference in terms of the starch hydrolysis percentage during the entire process. The M.I.D.A. system was able to digest simple starches and a more complex food in the correct compartments. In this study, better digestibility of the premium product was

  7. In vitro dynamic model simulating the digestive tract of 6-month-old infants

    Science.gov (United States)

    Gallo, Marianna; Tornatore, Fabio; Frasso, Annalisa; Saccone, Giulia; Budelli, Andrea; Barone, Maria V.

    2017-01-01

    Background In vivo assays cannot always be conducted because of ethical reasons, technical constraints or costs, but a better understanding of the digestive process, especially in infants, could be of great help in preventing food-related pathologies and in developing new formulas with health benefits. In this context, in vitro dynamic systems to simulate human digestion and, in particular, infant digestion could become increasingly valuable. Objective To simulate the digestive process through the use of a dynamic model of the infant gastroenteric apparatus to study the digestibility of starch-based infant foods. Design Using M.I.D.A (Model of an Infant Digestive Apparatus), the oral, gastric and intestinal digestibility of two starch-based products were measured: 1) rice starch mixed with distilled water and treated using two different sterilization methods (the classical method with a holding temperature of 121°C for 37 min and the HTST method with a holding temperature of 137°C for 70 sec) and 2) a rice cream with (premium product) or without (basic product) an aliquot of rice flour fermented by Lactobacillus paracasei CBA L74. After the digestion the foods were analyzed for the starch concentration, the amount of D-glucose released and the percentage of hydrolyzed starch. Results An in vitro dynamic system, which was referred to as M.I.D.A., was obtained. Using this system, the starch digestion occurred only during the oral and intestinal phase, as expected. The D-glucose released during the intestinal phase was different between the classical and HTST methods (0.795 grams for the HTST versus 0.512 for the classical product). The same analysis was performed for the basic and premium products. In this case, the premium product had a significant difference in terms of the starch hydrolysis percentage during the entire process. Conclusions The M.I.D.A. system was able to digest simple starches and a more complex food in the correct compartments. In this study

  8. Evaluation of three energy balance-based evaporation models for estimating monthly evaporation for five lakes using derived heat storage changes from a hysteresis model

    Science.gov (United States)

    Duan, Zheng; Bastiaanssen, W. G. M.

    2017-02-01

    The heat storage changes (Q t) can be a significant component of the energy balance in lakes, and it is important to account for Q t for reasonable estimation of evaporation at monthly and finer timescales if the energy balance-based evaporation models are used. However, Q t has been often neglected in many studies due to the lack of required water temperature data. A simple hysteresis model (Q t = a*Rn + b + c* dRn/dt) has been demonstrated to reasonably estimate Q t from the readily available net all wave radiation (Rn) and three locally calibrated coefficients (a-c) for lakes and reservoirs. As a follow-up study, we evaluated whether this hysteresis model could enable energy balance-based evaporation models to yield good evaporation estimates. The representative monthly evaporation data were compiled from published literature and used as ground-truth to evaluate three energy balance-based evaporation models for five lakes. The three models in different complexity are De Bruin-Keijman (DK), Penman, and a new model referred to as Duan-Bastiaanssen (DB). All three models require Q t as input. Each model was run in three scenarios differing in the input Q t (S1: measured Q t; S2: modelled Q t from the hysteresis model; S3: neglecting Q t) to evaluate the impact of Q t on the modelled evaporation. Evaluation showed that the modelled Q t agreed well with measured counterparts for all five lakes. It was confirmed that the hysteresis model with locally calibrated coefficients can predict Q t with good accuracy for the same lake. Using modelled Q t as inputs all three evaporation models yielded comparably good monthly evaporation to those using measured Q t as inputs and significantly better than those neglecting Q t for the five lakes. The DK model requiring minimum data generally performed the best, followed by the Penman and DB model. This study demonstrated that once three coefficients are locally calibrated using historical data the simple hysteresis model can offer

  9. Numerical simulation of a rare winter hailstorm event over Delhi, India on 17 January 2013

    Science.gov (United States)

    Chevuturi, A.; Dimri, A. P.; Gunturu, U. B.

    2014-12-01

    This study analyzes the cause of the rare occurrence of a winter hailstorm over New Delhi/NCR (National Capital Region), India. The absence of increased surface temperature or low level of moisture incursion during winter cannot generate the deep convection required for sustaining a hailstorm. Consequently, NCR shows very few cases of hailstorms in the months of December-January-February, making the winter hail formation a question of interest. For this study, a recent winter hailstorm event on 17 January 2013 (16:00-18:00 UTC) occurring over NCR is investigated. The storm is simulated using the Weather Research and Forecasting (WRF) model with the Goddard Cumulus Ensemble (GCE) microphysics scheme with two different options: hail and graupel. The aim of the study is to understand and describe the cause of hailstorm event during over NCR with a comparative analysis of the two options of GCE microphysics. Upon evaluating the model simulations, it is observed that the hail option shows a more similar precipitation intensity with the Tropical Rainfall Measuring Mission (TRMM) observation than the graupel option does, and it is able to simulate hail precipitation. Using the model-simulated output with the hail option; detailed investigation on understanding the dynamics of hailstorm is performed. The analysis based on a numerical simulation suggests that the deep instability in the atmospheric column led to the formation of hailstones as the cloud formation reached up to the glaciated zone promoting ice nucleation. In winters, such instability conditions rarely form due to low level available potential energy and moisture incursion along with upper level baroclinic instability due to the presence of a western disturbance (WD). Such rare positioning is found to be lowering the tropopause with increased temperature gradient, leading to winter hailstorm formation.

  10. Numerical simulation of a winter hailstorm event over Delhi, India on 17 January 2013

    Science.gov (United States)

    Chevuturi, A.; Dimri, A. P.; Gunturu, U. B.

    2014-09-01

    This study analyzes the cause of rare occurrence of winter hailstorm over New Delhi/NCR (National Capital Region), India. The absence of increased surface temperature or low level of moisture incursion during winter cannot generate the deep convection required for sustaining a hailstorm. Consequently, NCR shows very few cases of hailstorms in the months of December-January-February, making the winter hail formation a question of interest. For this study, recent winter hailstorm event on 17 January 2013 (16:00-18:00 UTC) occurring over NCR is investigated. The storm is simulated using Weather Research and Forecasting (WRF) model with Goddard Cumulus Ensemble (GCE) microphysics scheme with two different options, hail or graupel. The aim of the study is to understand and describe the cause of hailstorm event during over NCR with comparative analysis of the two options of GCE microphysics. On evaluating the model simulations, it is observed that hail option shows similar precipitation intensity with TRMM observation than the graupel option and is able to simulate hail precipitation. Using the model simulated output with hail option; detailed investigation on understanding the dynamics of hailstorm is performed. The analysis based on numerical simulation suggests that the deep instability in the atmospheric column led to the formation of hailstones as the cloud formation reached upto the glaciated zone promoting ice nucleation. In winters, such instability conditions rarely form due to low level available potential energy and moisture incursion along with upper level baroclinic instability due to the presence of WD. Such rare positioning is found to be lowering the tropopause with increased temperature gradient, leading to winter hailstorm formation.

  11. Numerical simulation of a rare winter hailstorm event over Delhi, India on 17 January 2013

    KAUST Repository

    Chevuturi, A.

    2014-12-19

    This study analyzes the cause of the rare occurrence of a winter hailstorm over New Delhi/NCR (National Capital Region), India. The absence of increased surface temperature or low level of moisture incursion during winter cannot generate the deep convection required for sustaining a hailstorm. Consequently, NCR shows very few cases of hailstorms in the months of December-January-February, making the winter hail formation a question of interest. For this study, a recent winter hailstorm event on 17 January 2013 (16:00–18:00 UTC) occurring over NCR is investigated. The storm is simulated using the Weather Research and Forecasting (WRF) model with the Goddard Cumulus Ensemble (GCE) microphysics scheme with two different options: hail and graupel. The aim of the study is to understand and describe the cause of hailstorm event during over NCR with a comparative analysis of the two options of GCE microphysics. Upon evaluating the model simulations, it is observed that the hail option shows a more similar precipitation intensity with the Tropical Rainfall Measuring Mission (TRMM) observation than the graupel option does, and it is able to simulate hail precipitation. Using the model-simulated output with the hail option; detailed investigation on understanding the dynamics of hailstorm is performed. The analysis based on a numerical simulation suggests that the deep instability in the atmospheric column led to the formation of hailstones as the cloud formation reached up to the glaciated zone promoting ice nucleation. In winters, such instability conditions rarely form due to low level available potential energy and moisture incursion along with upper level baroclinic instability due to the presence of a western disturbance (WD). Such rare positioning is found to be lowering the tropopause with increased temperature gradient, leading to winter hailstorm formation.

  12. Evidence of social deprivation on the spatial patterns of excess winter mortality.

    Science.gov (United States)

    Almendra, Ricardo; Santana, Paula; Vasconcelos, João

    2017-11-01

    The aims of this study are to identify the patterns of excess winter mortality (due to diseases of the circulatory system) and to analyse the association between the excess winter deaths (EWD) and socio-economic deprivation in Portugal. The number of EWD in 2002-2011 was estimated by comparing the number of deaths in winter months with the average number in non-winter months. The EWD ratio of each municipality was calculated by following the indirect standardization method and then compared with two deprivation indexes (socio-material and housing deprivation index) through ecological regression models. This study found that: (1) the EWD ratio showed considerable asymmetry in its geography; (2) there are significant positive associations between the EWD ratio and both deprivation indexes; and (3) at the higher level of deprivation, housing conditions have a stronger association with EWD than socio-material conditions. The significant association between two deprivation dimensions (socio-material and housing deprivation) and EWDs suggests that EWD geographical pattern is influenced by deprivation.

  13. Long-term variability in Northern Hemisphere snow cover and associations with warmer winters

    Science.gov (United States)

    McCabe, Gregory J.; Wolock, David M.

    2010-01-01

    A monthly snow accumulation and melt model is used with gridded monthly temperature and precipitation data for the Northern Hemisphere to generate time series of March snow-covered area (SCA) for the period 1905 through 2002. The time series of estimated SCA for March is verified by comparison with previously published time series of SCA for the Northern Hemisphere. The time series of estimated Northern Hemisphere March SCA shows a substantial decrease since about 1970, and this decrease corresponds to an increase in mean winter Northern Hemisphere temperature. The increase in winter temperature has caused a decrease in the fraction of precipitation that occurs as snow and an increase in snowmelt for some parts of the Northern Hemisphere, particularly the mid-latitudes, thus reducing snow packs and March SCA. In addition, the increase in winter temperature and the decreases in SCA appear to be associated with a contraction of the circumpolar vortex and a poleward movement of storm tracks, resulting in decreased precipitation (and snow) in the low- to mid-latitudes and an increase in precipitation (and snow) in high latitudes. If Northern Hemisphere winter temperatures continue to warm as they have since the 1970s, then March SCA will likely continue to decrease.

  14. Mimicking emotions: how 3-12-month-old infants use the facial expressions and eyes of a model.

    Science.gov (United States)

    Soussignan, Robert; Dollion, Nicolas; Schaal, Benoist; Durand, Karine; Reissland, Nadja; Baudouin, Jean-Yves

    2018-06-01

    While there is an extensive literature on the tendency to mimic emotional expressions in adults, it is unclear how this skill emerges and develops over time. Specifically, it is unclear whether infants mimic discrete emotion-related facial actions, whether their facial displays are moderated by contextual cues and whether infants' emotional mimicry is constrained by developmental changes in the ability to discriminate emotions. We therefore investigate these questions using Baby-FACS to code infants' facial displays and eye-movement tracking to examine infants' looking times at facial expressions. Three-, 7-, and 12-month-old participants were exposed to dynamic facial expressions (joy, anger, fear, disgust, sadness) of a virtual model which either looked at the infant or had an averted gaze. Infants did not match emotion-specific facial actions shown by the model, but they produced valence-congruent facial responses to the distinct expressions. Furthermore, only the 7- and 12-month-olds displayed negative responses to the model's negative expressions and they looked more at areas of the face recruiting facial actions involved in specific expressions. Our results suggest that valence-congruent expressions emerge in infancy during a period where the decoding of facial expressions becomes increasingly sensitive to the social signal value of emotions.

  15. High-frequency and meso-scale winter sea-ice variability in the Southern Ocean in a high-resolution global ocean model

    Science.gov (United States)

    Stössel, Achim; von Storch, Jin-Song; Notz, Dirk; Haak, Helmuth; Gerdes, Rüdiger

    2018-03-01

    This study is on high-frequency temporal variability (HFV) and meso-scale spatial variability (MSV) of winter sea-ice drift in the Southern Ocean simulated with a global high-resolution (0.1°) sea ice-ocean model. Hourly model output is used to distinguish MSV characteristics via patterns of mean kinetic energy (MKE) and turbulent kinetic energy (TKE) of ice drift, surface currents, and wind stress, and HFV characteristics via time series of raw variables and correlations. We find that (1) along the ice edge, the MSV of ice drift coincides with that of surface currents, in particular such due to ocean eddies; (2) along the coast, the MKE of ice drift is substantially larger than its TKE and coincides with the MKE of wind stress; (3) in the interior of the ice pack, the TKE of ice drift is larger than its MKE, mostly following the TKE pattern of wind stress; (4) the HFV of ice drift is dominated by weather events, and, in the absence of tidal currents, locally and to a much smaller degree by inertial oscillations; (5) along the ice edge, the curl of the ice drift is highly correlated with that of surface currents, mostly reflecting the impact of ocean eddies. Where ocean eddies occur and the ice is relatively thin, ice velocity is characterized by enhanced relative vorticity, largely matching that of surface currents. Along the ice edge, ocean eddies produce distinct ice filaments, the realism of which is largely confirmed by high-resolution satellite passive-microwave data.

  16. Modeling the monthly mean soil-water balance with a statistical-dynamical ecohydrology model as coupled to a two-component canopy model

    Directory of Open Access Journals (Sweden)

    J. P. Kochendorfer

    2010-10-01

    Full Text Available The statistical-dynamical annual water balance model of Eagleson (1978 is a pioneering work in the analysis of climate, soil and vegetation interactions. This paper describes several enhancements and modifications to the model that improve its physical realism at the expense of its mathematical elegance and analytical tractability. In particular, the analytical solutions for the root zone fluxes are re-derived using separate potential rates of transpiration and bare-soil evaporation. Those potential rates, along with the rate of evaporation from canopy interception, are calculated using the two-component Shuttleworth-Wallace (1985 canopy model. In addition, the soil column is divided into two layers, with the upper layer representing the dynamic root zone. The resulting ability to account for changes in root-zone water storage allows for implementation at the monthly timescale. This new version of the Eagleson model is coined the Statistical-Dynamical Ecohydrology Model (SDEM. The ability of the SDEM to capture the seasonal dynamics of the local-scale soil-water balance is demonstrated for two grassland sites in the US Great Plains. Sensitivity of the results to variations in peak green leaf area index (LAI suggests that the mean peak green LAI is determined by some minimum in root zone soil moisture during the growing season. That minimum appears to be close to the soil matric potential at which the dominant grass species begins to experience water stress and well above the wilting point, thereby suggesting an ecological optimality hypothesis in which the need to avoid water-stress-induced leaf abscission is balanced by the maximization of carbon assimilation (and associated transpiration. Finally, analysis of the sensitivity of model-determined peak green LAI to soil texture shows that the coupled model is able to reproduce the so-called "inverse texture effect", which consists of the observation that natural vegetation in dry climates tends

  17. Evaluation of three energy balance-based evaporation models for estimating monthly evaporation for five lakes using derived heat storage changes from a hysteresis model

    NARCIS (Netherlands)

    Duan, Z.; Bastiaanssen, W.G.M.

    2017-01-01

    The heat storage changes (Qt) can be a significant component of the energy balance in lakes, and it is important to account for Qt for reasonable estimation of evaporation at monthly and finer timescales if the energy balance-based evaporation models are used. However, Qt has been often neglected in

  18. Attribution of UK Winter Floods to Anthropogenic Forcing

    Science.gov (United States)

    Schaller, N.; Alison, K.; Sparrow, S. N.; Otto, F. E. L.; Massey, N.; Vautard, R.; Yiou, P.; van Oldenborgh, G. J.; van Haren, R.; Lamb, R.; Huntingford, C.; Crooks, S.; Legg, T.; Weisheimer, A.; Bowery, A.; Miller, J.; Jones, R.; Stott, P.; Allen, M. R.

    2014-12-01

    Many regions of southern UK experienced severe flooding during the 2013/2014 winter. Simultaneously, large areas in the USA and Canada were struck by prolonged cold weather. At the time, the media and public asked whether the general rainy conditions over northern Europe and the cold weather over North America were caused by climate change. Providing an answer to this question is not trivial, but recent studies show that probabilistic event attribution is feasible. Using the citizen science project weather@home, we ran over 40'000 perturbed initial condition simulations of the 2013/2014 winter. These simulations fall into two categories: one set aims at simulating the world with climate change using observed sea surface temperatures while the second set is run with sea surface temperatures corresponding to a world that might have been without climate change. The relevant modelled variables are then downscaled by a hydrological model to obtain river flows. First results show that anthropogenic climate change led to a small but significant increase in the fractional attributable risk for 30-days peak flows for the river Thames. A single number can summarize the final result from probabilistic attribution studies indicating, for example, an increase, decrease or no change to the risk of the event occurring. However, communicating this to the public, media and other scientists remains challenging. The assumptions made in the chain of models used need to be explained. In addition, extreme events, like the UK floods of the 2013/2014 winter, are usually caused by a range of factors. While heavy precipitation events can be caused by dynamic and/or thermodynamic processes, floods occur only partly as a response to heavy precipitation. Depending on the catchment, they can be largely due to soil properties and conditions of the previous months. Probabilistic attribution studies are multidisciplinary and therefore all aspects need to be communicated properly.

  19. Impact of warm winters on microbial growth

    Science.gov (United States)

    Birgander, Johanna; Rousk, Johannes; Axel Olsson, Pål

    2014-05-01

    Growth of soil bacteria has an asymmetrical response to higher temperature with a gradual increase with increasing temperatures until an optimum after which a steep decline occurs. In laboratory studies it has been shown that by exposing a soil bacterial community to a temperature above the community's optimum temperature for two months, the bacterial community grows warm-adapted, and the optimum temperature of bacterial growth shifts towards higher temperatures. This result suggests a change in the intrinsic temperature dependence of bacterial growth, as temperature influenced the bacterial growth even though all other factors were kept constant. An intrinsic temperature dependence could be explained by either a change in the bacterial community composition, exchanging less tolerant bacteria towards more tolerant ones, or it could be due to adaptation within the bacteria present. No matter what the shift in temperature tolerance is due to, the shift could have ecosystem scale implications, as winters in northern Europe are getting warmer. To address the question of how microbes and plants are affected by warmer winters, a winter-warming experiment was established in a South Swedish grassland. Results suggest a positive response in microbial growth rate in plots where winter soil temperatures were around 6 °C above ambient. Both bacterial and fungal growth (leucine incorporation, and acetate into ergosterol incorporation, respectively) appeared stimulated, and there are two candidate explanations for these results. Either (i) warming directly influence microbial communities by modulating their temperature adaptation, or (ii) warming indirectly affected the microbial communities via temperature induced changes in bacterial growth conditions. The first explanation is in accordance with what has been shown in laboratory conditions (explained above), where the differences in the intrinsic temperature relationships were examined. To test this explanation the

  20. Diagnostic model of 3-D circulation in the Arabian Sea and western equatorial Indian Ocean: Results of monthly mean sea surface topography

    Digital Repository Service at National Institute of Oceanography (India)

    Bahulayan, N.; Shaji, C.

    A three-dimensional diagnostic model has been developed to compute the monthly mean circulation and sea surface topography in the Western Tropical Indian Ocean north of 20 degrees S and west of 80 degrees E. The diagnostic model equations...

  1. Winter Frost and Fog

    Science.gov (United States)

    2005-01-01

    This somewhat oblique blue wide angle Mars Global Surveyor (MGS) Mars Orbiter Camera (MOC) image shows the 174 km (108 mi) diameter crater, Terby, and its vicinity in December 2004. Located north of Hellas, this region can be covered with seasonal frost and ground-hugging fog, even in the afternoon, despite being north of 30oS. The subtle, wavy pattern is a manifestation of fog. Location near: 28oS, 286oW Illumination from: upper left Season: Southern Winter

  2. Rule Optimization monthly reservoir operation Salvajina

    International Nuclear Information System (INIS)

    Sandoval Garcia, Maria Clemencia; Santacruz Salazar, Santiago; Ramirez Callejas, Carlos A

    2007-01-01

    In the present study a model was designed for the optimization of the rule for monthly operation of the Salvajina dam (Colombia) based in the technology) of dynamic programming. The model maximizes the benefits for electric power generation, ensuring at the same time flood regulation in winter and pollution relief during the summer. For the optimization of the rule of operation, it was necessary to define the levels and volumes of reserve and holding required for the control of flood zones in the Cauca river and to provide an effluent minimal flow and assure a daily flow at the Juanchito station (located 141 km downstream from the dam) of the Cauca river, 90 % of the time during the most critical summer periods.

  3. A binary genetic programing model for teleconnection identification between global sea surface temperature and local maximum monthly rainfall events

    Science.gov (United States)

    Danandeh Mehr, Ali; Nourani, Vahid; Hrnjica, Bahrudin; Molajou, Amir

    2017-12-01

    The effectiveness of genetic programming (GP) for solving regression problems in hydrology has been recognized in recent studies. However, its capability to solve classification problems has not been sufficiently explored so far. This study develops and applies a novel classification-forecasting model, namely Binary GP (BGP), for teleconnection studies between sea surface temperature (SST) variations and maximum monthly rainfall (MMR) events. The BGP integrates certain types of data pre-processing and post-processing methods with conventional GP engine to enhance its ability to solve both regression and classification problems simultaneously. The model was trained and tested using SST series of Black Sea, Mediterranean Sea, and Red Sea as potential predictors as well as classified MMR events at two locations in Iran as predictand. Skill of the model was measured in regard to different rainfall thresholds and SST lags and compared to that of the hybrid decision tree-association rule (DTAR) model available in the literature. The results indicated that the proposed model can identify potential teleconnection signals of surrounding seas beneficial to long-term forecasting of the occurrence of the classified MMR events.

  4. Modelling winter organic aerosol at the European scale with CAMx: evaluation and source apportionment with a VBS parameterization based on novel wood burning smog chamber experiments

    Science.gov (United States)

    Ciarelli, Giancarlo; Aksoyoglu, Sebnem; El Haddad, Imad; Bruns, Emily A.; Crippa, Monica; Poulain, Laurent; Äijälä, Mikko; Carbone, Samara; Freney, Evelyn; O'Dowd, Colin; Baltensperger, Urs; Prévôt, André S. H.

    2017-06-01

    We evaluated a modified VBS (volatility basis set) scheme to treat biomass-burning-like organic aerosol (BBOA) implemented in CAMx (Comprehensive Air Quality Model with extensions). The updated scheme was parameterized with novel wood combustion smog chamber experiments using a hybrid VBS framework which accounts for a mixture of wood burning organic aerosol precursors and their further functionalization and fragmentation in the atmosphere. The new scheme was evaluated for one of the winter EMEP intensive campaigns (February-March 2009) against aerosol mass spectrometer (AMS) measurements performed at 11 sites in Europe. We found a considerable improvement for the modelled organic aerosol (OA) mass compared to our previous model application with the mean fractional bias (MFB) reduced from -61 to -29 %. We performed model-based source apportionment studies and compared results against positive matrix factorization (PMF) analysis performed on OA AMS data. Both model and observations suggest that OA was mainly of secondary origin at almost all sites. Modelled secondary organic aerosol (SOA) contributions to total OA varied from 32 to 88 % (with an average contribution of 62 %) and absolute concentrations were generally under-predicted. Modelled primary hydrocarbon-like organic aerosol (HOA) and primary biomass-burning-like aerosol (BBPOA) fractions contributed to a lesser extent (HOA from 3 to 30 %, and BBPOA from 1 to 39 %) with average contributions of 13 and 25 %, respectively. Modelled BBPOA fractions were found to represent 12 to 64 % of the total residential-heating-related OA, with increasing contributions at stations located in the northern part of the domain. Source apportionment studies were performed to assess the contribution of residential and non-residential combustion precursors to the total SOA. Non-residential combustion and road transportation sector contributed about 30-40 % to SOA formation (with increasing contributions at urban and near

  5. Application of TRMM PR and TMI Measurements to Assess Cloud Microphysical Schemes in the MM5 Model for a Winter Storm

    Science.gov (United States)

    Han, Mei; Braun, Scott A.; Olson, William S.; Persson, P. Ola G.; Bao, Jian-Wen

    2009-01-01

    . This study employs this method to evaluate the accuracy of the simulated radiative properties by the MM5 model with different microphysical schemes. It is found that the representations of particle density, size, and mass in the different schemes in the MM5 model determine the model s performance when predicting a winter storm over the eastern Pacific Ocean. Schemes lacking moderate density particles (i.e. graupel), with snow flakes that are too large, or with excessive mass of snow or graupel lead to degraded prediction of the radiative properties as observed by the TRMM satellite. This study demonstrates the uniqueness of the combination of both an active microwave sensor (PR) and passive microwave sensor (TMI) onboard TRMM on assessing the accuracy of numerical weather forecasting. It improves our understanding of the physical and radiative properties of different types of precipitation particles and provides suggestions for better representation of cloud and precipitation processes in numerical models. It would, ultimately, contribute to answering questions like "Why did it not rain when the forecast says it would?"

  6. Mortality impact of extreme winter temperatures

    Science.gov (United States)

    Díaz, Julio; García, Ricardo; López, César; Linares, Cristina; Tobías, Aurelio; Prieto, Luis

    2005-01-01

    During the last few years great attention has been paid to the evaluation of the impact of extreme temperatures on human health. This paper examines the effect of extreme winter temperature on mortality in Madrid for people older than 65, using ARIMA and GAM models. Data correspond to 1,815 winter days over the period 1986 1997, during which time a total of 133,000 deaths occurred. The daily maximum temperature (Tmax) was shown to be the best thermal indicator of the impact of climate on mortality. When total mortality was considered, the maximum impact occured 7 8 days after a temperature extreme; for circulatory diseases the lag was between 7 and 14 days. When respiratory causes were considered, two mortality peaks were evident at 4 5 and 11 days. When the impact of winter extreme temperatures was compared with that associated with summer extremes, it was found to occur over a longer term, and appeared to be more indirect.

  7. Decontamination and winter conditions

    International Nuclear Information System (INIS)

    Quenild, C.; Tveten, U.

    1984-12-01

    The report deals with two decontamonation experiments under winter conditions. A snow-covered parking lot was contaminated, and the snow was subsequently removed using standard snow-moving equipment. The snow left behind was collected and the content of contaminant was determined. A non-radioactive contaminant was used. A decontamination factor exceeding 100 was obtained. Although the eksperimental conditions were close to ideal, it is reason to believe that extremely efficient removal of deposited materials on a snow surface is achivable. In another investigation, run-off from agricultural surface, contaminated while covered with snow, was measured A lycimeter was used in this experiment. A stable layer of ice and snow was allowed to form before contamination. The run-off water was collected at each thaw period until all snow and ice was gone. Cs-134 was used as contaminant. Roughly 30% of the Cs-134 with which the area was contaminated ran off with the melt water. Following a reactor accident situation, this would have given a corresponding reduction in the long term doses. Both of these experiments show that consequence calculation assumptions, as they are currently applied to large accident assessment, tend to overestimate the consequences resulting from accidents taking place under winter conditions

  8. Spirit's Winter Work Site

    Science.gov (United States)

    2006-01-01

    [figure removed for brevity, see original site] Annotated Version This portion of an image acquired by the Mars Reconnaissance Orbiter's High Resolution Imaging Science Experiment camera shows the Spirit rover's winter campaign site. Spirit was parked on a slope tilted 11 degrees to the north to maximize sunlight during the southern winter season. 'Tyrone' is an area where the rover's wheels disturbed light-toned soils. Remote sensing and in-situ analyses found the light-toned soil at Tyrone to be sulfate rich and hydrated. The original picture is catalogued as PSP_001513_1655_red and was taken on Sept. 29, 2006. NASA's Jet Propulsion Laboratory, a division of the California Institute of Technology in Pasadena, manages the Mars Reconnaissance Orbiter for NASA's Science Mission Directorate, Washington. Lockheed Martin Space Systems, Denver, is the prime contractor for the project and built the spacecraft. The High Resolution Imaging Science Experiment is operated by the University of Arizona, Tucson, and the instrument was built by Ball Aerospace and Technology Corp., Boulder, Colo.

  9. Winter School Les Houches

    CERN Document Server

    Lannoo, Michel; Bastard, Gérald; Voos, Michel; Boccara, Nino

    1986-01-01

    The Winter School held in Les Houches on March 12-21, 1985 was devoted to Semiconductor Heterojunctions and Superlattices, a topic which is recognized as being now one of the most interesting and active fields in semiconductor physics. In fact, following the pioneering work of Esaki and Tsu in 1970, the study of these two-dimensional semiconductor heterostructures has developed rapidly, both from the point of view of basic physics and of applications. For instance, modulation-doped heterojunctions are nowadays currently used to investigate the quantum Hall effect and to make very fast transistors. This book contains the lectures presented at this Winter School, showing in particular that many aspects of semiconductor heterojunctions and super­ lattices were treated, extending from the fabrication of these two-dimensional systems to their basic properties and applications in micro-and opto-electron­ ics. Among the subjects which were covered, one can quote as examples: molecular beam epitaxy and metallorgani...

  10. Assessing climate change impacts on winter cover crop nitrate uptake efficiency on the coastal plain of the Chesapeake Bay watershed using the SWAT model

    Science.gov (United States)

    Climate change is expected to exacerbate water quality degradation in the Chesapeake Bay watershed (CBW). Winter cover crops (WCCs) have been widely implemented in this region owing to their high effectiveness at reducing nitrate loads. However, little is known about climate change impacts on the ef...

  11. Assessing the impacts of future climate conditions on the effectiveness of winter cover crops in reducing nitrate loads into the Chesapeake Bay Watersheds using SWAT model

    Science.gov (United States)

    Winter cover crops (WCCs) have been widely implemented in the Coastal Plain of the Chesapeake Bay watershed (CBW) due to their high effectiveness at reducing nitrate loads. However, future climate conditions (FCCs) are expected to exacerbate water quality degradation in the CBW by increasing nitrat...

  12. Increased body mass of ducks wintering in California's Central Valley

    Science.gov (United States)

    Fleskes, Joseph P.; Yee, Julie L.; Yarris, Gregory S.; Loughman, Daniel L.

    2016-01-01

    Waterfowl managers lack the information needed to fully evaluate the biological effects of their habitat conservation programs. We studied body condition of dabbling ducks shot by hunters at public hunting areas throughout the Central Valley of California during 2006–2008 compared with condition of ducks from 1979 to 1993. These time periods coincide with habitat increases due to Central Valley Joint Venture conservation programs and changing agricultural practices; we modeled to ascertain whether body condition differed among waterfowl during these periods. Three dataset comparisons indicate that dabbling duck body mass was greater in 2006–2008 than earlier years and the increase was greater in the Sacramento Valley and Suisun Marsh than in the San Joaquin Valley, differed among species (mallard [Anas platyrhynchos], northern pintail [Anas acuta], America wigeon [Anas americana], green-winged teal [Anas crecca], and northern shoveler [Anas clypeata]), and was greater in ducks harvested late in the season. Change in body mass also varied by age–sex cohort and month for all 5 species and by September–January rainfall for all except green-winged teal. The random effect of year nested in period, and sometimes interacting with other factors, improved models in many cases. Results indicate that improved habitat conditions in the Central Valley have resulted in increased winter body mass of dabbling ducks, especially those that feed primarily on seeds, and this increase was greater in regions where area of post-harvest flooding of rice and other crops, and wetland area, has increased. Conservation programs that continue to promote post-harvest flooding and other agricultural practices that benefit wintering waterfowl and continue to restore and conserve wetlands would likely help maintain body condition of wintering dabbling ducks in the Central Valley of California.

  13. A Method for the Monthly Electricity Demand Forecasting in Colombia based on Wavelet Analysis and a Nonlinear Autoregressive Model

    Directory of Open Access Journals (Sweden)

    Cristhian Moreno-Chaparro

    2011-12-01

    Full Text Available This paper proposes a monthly electricity forecast method for the National Interconnected System (SIN of Colombia. The method preprocesses the time series using a Multiresolution Analysis (MRA with Discrete Wavelet Transform (DWT; a study for the selection of the mother wavelet and her order, as well as the level decomposition was carried out. Given that original series follows a non-linear behaviour, a neural nonlinear autoregressive (NAR model was used. The prediction was obtained by adding the forecast trend with the estimated obtained by the residual series combined with further components extracted from preprocessing. A bibliographic review of studies conducted internationally and in Colombia is included, in addition to references to investigations made with wavelet transform applied to electric energy prediction and studies reporting the use of NAR in prediction.

  14. Exploiting the atmosphere's memory for monthly, seasonal and interannual temperature forecasting using Scaling LInear Macroweather Model (SLIMM)

    Science.gov (United States)

    Del Rio Amador, Lenin; Lovejoy, Shaun

    2016-04-01

    . The corresponding space-time model (the ScaLIng Macroweather Model (SLIMM) is thus only multifractal in space where the spatial intermittency is associated with different climate zones. SLIMM exploits the power law (scaling) behavior in time of the temperature field and uses the long historical memory of the temperature series to improve the skill. The only model parameter is the fluctuation scaling exponent, H (usually in the range -0.5 - 0), which is directly related to the skill and can be obtained from the data. The results predicted analytically by the model have been tested by performing actual hindcasts in different 5° x 5° regions covering the planet using ERA-Interim, 20CRv2 and NCEP/NCAR reanalysis as reference datasets. We report maps of theoretical skill predicted by the model and we compare it with actual skill based on hindcasts for monthly, seasonal and annual resolutions. We also present maps of calibrated probability hindcasts with their respective validations. Comparisons between our results using SLIMM, some other stochastic autoregressive model, and hindcasts from the Canadian Seasonal to Interannual Prediction System (CanSIPS) and the National Centers for Environmental Prediction (NCEP)'s model CFSv2, are also shown. For seasonal temperature forecasts, SLIMM outperforms the GCM based forecasts in over 90% of the earth's surface. SLIMM forecasts can be accessed online through the site: http://www.to_be_announced.mcgill.ca.

  15. Winter fuels report

    International Nuclear Information System (INIS)

    1995-01-01

    The Winter Fuels Report is intended to provide concise, timely information to the industry, the press, policymakers, consumers, analysts, and State and local governments on the following topics: distillate fuel oil net production, imports and stocks on a US level and for all Petroleum Administration for Defense Districts (PADD) and product supplied on a US level; propane net production, imports and stocks on a US level and for PADD's I, II, and III; natural gas supply and disposition and underground storage for the US and consumption for all PADD's, as well as selected National average prices; residential and wholesale pricing data for heating oil and propane for those States participating in the joint Energy Information Administration (EIA)/State Heating Oil and Propane Program; crude oil and petroleum price comparisons for the US and selected cities; and a 6-10 day, 30-Day, and 90-Day outlook for temperature and precipitation and US total heating degree-days by city

  16. Winter fuels report

    Energy Technology Data Exchange (ETDEWEB)

    1990-11-29

    The Winter Fuels Report is intended to provide concise, timely information to the industry, the press, policymakers, consumers, analysts, and state and local governments on the following topics: distillate fuel oil net production, imports and stocks for all PADD's and product supplied on a US level; propane net product supplied on a US level; propane net production, imports and stocks for Petroleum Administration for Defense Districts (PADD) I, II, and III; natural gas supply and disposition and underground storage for the United States and consumption for all PADD's; residential and wholesale pricing data for propane and heating oil for those states participating in the joint Energy Information Administration (EIA)/State Heating Oil and Propane Program; crude oil and petroleum price comparisons for the United States and selected cities; and US total heating degree-days by city. 27 figs, 12 tabs.

  17. Comparative study of holt-winters triples exponential smoothing and seasonal Arima: Forecasting short term seasonal car sales in South Africa

    Directory of Open Access Journals (Sweden)

    Katleho Daniel Makatjane

    2016-02-01

    Full Text Available In this paper, both Seasonal ARIMA and Holt-Winters models are developed to predict the monthly car sales in South Africa using data for the period of January 1994 to December 2013. The purpose of this study is to choose an optimal model suited for the sector. The three error metrics; mean absolute error, mean absolute percentage error and root mean square error were used in making such a choice. Upon realizing that the three forecast errors could not provide concrete basis to make conclusion, the power test was calculated for each model proving Holt-Winters to having about 0.3% more predictive power. Empirical results also indicate that Holt-Winters model produced more precise short-term seasonal forecasts. The findings also revealed a structural break in April 2009, implying that the car industry was significantly affected by the 2008 and 2009 US financial crisis

  18. Validation of AquaCrop Model for Simulation of Winter Wheat Yield and Water Use Efficiency under Simultaneous Salinity and Water Stress

    Directory of Open Access Journals (Sweden)

    M. Mohammadi

    2016-02-01

    simulation of soil salinity. In general, the model accuracy for simulation yield and WP was better than simulation of biomass. The d (index of agreement values were very close to one for both varieties, which means that simulated reduction in grain yield and biomass was similar to those of measured ones. In most cases the R2 values were about one, confirming a good correlation between simulated and measured values. The NRMSE values in most cases were lower than 10% which seems to be good. The CRM values were close to zero (under- and over-estimation were negligible. Based on higher WP under deficit irrigation treatments (e.g. I3 compared to full irrigation treatments (e.g. I1 and I2, it seems logical to adopt I3 treatment, especially in Birjand as a water-short region, assigning the remaining 25% to another piece of land. By such strategy, WP would be optimized at the regional scale. Conclusion: The AquaCrop was separately and simultaneously nested calibrated and validated for all salinity treatments. The model accuracy under simultaneous case was slightly lower than that for separate case. According to the results, if the model is well calibrated for minimum and maximum irrigation treatments (full irrigation and maximum deficit irrigation, it could simulate grain yield for any other irrigation treatment in between these two limits. Adopting this approach may reduce the cost of field studies for calibrating the model, since only two irrigation treatments should be conducted in the field. AquaCrop model can be a valuable tool for modelling winter wheat grain yield, WP and biomass. The simplicity of AquaCrop, as it is less data dependent, made it to be user-friendly. Nevertheless, the performance of the model has to be evaluated, validated and fine-tuned under a wider range of conditions and crops. Keywords: Biomass, Plant modeling, Sensitivity analysis

  19. Nuclear winter or nuclear fall?

    Science.gov (United States)

    Berger, André

    Climate is universal. If a major modern nuclear war (i.e., with a large number of small-yield weapons) were to happen, it is not even necessary to have a specific part of the world directly involved for there to be cause to worry about the consequences for its inhabitants and their future. Indeed, smoke from fires ignited by the nuclear explosions would be transported by winds all over the world, causing dark and cold. According to the first study, by Turco et al. [1983], air surface temperature over continental areas of the northern mid-latitudes (assumed to be the nuclear war theatre) would fall to winter levels even in summer (hence the term “nuclear winter”) and induce drastic climatic conditions for several months at least. The devastating effects of a nuclear war would thus last much longer than was assumed initially. Discussing to what extent these estimations of long-term impacts on climate are reliable is the purpose of this article.

  20. The ScaLIng Macroweather Model (SLIMM): using scaling to forecast global-scale macroweather from months to decades

    Science.gov (United States)

    Lovejoy, S.; del Rio Amador, L.; Hébert, R.

    2015-09-01

    On scales of ≈ 10 days (the lifetime of planetary-scale structures), there is a drastic transition from high-frequency weather to low-frequency macroweather. This scale is close to the predictability limits of deterministic atmospheric models; thus, in GCM (general circulation model) macroweather forecasts, the weather is a high-frequency noise. However, neither the GCM noise nor the GCM climate is fully realistic. In this paper we show how simple stochastic models can be developed that use empirical data to force the statistics and climate to be realistic so that even a two-parameter model can perform as well as GCMs for annual global temperature forecasts. The key is to exploit the scaling of the dynamics and the large stochastic memories that we quantify. Since macroweather temporal (but not spatial) intermittency is low, we propose using the simplest model based on fractional Gaussian noise (fGn): the ScaLIng Macroweather Model (SLIMM). SLIMM is based on a stochastic ordinary differential equation, differing from usual linear stochastic models (such as the linear inverse modelling - LIM) in that it is of fractional rather than integer order. Whereas LIM implicitly assumes that there is no low-frequency memory, SLIMM has a huge memory that can be exploited. Although the basic mathematical forecast problem for fGn has been solved, we approach the problem in an original manner, notably using the method of innovations to obtain simpler results on forecast skill and on the size of the effective system memory. A key to successful stochastic forecasts of natural macroweather variability is to first remove the low-frequency anthropogenic component. A previous attempt to use fGn for forecasts had disappointing results because this was not done. We validate our theory using hindcasts of global and Northern Hemisphere temperatures at monthly and annual resolutions. Several nondimensional measures of forecast skill - with no adjustable parameters - show excellent

  1. The Scaling LInear Macroweather model (SLIM): using scaling to forecast global scale macroweather from months to decades

    Science.gov (United States)

    Lovejoy, S.; del Rio Amador, L.; Hébert, R.

    2015-03-01

    At scales of ≈ 10 days (the lifetime of planetary scale structures), there is a drastic transition from high frequency weather to low frequency macroweather. This scale is close to the predictability limits of deterministic atmospheric models; so that in GCM macroweather forecasts, the weather is a high frequency noise. But neither the GCM noise nor the GCM climate is fully realistic. In this paper we show how simple stochastic models can be developped that use empirical data to force the statistics and climate to be realistic so that even a two parameter model can outperform GCM's for annual global temperature forecasts. The key is to exploit the scaling of the dynamics and the enormous stochastic memories that it implies. Since macroweather intermittency is low, we propose using the simplest model based on fractional Gaussian noise (fGn): the Scaling LInear Macroweather model (SLIM). SLIM is based on a stochastic ordinary differential equations, differing from usual linear stochastic models (such as the Linear Inverse Modelling, LIM) in that it is of fractional rather than integer order. Whereas LIM implicitly assumes there is no low frequency memory, SLIM has a huge memory that can be exploited. Although the basic mathematical forecast problem for fGn has been solved, we approach the problem in an original manner notably using the method of innovations to obtain simpler results on forecast skill and on the size of the effective system memory. A key to successful forecasts of natural macroweather variability is to first remove the low frequency anthropogenic component. A previous attempt to use fGn for forecasts had poor results because this was not done. We validate our theory using hindcasts of global and Northern Hemisphere temperatures at monthly and annual resolutions. Several nondimensional measures of forecast skill - with no adjustable parameters - show excellent agreement with hindcasts and these show some skill even at decadal scales. We also compare

  2. Winter NH low-frequency variability in a hierarchy of low-order stochastic dynamical models of earth-atmosphere system

    Science.gov (United States)

    Zhao, Nan

    2018-02-01

    The origin of winter Northern Hemispheric low-frequency variability (hereafter, LFV) is regarded to be related to the coupled earth-atmosphere system characterized by the interaction of the jet stream with mid-latitude mountain ranges. On the other hand, observed LFV usually appears as transitions among multiple planetary-scale flow regimes of Northern Hemisphere like NAO + , AO +, AO - and NAO - . Moreover, the interaction between synoptic-scale eddies and the planetary-scale disturbance is also inevitable in the origin of LFV. These raise a question regarding how to incorporate all these aspects into just one framework to demonstrate (1) a planetary-scale dynamics of interaction of the jet stream with mid-latitude mountain ranges can really produce LFV, (2) such a dynamics can be responsible for the existence of above multiple flow regimes, and (3) the role of interaction with eddy is also clarified. For this purpose, a hierarchy of low-order stochastic dynamical models of the coupled earth-atmosphere system derived empirically from different timescale ranges of indices of Arctic Oscillation (AO), North Atlantic Oscillation (NAO), Pacific/North American (PNA), and length of day (LOD) and related probability density function (PDF) analysis are employed in this study. The results seem to suggest that the origin of LFV cannot be understood completely within the planetary-scale dynamics of the interaction of the jet stream with mid-latitude mountain ranges, because (1) the existence of multiple flow regimes such as NAO+, AO+, AO- and NAO- resulted from processes with timescales much longer than LFV itself, which may have underlying dynamics other than topography-jet stream interaction, and (2) we find LFV seems not necessarily to come directly from the planetary-scale dynamics of the interaction of the jet stream with mid-latitude mountain, although it can produce similar oscillatory behavior. The feedback/forcing of synoptic-scale eddies on the planetary

  3. Short-term forecasting of the chloride content in the mineral waters of the Ustroń Health Resort using SARIMA and Holt-Winters models

    Directory of Open Access Journals (Sweden)

    Dąbrowska Dominika

    2015-12-01

    Full Text Available The Ustroń S.A. Health Resort (southern Poland uses iodide-bromide mineral waters taken from Middle and Upper Devonian limestones and dolomites with a mineralisation range of 110-130 g/dm3 for curative purposes. Two boreholes - U-3 and U3-A drilled in the early 1970s were exploited. The aim of this paper is to estimate changes in mineral water quality of the Ustroń Health Resort by taking into consideration chloride content in the water from the U-3 borehole. The data has included the results of monthly analyses of chlorides from 2005 to 2015 during the tests carried out by the Mining Department of the Health Resort. The triple exponential smoothing (ETS function and the Seasonal Autoregressive Integrated Moving Average (SARIMA method of modelling time series were used for the calculations. The ability to properly forecast mineral water quality can result in a good status of the exploitation borehole and a limited number of failures in the exploitation system. Because of the good management of health resorts, it is possible to acquire more satisfied customers. The main goal of the article involves the real-time forecast accuracy, obtained results show that the proposed methods are effective for such situations. Presented methods made it possible to obtain a 24-month point and interval forecast. The results of these analyses indicate that the chloride content is forecast to be in the range of 72 to 83 g/l from 2015 to 2017. While comparing the two methods of analysis, a narrower range of forecast values and, therefore, greater accuracy were obtained for the ETS function. The good performance of the ETS model highlights its utility compared with complicated physically based numerical models.

  4. Statistical comparison of models for estimating the monthly average daily diffuse radiation at a subtropical African site

    International Nuclear Information System (INIS)

    Bashahu, M.

    2003-01-01

    Nine correlations have been developed in this paper to estimate the monthly average diffuse radiation for Dakar, Senegal. A 16-year period data on the global (H) and diffuse (H d ) radiation, together with data on the bright sunshine hours (N), the fraction of the sky's (Ne/8), the water vapour pressure in the air (e) and the ambient temperature (T) have been used for that purpose. A model inter-comparison based on the MBE, RMSE and t statistical tests has shown that estimates in any of the obtained correlations are not significantly different from their measured counterparts, thus all the nine models are recommended for the aforesaid location. Three of them should be particularly selected for their simplicity, universal applicability and high accuracy. Those are simple linear correlations between K d and N/N d , Ne/8 or K t . Even presenting adequate performance, the remaining correlations are either simple but less accurate, or multiple or nonlinear regressions needing one or two input variables. (author)

  5. Statistical comparison of models for estimating the monthly average daily diffuse radiation at a subtropical African site

    Energy Technology Data Exchange (ETDEWEB)

    Bashahu, M. [University of Burundi, Bujumbura (Burundi). Institute of Applied Pedagogy, Department of Physics and Technology

    2003-07-01

    Nine correlations have been developed in this paper to estimate the monthly average diffuse radiation for Dakar, Senegal. A 16-year period data on the global (H) and diffuse (H{sub d}) radiation, together with data on the bright sunshine hours (N), the fraction of the sky's (Ne/8), the water vapour pressure in the air (e) and the ambient temperature (T) have been used for that purpose. A model inter-comparison based on the MBE, RMSE and t statistical tests has shown that estimates in any of the obtained correlations are not significantly different from their measured counterparts, thus all the nine models are recommended for the aforesaid location. Three of them should be particularly selected for their simplicity, universal applicability and high accuracy. Those are simple linear correlations between K{sub d} and N/N{sub d}, Ne/8 or K{sub t}. Even presenting adequate performance, the remaining correlations are either simple but less accurate, or multiple or nonlinear regressions needing one or two input variables. (author)

  6. Establishment and verification of solar radiation calculation model of glass daylighting roof in hot summer and warm winter zone in China

    OpenAIRE

    Zheng, Caidan; Wu, Peihao; Costanzo, Vincenzo; Wang, Yuchen; Yang, Xiaokun

    2017-01-01

    In this paper, solar heat gain through glass daylighting roof is deeply studied by theoretical calculation method, taking Guangzhou in the Hot Summer and Warm Winter (HSWW) zone as an example. The direct solar radiation is calculated by Bouguer formula whereas the diffuse solar radiation is calculated by Berlage formula, representing the basis for the calculation method of the solar radiation intensity through the glass daylighting roof. Through the establishment of solar radiation calculatio...

  7. Regionalization of monthly rainfall erosivity patternsin Switzerland

    Science.gov (United States)

    Schmidt, Simon; Alewell, Christine; Panagos, Panos; Meusburger, Katrin

    2016-10-01

    One major controlling factor of water erosion is rainfall erosivity, which is quantified as the product of total storm energy and a maximum 30 min intensity (I30). Rainfall erosivity is often expressed as R-factor in soil erosion risk models like the Universal Soil Loss Equation (USLE) and its revised version (RUSLE). As rainfall erosivity is closely correlated with rainfall amount and intensity, the rainfall erosivity of Switzerland can be expected to have a regional characteristic and seasonal dynamic throughout the year. This intra-annual variability was mapped by a monthly modeling approach to assess simultaneously spatial and monthly patterns of rainfall erosivity. So far only national seasonal means and regional annual means exist for Switzerland. We used a network of 87 precipitation gauging stations with a 10 min temporal resolution to calculate long-term monthly mean R-factors. Stepwise generalized linear regression (GLM) and leave-one-out cross-validation (LOOCV) were used to select spatial covariates which explain the spatial and temporal patterns of the R-factor for each month across Switzerland. The monthly R-factor is mapped by summarizing the predicted R-factor of the regression equation and the corresponding residues of the regression, which are interpolated by ordinary kriging (regression-kriging). As spatial covariates, a variety of precipitation indicator data has been included such as snow depths, a combination product of hourly precipitation measurements and radar observations (CombiPrecip), daily Alpine precipitation (EURO4M-APGD), and monthly precipitation sums (RhiresM). Topographic parameters (elevation, slope) were also significant explanatory variables for single months. The comparison of the 12 monthly rainfall erosivity maps showed a distinct seasonality with the highest rainfall erosivity in summer (June, July, and August) influenced by intense rainfall events. Winter months have the lowest rainfall erosivity. A proportion of 62 % of

  8. Novel psychrotolerant picocyanobacteria isolated from Chesapeake Bay in the winter.

    Science.gov (United States)

    Xu, Yongle; Jiao, Nianzhi; Chen, Feng

    2015-08-01

    Picocyanobacteria are major primary producers in the ocean, especially in the tropical or subtropical oceans or during warm seasons. Many "warm" picocyanobacterial species have been isolated and characterized. However, picocyanobacteria in cold environments or cold seasons are much less studied. In general, little is known about the taxonomy and ecophysiology of picocyanobacteria living in the winter. In this study, 17 strains of picocyanobacteria were isolated from Chesapeake Bay, a temperate estuarine ecosystem, during the winter months. These winter isolates belong to five distinct phylogenetic lineages, and are distinct from the picocyanobacteria previously isolated from the warm seasons. The vast majority of the winter isolates were closely related to picocyanobacteria isolated from other cold environments like Arctic or subalpine waters. The winter picocyanobacterial isolates were able to maintain slow growth or prolonged dormancy at 4°C. Interestingly, the phycoerythrin-rich strains outperformed the phycocyanin-rich strains at cold temperature. In addition, winter picocyanobacteria changed their morphology when cultivated at 4°C. The close phylogenetic relationship between the winter picocyanobacteria and the picocyanobacteria living in high latitude cold regions indicates that low temperature locations select specific ecotypes of picocyanobacteria. © 2015 Phycological Society of America.

  9. Winter climate limits subantarctic low forest growth and establishment.

    Directory of Open Access Journals (Sweden)

    Melanie A Harsch

    Full Text Available Campbell Island, an isolated island 600 km south of New Zealand mainland (52 °S, 169 °E is oceanic (Conrad Index of Continentality  =  -5 with small differences between mean summer and winter temperatures. Previous work established the unexpected result that a mean annual climate warming of c. 0.6 °C since the 1940's has not led to upward movement of the forest limit. Here we explore the relative importance of summer and winter climatic conditions on growth and age-class structure of the treeline forming species, Dracophyllum longifolium and Dracophyllum scoparium over the second half of the 20th century. The relationship between climate and growth and establishment were evaluated using standard dendroecological methods and local climate data from a meteorological station on the island. Growth and establishment were correlated against climate variables and further evaluated within hierarchical regression models to take into account the effect of plot level variables. Winter climatic conditions exerted a greater effect on growth and establishment than summer climatic conditions. Establishment is maximized under warm (mean winter temperatures >7 °C, dry winters (total winter precipitation <400 mm. Growth, on the other hand, is adversely affected by wide winter temperature ranges and increased rainfall. The contrasting effect of winter warmth on growth and establishment suggests that winter temperature affects growth and establishment through differing mechanisms. We propose that milder winters enhance survival of seedlings and, therefore, recruitment, but increases metabolic stress on established plants, resulting in lower growth rates. Future winter warming may therefore have complex effects on plant growth and establishment globally.

  10. Winter Climate Limits Subantarctic Low Forest Growth and Establishment

    Science.gov (United States)

    Harsch, Melanie A.; McGlone, Matt S.; Wilmshurst, Janet M.

    2014-01-01

    Campbell Island, an isolated island 600 km south of New Zealand mainland (52°S, 169°E) is oceanic (Conrad Index of Continentality  = −5) with small differences between mean summer and winter temperatures. Previous work established the unexpected result that a mean annual climate warming of c. 0.6°C since the 1940's has not led to upward movement of the forest limit. Here we explore the relative importance of summer and winter climatic conditions on growth and age-class structure of the treeline forming species, Dracophyllum longifolium and Dracophyllum scoparium over the second half of the 20th century. The relationship between climate and growth and establishment were evaluated using standard dendroecological methods and local climate data from a meteorological station on the island. Growth and establishment were correlated against climate variables and further evaluated within hierarchical regression models to take into account the effect of plot level variables. Winter climatic conditions exerted a greater effect on growth and establishment than summer climatic conditions. Establishment is maximized under warm (mean winter temperatures >7 °C), dry winters (total winter precipitation <400 mm). Growth, on the other hand, is adversely affected by wide winter temperature ranges and increased rainfall. The contrasting effect of winter warmth on growth and establishment suggests that winter temperature affects growth and establishment through differing mechanisms. We propose that milder winters enhance survival of seedlings and, therefore, recruitment, but increases metabolic stress on established plants, resulting in lower growth rates. Future winter warming may therefore have complex effects on plant growth and establishment globally. PMID:24691026

  11. Winter climate limits subantarctic low forest growth and establishment.

    Science.gov (United States)

    Harsch, Melanie A; McGlone, Matt S; Wilmshurst, Janet M

    2014-01-01

    Campbell Island, an isolated island 600 km south of New Zealand mainland (52 °S, 169 °E) is oceanic (Conrad Index of Continentality  =  -5) with small differences between mean summer and winter temperatures. Previous work established the unexpected result that a mean annual climate warming of c. 0.6 °C since the 1940's has not led to upward movement of the forest limit. Here we explore the relative importance of summer and winter climatic conditions on growth and age-class structure of the treeline forming species, Dracophyllum longifolium and Dracophyllum scoparium over the second half of the 20th century. The relationship between climate and growth and establishment were evaluated using standard dendroecological methods and local climate data from a meteorological station on the island. Growth and establishment were correlated against climate variables and further evaluated within hierarchical regression models to take into account the effect of plot level variables. Winter climatic conditions exerted a greater effect on growth and establishment than summer climatic conditions. Establishment is maximized under warm (mean winter temperatures >7 °C), dry winters (total winter precipitation <400 mm). Growth, on the other hand, is adversely affected by wide winter temperature ranges and increased rainfall. The contrasting effect of winter warmth on growth and establishment suggests that winter temperature affects growth and establishment through differing mechanisms. We propose that milder winters enhance survival of seedlings and, therefore, recruitment, but increases metabolic stress on established plants, resulting in lower growth rates. Future winter warming may therefore have complex effects on plant growth and establishment globally.

  12. A WRF sensitivity study for summer ozone and winter PM events in California

    Science.gov (United States)

    Zhao, Z.; Chen, J.; Mahmud, A.; Di, P.; Avise, J.; DaMassa, J.; Kaduwela, A. P.

    2014-12-01

    Elevated summer ozone and winter PM frequently occur in the San Joaquin Valley (SJV) and the South Coast Air Basin (SCAB) in California. Meteorological conditions, such as wind, temperature and planetary boundary layer height (PBLH) play crucial roles in these air pollution events. Therefore, accurate representation of these fields from a meteorological model is necessary to successfully reproduce these air pollution events in subsequent air quality model simulations. California's complex terrain and land-sea interface can make it challenging for meteorological models to replicate the atmospheric conditions over the SJV and SCAB during extreme pollution events. In this study, the performance of the Weather Research and Forecasting Model (WRF) over these two regions for a summer month (July 2012) and a winter month (January 2013) is evaluated with different model configurations and forcing. Different land surface schemes (Pleim-Xiu vs. hybrid scheme), the application of observational and soil nudging, two SST datasets (the Global Ocean Data Assimilation Experiment (GODAE) SST vs. the default SST from North American Regional Reanalysis (NARR) reanalysis), and two land use datasets (the National Land Cover Data (NLCD) 2006 40-category vs. USGS 24-category land use data) have been tested. Model evaluation will focus on both surface and vertical profiles for wind, temperature, relative humidity, as well as PBLH. Sensitivity of the Community Multi-scale Air Quality Model (CMAQ) results to different WRF configurations will also be presented and discussed.

  13. Winter fuels report

    Energy Technology Data Exchange (ETDEWEB)

    1995-01-13

    The Winter Fuels Report is intended to provide concise, timely information to the industry, the press, policymakers, consumers, analysts, and State and local governments on the following topics: distillate fuel oil net production, imports and stocks on a US level and for all Petroleum Administration for Defense Districts (PADD) and product supplied on a US level; propane net production, imports and stocks on a US level and for PADD`s I, II, and III; natural gas supply and disposition and underground storage for the US and consumption for all PADD`s, as well as selected National average prices; residential and wholesale pricing data for heating oil and propane for those States participating in the joint Energy Information Administration (EIA)/State Heating Oil and Propane Program; crude oil and petroleum price comparisons for the US and selected cities; and a 6-10 day, 30-Day, and 90-Day outlook for temperature and precipitation and US total heating degree-days by city.

  14. Klaus Winter (1930 - 2015)

    CERN Multimedia

    2015-01-01

    We learned with great sadness that Klaus Winter passed away on 9 February 2015, after a long illness.   Klaus was born in 1930 in Hamburg, where he obtained his diploma in physics in 1955. From 1955 to 1958 he held a scholarship at the Collège de France, where he received his doctorate in nuclear physics under the guidance of Francis Perrin. Klaus joined CERN in 1958, where he first participated in experiments on π+ and K0 decay properties at the PS, and later became the spokesperson of the CHOV Collaboration at the ISR. Starting in 1976, his work focused on experiments with the SPS neutrino beam. In 1984 he joined Ugo Amaldi to head the CHARM experiment, designed for detailed studies of the neutral current interactions of high-energy neutrinos, which had been discovered in 1973 using the Gargamelle bubble chamber at the PS. The unique feature of the detector was its target calorimeter, which used large Carrara marble plates as an absorber material. From 1984 to 1991, Klau...

  15. Winter fuels report

    Energy Technology Data Exchange (ETDEWEB)

    1990-10-04

    The Winter Fuels Report is intended to provide concise, timely information to the industry, the press, policymakers, consumers, analysts, and state and local governments on the following topics: distillate fuel oil net production, imports and stocks for all PADD's and product supplied on a US level; propane net production, imports and stocks for Petroleum Administration for Defense Districts (PADD) I, II, and III; natural gas supply and disposition, underground storage, and consumption for all PADD's; residential and wholesale pricing data for propane and heating oil for those states participating in the joint Energy Information Administration (EIA)/State Heating Oil and Propane Program; crude oil price comparisons for the United States and selected cities; and US total heating degree-days by city. This report will be published weekly by the EIA starting the first week in October 1990 and will continue until the first week in April 1991. The data will also be available electronically after 5:00 p.m. on Thursday during the heating season through the EIA Electronic Publication System (EPUB). 12 tabs.

  16. Nuclear Winter: The implications for civil defense

    International Nuclear Information System (INIS)

    Chester, C.V.; Perry, A.M.; Hobbs, B.F.

    1987-01-01

    ''Nuclear Winter'' is the term given to hypothesized cooling in the northern hemisphere following a nuclear war due to injection of smoke from burning cities into the atmosphere. The voluminous literature on this subject produced since the original paper in 1983 by Turco, Toon, Ackerman, Pollack, and Sagen (TTAPS) has been reviewed. The widespread use of 3-dimensional global circulation models have resulted in reduced estimates of cooling; 15 to 25 0 C for a summer war and a few degrees for a winter war. More serious may be the possibility of suppression of convective precipitation by the altered temperature profiles in the atmosphere. However, very large uncertainties remain in input parameters, the models, and the results of calculations. We believe the state of knowledge about nuclear winter is sufficiently developed to conclude: Neither cold nor drought are likely to be direct threats to human survival for populations with the wherewithal to survive normal January temperatures; The principal threat from nuclear winter is to food production, and could present problems to third parties without food reserves; and Loss of a crop year is neither a new nor unexpected threat from nuclear war to the US and the Soviet Union. Both have at least a year's food reserve at all times. Both face formidable organizational problems in distributing their reserves in a war-damaged environment. The consequences of nuclear winter could be expected to fall more heavily on the Soviet Union than the US due to its higher latitude and less productive agriculture. This may be especially true if disturbances of rainfall amounts and distribution persist for more than a year. 6 refs

  17. Nuclear Winter: Implications for civil defense

    Energy Technology Data Exchange (ETDEWEB)

    Chester, C.V.; Perry, A.M.; Hobbs, B.F.

    1988-05-01

    ''Nuclear Winter'' is the term given to the cooling hypothesized to occur in the Northern Hemisphere following a nuclear war as the result of the injection of smoke from burning cities into the atmosphere. The voluminous literature on this subject produced since the paper was published in 1983 by Turco, Toon, Ackerman, Pollack, and Sagen (TTAPS) has been reviewed. Three-dimensional global circulation models have resulted in reduced estimates of cooling---15 to 25/degree/C for a summer war and a few degrees for a winter war. More serious may be the possibility of suppression of convective precipitation by the altered temperature profiles in the atmosphere. However, very large uncertainties remain in input parameters, the models, and the results of calculations. We believe the state of knowledge about nuclear winter is sufficiently developed to conclude: Neither cold nor drought is likely to be a direct threat to human survival for populations with the wherewithal to survive normal January temperatures. The principal threat from nuclear winter is to food production, and this could present problems to third parties who are without food reserves. Loss of a crop year is neither a new nor an unexpected threat from nuclear war to the United States and the Soviet Union. Both have at least a year's food reserve at all times. Both face formidable organizational problems in distributing their reserves in a war-damaged environment. The consequences of nuclear winter could be expected to fall more heavily on the Soviet Union than the United States due to its higher latitude and less productive agriculture. This may be especially true if disturbances of rainfall amounts and distribution persist for more than a year.

  18. Improving Timeliness of Winter Wheat Production Forecast in United States of America, Ukraine and China Using MODIS Data and NCAR Growing Degree Day

    Science.gov (United States)

    Vermote, E.; Franch, B.; Becker-Reshef, I.; Claverie, M.; Huang, J.; Zhang, J.; Sobrino, J. A.

    2014-12-01

    Wheat is the most important cereal crop traded on international markets and winter wheat constitutes approximately 80% of global wheat production. Thus, accurate and timely forecasts of its production are critical for informing agricultural policies and investments, as well as increasing market efficiency and stability. Becker-Reshef et al. (2010) used an empirical generalized model for forecasting winter wheat production. Their approach combined BRDF-corrected daily surface reflectance from Moderate resolution Imaging Spectroradiometer (MODIS) Climate Modeling Grid (CMG) with detailed official crop statistics and crop type masks. It is based on the relationship between the Normalized Difference Vegetation Index (NDVI) at the peak of the growing season, percent wheat within the CMG pixel, and the final yields. This method predicts the yield approximately one month to six weeks prior to harvest. In this study, we include the Growing Degree Day (GDD) information extracted from NCEP/NCAR reanalysis data in order to improve the winter wheat production forecast by increasing the timeliness of the forecasts while conserving the accuracy of the original model. We apply this modified model to three major wheat-producing countries: United States of America, Ukraine and China from 2001 to 2012. We show that a reliable forecast can be made between one month to a month and a half prior to the peak NDVI (meaning two months to two and a half months prior to harvest) while conserving an accuracy of 10% in the production forecast.

  19. Sage-grouse habitat selection during winter in Alberta

    Science.gov (United States)

    Carpenter, Jennifer L.; Aldridge, Cameron L.; Boyce, Mark S.

    2010-01-01

    Greater sage-grouse (Centrocercus urophasianus) are dependent on sagebrush (Artemisia spp.) for food and shelter during winter, yet few studies have assessed winter habitat selection, particularly at scales applicable to conservation planning. Small changes to availability of winter habitats have caused drastic reductions in some sage-grouse populations. We modeled winter habitat selection by sage-grouse in Alberta, Canada, by using a resource selection function. Our purpose was to 1) generate a robust winter habitat-selection model for Alberta sage-grouse; 2) spatially depict habitat suitability in a Geographic Information System to identify areas with a high probability of selection and thus, conservation importance; and 3) assess the relative influence of human development, including oil and gas wells, in landscape models of winter habitat selection. Terrain and vegetation characteristics, sagebrush cover, anthropogenic landscape features, and energy development were important in top Akaike's Information Criterionselected models. During winter, sage-grouse selected dense sagebrush cover and homogenous less rugged areas, and avoided energy development and 2-track truck trails. Sage-grouse avoidance of energy development highlights the need for comprehensive management strategies that maintain suitable habitats across all seasons. ?? 2010 The Wildlife Society.

  20. Excess mortality in winter in Finnish intensive care.

    Science.gov (United States)

    Reinikainen, M; Uusaro, A; Ruokonen, E; Niskanen, M

    2006-07-01

    In the general population, mortality from acute myocardial infarctions, strokes and respiratory causes is increased in winter. The winter climate in Finland is harsh. The aim of this study was to find out whether there are seasonal variations in mortality rates in Finnish intensive care units (ICUs). We analysed data on 31,040 patients treated in 18 Finnish ICUs. We measured severity of illness with acute physiology and chronic health evaluation II (APACHE II) scores and intensity of care with therapeutic intervention scoring system (TISS) scores. We assessed mortality rates in different months and seasons and used logistic regression analysis to test the independent effect of various seasons on hospital mortality. We defined 'winter' as the period from December to February, inclusive. The crude hospital mortality rate was 17.9% in winter and 16.4% in non-winter, P = 0.003. Even after adjustment for case mix, winter season was an independent risk factor for increased hospital mortality (adjusted odds ratio 1.13, 95% confidence interval 1.04-1.22, P = 0.005). In particular, the risk of respiratory failure was increased in winter. Crude hospital mortality was increased during the main holiday season in July. However, the severity of illness-adjusted risk of death was not higher in July than in other months. An increase in the mean daily TISS score was an independent predictor of increased hospital mortality. Severity of illness-adjusted hospital mortality for Finnish ICU patients is higher in winter than in other seasons.

  1. A 6-month mixed-effect pharmacokinetic model for post-transplant intravenous anti-hepatitis B immunoglobulin prophylaxis

    Directory of Open Access Journals (Sweden)

    Han S

    2017-07-01

    Full Text Available Seunghoon Han,1,2 Gun Hyung Na,3 Dong-Goo Kim3 1Department of Pharmacology, College of Medicine, The Catholic University of Korea, Seocho-gu, Seoul, South Korea; 2Pharmacometrics Institute for Practical Education and Training, The Catholic University of Korea, Seocho-gu, Seoul, South Korea; 3Department of Surgery, Seoul St Mary’s Hospital, The Catholic University of Korea, Seocho-gu, Seoul, South Korea Background: Although individualized dosage regimens for anti-hepatitis B immunoglobulin (HBIG therapy have been suggested, the pharmacokinetic profile and factors influencing the basis for individualization have not been sufficiently assessed. We sought to evaluate the pharmacokinetic characteristics of anti-HBIG quantitatively during the first 6 months after liver transplantation. Methods: Identical doses of 10,000 IU HBIG were administered to adult liver transplant recipients daily during the first week, weekly thereafter until 28 postoperative days, and monthly thereafter. Blood samples were obtained at days 1, 7, 28, 84, and 168 after transplantation. Plasma HBIG titer was quantified using 4 different immunoassay methods. The titer determined by each analytical method was used for mixed-effect modeling, and the most precise results were chosen. Simulations were performed to predict the plausible immunoglobulin maintenance dose. Results: HBIG was eliminated from the body most rapidly in the immediate post-transplant period, and the elimination rate gradually decreased thereafter. In the early post-transplant period, patients with higher DNA titer tend to have lower plasma HBIG concentrations. The maintenance doses required to attain targets in 90%, 95%, and 99% of patients were ~15.3, 18.2, and 25.1 IU, respectively, multiplied by the target trough level (in IU/L. Conclusion: The variability (explained and unexplained in HBIG pharmacokinetics was relatively larger in the early post-transplant period. Dose individualization based upon

  2. Impacts of +2 °C global warming on winter tourism demand in Europe

    NARCIS (Netherlands)

    Damm, Andrea; Greuell, Wouter; Landgren, Oskar; Prettenthaler, Franz

    2017-01-01

    Increasing temperatures and snow scarce winter seasons challenge the winter tourism industry. In this study the impacts of +2 °C global warming on winter tourism demand in Europe's ski tourism related NUTS-3 regions are quantified. Using time series regression models, the relationship between

  3. Seasonal overturning circulation in the Red Sea: 2. Winter circulation

    KAUST Repository

    Yao, Fengchao; Hoteit, Ibrahim; Pratt, Lawrence J.; Bower, Amy S.; Kö hl, Armin; Gopalakrishnan, Ganesh; Rivas, David

    2014-01-01

    The shallow winter overturning circulation in the Red Sea is studied using a 50 year high-resolution MITgcm (MIT general circulation model) simulation with realistic atmospheric forcing. The overturning circulation for a typical year, represented

  4. Winter Precipitation in North America and the Pacific-North America Pattern in GEOS-S2Sv2 Seasonal Hindcast

    Science.gov (United States)

    Li, Zhao; Molod, Andrea; Schubert, Siegfried

    2018-01-01

    Reliable prediction of precipitation remains one of the most pivotal and complex challenges in seasonal forecasting. Previous studies show that various large-scale climate modes, such as ENSO, PNA and NAO play significant role in winter precipitation variability over the Northern America. The influences are most pronounced in years of strong indices of such climate modes. This study evaluates model bias, predictability and forecast skills of monthly winter precipitation in GEOS5-S2S 2.0 retrospective forecast from 1981 to 2016, with emphasis on the forecast skill of precipitation over North America during the extreme events of ENSO, PNA and NAO by applying EOF and composite analysis.

  5. Winter/Summer Monsoon Experiment

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Winter/Summer Monsoon Experiment (MONEX) was conducted during the First Global GARP (Global Atmospheric Research Program) Experiment (FGGE). An international...

  6. The meaning of nuclear winter

    International Nuclear Information System (INIS)

    Geiger, H.J.

    1987-01-01

    In this paper the author reviews the history and origins of the basic ideas underlying nuclear winter; and findings and predictions of several groups regarding this topic. The author reviews some of the further developments and scientific analyses regarding nuclear winter since the initial announcements of 1983, touching on some of the revisions and controversies and trying to indicate the current status of the field

  7. Seeking explanations for recent changes in abundance of wintering Eurasian Wigeon (Anas penelope) in northwest Europe

    DEFF Research Database (Denmark)

    Fox, Anthony David; Dalby, Lars; Christensen, Thomas Kjær

    2016-01-01

    the range. However, because over 75% of the population of over 1 million individuals winters in Belgium, the Netherlands, UK and France, there was no evidence for a major movement in the centre of gravity of the wintering distribution. Between-winter changes in overall flyway abundance were highly......We analysed annual changes in abundance of Eurasian Wigeon (Anas penelope) derived from mid-winter International Waterbird Census data throughout its northwest European flyway since 1988 using log-linear Poisson regression modelling. Increases in abundance in the north and east of the wintering...... range (Norway, Sweden, Denmark, Germany, Switzerland), stable numbers in the central range (Belgium,Netherlands,UKand France) and declining abundance in the west and south of the wintering range (Spain and Ireland) suggest a shift in wintering distribution consistent with milder winters throughout...

  8. A model-based approach to adjust microwave observations for operational applications: results of a campaign at Munich Airport in winter 2011/2012

    Directory of Open Access Journals (Sweden)

    J. Güldner

    2013-10-01

    of model-based regression operators in order to provide unbiased vertical profiles during the campaign at Munich Airport. The results of this algorithm and the retrievals of a neural network, specially developed for the site, are compared with radiosondes from Oberschleißheim located about 10 km apart from the MWRP site. Outstanding deviations for the lowest levels between 50 and 100 m are discussed. Analogously to the airport experiment, a model-based regression operator was calculated for Lindenberg and compared with both radiosondes and operational results of observation-based methods. The bias of the retrievals could be considerably reduced and the accuracy, which has been assessed for the airport site, is quite similar to those of the operational radiometer site at Lindenberg above 1 km height. Additional investigations are made to determine the length of the training period necessary for generating best estimates. Thereby three months have proven to be adequate. The results of the study show that on the basis of numerical weather prediction (NWP model data, available everywhere at any time, the model-based regression method is capable of providing comparable results at a multitude of sites. Furthermore, the approach offers auspicious conditions for automation and continuous updating.

  9. Petroleum Supply Monthly

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    1996-02-01

    The Petroleum Supply Monthly (PSM) is one of a family of four publications produced by the Petroleum Supply Division within the Energy Information Administration (EIA) reflecting different levels of data timeliness and completeness. The other publications are the Weekly Petroleum Status Report (WPSR), the Winter Fuels Report, and the Petroleum Supply Annual (PSA). Data presented in the PSM describe the supply and disposition of petroleum products in the United States and major U.S. geographic regions. The data series describe production, imports and exports, inter-Petroleum Administration for Defense (PAD) District movements, and inventories by the primary suppliers of petroleum products in the United States (50 States and the District of Columbia). The reporting universe includes those petroleum sectors in primary supply. Included are: petroleum refiners, motor gasoline blenders, operators of natural gas processing plants and fractionators, inter-PAD transporters, importers, and major inventory holders of petroleum products and crude oil. When aggregated, the data reported by these sectors approximately represent the consumption of petroleum products in the United States. Data presented in the PSM are divided into two sections: Summary Statistics and Detailed Statistics.

  10. Petroleum supply monthly

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    1995-10-01

    The Petroleum Supply Monthly (PSM) is one of a family of four publications produced by the Petroleum Supply Division within the Energy Information Administration (EIA) reflecting different levels of data timeliness and completeness. The other publications are the Weekly Petroleum Status Report (WPSR), the Winter Fuels Report, and the Petroleum Supply Annual (PSA). Data presented in the PSM describe the supply and disposition of petroleum products in the United States and major US geographic regions. The data series describe production, imports and exports, inter-Petroleum Administration for Defense (PAD) District movements, and inventories by the primary suppliers of petroleum products in the United States (50 States and the District of Columbia). The reporting universe includes those petroleum sectors in primary supply. Included are: petroleum refiners, motor gasoline blends, operators of natural gas processing plants and fractionators, inter-PAD transporters, importers, and major inventory holders of petroleum products and crude oil. When aggregated, the data reported by these sectors approximately represent the consumption of petroleum products in the United States.

  11. Winter chilling speeds spring development of temperate butterflies.

    Science.gov (United States)

    Stålhandske, Sandra; Gotthard, Karl; Leimar, Olof

    2017-07-01

    Understanding and predicting phenology has become more important with ongoing climate change and has brought about great research efforts in the recent decades. The majority of studies examining spring phenology of insects have focussed on the effects of spring temperatures alone. Here we use citizen-collected observation data to show that winter cold duration, in addition to spring temperature, can affect the spring emergence of butterflies. Using spatial mixed models, we disentangle the effects of climate variables and reveal impacts of both spring and winter conditions for five butterfly species that overwinter as pupae across the UK, with data from 1976 to 2013 and one butterfly species in Sweden, with data from 2001 to 2013. Warmer springs lead to earlier emergence in all species and milder winters lead to statistically significant delays in three of the five investigated species. We also find that the delaying effect of winter warmth has become more pronounced in the last decade, during which time winter durations have become shorter. For one of the studied species, Anthocharis cardamines (orange tip butterfly), we also make use of parameters determined from previous experiments on pupal development to model the spring phenology. Using daily temperatures in the UK and Sweden, we show that recent variation in spring temperature corresponds to 10-15 day changes in emergence time over UK and Sweden, whereas variation in winter duration corresponds to 20 days variation in the south of the UK versus only 3 days in the south of Sweden. In summary, we show that short winters delay phenology. The effect is most prominent in areas with particularly mild winters, emphasising the importance of winter for the response of ectothermic animals to climate change. With climate change, these effects may become even stronger and apply also at higher latitudes. © 2017 The Authors. Journal of Animal Ecology © 2017 British Ecological Society.

  12. Retrospective forecasts of the upcoming winter season snow accumulation in the Inn headwaters (European Alps)

    Science.gov (United States)

    Förster, Kristian; Hanzer, Florian; Stoll, Elena; Scaife, Adam A.; MacLachlan, Craig; Schöber, Johannes; Huttenlau, Matthias; Achleitner, Stefan; Strasser, Ulrich

    2018-02-01

    This article presents analyses of retrospective seasonal forecasts of snow accumulation. Re-forecasts with 4 months' lead time from two coupled atmosphere-ocean general circulation models (NCEP CFSv2 and MetOffice GloSea5) drive the Alpine Water balance and Runoff Estimation model (AWARE) in order to predict mid-winter snow accumulation in the Inn headwaters. As snowpack is hydrological storage that evolves during the winter season, it is strongly dependent on precipitation totals of the previous months. Climate model (CM) predictions of precipitation totals integrated from November to February (NDJF) compare reasonably well with observations. Even though predictions for precipitation may not be significantly more skilful than for temperature, the predictive skill achieved for precipitation is retained in subsequent water balance simulations when snow water equivalent (SWE) in February is considered. Given the AWARE simulations driven by observed meteorological fields as a benchmark for SWE analyses, the correlation achieved using GloSea5-AWARE SWE predictions is r = 0.57. The tendency of SWE anomalies (i.e. the sign of anomalies) is correctly predicted in 11 of 13 years. For CFSv2-AWARE, the corresponding values are r = 0.28 and 7 of 13 years. The results suggest that some seasonal prediction of hydrological model storage tendencies in parts of Europe is possible.

  13. Defence Reporter. Winter 2012

    Science.gov (United States)

    2012-01-01

    TMAP Polarisation Slant Angle Module Documentation Dstl, Portsdown West (GB) (2012) This report documents the mathematics and Matlab implementation of...a TMAP , (Threat Modelling and Analysis Program) module calculating the polarisation slant angle for use in aircraft engagement modelling. The

  14. Arctic lake physical processes and regimes with implications for winter water availability and management in the National Petroleum Reserve Alaska.

    Science.gov (United States)

    Jones, Benjamin M; Arp, Christopher D; Hinkel, Kenneth M; Beck, Richard A; Schmutz, Joel A; Winston, Barry

    2009-06-01

    Lakes are dominant landforms in the National Petroleum Reserve Alaska (NPRA) as well as important social and ecological resources. Of recent importance is the management of these freshwater ecosystems because lakes deeper than maximum ice thickness provide an important and often sole source of liquid water for aquatic biota, villages, and industry during winter. To better understand seasonal and annual hydrodynamics in the context of lake morphometry, we analyzed lakes in two adjacent areas where winter water use is expected to increase in the near future because of industrial expansion. Landsat Thematic Mapper and Enhanced Thematic Mapper Plus imagery acquired between 1985 and 2007 were analyzed and compared with climate data to understand interannual variability. Measured changes in lake area extent varied by 0.6% and were significantly correlated to total precipitation in the preceding 12 months (p water-level monitoring, and lake-ice thickness measurements and growth models were used to better understand seasonal hydrodynamics, surface area-to-volume relations, winter water availability, and more permanent changes related to geomorphic change. Together, these results describe how lakes vary seasonally and annually in two critical areas of the NPRA and provide simple models to help better predict variation in lake-water supply. Our findings suggest that both overestimation and underestimation of actual available winter water volume may occur regularly, and this understanding may help better inform management strategies as future resource use expands in the NPRA.

  15. The impact of winter cold weather on acute myocardial infarctions in Portugal

    International Nuclear Information System (INIS)

    Vasconcelos, João; Freire, Elisabete; Almendra, Ricardo

    2013-01-01

    Mortality due to cardiovascular diseases shows a seasonal trend that can be associated with cold weather. Portugal is the European country with the highest excess winter mortality, but nevertheless, the relationship between cold weather and health is yet to be assessed. The main aim of this study is to identify the contribution of cold weather to cardiovascular diseases within Portugal. Poisson regression analysis based on generalized additive models was applied to estimate the influence of a human-biometeorological index (PET) on daily hospitalizations for myocardial infarction. The main results revealed a negative effect of cold weather on acute myocardial infarctions in Portugal. For every degree fall in PET during winter, there was an increase of up to 2.2% (95% CI = 0.9%; 3.3%) in daily hospital admissions. This paper shows the need for public policies that will help minimize or, indeed, prevent exposure to cold. -- Highlights: ► We model the relationship between daily hospitalizations due to myocardial infarctions and cold weather in Portugal. ► We use Physiological Equivalent temperature (PET) as main explanatory variable. ► We adjust the models to confounding factors such as influenza and air pollution. ► Daily hospitalizations increased up to 2.2% per degree fall of PET during winter. ► Exposure to cold weather has a negative impact on human health in Portugal. -- There is an increase of up to 2.2% in daily hospitalizations due to acute myocardial infarctions per degree fall of thermal index during the winter months in Portugal

  16. Spectrum of winter dermatoses in rural Yemen.

    Science.gov (United States)

    Al-Kamel, Mohamed A

    2016-05-01

    Surveys that have been carried out to determine the prevalence of skin diseases in rural Yemen are scarce or not available. To investigate the spectrum of winter dermatoses in a rural Yemeni community. A retrospective study was conducted at the dermatology outpatient clinic of the Al-Helal Specialized Hospital (Radaa' district of Al Bayda' Governorate) using data analysis of 700 selected records of patients managed during four months of the 2013-14 winter season. Seven hundred patients with 730 diseases were reported in this study; the major bulk of patients (46.57%) were in the >18-40-year age group, and females outnumbered males. By far, dermatitis, eczematous, and allergic disorders (38.49%) topped the list of the most frequent skin disorders groups, followed by skin infections and infestations (20%) and the pigmentary disorders (13.70%) group. Contact dermatitis (10.68%) was the most prevalent skin disorder, followed by hyperpigmentations (8.77%), acne (8.08%), viral infections (5.75%), atopic dermatitis (5.62%), and parasitic infestations (5.34%). This survey has documented the spectrum of winter dermatoses in a rural Yemeni community but also reflects the pattern of common dermatoses in the whole country. Dermatitis, eczematous, and allergic disorders, skin infections, and pigmentary disorders are the commonest groups. Contact dermatitis is the most prevalent disorder, and leishmaniasis is the most prevalent skin infectious disease. Climate, occupational, social, and environmental factors are the main contributors. Such statistics can form an important basis for community-based health policies. © 2015 The International Society of Dermatology.

  17. Prediction of 6 months left ventricular dilatation after myocardial infarction in relation to cardiac morbidity and mortality - Application of a new dilatation model to GISSI-3 data

    NARCIS (Netherlands)

    de Kam, PJ; Nicolosi, GL; Voors, AA; van den Berg, MP; Brouwer, J; van Veldhuisen, DJ; Barlera, S; Maggioni, AP; Giannuzzi, P; Temporelli, PL; Latini, R; van Gilst, WH

    Aims To predict the long-term left ventricular volume index early after myocardial infarction and to investigate the relationship between long-term left ventricular dilatation risk and clinical outcome. Methods and Results By applying a previously developed dilatation model, we predicted the 6-month

  18. The asymmetric effects of El Niño and La Niña on the East Asian winter monsoon and their simulation by CMIP5 atmospheric models

    Science.gov (United States)

    Guo, Zhun; Zhou, Tianjun; Wu, Bo

    2017-02-01

    El Niño-Southern Oscillation (ENSO) events significantly affect the year-by-year variations of the East Asian winter monsoon (EAWM). However, the effect of La Niña events on the EAWM is not a mirror image of that of El Niño events. Although the EAWM becomes generally weaker during El Niño events and stronger during La Niña winters, the enhanced precipitation over the southeastern China and warmer surface air temperature along the East Asian coastline during El Niño years are more significant. These asymmetric effects are caused by the asymmetric longitudinal positions of the western North Pacific (WNP) anticyclone during El Niño events and the WNP cyclone during La Niña events; specifically, the center of the WNP cyclone during La Niña events is westward-shifted relative to its El Niño counterpart. This central-position shift results from the longitudinal shift of remote El Niño and La Niña anomalous heating, and asymmetry in the amplitude of local sea surface temperature anomalies over the WNP. However, such asymmetric effects of ENSO on the EAWM are barely reproduced by the atmospheric models of Phase 5 of the Coupled Model Intercomparison Project (CMIP5), although the spatial patterns of anomalous circulations are reasonably reproduced. The major limitation of the CMIP5 models is an overestimation of the anomalous WNP anticyclone/cyclone, which leads to stronger EAWM rainfall responses. The overestimated latent heat flux anomalies near the South China Sea and the northern WNP might be a key factor behind the overestimated anomalous circulations.

  19. Seasonal prediction of winter extreme precipitation over Canada by support vector regression

    Directory of Open Access Journals (Sweden)

    Z. Zeng

    2011-01-01

    Full Text Available For forecasting the maximum 5-day accumulated precipitation over the winter season at lead times of 3, 6, 9 and 12 months over Canada from 1950 to 2007, two nonlinear and two linear regression models were used, where the models were support vector regression (SVR (nonlinear and linear versions, nonlinear Bayesian neural network (BNN and multiple linear regression (MLR. The 118 stations were grouped into six geographic regions by K-means clustering. For each region, the leading principal components of the winter maximum 5-d accumulated precipitation anomalies were the predictands. Potential predictors included quasi-global sea surface temperature anomalies and 500 hPa geopotential height anomalies over the Northern Hemisphere, as well as six climate indices (the Niño-3.4 region sea surface temperature, the North Atlantic Oscillation, the Pacific-North American teleconnection, the Pacific Decadal Oscillation, the Scandinavia pattern, and the East Atlantic pattern. The results showed that in general the two robust SVR models tended to have better forecast skills than the two non-robust models (MLR and BNN, and the nonlinear SVR model tended to forecast slightly better than the linear SVR model. Among the six regions, the Prairies region displayed the highest forecast skills, and the Arctic region the second highest. The strongest nonlinearity was manifested over the Prairies and the weakest nonlinearity over the Arctic.

  20. Winter survival of Scots pine seedlings under different snow conditions.

    Science.gov (United States)

    Domisch, Timo; Martz, Françoise; Repo, Tapani; Rautio, Pasi

    2018-04-01

    Future climate scenarios predict increased air temperatures and precipitation, particularly at high latitudes, and especially so during winter. Soil temperatures, however, are more difficult to predict, since they depend strongly on the fate of the insulating snow cover. 'Rain-on-snow' events and warm spells during winter can lead to thaw-freeze cycles, compacted snow and ice encasement, as well as local flooding. These adverse conditions could counteract the otherwise positive effects of climatic changes on forest seedling growth. In order to study the effects of different winter and snow conditions on young Scots pine (Pinus sylvestris L.) seedlings, we conducted a laboratory experiment in which 80 1-year-old Scots pine seedlings were distributed between four winter treatments in dasotrons: ambient snow cover (SNOW), compressed snow and ice encasement (ICE), flooded and frozen soil (FLOOD) and no snow (NO SNOW). During the winter treatment period and a 1.5-month simulated spring/early summer phase, we monitored the needle, stem and root biomass of the seedlings, and determined their starch and soluble sugar concentrations. In addition, we assessed the stress experienced by the seedlings by measuring chlorophyll fluorescence, electric impedance and photosynthesis of the previous-year needles. Compared with the SNOW treatment, carbohydrate concentrations were lower in the FLOOD and NO SNOW treatments where the seedlings had almost died before the end of the experiment, presumably due to frost desiccation of aboveground parts during the winter treatments. The seedlings of the ICE treatment showed dead needles and stems only above the snow and ice cover. The results emphasize the importance of an insulating and protecting snow cover for small forest tree seedlings, and that future winters with changed snow patterns might affect the survival of tree seedlings and thus forest productivity.

  1. Hydrologic consistency as a basis for assessing complexity of monthly water balance models for the continental United States

    Science.gov (United States)

    Martinez, Guillermo F.; Gupta, Hoshin V.

    2011-12-01

    Methods to select parsimonious and hydrologically consistent model structures are useful for evaluating dominance of hydrologic processes and representativeness of data. While information criteria (appropriately constrained to obey underlying statistical assumptions) can provide a basis for evaluating appropriate model complexity, it is not sufficient to rely upon the principle of maximum likelihood (ML) alone. We suggest that one must also call upon a "principle of hydrologic consistency," meaning that selected ML structures and parameter estimates must be constrained (as well as possible) to reproduce desired hydrological characteristics of the processes under investigation. This argument is demonstrated in the context of evaluating the suitability of candidate model structures for lumped water balance modeling across the continental United States, using data from 307 snow-free catchments. The models are constrained to satisfy several tests of hydrologic consistency, a flow space transformation is used to ensure better consistency with underlying statistical assumptions, and information criteria are used to evaluate model complexity relative to the data. The results clearly demonstrate that the principle of consistency provides a sensible basis for guiding selection of model structures and indicate strong spatial persistence of certain model structures across the continental United States. Further work to untangle reasons for model structure predominance can help to relate conceptual model structures to physical characteristics of the catchments, facilitating the task of prediction in ungaged basins.

  2. Learning through a Winter's Tale

    Science.gov (United States)

    Vidotto, Kristie

    2010-01-01

    In this article, the author shares her experience during the final semester of Year 11 Theatre Studies when she performed a monologue about Hermione from "The Winter's Tale". This experience was extremely significant to her because it nearly made her lose faith in one of the most important parts of her life, drama. She believes this…

  3. Monthly land cover-specific evapotranspiration models derived from global eddy flux measurements and remote sensing data

    Science.gov (United States)

    Yuan Fang; Ge Sun; Peter Caldwell; Steven G. McNulty; Asko Noormets; Jean-Christophe Domec; John King; Zhiqiang Zhang; Xudong Zhang; Guanghui Lin; Guangsheng Zhou; Jingfeng Xiao; Jiquan Chen

    2015-01-01

    Evapotranspiration (ET) is arguably the most uncertain ecohydrologic variable for quantifying watershed water budgets. Although numerous ET and hydrological models exist, accurately predicting the effects of global change on water use and availability remains challenging because of model deficiency and/or a lack of input parameters. The objective of this study was to...

  4. Validation of AquaCrop Model for Simulation of Winter Wheat Yield and Water Use Efficiency under Simultaneous Salinity and Water Stress

    OpenAIRE

    M. Mohammadi; B. Ghahraman; K. Davary; H. Ansari; A. Shahidi

    2016-01-01

    Introduction: FAO AquaCrop model (Raes et al., 2009a; Steduto et al., 2009) is a user-friendly and practitioner oriented type of model, because it maintains an optimal balance between accuracy, robustness, and simplicity; and it requires a relatively small number of model input parameters. The FAO AquaCrop model predicts crop productivity, water requirement, and water use efficiency under water-limiting and saline water conditions. This model has been tested and validated for different crops ...

  5. Application of GRACE to the assessment of model-based estimates of monthly Greenland Ice Sheet mass balance (2003-2012)

    Science.gov (United States)

    Schlegel, Nicole-Jeanne; Wiese, David N.; Larour, Eric Y.; Watkins, Michael M.; Box, Jason E.; Fettweis, Xavier; van den Broeke, Michiel R.

    2016-09-01

    Quantifying the Greenland Ice Sheet's future contribution to sea level rise is a challenging task that requires accurate estimates of ice sheet sensitivity to climate change. Forward ice sheet models are promising tools for estimating future ice sheet behavior, yet confidence is low because evaluation of historical simulations is challenging due to the scarcity of continental-wide data for model evaluation. Recent advancements in processing of Gravity Recovery and Climate Experiment (GRACE) data using Bayesian-constrained mass concentration ("mascon") functions have led to improvements in spatial resolution and noise reduction of monthly global gravity fields. Specifically, the Jet Propulsion Laboratory's JPL RL05M GRACE mascon solution (GRACE_JPL) offers an opportunity for the assessment of model-based estimates of ice sheet mass balance (MB) at ˜ 300 km spatial scales. Here, we quantify the differences between Greenland monthly observed MB (GRACE_JPL) and that estimated by state-of-the-art, high-resolution models, with respect to GRACE_JPL and model uncertainties. To simulate the years 2003-2012, we force the Ice Sheet System Model (ISSM) with anomalies from three different surface mass balance (SMB) products derived from regional climate models. Resulting MB is compared against GRACE_JPL within individual mascons. Overall, we find agreement in the northeast and southwest where MB is assumed to be primarily controlled by SMB. In the interior, we find a discrepancy in trend, which we presume to be related to millennial-scale dynamic thickening not considered by our model. In the northwest, seasonal amplitudes agree, but modeled mass trends are muted relative to GRACE_JPL. Here, discrepancies are likely controlled by temporal variability in ice discharge and other related processes not represented by our model simulations, i.e., hydrological processes and ice-ocean interaction. In the southeast, GRACE_JPL exhibits larger seasonal amplitude than predicted by the

  6. Predicting 6- and 12-Month Risk of Mortality in Patients With Platinum-Resistant Advanced-Stage Ovarian Cancer: Prognostic Model to Guide Palliative Care Referrals.

    Science.gov (United States)

    Foote, Jonathan; Lopez-Acevedo, Micael; Samsa, Gregory; Lee, Paula S; Kamal, Arif H; Alvarez Secord, Angeles; Havrilesky, Laura J

    2018-02-01

    Predictive models are increasingly being used in clinical practice. The aim of the study was to develop a predictive model to identify patients with platinum-resistant ovarian cancer with a prognosis of less than 6 to 12 months who may benefit from immediate referral to hospice care. A retrospective chart review identified patients with platinum-resistant epithelial ovarian cancer who were treated at our institution between 2000 and 2011. A predictive model for survival was constructed based on the time from development of platinum resistance to death. Multivariate logistic regression modeling was used to identify significant survival predictors and to develop a predictive model. The following variables were included: time from diagnosis to platinum resistance, initial stage, debulking status, number of relapses, comorbidity score, albumin, hemoglobin, CA-125 levels, liver/lung metastasis, and the presence of a significant clinical event (SCE). An SCE was defined as a malignant bowel obstruction, pleural effusion, or ascites occurring on or before the diagnosis of platinum resistance. One hundred sixty-four patients met inclusion criteria. In the regression analysis, only an SCE and the presence of liver or lung metastasis were associated with poorer short-term survival (P < 0.001). Nine percent of patients with an SCE or liver or lung metastasis survived 6 months or greater and 0% survived 12 months or greater, compared with 85% and 67% of patients without an SCE or liver or lung metastasis, respectively. Patients with platinum-resistant ovarian cancer who have experienced an SCE or liver or lung metastasis have a high risk of death within 6 months and should be considered for immediate referral to hospice care.

  7. NLDAS Noah Land Surface Model L4 Monthly 0.125 x 0.125 degree V002

    Data.gov (United States)

    National Aeronautics and Space Administration — This data set contains a series of land surface parameters simulated from the Noah land-surface model (LSM) for Phase 2 of the North American Land Data Assimilation...

  8. Contrasting effects of temperature and winter mixing on the seasonal and inter-annual variability of the carbonate system in the Northeast Atlantic Ocean

    Directory of Open Access Journals (Sweden)

    C. Dumousseaud

    2010-05-01

    Full Text Available Future climate change as a result of increasing atmospheric CO2 concentrations is expected to strongly affect the oceans, with shallower winter mixing and consequent reduction in primary production and oceanic carbon drawdown in low and mid-latitudinal oceanic regions. Here we test this hypothesis by examining the effects of cold and warm winters on the carbonate system in the surface waters of the Northeast Atlantic Ocean for the period between 2005 and 2007. Monthly observations were made between the English Channel and the Bay of Biscay using a ship of opportunity program. During the colder winter of 2005/2006, the maximum depth of the mixed layer reached up to 650 m in the Bay of Biscay, whilst during the warmer (by 2.6 ± 0.5 °C winter of 2006/2007 the mixed layer depth reached only 300 m. The inter-annual differences in late winter concentrations of nitrate (2.8 ± 1.1 μmol l−1 and dissolved inorganic carbon (22 ± 6 μmol kg−1, with higher concentrations at the end of the colder winter (2005/2006, led to differences in the dissolved oxygen anomaly and the chlorophyll α-fluorescence data for the subsequent growing season. In contrast to model predictions, the calculated air-sea CO2 fluxes (ranging from +3.7 to −4.8 mmol m−2 d−1 showed an increased oceanic CO2 uptake in the Bay of Biscay following the warmer winter of 2006/2007 associated with wind speed and sea surface temperature differences.

  9. 36 CFR 1002.19 - Winter activities.

    Science.gov (United States)

    2010-07-01

    ... RECREATION § 1002.19 Winter activities. (a) Skiing, snowshoeing, ice skating, sledding, innertubing, tobogganing and similar winter sports are prohibited on Presidio Trust roads and in parking areas open to...

  10. Classification guide: Sochi 2014 Paralympic Winter Games

    OpenAIRE

    2014-01-01

    The Sochi 2014 Paralympic Winter Games classification guide is designed to provide National Paralympic Committees (NPCs) and International Federations (IFs) with information about the classification policies and procedures that will apply to the Sochi 2014 Paralympic Winter Games.

  11. Essential Outdoor Sun Safety Tips for Winter

    Science.gov (United States)

    ... Weekend Warriors expand/collapse Vitamin D Essential Outdoor Sun Safety Tips for Winter Winter sports enthusiasts are ... skiing! Be Mindful of Time Spent in the Sun, Regardless of the Season If possible, ski early ...

  12. TRANSIT TIMING OBSERVATIONS FROM KEPLER. V. TRANSIT TIMING VARIATION CANDIDATES IN THE FIRST SIXTEEN MONTHS FROM POLYNOMIAL MODELS

    Energy Technology Data Exchange (ETDEWEB)

    Ford, Eric B. [Astronomy Department, University of Florida, 211 Bryant Space Sciences Center, Gainesville, FL 32111 (United States); Ragozzine, Darin; Holman, Matthew J. [Harvard-Smithsonian Center for Astrophysics, 60 Garden Street, Cambridge, MA 02138 (United States); Rowe, Jason F.; Barclay, Thomas; Borucki, William J.; Bryson, Stephen T.; Caldwell, Douglas A.; Kinemuchi, Karen; Koch, David G.; Lissauer, Jack J.; Still, Martin; Tenenbaum, Peter [NASA Ames Research Center, Moffett Field, CA 94035 (United States); Steffen, Jason H. [Fermilab Center for Particle Astrophysics, P.O. Box 500, MS 127, Batavia, IL 60510 (United States); Batalha, Natalie M. [Department of Physics and Astronomy, San Jose State University, San Jose, CA 95192 (United States); Fabrycky, Daniel C. [UCO/Lick Observatory, University of California, Santa Cruz, CA 95064 (United States); Gautier, Thomas N. [Jet Propulsion Laboratory/California Institute of Technology, Pasadena, CA 91109 (United States); Ibrahim, Khadeejah A.; Uddin, Kamal [Orbital Sciences Corporation/NASA Ames Research Center, Moffett Field, CA 94035 (United States); Kjeldsen, Hans, E-mail: eford@astro.ufl.edu [Department of Physics and Astronomy, Aarhus University, DK-8000 Aarhus C (Denmark); and others

    2012-09-10

    Transit timing variations provide a powerful tool for confirming and characterizing transiting planets, as well as detecting non-transiting planets. We report the results of an updated transit timing variation (TTV) analysis for 1481 planet candidates based on transit times measured during the first sixteen months of Kepler observations. We present 39 strong TTV candidates based on long-term trends (2.8% of suitable data sets). We present another 136 weaker TTV candidates (9.8% of suitable data sets) based on the excess scatter of TTV measurements about a linear ephemeris. We anticipate that several of these planet candidates could be confirmed and perhaps characterized with more detailed TTV analyses using publicly available Kepler observations. For many others, Kepler has observed a long-term TTV trend, but an extended Kepler mission will be required to characterize the system via TTVs. We find that the occurrence rate of planet candidates that show TTVs is significantly increased ({approx}68%) for planet candidates transiting stars with multiple transiting planet candidates when compared to planet candidates transiting stars with a single transiting planet candidate.

  13. Winter active bumblebees (Bombus terrestris achieve high foraging rates in urban Britain.

    Directory of Open Access Journals (Sweden)

    Ralph J Stelzer

    2010-03-01

    Full Text Available Foraging bumblebees are normally associated with spring and summer in northern Europe. However, there have been sightings of the bumblebee Bombus terrestris during the warmer winters in recent years in southern England. But what floral resources are they relying upon during winter and how much winter forage can they collect?To test if urban areas in the UK provide a rich foraging niche for bees we set up colonies of B. terrestris in the field during two late winter periods (2005/6 & 2006/7 in London, UK, and measured their foraging performance. Fully automatic radio-frequency identification (RFID technology was used in 2006/7 to enable us to record the complete foraging activity of individually tagged bees. The number of bumblebees present during winter (October 2007 to March 2008 and the main plants they visited were also recorded during transect walks. Queens and workers were observed throughout the winter, suggesting a second generation of bee colonies active during the winter months. Mass flowering shrubs such as Mahonia spp. were identified as important food resources. The foraging experiments showed that bees active during the winter can attain nectar and pollen foraging rates that match, and even surpass, those recorded during summer.B. terrestris in the UK are now able to utilise a rich winter foraging resource in urban parks and gardens that might at present still be under-exploited, opening up the possibility of further changes in pollinator phenology.

  14. Winter active bumblebees (Bombus terrestris) achieve high foraging rates in urban Britain.

    Science.gov (United States)

    Stelzer, Ralph J; Chittka, Lars; Carlton, Marc; Ings, Thomas C

    2010-03-05

    Foraging bumblebees are normally associated with spring and summer in northern Europe. However, there have been sightings of the bumblebee Bombus terrestris during the warmer winters in recent years in southern England. But what floral resources are they relying upon during winter and how much winter forage can they collect? To test if urban areas in the UK provide a rich foraging niche for bees we set up colonies of B. terrestris in the field during two late winter periods (2005/6 & 2006/7) in London, UK, and measured their foraging performance. Fully automatic radio-frequency identification (RFID) technology was used in 2006/7 to enable us to record the complete foraging activity of individually tagged bees. The number of bumblebees present during winter (October 2007 to March 2008) and the main plants they visited were also recorded during transect walks. Queens and workers were observed throughout the winter, suggesting a second generation of bee colonies active during the winter months. Mass flowering shrubs such as Mahonia spp. were identified as important food resources. The foraging experiments showed that bees active during the winter can attain nectar and pollen foraging rates that match, and even surpass, those recorded during summer. B. terrestris in the UK are now able to utilise a rich winter foraging resource in urban parks and gardens that might at present still be under-exploited, opening up the possibility of further changes in pollinator phenology.

  15. Reasons for Distress Among Burn Survivors at 6, 12, and 24 Months Postdischarge: A Burn Injury Model System Investigation.

    Science.gov (United States)

    Wiechman, Shelley A; McMullen, Kara; Carrougher, Gretchen J; Fauerbach, Jame A; Ryan, Colleen M; Herndon, David N; Holavanahalli, Radha; Gibran, Nicole S; Roaten, Kimberly

    2017-12-16

    To identify important sources of distress among burn survivors at discharge and 6, 12, and 24 months postinjury, and to examine if the distress related to these sources changed over time. Exploratory. Outpatient burn clinics in 4 sites across the country. Participants who met preestablished criteria for having a major burn injury (N=1009) were enrolled in this multisite study. Participants were given a previously developed list of 12 sources of distress among burn survivors and asked to rate on a 10-point Likert-type scale (0=no distress to 10=high distress) how much distress each of the 12 issues was causing them at the time of each follow-up. The Medical Outcomes Study 12-Item Short-Form Health Survey was administered at each time point as a measure of health-related quality of life. The Satisfaction With Appearance Scale was used to understand the relation between sources of distress and body image. Finally, whether a person returned to work was used to determine the effect of sources of distress on returning to employment. It was encouraging that no symptoms were worsening at 2 years. However, financial concerns and long recovery time are 2 of the highest means at all time points. Pain and sleep disturbance had the biggest effect on ability to return to work. These findings can be used to inform burn-specific interventions and to give survivors an understanding of the temporal trajectory for various causes of distress. In particular, it appears that interventions targeted at sleep disturbance and high pain levels can potentially effect distress over financial concerns by allowing a person to return to work more quickly. Copyright © 2017 American Congress of Rehabilitation Medicine. Published by Elsevier Inc. All rights reserved.

  16. Leadership in American Indian Communities: Winter Lessons

    Science.gov (United States)

    Metoyer, Cheryl A.

    2010-01-01

    Winter lessons, or stories told in the winter, were one of the ways in which tribal elders instructed and directed young men and women in the proper ways to assume leadership responsibilities. Winter lessons stressed the appropriate relationship between the leader and the community. The intent was to remember the power and purpose of that…

  17. 46 CFR 45.73 - Winter freeboard.

    Science.gov (United States)

    2010-10-01

    ... 46 Shipping 2 2010-10-01 2010-10-01 false Winter freeboard. 45.73 Section 45.73 Shipping COAST GUARD, DEPARTMENT OF HOMELAND SECURITY (CONTINUED) LOAD LINES GREAT LAKES LOAD LINES Freeboards § 45.73 Winter freeboard. The minimum winter freeboard (fw) in inches is obtained by the formula: fw=f(s)+T s...

  18. A comparison of monthly precipitation point estimates at 6 locations in Iran using integration of soft computing methods and GARCH time series model

    Science.gov (United States)

    Mehdizadeh, Saeid; Behmanesh, Javad; Khalili, Keivan

    2017-11-01

    Precipitation plays an important role in determining the climate of a region. Precise estimation of precipitation is required to manage and plan water resources, as well as other related applications such as hydrology, climatology, meteorology and agriculture. Time series of hydrologic variables such as precipitation are composed of deterministic and stochastic parts. Despite this fact, the stochastic part of the precipitation data is not usually considered in modeling of precipitation process. As an innovation, the present study introduces three new hybrid models by integrating soft computing methods including multivariate adaptive regression splines (MARS), Bayesian networks (BN) and gene expression programming (GEP) with a time series model, namely generalized autoregressive conditional heteroscedasticity (GARCH) for modeling of the monthly precipitation. For this purpose, the deterministic (obtained by soft computing methods) and stochastic (obtained by GARCH time series model) parts are combined with each other. To carry out this research, monthly precipitation data of Babolsar, Bandar Anzali, Gorgan, Ramsar, Tehran and Urmia stations with different climates in Iran were used during the period of 1965-2014. Root mean square error (RMSE), relative root mean square error (RRMSE), mean absolute error (MAE) and determination coefficient (R2) were employed to evaluate the performance of conventional/single MARS, BN and GEP, as well as the proposed MARS-GARCH, BN-GARCH and GEP-GARCH hybrid models. It was found that the proposed novel models are more precise than single MARS, BN and GEP models. Overall, MARS-GARCH and BN-GARCH models yielded better accuracy than GEP-GARCH. The results of the present study confirmed the suitability of proposed methodology for precise modeling of precipitation.

  19. External validation and clinical utility of a prediction model for 6-month mortality in patients undergoing hemodialysis for end-stage kidney disease.

    Science.gov (United States)

    Forzley, Brian; Er, Lee; Chiu, Helen Hl; Djurdjev, Ognjenka; Martinusen, Dan; Carson, Rachel C; Hargrove, Gaylene; Levin, Adeera; Karim, Mohamud

    2018-02-01

    End-stage kidney disease is associated with poor prognosis. Health care professionals must be prepared to address end-of-life issues and identify those at high risk for dying. A 6-month mortality prediction model for patients on dialysis derived in the United States is used but has not been externally validated. We aimed to assess the external validity and clinical utility in an independent cohort in Canada. We examined the performance of the published 6-month mortality prediction model, using discrimination, calibration, and decision curve analyses. Data were derived from a cohort of 374 prevalent dialysis patients in two regions of British Columbia, Canada, which included serum albumin, age, peripheral vascular disease, dementia, and answers to the "the surprise question" ("Would I be surprised if this patient died within the next year?"). The observed mortality in the validation cohort was 11.5% at 6 months. The prediction model had reasonable discrimination (c-stat = 0.70) but poor calibration (calibration-in-the-large = -0.53 (95% confidence interval: -0.88, -0.18); calibration slope = 0.57 (95% confidence interval: 0.31, 0.83)) in our data. Decision curve analysis showed the model only has added value in guiding clinical decision in a small range of threshold probabilities: 8%-20%. Despite reasonable discrimination, the prediction model has poor calibration in this external study cohort; thus, it may have limited clinical utility in settings outside of where it was derived. Decision curve analysis clarifies limitations in clinical utility not apparent by receiver operating characteristic curve analysis. This study highlights the importance of external validation of prediction models prior to routine use in clinical practice.

  20. Sampling Errors in Monthly Rainfall Totals for TRMM and SSM/I, Based on Statistics of Retrieved Rain Rates and Simple Models

    Science.gov (United States)

    Bell, Thomas L.; Kundu, Prasun K.; Einaudi, Franco (Technical Monitor)

    2000-01-01

    Estimates from TRMM satellite data of monthly total rainfall over an area are subject to substantial sampling errors due to the limited number of visits to the area by the satellite during the month. Quantitative comparisons of TRMM averages with data collected by other satellites and by ground-based systems require some estimate of the size of this sampling error. A method of estimating this sampling error based on the actual statistics of the TRMM observations and on some modeling work has been developed. "Sampling error" in TRMM monthly averages is defined here relative to the monthly total a hypothetical satellite permanently stationed above the area would have reported. "Sampling error" therefore includes contributions from the random and systematic errors introduced by the satellite remote sensing system. As part of our long-term goal of providing error estimates for each grid point accessible to the TRMM instruments, sampling error estimates for TRMM based on rain retrievals from TRMM microwave (TMI) data are compared for different times of the year and different oceanic areas (to minimize changes in the statistics due to algorithmic differences over land and ocean). Changes in sampling error estimates due to changes in rain statistics due 1) to evolution of the official algorithms used to process the data, and 2) differences from other remote sensing systems such as the Defense Meteorological Satellite Program (DMSP) Special Sensor Microwave/Imager (SSM/I), are analyzed.

  1. Winter to winter recurrence of atmospheric circulation anomalies over East Asia and its impact on winter surface air temperature anomalies.

    Science.gov (United States)

    Zhao, Xia; Yang, Guang

    2017-01-01

    The persistence of atmospheric circulation anomalies over East Asia shows a winter to winter recurrence (WTWR) phenomenon. Seasonal variations in sea level pressure anomalies and surface wind anomalies display significantly different characteristics between WTWR and non-WTWR years. The WTWR years are characterized by the recurrence of both a strong (weak) anomalous Siberian High and an East Asian winter monsoon over two successive winters without persistence through the intervening summer. However, anomalies during the non-WTWR years have the opposite sign between the current and ensuing winters. The WTWR of circulation anomalies contributes to that of surface air temperature anomalies (SATAs), which is useful information for improving seasonal and interannual climate predictions over East Asia and China. In the positive (negative) WTWR years, SATAs are cooler (warmer) over East Asia in two successive winters, but the signs of the SATAs are opposite in the preceding and subsequent winters during the non-WTWR years.

  2. Interdecadal variability of winter precipitation in Southeast China

    OpenAIRE

    Zhang, L.; Zhu, X.; Fraedrich, K.; Sielmann, F.; Zhi, X.

    2014-01-01

    Interdecadal variability of observed winter precipitation in Southeast China (1961–2010) is characterized by the first empirical orthogonal function of the three-monthly Standardized Precipitation Index (SPI) subjected to a 9-year running mean. For interdecadal time scales the dominating spatial modes represent monopole features involving the Arctic Oscillation (AO) and the sea surface temperature (SST) anomalies. Dynamic composite analysis (based on NCEP/NCAR reanalyzes) reveals the followin...

  3. Direct evidence for impact winter following the Cretaceous-Paleogene bolide impact

    Science.gov (United States)

    Vellekoop, J.; Sluijs, A.; Smit, J.; Schouten, S.; Sinninghe Damsté, J. S.; Brinkhuis, H.

    2012-12-01

    The Cretaceous/Paleogene (K/Pg) boundary, ~65.5 Ma, marks a mass-extinction event related the impact of a large asteroid on the Yucatan peninsula, Mexico. Model scenarios predict that the explosive injection of dust and sulfate aerosols into the stratosphere blocked incoming solar radiation, resulting in a cooling pulse of months to several decades, a so-called 'impact winter', but thus far, proxy records lack sufficient resolution to evaluate this hypothesis. We report on a major, short-lived drop in sea surface temperatures (SSTs) recorded in an unusually well preserved and stratigraphically expanded K/Pg boundary site in Texas, USA, based on TEX86 paleothermometry. Critically, the cooling directly post-dates impact-related tsunami deposits, and coincides with the deposition of extraterrestrial iridium representing aerosol fall out, restricting the age of the cooling to the first months to decades after impact. We interpret this cooling to reflect the first direct evidence for the "impact winter" at the K/Pg boundary. The combination of darkness and cooling must have been a key contributory element in the extinctions of many biological clades, including the dinosaurs, flying reptiles and marine reptiles.

  4. "Should I or shouldn't I?" Imitation of undesired versus allowed actions from peer and adult models by 18- and 24-month-old toddlers.

    Science.gov (United States)

    Seehagen, Sabine; Schneider, Silvia; Miebach, Kristin; Frigge, Katharina; Zmyj, Norbert

    2017-11-01

    Imitation is a common way of acquiring novel behaviors in toddlers. However, little is known about toddlers' imitation of undesired actions. Here we investigated 18- and 24-month-olds' (N=110) imitation of undesired and allowed actions from televised peer and adult models. Permissiveness of the demonstrated actions was indicated by the experimenter's response to their execution (angry or neutral). Analyses revealed that toddlers' imitation scores were higher after demonstrations of allowed versus undesired actions, regardless of the age of the model. In agreement with prior research, these results suggest that third-party reactions to a model's actions can be a powerful cue for toddlers to engage in or refrain from imitation. In the context of the present study, third-party reactions were more influential on imitation than the model's age. Considering the relative influence of different social cues for imitation can help to gain a fuller understanding of early observational learning. Copyright © 2017 Elsevier Inc. All rights reserved.

  5. On the Origins of Disorganized Attachment and Internal Working Models: Paper II. An Empirical Microanalysis of 4-Month Mother-Infant Interaction

    Science.gov (United States)

    Beebe, Beatrice; Lachmann, Frank; Markese, Sara; Buck, Karen A.; Bahrick, Lorraine E.; Chen, Henian; Cohen, Patricia; Andrews, Howard; Feldstein, Stanley; Jaffe, Joseph

    2012-01-01

    A microanalysis of 4-month mother-infant face-to-face communication predicted 12-month infant disorganized (vs. secure) attachment outcomes in an urban community sample. We documented a dyadic systems view of the roles of both partners, the roles of both self- and interactive contingency, and the importance of attention, orientation and touch, and as well as facial and vocal affect, in the co-construction of attachment disorganization. The analysis of different communication modalities identified striking intrapersonal and interpersonal intermodal discordance or conflict, in the context of intensely distressed infants, as the central feature of future disorganized dyads at 4 months. Lowered maternal contingent coordination, and failures of maternal affective correspondence, constituted maternal emotional withdrawal from distressed infants. This maternal withdrawal compromises infant interactive agency and emotional coherence. We characterize of the nature of emerging internal working models of future disorganized infants as follows: Future disorganized infants represent states of not being sensed and known by their mothers, particularly in moments of distress; they represent confusion about both their own and their mothers’ basic emotional organization, and about their mothers’ response to their distress. This internal working model sets a trajectory in development which may disturb the fundamental integration of the person. The remarkable specificity of our findings has the potential to lead to more finely-focused clinical interventions. PMID:23066334

  6. Hibernation in an antarctic fish: on ice for winter.

    Directory of Open Access Journals (Sweden)

    Hamish A Campbell

    Full Text Available Active metabolic suppression in anticipation of winter conditions has been demonstrated in species of mammals, birds, reptiles and amphibians, but not fish. This is because the reduction in metabolic rate in fish is directly proportional to the decrease in water temperature and they appear to be incapable of further suppressing their metabolic rate independently of temperature. However, the Antarctic fish (Notothenia coriiceps is unusual because it undergoes winter metabolic suppression irrespective of water temperature. We assessed the seasonal ecological strategy by monitoring swimming activity, growth, feeding and heart rate (f(H in N. coriiceps as they free-ranged within sub-zero waters. The metabolic rate of wild fish was extrapolated from f(H recordings, from oxygen consumption calibrations established in the laboratory prior to fish release. Throughout the summer months N. coriiceps spent a considerable proportion of its time foraging, resulting in a growth rate (G(w of 0.18 +/- 0.2% day(-1. In contrast, during winter much of the time was spent sedentary within a refuge and fish showed a net loss in G(w (-0.05 +/- 0.05% day(-1. Whilst inactive during winter, N. coriiceps displayed a very low f(H, reduced sensory and motor capabilities, and standard metabolic rate was one third lower than in summer. In a similar manner to other hibernating species, dormancy was interrupted with periodic arousals. These arousals, which lasted a few hours, occurred every 4-12 days. During arousal activity, f(H and metabolism increased to summer levels. This endogenous suppression and activation of metabolic processes, independent of body temperature, demonstrates that N. coriiceps were effectively 'putting themselves on ice' during winter months until food resources improved. This study demonstrates that at least some fish species can enter a dormant state similar to hibernation that is not temperature driven and presumably provides seasonal energetic

  7. Assessment of the APCC Coupled MME Suite in Predicting the Distinctive Climate Impacts of Two Flavors of ENSO during Boreal Winter

    Science.gov (United States)

    Jeong, Hye-In; Lee, Doo Young; Karumuri, Ashok; Ahn, Joong-Bae; Lee, June-Yi; Luo, Jing-Jia; Schemm, Jae-Kyung E.; Hendon, Harry H.; Braganza, Karl; Ham, Yoo-Geun

    2012-01-01

    Forecast skill of the APEC Climate Center (APCC) Multi-Model Ensemble (MME) seasonal forecast system in predicting two main types of El Nino-Southern Oscillation (ENSO), namely canonical (or cold tongue) and Modoki ENSO, and their regional climate impacts is assessed for boreal winter. The APCC MME is constructed by simple composite of ensemble forecasts from five independent coupled ocean-atmosphere climate models. Based on a hindcast set targeting boreal winter prediction for the period 19822004, we show that the MME can predict and discern the important differences in the patterns of tropical Pacific sea surface temperature anomaly between the canonical and Modoki ENSO one and four month ahead. Importantly, the four month lead MME beats the persistent forecast. The MME reasonably predicts the distinct impacts of the canonical ENSO, including the strong winter monsoon rainfall over East Asia, the below normal rainfall and above normal temperature over Australia, the anomalously wet conditions across the south and cold conditions over the whole area of USA, and the anomalously dry conditions over South America. However, there are some limitations in capturing its regional impacts, especially, over Australasia and tropical South America at a lead time of one and four months. Nonetheless, forecast skills for rainfall and temperature over East Asia and North America during ENSO Modoki are comparable to or slightly higher than those during canonical ENSO events.

  8. Report 3 energy market barometer - Winter 2014

    International Nuclear Information System (INIS)

    Schleich, Joachim; Cateura, Olivier; Faure, Corinne; Jacob, Jojo; Javaudin, Laurent; Molecke, Greg; Olsthoorn, Mark; Pinkse, Jonatan; Shomali, Azadeh; Vernay, Anne-Lorene

    2015-01-01

    This Winter 2014 edition of the Grenoble Ecole de Management (GEM) Energy Market Barometer documents the French energy experts' estimates of the future electricity mix in France and in the European Union, their assessment of the regulatory conditions in France for investments in energy technologies, and their expectations about the development of energy and CO_2-certificate prices. Key findings: - Fewer than one in four experts believes that the target to decrease nuclear power's share of the French power mix to 50% by 2025 will be met; - The share of renewable energy sources (other than hydropower) in the French power mix is expected to almost quadruple by 2030; - Renewable energy sources (other than hydropower) are believed to become the dominating source of electricity in the EU in 2030; - About two thirds of the experts think that current regulatory conditions in France are particularly accommodating for investments in energy efficiency and renewable energies; - Experts are divided over how supportive current and future regulatory conditions are for encouraging investments in nuclear power in France; - Electricity prices are expected to remain stable over the next six months but to increase over the next 5 years; - Oil prices are expected to continue to decrease over the next six month, but increase over the next 5 years; - CO_2 certificate prices are expected to rise only in the medium to longer term but levels remain rather low

  9. Development of a predictive model for 6 month survival in patients with venous thromboembolism and solid malignancy requiring IVC filter placement.

    Science.gov (United States)

    Huang, Steven Y; Odisio, Bruno C; Sabir, Sharjeel H; Ensor, Joe E; Niekamp, Andrew S; Huynh, Tam T; Kroll, Michael; Gupta, Sanjay

    2017-07-01

    Our purpose was to develop a predictive model for short-term survival (i.e. filter placement in patients with venous thromboembolism (VTE) and solid malignancy. Clinical and laboratory parameters were retrospectively reviewed for patients with solid malignancy who received a filter between January 2009 and December 2011 at a tertiary care cancer center. Multivariate Cox proportional hazards modeling was used to assess variables associated with 6 month survival following filter placement in patients with VTE and solid malignancy. Significant variables were used to generate a predictive model. 397 patients with solid malignancy received a filter during the study period. Three variables were associated with 6 month survival: (1) serum albumin [hazard ratio (HR) 0.496, P filter placement can be predicted from three patient variables. Our predictive model could be used to help physicians decide whether a permanent or retrievable filter may be more appropriate as well as to assess the risks and benefits for filter retrieval within the context of survival longevity in patients with cancer.

  10. Inertia gravity waves in the upper troposphere during the MaCWAVE winter campaign. Part II. Radar investigations and modelling studies

    Energy Technology Data Exchange (ETDEWEB)

    Serafimovich, A.; Zuelicke, C.; Hoffmann, P.; Peters, D.; Singer, W. [Leibniz-Inst. fuer Atmosphaerenphysik, Kuehlungsborn (Germany); Dalin, P. [Swedish Inst. of Space Physics, Kiruna (Sweden)

    2006-07-01

    We present an experimental and modelling study of a strong gravity wave event in the upper troposphere/lower stratosphere near the Scandinavian mountain ridge. Continuous VHP radar measurements during the MaCWAVE rocket and ground-based measurement campaign were performed at the Norwegian Andoya rocket range (ARR) near Andenes (69.3 N, 16 E) in January 2003. Detailed gravity wave investigations based on PSU/NCAR fifth-generation mesoscale model (MM5) data have been used for comparison with experimentally obtained results. The model data show the presence of a mountain wave and of an inertia gravity wave generated by a jet streak near the tropopause region. Temporal and spatial dependencies of jet induced inertia gravity waves with dominant observed periods of about 13 h and vertical wavelengths of {proportional_to}4.5-5 km are investigated with wavelet transform applied on radar measurements and model data. The jet induced wave packet is observed to move upstream and downward in the upper troposphere. The model data agree with the experimentally obtained results fairly well. Possible reasons for the observed differences, e.g. in the time of maximum of the wave activity, are discussed. Finally, the vertical fluxes of horizontal momentum are estimated with different methods and provide similar amplitudes. We found indications that the derived positive vertical flux of the horizontal momentum corresponds to the obtained parameters of the jet-induced inertia gravity wave, but only at the periods and heights of the strongest wave activity. (orig.)

  11. Communicating Certainty About Nuclear Winter

    Science.gov (United States)

    Robock, A.

    2013-12-01

    I have been spending much of my time in the past several years trying to warn the world about the continuing danger of nuclear weapons, and that the solution is a rapid reduction in the nuclear arsenal. I feel that a scientist who discovers dangers to society has an ethical duty to issue a warning, even if the danger is so scary that it is hard for people to deal with. The debate about nuclear winter in the 1980s helped to end the nuclear arms race, but the planet still has enough nuclear weapons, even after reductions planned for 2017 under the New START treaty, to produce nuclear winter, with temperatures plunging below freezing in the summer in major agricultural regions, threatening the food supply for most of the planet. New research by myself, Brian Toon, Mike Mills, and colleagues over the past six years has found that a nuclear war between any two countries, such as India and Pakistan, using 50 atom bombs each of the size dropped on Hiroshima could produce climate change unprecedented in recorded human history, and a world food crisis because of the agricultural effects. This is much less than 1% of the current global arsenal. Communicating certainty - what we know for sure - has been much more effective than communicating uncertainty. The limited success I have had has come from persistence and serendipity. The first step was to do the science. We have published peer-reviewed articles in major journals, including Science, Nature, Proceedings of the National Academy of Sciences, Journal of Geophysical Research, Atmospheric Chemistry and Physics, Physics Today, and Climatic Change. But policymakers do not read these journals. Through fairly convoluted circumstances, which will be described in this talk, we were able to get papers published in Scientific American and the Bulletin of Atomic Scientists. I have also published several encyclopedia articles on the subject. As a Lead Author of Chapter 8 (Radiative Forcing) of the recently published Fifth Assessment

  12. An optimized data fusion method and its application to improve lateral boundary conditions in winter for Pearl River Delta regional PM2.5 modeling, China

    Science.gov (United States)

    Huang, Zhijiong; Hu, Yongtao; Zheng, Junyu; Zhai, Xinxin; Huang, Ran

    2018-05-01

    Lateral boundary conditions (LBCs) are essential for chemical transport models to simulate regional transport; however they often contain large uncertainties. This study proposes an optimized data fusion approach to reduce the bias of LBCs by fusing gridded model outputs, from which the daughter domain's LBCs are derived, with ground-level measurements. The optimized data fusion approach follows the framework of a previous interpolation-based fusion method but improves it by using a bias kriging method to correct the spatial bias in gridded model outputs. Cross-validation shows that the optimized approach better estimates fused fields in areas with a large number of observations compared to the previous interpolation-based method. The optimized approach was applied to correct LBCs of PM2.5 concentrations for simulations in the Pearl River Delta (PRD) region as a case study. Evaluations show that the LBCs corrected by data fusion improve in-domain PM2.5 simulations in terms of the magnitude and temporal variance. Correlation increases by 0.13-0.18 and fractional bias (FB) decreases by approximately 3%-15%. This study demonstrates the feasibility of applying data fusion to improve regional air quality modeling.

  13. Modeling the long-term effect of winter cover crops on nitrate transport in artificially drained fields across the Midwest U.S.

    Science.gov (United States)

    A fall-planted cover crop is a management practice with multiple benefits including reducing nitrate losses from artificially drained fields. We used the Root Zone Water Quality Model (RZWQM) to simulate the impact of a cereal rye cover crop on reducing nitrate losses from drained fields across five...

  14. Bayesian hierarchical modelling of continuous non-negative longitudinal data with a spike at zero: An application to a study of birds visiting gardens in winter.

    Science.gov (United States)

    Swallow, Ben; Buckland, Stephen T; King, Ruth; Toms, Mike P

    2016-03-01

    The development of methods for dealing with continuous data with a spike at zero has lagged behind those for overdispersed or zero-inflated count data. We consider longitudinal ecological data corresponding to an annual average of 26 weekly maximum counts of birds, and are hence effectively continuous, bounded below by zero but also with a discrete mass at zero. We develop a Bayesian hierarchical Tweedie regression model that can directly accommodate the excess number of zeros common to this type of data, whilst accounting for both spatial and temporal correlation. Implementation of the model is conducted in a Markov chain Monte Carlo (MCMC) framework, using reversible jump MCMC to explore uncertainty across both parameter and model spaces. This regression modelling framework is very flexible and removes the need to make strong assumptions about mean-variance relationships a priori. It can also directly account for the spike at zero, whilst being easily applicable to other types of data and other model formulations. Whilst a correlative study such as this cannot prove causation, our results suggest that an increase in an avian predator may have led to an overall decrease in the number of one of its prey species visiting garden feeding stations in the United Kingdom. This may reflect a change in behaviour of house sparrows to avoid feeding stations frequented by sparrowhawks, or a reduction in house sparrow population size as a result of sparrowhawk increase. © 2015 The Author. Biometrical Journal published by WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  15. Inertia gravity waves in the upper troposphere during the MaCWAVE winter campaign – Part II: Radar investigations and modelling studies

    Directory of Open Access Journals (Sweden)

    A. Serafimovich

    2006-11-01

    Full Text Available We present an experimental and modelling study of a strong gravity wave event in the upper troposphere/lower stratosphere near the Scandinavian mountain ridge. Continuous VHF radar measurements during the MaCWAVE rocket and ground-based measurement campaign were performed at the Norwegian Andoya Rocket Range (ARR near Andenes (69.3° N, 16° E in January 2003. Detailed gravity wave investigations based on PSU/NCAR Fifth-Generation Mesoscale Model (MM5 data have been used for comparison with experimentally obtained results. The model data show the presence of a mountain wave and of an inertia gravity wave generated by a jet streak near the tropopause region. Temporal and spatial dependencies of jet induced inertia gravity waves with dominant observed periods of about 13 h and vertical wavelengths of ~4.5–5 km are investigated with wavelet transform applied on radar measurements and model data. The jet induced wave packet is observed to move upstream and downward in the upper troposphere. The model data agree with the experimentally obtained results fairly well. Possible reasons for the observed differences, e.g. in the time of maximum of the wave activity, are discussed. Finally, the vertical fluxes of horizontal momentum are estimated with different methods and provide similar amplitudes. We found indications that the derived positive vertical flux of the horizontal momentum corresponds to the obtained parameters of the jet-induced inertia gravity wave, but only at the periods and heights of the strongest wave activity.

  16. A modeling study of the thermosphere-ionosphere interactions during the boreal winter and spring 2015-2016: Tidal and planetary-scale waves effect on the ionospheric structure.

    Science.gov (United States)

    Sassi, F.; McDonald, S. E.; McCormack, J. P.; Tate, J.; Liu, H.; Kuhl, D.

    2017-12-01

    The 2015-2016 boreal winter and spring is a dynamically very interesting time in the lower atmosphere: a minor high latitude stratospheric warming occurred in February 2016; an interrupted descent of the QBO was found in the tropical stratosphere; and a large warm ENSO took place in the tropical Pacific Ocean. The stratospheric warming, the QBO and ENSO are known to affect in different ways the meteorology of the upper atmosphere in different ways: low latitude solar tides and high latitude planetary-scale waves have potentially important implications on the structure of the ionosphere. In this study, we use global atmospheric analyses from a high-altitude version of the High-Altitude Navy Global Environmental Model (HA-NAVGEM) to constrain the meteorology of numerical simulations of the Specified Dynamics Whole Atmosphere Community Climate Model, extended version (SD-WACCM-X). We describe the large-scale behavior of tropical tides and mid-latitude planetary waves that emerge in the lower thermosphere. The effect on the ionosphere is captured by numerical simulations of the Navy Highly Integrated Thermosphere Ionosphere Demonstration System (Navy-HITIDES) that uses the meteorology generated by SD-WACCM-X to drive ionospheric simulations during this time period. We will analyze the impact of various dynamical fields on the zonal behavior of the ionosphere by selectively filtering the relevant dynamical modes.

  17. Comparison of Selected Morphological, Rheological and Biochemical Parameters of Winter Swimmers' Blood at the End of One Winter Swimming Season and at the Beginning of Another.

    Science.gov (United States)

    Teległów, Aneta; Marchewka, Jakub; Tabarowski, Zbigniew; Rembiasz, Konrad; Głodzik, Jacek; Scisłowska-Czarnecka, Anna

    2015-01-01

    The aim of the study was to examine potential differences in the morphological, rheological and biochemical blood parameters of winter swimmers who remained physically active during the period between the end of one winter swimming season and the beginning of another. The study included a group of healthy winter swimmers (n = 17, all between 30 and 60 years of age). Six months following the end of winter season, the levels of mean corpuscular hemoglobin concentration and mean corpuscular hemoglobin turned out to be significantly higher, while erythrocyte count and hematocrit level significantly lower than at the baseline. Moreover, the break in winter swimming was reflected by a significant increase in median erythrocyte elongation index at all shear stress levels ≥ 1.13 Pa. The only significant changes in biochemical parameters of the blood pertained to an increase in the concentration of transferrin and to a decrease in the total protein, albumin and beta-1 globulin concentrations. Seasonal effort of winter swimmers between the end of one winter swimming season and the beginning of another has a positive influence on morphological, rheological and biochemical blood parameters.

  18. Six-monthly appointment spacing for clinical visits as a model for retention in HIV Care in Conakry-Guinea: a cohort study.

    Science.gov (United States)

    Bekolo, Cavin Epie; Diallo, Abdourahimi; Philips, Mit; Yuma, Joseph-Desire; Di Stefano, Letizia; Drèze, Stéphanie; Mouton, Jerome; Koita, Youssouf; Tiomtore, Ousseni W

    2017-12-13

    The outbreak of the Ebola virus disease (EVD) in 2014 led to massive dropouts in HIV care in Guinea. Meanwhile, Médecins Sans Frontières (MSF) was implementing a six-monthly appointment spacing approach adapted locally as Rendez-vous de Six Mois (R6M) with an objective to improve retention in care. We sought to evaluate this innovative model of ART delivery in circumstances where access to healthcare is restricted. A retrospective cohort study in 2014 of the outcome of a group of stable patients (viral load ≤1000 copies/μl) enrolled voluntarily in R6M compared with a group of stable patients continuing standard one to three monthly visits in Conakry. Log-rank test and Cox proportional hazards model were used to compare rates of attrition (deaths and defaulters) from care between the two groups. A linear regression analysis was used to describe the trend or pattern in the number of clinical visits over time. Included were 1957 adults of 15 years old and above of whom 1166 (59.6%) were enrolled in the R6M group and 791 (40.4%) in the standard care group. The proportion remaining in care at 18 months and beyond was 90% in the R6M group; significantly higher than the 75% observed in the control group (p Conakry despite restricted access to healthcare caused by the devastating EVD on the health system in Guinea. R6M could be rolled out as the model of care for stable patients where and when feasible as a strategy likely to improve retention in HIV care.

  19. Sensitivity of crop yield and N losses in winter wheat to changes in mean and variability of temperature and precipitation in Denmark using the FASSET model

    DEFF Research Database (Denmark)

    Patil, Raveendra Hanumantagoud; Lægdsmand, Mette; Olesen, Jørgen Eivind

    2012-01-01

    Sensitivity of wheat yield and soil nitrogen (N) losses to stepwise changes in means and variances of climatic variables were determined using the FASSET model. The LARS-WG was used to generate climate scenarios using observed climate data (1961–90) from two sites in Denmark, which differed...... loam. This study illustrates the importance of considering effects of changes to mean climatic factors, climatic variability and soil types on both crop yield and soil N losses....

  20. Modes of interannual variability in northern hemisphere winter atmospheric circulation in CMIP5 models: evaluation, projection and role of external forcing

    Science.gov (United States)

    Frederiksen, Carsten S.; Ying, Kairan; Grainger, Simon; Zheng, Xiaogu

    2018-04-01

    Models from the coupled model intercomparison project phase 5 (CMIP5) dataset are evaluated for their ability to simulate the dominant slow modes of interannual variability in the Northern Hemisphere atmospheric circulation 500 hPa geopotential height in the twentieth century. A multi-model ensemble of the best 13 models has then been used to identify the leading modes of interannual variability in components related to (1) intraseasonal processes; (2) slowly-varying internal dynamics; and (3) the slowly-varying response to external changes in radiative forcing. Modes in the intraseasonal component are related to intraseasonal variability in the North Atlantic, North Pacific and North American, and Eurasian regions and are little affected by the larger radiative forcing of the Representative Concentration Pathways 8.5 (RCP8.5) scenario. The leading modes in the slow-internal component are related to the El Niño-Southern Oscillation, Pacific North American or Tropical Northern Hemisphere teleconnection, the North Atlantic Oscillation, and the Western Pacific teleconnection pattern. While the structure of these slow-internal modes is little affected by the larger radiative forcing of the RCP8.5 scenario, their explained variance increases in the warmer climate. The leading mode in the slow-external component has a significant trend and is shown to be related predominantly to the climate change trend in the well mixed greenhouse gas concentration during the historical period. This mode is associated with increasing height in the 500 hPa pressure level. A secondary influence on this mode is the radiative forcing due to stratospheric aerosols associated with volcanic eruptions. The second slow-external mode is shown to be also related to radiative forcing due to stratospheric aerosols. Under RCP8.5 there is only one slow-external mode related to greenhouse gas forcing with a trend over four times the historical trend.

  1. Reduction of net primary productivity in southern China caused by abnormal low-temperature freezing in winter of 2008 detected by a remote sensing-driven ecosystem model

    Science.gov (United States)

    Ju, W.; Liu, Y.; Zhou, Y.; Zhu, G.

    2011-12-01

    Terrestrial carbon cycle is an important determinant of global climate change and affected by various factors, including climate, CO2 concentration, atmospheric nitrogen deposition and human activities. Extreme weather events can significantly regulate short-term even long-term carbon exchanges between terrestrial ecosystems and the atmosphere. During the period from the middle January to the middle February 2008, Southern China was seriously hit by abnormal low-temperature freezing, which caused serous damages to forests and crops. However, the reduction of net primary productivity (NPP) of terrestrial ecosystems caused by this extremely abnormal weather event has not been quantitatively investigated. In this study, the Boreal Ecosystem Productivity Simulator (BEPS) model was employed to assess the reduction of NPP in Southern China caused by the abnormal low-temperature freezing. Prior to the regional simulation, the BEPS model was validated using measured NPP in different ecosystems, demonstrating the ability of this model to simulate NPP reliably in China. Then, it was forced using meteorological data interpolated from observations of weather stations and leaf area index inversed from MODIS reflectance data to simulate national wide NPP at a 500 m resolution for the period from 2003 to 2008. The departures of NPP in 2008 from the means during 2003-2007 were used as the indicator of NPP reduction caused by the low-temperature freezing. It was found out that NPP in 2008 decreased significantly in forests of Southern China, especially in Guangdong, Fujian, Zhejiang, Guangxi, Jiangxi, and Hunan Provinces, in which the low-temperature freeing was more serious. The annul reduction of NPP was above 150 g C/m^2/yr in these areas. Key words: Net Primary Productivity, low-temperature freezing, BEPS model, MODIS Correspondence author: Weimin Ju Email:juweimin@nju.edu.cn

  2. Energy balance of a sparse coniferous high-latitude forest under winter conditions

    DEFF Research Database (Denmark)

    Gryning, Sven-Erik; Batchvarova, E.; Bruin, H.A.R. de

    2001-01-01

    was simulated for a three month period. For conditions with a cloud cover of less than 7 oktas good agreement between model predictions and measurements were found. For cloud cover 7 and 8 oktas a considerable spread can be observed. To apply the proposed energy balance model, the global radiation must......Measurements carried out in Northern Finland on radiation and turbulent fluxes over a sparse, sub-arctic boreal forest with snow covered ground were analysed. The measurements represent late winter conditions characterised by low solar elevation angles. During the experiment (12-24 March 1997) day...... and night were about equally long. At low solar elevation angles the forest shades most of the snow surface. Therefore an important part of the radiation never reaches the snow surface but is absorbed by the forest. The sensible heat flux above the forest was fairly large, reaching more than 100 W m(-2...

  3. Winter distribution of Calanus finmarchicus in the Northeast Atlantic

    DEFF Research Database (Denmark)

    Heath, M.R.; Fraser, J.G.; Gislason, A.

    2000-01-01

    Data from plankton sampling and Optical Plankton Counter deployments during six cruises between December of 1994 and 1999 have been used to derive a composite three-dimensional distribution of the abundance of Calanus finmarchicus during winter (December-January) in the Norwegian Sea and Northeast...... Northeast Atlantic, the concentration of wintering animals is around 30% of that in the Norwegian Sea and the vertical distribution is more diffuse and on average deeper. Modelling studies have shown that the overwinter distribution and transport are key factors determining the spatial persistence of C...

  4. The long-term effect of climate change on productivity of winter wheat in Denmark: a scenario analysis using three crop models

    DEFF Research Database (Denmark)

    Öztürk, Isik; Sharif, Behzad; Baby, Sanmohan

    2017-01-01

    ) A1B emission scenario for the 21st century using three process-based models; A 20-year set (1991–2010) of observed daily climate data from Aarslev, Denmark was used to form the baseline, from which the RCM data were generated. The simulation of crop growth was performed with increasing carbon...... dioxide (CO2) levels and under continuous mono-cropping system at different N input rates. Results indicated that grain yield and grain N will be reduced in the future despite increased CO2 concentration in the atmosphere. While the increased N input may increase yield, it will not increase grain N...

  5. The impact of winter heating on air pollution in China.

    Science.gov (United States)

    Xiao, Qingyang; Ma, Zongwei; Li, Shenshen; Liu, Yang

    2015-01-01

    Fossil-fuel combustion related winter heating has become a major air quality and public health concern in northern China recently. We analyzed the impact of winter heating on aerosol loadings over China using the MODIS-Aqua Collection 6 aerosol product from 2004-2012. Absolute humidity (AH) and planetary boundary layer height (PBL) -adjusted aerosol optical depth (AOD*) was constructed to reflect ground-level PM2.5 concentrations. GIS analysis, standard statistical tests, and statistical modeling indicate that winter heating is an important factor causing increased PM2.5 levels in more than three-quarters of central and eastern China. The heating season AOD* was more than five times higher as the non-heating season AOD*, and the increase in AOD* in the heating areas was greater than in the non-heating areas. Finally, central heating tend to contribute less to air pollution relative to other means of household heating.

  6. Winter therapy for the accelerators

    CERN Multimedia

    Corinne Pralavorio

    2016-01-01

    Hundreds of people are hard at work during the year-end technical stop as all the accelerators are undergoing maintenance, renovation and upgrade operations in parallel.   The new beam absorber on its way to Point 2 before being lowered into the LHC tunnel for installation. The accelerator teams didn’t waste any time before starting their annual winter rejuvenation programme over the winter. At the end of November, as the LHC ion run was beginning, work got under way on the PS Booster, where operation had already stopped. On 14 December, once the whole complex had been shut down, the technical teams turned their attention to the other injectors and the LHC. The year-end technical stop (YETS) provides an opportunity to carry out maintenance work on equipment and repair any damage as well as to upgrade the machines for the upcoming runs. Numerous work projects are carried out simultaneously, so good coordination is crucial. Marzia Bernardini's team in the Enginee...

  7. Arctic lake physical processes and regimes with implications for winter water availability and management in the national petroleum reserve alaska

    Science.gov (United States)

    Jones, Benjamin M.; Arp, C.D.; Hinkel, Kenneth M.; Beck, R.A.; Schmutz, J.A.; Winston, B.

    2009-01-01

    Lakes are dominant landforms in the National Petroleum Reserve Alaska (NPRA) as well as important social and ecological resources. Of recent importance is the management of these freshwater ecosystems because lakes deeper than maximum ice thickness provide an important and often sole source of liquid water for aquatic biota, villages, and industry during winter. To better understand seasonal and annual hydrodynamics in the context of lake morphometry, we analyzed lakes in two adjacent areas where winter water use is expected to increase in the near future because of industrial expansion. Landsat Thematic Mapper and Enhanced Thematic Mapper Plus imagery acquired between 1985 and 2007 were analyzed and compared with climate data to understand interannual variability. Measured changes in lake area extent varied by 0.6% and were significantly correlated to total precipitation in the preceding 12 months (p modeled lake area extent from 1985 to 2007 showed no long-term trends. In addition, high-resolution aerial photography, bathymetric surveys, water-level monitoring, and lake-ice thickness measurements and growth models were used to better understand seasonal hydrodynamics, surface area-to-volume relations, winter water availability, and more permanent changes related to geomorphic change. Together, these results describe how lakes vary seasonally and annually in two critical areas of the NPRA and provide simple models to help better predict variation in lake-water supply. Our findings suggest that both overestimation and underestimation of actual available winter water volume may occur regularly, and this understanding may help better inform management strategies as future resource use expands in the NPRA. ?? 2008 Springer Science+Business Media, LLC.

  8. Investigation of market efficiency and Financial Stability between S&P 500 and London Stock Exchange: Monthly and yearly Forecasting of Time Series Stock Returns using ARMA model

    Science.gov (United States)

    Rounaghi, Mohammad Mahdi; Nassir Zadeh, Farzaneh

    2016-08-01

    We investigated the presence and changes in, long memory features in the returns and volatility dynamics of S&P 500 and London Stock Exchange using ARMA model. Recently, multifractal analysis has been evolved as an important way to explain the complexity of financial markets which can hardly be described by linear methods of efficient market theory. In financial markets, the weak form of the efficient market hypothesis implies that price returns are serially uncorrelated sequences. In other words, prices should follow a random walk behavior. The random walk hypothesis is evaluated against alternatives accommodating either unifractality or multifractality. Several studies find that the return volatility of stocks tends to exhibit long-range dependence, heavy tails, and clustering. Because stochastic processes with self-similarity possess long-range dependence and heavy tails, it has been suggested that self-similar processes be employed to capture these characteristics in return volatility modeling. The present study applies monthly and yearly forecasting of Time Series Stock Returns in S&P 500 and London Stock Exchange using ARMA model. The statistical analysis of S&P 500 shows that the ARMA model for S&P 500 outperforms the London stock exchange and it is capable for predicting medium or long horizons using real known values. The statistical analysis in London Stock Exchange shows that the ARMA model for monthly stock returns outperforms the yearly. ​A comparison between S&P 500 and London Stock Exchange shows that both markets are efficient and have Financial Stability during periods of boom and bust.

  9. Seasonal variation in orthopedic health services utilization in Switzerland: the impact of winter sport tourism.

    Science.gov (United States)

    Matter-Walstra, Klazien; Widmer, Marcel; Busato, André

    2006-03-03

    Climate- or holiday-related seasonality in hospital admission rates is well known for many diseases. However, little research has addressed the impact of tourism on seasonality in admission rates. We therefore investigated the influence of tourism on emergency admission rates in Switzerland, where winter and summer leisure sport activities in large mountain regions can generate orthopedic injuries. Using small area analysis, orthopedic hospital service areas (HSAo) were evaluated for seasonality in emergency admission rates. Winter sport areas were defined using guest bed accommodation rate patterns of guest houses and hotels located above 1000 meters altitude that show clear winter and summer peak seasons. Emergency admissions (years 2000-2002, n = 135'460) of local and nonlocal HSAo residents were evaluated. HSAo were grouped according to their area type (regular or winter sport area) and monthly analyses of admission rates were performed. Of HSAo within the defined winter sport areas 70.8% show a seasonal, summer-winter peak hospital admission rate pattern and only 1 HSAo outside the defined winter sport areas shows such a pattern. Seasonal hospital admission rates in HSAo in winter sport areas can be up to 4 times higher in winter than the intermediate seasons, and they are almost entirely due to admissions of nonlocal residents. These nonlocal residents are in general -and especially in winter- younger than local residents, and nonlocal residents have a shorter length of stay in winter sport than in regular areas. The overall geographic distribution of nonlocal residents admitted for emergencies shows highest rates during the winter as well as the summer in the winter sport areas. Small area analysis using orthopedic hospital service areas is a reliable method for the evaluation of seasonality in hospital admission rates. In Switzerland, HSAo defined as winter sport areas show a clear seasonal fluctuation in admission rates of only nonlocal residents, whereas

  10. Model to Estimate Monthly Time Horizons for Application of DEA in Selection of Stock Portfolio and for Maintenance of the Selected Portfolio

    Directory of Open Access Journals (Sweden)

    José Claudio Isaias

    2015-01-01

    Full Text Available In the selecting of stock portfolios, one type of analysis that has shown good results is Data Envelopment Analysis (DEA. It, however, has been shown to have gaps regarding its estimates of monthly time horizons of data collection for the selection of stock portfolios and of monthly time horizons for the maintenance of a selected portfolio. To better estimate these horizons, this study proposes a model of mathematical programming binary of minimization of square errors. This model is the paper’s main contribution. The model’s results are validated by simulating the estimated annual return indexes of a portfolio that uses both horizons estimated and of other portfolios that do not use these horizons. The simulation shows that portfolios with both horizons estimated have higher indexes, on average 6.99% per year. The hypothesis tests confirm the statistically significant superiority of the results of the proposed mathematical model’s indexes. The model’s indexes are also compared with portfolios that use just one of the horizons estimated; here the indexes of the dual-horizon portfolios outperform the single-horizon portfolios, though with a decrease in percentage of statistically significant superiority.

  11. Exceptional Arctic warmth of early winter 2016 and attribution to global warming

    Science.gov (United States)

    van Oldenborgh, Geert Jan; Macias-Fauria, Marc; King, Andrew; Uhe, Peter; Philip, Sjoukje; Kew, Sarah; Karoly, David; Otto, Friederike; Allen, Myles; Cullen, Heidi

    2017-04-01

    The dark polar winters usually sport the coldest extremes on Earth, however this winter, the North Pole and the surrounding Arctic region have experienced record high temperatures in November and December, with daily means reaching 15 °C (27 °F) above normal and a November monthly mean that was 13 °C (23 °F) above normal on the pole. November also saw a brief retreat of sea-ice that was virtually unprecedented in nearly 40 years of satellite records, followed by a record low in November sea ice area since 1850. Unlike the Antarctic, Arctic lands are inhabited and their socio-economic systems are greatly affected by the impacts of extreme and unprecedented sea ice dynamics and temperatures, such as for example, the timing of marine mammal migrations, and refreezing rain on snow that prevents reindeer from feeding. Here we report on our multi-method rapid attribution analysis of North Pole November-December temperatures. To quantify the rarity of the event, we computed the November-December averaged temperature around the North Pole (80-90 °N) in the (short but North-pole covering) ERA-interim reanalysis. To put the event in context of natural variability, we use a longer and closely related time series based on the northern most meteorological observations on land (70-80 °N). This allows for a reconstruction of Arctic temperatures back to about 1900. We also perform a multi-method analysis of North Pole temperatures with two sets of climate models: the CMIP5 multi-model ensemble, and a large ensemble of model runs in the so-called Weather@Home project. Physical mechanisms that are responsible for temperature and sea ice variability in the North Pole region are also discussed. The observations and the bias-corrected CMIP5 ensemble point to a return period of about 50 to 200 years in the present climate, i.e., the probability of such an extreme is about 0.5% to 2% every year, with a large uncertainty. The observations show that November-December temperatures

  12. D:L-Amino Acid Modeling Reveals Fast Microbial Turnover of Days to Months in the Subsurface Hydrothermal Sediment of Guaymas Basin.

    Science.gov (United States)

    Møller, Mikkel H; Glombitza, Clemens; Lever, Mark A; Deng, Longhui; Morono, Yuki; Inagaki, Fumio; Doll, Mechthild; Su, Chin-Chia; Lomstein, Bente A

    2018-01-01

    We investigated the impact of temperature on the microbial turnover of organic matter (OM) in a hydrothermal vent system in Guaymas Basin, by calculating microbial bio- and necromass turnover times based on the culture-independent D:L-amino acid model. Sediments were recovered from two stations near hydrothermal mounds (community of microorganisms in the hydrothermal sediment demonstrated short turnover times. The modeled turnover times of microbial bio- and necromass in the hydrothermal sediments were notably faster (biomass: days to months; necromass: up to a few hundred years) than in the cold sediments (biomass: tens of years; necromass: thousands of years), suggesting that temperature has a significant influence on the microbial turnover rates. We suggest that short biomass turnover times are necessary for maintance of essential cell funtions and to overcome potential damage caused by the increased temperature.The reduced OM quality at the hyrothemal sites might thus only allow for a small population size of microorganisms.

  13. Wintertime Overnight NOx Removal in a Southeastern United States Coal-fired Power Plant Plume: A Model for Understanding Winter NOx Processing and its Implications

    Science.gov (United States)

    Fibiger, Dorothy L.; McDuffie, Erin E.; Dubé, William P.; Aikin, Kenneth C.; Lopez-Hilfiker, Felipe D.; Lee, Ben H.; Green, Jaime R.; Fiddler, Marc N.; Holloway, John S.; Ebben, Carlena; Sparks, Tamara L.; Wooldridge, Paul; Weinheimer, Andrew J.; Montzka, Denise D.; Apel, Eric C.; Hornbrook, Rebecca S.; Hills, Alan J.; Blake, Nicola J.; DiGangi, Josh P.; Wolfe, Glenn M.; Bililign, Solomon; Cohen, Ronald C.; Thornton, Joel A.; Brown, Steven S.

    2018-01-01

    Nitric oxide (NO) is emitted in large quantities from coal-burning power plants. During the day, the plumes from these sources are efficiently mixed into the boundary layer, while at night, they may remain concentrated due to limited vertical mixing during which they undergo horizontal fanning. At night, the degree to which NO is converted to HNO3 and therefore unable to participate in next-day ozone (O3) formation depends on the mixing rate of the plume, the composition of power plant emissions, and the composition of the background atmosphere. In this study, we use observed plume intercepts from the Wintertime INvestigation of Transport, Emissions and Reactivity campaign to test sensitivity of overnight NOx removal to the N2O5 loss rate constant, plume mixing rate, background O3, and background levels of volatile organic compounds using a 2-D box model of power plant plume transport and chemistry. The factor that exerted the greatest control over NOx removal was the loss rate constant of N2O5. At the lowest observed N2O5 loss rate constant, no other combination of conditions converts more than 10% of the initial NOx to HNO3. The other factors did not influence NOx removal to the same degree.

  14. Winter warming from large volcanic eruptions

    Science.gov (United States)

    Robock, Alan; Mao, Jianping

    1992-01-01

    An examination of the Northern Hemisphere winter surface temperature patterns after the 12 largest volcanic eruptions from 1883-1992 shows warming over Eurasia and North America and cooling over the Middle East which are significant at the 95-percent level. This pattern is found in the first winter after tropical eruptions, in the first or second winter after midlatitude eruptions, and in the second winter after high latitude eruptions. The effects are independent of the hemisphere of the volcanoes. An enhanced zonal wind driven by heating of the tropical stratosphere by the volcanic aerosols is responsible for the regions of warming, while the cooling is caused by blocking of incoming sunlight.

  15. Winter ecology of the Porcupine caribou herd, Yukon: Part III, Role of day length in determining activity pattern and estimating percent lying

    Directory of Open Access Journals (Sweden)

    D. E. Russell

    1986-06-01

    Full Text Available Data on the activity pattern, proportion of time spent lying and the length of active and lying periods in winter are presented from a 3 year study on the Porcupine caribou herd. Animals were most active at sunrise and sunset resulting in from one (late fall, early and mid winter to two (early fall and late winter to three (spring intervening lying periods. Mean active/lying cycle length decreased from late fall (298 mm to early winter (238 min, increased to a peak in mid winter (340 min then declined in late winter (305 min and again in spring (240 min. Mean length of the lying period increased throughout the 3 winter months from 56 min m early winter to 114 min in mid winter and 153 min in late winter. The percent of the day animals spent lying decreased from fall to early winter, increased throughout the winter and declined in spring. This pattern was related, in part, to day length and was used to compare percent lying among herds. The relationship is suggested to be a means of comparing quality of winter ranges.

  16. A model study of the pollution effects of the first 3 months of the Holuhraun volcanic fissure: comparison with observations and air pollution effects

    Directory of Open Access Journals (Sweden)

    B. M. Steensen

    2016-08-01

    Full Text Available The volcanic fissure at Holuhraun, Iceland started at the end of August 2014 and continued for 6 months to the end of February 2015, with an extensive lava flow onto the Holuhraun plain. This event was associated with large SO2 emissions, amounting up to approximately 4.5 times the daily anthropogenic SO2 emitted from the 28 European Union countries, Norway, Switzerland and Iceland. In this paper we present results from EMEP/MSC-W model simulations to which we added 750 kg s−1 SO2 emissions at the Holuhraun plain from September to November (SON, testing three different emission heights. The three simulated SO2 concentrations, weighted with the OMI (Ozone Monitoring Instrument satellite averaging kernel, are found to be within 30 % of the satellite-observed SO2 column burden. Constraining the SO2 column burden with the satellite data while using the kernel along with the three simulated height distributions of SO2, we estimate that the median of the daily burdens may have been between 13 and 40 kt in the North Atlantic area under investigation. We suggest this to be the uncertainty in the satellite-derived burdens of SO2, mainly due to the unknown vertical distribution of SO2. Surface observations in Europe outside Iceland showed concentration increases up to > 500 µg m−3 SO2 from volcanic plumes passing. Three well identified episodes, where the plume crossed several countries, are compared in detail to surface measurements. For all events, the general timing of the observed concentration peaks compared quite well to the model results. The overall changes to the European SO2 budget due to the volcanic fissure are estimated. Three-monthly wet deposition (SON of SOx in the 28 European Union countries, Norway and Switzerland is found to be more than 30 % higher in the model simulation with Holuhraun emissions compared to a model simulation with no Holuhraun emissions. The largest increases, apart from extreme values on

  17. A model study of the pollution effects of the first 3 months of the Holuhraun volcanic fissure: comparison with observations and air pollution effects

    Science.gov (United States)

    Steensen, Birthe Marie; Schulz, Michael; Theys, Nicolas; Fagerli, Hilde

    2016-08-01

    The volcanic fissure at Holuhraun, Iceland started at the end of August 2014 and continued for 6 months to the end of February 2015, with an extensive lava flow onto the Holuhraun plain. This event was associated with large SO2 emissions, amounting up to approximately 4.5 times the daily anthropogenic SO2 emitted from the 28 European Union countries, Norway, Switzerland and Iceland. In this paper we present results from EMEP/MSC-W model simulations to which we added 750 kg s-1 SO2 emissions at the Holuhraun plain from September to November (SON), testing three different emission heights. The three simulated SO2 concentrations, weighted with the OMI (Ozone Monitoring Instrument) satellite averaging kernel, are found to be within 30 % of the satellite-observed SO2 column burden. Constraining the SO2 column burden with the satellite data while using the kernel along with the three simulated height distributions of SO2, we estimate that the median of the daily burdens may have been between 13 and 40 kt in the North Atlantic area under investigation. We suggest this to be the uncertainty in the satellite-derived burdens of SO2, mainly due to the unknown vertical distribution of SO2. Surface observations in Europe outside Iceland showed concentration increases up to > 500 µg m-3 SO2 from volcanic plumes passing. Three well identified episodes, where the plume crossed several countries, are compared in detail to surface measurements. For all events, the general timing of the observed concentration peaks compared quite well to the model results. The overall changes to the European SO2 budget due to the volcanic fissure are estimated. Three-monthly wet deposition (SON) of SOx in the 28 European Union countries, Norway and Switzerland is found to be more than 30 % higher in the model simulation with Holuhraun emissions compared to a model simulation with no Holuhraun emissions. The largest increases, apart from extreme values on Iceland, are found on the coast of northern

  18. Summer fallow soil management - impact on rainfed winter wheat

    DEFF Research Database (Denmark)

    Li, Fucui; Wang, Zhaohui; Dai, Jian

    2014-01-01

    Summer fallow soil management is an important approach to improve soil and crop management in dryland areas. In the Loess Plateau regions, the annual precipitation is low and varies annually and seasonally, with more than 60% concentrated in the summer months from July to September, which...... is the summer fallow period in the winter wheat-summer fallow cropping system. With bare fallow in summer as a control, a 3-year location-fixed field experiment was conducted in the Loess Plateau to investigate the effects of wheat straw retention (SR), green manure (GM) planting, and their combination on soil...... water retention (WR) during summer fallow, winter wheat yield, and crop water use and nitrogen (N) uptake. The results showed that SR increased soil WR during summer fallow by 20 mm on average compared with the control over 3 experimental years but reduced the grain yield by 8% in the third year...

  19. Time-lapse imagery of Adélie penguins reveals differential winter strategies and breeding site occupation.

    Science.gov (United States)

    Black, Caitlin; Southwell, Colin; Emmerson, Louise; Lunn, Daniel; Hart, Tom

    2018-01-01

    Polar seabirds adopt different over-wintering strategies to survive and build condition during the critical winter period. Penguin species either reside at the colony during the winter months or migrate long distances. Tracking studies and survey methods have revealed differences in winter migration routes among penguin species and colonies, dependent on both biotic and abiotic factors present. However, scan sampling methods are rarely used to reveal non-breeding behaviors during winter and little is known about presence at the colony site over this period. Here we show that Adélie penguins on the Yalour Islands in the Western Antarctic Peninsula (WAP) are present year-round at the colony and undergo a mid-winter peak in abundance during winter. We found a negative relationship between daylight hours and penguin abundance when either open water or compact ice conditions were present, suggesting that penguins return to the breeding colony when visibility is lowest for at-sea foraging and when either extreme low or high levels of sea ice exist offshore. In contrast, Adélie penguins breeding in East Antarctica were not observed at the colonies during winter, suggesting that Adélie penguins undergo differential winter strategies in the marginal ice zone on the WAP compared to those in East Antarctica. These results demonstrate that cameras can successfully monitor wildlife year-round in areas that are largely inaccessible during winter.

  20. Time-lapse imagery of Adélie penguins reveals differential winter strategies and breeding site occupation

    Science.gov (United States)

    Southwell, Colin; Emmerson, Louise; Lunn, Daniel

    2018-01-01

    Polar seabirds adopt different over-wintering strategies to survive and build condition during the critical winter period. Penguin species either reside at the colony during the winter months or migrate long distances. Tracking studies and survey methods have revealed differences in winter migration routes among penguin species and colonies, dependent on both biotic and abiotic factors present. However, scan sampling methods are rarely used to reveal non-breeding behaviors during winter and little is known about presence at the colony site over this period. Here we show that Adélie penguins on the Yalour Islands in the Western Antarctic Peninsula (WAP) are present year-round at the colony and undergo a mid-winter peak in abundance during winter. We found a negative relationship between daylight hours and penguin abundance when either open water or compact ice conditions were present, suggesting that penguins return to the breeding colony when visibility is lowest for at-sea foraging and when either extreme low or high levels of sea ice exist offshore. In contrast, Adélie penguins breeding in East Antarctica were not observed at the colonies during winter, suggesting that Adélie penguins undergo differential winter strategies in the marginal ice zone on the WAP compared to those in East Antarctica. These results demonstrate that cameras can successfully monitor wildlife year-round in areas that are largely inaccessible during winter. PMID:29561876

  1. Monthly and diurnal variations of limnological conditions of two ponds

    Directory of Open Access Journals (Sweden)

    AKM Fazlur Rahaman

    2017-06-01

    Full Text Available A study on monthly and diurnal changes of limnological conditions of two ponds was conducted in the Bangladesh Agricultural University campus, Mymensingh. The research work was performed by studying the limnological parameters such as transparency, temperature, dissolved oxygen, free carbon dioxide, pH, total alkalinity, nitrate-nitrogen, phosphate-phosphorus and plankton. Diurnal variations of physico-chemical factors were studied fortnightly at 6 hrs intervals at 6 a.m., 12 noon, 6 p.m. and 12 midnight. The amounts of transparency, dissolved oxygen and pH were higher during winter months than in summer months in both the ponds. Transparency, water temperature, total alkalinity, NO3-N and PO4-P were higher during summer months than in winter months in both the ponds. But the amount of free carbon dioxide was higher during winter months than in summer months in pond 1 while in pond 2 the amount of free carbon dioxide was higher during summer months than in winter months. Qualitative and quantitative monthly variations of phytoplankton and zooplankton were observed in both the ponds during the study period. The highest amount of dissolved oxygen, pH and total alkalinity were recorded at 6 p.m. and the lowest amounts of those at 6 a.m. in both the ponds. The highest temperature was recorded at 12 noon and the lowest at 12 midnight. But the highest amount of free carbon dioxide was recorded at 6 a.m. and the lowest at 6 p.m. in both the ponds. All the factors showed appreciable diel variations throughout the study period, which indicate that the ponds are productive.

  2. Weather daily variation in winter and its effect on behavior and affective states in day-care children

    Science.gov (United States)

    Ciucci, Enrica; Calussi, Pamela; Menesini, Ersilia; Mattei, Alessandra; Petralli, Martina; Orlandini, Simone

    2011-05-01

    This study aimed to analyze the impact of winter weather conditions on young children's behavior and affective states by examining a group of 61 children attending day-care centers in Florence (Italy). Participants were 33 males, 28 females and their 11 teachers. The mean age of the children at the beginning of the observation period was 24.1 months. The day-care teachers observed the children's behavioral and emotional states during the morning before their sleeping time and filled in a questionnaire for each baby five times over a winter period of 3 weeks. Air temperature, relative humidity, air pressure and solar radiation data were collected every 15 min from a weather station located in the city center of Florence. At the same time, air temperature and relative humidity data were collected in the classroom and in the garden of each day-care center. We used multilevel linear models to evaluate the extent to which children's emotional and behavioral states could be predicted by weather conditions, controlling for child characteristics (gender and age). The data showed that relative humidity and solar radiation were the main predictors of the children's emotional and behavioral states. The outdoor humidity had a significant positive effect on frustration, sadness and aggression; solar radiation had a significant negative effect only on sadness, suggesting that a sunny winter day makes children more cheerful. The results are discussed in term of implications for parents and teachers to improve children's ecological environment.

  3. Psychosocial predator-based animal model of PTSD produces physiological and behavioral sequelae and a traumatic memory four months following stress onset.

    Science.gov (United States)

    Zoladz, Phillip R; Park, Collin R; Fleshner, Monika; Diamond, David M

    2015-08-01

    We have a well-established animal model of PTSD composed of predator exposure administered in conjunction with social instability that produces PTSD-like behavioral and physiological abnormalities one month after stress initiation. Here, we assessed whether the PTSD-like effects would persist for at least 4months after the initiation of the psychosocial stress regimen. Adult male Sprague-Dawley rats were exposed to either 2 or 3 predator-based fear conditioning sessions. During each session, rats were placed in a chamber for a 3-min period that terminated with a 30-s tone, followed by 1h of immobilization of the rats during cat exposure (Day 1). All rats in the stress groups received a second fear conditioning session 10days later (Day 11). Half of the stress rats received a third fear conditioning session 3weeks later (Day 32). The two cat-exposed groups were also exposed to daily unstable housing conditions for the entire duration of the psychosocial stress regimen. The control group received stable (conventional) housing conditions and an equivalent amount of chamber exposure on Days 1, 11 and 32, without cat exposure. Behavioral testing commenced for all groups on Day 116. The stress groups demonstrated increased anxiety on the elevated plus maze, impaired object recognition memory and robust contextual and cued fear conditioned memory 3months after the last conditioning session. Combined data from the two stress groups revealed lower post-stress corticosterone levels and greater diastolic blood pressure relative to the control group. These findings indicate that predator-based psychosocial stress produces persistent PTSD-like physiological and behavioral abnormalities that may provide insight into the neurobiological and endocrine sequelae in traumatized people with PTSD. Copyright © 2015 Elsevier Inc. All rights reserved.

  4. 33 CFR 100.109 - Winter Harbor Lobster Boat Race, Winter Harbor, ME.

    Science.gov (United States)

    2010-07-01

    ... 33 Navigation and Navigable Waters 1 2010-07-01 2010-07-01 false Winter Harbor Lobster Boat Race, Winter Harbor, ME. 100.109 Section 100.109 Navigation and Navigable Waters COAST GUARD, DEPARTMENT OF HOMELAND SECURITY REGATTAS AND MARINE PARADES SAFETY OF LIFE ON NAVIGABLE WATERS § 100.109 Winter Harbor...

  5. Controls on winter ecosystem respiration in temperate and boreal ecosystems

    Directory of Open Access Journals (Sweden)

    T. Wang

    2011-07-01

    Full Text Available Winter CO2 fluxes represent an important component of the annual carbon budget in northern ecosystems. Understanding winter respiration processes and their responses to climate change is also central to our ability to assess terrestrial carbon cycle and climate feedbacks in the future. However, the factors influencing the spatial and temporal patterns of winter ecosystem respiration (Reco of northern ecosystems are poorly understood. For this reason, we analyzed eddy covariance flux data from 57 ecosystem sites ranging from ~35° N to ~70° N. Deciduous forests were characterized by the highest winter Reco rates (0.90 ± 0.39 g C m−2 d−1, when winter is defined as the period during which daily air temperature remains below 0 °C. By contrast, arctic wetlands had the lowest winter Reco rates (0.02 ± 0.02 g C m−2 d−1. Mixed forests, evergreen needle-leaved forests, grasslands, croplands and boreal wetlands were characterized by intermediate winter Reco rates (g C m−2 d−1 of 0.70(±0.33, 0.60(±0.38, 0.62(±0.43, 0.49(±0.22 and 0.27(±0.08, respectively. Our cross site analysis showed that winter air (Tair and soil (Tsoil temperature played a dominating role in determining the spatial patterns of winter Reco in both forest and managed ecosystems (grasslands and croplands. Besides temperature, the seasonal amplitude of the leaf area index (LAI, inferred from satellite observation, or growing season gross primary productivity, which we use here as a proxy for the amount of recent carbon available for Reco in the subsequent winter, played a marginal role in winter CO2 emissions from forest ecosystems. We found that winter Reco sensitivity to temperature variation across space (

  6. Prediction of skull fracture risk for children 0-9 months old through validated parametric finite element model and cadaver test reconstruction.

    Science.gov (United States)

    Li, Zhigang; Liu, Weiguo; Zhang, Jinhuan; Hu, Jingwen

    2015-09-01

    Skull fracture is one of the most common pediatric traumas. However, injury assessment tools for predicting pediatric skull fracture risk is not well established mainly due to the lack of cadaver tests. Weber conducted 50 pediatric cadaver drop tests for forensic research on child abuse in the mid-1980s (Experimental studies of skull fractures in infants, Z Rechtsmed. 92: 87-94, 1984; Biomechanical fragility of the infant skull, Z Rechtsmed. 94: 93-101, 1985). To our knowledge, these studies contained the largest sample size among pediatric cadaver tests in the literature. However, the lack of injury measurements limited their direct application in investigating pediatric skull fracture risks. In this study, 50 pediatric cadaver tests from Weber's studies were reconstructed using a parametric pediatric head finite element (FE) model which were morphed into subjects with ages, head sizes/shapes, and skull thickness values that reported in the tests. The skull fracture risk curves for infants from 0 to 9 months old were developed based on the model-predicted head injury measures through logistic regression analysis. It was found that the model-predicted stress responses in the skull (maximal von Mises stress, maximal shear stress, and maximal first principal stress) were better predictors than global kinematic-based injury measures (peak head acceleration and head injury criterion (HIC)) in predicting pediatric skull fracture. This study demonstrated the feasibility of using age- and size/shape-appropriate head FE models to predict pediatric head injuries. Such models can account for the morphological variations among the subjects, which cannot be considered by a single FE human model.

  7. Monthly Weather Review

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Supplements to the Monthly Weather Review publication. The Weather Bureau published the Monthly weather review Supplement irregularly from 1914 to 1949. The...

  8. Exploratory Disposal and Reuse Feasibility Analysis of Winter Maintenance Wash Water.

    Science.gov (United States)

    Ullinger, Heather L; Kennedy, Marla J; Schneider, William H; Miller, Christopher M

    2016-01-01

    The Ohio Department of Transportation has more than 60 facilities without sewer access generating approximately 19 million gallons of winter maintenance wash water. Off-site disposal is costly, creating the need for sustainable management strategies. The objective of this study was to conduct an exploratory feasibility analysis to assess wash water disposal and potential reuse as brine. Based on a comprehensive literature review and relevant environmental chemistry, a sampling protocol consisting of 31 water quality constituents was utilized for monthly sampling at three geographically distinct Ohio Department of Transportation garages during the winter of 2012. Results were compared to local disposal and reuse guidance limits. Three constituents, including a maximum copper concentration of 858 ppb, exceeded disposal limits, and many constituents also failed to meet reuse limits. Some concentrations were orders of magnitude higher than reuse limits and suggest pre-treatment would be necessary if wash water were reused as brine. These water quality results, in conjunction with copper chemical equilibrium modeling, show pH and dissolved carbon both significantly impact the total dissolved copper concentration and should be measured to assess reuse potential. The sampling protocol and specific obstacles highlighted in this paper aid in the future development of sustainable wash water management strategies.

  9. Exploratory Disposal and Reuse Feasibility Analysis of Winter Maintenance Wash Water.

    Directory of Open Access Journals (Sweden)

    Heather L Ullinger

    Full Text Available The Ohio Department of Transportation has more than 60 facilities without sewer access generating approximately 19 million gallons of winter maintenance wash water. Off-site disposal is costly, creating the need for sustainable management strategies. The objective of this study was to conduct an exploratory feasibility analysis to assess wash water disposal and potential reuse as brine. Based on a comprehensive literature review and relevant environmental chemistry, a sampling protocol consisting of 31 water quality constituents was utilized for monthly sampling at three geographically distinct Ohio Department of Transportation garages during the winter of 2012. Results were compared to local disposal and reuse guidance limits. Three constituents, including a maximum copper concentration of 858 ppb, exceeded disposal limits, and many constituents also failed to meet reuse limits. Some concentrations were orders of magnitude higher than reuse limits and suggest pre-treatment would be necessary if wash water were reused as brine. These water quality results, in conjunction with copper chemical equilibrium modeling, show pH and dissolved carbon both significantly impact the total dissolved copper concentration and should be measured to assess reuse potential. The sampling protocol and specific obstacles highlighted in this paper aid in the future development of sustainable wash water management strategies.

  10. Interim Report 'Winter smog and traffic'.

    NARCIS (Netherlands)

    Bloemen, H.; Blom, T.; Bogaard, van den C.; Boluyt, N.; Bree, van L.; Brunekreef, B.; Hoek, G.; Zee, van der S.

    1994-01-01

    This report presents a halfway score of the research project "Winter smog and Traffic", one of the themes of the research programme "Air Pollution and Health". A state of the art is presented of the health effects associated with exposure to winter smog and of the toxicological effects caused by the

  11. Nuclear Winter: Scientists in the Political Arena

    Science.gov (United States)

    Badash, Lawrence

    2001-03-01

    The nuclear winter phenomenon is used to illustrate the many paths by which scientific advice reaches decision makers in the United States government. Because the Reagan administration was hostile to the strategic policy that the scientific discovery seemed to demand, the leading proponent of nuclear winter, Carl Sagan, used his formidable talent for popularization to reach a larger audience.

  12. How to Have a Healthy Winter | Poster

    Science.gov (United States)

    Without a doubt, winter is here. Between the icy weather and the recent hustle and bustle of the holidays, everyone is at an increased risk of getting sick. With that in mind, Occupational Health Services has a few simple tips for staying healthy this winter.

  13. Chapter 7: Migration and winter ecology

    Science.gov (United States)

    Deborah M. Finch; Jeffrey F. Kelly; Jean-Luc E. Cartron

    2000-01-01

    The willow flycatcher (Empidonax traillii) is a Neotropical migrant that breeds in North America, but winters in Central and northern South America. Little specific information is known about migration and wintering ecology of the southwestern willow flycatcher (E. t. extimus) (Yong and Finch 1997). Our report applies principally...

  14. Estimation of Genetic Parameters for First Lactation Monthly Test-day Milk Yields using Random Regression Test Day Model in Karan Fries Cattle

    Directory of Open Access Journals (Sweden)

    Ajay Singh

    2016-06-01

    Full Text Available A single trait linear mixed random regression test-day model was applied for the first time for analyzing the first lactation monthly test-day milk yield records in Karan Fries cattle. The test-day milk yield data was modeled using a random regression model (RRM considering different order of Legendre polynomial for the additive genetic effect (4th order and the permanent environmental effect (5th order. Data pertaining to 1,583 lactation records spread over a period of 30 years were recorded and analyzed in the study. The variance component, heritability and genetic correlations among test-day milk yields were estimated using RRM. RRM heritability estimates of test-day milk yield varied from 0.11 to 0.22 in different test-day records. The estimates of genetic correlations between different test-day milk yields ranged 0.01 (test-day 1 [TD-1] and TD-11 to 0.99 (TD-4 and TD-5. The magnitudes of genetic correlations between test-day milk yields decreased as the interval between test-days increased and adjacent test-day had higher correlations. Additive genetic and permanent environment variances were higher for test-day milk yields at both ends of lactation. The residual variance was observed to be lower than the permanent environment variance for all the test-day milk yields.

  15. 76 FR 27843 - National Building Safety Month, 2011

    Science.gov (United States)

    2011-05-13

    ... organizations and the public and private sectors--to implement effective standards and codes that sustain safe... and fire prevention codes help us withstand, mitigate, and rapidly recover from hurricanes, winter... Building Safety Month. I encourage citizens, government agencies, private businesses, nonprofit...

  16. Human impact parameterizations in global hydrological models improve estimates of monthly discharges and hydrological extremes: a multi-model validation study

    NARCIS (Netherlands)

    Veldkamp, T I E; Zhao, F; Ward, P J; Moel, H de; Aerts, J C J H; Schmied, H Müller; Portmann, F T; Masaki, Y; Pokhrel, Y; Liu, X; Satoh, Yusuke; Gerten, Dieter; Gosling, S N; Zaherpour, J; Wada, Yoshihide

    2018-01-01

    Human activity has a profound influence on river discharges, hydrological extremes and water-related hazards. In this study, we compare the results of five state-of-the-art global hydrological models (GHMs) with observations to examine the role of human impact parameterizations (HIP) in the

  17. Atmospheric Simulations Using OGCM-Assimilation SST: Influence of the Wintertime Japan Sea on Monthly Precipitation

    Directory of Open Access Journals (Sweden)

    Masaru Yamamoto Naoki Hirose

    2010-01-01

    Full Text Available Temperature data for the Japan Sea obtained from ocean data assimilation modeling is applied to atmospheric simulations of monthly precipitation for January 2005. Because the volume of flow of the Tsushima Warm Current was large during the winter season, the sea surface temperature (SST and coastal precipitation were higher in comparison with those in 2003. In order to evaluate influence of SST on monthly precipitation, we use surface temperatures of the Japan Sea in 2003 and 2005 for comparative simulations of precipitation for January 2005. The precipitation in experiment C (using cool SST data in 2003 is smaller than that in experiment W (using warm SST data in 2005 in a large part of the sea area, since the small evaporation results from the low SST over the upstream area of northwesterly winter monsoon. In the domain of 33.67 - 45.82°N and 125.89 - 142.9°E, the averaged evaporation and precipitation in experiment C are 10% and 13% smaller than those in experiment W, respectively. About half of the difference between the precipitations observed for January 2003 and 2005 in a heavy snow area is equal to the difference between the two simulations. Our results show that the mesoscale SST difference between 2003 and 2005 is related to the local difference of monthly precipitation.

  18. [Population trends and behavioral observations of wintering common cranes (Grus grus) in Yancheng Nature Reserve].

    Science.gov (United States)

    Li, Zhong-Qiu; Wang, Zhi; Ge, Chen

    2013-10-01

    To understand the population status and behavioural features of wintering common cranes in the Yancheng Nature Reserve, two transects were established and population trends were monitored every month over five recent winters from 2008 to 2013. Wintering behaviours were also observed in order to explore the possible effects of family size and age on time budgets. Results indicated that the populations were stable with a range of 303 to 707 individuals. Negative effects of coastal developments were not found on the wintering population of common cranes, which might be related to their diets and preference for artificial wetland habitats. We found a significant effect of age on time budgets, with juveniles spending more time feeding and less time alerting, which might be related to the needs of body development and skill learning. Family size did not affect the time budgets of the cranes, which indicated that adults did not increase vigilance investment even when raising a larger family.

  19. Benchmarking monthly homogenization algorithms

    Science.gov (United States)

    Venema, V. K. C.; Mestre, O.; Aguilar, E.; Auer, I.; Guijarro, J. A.; Domonkos, P.; Vertacnik, G.; Szentimrey, T.; Stepanek, P.; Zahradnicek, P.; Viarre, J.; Müller-Westermeier, G.; Lakatos, M.; Williams, C. N.; Menne, M.; Lindau, R.; Rasol, D.; Rustemeier, E.; Kolokythas, K.; Marinova, T.; Andresen, L.; Acquaotta, F.; Fratianni, S.; Cheval, S.; Klancar, M.; Brunetti, M.; Gruber, C.; Prohom Duran, M.; Likso, T.; Esteban, P.; Brandsma, T.

    2011-08-01

    The COST (European Cooperation in Science and Technology) Action ES0601: Advances in homogenization methods of climate series: an integrated approach (HOME) has executed a blind intercomparison and validation study for monthly homogenization algorithms. Time series of monthly temperature and precipitation were evaluated because of their importance for climate studies and because they represent two important types of statistics (additive and multiplicative). The algorithms were validated against a realistic benchmark dataset. The benchmark contains real inhomogeneous data as well as simulated data with inserted inhomogeneities. Random break-type inhomogeneities were added to the simulated datasets modeled as a Poisson process with normally distributed breakpoint sizes. To approximate real world conditions, breaks were introduced that occur simultaneously in multiple station series within a simulated network of station data. The simulated time series also contained outliers, missing data periods and local station trends. Further, a stochastic nonlinear global (network-wide) trend was added. Participants provided 25 separate homogenized contributions as part of the blind study as well as 22 additional solutions submitted after the details of the imposed inhomogeneities were revealed. These homogenized datasets were assessed by a number of performance metrics including (i) the centered root mean square error relative to the true homogeneous value at various averaging scales, (ii) the error in linear trend estimates and (iii) traditional contingency skill scores. The metrics were computed both using the individual station series as well as the network average regional series. The performance of the contributions depends significantly on the error metric considered. Contingency scores by themselves are not very informative. Although relative homogenization algorithms typically improve the homogeneity of temperature data, only the best ones improve precipitation data

  20. Combined Use of Landsat-8 and Sentinel-2A Images for Winter Crop Mapping and Winter Wheat Yield Assessment at Regional Scale

    Science.gov (United States)

    Skakun, Sergii; Vermote, Eric; Roger, Jean-Claude; Franch, Belen

    2017-01-01

    Timely and accurate information on crop yield and production is critical to many applications within agriculture monitoring. Thanks to its coverage and temporal resolution, coarse spatial resolution satellite imagery has always been a source of valuable information for yield forecasting and assessment at national and regional scales. With availability of free images acquired by Landsat-8 and Sentinel-2 remote sensing satellites, it becomes possible to provide temporal resolution of an image every 3-5 days, and therefore, to develop next generation agriculture products at higher spatial resolution (10-30 m). This paper explores the combined use of Landsat-8 and Sentinel-2A for winter crop mapping and winter wheat yield assessment at regional scale. For the former, we adapt a previously developed approach for the Moderate Resolution Imaging Spectroradiometer (MODIS) instrument at 250 m resolution that allows automatic mapping of winter crops taking into account a priori knowledge on crop calendar. For the latter, we use a generalized winter wheat yield forecasting model that is based on estimation of the peak Normalized Difference Vegetation Index (NDVI) from MODIS image time-series, and further downscaled to be applicable at 30 m resolution. We show that integration of Landsat-8 and Sentinel-2A improves both winter crop mapping and winter wheat yield assessment. In particular, the error of winter wheat yield estimates can be reduced up to 1.8 times compared to using a single satellite.

  1. Combined Use of Landsat-8 and Sentinel-2A Images for Winter Crop Mapping and Winter Wheat Yield Assessment at Regional Scale

    Directory of Open Access Journals (Sweden)

    Sergii Skakun

    2017-05-01

    Full Text Available Timely and accurate information on crop yield and production is critical to many applications within agriculture monitoring. Thanks to its coverage and temporal resolution, coarse spatial resolution satellite imagery has always been a source of valuable information for yield forecasting and assessment at national and regional scales. With availability of free images acquired by Landsat-8 and Sentinel-2 remote sensing satellites, it becomes possible to provide temporal resolution of 3–5 days, and therefore, to develop next generation agriculture products at higher spatial resolution (10–30 m. This paper explores the combined use of Landsat-8 and Sentinel-2A for winter crop mapping and winter wheat yield assessment at regional scale. For the former, we adapt a previously developed approach for the Moderate Resolution Imaging Spectroradiometer (MODIS instrument at 250 m resolution that allows automatic mapping of winter crops taking into account a priori knowledge on crop calendar. For the latter, we use a generalized winter wheat yield forecasting model that is based on estimation of the peak Normalized Difference Vegetation Index (NDVI from MODIS image time-series, and further downscaled to be applicable at 30 m resolution. We show that integration of Landsat-8 and Sentinel-2A improves both winter crop mapping and winter wheat yield assessment. In particular, the error of winter wheat yield estimates can be reduced up to 1.8 times compared to using a single satellite.

  2. Petroleum supply monthly, January 1996

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    1996-02-15

    The Petroleum Supply Monthly (PSM) is one of a family of four publications produced by the Petroleum Supply Division within the Energy Information Administration (EIA) reflecting different levels of data timeliness and completeness. The other publications are the Weekly Petroleum Status Report (WPSR), the Winter Fuels Report, and the Petroleum Supply Annual (PSA). Data presented in the PSM describe the supply and disposition of petroleum products in the United States and major US geographic regions. The data series describe production, imports and exports, inter-Petroleum Administration for Defense (PAD) District movements, and inventories by the primary suppliers of petroleum products in the United States (50 States and the District of Columbia). The reporting universe includes those petroleum sectors in primary supply. Included are: petroleum refiners, motor gasoline blenders, operators of natural gas processing plants and fractionators, inter-PAD transporters, importers, and major inventory holders of petroleum products and crude oil. When aggregated, the data reported by these sectors approximately represent the consumption of petroleum products in the United States. Data presented in the PSM are divided into two sections: Summary Statistics and Detailed Statistics.

  3. Petroleum supply monthly, October 1993

    Energy Technology Data Exchange (ETDEWEB)

    1993-10-26

    The Petroleum Supply Monthly (PSM) is one of a family of four publications produced by the Petroleum Supply Division within the Energy Information Administration (EIA) reflecting different levels of data timeliness and completeness. The other publications are the Weekly Petroleum Status Report (WPSR), the Winter Fuels Report, and the Petroleum Supply Annual (PSA). Data presented in the PSM describe the supply and disposition of petroleum products in the United States and major US geographic regions. The data series describe production, imports and exports, inter-Petroleum Administration for Defense (PAD) District movements, and inventories by the primary suppliers of petroleum products in the United States (50 States and the District of Columbia). The reporting universe includes those petroleum sectors in primary supply. Included are: petroleum refiners, motor gasoline blenders, operators of natural gas processing plants and fractionators, inter-PAD transporters, importers, and major inventory holders of petroleum products and crude oil. When aggregated, the data reported by these sectors approximately represent the consumption of petroleum products in the United States. Data presented in the PSM are divided into two sections: Summary Statistics and Detailed Statistics.

  4. Seasonal overturning circulation in the Red Sea: 2. Winter circulation

    Science.gov (United States)

    Yao, Fengchao; Hoteit, Ibrahim; Pratt, Larry J.; Bower, Amy S.; Köhl, Armin; Gopalakrishnan, Ganesh; Rivas, David

    2014-04-01

    The shallow winter overturning circulation in the Red Sea is studied using a 50 year high-resolution MITgcm (MIT general circulation model) simulation with realistic atmospheric forcing. The overturning circulation for a typical year, represented by 1980, and the climatological mean are analyzed using model output to delineate the three-dimensional structure and to investigate the underlying dynamical mechanisms. The horizontal model circulation in the winter of 1980 is dominated by energetic eddies. The climatological model mean results suggest that the surface inflow intensifies in a western boundary current in the southern Red Sea that switches to an eastern boundary current north of 24°N. The overturning is accomplished through a cyclonic recirculation and a cross-basin overturning circulation in the northern Red Sea, with major sinking occurring along a narrow band of width about 20 km along the eastern boundary and weaker upwelling along the western boundary. The northward pressure gradient force, strong vertical mixing, and horizontal mixing near the boundary are the essential dynamical components in the model's winter overturning circulation. The simulated water exchange is not hydraulically controlled in the Strait of Bab el Mandeb; instead, the exchange is limited by bottom and lateral boundary friction and, to a lesser extent, by interfacial friction due to the vertical viscosity at the interface between the inflow and the outflow.

  5. Transitions in Prognostic Awareness Among Terminally Ill Cancer Patients in Their Last 6 Months of Life Examined by Multi-State Markov Modeling.

    Science.gov (United States)

    Hsiu Chen, Chen; Wen, Fur-Hsing; Hou, Ming-Mo; Hsieh, Chia-Hsun; Chou, Wen-Chi; Chen, Jen-Shi; Chang, Wen-Cheng; Tang, Siew Tzuh

    2017-09-01

    Developing accurate prognostic awareness, a cornerstone of preference-based end-of-life (EOL) care decision-making, is a dynamic process involving more prognostic-awareness states than knowing or not knowing. Understanding the transition probabilities and time spent in each prognostic-awareness state can help clinicians identify trigger points for facilitating transitions toward accurate prognostic awareness. We examined transition probabilities in distinct prognostic-awareness states between consecutive time points in 247 cancer patients' last 6 months and estimated the time spent in each state. Prognostic awareness was categorized into four states: (a) unknown and not wanting to know, state 1; (b) unknown but wanting to know, state 2; (c) inaccurate awareness, state 3; and (d) accurate awareness, state 4. Transitional probabilities were examined by multistate Markov modeling. Initially, 59.5% of patients had accurate prognostic awareness, whereas the probabilities of being in states 1-3 were 8.1%, 17.4%, and 15.0%, respectively. Patients' prognostic awareness generally remained unchanged (probabilities of remaining in the same state: 45.5%-92.9%). If prognostic awareness changed, it tended to shift toward higher prognostic-awareness states (probabilities of shifting to state 4 were 23.2%-36.6% for patients initially in states 1-3, followed by probabilities of shifting to state 3 for those in states 1 and 2 [9.8%-10.1%]). Patients were estimated to spend 1.29, 0.42, 0.68, and 3.61 months in states 1-4, respectively, in their last 6 months. Terminally ill cancer patients' prognostic awareness generally remained unchanged, with a tendency to become more aware of their prognosis. Health care professionals should facilitate patients' transitions toward accurate prognostic awareness in a timely manner to promote preference-based EOL decisions. Terminally ill Taiwanese cancer patients' prognostic awareness generally remained stable, with a tendency toward developing

  6. Structural equation modelling of viral tropism reveals its impact on achieving viral suppression within 6 months in treatment-naive HIV-1-infected patients after combination antiretroviral therapy.

    Science.gov (United States)

    Mengoli, Carlo; Andreis, Samantha; Scaggiante, Renzo; Cruciani, Mario; Bosco, Oliviero; Ferretto, Roberto; Leoni, Davide; Maffongelli, Gaetano; Basso, Monica; Torti, Carlo; Sarmati, Loredana; Andreoni, Massimo; Palù, Giorgio; Parisi, Saverio Giuseppe

    2017-01-01

    To evaluate the role of pre-treatment co-receptor tropism of plasma HIV on the achievement of viral suppression (plasma HIV RNA 1.69 log 10 copies/mL) at the sixth month of combination antiretroviral therapy (cART) in a cohort of naive patients using, for the first time in this context, a path analysis (PA) approach. Adult patients with chronic infection by subtype B HIV-1 were consecutively enrolled from the start of first-line cART (T0). Genotypic analysis of viral tropism was performed on plasma and interpreted using the bioinformatic tool Geno2pheno, with a false positive rate of 10%. A Bayesian network starting from the viro-immunological data at T0 and at the sixth month of treatment (T1) was set up and this model was evaluated using a PA approach. A total of 262 patients (22.1% bearing an X4 virus) were included; 178 subjects (67.9%) achieved viral suppression. A significant positive indirect effect of bearing X4 virus in plasma at T0 on log 10 HIV RNA at T1 was detected (P = 0.009), the magnitude of this effect was, however, over 10-fold lower than the direct effect of log 10 HIV RNA at T0 on log 10 HIV RNA at T1 (P = 0.000). Moreover, a significant positive indirect effect of bearing an X4 virus on log 10 HIV RNA at T0 (P = 0.003) was apparent. PA overcame the limitations implicit in common multiple regression analysis and showed the possible role of pre-treatment viral tropism at the recommended threshold on the outcome of plasma viraemia in naive patients after 6 months of therapy. © The Author 2016. Published by Oxford University Press on behalf of the British Society for Antimicrobial Chemotherapy. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

  7. Addressing the immediate need for emergency providers in resource-limited settings: the model of a six-month emergency medicine curriculum in Haiti.

    Science.gov (United States)

    Rouhani, Shada A; Israel, Kerling; Leandre, Fernet; Pierre, Sosthène; Bollman, Brennan; Marsh, Regan H

    2018-04-06

    In many resource-limited settings, emergency medicine (EM) is underdeveloped and formal EM training limited. Residencies and fellowships are an ideal long-term solution but cannot meet immediate needs for emergency providers, while short-term programs are often too limited in content. We describe a third method successfully implemented in Haiti: a medium-duration certificate program to meet the immediate need for emergency specialists. In conjunction with the Haitian Ministry of Health and National Medical School, we developed and implemented a novel, 6-month EM certificate program to build human resources for health and emergency care capacity. The program consisted of didactic and supervised clinical components, covering core content in EM. Didactics included lectures, simulations, hands-on skill-sessions, and journal clubs. Supervised clinical time reinforced concepts and taught an EM approach to patient care. Fourteen physicians from around Haiti successfully completed the program; all improved from their pre-test to post-test. At the end of the program and 9-month post-program evaluations, participants rated the program highly, and most felt they used their new knowledge daily. Participants found clinical supervision and simulation particularly useful. Key components to our program's success included collaboration with the Ministry of Health and National Medical School, supervised clinical time, and the continual presence of a course director. The program could be improved by a more flexible curriculum and by grouping participants by baseline knowledge levels. Medium-duration certificate programs offer a viable option for addressing immediate human resource gaps in emergency care, and our program offers a model for implementation in resource-limited settings. Similar options should be considered for other emerging specialties in resource-limited settings.

  8. A Fleet of Low-Cost Sensor Based Air Quality Monitors Is Used to Measure Carbon Dioxide and Carbon Monoxide in Two Settings: In the Ambient Environment to Explore the Regional-Scale Spatial Variability of These Compounds Via a Distributed Network, and in Homes to Investigate How Heating during Winter Months can Impact Indoor Air Quality.

    Science.gov (United States)

    Casey, J. G.; Hannigan, M.; Collier, A. M.; Coffey, E.; Piedrahita, R.

    2016-12-01

    Affordable, small, portable, quiet tools to measure atmospheric trace gases and air quality enable novel experimental design and new findings. Members of the Hannigan Lab at the University of Colorado in Boulder have been working over the last few years to integrate emerging affordable gas sensors into such an air quality monitor. Presented here are carbon monoxide (CO) and carbon dioxide (CO2) measurements from two field experiments that utilized these tools. In the first experiment, ten air quality monitors were located northeast of Boulder throughout the Denver Julesburg oil and gas basin. The Colorado Department of Health and Environment has several air quality monitoring sites in this broader region, each in an Urban center. One goal of the experiment was to determine whether or not significant spatial variability of EPA criteria pollutants like CO, exists on a sub-regulatory monitoring grid scale. Another goal of the experiment was to compare rural sampling locations with urban sites. The monitors collected continuous data (sampling every 15 seconds) at each location over the course of several months. Our sensor calibration procedures are presented along with our observations and an analysis of the spatial and temporal variability in CO and CO2. In the second experiment, we used eight of our air quality monitors to better understand how home heating fuel type can impact indoor air quality in two communities on the Navajo Nation. We sought to compare air quality in homes using one of four different fuels for heat (wood, wood plus coal, pellet, and gas). There are many factors that contribute to indoor air quality and the impact of an emission source, like a woodstove, within a home. Having multiple, easily deployable, air quality monitors allowed us to account for many of these factors. We sampled four homes at a time, aiming for one home from each of our fuel groups in each sampling period. We sampled inside and outside of each home for a period of 3-4 days

  9. Contrasting Seasonal Survivorship of Two Migratory Songbirds Wintering in Threatened Mangrove Forests

    Directory of Open Access Journals (Sweden)

    Anna M. Calvert

    2010-06-01

    Full Text Available Long-distance migrants wintering in tropical regions face a number of critical conservation threats throughout their lives, but seasonal estimates of key demographic parameters such as winter survival are rare. Using mist-netting-based mark-recapture data collected in coastal Costa Rica over a six-year period, we examined variation in within- and between-winter survivorship of the Prothonotary Warbler (Protonotaria citrea; 753 young and 376 adults banded, a declining neotropical habitat specialist that depends on threatened mangrove forests during the nonbreeding season. We derived parallel seasonal survivorship estimates for the Northern Waterthrush (Seiurus noveboracensis; 564 young and 93 adults banded, a cohabitant mangrove specialist that has not shown the same population decline in North America, to assess whether contrasting survivorship might contribute to the observed differences in the species’ population trajectories. Although average annual survival probability was relatively similar between the two species for both young and adult birds, monthly estimates indicated that relative to Northern Waterthrush, Prothonotary Warblers exhibited: greater interannual variation in survivorship, especially within winters; greater variation in survivorship among the three study sites; lower average between-winter survivorship, particularly among females, and; a sharp decline in between-winter survivorship from 2003 to 2009 for both age groups and both sexes. Rather than identifying one seasonal vital rate as a causal factor of Prothonotary Warbler population declines, our species comparison suggests that the combination of variable within-winter survival with decreasing between-winter survival demands a multi-seasonal approach to the conservation of this and other tropical-wintering migrants.

  10. SU-D-204-05: Fitting Four NTCP Models to Treatment Outcome Data of Salivary Glands Recorded Six Months After Radiation Therapy for Head and Neck Tumors

    Energy Technology Data Exchange (ETDEWEB)

    Mavroidis, P; Price, A; Kostich, M; Green, R; Das, S; Marks, L; Chera, B [University North Carolina, Chapel Hill, NC (United States); Amdur, R; Mendenhall, W [University of Florida, Gainesville, FL (United States); Sheets, N [University of North Carolina, Raleigh, NC (United States)

    2016-06-15

    Purpose: To estimate the radiobiological parameters of four popular NTCP models that describe the dose-response relations of salivary glands to the severity of patient reported dry mouth 6 months post chemo-radiotherapy. To identify the glands, which best correlate with the manifestation of those clinical endpoints. Finally, to evaluate the goodness-of-fit of the NTCP models. Methods: Forty-three patients were treated on a prospective multiinstitutional phase II study for oropharyngeal squamous cell carcinoma. All the patients received 60 Gy IMRT and they reported symptoms using the novel patient reported outcome version of the CTCAE. We derived the individual patient dosimetric data of the parotid and submandibular glands (SMG) as separate structures as well as combinations. The Lyman-Kutcher-Burman (LKB), Relative Seriality (RS), Logit and Relative Logit (RL) NTCP models were used to fit the patients data. The fitting of the different models was assessed through the area under the receiver operating characteristic curve (AUC) and the Odds Ratio methods. Results: The AUC values were highest for the contralateral parotid for Grade ≥ 2 (0.762 for the LKB, RS, Logit and 0.753 for the RL). For the salivary glands the AUC values were: 0.725 for the LKB, RS, Logit and 0.721 for the RL. For the contralateral SMG the AUC values were: 0.721 for LKB, 0.714 for Logit and 0.712 for RS and RL. The Odds Ratio for the contralateral parotid was 5.8 (1.3–25.5) for all the four NTCP models for the radiobiological dose threshold of 21Gy. Conclusion: It was shown that all the examined NTCP models could fit the clinical data well with very similar accuracy. The contralateral parotid gland appears to correlated best with the clinical endpoints of severe/very severe dry mouth. An EQD2Gy dose of 21Gy appears to be a safe threshold to be used as a constraint in treatment planning.

  11. Natural gas monthly

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    1998-01-01

    The Natural Gas Monthly highlights activities, events, and analyses of interest to public and private sector organizations associated with the natural gas industry. Volume and price data are presented each month for natural gas production, distribution, consumption, and interstate pipeline activities. Producer-related activities and underground storage data are also reported. From time to time, the Natural Gas Monthly features articles designed to assist readers in using and interpreting natural gas information.

  12. FLDAS Noah Land Surface Model L4 Monthly Climatology 0.1 x 0.1 degree for Eastern Africa (MERRA-2 and CHIRPS) V001 (FLDAS_NOAH01_C_EA_MC) at GES DISC

    Data.gov (United States)

    National Aeronautics and Space Administration — The monthly climatology data set contains a series of land surface parameters simulated from the Noah 3.3 model in the Famine Early Warning Systems Network (FEWS...

  13. Winter Survival of Individual Honey Bees and Honey Bee Colonies Depends on Level of Varroa destructor Infestation

    Science.gov (United States)

    van Dooremalen, Coby; Gerritsen, Lonne; Cornelissen, Bram; van der Steen, Jozef J. M.; van Langevelde, Frank; Blacquière, Tjeerd

    2012-01-01

    Background Recent elevated winter loss of honey bee colonies is a major concern. The presence of the mite Varroa destructor in colonies places an important pressure on bee health. V. destructor shortens the lifespan of individual bees, while long lifespan during winter is a primary requirement to survive until the next spring. We investigated in two subsequent years the effects of different levels of V. destructor infestation during the transition from short-lived summer bees to long-lived winter bees on the lifespan of individual bees and the survival of bee colonies during winter. Colonies treated earlier in the season to reduce V. destructor infestation during the development of winter bees were expected to have longer bee lifespan and higher colony survival after winter. Methodology/Principal Findings Mite infestation was reduced using acaricide treatments during different months (July, August, September, or not treated). We found that the number of capped brood cells decreased drastically between August and November, while at the same time, the lifespan of the bees (marked cohorts) increased indicating the transition to winter bees. Low V. destructor infestation levels before and during the transition to winter bees resulted in an increase in lifespan of bees and higher colony survival compared to colonies that were not treated and that had higher infestation levels. A variety of stress-related factors could have contributed to the variation in longevity and winter survival that we found between years. Conclusions/Significance This study contributes to theory about the multiple causes for the recent elevated colony losses in honey bees. Our study shows the correlation between long lifespan of winter bees and colony loss in spring. Moreover, we show that colonies treated earlier in the season had reduced V. destructor infestation during the development of winter bees resulting in longer bee lifespan and higher colony survival after winter. PMID:22558421

  14. 'Downward control' of the mean meridional circulation and temperature distribution of the polar winter stratosphere

    Science.gov (United States)

    Garcia, Rolando R.; Boville, Byron A.

    1994-01-01

    According to the 'downward control' principle, the extratropical mean vertical velocity on a given pressure level is approximately proportional to the meridional gradient of the vertically integrated zonal force per unit mass exerted by waves above that level. In this paper, a simple numerical model that includes parameterizations of both planetary and gravity wave breaking is used to explore the influence of gravity wave breaking in the mesosphere on the mean meridional circulation and temperature distribution at lower levels in the polar winter stratosphere. The results of these calculations suggest that gravity wave drag in the mesosphere can affect the state of the polar winter stratosphere down to altitudes below 30 km. The effect is most important when planetary wave driving is relatively weak: that is, during southern winter and in early northern winter. In southern winter, downwelling weakens by a factor of 2 near the stratospause and by 20% at 30 km when gravity wave drag is not included in the calculations. As a consequence, temperatures decrease considerably throughout the polar winter stratosphere (over 20 K above 40 km and as much as 8 K at 30 km, where the effect is enhanced by the long radiative relaxation timescale). The polar winter states obtained when gravity wave drag is omitted in this simple model resemble the results of simulations with some general circulation models and suggest that some of the shortcomings of the latter may be due to a deficit in mesospheric momentum deposition by small-scale gravity waves.

  15. Energy market barometer report - Winter 2015

    International Nuclear Information System (INIS)

    Schleich, Joachim; Cartel, Melodie; Javaudin, Laurent; Molecke, Greg; Olsthoorn, Mark; Vernay, Anne-Lorene

    2016-01-01

    This Winter 2015 edition of the Grenoble Ecole de Management (GEM) Energy Market Barometer gauged the expectations of French energy experts regarding the low oil price and its consequences on alternative energy technologies. The experts were also asked about the investment climate for energy technologies in France. Key findings: - The energy experts consider the current low oil price a temporary phenomenon. The price of a barrel of crude oil (Brent) to reach US$ 55 at the end of the year (2016). About three quarters of respondents expect the price of oil to increase in 5 years and to exceed US$ 100 per barrel within 10 years. - The current weak price of crude oil is thought to have an adverse impact on the amount of investment in renewables for heat generation, in biofuels, and in energy efficiency technologies. - The experts view the current regulatory environment in France for investments in renewables, e-mobility, smart grids and energy efficiency favorably. They expect it to continue to improve over the next 5 years. However, nuclear energy and natural gas will not see their investment climate improved. - The recent developments on the global and national political stage have not moved most energy and CO_2 price expectations. The experts chart a progressive yet under-whelming raise in the price of CO_2 certificates in the medium to long term, from currently 8.5 euro/ton to euro 10-15 euro/ton in 5 years and 20-25 euro/ton in 10 years. - Prices of electricity, oil and natural gas are expected to rise in the medium term but remain stable over the next six months temporary phenomenon. Coal is the only energy carrier for which experts expect a decrease in price over the next five years

  16. [Morphophysiological and Behavioral Adaptations of Elk to Wintering].

    Science.gov (United States)

    Glushkov, V M; Kuznetsov, G V

    2015-01-01

    This paper studies morphometric parameters (body weight, weight of internal organs, body size, etc.) in 170 elk of various sex and age obtained in the Vyatka taiga area in winter. A number of physiological parameters (specific metabolism and thermal conductivity, heat loss rate, etc.) characterizing the metabolic rate and energy balance in the body were calculated for model animals (calf, male, and female). It is noted that in the transition from the first to the second half of winter the specific metabolism in model animals decreased from 20.6, 16.9, and 15.9 to 18.7, 15.4, and 14.5 kcal/(kg day), respectively. It is shown that changes in the rhythm of motor activity of elk are synchronized with the daily air temperature and the maximum flight distance depends on the amount of energy received by the body with food.

  17. A successful forecast of an El Nino winter

    International Nuclear Information System (INIS)

    Kerr, R.A.

    1992-01-01

    This year, for the first time, weather forecasters used signs of a warming in the tropical Pacific as the basis for a long-range prediction of winter weather patterns across the United States. Now forecasters are talking about the next step: stretching the lead time for such forecasts by a year or more. That seems feasible because although this Pacific warming was unmistakable by the time forecasters at the National Weather Service's Climate Analysis Center (CAC) in Camp Springs, Maryland, issued their winter forecast, the El Nino itself had been predicted almost 2 years in advance by a computer model. Next time around, the CAC may well be listening to the modelers and predicting El Nino-related patterns of warmth and flooding seasons in advance

  18. A path model analysis on predictors of dropout (at 6 and 12 months) during the weight loss interventions in endocrinology outpatient division.

    Science.gov (United States)

    Perna, Simone; Spadaccini, Daniele; Riva, Antonella; Allegrini, Pietro; Edera, Chiara; Faliva, Milena Anna; Peroni, Gabriella; Naso, Maurizio; Nichetti, Mara; Gozzer, Carlotta; Vigo, Beatrice; Rondanelli, Mariangela

    2018-02-22

    This study aimed to identify the dropout rate at 6 and 12 months from the first outpatient visit, and to analyze dropout risk factors among the following areas: biochemical examinations, anthropometric measures, psychological tests, personal data, and life attitude such as smoking, physical activity, and pathologies. This is a retrospective longitudinal observational study. Patients undergo an outpatient endocrinology visit, which includes collecting biographical data, anthropometric measurements, physical and pathological history, psychological tests, and biochemical examinations. The sample consists of 913 subjects (682 women and 231 men), with an average age of 50.88 years (±15.80) for the total sample, with a BMI of 33.11 ± 5.65 kg/m 2 . 51.9% of the patients abandoned therapy at 6 months after their first visit, and analyzing the dropout rate at 12 months, it appears that 69.5% of subjects abandon therapy. The main predictor of dropout risk factors at 6 and 12 months is the weight loss during the first 3 months (p dropout at 12 months. Patients who introduced physical activity had a reduction of - 17% (at 6 months) and -13% (at 12 months) of dropout risk (p dropout vs. other categories of worker (i = 0.58; p Dropout risk at 12 months decrease in patients with a previous history of cancer, Endocrine and psychic and behavioral disorders (p dropout.

  19. The effects of changes in snow depth on winter recreation

    Czech Academy of Sciences Publication Activity Database

    Zahradníček, Pavel; Rožnovský, J.; Štěpánek, Petr; Farda, Aleš; Brzezina, J.

    2016-01-01

    Roč. 7, č. 1 (2016), s. 44-54 ISSN 1804-2821 R&D Projects: GA MŠk(CZ) LO1415; GA ČR GA13-04291S; GA ČR(CZ) GA14-12262S Institutional support: RVO:67179843 Keywords : new snow * total snow depth * climate change * climate models * winter recreations Subject RIV: EH - Ecology, Behaviour

  20. Progress report, 24 months

    DEFF Research Database (Denmark)

    Juhl, Thomas Winther; Nielsen, Jakob Skov

    The work performed during the past 12 months (months 13 – 24) of the project has included the conclusion of Task 1 – Fundamental Studies and Task 2 – Multimirror Cutting Head Design. Work on Task 3 – Compact Cutting Head Design, and Task 4 – Interface Design has been carried out and the tests...... of the multimirror cutting head have been started....

  1. Progress report, 36 months

    DEFF Research Database (Denmark)

    Juhl, Thomas Winther; Nielsen, Jakob Skov

    The work performed during the past 12 months (months 13 – 24) of the project has included the conclusion of Task 1 – Fundamental Studies and Task 2 – Multimirror Cutting Head Design. Work on Task 3 – Compact Cutting Head Design, and Task 4 – Interface Design has been carried out and the tests...... of the multimirror cutting head have been started....

  2. Advanced decision support for winter road maintenance

    Science.gov (United States)

    2008-01-01

    This document provides an overview of the Federal Highway Administration's winter Maintenance Decision Support System (MDSS). The MDSS is a decision support tool that has the ability to provide weather predictions focused toward the road surface. The...

  3. Overview of climatic effects of nuclear winter

    International Nuclear Information System (INIS)

    Jones, E.M.; Malone, R.C.

    1985-01-01

    A general description of the climatic effects of a nuclear war are presented. This paper offers a short history of the subject, a discussion of relevant parameters and physical processes, and a description of plausible nuclear winter scenario. 9 refs

  4. Unusial winter 2011/2012 in Slovakia

    Czech Academy of Sciences Publication Activity Database

    Faško, P.; Lapin, M.; Matejovič, P.; Pecho, Jozef

    2012-01-01

    Roč. 15, č. 1 (2012), s. 19-26 ISSN 1335-339X Institutional support: RVO:68378289 Keywords : winter characteristics * climate variabilit * climate change * global warming Subject RIV: DG - Athmosphere Sciences, Meteorology

  5. Determinants of complementary feeding practices among mothers of 6-24 months failure to thrive children based on behavioral analysis phase of PRECEDE model, Tehran.

    Science.gov (United States)

    Shams, Nasibeh; Mostafavi, Firoozeh; Hassanzadeh, Akbar

    2016-01-01

    This study intended to clarify the determining factors of complementary feeding practices among Tehran 6-24 months failure to thrive children in order to use the results for planning the interventions to reduce the possible adverse effects. In this study, 132 mothers of three medical and health centers were chosen by random sampling among those centers operating under the supervision of south of Tehran District Health Center and study data were collected from them. A valid and reliable questionnaire as a data collection instrument developed based on behavioral analysis phase of PRECEDE model. Spearman and Pearson's correlation coefficient test were used to determine the statistical relationship between factors associated with complementary feeding practices among mothers. The mothers' knowledge was as follows: 0.8%, 20.4%, and 78.8% of them were good, medium, and poor, respectively. Mean scores for the mothers' performance in terms of supplementary feeding was 66.8. Pearson correlation indicated a positive and significant correlation between the mothers' performance with enabling and reinforcing factors, but there wasn't any significant relationship between the mothers' performance and knowledge about complementary feeding. According to the obtained results, reinforcing factors, and enabling factors are associated with the mothers' performance in terms of complementary feeding. Hence, attention to these issues is essential for better health interventions planning.

  6. SERSO: Summer sun against winter ice; SERSO: Mit Sommer-Sonne gegen Winter-Glatteis

    Energy Technology Data Exchange (ETDEWEB)

    Eugster, W J [Polydynamics Engineering, Zuerich (Switzerland); Hess, K [Polydynamics Engineering, Bremgarten-Bern (Switzerland); Hopkirk, R J [Polydynamics Engineering, Maennedorf (Switzerland)

    1997-12-01

    Road surfaces absorb energy from the incoming solar radiation in the summer months. The SERSO project was conceived to collect this energy, store it and reuse it during the following winter period to eliminate ice formation on those same road surfaces. The acronym SERSO (Sonnenenergierueckgewinnung aus Strassenoberflaechen) means `solar energy recuperation from road surfaces`. This pilot unit having been conceived, researched an applied to a bridge on the Swiss national expressway A8 near Daerligen on the south side of the lake of Thun was officially opened on 22nd August 1994. Heat exchanger tubes carrying a water/glycol heat transfer fluid were built into the roadbed on the bridge, covering a total area of some 1`300 m{sup 2}. In summer these collect heat from the exposed carriageways, which is then transported in a closed hydraulic circuit to the neighbouring cylindrical underground rock heat storage volume. Within a diameter of 31.5 m and a depth of 65 m heat is exchanged between the heat transfer fluid and the rock via an array of 91 borehole heat exchangers. The operation of the pilot plant has been accompanied by detailed measurement campaign, whereby a total of 132 sensors are interrogated by remote datalogger. The data consist of temperature measurements at several depths and positions both in the roadbed and in the rock storage volume, of energy fluxes in the hydraulic system and of relevant meteorological data. The experiences gianed during the first two years of operation have shown that sufficient heat can indeed be collected in summer to maintain the bridge free of ice during the following winter. Moreover the energy balances derived from the measurements in the low temperature rock heat store have confirmed the predicted storage efficiency. (orig./AKF) [Deutsch] cVerkehrsflaechen heizen sich im Sommer durch Sonneneinstrahlung stark auf. Diese Sommerwaerme zu sammeln, zwischenzuspeichern und im Winter zur Verhinderung von Glatteisbildung wieder zu

  7. D:L-Amino Acid Modeling Reveals Fast Microbial Turnover of Days to Months in the Subsurface Hydrothermal Sediment of Guaymas Basin

    Directory of Open Access Journals (Sweden)

    Mikkel H. Møller

    2018-05-01

    Full Text Available We investigated the impact of temperature on the microbial turnover of organic matter (OM in a hydrothermal vent system in Guaymas Basin, by calculating microbial bio- and necromass turnover times based on the culture-independent D:L-amino acid model. Sediments were recovered from two stations near hydrothermal mounds (<74°C and from one cold station (<9°C. Cell abundance at the two hydrothermal stations dropped from 108 to 106 cells cm-3 within ∼5 m of sediment depth resulting in a 100-fold lower cell number at this depth than at the cold site where numbers remained constant at 108 cells cm-3 throughout the recovered sediment. There were strong indications that the drop in cell abundance was controlled by decreasing OM quality. The quality of the sedimentary OM was determined by the diagenetic indicators %TAAC (percentage of total organic carbon present as amino acid carbon, %TAAN (percentage of total nitrogen present as amino acid nitrogen, aspartic acid:β-alanine ratios, and glutamic acid:γ-amino butyric acid ratios. All parameters indicated that the OM became progressively degraded with increasing sediment depth, and the OM in the hydrothermal sediment was more degraded than in the uniformly cold sediment. Nonetheless, the small community of microorganisms in the hydrothermal sediment demonstrated short turnover times. The modeled turnover times of microbial bio- and necromass in the hydrothermal sediments were notably faster (biomass: days to months; necromass: up to a few hundred years than in the cold sediments (biomass: tens of years; necromass: thousands of years, suggesting that temperature has a significant influence on the microbial turnover rates. We suggest that short biomass turnover times are necessary for maintance of essential cell funtions and to overcome potential damage caused by the increased temperature.The reduced OM quality at the hyrothemal sites might thus only allow for a small population size of microorganisms.

  8. Drought and Winter Drying (Pest Alert)

    Science.gov (United States)

    USDA Forest Service

    Drought and winter drying have periodically caused major damage to trees. Drought reduces the amount of water available in the soil. In the case of winter drying, the water may be in the soil, but freezing of the soil makes the water unavailable to the tree. In both cases, more water is lost through transpiration than is available to the plant. Symptoms of drought and...

  9. Coming to grips with nuclear winter

    International Nuclear Information System (INIS)

    Scherr, S.J.

    1985-01-01

    This editorial examines the politics related to the concept of nuclear winter which is a term used to describe temperature changes brought on by the injection of smoke into the atmosphere by the massive fires set off by nuclear explosions. The climate change alone could cause crop failures and lead to massive starvation. The author suggests that the prospect of a nuclear winter should be a deterrent to any nuclear exchange

  10. Twelve-month effects of the Groningen active living model (GALM) on physical activity, health and fitness outcomes in sedentary and underactive older adults aged 55-65

    NARCIS (Netherlands)

    de Jong, Johan; Lemmink, Koen A. P. M.; King, Abby C.; Huisman, Mark; Stevens, Martin

    Objective: To determine the effects on energy expenditure, health and fitness outcomes after 12 months of GALM. Methods: Subjects from matched neighbourhoods were assigned to an intervention (IG) (n = 79) or a waiting-list control group (CG) (n = 102). During the 12 months the IG attended two series

  11. New winter hardy winter bread wheat cultivar (Triticum aestivum L. Voloshkova

    Directory of Open Access Journals (Sweden)

    Л. М. Голик

    2007-12-01

    Full Text Available Creation of Initial raw for breeding of winter wheat by change of the development type under low temperatures influence was described. Seeds of spring wheat were vernalized in aluminum weighting bottle. By using low temperatures at sawing of M2-6 at the begin ind of optimal terms of sawing of winter wheat, new winter-hardy variety of Voloshkova was bred.

  12. Baraitser–Winter syndrome: An additional Egyptian patient with ...

    African Journals Online (AJOL)

    Rabah M. Shawky

    2015-05-08

    May 8, 2015 ... Abstract We report a 3.5 year old male child, second in order of birth of non consanguineous ... in this syndrome, bilateral congenital ptosis, hypertelorism, moderate mental .... ged from 2 month to 14 years and it may be intractable in some ... retardation: Baraitser–Winter syndrome or Noonan syndrome? J.

  13. Migration patterns and wintering range of common loons breeding in the Northeastern United States

    Science.gov (United States)

    Kenow, K.P.; Adams, D.; Schoch, N.; Evers, D.C.; Hanson, W.; Yates, D.; Savoy, L.; Fox, T.J.; Major, A.; Kratt, R.; Ozard, J.

    2009-01-01

    A study, using satellite telemetry, was conducted to determine the precise migration patterns and wintering locations of Common Loons (Gavia immer) breeding in the northeastern United States. Transmitters were implanted in 17 loons (16 adults and one juvenile) that were captured on breeding lakes in New York, New Hampshire, and Maine during the summers of 2003, 2004, and 2005. Transmitters from ten of the birds provided adequate location data to document movement to wintering areas. Most adult loons appeared to travel non-stop from breeding lakes, or neighboring lakes (within 15 km), to the Atlantic coast. Adult loons marked in New Hampshire and Maine wintered 152 to 239 km from breeding lakes, along the Maine coast. Adult loons marked in the Adirondack Park of New York wintered along the coasts of Massachusetts (414 km from breeding lake), Rhode Island (362 km), and southern New Jersey (527 km). Most of the loons remained relatively stationary throughout the winter, but the size of individual wintering areas of adult loons ranged from 43 to 1,159 km 2, based on a 95% fixed kernel utilization distribution probability. A juvenile bird from New York made a number of stops at lakes and reservoirs en route to Long Island Sound (325 km from breeding lake). Maximum functional life of transmitters was about 12 months, providing an opportunity to document spring migration movements as well. This work provides essential information for development and implementation of regional Common Loon conservation strategies in the Northeastern U.S.

  14. Frequent arousals from winter torpor in Rafinesque's big-eared bat (Corynorhinus rafinesquii).

    Science.gov (United States)

    Johnson, Joseph S; Lacki, Michael J; Thomas, Steven C; Grider, John F

    2012-01-01

    Extensive use of torpor is a common winter survival strategy among bats; however, data comparing various torpor behaviors among species are scarce. Winter torpor behaviors are likely to vary among species with different physiologies and species inhabiting different regional climates. Understanding these differences may be important in identifying differing susceptibilities of species to white-nose syndrome (WNS) in North America. We fitted 24 Rafinesque's big-eared bats (Corynorhinus rafinesquii) with temperature-sensitive radio-transmitters, and monitored 128 PIT-tagged big-eared bats, during the winter months of 2010 to 2012. We tested the hypothesis that Rafinesque's big-eared bats use torpor less often than values reported for other North American cave-hibernators. Additionally, we tested the hypothesis that Rafinesque's big-eared bats arouse on winter nights more suitable for nocturnal foraging. Radio-tagged bats used short (2.4 d ± 0.3 (SE)), shallow (13.9°C ± 0.6) torpor bouts and switched roosts every 4.1 d ± 0.6. Probability of arousal from torpor increased linearly with ambient temperature at sunset (Pdata show Rafinesque's big-eared bat is a shallow hibernator and is relatively active during winter. We hypothesize that winter activity patterns provide Corynorhinus species with an ecological and physiological defense against the fungus causing WNS, and that these bats may be better suited to withstand fungal infection than other cave-hibernating bat species in eastern North America.

  15. No evidence that migratory geese disperse avian influenza viruses from breeding to wintering ground.

    Directory of Open Access Journals (Sweden)

    Shenglai Yin

    Full Text Available Low pathogenic avian influenza virus can mutate to a highly pathogenic strain that causes severe clinical signs in birds and humans. Migratory waterfowl, especially ducks, are considered the main hosts of low pathogenic avian influenza virus, but the role of geese in dispersing the virus over long-distances is still unclear. We collected throat and cloaca samples from three goose species, Bean goose (Anser fabalis, Barnacle goose (Branta leucopsis and Greater white-fronted goose (Anser albifrons, from their breeding grounds, spring stopover sites, and wintering grounds. We tested if the geese were infected with low pathogenic avian influenza virus outside of their wintering grounds, and analysed the spatial and temporal patterns of infection prevalence on their wintering grounds. Our results show that geese were not infected before their arrival on wintering grounds. Barnacle geese and Greater white-fronted geese had low prevalence of infection just after their arrival on wintering grounds in the Netherlands, but the prevalence increased in successive months, and peaked after December. This suggests that migratory geese are exposed to the virus after their arrival on wintering grounds, indicating that migratory geese might not disperse low pathogenic avian influenza virus during autumn migration.

  16. TARP Monthly Housing Scorecard

    Data.gov (United States)

    Department of the Treasury — Treasury and the U.S. Department of Housing and Urban Development (HUD) jointly produce a Monthly Housing Scorecard on the health of the nation’s housing market. The...

  17. Molecule of the Month

    Indian Academy of Sciences (India)

    Molecule of the Month - Adamantane - A Plastic Piece of Diamond. J Chandrasekhar. Volume 16 Issue 12 ... Keywords. Adamantane; diamondoid systems; plastic crystals. ... Resonance – Journal of Science Education | News. © 2017 Indian ...

  18. Oceanographic Monthly Summary

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Oceanographic Monthly Summary contains sea surface temperature (SST) analyses on both regional and ocean basin scales for the Atlantic, Pacific, and Indian Oceans....

  19. River catchment rainfall series analysis using additive Holt-Winters method

    Science.gov (United States)

    Puah, Yan Jun; Huang, Yuk Feng; Chua, Kuan Chin; Lee, Teang Shui

    2016-03-01

    Climate change is receiving more attention from researchers as the frequency of occurrence of severe natural disasters is getting higher. Tropical countries like Malaysia have no distinct four seasons; rainfall has become the popular parameter to assess climate change. Conventional ways that determine rainfall trends can only provide a general result in single direction for the whole study period. In this study, rainfall series were modelled using additive Holt-Winters method to examine the rainfall pattern in Langat River Basin, Malaysia. Nine homogeneous series of more than 25 years data and less than 10% missing data were selected. Goodness of fit of the forecasted models was measured. It was found that seasonal rainfall model forecasts are generally better than the monthly rainfall model forecasts. Three stations in the western region exhibited increasing trend. Rainfall in southern region showed fluctuation. Increasing trends were discovered at stations in the south-eastern region except the seasonal analysis at station 45253. Decreasing trend was found at station 2818110 in the east, while increasing trend was shown at station 44320 that represents the north-eastern region. The accuracies of both rainfall model forecasts were tested using the recorded data of years 2010-2012. Most of the forecasts are acceptable.

  20. Surface wind energy trends near Taiwan in winter since 1871

    Directory of Open Access Journals (Sweden)

    Lei Zhang

    2017-01-01

    Full Text Available The tropical surface wind speed in boreal winter reaches a maximum near Taiwan. This stable wind resource may be used for future clean energy development. How this surface wind energy source has changed in past 141 years is investigated using the 20th century reanalysis dataset and CMIP5 models. Our observational analysis shows that the surface wind speed experienced a weakening trend in the past 141 years (1871 - 2010. The average decreasing rate is around -1.4 m s-1 per century. The decrease is primarily attributed to the relative sea surface temperature (SST cooling in the subtropical North Pacific, which forces a large-scale low-level anti-cyclonic circulation anomaly in situ and is thus responsible for the southerly trend near Taiwan. The relative SST trend pattern is attributed mainly to the greenhouse gas effect associated with anthropogenic activities. The southerly trend near Taiwan is more pronounced in the boreal winter than in summer. Such seasonal difference is attributed to the reversed seasonal mean wind, which promotes more efficient positive feedback in the boreal winter. The CMIP5 historical run analysis reveals that climate models capture less SST warming and large-scale anti-cyclonic circulation in the subtropical North Pacific, but the simulated weakening trend of the surface wind speed near Taiwan is too small.

  1. Seasonal forecasts of northern hemisphere winter 2009/10

    International Nuclear Information System (INIS)

    Fereday, D R; Maidens, A; Arribas, A; Scaife, A A; Knight, J R

    2012-01-01

    Northern hemisphere winter 2009/10 was exceptional for atmospheric circulation: the North Atlantic Oscillation (NAO) index was the lowest on record for over a century. This contributed to cold conditions over large areas of Eurasia and North America. Here we use two versions of the Met Office GloSea4 seasonal forecast system to investigate the predictability of this exceptional winter. The first is the then operational version of GloSea4, which uses a low top model and successfully predicted a negative NAO in forecasts produced in September, October and November 2009. The second uses a new high top model, which better simulates sudden stratospheric warmings (SSWs). This is particularly relevant for 2009/10 due to its unusual combination of a strong El Niño and an easterly quasi-biennial oscillation (QBO) phase, favouring SSW development. SSWs are shown to play an influential role in surface conditions, producing a stronger sea level pressure signal and improving predictions of the 2009/10 winter. (letter)

  2. Correlation analyses of Baltic Sea winter water mass formation and its impact on secondary and tertiary production

    Directory of Open Access Journals (Sweden)

    Jörn Schmidt

    2007-09-01

    Full Text Available The thermal stratification of the upper water layers in the BalticSea varies seasonally in response to the annual cycle of solarheating and wind-induced mixing. In winter, the stratificationdown to the halocline is almost completely eroded by convectionand strong wind mixing. Monthly averaged temperature profilesobtained from the ICES hydrographic database were used to studythe long-term variability (1950 to 2005 of winter water massformation in different deep basins of the Baltic Sea east ofthe island of Bornholm. Besides strong interannual variabilityof deep winter water temperatures, the last two decades showa positive trend (increase of 1-1.5°C. Correlationsof winter surface temperatures to temperatures of the winterwater body located directly above or within the top of the haloclinewere strongly positive until the autumn months. Such a closecoupling allows sea surface temperatures in winter to be usedto forecast the seasonal development of the thermal signaturein deeper layers with a high degree of confidence. The most significantimpact of winter sea surface temperatures on the thermal signaturein this depth range can be assigned to February/March. Strongersolar heating during spring and summer results in thermal stratificationof the water column leading to a complete decoupling of surfaceand deep winter water temperatures. Based on laboratory experiments,temperature-dependent relationships were utilised to analyseinterannual variations of biological processes with special emphasison the upper trophic levels (e.g., stage-specific developmentalrates of zooplankton and survival rates of fish eggs.

  3. Monthly variations of diurnal rainfall in north coast of West Java Indonesia during boreal winter periods

    Science.gov (United States)

    Yulihastin, E.; Trismidianto

    2018-05-01

    Diurnal rainfall during the active monsoon period is usually associated with the highest convective activity that often triggers extreme rainfall. Investigating diurnal rainfall behavior in the north coast of West Java is important to recognize the behavioral trends of data leading to such extreme events in strategic West Java because the city of Jakarta is located in this region. Variability of diurnal rainfall during the period of active monsoon on December-January-February (DJF) composite during the 2000-2016 period was investigated using hourly rainfall data from Tropical Rainfall Measuring Mission (TRMM) 3B41RT dataset. Through the Empirical Mode Decomposition method was appears that the diurnal rain cycle during February has increased significantly in its amplitude and frequency. It is simultaneously shows that the indication of extreme rainfall events is related to diurnal rain divergences during February shown through phase shifts. The diurnal, semidiurnal, and terdiurnal cycles appear on the characteristics of the DJF composite rainfall data during the 2000-2016 period.The significant increases in amplitude occurred during February are the diurnal (IMF 3) and terdiurnal (IMF 1) of rainfall cycles.

  4. Winter barley mutants created in the Ukraine

    International Nuclear Information System (INIS)

    Zayats, O.M.

    2001-01-01

    Full text: Increasing fodder and protein production is one of the objectives of the development of agriculture in Ukraine. Higher productivity of fodder crops, due to new highly productive varieties, is the means to meet this aim. Winter barley is an important crop for fodder purposes. The climate of the Ukraine is favourable for growing this crop. The areas used for the growth of winter barley are however, small (500,000-550,000 ha) and there is a shortage of good quality varieties. The main aim of the work was therefore to create new varieties of highly productive winter barley, of good quality. The new varieties and mutation lines of winter barley were created under the influence of water solutions of N-nitroso-N-methylurea (NMH - 0,012, 0,005%), N-nitroso-N-ethylurea (NEH - 0,05; 0.025; 0,012%) ethyleneimine (EI - 0,02; 0,01; 0,005%) on winter barley seeds of the varieties of local and foreign selections. On the basis of many years of investigations (1984-94) the following mutations were described: hard-grained, winter-hardiness, earliness, middle-maturity, late-maturity, wide and large leaves, narrow leaves, multinodal, great number of leaves, great number of flowers, strong stem (lodging resistant), tallness, semi-dwarfness, dwarfness, and high productivity. Particularly valuable are mutants with high productivity of green bulk. Their potential yield is 70 t/ha. As a result of the work two varieties of winter barley 'Shyrokolysty' and 'Kormovy' were released into the State register of plant varieties of the Ukraine. The other valuable mutant genotypes are used in cross breeding programmes. (author)

  5. Carryover effects associated with winter location affect fitness, social status, and population dynamics in a long-distance migrant.

    Science.gov (United States)

    Sedinger, James S; Schamber, Jason L; Ward, David H; Nicolai, Christopher A; Conant, Bruce

    2011-11-01

    We used observations of individually marked female black brant geese (Branta bernicla nigricans; brant) at three wintering lagoons on the Pacific coast of Baja California-Laguna San Ignacio (LSI), Laguna Ojo de Liebre (LOL), and Bahía San Quintín (BSQ)-and the Tutakoke River breeding colony in Alaska to assess hypotheses about carryover effects on breeding and distribution of individuals among wintering areas. We estimated transition probabilities from wintering locations to breeding and nonbreeding by using multistratum robust-design capture-mark-recapture models. We also examined the effect of breeding on migration to wintering areas to assess the hypothesis that individuals in family groups occupied higher-quality wintering locations. We used 4,538 unique female brant in our analysis of the relationship between winter location and breeding probability. All competitive models of breeding probability contained additive effects of wintering location and the 1997-1998 El Niño-Southern Oscillation (ENSO) event on probability of breeding. Probability of breeding in non-ENSO years was 0.98 ± 0.02, 0.68 ± 0.04, and 0.91 ± 0.11 for females wintering at BSQ, LOL, and LSI, respectively. After the 1997-1998 ENSO event, breeding probability was between 2% (BSQ) and 38% (LOL) lower than in other years. Individuals that bred had the highest probability of migrating the next fall to the wintering area producing the highest probability of breeding.

  6. Carryover effects associated with winter location affect fitness, social status, and population dynamics in a long-distance migrant

    Science.gov (United States)

    Sedinger, James S.; Schamber, Jason L.; Ward, David H.; Nicolai, Christopher A.; Conant, Bruce

    2011-01-01

    We used observations of individually marked female black brant geese (Branta bernicla nigricans; brant) at three wintering lagoons on the Pacific coast of Baja California—Laguna San Ignacio (LSI), Laguna Ojo de Liebre (LOL), and Bahía San Quintín (BSQ)—and the Tutakoke River breeding colony in Alaska to assess hypotheses about carryover effects on breeding and distribution of individuals among wintering areas. We estimated transition probabilities from wintering locations to breeding and nonbreeding by using multistratum robust-design capture-mark-recapture models. We also examined the effect of breeding on migration to wintering areas to assess the hypothesis that individuals in family groups occupied higher-quality wintering locations. We used 4,538 unique female brant in our analysis of the relationship between winter location and breeding probability. All competitive models of breeding probability contained additive effects of wintering location and the 1997–1998 El Niño–Southern Oscillation (ENSO) event on probability of breeding. Probability of breeding in non-ENSO years was 0.98 ± 0.02, 0.68 ± 0.04, and 0.91 ± 0.11 for females wintering at BSQ, LOL, and LSI, respectively. After the 1997–1998 ENSO event, breeding probability was between 2% (BSQ) and 38% (LOL) lower than in other years. Individuals that bred had the highest probability of migrating the next fall to the wintering area producing the highest probability of breeding.

  7. Winter wheat quality monitoring and forecasting system based on remote sensing and environmental factors

    International Nuclear Information System (INIS)

    Haiyang, Yu; Yanmei, Liu; Guijun, Yang; Xiaodong, Yang; Chenwei, Nie; Dong, Ren

    2014-01-01

    To achieve dynamic winter wheat quality monitoring and forecasting in larger scale regions, the objective of this study was to design and develop a winter wheat quality monitoring and forecasting system by using a remote sensing index and environmental factors. The winter wheat quality trend was forecasted before the harvest and quality was monitored after the harvest, respectively. The traditional quality-vegetation index from remote sensing monitoring and forecasting models were improved. Combining with latitude information, the vegetation index was used to estimate agronomy parameters which were related with winter wheat quality in the early stages for forecasting the quality trend. A combination of rainfall in May, temperature in May, illumination at later May, the soil available nitrogen content and other environmental factors established the quality monitoring model. Compared with a simple quality-vegetation index, the remote sensing monitoring and forecasting model used in this system get greatly improved accuracy. Winter wheat quality was monitored and forecasted based on the above models, and this system was completed based on WebGIS technology. Finally, in 2010 the operation process of winter wheat quality monitoring system was presented in Beijing, the monitoring and forecasting results was outputted as thematic maps

  8. Winter fidelity and apparent survival of lesser snow goose populations in the Pacific flyway

    Science.gov (United States)

    Williams, C.K.; Samuel, M.D.; Baranyuk, Vasily V.; Cooch, E.G.; Kraege, Donald K.

    2008-01-01

    The Beringia region of the Arctic contains 2 colonies of lesser snow geese (Chen caerulescens caerulescens) breeding on Wrangel Island, Russia, and Banks Island, Canada, and wintering in North America. The Wrangel Island population is composed of 2 subpopulations from a sympatric breeding colony but separate wintering areas, whereas the Banks Island population shares a sympatric wintering area in California, USA, with one of the Wrangel Island subpopulations. The Wrangel Island colony represents the last major snow goose population in Russia and has fluctuated considerably since 1970, whereas the Banks Island population has more than doubled. The reasons for these changes are unclear, but hypotheses include independent population demographics (survival and recruitment) and immigration and emigration among breeding or wintering populations. These demographic and movement patterns have important ecological and management implications for understanding goose population structure, harvest of admixed populations, and gene flow among populations with separate breeding or wintering areas. From 1993 to 1996, we neckbanded molting birds at their breeding colonies and resighted birds on the wintering grounds. We used multistate mark-recapture models to evaluate apparent survival rates, resighting rates, winter fidelity, and potential exchange among these populations. We also compared the utility of face stain in Wrangel Island breeding geese as a predictor of their wintering area. Our results showed similar apparent survival rates between subpopulations of Wrangel Island snow geese and lower apparent survival, but higher emigration, for the Banks Island birds. Males had lower apparent survival than females, most likely due to differences in neckband loss. Transition between wintering areas was low (exchange between the Banks and northern Wrangel Island populations. Face staining was an unreliable indicator of wintering area. Our findings suggest that northern and southern

  9. Examining winter visitor use in Yellowstone National Park

    Science.gov (United States)

    Mae A. Davenport; Wayne A. Freimund; William T. Borrie; Robert E. Manning; William A. Valliere; Benjamin Wang

    2000-01-01

    This research was designed to assist the managers of Yellowstone National Park (YNP) in their decision making about winter visitation. The focus of this report is on winter use patterns and winter visitor preferences. It is the author’s hope that this information will benefit both the quality of winter experiences and the stewardship of the park resources. This report...

  10. First Direct Evidence for Natal Wintering Ground Fidelity and Estimate of Juvenile Survival in the New Zealand Southern Right Whale Eubalaena australis.

    Science.gov (United States)

    Carroll, E L; Fewster, R M; Childerhouse, S J; Patenaude, N J; Boren, L; Baker, C S

    2016-01-01

    Juvenile survival and recruitment can be more sensitive to environmental, ecological and anthropogenic factors than adult survival, influencing population-level processes like recruitment and growth rate in long-lived, iteroparous species such as southern right whales. Conventionally, Southern right whales are individually identified using callosity patterns, which do not stabilise until 6-12 months, by which time the whale has left its natal wintering grounds. Here we use DNA profiling of skin biopsy samples to identify individual Southern right whales from year of birth and document their return to the species' primary wintering ground in New Zealand waters, the Subantarctic Auckland Islands. We find evidence of natal fidelity to the New Zealand wintering ground by the recapture of 15 of 57 whales, first sampled in year of birth and available for subsequent recapture, during winter surveys to the Auckland Islands in 1995-1998 and 2006-2009. Four individuals were recaptured at the ages of 9 to 11, including two females first sampled as calves in 1998 and subsequently resampled as cows with calves in 2007. Using these capture-recapture records of known-age individuals, we estimate changes in survival with age using Cormack-Jolly-Seber models. Survival is modelled using discrete age classes and as a continuous function of age. Using a bootstrap method to account for uncertainty in model selection and fitting, we provide the first direct estimate of juvenile survival for this population. Our analyses indicate a high annual apparent survival for juveniles at between 0.87 (standard error (SE) 0.17, to age 1) and 0.95 (SE 0.05: ages 2-8). Individual identification by DNA profiling is an effective method for long-term demographic and genetic monitoring, particularly in animals that change identifiable features as they develop or experience tag loss over time.

  11. The electricity supply-demand balance for the winter of 2015-2016. Synthesis - November 2015

    International Nuclear Information System (INIS)

    2015-11-01

    Twice a year, RTE publishes a forecast study of the electricity supply and demand in continental France for the summer and winter periods. The study is based on the information supplied by electric utilities concerning the expected availability of power generation means and on statistical meteorological models. Safety margins are calculated using thousands of probabilistic scenarios combining various production and consumption situations. This report is the forecast study for the winter of 2015-2016

  12. Impacts of climate change for Swiss winter and summer tourism: a general equilibrium analysis

    OpenAIRE

    Thurm, Boris; Vielle, Marc; Vöhringer, Frank

    2017-01-01

    Tourism could be greatly affected by climate change due to its strong dependence on weather. In Switzerland, the sector represents an appreciable share of the economy. Thus, studying climate effects on tourism is necessary for developing adequate adaptation strategies. While most of the studies focused on winter tourism, we investigate the climate change impacts on both winter and summer tourism in Switzerland. Using a computable general equilibrium (CGE) model, we simulate the impacts of tem...

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

    Science.gov (United States)

    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

  14. Root development of fodder radish and winter wheat before winter in relation to uptake of nitrogen

    DEFF Research Database (Denmark)

    Wahlström, Ellen Margrethe; Hansen, Elly Møller; Mandel, A.

    2015-01-01

    occurred. Quantitative data is missing on N leaching of a catch crop compared to a winter cereal in a conventional cereal-based cropping system. The aim of the study was to investigate whether fodder radish (Raphanus sativus L.) (FR) would be more efficient than winter wheat (Triticum aestivum L.) (WW...

  15. Genomic Prediction of Manganese Efficiency in Winter Barley

    Directory of Open Access Journals (Sweden)

    Florian Leplat

    2016-07-01

    Full Text Available Manganese efficiency is a quantitative abiotic stress trait controlled by several genes each with a small effect. Manganese deficiency leads to yield reduction in winter barley ( L.. Breeding new cultivars for this trait remains difficult because of the lack of visual symptoms and the polygenic features of the trait. Hence, Mn efficiency is a potential suitable trait for a genomic selection (GS approach. A collection of 248 winter barley varieties was screened for Mn efficiency using Chlorophyll (Chl fluorescence in six environments prone to induce Mn deficiency. Two models for genomic prediction were implemented to predict future performance and breeding value of untested varieties. Predictions were obtained using multivariate mixed models: best linear unbiased predictor (BLUP and genomic best linear unbiased predictor (G-BLUP. In the first model, predictions were based on the phenotypic evaluation, whereas both phenotypic and genomic marker data were included in the second model. Accuracy of predicting future phenotype, , and accuracy of predicting true breeding values, , were calculated and compared for both models using six cross-validation (CV schemes; these were designed to mimic plant breeding programs. Overall, the CVs showed that prediction accuracies increased when using the G-BLUP model compared with the prediction accuracies using the BLUP model. Furthermore, the accuracies [] of predicting breeding values were more accurate than accuracy of predicting future phenotypes []. The study confirms that genomic data may enhance the prediction accuracy. Moreover it indicates that GS is a suitable breeding approach for quantitative abiotic stress traits.

  16. Prediction of Malaysian monthly GDP

    Science.gov (United States)

    Hin, Pooi Ah; Ching, Soo Huei; Yeing, Pan Wei

    2015-12-01

    The paper attempts to use a method based on multivariate power-normal distribution to predict the Malaysian Gross Domestic Product next month. Letting r(t) be the vector consisting of the month-t values on m selected macroeconomic variables, and GDP, we model the month-(t+1) GDP to be dependent on the present and l-1 past values r(t), r(t-1),…,r(t-l+1) via a conditional distribution which is derived from a [(m+1)l+1]-dimensional power-normal distribution. The 100(α/2)% and 100(1-α/2)% points of the conditional distribution may be used to form an out-of sample prediction interval. This interval together with the mean of the conditional distribution may be used to predict the month-(t+1) GDP. The mean absolute percentage error (MAPE), estimated coverage probability and average length of the prediction interval are used as the criterions for selecting the suitable lag value l-1 and the subset from a pool of 17 macroeconomic variables. It is found that the relatively better models would be those of which 2 ≤ l ≤ 3, and involving one or two of the macroeconomic variables given by Market Indicative Yield, Oil Prices, Exchange Rate and Import Trade.

  17. Seasonal overturning circulation in the Red Sea: 2. Winter circulation

    KAUST Repository

    Yao, Fengchao

    2014-04-01

    The shallow winter overturning circulation in the Red Sea is studied using a 50 year high-resolution MITgcm (MIT general circulation model) simulation with realistic atmospheric forcing. The overturning circulation for a typical year, represented by 1980, and the climatological mean are analyzed using model output to delineate the three-dimensional structure and to investigate the underlying dynamical mechanisms. The horizontal model circulation in the winter of 1980 is dominated by energetic eddies. The climatological model mean results suggest that the surface inflow intensifies in a western boundary current in the southern Red Sea that switches to an eastern boundary current north of 24N. The overturning is accomplished through a cyclonic recirculation and a cross-basin overturning circulation in the northern Red Sea, with major sinking occurring along a narrow band of width about 20 km along the eastern boundary and weaker upwelling along the western boundary. The northward pressure gradient force, strong vertical mixing, and horizontal mixing near the boundary are the essential dynamical components in the model\\'s winter overturning circulation. The simulated water exchange is not hydraulically controlled in the Strait of Bab el Mandeb; instead, the exchange is limited by bottom and lateral boundary friction and, to a lesser extent, by interfacial friction due to the vertical viscosity at the interface between the inflow and the outflow. Key Points Sinking occurs in a narrow boundary layer along the eastern boundary Surface western boundary current switches into an eastern boundary current Water exchange in the Strait of Bab el Mandeb is not hydraulically controlled © 2014. American Geophysical Union. All Rights Reserved.

  18. Monthly progress report

    International Nuclear Information System (INIS)

    1975-06-01

    This monthly report of the SCPRI exposes an interpretation of the principal results concerning the surveillance of radioactivity in the environment: atmospheric dusts(air at ground level, high altitude air), rainwater, surface water, underground water, irrigation water, drinking water, food chain (milk, plants, cattle, fish), sea water around nuclear plant sites and other sites. The activities of various radioisotopes are presented in tables ( 7 Be, 95 Zr and 95 Nb, 103 Ru, 131 I, 137 Cs, 140 Ba and 140 La, 90 Sr, 106 Ru and 106 Rh, 226 Ra, 54 Mn, U and T). A monthly bibliographic selection is also presented [fr

  19. Monthly progress report

    International Nuclear Information System (INIS)

    1975-03-01

    This monthly report of the SCPRI exposes an interpretation of the principal results concerning the surveillance of radioactivity in the environment: atmospheric dusts (air at ground level, high altitude air), rainwater, surface water, underground water, irrigation water, drinking water, food chain (milk, plants, cattle, fish), sea water around nuclear plant sites and other sites. The activities of various radioisotopes are presented in tables ( 7 Be, 95 Zr and 95 Nb, 103 Ru, 131 I, 137 Cs, 140 Ba and 140 La, 90 Sr, 106 Ru and 106 Rh, 226 Ra, 54 Mn, U and T). A monthly bibliographic selection is also presented [fr

  20. 24-month fuel cycles

    International Nuclear Information System (INIS)

    Rosenstein, R.G.; Sipes, D.E.; Beall, R.H.; Donovan, E.J.

    1986-01-01

    Twenty-four month reload cycles can potentially lessen total power generation costs. While 24-month cores increase purchased fuel costs, the longer cycles reduce the number of refueling outages and thus enhance plant availability; men-rem exposure to site personnel and other costs associated with reload core design and licensing are also reduced. At dual unit sites an operational advantage can be realized by refueling each plant alternately on a 1-year offset basis. This results in a single outage per site per year which can be scheduled for off-peak periods or when replacement power costs are low

  1. Monthly progress report

    International Nuclear Information System (INIS)

    1975-04-01

    This monthly report of the SCPRI exposes an interpretation of the principal results concerning the surveillance of radioactivity in the environment: atmospheric dusts (air at ground level, high altitude air), rainwater, surface water, underground water, irrigation water, drinking water, food chain (milk plants, cattle, fish), seawater around nuclear plant sites and other sites. The activities of various radioisotopes are presented in tables ( 7 Be, 95 Zr and 95 Nb, 103 Ru, 131 I, 137 Cs, 140 Ba and 140 La, 90 Sr, 106 Ru and 106 Rh, 226 Ra, 54 Mn U and T). A monthly bibliographic selection is also presented [fr

  2. Monthly progress report

    International Nuclear Information System (INIS)

    1975-01-01

    This monthly report of the SCPRI exposes an interpretation of the principal results concerning the surveillance of radioactivity in the environment: atmospheric dusts (air at ground level, high altitude air), rainwater, surface water, underground water, irrigation water, drinking water, food chain (milk, plants, cattle, fish), sea water around nuclear plant sites and other sites. The activities of various radioisotopes are presented in tables ( 7 Be, 95 Zr and 95 Nb, 103 Ru, 131 I, 137 Cs, 140 Ba and 140 La, 90 Sr, 106 Ru and 106 Rh, 226 Ra, 54 Mn, U and T). A monthly bibliographic selection is also presented [fr

  3. Monthly progress report

    International Nuclear Information System (INIS)

    1975-02-01

    This monthly report of the SCPRI exposes an interpretation of the principal results concerning the surveillance of radioactivity in the environment: atmospheric dusts (air at ground level, high altitude air), rainwater, surface water, underground water, irrigation water, drinking water, food chain (milk, plants, cattle, fish), sea water around nuclear plant sites and other sites. The activities of various radioisotopes are presented in tables ( 7 Be, 95 Zr and 95 Nb, 103 Ru, 131 I, 137 Cs, 140 Ba and 140 La, 90 Sr, 106 Ru and 106 Rh, 226 Ra, 54 Mn, U and T). A monthly bibliographic selection is also presented [fr

  4. [Paediatric emergencies; example of the management of winter epidemics].

    Science.gov (United States)

    Mercier, Jean-Christophe; Bellettre, Xavier; Lejay, Émilie; Desmarest, Marie; Titomanlio, Luigi

    2015-01-01

    Every year, epidemics of viral bronchiolitis and gastroenteritis occur with a significant increase in the number of visits (by a factor 1.8) and hospitalisations that can over-exceed bed capacity leading to transfer sick children to other hospitals. This kind of hospital 'crisis' is not limited to paediatrics, big cities or western nations. It is a worldwide worrying problem. Because our hospital sits in the Northern districts of Paris where a large community of m.ncants lives in poverty, our number of visits is high (mean 250 per day), and winter epidemics further jeopardise the difficult equilibrium achieved between quality management and waiting times. Thus, we have taken various initiatives in terms of organisation of the paediatric emergency department and other wards, including a "fast track" clinic, the opening of beds dedicated to winter epidemics, the institution of a "bed manager" in order to more easily find a bed, and a larger use of home hospitalisations. Furthermore, we created a specific committee which may decide on various indicators of tension whether it is necessary to cancel programmed hospitalisations or surgery.in order to resolve the emergency crisis. This kind of organisation can serve as a model for other hospitals facing winter epidemics crises.

  5. Observed Decrease of North American Winter Temperature Variability

    Science.gov (United States)

    Rhines, A. N.; Tingley, M.; McKinnon, K. A.; Huybers, P. J.

    2015-12-01

    There is considerable interest in determining whether temperature variability has changed in recent decades. Model ensembles project that extratropical land temperature variance will detectably decrease by 2070. We use quantile regression of station observations to show that decreasing variability is already robustly detectable for North American winter during 1979--2014. Pointwise trends from GHCND stations are mapped into a continuous spatial field using thin-plate spline regression, resolving small-scales while providing uncertainties accounting for spatial covariance and varying station density. We find that variability of daily temperatures, as measured by the difference between the 95th and 5th percentiles, has decreased markedly in winter for both daily minima and maxima. Composites indicate that the reduced spread of winter temperatures primarily results from Arctic amplification decreasing the meridional temperature gradient. Greater observed warming in the 5th relative to the 95th percentile stems from asymmetric effects of advection during cold versus warm days; cold air advection is generally from northerly regions that have experienced greater warming than western or southwestern regions that are generally sourced during warm days.

  6. Volcanos and el Nino - signal separation in Winter

    International Nuclear Information System (INIS)

    Kirchner, I.; Graf, H.F.

    1993-01-01

    The aim of this study is the detection of climate signals following violent volcanic eruptions in relation to those forced by El Nino during winter in higher latitudes of the northern hemisphere. The applied statistical methods are a combination of the local t-test statistics and signal detection methods based on Empirical Orthogonal Functions (EOFs). The observed effect of local cooling due to the volcanic reduction of shortwave radiation over large land areas (like Asia) in subtropical regions, the observed advective warming over Eurasia and the advective cooling over Greenland is well simulated in the model. The radiative cooling near the surface is important for the volcano signal in the subtropics, but it is only weak in high latitudes during winter. The local anomalies in the El Nino forcing region in the tropics, and the warming over North America in middle and high latitudes are simulated as observed. The combination of high stratospheric aerosol loading and El Nino leads to a climate perturbation stronger than for forcing with El Nino or stratospheric aerosol alone. Over Europe, generally the volcanic signal dominates, and in the Pacific region the El Nino forcing determines the observed and the simulated anomalies in winter. (orig./KW)

  7. Volcanos and el Nino - signal separation in Winter

    Energy Technology Data Exchange (ETDEWEB)

    Kirchner, I.; Graf, H.F.

    1993-12-01

    The aim of this study is the detection of climate signals following violent volcanic eruptions in relation to those forced by El Nino during winter in higher latitudes of the northern hemisphere. The applied statistical methods are a combination of the local t-test statistics and signal detection methods based on Empirical Orthogonal Functions (EOFs). The observed effect of local cooling due to the volcanic reduction of shortwave radiation over large land areas (like Asia) in subtropical regions, the observed advective warming over Eurasia and the advective cooling over Greenland is well simulated in the model. The radiative cooling near the surface is important for the volcano signal in the subtropics, but it is only weak in high latitudes during winter. The local anomalies in the El Nino forcing region in the tropics, and the warming over North America in middle and high latitudes are simulated as observed. The combination of high stratospheric aerosol loading and El Nino leads to a climate perturbation stronger than for forcing with El Nino or stratospheric aerosol alone. Over Europe, generally the volcanic signal dominates, and in the Pacific region the El Nino forcing determines the observed and the simulated anomalies in winter. (orig./KW)

  8. The engineering approach to winter sports

    CERN Document Server

    Cheli, Federico; Maldifassi, Stefano; Melzi, Stefano; Sabbioni, Edoardo

    2016-01-01

    The Engineering Approach to Winter Sports presents the state-of-the-art research in the field of winter sports in a harmonized and comprehensive way for a diverse audience of engineers, equipment and facilities designers, and materials scientists. The book examines the physics and chemistry of snow and ice with particular focus on the interaction (friction) between sports equipment and snow/ice, how it is influenced by environmental factors, such as temperature and pressure, as well as by contaminants and how it can be modified through the use of ski waxes or the microtextures of blades or ski soles. The authors also cover, in turn, the different disciplines in winter sports:  skiing (both alpine and cross country), skating and jumping, bob sledding and skeleton, hockey and curling, with attention given to both equipment design and on the simulation of gesture and  track optimization.

  9. Prevalence of operator fatigue in winter maintenance operations.

    Science.gov (United States)

    Camden, Matthew C; Medina-Flintsch, Alejandra; Hickman, Jeffrey S; Bryce, James; Flintsch, Gerardo; Hanowski, Richard J

    2018-02-02

    Similar to commercial motor vehicle drivers, winter maintenance operators are likely to be at an increased risk of becoming fatigued while driving due to long, inconsistent shifts, environmental stressors, and limited opportunities for sleep. Despite this risk, there is little research concerning the prevalence of winter maintenance operator fatigue during winter emergencies. The purpose of this research was to investigate the prevalence, sources, and countermeasures of fatigue in winter maintenance operations. Questionnaires from 1043 winter maintenance operators and 453 managers were received from 29 Clear Road member states. Results confirmed that fatigue was prevalent in winter maintenance operations. Over 70% of the operators and managers believed that fatigue has a moderate to significant impact on winter maintenance operations. Approximately 75% of winter maintenance operators reported to at least sometimes drive while fatigued, and 96% of managers believed their winter maintenance operators drove while fatigued at least some of the time. Furthermore, winter maintenance operators and managers identified fatigue countermeasures and sources of fatigue related to winter maintenance equipment. However, the countermeasures believed to be the most effective at reducing fatigue during winter emergencies (i.e., naps) were underutilized. For example, winter maintenance operators reported to never use naps to eliminate fatigue. These results indicated winter maintenance operations are impacted by operator fatigue. These results support the increased need for research and effective countermeasures targeting winter maintenance operator fatigue. Copyright © 2018 Elsevier Ltd. All rights reserved.

  10. Hippocampal Astrocytes in Migrating and Wintering Semipalmated Sandpiper Calidris pusilla.

    Science.gov (United States)

    Carvalho-Paulo, Dario; de Morais Magalhães, Nara G; de Almeida Miranda, Diego; Diniz, Daniel G; Henrique, Ediely P; Moraes, Isis A M; Pereira, Patrick D C; de Melo, Mauro A D; de Lima, Camila M; de Oliveira, Marcus A; Guerreiro-Diniz, Cristovam; Sherry, David F; Diniz, Cristovam W P

    2017-01-01

    Seasonal migratory birds return to the same breeding and wintering grounds year after year, and migratory long-distance shorebirds are good examples of this. These tasks require learning and long-term spatial memory abilities that are integrated into a navigational system for repeatedly locating breeding, wintering, and stopover sites. Previous investigations focused on the neurobiological basis of hippocampal plasticity and numerical estimates of hippocampal neurogenesis in birds but only a few studies investigated potential contributions of glial cells to hippocampal-dependent tasks related to migration. Here we hypothesized that the astrocytes of migrating and wintering birds may exhibit significant morphological and numerical differences connected to the long-distance flight. We used as a model the semipalmated sandpiper Calidris pusilla , that migrates from northern Canada and Alaska to South America. Before the transatlantic non-stop long-distance component of their flight, the birds make a stopover at the Bay of Fundy in Canada. To test our hypothesis, we estimated total numbers and compared the three-dimensional (3-D) morphological features of adult C. pusilla astrocytes captured in the Bay of Fundy ( n = 249 cells) with those from birds captured in the coastal region of Bragança, Brazil, during the wintering period ( n = 250 cells). Optical fractionator was used to estimate the number of astrocytes and for 3-D reconstructions we used hierarchical cluster analysis. Both morphological phenotypes showed reduced morphological complexity after the long-distance non-stop flight, but the reduction in complexity was much greater in Type I than in Type II astrocytes. Coherently, we also found a significant reduction in the total number of astrocytes after the transatlantic flight. Taken together these findings suggest that the long-distance non-stop flight altered significantly the astrocytes population and that morphologically distinct astrocytes may play

  11. Polar-Tropical Coupling in the Winter Stratosphere

    Science.gov (United States)

    Scott, R.

    2017-12-01

    A distinct pattern of enhanced equatorial potential vorticitygradients during QBO westerly anomalies, enhanced subtropicalgradients during QBO easterlies, is used to motivate a new formulationof dynamical coupling between the tropics and winter polar vortexbased on remote transfer of finite amplitude wave activity defined interms of lateral potential vorticity displacements. While the weakpotential vorticity gradients in the surf zone imply laterallyevanescent Rossby waves, transfer of wave activity from the polarvortex edge to the subtropical barrier or to the QBO westerly phaseequatorial gradients arises from nonlocality of potential vorticityinversion and the large horizontal displacements of the vortex edge.Our approach goes beyond the traditional description of the effect ofQBO wind anomalies on linear wave propagation through the stratospherevia wave reflection at the zero wind line; linear wave theory isappealing but neglects the long horizontal and vertical wavelengthsinvolved and the inhomogeneous background potential vorticity. Aparticular issue of outstanding interest is whether and how therelatively shallow QBO anomalies can influence the deep verticallypropagating waves on the edge of the winter stratospheric polarvortex. Process studies with a mechanistic model with prescribed QBOand carefully controlled high-latitude wave forcing are analyzed,guided by a reexamination of meteorological reanalysis, to address howsuch a dynamical linkage may influence in particular the resonantexcitation of the winter vortex, and the occurrence ofvortex-splitting sudden warming events. We quantify the associatedtransfer of wave activity from vortex edge to the tropics, considerunder what conditions this becomes a significant source of easterlymomentum in the driving of the QBO itself, and how the structure ofthe Brewer-Dobson circulation varies in response to the location ofthe QBO westerly winds in any given winter.